varundus 2026-08-12 14:00

Zotero/001_artiklid/1106v1003.md

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+---
+category: literaturenote
+citekey: 1106v1003
+title: 1106v1-003
+authors: ""
+zotero_storage: Y63IV4B8
+collections: imporditud
+folder: 001_artiklid
+status: converted
+---
+# **Evaluating Alternative Maintenance Strategies for Low-Volume Roads in Sub-Saharan Africa**
+
+C.C.COOK
+
+Recent applications ofthe World Bank's Highway Design and Maintenance (HDM) model in sub-Saharan Africa indicate that periodic maintenance is generally justified by vehicle operating cost savings only on paved roads with traffic levels of more than 100 vehicles per day (vpd) and on unpaved roads with traffic levels of more than 50 vehicles per day. If traffic levels are below 50 vpd on paved roads and 20 vpd on unpaved roads, the HD M indicates that periodic maintenance should be postponed indefinitely. Road rehabilitation in potentially productive areas often appears economically justified at lower traffic volumes, based on the increase in agricultural production that occurs when road access is provided. These benefits may be lost if a rehabilitated road is allowed to deteriorate because of lack of maintenance. The potential loss of agricultural production is not considered in the HDM evaluation of an optimal road maintenance strategy. The relationship between road condition and agricultural productivity to develop an appropriate maintenance strategy for low-volume roads in sub-Saharan Africa is examined in this paper. Timely periodic maintenance is generally justified ifthe initial road construction investment was justified. If the expected increases in agricultural production or the related generated traffic is slow to materialize, the preferred economic strategy would be to defer periodic maintenance for 2 to 4 years. It is critical that roads be maintained routinely to preserve road access, which is the key to the effects of road investments on development.
+
+The countries of sub-Saharan Africa share several characteristics that lead to low traffic volumes on most of their rural roads. Much of sub-Saharan Africa is still sparsely populated. This population is largely engaged in subsistence agriculture and often employs shifting cultivation, combined with or complemented by transhumant or nomadic herding. The modern transport needs associated with these traditional patterns of economic activity are minimal.
+
+The region is characterized by extremes of temperature and rainfall, which result in wide variations in vegetative cover and soil quality. Generally speaking, soils that are suitable for road building have relatively low agricultural potential, whereas soils with high agricultural potential are not well adapted for road construction and maintenance. The variations in climate also affect the choice of appropriate road maintenance strategies because, at low traffic volumes, climate is much more important than traffic in determining the rate of road deterioration.
+
+The traditional approach to development in sub-Saharan Africa has been to encourage the rural population to produce cash crops for export to generate cash income that can then be exchanged for manufactured goods. Extensive road networks have been built, at considerable cost, in pursuit of this objective. In many cases, these road building programs have been associated with complementary investments to promote crop production or with rural development projects to promote rural welfare. However, growth in agricultural production has not kept pace with the growth of the population, which has resulted in declining levels of economic activity and low traffic volumes on much of the present road network.
+
+Sub-Saharan African countries today are faced with critical decisions regarding the use of their scarce public resources. In the past, many countries have invested heavily in roads without allocating the necessary funds in their recurrent budgets to maintain these assets. Consequently, the benefits expected from these investments have not been fully realized. Roads that have been allowed to deteriorate due to lack of maintenance now require expensive rehabilitation or even complete reconstruction. Yet it is difficult to justify maintenance expenditures when traffic volumes remain low.
+
+The World Bank called attention to the road maintenance problem in 1980 and has since been giving continuous attention to the development of analytic tools for planning and programming maintenance expenditures in the most cost-effective manner (1, 2). More recently, it has focused attention on the resource allocation problems raised by road deterioration in the absence of adequate maintenance (3). Although the problem is worldwide, the Bank has been giving particular attention to sub-Saharan Africa, where development efforts have been least successful and where resource constraints are most severe.
+
+Recent applications of the Bank's analytic tools, the Highway Design and Maintenance (HOM) model and its companion Expenditure Budgeting Model, have been made using the road networks of several sub-Saharan African countries. This work has shown that periodic maintenance is generally justified by user cost savings at traffic levels approaching 100 vehicles per day (vpd) for paved roads and 50 vpd for earth roads. There is a gray area in which periodic maintenance may or may not be justified, depending on the unit costs of the maintenance activity and on the vehicle mix using the road. This gray area lies roughly between 50 and 100 vpd for paved roads and between 20 and· 50 vpd for gravel roads. The HOM analysis indicates that below these traffic levels periodic maintenance should be postponed indefinitely.
+
+At the same time, however, road rehabilitation and construction studies often show that larger infrastructure investments would be viable-at lower initial traffic levels. The reason for this apparent inco~sistency is that construction and rehabilitation studies take into ac~ount the effect of road improvements in generating- or regenerating-economic activity in the surrounding area, apart from the normal growth of traffic that is
+
+considered in maintenance analysis. The purpose of this paper is to examine the reiaiionship between road condition and agricultural productivity in greater detail to determine the most appropriate maintenance strategy for low-volume roads.
+
+## METHODOLOGICAL APPROACHES
+
+Tin: classic methodology for estimating the benefits of road investment is based on user cost savings (4). This methodology underlies the HOM model, which estimates user costs as a function of changing road conditions for a given vehicle mix, traffic growth pattern, and time period. The application of different maintenance and improvement strategies, with their associated cost streams, produces different road conditions over time, with associated user cost streams. The HOM model defines the optimal strategy as the one that has the lowest total net present value. The Expenditure Budgeting Model will select the next best program of maintenance activity under budget constraints, when sufficient funds are not available to implement the optimal strategy.
+
+It has long been recognized that user cost savings reflect only a rough measurement of the benefits accruing to society from road investments (5). In particular, the user cost approach does not adequately describe what happens when road access is provided in rural areas. Rural road construction is not merely an incremental change in an existing situation. Roads fundamentally transform the rural way of life by providing opportunities for contact and communication with a wider world. In particular, rural roads provide access to markets, which enables specialization of production and exchange between producers and consumers. Road access is a prerequisite for development programs that are based on the production of cash crops, for which imported inputs and information are needed, as well as markets in which surplus production can be sold. In short, rural roads facilitate the transformation of the rural economy from a static system based on subsistence to a dynamic system based on trade with the outside world.
+
+A methodology to justify rural road investments in terms of the value added in agriculture as a result of the expected change in production has been developed by Carnemark et al. (6). This approach is commonly used in evaluating rural road investments that are part of a rural development package. Beenhakker has shown that the value-added approach is conceptually equivalent to the user cost savings approach (7). If rural markets were perfect and if all transactions were reflected in transport activity, the benefits of rural road investments would indeed correspond to measurable changes in traffic.
+
+The value-added approach assumes that, by reducing transport costs, a rural road improvement will provide an adequate incentive for traders to purchase cash crops at a price that makes it rewarding for the farmer to produce them. It further assumes that these reduced transport costs will be in effect over the life of the project-in other words, that the road will be maintained so that its condition will not deteriorate. Maintenance costs are included in calculating the costs of the improvement. Consequently, if the initial investment is justified, subsequent maintenance should also be justified.
+
+## THE PROBLEM
+
+A maintenance planner could be faced with a problem 5 to JO years after the initial investment was made, that traffic on the road does not appear to justify the planned investment in pefiodic inaintenance. Should the road be abandoned? Should it be allowed to deteriorate to the point where rehabilitation will become necessary? Or should it be maintained, regardless of present traffic levels, in order to preserve the benefits of the rural development program?
+
+The answers to these questions are not obvious. *A* number of other questions need to be answered before a truly optimal maintenance policy can be determined.
+
+## Has the Rural Development Program Failed?
+
+It is possible that the failure of traffic to materialize reflects a genuine failure of the development process. This may be due to physical constraints that were not adequately taken into account in planning investments, such as limited area of suitable soils or inadequate water supply. It may be due to socioeconomic factors such as inappropriate land tenure systems, labor force constraints, or lack of marketing and credit facilities. It may be due to incorrect sector policies on matters such as pricing and taxation, or to the promotion of unsuitable technical packages. Finally, it may be due to unfavorable changes in international commodity markets. All of these are factors over which the maintenance planner has no control. There is no reason to expect that additional investment in road maintenance will reverse the situation, and periodic maintenance in this case is not justified.
+
+#### Is the Lag Time Longer Than Expected?
+
+Rural development prograJ.ll.S are frequently opt1m1st1c in forecasting the speed with which new technologies will be adopted and new production will take place. The expected change process often does take place but at a somewhat slower rate than expected. This delay reduces the rate of return on the original investment package, but this is not the concern of the maintenance planner. From his point of view, the original investment is a sunken cost. What he must be concerned with is the return on a periodic maintenance investment that will keep the road in service for a longer period. Because periodic maintenance represents only a fraction of the cost of the original investment, periodic maintenance is likely to be justified in this case.
+
+# Is the Development Process Taking a Different Form?
+
+Although rural development programs often fail to achieve their intended objectives, particularly if those objectives are defined in terms of the increased production of cash crops, they may well achieve other results that could be seen as contributing to rural welfare. Many of these results depend directly on road access, even though they do not generate great amounts of traffic. Farmers may apply extension advice and inputs such as fertilizer and pesticides to the production of food crops for on-farm consumption and local exchange. Women may be able to diversify family diets through small-scale production of vegetables, fruits, and poultry products. Health and education services may reach out to rural areas, and human factors of production may improve. A wider range of commercial goods may appear in local markets, thereby providing incentives for
+
+more productive use-of leisure time in cash-generating activities. Underutilized labor may respond to a wider range of employment opportunities. A growing network of social relations may begin to link the rural community into regional and national systems.
+
+In this situation, a real cost is associated with road deterioration, especially when a road reaches the point where it is no longer trafficable. Rising road user costs due to deterioration create negative incentives for road use to service providers, traders, and transporters from outside the area, as well as to those rural residents who can afford to use vehicles. At some point, the costs will become too great, and the critical actors in the rural development process will simply cease to use the roads. In an extreme case, the countryside will revert to a subsistence economy, but with this difference-rural residents, the "beneficiaries" of the original investment, will have become deeply disillusioned about development and will be more reluctant to take the risks associated with change and growth in the future.
+
+## **A MODEL FOR EVALUATING MAINTENANCE INVESTMENT**
+
+A proposed model for evaluating alternative strategies for the maintenance of improved low-volume rural roads in potentially productive agricultural areas is described in the following paragraphs. The model is based on experience in sub-Saharan Africa, where road deterioration followed by reversion to a subsistence economy can frequently be observed. The principles of the model, however, can be applied to any developing area. In cases where the development process is less problematic than it is in sub-Saharan Africa, the priority of periodic maintenance should be more readily demonstrated.
+
+Consider the case of an unpaved road, the initial construction cost of which is C, and the expected lifetime of which is t years with annual routine maintenance costs of r(C) and periodic maintenance costs every n years of p(C). It is assumed at the time of road construction that agricultural production will increase by x percent per year for y years as a result of the road. For the sake of simplicity, it can be assumed that no complementary investments are needed to generate this change in production.
+
+The benefit of the investment is the value added due to the increase in agricultural productivity, or the difference between the farmgate value of production and the cost of inputs (including farm labor) multiplied by the increment of production. Again for the sake of simplicity, let us assume that the crop mix, the farmgate price of crops, and the cost of inputs do not change over the analysis period. (This assumption is commonly made to ease the computation of expected benefits, but it is not essential to the analysis. What matters is what will happen to the net value added in agriculture, taking into account all of these factors.) Total benefits are represented by the discounted stream of incremental producti~n benefits and total costs by the discounted stream of construction and maintenance costs.
+
+To illustrate this model, let us assume that the lifetime of the road is 25 years, annual routine maintenance costs are 5 percent of construction costs, and periodic maintenance costs are 20 percent of construction costs every 8 years. Let us further assume that the value of agricultural production (V) will increase by 5 percent per year for IO years as a result of road construction. (This factor could also represent the share of the growth in value added that is attributable to roads that are part of integrated rural development projects.)
+
+In this case, the present value of benefits (discounted at 12 percent) is 2.555(V) and the present value of costs (discounted at 12 percent) is l.3 I 7(C). The investment is justified when the net present value (benefits minus costs) is greater than zero or, in other words, the rate of return is greater than 12 percent. The limitingcaseisgivenby2.555(V) = l.317(C),orC = I.94(V).ln other words, under the assumptions outlined above, the investment is justified when construction costs are approximately twice the value added in agriculture prior to construction. The rate of return on the case where C = 2V is 11.6 percent.
+
+Let us now consider what will happen if the roads are not periodically maintained. If routine road maintenance is regularly performed, unit road user costs will remain approximately constant for the first 8 years. After that, the road will begin to deteriorate and user costs will gradually increase. Eventually, the condition of the road will reach a point where user costs will become a major deterrent to traffic and the road will be, for all practical purposes, abandoned. If routine maintenance is not regularly performed, the road will deteriorate much more rapidly and will eventually become impassable and therefore will require complete rehabilitation. However, for this example, let us assume that routine maintenance continues and that the road gradually deteriorates until the surface is completely lost (Figure I).
+
+A critical assumption concerns the rate of growth of user costs with deferred maintenance. Let us assume that after the first 8 years, user costs will increase by about I 0 percent per year in the absence of timely periodic maintenance. If the benefits of value added in agriculture decrease in proportion to increased user costs, this would mean a loss of 9 percent in the benefits expected in year 9 and of about 18 percent in the benefits expected in year 10. In the following years, expected agricultural benefits will not increase, and losses due to road deterioration will continue to mount. If no periodic maintenance is done, these losses could amount to 80 percent of incremental annual production by the end of the analysis period.
+
+In actual fact, however, user costs do not increase indefinitely. At some point, the surface of the road will become completely worn away but the structure, which is preserved through routine maintenance, will still remain intact. Let us assume that this occurs after about 6 years of deterioration, when the road reaches its worst condition consistent with continued routine maintenance. At this point, losses would amount to about 40 percent of potential benefits. Under these assumptions, with an initial investment the rate of return of which is 11.6 percent, the rate of return for a timely investment in periodic maintenance, calculated over a 14-yr period, treating previous investments as sunk costs, and assuming that routine maintenance is regularly provided, is 12.4 percent.
+
+#### **SENSITIVITY TO ASSUMPTIONS**
+
+Before using this model to explore the effects of deferred maintenance, let us examine the effects of possible changes in some of the basic assumptions. For example, if the pattern of increasing agricultural production originally attributed to the road had been expected to extend over 15 years, the periodic maintenance investment would have a rate of return of 27.3 percent (Figure 2). In this case, failure to maintain the road in year 8 would cause agricultural production to level off at about
+
+![](_page_3_Figure_0.jpeg)
+
+FIGURE 1 Benefits or timely periodk maintenance; benefit growth = 10 years and maintenance interval= 8 years.
+
+![](_page_3_Figure_2.jpeg)
+
+Fl G URE 2 Benefits or timely periodic maintenance; benefit growth = 15 years and maintenance interval = 8 years.
+
+50 percent of the maximum potential production. If periodic maintenance is done in year 8, agricultural production will reach its expected maximum in year 15, as planned. Failure to execute periodic maintenance a second time in year 16 would cause this maximum production to decline, but it would level off at the rate corresponding to the maximum road deterioration, which in this case would be higher than the maximum benefits gained with no periodic maintenance.
+
+If periodic maintenance is needed at more frequent intervals, a smaller proportion of the benefits depends on each maintenance expenditure and the expenditure becomes more difficult to justify. For example, if periodic maintenance needs to be performed after 5 years, and benefits are expected to grow over IO years, the rate of return on the periodic maintenance investment alone would be -5 .9 percent (Figure 3). In this case, benefits in the absence of timely road maintenance would reach a level just slightly higher than those corresponding to the maximum road deterioration. If benefits were expected to extend over 15 years, a failure to perform periodic maintenance in year 5 would cause the benefits to plateau at less than 40 percent of their potential (Figure 4). Periodic maintenance would be needed again in year 10 and if it were not performed, the benefits would peak at about 60 percent of the potential and then decline to the level corresponding to maximum road deterioration.
+
+The model is also somewhat sensitive to the proportion of the original construction costs required for periodic maintenance, which is here assumed to be 20 percent. If, in our example, periodic maintenance costs 25 percent of construction costs, the rate of return on an 8-yr cycle with a I 0-yr benefit growth period would fall to 8.3 percent, and the expenditure would no longer be justified. With benefits growing over 15 years, the rate of return would be 23.1 percent instead of27.3 percent. If periodic maintenance would be necessary after 5 years, the rate of return would be -9.2 percent with a JO-yr benefit period and 5.6 percent with a 15-yr period.
+
+Finally, our example considers an original investment, the rate of return of which is close to 12 percent, which is generally accepted as the minimum rate needed to justify an investment package. An initial investment with a higher rate of return would clearly justify a greater expenditure on periodic maintenance, all other things being equal.
+
+## EFFECTS OF ALTERNATIVE MAINTENANCE STRATEGIES
+
+Consider the alternative strategy of deferring periodic maintenance (Figures 5 and 6). One consequence of deferral is a higher cost when the maintenance does take place, which will be calculated by spreading the assumed cost over the time period considered. Thus, if periodic maintenance is required.every 8 years and costs 20 percent of construction costs, it is assumed that each year of deferral would add 2.5 percent to the cost factor. If periodic maintenance has to be done every 5 years and costs 20 percent of construction costs, each year of deferral would add 4 percent to the cost factor.
+
+A major consequence of deferral is that benefits of the original investment are reduced for the years when periodic maintenance should have taken place but did not. These reductions represent the losses that would have been avoided if periodic maintenance had been performed in a timely manner. We will assume that deferred periodic maintenance restores the
+
+![](_page_4_Figure_10.jpeg)
+
+Fl GU RE 3 Benefits of timely periodic maintenance; benefit growth = 10 years and maintenance interval = 5 years.
+
+![](_page_5_Figure_1.jpeg)
+
+FIGURE 4 Benefits of timely periodic maintenance; benefit growth = 15 years and maintenance interval = 5 years.
+
+![](_page_5_Figure_3.jpeg)
+
+FIGURES Benefits of deferred maintenance (10 years); benefit growth= 10 years and maintenance interval = 8 years.
+
+![](_page_6_Figure_2.jpeg)
+
+FIGURE 6 Benefits of deferred maintenance (8 years); benefit growth = 10 years and maintenance interval= 5 years.
+
+road surface to its original good condition, and that routine maintenance retains this condition until periodic maintenance is due once again.
+
+In the case of maintenance, which should, from a technical point of view, be done every 8 years, rates of return can be calculated for maintenance deferred to years 10, 12, 14, or 16 (Table 1). This comparison shows that deferred maintenance would give the highest rate of return between year 12 and year 14. To determine the optimal year for deferred maintenance, the net present values of these alternative strategies are compared for the year of timely periodic maintenance, which is the year in which the decision has to be made. This analysis suggests that year 12 is the optimal year in both cases (Figures 7 and 8).
+
+A similar analysis for the situation in which periodic maintenance is needed every *5* years is shown in Table 2. In this
+
+TABLE I MAINTENANCE INTERVAL OF 8 YEARS
+
+| Benefit growth over JO years    | NPVin<br>Year 8 | IRR(%), |
+|---------------------------------|-----------------|---------|
+|                                 |                 |         |
+|                                 |                 |         |
+| Timely maintenance (Year 8)     | 0.004           | 12.4    |
+| Deferred maintenance (Year I 0) | 0.020           | I6.3    |
+| Deferred mllintenance (Year 12) | 0.054           | 19.8    |
+| Deferred maintenance (Year 14)  | 0.039           | I6.9    |
+| Deferred maintenance (Year I6)  | 0.000           | 12.0    |
+| Benefit growth over 15 years ·  |                 |         |
+| Timely maintenance (Year 8)     | 0.235           | 27.3    |
+| Deferred maintenance (Year IO)  | 0.296           | 38.0    |
+| Deferred maintenance (Year I 2) | 0.306           | 47.1    |
+| Deferred maintenance (Year I4)  | 0.248           | 45.8    |
+| Deferred maintenance (Year 16)  | 0.180           | ~9.5    |
+
+case, deferring periodic maintenance to years 8, IO, 12, or 15 was considered. As shown in Table 2, periodic maintenance is never justified in this case, but timely maintenance is the optimal strategy if benefits extend over lO years, and deferring periodic maintenance to year IO is the optimal strategy if benefits are expected to extend over 15 years.
+
+TABLE 2 MAINTENANCE INTERVAL OF 5 YEARS
+
+|                                | NPVin  |        |
+|--------------------------------|--------|--------|
+|                                | Year 5 | IRR(%) |
+| Bene/ii growlh over 10 years   |        |        |
+| Timely maintenance (Year 5)    | -0.124 | -5 .9  |
+| Deferred maintenance (Year 8)  | -0.136 | -8.8   |
+| Deferred maintenance (Year IO) | -O.I47 | -I2.4  |
+| Deferred maintenance (Year 12) | -0.156 | -20.3  |
+| Deferred maintenance (Year 15) | -0.163 | -24.1  |
+| Benefit growth over 15 years   |        |        |
+| Timely maintenance (Year 5)    | -0.047 | 8.2    |
+| Deferred maintenance (Year 8)  | -0.063 | 4.8    |
+| Deferred maintenance (Year IO) | -0.050 | 6.0    |
+| Deferred maintenance (Year 12) | -0.053 | 4.8    |
+| Deferred maintenance (Year 15) | -0.068 | 0.8    |
+
+# CONCLUSIONS
+
+The conditions under which periodic maintenance investment in unpaved rural roads can be justified by losses avoided in agriculture alone are relatively restrictive. In the case of a barely feasible initial investment, the benefits of which extend over 10 years, timely periodic maintenance is likely to be justified only if
+
+![](_page_7_Figure_1.jpeg)
+
+FIGURE 7 Benefits of deferred maintenance (12 years); benefit growth = 10 years and maintenance interval = 8 years.
+
+![](_page_7_Figure_3.jpeg)
+
+FIGURE 8 Benefits of deferred maintenance (12 years); benefit growth= 15 years and maintenance interval= 8 years.
+
+maintenance costs are less than 20 percent of construction costs and the maintenance interval is 8 years or more. Furthermore, even in this case, a more efficient use of resources will be achieved by deferring maintenance for 2 to 4 years. Should b~nefit growth extend over a longer period, timely maintenance would become more feasible, but the economically optimal year of maintenance would still be 2 to 4 years later than the year that would be selected according to technical criteria.
+
+Roads that require periodic maintenance at frequent, 5-yr intervals are difficult to justify with agricultural benefits.Unless the costs of such maintenance are considerably less in relation to construction costs than we have assumed here (or construction costs are less in relation to agricultural value added), it might be worthwhile to consider an alternative design standard with higher initial costs that can support traffic for a longer time before periodic maintenance would be needed.
+
+Two caveats should be noted here. The first is a reminder that the model assumes th!lt routine maintenance is regularly performed, even in the absence of periodic maintenance, thereby ensuring that the road does not suffer serious structural deterioration. Expenditures on routine maintenance are almost al ways justified, even at extremely low traffic levels. However, it is often the case that routine maintenance is not done or is not correctly done. In this situation, the road will deteriorate faster and the benefits and costs of periodic maintenance will be higher than shown here.
+
+A second caveat is that the benefits here calculated in terms of losses avoided in agriculture are at least partly reflected in agricultural traffic. Therefore, they cannot simply be added to the user cost savings for existing and projected traffic. Theoretically, user cost savings for non-agricultural traffic could be counted in addition to losses avoided in agriculture. However, in practice it is often difficult to distinguish between agricultural and non-agricultural traffic in rural areas. Therefore, the most prudent approach would be to analyze alternative maintenance strategies either in terms of user cost savings (for traffic volumes above 50 vpd for paved ro&ds or 20 vpd for earth roads) or of value added in agriculture (for roads with lower traffic volumes).
+
+### **OTHER** CONSIDERATIONS
+
+Non-economic considerations often play a major role in government decision-making on the maintenance of lowvolume roads in areas of strategic or political significance. A minimal priority network is needed in each country to ensure social cohesion and to enable governments to fulfill their obligations in times of crisis, such as war or famine. In such cases, the appropriate maintenance strategy would be the least costly alternative to ensure minimum access. In countries where traffic levels are extremely low, it may be more sensible for governments to seek alternative solutions to meet basic access needs instead of maintaining an extensive road network.
+
+#### **REFERENCES**
+
+- l. *The Road Maintenance Problem and International Assistance.*  World Bank, Washington, D.C., 1981.
+- 2. *Highway Design and Maintenance Model.* Vol. 3. World Bank, Washington, D.C., 1985.
+- 3. *The Road Deterioration Problem in Developing Counlries.*  World Bank, Washington, forthcoming. Some initial findings were presented in Asif Faiz and Clell Harral, "The Road Deterioration Problem in Developing Countries: The State of the Road Networks," and related papers presented at the Transportation Research Board 66th Annual Meeting, January 1987.
+- 4. R. Winfrey. *Economic Analysis for Highways.* International Textbook Company, 1968; also, H. G. VanderTakand Anandarup Ray, *The Economic Benefits of Road Transpor/ Projects,* World Bank Staff Occasional Paper No. 13, 1971.
+- *5.* A. A. Walters. *The Economics of Road User Charges.* World Bank Staff Occasional Paper No. 5, 1968.
+- 6. C. Carnemark, J. Biderman, and D. Bovet. *The Economic Analysis of Rural Road Projects.* World Bank Staff Working Paper 241. Washington, D.C., 1976.
+- 7. **H.** L. Beenhakker. *lden1ification and Appraisal of Rural Road Projects.* World Bank Staff Working Paper 362. Washington, D.C., 1979.
+
+*The views and interprelations presenled in !his paper are those of the author and should not be attribUled to the World Bank, to its affiliated organizations, or to any individual acting in their behalf.*

Zotero/001_artiklid/2016aastariigieelarveseadus.md

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+---
+category: literaturenote
+citekey: 2016aastariigieelarveseadus
+title: 2016. aasta riigieelarve seadus – Riigi Teataja
+authors: ""
+url: "https://www.riigiteataja.ee/akt/123122015006"
+zotero_key: PBUSF6K2
+zotero_storage: VZMEB93S
+collections: magistritöö / seadused
+folder: 001_artiklid
+status: converted
+---
+Väljaandja: Riigikogu Akti liik: seadus
+
+Teksti liik: algtekst-terviktekst Redaktsiooni jõustumise kp: 01.01.2016 Redaktsiooni kehtivuse lõpp: 23.11.2016 Avaldamismärge: RT I, 23.12.2015, 6
+
+> Välja kuulutanud Vabariigi President 18.12.2015 otsus nr 717
+
+# **2016. aasta riigieelarve seadus**
+
+Vastu võetud 09.12.2015
+
+**§ 1. Riigieelarve tulud, kulud, investeeringud ja finantseerimistehingud**
+
+|  | Leht 2 / 40 | 2016. aasta riigieelarve seadus |  |
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+|  | 2016. aasta riigieelarve seadus<br>Leht 3 / 40 |  |
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+| Leht 6 / 40<br>2016. aasta riigieelarve seadus |  |  |  |
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+|  | Leht 8 / 40 | 2016. aasta riigieelarve seadus |  |
+|--|-------------|---------------------------------|--|
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+|  |             |                                 |  |
+
+|  | 2016. aasta riigieelarve seadus<br>Leht 9 / 40 |  |  |  |  |  |  |  |  |  |
+|--|------------------------------------------------|--|--|--|--|--|--|--|--|--|
+|  |                                                |  |  |  |  |  |  |  |  |  |
+
+| Leht 10 / 40<br>2016. aasta riigieelarve seadus |  |
+|-------------------------------------------------|--|
+|                                                 |  |
+|                                                 |  |
+
+| 2016. aasta riigieelarve seadus<br>Leht 11 / 40 |  |
+|-------------------------------------------------|--|
+|                                                 |  |
+
+|  |  | 2016. aasta riigieelarve seadus<br>Leht 17 / 40 |  |
+|--|--|-------------------------------------------------|--|
+
+|  | Leht 18 / 40 | 2016. aasta riigieelarve seadus |  |
+|--|--------------|---------------------------------|--|
+|  |              |                                 |  |
+|  |              |                                 |  |
+|  |              |                                 |  |
+
+|  |  | 2016. aasta riigieelarve seadus<br>Leht 19 / 40 |  |
+|--|--|-------------------------------------------------|--|
+|  |  |                                                 |  |
+|  |  |                                                 |  |
+|  |  |                                                 |  |
+
+|  | Leht 20 / 40 | 2016. aasta riigieelarve seadus |  |
+|--|--------------|---------------------------------|--|
+|  |              |                                 |  |
+|  |              |                                 |  |
+
+|  |  | 2016. aasta riigieelarve seadus<br>Leht 23 / 40 |  |
+|--|--|-------------------------------------------------|--|
+|  |  |                                                 |  |
+|  |  |                                                 |  |
+
+|  | Leht 24 / 40 | 2016. aasta riigieelarve seadus |  |
+|--|--------------|---------------------------------|--|
+|  |              |                                 |  |
+|  |              |                                 |  |
+|  |              |                                 |  |
+
+|  | Leht 28 / 40 | 2016. aasta riigieelarve seadus |  |
+|--|--------------|---------------------------------|--|
+|  |              |                                 |  |
+|  |              |                                 |  |
+|  |              |                                 |  |
+
+|  |  | 2016. aasta riigieelarve seadus<br>Leht 29 / 40 |  |
+|--|--|-------------------------------------------------|--|
+|  |  |                                                 |  |
+|  |  |                                                 |  |
+|  |  |                                                 |  |
+
+|  | Leht 30 / 40 | 2016. aasta riigieelarve seadus |  |
+|--|--------------|---------------------------------|--|
+
+|  | Leht 32 / 40 | 2016. aasta riigieelarve seadus |  |
+|--|--------------|---------------------------------|--|
+|  |              |                                 |  |
+|  |              |                                 |  |
+|  |              |                                 |  |
+
+|  |  | 2016. aasta riigieelarve seadus<br>Leht 33 / 40 |  |
+|--|--|-------------------------------------------------|--|
+|  |  |                                                 |  |
+|  |  |                                                 |  |
+
+|  |  | 2016. aasta riigieelarve seadus<br>Leht 35 / 40 |  |
+|--|--|-------------------------------------------------|--|
+|  |  |                                                 |  |
+|  |  |                                                 |  |
+
+| Leht 36 / 40<br>2016. aasta riigieelarve seadus |  |  |  |  |
+|-------------------------------------------------|--|--|--|--|
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+
+# **§ 2. Seadustest tulenevate määrade ja piirsummade kehtestamine**
+
+- (1) Õppetoetuste ja õppelaenu seaduse alusel kehtestatavad määrad on:
+- 1) üliõpilase vajaduspõhise õppetoetuse saamiseks arvestatava keskmise sissetuleku ülemmäär 358 eurot kuus vastavalt seaduse § 5 lõike 2<sup>1</sup> punktile 3;
+- 2) kutseõppe õppekava õpilase põhitoetuse suurus 60 eurot õppekuus vastavalt seaduse § 12 lõikele 1;
+- 3) doktoranditoetuse suurus 422 eurot kalendrikuus vastavalt seaduse § 12 lõikele 1;
+- 4) üliõpilase vajaduspõhise õppetoetuse suurus taotleja ühe kuu sissetuleku korral kuni 89,50 eurot 220 eurot õppekuus, sissetuleku korral vahemikus 89,51 kuni 179 eurot 135 eurot õppekuus ning sissetuleku korral vahemikus 179,01 kuni 358 eurot 75 eurot õppekuus vastavalt seaduse § 12 lõikele 2;
+- 5) üliõpilase vajaduspõhise eritoetuse suurus 135 eurot õppekuus vastavalt seaduse § 12 lõikele 1;
+- 6) üliõpilase põhitoetuse suurus 55,93 eurot ja täiendava toetuse suurus 28,13 eurot õppekuus vastavalt seaduse § 42 lõikele 5.
+- (2) Põhikooli- ja gümnaasiumiseaduse § 77 lõike 3 alusel kehtestatav õpetaja lähtetoetuse suurus on 12 783 eurot.
+- (3) Tartu Ülikooli seaduse § 7<sup>3</sup> lõike 1 alusel kehtestatav maksimaalne arst-residendi koha maksumus on 2542,7 eurot kuus.
+- (4) Riiklike peretoetuste seaduse § 4 lõigete 2 ja 3 alusel kehtestatav lapsetoetuse määr on 9,59 eurot kuus ja lapsehooldustasu määr 76,70 eurot kuus.
+- (5) Vanemahüvitise seaduse § 3 lõike 6 alusel kehtestatav vanemahüvitise määr on 390 eurot kuus.
+- (6) Puuetega inimeste sotsiaaltoetuste seaduse § 5 lõike 1 alusel kehtestatav puuetega inimeste sotsiaaltoetuste määr on 25,57 eurot kuus.
+- (7) Tööturuteenuste ja -toetuste seaduse alusel kehtestatavad määrad on:
+- 1) ettevõtluse alustamise toetuse ülemmäär 4474 eurot vastavalt seaduse § 19 lõikele 9;
+- 2) tugiisikuga töötamise teenuse osutamise eest makstav tunnitasu määr 2,56 eurot vastavalt seaduse § 23 lõikele 6;
+- 3) töötutoetuse päevamäär 4,41 eurot vastavalt seaduse § 31 lõikele 1;
+- 4) stipendiumi päevamäär 3,84 eurot vastavalt seaduse § 35 lõikele 6;
+- 5) sõidu- ja majutustoetuse määr ühe kilomeetri kohta 0,10 eurot ja ülemmäär 26 eurot päevas vastavalt seaduse § 37 lõikele 5;
+- 6) madala sissetulekuga töötavale isikule tehtava tagasimakse suuruse arvutamise aluseks olev määr 228 eurot vastavalt seaduse § 37<sup>3</sup> lõikele 4;
+- 7) tööalase rehabilitatsiooni teenuse osutamise ülemmäär 1800 eurot koos käibemaksuga kalendriaastas vastavalt seaduse § 23<sup>1</sup> lõikele 4.
+- (8) Sotsiaalhoolekande seaduse alusel kehtestatavad määrad on:
+- 1) üksi elava isiku või perekonna esimese liikme toimetulekupiir 130 eurot kuus;
+- 2) psüühiliste erivajadustega inimeste erihoolekande kogukonnas elamise teenusele suunatud isiku maksimaalne omaosalus 230 eurot kuus ning ööpäevaringsele erihooldusteenusele suunatud isiku maksimaalne omaosalus 230 eurot kuus, kui ööpäevaringset erihooldusteenust osutatakse hoolekandeasutuse ühes või igas eraldiseisvas hoones korraga rohkem kui kaheteistkümnele isikule, ja ööpäevaringsele erihooldusteenusele suunatud isiku maksimaalne omaosalus 270 eurot kuus, kui ööpäevaringset erihooldusteenust osutatakse hoolekandeasutuse ühes või igas eraldiseisvas hoones kuni kaheteistkümnele isikule;
+- 3) ööpäevaringse erihooldusteenuse maksimaalne maksumus kohtumäärusega hoolekandeasutusse paigutatud isiku kohta 909 eurot kuus ja alaealise isiku kohta 1945 eurot kuus;
+- 4) vajaduspõhise peretoetuse sissetulekupiir perekonna esimese liikme kohta 358 eurot kuus.
+- (9) Riikliku matusetoetuse seaduse § 6 lõike 1 alusel kehtestatav matusetoetuse suurus on 250 eurot.
+- (10) Sotsiaalmaksuseaduse § 2<sup>1</sup> alusel kehtestatav sotsiaalmaksu maksmise aluseks olev kuumäär on 390 eurot.
+- (11) Spordiseaduse § 13 lõike 2 alusel kehtestatav olümpiavõitja toetuse määr on 650 eurot kuus.
+- (12) Riigieelarve seaduse alusel kehtestatavad määrad on:
+- 1) riigi võlakohustuste suurim lubatud jääk 1 840 000 000 eurot vastavalt seaduse § 69 lõikele 2;
+- 2) Vabariigi Valitsuse antavate laenude ja riigigarantiide suurim lubatud jääk 577 000 000 eurot vastavalt seaduse § 61 lõikele 5.
+- (13) Kooskõlas välissuhtlemisseaduse § 20 punktiga 5 ei ole vaja Riigikogus ratifitseerida välislepinguid, millest ühelgi eesseisval eelarveaastal Eesti Vabariigile tulenevate varaliste kohustuste või saamata jääva tulu maht ei ületa 3 protsenti riigiasutusele, kelle algatusel välisleping sõlmitakse, jooksvaks eelarveaastaks ettenähtud kulude summast.
+- (14) Muuseumiseaduse alusel on:
+
+- 1) 2016. aasta jooksul eksponeeritavate näituste riigi tagatava näituse kahjuhüvitise kogusumma piirmäär 42 000 000 eurot vastavalt seaduse § 28 lõike 3 punktile 1;
+- 2) omavastutuse suurus 2000 eurot ühe näituse kohta vastavalt seaduse § 28 lõike 3 punktile 2;
+- 3) kümmet miljonit eurot ületava väärtusega näituse "Fotorealism: 50 aastat hüperrealistlikku maali", mille omanik on Tübingeni *Institut für Kulturaustausch* Saksamaalt, kavandatav vedamise periood 28. veebruarist 30. juunini 2016, eksponeerimise periood 17. märtsist 12. juunini 2016 vastavalt seaduse § 28 lõike 3 punktile 3.
+
+# **§ 3. Kohaliku omavalitsuse üksustele tasandus- ja toetusfondi jaotamise põhimõtted**
+
+(1) Tasandusfondi toetus *T* arvutatakse järgmiselt:
+
+$$T = (AK - AT) * k$$
+, kus
+
+$$AK = \sum_{n=1}^{6} C_n * P_n$$
+
+$$AT = (TM_{2015} + RM_{2015}) * 0,5 + (TM_{2014} + RM_{2014}) * 0,3 + (TM_{2013} + RM_{2013}) * 0,2 + MM_{40155}$$
+
+$$\sum_{n=0}^{6} C_n * P_n$$
+
+- *T* tasandusfondi suurus konkreetses kohaliku omavalitsuse üksuses;
+- *AK* konkreetse kohaliku omavalitsuse üksuse arvestuslik keskmine tegevuskulu;
+- *AT* konkreetse kohaliku omavalitsuse üksuse arvestuslikud tulud;
+- k toetustaseme koefitsient väärtusega 0,9;
+- *C<sup>n</sup>* konkreetse kohaliku omavalitsuse üksuse laste (0–6 eluaastat) arv, kooliealiste (7–18 eluaastat) arv, tööealiste (19–64 eluaastat) arv, vanurite (65+ eluaastat) arv rahvastikuregistri andmetel, kohalikest teedest maanteede ja tänavate arvestuslik pikkus (kõvakattega maanteed koefitsiendiga 0,26; tänavad 0,74; mittekõvakattega maanteed 0,047) kilomeetrites riikliku teeregistri andmetel ning hooldatavate ja hooldajateenust saavate puudega isikute kaalutud keskmine arv aastatel 2006–2008 hooldajatoetuse aruandele vastavalt;
+- *P<sup>n</sup>* kohaliku omavalitsuse üksuste arvestuslik keskmine tegevuskulu ühe lapse, kooliealise, tööealise, vanuri, hooldatava ja hooldajateenust saava puudega isiku kohta ning kohalikest teedest maanteede ja tänavate arvestusliku pikkuse ühe kilomeetri kohta eurodes;
+  - konkreetse kohaliku omavalitsuse üksuse laste arvu, kooliealiste arvu, tööealiste arvu, vanurite arvu, hooldatavate ja hooldajateenust saavate puudega isikute kaalutud keskmise arvu ning kohalikest teedest maanteede ja tänavate arvestuslike koefitsientidega korrigeeritud pikkuse kilomeetrites ja iga vastava näitaja osas ühe ühiku kohta arvutatud arvestusliku keskmise tegevuskulu korrutiste kogusumma eurodes;
+- *TM* üksikisiku tulumaksu laekumine konkreetses kohaliku omavalitsuse üksuses vastavalt 2013., 2014. ning 2015. aastal korrutatuna 11,6-ga ning jagatuna vastaval aastal kehtinud tulumaksuseaduse redaktsiooni § 5 lõike 1 punktis 1 toodud määraga;
+  - konkreetse kohaliku omavalitsuse üksuse arvestuslik maamaks (1,25 protsenti üldise maa ja 0,6 protsenti põllumajandusmaa maksustamise hinnast 2015. aastal), millest on maha arvatud looduskaitsealade soodustused, sealhulgas alates 2016. aastast kehtima hakkavad looduskaitsealade soodustused, mille mõju on suurem kui 1000 eurot kohaliku omavalitsuse kohta, ning kodualuse ja ühiskondlike ehitiste aluse maa maksuvabastuse mõju;
+
+*RM* – konkreetse kohaliku omavalitsuse üksuse kohaliku tähtsusega maardlate maavarade kaevandamisõiguse tasu laekumine vastavalt 2013., 2014. ning 2015. aastal.
+
+ (2) Toetusfondi vahendite jaotamise arvnäitajad, arvnäitajate väärtused ja arvnäitajatega arvestamise alused kehtestab Vabariigi Valitsus riigieelarve seaduse § 48 lõikes 4 nimetatud määrusega.
+
+#### **§ 4. Valitsemisalade tegevuskulude liigendamine**
+
+- (1) Minister ja riigisekretär liigendavad oma valitsemis- või haldusala eelarve TK-objektikoodiga kavandatud vahendid majandusliku sisu järgi ja administratiivselt, lähtudes kulude täpsustumisest erinevate toetuse saajate vahel.
+- (2) Käesoleva seaduse § 1 6. osa 9. jao *Rahandusministeeriumi valitsemisala* konto 70 *Saadud siirded riigiasutustelt* arvel tehtavate maantee-, vee- ja õhutranspordi korraldamise kulude jaotuse maavalitsuste vahel kinnitab majandus- ja taristuminister.
+- (3) Käesoleva seaduse § 1 6. osa 9. jao *Rahandusministeeriumi valitsemisala* konto 70 *Saadud siirded riigiasutustelt* arvel tehtavate sotsiaalse kaitse kulude jaotuse maavalitsuste vahel kinnitab sotsiaalkaitseminister ning ennetustegevuste ja teenuste jaotuse maavalitsuste vahel kinnitab tervise- ja tööminister.
+- (4) Käesoleva seaduse § 1 6. osa 9. jao *Rahandusministeeriumi valitsemisala* konto 70 *Saadud siirded riigiasutustelt* arvel rahvastikuregistriga seotud ülesannete täitmiseks tehtavate kulude jaotuse maavalitsuste vahel kinnitab siseminister.
+
+## **§ 5. Tegevusala alusel määratud kulude tegemine**
+
+- (1) Vabariigi Valitsusel on õigus teha muudatusi käesoleva seadusega määratud kulude tegevusala klassifikaatori COFOG liigenduses ministeeriumide valitsemisalade ja Riigikantselei haldusala ning põhiseaduslike institutsioonide vahel administratiivselt ja majandusliku sisu järgi.
+- (2) Ministeeriumidel oma valitsemisala ja Riigikantseleil oma haldusala piires ning põhiseaduslikel institutsioonidel on õigus teha muudatusi käesoleva seadusega määratud kulude tegevusala klassifikaatori COFOG liigenduses administratiivselt ja majandusliku sisu järgi.
+
+### **§ 6. Riigi Kinnisvara Aktsiaseltsile riigieelarves planeeritud rendikulu mahtude muutmine**
+
+ Vabariigi Valitsusel on õigus põhjendatud juhtudel muuta ministeeriumile, Riigikantseleile või põhiseaduslikule institutsioonile käesoleva seaduse §-s 1 eelarve kontodel 5, 450, 650 ja 206 objektikoodiga SE000028 *Vahendid Riigi Kinnisvara ASile* ettenähtud vahendeid riigieelarves vastavale ministeeriumile, Riigikantseleile või põhiseaduslikule institutsioonile samal eelarve kontol ettenähtud vahendite ulatuses.
+
+# **§ 7. Haridus- ja Teadusministeeriumi valitsemisala eelarve kasutamine ja täiendav liigendamine**
+
+ Haridus- ja teadusministril on õigus muuta käesoleva seaduse § 1 6. osa 2. jao *Haridus- ja Teadusministeeriumi valitsemisala* programmidesisest vahendite liigendust tegevuskulude ja investeeringute vahel, muutmata seejuures riigieelarve seaduse § 31 lõike 1 alusel Vabariigi Valitsuse kehtestatud investeeringute kinnisasjadesse liigendust objektide kaupa. Haridus- ja teadusministri tehtavad muudatused kooskõlastatakse eelnevalt Rahandusministeeriumiga riigieelarve seaduse § 35 lõike 4 alusel sätestatud korra kohaselt.
+
+#### **§ 8. Eesti Haigekassa eelarvepositsioon**
+
+ Eesti Haigekassa seaduse § 36 lõike 1<sup>2</sup> alusel kinnitatav Eesti Haigekassa põhitegevuse tulem on järgmine:
+
+- 1) 2016. aastal –9,1 miljonit eurot;
+- 2) 2017. aastal –1,3 miljonit eurot;
+- 3) 2018. aastal –0,9 miljonit eurot;
+- 4) 2019. aastal 0 eurot.
+
+Eiki Nestor Riigikogu esimees

Zotero/001_artiklid/63284820080110112047.md

@@ -0,0 +1,258 @@
+---
+category: literaturenote
+citekey: 63284820080110112047
+title: 63_2848_20080110112047
+authors: ""
+zotero_storage: L5YBXS5F
+collections: imporditud
+folder: 001_artiklid
+status: converted
+---
+# **LOCAL TESTS OF THE OPERATING SPEED MODELS FOR CURVES**
+
+*Piras C.* 
+
+*PhD Student – University of Cagliari* – *[cpiras@unica.it](mailto:cpiras@unica.it)* 
+
+*Pinna F.* 
+
+*Researcher – University of Cagliari – [fpinna@unica.it](mailto:fpinna@unica.it)*
+
+### **ABSTRACT**
+
+The paper aims to test operating speed models for curve sections on local two lane rural roads.
+
+In the beginning, the most important national and international models, which enable to calculate operating speed, are summed up. The form of the prediction models and number of variables used in each of them vary considerably. The most common operating speed models, proposed by many researchers of different countries, provide V85 as a function of the Degree of Curvature (DC) or of the Curvature Change Rate of the single curve (CCRs). All operating speed models, considered in this paper, are developed through regression analysis of collected speeds of free passenger cars.
+
+Afterward speed data are recorded on local curves. Different constraints have been imposed to select curve sites: rural area, relatively low traffic volume, marked and paved roadways with constant lane width, no stop control or intersections near to curve, the design speed ranges from 60 km/h to 100 km/h and the general speed limit is 90 km/h (in accordance with the "Italian Road Code"), longitudinal grades ≤ 5%.
+
+Subsequently, the most important national and international models, which have been gathered preceding, are applied on chosen curve sections, in order to calculate V85.
+
+Speed surveys are compared with the results of the models application.
+
+The article includes also a summary of the data collected and the results of a statistical analysis showing speed trends.
+
+The target of the paper is to verify on local roads the applicability of the existing speed models in order to implement them in the following step of the research work.
+
+*Keywords: two-lane rural highway, speed prediction, operating speed, design consistency* 
+
+### **1. INTRODUCTION**
+
+In the last years, in order to increase road safety, the importance given to the respect of the driver expectancy is improved. Several studies show that geometric design consistency enhances road safety conditions. The complex relationships between road features and driver behaviour play a very important role in collision occurrence. In fact, accident probability is higher where alignment consistency lacks. For this reason, different studies show that parameters, which are still present in some guidelines in force in many countries, are outdated.
+
+The most common criteria for design consistency evaluation are based on the operating speed concept. AASHTO defines operating speed as "the speed at which drivers are observed operating their vehicles during free-flow conditions, the 85th percentile of the distribution of observed speeds is the most frequently used measure of the operating speed associated with a particular location or geometric feature"[1]. Besides, the distribution of operating speed on alignment is a quantitative measure of the general character of the road and the relationships between driver behaviour and highway. In fact, the distribution of operating speed may identify a geometric inconsistency when there is a high rate of change for successive roadway sections. Several design standards use already operating speed concept to select design speed values and/or alignment element admissible values.
+
+The concept of geometric design consistency is also used to correlate accident risk with geometric alignment. Along horizontal curves accident rate is up to 4 times higher than tangents. For this reason, the majority of operating speed studies focus on horizontal curves of two-lane rural highways, even if there are also many tangent models.
+
+The principal target of this paper is testing curve speed models, for two lane rural roads, on local highways using data collected on different horizontal curve sections.
+
+Before, the most important national and international models, that permit to calculate operating speed, are reviewed. Subsequently, these models are tested on three sections of two lane rural roads. Next speed surveys are carried out. Only passenger vehicles are included in this study.
+
+The research project, which is carried out by the Department of Land Engineering of the University of Cagliari, aims to develop a speed model between road features (e.g. CCR, available sight distance) and operating speed.
+
+## **2. SPEED MODELS**
+
+Several studies show that the car speed plays an important role in accident occurrence, in particular when considerable high speed reductions are required. Therefore, the design standards of different countries require to compare design speeds of adjacent sections, in order to limit the difference between their values.
+
+Many countries still use the design speed as base parameter to calculate the limit values of the alignment elements. On the one hand the standard of some countries are based on the operating speed concept, on the other hand the most of guidelines of the other refer to this concept only in the post-road design. Finally, several countries use the expected operating speed as base to select design speed or/and specific geometric element values and to reduce design inconsistencies.
+
+For example, the Australian standards are based on McLean research that defines 85th percentile speed as a function of the curve radius and the desired speed, which is "the speed at which driver chooses to travel under free-flow conditions, when they are not constrained by alignment features" [2].
+
+The form of the operating speed prediction models and number of variables used in each of them vary considerably. The most common operating speed models, proposed by many researchers of different countries, provide V85 as a function of the Degree of Curvature (DC) or of the Curvature Change Rate of the single curve (CCRs) or of the Radius (R). These parameters are given by the following equations:
+
+$$DC = 100 \times \left(360 / 2\pi R\right) \tag{Eq. 1}$$
+
+$$CCRs = [63700 \times (\frac{L_{c1}}{2R} + \frac{L_{cr}}{R} + \frac{L_{c2}}{2R})]/L$$
+ (Eq. 2)
+
+(where: DC [degree/100 m], R = radius of circular curve [m], CCRs [gon/km], Lc1 and Lc2 = lengths of clothoids (preceding and succeeding circular curve) [m], Lcr = length of circular curve [m], L = overall length of curve section [km], 63700 = 200/π × 103 ).
+
+In this paragraph several models that permit to calculate operating speed as a function of CCRs [Table 1] and curve radius are reviewed [Table 2].
+
+| Model                             | Equation                              | R2   |  |  |
+|-----------------------------------|---------------------------------------|------|--|--|
+| McLean - Australia [2]            | V85 = 101.2 – 0.043 CCRs              | 0.87 |  |  |
+| Lamm et al. – Germany [2]         | V85 = 106<br>/ (8270 + 8.01 CCRs)     | 0.73 |  |  |
+| Lamm et al. [2]                   | V85 = 95.6 – 0.0438 CCRs              | 0.82 |  |  |
+| Psarianos et al. – Greece [2]     | V85 = 106<br>/ (10150.1 + 8.529 CCRs) | 0.81 |  |  |
+| Lamm et al – United States [2]    | V85 = 93.85 – 0.05 CCRs               | 0.79 |  |  |
+| Krammes and Ottesen [2]           | V85 = 103.04 – 0.053 CCRs             | 0.80 |  |  |
+| where: V85 [km/h]; CCRs [gon/km]. |                                       |      |  |  |
+
+**Table 1 Operating speed prediction models using CCRs value** 
+
+![](_page_3_Figure_1.jpeg)
+
+**Figure 1 Graph representing analytical models where V85 is expressed as a function of CCRs** 
+
+All operating speed models considered in this paper are developed through regression analysis of adopted speed on two lane rural roads of free passenger cars (headway of at least 5 seconds). Speed data are recorded with dry and wet pavement conditions, on longitudinal grades ≤ 6% (even if its effect is generally ignored).
+
+In the tables, the international models that better represent local situations have been summarized.
+
+| Model                     | Equation                            | R2   |  |  |
+|---------------------------|-------------------------------------|------|--|--|
+| Ottesen and Krammes [3]   | V85 = 103.66 – 1.95 · (1746.38 / R) | 0.80 |  |  |
+| Kannelaidis et al. [4]    | V85 = 129.88 – (623.1 / √R)         | 0.78 |  |  |
+| Lamm et al. [2]           | V85 = 94.398 – (3188.656/R)         | 0.79 |  |  |
+| where: V85 [km/h]; R [m]. |                                     |      |  |  |
+
+**Table 2 Operating speed prediction models using radius value** 
+
+![](_page_4_Figure_1.jpeg)
+
+**Figure 2 Graph representing analytical models where V85 is expressed as a function of horizontal radius, R** 
+
+### **2.1 Italy**
+
+A study, carried out by the Department of Civil Engineering of the University of Trieste, proposes an operating speed prediction model for curves and tangents. The researchers define also environmental speed: as the maximum speed that can be reached on tangents or very large radius curves belonging to a homogeneous road section identified by an analysis of the curvature change rate, CCR [5]. They provide a prediction model to obtain the operating speed as a function of the horizontal radius and the environmental speed, which is obtained as a function of the road section geometric features. Starting with Australian study, speed environment represents the speed which drivers go at when they are not conditioned by traffic or by features of the single road elements [5]. The environmental speed value depends on the road section geometric characteristics, available sight distance, frequency of junctions and accesses, terrain type, carriageway width, and so on.
+
+$$V_{env} = 200.97 \times CCR - 0.16 \tag{Eq. 3}$$
+
+(where: R2 = 0.87, Venv [km/h], CCR [gon/km])
+
+All data are collected during daylight hours under dry pavement condition and in the presence of low traffic. The researchers consider roads with the usual cross sections of Italian two-lane rural roads: with two lanes (3,25 ≤ lane width ≤ 3,75 m), with two paved shoulders (0 ≤ shoulder width ≤ 1,50 m), with the longitudinal grade ≤ 4.00% (even if prediction models are not influenced by grades).
+
+They test the influence of the length of the curve, the radius of the preceding curve, the length of the preceding tangent and the super-elevation. In the prediction of speed value on curve the most significant are the radii of the curves (R) and the environmental speed (Venv) of the homogenous section.
+
+$$V_{85} = V_{env}/(1 + 4.75/R \times 0.58)$$
+ (Eq. 4)
+
+ (where: R2 = 0.88, R = the curve radius [m], Venv and V85 [km/h]).
+
+Most speed prediction models estimate the operating speed on horizontal curves using two-dimensional alignment variables. A few models consider the effects of vertical grades on speed; some specify a range of grades in which it is valid.
+
+### **3. LOCAL TESTS**
+
+The preliminary aim of this research is to collect vehicle speeds on a particular site, in order to test V85 models that have been explained above. Several two-lane rural highway segments are chosen for data collection. The following constraints have been imposed for the selection of curve sites: rural area, relatively low traffic volume, marked and paved roadways with constant lane width, no stop control or intersections near to curves, maximum longitudinal grade 4,00 %. All data are collected during daylight hours, in good weather conditions and with a dry pavement. The data collecting excludes non-passenger cars and vehicles with less than 5 second headway from the previous vehicle (free flow). The speed surveys are carried out using a radar speedometer. Road alignments is made up of tangent and circular curves, there are not clothoids. In fact, highways chosen are designed with preceding guidelines within them clothoids was not mentioned.
+
+### **3.1 Site n. 1 – S.S. n. 547**
+
+The curve section is located along the S.S. n. 547. The cross-section is made up of two lanes that are 3,50 m wide, no paved shoulders which are 1,00 m wide, Longitudinal grade is 3,75 %.
+
+![](_page_5_Figure_9.jpeg)
+
+**Figure 3 Plan of site n. 1 – S.S. n. 547** 
+
+The speed data are collected at a middle point of circular curve (R = 70 m). A total of 253 individual speed observations are collected on both directions. The operating speed registered is 61 km/h.
+
+![](_page_6_Figure_1.jpeg)
+
+**Figure 4 Speed distribution on site n. 1** 
+
+### **3.2 Site n. 2 – S.S. n. 125**
+
+The curve section is located along the S.S. n. 125. The cross-section is made up of two lanes that are 3,25 m wide, no paved shoulders which are 0,50 m wide. Longitudinal grade is 2,70 %.
+
+![](_page_6_Figure_5.jpeg)
+
+**Figure 5 Plan of site n. 2 – S.S. n. 125** 
+
+The speed data are collected at middle point of circular curve (R = 55 m). A total of 168 individual speed observations are collected on both directions. The operating speed registered is 49 km/h.
+
+![](_page_7_Figure_1.jpeg)
+
+**Figure 6 Speed distribution on site n. 2** 
+
+### **3.3 Site n. 3 – S.S. n. 125 (new section)**
+
+The cross section of the roads are equal to those recommended by the new Italian guidelines for two-lane rural roads (type C1) [6]: it is 10.5 m width (two lanes width 3.75 m and two shoulders width 1.50 m). All the geometric elements of the horizontal and vertical alignments are designed according to the Italian design guidelines [6]. The general speed limit is 90 km/h (in accordance with the "Italian Road Code").
+
+The speed data are collected on a middle point of the circular curve (R = 1500 m). A total of 208 individual speed observations are collected on both directions. The horizontal curve is preceded and succeeded by clothoids.
+
+The operating speed registered is 129 km/ h.
+
+![](_page_7_Figure_7.jpeg)
+
+**Figure 7 Plan of site n. 3 – S.S. n. 125** 
+
+![](_page_8_Figure_1.jpeg)
+
+**Figure 8 Speed distribution on site n. 3** 
+
+All results are summarized in the Table 3
+
+**Table 3 Operating speed registered on several sites** 
+
+|          | R    | L   | CCRs | i    | V85 |
+|----------|------|-----|------|------|-----|
+| Site n.1 | 70   | 60  | 910  | 3,75 | 61  |
+| Site n.2 | 55   | 80  | 1158 | 2,70 | 49  |
+| Site n.3 | 1500 | 285 | 30   | 3,00 | 129 |
+
+where: L = length of horizontal curve [m], V85 = operating speed [km/h]; CCRs = Curvature Change Rate of the single curve [gon/km]; R = curve radius[m]; i = longitudinal grade [%].
+
+For the preliminary estimation of operating speed, the predicting model, which have been found in literature, are used. The results are summarized in the Table 4.
+
+The paper wants to test, on some significant sections, several national and international models in order to implement the most significant with another variables, for example available sight distance.
+
+The comparison between speeds observed on curve sections shows that the V85 collected is not perfectly in accordance with the results of the different relationships that are analysed above, even if they are similar.
+
+It is most important to underline that although two sites have a relatively small radius, the operating speed models results are similar to speed collected.
+
+Instead it is significant that on the site located in the road designed in accordance with new Italian design standards [6] operating speed gathered is bigger than ones calculated using analytical models.
+
+**Table 4 Operating speed values** 
+
+|                                                     |                                          | Site n.1          | Site n.2          | Site n.3          |  |
+|-----------------------------------------------------|------------------------------------------|-------------------|-------------------|-------------------|--|
+| Model                                               | Equation                                 | V85<br>(surveyed) | V85<br>(surveyed) | V85<br>(surveyed) |  |
+|                                                     |                                          | 61                | 49                | 129               |  |
+| McLean<br>Australia                                 | V85 = 101.2 – 0.043 CCRs                 | 62                | 51                | 100               |  |
+| Lamm et<br>al.<br>Germany                           | V85 = 106<br>/ (8270 + 8.01 CCRs)        | 64                | 57                | 118               |  |
+| Psarianos<br>et al.                                 | V85 = 106<br>/ (10150.1 + 8.529<br>CCRs) | 56                | 50                | 96                |  |
+| Lamm et<br>al. United<br>States                     | V85 = 93.85 – 0.05 CCRs                  | 48                | 36                | 92                |  |
+| Krammes<br>and<br>Ottesen                           | V85 = 103.04 – 0.053 CCRs                | 55                | 42                | 101               |  |
+| Ottesen<br>and<br>Krammes                           | V85 = 103.66 – 1.95 · (1746.38 /<br>R)   | 55                | 42                | 101               |  |
+| Kannelaidis<br>et al.                               | V85 = 129.88 – (623.1 / √R)              | 55                | 46                | 114               |  |
+| University<br>of Trieste                            | Venv = 200.97 · CCR –0.16                | 68                | 65                | 116               |  |
+|                                                     | V85c = Venv / (1 + 4.75 / R 0.58)        | 48                | 44                | 109               |  |
+| where: V85 [km/h]; Venv [km/h] CCRs [gon/km]; R [m] |                                          |                   |                   |                   |  |
+
+The table underlines like the models considered are linked with local road environment. In fact there are high differences among several results. For this reason, drawing up a model, locally valid, could be necessary. The target of this first step of project research is to know local validity of some operating speed models.
+
+### **4. CONCLUSION**
+
+Finally the aim is improving these prediction models or drawing up a new model. Therefore it will be necessary to enlarge sample data and to consider some other independent variables, as for instance available sight distance. An experimental survey is actually ongoing.
+
+10
+
+Once such variables as category of the road, characteristics of the traffic, and so on, have been identified, we can determine some relationships, which are valid not only locally. As a consequence, it is opportune to widen the sample of roads studied.
+
+Further surveys will be carried out in order to complete the test of the model explained above. The aim of the analysis was to investigate the relationship between the operating speed and the geometric features, into the studies of several countries, in order to create an operating speed model, where the V85 is expressed as a function of CCR and available sight distance.
+
+This paper represents a first step, of our research project, that, starting from the existing models, wants to create a model locally valid. The following step will be select other sites to know the models, which represent better the driver behavior on rural roads, which are designed in accordance with the new Italian Road Guidelines.
+
+### **ENDNOTES**
+
+- [1] AASTHO American Association of State Highway and Transportation Officials (2001) - *A Policy on Geometric Design of Highways and Streets* - AASTHO, Washington D.C.
+- [2] LAMM, R. PSARIANOS, B. MAILAENDER, T. (1999) *Highway Design and Traffic Safety Engineering Handbook -* McGraw-Hill Handbooks, New York, United States.
+- [3] OTTESEN, J.L. KRAMMES, R. (2000) "Speed-Profile Model for a Design-Consistency Evaluation Procedure in the United States" - *Transportation Research Record 1701 National Research Council*, Washington D.C., pp. 76 – 85.
+- [4] GIBREEL, G.M. EASA, S.M. EL-DIMEERY, I.A. (2001) "Prediction of Operating Speed on Three-Dimensional Highway Alignments" - *Journal of Transportation Engineering 127*, RE No. 1127, pp. 21 – 30.
+- [5] CRISMAN, B. MARCHIONNA, A. PERCO, P. ROBBA, A. ROBERTI, R. (2005) "Operating Speed Prediction Model for Two-Lane Rural Roads" - *3rd International Symposium on Highway Geometric Design*, Chicago, USA.
+- [6] MINISTERO DELLE INFRASTRUTTURE E DEI TRASPORTI, (2001) *Norme funzionali e geometriche per la costruzione delle strade D.M. 05/11/2001* - Roma, Italy.
+
+### **REFERENCES**
+
+AASTHO American Association of State Highway and Transportation Officials (2001) - *A Policy on Geometric Design of Highways and Streets*, AASTHO, Washington D.C. BIRD, R. N. HASHIM, I.H. (2005) - "Operating Speed and Geometry Relationships for Rural Single Carriageways in the UK" - *3rd International Symposium on Highway Geometric Design*, Chicago, USA.
+
+BEVILACQUA, A. DI MINO, G. NIGRELLI, J. (2005) - *An Experimental Investigation on the Relationship Between Speed and Road Geometry* - 3rd International SIIV Congress, Bari, Itlay.
+
+CRISMAN, B. MARCHIONNA, A. PERCO, P. ROBBA, A. ROBERTI, R. (2005) - "Operating Speed Prediction Model for Two-Lane Rural Roads" - *3rd International Symposium on Highway Geometric Design*, Chicago, USA.
+
+CUNNINGHAM, J. (2005) - "Recent Developments in Geometric Design in Australia" - *3rd International Symposium on Highway Geometric Design*, Chicago, USA.
+
+FIGUEROA, A. M. TARKO, A.P. (2005) - "Free-flow Speed Changes in the Vicinity of Horizontal Curves" - *3rd International Symposium on Highway Geometric Design*, Chicago, USA.
+
+HASSAN, Y. MISAGHI, P. ADATTA, M. (2005) - "Speed-Based Measures for Evaluation of Design Consistency on Canadian Roads" - *3rd International Symposium on Highway Geometric Design*, Chicago, USA.
+
+GIBREEL, G.M. EASA, S.M. EL-DIMEERY, I.A. (2001) - "Prediction of Operating Speed on Three-Dimensional Highway Alignments" - *Journal of Transportation Engineering 127*, RE No. 1127, pp. 21 – 30.
+
+LAMM, R. PSARIANOS, B. MAILAENDER, T. (1999) - *Highway Design and Traffic Safety Engineering Handbook -* McGraw-Hill Handbooks, New York, United States.
+
+MINISTERO DELLE INFRASTRUTTURE E DEI TRASPORTI, (2001) - *Norme funzionali e geometriche per la costruzione delle strade D.M. 05/11/2001* - Roma, Italy. OTTESEN, J.L. KRAMMES, R. (2000) – "Speed-Profile Model for a Design-Consistency Evaluation Procedure in the United States" - *Transportation Research* 
+
+*Record 1701 National Research Council*, Washington D.C., pp. 76 – 85. RICHL, L. SAYED, T. (2005) - "Effect of Speed Prediction Models on Design
+
+Consistency" - *3rd International Symposium on Highway Geometric Design*, Chicago, USA.
+
+ZIMMERMANN, M. (2005) - "Increased Safety Resulting from Quantitative Evaluation of Sight Distances and Visibility Conditions of Two-Lane Rural Roads", *3rd International Symposium on Highway Geometric Design*, Chicago, USA.

Zotero/001_artiklid/Road Safety Indicators/ahmedroadtrafficaccidentalinjuries2023.md

@@ -0,0 +1,185 @@
+---
+category: literaturenote
+citekey: ahmedroadtrafficaccidentalinjuries2023
+title: "Road traffic accidental injuries and deaths: A neglected global health issue"
+authors: "Ahmed, Sirwan K.; Mohammed, Mona G.; Abdulqadir, Salar O.; El‐Kader, Rabab G. Abd; El‐Shall, Nahed A.; Chandran, Deepak; Rehman, Mohammad E. Ur; Dhama, Kuldeep"
+year: 2023
+date: 2023-05-02 2023-5-02
+doi: 10.1002/hsr2.1240
+publication: Health Science Reports
+url: "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10154805/"
+zotero_key: NGMCCUST
+zotero_storage: XJNEMQED
+collections: doktoritöö / HLO
+folder: 001_artiklid/Road Safety Indicators
+firstAuthor: "Ahmed, Sirwan K."
+status: converted
+---
+#### PERSPECTIVE
+
+![](_page_0_Picture_5.jpeg)
+
+# Road traffic accidental injuries and deaths: A neglected global health issue
+
+Sirwan K. Ahmed1,[2](https://orcid.org/0000-0002-8361-0546) | Mona G. Mohammed[3](https://orcid.org/0000-0002-7041-444X) | Salar O. Abdulqadir[2](https://orcid.org/0000-0002-4831-9577) | Rabab G. Abd El‐Kader3,4 | Nahed A. El‐Shall[5](http://orcid.org/0000-0002-2013-487X) | Deepak Chandran[6](https://orcid.org/0000-0002-9873-6969) | Mohammad E. Ur Rehman<sup>7</sup> | Kuldeep Dhama8
+
+#### Correspondence
+
+Sirwan K. Ahmed, Department of Pediatrics, Rania Pediatric & Maternity Teaching Hospital, Rania, Sulaymaniyah, Kurdistan Region 46012, Iraq; Department of Nursing, University of Raparin, Rania, Sulaymaniyah, Kurdistan Region 46012, Iraq.
+
+Email: [sirwan.ahmed1989@gmail.com](mailto:sirwan.ahmed1989@gmail.com) and [sirwan.k.ahmed@uor.edu.krd](mailto:sirwan.k.ahmed@uor.edu.krd)
+
+# Abstract
+
+Across the world, traffic accidents cause major health problems and are of concern to health institutions; nearly 1.35 million people are killed or disabled in traffic accidents every year. In 2019, 93% of road traffic injury‐related mortality occurred in low‐ and middle‐income countries with an estimated burden of 1.3 million deaths. This issue is growing; by 2030, road traffic injuries will be the seventh leading cause of death globally. The present report highlights an overview of road traffic accidents, accidental injuries, and deaths, associated risk factors, important precautions, safety rules, and counteracting management strategies. In modern cultures, road accidents are a major source of death and serious injuries. Road traffic injuries are a substantial yet underserved public health issue around the world that requires immediate attention. To prevent accidents in the long term, it is essential to adopt conservative preventive measures that can minimize collisions and promote a safe road environment.
+
+# KEYWORDS
+
+autonomous vehicles, death, global health, management, prevention, risk factors, road traffic accidents
+
+<sup>1</sup> Department of Pediatrics, Rania Pediatric & Maternity Teaching Hospital, Rania, Iraq
+
+<sup>2</sup> Department of Nursing, University of Raparin, Rania, Iraq
+
+RAK College of Nursing, RAK Medical and Health Sciences University, Ras Al Khaimah, UAE
+
+<sup>4</sup> Faculty of Nursing, Mansoura University, Mansoura, Egypt
+
+<sup>5</sup> Department of Poultry and Fish Diseases, Faculty of Veterinary Medicine, Alexandria University, Edfina, Egypt
+
+<sup>6</sup> Department of Veterinary Sciences and Animal Husbandry, Amrita School of Agricultural Sciences, Amrita Vishwa Vidyapeetham University, Coimbatore, Tamil Nadu, India
+
+<sup>7</sup> Department of Medicine, Rawalpindi Medical University, Rawalpindi, Pakistan
+
+<sup>8</sup> Division of Pathology, ICAR‐Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India
+
+This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
+
+<sup>© 2023</sup> The Authors. Health Science Reports published by Wiley Periodicals LLC.
+
+# 1 | INTRODUCTION
+
+Across the world, traffic accidents cause majorhealth problems and are of concern to health institutions, nearly 1.35 million people are killed or disabled in traffic accidents every year, about 3700 people die every day in fatal accidents alone, half of which are cyclists, motorcyclists, or pedestrians, as vulnerable road users.[1](#page-4-0) For example, in the United States, car accidents are considered one of the main causes of death. In 2020 alone, about 40,000 people died in a traffic accident and about 2.1 million people visited emergency units due to traffic accidents. That is estimated at \$430 billion in medical costs and quality of life and lives lost.[2](#page-4-1)
+
+Traffic injuries are the leading cause of death among children and youth aged 5–29, with 20 to 50 million injuries that do not cause death but cause disability and serious economic damage to individuals, families, and countries; the loss is due to the cost of medical care and lost wages of the infected or deceased person. Their families are often forced to leave work or school to care for their injured in traffic accidents. According to the WHO, the cost of road traffic crashes in most countries is estimated to be around 3% of their GDP.[3](#page-4-2) The present report highlights an overview of road traffic accidents, accidental injuries, and deaths, associated risk factors, important precautions, safety rules, and counteracting management strategies.
+
+# 2 | CONCEPT DEFINITIONS
+
+An accident is defined as an unexpected and uncontrollable incident in which the action and reaction of an item or person causes personal injury or property damage. A traffic accident is defined as the failure of the road vehicle driver system to perform one or more activities required for the trip to be completed without harm or loss. Traffic accidents are mostly caused by poor maintenance of the road network and a lack of efficient and systematic enforcement.[4](#page-4-3)
+
+The main contributors to traffic accidents include poor road conditions, reckless passing, drowsy driving, sleepwalking, intoxication, illness, use of mobile phones, eating and drinking in the car, inattention in the event of a street accident, and the inability of other drivers to react quickly enough to the situation.[5,6](#page-4-4) Regardless of the vehicle type, traumatic injuries after traffic accidents can affect any part of the body. Vulnerable parts of the body that lead to fatal consequences include the head, chest, abdominal pelvis, and spine.[7](#page-4-5)
+
+The general health and well‐being of citizens in the United States depend on safe transportation. It is a crucial component of the country's transportation and travel infrastructure.[8](#page-4-6) Safety breaches occur through harms caused by inadvertent behaviors or events. The main objective of transportation safety planning is to increase safety by supporting initiatives to create policies, programs, and projects related to all transportation infrastructure, and it also aims to reduce the number of injuries and deaths caused by traffic accidents on public roads.[9](#page-4-7) Establishing a strong transportation policy will have a direct impact on individual health, such as reducing exposure to air pollution and the problems caused by air pollution. Furthermore, it is the right of everyone to have access to safe, healthy, and affordable transportation. The government then prioritizes supporting a healthy society with innovative and modern designs and providing appropriate and safe opportunities by building a safe and an appropriate transportation infrastructure that can reduce the rate of injuries and deaths from transportation accidents is a priority of the government.[10](#page-4-8)
+
+# 3 | CAUSES AND RISK FACTORS
+
+Regarding risk factors for traffic accidents, socioeconomic status is considered the main cause of traffic accidents. According to WHO data, road traffic accidents disproportionately affect low‐ and middle‐income countries, where 90% of all road traffic deaths occur despite these countries having only 60% of the world's vehicles, African countries have higher rates of traffic accidents than European countries, which have lower rates of traffic accidents, even in high‐income countries, people with poor economic conditions are more likely to be involved in traffic accidents.[3](#page-4-2) Traffic and road accidents are considered one of the leading human causes of death among children and adolescents aged 5–29 years. Another reason is sex; men are more likely to be involved in traffic accidents than women, especially young men under the age of 25, hey accounting for 3 out of 4 deaths in traffic accidents (73%), which is three times more likely than their peer girls. However, the greatest causes of death in traffic accidents are not wearing seat belts, restraining children, and not wearing helmets, which certainly reduces the risk of brain injury and death in motorcycle accidents, the risk of injury and death to the back seat and front passengers is also related to the use of seatbelts.[3](#page-4-2)
+
+In general, the approach to the road safety system approach is more based on the risk‐based method, considering human mistakes and trying to ensure the safety of road users. In general, the approach to the road safety system approach is more based on the risk‐based method, considering human errors, and trying to ensure the safety of road users. The system can be designed to be forgiving of human errors and consider human sensitivity toward traffic victims, including; safety roads, roadside safety, safety speed, safety vehicles and safe users, and all these principles must be considered to reduce the number of victims in traffic accidents.[3](#page-4-2)
+
+There is a direct relationship between speeds and the possibility occurring of an accident, as well as severity of the events; with a 1% increase in mean speeds increases the probability occurring of the fatal crash by 4% and an increase in the risk of serious injuries by 3%. The use of alcohol and other substances while driving increases the risk of fatal accidents, resulting in serious deaths or injuries. If a driver's test of alcohol is more than 0.04 grams per deciliter (G/DL), the risk of traffic accidents is very high. Then the type of drug used by drivers will change the result of traffic accidents, for example, those who have used a stimulant drug such as amphetamines are five times more likely to have a fatal accident than those who did not take the drug.[3](#page-4-2)
+
+Another cause of traffic accidents is being busy while driving, which can cause serious damage. Mobile operation is a crucial issue for driving safety that requires intervention. For example, when people are busy with their mobile phones while driving, the risk of traffic accidents increases about four times more than those who do not use their mobile phones while driving. The reason is that the use of mobile phones while driving disrupts the person's reaction to the brakes and traffic signs and makes it unable to stay on the line and follow the appropriate distance. What is expected to increase day by day increases the risk of crash with mobile phone use.[3](#page-4-2)
+
+Furthermore, road design has a significant impact on road safety. This covers the safety of all road users, for example, pedestrians, cyclists, and motorcyclists. It is very important to consider the safety of all road users when designing roads. To reduce the risk of accidents for road users, streets, cycle lanes, safe crossings, and other traffic calming measures are very important. Then, unsafe vehicles that are not of good quality or do not meet fundamental norms of vehicle safety, because, of course, vehicle safety is very important to prevent traffic accidents and reduce the risk of accidents. According to available data, the risk of traffic accidents for vehicle occupants and pedestrians increases significantly in the absence of fundamental norms of vehicle safety requirements[.3](#page-4-2)
+
+#### 4 | MANAGEMENT
+
+Medical management it is very important to familiarize drivers and people that in the event of a road accident, the first step is to call an ambulance and road health centers immediately and go to a nearby hospital. Medication can aid in healing if the injury is not too severe. The administration of tetanus shots and pain relievers by injection is an example of common safety precautions[.11](#page-4-9) In the event of severe blood loss, a blood transfusion may be necessary. In case of bone fractures, doctors do very well and scientifically place the bones in place, and the replacement of a bone that has been dislocated, but does not need surgery is called a closed reduction. In extreme circumstances, surgical intervention is required to operate on the victims of fatal accidents in emergency to save their lives. The surgeon also should be aware of the hidden injuries beneath a seemingly healthy abdomen and other parts of the body. Blunt organ trauma, as well as penetrating spine and back trauma, are all possibilities[.12,13](#page-4-10)
+
+However, delays in identifying and treating people injured in a road traffic accident worsen their conditions. In addition, secure the treatment of pre‐hospital for the injured in traffic accidents as soon as possible and then receive the necessary treatment in the hospital is to increase the standard of health care for postcrash care and is considered one of the necessary tasks.
+
+The implementation of traffic laws by drivers, including the law on drinking during driving, wearing safety belts, complying with speed limits, wearing helmets, and stabilizing children strictly in private places, reducing the death rate and injuries related to these special behaviors[.3](#page-4-2)
+
+Injuries and fatalities from motor vehicle collisions can be avoided by following appropriate precautions and safety rules. Understanding the dangers and taking precautions to ensure health and safety while driving, at home or abroad, can help prevent these accidents and deaths. Always buckle up, regardless of how short the trip of your trip/travel is a car passenger whether sit in front or back seat of the car, should be sure he is tied with belt seats, and children should be attached in the back of the car on a special seat that is suitable for their age, height, and weight. When operating a motorcycle, motorbike, or bicycle, always wear a helmet. Avoid traveling with a drunk driver and never drive while drunk or high. Speed limits must be respected and drive without interruptions or distractions. For example, refrain from texting, emailing, or accessing social networks while driving. Crossing the street should always be done with caution, especially in countries where the steering wheel is on the left side of the car. Only use cabs that are clearly identified and try to choose seatbelt‐equipped taxis. Avoid traveling in large, heavy, or packed minivans or buses that are top‐heavy, overweight, or packed.[14,15](#page-5-0)
+
+It is the duty of governments to work to provide the conditions of road safety, which is in coordination with different sectors such as transportation, health, law, education, and civilian organizations that work to raise awareness of society. Then design a safe traffic infrastructure, stabilize equipment and signs roads, improve the quality of vehicles and other means of transportation, monitor traffic accidents for victims and repair roads, implement and establish traffic laws related to traffic dangers, expand transportation trails, conduct scientific research, raise awareness of society with traffic laws and using the means of transportation.[3,10](#page-4-2)
+
+Existing interventions in high‐income countries aimed at reducing road traffic accidents and injuries have shown to be effective.[15](#page-5-1) Speed cameras, seatbelt laws, and campaigns have all been successful in reducing the number of accidents and injuries on the roads.[15](#page-5-1)
+
+Collecting and monitoring data on road traffic accidents and injuries is crucial for understanding trends and identifying areas where improvements can be made. Data can provide insight into the causes of accidents and injuries, which can help inform interventions and policies. Types of data needed include the number and severity of accidents, the demographics of those involved, and the types of vehicles and infrastructure involved.[16](#page-5-2) Challenges in collecting and analyzing data include inconsistencies in reporting, limited resources for data collection and analysis, and privacy concerns.[17](#page-5-3)
+
+Government agencies have a significant role to play in setting road safety regulations and standards, as well as providing funding for infrastructure improvements and education and training programs. Vehicle manufacturers can also contribute by designing and producing safer vehicles with advanced safety features. Road safety organizations can raise awareness and promote education and training programs for drivers, pedestrians, and cyclists.
+
+Emerging technologies, such as autonomous vehicles, have the potential to greatly reduce the number of accidents caused by human error. However, this technology is still in its early stages, and there are many challenges that need to be addressed before it can be fully implemented. Implications for road safety policies and programs include creating new safety regulations, providing training for law enforcement officers and emergency responders on how to deal with autonomous vehicles, and ensuring that infrastructure is designed to accommodate these new technologies.
+
+An overview of accident and death injuries and deaths in road traffic, associated risk factors, salient precautions, safety rules, and counteracting management strategies to be adopted is shown in Figure [1](#page-3-0).
+
+To reduce traffic accidents and the damage caused by traffic accidents, we can rely on raising awareness among people in general
+
+<span id="page-3-0"></span>![](_page_3_Figure_7.jpeg)
+
+FIGURE 1 A pictorial representation on road traffic accidental injuries and deaths, risk factors, salient precautions, safety rules, and management strategies. Figure was designed by [Biorender.com](http://Biorender.com) program.
+
+<span id="page-3-1"></span>TABLE 1 Strategies to reduce traffic accidents.
+
+| 1 | Education and<br>Training     | One of the most effective ways to raise public awareness about road safety is through education and training.<br>Governments, NGOs, and other organizations can conduct training sessions for drivers, pedestrians, and other road<br>users to teach them about safe driving practices, traffic rules, and pedestrian safety. |
+|---|-------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| 2 | Campaigns                     | Awareness campaigns can be launched through various mediums, such as billboards, radio, TV, social media, and other<br>platforms to reach a wider audience. These campaigns can highlight the importance of road safety and the<br>consequences of reckless driving.                                                          |
+| 3 | Infrastructure<br>Development | Improving infrastructure such as road signage, pedestrian crossings, and street lighting can help in reducing accidents.<br>Governments can also construct speed bumps, roundabouts, and other traffic‐calming measures to reduce speeding<br>and improve road safety.                                                        |
+| 4 | Law Enforcement               | Effective law enforcement can deter reckless driving and encourage adherence to traffic rules. Governments can increase<br>the number of traffic police and use technology such as speed cameras to catch violators and enforce penalties.                                                                                    |
+| 5 | Partnerships                  | Partnerships between governments, NGOs, and other organizations can help to overcome barriers in low‐income<br>countries. For example, NGOs can provide funding and expertise to governments for road safety programs.                                                                                                        |
+| 6 | Community<br>Engagement       | Community engagement is important to create a sense of ownership and responsibility towards road safety. Local<br>organizations can conduct awareness campaigns and engage with communities to encourage safe driving practices<br>and promote pedestrian safety.                                                             |
+
+and drivers in particular. Also, orient them about the risks, safety measures, and necessary preventive measures during driving. In general, it can be said that public awareness, road safety infrastructure, and traffic rules are the most effective reasons for reducing traffic accidents. Transportation is not only important in contemporary life, but has also become crucial and resourceful.
+
+Raising public awareness and overcoming barriers in low‐income countries to reduce traffic accidents, injuries, and deaths can be achieved through several strategies (Table [1](#page-3-1)).
+
+# 5 | CONCLUSION
+
+Increased traffic input is unavoidable; however, the outcome must be taken carefully in terms of producing accidents. It should be noted that the increase in accidents requires safety. In modern cultures, road accidents are a major source of death and serious injuries. Road traffic injuries are a substantial yet underserved public health issue around the world that requires immediate attention. Conservative preventive approaches to successful long‐term prevention are needed. Road transportation is the most complex and deadly system that people must face on a daily basis. Road safety management aims to preserve and improve the current safety of a road network by minimizing collisions and creating a safe road environment for its users, allowing it to be used in an effective and safe way in the future. It is concerned with the execution of road safety regulations, administration, and organization in the authorities in charge of reducing road collisions and fatalities.
+
+## AUTHOR CONTRIBUTIONS
+
+Sirwan K. Ahmed: Conceptualization; data curation; formal analysis; investigation; methodology; project administration; resources; software; supervision; validation; visualization; writing—original draft; writing—review and editing. Mona G. Mohammed: Data curation; methodology; resources; software; validation; visualization; writing original draft; writing—review and editing. Salar O. Abdulqadir: Data curation; formal analysis; investigation; methodology; resources; validation; visualization; writing—review and editing. Rabab G. Abd El‐Kader: Data curation; investigation; resources; validation; writing review and editing. Nahed A. El‐Shall: Resources; writing—review and editing. Deepak Chandran: Data curation; formal analysis; resources; software; validation; visualization; writing—review and editing. Mohammad E. Ur Rehman: Resources; writing—review and editing. Kuldeep Dhama: Data curation; formal analysis; investigation; methodology; resources; software; supervision; validation; visualization; writing—review and editing.
+
+#### ACKNOWLEDGMENTS
+
+The authors thank their respective institutes and universities.
+
+#### CONFLICT OF INTEREST STATEMENT
+
+The authors declare no conflict of interest.
+
+### DATA AVAILABILITY STATEMENT
+
+All data presented in the present review is available online and can be accessed from the appropriate reference in the reference list.
+
+#### ETHICS STATEMENT
+
+Not required.
+
+#### TRANSPARENCY STATEMENT
+
+The lead author Sirwan Khalid Ahmed affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.
+
+#### ORCID
+
+Sirwan K. Ahmed <https://orcid.org/0000-0002-8361-0546> Mona G. Mohammed <https://orcid.org/0000-0002-7041-444X> Salar O. Abdulqadir <https://orcid.org/0000-0002-4831-9577> Nahed A. El‐Shall <http://orcid.org/0000-0002-2013-487X> Deepak Chandran <https://orcid.org/0000-0002-9873-6969> Mohammad E. Ur Rehman [https://orcid.org/0000-0001-](https://orcid.org/0000-0001-8118-4849) [8118-4849](https://orcid.org/0000-0001-8118-4849)
+
+Kuldeep Dhama <https://orcid.org/0000-0001-7469-4752>
+
+## REFERENCES
+
+- <span id="page-4-0"></span>1. World Health Organization (WHO). Global Status Report on Road Safety 2018; 2018. [https://www.who.int/publications/i/item/978](https://www.who.int/publications/i/item/9789241565684) [9241565684](https://www.who.int/publications/i/item/9789241565684)
+- <span id="page-4-1"></span>2. Centers for Disease Control and Prevention (CDC). Transportation Safety; 2022. <https://www.cdc.gov/transportationsafety/index.html>
+- <span id="page-4-2"></span>3. World Health Organization (WHO). Road Traffic Injuries; 2022. [https://](https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries) [www.who.int/news-room/fact-sheets/detail/road-traffic-injuries](https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries)
+- <span id="page-4-3"></span>4. Eid HO, Abu‐Zidan FM. Distraction‐related road traffic collisions. Afr Health Sci. 2017;17:491‐499.
+- <span id="page-4-4"></span>5. Ashraf I, Hur S, Shafiq M, Park Y. Catastrophic factors involved in road accidents: underlying causes and descriptive analysis. PLoS One. 2019;14:e0223473.
+- 6. Sun L‐L, Liu D, Chen T, He M‐T. Road traffic safety: an analysis of the cross‐effects of economic, road and population factors. Chin J Traumatol. 2019;22:290‐295.
+- <span id="page-4-5"></span>7. Zaloshnja E, Miller TR, Hendrie D. Effectiveness of child safety seats vs safety belts for children aged 2 to 3 years. Arch Pediatr Adolesc Med. 2007;161:65‐68.
+- <span id="page-4-6"></span>8. Hull R, Herbel S, Gaines D, Waldheim N. Building Links to Improve Safety: How Safety and Transportation Planning Practitioners Work Together. United States. Federal Highway Administration. Office of Safety; 2016.
+- <span id="page-4-7"></span>9. Centers for Disease Control and Prevention (CDC). CDC Transportation Recommendations; 2018. [https://www.cdc.gov/](https://www.cdc.gov/transportation/) [transportation/](https://www.cdc.gov/transportation/)
+- <span id="page-4-8"></span>10. Ang BH, Chen WS, Lee SWH. Global burden of road traffic accidents in older adults: a systematic review and meta‐regression analysis. Arch Gerontol Geriat. 2017;72:32‐38.
+- <span id="page-4-9"></span>11. Salvagioni DAJ, Mesas AE, Melanda FN, et al. Prospective association between burnout and road traffic accidents in teachers. Stress Health. 2020;36:629‐638.
+- <span id="page-4-10"></span>12. Deresse E, Komicha MA, Lema T, Abdulkadir S, Roba KT. Road traffic accident and management outcome among in Adama
+
+- Hospital Medical College. Central Ethiopia Pan Afr Med J. 2021;38:190.
+- 13. Centers for Disease Control and Prevention (CDC). Road Traffic Injuries and Deaths—A Global Problem; 2020. [https://www.cdc.gov/](https://www.cdc.gov/injury/features/global-road-safety/index.html) [injury/features/global-road-safety/index.html](https://www.cdc.gov/injury/features/global-road-safety/index.html)
+- <span id="page-5-0"></span>14. Sauber‐Schatz EK BM, Parker EM, Sleet DA. CDC Health Information for International Travel (Yellow Book). Chapter 8 – Travel by Air, Land & Sea – Road & Traffic Safety; 2020. [https://](https://wwwnc.cdc.gov/travel/yellowbook/2020/travel-by-air-land-sea/road-and-traffic-safety) [wwwnc.cdc.gov/travel/yellowbook/2020/travel-by-air-land](https://wwwnc.cdc.gov/travel/yellowbook/2020/travel-by-air-land-sea/road-and-traffic-safety)[sea/road-and-traffic-safety](https://wwwnc.cdc.gov/travel/yellowbook/2020/travel-by-air-land-sea/road-and-traffic-safety)
+- <span id="page-5-1"></span>15. Ernstberger A, Joeris A, Daigl M, et al. Decrease of morbidity in road traffic accidents in a high income country—an analysis of 24,405 accidents in a 21 year period. Injury. 2015;46: S135‐S143.
+
+- <span id="page-5-2"></span>16. Imprialou M, Quddus M. Crash data quality for road safety research: current state and future directions. Accident Anal Preven. 2019;130: 84‐90.
+- <span id="page-5-3"></span>17. Chang F‐R, Huang H‐L, Schwebel DC, Chan AHS, Hu G‐Q. Global road traffic injury statistics: challenges, mechanisms and solutions. Chin J Traumatol. 2020;23:216‐218.
+
+How to cite this article: Ahmed SK, Mohammed MG, Abdulqadir SO, et al. Road traffic accidental injuries and deaths: A neglected global health issue. Health Sci Rep. 2023;6:e1240. [doi:10.1002/hsr2.1240](https://doi.org/10.1002/hsr2.1240)

Zotero/001_artiklid/Road Safety Indicators/carterroadsafetyfundamentalsconcepts2017.md

@@ -0,0 +1,4507 @@
+---
+category: literaturenote
+citekey: carterroadsafetyfundamentalsconcepts2017
+title: "Road Safety Fundamentals: Concepts, Strategies, and Practices that Reduce Fatalities and Injuries on the Road"
+authors: "Carter, Daniel; Gelinne, Dan; Kirley, Bevan; Sundstrom, Carl; Srinivasan, Raghavan; Palcher-Silliman, Jennifer; United States. Department of Transportation. Federal Highway Administration. Office of Safety"
+year: 2017
+date: 2017-11-01 2017-11-01
+url: /view/dot/49570
+zotero_key: CQRDSY86
+zotero_storage: DJC4MAUZ
+collections: doktoritöö / HLO
+folder: 001_artiklid/Road Safety Indicators
+firstAuthor: "Carter, Daniel"
+status: converted
+---
+# **Road Safety Fundamentals**
+
+![](_page_0_Picture_1.jpeg)
+
+**Concepts, Strategies, and Practices that Reduce Fatalities and Injuries on the Road**
+
+![](_page_0_Picture_3.jpeg)
+
+## **Notice**
+
+This document is disseminated under the sponsorship of the U.S. Department of Transportation (USDOT) in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document.
+
+The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers' names appear in this report only because they are considered essential to the objective of the document.
+
+## **Quality Assurance Statement**
+
+The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.
+
+This document can be downloaded for free in full or by individual unit at: [https://rspcb.safety.fhwa.dot.gov/r](https://rspcb.safety.fhwa.dot.gov/training.aspx)sf/
+
+| 1. Report No.<br>FHWA-SA-18-003                                                                                                                                                                                                                      | 2. Government Accession No.                                                                                                                                                                                                                                                                   |                                 | 3. Recipient's Catalog No.                                                                         |
+|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------|----------------------------------------------------------------------------------------------------|
+| 4. Title and Subtitle<br>Road Safety Fundamentals:<br>on the Road                                                                                                                                                                                    | Concepts, Strategies, and Practices that Reduce Fatalities and Injuries                                                                                                                                                                                                                       | 5. Report Date<br>November 2017 |                                                                                                    |
+| 7. Author(s)                                                                                                                                                                                                                                         |                                                                                                                                                                                                                                                                                               |                                 | 6. Performing Organization Code                                                                    |
+| Lead Editor: Daniel Carter, P.E., Senior Research Associate                                                                                                                                                                                          |                                                                                                                                                                                                                                                                                               |                                 |                                                                                                    |
+| Unit Authors:                                                                                                                                                                                                                                        | Unit 1: Dan Gelinne, Program Coordinator, UNC Highway Safety                                                                                                                                                                                                                                  |                                 | 8. Performing Organization Report No.                                                              |
+| Research Center<br>Center<br>Research Center                                                                                                                                                                                                         | Unit 2: Bevan Kirley, Research Associate, UNC Highway Safety Research<br>Unit 3: Carl Sundstrom, P.E., Research Associate, UNC Highway Safety<br>Unit 4: Raghavan Srinivasan, Ph.D., Senior Transportation Research                                                                           | and Address                     | 9. Performing Organization Name<br>University of North Carolina,<br>Highway Safety Research Center |
+| Engineer; Daniel Carter<br>Manager, UNC Highway Safety Research Center                                                                                                                                                                               | Unit 5: Daniel Carter; Jennifer Palcher-Silliman, Communications                                                                                                                                                                                                                              |                                 | 10. Work No. (TRAIS)                                                                               |
+| Safety Research Center                                                                                                                                                                                                                               | Layout and Graphics: Graham Russell, Graphic Designer, UNC Highway                                                                                                                                                                                                                            |                                 | 11. Contract or Grant No.                                                                          |
+| Technical Editors: Jennifer Palcher-Silliman; Patty Harrison,<br>Communications Specialist, UNC Highway Safety Research Center;<br>Caroline Mozingo, Senior Manager of Communications, Education and<br>Outreach, UNC Highway Safety Research Center |                                                                                                                                                                                                                                                                                               | Text book                       | 13. Type of Report and Period Covered                                                              |
+| 12. Sponsoring Agency Name and Address<br>Federal Highway Administration Office of Safety<br>1200 New Jersey Ave., SE<br>Washington, DC 20590                                                                                                        |                                                                                                                                                                                                                                                                                               |                                 | 14. Sponsoring Agency Code                                                                         |
+| 15. Supplementary Notes                                                                                                                                                                                                                              | The project manager for the textbook was Felix H. Delgado, P.E., FHWA Office of Safety                                                                                                                                                                                                        |                                 |                                                                                                    |
+| 16. Abstract                                                                                                                                                                                                                                         | This book provides an introduction to the fundamental concepts of road safety. The book's goal is to equip<br>the reader with a broad base of knowledge about road safety. Thus, the focus is in communicating concepts<br>rather than providing instruction in detailed analysis procedures. |                                 |                                                                                                    |
+| students in a university setting.                                                                                                                                                                                                                    | The audience for this book is two-fold. First, this is intended for those whose job addresses some aspect of<br>road safety, particularly in a public agency setting. Second, this book is intended for professors and                                                                        |                                 |                                                                                                    |
+| disciplines will benefit from the concepts presented here.                                                                                                                                                                                           | This book seeks to lay the foundation of road safety knowledge regardless of a particular discipline.<br>Professionals with a background in engineering, planning, public health, law enforcement, and other                                                                                  |                                 |                                                                                                    |
+| 17. Key Words                                                                                                                                                                                                                                        |                                                                                                                                                                                                                                                                                               |                                 | 18. Distribution Statement                                                                         |
+
+**No restrictions**
+
+22. Price **FREE**
+
+**data, multidisciplinary approaches**
+
+19. Security Classif. (of this report) **Unclassified**
+
+**road safety, road safety management process, site-level management, system level management, human behavior, safety performance measures, road safety**
+
+> 20. Security Classif. (of this report) **Unclassified**
+
+21. No. of Pages
+
+**188**
+
+![](_page_3_Picture_0.jpeg)
+
+## **TABLE OF CONTENTS**
+
+## **UNIT <sup>1</sup> Foundations of Road Safety**
+
+ **Chapter 1: Context of Road Safety**
+
+ **Chapter 2: Road Safety Through the Years**
+
+ **Chapter 3: Multidisciplinary Approaches**
+
+ **Chapter 4: Road Users**
+
+# **UNIT <sup>2</sup> Human Behavior and Road Safety Chapter 5: Understanding Human Behavior**
+
+ **Chapter 6: Changing Human Behavior**
+
+# **UNIT <sup>3</sup> Measuring Safety Chapter 7: Importance of Safety Data**
+
+ **Chapter 8: Types of Safety Data**
+
+ **Chapter 9: Improving Safety Data Quality**
+
+## **UNIT <sup>4</sup> Solving Safety Problems**
+
+ **Chapter 10: Road Safety Management Process**
+
+ **Chapter 11: Site-Level Safety Management**
+
+ **Chapter 12: System-Level Safety Management**
+
+## **UNIT <sup>5</sup> Implementing Road Safety Efforts**
+
+ **Chapter 13: Who Does What**
+
+ **Chapter 14: Road Safety Research**
+
+ **Chapter 15: Strategic Communications**
+
+ **Chapter 16: Advancing Road Safety**
+
+## **INTRODUCTION**
+
+This book provides an introduction to many of the fundamental concepts of road safety. These concepts cover areas such as the nature of road safety issues, human behavior in the road environment, and identifying and solving road safety problems. The goal of this book is to equip the reader with a broad base of knowledge about road safety. Thus, the focus of the text is in communicating concepts rather than providing instruction in detailed analysis procedures.
+
+The audience for this book is two-fold. First, this is intended for those whose job addresses some aspect of road safety, particularly in a public agency setting. This is especially relevant for individuals who have been tasked with managing road safety but who do not have formal training in road safety management. In order to show practical applications of each road safety concept, this book contains many examples that demonstrate the concepts in real-world settings. Second, this book is intended for professors and students in a university setting who can use individual units or this entire book to add an emphasis on road safety as part of graduatelevel work. Each unit provides learning objectives and sample exercises to assist professors as they incorporate content into their courses.
+
+As a final note, this book is intended to lay the foundation of road safety knowledge regardless of a particular discipline. Professionals with a background in engineering, planning, public health, law enforcement, and other disciplines will benefit from the concepts presented here.
+
+## **ABOUT THIS BOOK**
+
+This book is divided into five units according to major topics of road safety knowledge. Each unit is divided into multiple chapters that address the primary concepts of the unit. The beginning of each unit provides a list of learning objectives that indicate what the reader will be able to understand, describe, identify, or otherwise do by the end of the unit.
+
+Each chapter presents call-out boxes, glossary definitions, and references as shown below.
+
+**Call-out boxes** are provided throughout the book to provide examples of concepts presented in the chapter.
+
+conference for March 1926. During the interim between the two drew up a model "**Uniform Vehicle Code**" covering registration and titling of vehicles, licensing of drivers, and operation of vehicles on the highways. The code incorporated the best features of the numerous and varied State laws then on the statute books. The second conference approved this code and recommended it to the State legislatures as the basis for uniform motor vehicle legislation.
+
+Studies following this 1926 conference concluded that determining the causes of crashes was far more difficult than they had presumed. The problem warranted a sustained program of research by a national organization. The Conference agreed, and the Highway Research Board (HRB) organized the Committee on Causes and Prevention of Highway Accidents
+
+**Balanced Design for Safety** In the 1920s and 1930s, it was good
+
+engineering practice to design new highways as much as possible in long straight lines or "tangents." When it became necessary to change direction, the engineer laid out a circular curve, the radius of which he selected to fit
+
+the ground with the least construction policy. In practice, engineers made the it was cheaper to do so, but with little consistency. Engineers expected motorists driving these roads to adjust their speeds curves safe design speed might be considerably lower than the posted
+
+and safe design speed on curves. In 1935, highway engineer Joseph Barnett of the BPR an "assumed design speed," a comfortable top speed for drivers outside of urban areas.
+
+highway engineers to worry about this inconsistency between posted speed limits
+
+the country, and between 1921 and 1939, the distance of paved roads
+
+of State Highway Officials in 1938, Barnett's "balanced design" concept became a permanent feature of U.S. roadway design. Today, standards for designing curves, such as design speed, curve radius and superelevation (the tilt of the road through Geometric Design of Highways and Streets, State Highway Transportation Officials.
+
+ROAD SAFETY FUNDAMENTALS UNIT 1: FOUNDATIONS OF ROAD SAFETY **1-13**
+
+nationwide. The HRB played a major part in subsequent efforts to reduce
+
+#### **Federal Government Role in Highway Development**
+
+The growing use of motor vehicles during the 1920s was mirrored by the expansion of the Federal building roads. In its early form, the Office of Public Roads was organized under the U.S. Department of Agriculture, playing a large role in
+
+Following the Federal Aid Road Act of 1916, this office would become the Bureau of Public Roads (BPR), with State highway departments on road projects. Work continued on the expansion of highways across Federal Highway Printing Office,
+
+**Uniform Vehicle Code** A code covering registration and licensing of
+
+**C**
+
+the highways.
+
+**Glossary definitions** are provided along the side of the page. These correspond to words in bold face in the page content.
+
+#### **References C**
+
+to source material are provided along the side of the page. These are numbered consecutively through the unit and correspond to numbers in the page content.
+
+![](_page_7_Picture_0.jpeg)
+
+## **Foundations of Road Safety UNIT 1**
+
+#### **LEARNING OBJECTIVES**
+
+After reading the chapters and completing exercises in Unit 1, the reader will be able to:
+
+- J **DESCRIBE** the importance of road safety and how it relates to public health, economic, environmental and demographic trends
+- J **RECOGNIZE** roles and responsibilities of various disciplines and approaches to improving road safety
+- J **DISTINGUISH** between nominal and substantive safety
+- J **IDENTIFY** key points in the history of road safety in the U.S., including key legislation and agency formation, and understand how these decisions have shaped today's roadways
+- J **IDENTIFY** different groups of road users and challenges unique to each group
+
+## **Context of Road Safety**
+
+Road safety is an important part of everyday life. Across the nation, people use roads and sidewalks to get to work, school, stores, and home. Public agencies work to ensure that people arrive at their destination without incident.
+
+However, not every trip is without incident. Deaths and injuries resulting from motor vehicle crashes represent a significant public health concern. The World Health Organization (WHO) estimates that motor vehicle crashes kill more than 1 million people around the world each year, and seriously injure as many as 20 to 50 million.**<sup>1</sup>** These crashes affect all road users, from vehicle drivers and passengers to pedestrians, bicyclists, and transit users.
+
+Though road safety in the U.S. has steadily improved over time, it remains a priority for transportation agencies, legislators, and advocacy organizations. Over the past 10 years in the U.S., an average of approximately 37,000
+
+![](_page_8_Figure_6.jpeg)
+
+**FIGURE 1-2**: Traffic Fatalities in the U.S. by Person Type, 2013 (Source: NHTSA FARS)
+
+people were killed each year and an estimated 2.3 million were injured in motor vehicle crashes.**<sup>2</sup>** While many of these deaths and injuries are sustained by motor vehicle passengers and drivers,
+
+![](_page_8_Figure_9.jpeg)
+
+[http://www.who.int/](http://www.who.int/features/factfiles/roadsafety/en) [features/factfiles/](http://www.who.int/features/factfiles/roadsafety/en) [roadsafety/en](http://www.who.int/features/factfiles/roadsafety/en)
+
+### **2**
+
+National Highway Traffic Safety Administration (NHTSA). Fatality Analysis Reporting System (FARS). [http://www.nhtsa.](https://www.nhtsa.gov/research-data/fatality-analysis-reporting-system-fars) [gov/FARS](https://www.nhtsa.gov/research-data/fatality-analysis-reporting-system-fars)
+
+![](_page_8_Figure_13.jpeg)
+
+**FIGURE 1-1**: Traffic Fatalities in the U.S. by Year, 1983-2013 (Source: NHTSA FARS)
+
+![](_page_9_Figure_0.jpeg)
+
+**FIGURE 1-3**: Fatality Rate and Vehicle Miles Traveled, 1966-2013 (Source: NHTSA FARS)
+
+#### **Crash frequency**
+
+The number of crashes occurring per year or other unit of time.
+
+#### **Crash rate**
+
+The number of crashes normalized by a particular population or metric of exposure.
+
+#### **Crash outcome**
+
+Measured by the types of injuries sustained to the people involved in the crash.
+
+they also impact motorcyclists, pedestrians, bicyclists, and users of transit vehicles. This challenge requires a comprehensive approach to improving safety, involving numerous stakeholders and decision makers from a variety of perspectives and disciplines.
+
+## **Defining Safety**
+
+In the simplest terms, safety can be defined as the absence of risk or danger. Focusing this term to address transportation, road safety can be characterized by the ability of a person to travel freely without injury or death. A perfectly safe transportation system would not experience crashes between various road users. Though absence of all crashes is an optimal condition, and many transportation agencies have a goal of zero deaths on the road, the reality is that people continue to get injured or killed on streets and highways across the nation. The challenge posed to the road safety field is to minimize the frequency of crashes and the resulting deaths and injuries using all currently available tools, knowledge, and technology. This challenge is made
+
+more complex due to the multitude of factors influencing safety, from infrastructure to vehicle design to human behavior.
+
+Road safety professionals typically measure safety by the number and rate of crashes and by the severity of those crashes. **Crash frequency**, or the number of crashes occurring per year or other unit of time, is another commonly used metric. **Crash rates** are numbers of crashes normalized by a particular population or metric of exposure. Commonly cited crash rates include crashes per 100,000 people living in a particular State, city or country. Some crash rates present crash numbers per miles traveled or licensed drivers. **Crash outcomes** can be measured by the types of injuries sustained to the people involved in the crash, typically categorized by fatalities and injury severity. Focusing on crashes that result in severe injuries and fatalities is one strategy that agencies use to prioritize their safety activities.
+
+In addition to the measures described above, safety professionals can use surrogate measures, such as
+
+conflicts (near misses), avoidance maneuvers, and the time to collision if no evasive action is taken, to determine the level of safety risk and identify specific problems. Safety problems may exist even in locations that do not have a demonstrated history of crashes, just as someone who smokes is at higher risk for lung cancer even if no cancer has yet been detected. This can be especially true for non-motorized road user safety, such as pedestrians and bicyclists, since crashes involving these road users may be infrequent and appear random at first sight. In such locations where crashes are sparse or distributed across the system, safety professionals can use surrogate measures to fill the gaps and assess the road's level of risk. Observing traffic at an intersection, for example, may reveal a pattern of near misses and other conflicts between vehicles and pedestrians. This pattern may not appear in crash data, but can be a valuable source of information to highlight the potential for safety risk.
+
+Safety perception is also an important consideration for travel choices. There are a number of reasons why someone may or may not choose a particular route to drive, walk or bike. Pedestrians who perceive an intersection to be unsafe may cross in a midblock location, where they are more easily able to find a gap in traffic. Motorists may feel uneasy about making a left turn across multiple lanes of traffic, so they may choose to turn right and travel out of their way to perform a U-turn instead. Safety perception impacts road user decisions but is not easily understood by looking at crash data. Safety professionals
+
+can use surveys, driving simulators, and other modern technologies to understand the safety perception of road users.
+
+Evaluating the safety of a particular network, corridor or intersection requires an understanding of both nominal and substantive safety. Originally introduced by Dr. Ezra Hauer,**<sup>3</sup>** these terms offer a helpful framework for assessing the safety of a particular location. Decades of research and evaluation in the field of road safety have revealed a wealth of knowledge concerning the proper designs and policies that contribute to the safety of a particular location. Roadways constructed according to the best and latest recommended research and design standards are said to be nominally safe. **Nominal safety** is an absolute statement about the safety of a location based only on its adherence to a particular set of design standards and related criteria. A road that was nominally safe when it was first opened to traffic may become nominally unsafe when the roadway design standards change, even though the road's crash performance has not changed.
+
+While nominal safety considers the design of a road, it does not incorporate any information about the frequency, type and severity of crashes occurring on the facility. The historical and long-term objective safety of a location based on crash data is known as **substantive safety**. A particular intersection that has experienced fewer than expected crashes over an extended period will be referred to as a substantively safe location, while a corridor with a higher than expected number of crashes is substantively unsafe.
+
+**3**
+
+Hauer, E. *Observational Before/After Studies in Road Safety. Estimating the Effect of Highway and Traffic Engineering Measures on Road Safety.* Pergamon Press. 1997.
+
+### **Nominal safety**
+
+An absolute statement about the safety of a location based only on its adherence to a particular set of design standards and related criteria.
+
+#### **Substantive safety**
+
+Historical and long-term objective safety of a location based on crash data.
+
+Unlike nominal safety, substantive safety operates on a continuum and allows for a range of explanations as to why a particular safety problem exists.
+
+Another key distinction is the fact that a location can be nominally safe – adhering to all standards and design criteria – while experiencing high rates of crashes, making it substantively unsafe. Similarly, a substantively safe location (one that has a lower than expected crash rate) may be nominally unsafe if it does not meet the applicable design standards.
+
+Agencies and safety professionals should strive to prioritize the substantive safety of a facility. Simply building a road that meets all the current design standards will not ensure that the road is substantively safe. Using professional judgement to prioritize safety improvements and select appropriate designs within a range of options, based on observations of road user behavior and other available data, will increase the chance that all factors are considered. The end result will be a road that moves a step closer to the ultimate goal of having a transportation system free of injuries and deaths.
+
+## **Road Safety Decisions and Trade-offs**
+
+The goal of improving safety exists alongside other goals of the transportation system, such as mobility, efficient movement of people and goods, environmental concerns, public health, and economic goals. In this way, transportation professionals and policy makers often refer to
+
+![](_page_11_Figure_5.jpeg)
+
+**FIGURE 1-4**: Comparison of nominal and substantive concepts of [safety http://](https://safety.fhwa.dot.gov/geometric/pubs/mitigationstrategies/chapter1/1_comparnominal.cfm) [safety.fhwa.dot.gov/geometric/pubs/miti](https://safety.fhwa.dot.gov/geometric/pubs/mitigationstrategies/chapter1/1_comparnominal.cfm) [gationstrategies/chapter1/1\\_comparnom](https://safety.fhwa.dot.gov/geometric/pubs/mitigationstrategies/chapter1/1_comparnominal.cfm) [inal.cfm](https://safety.fhwa.dot.gov/geometric/pubs/mitigationstrategies/chapter1/1_comparnominal.cfm) (Source: NCHRP Report 480, Transportation Research Board, 2002)
+
+trade-offs – making a decision to favor one goal at the expense of another. While those in the field of road safety continually look for new designs and technologies to advance all goals, there continue to be many instances where public agencies must weigh competing goals for a location or portion of the road network and decide what trade-offs should be made for the goal of increasing road safety.
+
+Below are several examples:
+
+J **Roundabouts:** A city may decide to install a roundabout at an intersection to decrease the potential conflicts between various movements at the intersection. Safety is improved, especially related to left-turns, since all turns are now part of the circle. However, a roundabout does require traffic on the main road to slow their speeds and navigate through the roundabout. During heavy traffic, especially
+
+if it is unbalanced among the intersection legs, this may cause a decrease in the overall throughput of the intersection. However, this is a trade-off to produce fewer crashes.
+
+- J **Bicycle Helmet Requirements:**  In order to improve bicyclist safety, some jurisdictions have adopted ordinances that require bicyclists to wear helmets. In practice, this can reduce the risk of head injuries among cyclists, but it may also reduce the number of people who choose to ride a bicycle. Adopting such ordinances would prioritize safety while potentially reducing bicycle ridership.
+- J **Red Light Cameras:** Red light camera enforcement monitors signalized intersections and
+
+records information about those who violate red light laws, typically resulting in citations through the mail. These cameras have been shown to improve safety by decreasing the types of crashes that result in serious injury,**<sup>4</sup>** but installing the cameras can be met with significant public opposition.
+
+J **Protected Left Turns:** To minimize the risk of severe left-turn crashes at signalized intersections, engineers may choose to provide left turning drivers an exclusive protected left turn phase (green arrow). While this minimizes crash risk by separating the left turning vehicles from other movements, it also requires that extra time be added specifically for left
+
+Council, et al. Safety Evaluation of Red-Light Cameras. Federal Highway Administration. April 2005. [https://](https://www.fhwa.dot.gov/publications/research/safety/05048/05048.pdf) [www.fhwa.dot.](https://www.fhwa.dot.gov/publications/research/safety/05048/05048.pdf) [gov/publications/](https://www.fhwa.dot.gov/publications/research/safety/05048/05048.pdf) [research/safety/](https://www.fhwa.dot.gov/publications/research/safety/05048/05048.pdf) [05048/05048.pdf](https://www.fhwa.dot.gov/publications/research/safety/05048/05048.pdf) 
+
+**4**
+
+![](_page_12_Picture_6.jpeg)
+
+![](_page_13_Picture_0.jpeg)
+
+turns, which can increase delay for the rest of the traffic at the intersection.
+
+- J **Rumble Strips:** In rural locations, rumble strips can be installed as a measure to alert drivers when they are running off the road. However, these rumble strips are usually installed on the edge of the road or the paved shoulder where bicyclists can safely and comfortably ride separated from traffic. This may result in bicyclists riding in the road where they are more vulnerable to crashes with motor vehicles.
+- J **Trees and Landscaping:** Street trees, shrubs, and other vegetation can serve a valuable purpose in roadside environments – particularly creating shade for the sidewalk, serving as a buffer between the road and sidewalk area, and even creating "visual friction" that can keep vehicle speeds down. However, trees can also pose a safety risk for vehicles that run off the road and collide with them. Vegetation that is
+
+- too close to an intersection can restrict sight distance, contributing to crashes. Selected tree and vegetation removal is an excellent example of a trade-off between safety and other beneficial features of trees.
+- J **Traffic Signal Installation:** A high-speed, high-volume road with multiple traffic lanes may separate housing developments from an elementary school. In order for children living in the housing development to safely travel to and from school, a traffic signal and crosswalk may be installed along the busy road. Motorists will be delayed since they are required to stop for a period of time while the students cross, but the crossing is safer for those students.
+- J **Access Management:** Left turns in and out of shopping centers, especially along multilane roads, can result in severe injuries to motorists when crashes occur. Eliminating these left turns by building raised median islands and consolidating driveways
+
+can eliminate these risky movements; however, this prevents direct access to the stores by potential customers.
+
+Sometimes improving safety for one group of road users may negatively impact the safety of another group. It can also be the case that improving mobility for a group of road users may negatively affect the safety of that same group. There is no absolutely correct answer to many of these trade-offs, as they are all context-specific. Transportation professionals need to discuss the various trade-offs in the context of a particular community's transportation goals. These types of trade-offs are made every day, and require the cooperation of numerous agencies and stakeholders, all of whom have a role to play in transportation decision-making. Despite the temptation to study road safety as a self-contained system, there are a multitude of factors influencing and being influenced by road safety and travel behavior. In order to make informed decisions
+
+![](_page_14_Picture_2.jpeg)
+
+about the transportation system, transportation professionals must understand the impacts – both positive and negative – that design, operations, and policy decisions have on the safety of the transportation network as well as the impacts on other areas such as public health, mobility, environmental quality, and economic growth.
+
+#### **EXERCISES**
+
+- J **LIST** various ways to measure the safety of a road and describe the advantages and disadvantages of each. Consider factors such as the type of information each safety measure provides as well as other issues such as how it can be collected.
+- J **DESCRIBE** a change that could be made to a road or intersection that would improve one transportation goal (e.g., traffic operations, public health, mobility and access, environmental quality, or economic growth) at the expense of the safety of road users.
+- J **DESCRIBE** a change that could be made to a road or intersection that would improve road safety at the expense of another transportation goal (e.g., traffic operations, public health, mobility and access, environmental quality, or economic growth).
+- J **DESCRIBE** a change that could be made to a road or intersection that would improve safety for a road user but not at the expense of other users, or other goals.
+
+## **Road Safety Through the Years**
+
+When examining current efforts to address road safety, it is useful to view them in the context of American transportation history. Recent decades have witnessed numerous advances in the field of road safety. This growing national consciousness about the need for safer roads provides a stark contrast to the first half of the twentieth century when the focus was on highway expansion. The following chapter will provide an overview of the major milestones and achievements that led to the transportation system we have today, as well as the policies and practices that were implemented to address a growing safety problem.
+
+## **Late Nineteenth Century and the Popularity of Bicycling**
+
+An exploration of the history of road safety in the U.S. can begin at many different points – some of our roads were developed as precolonial routes and others were trails blazed by Native Americans. In terms of lasting influence on the modern transportation network,
+
+however, it is most useful to begin the discussion in the late nineteenth century.
+
+In the 1880s and 1890s, bicycles were the dominant vehicle on our nation's roads. With the introduction of the "safety" bicycle, with two wheels of the same size, and the pneumatic tire in the late 1880s, the bicycling craze became an economic, political, and social force in the U.S. By 1890, the U.S. was manufacturing more than 1 million bicycles each year.
+
+At that time, bicyclist behavior particularly careless or risk-taking behavior—was a contributing factor to bicycle crashes. However, the biggest contributor to crashes existed outside the cities; the poor condition of the nation's roads made cycling a laborious and dangerous process. Bicycle groups worked at the Federal, State, and local levels to secure road improvement legislation. The work of these advocacy groups became known as the Good Roads Movement.
+
+![](_page_15_Picture_9.jpeg)
+
+Three men with bicycles on bridge near Pierce Mill, Washington, D.C., 1885. *(Source: Brady-Handy Collection, U.S. Library of Congress)*
+
+#### **Consequences of Speeding**
+
+As in modern times, in the early days of the automobile, posted speed limits were set far below the speed of which most motor vehicles were capable.
+
+With faster and heavier traffic, it became dangerous to drive in the middle of the road and the States began painting centerlines on the pavements to channel traffic in lanes. At 40 miles per hour, these lanes appeared uncomfortably narrow to most motorists, especially when passing trucks. The lane lines also caused trucks to run closer to the shoulder, causing the slab edges and corners of the road to break. To provide greater safety and reduce edge damage, State highway departments built wider pavements and made new roads straighter.
+
+To build support, advocates tailored their message to farmers with the argument that bad roads, by increasing transportation expenditures, cost more than good roads. While engineers, writers, and politicians joined the movement, bicyclists dominated the Good Roads Movement until cars arrived in the early twentieth century.**<sup>5</sup>**
+
+By the close of century, automobiles had slowly begun to share the roads with bicyclists and pedestrians, benefitting from many of the road improvement efforts spearheaded by cycling groups. In 1899, a motor vehicle struck and killed a New York City pedestrian. This event marked the first time in the U.S. that a person was killed in a crash involving a motor vehicle.**<sup>6</sup>**
+
+## **Rise of Motor Vehicles in the Early Twentieth Century**
+
+In 1905, only 78,000 automobiles, most of which were confined to the cities, traveled the U.S. Ten years
+
+These improvements along with mechanical advances in vehicles, such as more powerful engines and four-wheel brakes, in turn encouraged even faster speeds.
+
+Thus, after 1918, highway design followed a spiral of cause and effect, resulting in faster and faster speeds and wider and wider pavements. The motivating force behind this spiral was the driving speed preferences of the great mass of vehicle operators. The public authorities were never able to impose or enforce speed limits for very long if the majority of drivers considered the limits unreasonably low. Now, many current engineering practices use the 85th percentile speed – or the speed at which the majority of drivers travel – as the method of setting speed limits.
+
+later, 2.33 million automobiles were traveling the country's roads, and by 1918, this number had increased to 5.55 million. Mass production made this increase possible as it lowered vehicle manufacturing costs, putting vehicles within the reach of the middle class. As more vehicles became available at a lower price, the pattern of daily travel in the U.S. began to shift. Longer vehicle trips replaced shorter trips by foot or bicycle, and development patterns began to follow suit. The motor age had arrived, and with it a new kind of highway would evolve, designed specifically for motor vehicles.
+
+Expansion of automobile use had immediate positive effects on the national economy and quality of life around the country. Yet proliferation of motor vehicles also had a negative side. As millions of new drivers took to the roads, traffic crashes increased rapidly—tripling from 10,723 in 1918 to 31,215 in 1929.**<sup>7</sup>**
+
+**5**
+
+Source: Richard F. Weingroff, "A Peaceful Campaign of Progress and Reform: The Federal Highway Administration at 100," *Public Roads 57*, no. 2 (Autumn, 1993), [http://www.](https://www.fhwa.dot.gov/publications/publicroads/93fall/p93au1.cfm) [fhwa.dot.gov/](https://www.fhwa.dot.gov/publications/publicroads/93fall/p93au1.cfm) [publications/](https://www.fhwa.dot.gov/publications/publicroads/93fall/p93au1.cfm) [publicroads/93fall/](https://www.fhwa.dot.gov/publications/publicroads/93fall/p93au1.cfm) [p93au1.cfm](https://www.fhwa.dot.gov/publications/publicroads/93fall/p93au1.cfm)
+
+**6**
+
+Soniak, Matt. When and Where Was the First Car Accident? Mental Floss. 2 December 2012. [http://mentalfloss.](http://mentalfloss.com/article/31807/when-and-where-was-first-car-accident) [com/article/31807/](http://mentalfloss.com/article/31807/when-and-where-was-first-car-accident) [when-and-where](http://mentalfloss.com/article/31807/when-and-where-was-first-car-accident)[was-first-car](http://mentalfloss.com/article/31807/when-and-where-was-first-car-accident)[accident](http://mentalfloss.com/article/31807/when-and-where-was-first-car-accident)
+
+**7**
+
+Source: *America's Highways, 1776-1976: A History of the Federal-Aid Program*. Federal Highway Administration (U.S. Government Printing Office, Washington D.C., 1976).
+
+![](_page_17_Picture_0.jpeg)
+
+Secretary of Commerce Herbert Hoover, center, with President Calvin Coolidge, right, in February 1924. *(Source: Harris & Ewing Collection, U.S. Library of Congress)*
+
+## **Shifting Attention to Safety**
+
+Recognizing the rise in crashes and resulting injuries and fatalities, Secretary of Commerce Herbert Hoover convened the First National Conference on Street and Highway Safety in Washington, D.C., in December 1924. Here, for the first time, representatives of State highway and motor vehicle commissions, law enforcement, insurance companies, automobile associations and a multitude of other stakeholders and interest groups met in one place to discuss how to address the growing number of fatalities and serious injuries.
+
+Prior to the conference, committees were established to perform research into areas such as planning and zoning, traffic control, motor vehicles, statistics, and other areas related to road safety. These committees reported wide differences in traffic regulations from State to State and city to city. For instance, twenty States did not attempt to collect crash statistics, only eight States required reporting crashes that resulted in personal
+
+injury, and 38 required railroads and common carriers to report highway crashes. Other committees devoted their attention to issues like traffic control and vehicle speeds, infrastructure and maintenance concerns, and issues impacting vehicles and their drivers.
+
+Conference participants supported a wide range of measures to reduce the rate of crashes and recommended that legislative, administrative, technical, and educational bodies adopt them. Conference participants also recommended that the States take the lead by passing adequate motor vehicle laws and setting up suitable agencies for administering the laws, policing the highways, registering vehicles, and licensing drivers.
+
+To the Federal Government, the conference assigned the role of encouragement, assembly and distribution of information, and the development of recommended practices. Adoption and implementation of these recommended practices would be left to the individual States.
+
+Secretary Hoover called a second conference for March 1926. During the interim between the two conferences, a special committee drew up a model "**Uniform Vehicle Code**" covering registration and titling of vehicles, licensing of drivers, and operation of vehicles on the highways. The code incorporated the best features of the numerous and varied State laws then on the statute books. The second conference approved this code and recommended it to the State legislatures as the basis for uniform motor vehicle legislation.
+
+Studies following this 1926 conference concluded that determining the causes of crashes was far more difficult than they had presumed. The problem warranted a sustained program of research by a national organization. The Conference agreed, and the Highway Research Board (HRB) organized the Committee on Causes and Prevention of Highway Accidents
+
+to coordinate crash research nationwide. The HRB played a major part in subsequent efforts to reduce the consequences of crashes.**<sup>8</sup>**
+
+## **Federal Government Role in Highway Development**
+
+The growing use of motor vehicles during the 1920s was mirrored by the expansion of the Federal Government's role in funding and building roads. In its early form, the Office of Public Roads was organized under the U.S. Department of Agriculture, playing a large role in funding roadways within national parks and forests.
+
+Following the Federal Aid Road Act of 1916, this office would become the Bureau of Public Roads (BPR), charged with working cooperatively with State highway departments on road projects. Work continued on the expansion of highways across the country, and between 1921 and 1939, the distance of paved roads
+
+### **Uniform Vehicle Code**
+
+A code covering registration and titling of vehicles, licensing of drivers, and operation of vehicles on the highways.
+
+**8**
+
+Source: *America's Highways, 1776-1976: A History of the Federal-Aid Program*. Federal Highway Administration (U.S. Government Printing Office, Washington D.C., 1976).
+
+### **Balanced Design for Safety**
+
+In the 1920s and 1930s, it was good engineering practice to design new highways as much as possible in long straight lines or "tangents." When it became necessary to change direction, the engineer laid out a circular curve, the radius of which he selected to fit the ground with the least construction cost, but which could not be less than a certain minimum fixed by department policy. In practice, engineers made the curves sharper than this minimum when it was cheaper to do so, but with little consistency. Engineers expected motorists driving these roads to adjust their speeds to the varying radii, and on the sharper curves safe design speed might be considerably lower than the posted speed limit.
+
+Increasing concern for road safety led many highway engineers to worry about this inconsistency between posted speed limits and safe design speed on curves. In 1935, highway engineer Joseph Barnett of the BPR proposed that all new rural roads conform to an "assumed design speed," a comfortable top speed for drivers outside of urban areas.
+
+With its adoption by American Association of State Highway Officials in 1938, Barnett's "balanced design" concept became a permanent feature of U.S. roadway design. Today, standards for designing curves, such as design speed, curve radius and superelevation (the tilt of the road through a curve) are provided in A Policy on Geometric Design of Highways and Streets, produced by the American Association for State Highway Transportation Officials.
+
+#### **Safety Signs**
+
+Before World War I, most States were using signs to warn road users of danger ahead, particularly at railroad crossings; railroad companies themselves were required to post warning signs at all public road crossings. However, there was little agreement between States about the specific design of these warning devices, and the signs were a variety of shapes, sizes, and colors.
+
+In 1929, the American Engineering Council surveyed sign practices in all U.S. cities with a population of more than 50,000
+
+and created a document that was, in effect, a manual of the best practices of the time. Recognizing the need for standard practices for signs in rural and urban areas, the American Association of State Highway Officials and the National Conference on Street and Highway Safety organized a Joint Committee on Uniform Traffic Control Devices in 1931 and introduced a new manual for national use in 1935. The manual of best practices changed over time to become the Manual on Uniform Traffic Control Devices.
+
+**9**
+
+Source: Weingroff, Richard. *A Peaceful Campaign Of Progress And Reform: The Federal Highway Administration at 100*. Public Roads Magazine. Vol. 57 No. 2. July 1993. [http://www.](https://www.fhwa.dot.gov/publications/publicroads/93fall/p93au1.cfm) [fhwa.dot.gov/](https://www.fhwa.dot.gov/publications/publicroads/93fall/p93au1.cfm) [publications/](https://www.fhwa.dot.gov/publications/publicroads/93fall/p93au1.cfm) [publicroads/93fall/](https://www.fhwa.dot.gov/publications/publicroads/93fall/p93au1.cfm) [p93au1.cfm](https://www.fhwa.dot.gov/publications/publicroads/93fall/p93au1.cfm)
+
+increased from 387,000 miles to nearly 1.4 million miles.**<sup>9</sup>** The BPR recognized that the antiquated highway system was one of the contributing causes of the high crash toll, but did not go so far as to identify primary crash causes or recommend potential solutions.
+
+During this time, an emphasis was placed on expanding the Federal role in the process of highway design and development. This effort culminated in 1944 when Congress approved the development of a National System of Interstate Highways along with that year's Federal Aid Highway Act. Though expansive in scope, calling for a 40,000 mile network, the legislation was not accompanied by any funds to support the development of these highways. Without funding, the legislation did not significantly expand the highway system.
+
+Road safety continued to present a national concern. In May 1946, President Harry S. Truman spoke at the Highway Safety Conference to rally public support to improve State motor vehicle laws, driver licensing, and education. After summarizing
+
+![](_page_19_Picture_9.jpeg)
+
+President Harry S. Truman, 1945. *(Source: U.S. Library of Congress)*
+
+his unsuccessful efforts as a U.S. senator to enact Federal legislation on motor vehicle registration and driver licensing, the President said Congress was not yet ready to interfere with what many perceived as State prerogatives. However, he noted that the Federal Government would not stand aside if the rates of highway fatalities continued to rise.**<sup>10</sup>**
+
+#### **10**
+
+*D. Eisenhower and the Federal Role in Highway Safety*, accessed May 23, 2013, [http://www.](http://www.fhwa.dot.gov/infrastructure/safetyin.cfm) [fhwa.dot.gov/](http://www.fhwa.dot.gov/infrastructure/safetyin.cfm) [infrastructure/](http://www.fhwa.dot.gov/infrastructure/safetyin.cfm)
+
+[safetyin.cfm](http://www.fhwa.dot.gov/infrastructure/safetyin.cfm)
+
+Source: Richard F. Weingroff and the assistance of Sonquela Seabron, *President Dwight* 
+
+![](_page_20_Picture_0.jpeg)
+
+President Dwight D. Eisenhower speaks to the White House Conference on Highway Safety, 1954. *(Source: Eisenhower Presidential Library)*
+
+## **Post War Development and Growth**
+
+Economic conditions following World War II led to even higher levels of driving and automobile ownership. Personal savings of almost \$44 billion created a market for housing and other types of goods, chief among them new automobiles. Automobile production jumped from a nearly 70,000 in 1945 to 3.9 million in 1948.
+
+Because of this increase in vehicle production, motor vehicle registrations spiked and the number of drivers on the nation's roads and highways reached unprecedented levels. Under wartime rationing of rubber, and specifically tires, States had implemented speed controls to reduce wear and tear and improve tire longevity. With the end of rationing and emergency speed controls at the conclusion of the war, highway travel returned to pre-war levels and began a steady climb of about 6 percent per year, which would continue for nearly three decades.
+
+While the increasing popularity of low density housing development (i.e., the suburbs) and the availability of motor vehicles created perfect conditions for more driving,
+
+the nation's roads and highways were unprepared for the increase in traffic. Under wartime restrictions, States were unable to adequately maintain their highways. With widespread operation of overloaded trucks and reduced maintenance, the State highway systems were in worse structural shape post-war than before the war.
+
+## **Development of the Interstate Highway System**
+
+Though the National System of Interstate Highways had been established by legislation in 1944, little progress was made over the next decade. Without funding, established routes were slow to develop. That changed in 1956, when President Dwight D. Eisenhower signed the Federal-Aid Highway Act of 1956. This legislation linked the development of the interstate highway system to the interest of national defense and assigned funding that would rapidly expand the highway network.**<sup>11</sup>** The act established a dedicated funding stream and a plan for highway development that launched the nation into an unprecedented era of expansion in which new interstate corridors linked cities and towns to one another.
+
+**11**
+
+[http://www.](https://www.fhwa.dot.gov/publications/publicroads/06jan/01.cfm) [fhwa.dot.gov/](https://www.fhwa.dot.gov/publications/publicroads/06jan/01.cfm) [publications/](https://www.fhwa.dot.gov/publications/publicroads/06jan/01.cfm) [publicroads/](https://www.fhwa.dot.gov/publications/publicroads/06jan/01.cfm) [06jan/01.cfm](https://www.fhwa.dot.gov/publications/publicroads/06jan/01.cfm)
+
+**12 13**
+
+Source: Richard F. Weingroff and the assistance of Sonquela Seabron, *President Dwight D. Eisenhower and the Federal Role in Highway Safety*, accessed May 23, 2013, [http://www.](https://www.fhwa.dot.gov/infrastructure/safetyin.cfm) [fhwa.dot.gov/](https://www.fhwa.dot.gov/infrastructure/safetyin.cfm) [infrastructure/](https://www.fhwa.dot.gov/infrastructure/safetyin.cfm) [safetyin.cfm](https://www.fhwa.dot.gov/infrastructure/safetyin.cfm)
+
+#### **14**
+
+[http://www.](https://www.fhwa.dot.gov/infrastructure/50interstate.cfm) [fhwa.dot.gov/](https://www.fhwa.dot.gov/infrastructure/50interstate.cfm) [infrastructure/](https://www.fhwa.dot.gov/infrastructure/50interstate.cfm) [50interstate.cfm](https://www.fhwa.dot.gov/infrastructure/50interstate.cfm)
+
+#### **15**
+
+Title 49 of the United States Code, Chapter 301, Motor Vehicle Safety, [https://www.gpo.](https://www.gpo.gov/fdsys/pkg/USCODE-2009-title49/html/USCODE-2009-title49-subtitleVI.htm) [gov/fdsys/pkg/](https://www.gpo.gov/fdsys/pkg/USCODE-2009-title49/html/USCODE-2009-title49-subtitleVI.htm) [USCODE-2009](https://www.gpo.gov/fdsys/pkg/USCODE-2009-title49/html/USCODE-2009-title49-subtitleVI.htm) [title49/html/](https://www.gpo.gov/fdsys/pkg/USCODE-2009-title49/html/USCODE-2009-title49-subtitleVI.htm) [USCODE-2009](https://www.gpo.gov/fdsys/pkg/USCODE-2009-title49/html/USCODE-2009-title49-subtitleVI.htm) [title49-subtitleVI.](https://www.gpo.gov/fdsys/pkg/USCODE-2009-title49/html/USCODE-2009-title49-subtitleVI.htm) [htm](https://www.gpo.gov/fdsys/pkg/USCODE-2009-title49/html/USCODE-2009-title49-subtitleVI.htm)
+
+#### **16**
+
+Federal Motor Vehicle Safety Standard (FMVSS) No. 218, [https://www.federal](https://www.federalregister.gov/documents/2015/05/21/2015-11756/federal-motor-vehicle-safety-standards-motorcycle-helmets) [register.gov/](https://www.federalregister.gov/documents/2015/05/21/2015-11756/federal-motor-vehicle-safety-standards-motorcycle-helmets) [documents/2015/05/](https://www.federalregister.gov/documents/2015/05/21/2015-11756/federal-motor-vehicle-safety-standards-motorcycle-helmets) [21/2015-11756/](https://www.federalregister.gov/documents/2015/05/21/2015-11756/federal-motor-vehicle-safety-standards-motorcycle-helmets) [federal-motor](https://www.federalregister.gov/documents/2015/05/21/2015-11756/federal-motor-vehicle-safety-standards-motorcycle-helmets)[vehicle-safety](https://www.federalregister.gov/documents/2015/05/21/2015-11756/federal-motor-vehicle-safety-standards-motorcycle-helmets)[standards](https://www.federalregister.gov/documents/2015/05/21/2015-11756/federal-motor-vehicle-safety-standards-motorcycle-helmets)[motorcycle-helmets](https://www.federalregister.gov/documents/2015/05/21/2015-11756/federal-motor-vehicle-safety-standards-motorcycle-helmets)
+
+Despite the enthusiasm of political and business leaders, the growth of this system was not without its critics. These critics primarily denounced the destruction of homes and separation of communities that sometimes resulted from new highways bisecting established neighborhoods. Though this opposition halted projects in some locations, it did not stop the expansion of the interstate highway system.
+
+## **Highway Safety Act of 1966**
+
+In 1964, the U.S. faced a sharp rise in the number of traffic fatalities. An increased number of vehicles on the roadways combined with a public culture that did not prioritize roadway safety consciousness led to 47,700 deaths on the nation's highways, an increase of 10 percent over the number of fatalities that occurred in 1963. These deaths prompted the nation to take a hard look at road safety efforts and resulted in Congressional hearings in March 1965 to raise public awareness of the growing national crisis.**<sup>12</sup>**
+
+To respond to these trends, the nation needed a change of direction in the design and operation of its roads and vehicles. This change began with reviewing safety standards in these areas and conducting research to identify effective measures to improve safety. The 1960s was a pivotal decade for road safety due to the passage of laws that provided funding and new policies. On September 9, 1966, President Lyndon B. Johnson signed the National Traffic and Motor Vehicle Safety Act of 1966 and the Highway Safety Act of 1966. The signing ceremony in the Rose Garden
+
+of the White House marked a transformation in the role of the Federal Government in road safety. This role had been growing during the Eisenhower administration, but became a larger area of emphasis as fatalities on the nation's highways climbed toward 50,000. Those in the federal government observed that the steps taken during the previous two decades to reverse the climbing number of fatalities had failed, and they believed that road safety should no longer be left solely to the responsibility of the States, the automobile industry, and the individual drivers.**<sup>13</sup>**
+
+This legislation established the U.S. Department of Transportation (USDOT) and transformed the Bureau of Public Roads into the Federal Highway Administration (FHWA). New bureaus were added to address safety in areas of growing concern, such as the Bureau of Motor Carrier Safety and National Highway Safety Bureau (these would later become the Federal Motor Carrier Safety Administration and the National Highway Traffic Safety Administration, respectively). The USDOT proceeded to develop programs and initiatives and pave the way for activities still in place today.**<sup>14</sup>**
+
+Advances in vehicle design and policy were also an area of emphasis during the 1960s. In 1968, federal legislation required vehicles to provide seat belts. **<sup>15</sup>** Federal law also required States to begin implementing motorcycle helmet laws in order to qualify for particular sources of funding.**<sup>16</sup>** These requirements led to more widespread implementation of safety policies through the late
+
+![](_page_22_Picture_0.jpeg)
+
+President Lyndon B. Johnson signs the National Traffic and Motor Vehicle Safety Act of 1966 and the Highway Safety Act of 1966. *(Source: LBJ Presidential Library)*
+
+1960s and 1970s. Section 402 of the Highway Safety Act established a revenue stream for funding to directly support State programs aimed at improving road safety. Known as the State and Community Highway Safety Grant Program, the funds originally supported a variety of program areas, including many many behavioral safety programs that are still in existence today. **<sup>17</sup>**
+
+## **Energy Crises and Safety Legislation in the 1970s and 1980s**
+
+The 1970s and 1980s were characterized by energy crises in 1973 and 1979 that had immediate and lasting impacts on travel trends. Vehicle Miles Traveled (VMT) decreased following each of these events, as Americans drove less due to rising fuel costs. Strategic legislative action by Congress, such as the National Maximum Speed Law of 1974 which prohibited speeds higher than 55 miles per hour also
+
+helped by decreasing fuel costs. The law would later be repealed in 1995, allowing States to set their own maximum speed limits.
+
+Between 1970 and 2007, there were two periods of time when VMT decreased from the previous year. These years include 1974 and 1979, each of which saw a roughly 18 billion mile decrease in VMT from the previous year.**<sup>18</sup>** As driving decreased, so did traffic fatalities. From 1973 to 1974, for example, traffic fatalities went down 16 percent – the largest single year decline since 1941-1942.**<sup>19</sup>** Driving levels began to increase again once fuel costs normalized, so the reductions were not sustained beyond the period of economic stagnation.
+
+The Highway Safety Act of 1973 established a specific methodology for improving roadway safety from an engineering perspective. It required the States to first survey all hazardous locations and examine **17**
+
+Governors Highway Safety Association. Section 402 State and Community Highway Safety Grant Program. [http://www.ghsa.](http://www.ghsa.org/about/federal-grant-programs/402) [org/about/federal](http://www.ghsa.org/about/federal-grant-programs/402)[grant-programs/402](http://www.ghsa.org/about/federal-grant-programs/402)
+
+**18**
+
+[http://www.](https://www.fhwa.dot.gov/policyinformation/travel_monitoring/tvt.cfm) [fhwa.dot.gov/](https://www.fhwa.dot.gov/policyinformation/travel_monitoring/tvt.cfm) [policyinformation/](https://www.fhwa.dot.gov/policyinformation/travel_monitoring/tvt.cfm) [travel\\_monitoring/](https://www.fhwa.dot.gov/policyinformation/travel_monitoring/tvt.cfm) [tvt.cfm](https://www.fhwa.dot.gov/policyinformation/travel_monitoring/tvt.cfm)
+
+**19**
+
+[https://crashstats.](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811346) [nhtsa.dot.gov/Api/](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811346) [Public/ViewPub](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811346) [lication/811346](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811346)
+
+#### **20**
+
+Source: "HSIP History," accessed October 22, 2013, [http://safety.fhwa.](https://safety.fhwa.dot.gov/hsip/gen_info/hsip_history.cfm) [dot.gov/hsip/gen\\_](https://safety.fhwa.dot.gov/hsip/gen_info/hsip_history.cfm) [info/hsip\\_history.cfm](https://safety.fhwa.dot.gov/hsip/gen_info/hsip_history.cfm) and "Subchapter J— Highway Safety: Part 924—Highway Safety Improvement Program," accessed October 21, 2013, [http://www.](https://www.gpo.gov/fdsys/pkg/CFR-2003-title23-vol1/pdf/CFR-2003-title23-vol1-chapI-subchapJ.pdf) [gpo.gov/fdsys/pkg/CFR-](https://www.gpo.gov/fdsys/pkg/CFR-2003-title23-vol1/pdf/CFR-2003-title23-vol1-chapI-subchapJ.pdf)[2003-title23-vol1/pdf/](https://www.gpo.gov/fdsys/pkg/CFR-2003-title23-vol1/pdf/CFR-2003-title23-vol1-chapI-subchapJ.pdf) [CFR-2003-title23-vol1](https://www.gpo.gov/fdsys/pkg/CFR-2003-title23-vol1/pdf/CFR-2003-title23-vol1-chapI-subchapJ.pdf) [chapI-subchapJ.pdf.](https://www.gpo.gov/fdsys/pkg/CFR-2003-title23-vol1/pdf/CFR-2003-title23-vol1-chapI-subchapJ.pdf)
+
+#### **21**
+
+Source: "What is the Motor Carrier Safety Assistance Program (MCSAP)?" accessed May 23, 2013, [https://www.](https://www.federalregister.gov/documents/2000/03/21/00-6819/motor-carrier-safety-assistance-program) [federalregister.gov/](https://www.federalregister.gov/documents/2000/03/21/00-6819/motor-carrier-safety-assistance-program) [documents/2000/03/](https://www.federalregister.gov/documents/2000/03/21/00-6819/motor-carrier-safety-assistance-program) [21/00-6819/motor](https://www.federalregister.gov/documents/2000/03/21/00-6819/motor-carrier-safety-assistance-program)[carrier-safety](https://www.federalregister.gov/documents/2000/03/21/00-6819/motor-carrier-safety-assistance-program)[assistance-program](https://www.federalregister.gov/documents/2000/03/21/00-6819/motor-carrier-safety-assistance-program)
+
+### **22**
+
+[http://www.iihs.org/](http://www.iihs.org/iihs/topics/laws/safetybeltuse) [iihs/topics/laws/](http://www.iihs.org/iihs/topics/laws/safetybeltuse) [safetybeltuse](http://www.iihs.org/iihs/topics/laws/safetybeltuse)
+
+#### **23**
+
+Source: "Intermodal Surface Transportation Efficiency Act of 1991 Information," last updated May 16, 2013, accessed July 05, 2013, [http://www.fhwa.](https://www.fhwa.dot.gov/planning/public_involvement/archive/legislation/istea.cfm) [dot.gov/planning/](https://www.fhwa.dot.gov/planning/public_involvement/archive/legislation/istea.cfm) [public\\_involvement/](https://www.fhwa.dot.gov/planning/public_involvement/archive/legislation/istea.cfm) [archive/legislation/](https://www.fhwa.dot.gov/planning/public_involvement/archive/legislation/istea.cfm) [istea.cfm.](https://www.fhwa.dot.gov/planning/public_involvement/archive/legislation/istea.cfm)
+
+#### **24**
+
+See next page.
+
+![](_page_23_Figure_10.jpeg)
+
+the causes of crashes at these sites. A benefit/cost analysis was then performed to prioritize needed improvements. This process set the stage for the current safety management processes and would be refined and improved over the years.
+
+The Highway Safety Act of 1973 also clarified the relationship between the Federal Government and the States. The Federal Government was to direct policy and program components, while the States were responsible for implementing those policies and programs.**<sup>20</sup>**
+
+During the 1970s, Congress also established the Motor Carrier Safety Assistance Program (MCSAP). This program provides financial assistance to States to reduce the number and severity of crashes and hazardous materials incidents involving commercial motor vehicles (CMV) through inspection and enforcement programs focused on trucks, carriers, and driver regulations. **<sup>21</sup>**
+
+Vehicle safety continued to be a priority in the 1970s and 1980s, as more States began to implement laws requiring the use of seat belts and motorcycle helmets. New York became the first State to adopt a mandatory seat belt law in 1984, and other States soon followed suit.**<sup>22</sup>**
+
+The Federal Motor Vehicle Safety Standard 213 brought attention to child passenger safety. This standard was the first to outline specific requirements for restraint systems designed for children.
+
+## **Multimodal Shift in the 1990s**
+
+The 1990s saw a shift from transportation policies that focused on motor vehicle safety and efficiency to an acknowledgement of alternate modes of transportation, such as bicycling, walking and use of public transit. The Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) added a multimodal perspective to the Federal-aid highway program.
+
+While ISTEA was not specifically focused on transportation safety, it created some programs to promote safer travel. For example, ISTEA enhanced road safety with new programs that encouraged the use of safety belts and motorcycle helmets.**<sup>23</sup>** The legislation also required the installation of airbags for drivers and front passengers in all cars and trucks.**<sup>24</sup>**
+
+In 1998, the Transportation Equity Act for the 21st Century (TEA-21) provided more focus for roadway safety planning by establishing safety and security as planning
+
+![](_page_24_Figure_0.jpeg)
+
+Officers use specialized devices to measure drivers' blood alcohol content.
+
+priorities. Prior to TEA-21, a State or Metropolitan Planning Organization (MPO) may have incorporated safety in its goals or long-range transportation plan, but specific strategies to increase safety were seldom included in statewide and metropolitan planning processes or documents.
+
+TEA-21 established the Highway Safety Infrastructure program (not to be confused with the Highway Safety Improvement Program, which would be developed several years later), which funded safety improvement projects to eliminate safety problems.
+
+The TEA-21 legislation also encouraged States to adopt and implement effective programs to improve the quality (e.g. timeliness, accuracy, completeness, uniformity and accessibility) of State data needed to identify safety priorities for national, State and local road safety programs.**<sup>25</sup>**
+
+Motor Vehicle Safety Acts are signed, creating
+
+Not to be lost among the TEA-21 legislation, another pivotal moment in transportation legislation came in 2000 when an important provision related to alcohol was included in the USDOT appropriation act. The appropriation carried a requirement that all States must enact laws to limit the legal **blood alcohol content** (BAC) of drivers to 0.08 percent.**<sup>26</sup>** This limit was in line with similar limits imposed on drivers in other countries, though some European countries limit the legal BAC to 0.05 percent.
+
+While 19 States and Washington, D.C., had already enacted this law, the Federal mandate provided a further incentive for other States to do so: States that did not pass the law by 2004 would forego a portion of their transportation funding. Though specific laws vary, each State now recognizes the legal limit of 0.08 percent blood alcohol content.**<sup>27</sup>**
+
+**24**
+
+[http://www.history.](http://www.history.com/this-day-in-history/federal-legislation-makes-airbags-mandatory) [com/this-day-in](http://www.history.com/this-day-in-history/federal-legislation-makes-airbags-mandatory)[history/federal](http://www.history.com/this-day-in-history/federal-legislation-makes-airbags-mandatory)[legislation-makes](http://www.history.com/this-day-in-history/federal-legislation-makes-airbags-mandatory)[airbags-mandatory](http://www.history.com/this-day-in-history/federal-legislation-makes-airbags-mandatory)
+
+**25**
+
+Source: "TEA-21 – Transportation Equity Act for the 21st Century Fact Sheets," last modified April 5, 2011, accessed June 2, 2013, [http://www.](https://www.fhwa.dot.gov/tea21/factsheets/index.htm) [fhwa.dot.gov/tea21/](https://www.fhwa.dot.gov/tea21/factsheets/index.htm) [factsheets/index.htm](https://www.fhwa.dot.gov/tea21/factsheets/index.htm)
+
+### **Blood alcohol content**
+
+The percentage of alcohol in a person's blood, used to measure driver intoxication.
+
+**26**
+
+Rodriguez-Iglesias, C.; Wiliszowski, ClH.; Lacey, J.H. Legislative History of .08 Per Se Laws, National Highway Traffic Safety Administration, Report No. DOT HS 809 286, June 2001
+
+**27**
+
+[http://www.ghsa.org/](http://www.ghsa.org/state-laws/issues/alcohol%20impaired%20driving) [html/stateinfo/laws/](http://www.ghsa.org/state-laws/issues/alcohol%20impaired%20driving) [impaired\\_laws.html](http://www.ghsa.org/state-laws/issues/alcohol%20impaired%20driving)
+
+![](_page_25_Figure_0.jpeg)
+
+## **Legislation in the 21st Century**
+
+Twenty-first century legislation continued to move Federal transportation funding and policy in the direction of focusing on multimodal, data-driven approaches to improving the transportation system. One specific area of focus was a move toward safety planning. Transportation safety planning shifts the focus of traditional planning efforts to a more comprehensive process that integrates safety into transportation decision-making. Safety planning encompasses corridors and entire transportation networks at the local, regional, and State levels, as well as specific sites.**<sup>28</sup>**
+
+In 2005, Congress passed the Safe, Accountable, Flexible, and Efficient Transportation Equity Act—A Legacy for Users (SAFETEA-LU). SAFETEA-LU raised the stature of Federal road safety programs by establishing the Highway Safety Improvement Program (HSIP) as a core Federal-aid program tied to strategic safety planning and performance. HSIP is one of six core Federal-aid programs under which funds are apportioned directly to the States. One of the major elements of the HSIP was
+
+the requirement for each State to develop and implement a Strategic Highway Safety Plan (SHSP).**<sup>29</sup>** The plans sought to establish data-driven approaches that were coordinated with a broad range of stakeholders and utilized a diverse set of disciplines (e.g., engineering, enforcement, education and emergency response). These datadriven plans had to include clear methods for measuring progress toward safety goals.
+
+The Moving Ahead for Progress in the 21st Century Act (MAP-21) was signed into law in 2012. The 2012 legislation transformed the policy and programmatic framework for investments in the country's transportation infrastructure, enhancing the programs and policies established in 1991.
+
+MAP-21 doubled funding for road safety improvement projects, strengthened the linkage among modal safety programs and created a positive agenda to make significant progress in reducing highway fatalities and serious injuries. It provided increased focus on the importance of high quality data, transportation infrastructure and the safety of local streets.
+
+**28**
+
+Source: "Transportation Safety Planning (TSP)," accessed August 13, 2013, [http://safety.fhwa.](https://safety.fhwa.dot.gov/tsp/) [dot.gov/hsip/tsp/](https://safety.fhwa.dot.gov/tsp/) and "Transportation Safety Planning Fact Sheet," accessed August 13, 2013, [http://safety.fhwa.](https://safety.fhwa.dot.gov/tsp/fact_sheet.cfm) [dot.gov/hsip/tsp/](https://safety.fhwa.dot.gov/tsp/fact_sheet.cfm) [fact\\_sheet.cfm](https://safety.fhwa.dot.gov/tsp/fact_sheet.cfm).
+
+**29**
+
+Title 23 United States Code § 148
+
+## **Conclusion**
+
+Exploring the history of travel trends and safety in the U.S. helps illustrate how past decisions have led to the transportation system seen today. Safety has not always been a deciding factor in how roads are built. However, today, safety is a top priority of the USDOT.**<sup>30</sup>** Most State and local transportation agencies share USDOT's goal; some have even set goals to reduce total traffic fatalities to zero. These "vision zero" and "toward zero deaths" goals are guiding transportation projects by requiring safety to be incorporated into every step of project planning, design, construction and operation.
+
+Future safety issues will certainly arise as technological advancements lead to changes in the vehicle fleet. Autonomous and potentially driverless vehicles are being developed and tested across the world. Though safety improvements are touted as a benefit of these advanced vehicles, safety will continue to be a priority as they
+
+![](_page_26_Picture_3.jpeg)
+
+begin to share the roads with older vehicles, bicyclists, and pedestrians. As can be learned from the history of road safety in the U.S., complex problems must be met with safety advancements, legislative action, and collaboration.
+
+#### **30**
+
+U.S. Department of Transportation. Strategic Plans. November 2015. [https://www.](https://www.transportation.gov/mission/budget/dot-budget-and-performance-documents#StrategicPlans) [transportation.gov/](https://www.transportation.gov/mission/budget/dot-budget-and-performance-documents#StrategicPlans) [mission/budget/](https://www.transportation.gov/mission/budget/dot-budget-and-performance-documents#StrategicPlans) [dot-budget-and](https://www.transportation.gov/mission/budget/dot-budget-and-performance-documents#StrategicPlans)[performance](https://www.transportation.gov/mission/budget/dot-budget-and-performance-documents#StrategicPlans)[documents#](https://www.transportation.gov/mission/budget/dot-budget-and-performance-documents#StrategicPlans) [StrategicPlans](https://www.transportation.gov/mission/budget/dot-budget-and-performance-documents#StrategicPlans)
+
+#### **EXERCISES**
+
+- J **RESEARCH** a federal transportation law addressed in this chapter and write a summary about the law, emphasizing the safety aspects.
+- J **FIND** a recent news article that involves road safety (more than just a local news article on a recent crash) and write a summary describing the effort undertaken by the public agency, how it was received by the public, and whether it was shown to be effective in increasing road safety.
+- J **USE** https://www.govtrack.us to find a transportation bill currently proposed or under review by Congress. Describe how the legislation would be expected to affect road safety.
+- J **RESEARCH** the legal driving Blood Alcohol Content (BAC) by state in the U.S. and create a table showing the comparison. Select one state where the legal BAC is lower than the federal requirement, locate a paper or news article describing how that BAC level was decided, and write a summary.
+
+## **Multidisciplinary Approaches**
+
+![](_page_27_Picture_3.jpeg)
+
+Road safety is a complex issue, and any efforts to improve safety must address not only the roadway but also road user behavior, vehicle design, interaction between road users, and the effect of the roadway on all road users. Road safety partners include anyone who influences road user safety, including those in infrastructure safety, behavioral roadway safety, transportation planning, public health, public safety and many other disciplines. Each of these disciplines is able to provide a unique perspective and each has specific methods for addressing road safety. It is becoming increasingly common for these various disciplines to work in collaboration with one another to address road safety through comprehensive programs. Instead of focusing on traditional "silos" of activity, agencies hope that this interaction and collaboration among various disciplines will lead to continued safety improvements.
+
+#### **The E's**
+
+A popular multidisciplinary approach to road safety is sometimes referred to as the "four E's": Engineering, Education, Enforcement, and Emergency response. These E's broadly represent the various disciplines that bring together stakeholders who care about making the road safe for all users. Sometimes a fifth "E" for evaluation is added to this list to represent the important role of evaluating what works and what doesn't. This emphasizes the fact that good data is crucial to the improvement of road safety.
+
+This chapter will discuss road safety efforts from the disciplines of roadway design and engineering, public education, and enforcement campaigns. Working in collaboration with one another, as described above, these groups can share the burden of road safety responsibilities and create comprehensive programs to address the various factors that may contribute to crashes.
+
+## **Roadway Design and Engineering**
+
+Several types of transportation professionals are responsible for roadway safety engineering. Broadly speaking, the roadway safety engineering community includes transportation planners and engineers.
+
+Transportation planning plays a critical role in determining the shape of the transportation system and provides an early opportunity for professionals to address safety needs. Before a road project is designed or built, it is influenced by any number of comprehensive and strategic transportation plans that are coordinated to ensure that the system being developed is one that matches the vision of the local community. Planners work with stakeholders such as the general public, business owners, policy makers, and advocates to establish plans for how the transportation system can best serve every group's needs.
+
+In the past, the traditional planning process focused on economic development, environmental quality, and mobility as the three primary concerns. Most States consider infrastructure safety improvements as part of preservation or improvements projects or within operational changes undertaken by traffic offices. States are now able to use the Highway Safety Improvement Program (HSIP) to fund safety projects in at high priority locations. This program allows development of targeted solutions and approaches that address the contributing factors to collisions, thereby seeking to achieve a higher return on safety investments.
+
+Roadway engineers work on the design, construction and system preservation of the roadways. In particular, engineers are charged with designing roads that minimize the chance that crashes will occur while balancing the needs for efficiency and mobility. Engineers also work to design roads and intersection in such a way that minimizes crash severity and injury risk when crashes do occur. Engineers affect the safety of the built environment by incorporating safety in to the planning process at the beginning of a project; selecting design alternatives that prioritize safety considerations; using design elements that maximize the safety of each part of the road or intersection; ensuring quality and safe construction, operation, and maintenance of the roads; and addressing safety problems at existing locations.
+
+Infrastructure improvements such as paved shoulders, rumble strips, and improved nighttime visibility may prevent drivers from veering off the roadway, and still other opportunities exist for improving the roadside and road user behavior. For example, when a driver veers off the roadway, it is important to provide a roadside environment that reduces the potential for crashes and injury. Roadside slopes and objects such as drainage structures, trees, and utility poles are examples of roadside elements that engineers can target for improvements to road safety performance. One engineering method to increase roadside safety is to create a clear zone—an unobstructed, traversable roadside area that allows a driver to stop safely or regain control of the vehicle that has left the roadway.
+
+Countermeasures that Work: A Highway safety Countermeasures Guide for State Highway Safety Offices, 7th edition, 2013 DOT HS 811 727
+
+#### **Countermeasures That Work**
+
+Countermeasures That Work**<sup>31</sup>** is a comprehensive guidance document providing details of different programs and interventions that are effective in improving safety. The guide is published regularly by NHTSA.
+
+Engineering solutions must incorporate the different needs and preferences of a variety of user groups. As mentioned previously, this often means that tough decisions and trade-offs must be made to arrive at infrastructure solutions that balance the needs of different users. This trade-off can be illustrated with an example of a signalized intersection. Improving intersection safety for pedestrians may involve adding pedestrian crossing time to the signal or separating turn movements to eliminate high risk conflicts. Protected left-turn phases can also improve safety for vehicles, as shown previously. But these new or longer signal phases either add time to the cycle length or keep the same length while reducing time for the through movements. Regardless, the result is more delay to both pedestrians and motorists. In such situations, it is necessary to consider all of these needs and select the appropriate signal timing that meets the needs of all users. Adhering to design standards – creating nominally safe conditions – is only one aspect of the complex roadway design and engineering field. Addressing substantive safety through design strategies requires an understanding of multiple perspectives, trade-offs and user needs.
+
+## **Public Education and Enforcement Campaigns**
+
+Public education and communications campaigns are commonly used to improve road user attitudes and awareness. The structure and delivery methods of these campaigns can take many forms. However, they generally involve materials (media advertisements, informational brochures, posters, presentations, etc.) to inform people of a desired behavior and the benefits of such behavior (or conversely, the risks of an unwanted behavior).
+
+While standalone informational or educational campaigns can improve awareness or perceptions about road safety issues, they are unlikely to change road user behavior. Rather, campaigns that educate the public about increased law enforcement efforts aimed at a particular behavior have been shown to be effective. Generally referred to as "high-visibility enforcement" these campaigns increase the perceived enforcement of a particular law. When people believe there is a high probability of being caught, they are more likely to follow the law. The Click it or Ticket campaign is one of the most widely known examples of high-visibility enforcement. In this case, simply enforcing the seatbelt law was not sufficient. The key to this program's success was the media coverage and other informational campaigns telling the public that law enforcement officers are looking for people who are not wearing a seatbelt. In other words, for those people who do not typically wear a seatbelt, the law itself was not sufficient motivation to change. The motivation came from a
+
+![](_page_30_Picture_0.jpeg)
+
+perceived threat of being caught and ticketed.
+
+When safety professionals analyze possible educational campaigns, they must consider the factors that affect people's behavior and the probability that the campaign will change such behavior. Simply communicating safety messages and enforcing laws may not lead to a change in behavior if a road is designed in a way that allows (or unintentionally encourages) unsafe behaviors. For example, to address a speeding problem on a wide multilane arterial where the posted speed is 35 miles per hour, enforcement and education may not be the only solution. Narrowing the roadway and creating more "visual friction" along the roadside may be needed to alter the desired design speed of
+
+#### **Targeted Enforcement**
+
+To reinforce pedestrian safety laws, police departments can initiate targeted enforcement operations at crosswalks. Under this approach, a law enforcement officer in plain clothes will attempt to cross the street at an uncontrolled crosswalk. Drivers who do not yield to the officer will be pulled over and either cited or warned by patrol vehicles waiting beyond the crosswalk. More info: [http://www.nhtsa.gov/staticfiles/](http://www.nhtsa.gov/staticfiles/nti/pdf/812059-PedestrianSafetyEnforceOperaHowToGuide.pdf) [nti/pdf/812059-PedestrianSafetyEnforce](http://www.nhtsa.gov/staticfiles/nti/pdf/812059-PedestrianSafetyEnforceOperaHowToGuide.pdf) [OperaHowToGuide.pdf](http://www.nhtsa.gov/staticfiles/nti/pdf/812059-PedestrianSafetyEnforceOperaHowToGuide.pdf)
+
+the road. Supplemental education and enforcement campaigns can then help reinforce the proper behavior. This emphasizes the need for cooperation and coordination between disciplines to accomplish
+
+meaningful improvements to road safety.
+
+Zegeer, C. V., Blomberg, R. D., Henderson, D., Masten, S. V., Marchetti, L., Levy, M. M., Fan, Y., Sandt, L. S., Brown, A., Stutts, J., & Thomas, L. J. (2008b). Evaluation of Miami–Dade pedestrian safety demonstration project. Transportation Research Record 2073, 1-10.
+
+While there is evidence to suggest some success for well-designed and executed safety education campaigns when they are targeted at children,**<sup>32</sup>** the same results have not been shown for teens and adults when an educational campaign stands alone. Though well-intentioned, these approaches generally assume that people are not performing the desired behavior simply because they lack the appropriate information. However, this idea fails to take into account the fact that, in general, most human behavior is not the result of conscious, rational deliberation. People are largely influenced by emotions, values, social context, and culture, among many other factors. Thus, simply being presented with information or facts alone is unlikely to lead to any lasting behavior change. In the context of transportation safety, most people do not engage in risky or undesirable behaviors due to a lack of knowledge about the desired behavior. Instead, people act based on a variety of contributing factors.
+
+For example, consider the behavior of a pedestrian on a multi-lane undivided arterial. The goal of the pedestrian is to get to a bus stop located directly across the street from his current location. The pedestrian almost certainly knows that the desired behavior is to walk a quarter mile to the signalized intersection, wait and cross with the crossing signal, and then to backtrack a quarter mile to the bus station. However, instead the pedestrian chooses to cross in the middle of the block. The fact is that there are many factors that
+
+![](_page_31_Picture_5.jpeg)
+
+#### **Bicycle Safer Journey**
+
+Bicycle Safer Journey is an educational program intended to provide bicycle safety skills and education to children. The program uses interactive video lessons to teach children safe bicycling skills and provides resources for parents and teachers. The program can be accessed online at [http://www.](http://www.pedbikeinfo.org/bicyclesaferjourney/) [pedbikeinfo.org/bicyclesaferjourney.](http://www.pedbikeinfo.org/bicyclesaferjourney/)
+
+influence the pedestrian's decision to cross mid-block (time, ability, weather, etc.), but likely the most important factor is that doing so just makes sense. People are wired to choose the option that makes the most intuitive sense. Efforts to change this behavior only through signs, posters or other educational campaigns will likely have only minimal effect.
+
+Similar examples can be found throughout the transportation safety field. Most people already know they should wear their seatbelt, obey posted speed limit signs, and limit distractions while driving. Yet some people refuse to wear a seatbelt,
+
+![](_page_32_Picture_0.jpeg)
+
+#### **Click It or Ticket**
+
+Click It or Ticket is a successful seat belt enforcement campaign that has helped to increase the national seat belt usage rate. The program uses public education to communicate the law and risks of not using seat belts in a variety of settings. The campaigns provide waves of education and enforcement along with high visibility media coverage to publicize and sustain the campaign. NHTSA manages this campaign annually with assistance from the State Highway Safety offices, law enforcement agencies, and national- and local-paid advertising.
+
+some people speed, and some people text while driving. Knowledge alone is not enough.
+
+Successful education and enforcement campaigns recognize the reality of people's behaviors and apply this knowledge to the safety efforts. For example, social norms and cultural influences can provide some explanation for why certain behaviors are common - even those behaviors known to be unsafe. Marketing interventions based on social norms have been applied
+
+### **Media Campaign Effectiveness**
+
+Well planned and executed media campaigns centered on reducing alcohol-impaired driving can be effective in reducing the occurrence of alcohol related crashes. A study in 2004 pointed to a 13 percent decrease in alcohol related crashes following these types of campaigns.**<sup>33</sup>**
+
+to the areas of distracted driving and driving under the influence of alcohol. Such methods provide a way to examine safety problems and **33**
+
+Elder, R.W., et al. Effectiveness of mass media campaigns for reducing drinking and driving and alcohol-involved crashes: a systematic review. July 2004. [http://](http://www.sciencedirect.com/science/article/pii/S0749379704000467) [www.sciencedirect.](http://www.sciencedirect.com/science/article/pii/S0749379704000467) [com/science/](http://www.sciencedirect.com/science/article/pii/S0749379704000467) [article/pii/](http://www.sciencedirect.com/science/article/pii/S0749379704000467) [S0749379704000467](http://www.sciencedirect.com/science/article/pii/S0749379704000467)
+
+![](_page_33_Picture_0.jpeg)
+
+#### **Strategic Highway Safety Plan**
+
+Provides a framework for developing a coordinated and comprehensive approach to addressing road safety across a State.
+
+**34**
+
+[https://safety.](https://safety.fhwa.dot.gov/shsp/guidebook/) [fhwa.dot.gov/shsp/](https://safety.fhwa.dot.gov/shsp/guidebook/) [guidebook/](https://safety.fhwa.dot.gov/shsp/guidebook/)
+
+**35**
+
+[http://safety.fhwa.](https://safety.fhwa.dot.gov/systemic/) [dot.gov/systemic](https://safety.fhwa.dot.gov/systemic/)
+
+what might be done to address them through education and enforcement.
+
+## **Comprehensive Safety Programs**
+
+While each discipline has its own strengths, significant improvements in roadway safety are more likely when a program encompasses many disciplines rather than just one. Interdisciplinary team efforts can take on safety problems using multiple approaches and are therefore greater in scope than individual disciplines working in isolation. The need for this "multiple approach" solution requires collaboration among many parties. This type of collaboration is most clearly seen when agencies seek to create a comprehensive safety plan. Creating a comprehensive safety plan for a city, county, or state must be a data driven process. In doing so, agencies first begin by analyzing their safety data to identify emphasis areas where concentrated efforts are likely to yield the largest
+
+reduction in fatalities and serious injuries.
+
+A State's **Strategic Highway Safety Plan** (SHSP) is an example of a comprehensive safety plan, and one of the best examples of a multidisciplinary, data driven planning effort. A State SHSP provides a framework for developing a coordinated and comprehensive approach to addressing road safety across a State. In the development of a State's SHSP, safety stakeholders from across the State and across disciplines will consider all the data available (i.e., crash, injury surveillance, roadway and traffic, vehicle, enforcement, and driver data) that will help an agency understand where more safety emphasis is needed.**<sup>34</sup>** Beyond crash records, an agency may choose to rely on alternate data sources like roadway characteristics and its own knowledge of crash risk to pursue systemic safety strategies. A systemic approach proactively identifies locations that may have a high risk of crashes but where the risk has not yet resulted in actual crashes.**<sup>35</sup>**
+
+Demographic data showing where population growth has occurred, or where it is expected, can also influence an agency's safety plans. One of the most critical components of the SHSP is an evaluation of past efforts, so that the agency can know what strategies are working and so that progress toward goals can be measured and tracked over time.
+
+Road safety planning, like the field of safety itself, is multidisciplinary in nature and relies upon the expertise and involvement of numerous perspectives. Once developed, these safety plans influence activities ranging from roadway design and engineering to law enforcement and safety education.
+
+Each of the agencies and organizations involved in transportation safety brings a unique and valuable perspective to bear on the roadway safety problem. Their competing philosophies, worldviews and problem solving approaches, however, can make collaboration difficult. Creating a foundation
+
+for effective collaboration and establishing a process to support collaborative efforts are two ways to overcome these barriers. One way to create a foundation for collaboration is to ensure that each agency understands the impact that its actions have on road safety and that each makes safety its top priority. The example of a State Strategic Highway Safety Plan shows this type of collaboration. The SHSP process brings together all potential areas of safety emphasis, including intersections, non-motorized users, rural crashes, and others, and uses a data driven approach to identify priorities and areas of need. This foundation can be further strengthened by identifying which agencies or organizations are responsible for implementing each of the strategies identified in the SHSP.
+
+In the U.S., no single player manages all programs and disciplines that impact road safety. Therefore, collaboration among all players is fundamental to consistently reduce serious injuries and fatalities.
+
+#### **EXERCISES**
+
+- J **FIND** the website for your State or local road safety program. Identify initiatives that your State or local agency is implementing in the areas of planning, engineering, education, and enforcement.
+- J **CONSIDER** a hypothetical situation where it is your job to convene a team of professionals to visit a high crash intersection and explore possible solutions to the safety problem. Create a list of the people who should be included on that team and briefly describe each person's role. Be sure to
+- consider the many different types of programs and strategies that can be used to improve road safety.
+- J **SELECT** an area of concern, either a specific type of road user or an unsafe behavior, and discuss how road safety in this topic area could be addressed or improved through multiple disciplines. Possible topics include:
+  - J Older drivers
+  - J Underage drinking
+  - J Fatigued or drowsy driving
+  - J Pedestrians
+
+## **Road Users**
+
+Drivers of motor vehicles are far from the only users of the road, despite accounting for the majority of trips taken in the U.S. The public right-of-way on most roads is usually shared by a number of different users, traveling by a variety of modes for any number of different reasons. Transportation professionals must understand the mobility and safety needs of different user groups and how they interact with one another to gain a better understanding of safety problems and their potential solutions.
+
+Road user groups include:
+
+- J Passenger vehicle drivers and occupants
+- J Drivers of trucks and other large vehicles
+- J Motorcyclists
+- J Pedestrians
+- J Bicyclists
+
+## **Passenger Vehicle Drivers and Occupants**
+
+Passenger vehicles are typically defined as sedans, pickup trucks, minivans, and sport utility vehicles and represent the primary mode of transportation for the majority of Americans. Since these vehicles account for the vast majority of registered vehicles and vehicle miles traveled, it is not surprising that much of the transportation infrastructure prioritizes the needs of these drivers.
+
+However, despite the priority given to drivers of passenger vehicle, there remain many unresolved safety issues for these drivers. At the core of most of these issues are the driver's actions while navigating the road network. Engineers may work to make a road nominally safe by ensuring it follows the latest recommendations and design standards. However, drivers do not always interact with the road system as road designers expect them to. Thus, a nominally safe road may be much less safe in a substantive sense. While the common reaction has been to assume that some fault or "driver error" led to the crash, this approach fails to take into account a common behavioral principle known as behavioral adaptation. Simply put, behavioral adaptation refers to the unconscious process by which people react to their environment -- people cannot be considered to be a constant in the system.
+
+Consider a town that wants to resurface and widen a two-lane collector roadway through an older neighborhood with mature street trees. The existing road has 9.5 foot wide lanes, a 30 mi/h (48 ki/h) speed limit, and street trees between the roadway and sidewalk. Design guidance may suggest a typical lane width of 12 feet and a wider roadside clear zone. It is easy to assume that the safest choice would be to design a road with the widest lanes possible and removal
+
+![](_page_36_Picture_0.jpeg)
+
+The intended speed of this road is 35 miles per hour, but the wide design of the road and the number of lanes leads drivers to drive much faster.
+
+of the roadside hazards. However, after this resurfacing and widening project was completed, both traffic speeds and crash severity along this roadway may increase considerably. On the surface, this may seem counterintuitive.
+
+In essence, most people drive at a speed that *feels* safe to them. To reach this "safe speed," people unconsciously assess the roadway and its characteristics. Navigating a narrow, curvy road with significant roadside hazards is more challenging than navigating a straight, wide road with large clear zones, so people unconsciously drive slower and more cautiously on the narrow road. When the driving task is made easier by widening the lanes and removing roadside
+
+hazards, people will not maintain their original behavior. In fact, the assumption should be that people will adapt to this change and unconsciously change their behavior accordingly, in this case by increasing their speed.
+
+Behavioral adaptation is not specific to passenger vehicles. When designing the transportation infrastructure, engineers must consider how human behavior plays affects all roadway users. Roadway designers must design roads not for the way in which they would like users to behave, but for the way in which users actually behave. Behavior of drivers and other road users will be covered in a greater detail in Unit 2.
+
+## **Drivers of Trucks and Other Large Vehicles**
+
+Much of the transportation network across the country serves an important commercial need. Truck drivers, in particular, play a significant role in the national economy and are responsible for moving goods between and within cities and States. Large trucks account for only 4 percent of registered vehicles in the U.S., but they make up 9 percent of total vehicle miles traveled and accounted for 12 percent of total traffic fatalities in 2013.**<sup>36</sup>** These large trucks share space on the roads with passenger vehicles, and have their own safety needs. Nationally in 2013, there were just under 4,000 people killed in crashes involving large trucks, and 71 percent of them were occupants of the other vehicle involved in the crash. However, large truck safety has improved over time. Between 2004 and 2013, the miles covered by large trucks increased by roughly 25 percent, while fatalities involving large trucks decreased by about 20 percent (from 4,902 to 3,906).**<sup>37</sup>**
+
+Commercial trucks are not the only large vehicles on the roads. Transit vehicles occupy space on our roadways as well, though they typically serve pedestrians and bicyclists. Transit vehicles that share space with passenger vehicles also have unique needs and challenges. Many of the safety issues associated with transit vehicles are similar to those of large trucks. Bus operators have to consider how stopping in traffic impacts the flow and operation of the transportation system, and must also consider the safety of their passengers boarding and disembarking the vehicle.
+
+Road designs that accommodate large vehicles can sometimes be directly at odds with designs that favor pedestrians and bicyclists. For example, a pedestrian is more comfortable crossing an intersection if the turns are very tight, where the distance between corners in minimized to shorten the walking distance and decrease the time in the roadway. Large trucks and buses, however, require a larger turning radius (when compared to passenger vehicles) in order to turn safely. When designing intersections for large trucks, designers are tempted to increase the amount of space in an intersection and widen the corners. This change will make the turn easier, but it will also be more uncomfortable (and possibly less safe) for pedestrians. As described previously, these trade-offs need to be assessed and discussed when planning road projects.
+
+## **Motorcyclists**
+
+In recent years, motorcycling has become increasingly popular throughout the U.S. Since 2000 the number of registered motorcycles in the U.S. has nearly doubled. **<sup>38</sup> <sup>39</sup>** The result was a 71% increase in the number of motorcyclist fatalities (from 2,897 in 2000 to 4,957 in 2012). Motorcyclists represented 15 percent of all traffic fatalities in 2012, compared to just 7 percent of fatalities in 2000. **<sup>40</sup>** Motorcyclists are significantly overrepresented in traffic fatalities since they account for only 3 percent of registered vehicles and 0.7 percent of total vehicle miles traveled in 2012.**<sup>41</sup>**
+
+**36**
+
+[http://www-nrd.](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812150) [nhtsa.dot.gov/](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812150) [Pubs/812150.pdf](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812150)
+
+**37**
+
+**38**
+
+[http://www.](https://www.fhwa.dot.gov/policyinformation/statistics/2013/pdf/mv1.pdf) [fhwa.dot.gov/](https://www.fhwa.dot.gov/policyinformation/statistics/2013/pdf/mv1.pdf) [policyinformation/](https://www.fhwa.dot.gov/policyinformation/statistics/2013/pdf/mv1.pdf) [statistics/2013/pdf/](https://www.fhwa.dot.gov/policyinformation/statistics/2013/pdf/mv1.pdf) [mv1.pdf](https://www.fhwa.dot.gov/policyinformation/statistics/2013/pdf/mv1.pdf)
+
+**39**
+
+[https://www.fhwa.](https://www.fhwa.dot.gov/ohim/hs00/pdf/mv1.pdf) [dot.gov/ohim/hs00/](https://www.fhwa.dot.gov/ohim/hs00/pdf/mv1.pdf) [pdf/mv1.pdf](https://www.fhwa.dot.gov/ohim/hs00/pdf/mv1.pdf)
+
+**40**
+
+[http://www-fars.](https://www-fars.nhtsa.dot.gov/Main/index.aspx) [nhtsa.dot.gov/](https://www-fars.nhtsa.dot.gov/Main/index.aspx) [Main/index.aspx](https://www-fars.nhtsa.dot.gov/Main/index.aspx)
+
+**41**
+
+[http://www-nrd.](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812035) [nhtsa.dot.gov/](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812035) [Pubs/812035.pdf](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812035)
+
+![](_page_38_Picture_0.jpeg)
+
+In general, many of the roadway modifications done to improve safety for passenger vehicles can pose a challenge for motorcyclists. Rumble strips can be difficult to traverse, especially at low speeds. Guard rails, in particular cable barriers, can present a serious hazard to a motorcyclist impacting one at a high speed. Within the driving environment, motorcyclists are small compared to larger vehicles and can be difficult to see, especially early or late in the day when lighting levels are lower.
+
+## **Pedestrians**
+
+Walking is the most basic form of transportation. At some point during a typical day, nearly every person is a pedestrian. People walk to get to a bus station, to go from home to school, or to get from a
+
+parked vehicle to the front door of a business. Some walking trips are taken out of necessity – not all households own a vehicle, **<sup>42</sup>** and children and individuals with disabilities may not have the option to drive. Many more walking trips are taken by choice, especially for exercise or health. A 2012 survey found that 39 percent of trips taken by foot are done for exercise or personal health purposes. **<sup>43</sup>** Walking is also more common in densely populated urban areas, due to the close proximity of destinations and other services like transit stations.
+
+Regardless of the reasons for walking, this mode accounts for nearly 11 percent of all trips taken in the U.S., according to the 2009 National Household Travel Survey (NHTS). **<sup>44</sup>** The NHTS shows that about a third of all trips taken in the U.S. are shorter than one mile, and 35 percent of these trips are taken by foot. In the 2005 Traveler Opinion and Perception Survey (TOP), conducted by FHWA, data showed that about 107.4 million Americans (51 percent of the traveling public) use walking as a regular mode of travel. **<sup>45</sup>**
+
+Pedestrians (along with bicyclists) are among the most vulnerable road users, and this is reflected in crash data. The 4,743 pedestrians killed in 2012 represented 14.1 percent of total traffic fatalities in the U.S. that year. Between 2008 and 2012, motor vehicle fatalities decreased 13 percent, while pedestrian fatalities increased 8 percent. Within the population of pedestrians, there are certain groups which are especially vulnerable. These include young children, older adults, and individuals with disabilities.
+
+**42**
+
+[https://info.ornl.gov/](https://info.ornl.gov/sites/publications/Files/Pub50854.pdf) [sites/publications/](https://info.ornl.gov/sites/publications/Files/Pub50854.pdf) [Files/Pub50854.pdf](https://info.ornl.gov/sites/publications/Files/Pub50854.pdf)
+
+**43**
+
+[http://www.](http://www.pedbikeinfo.org/data/factsheet_general.cfm) [pedbikeinfo.org/](http://www.pedbikeinfo.org/data/factsheet_general.cfm) [data/factsheet\\_](http://www.pedbikeinfo.org/data/factsheet_general.cfm) [general.cfm](http://www.pedbikeinfo.org/data/factsheet_general.cfm)
+
+**44**
+
+[http://www.](http://www.pedbikeinfo.org/cms/downloads/15-year_report.pdf) [pedbikeinfo.org/](http://www.pedbikeinfo.org/cms/downloads/15-year_report.pdf) [cms/downloads/15](http://www.pedbikeinfo.org/cms/downloads/15-year_report.pdf) [year\\_report.pdf](http://www.pedbikeinfo.org/cms/downloads/15-year_report.pdf)
+
+**45**
+
+[http://www.fhwa.](https://www.fhwa.dot.gov/reports/traveleropinions/1.htm) [dot.gov/reports/](https://www.fhwa.dot.gov/reports/traveleropinions/1.htm) [traveleropinions/](https://www.fhwa.dot.gov/reports/traveleropinions/1.htm) [1.htm](https://www.fhwa.dot.gov/reports/traveleropinions/1.htm)
+
+![](_page_39_Picture_0.jpeg)
+
+Before (left) and after (right) pictures of Stone Way North. *(Source: Seattle DOT)*
+
+#### **Road Diet**
+
+In 2008, Seattle Department of Transportation implemented a road diet on a 1.2-mile (1.9-kilometer) section of Stone Way North from N 34th Street to N 50th Street. In addition to serving motor vehicles, this segment of Stone Way North helps connect a bicycle path with a park. Within five blocks are eight schools, two libraries, and five parks.
+
+The modified segment was originally a four-lane roadway carrying 13,000 vehicles per day. For this corridor, the city's 2007 bicycle master plan recommended climbing lanes and shared lane markings (previously known as
+
+80 percent following the project. *Summarized from a 2011 Public Roads article: [http://www.fhwa.dot.gov/publications/](https://www.fhwa.dot.gov/publications/publicroads/11septoct/05.cfm)*
+
+Young children are a vulnerable road user group, and may be more likely than adults to rely on walking as a primary transportation mode – especially before they are old enough to drive. One area of concern is creating a safe environment for young children when they walk to school. Safety professionals need to ensure that sidewalks and street crossings have the appropriate measures to assist children in traveling safely, and educate children about safe walking.
+
+Another vulnerable portion of the pedestrian population includes those who are blind or visually
+
+*[publicroads/11septoct/05.cfm](https://www.fhwa.dot.gov/publications/publicroads/11septoct/05.cfm)* impaired. These pedestrians have increased challenges in navigating the road safely, particularly at street crossings. Challenges faced by a blind or visually impaired pedestrian include finding the appropriate crossing point at an intersection corner or midblock location, determining the appropriate time to cross, and crossing quickly and accurately. Both crossing and traversing a sloped sidewalk can be equally difficult for an individual in a wheelchair, where even slight cracks or bumps in the sidewalk can present
+
+major obstacles. The difficulties of these challenges increase at locations
+
+"sharrows"). The cross section reduced the number of travel lanes to add bicycle lanes and parking on both sides. The resulting corridor saw a decrease in the 85th percentile speed, while the overall capacity remained relatively unchanged despite the reduction in the number of lanes. The number of bicyclists on the corridor increased by 35 percent, but crashes involving bicyclists did not increase. Pedestrian crashes declined by
+
+with unusual geometry, irregularly timed signals, or non-stop vehicle flow such as roundabouts and channelized turn lanes.
+
+Older adults face many challenges as well. There are a number of age-related changes that affect the functional ability of older adults to safely walk and cross the street. These changes include diminished physical capability, sensory perception, cognitive skills and lag in reflexive responses. Eyesight deterioration can diminish an older person's ability to see and read guide signs, slow their reaction time and decrease their ability to gauge a vehicle's approaching speed or proximity. **<sup>46</sup>**
+
+Drivers and pedestrians share responsibility for many pedestrian fatalities, as both parties attempt to navigate through the same space at the same time. Though we know that certain factors are likely to result in more severe pedestrian crashes, such as speed **<sup>47</sup>**, no single cause stands out as the major contributor to pedestrian crashes. For this reason, no single countermeasure alone would likely make a substantial impact on the number of pedestrian crashes. A successful countermeasure program should use a mix of engineering, environmental, educational and enforcement measures to improve pedestrian safety. **<sup>48</sup>**
+
+![](_page_40_Picture_3.jpeg)
+
+Source: "Identifying Countermeasure Strategies to Increase Safety to Older Pedestrians," National Highway Traffic Safety Administration, 1.
+
+![](_page_40_Picture_5.jpeg)
+
+[https://www.](https://www.aaafoundation.org/sites/default/files/2011PedestrianRiskVsSpeed.pdf) [aaafoundation.org/](https://www.aaafoundation.org/sites/default/files/2011PedestrianRiskVsSpeed.pdf) [sites/default/files/](https://www.aaafoundation.org/sites/default/files/2011PedestrianRiskVsSpeed.pdf) [2011Pedestrian](https://www.aaafoundation.org/sites/default/files/2011PedestrianRiskVsSpeed.pdf) [RiskVsSpeed.pdf](https://www.aaafoundation.org/sites/default/files/2011PedestrianRiskVsSpeed.pdf)
+
+#### **48**
+
+Source: "Identifying Countermeasure Strategies to Increase Safety to Older Pedestrians," National Highway Traffic Safety Administration, 36
+
+![](_page_40_Picture_9.jpeg)
+
+## **Bicyclists**
+
+Bicyclists were some of the first users of U.S. roads, and the group that made the earliest push to improve road conditions. In recent years, bicycling has seen a rise in popularity for both recreation and transportation. Data from the 2009 NHTS showed that while only 1 percent of all trips are taken by bicycle, the number of bicycle trips doubled between 1990 and 2009.**<sup>49</sup>**
+
+While bicyclists account for only 1 percent of all trips, the 726 bicyclist fatalities in 2012 represented 2 percent of all traffic fatalities that year.**<sup>50</sup>** While the number of bicyclists killed has risen only slightly since 2008, the decline in motor vehicle deaths means that bicyclists account for an increasing share of total traffic fatalities.
+
+Bicyclists face unique challenges as road users. More often than not, bicyclists share space with motor vehicles and are considered legal users of the road in most locations. Many potential bicycle riders are not comfortable sharing the road with heavy vehicular traffic and may be deterred from riding their
+
+bicycles. Intersections can also pose a challenge to bicycle riders when they include high volumes of turning traffic and a large number of lanes. These barriers to bicycling, busy street segments and intersections, often discourage potential riders even when the rest of a bicycle network is comfortable. Many bicyclists are willing to go out of their way to use a route that has lower vehicle volumes and speeds, or bicycle facilities that are separated from traffic. Safe bicycle facilities can also improve connections to shopping, transit, jobs, schools, and essential services.
+
+## **Conclusion**
+
+Successful road safety programs will consider the needs of all users when planning and developing transportation projects. Each user group plays an important role in the transportation system, and each has unique safety needs that safety professionals must consider. Road user decisions are influenced by a variety of factors, and the combinations of factors that result in particular travel behavior cannot easily be categorized or understood in simple terms.
+
+## **49**
+
+[http://www.](http://www.pedbikeinfo.org/cms/downloads/15-year_report.pdf) [pedbikeinfo.org/](http://www.pedbikeinfo.org/cms/downloads/15-year_report.pdf) [cms/downloads/](http://www.pedbikeinfo.org/cms/downloads/15-year_report.pdf) [15-year\\_report.pdf](http://www.pedbikeinfo.org/cms/downloads/15-year_report.pdf)
+
+**50**
+
+[http://www-nrd.](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812018) [nhtsa.dot.gov/](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812018) [Pubs/812018.pdf](https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812018)
+
+#### **EXERCISES**
+
+- J **PROVIDE** an example of a road project where the changes resulted in improvements for one user group, but negatively impacted another group. This example could be hypothetical or based on a real world experience.
+- J **VISIT** the Fatality Analysis Reporting System (FARS) Encyclopedia home page (http://www-fars.nhtsa.dot.gov/Main/
+
+index.aspx). Use the data available for the most recent year to document fatality numbers for the different road user groups discussed in this chapter (e.g. motorists, pedestrians, bicyclists). What other information on road user safety can you find with the tools available in FARS, and what data is not included?
+
+THIS PAGE INTENTIONALLY LEFT BLANK
+
+![](_page_43_Picture_0.jpeg)
+
+## **Human Behavior and Road Safety UNIT 2**
+
+#### **LEARNING OBJECTIVES**
+
+After reading the chapters and completing exercises in Unit 1, the reader will be able to:
+
+- J **EXPLAIN** the systems that drive human behavior and give examples of each
+- J **EXPLAIN** why it is important to consider the nature of human behavior when designing and implementing systems or programs
+
+## **Understanding Human Behavior**
+
+## **Introduction**
+
+Guinea worm disease is a parasitic infection that occurs in remote parts of Africa. Symptoms of Guinea worm disease can be debilitating and lead to secondary infections, both of which can affect an infected person's ability to perform everyday tasks including working, harvesting food and caring for children. The disease is caused by drinking water contaminated with Guinea worm larvae. When a worm is mature, it creates a painful blister on the infected person's skin. If the person immerses the affected body part in water, it can temporarily relieve the pain from the blister. However, this also allows the worm to release eggs into the water, continuing the infection cycle by spreading the disease to others**<sup>1</sup>** .
+
+There were 3.5 million cases of Guinea worm disease throughout the world in 1986. By 2015, there were only 22 cases. In 30 years the disease has been nearly eradicated — the only human disease to be eradicated besides smallpox**2,3**. How were such large advances made in only 30 years, and what does this have to do with road safety?
+
+Unlike smallpox, there are no known medicines or vaccines that prevent Guinea worm disease. Eradication, therefore, required a different approach: changing human behavior.
+
+## **The Human Factor**
+
+A report from the National Cooperative Highway Research Program (NCHRP) defines "human factors" as follows:
+
+*Human factors is an applied, scientific discipline that tries to enhance the relationship between devices and systems, and the people who are meant to use them. As a discipline, human factors approaches system design with the "user" as its focal point. Human factors practitioners bring expert* 
+
+Cairncross, S., Muller, R., and Zagaria, N. (2002). Dracunculiasis (Guinea Worm Disease) and the Eradication Initiative. Clinical Microbiology Reviews, 223-246.
+
+World Health Organization and the Carter Center, Eradication of Guinea Worm Disease: Case Statement, 2016. Available at: [https://](https://www.cartercenter.org/resources/pdfs/health/guinea_worm/2016-gw-case-statement.pdf) [www.cartercenter.](https://www.cartercenter.org/resources/pdfs/health/guinea_worm/2016-gw-case-statement.pdf) [org/resources/pdfs/](https://www.cartercenter.org/resources/pdfs/health/guinea_worm/2016-gw-case-statement.pdf) [health/guinea\\_](https://www.cartercenter.org/resources/pdfs/health/guinea_worm/2016-gw-case-statement.pdf) [worm/2016-gw-case](https://www.cartercenter.org/resources/pdfs/health/guinea_worm/2016-gw-case-statement.pdf)[statement.pdf](https://www.cartercenter.org/resources/pdfs/health/guinea_worm/2016-gw-case-statement.pdf)
+
+![](_page_44_Picture_15.jpeg)
+
+WHO, Dracunculiasis Fact Sheet. May 2016. Available at: [http://www.who.](http://www.who.int/mediacentre/factsheets/fs359/en/) [int/mediacentre/](http://www.who.int/mediacentre/factsheets/fs359/en/) [factsheets/fs359/en/](http://www.who.int/mediacentre/factsheets/fs359/en/)
+
+![](_page_44_Picture_17.jpeg)
+
+4
+
+John L. Campbell, Monica G. Lichty; et al. (2012). National Cooperative Highway Research Program Report 600: Human Factors Guidelines for Road Systems (Second Edition). Washington, D.C.: Transportation Research Board.
+
+Kahneman, D. (2011) Thinking, Fast and Slow. Farrar, Straus and Giroux
+
+*knowledge concerning the capabilities and limitations of human beings that are important for the design of devices and systems of many kinds.***<sup>4</sup>**
+
+In road safety, the term human factors is typically used to describe how people respond to the roadway environment. However, people are not simply users of the transportation system. Humans also design, engineer, build and maintain the roadway environment, the vehicles using it and the laws governing behavior of roadway users and vehicle manufacturers. In that sense, the entire transportation system is a product of human factors. The term human factors conveys an oversimplified notion of the role of human behavior in transportation safety. The human part of the equation is more complex than simply a list of discrete factors.
+
+## **Key Principles of Human Behavior**
+
+To understand human behavior, it is important to bear in mind four key principles.
+
+- J Human behavior is guided by two different systems (deliberative and intuitive).
+- J Humans are not exclusively logical, rational beings.
+- J Human behavior is heavily influenced by the environment.
+- J Humans make mistakes.
+
+Let's discuss these concepts as they relate to road safety.
+
+## **Human behavior is guided by two different systems**
+
+Human behavior is largely guided by
+
+two different systems – a deliberate, rational system (deliberative) and an implicit, unconscious system (intuitive)**<sup>5</sup>** .
+
+The deliberative system is a conscious system wherein a person considers information using rational thought, logic and reasoning in deciding on an action.
+
+#### **For example:**
+
+When driving home after work, a driver decides to change routes to avoid an area that is usually congested at this time of day.
+
+In this example, the driver considered the available information (time of day and previous experience with that location) and made a conscious decision to take another route.
+
+The intuitive system is an implicit, unconscious process by which a person makes nearly instantaneous decisions and takes a resulting action.
+
+#### **For example:**
+
+As a driver approaches a signalized intersection, the light turns yellow. Without conscious thought, the driver either proceeds through the intersection or comes to a stop.
+
+In this example, the driver receives information from the environment (the yellow light), combines it with an understanding of the specific circumstance based on the driver's previous experiences, and takes an action almost immediately. It is important to realize the intuitive system acts nearly instantaneously without the driver's awareness of the process.
+
+We often incorrectly assume that human behavior is largely controlled by the deliberative system when, in fact, most behaviors are a result of the intuitive system. In other words, most human behavior is not the result of conscious, rational deliberation. For most actions, we don't have enough time or available information to do a logical analysis before acting. The intuitive system allows us to act without this timeconsuming conscious decisionmaking process.
+
+To think of this another way, consider the deliberative system as similar to the decision making process of a computer. Computers function exclusively using a deliberative system. They take in information, process it using explicit algorithms and deliver a result. However, humans do not function this way. They generally make decisions that appear to reflect instinctual processes rather than systematic rational considerations.
+
+## **Humans are not exclusively logical, rational beings**
+
+Although people take in and interpret information, they do so in the context of a number of factors, such as prior experience, emotions, cultural norms, moral beliefs, social pressures, convenience, habits and financial considerations, among many others. Rational calculations based on objective evidence are often not even possible, and when they are, they must compete with these other influences. This is why people often make decisions that are not necessarily the most appropriate choice for their health and wellbeing.
+
+We know that cooking dinner at home may be healthier, but sometimes it is easier and more convenient to have a pizza delivered instead. We know we should exercise more and get the recommended amount of sleep each night, but work, family and other obligations
+
+### **Flossing and human behavior**
+
+At some point in your life, you have probably been told that regular flossing is good for your dental health. Through the years, you've likely had conversations about flossing with your dentist or dental hygienist who encouraged you to floss more. Perhaps they showed you the proper way to floss and sent you home with your own floss in an effort to encourage you to start. For a few days or weeks after the appointment, you may have deliberately flossed more regularly. But if you're like most people, you soon reverted to old habits, and the floss sat unused in a cabinet. Why do we do this?
+
+Typically, programs aimed at influencing human behavior take an educational or informational approach on the assumption that people act a certain way because
+
+they lack knowledge about the potential consequences, benefits or alternatives. Surely, if people simply were aware of the benefits of flossing or the consequences of not flossing, they would change their behavior and become regular flossers. This approach appeals to the belief that human behavior is rational.
+
+Although commonly used, this approach fails to take into account the complexities of human behavior. Other factors influence our behaviors – flossing is inconvenient, takes time and can be uncomfortable. The negative consequences of not flossing (e.g., gum disease) are not immediately visible. Although people repeatedly hear messages explaining why flossing is important, rates of flossing among the general population remain low.
+
+can make this difficult. We know we should get a flu shot, but a fear of needles may keep us away.
+
+Humans are largely intuitive beings which means their actions are rarely the result of a systematic, rational decision making process. For years, many people did not brush their teeth daily, even though the benefits of brushing were widely known. It was not until mint flavoring was added to toothpaste that daily brushing became the norm. That is, information about the benefits of brushing did little to change behavior; what convinced people to brush was a desire for the clean feeling they associated with the mint.**<sup>6</sup>** Because the factors that affect human behavior are complex and interrelated, behavior is not easily changed. When attempting to change the behavior of others, we tend to assume that people are entirely logical and rational beings. However, experience repeatedly shows this is not the case.
+
+This situation is not unique to dental hygiene. We regularly do things that we generally realize are not in our best interest. We don't eat the recommended amounts of fruits and vegetables. We don't get enough sleep. We don't exercise as much as we should. Think about examples from your own life.
+
+## **Human behavior is heavily influenced by the environment**
+
+Often the environment has a much stronger influence on a person's behavior than internal conditions (e.g., attitudes and personality) commonly assumed to be influential. The environment includes the physical environment, as well as
+
+#### **Optical Speed Bars**
+
+Optical Speed Bars (OSBs) have shown promise in reducing vehicle speeds in advance of hazardous locations**<sup>7</sup>** . OSBs are a series of white rectangular markings, placed just inside both edges of the travel lane and spaced progressively closer, to create the illusion of increasing speed when traveling at a constant rate as well as the impression of a narrower lane**<sup>8</sup>** . A compelling characteristic of optical speed bars is that they operate on intuitive, rather than conscious, decisions made by drivers/riders. By creating a sense of increasing speed as riders approach a dangerous curve, they should induce riders to slow down – as an instinctive reaction rather than a conscious decision.
+
+social and organizational contexts, such as policies and social norms.
+
+Given that most behavior is intuitive, people generally do not know the true reasons for their actions, nor can they validly articulate what might influence their actions. People can usually provide explanations for their behavior after the fact, but research shows people are often not aware of the strong influence of environmental factors on their behavior. An example in Unit 1 of this book describes a town that aims to resurface and widen a
+
+6
+
+Duhigg, Charles. The Power of Habit: Why We Do What We Do in Life and Business
+
+Gates TJ, Qin X, Noyce DA. Effectiveness of Experimental Transverse-Bar Pavement Marking as Speed-Reduction Treatment on Freeway Curves. In Transportation Research Record: Journal of the Transportation Research Board, No. 2056, Transportation Research Board of the National Academies, Washington, D.C., 2008, pp. 95–103.
+
+Federal Highway Administration. Engineering Countermeasures for Reducing Speeds: A Desktop Reference of Potential Effectiveness. [http://safety.fhwa.](https://safety.fhwa.dot.gov/roadway_dept/horicurves/fhwasa07002/ch7.cfm) [dot.gov/roadway\\_](https://safety.fhwa.dot.gov/roadway_dept/horicurves/fhwasa07002/ch7.cfm) [dept/horicurves/](https://safety.fhwa.dot.gov/roadway_dept/horicurves/fhwasa07002/ch7.cfm) [fhwasa07002/ch7.](https://safety.fhwa.dot.gov/roadway_dept/horicurves/fhwasa07002/ch7.cfm) [cfm](https://safety.fhwa.dot.gov/roadway_dept/horicurves/fhwasa07002/ch7.cfm).
+
+#### **Environment affects behavior**
+
+Research has shown that people are more likely to help another person (in a nonemergency situation) if they see someone else helping first. Social psychologist Robert Cialdini demonstrated this by counting donations given to a street musician with and without a colleague first modeling the behavior by donating money. He found that many more people gave the musician money when the behavior was modeled than in the control condition with no behavior modeling (eight donations in the modeled condition versus one donation in the control condition). Further, when people in the modeled condition were asked why they donated, no one realized that they had been influenced by the behavior of another person. Instead, they attributed their donations to something else, such as enjoyment of the song or how they felt about the person playing the music**9,10,11**.
+
+two-lane collector roadway through a neighborhood with mature trees. However, after completing the project, both speeds and crash severity increased. Behavioral adaptation refers to the unconscious process by which people react to their environment. While driving, people unconsciously assess the roadway and its characteristics and modify their behaviors accordingly.
+
+This may seem counterintuitive, but as discussed, human behavior is an intuitive process that is heavily influenced by the environment. A wider road with limited roadside hazards feels safer and people unconsciously adapt their behavior accordingly. You should assume people would not maintain their original behavior when the driving environment is changed.
+
+Roadway designers must design roads not for the way in which they would like users to behave, but for the way in which users actually will behave. In general, people don't just do what they are told to do — by a sign, a law or another person. Instead, they integrate information from many parts of their environment along with their own historical experience as they determine (usually non-consciously) what they should do in a given situation**<sup>12</sup>**.
+
+## **Humans make mistakes**
+
+Both our deliberative and intuitive systems can lead us to make mistakes. Actions reached by a deliberative process can be mistaken if we fail to consider all relevant information or if we process it incorrectly. Similarly, our intuitive system can lead to errors in situations with which we have little or no experience. Experience helps to refine the intuitive processes, so the likelihood of mistakes declines with exposure to situations. However, mistakes are inevitable and the transportation infrastructure needs to be designed with the recognition that road users will make mistakes and that they will often make them in predictable ways.
+
+Have you ever looked down at your speedometer and realized that you were driving substantially over the speed limit? You probably didn't make a conscious (deliberative) decision to exceed the speed limit. Instead, you reached that speed by taking cues about the proper speed from your environment (intuitive). Characteristics of the road, such as wide lanes, multiple travel lanes,
+
+9
+
+Cialdini. R.B. (20005). Basic Social Influence Is Underestimated. Psychological Inquiry, 16: 158-161
+
+Cialdini, R.B., Demaine, L.J., Sagarin, B.J., Barrett, D.W., Rhoads, K., & Winter, P.L. (2006). Managing social norms for persuasive impact. Social Influence, 1: 3-15
+
+Cialdini, R.B. (2007). Descriptive social norms as underappreciated sources of social control. Psychometrika, 72: 263-268
+
+Etzioni, Amitai. Human Beings Are Not Very Easy To Change After All, Saturday Review, June, 1972.
+
+![](_page_49_Picture_0.jpeg)
+
+**FIGURE 2-1**: Example of unconscious clues leading to higher speed
+
+presence of a median and long gentle curves, convey the message that the road can accommodate high speeds. Additionally, the speed of other vehicles is a particularly salient indicator of the right speed.
+
+Recall this example from Unit 1 (Figure 1-1). Although the posted speed limit is 35 mph, many people drive much faster than that. This is not because they all have a blatant disregard for safety. Instead, they are unconsciously taking cues from their environment, which is telling them it is safe to travel at a higher speed. Add to this the fact that modern vehicles have been engineered for occupant comfort, so many of the auditory and haptic cues (e.g., wind noise, bumps, road noise, etc.) that previously gave drivers feedback about their speed have been eliminated. On a road
+
+with very few other vehicles, the only clear clue to one's speed is the speedometer.
+
+Roads constructed according to the recommended design standards may be considered safe, but in reality, they may only be nominally safe. The fact that some road designs encourage higher speeds can make it substantively unsafe. The transportation system is designed, built, maintained, governed and used by humans. It is often cited that human error contributes to more than 90% of traffic crashes, most often referring to a road user error. However, it is important to remember that errors by road users are not the only human errors that can occur.
+
+#### **For example:**
+
+On a rural two-lane road, an SUV
+
+driver over-compensates when a tire slips off the roadway causing the vehicle to roll over and strike a tree on the opposite side of the road.
+
+Where was the human error in this example? Was it in the driver who didn't stay on the road and overcompensated with steering? Was the road maintained improperly or inadequately? Could the crash have been prevented if edgeline rumble strips had been installed, or if the road had a paved shoulder instead of a soft gravel shoulder? Should the tree next to the roadway have been removed? Could SUVs be designed so they are less susceptible to roll over? The answer is that a combination of several of these caused the crash, not simply the driver's error. Just as
+
+in airplane crashes, it is quite rare that any single factor in a motor vehicle crash was the sole reason for the crash or for its severity.
+
+Meeting nominal safety does not guarantee that a crash will never occur, nor does it guarantee that users will behave in the intended way. Those in charge of the road should use professional judgement to prioritize safety improvements and select appropriate designs within a range of options based on consideration of road user behavior. Unit 3 discusses how many kinds of data, such as crash data and behavioral observation, can be used to evaluate the substantive safety of the road.
+
+#### **EXERCISES**
+
+- J **MAKE** a list of your own driving behaviors. What behaviors involve the deliberative system? What behaviors are intuitive?
+- J **WORK** with your state department of transportation to identify a crash cluster in your area. It's highly unlikely that many
+
+drivers have independently made the same mistake at the same location. What characteristics of the roadway as designed or built — may have contributed to this cluster of crashes? What modifications might be made that would not be offset by behavioral adaptation?
+
+![](_page_50_Picture_8.jpeg)
+
+## **Changing Human Behavior**
+
+Let's return to the Guinea worm disease example. You may be wondering why something so seemingly unrelated to improving safety in a modern transportation system was used to introduce this unit. The fact that Guinea worm disease is nearly extinct in only 30 years is a tremendous achievement. The fact that it was done through behavior change alone, without the use of vaccines or medication, is unprecedented.
+
+Road safety professionals would be wise to consider the successful approach to eradicate Guinea worm disease. Although the desired behaviors may be different, the general strategies for influencing human behavior are the same. Even though changing human behavior is exceedingly difficult, it is possible to achieve behavior change. However, this requires that we take into account the nature of human behavior instead of assuming that simply providing information is sufficient.
+
+## **Understanding factors that influence human behavior**
+
+To change human behavior, it is important to identify and understand not only the target behavior but also any other factors that influence the behavior. Attempting to change a behavior without a full understanding of the many contributing factors will almost certainly fail.
+
+![](_page_51_Picture_8.jpeg)
+
+**FIGURE 2-2**: Guinea worm disease hotspots in Africa
+
+![](_page_52_Figure_0.jpeg)
+
+**FIGURE 2-3**: Guinea worm disease factors, behaviors and outcomes
+
+Doctors knew that Guinea worm disease spreads by people drinking contaminated water, and contamination of the water supply occurred when an infected person used the water supply to temporarily relieve the symptoms of infection. Hence, the eradication campaign focused on two main behaviors:
+
+- J Drinking contaminated water
+- J Using drinking water sources to temporarily relieve the pain caused by the infection
+
+Simply identifying these behaviors was not sufficient. In order to be successful, public health officials considered many other factors influencing these behaviors.
+
+**Why were people drinking contaminated water?**
+
+- J **Availability** Uncontaminated drinking water may not have been available in the community.
+- J **Money** People and communities lacked financial resources to obtain clean drinking water.
+- J **Understanding** People did not know that the water was contaminated and/or how the
+
+disease was transmitted.
+
+J **Lack of immediate consequences** – Guinea worm disease symptoms did not appear until one year post-infection.
+
+**Why were people using drinking water to relieve the pain caused by the infection?**
+
+- J **Immediate benefit**  Water submersion resulted in immediate pain relief.
+- J **Limited availability of water** Because water is scarce, most water sources were used for drinking.
+- J **Unavailability of alternative treatments** – The lack of medical infrastructure meant limited access to treatment options.
+- J **Money** People lacked financial resources to obtain medical treatment even when available.
+  - J **Understanding**  People lacked knowledge about how the disease is transmitted.
+
+A thorough understanding of the factors that influence behavior is necessary to develop a plan for behavior change.
+
+look for the cause of the outcome, instead we need to look for the weak links in the causal chain and intervene at these links. In the case of Guinea worm disease, the limited availability of water and lack of understanding about the disease and its transmission were factors influencing both behaviors. Thus, these factors were targeted in the intervention.
+
+To develop a plan, we cannot merely
+
+Public health officials informed the people about the dangers of drinking contaminated water and how the water was becoming contaminated. However, they knew that simply providing this information would not be sufficient.
+
+In order to make the right behavior the easy choice, officials combined education with environmental change – they educated people on guinea worm disease and made clean water more accessible. Water sources known to be contaminated were treated to prevent transmission, and new clean water sources were created. When water sources could not be treated, villagers were given cloth filters to decontaminate their water before drinking. When people had access to clean water, they were less likely to drink contaminated water, thus significantly reducing the chance of infection**<sup>13</sup>**. This change to the environment (i.e., making clean water available) proved to be key in eliminating the disease.
+
+While this is an oversimplified description of the complex and multifaceted approach that occurred over 30 years, it highlights what can be accomplished when principles of behavior change are at the core of a
+
+comprehensive approach.
+
+## **Approaches to Changing Behavior**
+
+We are constantly exposed to attempts to influence our behavior. Consider the following things that you may encounter in everyday life:
+
+- J A brochure in your doctor's office about the benefits of getting a flu shot
+- J A requirement that restaurants include nutritional information in their menu
+- J Stores that charge for plastic shopping bags
+- J Public service announcements (PSAs) about bullying
+- J Cities that provide large recycling bins and small garbage bins
+- J A law requiring that everyone wear seatbelts
+
+Most of these attempts either provide information (e.g., a brochure with information about flu shots or a PSA detailing the negative impact of bullying), or they change the environment in such a way to encourage a different behavior (e.g., stores that charge for plastic shopping bags or cities that provide large recycling bins and small garbage bins). Understanding the nature of the problem is important in determining which approach has the best chance of success.
+
+## **Education, safety messages and raising awareness**
+
+Education and awareness-raising campaigns are often the first and only tools tried when attempting to influence behavior. In general,
+
+13
+
+Cairncross, S., Muller, R., and Zagaria, N. (2002). Dracunculiasis (Guinea Worm Disease) and the Eradication Initiative. Clinical Microbiology Reviews, 223-246.
+
+![](_page_54_Figure_0.jpeg)
+
+This tip card from the early 1900s was likely ineffective in changing the crossing habits of people since it relied solely on providing information.
+
+the goal of such campaigns is to communicate information with the assumption that once the audience is aware of the information, they will then act in the desired manner. In other words, educational campaigns appeal to the deliberative system and assume that human behavior is usually a product of rational thought. Because of this, information alone almost never works. However, information can be helpful as part of a more comprehensive program.
+
+Far too often information-based approaches are used in isolation, without careful consideration of whether the problem can be effectively addressed through raising awareness alone. Is the information new to the audience? Is it likely that knowing this information will produce the desired outcome? To draw from a previous
+
+example: does simply knowing that you should floss convince you to floss regularly?
+
+Consider the effect of an educational campaign on Guinea worm disease. Would an educational or awareness raising campaign be enough to produce lasting and consistent behavior change? On the one hand, there was a lack of knowledge about the disease among those affected, especially about how the disease was transmitted. However, this education cannot influence the additional — and likely more important — factors contributing to the problem. For example, education will not improve the availability of clean drinking water or access to alternative medical resources, nor will it provide the financial resources necessary to increase access to either. Thus, an education campaign, on its own, would not
+
+![](_page_55_Picture_0.jpeg)
+
+have been a successful tactic. Instead, health officials needed a more comprehensive approach.
+
+The same considerations can be applied to road safety problems. Consider the following example:
+
+Your city manager notices an increase in pedestrian crashes following the placement of a new bus stop on Elm Street, a busy multi-lane road without a median. The bus stop is located in the middle of the block across from a large shopping center (Figure 2-4). The nearby intersections on either side are signalized and have street lights, crosswalks and pedestrian signals. The intersection and crosswalks meet all applicable design standards and are therefore nominally safe. Although city engineers intended that people would cross the street at the intersections, observations show that many people are crossing mid-block from the shopping center to the bus stop, resulting in frequent conflicts with vehicles. The city wants to improve safety in this area and has decided to undertake a media campaign encouraging people to cross only at crosswalks.
+
+**What behavior is being targeted?** Crossing Elm Street midblock.
+
+**What are the other factors influencing this behavior?**
+
+- J **Convenience** Crossing midblock provides a more direct route to the bus stop. People coming from the shopping center are likely carrying shopping bags, which could be difficult to carry long distances.
+- J **Previous experience** It is likely that people have successfully crossed similar streets (or even the same street) in this manner many other times, so their limited previous experience suggests this is a safe option. (we say limited experience because people not likely to be aware of the location's crash history).
+- J **Time pressure** Buses run on a schedule, and people may want to cross as quickly as possible to be sure they catch the next bus.
+
+Is an educational or awareness raising campaign targeting this behavior likely to be effective? No. In all likelihood, people who are
+
+crossing the street in this spot know there are crosswalks at the nearby intersections. They are crossing the street here because it is easier and more convenient, and their previous experiences tell them they will be successful. Additional information is unlikely to alter these factors; therefore an informational or awareness-raising campaign alone will not be effective. However, that does not mean that all hope is lost. Improving the safety of pedestrians crossing Elm Street is still possible with the right approach.
+
+## **Changing the environment**
+
+A preferred alternative to education is changing the environment. We know that people act based on information gleaned from the world around them, and that most of our behavior is unconscious and driven by the intuitive system. By changing the environment, people can be moved towards the behavior of interest. In other words – if you
+
+can't change the person, change the world so that the person will follow.
+
+We know that people are crossing Elm Street mid-block because it is quicker, easier and more convenient than using the crosswalks at the nearby intersections. Information or awareness campaigns are unlikely to influence this behavior because the behavior is not due to a lack of awareness or information. Instead, we need to change the environment so that the pedestrians are no longer crossing somewhere other than a marked crosswalk.
+
+Possible changes to the environment include building a wall or putting up a fence to deter people from crossing at the mid-block, or building a pedestrian bridge to keep people out of the flow of traffic. These solutions might be cost prohibitive, and research shows that most pedestrians will still cross a street at ground level even when a pedestrian bridge is available.**14,15**
+
+![](_page_56_Picture_6.jpeg)
+
+Moore, R.L., Older, S.J., Pedestrians and Motors are Compatible in Today's World. Traffic Engineering, Institute of Transportation Engineers, Washington, DC, September, 1965.
+
+![](_page_56_Picture_8.jpeg)
+
+Rasanen, M, T. Lajunen, F. Alticafarbay, and C. Aydin, Pedestrian Self Reports of Factors Influencing the Use of Pedestrian Bridges, Accident Analysis and Prevention, 39, pp. 969-973, 2007.
+
+![](_page_56_Picture_10.jpeg)
+
+**FIGURE 2-5**: Pedestrian hybrid beacon (Source: pedbikeimages.org/Mike Cynecki)
+
+Another approach would be to move the bus stop closer to the existing crosswalks, assuming people will choose to cross at the crosswalk since it is now more convenient. Finally, another alternative would be to install a marked crosswalk with a pedestrian hybrid beacon close to the area where people are crossing (Figure 2-5). This solution recognizes the factors influencing people's behavior and provides an alternative that would improve safety and be acceptable to pedestrians.
+
+16
+
+Tison, J. & Williams, A.F. (2012). Analyzing the First Years of the Click It or Ticket Mobilizations (DOT HS 811 232). Washington, D.C.: National Highway Traffic Safety Administration.
+
+#### 17
+
+Pickrell, T. M., & Li, R. (2016, February). Seat Belt Use in 2015—Overall Results (Traffic Safety Facts Research Note. Report No. DOT HS 812 243). Washington, DC: National Highway Traffic Safety Administration.
+
+We know that people respond in predictable ways to their environments — far more than to internal conditions like attitudes and personality. Environment can include both the physical (built) environment and things like policies, laws and social norms. Let's revisit the speeding example from earlier in the unit (Figure 2-1). Although the posted speed limit is 35 mph, in reality many people drive much faster than that. What might we do to get drivers to slow down on this road? One option is to post additional speed limit signs or run local PSAs about the dangers of speeding. However, consider whether informational signs would result in lower speeds. Are drivers speeding because they are not aware of the speed limit? Are drivers unaware of the potential dangers of high speeds? The answer to both of these questions is "not likely."
+
+One example of environmental change to reduce driver speed is the use of traffic calming measures. Features such as speed humps and mini roundabouts are examples of physical alterations to the driving environment that influence how
+
+![](_page_57_Picture_7.jpeg)
+
+Seat belt use in the United States has a remarkably similar, though opposite trajectory to that of Guinea worm disease. Though seatbelts were required in U.S. vehicles starting in the late 1960s, use of this equipment was low. Observational surveys from the early to mid-1980s found use of 5-14 percent.**<sup>16</sup>** By 2015, however, observed seatbelt use had climbed to 88.5 percent.**<sup>17</sup>**
+
+As with Guinea worm disease, no single effort was responsible for increasing seat belt use in the United States. Instead, efforts that focused on changing the environment (e.g., enactment of seat belt and child passenger safety laws) were coupled with high visibility enforcement (e.g., Click-it-or-Ticket). Education played a role in these efforts, but not in raising awareness for the dangers of not wearing seat belts. Rather, education was needed to inform people that belt use is required and, especially, to create the perception among the driving public that police were actively enforcing seat belt laws.
+
+road users respond. In the previous speeding example, the overall design of the road has already been established, but the lanes could be narrowed or even reduced to one in each direction to communicate, "This is a road where you should drive slower." Traffic calming addresses the intuitive system in that it results in drivers slowing down
+
+without being aware of doing so.**<sup>18</sup>**
+
+## **Consider behavior in addressing travel safety**
+
+Making strides in road safety is possible. However, as with the near eradication of Guinea worm disease, significant achievements will not happen overnight. When implementing a program or intervention aimed at changing behavior, it is important to remember that any road safety issue is likely the result of a combination of factors. Consequently, it is unlikely that any one program or intervention will completely solve the problem. However, combining behavioral science principles with engineering design can help to produce significant advances. See Unit 4 for a discussion of how to identify and address road safety problems.
+
+## **Conclusion**
+
+In short, human behavior is extraordinarily complex. Consequently, it is difficult to influence. Simple, common sense approaches like merely raising awareness or otherwise providing information about an issue virtually never succeed.
+
+**Humans are not exclusively logical, rational beings.**
+
+We often assume human behavior is controlled by a logical deliberative process when, in fact, most behaviors are a result of an intuitive process. Many factors influence behavior including education, emotions, cultural norms, religious beliefs, social pressures, convenience, habits and finances. Understanding human behavior
+
+and the many factors that influence behavior is crucial to solving safety problems.
+
+**People generally don't simply do what they are told to do.**
+
+Information and awareness-raising campaigns are often the first tools used in efforts to influence behavior. However, these approaches are too often adopted without careful consideration of whether the behavior is likely to be changed merely with information (which the public often already has).
+
+The environment heavily influences human behaviors. We are constantly processing information and adjusting our behaviors accordingly. Most of this behavior is unconscious and driven by the intuitive system.
+
+**Changing behavior requires an understanding of all influencing factors.**
+
+Before attempting to influence behavior, it is essential to identify and understand the important factors influencing a behavior. Targeting a behavior without a full understanding of these factors will almost certainly be unsuccessful.
+
+Because so much of what we do is intuitive and heavily influenced by our environment, we sometimes respond to the transportation infrastructure in ways not anticipated by the engineers who designed it. By changing the environment, people can be nudged towards the behavior of interest.**<sup>19</sup>** In other words, if you can't change the person (and you usually can't!), change the world so that the person will follow.
+
+18
+
+Lewis-Evans, B. & Charlton, S.G. (2006), Explicit and implicit processes in behavioural adaptation to road width. Accident Analysis & Prevention, 38, 610-617.
+
+19
+
+Thaler, R.H., and Sunstein, C.R. Nudge: Improving Decisions About Health, Wealth, and Happiness.
+
+![](_page_59_Picture_0.jpeg)
+
+Bus stop with crossing pedestrians in Portland, Ore. (Source: pedbikeimages.org/Laura Sandt)
+
+**The transportation system is designed, built, maintained, governed and used by humans.**
+
+Using the term human factors to refer exclusively to the user perspective (i.e., drivers, pedestrians, etc.) can easily convey an oversimplified notion of the role of humans in the transportation system. From design to use, humans play a role in every step of the transportation system. In that sense, the entire transportation system is a product of human factors. For that reason, safety professionals must consider both the role of the environment (e.g., transportation
+
+infrastructure) and the user when trying to understand behavior and develop solutions to safety problems.
+
+In sum, significant advances in road safety are possible, but changes will not happen overnight. Human behavior is not easy to change. With thoughtful, comprehensive approaches that take into account an understanding of human behavior and the environment in which people live, we can develop programs, policies and countermeasures that have a better chance of significantly improving road safety.
+
+#### **EXERCISES**
+
+- J **CREATE** a causal diagram to model the behavior(s) and environmental factor(s) that contribute to the following.
+  - J The flu
+  - J Unhelmeted motorcyclist fatalities
+
+J Using the causal diagrams from exercise 1, **IDENTIFY** the weak links in the causal chain and describe an intervention aimed at changing the target behavior(s).
+
+THIS PAGE INTENTIONALLY LEFT BLANK
+
+![](_page_61_Picture_0.jpeg)
+
+## **Measuring Safety UNIT 3**
+
+#### **LEARNING OBJECTIVES**
+
+After reading the chapters and completing exercises in Unit 3, the reader will be able to:
+
+- J **DESCRIBE** why measuring safety is important
+- J **IDENTIFY** the different types of available data
+- J **UNDERSTAND** the challenges and accuracy of data
+- J **SELECT** data for different road safety objectives
+
+## **Importance of Safety Data**
+
+Good quality safety data are the core of any successful effort to improve road safety. Local, State, and Federal agencies use crash data as well as roadway, vehicle, driver history, emergency response, hospital, and enforcement data to improve road safety. All of these data sources can be used, in isolation or jointly, to produce projects, programs, and guide policies that reduce injuries and save lives. These types of data are collectively categorized as safety data in this book.
+
+Safety professionals in many disciplines – highway design, transportation planning, operations, road maintenance, law enforcement, education, emergency response services, policy makers, infrastructure program management, road safety management, and public health – use safety data to identify problem areas, select countermeasures, and monitor countermeasure impact.
+
+Road safety management and project development has become increasingly data-driven and evidence-based. This approach to road safety emphasizes safety performance (i.e., number of crashes), rather than solely adhering to engineering standards, personal experience, beliefs, and intuition. For example, in the past, road improvements were considered "safe" if the improvements met the standards contained in the Manual on Uniform Traffic Control
+
+Devices (MUTCD) and A Policy on Geometric Design of Highway and Streets, also known as the Green Book**1,2**. However, most of these standards are engineering based (i.e., nominal safety as discussed in Unit 1), and were not necessarily based on an evaluation of actual road safety performance. Presently, transportation professionals use safety data (such as crash data, road characteristics, and traffic volume) to evaluate road safety performance and inform their decisions. This substantive approach challenges professionals to quantify the expected consequences and outcomes of safety strategies in real measurements, such as the expected number of crashes, injuries, and fatalities.
+
+The selection of road safety measures and treatments can benefit from an understanding of the intricacies and limitations of safety data. This unit presents many kinds of safety data, explores the current process used to collect data, and discusses the impact that these processes have on data quality (i.e., accuracy and reliability). The unit also discusses ways to improve data quality and analysis.
+
+## **Relating Nominal and Substantive Safety to Data**
+
+The concepts of nominal and substantive safety were first introduced in Unit 1 of this textbook. Nominal safety refers to whether
+
+Manual on Uniform Traffic Control Devices (MUTCD), Federal Highway Administration, 2009.
+
+A Policy on Geometric Design of Highways and Streets, American Associations of State Highway Transportation Officials, 6th edition, 2011.
+
+or not a design (or design element) meets minimum design criteria based on national or State standards and guidance documents, such as the AASHTO Green Book or the MUTCD. Substantive safety refers to the actual safety performance, such as expected number of collisions by type and severity on a road.
+
+The contrast of these concepts is directly linked to this discussion of safety data. To determine if a road is nominally safe we do not need safety data; we only need to know if all design standards were followed. However, we need high quality safety data and data analysis to determine if a road is substantively safe. Typically, the analysis includes estimating the expected number of crashes and comparing it against the road's actual safety performance. More information on safety analysis is presented in Unit 4, Solving Safety Problems.
+
+## **Use of Safety Data in Road Safety Management**
+
+Data are integral to safety decision making, both in prioritizing investments and in identifying analyzing the most effective techniques and interventions. The more comprehensive and accurate the data, the better the resulting decisions. Understanding contributing factors to crashes and how best to implement potential countermeasures is complex, and it may involve a variety of agencies and historical data challenges. Because of this complexity, both accurate data and high quality data analysis is necessary for road safety management. A great database is only as useful as the analysis and application of that data. Table 3-1 explores the relationship between data quality and data analysis quality and shows why agencies should strive to improve both of these areas.
+
+![](_page_63_Picture_4.jpeg)
+
+#### **HIGH QUALITY ANALYSIS LOW QUALITY ANALYSIS**
+
+#### **BEST CASE**
+
+## **HIGH QUALITY DATA**
+
+The agency is likely to reach the best safety decisions. Analysts are aware of data capabilities and limitations. This is the most expensive to achieve, due to the need for good data and training on how to conduct analyses.
+
+#### **MISSED OPPORTUNITY**
+
+The agency needs to invest in high quality analysis. Otherwise, the agency has wasted money in databases that are not being utilized to their potential. Good data with poor analysis will lead to poor decisions.
+
+#### **PROMISING**
+
+## **LOW QUALITY DATA**
+
+A robust analysis that recognizes the limitations of the data can still produce useful results. The agency should focus on improving data quality.
+
+#### **WORST CASE**
+
+Poor data and poor analysis will lead to bad decisions. The agency may be better off relying on judgment.
+
+**TABLE 3-1**: Data and Analysis Quality Comparison
+
+Crash data analysis using quantifiable metrics and scientifically defensible methods can help decision makers improve road safety by reducing more injuries and saving more lives at a lower cost. Accurate crash data help determine crash and severity trends, such as increases or decreases in certain types of crashes. Data also help safety professionals pinpoint high crash locations and identify highrisk users, such as younger drivers, older drivers, impaired drivers, and motorcyclists. Examining the characteristics of crashes allows road safety professionals to identify contributing crash factors related to roadway environment, design, or behavioral adaptations. This type of analysis will lead to a more effective selection of countermeasures that will reduce future crash occurrences or crash severity. Planners and engineers can use crash data to show quantitative information to decision makers on
+
+how specific planning guidance, design proposals, or engineering countermeasures can save lives.
+
+Safety professionals could seek to improve safety by relying merely on their gut judgment. The results of such an approach, however, would be quite unreliable. As shown in Table 3-1, safety professionals can improve their decision making process by using high quality data together with robust analysis processes. This unit will focus on the data itself. The use of the data in safety management is presented and discussed in Unit 4.
+
+Good quality safety data and analysis are the keys to identifying real safety issues on roads and evaluating the best methods for improving safety. The following chapters provide an overview of different types of safety data and of ways in which agencies can improve the quality of their data.
+
+## **Types of Safety Data**
+
+As highway safety analysis methods continue to evolve, it is equally important to focus on quality data to conduct these safety analyses. Transportation agencies can and should incorporate road characteristics, traffic volume, and enforcement and citation data, and other information into their safety analysis processes. This will enable them to better identify safety problems and prescribe solutions that improve safety and make more efficient use of safety funds.
+
+Single sources of safety data also do not give a complete picture of the safety risks on our roads. For example, using crash data by itself leaves safety practitioners with purely reactive approaches identifying locations where crashes have already happened. By combining crash data with other types of data, more details begin to emerge. For example, by combining crash data and detailed road inventory information, safety practitioners can develop a more in-depth understanding of the road attributes that contribute to crash risk. This will allow them to adopt a proactive approach, seeking out those factors associated with a high risk of crashes and addressing sites that share those "**elements**" before a crash occurs.
+
+Crash, roadway, and traffic data should be integrated or combined using common or "linking" reference systems, such as mileposts
+
+#### **Chicago's Use of Injury Data to Benchmark Safety Goals and Progress**
+
+Chicago DOT completed a comprehensive pedestrian crash analysis in 2011 to inform the citywide Chicago Pedestrian Plan. This analysis evaluated various crash types, contributing environmental factors, and different age groups using the Illinois Department of Transportation crash data files. The findings present crash density citywide, by ward, and around schools. The data also highlighted key crash conditions and served as a benchmark for measuring the City of Chicago's road safety goals.
+
+Reference: City of Chicago 2011 Pedestrian Crash Analysis, Summary Report, Chicago Department of Transportation, Accessed September 2016 at [https://www.](https://www.cityofchicago.org/city/en/depts/cdot/supp_info/2011_pedestrian_crashanalysis.html) [cityofchicago.org/city/en/depts/cdot/supp\\_](https://www.cityofchicago.org/city/en/depts/cdot/supp_info/2011_pedestrian_crashanalysis.html) [info/2011\\_pedestrian\\_crashanalysis.html](https://www.cityofchicago.org/city/en/depts/cdot/supp_info/2011_pedestrian_crashanalysis.html)
+
+or geospatial position. These data should also have the ability to be linked to the State's other road safety databases, including citation data or injury surveillance systems. Additionally, commercial motor vehicle data could also be linked based upon common data elements involved in crashes and inspections.
+
+Not all types of safety data are available or used by all practitioners. Safety data exist in distinct databases that are maintained by different agencies and often are accessible only to those agencies. One role for safety professionals is to bring together safety databases
+
+#### **Roadway elements**
+
+Physical features of the road such as travel lanes, shoulder width, pavement condition, and roadside characteristics
+
+and analyze them using logical and statistically robust processes.
+
+Safety data can be categorized into two groups based on criteria of core data needs for safety evaluations, data availability, accuracy, and usefulness to safety practitioners and researchers. Some safety data are used often and are critical to safety analysis for many agencies. Other safety data are used less often but can be supplemental to specific safety analyses. This chapter provides general information on safety data in these two groups:
+
+#### **Critical data**
+
+- J Crashes
+- J Traffic volume
+- J Road characteristics
+
+#### **Supplemental data**
+
+- J Conflicts and avoidance maneuvers
+- J Injury surveillance and emergency medical systems
+- J Driver history
+- J Vehicle registrations
+- J Citations and enforcement
+- J Naturalistic
+- J Driving simulator
+- J Public opinion
+- J Behavioral observation
+
+## **Crash Data**
+
+#### **Description**
+
+Crash data is the most widely used type of safety data, and it is essential in road safety analysis. Crashes are currently viewed as the most objective and reliable measurements of road safety. However, there are challenges with crash data, such as human error in reporting, unreported crashes, and the length
+
+of time it often takes for crashes to be entered into a database. Crash data is also the primary measure of effectiveness for safety efforts, since the goal is to decrease crash occurrences and lower the severity of crashes that do occur. Crash records typically provide details on events leading to the crash, vehicles, and people involved in crashes, as well as the consequences of crashes, such as fatalities, injuries, property damage, and citations.
+
+#### **Data collection process**
+
+Crash data collection begins when a State highway patrol trooper or local police officer arrives at the crash scene. The officer completes a crash report, documenting the specifics of the crash. While the specifics and level of detail of the crash data vary from State to State, in general, the most basic crash data consist of where and when the crash occurred, what type of crash it was, and who was involved. The specific data collected on crashes is determined by State agencies, local government agencies, and often a coalition of law enforcement agencies. The exact data fields and coding differ from State to State. The level of detail in a crash report may also differ by the severity of a crash. For instance, in some States property damage only crashes (PDO) are self-reported and, thus, often have less information than injury crashes, which are reported by law enforcement officers.
+
+States also differ in the threshold of what is required for a crash to be reported. Reporting of crashes can vary by threshold requirements, such as "only injury crashes" or "PDO crashes over an estimated \$2,000 in damage." These thresholds are
+
+- **Crash date and time**: The date (year, month, and day) and time (00:00-23:59) when the crash occurred. **B**
+- **Crash county**: The county or equivalent specific crash within a State. entity where the crash physically occurred. **C**
+- **Case identifier**: The unique identifier within a given year that identifies a **A**
+
+**Contributing circumstances, road**: Apparent condition of the
+
+**Roadway surface** 
+
+**I**
+
+**conditions**: The
+
+condition at the time and place of a crash.
+
+road that may have contributed to the crash.
+
+**Weather conditions**: The prevailing atmospheric conditions that existed at the time of the crash. **K**
+
+**Contributing circumstances, environment**: Apparent environmental conditions which may have contributed to the crash. **L**
+
+**Light conditions**: The type/level of light that existed at the time of the motor vehicle crash. **M**
+
+![](_page_67_Figure_8.jpeg)
+
+- **Manner of crash/collision impact**: The identification of the manner in which two motor vehicles in transport initially came together without regard to the direction of force. This data element refers only to crashes where the first harmful event involves a collision between two motor vehicles in transport. **N**
+- **First harmful event**: The first injury or damage-producing event that characterizes the crash type. **O**
+  - **Location of first harmful event relative to the trafficway**: The location of the first harmful event as it relates to its position within or outside the trafficway. **P**
+- warning sign. **School bus-related**: Indicates whether a school bus or motor vehicle functioning as a school bus for a school-related purpose is involved in the crash. The school bus, with or without a passenger on board, must be directly involved as a contact motor vehicle or indirectly involved as a non-contact motor vehicle (children struck when boarding or alighting from the school bus, two vehicles colliding as the result of the stopped school bus, etc.). **Q Q R S** Crash sketch/ diagram Crash narrative **N,O,P**
+
+**FIGURE 3-1** (above, left): Data elements on a crash report form. (Source: North Carolina DOT)
+
+**Work zonerelated**: A crash that occurs in or related to a construction, maintenance, or utility work zone, whether or not workers were actually present at the time of the crash. Work zone-related crashes may also include those involving motor vehicles slowed or stopped because of the work zone, even if the first harmful event occurred before the first **R**
+
+**Source of information**: Affiliation of the person completing the crash report. **S**
+
+unrelated to the number of crashes that are actually occurring on a road, but the reported numbers could look quite different. Changes to the crash reporting thresholds can happen abruptly and may significantly affect the crash data. Consider how the safety of a road, based on reported crashes, would appear in the years before and after a crash reporting threshold change from \$1,000 to \$4,000. You would expect to see fewer reported crashes after the change, since crashes with damage below \$4,000 would no longer be reported, even though there may be no real change in the number of crashes occurring.
+
+After the crash investigation is completed by the officer for the investigating agency, it usually undergoes an internal quality review. Passing the internal review, the crash report is sent to the State crash database. In some cases, the data is transmitted electronically, while in other cases the State agency receives a paper copy of the crash report.
+
+The agency that maintains crash data for the State may be the State department of transportation (DOT), the department of motor vehicles (DMV), or a State law enforcement agency. This agency will in turn make the data available to various other agencies. Federal, State, and local governments, as well as metropolitan planning organizations, advocacy groups, auto and insurance industries, and private consultants request crash data to conduct various transportation planning activities and analysis. The agency maintaining the data may provide raw or filtered datasets to local agencies and to national databases, such as the
+
+National Highway Traffic Safety Administration's (NHTSA's) Fatality Analysis Reporting Systems (FARS).
+
+The time between the crash occurrence and the availability of the crash data from the State crash database varies and typically depends on the type of crash reporting system and the State and local government capabilities. This time period between crash occurrence and the report's availability for analysis defines the timeliness of the crash data. While some agencies can provide complete data with a very short turnaround (i.e., less than a month), others take significantly longer (i.e., up to two years) due to backlogs and personnel shortages. Agencies who have the majority of their crashes reported electronically from law enforcement typically have shorter turnarounds on the crash data.
+
+#### **Common data elements**
+
+Common data elements for crash data include information on date, location, injury severity, types of vehicles, and characteristics of persons involved. Crash narratives and diagrams are typically found in the original crash reports, though generally not in the crash database. Narratives and diagrams are most useful when the safety professional desires to know the exact location of the crash, such as the particular approach of an intersection.
+
+NHTSA developed the Model Minimum Uniform Crash Criteria (MMUCC) in 1998 as a model set of data elements that should be collected to enable safety professionals to conduct data-driven analyses. States are encouraged to adopt MMUCC standards,
+
+though they are not required to match these recommendations. MMUCC, currently in its fourth edition, recommends the crash data elements listed below. Chapter 9 presents further information on MMUCC on page 3-30.
+
+#### **Data sources and custodians**
+
+Crash details may be available from different sources or systems. State agencies and institutions typically maintain the State crash database. These include State departments of transportation, departments of motor vehicles, departments of public safety, or in some cases, State universities under contract to a specific department. Local agencies, such as cities or metropolitan planning organizations, may also maintain their own crash databases within local record management systems. These local systems are most frequently housed by the local police, public works, or transportation departments.
+
+#### **Transportation safety applications**
+
+Crash data serve as the primary observable measure of safety (or lack thereof) on the road. Transportation professionals can use crash data to analyze a single crash, a specific site, an entire corridor, or a large area, such as in regional or Statewide planning. Crash data can be used to provide guidance to transportation decision makers and to guide the formation of safety legislation.
+
+#### **Coordination or integration with other data sets**
+
+In transportation departments, other data elements frequently used along with crash data include road characteristics and traffic volume
+
+data. For example, by combining road characteristics with crash data, safety professionals are able to identify road elements that may lead to higher frequency or injury severity of crashes, and therefore develop a systemic approach to reduce that crash risk at many of the locations that have those risk elements. Using traffic volume, agencies can calculate crash rates (e.g., crashes per road vehicle) to better identify locations requiring safety improvements.
+
+#### **Caution on the use of crash rates**
+
+Crash rate calculation (crashes per amount of traffic) is a simplistic measure that may be useful when comparing sites with similar characteristics and traffic volumes. However, the relationship between crashes and volume is not linear and can therefore lead to wrong conclusions if that assumption is made when considering volume increases on a road or comparing roads of different types. Unit 4 discusses how an analyst can use safety performance functions to avoid this error.
+
+#### **Data challenges and gaps**
+
+Some of the most common issues found in crash reporting include incomplete data (for example a driver's blood alcohol content is often missing), delays in entering the data into databases, inaccurate crash locations, and wrongly assigned fault and wrong choice of crash type. Some of these issues can be fixed by training police officers and those who enter the data into the database, as well as by using technology checks in data collection. Agencies should periodically conduct independent quality checks on the accuracy and reliability of their data.
+
+#### **Challenges with the Use of Crash Data to Systemically Identify High Risk Locations**
+
+The Oregon DOT identified pedestrian and bicycle crashes as one of its primary focus areas for infrastructure funding. While pedestrians and bicyclists account for more than 15% of all traffic fatalities statewide, the locations of serious injuries and fatalities appear to be random. Therefore, in 2013, ODOT set out to develop a program that focuses the limited available funding for infrastructure countermeasures on locations with the greatest crash potential. In order to identify these higherrisk locations, ODOT is working to discover behavioral patterns and road conditions that lead to pedestrian and bicycle crashes. While a promising approach, this analysis is constrained by the limited availability
+
+of road information (e.g., bicyclist and pedestrian volumes, the presence of crosswalks, turn lanes, driveway activity, and sight distances). While the lack of these data does not preclude such an analysis, it does reduce the certainty of the findings. An additional benefit from this effort is that it has helped ODOT identify current data deficiencies which ODOT is currently working to fix.
+
+Reference: Pedestrian and Bicycle Safety Implementation Plan, Oregon Department of Transportation, February 2014. Accessed September 2016 at [https://www.oregon.gov/](https://www.oregon.gov/ODOT/HWY/TRAFFIC-ROADWAY/docs/pdf/13452_report_final_partsA+B.pdf) [ODOT/HWY/TRAFFIC-ROADWAY/docs/](https://www.oregon.gov/ODOT/HWY/TRAFFIC-ROADWAY/docs/pdf/13452_report_final_partsA+B.pdf) [pdf/13452\\_report\\_final\\_partsA+B.pdf](https://www.oregon.gov/ODOT/HWY/TRAFFIC-ROADWAY/docs/pdf/13452_report_final_partsA+B.pdf)
+
+## **Traffic Volume Data**
+
+#### **Description**
+
+Traffic volume data indicates how many road users travel on a road or through an intersection. The most prevalent type of volume data is a count of daily use by motorized vehicle traffic. This type of traffic volume data can be measured in many ways depending on the intended use. Volume measurements include:
+
+- J Annual average daily traffic (AADT)
+- J Average daily traffic (ADT)
+- J Total entering vehicles (TEV) for intersections
+- J Turning movement counts
+- J Vehicle miles traveled (VMT)
+- J Pedestrian counts
+- J Bicyclist counts
+- J Percentage of traffic for specific vehicle types (e.g., heavy trucks or motorcycles)
+
+AADT is the average number of vehicles passing through a segment from both directions of the mainline route for all days of a specified year. As AADT requires continuous year-round counting, these data are often unavailable for many road segments. In these cases, ADT is used to estimate AADT by using shorter duration counts of that road and then adjusting those volumes by daily and seasonal factors. Other data used for crash analysis include turning movement counts and TEV at intersections and VMT on a road segment, which is a measure of segment length and traffic volume. VMT are useful for highway planning and management, and a common measure of road use. Along with other data, VMT is often used to estimate congestion, air quality, and expected gas tax revenues, and can serve as a proxy for the level of a region's economic activity. Volume data is also occasionally collected for bicyclists and pedestrians at road segments and crossing locations.
+
+#### **Data collection process**
+
+Volume data can be collected automatically or manually. Vehicle volume data is typically collected using automated counters, such as magnetic induction loops, pneumatic tube counters, microwave, radar, or video detection. These automated counters can also be configured to classify vehicles and produce counts by vehicle type (e.g., trucks, single passenger vehicles, etc.). For shorter durations or occasional counts, transportation agencies use manual traffic counts performed by observers, either in the field or through video cameras. Manual counting is also used often for bicyclist or pedestrian counts, although there are a number of additional technologies, such as infrared beams, that can be used to collect non-motorized volume data. These manual counts can range in length from one-hour counts to full-day counts, depending on the agency's needs and practices. Fitness tracking apps may also provide additional information to jurisdictions regarding where bicyclist and pedestrian activity is occurring. Some care is needed when using these data due to the selfselection bias present from users having to opt-in to the tracking and only using for specific types of activities (e.g., fitness cycling rather than commuting).
+
+Each State has its own traffic data collection needs, priorities, budget, and geographic and organizational constraints. These differences cause agencies to select different equipment for data collection, use different data collection plans, and emphasize different data reporting outputs. The FHWA Traffic Monitoring Guide (TMG) highlights
+
+#### **What's the difference between ADT and AADT?**
+
+Short term traffic counts are typically collected at a location for a 12-, 18-, or 24-hour period. Average Daily Traffic (ADT) is the count of traffic calculated to reflect the 24-hour (daily) volume of the date it was collected. The Annual Average Daily Traffic (AADT) is calculated for an entire year from the ADT by adjusting that simple average traffic volume to take into account the different travel patterns that occur during short duration count periods. For example, a summer traffic count taken in a beach vacation town would need to be adjusted downward to reflect the average traffic volume for the year, since traffic would be much higher in the summertime.
+
+best practices and provides guidance to highway agencies in traffic volume data collection, analysis, and reporting3 . The TMG presents recommendations to improve and advance current programs with a view towards the future of traffic monitoring. Traffic data is used to assess current and past performance and to predict future performance. Some States are utilizing traffic data from intelligent transportation systems (ITS) to support coordination of planning and operations functions at the Federal and State levels.
+
+#### **Common data elements**
+
+Volume data must include the counted volume, location, date, and duration of the count. Depending on the method used, the volume data may also contain information on vehicle classification, speed, or weight; lane position; weather; and directional factors. From these data, transportation professionals can calculate the average number of
+
+Traffic Monitoring Guide, Federal Highway Administration, Office of Highway Policy Information, September 2013.
+
+vehicles that traveled each segment of road and daily vehicle miles traveled for specific groups of facilities, vehicle types, and vehicle speeds.
+
+#### **Data sources and custodians**
+
+State highway agencies collect and maintain traffic volume data for State-controlled roads. These data are shared with the U.S. Department of Transportation in order to monitor road usage and safety trends. Local jurisdictions also collect and maintain traffic volume data; the scope, consistency, and quality of these data varies by jurisdiction.
+
+#### **Transportation safety applications**
+
+Agencies use volume data to support activities in design, maintenance, operations, safety, environmental analysis, finance, engineering, economics, and performance management. For instance, total traffic volume estimates or forecasts on a section of road are used to generate State and nationwide
+
+estimates of total distance traveled. Annual traffic volumes are also essential in network screening, diagnosis, and the selection of countermeasures (see further presentation of these processes in Unit 4). When selecting appropriate crash modification factors (CMFs) to estimate the benefit of potential countermeasures, a safety practitioner must use traffic volumes to confirm that the CMFs are suitable for the site in consideration.
+
+#### **Coordination or integration with other data sets**
+
+Other data elements frequently used with traffic volume data in safety applications include road characteristic inventories and crash data. For example, an agency that uses traffic volume and crashes together can identify sites with highest potential for safety improvements and target specific crash types. This allows them to better identify and prioritize locations for safety improvements.
+
+#### **Spatial Data and Road Safety**
+
+Many of the types of data presented in this chapter can be stored in a spatial format and displayed in a GIS. GIS is a particularly powerful tool designed to store, manipulate, analyze, and visualize data that is linked to a location. This makes it valuable to highway safety practitioners who can use a common referencing system for much of their highway data and link it together in GIS. For example, a single GIS database can contain road attributes, such as number of lanes, pavement condition, and lighting; crash information; and traffic volumes. This information can then be used to analyze crash hotspots and trends, such as multi-vehicle crashes in the vicinity of signalized intersections.
+
+![](_page_73_Picture_10.jpeg)
+
+This GIS map displays signalized intersections as squares and crashes as dots and allows the analyst to easily identify crashes occurring within 150 feet of a signalized intersection (denoted by circular areas around each intersection).
+
+#### **Data challenges and gaps**
+
+One of the biggest challenges in collecting accurate volume data is implementing a quality assurance process to ensure that counts are accurately recorded. Traffic volume for most roads is also based on sampling, which leads to estimates of volume on much of the road. As technology continues to develop and become more prevalent on our roads and in our vehicles, the accuracy will improve considerably. Additionally, pedestrian and bicyclist counts are more susceptible to higher variability due to their lower volumes; thus, longer count durations and additional locations are required for accurate data applications.
+
+## **Road Characteristics Data**
+
+#### **Description**
+
+Road characteristics data is also referred to as road inventory data. The most basic road characteristics data typically includes road name or route number, road classification, location coordinates, number of lanes, lane width, shoulder width, and median type. Intersection characteristics typically include road names, area type, location coordinates, traffic control, and lane configurations. The collection of these data elements supports an enhanced safety analysis and investment decision making when combined with other datasets, such as crash information.
+
+#### **Data collection process**
+
+Road characteristics data can be collected through several methods including photo or video logs, field surveys, aerial surveys, integrated GIS and global positioning systems (GPS) mapping, and vehiclemounted Light Detection and
+
+![](_page_74_Figure_14.jpeg)
+
+**FIGURE 3-2**: This image from the FHWA Model Inventory of Roadway Elements (v. 1.0) illustrates roadway elements.
+
+Ranging (LIDAR) technology. Some States find it more cost effective to purchase these data from third party providers.
+
+#### **Common data elements**
+
+Transportation agencies typically collect those road characteristics that they need or can be collected based on the available funds. Road characteristics are collected for many different purposes, such as road maintenance and improvement projects. Given that States have different priorities and funding structures, the elements of road characteristics data is not the same from State to State or among local agencies.
+
+To provide guidance on road characteristics that are the most needed for safety analysis, the FHWA developed the Model Inventory of Roadway Elements (MIRE). MIRE provides a recommended (but not required) list of road characteristics elements specifically for safety analysis. The elements are divided into the categories shown in Table 3-2. Chapter 9 presents further
+
+information on MIRE on page 3-32.
+
+#### **Data sources and custodians**
+
+Road characteristics data are collected at both the local and Statewide levels. At the local level, having data on details, such as traffic control devices, sidewalks, or the number of travel lanes, can be beneficial for safety evaluations and safety project prioritization. These data are maintained by the city or by a higher level agency such as a MPO.
+
+State road characteristics data include physical road attributes, traffic control devices, rail grade crossings, and structures, such as bridges and tunnels. Each State highway agency, some local transportation and public works departments, and regional planning agencies collect and maintain road characteristics data. In addition, most States also have supplemental inventory data for bridges as part of the National Bridge Inventory and railroad grade crossings as part of the Federal Railroad Administration's Railroad Grade Crossing Inventory. These databases usually can be linked to the Statewide road inventory.
+
+#### **Transportation safety applications**
+
+Road safety professionals can use road characteristics data to access data about the physical characteristics of crash sites or other priority sites. Road characteristics data is essential for network screening, development or calibration of crash prediction models, and related applications. These data are also valuable on the large scale level to estimate where crashes are expected to occur on the system.
+
+#### **Coordination with other data sets**
+
+Road characteristics data can be linked with crash and volume data to improve safety analysis and problem identification. Combining datasets in this way allows safety professionals to identify areas with a high
+
+| CATEGORY          | EXAMPLES OF MIRE DATA ELEMENTS                                                                                                                                                                     |
+|-------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Roadway Segment   | Roadway classification<br>Paved surface characteristics<br>Number and type of travel lanes<br>Shoulder, median, and roadside descriptors<br>Pedestrian and bicyclist facilities<br>Traffic volumes |
+| Roadway Alignment | Curve and grade information                                                                                                                                                                        |
+| Roadway Junction  | Traffic control devices<br>Intersection features<br>Interchange and ramp descriptors                                                                                                               |
+|                   |                                                                                                                                                                                                    |
+
+**TABLE 3-2**: Categories of MIRE Elements
+
+![](_page_76_Figure_0.jpeg)
+
+**FIGURE 3-3:** Using Safety Data Together
+
+potential for safety improvements (by means of a network screening process) and identify appropriate countermeasures. However, the road characteristics data must share a common reference system with the crash and volume data in order to link them together. The most common methods of linking road data with crash or volume data use a linear referencing system, such as routes and mileposts, or a spatial referencing system, where all files share the same coordinate system.
+
+#### **Data challenges and gaps**
+
+Collecting accurate road characteristics data can be a timeconsuming and expensive process. Data collection that is done only for part of a road network results in gaps in inventories of road features such as the location of guardrails, shoulder widths, and rumble strips. Transportation agencies are continually looking for newer technologies to streamline the collection of this detailed data. Also, it is more common for road characteristics data to be fuller and more detailed for State system roads compared to local roads, since local agencies typically have less funding, fewer staff, and less general prioritization for collecting road characteristics data.
+
+![](_page_77_Picture_0.jpeg)
+
+Observing interactions between road users, like these drivers and crossing pedestrians, can be a good way to gain supplemental data about safety effects.
+
+## **Supplemental Safety Data**
+
+In addition to the critical transportation safety datasets (crashes, road characteristics, and traffic volume), there are many other datasets that can be used and combined to conduct additional types of evaluations on the effectiveness of programs, human behaviors and safe decision making, and public opinions.
+
+**Conflicts, Avoidance Maneuvers, and Other Interactions**
+
+Observing conflicts between road users, avoidance maneuvers, such as swerving or hard braking, and other interactions, such as failures to yield can provide valuable information
+
+on road safety. These other measures of safety are referred to as surrogate measures. They occur more frequently than actual crashes and therefore enable agencies to identify safety risks more quickly and in a proactive manner (i.e., before the crash occurs). However, by their nature of being surrogates, there is potential for inaccuracy in determining which types of conflicts are good indicators of crashes.
+
+Surrogate safety data is collected by in-field observers or through recordings that capture the behaviors and interactions of road users. These recordings can be made through stationary cameras or dashboard-mounted video cameras.
+
+Increasingly, researchers are using programs to automatically identify potential events. This eliminates the need to scan visually through the entire video.
+
+Observing interactions between road users can provide valuable information on the safety effect of certain road elements, such as signals or signs, and help identify the probability of crashes under different conditions. If a reliable relationship between the observations and crashes is known, such studies may also provide insights into the potential for safety issues between road users, such as between vehicle drivers and pedestrians.
+
+However, one of the biggest challenges for using observations of road user interactions is that they are surrogate measures of safety. To date, we lack good research that would quantitatively equate surrogate measures of safety to crash data. If such relationships were known, safety professionals could conduct evaluations with a large number of surrogate measures in a relatively short period of time. This contrasts with the need to wait for years for sufficient crash data to support a good analysis.
+
+#### **Injury Surveillance and Emergency Medical Systems Data**
+
+Injury surveillance systems (ISS) typically provide data on emergency medical systems (EMS), hospital emergency departments, hospital admissions/discharges, trauma registry, and long-term rehabilitation. This information is used to track injury causes, severity, costs, and outcomes. Although an injury associated with
+
+#### **Evaluation of Children Involved in Off-Roadway Crashes Using Trauma Center Records**
+
+Many off-roadway crashes are not reported by law enforcement and are thus missed when conducting safety evaluations using police crash reports. One group that is particularly affected by this lack of data is young children injured by passenger vehicles in driveways and parking lots. This lack of information provides safety professionals with little knowledge about crash risk factors and actual incident rates that could be used to allocate resources and promote safety interventions and good design and behaviors. A 2010 study (Rice et al.) in California used records from eight trauma centers to identify the frequency and characteristics of these crashes. This study highlighted the inconsistencies with external causeof-injury codes used by emergency departments, but suggests that there is value to surveillance of off-roadway pedestrian injuries at trauma centers as a way of identifying incidents that are not captured by other data sources.
+
+Reference: Rice TM, Trent RB, Bernacki K, Rice JK, Lovette B, Hoover E, Fennell J, Aistrich, AZ, Wiltsek D, Corman E, Anderson CL, Sherck J. (2012). Trauma center-based surveillance of nontraffic pedestrian injury among California children. Western Journal of Emergency Medicine; 13.2.
+
+a traffic crash is only one type of injury in these medical systems, traffic crash injuries can be a useful source of data in bridging the gap between traditional traffic safety and public health issues. Hospital records are also often the only source of information on bicycle and pedestrian crashes that are not recorded by the police, such as those that occur in non-roadway locations like parking lots and driveways.
+
+Hospitals often use the external cause of injury classifications to code causes of patient injuries, including those from traffic crashes. These data can provide a description of injury severity, type of crash (e.g., motor vehicle passenger, bicyclist), and, in some cases, the location of incident. However, the data is often incomplete or non-specific. In order to provide a more comprehensive understanding of motor vehicle crash outcomes, NHTSA developed the Crash Outcome Data Evaluation System (CODES), which links crash, vehicle, and behavior characteristics to their specific medical and financial outcomes. Hospital injury data most often includes date, injury severity, cause, and demographic information. Personal identifying information is not included.
+
+Hospital data can be used by a variety of governmental and non-governmental agencies to investigate the causes of injuries. Based on this analysis, the agencies can develop a safety campaign to reduce injuries to particular
+
+demographics. It can also be used to identify the full magnitude of crashes for a specific user group or demographic that is not recorded or reported by law enforcement. For example, hospital data can help safety professionals better understand the number of bicyclist crashes, since many bicycle-related crashes are not reported to law enforcement.
+
+Hospital data are often difficult to use for those who administer roads, primarily the State DOT. The data is time consuming to acquire and may not contain complete data. Additionally, since there are no personal identifiers relating hospital injury data to specific crash records, the linkage is difficult and is seldom done. For these reasons, State DOTs rarely use these data; it is most often employed by public health researchers. However, there continues to be efforts at both Federal and State levels to develop better ways to integrate injury surveillance and emergency medical systems data with crash data.
+
+Hospital data can be used to investigate causes of injuries, and is often the only source of information on some bicycle and pedestrian crashes.
+
+![](_page_79_Picture_5.jpeg)
+
+#### **Driver History Data**
+
+Departments of Motor Vehicles (DMVs) maintain driver history data on all licensed drivers in the State. DMVs typically create a driver record when a person enters the State licensing system to obtain a driver's license or when an unlicensed driver commits a violation or is involved in a crash. State driver history databases interact with the National Driver Register (NDR) and the Commercial Driver License Information Systems (CDLIS) to prevent drivers with a history of atfault crashes or inordinate number of citations from obtaining multiple or subsequent licenses.
+
+The driver history data contain information such as:
+
+- J Basic identifiers (e.g., name, address, driver license number)
+- J Demographics (e.g., age, birth date, gender)
+- J Information relevant to license and driver improvement actions (e.g., license issue, expiration and renewal dates, license class, violation dates, suspension periods)
+
+One challenge with using these data is that they are almost never shared outside a DMV. State or local DOTs do not have access to these data while developing their HSIPs (or conducting location specific safety studies). Sharing driver history data nationally is limited and could be improved by creating inter-agency data sharing partnerships that address privacy concerns and allow State DOTs to work with the data.
+
+#### **Vehicle Registration Data**
+
+Vehicle registration data includes
+
+information about registered vehicles in a State and is also typically maintained by the DMV. Vehicle registration systems may also contain information regarding commercial vehicles and carriers registered in a particular State and licensed to travel in other States. These data can provide information on the vehicle population within a State or county to be used in large scale safety analysis. These data can also help identify owners in the event of a crash or traffic violation.
+
+Typical vehicle registration data may include owner information, license plate number, vehicle make, model, and year of manufacture, body type, vehicle identification number, and miles traveled. Common data for commercial vehicles may include U.S. Department of Transportation (DOT) number, carrier information, and inspection or out-of-service information.
+
+#### **Citations and Enforcement**
+
+Citation data refers to data on individual drivers that records any illegal actions that were cited by a law enforcement officer. It includes traffic violations, such as reckless driving, driving under the influence, and not carrying adequate car insurance; traffic crashes; driver's license suspensions, revocations, and cancellations; and failures to appear in court. The data can also include the traffic infractions that have been adjudicated by the courts.
+
+These data are helpful in identifying and tracking those individuals with a higher potential for unsafe driving behaviors. In an attempt to control crash occurrences, States may monitor high-risk drivers by reviewing their driver history
+
+records, paying particular attention to driver citations. Ideally, States track a citation from the time it is issued by a law enforcement officer through its disposition in a court of law. Citation information tracked and linked to driver history files enable States to screen drivers with a history of frequent citations for actions known to increase crash risk. States have found citation tracking systems useful in detecting repeat traffic offenders prior to conviction. It can also be used to track the behavior of particular law enforcement agencies and the courts with respect to dismissals and plea bargains. Many law enforcement agencies use citations as a method of tracking and measuring the effectiveness of enforcement efforts.
+
+Some constraints exist with the use of citation and enforcement data to help prevent crashes. Some States have difficulty in maintaining accurate citation information because local jurisdictions may collect different data elements from varying citation forms. Obtaining and managing judicial information is also a challenge because of the various levels of court administration and jurisdiction. Unfortunately, in some States judges do not have access to the offender's driver history at the time of sentencing, so many offenders escape the stricter penalties sanctioned for repeat offenses. In addition, the traffic safety community often lacks access to adjudication information due to privacy concerns.
+
+#### **Naturalistic Driving Data**
+
+Naturalistic driving data are driver behavior data collected during
+
+actual driving trips through technology placed in the vehicle. This technology typically includes video camera views of the driver, speed and vehicle motion sensors, and location tracking equipment. Data such as video might be collected on a continuous basis, or only after certain events like hard braking. Using data collected by this equipment, researchers are able to gather information on the underlying causes of crashes by observing drivers in a natural driving situation. Frequently collected data include road environment information, such as weather; driver information, such as eye movements; and information on vehicle movement including location on the road, acceleration, deceleration, and speed.
+
+### **Strategic Highway Research Program 2**
+
+The largest naturalistic study in the United States to date is the second Strategic Highway Research Program (SHRP2), which included over 3,400 drivers participating in the study. SHRP2 data includes over 5,400,000 individual trips and over 36,000 crash, near crash, and baseline driving events. FHWA provides more information on SHRP2 at [https://www.fhwa.dot.gov/](https://www.fhwa.dot.gov/goshrp2) [goshrp2.](https://www.fhwa.dot.gov/goshrp2)
+
+These data are used to evaluate how drivers interact with and react to the road, other road users, and other environmental features. Driver observation is used to understand fundamental issues of driver behavior and to develop improved safety countermeasures. The data are primarily used in research studies on a variety of topics. The data from the SHRP2 program have been used to study safety
+
+![](_page_82_Picture_0.jpeg)
+
+Driving simulators like this one are often used to evaluate driver behavior under specific conditions and in a cost-effective way.
+
+issues including prevention of road departures, driver reaction to posted speed limits, and driver response to curves in the road, in addition to many non-safety-related topics.
+
+A challenge with collecting a large amount of naturalistic data is the high cost of recruiting participants, instrumenting vehicles, and reducing and analyzing the data. The process of coding (observing) the behaviors of the driver while driving is time-consuming and is typically conducted on a frame-byframe basis, leading to expensive data collection and lengthy study periods. The data are highly private (i.e., contains videos of driver faces), and therefore are typically difficult to access or distribute. Despite these challenges, naturalistic driving data provides a unique and extremely
+
+insightful look at fundamental issues of road safety.
+
+#### **Driving Simulator Data**
+
+Due to the high cost of naturalistic driving studies and the rarity of traffic crashes, driving simulators are often used to efficiently and safely evaluate driver behavior under different conditions. Researchers are able to study many different conditions and complex environments without exposing drivers to danger through replicating a wide range of road, traffic, and environmental conditions, as well as driver behaviors such as distractions, impairment, and fatigue. New types of road designs can be guided by the use of simulators, particularly complex features, such as urban highway interchanges.
+
+Simulators can also be used for driver education to teach people about the effects of driver distractions or to prepare young drivers for different conditions before they encounter them on the road. Truck simulators are used to replicate the driving environment for different types of commercial trucks and used to safely train new drivers.
+
+#### **Public Opinion Data**
+
+Feedback from the general public can be a useful source of information for safety professionals. Safety professionals can use information on road safety issues and concerns from the public to identify specific locations or types of conditions where people have real or perceived traffic safety concerns.
+
+There are many different ways to collect this information, such as a phone-based survey, web-based tools (pins on maps or online forms), meetings, or intercept surveys. Common data collected are the type of concern, location, and type of mode (i.e., walking, bicycling, transit user, or driving).
+
+These data are typically collected at the local level, frequently as part of a transportation planning process or as a collaborative effort with law enforcement. Bringing residents and police officers to join the road safety audit teams or diagnosis teams during their field visits is also a beneficial way to learn about the experiences of the road users in the study area.
+
+These data may provide valuable insights about what the travelling public perceives as dangerous; however, it may be a biased sample
+
+![](_page_83_Figure_6.jpeg)
+
+**FIGURE 3-4**: Observations of motorcyclists showed how many were wearing DOT-compliant helmets (Source: National Occupant Protection Use Survey)
+
+based on those who self-select to provide the information to the researching agencies. Findings will be subjective as each person perceives a condition based on their individual experiences only. Different persons perceive different issues and recommend different "best" solutions for the same condition. Conclusions based on survey findings should be used with care.
+
+#### **Behavioral Observation**
+
+Observational surveys of road user behaviors are an effective method of data collection on information that may otherwise be inaccurately recorded due to self-reporting bias or are difficult to capture through other means. Several examples of data typically recorded using direct observation are the use of mobile devices (texting or calling), right turn on red, safety belt use, motorcycle or bicycle helmet use, and traffic control violations, such as rolling through stop signs.
+
+These data are collected through observing road users on the road. Large scale surveys collecting a high number of observations will provide the most accurate sample of the road user population in the study area. Additionally, robust observation data will cover differing road types and land use characteristics and contain observations at different times of day, week, and season. An example of a large-scale data collection effort is the National Occupant Protection Use Survey conducted annually by NHTSA. In 2013, over 52,000 occupants were observed in nearly 40,000 vehicles. The data, summaries, and evaluations from this program may be viewed on the NHTSA website**<sup>4</sup>** .
+
+## **Data Users**
+
+While many agencies use safety data, most of them have different goals. For example, a city traffic engineer may have a specific scope for identifying and treating specific high priority sites, whereas a safety analysist with a State may be focused on safety at the system level. Moreover, safety researchers and graduate students may be focused on a whole range of safety evaluations that are not intended to be action plans to improve safety at a specific site or system. Each type of data user may have different levels of access to these various types of safety data.
+
+The following tables provide common uses and data needs for these different types of data users.
+
+| 4 |                                      |
+|---|--------------------------------------|
+|   | https://crashstats.<br>nhtsa.dot.gov |
+
+|                      | DATA TYPE                                                                                | USEFULNESS   | ACCESSIBILITY | OFTEN PAIRED                                    |
+|----------------------|------------------------------------------------------------------------------------------|--------------|---------------|-------------------------------------------------|
+|                      | Crash                                                                                    | Essential    | High          | Road characteristics,<br>Traffic volumes        |
+|                      | Road characteristics                                                                     | Essential    | High          | Crash,<br>Traffic volumes                       |
+|                      | Traffic volumes                                                                          | Essential    | High          | Crash,<br>Road characteristics                  |
+|                      | Naturalistic driving                                                                     | Supplemental | Moderate      |                                                 |
+|                      | Conflicts/avoidance<br>maneuvers                                                         | Supplemental | Low           | Road characteristics,<br>Traffic volumes        |
+| MICS AND RESEARCHERS | Citations                                                                                | Supplemental | Low           | Crash, Traffic volumes,<br>Road characteristics |
+|                      | Driving simulator                                                                        | Supplemental | Low           | Road characteristics                            |
+| ACADE                | Behavior observation                                                                     | Supplemental | Low           | Crash,<br>Road characteristics                  |
+|                      | Injury surveillance                                                                      | Supplemental | Very low      |                                                 |
+|                      | Driver history                                                                           | Supplemental | Very low      |                                                 |
+|                      | Vehicle registration                                                                     | Supplemental | Very low      |                                                 |
+|                      | Public opinion                                                                           | Supplemental | Very low      |                                                 |
+|                      | TABLE 3-3 (above/next page): Data Use by Safety Professionals, Academics and Researchers |              |               |                                                 |
+
+|                  | DATA TYPE                        | USEFULNESS    | ACCESSI<br>BILITY | OFTEN PAIRED                             |
+|------------------|----------------------------------|---------------|-------------------|------------------------------------------|
+|                  | Crash                            | Essential     | High              | Road characteristics,<br>Traffic volumes |
+|                  | Road<br>characteristics          | Essential     | High              | Crash,<br>Traffic volumes                |
+| ONALS            | Traffic volumes                  | Essential     | High              | Crash,<br>Road characteristics           |
+| M LEVEL ANALYSIS | Public opinion                   | Supplemental  | High              | Crash,<br>Road characteristics           |
+| SAFETY PROFESSI  | Conflicts/avoidance<br>maneuvers | Non-essential | Low               | Road characteristics,<br>Traffic volumes |
+|                  | Citations                        | Non-essential | Low               |                                          |
+| FOR SYSTE        | Behavior<br>observation          | Non-essential | Low               |                                          |
+|                  | Injury surveillance              | Non-essential | Very low          |                                          |
+|                  | Driver history                   | Non-essential | Very low          |                                          |
+|                  | Vehicle registration             | Non-essential | Very low          |                                          |
+|                  | Naturalistic driving             | Non-essential | Very low          |                                          |
+|                  | Driving simulator                | Non-essential | Very low          |                                          |
+
+|                                       | DATA TYPE                        | USEFULNESS    | ACCESSI<br>BILITY | OFTEN PAIRED                                    |
+|---------------------------------------|----------------------------------|---------------|-------------------|-------------------------------------------------|
+|                                       | Crash                            | Essential     | High              | Road characteristics,<br>Traffic volumes        |
+|                                       | Road<br>characteristics          | Essential     | High              | Crash,<br>Traffic volumes                       |
+|                                       | Traffic volumes                  | Essential     | High              | Crash,<br>Road characteristics                  |
+| ONALS                                 | Public opinion                   | Supplemental  | High              | Crash,<br>Road characteristics                  |
+| FOR SPECIFIC SITES<br>SAFETY PROFESSI | Conflicts/avoidance<br>maneuvers | Supplemental  | Low               | Road characteristics,<br>Traffic volumes        |
+|                                       | Citations                        | Supplemental  | Low               | Crash, Traffic volumes,<br>Road characteristics |
+|                                       | Behavior<br>observation          | Supplemental  | Low               | Crash,<br>Road characteristics                  |
+|                                       | Injury surveillance              | Non-essential | Very low          |                                                 |
+|                                       | Driver history                   | Non-essential | Very low          |                                                 |
+|                                       | Vehicle registration             | Non-essential | Very low          |                                                 |
+|                                       | Naturalistic driving             | Non-essential | Very low          |                                                 |
+|                                       | Driving simulator                | Non-essential | Very low          |                                                 |
+
+#### **Other Types of Road Safety Data**
+
+Additional types of data can also be useful to road safety professionals. These types of data may include:
+
+#### **Insurance data**
+
+(e.g., carrier, policy number, expiration date, claims cost)
+
+These data can provide insights into associations between insurance status and safety.
+
+#### **Demographic data**
+
+(e.g., population by gender, age, rural/ urban, residence, and ethnicity)
+
+These data can be used for normalizing crash data to a state's general population.
+
+#### **Safety program evaluation data**
+
+(e.g., surveys, assessments, inspections)
+
+These data can provide feedback on the effectiveness of a new safety program.
+
+#### **Maintenance data**
+
+(e.g., guardrail replacement)
+
+These data may indicate where unreported crashes are occurring.
+
+#### **EXERCISES**
+
+- J **IDENTIFY** possible relationships between the safety data presented in this chapter and census data (e.g., traffic safety vs. population density).
+- J **CONSIDER** if, in the future, vehicles store pre-crash data in a "black box" type of event recording device. What types of data would you like it to store and how would you use this data (i.e., what types of analysis would you recommend conducting)?
+- J **EXPLORE** what type of safety analysis could be made possible using communication between vehicles (V2V) and also between vehicles and infrastructure (V2I - i.e., roads, intersections, etc.).
+- J **DETERMINE** how safety professionals can incorporate operational data, such as those from dynamic tolling lanes and speed sensors, into a safety analysis program.
+
+## **Improving Safety Data Quality**
+
+## **Quality Measures Of Data**
+
+The previous chapters in this unit have made the case that data are critical when seeking to improve road safety. However, simply having data is not enough. Good decisions require good data. When collecting, recording, maintaining, and analyzing safety data, road safety professionals must focus on the quality of data. Data-driven analysis tools are continually advancing and can help set priorities and select appropriate safety strategies, but the need for quality data to drive these tools is clear. Professionals commonly recognize that data quality can be measured on six criteria – timeliness, accuracy, completeness, uniformity, integration, and accessibility. Each of these criteria are presented in this chapter.
+
+#### **Timeliness**
+
+Timeliness is a measure of how quickly an event is available within a data system. State and local agencies can use technologies to automate crash data collection and quickly process police crash reports for analytic use. However, some agencies still rely on traditional methods, such as paper form data collection and manual data entry; these data collection methods can result in significant time lags. Many States, however, are moving closer to real-time data collection methods by using electronic reporting to improve the timeliness of data collection and submission.
+
+#### **Accuracy**
+
+Accuracy is a measure of how reliable the data are and whether they correctly represent reality. For example, exact crash location is an important detail for accuracy. A crash occurring at the intersection of First Street and Main Street should be recorded as occurring at that intersection. Accurate data are crucial during the analysis phase to generate road safety statistics and to pinpoint safety problems. Errors may occur at any stage of the data collection process. Common data accuracy errors include:
+
+- J Typographic errors (for data entered manually )
+- J Inaccurate and vague descriptions of the crash location
+- J Incorrect descriptions or entry of road names, road surface, level of accident severity, vehicle types, etc.
+- J Subjectivity on details that rely on the opinion of the reporting officer (e.g., property damage thresholds, excessive speed for conditions)
+
+Technology can and is currently being used to improve accuracy and reduce errors. Automatic internal data quality checks are important for this purpose. These types of checks would determine if two data fields contain possibly conflicting data, and if so, bring it to the attention of the data analyst. An example of
+
+![](_page_88_Picture_0.jpeg)
+
+Many police officers now use in-car computers to complete and submit electronic crash reports, increasing the timeliness of data availability. (Source: Town of Hanover, NH)
+
+conflicting data fields would be a crash type recorded as "rear end" but the crash report says that one car was hit on the "side".
+
+#### **Completeness**
+
+Completeness is a measure of missing information. It may range from missing data on the individual crash forms to missing information due to unreported crashes.
+
+Unreported crashes, particularly non-injury crashes, present a drawback to crash data analysis. Without knowing about these crashes, we cannot recognize the full magnitude of certain types of crashes (e.g., pedestrian involved crashes). Non-injury crashes, or property damage only (PDO) crashes, involve damage less than a specified threshold (e.g., \$1,000); these thresholds vary from State to State. The parties involved in PDO crashes
+
+are typically not required to report the crash and often agree to work out the financial damages personally or through their automobile insurance policies. In some States, even when PDOs are reported, they are not always added into the crash database.
+
+In addition to the limitations from absent data due to unreported crashes, fluctuations in the thresholds (i.e., dollar amounts) can make it difficult to compare data from previous years. Unreported PDO crashes are one of many measures of "completeness" that road safety professionals must consider when collecting and analyzing data. A lack of complete data hinders the ability to measure the effectiveness of safety countermeasures (e.g., safety belts, helmets, and red light cameras) or change in crash severity.
+
+#### **Uniformity**
+
+Uniformity is a measure of how consistent information is coded in the data system or how well it meets accepted data standards. Numerous law enforcement agencies within each State, some of which are not the primary users of the crash data, are responsible for crash data collection. The challenge for States is ensuring there is consistency among the various agencies when collecting and reporting crash data. One example of inconsistent or nonuniform data can be the location of a crash. If one agency, for example the State highway patrol, uses GPS to document a crash at one of several entrances (driveways) to a shopping center, but the city police use a linear reference system (e.g., distance from an intersection), there is a potential for inconsistent crash location data.
+
+The Model Minimum Uniform Crash Criteria (MMUCC) is used by States to ensure uniform crash data. MMUCC is an optional guideline that presents a model minimum set of uniform variables or data elements for describing a motor vehicle crash. This uniformity assists transportation safety professionals and governments in making decisions that lead to safety improvements. Similarly, MIRE provides a recommended list of elements to use when reporting road and traffic characteristics, thereby increasing uniformity of road network data. More information on MMUCC and MIRE is presented at the end of this chapter.
+
+#### **Integration**
+
+Data integration is a measure of whether different databases can
+
+### **Crash Data Improvement Program**
+
+The Federal government established the Crash Data Improvement Program (CDIP) to provide states with a means to measure the quality of the information within their crash database. It is intended to provide the states with metrics that can be used to establish measures of where their crash data stand in terms of its timeliness, the accuracy and completeness of the data, the consistency of all reporting agencies reporting the information in the same way, the ability to integrate crash data with other safety databases, and how the state makes the crash data accessible to users. Additionally, CDIP was established to help familiarize the collectors, processors, maintainers, and users with the concepts of data quality and how quality data help to improve safety decisions. CDIP also included a guide that presents information on each data quality characteristic and how to measure them.
+
+Reference: Crash Data Improvement Program, National Highway Traffic Safety Administration, [https://safety.fhwa.dot.](https://safety.fhwa.dot.gov/cdip/summary.cfm) [gov/cdip/summary.cfm](https://safety.fhwa.dot.gov/cdip/summary.cfm)
+
+be linked together to merge the information in each database into a combined database. Each State maintains its own crash database. However, crash data alone do not typically provide sufficient details on issues like environmental risk factors, driver experience, or medical consequences. Linking crash data to other databases, such as road characteristics, driver licensing, vehicle registration, and hospital outcome data assists analysts and planners in evaluating the relationship of the circumstances of the crash and other factors (e.g., human, road, medical treatment) at the time of the crash. In addition, integrated databases promote collaboration among agencies, which can lead to improvements in the data and the data collection process.
+
+Some data are more challenging to integrate with other data sets. For example, hospital data are difficult to integrate with crash data due to the lack of a common identification system (as well as medical privacy laws). This is different from crash, road characteristics, and volume data, which can share a common referencing system on the road and thus be integrated and linked more easily for analysis.
+
+Spatially-located data in a GIS system can be integrated simply based on spatial position. This geographic integration can assist agencies in bringing together data that were gathered by various departments or agencies that may use different data storage standards and reference systems.
+
+#### **Accessibility**
+
+Accessibility is a measure of how easy it is to retrieve and manipulate safety data in a system, in particular by those entities that are not the data system owners. Complete, accurate, and timely data easily made available to localities, MPOs, and other safety partners can greatly enhance transportation planning and safety investments. Agencies or departments who house safety data, especially crash data, should consider how accessible the data are to external parties and how the process of obtaining data could be streamlined.
+
+## **Data Improvement Strategies**
+
+Local, State, and Federal agencies, as well as non-governmental organizations, require accurate data to be available for analysis and problem solving. Thus, programs to improve data should be in the work programs of all agencies invested in road safety. Data could be improved by changes in policy, technology, assessments, and training.
+
+#### **Policy**
+
+With so many agencies and organizations involved in the data collection process, published policy is a necessity. A standard set of procedures can provide a clear expectation of each agency's roles and responsibilities in data collection. Federal guidance and State legislation or administrative policy and regulations generally form a basis for policy. An example of Federal guidance comes from the provision in the MAP-21 transportation legislation that requires States to collect a comprehensive set of roadway and traffic fundamental data elements (FDEs) on all public roads**<sup>5</sup>** .
+
+#### **Technology**
+
+Technology plays an important role in data collection improvement. Federal legislation provides funds that allow States to improve their data collection systems with the latest technology for quality data collection and integration. Technology is not static and is always changing. Some technology examples that help facilitate data collection include electronic crash reporting systems, GPS location devices, barcode or magnetic strip technologies, wireless communications, error checking, and conflicting fields.
+
+#### **Assessments**
+
+Assessments are official evaluations that government agencies conduct
+
+Moving Ahead for Progress in the 21st Century Act, Section 1112, §148(f)(2)
+
+to determine the effectiveness of a traffic safety process or program. A team of outside experts conducts a comprehensive assessment of the highway safety program using an organized, objective approach and well-defined procedures that:
+
+- J Provide an overview of the program's current status in comparison to pre-established standards
+- J Note the program's strengths and weaknesses
+- J Provide recommendations for improvement
+
+Both FHWA and NHTSA provide these types of assessments, such as the Roadway Data Improvement Program (RDIP), which can improve the quality of an agency's data through expert technical assistance and fresh perspectives. When State agencies request an RDIP assessment, an FHWA team reviews and assesses a State's roadway data system for the content of the data collected; for the ability to use, manage and share the data; and to offer recommendations for improving the road data. The RDIP also examines the State's ability to coordinate and exchange road data with local agencies, such as those in cities, counties, and MPOs**<sup>6</sup>** .
+
+#### **Training**
+
+Education and training of transportation professionals play a vital role in improving data and data collection. For example, law enforcement officers create the crash data that is used by safety professionals to conduct studies and evaluate road safety. Thus, law enforcement need to understand how crash data are
+
+used in policy development and investment decisions, infrastructure improvements, and safety planning. Through proper education and training programs, law enforcement can have a broader perspective of their contribution to reducing crashes through improved data reporting. Other examples include training transportation professionals on the latest data collection tools and technology, advising court officials and adjudicators on important changes to safety legislation and penalties, and training personnel on how to handle crash reports with inaccurate or missing information.
+
+## **Federal Guidance**
+
+The following two sections present examples of Federal guidance that leads State agencies into improving the quality of their safety data.
+
+### **Model Minimum Uniform Crash Criteria**
+
+Statewide motor vehicle traffic crash data systems provide the basic information necessary for effective road safety efforts at any level of government—local, State, or Federal. Unfortunately, the use of State crash data is often hindered by the lack of uniformity between and within States. Data definitions, the number and type of data elements, and the threshold for collecting data varies from jurisdiction to jurisdiction. The Model Minimum Uniform Crash Criteria (MMUCC) was developed to help bring greater uniformity to crash data collection and provide national guidance to data collectors. MMUCC represents a voluntary and collaborative effort to generate uniform, accurate, reliable, and credible crash data to
+
+6
+
+Federal Highway Administration Roadway Safety Data Program, [http://safety.fhwa.](https://safety.fhwa.dot.gov/rsdp/technical.aspx) [dot.gov/rsdp/](https://safety.fhwa.dot.gov/rsdp/technical.aspx) [technical.aspx](https://safety.fhwa.dot.gov/rsdp/technical.aspx)
+
+support data-driven highway safety decisions at a State and a national level. MMUCC serves as a foundation for State crash data systems.
+
+Since MMUCC is a minimum set of recommended crash data, States and localities may choose to collect additional motor vehicle crashrelated data elements if they feel the data are necessary to enhance decision-making. Implementation of MMUCC is a collaborative effort involving the Governors Highway Safety Association, FHWA, NHTSA, and the Federal Motor Carrier Safety Administration (FMCSA).
+
+The MMUCC Guideline is updated every four or five years to address emerging highway safety issues, simplify the list of recommended data elements, and clarify definitions of each data element.
+
+#### **MMUCC Data Elements**
+
+MMUCC consists of data elements recommended to be collected by investigators at the crash scene. From the crash scene information, additional data elements can be derived to assist law enforcement. Additional data elements are available through linkage to driver history, hospital and other health/ injury data, and road inventory data. Each group of data elements has a unique identifier that describes the type of data element and whether it is derived or linked data.
+
+MMUCC data elements are divided into four major groups that describe various aspects of a crash: crash, vehicle, person, and roadway. Each data element includes a definition, a set of specific attributes, and a rationale for the specific attribute.
+
+For the entire list of MMUCC data
+
+#### **MMUCC Example Element**
+
+The following is the MMUCC format for "Person Data Element Derived from Collected Data."
+
+PD1. Age
+
+Definition: The age in years of the person involved in the crash
+
+Source: This data element is derived from Date of Birth (P2) and Crash Date and Time (C3).
+
+#### Attribute:
+
+*•* Age in years
+
+Rationale: Age is necessary to determine the effectiveness of safety countermeasures appropriate for various age groups.
+
+elements, refer to the latest edition of the MMUCC Guideline located at **www.mmucc.us**.
+
+The MMUCC data elements represent a core set of data elements. The fourth edition (2012) of the MMUCC Guideline contains 110 data elements and recommends that States collect all 110 data elements. To reduce the data collection burden, MMUCC recommends that law enforcement at the scene should collect 77 of the 110 data elements. From crash scene information, 10 data elements can be derived, while the remaining 23 data elements should be obtained after linkage to other State data files. States unable to link to other State data to obtain the MMUCC linked data elements should collect, at a minimum, those linked data elements feasible for collecting on the crash report. At the same time, States should work to develop data linkage capabilities so they eventually are able to obtain, via linkage, all of the information to be generated by the MMUCC linked data elements.
+
+Segment location/linkage elements Segment classification Segment cross section Segment roadside descriptors Other segment descriptors Segment traffic flow data Segment traffic operations/control data
+
+Other supplemental segment descriptors
+
+**ROADWAY SEGMENT ROADWAY ALIGNMENT**
+
+Horizontal curve data Vertical curve data
+
+#### **ROADWAY JUNCTION**
+
+At-grade intersection/junctions Interchange and ramp descriptors
+
+**FIGURE 3-5**: MIRE Data Elements Category Descriptors (Source: MIRE version 1.0)
+
+### **Model Inventory of Roadway Elements**
+
+Critical safety data include not only crash data, but also road inventory data, traffic data, and other information. State DOTs need accurate and detailed data on road characteristics as they develop and implement strategic highway safety plan (SHSPs) and look toward making more data driven safety investments.
+
+With the need for and availability of so many types of data, the question becomes "How can transportation agencies be sure that they are collecting the necessary roadway data to make effective road safety decisions?" MIRE is a vitally important resource that defines the data needed to help transportation agencies build a road characteristics database that will lead to good safety analysis. MIRE defines 202 individual characteristics of the road system that should be collected. These characteristics are referred to as data elements. The elements fall into three broad categories:
+
+- J Roadway segment descriptors
+- J Roadway alignment descriptors
+
+#### J Roadway junction descriptors
+
+Most State and local transportation agencies do not have all the data needed to use analysis tools such as SafetyAnalyst, the Interactive Highway Safety Design Model, and other tools and procedures identified in the Highway Safety Manual. MIRE provides a structure for road inventory data that allows State and local transportation agencies to use these analysis tools with their own data rather than relying on default values that may not reflect local conditions.
+
+As the need for road inventory information has increased, new and more efficient technologies to collect road characteristics have emerged. However, the collected data need a framework for common information sharing. Just as MMUCC provides guidance for consistent crash data elements, MIRE provides a structure for roadway inventory data elements using consistent definitions and attributes. It defines each element, provides a list of attributes for coding, and assigns a priority status rating of "critical" or "value added" based on the element's importance for use in analytic tools, such as
+
+SafetyAnalyst.
+
+The latest version of MIRE can be viewed and downloaded from the FHWA Office of Safety site, **http:// safety.fhwa.dot.gov/tools/data\_tools/ mirereport/.**
+
+Figure 3-5 displays a breakdown of the major data element categories and subcategories contained in MIRE. MIRE further breaks down each subcategory into individual data elements. For a complete listing of MIRE data elements, refer to the MIRE publication.
+
+While the complete list of MIRE elements is rather extensive, there are a basic set of elements within MIRE called the Fundamental Data Elements (FDE) that an agency needs to conduct safety analyses regardless of the specific analysis tools used or methods applied. As discussed, the need for improved and more robust safety data is increasing due to the development of a new generation of safety data analysis tools and methods.
+
+## **Linking Data Through A Referencing System**
+
+The types of road safety data presented in this unit are only useful as much as they are capable of being linked through a common geospatial relational location referencing system. States recognize that they must have a common relational location referencing system (i.e., geographic information system or linear referencing system) for all public roads if they are going
+
+to integrate different types of safety data. If all safety data are referenced to the same system, the road characteristics data can be linked with the crash data, which would permit the State to identify locations on all public roads where crash patterns are occurring that can be reduced through known countermeasures.
+
+In most States, development of a common referencing system for all public roads will require significant effort and cooperation with local agencies. The Federal Highway Performance Monitoring System requires GIS-based referencing for all roads in the Federal-aid highway system, interstate highways, and public roads not classified as local roads or rural minor collectors.**<sup>7</sup>** However, significant travel occurs on local roads and rural minor collectors. Some local agencies have or are developing, their own GIS-based referencing systems for roads in their inventory data. Light detection and ranging (LIDAR) systems are often used to accurately survey the road network. The State should work with local agencies to incorporate these referencing systems into the State base map. Once the referencing systems are combined, attribute data for additional mileage can be added when either State or local agencies develop or expand inventories. Moreover, as stated above, this will lead to the ability to link crashes with inventory and traffic data, enabling the State to use the more advanced problem identification methods on more and more miles of public roads.
+
+Memorandum on Geospatial Network for All Public Roads, Office of Highway Policy Information, August 7, 2012. Accessed October 2017 at [https://](https://www.fhwa.dot.gov/policyinformation/hpms/arnold.pdf) [www.fhwa.dot.gov/](https://www.fhwa.dot.gov/policyinformation/hpms/arnold.pdf) [policyinformation/](https://www.fhwa.dot.gov/policyinformation/hpms/arnold.pdf) [hpms/arnold.pdf](https://www.fhwa.dot.gov/policyinformation/hpms/arnold.pdf)
+
+## **Conclusion**
+
+Data are crucial to improving road safety. Safety data consist of various kinds of data that can be used to identify safety problems and priorities so that safety partners in many agencies can address important issues. Data such as crash data, traffic volume data, and road characteristics data are often used and are critical for safety analysis by many agencies. Other data, such
+
+as conflict observations, emergency medical data, and citation data, can be useful in a supplemental role for specific studies. Regardless of the type of safety data, the quality of the data is vitally important. Agencies that collect safety data should strive to improve their timeliness, accuracy, completeness, uniformity, integration, and accessibility to maximize their potential to drive good decisions.
+
+#### **EXERCISES**
+
+- J **SELECT** a scenario below. Assume that you are using crash data as your primary data to inform your decisions. Explain how each of the six quality criteria discussed in this chapter could affect your evaluation of the current safety situation and your recommendations.
+  - J You are prioritizing intersections in a city to be treated with enhanced visibility treatments, such as larger signs, wider markings, and additional signal heads.
+  - J You are developing a public outreach effort to communicate the need to yield to pedestrians at crosswalks. You wish to focus your efforts to the areas of the city where failing to yield to pedestrians is the most rampant.
+
+J You are recommending safety improvements to an interchange that was identified based on having a higher number of expected crashes than other interchanges of the same type.
+
+Given the scenario you selected above, how do you think the availability of other types of data could affect your recommendations? Such data may include any of the data types covered in Chapter 3.2. (e.g., EMS and hospital injury data, enforcement citations, public complaints, or other data). What additional information could this reveal?
+
+J **IDENTIFY** programs or policies that exist in your state or local agency to improve data. This may include any of the types of safety data covered in Chapter 3.2.
+
+THIS PAGE INTENTIONALLY LEFT BLANK
+
+![](_page_97_Picture_0.jpeg)
+
+## **Solving Safety Problems UNIT 4**
+
+#### **LEARNING OBJECTIVES**
+
+After reading the chapters and completing exercises in Unit 4, the reader will be able to:
+
+- J **IDENTIFY** three major components of road safety management
+- J **DEFINE** the process of conducting site-level and system-level safety management
+- J **USE** safety data to identify safety issues and develop strategies to solving those issues
+
+## **Road Safety Management**
+
+Road safety management refers to the process of identifying safety problems, devising potential strategies to combat those safety problems, and selecting and implementing the strategies. Effective safety management is also proactive and looks for ways to prevent safety problems before they arise. High quality safety data should be used to determine the nature of the road safety problems and how best to solve them. As discussed in Unit 3, the clearest and most readily available indicators of road safety problems are crash data. These data can be used to identify safety problems on a large or a small scale. Other data, such as roadway characteristics, traffic volume, citations, and driver history, can be integrated with crash data to assist in identifying safety trends and high priority locations.
+
+## **Data quality issues should not prevent a data-driven process**
+
+Every transportation agency will acknowledge that it does not have perfect data. All data have issues related to accuracy, coverage, timeliness, and other factors. One agency's crash data may have an incomplete record of low severity crashes. Another agency may have very little data on the traffic volume on low volume rural roads. However, data quality issues should not prevent a transportation agency from using the data to drive its safety management efforts. Even
+
+![](_page_98_Picture_6.jpeg)
+
+while the agency strives to improve its data, the data on hand should be used in the process of identifying safety problems and devising solutions to those problems.
+
+## **Data needs for safety analysis**
+
+High quality safety analysis demands high quality data. Unfortunately, poor data availability and low quality limit the types of analyses that can be conducted. The data requirements depend on the type of analysis and what safety questions are being asked. Table 4-1 provides examples of various categories of safety analysis and lists the data that would be needed to conduct them.**<sup>1</sup>**
+
+**1**
+
+Applying Safety Data and Analysis to Performance-Based Transportation Planning, e-Guidebook, FHWA, [http://safety.](https://safety.fhwa.dot.gov/tsp/fhwasa15089/appb.cfm) [fhwa.dot.gov/tsp/](https://safety.fhwa.dot.gov/tsp/fhwasa15089/appb.cfm) [fhwasa15089/](https://safety.fhwa.dot.gov/tsp/fhwasa15089/appb.cfm) [appb.cfm](https://safety.fhwa.dot.gov/tsp/fhwasa15089/appb.cfm)
+
+|                                          | SAFETY ANALYSIS<br>QUESTION                                                                                                                                                                                   | D<br>A<br>T<br>A NEEDS                                                                                                                                                                                                                                                                                                                                                                                                                                  |
+|------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| MARKING<br>BENCH                         | How many fatalities<br>and serious injuries are<br>occurring in my area?<br>How does this<br>compare to other<br>areas of my State?                                                                           | Total crashes<br>Total fatalities and serious injuries<br>High-level roadway data — roadway ownership,<br>functional classification<br>Agency geographic boundary information                                                                                                                                                                                                                                                                           |
+| CONTRIBUTING FACTORS<br>CRASH TRENDS AND | What type of road users<br>are involved in crashes?<br>When are the<br>crashes occurring?<br>What are the major<br>contributing factors<br>to crashes?                                                        | Crash severity — fatality, injury type,<br>property damage only<br>Crash incidence data — time of day, day,<br>month, weather, etc.<br>Crash type — road departure, intersection,<br>head-on, angle, etc.<br>Contributing factors — age, impairment,<br>seatbelt usage, speed, etc.                                                                                                                                                                     |
+| MENT<br>MPROVE<br>SITES FOR SAFETY I     | What locations<br>(intersections or<br>segments) show the<br>most potential for<br>safety improvements?                                                                                                       | Crash severity<br>Crash location<br>Roadway and roadside characteristics — intersection<br>control, number of lanes, presence and type of<br>shoulder, presence and type of median, posted<br>speed, horizontal and vertical alignment, etc.<br>Traffic volume data — intersection total entering<br>traffic volume, roadway segment volume per<br>million vehicle miles.<br>Calibrated safety performance functions,<br>if predictive methods are used |
+| SAFETY RISK FACTORS                      | What are the common<br>characteristics of<br>locations with crashes?<br>What are the<br>countermeasures<br>to address these<br>characteristics?<br>How should we prioritize<br>system-wide<br>implementation? | Crash severity<br>Crash location<br>Roadway and roadside characteristics — intersection<br>control, number of lanes, presence and type of<br>shoulder, presence and type of median, posted<br>speed, horizontal and vertical alignment, etc.<br>Traffic volume data — intersection total entering<br>traffic volume, roadway segment volume per<br>million vehicle miles.                                                                               |
+|                                          |                                                                                                                                                                                                               | TABLE 4-1: Safety analysis categories, questions, tools and data needs.                                                                                                                                                                                                                                                                                                                                                                                 |
+
+## **Safety data as performance measures**
+
+A transportation agency has many types of data at its disposal for identifying safety problems, but the agency must select which type(s) of data will be the **performance measures** used to identify the road safety emphasis areas. Federal legislation has focused increasingly on fatal crashes and serious injury crashes as performance measures for road safety.
+
+Table 4-2 provides examples of performance measures developed by the National Highway Traffic Safety Administration (NHTSA) and the Governors Highway Safety Association (GHSA) that could be used to identify safety priorities.**<sup>2</sup>** The sources of the data could be State crash data files, the Fatality Analysis Reporting System (FARS), surveys conducted by the State, or grant applications from law enforcement and other departments. The section on Network Screening in Chapter 11 presents a more detailed discussion of crash-based performance measures and how they can be used to identify sites that are high priority for safety treatment.
+
+#### **Performance measure**
+
+A numerical metric used to monitor changes in system condition and performance against established visions, goals, and objectives.
+
+#### **2**
+
+Grant activity reporting
+
+Grant activity reporting
+
+reporting
+
+National Highway Traffic Safety Administration (NHTSA). 2007. Performance Measures Discussion. 408 Team Document #005, October 29, 2007. National Highway Traffic Safety Administration.
+
+| Number of traffic fatalities (three-year or five-year moving averages)                                                                | FARS                      |
+|---------------------------------------------------------------------------------------------------------------------------------------|---------------------------|
+| Number of serious injuries in traffic crashes                                                                                         | State crash<br>data files |
+| Fatalities/VMT (including rural, urban, and total fatalities)                                                                         | FARS, FHWA                |
+| Number of unrestrained passenger vehicle occupant fatalities, seat positions                                                          | FARS                      |
+| Number of fatalities in crashes involving a driver or motorcycle operator<br>with a blood alcohol concentration of .08 g/dL or higher | FARS                      |
+| Number of speeding-related fatalities                                                                                                 | FARS                      |
+| Number of motorcyclist fatalities                                                                                                     | FARS                      |
+
+Number of unhelmeted motorcyclist fatalities FARS
+
+Number of drivers 20 or younger involved in fatal crashes FARS
+
+Number of pedestrian fatalities FARS
+
+Observed seat belt use for passenger vehicles, front seat outboard occupants Survey
+
+Number of seat belt citations issued during grant-funded
+
+Number of impaired-driving arrests made during grant-funded
+
+**DESCRIPTION SOURCES**
+
+**TABLE 4-2**: Safety performance measures and data sources (*Source: NHTSA 2007*)
+
+Number of speed citations issued during grant-funded activities Grant activity
+
+enforcement activities
+
+enforcement activities
+
+![](_page_101_Picture_0.jpeg)
+
+## **Components of safety management**
+
+The safety management process can be viewed in three general components. These components are carried out by the agency (or agencies) responsible for managing the safety of the road system:
+
+- J **Identifying safety problems –** The agency uses crash data and other safety data to identify road safety problems or problem locations.
+- J **Developing potential safety strategies –** The agency develops potential strategies to address the identified safety problems. These strategies might also be referred to as countermeasures or treatments.
+- J **Selecting and implementing strategies –** The agency weighs the potential strategies and decides which ones to implement.
+
+## **Levels of safety management**
+
+Although all road safety management follows the same three general components listed above, the specific steps of the safety management process will be different depending on the scope. The process might be intended to address specific site-level issues, such as crash patterns at high priority intersections, curves, or corridors. On a larger scale, the process might be intended to address system-level issues, such as problems that can be addressed by policies, design standards, or broad ranging campaigns of education or enforcement. The following chapters will discuss safety management for these two levels: Chapter 11 presents site-level safety management; Chapter 12 presents system-level safety management.
+
+## **Site-Level Safety Management**
+
+Site-level safety management is the process of identifying and addressing safety issues at high priority **sites**. This contrasts with safety issues that are addressed for an entire transportation system (i.e., all roads in a city, county, or State). System-level safety management is covered in Chapter 12.
+
+Agencies responsible for road safety often conduct some form of site-level safety management. They identify particular sites of concern and determine how best to address the safety problems at these priority sites. The methods of identifying priority sites and the safety strategies used to treat the sites differ according to the type of agency. A department of transportation (DOT) may install a sign or pavement marking; a law enforcement agency might increase enforcement in the area of the site. Regardless of the type of agency, it is important to conduct site-level safety management in a manner that uses good analysis methods driven by safety data.
+
+Chapter 10 presented road safety management in terms of three general components:
+
+- J **Identifying safety problems**
+- J **Developing potential safety strategies**
+- J **Selecting and implementing strategies**
+
+![](_page_102_Figure_9.jpeg)
+
+**FIGURE 4-1**: Schematic Illustrating the Steps of Site-level Safety Management
+
+When discussing site-level safety management, these three components can be further divided into six distinct steps. This sixstep process is common to the engineering discipline and is presented in Part B of the first edition of the Highway Safety Manual**<sup>3</sup>** (HSM). The process, shown in Figure 4-1, will be the framework for the discussion of site-level safety management in this chapter. The material presented in this chapter is based on the guidance presented in the HSM and material from a series of documents entitled "Reliability of Safety Management Methods" published by FHWA. These FHWA
+
+#### **Site**
+
+A narrowly defined location of interest for safety analysis, such as an intersection, road section, interchange, or midblock crossing.
+
+**3**
+
+Highway Safety Manual, First edition, American Association of State Highway Transportation Officials, 2010.
+
+## **4**
+
+Srinivasan, R., F. Gross, B. Lan, G. Bahar (2016), *Reliability of Safety Management Methods: Network Screening*, Report No. FHWA-SA-16-037, Federal Highway Administration, Washington, D.C.
+
+#### **5**
+
+Srinivasan, R., G. Bahar, F. Gross (2016), *Reliability of Safety Management Methods: Diagnosis*, Report No. FHWA-SA-16-038, Federal Highway Administration, Washington, D.C.
+
+#### **6**
+
+Bahar, G. R. Srinivasan, F. Gross, (2016), *Reliability of Safety Management Methods: Countermeasure Selection*, Report No. FHWA-SA-16-039, Federal Highway Administration, Washington, D.C.
+
+#### **7**
+
+Srinivasan, R., F. Gross, G. Bahar (2016), *Reliability of Safety Management Methods: Safety Effectiveness Evaluation*, Report No. FHWA-SA-16-040, Federal Highway Administration, Washington, D.C.
+
+See next page.
+
+## **SAFETY MANAGEMENT**
+
+#### **COMPONENTS STEPS OF SITE-LEVEL SAFETY MANAGEMENT**
+
+#### **IDENTIFY SAFETY PROBLEMS**
+
+**Step 1. Network screening:** Identify locations that could benefit from treatments to reduce crash frequency and severity.
+
+**Step 2. Diagnosis:** Identify crash trends and patterns based on reported crashes, assess the crash types and severity levels, and study other elements that characterize the crashes.
+
+#### **DEVELOP POTENTIAL SAFETY SOLUTIONS**
+
+**Step 3. Countermeasure selection:** Identify appropriate countermeasures to target crash contributing factors and reduce crash frequency and severity at identified locations.
+
+**Step 4. Economic appraisal:** Estimate the economic benefit and cost associated with implementing a particular countermeasure or set of countermeasures.
+
+#### **SELECT AND IMPLEMENT STRATEGIES**
+
+**Step 5. Project prioritization:** Develop a prioritized list of safety improvement projects, considering available resources.
+
+**Step 6. Safety effectiveness evaluation:** Evaluate how a particular countermeasure (or group of countermeasures) has affected crash frequency and severity where it was installed.
+
+**TABLE 4-3**: Steps of the Site-level Safety Management Process
+
+documents provide in-depth guidance and examples on the following topics:
+
+- J **Network screening** The network screening guide describes various methods and the latest tools to support network screening.**<sup>4</sup>**
+- J **Diagnosis** The diagnosis information guide describes various methods and the latest tools to support diagnosis.**<sup>5</sup>**
+- J **Countermeasure selection** The countermeasure selection information guide describes various methods and the latest tools to support countermeasure selection.**<sup>6</sup>**
+
+### J **Safety effectiveness evaluation**
+
+- The safety effectiveness evaluation guide describes various methods and the latest tools to support safety effectiveness evaluation.**<sup>7</sup>**
+- J **Systemic safety programs** The systemic safety programs guide describes the state-of-the-practice and the latest tools to support systemic safety analysis.**<sup>8</sup>**
+
+The six steps of the site-level safety management process relate to the three general components of safety management as shown in Table 4-3. Each step is presented in more detail through the following sections in this chapter.
+
+## **Step 1. Network screening**
+
+Network screening refers to the process of selecting high priority sites that need safety treatment, often through an analysis of crash data. There are many ways in which an agency can use crash data to prioritize sites, ranging from simplistic methods, which are easy to understand and implement but can be inaccurate or ineffective, to more advanced methods, which require statistical expertise and more data but provide a better prioritization of sites.
+
+For many years, the most prevalent methods for ranking specific sites for safety improvements were based on historical crash data alone. Many agencies still use these methods to allocate their road safety funds. Agencies that prioritize sites by historical **crash frequency** identify those sites that have the highest number of crashes in a certain time period (typically three to five years). This serves to assist agencies in addressing the magnitude of the problem, that is, attempting to address the highest number of crashes. By its nature, this method typically identifies sites that have high amounts of traffic (either vehicles, pedestrians, or other road users). However, this method may miss abnormally hazardous sites that do not present a relatively large number of crashes. Another variation of the crash frequency method uses **crash severity**, in which agencies weight the crash frequency by giving greater weight to higher severity crashes. This method counteracts some of the bias in the crash frequency method. For example, a general high crash frequency may prioritize a busy
+
+intersection that has many crashes, but a closer examination reveals that most crashes are low speed, low severity rear-end crashes. The crash severity method would lower the priority of this intersection in favor of other sites where more serious crashes occur.
+
+Some agencies prioritize sites by the historical **crash rate**. This method incorporates traffic volume to augment the crash data. The crash frequency at a site is divided by the traffic volume – either the annual average daily traffic (for road segments), total entering volume (for vehicle traffic at intersections), or other volumes, such as pedestrian crossing volume. The typical unit for this method is crashes per 100 million vehicle miles traveled for road segments or crashes per 100 million entering vehicles for intersections. Crash rate in these units is calculated as:
+
+**Crash rate per 100 million vehicle miles traveled**
+
+**<sup>=</sup> (C×100,000,000) (V×365×N×L)**
+
+**C** = Number of crashes in the study period
+
+**V** = Traffic volumes using average annual daily traffic (AADT) volumes
+
+**N** = Number of years of data
+
+**L** = Length of the roadway segment in miles
+
+This approach of prioritizing sites by crash rate serves to counteract the bias of crash frequency that overly prioritizes sites with high volume, since higher volume decreases the crash rate. However, it may inefficiently prioritize sites with very low volumes.
+
+**8**
+
+(from previous page) Gross, F., T. Harmon, G. Bahar, K. Peach (2016), *Reliability of Safety Management Methods: Systemic Safety Programs*, Report No. FHWA-SA-16-041, Federal Highway Administration, Washington, D.C.
+
+#### **Crash frequency**
+
+The number of observed crashes per year.
+
+#### **Crash severity**
+
+The level of injury severity of the crash as an event, typically determined by the highest severity injury of any person involved in the crash.
+
+#### **Crash rate**
+
+The number of observed crashes per unit of traffic volume passing through the location.
+
+Agencies might use a combination of these two methods. They may set a minimum crash rate to generate an initial list of priority sites and then prioritize that group by crash frequency or severity. Regardless, these simplistic methods are known to have potential biases. One of the most prevalent biases is that the crash history used to prioritize sites with these methods usually reflects only the short-term trend of crashes. Given that the yearto-year occurrence of crashes at a location is random, it can be the case that a short-term crash history (one to three years) may be relatively high, but in the long run (ten years), the crashes would return to a lower amount, even if no safety improvements were done. This effect creates selection bias or **regression-to-the-mean** (RTM) bias in
+
+As the years progressed, many transportation safety professionals recognized that while these simplistic methods did identify sites that benefited from safety improvement, they were not the locations where safety funds could be spent the most effectively. The selection of high crash sites was subject to RTM bias. Also, sites with high numbers of crashes were typically complex and required expensive reconstruction in order to reduce crashes appreciably. The question became, "How could road safety funds be spent in a way that provided the biggest bang for the buck?"
+
+the safety analysis of this location.
+
+As the science of road safety advanced, researchers developed more advanced approaches for prioritizing sites for safety improvements. Dr. Ezra Hauer
+
+**Comparing road segments by crash frequency and rate**
+
+**Road Segment A:** A three-mile section of road that has had **four** crashes over five years and has a traffic volume of **4,000** vehicles per day.
+
+**Road Segment B:** A three-mile section of road that has had **10** crashes over five years and has a traffic volume of **12,000** vehicles per day.
+
+If an agency is comparing these segments based on crash frequency, they would prioritize road segment B for having 10 crashes compared to road segment A which had four crashes.
+
+If comparing these segments based on crash rate, the agency would calculate the crash rate of road segment A as (4 crashes x 100,000,000) / (4,000 vehicles per day x 365 x 5 years x 3 miles) = 18.2 crashes per 100 million vehicle miles traveled. Following the same calculation, road segment B has a rate of 15.2 crashes per 100 million vehicle miles traveled. According to crash rate, the agency would prioritize road segment A. The prioritization of these two segments changes when traffic volume is taken into account.
+
+pushed forward a movement to identify "sites with promise."**<sup>9</sup>** The main idea was to identify sites that experienced more crashes than would be expected from a site with that particular set of characteristics. In many cases, these abnormally performing sites could be addressed with low cost safety treatments, such as larger signs or pavement markings with greater visibility. This approach uses statistical regression models that predict crashes for a given set of characteristics. These models demonstrate the advantage of bringing together different types of safety data, which in this case could include crash data, roadway characteristics, and traffic volume.
+
+#### **Regressionto-the-mean**
+
+The fact that a short term examination of crash history at a location is likely inaccurate (e.g., lower or higher than its true safety performance). When a longer time period of crash history is examined, the crash frequency will "regress" to its "mean" and provide a better picture of the long term average crash frequency.
+
+**9**
+
+Hauer, E. (1997), *Observational Before After Studies in Road Safety*, Elsevier Science, New York.
+
+The most basic of these regression methods calculates **predicted crashes**. This method requires information about certain geometric and operational characteristics, such as traffic volume, number of lanes, and type of road.
+
+An SPF is developed or calibrated using data from an entire jurisdiction or State, so it is independent of the crash history
+
+of the specific site. This means that the predicted crash value is unaffected by the bias caused by RTM. Using SPFs, transportation agencies can predict crash values for many sites and prioritize the sites according to the highest predicted values. Another use of the predictive method is in systemic safety treatments, presented in Chapter 12 under Risk Based Prioritization.
+
+#### **Predicted crashes**
+
+The frequency of crashes per year that would be predicted for a site based on the result of a crash prediction model, called a safety performance function (SPF).
+
+| PERFORMANCE MEASURE                                                      | ACCOUNTS<br>FOR TRAFFIC<br>VOLUME | ACCOUNTS<br>FOR<br>RTM BIAS   | ACCOUNTS<br>FOR CRASH<br>SEVERITY |
+|--------------------------------------------------------------------------|-----------------------------------|-------------------------------|-----------------------------------|
+| 1. Average crash frequency                                               | No                                | No                            | Not explicitly*                   |
+| 2. Crash rate                                                            | Yes                               | No                            | Not explicitly*                   |
+| 3. Equivalent property damage only<br>(EPDO) average crash frequency     | No                                | No                            | Yes                               |
+| 4. Relative severity index                                               | No                                | No                            | Yes                               |
+| 5. Critical rate                                                         | Yes                               | No                            | Not explicitly*                   |
+| 6. Excess predicted average crash<br>frequency using method of moments   | No                                | No                            | Not explicitly*                   |
+| 7. Level of service of safety                                            | Yes                               | No                            | Not explicitly*                   |
+| 8. Excess predicted average crash<br>frequency using SPFs                | Yes                               | No                            | Not explicitly*                   |
+| 9. Probability of specific crash types<br>exceeding threshold proportion | No                                | Not affected<br>by RTM bias** | Not explicitly*                   |
+| 10. Excess proportion of<br>specific crash types                         | No                                | Not affected<br>by RTM bias** | Not explicitly*                   |
+| 11. Expected average crash frequency<br>with empirical Bayes adjustments | Yes                               | Yes                           | Not explicitly*                   |
+| 12. EPDO average crash frequency<br>with EB adjustment                   | Yes                               | Yes                           | Yes                               |
+| 13. Excess expected average crash<br>frequency with EB adjustment        | Yes                               | Yes                           | Not explicitly*                   |
+
+<sup>\*</sup> While these measures do not explicitly mention severity, analysts can adapt any of the measures to consider any severity level.
+
+**TABLE 4-4**: Performance Measures for Network Screening *(Source: Highway Safety Manual, 1st ed.)*
+
+<sup>\*\*</sup> These two measures will not be affected by RTM only if they are based on data from a long time period.
+
+#### **10**
+
+Srinivasan, R., D. Carter, and K.Bauer (2013), *Safety Performance Function Decision Guide: SPF Calibration vs SPF Development*, Report No. FHWA-SA-14-004, Federal Highway Administration, Washington, DC.
+
+#### **11**
+
+R. Srinivasan and K. Bauer (2013), *Safety Performance Development Guide: Developing Jurisdiction-Specific SPFs*, Report FHWA-SA-14-005, Federal Highway Administration, Washington, DC
+
+#### **12**
+
+Bahar, G (2014), *User's Guide to Develop Highway Safety Manual Safety Performance Function Calibration Factors*, HR 20- 7(332), National Cooperative Highway Research Program, American Association of State Highway and Transportation Officials, Standing Committee on Traffic Safety, Washington, DC.
+
+**Expected crashes, excess crashes**
+
+See next page.
+
+#### **Where can I get safety performance functions for my State?**
+
+SPFs can be obtained in two ways:
+
+- **1)** SPFs can be developed from scratch using crash, roadway, and traffic volume data from roads and intersections in the State. This requires significant data to be collected on hundreds of sites. A statistical expert must use these data to develop SPFs that are tailor made for that State.
+- **2)** SPFs can be obtained from national resources, such as the HSM; then calibrated for the particular State of interest. This requires data to be collected on a smaller number of sites than is required for developing a new SPF.
+
+The crashes predicted by the SPF are compared to the crashes observed on the State's roads, and an analyst calculates a calibration factor to adjust the SPF prediction appropriately for the State.
+
+SPF development or calibration is typically handled by the State DOT. FHWA provides guidance on deciding between developing a new SPF or calibrating an existing one.**<sup>10</sup>** States that decide to develop new SPFs can refer to guidance in a related FHWA publication.**<sup>11</sup>** NCRHP provides guidance for those who decide to calibrate existing SPFs.**<sup>12</sup>**
+
+The first edition of the HSM lists several benefits of the predictive method, including:
+
+- J RTM bias is addressed as the method concentrates on longterm expected average crash frequency rather than shortterm observed crash frequency.
+- J Reliance on availability of limited crash data for any one site is reduced by incorporating predictive relationships based on data from many similar sites.
+- J The method accounts for the fundamentally nonlinear relationship between crash frequency and traffic volume.
+
+Agencies can also use the predicted crashes in combination with actual crash history at the site of interest to calculate **expected crashes**. A method called empirical Bayes (EB) brings these two values together to reflect a crash frequency that incorporates the general crash prediction from the SPF with the real world experience of crash history at the site to provide an accurate estimation of how many crashes should be expected at the
+
+site (see more detailed discussion of the EB method later in this step). Some agencies may also calculate **excess crashes** as a measure for site prioritization. This is the difference between the expected crashes and the observed crash frequency at the site.
+
+## **Performance measures in network screening**
+
+The key to effective network screening is selecting an appropriate performance measure. Network screening methods should appropriately account for three major factors that can affect the screening outcome:
+
+- J **Differences in traffic volumes**
+- J **Possible bias due to RTM**
+- J **Crash severity**
+
+Table 4-4 lists the thirteen performance measures discussed in the HSM with an indication of their ability to account for these major factors. While some measures directly account for crash severity (e.g., relative severity index), analysts can adapt any of the measures to account for crash severity.
+
+## **Accounting for differences in traffic volumes**
+
+As discussed earlier, analysts have traditionally used crash rates to account for differences in traffic volume among sites. Crash rate is the ratio of crash frequency to exposure, which is typically the traffic volume. Crash rates implicitly assume a linear relationship between crash frequency and traffic volume; however, many studies have shown that the relationship between crashes and traffic volume is nonlinear, and the shape of this relationship depends on the type of facility. Nonlinear relationships,
+
+such as SPFs, are more appropriate than linear relationships, such as crash rates to account for differences in traffic volume among sites.
+
+SPFs are a more reliable method to account for differences in traffic volume among sites because they reflect the nonlinear relationship between crash frequency and traffic volume. The SPF is an equation that represents a best-fit model that relates annual observed crashes to the site characteristics including annual traffic volume and other site characteristics. Typically, SPFs are estimated for a particular crash type for a type of facility (e.g., run-off-road crashes on rural two
+
+#### **Expected crashes**
+
+The frequency of crashes per year that represents the combination of the predicted crashes and the observed crashes that actually occurred at the site.
+
+#### **Excess crashes**
+
+The difference between the expected crashes and the observed crash frequency at the site.
+
+![](_page_108_Figure_8.jpeg)
+
+**FIGURE 4-2**: Example of SPF for multi-vehicle crashes on rural, 4-lane freeways
+
+![](_page_108_Figure_10.jpeg)
+
+**FIGURE 4-3**: Example of SPF for single-vehicle crashes on rural, 4-lane freeways
+
+**13**
+
+R. Srinivasan and K. Bauer (2013), Safety Performance *Development Guide: Developing Jurisdiction-Specific SPFs*, Report FHWA-SA-14-005, Federal Highway Administration, Washington, DC.
+
+**14**
+
+[http://www.](http://www.safetyanalyst.org) [safetyanalyst.org/](http://www.safetyanalyst.org)
+
+**15**
+
+G. Bahar and E. Hauer (2014), *Users Guide to Develop HSM SPF Calibration Factors*, NCHRP Project 20-7(332).
+
+**16**
+
+Susan Herbel, Lorrie Laing, Colleen McGovern (2010), *Highway Safety Improvement Program (HSIP) Manual*, FHWA-SA-09-029, Federal Highway Administration, Washington, DC.
+
+lane roads) using data from an entire jurisdiction or State. Figure 4-2 and Figure 4-3 show example SPFs where the points represent observed crashes at specific traffic volumes for individual sites, and the solid line represents the bestfit model (i.e., the SPF). If the relationship between exposure and crash frequency were linear, then the solid line would be a straight line instead of a curve. These two figures also demonstrate the nature of SPFs – each curve is different. For the rural, four lane freeways used in this example, multi-vehicle crashes rise exponentially with more traffic volume (Figure 4-2) but singlevehicle crashes behave differently; they level off with increasing levels of traffic volume (Figure 4-3).
+
+An SPF produces the average number of crashes that would be predicted for sites with a particular set of characteristics. By comparing a site's observed number of crashes with the predicted number of crashes from an SPF, it may be possible to identify sites that experience more crashes than one would expect from a site with that particular set of characteristics. Sites where the observed number of crashes is larger than the predicted number of crashes from an SPF warrant further review and diagnosis. Two measures in Table 4-4, level of service of safety (LOSS) and the excess predicted average crash frequency using SPFs, use the observed crash frequency and predicted frequency from an SPF to identify sites with promise.
+
+Ideally, SPFs should be estimated using data from the same jurisdiction as the site(s) being studied.**<sup>13</sup>** However, that may
+
+#### **SPF Example 1**
+
+Some States use Safety Analyst, a software tool from AASHTO, to identify sites that may benefit from a safety treatment.**<sup>14</sup>** The following is an SPF from Safety Analyst that predicts the total number of crashes on rural multilane divided roads:
+
+$$P = L \times e^{-5.05} \times (AADT)^{0.66}$$
+
+**P** is the total number of crashes in one year on a segment of length **L**.
+
+This is a relatively simple SPF where the predicted number of crashes per mile is a function of just AADT. For example, if the AADT is 45,000, then the predicted number of crashes for a one mile segment based on the SPF will be the following:
+
+> **P = 1 × e-5.05 × 450000.66 =7.55 crashes per year**
+
+not always be possible due to the availability of data or lack of statistical expertise. In that case, the SPFs developed from another jurisdiction could be calibrated using data from the jurisdiction with the study sites.**<sup>15</sup>**
+
+## **Avoiding bias due to regression-to-the-mean**
+
+As previously discussed, RTM describes the situation when periods with relatively high crash frequencies are followed by periods with relatively low crash frequencies simply due to the random nature of crashes. Figure 4-4 illustrates RTM, comparing the difference between short-term average and long-term average crash history.**<sup>16</sup>** Due to RTM, the short-term average is not a reliable estimate of the long-term crash propensity of a particular site. If an agency selects sites based
+
+#### **SPF Example 2**
+
+Bauer and Harwood**<sup>17</sup>** provide a more complex SPF for fatal and injury crashes on rural two lane roads. This model provides
+
+a crash prediction that is more tailored to characteristics of the site, such as curve radius and vertical grade of the road:
+
+$$\begin{aligned} N_{\text{FI}} &= \exp\left[-8.76 + 1.00 \times \ln(\text{AADT}) + 0.044 \times \text{G} + 0.19 \times \ln(2 \times 5730/\text{R}) \times \text{I}_{\text{HC}} \\ &+ 4.52 \times (1/\text{R})(1/\text{L}_{c}) \times \text{I}_{\text{HC}}\right] \end{aligned}$$
+
+**NFI** = fatal-and-injury crashes per mile per year
+
+**AADT** = annual average daily traffic (vehicles/day)
+
+**G** = absolute value of percent grade; 0% for level tangents; ≥ 1% otherwise
+
+**R** = curve radius (ft); missing for tangents
+
+**I HC** = horizontal curve indicator: 1 for horizontal curves; 0 otherwise
+
+**LC** = horizontal curve length (mi); not applicable for tangents
+
+**ln** = natural logarithm function
+
+**17**
+
+Bauer, K. and Harwood, D., Safety Effects of Horizontal Curve and Grade Combinations on Two-Lane Highways, Federal Highway Administration, Report No. FHWA-HRT-13-077, January 2014.
+
+on high short-term average crash history, crashes at those sites may be lower in the following years due to RTM, even if the agency does not install countermeasures at those sites.
+
+If RTM is not properly accounted for, sites with a randomly high count of crashes in the short term could be incorrectly identified as having a high potential for improvement, and vice versa. In this case, scarce resources may be inefficiently used on such sites while sites with a truly high potential for cost effective safety improvement remain unidentified.
+
+One approach to address RTM bias is to use the EB method. The EB method is a statistical method that combines the observed crash frequency (obtained from crash reports) with the predicted crash frequency (derived from the appropriate SPF) to calculate the expected crash frequency for a site of interest. This method pulls the crash count towards the mean, accounting for the RTM bias.
+
+The EB method is illustrated in Figure 4-5, which illustrates how the observed crash frequency is combined with the predicted crash frequency based on the SPF.**<sup>18</sup>** The
+
+![](_page_110_Figure_17.jpeg)
+
+**FIGURE 4-4**: Chart to illustrate RTM phenomenon *(Source: HSIP Manual, 2010)*
+
+**18**
+
+Susan Herbel, Lorrie Laing, Colleen McGovern (2010), *Highway Safety Improvement Program (HSIP) Manual*, FHWA-SA-09-029, Federal Highway Administration, Washington, DC.
+
+![](_page_111_Figure_0.jpeg)
+
+**FIGURE 4-5**: Schematic to illustrate the empirical Bayes method *(Source: HSIP Manual, 2010)*
+
+EB method is applied to calculate an expected crash frequency or corrected value, which lies somewhere between the observed value and the predicted value from the SPF.
+
+Mathematically, the expected number of crashes can be written as a function of the predicted value from the SPF and the observed crashes in the following manner:
+
+$$N_{\text{expected}} = w \times N_{\text{predicted}} + (1 - w) \times N_{\text{observed}}$$
+
+**Nexpected** <sup>=</sup> expected average crash frequency for a certain study period
+
+**w** = weighted adjustment to be placed on the SPF prediction (0 < w < 1)
+
+**Npredicted** <sup>=</sup> predicted average crash frequency predicted using an SPF for the study period under the given conditions
+
+**Nobserved** <sup>=</sup> observed crash frequency at the site over the study period
+
+The weight w is a function of the predicted crash frequency (Npredicted) and a statistical parameter called the overdispersion parameter of the SPF. Procedures to estimate the expected
+
+average crash frequency are provided in Part B of the HSM. For example, if the observed crash frequency in a particular site was nine crashes per year, the predicted crash frequency from the SPF was 6.4 crashes per year, and the w was 0.3, then Nexpected will be as follows:
+
+$$N_{\text{expected}} = 0.3 \times 6.4 + (1 - 0.3) \times 9$$
+  
+= 8.22 crashes per year
+
+**Equation <sup>1</sup>** We can prioritize sites by calculating the difference between the EB expected crashes at a particular site and the predicted crashes from an SPF. By comparing EB expected crashes at a particular site instead of observed crashes, we account for possible bias due to RTM.
+
+> The first eight measures presented in Table 4-4 do not account for possible bias due to RTM. Measure 9 (probability of specific crash types exceeding threshold proportion) and measure 10 (excess proportion of specific crash types) are not affected by RTM unless they are based on short-term crash history. Measure 11 (expected average crash frequency with EB adjustments), measure 12 (EPDO average crash frequency
+
+with EB adjustment), and measure 13 (excess expected average crash frequency with EB adjustment) account for possible bias due to RTM using the EB adjustments.
+
+## **Accounting for crash severity**
+
+The severity of crashes at a location can (and should) have a bearing on the priority of the site for safety treatment. Three of the measures in Table 4-4, measure 3 (EPDO average crash frequency), measure 4 (relative severity index), and measure 12 (EPDO average crash frequency with EB adjustment), directly account for crash severity. Measures 3 and 12 use the EPDO method, which converts all crashes to a common unit, namely property damage only (PDO) crashes. Using these measures, the analyst assigns points to each crash based on its crash severity level. A PDO crash typically receives one point and the points increase as the severity of the crash increases.
+
+While other measures do not explicitly mention severity, analysts can adapt any of the measures to consider any severity level. For example, an analyst could use crash frequency and focus on the frequency of fatal and severe injury crashes to priority rank sites. It is important to note that the severity distribution of crashes may be a function of site characteristics including AADT. For example, sections with higher AADT values may be associated with lower speeds and consequently fewer severe crashes.
+
+## **Step 2. Diagnosis**
+
+Diagnosis is the second step in the roadway safety management process, following network
+
+screening. Diagnosis is the process of further investigating the sites and issues identified from network screening. The intent of diagnosis is to identify crash patterns and the factors that contribute to crashes at the identified sites. Thorough diagnosis can also identify potential safety issues that have not yet manifested in crashes. Diagnosis often involves a review of the crash history, traffic operations, and general site conditions. While safety professionals could review these data from the office, a field visit provides the opportunity to observe road user behavior and site characteristics that are not available in the data. Sometimes, safety professionals may also conduct a field review at night or at other times that crash history has indicated to be of concern. It is important to diagnose the cause of the problem before developing potential countermeasures, just as a doctor examines symptoms to diagnose an underlying disease before formulating a prescription. Otherwise, resources may be misallocated if a countermeasure that does not target the underlying issues is selected and implemented.
+
+The Haddon Matrix is a framework to identify possible contributing factors (e.g., driver, vehicle, and roadway/ environment) which are crossreferenced against possible crash conditions before, during, and after a crash to identify possible reasons for events. This comprehensive understanding of crash contributing factors is important for the diagnosis of safety problems. An example of the Haddon Matrix is presented later under Countermeasure Selection on page 4-20.
+
+The HSM recommends that diagnosis include the following parts:
+
+- J **A review of safety data**
+- J **An assessment of supporting documentation**
+- J **An assessment of field conditions**
+
+## **Safety data review**
+
+An analyst can conduct a detailed review of the crash data from police reports to identify patterns. This could involve reviewing the crash type, severity, sequence of events, and contributing circumstances. Different visualization tools, such pie charts, bar charts, or tabular summaries, can be used to display various crash statistics. In addition to reviewing descriptive statistics, analysts can use various methods to identify underlying safety issues based on the recognition of crash patterns.
+
+One method would be to identify locations that have a proportion of a specific collision type relative to the total collisions that is higher than some average or threshold proportion value for similar road types. Kononov found that looking at the percentage distribution of collisions by collision type can reveal the "existence of collision patterns susceptible to correction" that may or may not be accompanied by the overrepresentation in expected or expected excess collisions.**<sup>19</sup>** Heydecker and Wu originally proposed this method.**<sup>20</sup>** The method is identical for different location types. However, only similar location types should be analyzed together because collision patterns will naturally differ. For example, the collision patterns are different
+
+for stop-controlled intersections, signalized intersections, and twolane roads, so the method would be applied separately to the three types of facilities and separately for urban and rural environments. Another method would be to investigate sites that experience a gradual or sudden increase in mean collision frequency.**<sup>21</sup>**
+
+Following the detailed review of the crash data, the analyst can create collision diagrams, condition diagrams, and crash maps to summarize the crash information by location. A collision diagram is a tool to identify and display crash patterns. Many resources, including the HSM, provide guidance on developing collision diagrams. Examples of collision diagrams are shown in Figure 4-6 and Figure 4-7. Each crash at the site is displayed according to where it occurred, what type of crash it was, how severe it was, and various other characteristics. An analyst uses symbols to visually represent many of these characteristics.
+
+Condition diagrams include a drawing with information about the site characteristics including information about the roadway (e.g., number of lanes, presence of medians, pedestrian and bicycle facilities, shoulder information), surrounding land uses, and pavement conditions. Condition diagrams can be overlaid on top of collisions diagrams to gain further insight to the crash patterns.
+
+Crash mapping involves the use of geographic information systems (GIS) to integrate information from the roadway network with information from geocoded crash data. If the geocoded crash data are
+
+Kononov, J. (2002), Identifying Locations with Potential for Collision Reductions: Use of Direct Diagnostics and Pattern Recognition Methodologies, *Transportation Research Record* 
+
+*1784*, pp. 153-158.
+
+#### **20**
+
+**19**
+
+Heydecker, B. J., and J. Wu (1991), Using the Information in Road Accident Records Proc., 19th PTRC Summer Annual Meeting, London.
+
+#### **21**
+
+Hauer, E. (1996), Detection of Safety Deterioration in a Series of Accident Counts. *Transportation Research Record 1542*, 38-43.
+
+Hauer, E. (1996), Statistical Test of the Difference between Expected Accident Frequencies, *Transportation Research Record 1542*, 24-29.
+
+![](_page_114_Figure_0.jpeg)
+
+![](_page_114_Figure_1.jpeg)
+
+accurate, then crash mapping can provide valuable insights into crash locations and crash patterns.
+
+## **Assess supporting documentation**
+
+This step involves a review of documented information about the site along with interviews of local transportation professionals to obtain additional perspectives on the safety data review from the previous step. Examples of supporting documentation include traffic volumes, construction plans and design criteria, photos and maintenance logs, weather patterns, and recent traffic studies in the area.
+
+## **Assess field conditions**
+
+Field observations are useful for supplementing crash data and can help the analyst understand the behavior of drivers, pedestrians, and bicyclists. The first stage of the field investigation should be an on-site examination of a road user's experience. Those conducting the assessment should travel through the site at different times of the day using different modes of transportation (e.g., driving, walking, and bicycling). Assessors should observe the mix of vehicle traffic and other road users. They should also observe traffic movements, conflicts, and
+
+| ROAD SAFETY AUDIT                                                                              | TRADITIONAL SAFETY REVIEW                                                               |
+|------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------|
+| Independent, multi-disciplinary team                                                           | Safety review team within the project team<br>with only safety and/or design experience |
+| Considers all potential road users (pedestrians,<br>bicyclists, motor vehicles, transit users) | Often concentrates only on motor vehicles                                               |
+| Accounts for road user capabilities<br>and limitations                                         | Safety reviews do not normally<br>consider human factor issues                          |
+| Always generates a formal report                                                               | Often does not generate a formal report                                                 |
+| Always generates a formal response report                                                      | Often does not generate a formal<br>response report                                     |
+| TABLE 4-5: Differences between Road Safety Audit and Traditional Road Safety Review            |                                                                                         |
+
+**TABLE 4-5**: Differences between Road Safety Audit and Traditional Road Safety Review *(Source: FHWA)*
+
+operating speeds. Those conducting the field review could determine whether the road and intersection characteristics are consistent with driver expectation and if roadside recovery zones are clear and traversable.
+
+## **Road safety audits**
+
+One method to assess field conditions is a road safety audit (RSA). This is the formal safety performance examination of an existing or future road or intersection by an independent, multidisciplinary team. An RSA qualitatively estimates and reports on existing and potential road safety issues and identifies opportunities for safety improvements for all road users. FHWA encourages States, local jurisdictions and tribal governments to integrate RSAs into the project development process for new roads and intersections and to conduct RSAs on existing ones.
+
+The purpose of an RSA is to answer the following questions:
+
+- J **What elements of the road may present a safety concern, and to what extent, to which road users, and under what circumstances?**
+- J **What opportunities exist to eliminate or mitigate identified safety concerns?**
+
+The multidisciplinary audit team consists of people who represent different areas of expertise, such as engineering (e.g., design, traffic, and maintenance), law enforcement, safety educators, public officials, community traffic safety advocates, and others. Any phase of project development (planning, preliminary engineering, design, construction) and any sized project from minor intersection and roadway retrofits to mega-projects are eligible for an RSA.
+
+Most State DOTs have established safety review processes. However, RSAs and a traditional safety reviews are different. Table 4-5 shows the difference between an RSA and a traditional safety review.**<sup>22</sup>**
+
+### **22**
+
+"Road Safety Audits (RSA)," accessed August 7, 2013, [http://safety.fhwa.](https://safety.fhwa.dot.gov/rsa/) [dot.gov/rsa/](https://safety.fhwa.dot.gov/rsa/)
+
+### **International Road Assessment Programme**
+
+The International Road Assessment Programme (iRAP) conducts safety inspections on high-risk roads in more than 70 countries. The iRAP inspectors perform a detailed road survey, focusing on road attributes that are known to be associated with crash risk. These include intersection design, number of lanes, roadside hazards, and provisions for pedestrian crossings. The inspectors use these data to develop a star rating, which reflects the level of safety of the road, and provide detailed feedback to the government agency in the form of an assessment report. iRAP also provides a Road Safety Toolkit, which helps engineers, planners, and policy makers develop safety plans for all road users.**23**
+
+## **Step 3. Countermeasure selection**
+
+After diagnosing the safety issues at the site, analysts select countermeasures to address the contributing factors for observed crashes. The first part of countermeasure selection is to identify countermeasures to target the underlying safety issues. Analysts can use tools like the Haddon Matrix and resources like the NCHRP Report 500 series to identify targeted countermeasures to address or mitigate underlying contributing factors.
+
+## **Identifying contributing factors**
+
+The Haddon Matrix is a tool originally developed for injury prevention, but it is directly applicable to highway safety in both diagnosis and countermeasure selection.**<sup>24</sup>** The Haddon Matrix is useful to gain a comprehensive understanding of crash contributing factors. Analysts can use the Haddon Matrix to identify human, vehicle, and roadway factors contributing to the frequency and severity of crashes prior to, during, and after the crash event. Then, analysts can identify targeted reactive and proactive countermeasures to address or mitigate the underlying contributing factors for the given site. Chapter 6 of the 1st edition of the HSM provides further discussion of the Haddon Matrix.
+
+The Haddon Matrix is comprised of nine cells to identify human, vehicle, and roadway factors contributing to the target crash type or severity outcome before, during, and after the crash. Precrash factors speak to the factors or actions prior to the crash that contributed to the occurrence of the crash. Crash factors speak to those factors or actions that occurred at the moment of the crash. Post-crash factors speak to factors that come into play after the crash that affect the severity of the injuries or speed of response. Examples of human factors include fatigue, inattention, age, and failure to wear a seat belt. Vehicle factors include bald tires, airbag operations, and worn brakes. Examples of roadway factors include pavement friction, weather, grade, and limited sight distance.
+
+Table 4-6 is an example application of the Haddon Matrix from the Highway Safety Improvement Program (HSIP) Manual for crashes in an urban area.**<sup>25</sup>** The top-left cell identifies driver behaviors or characteristics that may contribute to the likelihood or the severity of a collision, such as poor vision or reaction time, alcohol consumption, speeding, and risk taking. These
+
+**23**
+
+[org/](http://toolkit.irap.org/)
+
+<http://www.irap.net/> [http://toolkit.irap.](http://toolkit.irap.org/)
+
+**24**
+
+Haddon, W., Jr. (1972). A logical framework for categorizing highway safety phenomena and activity. *Journal of Trauma 12*: 193–207.
+
+**25**
+
+Susan Herbel, Lorrie Laing, Colleen McGovern (2010), *Highway Safety Improvement Program (HSIP) Manual,* FHWA-SA-09-029, Federal Highway Administration, Washington, DC.
+
+*Highway Safety Improvement Program Manual.*  Federal Highway Administration, Washington, D.C., 2010, Chapter 3
+
+factors should be considered when selecting countermeasures. For example, based on these human factors, successful countermeasures may be those that improve visibility or reduce speeding. The matrix in its entirety provides a range of potential issues that can be addressed through a variety of countermeasures including education, enforcement, engineering, and emergency response solutions.
+
+## **Countermeasure resources and tools**
+
+Diagnosing a roadway safety problem and identifying effective countermeasures is a skill developed through education, training, research, and experience. Many resources are available to help transportation professionals analyze and develop countermeasures. Since the transportation field continuously generates new knowledge and countermeasure approaches, it is
+
+important to stay informed of the available resources and tools.**<sup>26</sup>**
+
+Some of the most useful resources and tools for countermeasure guidance and selection are listed below (alphabetically):
+
+- J **Bicycle Safety Guide and Countermeasure Selection System (BIKESAFE, www.pedbikesafe. org/bikesafe)** – This resource provides practitioners with the latest information available for improving the safety and mobility of those who bike. The online tools provide the user with a list of possible engineering, education, or enforcement treatments to improve bicycle safety and/or mobility based on user input about a specific location.
+- J **Countermeasures That Work: A Highway Safety Countermeasure Guide for State Highway Safety Offices** – This document serves as a basic reference to help state
+
+| PERIOD        | HUMAN                                                                 | VEHICLE/<br>EQUIPMENT                                            | PHYSICAL<br>ENVIRONMENT                    | SOCIO<br>ECONOMIC                                                   |
+|---------------|-----------------------------------------------------------------------|------------------------------------------------------------------|--------------------------------------------|---------------------------------------------------------------------|
+| PRE<br>CRASH  | Poor vision or<br>reaction time,<br>alcohol, speeding,<br>risk taking | Failed brakes,<br>missing lights,<br>lack of warning<br>systems  | Narrow<br>shoulders,<br>ill-timed signals  | Cultural norms<br>permitting<br>speeding, red<br>light running, DUI |
+| CRASH         | Failure to<br>use occupant<br>restraints                              | Malfunctioning<br>safety belts,<br>poorly engineered<br>air bags | Poorly designed<br>guardrails              | Lack of<br>vehicle design<br>regulations                            |
+| POST<br>CRASH | High<br>susceptibility,<br>alcohol                                    | Poorly designed<br>fuel tanks                                    | Poor emergency<br>communication<br>systems | Lack of support<br>for EMS and<br>trauma systems                    |
+
+**TABLE 4-6**: Haddon Matrix for crashes in an urban area *(Source: HSIP Manual)*
+
+highway safety offices (SHSOs) select effective, evidence-based countermeasures for traffic safety problem areas related to user behaviors, such as alcohol-impaired and drugged driving, seat belts and child restraints, and aggressive driving and speeding.**<sup>27</sup>**
+
+- J **Crash Modification Factors Clearinghouse (www. cmfclearinghouse.org)** – This website offers transportation professionals a central, online repository of crash modification factors (CMFs) that indicate the safety effect on crashes due to infrastructure improvements. The website also provides additional information and resources related to CMFs. This site is funded by FHWA.
+- J **FHWA Proven Countermeasures (safety.fhwa.dot.gov/ provencountermeasures)** – FHWA regularly compiles a list of countermeasures that have been shown to be effective in reducing crashes but have yet to be widely applied on a national basis.
+- J **Handbook for Designing Roadways for the Aging Population (safety. fhwa.dot.gov/older\_users/ handbook)** – This FHWA guide provides practitioners with a practical information source that links aging road user performance to highway design, operational, and traffic engineering features. This handbook supplements existing standards and guidelines in the areas of highway geometry, operations, and traffic control devices.**<sup>28</sup>**
+
+- J **Highway Safety Manual (www. highwaysafetymanual.org)** – This document provides science-based knowledge and tools to conduct safety analyses, allowing for safety to be quantitatively evaluated alongside other transportation performance measures, such as traffic operations, environmental impacts, and construction costs.
+- J **National Cooperative Highway Research Program (NCHRP) Report 500 Series (safety. transportation.org/guides.aspx)** – This resource is a collection of 23 reports in which relevant information is assembled into single concise volumes, each pertaining to specific types of highway crashes (e.g., run-off-the-road, head-on) or contributing factors (e.g., aggressive driving) related to behaviors, vehicles, and roadways. Countermeasures are categorized as proven, tried, and experimental.
+- J **Pedestrian Safety Guide and Countermeasure Selection System (PEDSAFE, www.pedbikesafe. org/pedsafe)** – This resource provides practitioners with the latest information available for improving the safety and mobility of those who walk. The online tools provide the user with a list of possible engineering, education, or enforcement treatments to improve pedestrian safety and/ or mobility based on user input about a specific location.
+
+**27**
+
+Goodwin, A., Thomas, L., Kirley, B., Hall, W., O'Brien, N., & Hill, K. (2015). *Countermeasures that work: A highway safety countermeasure guide for State highway safety offices*, Eighth edition. (Report No. DOT HS 812 202). Washington, DC: National Highway Traffic Safety Administration. Accessed February 2017 at [www.nhtsa.](http://www.nhtsa.gov/staticfiles/nti/pdf/812202-CountermeasuresThatWork8th.pdf) [gov/staticfiles/](http://www.nhtsa.gov/staticfiles/nti/pdf/812202-CountermeasuresThatWork8th.pdf) [nti/pdf/812202-](http://www.nhtsa.gov/staticfiles/nti/pdf/812202-CountermeasuresThatWork8th.pdf) [Countermeasures](http://www.nhtsa.gov/staticfiles/nti/pdf/812202-CountermeasuresThatWork8th.pdf) [ThatWork8th.pdf](http://www.nhtsa.gov/staticfiles/nti/pdf/812202-CountermeasuresThatWork8th.pdf)
+
+**28**
+
+Brewer, M., D. Murillo, A. Pate (2014). *Handbook for Designing Roadways for the Aging Population*, Report No. FHWA-SA-14-015, Federal Highway Administration, Washington, D.C.
+
+**29**
+
+[www.](http://www.cmfclearinghouse.org) [cmfclearinghouse.](http://www.cmfclearinghouse.org) [org](http://www.cmfclearinghouse.org)
+
+## **Identifying and selecting countermeasures**
+
+After identifying potential countermeasures to target the underlying issues, safety professionals must estimate the safety impact of countermeasures, individually and in combination. It is important to consider positive and negative safety impacts. Subsequent steps of the roadway safety management process (i.e., economic appraisal and project prioritization) include the consideration of other parameters, such as constructability, environmental impacts, and cost.
+
+The agency that will be making the final decision on countermeasure selection should make sure to coordinate with other safety partners to ensure that the countermeasure is appropriate for all parties. For example, a DOT should coordinate with law enforcement and emergency response to make sure that a proposed engineering installation will interfere with enforcement activities or impede emergency responders.
+
+For infrastructure improvements, CMFs associated with different countermeasures provide a mechanism for determining the safety effect of different countermeasures. A CMF is a multiplicative factor used to compute the expected number of crashes after implementing a given countermeasure at a specific site.
+
+- J If the CMF for a particular treatment is less than 1.0, then that countermeasure is expected to reduce crashes.
+- J If the CMF for a particular treatment is greater than 1.0,
+
+### **Guidance on CMF application**
+
+FHWA provides an extensive selection of guidance on selecting and applying CMFs through the CMF Clearinghouse (**www.cmfclearinghouse.org**). They present answers to frequently asked questions, such as "How can I apply multiple CMFs?" and "How do I choose between CMFs in my search results that have the same star rating but different CMF values?" The website also houses an archive of annual webinars in which experienced CMF users talk about issues related to applying CMFs in real world situations.
+
+then that countermeasure is expected to increase crashes.
+
+J A CMF of 1.0 implies that a countermeasure will not have any effect on safety.
+
+For example, if the expected number of crashes without a countermeasure is 5.6 crashes per year, and the CMF for the particular countermeasure is 0.8, then the expected number of crashes with the countermeasure is:
+
+#### **5.6 crashes per year x 0.8 = 4.48 crashes per year**
+
+It is important to recognize that some countermeasures may decrease some types of crashes but increase other types. For example, installing a traffic signal would be expected to decrease severe collisions, such as right angle and left turn crashes, but it would be expected to increase less severe crashes, such as rear ends.
+
+The CMF Clearinghouse and the first edition of the HSM provide CMFs for a variety of countermeasures.**<sup>29</sup>** Only those CMFs that passed a set of inclusion criteria based on quality and reliability were included in the HSM. The CMFs in the clearinghouse are provided for any published study, regardless of quality, and are continuously updated based on the latest research. The CMFs in the clearinghouse are reviewed and given a star quality rating ranging from one to five stars, based on the quality of the study. Higher stars imply a better quality CMF.
+
+CMFs should be applied to situations that closely match those from which the CMF was developed. Several variables can be used to match a CMF to a given scenario including roadway type, area type, segment or intersection geometry, intersection traffic control, and traffic volume. However, it is
+
+critical for practitioners to use engineering judgment when a CMF is not available for the situations encountered as there are some cases for which a CMF that was developed for different conditions might be the best available.
+
+## **Step 4. Economic appraisal**
+
+An economic appraisal of alternative countermeasures should be conducted to ensure that safety funds are being used as efficiently as possible. This appraisal helps transportation agencies achieve their desired safety performance the fastest and at the lowest possible cost. An agency can compare
+
+#### **Calculating benefits due to crash reduction**
+
+A city has a stop-controlled intersection with an expected crash frequency of 10 crashes per year, consisting of one A-injury crash, one B-injury crash, two C-injury crashes, and six PDO crashes.
+
+The city is considering installing a roundabout at the intersection. Based on a search of the FHWA CMF Clearinghouse, they decide that they will use a CMF of 0.19 in the calculation of the crash reduction benefit.**<sup>30</sup>** This CMF applies only to serious and minor injury crashes, so they do not use it to estimate any reduction to fatal or PDO crashes (see note).
+
+They multiply the CMF by the expected crashes before roundabout installation to determine the expected crashes after installation:
+
+|     | CRASH SEVERITY                                         | FATAL | A<br>INJURY | B<br>INJURY | C<br>INJURY | PDO |
+|-----|--------------------------------------------------------|-------|-------------|-------------|-------------|-----|
+| I   | Expected Crashes per Year<br>before Roundabout         | 0     | 1           | 1           | 2           | 6   |
+| II  | CMF                                                    | N/A   | 0.19        | 0.19        | 0.19        | N/A |
+| III | Expected Crashes per Year<br>after Roundabout (I x II) | 0     | 0.19        | 0.19        | 0.38        | 6   |
+| IV  | Crash reduction benefit (I<br>minus III)               | 0     | 0.81        | 0.81        | 1.62        | 0   |
+
+Thus, the benefit of a roundabout installation is expected to be a reduction of 0.81 A-injury crashes, 0.81 B-injury crashes, and 1.62 C-injury crashes per year.
+
+*NOTE: A roundabout would also likely bring a reduction to fatal and PDO crashes (i.e., additional CMFs could be incorporated), but the example has been simplified to a single CMF for illustration purposes.*
+
+**30**
+
+Rodegerdts et al., "NCHRP Report 572: Applying Roundabouts in the United States." Washington, D.C., Transportation Research Board, National Research Council, (2007)
+
+the benefits expected from the countermeasure to the estimated costs of the countermeasure.
+
+Some safety countermeasures have a higher-cost value than others. Geometric improvements to the road, such as straightening a tight curve to reduce run-off-road crashes, tend to be very expensive. Installing a curve warning sign and in curve delineation may address the same problem, but at a much lower cost. Although both countermeasures address the same problem, the actual safety benefit may not be the same. Safety professionals take the relative costs and benefits into consideration when prioritizing among countermeasures. Part of calculating the cost of a countermeasure is considering how those costs vary over time, while taking into consideration any maintenance costs and long term effectiveness.
+
+## **Estimating benefits**
+
+The primary benefit of a countermeasure is a reduction in crash frequency or severity. To estimate the safety benefits, a safety professional should use CMFs, such as those discussed in the countermeasure selection step. CMFs can be applied to the actual crashes or expected crashes based on the EB method. Expected crashes are preferred because they account for possible bias due to RTM. The estimated change in crashes represents the expected benefit from the countermeasure.
+
+For each proposed countermeasure, the change in crash frequency and/ or severity needs to be converted to monetary value, based on the monetary value of the type of
+
+| INJURY<br>SEVERITY LEVEL | COMPREHENSIVE<br>CRASH COST |
+|--------------------------|-----------------------------|
+| Fatality (K)             | \$4,008,900                 |
+| Disabling Injury (A)     | \$216,000                   |
+| Evident Injury (B)       | \$79,000                    |
+| Fatal/Injury (K/A/B)     | \$158,200                   |
+| Possible Injury (C)      | \$44,900                    |
+| PDO (O)                  | \$7,400                     |
+
+**TABLE 4-7**: Crash Costs by Severity Level in the Highway Safety Manual, 1st ed.
+
+crashes reduced. This monetary value is also called the crash cost. Crash costs are based on costs to society, such as lost productivity, medical costs, legal and court costs, emergency service costs, insurance administration costs, congestion costs, property damage, and workplace losses.**<sup>31</sup>**
+
+The benefit from the countermeasure is the sum of the crash costs for crashes prevented by the countermeasure. Assigning costs to crashes is a topic that is under constant discussion and revision nationwide. States differ widely in the dollar amount that they assign to crashes, though all States apply higher values to more severe crashes. The CMF Clearinghouse provides a synthesis of crash costs that are used by various States.**<sup>32</sup>**
+
+Additionally, the first edition of the HSM provided a list of crash costs by severity level (Table 4-7). However, since the publication of the first HSM in 2010, the USDOT has issued periodic recommendations that dramatically raised the values. For instance, the monetary value of a
+
+### **31**
+
+Blincoe, L. J., Miller, T. R., Zaloshnja, E., and Lawrence, B. A. The economic and societal impact of motor vehicle crashes, 2010. (Revised), National Highway Traffic Safety Administration, Report No. DOT HS 812 013, Washington, DC, May 2015.
+
+#### **32**
+
+[http://www.](http://www.cmfclearinghouse.org/resources_servlifecrashcostguide.cfm) [cmfclearinghouse.](http://www.cmfclearinghouse.org/resources_servlifecrashcostguide.cfm) [org/resources\\_](http://www.cmfclearinghouse.org/resources_servlifecrashcostguide.cfm) [servlifecrash](http://www.cmfclearinghouse.org/resources_servlifecrashcostguide.cfm) [costguide.cfm](http://www.cmfclearinghouse.org/resources_servlifecrashcostguide.cfm)
+
+fatal crash was listed as \$4 million in the HSM, but recommended as over \$9 million in a 2013 policy memo from USDOT.**<sup>33</sup>**
+
+Although countermeasures are primarily expected to reduce crashes, there might be other benefits, including reduced travel times or lower fuel consumption. For example, a roundabout can decrease total delay at an intersection if applied and configured properly. An AASHTO publication provides guidance on estimating these other non-safety benefits.**<sup>34</sup>**
+
+## **Estimating costs**
+
+The costs of the proposed countermeasure include the startup cost and the ongoing operational and maintenance costs. These costs can usually be estimated based on costs of materials, labor cost per personhour, cost of additional right-ofway, and past experience with
+
+similar countermeasures. Table 4-8 illustrates the types of startup and ongoing costs that would be incurred for various countermeasures.
+
+## **Service life**
+
+Another important consideration when calculating the benefits and costs of a countermeasure is the length of time that the countermeasure will last. This is referred to as the service life. Countermeasures, such as road edgelines or pavement reflectors, will have a much shorter service life (e.g., three to five years) than countermeasures, such as traffic signal installation or sidewalk construction (e.g., 20 years or more). Many States have a standard list of the service life values used for common countermeasures. The CMF Clearinghouse provides a survey of service life values used by various States for many different countermeasures.**<sup>35</sup>**
+
+Trottenberg, Polly, and Robert Rivkin, "Revised Departmental Guidance 2013: Treatment of the Value of Preventing Fatalities and Injuries," USDOT Office of the Secretary of Transportation, 2013.
+
+**34**
+
+User and Non-User Benefit Analysis for Highways, American Association of State Highway Transportation Officials, September 2010
+
+**35**
+
+[http://www.](http://www.cmfclearinghouse.org/resources_servlifecrashcostguide.cfm) [cmfclearinghouse.](http://www.cmfclearinghouse.org/resources_servlifecrashcostguide.cfm) [org/resources\\_](http://www.cmfclearinghouse.org/resources_servlifecrashcostguide.cfm) [servlifecrash](http://www.cmfclearinghouse.org/resources_servlifecrashcostguide.cfm) [costguide.cfm](http://www.cmfclearinghouse.org/resources_servlifecrashcostguide.cfm)
+
+#### **Calculating monetary benefit of crash reduction**
+
+The previous example showed that a city calculated a crash savings of 0.81 A-injury crashes, 0.81 B-injury crashes, and 1.62 C-injury crashes per year by installing a roundabout. The city has examined guidance from the HSM, guidance from
+
+USDOT, and experiences of other cities and States and determined a standard set of crash costs they will use for all benefit/ cost calculations. They apply these costs to determine the monetary benefit of the expected crash reductions:
+
+|    | CRASH SEVERITY                                  | FATAL   | A<br>INJURY | B<br>INJURY | C<br>INJURY | PDO      |
+|----|-------------------------------------------------|---------|-------------|-------------|-------------|----------|
+| IV | Crash Reduction Benefit                         | 0       | 0.81        | 0.81        | 1.62        | 0        |
+| V  | This City's Standard Crash Cost                 | \$5 mil | \$400,000   | \$100,000   | \$60,000    | \$10,000 |
+| VI | Monetary benefit of crash<br>reduction (IV x V) | 0       | \$324,000   | \$81,000    | \$97,200    | 0        |
+
+Thus, the city expects a total monetary benefit of \$324,000+\$81,000+\$97,200 = **\$502,000** per year due to reduction in crashes.
+
+| COUNTERMEASURE                              | STARTUP COST                                                                                                           | ONGOING COST<br>DURING SERVICE LIFE                                               |  |
+|---------------------------------------------|------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------|--|
+| Install curve<br>warning sign               | Low – sign material, minimal<br>labor for installation                                                                 | None                                                                              |  |
+| Install roundabout                          | High – Design plan, purchase<br>of additional right-of-way,<br>material, labor, traffic control<br>during construction | Low – maintenance of<br>grass and decorative<br>vegetation                        |  |
+| Install traffic signal                      | High – Timing plan, material,<br>labor for installation, traffic<br>control during construction                        | Moderate – electricity,<br>bulb replacements, repairs,<br>modifications to timing |  |
+| TABLE 4-8: Examples of Countermeasure Costs |                                                                                                                        |                                                                                   |  |
+
+The service life is used in the calculation of the present value of the benefits and costs of the proposed countermeasure. The calculation of present value includes a discount rate that reflects the time value of money (i.e., present dollars are worth more than future dollars). Present value of countermeasure benefits is calculated as follows:
+
+$$PV = A \times \frac{(1+i)^{y}-1}{i \times (1+i)^{y}}$$
+
+**PV =** present value of benefits
+
+**A =** annual benefit (i.e., monetary value of crashes prevented)
+
+**i =** discount rate
+
+**y =** service life of countermeasure
+
+Calculating present value in this way assumes a uniform annual benefit. The HSIP Manual demonstrates how to calculate present value if the benefits or costs each year are not the same.**<sup>36</sup>**
+
+The present value of annual costs (i.e., operational and maintenance costs) can be calculated in the same manner as for benefits. However, for
+
+### **Calculating the present value of a crash reduction benefit**
+
+From the previous example, the city plans to install a roundabout and expects to see a benefit from crash reductions resulting in savings of \$502,000 per year. They estimate that the roundabout will have a service life of 20 years and they determine that a discount rate of 5% is appropriate. They calculate the present value of benefits as:
+
+$$PV = $502,000 \times \frac{(1+0.05)^{20}-1}{0.05 \times (1+0.05)^{20}}$$
+$$= $6,256,030$$
+
+costs, the final present value must also include the startup cost in the year of installation (see examples in Table 4-8).
+
+## **Methods for economic appraisal**
+
+There are several methods for using the values of estimated benefits and costs to evaluate the economic effectiveness of safety improvement projects at a particular site. In particular, these methods
+
+**36**
+
+Herbel, Susan, Lorrie Laing, Colleen McGovern, Highway Safety Improvement Program (HSIP) Manual, Federal Highway Administration, FHWA-SA-09-029, January 2010
+
+are useful in situations where a safety professional is considering several alternatives and desires to choose the countermeasure with the greatest benefit for the cost.
+
+The HSIP Manual contains guidance on three methods - net present value, benefit/cost ratio, and cost effectiveness index.**<sup>37</sup>** Net present value (NPV) is generally regarded as the most economically appropriate method, though the other two methods have certain advantages, as discussed below. The following sections provide quoted guidance from the HSIP Manual on economic appraisal.
+
+#### **Net Present Value**
+
+The NPV method, also called the net present worth (NPW) method, expresses the difference between the present values of benefits and costs of a safety improvement project. The NPV method has two basic functions: 1) determining which countermeasure(s) is/are most cost efficient based on the highest NPV and 2) determining whether a countermeasure's benefits are greater than its costs (i.e., the project has a NPV greater than zero).
+
+The formula for NPV is:
+
+**NPV = PVB − PVC**
+
+**PVB =** Present value of benefits
+
+**PVC =** Present value of costs
+
+A countermeasure will result in a net benefit if the NPV is greater than zero. Table 4-9 summarizes the NPV calculations of four alternative countermeasures.
+
+For Alternative A, the NPV can be calculated as follows:
+
+**NPV = \$1,800,268 − \$500,000 = \$1,300,268**
+
+The same calculation is performed for the other three countermeasure alternatives, and rank each countermeasure based on its NPV. As shown, all four alternatives are economically justified with a NPV greater than zero. However, Alternative B has the greatest NPV for this site based on this method.
+
+#### **Benefit/Cost Ratio and Analysis**
+
+The benefit/cost ratio (BCR) is the ratio of the present value of a project's benefits to the present value of a project's costs.
+
+|  | 37 |
+|--|----|
+|  |    |
+
+Herbel, Susan, Lorrie Laing, Colleen McGovern, Highway Safety Improvement Program (HSIP) Manual, Federal Highway Administration, FHWA-SA-09-029, January 2010.
+
+| ALTERNATIVE<br>COUNTERMEASURE | PRESENT<br>VALUE OF<br>BENEFITS (I) | PRESENT<br>VALUE OF<br>COSTS (II) | NET<br>PRESENT<br>VALUE (I-II) | ALTERNATIVE<br>RANK |
+|-------------------------------|-------------------------------------|-----------------------------------|--------------------------------|---------------------|
+| A                             | \$1,800,268                         | \$500,000                         | \$1,300,268                    | 3                   |
+| B                             | \$3,255,892                         | \$1,200,000                       | \$2,055,892                    | 1                   |
+| C                             | \$3,958,768                         | \$2,100,000                       | \$1,858,768                    | 2                   |
+| D                             | \$2,566,476                         | \$1,270,000                       | \$1,296,476                    | 4                   |
+
+**TABLE 4-9**: Net Present Value *(Source: HSIP Manual, Chapter 4)*
+
+The formula for BCR is:
+
+**BCR = PVB / PVC**
+
+**PVB =** Present value of benefits
+
+**PVC =** Present value of costs
+
+Table 4-10 shows an example of using BCR to prioritize four alternatives.
+
+A project with a BCR greater than 1.0 indicates that the benefits outweigh the costs. However, the BCR is not applicable for comparing various countermeasures or multiple projects at various sites; this requires an incremental benefit/cost analysis.
+
+An incremental benefit/cost analysis provides a basis of comparison of the benefits of a project for the dollars invested. It allows the analyst to compare the economic effectiveness of one project against another; however, it does not consider budget constraints. Optimization methods are best for prioritizing projects based on monetary constraints. An in-depth explanation of incremental benefit/cost analysis and an example is provided in Chapter 4 of the HSIP Manual.
+
+When conducting a benefit/
+
+cost analysis, transportation professionals compare all of the benefits associated with a countermeasure (e.g., crash reduction), expressed in monetary terms, to the cost of implementing the countermeasure. A benefit/cost analysis provides a quantitative measure to help safety professionals prioritize countermeasures or projects and optimize the return on investment.
+
+#### **Cost-Effectiveness Index**
+
+In situations where it is not possible or practical to monetize countermeasure benefits, transportation professionals can use the cost-effectiveness index method in lieu of the NPV or BCR. Cost-effectiveness is simply the amount of money invested divided by the crashes reduced. The result is a number that represents the cost of the avoided crashes of a certain countermeasure. The countermeasure with the lowest value is the most cost-effective and therefore ranked first.
+
+#### **Cost-Effectiveness Index = PVC/CR**
+
+**PVC =** Present value of project cost
+
+| ALTERNATIVE<br>COUNTERMEASURE | PRESENT<br>VALUE OF<br>BENEFITS (I) | PRESENT<br>VALUE OF<br>COSTS (II) | BENEFIT/<br>COST<br>RATIO (I/II) | ALTERNATIVE<br>RANK |
+|-------------------------------|-------------------------------------|-----------------------------------|----------------------------------|---------------------|
+| A                             | \$1,800,268                         | \$500,000                         | 3.6                              | 1                   |
+| B                             | \$3,255,892                         | \$1,200,000                       | 2.7                              | 2                   |
+| C                             | \$3,958,768                         | \$2,100,000                       | 1.9                              | 4                   |
+| D                             | \$2,566,476                         | \$1,270,000                       | 2.0                              | 3                   |
+
+**TABLE 4-10**: Example of Benefit/Cost Ratio Prioritization *(Source: HSIP Manual, Chapter 4)*
+
+| ALTERNATIVE<br>COUNTERMEASURE | PRESENT<br>VALUE OF<br>COSTS | TOTAL<br>CRASH<br>REDUCTION | COST<br>EFFECTIVE-<br>NESS INDEX | ALTERNATIVE<br>RANK |
+|-------------------------------|------------------------------|-----------------------------|----------------------------------|---------------------|
+| A                             | \$500,000                    | 43                          | \$11,628                         | 1                   |
+| B                             | \$1,200,000                  | 63                          | \$19,048                         | 3                   |
+| C                             | \$2,100,000                  | 70                          | \$30,000                         | 4                   |
+| D                             | \$1,270,000                  | 73                          | \$17,397                         | 2                   |
+
+**TABLE 4-11**: Cost-Effectiveness Index *(Source: HSIP Manual, Chapter 4)*
+
+#### **CR =** Total crash reduction
+
+The Cost-Effectiveness Index is a simple and quick method that provides an indication of a project's value. Transportation professionals can use this formula and compare its results with other safety improvement projects. The Cost-Effectiveness Index method, however, does not account for value differences between reductions in fatal crashes compared to injury crashes, and whether a project is economically justified.**<sup>38</sup>**
+
+Table 4-11 summarizes the calculations using the costeffectiveness index method to rank alternative countermeasures, given the present value of the costs and the total crash reduction.
+
+For Alternative A, calculate the costeffectiveness index as follows:
+
+#### **Cost-effectiveness index = 500,000/43 = 11,628**
+
+Calculate the Cost-Effectiveness Index for the remaining alternatives and rank each countermeasure based on its Cost-Effectiveness Index value. With this method, the lowest index is the highest priority and
+
+therefore ranked first. Alternative A is ranked first, since it has the lowest cost associated with each crash reduction.
+
+The above example uses the number of crashes to determine the costeffectiveness index. Transportation professionals can use this same method using EPDO crash numbers, which has the advantage of considering severity.
+
+## **Step 5. Project prioritization**
+
+If a transportation agency is considering installing countermeasures at one or more sites out of a group of potential sites, they will need to prioritize which projects they will implement. Ideally, the agency would implement all projects that bring a safety benefit (e.g., all those with a NPV greater than zero or a BCR greater than one). However, all agencies work within a limited budget and must prioritize where safety funds are spent.
+
+The agency can use steps 1 through 4 of this process to determine which countermeasure(s) would be used at each potential treatment
+
+**38**
+
+*Highway Safety Improvement Program Manual.* Federal Highway Administration (Washington D.C., 2010), Chapter 4
+
+site and to conduct an economic appraisal of the expected effect of the countermeasure. The next step is to determine project priorities. The HSM discusses how projects can be prioritized by economic effectiveness, incremental benefit/cost analysis, or various optimization methods.
+
+## **Prioritizing by economic effectiveness**
+
+Projects can be prioritized by ranking projects or project alternatives by the economic appraisal values produced in step 4. An agency might select those projects with the highest NPV, the highest BCR, or the highest cost effectiveness index. When using NPV the goal of a safety professional should be to implement all projects that have an NPV greater than zero, since each one brings a safety benefit. However, this is not possible since funds are limited, thus the goal should be to implement the group of projects that have the greatest combined NPV when added together (NPV is an additive property). Maximizing the NPV of a group of projects is different from prioritizing projects with high NPV. In other words, it may be best to implement numerous low cost projects with low NPV than one high cost project with a high NPV – but not higher than the NPV of all the low cost projects added up.
+
+## **Prioritizing by incremental benefit/cost analysis**
+
+This method involves ranking all projects with benefit cost ratio greater than 1.0 in increasing order of their estimated cost. An analyst calculates an incremental BCR as such:
+
+**Incremental BCR =**
+
+**(Benefit of Project A − Benefit of Project B)** 
+
+**(Cost of Project A − Cost of Project B)** 
+
+If the incremental BCR is greater than 1.0, the project with the higher cost is compared to the next project on this list; however, if the incremental BCR is less than 1.0, the project with the lower cost is compared to the next project on the list. This process is repeated and the project selected in the last pairing is the considered the best economic investment.
+
+## **Prioritizing by optimization methods**
+
+Optimization methods take into account certain constraints when prioritizing projects. Linear programming, integer programming, and dynamic programming (refer to Chapter 8, Appendix A, HSM, 2010) are optimization methods consistent with an incremental benefit/cost analysis, but they also account for budget constraints in the development of the project list. These optimization methods are more likely to be incorporated into a software package, rather than manually calculated. Multiobjective resource allocation is another optimization method. It incorporates nonmonetary elements (including decision factors not related to safety) into the prioritization process.
+
+Safety professionals may use software applications to select and rank countermeasures. The SafetyAnalyst tool from AASHTO includes economic appraisal and priority ranking tools.**<sup>39</sup>** The economic appraisal tool calculates
+
+**39**
+
+[http://www.](http://www.safetyanalyst.org) [safetyanalyst.org/](http://www.safetyanalyst.org)
+
+![](_page_128_Picture_0.jpeg)
+
+the BCR and other metrics for a set of countermeasures. The priorityranking tool ranks proposed improvement projects based on the benefit and cost estimates from the economic appraisal tool. The priority-ranking tool can also determine an optimal set of projects to maximize safety benefits.
+
+## **Step 6. Safety effectiveness evaluation**
+
+Once a countermeasure has been implemented at a site, or group of sites, it is important to determine whether it was effective in addressing the safety problem. For a safety professional to evaluate the countermeasure, he or she must determine how the countermeasure affected the frequency, type, and severity of crashes. For example, did the installation of a roundabout reduce the frequency of angle crashes? If so, by how much? Did it cause an increase to any other types of crashes? A countermeasure evaluation can result in a CMF
+
+for the countermeasure, which quantifies the effect on crashes (see CMF discussion in Step 4).
+
+Two documents entitled A Guide to Developing Quality Crash Modification Factors**<sup>40</sup>** (from FHWA) and Recommended Protocols for Developing Crash Modification Factors**<sup>41</sup>** (from NCHRP) provide guidance on the different methods for conducting evaluations. The following is an overview of study designs and methods for conducting evaluations.
+
+## **Categories of Study Designs**
+
+Study designs fall into two broad categories - experimental and observational. Experimental studies are conducted when sites are selected at random for treatment. There is general consensus that experimental studies are the most rigorous way to establish causality.**<sup>42</sup>** In contrast, observational studies are conducted when sites are not selected as part of an experiment but selected for other reasons including
+
+**40**
+
+Gross, F., B. Persaud, and C. Lyon (2010), *A Guide for Developing Quality Crash Modification Factors*, Report FHWA-SA-10-032, Federal Highway Administration, Washington, D.C. Available at [http://www.](http://www.cmfclearinghouse.org/resources_develop.cfm) [cmfclearinghouse.](http://www.cmfclearinghouse.org/resources_develop.cfm) [org/resources\\_](http://www.cmfclearinghouse.org/resources_develop.cfm) [develop.cfm.](http://www.cmfclearinghouse.org/resources_develop.cfm) Accessed July 2016.
+
+**41**
+
+Carter, D., R. Srinivasan, F. Gross, and F. Council (2012), R*ecommended Protocols for Developing Crash Modification Factors*, Prepared as part of NCHRP Project 20-07 (Task 314), Washington, D.C. Available at [http://www.](http://www.cmfclearinghouse.org/resources_develop.cfm) [cmfclearinghouse.](http://www.cmfclearinghouse.org/resources_develop.cfm) [org/resources\\_](http://www.cmfclearinghouse.org/resources_develop.cfm) [develop.cfm.](http://www.cmfclearinghouse.org/resources_develop.cfm) Accessed July 2016.
+
+**42**
+
+Elvik, R. (2011a), Assessing Causality in Multivariate Accident Models, *Accident Analysis and Prevention*, Vol. 43, pp. 253-264.
+
+**43**
+
+Elvik, R. (2011a), Assessing Causality in Multivariate Accident Models, *Accident Analysis and Prevention*, Vol. 43, pp. 253-264.
+
+safety. Truly experimental studies are not common in road safety partly because of potential liability considerations (i.e., a random selection may result in an agency being held liable for failing to treat some sites that have demonstrated high crash history). Observational studies are more common in countermeasure evaluations because most transportation agencies prioritize installation sites based on some kind of past safety performance (see Step 1, Network Screening).
+
+Observational studies of countermeasures can be broadly classified into cross-sectional studies and before-after studies. In cross-sectional studies, an analyst compares a group of sites with a certain feature to a group of sites without that feature. For example, an analyst might compare the safety performance of a group of stop-controlled intersections to that of a group of yield-controlled intersections to determine the effect of the type of traffic control on crashes. Cross-sectional studies can also be thought of as "with/without" studies. In before-after studies, an analyst takes a group of sites and compares the safety performance in the period before a countermeasure is implemented to the period after the countermeasure is implemented. For example, in a before-after study, an analyst could evaluate the effect of converting a stop-controlled intersection to a roundabout by comparing safety data before the roundabout conversion to the safety data afterwards.
+
+CMFs that result from crosssectional studies are not considered to be as robust as those resulting
+
+from a before-after study. In a typical before-after study, an analyst deals with same roadway unit located in a particular place, most likely used by the same road users during the before and after period. Since most of these factors can be assumed to be constant or almost constant in the before and after periods, they are less likely to cause significant biases. On the other hand, "cross-sectional studies compare different roads, used by different road users, located at different places and subject to different weather conditions. Besides, these roads will differ in very many other ways that are not measured."**<sup>43</sup>** However, there are issues in both types of studies that need to be addressed, and they are briefly discussed below.
+
+## **Cross sectional studies**
+
+Analysts use cross-sectional studies to compare the safety of a group of sites with a feature with the safety of a group of sites without that feature. The resulting CMF can be derived by taking the ratio of the average crash frequency of sites with the feature to the average crash frequency of sites without the feature. For this method to work, the two groups of sites should be similar in their characteristics except for the feature. In practice, this is difficult to accomplish and multiple variable regression models are used. These cross-sectional models are also called SPFs. The coefficients of the variables from these equations are used to estimate the CMF associated with a treatment.
+
+Guidance from FHWA on developing CMFs says that "the basic issue with the cross-sectional design is
+
+### **Using cross-sectional modeling to calculate a CMF for widening shoulders**
+
+A CMF can be obtained from a cross sectional model. Suppose the intent is to estimate the CMF for shoulder width based on the following SPF, which was
+
+Y = exp [ 
+$$0.8727 + 0.4414 \times ln(\frac{AADT}{10000}) + 0.4293 \times (\frac{AADT}{10000}) - 0.0164 \times SW$$
+]
+
+Where, AADT is the annual average daily traffic and SW is the width of the paved shoulder in feet. If the intent is to estimate the CMF of changing the shoulder width from three to six feet, then the CMF can
+
+estimated to predict the number of crashes per mile per year on rural two-lane roads in mountainous roads with paved shoulders (Appendix B of Srinivasan and Carter, 2011**<sup>44</sup>**):
+
+$$+) + 0.4293 \times (\frac{AADT}{10000}) - 0.0164 \times SW$$
+
+be estimated as the ratio of the predicted number of crashes when the shoulder width is six feet to the predicted number of crashes when the shoulder width is three feet:
+
+$$\text{CMF} = \frac{\exp \left[ \ 0.8727 + 0.4414 \times \ln \left( \frac{\text{AADT}}{10000} \right) + 0.4293 \times \left( \frac{\text{AADT}}{10000} \right) - 0.0164 \times 6 \ \right]}{\exp \left[ \ 0.8727 + 0.4414 \times \ln \left( \frac{\text{AADT}}{10000} \right) + 0.4293 \times \left( \frac{\text{AADT}}{10000} \right) - 0.0164 \times 3 \ \right]}$$
+
+This ratio simplifies to:
+
+$$CMF = exp[-0.0164 \times (6-3)] = 0.952$$
+
+This CMF of 0.952 indicates that changing the shoulder width from three to six feet would be expected to reduce crashes (since the CMF is less than 1.0). Specifically, the expected change in crashes would be a 4.8% reduction (1.0 – 0.952 x 100 = 4.8).
+
+However, it is important to recognize that this CMF of 0.952 is the midpoint in a range of possible values (i.e., the confidence interval). This range can be calculated by using the standard deviation of the CMF. In order to estimate the standard deviation, the standard error of the coefficient of SW is needed, which was reported to be 0.0015 in the original study. The high and low ends of the confidence interval are calculated using -0.0164+0.0015, and then using -0.0165-0.0015, and the difference between the two is divided by two. The equation is given below:
+
+StDev(CMF) = 
+$$\frac{\exp \left[-0.0164 + 0.0015 \times (6-3)\right] - \exp \left[-0.0164 - 0.0015 \times (6-3)\right]}{2} = 0.004$$
+
+The approximate 95% confidence interval for the CMF is (0.952-1.96×0.004, 0.952+1.96×0.004), which translates to a range of 0.944 to 0.960. Since the entire 95% confidence interval is below 1.0, the CMF is statistically significant, thereby indicating that widening the shoulder from three to six feet is very likely to reduce crashes.
+
+that the comparison is between two distinct groups of sites. As such, the observed difference in crash experience can be due to known or unknown factors, other than the feature of interest. Known factors, such as traffic volume or geometric characteristics, can be controlled for in principle by estimating a multiple variable regression model and inferring the CMF for a feature from its coefficient. However, the
+
+issue is not completely resolved since it is difficult to properly account for unknown, or known but unmeasured, factors. For these reasons, caution needs to be exercised in making inferences about CMFs derived from crosssectional designs. Where there are sufficient applications of a specific countermeasure, the before-after design is clearly preferred."**<sup>45</sup>**
+
+**44**
+
+Srinivasan, R. and D. Carter (2011), *Development of Safety Performance Functions for North Carolina*, Report FHWA/NC/2010- 09, Submitted to NCDOT, December 2011.
+
+**45**
+
+Gross, F., B. Persaud, and C. Lyon (2010), *A Guide for Developing Quality Crash Modification Factors*, Report FHWA-SA-10-032, Federal Highway Administration, Washington, D.C. Available at [http://www.](http://www.cmfclearinghouse.org/resources_develop.cfm) [cmfclearinghouse.](http://www.cmfclearinghouse.org/resources_develop.cfm) [org/resources\\_](http://www.cmfclearinghouse.org/resources_develop.cfm) [develop.cfm.](http://www.cmfclearinghouse.org/resources_develop.cfm) Accessed July 2016.
+
+#### **46**
+
+Gooch, J.P., Gayah, V.V., and Donnell, E.T. (2016), Quantifying the Safety Effects of Horizontal Curves on Two-Way, Two-Lane Rural Roads, *Accident Analysis and Prevention*, Vol. 92, pp. 71-81.
+
+#### **47**
+
+Holmes, W.M., (2013). *Using Propensity Scores in Quasi-Experimental Designs.* SAGE Publications.
+
+#### **48**
+
+Wood, J., Porter, R., (2013). Safety impacts of design exceptions on non-freeway segments. *Transport. Res. Rec.: J. Transport.* Res. Board 2358, 29–37.
+
+#### **49**
+
+Gross, F., B. Persaud, and C. Lyon (2010), *A Guide for Developing Quality Crash Modification Factors*, Report FHWA-SA-10-032, Federal Highway Administration, Washington, D.C. Available at [http://](http://www.cmfclearinghouse.org/resources_develop.cfm) [www.cmfclearing](http://www.cmfclearinghouse.org/resources_develop.cfm)  [house.org/](http://www.cmfclearinghouse.org/resources_develop.cfm) [resources\\_ develop.](http://www.cmfclearinghouse.org/resources_develop.cfm) [cfm.](http://www.cmfclearinghouse.org/resources_develop.cfm) Accessed July 2016.
+
+#### **50**
+
+See next page.
+
+![](_page_131_Picture_10.jpeg)
+
+One way to account for some of the limitations of cross-sectional regression models is to use the propensity scores-potential outcome method. This method uses the "individual traits of a site to calculate its propensity score, defined as a measure of the likelihood of that site receiving a specific treatment. Sites with and without the treatment are then matched based on their propensity scores."**<sup>46</sup>** The matched data are then used to estimate a cross sectional regression model. The propensity score method has been shown to reduce selection bias by accounting for the non-random assignment of treatment sites.**<sup>47</sup>** Recently, the propensity score method is starting to be used in place of traditional cross-sectional methods to conduct evaluations.**<sup>48</sup>**
+
+Other types of cross-sectional methods include case control and cohort methods. "Case-control studies select sites based on outcome status (e.g., crash or no crash) and then determine the prior treatment (or risk factor) status within each outcome group."**<sup>49</sup>** Another critical component of many case-control studies is the matching of cases with controls in order to control for the effect of confounding factors. In cohort studies, sites are assigned to a particular cohort based on current treatment status and followed over time to observe exposure and event frequency. One cohort may include the treatment and the other may be a control group without the treatment. The time to a crash in these groups is used to determine a relative risk, which is the percentage change in the probability of a crash given the treatment.**<sup>50</sup>**
+
+## **Before after studies**
+
+An analyst can use a before-after study to evaluate a countermeasure by comparing the crashes before the countermeasure was installed to the crashes after installation. This study design is advantageous because the only change that has occurred at the site is the countermeasure installation (assuming the analyst has researched the site histories to discard any sites at which other significant changes occurred).
+
+There are issues for consideration with this study design as well. The analyst must know when the countermeasure was installed and must have data, such as crash and traffic volume, available in the before and after periods. For high-cost, high-profile countermeasures, such as road widening or traffic signal installation, the installation records will be readily available. However, for low-cost countermeasures, such as sign installations, there may be little to no documentation on when they were installed.
+
+The analyst might simply compare the number of crashes per year before the countermeasure to the number of crashes per year after the countermeasure, known as a simple or naïve before-after evaluation. Although a simple before-after evaluation can be done easily using only crash data, it is prone to significant bias. One of the most influential biases for this method is the possible bias due to RTM. As discussed earlier, RTM describes a situation in which crash rates are artificially high during the before period and would have been reduced even without an improvement to the site. Programs focused on highhazard locations are vulnerable to the RTM bias. This potential bias is greatest when sites are chosen because of their extreme value (e.g., high number of crashes or crash rate) in a given time period. A simple before-after evaluation has a high likelihood of showing a much greater benefit from the safety treatment than actually occurred.
+
+As discussed earlier under the network screening section, the EB method is one of the methods that has been found to be effective in dealing with the possible bias due to RTM. The following steps are needed to conduct an EB before-after evaluation:
+
+- **1. IDENTIFY** a reference group of sites without the treatment, but similar to the treatment sites in terms of the major factors that affect crash risk including traffic volume and other site characteristics. One way to identify a reference group that is similar to the treatment is to use the propensity score method discussed earlier under crosssectional studies.
+- **2.** Using data from the reference site, **ESTIMATE** SPFs using data from the reference sites relating crashes to independent variables, such as traffic volume and other site characteristics. As discussed in the following steps, SPFs are used in the EB method to predict the average number of crashes based on AADT and site characteristics. By selecting the reference group to be similar to the treatment group in terms of the major risk factors, we can reduce the possible bias due to confounding on these predictions.
+
+Carter, D., R. Srinivasan, F. Gross, and F. Council (2012), *Recommended Protocols for Developing Crash Modification Factors*, Prepared as part of NCHRP Project 20-07 (Task 314), Washington, D.C. Available at [http://www.](http://www.cmfclearinghouse.org/resources_develop.cfm) [cmfclearinghouse.](http://www.cmfclearinghouse.org/resources_develop.cfm) [org/resources\\_](http://www.cmfclearinghouse.org/resources_develop.cfm) [develop.cfm.](http://www.cmfclearinghouse.org/resources_develop.cfm) Accessed July 2016.
+
+#### **Using an EB before-after evaluation to develop a CMF for signal phasing changes**
+
+**51**
+
+Srinivasan, R. et al., *Evaluation of Safety Strategies at Signalized Intersections*, NCHRP Report 705, Washington, DC.
+
+This example is an illustration of an EB before-after evaluation that was conducted as part of NCHRP Project 17-35.**<sup>51</sup>** The countermeasure was a change from permissive to protected-permissive left turn phasing at signalized intersections in North Carolina. Data from twelve locations were used in this evaluation. A reference group of 49 signalized intersections was identified for the development of SPFs. The analysis looked at total intersection crashes, injury and fatal crashes, rear end crashes, and left turn opposing through (LTOT) crashes. In this example, only the data for LTOT crashes will be used.
+
+The SPF for LTOT crashes based on the data from the reference group was:
+
+**LTOT crashes/intersection/year = e-0.3696 (MajAADT/10000) 0.5564 e0.6585×(MinAADT / 10000)**
+
+Where, MajAADT is the major road AADT and the MinAADT is the minor road AADT. The overdispersion parameter (k) for this SPF was 0.5641.
+
+In the first site of this study, there were 10 observed crashes in the before period (Xb ), and the predicted number of crashes from the SPF in the before period was 5.535 (Pb ). The formula for obtaining the EB estimate of the expected crashes in the before period (EBb ) is as follows:
+
+$$EB_b = w \times P_b + (1 - w) \times X_b$$
+
+Where, Xb is the observed crashes in the before period, and w is the EB weight that is calculated as follows:
+
+$$w = \frac{1}{(1 + k \times P_b)}$$
+
+Where, k is the overdispersion parameter for the estimated SPF.
+
+In this example:
+
+$$W = \frac{1}{(1 + 0.5641 \times 5.535)} = 0.243$$
+
+The EB estimate of the crashes in the before period (EBb ) = 5.535\*0.243 + 10\*(1-0.243) = 8.917 crashes.
+
+The predicted number of crashes from the SPF in the after period was 11.391 (Pa ).
+
+The formula for the EB expected number of crashes that would have occurred in the after period had there been no countermeasure is given by:
+
+$$\pi = EB_b \times (P_a/P_b)$$
+
+In this example, the EB expected number of crashes in the after period had the countermeasure not been implemented (π) is equal to:
+
+**8.917 × ( 11.391 / 5.535 ) = 18.350 crashes**
+
+The variance of this expected number of crashes is also estimated in this step:
+
+$$Var(\pi) = \pi \times (P_a/P_b) \times (1 - w)$$
+
+Where, Pa is the SPF predictions in the after period. In this example, the variance of ππ is estimated as follows:
+
+Var(
+$$\pi$$
+) = 18.350 × (11.391 / 5.535)  
+× (1 - 0.243) = 28.603
+
+This process was repeated for all 12 sites. Based on the data for all the 12 sites that were used in the evaluation, the actual crashes in the after period were 115, the EB expected crashes had the countermeasure not been implemented was 131.933 with a variance of 140.080.
+
+*(continued on next page)*
+
+The formula for the CMF and its standard deviation (StDev) are as follows:
+
+$$CMF = \frac{\frac{\lambda_{sum}}{\pi_{sum}}}{1 + \frac{Var(\pi_{sum})^2}{\pi_{sum}^2}}$$
+
+StDev(CMF) =
+$$\frac{\text{CMF}^2 \frac{\text{Var}(\lambda_{\text{sum}})}{\lambda_{\text{sum}}^2} + \frac{\text{Var}(\pi_{\text{sum}})}{\pi_{\text{sum}}^2}}{(1 + \frac{\text{Var}(\pi_{\text{sum}})}{\pi_{\text{sum}}^2})^2}$$
+
+Where, λsum is the total number of crashes that occurred in the after period, for all the treated sites in the sample, πsum is the total number of expected crashes in the after period had the countermeasure not been implemented, and Var represents the variance. Since crashes are assumed to be Poisson distributed, Var(λsum) is usually assumed to be equal to λsum. So, (Var(λsum))/ (λsum ) will be equal to 1/λsum.
+
+In this example, the overall CMF was calculated as:
+
+$$CMF = \frac{\frac{115}{131.933}}{1 + \frac{140.080}{131.933^2}} = 0.865$$
+
+This CMF of 0.865 indicates that the countermeasure (changing from permissive to protected-permissive left turn phasing) would decrease crashes, since the CMF is less than 1.0. It would be expected to decrease crashes by 13.5% (1.0 – 0.865 x 100 = 13.5).
+
+Again, it is important to recognize that the
+
+CMF is the midpoint of a range of possible values (i.e., the confidence interval). The standard deviation of the CMF can be estimated as follows:
+
+StDev(CMF) =
+$$\frac{0.865^{2} \left(\frac{1}{115} + \frac{140.080}{131.933^{2}}\right)}{\left(1 + \frac{140.080}{131.933^{2}}\right)^{2}} = 0.111$$
+
+Based on this standard deviation of the CMF, the approximate 95% confidence interval is (0.865-1.96×0.111, 0.865+1.96×0.111), which translates to a range of 0.647 to 1.083. Since this confidence interval includes values greater than 1.0, the CMF is not statistically different from 1.0 at the 95% confidence level. This indicates that there is less confidence that this countermeasure will reduce crashes compared to a countermeasure whose CMF is significantly different from 1.0.
+
+Gross, F., B. Persaud, and C. Lyon (2010), *A Guide for Developing Quality Crash Modification Factors*, Report FHWA-SA-10-032, Federal Highway Administration, Washington, D.C. Available at [http://www.](http://www.cmfclearinghouse.org/resources_develop.cfm) [cmfclearinghouse.](http://www.cmfclearinghouse.org/resources_develop.cfm) [org/resources\\_](http://www.cmfclearinghouse.org/resources_develop.cfm) [develop.cfm.](http://www.cmfclearinghouse.org/resources_develop.cfm) Accessed July 2016.
+
+#### **53**
+
+Carter, D., R. Srinivasan, F. Gross, and F. Council (2012), *Recommended Protocols for Developing Crash Modification Factors*, Prepared as part of NCHRP Project 20-07 (Task 314), Washington, D.C. Available at [http://www.](http://www.cmfclearinghouse.org/resources_develop.cfm) [cmfclearinghouse.](http://www.cmfclearinghouse.org/resources_develop.cfm) [org/resources\\_](http://www.cmfclearinghouse.org/resources_develop.cfm) [develop.cfm.](http://www.cmfclearinghouse.org/resources_develop.cfm) Accessed July 2016.
+
+#### **54**
+
+B. Persaud and C. Lyon (2007), Empirical Bayes Before After Studies: Lessons Learned from Two Decades of Experience and Future Directions, *Accident Analysis and Prevention*, 39(3):546-55.
+
+- **3.** In estimating SPFs, **CALIBRATE** annual SPF multipliers to account for the temporal effects (e.g., variation in weather, demography, and crash reporting) on safety. The annual SPF multiplier is the ratio of the observed crashes to the predicted crashes from the SPF. In using the annual SPF multipliers from the SPFs to account for temporal effects, it is assumed that the trends in the crash counts are similar in the treatment and reference groups.
+- **4. USE** the SPFs, annual SPF multipliers, and data on traffic volumes for each year in the before period for each treatment site to estimate the number of crashes that would be predicted for the before period in each site.
+- **5. CALCULATE** the EB estimate of the expected crashes in the before period at each treatment site as the weighted sum of the actual crashes in the before period and predicted crashes from Step 4.
+- **6.** For each treatment site, **ESTIMATE** the product of the EB estimate of the expected crashes in the before period and the SPF predictions for the after period divided by these predictions for the before period. This is the EB expected number of crashes that would have occurred had there been no treatment. The variance of this expected number of crashes is also estimated in this step.
+
+The expected number of crashes without the treatment along with the variance of this parameter and the number of reported crashes after the treatment is used to calculate the CMF and the standard deviation of the CMF. This procedure is repeated for each treated site. Once CMFs have been calculated for each individual site in a group of treated sites, the CMFs can be combined to calculate the overall effectiveness of the countermeasure. More details on this procedure are provided in the previously mentioned guidance documents.**52,53**
+
+In some cases, treatments may be installed system-wide for a particular type of facility. For example, a jurisdiction may decide to increase the retroreflectivity of all their stop signs. Since sites are not specifically selected based on their crash history, the bias due to RTM is minimal. However, it is still necessary to account for changes in traffic volume and other trends. To evaluate the safety of such installations, an EB method could still be used, and while a reference group is not necessary, a comparison group is necessary in order to account for trends. SPFs can be estimated using the before-data from the treatment sites and these SPFs can be used to account for changes in traffic volumes. In addition, SPFs could be estimated for a group of comparison sites and the annual factors from these SPFs can be used to account for trends. Further details about such evaluations can be found elsewhere.**<sup>54</sup>**
+
+## **System-Level Safety Management**
+
+System-level safety management involves addressing road safety issues that affect the broad transportation system, as opposed to treating specific high priority sites. The size and scope of the transportation system depends on the agency or jurisdiction. For a State DOT, the transportation system would consist of all Stateowned roads, signals, bridges, and other features across the entire State, whereas the transportation system for a town would consist of a much smaller area and roadway network. Road safety at a systemlevel often has to do with policies, whether design policies for the construction and operation of roads and intersections, driver policies for licensing, or vehicle policies that require certain safety technologies. Other system-level efforts would include broad media or enforcement campaigns.
+
+Recall that Chapter 10 presented road safety management in terms of three general components:
+
+- J **Identifying safety problems**
+- J **Developing potential safety strategies**
+- J **Selecting and implementing strategies**
+
+This chapter will discuss how each of these components can be addressed at a system-level.
+
+#### **System-wide vs. systemic?**
+
+System-wide is a general term that refers to treating safety issues across an entire transportation system using policies or campaigns. Systemic is a more specific term that refers to identifying a subset of a transportation system based on risk factors and implementing safety efforts that address the particular characteristics of that subset. See page 4-41 for more discussion on the systemic approach.
+
+## **Identifying safety problems**
+
+To identify safety problems on a system-level, safety professionals analyze safety data that apply to the entire jurisdiction. They examine crash data and link crashes to other safety data to determine the nature and locations of safety problems. Problem identification on a system-level involves identifying crash trends and using risk-based methods to prioritize safety efforts.
+
+## **Identifying crash type trends**
+
+Safety professionals can examine crash types and contributing factors to determine the nature of crashes within their agency's jurisdiction. This type of examination may reveal crash trends, such as those related to alcohol involvement, seat belt use, driver age, or vulnerable road users. For example, crash data might show that crashes involving unbelted occupants have been increasing over the past several
+
+years, or it might show that the number of crashes involving unbelted occupants is significantly higher than other nearby agencies, such as adjacent counties or States. This would lead an agency to consider how to increase seat belt use, perhaps through media campaigns, increased enforcement, or educational campaigns in schools. This type of agency-wide analysis of crash data can demonstrate broad scale trends that need to be addressed through broad scale efforts.
+
+It is important that safety professionals are specific when identifying safety problems in crash trends. For example, "crashes involving teen drivers" is not defined well enough, because the causes of crashes for 16 year-olds is markedly different from those of older, more experienced teens. Crashes in which teens are victims of other drivers' errors require different solutions from those where the teen was at fault. Similarly, the cause of crashes depends greatly on the specific time, place and driving environment. A better target crash type would be "crashes occurring between 7-9 a.m. involving 16-year old drivers."
+
+## **Example of safety problem identification in State Highway Safety Plans**
+
+A good example of identifying safety problems from crash type trends can be seen in how States develop **strategic highway safety plans** (SHSPs). The development of a SHSP involves the identification of safety problems on the State and local roads. A State analyzes safety data to determine the priorities, referred
+
+### **Florida's emphasis on motorcyclist safety**
+
+The State of Florida examined its crash data to identify emphasis areas in the development of their SHSP in 2012. One area that continued to be a focus was motorcyclist safety. The data indicated that crashes involving motorcycles had decreased somewhat during the time period analyzed (2006 to 1010) but remained a significant portion of the crashes on Florida roads. Florida's safety professionals recognized that since Florida hosts numerous national motorcycle events, the state's SHSP should have motorcycle safety as an emphasis area.
+
+![](_page_137_Figure_6.jpeg)
+
+**FIGURE 4-8.** Florida motorcycle crash trend 2006-2010
+
+to as emphasis areas. The analysis can involve an examination of crash proportions between categories of crashes, crash trends, crash severity (e.g., fatal and serious injury), or more advanced crash modeling techniques. As presented in the call-out boxes, Ohio and Florida conducted analyses of their crash data and identified areas of concern.
+
+#### **Strategic highway safety plan**
+
+A statewidecoordinated safety plan that provides a comprehensive framework for reducing highway fatalities and serious injuries on all public roads.
+
+### **Ohio's emphasis on older driver safety**
+
+Ohio developed a SHSP in 2014 in which they identified fifteen emphasis areas. One of the emphasis areas was the safety of older drivers (65 and older). The crash data showed that older driver-related crashes accounted for 18% of highway deaths and 16% of serious injuries. They recognized that these numbers would likely increase with an aging population. The crash trends over the time period examined (2003 to 2013) showed a slight upward trend to older driver serious injuries and a slight downward trend to older driver fatalities. This contrasted to other types of crashes that experienced significant declines. These reasons motivated Ohio to make older driver safety an emphasis area in their 2014 SHSP.
+
+![](_page_138_Picture_2.jpeg)
+
+## **Risk based prioritization – the systemic approach**
+
+Chapter 11 presented various methods of selecting high priority sites through a process of network screening based on crash data. Many safety professionals recognize that this process of identifying specific locations using past crash data does not adequately address the fact that there may be locations that pose a safety threat but have not yet experienced many (or any) crashes. This recognition led to an increased use of risk-based prioritization, also called the **systemic** approach.**<sup>55</sup>**
+
+In this approach, a transportation agency identifies priority locations based on the presence of risk factors rather than crashes. In the medical field, doctors pay attention to factors that may elevate a person's risk for disease. A history of smoking, poor eating habits, and a lack of exercise
+
+may indicate a higher-than-average risk for heart disease, even if the person has not yet experienced heart problems. Similarly, a section of road with certain characteristics, such as sharp curvature, old pavement, or lack of visibility, may be at risk for run-off-road crashes, even if none have occurred yet. Agencies can be proactive in their approach to safety management by identifying and treating these sites before crashes occur. These treatments are often low cost, such as signs and markings, so many systemic-identified locations can be treated within an agency's limited budget.
+
+An agency using the systemic approach selects the focus crash type(s) and identifies risk factors associated with the focus crashes. Risk factors are site characteristics (e.g., design and operational features) that are common across
+
+#### **Systemic**
+
+The process of identifying road or intersection characteristics that increase the risk of crashes and selecting locations for safety treatment based on the presence of these risk factors.
+
+**55**
+
+[http://safety.fhwa.](https://safety.fhwa.dot.gov/systemic/) [dot.gov/systemic/](https://safety.fhwa.dot.gov/systemic/)
+
+locations with the focus crash type(s). The agency can identify risk factors by analyzing crash data from their jurisdiction or by reviewing previous research studies. Using the list of risk factors as a guide, the agency identifies a list of sites with those specific characteristics, and then develops targeted treatments to address or mitigate the specific risk factors. The agency can apply crash history and other thresholds to reduce the list of sites based on available resources and program objectives.
+
+The systemic approach has two attractive features. First, an agency can employ the systemic approach even for roads or intersections where crash data are not fully available (e.g., where location accuracy is questionable or underreporting is a problem). For instance, locating crashes accurately and precisely in rural areas or on non-State owned urban roads can be difficult. Second, the systemic approach is useful for treating safety issues where crashes are highly dispersed, such as on rural or low volume roads. Specifically, agencies can use the systemic approach to address existing and potential safety issues across a large portion of the network (e.g., shoulder rumble strips on all rural, two-lane roads with a certain shoulder width and traffic volume level).
+
+## **Developing potential safety strategies**
+
+After safety professionals analyze data and identify safety problems, they must develop potential strategies to address the problems. It is important to engage safety stakeholders and other partners
+
+when selecting potential strategies as they may provide unique perspectives. Safety professionals should seek to involve local officials, citizens, and safety partners to produce effective multidisciplinary strategies. For example, addressing a particular safety problem with law enforcement and education can be far more economical than implementing a multimilliondollar engineering fix. On the other hand, law enforcement tends to be effective only during the time in which it is active, so a more permanent engineering measure may be needed in some cases. It is often the case that a combination of strategies is necessary to effectively address the multitude of contributing factors.
+
+On a system level, agencies must think broadly across the many disciplines represented by those who have a stake in road safety. Potential strategies might address infrastructure policies and practices (e.g., design standards, speed limits, etc.) or they may be directed at specific population focused efforts (e.g., seat belt laws, helmet laws, young driver restrictions, etc.).
+
+Just as the identification of problems was based on safety data, so too must the development and selection of strategies be driven by the data. If an agency identified concerning trends in certain types of crashes, then they should further examine the crash data to determine how best to address the safety problem. For example, Figure 4-9 shows an example of alcohol-related crashes where an agency identified a spike in frequency (or high pole) of crashes occurring near 2:00 AM. Further examination revealed that bars in
+
+#### **Case Study: Systemic Analysis in Thurston County, Washington**
+
+The Thurston County Public Works Department in Washington conducted a systemic safety analysis for their road network. Based on a review of severe crashes, Thurston County decided to focus on roadway departure crashes in horizontal curves on arterial and collector roadways when it found that:
+
+- **1.** Most of the severe crashes occurred due to roadway departures, and that
+- **2.** 81% of the severe curve /roadway departure crashes occurred on arterial and collector roads. Because this effort coincided with ongoing efforts to identify and upgrade warning signs for horizontal curves on their County road system, Thurston County chose to focus on currently signed horizontal curves.
+
+Thurston County accessed an inventory of their roads and intersections through a database maintained by the Statewide County Road Advisory Board. In addition, Thurston County assembled crash data for the 2006-to-2010 timeframe from the Washington State DOT crash database. They linked the road, intersection, and curve data with crash data and used these data to identify risk factors. Thurston County assembled a list of 19 potential risk factors and then performed a descriptive statistics analysis to identify 9 risk factors for use in screening and prioritizing candidate locations. The identified risk factors were:
+
+- J **Roadway class of major rural collector**
+- J **Presence of an intersection**
+- J **Traffic volume of 3,000 to 7,500 annual average daily traffic**
+- J **Edge clearance rating of 3**
+- J **Paved shoulders equal to or greater than 4 feet in width**
+- J **Presence of a vertical curve**
+- J **Consecutive horizontal curves (windy roads)**
+
+- J **Speed differential between posted approach speed and curve advisory speed of 0, 5, and 10 miles per hour**
+- J **Presence of a visual trap (a minor road on the tangent extended)**
+
+Thurston County decided that a risk factor could be worth one point or a one-half point. Those factors present in at least 30% of the severe (fatal and injury) crashes and overrepresented by at least 10% (when comparing the proportion of all locations with the proportion of severe crash locations) were used as a guideline to have a high confidence and assigned one point in the risk assessment process. The risk factors that had a lower confidence in their relative data were assigned one-half point.
+
+Thurston County then tallied the number of risk factors present for each of the curves. The risk factor totals for the ten curves with the highest scores ranged from 4.5 to 6.0. All 270 signed curves were prioritized for potential low cost safety investments. They identified the following low-cost, low-maintenance countermeasures with documented crash reductions to implement at the selected locations:
+
+- J **Traffic signs** enhanced curve delineation with the addition of chevrons and larger advance warning signs
+- J **Pavement markings** dotted extension lines at intersections and recessed raised pavement markers
+- J **Shoulder rumble strips**
+- J **Roadside improvements** object removal, guardrail, and slope flattening
+
+Systemic analysis provided Thurston County a proactive, data-driven, and defensible approach to identifying curves for improvement prior to a severe crash occurring, rather than reacting after an incident has occurred.**<sup>56</sup>**
+
+**56**
+
+"Thurston County, Washington, Public Works Department Applies Systemic Safety Project Selection Tool" FHWA-SA-13-026, June 2013. [http://](https://safety.fhwa.dot.gov/systemic/) [safety.fhwa.dot.gov/](https://safety.fhwa.dot.gov/systemic/) [systemic/](https://safety.fhwa.dot.gov/systemic/)
+
+![](_page_141_Figure_0.jpeg)
+
+**FIGURE 4-9.** Example of "high pole" in crash data *(Source: NCHRP Report 501)*
+
+that jurisdiction closed at 2:00 AM. This could lead to potential strategies, such as increased enforcement of impaired driving at that time of night and in the vicinity of bars.
+
+It is also important to use the data to determine the necessary scope of the intervention. If the data show that the problem exists year-round, then the solution needs to match that. For example, a "safe ride program" for drinkers to get home on New Year's Eve is not going to significantly impact the problem of impaired driving overall.
+
+Critical thinking is needed to develop effective solutions to the safety problems at hand. Analysts should look for characteristics of crash trends that could be addressed by practical strategies. An NCHRP report on an integrated safety management process states that safety professionals should use safety data to perform "further analyses of those characteristics that are found to be significantly or practically over-represented on a percentage or rate basis."**<sup>57</sup>** The report gives a set of guidelines to be considered in analyzing crash data to identify trends and develop potential safety strategies:
+
+#### **Consider How Specific Behaviors Influence the Safety Problem**
+
+Safety professionals must identify and target road user behaviors that contribute to the identified safety problem. The target behavior should be specific. For example, "safe driving" is not a specific behavior that can be changed because it involves a number of different behaviors. However, "speeding on Main Street" is a specific behavior that can be targeted. It is also important to consider the factors influencing this behavior. Why are people speeding on Main Street? Which social, cultural, or environmental factors are influencing this behavior? Does it vary by time of day or week, perhaps reflecting the kind of drivers who are speeding?
+
+- **1. ASK** the questions, "Is this information sufficient for action item development? If not, what further information is needed to act on this finding?"
+- **2. CONSIDER** cross tabulations of two variables within the subset of data that pertains to the activities under consideration if one or more of the following types of conditions hold:
+  - J If the activities are time critical (e.g., all selective
+
+**57**
+
+Bahar, G., M. Masliah, C. Mollett, and B. Persaud, Integrated Safety Management Process, National Cooperative Highway Research Program, Report 501, Transportation Research Board of the National Academies, Washington, D.C., 2003
+
+enforcement strategies), perform a time-of-day by day-of-the-week analysis. As an example, alcoholrelated crashes will likely be over-represented in the early morning and on weekend days. A logical approach is to perform a cross tabulation of time-of day by day-of-theweek to determine the best times and days for driving under the influence (DUI) selective enforcement. The goal of the procedure at this point is to determine additional details (who, what, where, when, and how) for those crash types identified by the analyses performed to this point.
+
+- J If the over-represented variable is not constant over all crash severities, cross tabulate the variable by severity (e.g., nighttime, rural, and older-driver crashes tend to be more severe).
+- J If the activities can be targeted to geographic location, age group, gender, race, or any other demographic factor within the crash records, consider these variables for cross tabulation with other overrepresented variables.
+- **3. CONSIDER** creating subsets of the data for additional comparisons where activities are to be targeted to a particular subgroup of the population. For example, insight into a graduated driver's license strategy can be obtained by comparing 16-yearold causal driver crashes against
+
+17- to 20-year-old causal driver crashes. As another example, insight into youth alcohol enforcement activities can be attained by comparing alcohol-related crashes of 16 to 20-year-old causal drivers against alcohol-related crashes of their 21-year-old and older counterparts. Each of these types of comparisons can show differences between the respective subpopulations.
+
+- **4. USE** the results of each analysis to determine what further information is needed before the best decision can be made, and repeat the analysis with the additional information.
+- **5. PERSIST** and maintain a thread of evidence until the information available has been exhausted. If the information generated indicates a significant factor, create further subsets of the data (e.g., youth-pedestrian crashes), and repeat the entire analysis.
+- **6. REJECT** any strategies and activities at this point that the data clearly show to be counterproductive (i.e., activities that will consume resources that could be better applied elsewhere). Maintain a list of all potential strategies and corresponding activities that will be subjected to further analysis in the optimization procedure.**<sup>58</sup>**
+
+Many system-level safety strategies focus on behaviors of drivers and other road users. Resources like Countermeasures That Work provide a useful listing of potential safety strategies for system-level safety management.**<sup>59</sup>** The excerpt from *Countermeasures That Work* in
+
+**58**
+
+Bahar, G., M. Masliah, C. Mollett, and B. Persaud, Integrated Safety Management Process, National Cooperative Highway Research Program, Report 501, Transportation Research Board of the National Academies, Washington, D.C., 2003
+
+**59**
+
+Goodwin, A., Thomas, L., Kirley, B., Hall, W., O'Brien, N., & Hill, K. *Countermeasures That Work: A Highway Safety Countermeasure Guide for State Highway Safety Offices*, Eighth edition, National Highway Traffic Safety Administration, Report No. DOT HS 812 202, Washington, DC, 2015.
+
+#### **FIGURE 4-10.** Potential Safety Strategies to Address Speeding and Aggressive Driving
+
+#### **1. Laws**
+
+| COUNTERMEASURE              | EFFECTIVENESS | COST | USE  | TIME  |
+|-----------------------------|---------------|------|------|-------|
+| 1.1 Speed limits            | †<br>    | \$   | High | Short |
+| 1.2 Aggressive driving laws |          | \$   | Low  | Short |
+
+- † When enforced and obeyed
+- **2. Enforcement**
+
+| COUNTERMEASURE                  | EFFECTIVENESS | COST        | USE       | TIME   |
+|---------------------------------|---------------|-------------|-----------|--------|
+| 2.1 Automated enforcement       |          | †<br>\$\$\$ | Medium    | Medium |
+| 2.2 High-visibility enforcement |          | \$\$\$      | ††<br>Low | Medium |
+| 2.3 Other enforcement methods   |          | Varies      | Unknown   | Varies |
+
+- † Can be covered by income from citations
+- †† For aggressive driving, but use of short-term, high-visibility enforcement campaigns for speeding is more widespread
+- **3. Penalties and Adjudication**
+
+| COUNTERMEASURE                    | EFFECTIVENESS | COST   | USE     | TIME   |
+|-----------------------------------|---------------|--------|---------|--------|
+| 3.1 Penalty types and levels      |          | Varies | High    | Low    |
+| 3.2 Diversion and plea agreements |          | Varies | Unknown | Varies |
+
+#### **4. Communications and Outreach**
+
+| COUNTERMEASURE                                   | EFFECTIVENESS | COST   | USE    | TIME   |
+|--------------------------------------------------|---------------|--------|--------|--------|
+| 4.1 Public Information<br>supporting enforcement |          | Varies | Medium | Medium |
+
+### **Effectiveness:**
+
+|  | Demonstrated to be effective by several<br>high-quality evaluations with consistent results                          |
+|-------|----------------------------------------------------------------------------------------------------------------------|
+|  | Demonstrated to be effective in certain situations                                                                   |
+|  | Likely to be effective based on balance of evidence<br>from high-quality evaluations or other sources                |
+|  | Effectiveness still undetermined; different methods of<br>implementing this countermeasure produce different results |
+|  | Limited or no high-quality evaluation evidence                                                                       |
+
+Figure 4-10 gives a list of potential strategies for addressing speedingrelated crashes, from either laws, enforcement, penalties and adjudication, or communications and outreach. The list also includes an indication of the effectiveness, cost, current usage, and time of each strategy, which are all important considerations when selecting safety strategies to implement.
+
+If the agency identifies safety problems from a systemic analysis, the potential safety strategies should address the types of crashes that were related to the roadway characteristic risk factors. These strategies may often be engineering improvements related to the risk factors. For example, if an examination of crash trends may highlight run-off-road crashes, and a systemic analysis would identify the type(s) of road on which run-off-road crashes are likely to occur. Table 4-12 shows a list of potential safety strategies that could be implemented for engineering treatments for a run-off-road crash problem. In a systemic approach, these engineering treatments would be implemented across some or all roads meeting the risk factors that increase the likelihood of run-offroad crashes.
+
+## **Example of system-level safety strategies in state highway safety plans**
+
+SHSPs provide many good examples of system-level strategies that address safety problems identified through analysis of crash and other safety data. The previous section showed how Ohio and Florida had identified safety priorities on older drivers and motorcyclists,
+
+### **Florida's strategies for motorcyclist safety**
+
+After identifying motorcyclist safety as an emphasis area in their 2012 SHSP, Florida identified a list of strategies to address motorcyclist safety. Example strategies include:
+
+- J **Promote personal protective gear and its value in reducing motorcyclist injury levels and increasing rider conspicuity**
+- J **Promote adequate rider training and preparation to new and experienced motorcycle riders by qualified instructors at Stateapproved training centers**
+- J **Incorporate motorcycle-friendly policies and practices into roadway design, traffic control, construction, operation, and maintenance**
+- J **Develop and implement communications strategies that target high-risk populations and improve public awareness of motorcycle crash problems and programs.**
+
+respectively. The SHSPs from these States also demonstrated the types of safety strategies each State intended to pursue to combat the safety problems in these areas.
+
+## **Selecting and implementing strategies**
+
+A transportation agency must determine which of the potential strategies they will implement to address the identified safety problems. Since system-level safety solutions can involve broad changes to policies, design practices, or jurisdiction-wide road user behavior, there are different issues to consider compared to implementing a safety countermeasure at a specific
+
+| OBJECTIVES                                                                | COUNTERMEASURES                                                                                                                                                     | RELATIVE<br>COST TO<br>IMPLEMENT<br>AND OPERATE | EFFECTIVE-<br>NESS |
+|---------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------|--------------------|
+| 15.1 A: KEEP<br>VEHICLES<br>FROM<br>ENCROACHING                           | 15.1A1: Install shoulder<br>rumble strips                                                                                                                           |                                                 | Tried              |
+| ON THE<br>ROADSIDE                                                        | 15.1 A2: Install edgelines<br>"profile marking", edgeline<br>rumble strips or modified<br>shoulder rumble strips on<br>section with narrow or no<br>paved shoulders | Low                                             | Experimental       |
+|                                                                           | 15.1 A5: Provide improved<br>highway geometry for<br>horizontal curves                                                                                              | High                                            | Proven             |
+|                                                                           | 15.1 A6: Provide enhanced<br>pavement markings                                                                                                                      | Low                                             | Tried              |
+|                                                                           | 15.1 A7: Provide skid<br>resistance pavement surfaces                                                                                                               | Moderate                                        | Proven             |
+| 15.1 B:<br>MINIMIZE THE<br>LIKELIHOOD<br>OF CRASHING<br>INTO AN           | 15.1 B1: Design safer slopes<br>and ditches to prevent<br>rollovers                                                                                                 | Moderate                                        | Proven             |
+| OBJECT OR<br>OVERTURNING<br>IF THE VEHICLE<br>TRAVELS OFF<br>THE SHOULDER | 15.1 B2: Remove/relocate<br>objects in hazardous locations                                                                                                          | Moderate<br>to High                             | Proven             |
+| 15.1 C: REDUCE<br>THE SEVERITY<br>OF THE CRASH                            | 15.1 C1: Improve design of<br>roadside hardware                                                                                                                     | Moderate<br>to High                             | Tried              |
+|                                                                           | 15.1 C2: Improve design and<br>application of barrier and<br>attenuation systems                                                                                    | Moderate<br>to High                             | Tried              |
+
+**TABLE 4-12.** Potential Safety Strategies for Run-Off-Road Crashes *(Source: NCHRP 500, Volume 6)*
+
+location. Many more people will be affected by the system-level changes. This carries great promise in that safety might be improved across an entire system, but it also carries unique challenges.
+
+Agencies will need to consider the following questions when selecting strategies to implement:
+
+- J **Safety effectiveness**  How likely will it address the safety problem?
+- J **Public acceptance**  How will the strategy be accepted by the public? What kind of marketing will be needed to communicate the intent and benefit of the strategy?
+- J **Stakeholders and partners** Which parties will need to be involved in implementing the strategy?
+- J **Cost efficiency** What kind of return on the dollar would be expected?
+- J **Time** How long will it take to implement the strategy?
+
+Communication is critically important for system-level safety strategies. Both the general public and road users affected by the strategy must understand the benefits. Other public agencies may need to integrate their efforts with the proposed safety strategy. Administrators, lawmakers, and other key decision-making personnel must understand how the strategy will improve road safety for their constituency and bring an overall financial benefit. Unit 5 provides more discussion on communication, marketing, and
+
+### **Ohio's strategies for older driver safety**
+
+Ohio identified three strategies to address the older driver emphasis area in their 2014 SHSP:
+
+- J Coordinate older driver messages developed by multi-agency communication committee.
+- J Create a comprehensive and coordinated outreach effort that educates older drivers and their caregivers on driving risks and remedies.
+- J Encourage roadway design and engineering measures that reduce the risks of traffic crashes for older drivers.
+
+outreach for agencies who seek to implement system-level safety strategies.
+
+Evaluating a system-level strategy (e.g., program or intervention) to determine its effectiveness is a critical but often overlooked step. The transportation agency in charge should evaluate the effect of the safety strategy using good quality data; ideally the same type of data that was used to identify the safety problem initially. If a program or intervention is not effective, the overseeing agency should consider why this might be the case. Can the program be improved, or should other approaches be considered instead? If successful, how can the intervention be institutionalized to ensure long term support (and therefore lasting change)? Finally, it is important to remember that success or failure in one location does not guarantee the same results at a different location.
+
+## **Example of System-Level Safety Management**
+
+The following provides an example of using system-level safety management to address a specific problem. This example demonstrates the three general components of safety management presented in this unit.
+
+### **1. Identify the safety problem.**
+
+County A noticed a large number of crashes involving 16-17 year old drivers occurring weekdays between 11:00am and 1:00pm. Neighboring counties have not experienced this problem. County officials coordinate with school district staff to tackle this issue.
+
+In exploring the problem, the officials discover that County A is the only jurisdiction that has an open campus lunch policy allowing students to leave school during their lunch period. Allowing teens to leave campus during lunch means there are many young, inexperienced drivers on the roads at the same time. They may be carrying additional passengers which research has established leads to an increased risk of a fatal crash.**60,61** The brief lunch period also results in pressure to get back in time for the next class. Combined, these factors lead to a risky driving situation and an increased risk of crashing.
+
+**61**
+
+**60**
+
+Chen, L., Baker, S.P., Braver, E.R., & Li, G. (2000). Carrying Passengers as a Risk Factor for Crashes Fatal to 16- and 17-Year-Old Drivers. Journal of the American Medical Association, 283, 1578-1582.
+
+Tefft B.C., Williams A.F., & Grabowski J.G. (2013). Teen driver risk in relation to age and number of passengers, United States, 2007-2010. Traffic Injury Prevention, 14, 283-292.
+
+## **2. Develop potential safety strategies.**
+
+In this situation, an informational approach that simply tells teenagers about the problem would likely not make a difference. Teens are not crashing because they lack information about the importance of safe driving or the consequences of
+
+unsafe driving. Teens are crashing largely because they lack the driving experience that equips most drivers to intuitively/near instantaneously do the things necessary to avoid crashing. Because of this, changing the environment is more likely to be effective.
+
+The officials recognize that eliminating the policy that allows students to leave campus during lunch would lead to a reduction in crashes during this time. This policy would eliminate exposure to the risky driving situation and reduce the potential for crashes.
+
+#### **3. Select and implement strategies.**
+
+The school districts accordingly eliminate the policy allowing students to leave campus during lunch. They recognize that this policy change should be evaluated to determine its safety effect. Crash data would be needed to examine whether the closed school lunch policy has an effect on weekday crashes between 11:00am and 1:00pm. However, it will take many years to accumulate enough data for this evaluation. In this example, there is a proxy measure that can be used in the interim. A before and after observational survey with an appropriate control could quantify the number of students leaving campus during lunch before and after the change. In this case the officials know that the proxy measure (reduced driving from 11:00am to 1:00 pm) is a guaranteed indicator of crash reduction for this specific problem. However, it is not often the case that proxy measures are so closely aligned to the outcome of interest.
+
+![](_page_148_Picture_0.jpeg)
+
+## **Unit Summary**
+
+Solving road safety problems requires a comprehensive process to identify safety problems, develop potential safety strategies, and select and implement those strategies. To get the most effective results, this process must be based on solid safety data, particularly good quality crash data. The methods of undertaking the safety management process will depend on the scope of the effort.
+
+Safety management of individual sites involves a six-step process of screening the network for highpriority sites, diagnosing the safety issues at those sites, selecting appropriate countermeasures,
+
+conducting an economic appraisal for all options, prioritizing the countermeasure projects based on estimated costs and benefits, and evaluating the countermeasure performance afterwards. Safety management at a system-level involves identifying safety problems by examining crash trends or using a systemic approach to identifying high-risk road characteristics. State agencies who are developing system-wide safety strategies must examine the data trends and the road users involved. They must consider factors, such as how system-wide policies and programs will be accepted by the public and who will be the partners to involve in implementing the safety strategy.
+
+#### **EXERCISES**
+
+- J **PRESENT** an example road safety problem and compare and contrast the ways in which the problem could be addressed at a system-level vs. site-level.
+- J Your state has a small, rural, mountainous county where a large number of motorcycle crashes are happening. The crash rate per registered motorcycle in this county is nearly 10 times the state average. Upon further investigation you learn that this county is a popular motorcycling tourist destination. People come from all over the country to ride the curvy mountain roads. In fact, the majority of people involved in crashes are not from that area at all. Clusters of crashes occur on certain curves. What are some approaches that could be used to reduce crashes in this county? How could these approaches be evaluated? In particular, **DETAIL** how you would apply the three major components described in this unit:
+  - J Identify the safety problem
+  - J Develop potential safety strategies
+  - J Selecting and implement strategies
+
+When you work through this process, recall the discussion of human behavior from Unit 2. What are possible behaviors leading to the safety problem? What other factors could be influencing this behavior? How does this affect your identification and selection of potential safety strategies?
+
+J If possible, **OBTAIN** three to five years of crash data for an intersection or section of road in your area. You will likely need to contact the controlling agency – the State DOT, county, or city. Describe how you would apply the steps in Chapter
+
+- 11 on site-level safety management to this location (the network screening step would not apply since this location is already identified). Consider safety strategies across a range of disciplines (e.g., engineering, law enforcement, public communication and education, etc.).
+- J This exercise should be conducting using the Excel spreadsheet that accompanies this book. The goal of this exercise is to **USE** selected performance metrics to create a ranked list of sites for further investigation as part of a network screening effort. The Excel spreadsheet includes nearly 1,400 intersections, or sites. Each site has a unique ID number, traffic volume data, and other information about its location and characteristics. Three performance metrics have been calculated for each site. These have been calculated using five years of data (2010-2014) and one year of data (2014), resulting in a total of six performance metrics per site. Your assignment is to rank the sites using these various performance metrics and document the results. Document the twenty highest priority sites based on each method. Use the results to answer the following questions:
+  - J What were some of the sites that routinely ranked in the top twenty? What were some of their characteristics (volumes, number of lanes, stop/signal control)?
+  - J Were there any sites that were only occasionally present in the top twenty? What were some characteristics of these sites?
+
+THIS PAGE INTENTIONALLY LEFT BLANK
+
+![](_page_151_Picture_0.jpeg)
+
+## **Implementing Road Safety Efforts UNIT 5**
+
+#### **LEARNING OBJECTIVES**
+
+After reading the chapters and completing exercises in Unit 5, the reader will be able to:
+
+- J **IDENTIFY** the current road safety partner agencies and define their role in addressing safety problems
+- J **DEFINE** three areas of road safety research
+- J **DEFINE** the characteristics of strategic communications
+- J **RECOGNIZE** potential avenues for advancing road safety efforts
+
+## **Who Does What**
+
+The greatest gains in road safety occur when transportation agencies work together rather than tackling problems alone. This can be challenging given the fragmented nature of transportation governance in the U.S. There are numerous agencies operating in different focus areas and at different levels. This chapter presents an overview of the various agencies and organizations that have a direct hand in advancing road safety and the initiatives that they undertake.
+
+U.S. transportation agencies are typically structured around particular focus areas, such as roadway, vehicles, or road users. This approach is also seen on the
+
+international scale – the United Nations (U.N.) used a generalization called the "Five Pillar" structure as part of the Decade of Action for Road Safety. **<sup>1</sup>** The U.N. recognized that efforts to improve road safety must address various pillars including road safety
+
+management, safer roads and mobility, safer vehicles, safer road users, and better post-crash response. **<sup>2</sup>**
+
+Likewise, U.S. transportation agencies are organized to address focus areas that are similar in theme to the U.N. five pillars, though not the same. Table 5-1 shows how agencies at all levels (Federal, State, and local) address five focus areas in road safety.
+
+**1**
+
+United Nations, A/RES/64/255, Geneva, 2010
+
+**2**
+
+Global Status Report on Road Safety 2013: Supporting a Decade of Action, World Health Organization, ISBN 978 92 4 156456 4, 2013.
+
+| FOCUS AREA                     | FEDERAL                                                               | STATE                                                                            | LOCAL                                                                |
+|--------------------------------|-----------------------------------------------------------------------|----------------------------------------------------------------------------------|----------------------------------------------------------------------|
+| Road Design /<br>Environment   | Federal Highway<br>Administration                                     | Departments of<br>transportation                                                 | City public works<br>Metropolitan/rural<br>planning organizations    |
+| Road User<br>Behavior          | National Highway<br>Traffic Safety<br>Administration<br>Federal Motor | Highway safety offices<br>Departments of<br>motor vehicles<br>Health departments | No specific agency                                                   |
+| Vehicle Design /<br>Technology | Carrier Safety<br>Administration                                      | Departments of<br>motor vehicles                                                 | No specific agency                                                   |
+| Law Enforcement                | No specific agency                                                    | State police /<br>highway patrol                                                 | Police departments                                                   |
+| Transit Safety                 | Federal Transit<br>Administration                                     | No specific agency                                                               | Metropolitan planning<br>organizations<br>Municipal transit agencies |
+
+**TABLE 5-1**: Transportation Agencies by Focus Area
+
+## **Federal Agencies**
+
+The Federal role in implementing road safety initiative is carried out largely through the U.S. Department of Transportation (USDOT) and the many agencies under that department. These agencies are each tasked with a specific focus area as the Federal Government seeks to address safety issues for various modes of travel. These agencies include:
+
+- J **Federal Highway Administration**
+- J **National Highway Traffic Safety Administration**
+- J **Federal Motor Carrier Safety Administration**
+- J **Federal Transit Administration**
+- J **Federal Railroad Administration**
+
+## **Federal Highway Administration**
+
+**www.fhwa.dot.gov**
+
+**Focus Area: Road Design and Environment**
+
+The Federal Highway Administration (FHWA) works to reduce highway fatalities through partnerships with State and local agencies, community groups, and private industry. The FHWA Office of Safety advocates designs and technologies that improve road safety and administers safety programs, such as the Highway Safety Improvement Program (HSIP). FHWA's Resource Center also provides technical assistance, technology deployment, and training. FHWA has a significant role in safety research through the Office of Safety Research and Development, which develops and implements safety innovations through teams of research engineers, scientists, and psychologists.
+
+In addition, FHWA oversees the Local and Tribal Technical Assistance Program (LTAP/TTAP), which provides information and training programs to local agencies and Native American Indian tribes to improve road safety.**<sup>3</sup>** Further, FHWA maintains division offices in each state to deliver assistance to partners and customers in highway transportation and safety services at the State level.
+
+## **National Highway Traffic Safety Administration**
+
+**www.nhtsa.gov**
+
+**Focus Areas: Road User Behavior and Vehicle Design and Technology**
+
+The National Highway Traffic Safety Administration (NHTSA) focuses on the safety of the vehicle, driver, and road user. NHTSA investigates safety defects in motor vehicles, establishes and enforces safety performance standards for motor vehicles and motor vehicle equipment, sets and enforces fuel economy standards, collects data, and conducts research on driver behavior and traffic safety, and helps states and local communities reduce the threat of impaired driving and other dangerous road user behaviors.
+
+NHTSA carries out research and demonstration programs in many behavioral areas including impaired driving, occupant protection, speed management (shared with FHWA), pedestrian, motorcycle and bicycle safety, older and younger road users, drowsy, and distracted driving. NHTSA is also the lead Federal agency for emergency medical services (EMS) and 9-1-1 systems.
+
+**4**
+
+"Who We Are and What We Do," accessed June 20, 2013, [https://www.](https://www.nhtsa.gov/about-nhtsa) [nhtsa.gov/about](https://www.nhtsa.gov/about-nhtsa)[nhtsa](https://www.nhtsa.gov/about-nhtsa).
+
+"About the National Program," last updated June 20, 2013, accessed June 20, 2013, [http://](http://www.ltap.org/about/) [www.ltap.org/about/](http://www.ltap.org/about/).
+
+## **Federal Motor Carrier Safety Administration**
+
+**www.fmcsa.dot.gov**
+
+**Focus Areas: Road User Behavior and Vehicle Design and Technology**
+
+The Federal Motor Carrier Safety Administration (FMCSA) focuses on reducing crashes, injuries, and fatalities involving commercial use of large trucks and buses. FMCSA develops and enforces researchbased regulations that balance safety and efficiency. The agency manages safety information systems to enforce safety regulations with regards to drivers who have high risk in factors, such as health, age, experience, and education.
+
+FMCSA also targets educational messages to carriers, commercial drivers, and the public.**<sup>5</sup>** Some key programs administered by the agency include:
+
+J **Commercial Driver's License Program:** FMCSA develops,
+
+- monitors, and ensures compliance with the commercial driving licensing standards for drivers, carriers, and States.
+- J **Motor Carrier Safety Identification and Information Systems:** FMCSA provides safety data, State and national crash statistics, current analysis results, and detailed motor carrier safety performance data to industry and the public. This data allows Federal and State enforcement officials to target inspections and investigations on higher risk carriers, vehicles, and drivers.
+- J **Safety education and outreach:** FMCSA implements educational strategies to increase motor carrier compliance with the safety regulations and reduce the likelihood of a commercial vehicle crash. Messages are aimed at all highway users including passenger car drivers, truck drivers, pedestrians, and bicyclists.**<sup>6</sup>**
+
+**5**
+
+"About FMCSA," accessed June 20, 2013, [https://www.](https://www.fmcsa.dot.gov/mission/about-us) [fmcsa.dot.gov/](https://www.fmcsa.dot.gov/mission/about-us) [mission/about-us](https://www.fmcsa.dot.gov/mission/about-us).
+
+**6**
+
+"Key FMCSA Programs," accessed October 15, 2013, [https://](https://www.fmcsa.dot.gov/mission/we-are-fmcsa-brochure) [www.fmcsa.dot.gov/](https://www.fmcsa.dot.gov/mission/we-are-fmcsa-brochure) [mission/we-are](https://www.fmcsa.dot.gov/mission/we-are-fmcsa-brochure)[fmcsa-brochure.](https://www.fmcsa.dot.gov/mission/we-are-fmcsa-brochure)
+
+![](_page_154_Picture_13.jpeg)
+
+The Federal Motor Carrier Safety Administration develops, monitors, and ensures compliance with commercial driving licensing standards.
+
+![](_page_155_Picture_0.jpeg)
+
+The Federal Transit Administration seeks to improve public transportation, such as buses.
+
+## **Federal Transit Administration**
+
+**www.transit.dot.gov**
+
+**Focus Area: Transit Safety**
+
+The Federal Transit Administration (FTA) seeks to improve public transportation by assisting State and local governments with planning, implementation, and financing of public transportation projects.**<sup>7</sup>** FTA manages many transit-oriented safety programs including:
+
+- J **Bus and Bus Facilities:** This program provides capital funding to replace, rehabilitate, and purchase buses and related equipment and to construct busrelated facilities.
+- J **Public Transportation Emergency Relief Program:** This program helps States and public transportation systems pay
+
+for protecting, repairing, and/ or replacing equipment and facilities that may suffer or have suffered serious damage because of an emergency including natural disasters.
+
+- J **Research, Development, Demonstration, and Deployment Projects:** This program supports research activities that improve the safety, reliability, efficiency, and sustainability of public transportation.
+- J **Transit Safety and Oversight:** FTA has the authority to establish and enforce a new comprehensive framework to oversee the safety of public transportation throughout the United States as it pertains to heavy rail, light rail, buses, ferries, and streetcars.**<sup>8</sup>**
+
+**7**
+
+"Federal Transit Administration," last updated September 6, 2013, [https://](https://www.usa.gov/federal-agencies/federal-transit-administration) [www.usa.gov/](https://www.usa.gov/federal-agencies/federal-transit-administration) [federal-agencies/](https://www.usa.gov/federal-agencies/federal-transit-administration) [federal-transit](https://www.usa.gov/federal-agencies/federal-transit-administration)[administration](https://www.usa.gov/federal-agencies/federal-transit-administration).
+
+**8**
+
+"MAP-21 Programs," accessed October 16, 2013, [https://](https://www.transit.dot.gov/regulations-and-guidance/legislation/map-21/map-21-program-fact-sheets) [www.transit.dot.](https://www.transit.dot.gov/regulations-and-guidance/legislation/map-21/map-21-program-fact-sheets) [gov/regulations](https://www.transit.dot.gov/regulations-and-guidance/legislation/map-21/map-21-program-fact-sheets)[and-guidance/](https://www.transit.dot.gov/regulations-and-guidance/legislation/map-21/map-21-program-fact-sheets) [legislation/map-21/](https://www.transit.dot.gov/regulations-and-guidance/legislation/map-21/map-21-program-fact-sheets) [map-21-program](https://www.transit.dot.gov/regulations-and-guidance/legislation/map-21/map-21-program-fact-sheets)[fact-sheets.](https://www.transit.dot.gov/regulations-and-guidance/legislation/map-21/map-21-program-fact-sheets)
+
+## **Federal Safety Programs**
+
+Federal agencies advance road safety through numerous programs and initiatives. Federal programs can be very influential due to large funding sources provided by Federal legislation. These funds are often distributed to State and local levels to implement various improvements to roads and intersections.
+
+Specific funding programs can change with each new piece of transportation legislation. However, it may be useful to look at an overview of some of the types of current and past funding programs. Below are listed a few programs that have been widely used through the years to develop and implement improvements to road safety:
+
+- J **Highway Safety Improvement Program (FHWA)**
+- J **Traffic Records Improvement Grants (NHTSA)**
+- J **Safety Data Improvement Program Grant (FMCSA)**
+
+## **Highway Safety Improvement Program (FHWA)**
+
+HSIP is a Federal program focused on infrastructure improvements that will lead to significant reduction in traffic fatalities and serious injuries on all public roads. HSIP is Federally funded and administered by FHWA, but it is implemented by the State departments of transportation per the strategies laid out in the State's Strategic Highway Safety Plan (SHSP). Funding is provided for safety-related infrastructure improvements, such as sidewalks, traffic calming, or signing upgrades. The States are required to develop a **data-driven**, strategic approach
+
+for improving highway safety through the implementation of such infrastructure improvements.**<sup>9</sup>** States are also required to report to the U.S. Secretary of Transportation on progress made implementing highway safety improvements and the extent to which fatalities and serious injuries on all public roads have been reduced.
+
+## **Traffic Records Improvement Grants (NHTSA)**
+
+NHTSA administers Federal funding to encourage States to implement programs that will improve the timeliness, accuracy, completeness, uniformity, integration, and accessibility of State data used in traffic safety programs. The Federal SAFETEA-LU legislation established this program of incentive grants, and the funding continued under subsequent legislation. The funds were to be used to evaluate the effectiveness of efforts to make safety data improvements, to link safety data systems within the State, and to improve the compatibility of the State data system with national data systems and data systems of other States. A State may use these grant funds only to implement such data improvement programs. To qualify, a State must meet certain requirements including a functioning Traffic Records Coordinating Committee (TRCC), a strategic plan to address data deficiencies, and a regular traffic records assessment.**<sup>10</sup>**
+
+## **Safety Data Improvement Program Grant (FMCSA)**
+
+The Safety Data Improvement Program (SaDIP), administered by FMCSA, provides financial and **9**
+
+Source: "Highway Safety Improvement Program (HSIP)," accessed August 12, 2013, http://safety. fhwa.dot.gov/hsip/ and "HSIP History," accessed August 12, 2013, [http://](https://safety.fhwa.dot.gov/hsip/gen_info/hsip_history.cfm) [safety.fhwa.dot.](https://safety.fhwa.dot.gov/hsip/gen_info/hsip_history.cfm) [gov/hsip/gen\\_info/](https://safety.fhwa.dot.gov/hsip/gen_info/hsip_history.cfm) [hsip\\_history.cfm.](https://safety.fhwa.dot.gov/hsip/gen_info/hsip_history.cfm)
+
+#### **10**
+
+NHTSA, Section 408 SAFETEA-LU Fact Sheet, [https://one.](https://one.nhtsa.gov/Laws-&-Regulations/Section-408-SAFETEA–LU-Fact-Sheet) [nhtsa.gov/Laws-](https://one.nhtsa.gov/Laws-&-Regulations/Section-408-SAFETEA–LU-Fact-Sheet) [&-Regulations/](https://one.nhtsa.gov/Laws-&-Regulations/Section-408-SAFETEA–LU-Fact-Sheet) [Section-408-](https://one.nhtsa.gov/Laws-&-Regulations/Section-408-SAFETEA–LU-Fact-Sheet) [SAFETEA%](https://one.nhtsa.gov/Laws-&-Regulations/Section-408-SAFETEA–LU-Fact-Sheet) [E2%80%93](https://one.nhtsa.gov/Laws-&-Regulations/Section-408-SAFETEA–LU-Fact-Sheet) [LU-Fact-Sheet](https://one.nhtsa.gov/Laws-&-Regulations/Section-408-SAFETEA–LU-Fact-Sheet)
+
+#### **Data-driven**
+
+An approach of which the priorities are determined by examination of crash data or other objective and reliable safety data, rather than priorities set by preferences of a few parties, current "hot" topics, or high profile rare events.
+
+technical assistance to States to improve data collected on truck and bus crashes that result in injuries or fatalities. The assistance is provided to State departments of public safety, departments of transportation, or State law enforcement agencies. SaDIP funds have been used to hire staff to code safety performance data, purchase software for field data collection, and revise outdated crash forms.
+
+FMCSA maintains the Motor Carrier Management Information System (MCMIS) and supplies access to the system for designated employees in each State through SAFETYNET, an online network of safety data. States use MCMIS and SAFETYNET to enter data on motor carriers, drivers, compliance reviews, inspections, and crashes. At the national level, FMCSA uses the data to characterize the safety experience of commercial motor vehicles, and to help States with the task of identifying high risk carriers and drivers. The data are also used by motor carrier companies, safety researchers, advocacy groups, insurance companies, the public, and a variety of other entities.
+
+## **State Agencies**
+
+All fifty States, the District of Columbia, and Puerto Rico administer road safety programs. State agencies administer roadway systems, driver licensing, injury prevention programs, traffic law enforcement, and other road safety activities. However, assignment of these responsibilities varies widely from State to State. In many cases, two or three government agencies are responsible for most or all of these activities. Other States distribute these responsibilities to numerous agencies and offices. Regardless of how these responsibilities are distributed, States share a vital role in improving road safety for all citizens.
+
+In general, State agencies that address road safety issues include:
+
+- J State departments of transportation
+- J State highway safety offices
+- J State departments of motor vehicles
+- J State highway patrols
+- J State health departments
+
+State departments of transportation oversee design, construction, maintenance, and operation of roads.
+
+![](_page_157_Picture_11.jpeg)
+
+## **State Departments of Transportation**
+
+#### **Focus Area: Road Design and Environment**
+
+Each State has a department of transportation (DOT), which oversees the design, construction, maintenance, and operation of the State's roads. This agency may also be called the State Highway Administration or Department of Roads. State DOTs have many official responsibilities. For highway safety issues, State DOTs have official transportation planning, programming, and project implementation responsibility. These agencies typically oversee all Interstate highways and most primary highways (State highways). State DOTs focus on roadway safety, and thus work in direct partnership with FHWA. They serve as liaisons between the Federal and local transportation agencies and provide resources and technical assistance to local agencies. State DOTs coordinate the use of Federal HSIP funds to improve roads and intersections on the local level.
+
+In some States, the DOT administers, maintains, and operates county and city streets or secondary roads. State DOTs also work cooperatively with tolling authorities, ports, local agencies, and special districts that own, operate, or maintain portions of the transportation network.
+
+The State DOT typically leads the development of the SHSP, a statewide-coordinated safety plan that provides a comprehensive framework for reducing highway fatalities and serious injuries on all public roads. The State DOT
+
+also develops long-range (20 to 30 year) transportation plans and short range (five to 10 year) plans that outline the vision of the transportation network and which projects will be constructed to fulfill that vision.
+
+## **State Highway Safety Offices**
+
+#### **Focus Area: Road User Behavior**
+
+State Highway Safety Offices (SHSOs) administer a variety of national highway safety grant programs authorized and funded through Federal legislation.**<sup>11</sup>** The governor of each State appoints a highway safety representative to administer the Federal Highway Safety Grant Program and numerous other highway safety programs designated by Congress. The governor's representative promotes safety initiatives in the State, such as high visibility enforcement campaigns like Click It or Ticket.
+
+The State Highway Safety Office focuses on behavioral aspects of roadway users, and thus works in direct partnership with NHTSA. Safety programs implemented by the SHSO include:
+
+- J Encouraging safety belt, child car seat, and helmet use
+- J Discouraging impaired driving
+- J Promoting motorcycle safety
+- J Improving the skills of younger and older drivers
+
+## **State Departments of Motor Vehicles**
+
+**Focus Area: Vehicle Design and Technology**
+
+State Departments of Motor Vehicles
+
+**11**
+
+"SHSO Programs & Funding," accessed June 20, 2013, [http://www.ghsa.](http://www.ghsa.org/about/federal-grant-programs) [org/about/federal](http://www.ghsa.org/about/federal-grant-programs)[grant-programs](http://www.ghsa.org/about/federal-grant-programs).
+
+#### **Coordinated**
+
+People from many agencies come together to develop an SHSP, including those from the department of transportation, department of motor vehicles, state highway patrol, public health, universities, and others.
+
+#### **Comprehensive**
+
+Using all types of strategies to improve road safety, such as infrastructure improvements, law enforcement, and campaigns to change driver behavior. This is seen in the types of crashes which serve as the focus areas of an SHSP, such as speeding related crashes, which are most effectively addressed through a combination of speed enforcement, engineering modifications, and behavioral campaigns.
+
+State highway patrols enforce motor vehicle laws and regulations, investigate crashes, and work to identify enforcement needs.
+
+![](_page_159_Picture_5.jpeg)
+
+(DMVs) administer State programs for driver licensing, and automobile inspection and registration. Generally, DMVs reside either within the State DOT or a department of public safety. A few States have a cabinet-level DMV.
+
+The DMV is responsible for identifying at-risk drivers and maintaining driver records. The agency also implements driver license standards, monitors graduated licensing programs, and establishes requirements for driver education. Some State DMVs also serve as the primary owners of the statewide crash data.
+
+## **State Highway Patrols**
+
+#### **Focus Area: Law Enforcement**
+
+State highway patrols (also known as State police and State patrols) operate in every State except Hawaii. State police patrol highways and enforce motor vehicle laws and regulations.
+
+State law enforcement agencies play an important role in reducing the frequency and severity of crashes. At the scene of crashes, State police direct traffic, administer first aid, call for emergency equipment, write traffic citations, and complete crash reports.
+
+State highway patrols also
+
+investigate motor vehicle crashes, which are important sources of State and Federal crash data. They work closely with State highway safety representatives to identify enforcement needs. They play a vital role in implementing impaired driving laws, safety belt use, and other safety programs. Certain troopers in the State highway patrol are tasked with inspecting large trucks to ensure the driver and the vehicle comply with safety regulations, such as vehicle size and weight, driver hours of service, and medical fitness.
+
+## **State Health Departments**
+
+#### **Focus Area: Road User Behavior**
+
+State health departments also play an important role in reducing crash severity. These agencies are typically responsible for statewide trauma center planning. State health departments provide training, certification, and technical assistance for EMS providers, administer injury prevention programs, and maintain trauma and injury databases. Some State health departments coordinate with other public agencies and community groups to promote young driver safety, older driver safety, child passenger safety, and pedestrian and bicycle safety.
+
+## **State Safety Plans and Programs**
+
+State agencies use numerous approaches to improve road safety within their State. Often, they seek to identify State-specific safety issues and direct Federal or State funding to solve those issues. State agencies take the lead in developing statewide safety plans or programs, many of which are encouraged or required by the Federal Government. Although States differ in their specific safety improvement efforts, the following plans or programs are developed in every State:
+
+- J **Strategic Highway Safety Plan**
+- J **Long Range Transportation Plan**
+- J **Statewide Transportation Improvement Program**
+- J **Railway-Highway Crossing Program**
+- J **Highway Safety Program**
+
+Although the HSIP was previously covered under Federal safety programs, it should be noted that the State plays the major role in selecting locations that need safety improvement, designing, and implementing the safety improvement, and reporting annually on all the HSIP funded projects that were constructed that year.
+
+## **Strategic Highway Safety Plan**
+
+A State's SHSP is a statewide**coordinated** safety plan that provides a **comprehensive** framework for reducing highway fatalities and serious injuries on all public roads. An SHSP identifies a State's key safety needs and guides investment decisions toward strategies with the
+
+highest potential to save lives and prevent injuries. Since 2005, Federal legislation has required States to develop, implement,evaluate, and update their SHSP.**12,13**
+
+The State DOT develops an SHSP in a cooperative process with local, State, Federal, tribal, and private sector safety stakeholders. It is a data-driven, multi-year plan that establishes statewide goals, objectives, and key emphasis areas. The development of an SHSP provides a venue for highway safety partners in the State to align goals, leverage resources (i.e., combine Federal and State resources), and collectively address the State's safety challenges.**<sup>14</sup>**
+
+An ideal SHSP meets several criteria:
+
+- J It addresses engineering, management, operation, education, enforcement, and emergency service elements of highway safety as key factors in evaluating highway projects.
+- J It considers safety needs of, and high-fatality segments of, all public roads.
+- J It considers the results of State, regional, or local transportation and highway safety planning processes.
+- J It describes strategies to reduce or eliminate safety hazards.
+- J It gains approval of the governor of the State or a responsible State agency.**<sup>15</sup>**
+
+As mentioned on page 5-5, in order to spend HSIP funds, a State must have a current SHSP, produce a program of projects or strategies to reduce safety problems, and evaluate the SHSP on a regular basis.**<sup>16</sup>**
+
+**Coordinated, Comprehensive**
+
+See previous page.
+
+**12**
+
+"Strategic Highway Safety Plans: A Champion's Guidebook to Saving Lives 2nd ed.," Federal Highway Administration (Washington, D.C., October 2012), History and Background, [http://](https://safety.fhwa.dot.gov/shsp/guidebook/) [safety.fhwa.dot.](https://safety.fhwa.dot.gov/shsp/guidebook/) [gov/hsip/shsp/](https://safety.fhwa.dot.gov/shsp/guidebook/) [guidebook/ovrvw.](https://safety.fhwa.dot.gov/shsp/guidebook/) [cfm](https://safety.fhwa.dot.gov/shsp/guidebook/)
+
+**13 14**
+
+"Strategic Highway Safety Plan (SHSP)," accessed August 13, 2013, [http://safety.](https://safety.fhwa.dot.gov/shsp/) [fhwa.dot.gov/hsip/](https://safety.fhwa.dot.gov/shsp/) [shsp/.](https://safety.fhwa.dot.gov/shsp/)
+
+**15**
+
+"Map-21," Title 23 U.S.C. (2012), accessed August 19, 2013, [http://www.](http://www.gpo.gov/fdsys/pkg/PLAW-112publ141/pdf/PLAW-112publ141.pdf) [gpo.gov/fdsys/pkg/](http://www.gpo.gov/fdsys/pkg/PLAW-112publ141/pdf/PLAW-112publ141.pdf) [PLAW-112publ141/](http://www.gpo.gov/fdsys/pkg/PLAW-112publ141/pdf/PLAW-112publ141.pdf) [pdf/PLAW-](http://www.gpo.gov/fdsys/pkg/PLAW-112publ141/pdf/PLAW-112publ141.pdf)[112publ141.pdf](http://www.gpo.gov/fdsys/pkg/PLAW-112publ141/pdf/PLAW-112publ141.pdf)
+
+**16**
+
+"Highway Safety Improvement Plan (HSIP)," accessed August 14, 2013, [http://www.fhwa.](https://www.fhwa.dot.gov/map21/factsheets/hsip.cfm) [dot.gov/map21/hsip.](https://www.fhwa.dot.gov/map21/factsheets/hsip.cfm) [cfm](https://www.fhwa.dot.gov/map21/factsheets/hsip.cfm).
+
+## **Long-Range Transportation Plans**
+
+Long-range transportation plans (LRTPs) identify transportation goals, objectives, needs, and performance measures over a 20- to 25-year horizon and provide policy and strategy recommendations for accommodating those needs. LRTPs are prepared at both the State and MPO level. LRTPs are fiscally-unconstrained and typically present a systems-level approach that considers roadways, transit, pedestrian, and bicycle facilities. LRTP's have wide scopes; the components of the plan may be policy-oriented and strategic or focused on specific projects. The types of improvements range widely, as well. Safety-focused improvements in a LRTP may be directed at infrastructure, such as building new interchanges or bringing certain highways up to current design standards, or behavioral efforts, such as addressing seat belt use or
+
+**18**
+
+**17**
+
+"Railway-Highway Crossings Program," accessed August 9, 2013, [http://](https://www.fhwa.dot.gov/map21/factsheets/rhc.cfm) [www.fhwa.dot.gov/](https://www.fhwa.dot.gov/map21/factsheets/rhc.cfm) [map21/rhc.cfm.](https://www.fhwa.dot.gov/map21/factsheets/rhc.cfm)
+
+Title 49, United States Code, § 5304
+
+**19**
+
+Railroad-Highway Grade Crossing Handbook 2nd ed. Federal Highway Administration (Washington D.C., August 2007)
+
+## **Statewide Transportation Improvement Programs**
+
+aggressive driving.
+
+The Statewide Transportation Improvement Program (STIP) identifies the funding and scheduling of transportation projects throughout the State that support the goals identified in the LRTP. STIPs are short-range (typically an outlook of five to ten years) and fiscally constrained, meaning that the projects must have designated funding. While many STIP projects are constructed for capacity or mobility reasons (i.e., build a bypass or widen a road), there are also STIP projects that are
+
+focused on improving safety, such as widening shoulders or installing rumble strips. Projects included in STIPs must have identified funding sources (e.g., HSIP, State, or local funding). The State DOT identifies projects in areas outside MPOs, such as rural areas and smaller urban jurisdictions, for inclusion in the STIP.**<sup>17</sup>**
+
+## **Railway-Highway Crossings Program**
+
+The Railway-Highway Crossings Program funds safety improvements to reduce the number of fatalities, injuries, and crashes at public grade crossings.**<sup>18</sup>** A grade crossing is a location where a public highway, road, street, or private roadway (including associated sidewalks and pathways) crosses a railroad track at the same level as the street. These locations are high-risk spots for road users. The United States has more than 200,000 grade crossings.**<sup>19</sup>** Types of crossing improvements that the Railway-Highway Crossings Program implements include:
+
+- J **Crossing approach improvements:** projects such as channelization, new or upgraded signals on the approach, guardrail, pedestrian/ bicycle path improvements near the crossing, and illumination
+- J **Crossing warning sign and pavement marking Improvements:** projects such as signs, pavement markings, and/or delineation where these project activities are the predominant safety improvements
+- J **Active grade crossing equipment installation/upgrade:** projects such as new or upgraded flashing lights and gates, track circuitry,
+
+![](_page_162_Picture_0.jpeg)
+
+The Railway-Highway Crossings Program funds safety improvements at crossings.
+
+wayside horns, and signal improvements such as railwayhighway signal interconnection and pre-emption.**<sup>20</sup>**
+
+## **Highway Safety Program**
+
+Each State administers a Highway Safety Program, approved by the U.S. Secretary of Transportation. The program is designed to reduce deaths and injuries on the road by targeting user behavior through education and enforcement campaigns.**<sup>21</sup>** The State conducts this program through the State highway safety office. A State is eligible for SHSP grants by having and implementing an approved
+
+Highway Safety Plan (HSP). The HSP establishes goals, performance measures, targets, strategies, and projects to improve highway safety in the State. It also documents the State's efforts to coordinate with the goals and strategies in the SHSP. However, the Highway Safety Program is distinct from an SHSP. SHSPs target improvements to infrastructure and road users, and are broad in content and context, while highway safety programs focus more on road user behavior.**<sup>22</sup>** An HSP might address issues such as excess speeds, proper use of occupant protection devices, driving while impaired, and quality of traffic records data.**<sup>23</sup>**
+
+**20**
+
+"Railway-Highway Crossings Program Reporting Guidance," accessed August 9, 2013, [http://](https://www.fhwa.dot.gov/map21/guidance/guiderhcp.cfm) [www.fhwa.dot.gov/](https://www.fhwa.dot.gov/map21/guidance/guiderhcp.cfm) [map21/guidance/](https://www.fhwa.dot.gov/map21/guidance/guiderhcp.cfm) [guiderhcp.cfm.](https://www.fhwa.dot.gov/map21/guidance/guiderhcp.cfm)
+
+**21 23**
+
+"MAP-21," Title 23, U.S.C. (2012), accessed August 16, 2013, [http://](https://www.fhwa.dot.gov/map21/docs/title23usc.pdf) [www.fhwa.dot.](https://www.fhwa.dot.gov/map21/docs/title23usc.pdf) [gov/map21/docs/](https://www.fhwa.dot.gov/map21/docs/title23usc.pdf) [title23usc.pdf, Sec.](https://www.fhwa.dot.gov/map21/docs/title23usc.pdf)  [402.](https://www.fhwa.dot.gov/map21/docs/title23usc.pdf)
+
+**22**
+
+"MAP-21," Title 23, U.S.C. (2012), accessed August 16, 2013, [http://](https://www.fhwa.dot.gov/map21/docs/title23usc.pdf) [www.fhwa.dot.](https://www.fhwa.dot.gov/map21/docs/title23usc.pdf) [gov/map21/docs/](https://www.fhwa.dot.gov/map21/docs/title23usc.pdf) [title23usc.pdf](https://www.fhwa.dot.gov/map21/docs/title23usc.pdf), Sec. 148.
+
+## **Local Agencies**
+
+intersections.
+
+Local agencies, such as city and county governments, play an important role in improving road safety and identifying and selecting transportation projects. These agencies that administer roads at the local level may be called by various names: public road agency, department of public works, departments of transportation, or road commissions. Due to their smaller size, many local agencies may not have a staff member who is specifically focused on road safety. The urban nature of their jurisdiction naturally causes their efforts to be focused on different types of road safety topics than a State DOT. For example, a city transportation department would typically focus on urban elements such as sidewalks, transit accommodations, and high density access management, where as a State DOT would typically be focused on more rural elements, such as high speed curves and isolated
+
+Most safety issues for local streets, intersections, or corridors are the responsibility of the city or county government. These agencies supplement State laws, establish traffic laws in their jurisdictions, and determine penalties for noncompliance. Local law enforcement agencies investigate crashes and submit crash data to State and Federal agencies. City and county planning and engineering staff help plan and design roads, bike lanes, and sidewalks. Many local police departments partner with State police to implement impaired driving, work zone safety, motorcycle safety, heavy truck, and safety belt education and enforcement programs. In some States, the State DOT owns many of the major roads in the city
+
+### **Charlotte Pedestrian Safety**
+
+The City of Charlotte developed its Transportation Action Plan (TAP) in 2011 to describe how to reach its safety and mobility transportation goals. The plan emphasized the safety of all road users and included objectives such as constructing 375 miles of new sidewalk by 2035.**<sup>24</sup>** To support the goal of pedestrian safety, Charlotte developed Charlotte WALKS, the city's first comprehensive Pedestrian Plan. This plan identified new strategies to meet the pedestrian safety and walkability goals in Charlotte's TAP.**<sup>25</sup>**
+
+and may coordinate with the local agency to identify potential safety improvements and get them installed. Many local agencies also collaborate with the State DOT to develop a Local Road Safety Plan.
+
+At the regional level, metropolitan planning organizations (MPOs) plan, program, and coordinate Federal highway and transit investments. When an urban area meets certain minimum characteristics (e.g., population), Federal law requires the creation of an MPO for the region to qualify for Federal highway or transit funds in urbanized areas. MPOs do not typically own or operate the transportation systems in their jurisdiction. MPOs play a coordination and consensus-building role in planning and programming funds for capital improvements, maintenance, and operations. MPOs involve local transportation providers in the planning process by coordinating with transit agencies, State and local highway departments, airport authorities, maritime operators, rail-freight operators, Amtrak, port operators, private providers of public transportation, and others within the MPO region.**<sup>26</sup>**
+
+#### **24**
+
+The City of Charlotte Transportation Action Plan Policy Document, 5 Year Update, August 22, 2011.
+
+#### **25**
+
+[http://charlottenc.](http://charlottenc.gov/Transportation/Programs/Pages/default.aspx) [gov/Transportation/](http://charlottenc.gov/Transportation/Programs/Pages/default.aspx) [Programs/Pages/](http://charlottenc.gov/Transportation/Programs/Pages/default.aspx) [default.aspx](http://charlottenc.gov/Transportation/Programs/Pages/default.aspx)
+
+#### **26**
+
+The Transportation Planning Process Briefing Book, Federal Highway Administration and Federal Transit Administration, 2015 Update, [http://www.fhwa.](https://www.fhwa.dot.gov/planning/publications/briefing_book/fhwahep15048.pdf) [dot.gov/planning/](https://www.fhwa.dot.gov/planning/publications/briefing_book/fhwahep15048.pdf) [publications/](https://www.fhwa.dot.gov/planning/publications/briefing_book/fhwahep15048.pdf) [briefing\\_book/](https://www.fhwa.dot.gov/planning/publications/briefing_book/fhwahep15048.pdf) [fhwahep15048.pdf](https://www.fhwa.dot.gov/planning/publications/briefing_book/fhwahep15048.pdf)
+
+![](_page_164_Picture_0.jpeg)
+
+## **Other Safety Partners**
+
+Although government agencies have the support of large budgets and institutional authority to implement improvements to road safety, they are not the only entities working to improve road safety. Government agencies work with partners from a variety of fields to improve the nation's roadways including those in private industry, special interest groups, and professional organizations.
+
+## **Private industry**
+
+#### **Automobile Manufacturers**
+
+Auto manufacturers have a critical effect on road safety by designing vehicles that assist the driver in avoiding crashes and that absorb energy in crashes that do occur. Federal standards stipulate that vehicles must have certain safety improvements, such as seat belts, air bags, and electronic stability control.**<sup>27</sup>** However, auto manufacturers have also implemented various non-required safety improvements. These improvements typically make use of emerging technologies or materials.
+
+For instance, in the early 2000's, auto manufacturers began
+
+manufacturing vehicles that had "smart" technologies to improve safety, such as collision warnings and assisted braking. These technologies, which were not required by the government, addressed some of the most common crash types, such as rear end crashes. These improvements also set the stage for more advanced automated vehicle designs and technologies.
+
+### **Insurance Companies**
+
+Insurance companies often assist in identifying ways to improve safety on the nation's roads. The most notable organization in this respect is the Insurance Institute for Highway Safety (IIHS) and its sister organization, the Highway Loss Data Institute (HLDI). These are organizations that study road safety issues and use insurance data to provide data-based evidence of safety by vehicle make and model. These organizations are funded by a pooled group of insurance companies and associations. IIHS runs the Vehicle Research Center, which conducts crash tests of many vehicle types to encourage auto manufacturers to produce safer vehicles and inform the consumer on vehicle safety ratings.
+
+**27**
+
+Title 49 of the United States Code, Chapter 301, Motor Vehicle Safety; and Federal Motor Vehicle Safety Standard (FMVSS) No. 218
+
+## **Special interest groups**
+
+Special interest groups are associations of individuals or organizations that promote their common interests by influencing the legislative process at the local, State, and/or Federal levels of government. Many interest groups also serve other functions, such as providing services and information to their members. Interest groups fill a vital role in advancing the cause of safety-related legislation.
+
+A few examples of road safetyfocused interest groups include the AAA Foundation for Traffic Safety, National Safety Council, Mothers Against Drunk Driving (MADD), the American Council of the Blind, and the National Federation of the Blind. There are many other interest groups involved in influencing transportation and safety legislation. These groups engage in a variety of activities, such as sponsoring independent research and evaluation, mobilizing citizens to contact their legislators in support of or against certain pieces of legislation, and disseminating policy reports in support of or against legislation affecting the safety of the road users they represent.
+
+## **Professional organizations**
+
+Professional organizations bring together road safety professionals from common backgrounds or spheres of influence to foster discussion and advancement of safety issues. Members of these organizations who recognize emerging road safety issues can use the power of the group to advocate legislation or sponsor research to address these issues.
+
+![](_page_165_Picture_5.jpeg)
+
+#### **American Council of the Blind (ACB) and National Federation of the Blind (NFB)**
+
+The ACB and NFB represent the interests of people who are blind or visually impaired. These organizations work to inform legislators, city and State agencies, and the public about road safety issues that are unique to individuals with visual impairment. They promote policies and practices that assist visually impaired individuals in traveling safety and independently. These include enhancements, such as auditory stop announcements on buses and accessible pushbuttons that provide information about street crossing signals.
+
+These organizations often hold regular conferences that allow safety professionals to network, share ideas, and gain knowledge from others in their field. The organizations also provide training opportunities that help advance and disseminate road safety knowledge.
+
+There are many professional organizations covering many disciplines that relate to road safety. While this textbook is not intended to provide an encyclopedic listing, a few examples are listed below.
+
+### **American Association of State Highway Transportation Officials (AASHTO)**
+
+AASHTO members consist of representatives from highway and transportation departments in the 50 States, the District of Columbia, and Puerto Rico. AASHTO provides tools such as Safety Analyst, an analytical software package, and publishes the Highway Safety Manual, which provides an analytical and quantitative framework for analyzing a road's safety performance. AASHTO focuses on emerging safety issues through its Standing Committee on Highway Traffic Safety. AASHTO inspired the development of a national safety plan called Toward Zero Deaths, committed to reducing the number of highway fatalities to zero.
+
+#### **Institute of Transportation Engineers (ITE)**
+
+ITE is an association of transportation professionals who are responsible for meeting mobility and safety needs. ITE promotes professional development of its members and facilitates the application of technology and scientific principles to the safety of ground transportation. ITE's Transportation Safety Council covers issues, such as roadside safety, pedestrian and bicyclist safety, and work zone safety.
+
+### **Association of Transportation Safety Information Professionals (ATSIP)**
+
+ATSIP focuses on data and is the leading advocate for improving the quality and use of transportation safety information. ATSIP furthers the development and sharing of traffic records system procedures, tools, and professionalism. Its goal is to improve the quality of safety data and encourage their use in safety programs and policies.
+
+### **Governors Highway Safety Association (GHSA)**
+
+GHSA represents the State and territorial highway safety offices that implement programs to address behavioral highway safety issues including occupant protection, impaired driving, and speeding. GHSA provides leadership and advocacy for the States and territories to improve traffic safety, influence national policy, enhance program management, and promote best practices.
+
+## **International Organizations**
+
+As of 2017, there is no U.S. organization that combines the narrow focus of improving road safety and a broad multidisciplinary approach. The current inventory of U.S. professional organizations is usually specific to a type of discipline, such as engineering or behavioral science. Looking beyond the U.S. borders shows that other countries have formed organizations that bring together many different disciplines to address road safety including the following:
+
+- J World Road Association (PIARC, after its former name Permanent International Association of Road Congresses), **www.piarc.org/en/**
+- J La Prévention Routière Internationale (PRI), **www.lapri.org**
+- J United Nations Road Safety Collaboration, **www.who.int/roadsafety/en/**
+- J Global Road Safety Partnership, **www.grsproadsafety.org**
+- J International Road Federation, **www.irf.global**
+
+#### **EXERCISES**
+
+- J **RESEARCH** a recent road safety project in your city, county, State, or region. Identify the roles and responsibilities of the Federal, State, and/or local governmental agencies in the project. Prepare a brief report for a class presentation.
+- J **USE** your local, State, or regional highway department's website to determine its most pressing road safety concerns. Prepare a brief report that explains the concerns, how the agency identified them, the proposed remedies, and the agency's next steps.
+- J **PREPARE** a brief presentation that summarizes how your local government administers roadway programs. Identify the form of government (city, county, municipality, parish, etc.), the local agencies, and their responsibilities to roadway safety programs.
+- J **RESEARCH** a private or nonprofit interest group that works to improve road safety. Prepare a class presentation that includes a brief history of the interest group, a synopsis of important and successful campaigns, and a summary of its current work. Some examples of private or nonprofit interest groups include the Automobile Association of America (AAA), Mothers against Drunk Driving (MADD), the Insurance Institute for Highway Safety (IIHS), and the American Bikers Aimed Toward Education (ABATE), and many others.
+- J **RESEARCH** your local, State, or regional transportation safety planning group. Prepare a brief report that identifies the group's current safety goal(s), explains how the group plans to alleviate the safety challenge(s), and describes the group's strategic communications plan.
+
+- J **RESEARCH** a private sector or industry association that works to improve road safety. Prepare a class presentation that includes a brief history of the interest group, a synopsis of important and successful campaigns, and a summary of its current work. Some examples of private sector or industry associations include the American Insurance Association (AIA), the American Traffic Safety Services Association (ATSSA), the American Road and Transportation Builders Association (ARTBA), the National Association of County Engineers (NACE), the American Public Works Association (APWA), and many others.
+- J **FIND OUT** how professional associations like the National League of Cities, the American Association of State Highway Transportation Officials (AASHTO), the Governor's Highway Safety Association (GHSA), and the Standing Committee on Highway Traffic Safety (SCOHTS) influence road safety policy. What are some examples of past successful campaigns?
+- J Using the State DOT website, **RESEARCH** your home State's Highway Safety Program. Prepare a brief presentation that identifies the State and describes how it is working to improve roadway safety. You may want to focus on the State's efforts with a particular road user or road safety provider. Be sure to include details about how the State identified the safety challenge(s), how the State chose its countermeasure(s), and how its efforts measure against national performance criteria.
+
+## **Road Safety Research**
+
+Road safety practitioners are constantly seeking the most effective means for preventing injuries and fatalities on the road. To accomplish this, they need to understand the nature of the road safety problems and which behavioral or infrastructure countermeasures are the best at addressing these problems. When weighing two possible safety treatments, they need to know which one is more effective (would prevent more crashes) and more efficient (preventing crashes at a lower cost). Additionally, safety practitioners work with a limited budget, so they need to know which safety treatment is more cost effective, that is, how many crashes can be prevented for the same dollar spent. These goals lead to many questions, such as:
+
+- J What age range should be targeted in a young driver safety program?
+- J What is an effective strategy for preventing run-off-road crashes?
+- J How many crashes would be expected on one type of road versus another type?
+- J How many serious injuries could be prevented by installing additional safety measures at a signalized intersection?
+
+Research is the key to answering these questions and providing quality information to the safety
+
+![](_page_168_Picture_9.jpeg)
+
+practitioner. Unit 3 of this textbook provides a look at the various types of safety data and how they can be used together. Good research analyzes one or more kinds of safety data to gain knowledge on ways to prevent crashes or decrease injuries when crashes do occur.
+
+## **General Types of Road Safety Research**
+
+The intention of this chapter is not to summarize the entire field of road safety research, but rather to provide an overview that will show what types of research have been conducted within the topic of road safety.
+
+|                     | RESEARCH QUESTION EXAMPLES                                              |                                                                                    |  |  |  |  |
+|---------------------|-------------------------------------------------------------------------|------------------------------------------------------------------------------------|--|--|--|--|
+|                     | PROBLEM IDENTIFICATION                                                  | EVALUATION                                                                         |  |  |  |  |
+|                     | What are characteristics of crashes<br>involving teen drivers?          | What is the safety effect of instituting<br>a graduated driver license law?        |  |  |  |  |
+| PERSON              | What type of driver is overrepresented<br>in alcohol-related crashes?   | Has the arrival of ride-sharing apps in<br>cities reduced alcohol-related crashes? |  |  |  |  |
+|                     | What models of vehicle are more<br>prone to run-off-road crashes?       | What is the effect of an antilock<br>braking system on run-off-road crashes?       |  |  |  |  |
+| VEHICLE             | What factors are associated with<br>large truck-related crashes?        | What is the effect of airbags on<br>injury severity?                               |  |  |  |  |
+|                     | What road features are associated<br>with run-off-road crashes?         | What is the safety effect of installing<br>rumble strips?                          |  |  |  |  |
+| MENT                | How does lane width influence<br>driver speed?                          | What is the safety effect of narrowing<br>lanes on urban roads?                    |  |  |  |  |
+| ENVIRON<br>AD<br>RO | Are some land development patterns<br>riskier from a safety standpoint? | What is the safety effect of controlling<br>road access in dense urban areas?      |  |  |  |  |
+
+**TABLE 5-2**: Safety Research Categorization
+
+One way that these road safety research projects can be generally categorized is by grouping them by the safety factor they address: the person, the vehicle, or the roadway. For each of these categories, safety research typically focuses either on identifying safety problems or on evaluating solutions to safety problems. Table 5-2 demonstrates this classification of safety research areas and provides example questions that would drive research studies in each area.
+
+While this chapter presents road safety research in terms of identifying problems or evaluating solutions, researchers also play key roles in developing new solutions to road safety problems. For example, the Florida Department
+
+of Transportation (FDOT) was experiencing thousands of crashes, including many fatalities, in construction work zones and sought an alternative to the traditional work-zone barrier. University of Florida civil engineering researchers hired by FDOT developed a new type of portable temporary lowprofile barrier that can redirect cars and small trucks, preventing them from crashing into the work zone and protecting the passengers in the vehicle. The barrier was advantageous in that it could be broken down into small inexpensive segments that are easy to install and move around.**<sup>26</sup>** Additional research was carried out to evaluate this new type of barrier in terms of criteria like crash performance and durability.
+
+**26**
+
+University of Florida, Office of Technology Licensing, "Portable Temporary Low-Profile Barrier (PTB) for Roadside Safety", UF #11052, US Patent 6,767,158
+
+## **Examples of Road Safety Research**
+
+The following sections provide descriptions and examples of research studies. These examples will give the reader a look at the types of studies that are conducted within each of the six categories shown in Table 5-2.
+
+## **Research on the Person**
+
+#### **Problem Identification**
+
+The IIHS sponsored a study to examine the characteristics of crashes involving 16-year old drivers. The researchers used crash data from NHTSA's General Estimates System (a national crash database built on sampling from police agencies around the U.S.). They compared crash involvement of sixteen-year-olds to that of other age categories of drivers and found that sixteen-year-olds were more likely to be involved in single-vehicle crashes and night time crashes (6:00pm to 11:59pm). Sixteen-year-olds were also more likely to have received a moving violation and been at fault for a crash. They were also more likely to be accompanied by other teenage passengers. Researchers also found some indications that drivers with less on-the-road experience (females in this study) were proportionately more involved in crashes.**<sup>28</sup>**
+
+#### **Evaluation of Solutions**
+
+In 1997, Michigan instituted its Graduated Driver Licensing (GDL) program to address the high rate of fatal crashes involving teen drivers. This program required teen drivers to gain driving experience under
+
+relatively low risk conditions before obtaining full driving privileges. A new driver would progress through Level 1 (a learner's stage requiring extensive supervised practice), Level 2 (an intermediate stage which prohibited teenage passengers and driving at night), and Level 3 (full licensure with no restrictions). NHTSA funded a group of researchers to evaluate the effect of the GDL program on the crash risk of 16-year-old drivers. The researchers examined Michigan statewide crash data from 1996 (pre-GDL) and 1998 and 1999 (post-GDL). They analyzed the pre-GDL and post-GDL rates of 16-yearold drivers involved in crashes by unit of the statewide population. Researchers also compared to crash rates of drivers over age 25 to control for any other trends. They found that the overall crash risk for 16-year-old drivers decreased 25% by the year 1999 (two years after GDL was implemented). They also found significant reductions in many specific crash types, such as night crashes and single vehicle crashes. These findings showed a significant benefit to the GDL program and served to support GDL implementation in other States.**<sup>29</sup>**
+
+## **Research on the Vehicle**
+
+#### **Problem Identification**
+
+The design of a vehicle, particularly how well it protects the occupants in the event of a crash, can have a significant effect on injuries sustained in the crash. A group of researchers from the IIHS investigated the relation of vehicle roof strength to occupant injury during crashes. They examined crash data from fourteen States
+
+**28**
+
+Ulmer, Robert G., Allan F. Williams, and David F. Preusser, Crash Involvements of 16-Year-Old Drivers, Journal of Safety Research, Vol. 28, No. 2, pp 97-103, 1997. [http://www.](http://www.sciencedirect.com/science/article/pii/S0022437596000412) [sciencedirect.com/](http://www.sciencedirect.com/science/article/pii/S0022437596000412) [science/article/pii/](http://www.sciencedirect.com/science/article/pii/S0022437596000412) [S0022437596000412](http://www.sciencedirect.com/science/article/pii/S0022437596000412)
+
+**29**
+
+Shope, J., L. Molnar, M. Elliott, P. Waller. Graduated Driver Licensing in Michigan: Early Impact on Motor Vehicle Crashes Among 16-Year-Old Drivers. Journal of the American Medical Association, Vol. 286, No. 13, October, 2001. [http://jama.](https://jamanetwork.com/journals/jama/fullarticle/194251) [jamanetwork.](https://jamanetwork.com/journals/jama/fullarticle/194251) [com/article.aspx?](https://jamanetwork.com/journals/jama/fullarticle/194251)  [articleid=194251](https://jamanetwork.com/journals/jama/fullarticle/194251)
+
+#### **30**
+
+Brumbelow, M., E. Teoh, D. Zuby, and A. McCartt. Roof Strength and Injury Risk in Rollover Crashes. Traffic Injury Prevention, 10:252-265, 2009. DOI: 10.1080/ 15389580902781343
+
+Kahane, C., and J. Dang. The Long-Term Effect of ABS in Passenger Cars and LTVs. National Highway Traffic Safety Administration, Report DOT HS 811 182, August 2009.
+
+**32**
+
+Bauer, K.M. and Harwood, D.W. Safety Effects of Horizontal Curve and Grade Combinations on Rural Two-Lane Highways, Report No. FHWA-HRT-13-077, Federal Highway Administration, Washington, DC, 2013.
+
+for single-vehicle rollover crashes involving midsize SUVs. They also used a rating of roof strength for each vehicle type in the crash data. Their findings showed that the crush resistance of a vehicle's roof was strongly related to the risk of fatal or incapacitating injury to the occupants. This research identified one statistically significant factor (roof strength) in the severity of rollover crashes. The researchers also recommended the study of other vehicle factors to determine their effect on the severity of rollover crashes.**<sup>30</sup>**
+
+#### **Evaluation of Solutions**
+
+Anti lock braking system (ABS) is a technology that was developed to combat the problem of drivers losing control of their vehicle during hard braking due to locked wheels. ABS modulates braking power to prevent a vehicle's wheels from locking up. Since this technology requires drivers to employ it correctly (i.e., step and hold on the brake rather than pumping), the Federal Government conducted a public information campaign in 1995 to inform drivers how to use ABS correctly. The NHTSA sponsored a study that took a long term look at the effect of ABS from 1995 to 2007. The researchers used crash data from two Federal databases (the Fatality Analysis Reporting System and the General Estimates System of the National Automotive Sampling System) to estimate the long-term effectiveness of ABS for passenger cars, light trucks, and vans. They found that ABS reduced fatal crashes with pedestrians but increased fatal run-off-road crashes. ABS proved to be quite effective in reducing nonfatal crashes in all types of vehicles.
+
+This result is for the ABS alone; the authors recognized that electronic stability control (a technology which automatically applies brakes to individual wheels to keep the driver on the road) would soon be paired with ABS for potentially greater crash reductions.**<sup>31</sup>**
+
+## **Research on the Road Environment**
+
+#### **Problem Identification**
+
+Curves on the road, both horizontal and vertical, are known to be problem spots for road safety. They are particularly concerning when they occur together, such as a horizontal curve at the peak of a hill. FHWA sponsored a study to identify and quantify the road and curve characteristics that are associated with higher instances of crashes. The researchers examined curves in Washington State using crash data and roadway characteristics contained in the Highway Safety Information System (HSIS). They analyzed locations where horizontal and vertical curves occurred independently, as well as locations where both occurred in the same place. The researchers developed equations that predicted the effect on crash frequency for each type of curve combination. These predictive equations included road and curve characteristics found to affect the frequency of crashes. These characteristics included the sharpness of the vertical curve and the radius of the horizontal curve.**<sup>32</sup>**
+
+#### **Evaluation of Solutions**
+
+Rumble strips are expected to decrease crashes by generating noise to alert sleepy or inattentive drivers that they are about to leave
+
+#### **How Research Affects Implementation: Motorcycle Helmets**
+
+Motorcycle helmets are now a common road safety element to reduce serious head injuries, but they were not always so. The original interest in motorcycle helmets began when Colonel T.E. Lawrence (better known as Lawrence of Arabia) died after suffering a head injury in a motorcycle crash. One of the physicians who attended him, Hugh Cairns, was moved by the incident and began studying the prevalence of head injuries among motorcyclists in the British Army. His work ultimately led to helmets becoming mandatory in the British Army and the U.K.
+
+Early motorcycle helmets were leather caps that did little to protect riders. Then in the 1950s, Roth and Lombard came up with the idea of using a crushable, energy absorbing
+
+![](_page_172_Picture_3.jpeg)
+
+material (Styrofoam) inside the helmet. A study in 1957 by a physician named George Snively helped this new type of helmet take hold through unusual means – testing six popular motorcycle helmets on human cadavers. The Roth and Lombard helmet with the protective lining was by far the most effective in preventing head injuries.
+
+Many more studies have documented the effectiveness of motorcycle helmets. This eventually led to standards for motorcycle helmets and universal helmet laws.**33,34**
+
+Maartens, N., A. Wills, and C. Adams. Lawrence of Arabia, Sir Hugh Cairns, and the Origin of Motorcycle Helmets. Neurosurgery, Vol. 50, No. 1, January 2002.
+
+## **Major Road Safety Research Sponsors and Research Programs**
+
+Most road safety research is funded by the government, through state or federal agencies. However, some research is also funded by privately run companies or foundations. The organizations that sponsor research projects are often focused on one category of research. The list below presents a look at some of the major research sponsors and their area of focus in road safety research.
+
+## **Federal Research Sponsors**
+
+#### **Federal Highway Administration**
+
+FHWA sponsors research studies on a variety of road safety topics, and their primary focus is on the roadway or the built environment. This research investigates the impact of road characteristics on
+
+**34**
+
+Liu, B., R. Ivers, R. Norton, S. Blows, S.K. Lo. Helmets for preventing injury in motorcycle riders (review). The Cochrane Collaboration, John Wiley and Sons, Ltd. January 2008. DOI: 10.1002/14651858. CD004333.pub3
+
+**35**
+
+Lyon, Craig; Bhagwant Persaud; and Kimberly Eccles. "Safety Evaluation of Centerline Plus Shoulder Rumble Strips." Federal Highway Administration, Report FHWA-HRT-15-048, 2015.
+
+the travel lane. Rumble strips on both the centerline and shoulder ensure that drivers are alerted no matter which side of the lane they depart. FHWA, through a pooled fund from 38 States, conducted a study to determine the safety effect of installing centerline and shoulder rumble strips on rural two-lane roads. The researchers gathered data on roads in three States and compared crash performance for roads where the rumble strips were installed versus roads without rumble strips. The analysis showed that the combined rumble strip strategy was effective at reducing crashes. As expected, the greatest crash reductions were for crash types that were related to lane departure including headon crashes (37% decrease), runoff-road crashes (26% decrease), and sideswipe-opposite-direction crashes (24% decrease).**<sup>35</sup>**
+
+**36**
+
+[https://www.fhwa.](https://www.fhwa.dot.gov/research/tfhrc/programs/safety/index.cfm) [dot.gov/research/](https://www.fhwa.dot.gov/research/tfhrc/programs/safety/index.cfm) [tfhrc/programs/](https://www.fhwa.dot.gov/research/tfhrc/programs/safety/index.cfm) [safety/index.cfm](https://www.fhwa.dot.gov/research/tfhrc/programs/safety/index.cfm)
+
+**37**
+
+[https://www.nhtsa.](https://www.nhtsa.gov/research-data) [gov/research-data](https://www.nhtsa.gov/research-data)
+
+road safety and seeks solutions to known safety problems. The FHWA Offices of Safety and Safety Research and Development conduct research to address issues including driver interaction with the roadway, intersection safety, pedestrian and bicycle safety, and keeping vehicles on the roadway.**36** The FHWA Turner-Fairbank Research Center houses more than 20 laboratories, data centers, and support facilities, and conducts applied and exploratory advanced research in road safety, among other topics. Additionally, FHWA staff participates and provides input to many other venues of research around the nation.
+
+#### **National Highway Traffic Safety Administration**
+
+NHTSA studies behaviors and attitudes in road safety, focusing on drivers, passengers, pedestrians, and motorcyclists. Research sponsored by NHTSA identifies and measures behaviors involved in crashes or associated with injuries, and develops and refines countermeasures to deter unsafe behaviors and promote safe alternatives. The research topics include occupant protection, distracted driving, motorcycle safety, speeding, and young drivers.**<sup>37</sup>**
+
+#### **Transportation Research Board**
+
+The Transportation Research Board (TRB) is part of the National Academies of Sciences and provides advice to the nation and informs public policy decisions. TRB plays a major role in road safety research. It hosts an annual meeting where transportation professionals
+
+#### **How Research Affects Implementation: Safety EdgeSM**
+
+The ultimate intent of safety research is to provide solid data to affect the way that safety measures are carried out in the real world. The development of Safety EdgeSM is a good example of this.
+
+Drivers who run off the road and then try to regain control often go too far and over-steer, leading to veering into the opposite lane or running off the road on the other side. This problem is made worse when the soil is eroded away from the pavement edge, creating a drop off. This safety concern was recognized in the 1980s, and the 1989 AASHTO Roadside Design Guide included a recommendation for adding a sloped edge to the pavement to assist drivers in regaining control onto the roadway. A few States attempted this treatment, but it was not widely implemented. Through the following years, other research showed a correlation between drop off crashes and fatalities.
+
+![](_page_173_Picture_13.jpeg)
+
+In the early 2000s, several States (Georgia, New York, Colorado, and Indiana) decided to install several miles of the sloped edge as demonstration project. The FHWA sponsored a research study to evaluate the effect of the sloped edge, now called Safety EdgeSM, on run-off-road crashes. The results showed a positive effect, and this finding swayed many safety offices in favor of the treatment. Those now in favor of Safety EdgeSM worked to get other offices, such as pavement offices, on board with the idea. Eventually it became a widespread practice, and by 2015, forty States required Safety EdgeSM to some degree in their design policies.**<sup>38</sup>**
+
+**38**
+
+Graham, J.L., Richard, K.R. , O'Laughlin, M.K., Harwood, D.W., "Safety Evaluation of the Safety Edge Treatment" Report No. FHWA-HRT-11-024, Federal Highway Administration, Washington, DC. (2011) [http://www.](https://www.fhwa.dot.gov/publications/research/safety/11024/11024.pdf) [fhwa.dot.gov/](https://www.fhwa.dot.gov/publications/research/safety/11024/11024.pdf) [publications/](https://www.fhwa.dot.gov/publications/research/safety/11024/11024.pdf) [research/](https://www.fhwa.dot.gov/publications/research/safety/11024/11024.pdf) [safety/11024/11024.](https://www.fhwa.dot.gov/publications/research/safety/11024/11024.pdf) [pdf](https://www.fhwa.dot.gov/publications/research/safety/11024/11024.pdf)
+
+from around the world present new research on many different transportation topics. The papers presented at the annual meeting are peer-reviewed, and a portion of them are published in the Transportation Research Record.
+
+TRB also maintains standing committees that provide direction to the research field and assist in disseminating research findings. Committees such as Transportation Safety Management, Highway Safety Performance, Pedestrians, Occupant Protection, and many others specifically address topics related to road safety. TRB manages the National Cooperative Highway Research Program (NCHRP), described below.
+
+## **State Research Sponsors**
+
+#### **American Association of State Highway Transportation Officials (AASHTO)**
+
+AASHTO is the organization behind NCHRP. The NCHRP funds many road safety research projects each year on a variety of topics that are integral to the State departments of transportation (DOTs) and transportation professionals at all levels of government and the private sector. The NCHRP is administered by the Transportation Research Board (TRB) and sponsored by individual State departments of transportation. The research projects are conducted in cooperation with FHWA (FHWA). Individual projects are conducted by contractors with oversight provided by volunteer panels of expert stakeholders. NCHRP projects cover a wide range of highway topics, but there is a specific focus area for safety.**<sup>39</sup>** AASHTO also maintains
+
+#### **Other Research Sponsors**
+
+Although the majority of road safety research is funded by government sources, private companies and organizations also participate in funding road safety research. Prominent examples of these are the IIHS and the American Automobile Association Foundation for Traffic Safety.
+
+several committees that oversee road safety topics including the Standing Committee on Highway Traffic Safety and the Subcommittee on Safety Management. These groups decide which research topics should be prioritized for funding under NCHRP.
+
+#### **State Research Programs**
+
+In addition to participating in large scale research efforts, such as NCHRP, State departments of transportation often fund road safety research projects on topics that are of particular interest to their State. They use portions from Federal funds that are specially designated for research projects. Every State has a different process for how the research projects are conceived and conducted, but a common arrangement is that the State DOT contracts with universities in the State to conduct the research. The research topics typically pertain to current road safety issues that are high priority within the State or issues related to geography, terrain, weather, driver population, or other such factors that may be particular to that State. For example, a State in a snowy climate may sponsor a research project on how snowplowing affects the visibility and durability of inpavement reflective markers.
+
+[http://www.trb.org/](http://www.trb.org/NCHRP/NCHRP.aspx) [NCHRP/NCHRP.](http://www.trb.org/NCHRP/NCHRP.aspx) [aspx](http://www.trb.org/NCHRP/NCHRP.aspx) **39**
+
+## **Strategic Communications**
+
+A key part of many efforts to improve road safety is sharing safety messages through strategic communications. This chapter provides an outline of the most basic elements of strategic communications that transportation safety professionals should use when working with their communications teams to craft and disseminate messages that seek to improve traffic safety culture. As mentioned in Unit 1, strategic communications programs like public education campaigns are commonly used to improve road user attitudes and awareness.
+
+A strategic communications program involves elements of communications, marketing, and public outreach. These components often overlap and are not easily separated into distinct categories with unique functions. Strategic communications is more than the sum of its parts. Rather, it is a structured methodology that fuses messaging with marketing while garnering public support.
+
+Several examples demonstrate that strategic communications can result in behavioral changes. An effort in the late 1980s to stop impaired driving resulted in substantial decreases in Driving Under the Influence (DUI) citations. NHTSA saw successful results from the implementation of the "Buckle Up America Campaign" and the National Safety Council's "Airbag and Seat Belt Safety Campaign" and the high-
+
+![](_page_175_Picture_6.jpeg)
+
+Public education campaigns like this one are commonly used to improve road user attitudes and awareness. *(Source: NHTSA)*
+
+visibility public information program "Click It or Ticket" safety belt enforcement campaign. Strategic communications was a key element of all of these efforts.
+
+Other examples of communications efforts include:
+
+- J Campaigns with careful pre-testing and delineation of a target group that receives the messages.
+- J Longer-term programs that deliver a message in sufficient intensity over time.
+
+- J Education programs built around behavioral change models, using interactive methods to teach skills to resist social influences through role playing.
+- J Public information campaigns that accompany other ongoing prevention activities.
+- J Programs conducted as part of a broader community effort or in support of law enforcement.
+
+An effective strategic communications program, like any effective endeavor, needs a plan. The following are key steps in developing a strategic communications plan that every road safety professional should know:
+
+- **1. Develop objectives**
+- **2. Identify target audience**
+- **3. Design messaging**
+- **4. Select communications channels**
+- **5. Determine budget and resources**
+- **6. Measure results**
+
+Each step of this communications plan outline is discussed in the sections below.
+
+## **1. Develop Objectives**
+
+The first phase in creating a strategic communications plan is to determine objectives. A welldesigned communications strategy may achieve multiple goals, such as informing the public about transportation safety issues, educating key political leaders on their roles in saving lives, and encouraging active participation from safety partners.
+
+To develop objectives, safety professionals must start by defining what "success" should look like. Important questions include:
+
+- J What are we trying to achieve?
+- J Do we want people to take a new action, or do we want people to modify an old behavior?
+- J How do we know when we have achieved our goal (i.e., what are our target metrics)?
+
+Establishing measurable goals is an important piece that should be not be overlooked. Having a target or measurable goal (metric) makes it simpler to gauge the success of a campaign.
+
+## **2. Identify Target Audience**
+
+After developing communications objectives, the next step is deciding what populations to target. For example, safety professionals must decide if the program should be aimed at the general public or a specific sub-set of the population, such as young drivers, pedestrians, or people who drive aggressively. A message could also be aimed at road safety professionals and government officials. In addition to a target audience or audiences, secondary audiences may be included. For instance, if the program targets young drivers, a secondary audience may include the parents of these novice drivers.
+
+## **3. Design Messaging**
+
+Once safety professionals identify the target audience, they must determine what the message will be. A key step is to define the problem that needs to be solved in order to craft the message. Messaging should be designed so that it encourages specific actions, and draws upon established
+
+#### **Watch for Me NC**
+
+Watch for Me NC is a comprehensive program run by the North Carolina Department of Transportation (NCDOT) in partnership with local communities. It is aimed at reducing the number of pedestrians and bicyclists crashes.
+
+The Watch for Me NC program involves two key elements: 1) safety and educational messages directed toward drivers, pedestrians, and bicyclists, and 2) enforcement efforts by area police to crack down on some of the violations of traffic safety laws. Local programs are typically led by municipal, county, or regional government staff with the involvement of many others including pedestrian and bicycle advocates, city planners, law enforcement agencies, engineers, public health professionals, elected officials, school administrators and others.
+
+All North Carolina communities are encouraged to use Watch for Me NC campaign materials to improve pedestrian and bicyclist safety in their communities.
+
+objectives to determine what those actions should be. Designing the message will bring about questions like these: "Is the intended action a change in safety funding or policies? Or is the goal a change in user behavior?" Focusing efforts on strategies that connect with the target audience is particularly important in today's environment of tight budgets and scarce resources.
+
+After message development, safety professionals should consider pretesting the message with the target audience. A pre-test can identify points of view of the target audience, provide unexpected insights or reactions that can help further refine messaging, and help determine if the communications plan will improve the chance of accomplishing the stated objectives.
+
+![](_page_177_Picture_6.jpeg)
+
+## **4. Select Communications Channels**
+
+Carefully crafted messages need to be conveyed through appropriate channels in order to be effective. Communications channels include the personal and the non-personal. Personal channels include the advocate channel (advocates championing the objectives of a campaign), expert channel (independent experts making statements to the target audience), and social channel (word of mouth communications). Non-personal channels include media, events, and public outreach – examples of common non-personal dissemination techniques include, but are not limited to, the following:
+
+J Brochures
+
+- J Conferences/workshops
+- J Dynamic message signs
+- J Media advisories
+- J New media (e.g., blogs, podcasts, Facebook pages)
+- J News media events
+- J Newsletters and press releases
+- J Public service announcements
+- J Print, radio, and television advertising
+- J Social media
+- J Websites
+
+Safety professionals must work with the communications team to determine the right media mix, which is the combination of communication channels needed to meet communications objectives. Together they must figure out which channels -- personal and/ or non-personnel – and which tactics will help meet the stated road safety goals. For example, personal channels may work well with government officials, while non-personnel channels may work best with reaching out to the public. Also, a detailed timeline of channels and tactics to employ, is crucial for implementing a strategic communications plan.
+
+## **5. Determine Budget and Resources**
+
+Implementing a comprehensive communications program requires resources like money, staff, and time. Therefore, developing a budget for the program is an integral part of carrying out the plan. Safety professionals should consider every element of the proposed plan, and make sure there are resources to
+
+cover them all. For instance, it may be necessary to hire an outside firm to help develop and refine messages and tactics, and that should be factored into the budget. All program expenses should be tracked to determine how well the budget has been met when measuring results.
+
+## **6. Measure Results**
+
+Evaluation of a strategic communications program is essential. Without evaluation, current programs may waste resources and fail to contribute to a road safety program's goals. Evaluations help safety professionals learn from outcomes and help them allocate funds in the most efficient manner. If a program does not meet expected metrics, they should re-examine the program and/or move the resources to other efforts.
+
+To measure the results of the program, safety professionals must go back to the objectives and predetermined measurable goals and targets. The original questions in Step 1 will guide the evaluation of the success of the program. Surveys, focus groups, and/or one-on-one interviews are often good ways of measuring the performance of a strategic communications program.
+
+As far as data allow, safety professionals should also attempt to compare the effectiveness of communication campaigns in the same way that they compare the performance of traditional infrastructure countermeasures. The comparison will help identify campaigns that are both effective and efficient.
+
+## **Advancing Road Safety**
+
+This chapter covers the crucial role that safety leaders, champions, and coalitions play in road safety management. While the various agencies and organizations involved in road safety bring unique and valuable perspectives to the problem of road safety, they also bring competing philosophies and problem-solving approaches. Bringing these various entities together to develop and implement an effective road safety program is a challenge.
+
+The major topics include:
+
+- J **Leaders**
+- J **Champions**
+- J **Coalitions**
+
+## **Leaders**
+
+Leadership is essential in any field, but it is particularly important in road safety for three major reasons:
+
+- J The safety field is diverse. It draws on the skills of educators, politicians, advocates, bureaucrats, public servants, and others. These groups sometimes work in harmony, but too often, they work in isolation. Leaders are necessary for cohesion in a complex, multi-stakeholder environment.
+- J A great deal of technical knowledge is available in the safety field regarding the most effective means of addressing the contributing factors to crashes.
+
+- However, technical knowledge is not sufficient for change to occur. Leadership is necessary to ensure technical knowledge is used.
+- J Road safety programs and projects compete with other public sector priorities. Without strong leaders to support the safety cause, public sector decision makers might not consider or prioritize safety.
+
+#### **Leadership Activities**
+
+Leaders are an instrumental part of any planning process, and road safety programs are no exception. Leaders bring people together, provide essential direction, and motivate people to participate in and implement the program. Leaders should be engaged and actively involved in the process.
+
+Consider a few examples of leadership in safety:
+
+- J State DOT leaders decide that reducing fatal and serious crashes should be the first priority of the department. They garner staff support to make funding and structural changes to the organization to support the shift in priorities.
+- J Law enforcement officers develop new incentive programs to encourage officers to identify and arrest impaired drivers. They successfully sell the program to their managers.
+
+![](_page_180_Picture_0.jpeg)
+
+Leaders bring people together, provide essential direction, and motivate people.
+
+- J A trauma nurse initiates a "teachable moments" campaign in which nurses teach patients about the risks associated with drinking and driving.
+- J A mayor recognizes that many streets in her city are not suitable for safe travel by pedestrians and garners support and funding from the city council to build sidewalks and improve the safety of transit stops.
+
+In each of these examples, the leaders recognized a need for change, acted on the need, and inspired others to follow. Anyone with drive, dedication, and a good idea can lead.
+
+#### **Leadership Traits and Skills**
+
+Good leaders influence policy direction, set priorities, and define performance expectations. They energize the road safety process and see to it that a plan is developed, and once developed, is implemented. They are risk takers, problems solvers, and creative thinkers committed to doing what is necessary to advance the cause, which sometimes means breaking traditional institutional barriers and balancing competing agency priorities.
+
+Leaders are often known as program managers, and their activities keep the implementation process on track. They manage the process and attend to the day-to-day tasks of arranging, facilitating, and documenting meetings, tracking progress, and moving discrete activities through to completion.
+
+Leaders are needed throughout all stages of road safety development, implementation, and evaluation. They communicate the safety vision and support a collaborative framework that enables safety stakeholders to participate actively in implementation.
+
+#### **Leadership Development**
+
+To expand leadership support, begin with the safety partners already committed to the safety concept and process. Encourage the leadership of those partners to contact their peers, explain the significance of their efforts, and marshal support. Their endorsement of the safety vision should include encouraging staff to stay engaged and building relationships across organizational boundaries and traditional areas of responsibility.
+
+Leadership support affects agencies or organizations internally by granting permission to dedicate time and resources to the safety effort.
+
+It also holds those responsible for safety accountable. Leadership should recognize that this is an ongoing process and institutionalize the change in the safety decisionmaking culture.
+
+The safety program manager may perform either as a part- or fulltime permanent role; experience demonstrates a dedicated role is preferable.
+
+## **Champions**
+
+Successful road safety programs call for at least one champion to assist in gathering all critical safety partners into a collaborative group. Champions provide enthusiasm and support for the safety programs.
+
+![](_page_181_Picture_7.jpeg)
+
+Like leaders, champions must be credible and accountable, have excellent interpersonal and organizational skills, and be skilled expediters.
+
+#### **Champion Activities**
+
+Safety champions help secure the necessary leadership, resources, visibility, support, and commitment of all partners. Sometimes the DOT leadership, or the leadership of the primary sponsoring agency, appoints the champion. A safety champion can reside at any level within the organizational structure and can perform various functions.
+
+For example, a safety champion may lead the executive committee that meets periodically to solve problems, remove barriers, track progress, and recommend further action. The role of the executive committee is to decide which projects or strategies are funded based on input from the emphasis area teams, and to prioritize them based on benefit/cost analysis, expected fatality reductions, and the extent to which they address the project's goals and objectives.
+
+Where relationships are not fully developed, the champion may have to put in additional effort to keep the full range of safety partners committed and actively participating.
+
+#### **Champion Traits and Skills**
+
+FHWA published the "Strategic Highway Safety Plan Implementation Process Model" that identifies two types of transportation safety champions.**<sup>39</sup>** The first have access to resources and the ability to implement change. In other words, they may
+
+not be involved in the day-today management responsibility for program development and implementation, but they are able to "move mountains" in terms of resource allocation and policy support. The second are leaders who inspire others to follow their direction. These champions are people who provide enthusiasm and support to transportation project implementation. They tend to be subject matter experts and highly respected within their own agencies and in the safety community.
+
+#### **Succession Planning**
+
+All agencies and organizations undergo staff changes, and it is essential to train the leaders of tomorrow to ensure that the focus on safety continues into the future. This can be accomplished by assigning leadership responsibilities for program implementation to newer staff and by ensuring that all staff have opportunities to engage and lead during meetings and other activities.
+
+To ensure continuity when an individual champion or leader retires, takes a position in another organization, or moves out of State, a systematic approach to identifying their replacement is necessary. The selection process should be based on individual skills, leadership traits, and the position held within a stakeholder organization. One way to institutionalize the selection of safety committee members is to link their selection to the position they hold within the stakeholder organization. For example, whoever assumes the previous safety champion or committee member's position should also become the new committee member.
+
+**39**
+
+[http://safety.fhwa.](http://safety.fhwa.dot.gov/hsip/shsp/) [dot.gov/hsip/shsp/](http://safety.fhwa.dot.gov/hsip/shsp/)
+
+## **Coalitions**
+
+Safety partners and organizations bring unique and valuable perspectives to bear on the transportation safety problem. However, differing philosophies, competing priorities, and varying business cultures may make collaboration a challenge. Coalitions are an opportunity for road safety leaders and champions to bring together the various disciplines and agencies and focus on the shared goal of reducing crashes. Whether coalitions are short-term, longterm, or permanent, they offer road safety collaborators the prospect of solving complex issues through partnerships.
+
+#### **Safety Partners**
+
+The organizational structure of agencies and interagency working relationships are important factors to consider when bringing safety partners together. Rather than create entirely new committees, a champion should build upon existing relationships, interagency working groups, and committees.
+
+Many States have functioning transportation safety committees, such as a TRCC, an Executive Committee for Highway Safety, or a Towards Zero Deaths (TZD) coalition. Regardless of how safety partners are brought together and organized to contribute to the safety process, champions should look for ways to expand membership to include a broad range of partners, such as insurance, trucking and motor coach companies, fire and rescue, local businesses, and others.
+
+When States implement the Federally required SHSPs, their safety partners typically include those that are Federally required, such as EMS providers, health and education departments, Motor Carrier Safety Assistance Program (MCSAP) managers, local agencies, tribal governments, special interest groups (e.g., MADD), and others.
+
+With an emphasis on wide-ranging collaboration that includes many external partners, it can be easy to overlook the importance of broad DOT involvement, as well. Early involvement of planning, design, operations, and maintenance will enhance the implementation of safety strategies, especially if they are new or experimental.
+
+Some champions bring partners together by convening a safety summit or meeting. This could be a large initial kickoff meeting or a meeting of the safety working group or steering committee. It provides an opportunity to learn about each of the safety partner priorities and understand what they contribute. Coalitions should give participants the opportunity to describe their safety concerns and current programs. This may advance the discussion of critical safety issues, identify opportunities, and forge an agreement on how to proceed.
+
+#### **Benefits of Collaboration**
+
+Engineering, planning, emergency response, and behavioral approaches all have roles to play in addressing road safety. Professionals in these various disciplines have different skill sets, and they approach solutions using different methods. Dramatic improvements in roadway safety are more likely to result through a combination of techniques than from techniques from a single discipline. This need
+
+for multidisciplinary solutions necessitates collaboration.
+
+## **Unit Summary**
+
+Improving road safety is a complex endeavor requiring the knowledge and expertise of a wide range of professionals. Road safety improvement is a joint effort across many Federal, State, and local agencies, each with their own particular focus area.
+
+Federal agencies often play a role in providing funding and national cooperation for focused road safety efforts. State and local agencies implement road safety improvements, either for roads and intersections in their jurisdiction, or on the road users themselves. The efforts of these government agencies is supported by a broad base of
+
+road safety research, which provides knowledge on identifying safety problems or evaluating potential solutions. Strategic communications allow all road safety partners to be effective in their efforts to improve road safety, either in communicating to the public or to transportation professionals.
+
+Leadership is essential in the road safety field. The diversity of the field, the importance of coordination among disciplines, and the need to defend safety programs among a host of competing public sector priorities all contribute to the need for strong leadership. Successfully implementing road safety efforts relies on safety champions and coalitions that bring together safety partners from all agencies and disciplines.
+
+#### **EXERCISES**
+
+- J **IDENTIFY** a road safety leader in your community, State, or region. Determine the leader's area(s) of concern, observe how the leader engages with the transportation safety community, and assess the leader's success. Write a brief report summarizing your research. Include an explanation for why or why not the leader was successful.
+- J FHWA has explicitly stated that a "safety champion" should lead safety efforts, specifically development of State SHSPs. Using your home State's DOT website, **RESEARCH** past or present safety champions. Prepare a brief class presentation that identifies the champion, explains why he or she was chosen for the role, what the requirements of the position were, and
+
+- what projects the State implemented under the champion's guidance. Be sure to include an assessment of the champion's tenure.
+- J Coalition building requires a thoughtful, reasoned approach. **CHOOSE** an important road safety issue that the transportation community is still studying. Propose a list of coalition members that could best approach the issue from all available disciplines and interests. Be sure to keep the list reasonable. In a report, summarize the safety issue and introduce the coalition members. Explain why each member is critical to the coalition and the expectations for each member's contributions.
+
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+
+![](_page_186_Picture_0.jpeg)
+
+**Road Safety Fundamentals is available for free at: https://rspcb.safety.fhwa.dot.gov/rsf/**
+
+![](_page_187_Picture_1.jpeg)
+
+**FHWA, Office of Safety**
+
+Felix H. Delgado, P.E. Felix.Delgado@dot.gov

Zotero/001_artiklid/Road Safety Indicators/chenglobalmacroeconomicburdenroad2019.md

@@ -0,0 +1,400 @@
+---
+category: literaturenote
+citekey: chenglobalmacroeconomicburdenroad2019
+title: "The global macroeconomic burden of road injuries: estimates and projections for 166 countries"
+authors: "Chen, Simiao; Kuhn, Michael; Prettner, Klaus; Bloom, David E."
+year: 2019
+date: 2019-09-01 2019-09-01
+doi: 10.1016/S2542-5196(19)30170-6
+publication: The Lancet Planetary Health
+url: "https://www.thelancet.com/journals/lanplh/article/PIIS2542-5196%2819%2930170-6/fulltext"
+zotero_key: MX4TN5E2
+zotero_storage: 9NND7AWJ
+collections: doktoritöö / HLO
+folder: 001_artiklid/Road Safety Indicators
+firstAuthor: "Chen, Simiao"
+status: converted
+---
+# **The global macroeconomic burden of road injuries: estimates and projections for 166 countries**
+
+![](_page_0_Picture_2.jpeg)
+
+*Simiao Chen, Michael Kuhn, Klaus Prettner, David E Bloom*
+
+# **Summary**
+
+**Background Road injuries are among the ten leading causes of death worldwide and also impede economic wellbeing and macroeconomic performance. Beyond medical data on the incidence of road injuries and their resulting morbidity and mortality, a detailed understanding of their economic implications is a prerequisite for sound, evidence-based policy making. We aimed to determine global macroeconomic costs of road traffic injuries and their cross-country distribution.**
+
+**Methods We calculated the economic burden of all road traffic-related injuries for 166 countries by use of a macroeconomic model that accounts for the effect of fatal and non-fatal injuries on labour supply, age-specific differences in education and experience of those who are affected by road accidents, and the diversion of injury-related treatment expenses from savings, which results in lower investment.**
+
+**Findings We estimated that road injuries will cost the world economy US\$1·8 trillion (constant 2010 US\$) in 2015–30, which is equivalent to an annual tax of 0·12% on global gross domestic product. Although low-income and middleincome countries have the largest health burden, their share of the economic burden of road injuries is only 46·4% of the global loss, reflecting in part higher productivity (and earnings) in high-income countries, but also prominently higher treatment costs. Our results also indicate that treatment costs account for a greater proportion of the economic burden in high-income countries than in low-income countries.**
+
+**Interpretation The macroeconomic burden of road injuries is sizeable and distributed unequally across countries and world regions. This finding suggests a case for nuanced policy making. Our framework should provide a good starting point for the more detailed analysis of policies both at country level and across different countries.**
+
+**Funding National Institute on Aging.**
+
+**Copyright © 2019 The Authors(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.**
+
+# **Introduction**
+
+Road traffic injuries are among the ten leading causes of death worldwide, and they are the leading cause of death among young adults aged 15–29 years.1 Such accidents also lead to 20–50 million non-fatal injuries, and many people incur a disability as a result of their injury.2 According to WHO, 1·25 million people worldwide died in road traffic accidents in 2013.1 To provide some context, this figure is more than five times the death toll of the 2004 Indian Ocean tsunami,3 one of the deadliest natural disasters ever recorded. The worldwide prevalence, incidence, and mortality of road injuries are shown in detail in the appendix (pp 1–2).
+
+Although the human burden in terms of pain and suffering of those affected by road accidents—the victims, their families, and their friends—is beyond quantification, these accidents also inflict a large economic toll. Understanding the macroeconomic burden of road injuries and how they are distributed among world regions and countries is essential for policy making.
+
+The published literature on the consequences of road injuries broadly comprises two strands. One strand deals with the effectiveness (in terms of saving lives) of global interventions in reducing road injuries.4 Although some studies derive measures of cost-effectiveness,5 they focus on the cost of the intervention but do not assign a monetary value to the loss arising from road injuries. Establishing such a value (ie, the economic burden of road injuries) is the focus of the second strand. Although a few studies6–12 have estimated the economic burden of road injuries for one or a small number of countries, most of these approaches are based on aggregating the direct and indirect costs of road traffic accidents in different countries (the cost of illness approach) or on multiplying the cases of injuries and deaths due to road traffic accidents by the willingness of individuals to pay to avoid risks (the value of statistical life approach). However, in real economies, jobs do not remain vacant indefinitely, because companies substitute lost labour with new workers or machines (physical capital). Furthermore, approaches to date have been static and have, therefore, failed to account for the dynamics of morbidity-related and mortality-related changes in the population and the implications of treatment costs for savings (and, thus, the accumulation of capital).
+
+*Lancet Planet Health* **2019; 3: e390–98**
+
+**Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany** (S Chen ScD)**; Wittgenstein Centre, Vienna Institute of Demography, Vienna, Austria**  (M Kuhn PhD)**; Institute of Economics, University of Hohenheim, Stuttgart, Germany** (Prof K Prettner PhD)**; and Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA**  (Prof D E Bloom PhD)
+
+Correspondence to: Dr Simiao Chen, Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg 69120, Germany **simiao.chen@uni-heidelberg.**
+
+**de**
+
+See **Online** for appendix
+
+### **Research in context**
+
+#### **Evidence before this study**
+
+We searched MEDLINE, PubMed, Google Scholar, and references from relevant articles using the search terms "road injury" (or "road traffic injury") and "economic burden" (including the variants "economic cost" and "economic loss") in the title or abstract. Articles dated between Jan 1, 1960, and March 1, 2018, were included in this search. Previous approaches were based on aggregating the direct and indirect costs of road traffic accidents in different countries (the cost of illness approach) or on multiplying the cases of injuries and deaths due to road traffic accidents by the willingness of individuals to pay to avoid risks (the value of statistical life approach). However, in real economies, jobs do not remain vacant indefinitely, because companies substitute lost labour with new workers or machines (physical capital). Furthermore, approaches to date were static and failed to account for the dynamics of morbidity-related and mortality-related changes in the population and the implications of treatment costs for savings (and, thus, the accumulation of capital). One study improved on previous approaches by implicitly considering some of these effects and using growth regressions to estimate the macroeconomic effects of road injury for five countries. However, growth regressions might lead to biased estimates because of reverse causality and omitted variables. Use of a simulation model grounded in dynamic macroeconomic theory can address these disadvantages and provide complementary estimates. Additionally, we did not encounter any research that estimated and projected the macroeconomic costs for all the countries in the world.
+
+# **Added value of this study**
+
+We used a theory-based simulation model that describes how the sum of workers, weighted by their human capital in terms of education and experience, combine with physical capital in producing goods and services to estimate the macroeconomic burden of road injuries for 166 countries. We simulated the projected effects of road injuries on the underlying economies' production potential (ie, measuring the cost of injuries in terms of gross domestic product [GDP]) and accounted for economic adjustments in response to road injury casualties, more inclusive measures of economic loss than earnings, which constitute only one part of GDP, the effects on human capital differentiated by age-specific experience and education levels,
+
+A World Bank study13 infers growth effects from the coefficient estimate of mortality in growth regressions. The advantage of this approach is that, when the regression is appropriately specified, the estimated growth effect is clear from the final result, which already incorporates economic adjustment mechanisms. Because they use panel data, these growth regressions are naturally dynamic. Consequently, this method overcomes some of the crucial shortcomings of the cost of illness and value of statistical life approaches. However, this approach only and the effects on physical capital caused by a reduction in savings. We found that road injuries will cost the world economy about US\$1·8 trillion (measured in constant prices as of 2010) in 2015–30. The macroeconomic tolls of road injuries distribute differently among regions and countries. The highest aggregate economic burdens occur in the USA (\$487 billion), China (\$364 billion), and India (\$101 billion), which have the three largest populations in the world. Our results also indicate that treatment costs and their effects on savings and physical capital accumulation have a greater role in high-income countries than in low-income countries. More than 30% of the total economic burden from road injuries derives from physical capital loss in high-income countries, whereas physical capital loss accounts for less than 5% of the total economic burden in low-income countries. The macroeconomic burden of road injuries varies by World Bank income group. Despite the large fraction of disability-adjusted life-years (DALYs) that accrue in low-income and middle-income countries (almost 90%), their share of the economic burden of road injuries is only 46·4% of the global loss, reflecting not only higher productivity (and earnings) in high-income countries, but also higher treatment costs.
+
+#### **Implications of all the available evidence**
+
+This analysis suggests that the macroeconomic burden of road injuries is large and distributed unequally across countries and world regions. High-income countries have the highest macroeconomic burden of road injuries, whereas low-income and middle-income countries bear the greatest health burdens. This disparity of distribution might be driven by differences in economic development, where the productivity is higher and the workforce is better educated in high-income countries, leading to a larger loss of human capital from road injury, and more advanced health-care systems reduce the loss in DALYs but come at much higher treatment costs. Although the macroeconomic burden of road injuries on low-income countries is relatively light, it is likely to rise in the course of economic development if the growth in motorisation and traffic density outpaces development of infrastructure and law enforcement. The fact that low-income and middle-income countries bear the majority of the human toll underscores the need for improvements on multiple fronts, including infrastructure, law enforcement, public awareness, and emergency response systems.
+
+allows for assessment of severe diseases that affect many people (such as cardiovascular diseases). Detecting a significant growth effect for less impactful diseases is difficult, given the small sample sizes that typically underly growth regressions.14 Thus, the World Bank study13 does not include road traffic mortality directly but instead includes overall mortality in the regressions and infers from this number the effect of road traffic-related mortality. Furthermore, growth regressions are susceptible to imprecise parameter estimation and to various biases when sparse data on important control variables (eg, fertility and trade openness) are available. 15 This World Bank study13 also focused on the macroeconomic effects of road injuries for five countries; therefore, a comprehensive global estimate of the macroeconomic burden of road injuries, based on the simulation of an economy's productive capacity at the aggregate level and the extent to which road injuries affect the productive capacity, is still needed.
+
+To fill this gap, we aimed to use a theory-based simulation model that describes how the sum of workers, weighted by their human capital in terms of education and experience combines with physical capital in producing goods and services16 to estimate the macroeconomic burden of road injuries.
+
+# **Methods**
+
+# **Model description**
+
+We simulated the projected effect of road injuries on the underlying economy's production potential (ie, measuring the cost of injuries in terms of gross domestic product [GDP]). In doing so, we accounted for (1) economic adjustments in response to road injury casualties; (2) more inclusive measures of economic loss than earnings, which constitute only a part of GDP; (3) the effect on human capital differentiated by agespecific experience and education; and (4) the effect on physical capital caused by reduced savings from those injured individuals, because a proportion of the costs of treating road accident-related injuries could have gone into savings if no road injury had occurred.17 This approach has previously been used to assess the macroeconomic burden of non-communicable diseases in east Asian countries and the USA.18–20
+
+We estimated road injuries' effect on economic output for 166 countries. The definition of a road injury follows the Global Burden of Diseases, Injuries, and Risk Factors Study's (GBD's) injury codes and categories.21 Of these 166 countries, 138 countries have all data inputs necessary for our projections (appendix pp 5–6). We directly calculated the macroeconomic burden of road injuries for these 138 countries using the health macroeconomic model described in detail in Bloom et al 18 and in the appendix (pp 2–5). In applying the model, we first recognised that injuries from road accidents affect the economy through the loss of effective labour supply due to mortality and morbidity. Higher injury-induced mortality rates reduce the population, and therefore the number of working-age individuals, and non-fatal injuries reduce productivity and increase absenteeism. Additionally, a certain share of household resources is diverted from savings to finance out-of-pocket treatment costs. At the same time, insurance-funded coverage of road injury treatment costs translates into higher private health insurance premia and public health insurance taxes. Both channels lead to a loss of aggregate savings or investment across the population and hamper
+
+|                         | Economic burden, millions<br>of constant 2010 US\$<br>(lower and upper bound) | Percentage of total gross<br>domestic product in<br>2015–30<br>(lower and upper bound) | Per capita loss,<br>constant 2010 US\$<br>(lower and upper<br>bound) |
+|-------------------------|-------------------------------------------------------------------------------|----------------------------------------------------------------------------------------|----------------------------------------------------------------------|
+| East Asia and Pacific   |                                                                               |                                                                                        |                                                                      |
+| Australia               | 25 539 (21 505–30447)                                                         | 0·099% (0·084–0·118)                                                                   | 979 (825–1167)                                                       |
+| Brunei                  | 402 (285–540)                                                                 | 0·146% (0·103–0·196)                                                                   | 909 (644–1221)                                                       |
+| Cambodia                | 893 (574–1343)                                                                | 0·208% (0·134–0·313)                                                                   | 52 (33–78)                                                           |
+| China                   | 363978 (337 113–389896)                                                       | 0·154% (0·143–0·165)                                                                   | 255 (236–273)                                                        |
+| Fiji                    | 58 (40–84)                                                                    | 0·077% (0·053–0·111)                                                                   | 63 (43–91)                                                           |
+| Indonesia               | 22 280 (19734–25 133)                                                         | 0·094% (0·083–0·106)                                                                   | 80 (71–90)                                                           |
+| Japan                   | 69326 (66377–73 312)                                                          | 0·067% (0·064–0·071)                                                                   | 554 (530–586)                                                        |
+| Laos                    | 543 (271–823)                                                                 | 0·189% (0·094–0·287)                                                                   | 74 (37–112)                                                          |
+| Malaysia                | 13064 (9815–16620)                                                            | 0·168% (0·126–0·214)                                                                   | 386 (290–491)                                                        |
+| Mongolia                | 372 (269–502)                                                                 | 0·134% (0·097–0·181)                                                                   | 114 (82–153)                                                         |
+| New Zealand             | 4742 (4165–5401)                                                              | 0·138% (0·121–0·158)                                                                   | 965 (848–1099)                                                       |
+| Philippines             | 6064 (4613–7899)                                                              | 0·084% (0·064–0·109)                                                                   | 53 (41–70)                                                           |
+| Singapore               | 2683 (2286–3160)                                                              | 0·046% (0·039–0·054)                                                                   | 447 (381–527)                                                        |
+| South Korea             | 22 745 (19754–26387)                                                          | 0·090% (0·078–0·104)                                                                   | 439 (381–510)                                                        |
+| Thailand                | 15097 (11994–18459)                                                           | 0·179% (0·142–0·218)                                                                   | 217 (173–266)                                                        |
+| Vietnam                 | 7826 (5164–10938)                                                             | 0·189% (0·125–0·264)                                                                   | 78 (51–109)                                                          |
+| Europe and central Asia |                                                                               |                                                                                        |                                                                      |
+| Albania                 | 274 (187–397)                                                                 | 0·098% (0·067–0·141)                                                                   | 94 (64–136)                                                          |
+| Armenia                 | 272 (229–322)                                                                 | 0·101% (0·085–0·119)                                                                   | 93 (79–111)                                                          |
+| Austria                 | 5359 (4648–6188)                                                              | 0·069% (0·060–0·080)                                                                   | 608 (527–702)                                                        |
+| Azerbaijan              | 812 (590–1115)                                                                | 0·078% (0·057–0·108)                                                                   | 79 (58–109)                                                          |
+| Belarus                 | 1191 (973–1470)                                                               | 0·105% (0·086–0·130)                                                                   | 128 (104–157)                                                        |
+| Belgium                 | 7219 (6141–8486)                                                              | 0·079% (0·067–0·093)                                                                   | 618 (526–726)                                                        |
+| Bosnia and Herzegovina  | 378 (295–482)                                                                 | 0·099% (0·077–0·126)                                                                   | 109 (85–139)                                                         |
+| Bulgaria                | 1596 (1372–1875)                                                              | 0·142% (0·122–0·167)                                                                   | 235 (202–276)                                                        |
+| Croatia                 | 1421 (1208–1678)                                                              | 0·123% (0·104–0·145)                                                                   | 351 (299–414)                                                        |
+| Cyprus                  | 423 (341–523)                                                                 | 0·086% (0·070–0·107)                                                                   | 349 (282–432)                                                        |
+| Czech Republic          | 5494 (4816–6301)                                                              | 0·120% (0·105–0·138)                                                                   | 519 (455–595)                                                        |
+| Denmark                 | 4180 (3540–4941)                                                              | 0·066% (0·056–0·078)                                                                   | 715 (606–846)                                                        |
+| Estonia                 | 444 (352–565)                                                                 | 0·091% (0·072–0·116)                                                                   | 349 (276–443)                                                        |
+| Finland                 | 2818 (2358–3372)                                                              | 0·061% (0·051–0·073)                                                                   | 503 (421–602)                                                        |
+| France                  | 37847 (32 157–44671)                                                          | 0·075% (0·064–0·089)                                                                   | 554 (471–654)                                                        |
+| Germany                 | 54069 (45 530–64565)                                                          | 0·079% (0·067–0·095)                                                                   | 657 (553–784)                                                        |
+| Greece                  | 3164 (2697–3705)                                                              | 0·072% (0·062–0·085)                                                                   | 288 (245–337)                                                        |
+| Hungary                 | 2869 (2459–3413)                                                              | 0·098% (0·084–0·117)                                                                   | 302 (259–359)                                                        |
+| Iceland                 | 212 (168–265)                                                                 | 0·065% (0·052–0·082)                                                                   | 633 (503–794)                                                        |
+| Ireland                 | 5356 (4711–6175)                                                              | 0·074% (0·065–0·085)                                                                   | 1081 (951–1246)                                                      |
+| Italy                   | 23 554 (20353–27 259)                                                         | 0·066% (0·057–0·076)                                                                   | 400 (346–463)                                                        |
+| Kazakhstan              | 4773 (3987–5685)                                                              | 0·124% (0·103–0·147)                                                                   | 249 (208–297)                                                        |
+| Kyrgyzstan              | 201 (166–243)                                                                 | 0·151% (0·125–0·183)                                                                   | 31 (26–38)                                                           |
+| Latvia                  | 602 (469–771)                                                                 | 0·102% (0·080–0·131)                                                                   | 327 (254–418)                                                        |
+| Lithuania               | 978 (840–1145)                                                                | 0·109% (0·094–0·128)                                                                   | 349 (299–408)                                                        |
+|                         |                                                                               |                                                                                        |                                                                      |
+| Luxembourg              | 892 (726–1090)                                                                | 0·072% (0·058–0·088)                                                                   | 1465 (1192–1791)                                                     |
+| Moldova                 | 167 (142–196)                                                                 | 0·108% (0·092–0·127)                                                                   | 42 (36–50)                                                           |
+| Netherlands             | 9791 (8503–11290)                                                             | 0·058% (0·051–0·067)                                                                   | 567 (492–654)                                                        |
+| Norway                  | 5854 (5596–6140)                                                              | 0·068% (0·065–0·071)                                                                   | 1052 (1005–1103)                                                     |
+| Poland                  | 15674 (13 556–18231)                                                          | 0·134% (0·116–0·156)                                                                   | 417 (361–485)                                                        |
+| Portugal                | 2505 (2071–3030)                                                              | 0·059% (0·049–0·072)                                                                   | 247 (205–299)<br>(Table 1 continues on next page)                    |
+
+|                                | Economic burden, millions<br>of constant 2010 US\$<br>(lower and upper bound) | Percentage of total gross<br>domestic product in<br>2015–30<br>(lower and upper bound) | Per capita loss,<br>constant 2010 US\$<br>(lower and upper<br>bound) |
+|--------------------------------|-------------------------------------------------------------------------------|----------------------------------------------------------------------------------------|----------------------------------------------------------------------|
+| (Continued from previous page) |                                                                               |                                                                                        |                                                                      |
+| Romania                        | 4539 (3907–5252)                                                              | 0·106% (0·091–0·122)                                                                   | 237 (204–274)                                                        |
+| Russia                         | 50547 (48746–54386)                                                           | 0·172% (0·166–0·185)                                                                   | 354 (341–381)                                                        |
+| Serbia                         | 832 (685–1011)                                                                | 0·100% (0·083–0·122)                                                                   | 97 (80–118)                                                          |
+| Slovakia                       | 2557 (2112–3123)                                                              | 0·119% (0·099–0·146)                                                                   | 472 (390–576)                                                        |
+| Slovenia                       | 1207 (1017–1453)                                                              | 0·117% (0·099–0·141)                                                                   | 585 (493–704)                                                        |
+| Spain                          | 18200 (15919–20832)                                                           | 0·067% (0·058–0·076)                                                                   | 393 (344–450)                                                        |
+| Sweden                         | 6988 (6222–7931)                                                              | 0·068% (0·060–0·077)                                                                   | 682 (607–774)                                                        |
+| Switzerland                    | 8530 (7438–9914)                                                              | 0·074% (0·064–0·086)                                                                   | 971 (847–1129)                                                       |
+| Tajikistan                     | 124 (95–160)                                                                  | 0·064% (0·049–0·082)                                                                   | 13 (10–16)                                                           |
+| Turkey                         | 18195 (14069–22 502)                                                          | 0·079% (0·061–0·098)                                                                   | 215 (167–266)                                                        |
+| Ukraine                        | 3804 (2938–4658)                                                              | 0·157% (0·121–0·192)                                                                   | 89 (68–108)                                                          |
+| UK                             | 24048 (23002–25 103)                                                          | 0·049% (0·047–0·051)                                                                   | 353 (338–368)                                                        |
+| Latin America and Caribbean    |                                                                               |                                                                                        |                                                                      |
+| Argentina                      | 7342 (5879–9183)                                                              | 0·093% (0·075–0·117)                                                                   | 158 (127–198)                                                        |
+| The Bahamas                    | 217 (161–288)                                                                 | 0·117% (0·087–0·155)                                                                   | 542 (400–717)                                                        |
+| Barbados                       | 62 (46–82)                                                                    | 0·080% (0·059–0·105)                                                                   | 227 (169–298)                                                        |
+| Belize                         | 54 (41–68)                                                                    | 0·190% (0·146–0·239)                                                                   | 134 (103–168)                                                        |
+| Bolivia                        | 658 (274–1048)                                                                | 0·117% (0·049–0·186)                                                                   | 55 (23–88)                                                           |
+| Brazil                         | 56988 (52 347–60648)                                                          | 0·140% (0·128–0·149)                                                                   | 263 (242–280)                                                        |
+|                                |                                                                               |                                                                                        |                                                                      |
+| Chile                          | 4241 (3422–5252)                                                              | 0·082% (0·066–0·101)                                                                   | 226 (183–280)                                                        |
+| Colombia                       | 7763 (5906–9984)                                                              | 0·108% (0·082–0·139)                                                                   | 152 (116–196)                                                        |
+| Costa Rica                     | 1161 (898–1448)                                                               | 0·125% (0·096–0·155)                                                                   | 227 (175–283)                                                        |
+| Dominican Republic             | 4947 (3506–6714)                                                              | 0·296% (0·210–0·401)                                                                   | 436 (309–592)                                                        |
+| Ecuador                        | 2322 (1884–2833)                                                              | 0·152% (0·123–0·185)                                                                   | 130 (105–158)                                                        |
+| El Salvador                    | 629 (409–928)                                                                 | 0·156% (0·101–0·230)                                                                   | 96 (62–142)                                                          |
+| Guatemala                      | 1178 (862–1559)                                                               | 0·115% (0·084–0·152)                                                                   | 63 (46–83)                                                           |
+| Honduras                       | 399 (238–603)                                                                 | 0·098% (0·058–0·148)                                                                   | 40 (24–60)                                                           |
+| Jamaica                        | 173 (106–254)                                                                 | 0·071% (0·044–0·105)                                                                   | 60 (36–87)                                                           |
+| Mexico                         | 21026 (19903–22 202)                                                          | 0·089% (0·084–0·094)                                                                   | 153 (145–162)                                                        |
+| Panama                         | 826 (667–1006)                                                                | 0·079% (0·063–0·096)                                                                   | 187 (151–227)                                                        |
+| Paraguay                       | 921 (634–1296)                                                                | 0·169% (0·116–0·238)                                                                   | 127 (87–179)                                                         |
+| Peru                           | 2298 (1669–3086)                                                              | 0·058% (0·042–0·078)                                                                   | 67 (49–90)                                                           |
+| Suriname                       | 118 (87–155)                                                                  | 0·142% (0·104–0·187)                                                                   | 206 (151–271)                                                        |
+| Uruguay                        | 1011 (796–1262)                                                               | 0·108% (0·085–0·134)                                                                   | 288 (227–360)                                                        |
+| Middle East and north Africa   |                                                                               |                                                                                        |                                                                      |
+| Bahrain                        | 295 (240–365)                                                                 | 0·047% (0·039–0·059)                                                                   | 170 (138–210)                                                        |
+| Egypt                          | 10674 (6584–15 169)                                                           | 0·177% (0·109–0·252)                                                                   | 100 (62–142)                                                         |
+| Iraq                           | 2060 (1646–2534)                                                              | 0·053% (0·043–0·066)                                                                   | 46 (37–57)                                                           |
+| Israel                         | 4089 (3459–4844)                                                              | 0·071% (0·060–0·085)                                                                   | 454 (384–537)                                                        |
+| Jordan                         | 544 (405–708)                                                                 | 0·093% (0·069–0·122)                                                                   | 53 (39–69)                                                           |
+| Kuwait                         | 1833 (1590–2086)                                                              | 0·072% (0·062–0·082)                                                                   | 414 (359–471)                                                        |
+| Lebanon                        | 846 (434–1253)                                                                | 0·108% (0·056–0·161)                                                                   | 147 (76–218)                                                         |
+| Malta                          | 204 (177–236)                                                                 | 0·078% (0·067–0·090)                                                                   | 483 (419–559)                                                        |
+| Morocco                        | 3890 (2468–6522)                                                              | 0·163% (0·103–0·273)                                                                   | 102 (65–172)                                                         |
+| Oman                           | 4304 (3180–5581)                                                              | 0·321% (0·237–0·416)                                                                   | 819 (605–1063)                                                       |
+| Qatar                          | 2497 (2020–3076)                                                              | 0·078% (0·063–0·096)                                                                   | 866 (700–1066)                                                       |
+| Saudi Arabia                   | 24328 (14997–33 171)                                                          | 0·202% (0·124–0·275)                                                                   | 679 (418–925)                                                        |
+| Tunisia                        | 1681 (1165–2267)                                                              | 0·177% (0·122–0·238)                                                                   | 139 (96–187)                                                         |
+
+economy-wide physical capital accumulation. However, any shifts from consumption into health care do not count as a loss, because they are simply a sectoral reallocation of resources within a full-employment economy, of which the health-care sector forms a part. In other words, health system costs are costs for services provided that have a return to the economy: for example, salaries for nurses and physicians, returns to investments in building hospitals and training residents, or returns to providers of medical devices and pharmaceuticals. In our model, these are not losses but rather part of the economic cycle.
+
+To quantify the macroeconomic burden of road injuries, we compared aggregate output (GDP) across the following two scenarios over the period 2015–30: the status quo scenario, in which no interventions are implemented that could reduce the mortality rate of road injuries relative to current and projected rates, and a counterfactual scenario, in which we assumed the complete elimination of road injuries at zero cost. We then calculated the macroeconomic burden of road injuries as the cumulative difference in projected annual GDP between these two scenarios. Although the baseline estimates are undiscounted, we also provide the figures subject to discount rates of 2% and 3%.
+
+#### **Data sources**
+
+We considered data for 166 countries and for a set of World Bank regions. The GDP projections for the status quo scenario and the saving rate are taken from the World Bank's database.22–24 The mortality and morbidity data (years of life lost due to premature mortality and years lost due to disability) are from GBD 2017.21 We relied on the International Labour Organization for agespecific labour force projections,25 the Barro-Lee education database for age-specific data on average years of schooling,26 and a 2014 World Bank report for returns on education.27 Using these data sources, we calculated human capital according to the Mincer equation28 and inferred the experience-related human capital component from the corresponding estimates of Heckman and colleagues.29 The physical capital data are taken from the Penn World Table projections,30 with the value for the output elasticity of physical capital (the percentage change in output for a 1% change in the physical capital stock) following standard economic estimates.31
+
+The total treatment cost of road injuries in the USA is based on the Cost of Injury Reports from the Centers for Disease Control and Prevention;32 their total treatment cost estimate includes the medical cost for fatal injuries, non-fatal hospitalised injuries, and non-fatal emergency department visits due to road accidents. We calculated the per case costs for the countries with data (ie, the USA) and extrapolated costs for countries without data, under the assumption that the per case costs are proportional to the per capita health expenditure. This technique has been used in previous studies.33,34 Further details on assumptions and other parameter values and data sources used in the macroeconomic model are provided in the appendix (pp 5–6). To make estimates among countries comparable, all costs were converted to US\$ with 2010 constant prices.
+
+For 28 countries, some data (mostly on education, physical capital, and the saving rate) are incomplete, although reliable data are available on GDP and the mortality and incidence of road injuries. We used a linear projection to approximate the economic burden of road injuries for these countries (appendix pp 6–7).
+
+#### **Sensitivity analysis**
+
+We also did sensitivity analyses (for the 138 countries that had all the data necessary to compute the costs directly on the basis of our model; appendix p 7) by varying the mortality and morbidity rates. The baseline estimates were calculated with the mean mortality and morbidity data from GBD. In the sensitivity analysis, best-case and worst-case estimates were calculated on the basis of the lower and upper bounds of GBD mortality and morbidity data. In the main analyses, we provided the undiscounted estimates following previous studies.18,20,33 In additional analyses, we also presented the discounted estimates for each country by World Bank region and by World Bank income group, assuming a discount rate of 2% and 3%.
+
+# **Role of the funding source**
+
+The funder had no role in the data collection, study design, analysis, interpretation, writing of the manuscript, or the decision to submit. The corresponding author had full access to all the data and had final responsibility for the decision to submit for publication.
+
+# **Results**
+
+We calculated the macroeconomic burden of road injuries as the difference in total GDP in 2015–30 between the status quo scenario and the counterfactual scenario (in which all road accidents are eliminated) for the 138 countries with complete data, representing more than 90% of the world's population (table 1). We also calculated the indirect estimates for the 28 countries for which we did not have full data (appendix p 7) and the discounted estimates (appendix pp 7–10). Among all countries, the USA has the largest economic burden of road injuries of \$487 billion, followed by China (\$364 billion) and India (\$101 billion; figure 1). In terms of percentage of GDP, Yemen (0·33%) and Oman (0·32%) have the largest burden (figure 2), whereas the per capita figures are highest in Luxembourg with \$1465, the USA with \$1444, Ireland with \$1081, and Norway with \$1052.
+
+Globally, we estimated the macroeconomic loss of road injuries to be \$1·797 trillion over 2015–30 (table 2). This number is \$1·460 trillion if discounted at 2% or \$1·317 trillion if discounted at 3% (appendix pp 10–11). Our result implies that the burden of road injuries is
+
+|                                | Economic burden, millions<br>of constant 2010 US\$<br>(lower and upper bound) | Percentage of total gross<br>domestic product in<br>2015–30<br>(lower and upper bound) | Per capita loss,<br>constant 2010 US\$<br>(lower and upper<br>bound) |
+|--------------------------------|-------------------------------------------------------------------------------|----------------------------------------------------------------------------------------|----------------------------------------------------------------------|
+| (Continued from previous page) |                                                                               |                                                                                        |                                                                      |
+| Yemen                          | 880 (591–1373)                                                                | 0·328% (0·220–0·512)                                                                   | 28 (19–43)                                                           |
+| North America                  |                                                                               |                                                                                        |                                                                      |
+| Canada                         | 27 573 (22 790–33 318)                                                        | 0·082% (0·067–0·099)                                                                   | 719 (594–869)                                                        |
+| USA                            | 487147 (45 3399–51 3884)                                                      | 0·157% (0·146–0·165)                                                                   | 1444 (1344–1523)                                                     |
+| South Asia                     |                                                                               |                                                                                        |                                                                      |
+| Bangladesh                     | 2793 (1613–4032)                                                              | 0·063% (0·036–0·091)                                                                   | 16 (9–23)                                                            |
+| Bhutan                         | 47 (21–70)                                                                    | 0·083% (0·037–0·125)                                                                   | 55 (25–83)                                                           |
+| India                          | 100933 (87476–112 282)                                                        | 0·153% (0·133–0·170)                                                                   | 71 (62–79)                                                           |
+| Nepal                          | 778 (321–1342)                                                                | 0·167% (0·069–0·288)                                                                   | 25 (10–43)                                                           |
+| Pakistan                       | 13426 (6349–20587)                                                            | 0·274% (0·130–0·421)                                                                   | 62 (29–95)                                                           |
+| Sri Lanka                      | 2035 (1301–3062)                                                              | 0·120% (0·077–0·180)                                                                   | 96 (61–145)                                                          |
+| Sub-Saharan Africa             |                                                                               |                                                                                        |                                                                      |
+| Angola                         | 2867 (1871–4247)                                                              | 0·155% (0·101–0·230)                                                                   | 80 (52–119)                                                          |
+| Benin                          | 409 (176–664)                                                                 | 0·183% (0·079–0·297)                                                                   | 31 (14–51)                                                           |
+| Botswana                       | 217 (164–285)                                                                 | 0·062% (0·047–0·082)                                                                   | 87 (65–114)                                                          |
+| Burkina Faso                   | 371 (233–544)                                                                 | 0·123% (0·077–0·180)                                                                   | 16 (10–24)                                                           |
+| Burundi                        | 43 (26–73)                                                                    | 0·115% (0·068–0·193)                                                                   | 3 (2–6)                                                              |
+| Cameroon                       | 782 (494–1198)                                                                | 0·104% (0·066–0·159)                                                                   | 28 (18–43)                                                           |
+| Cape Verde                     | 26 (17–36)                                                                    | 0·066% (0·044–0·093)                                                                   | 45 (30–64)                                                           |
+| Comoros                        | 12 (8–18)                                                                     | 0·102% (0·067–0·151)                                                                   | 13 (9–20)                                                            |
+| Congo (Brazzaville)            | 421 (251–665)                                                                 | 0·190% (0·113–0·301)                                                                   | 69 (41–109)                                                          |
+| DR Congo                       | 1475 (964–2196)                                                               | 0·218% (0·142–0·324)                                                                   | 15 (10–23)                                                           |
+| Ethiopia                       | 1034 (829–1281)                                                               | 0·067% (0·054–0·083)                                                                   | 9 (7–11)                                                             |
+| Gabon                          | 368 (253–518)                                                                 | 0·100 (0·069–0·140)                                                                    | 164 (112–230)                                                        |
+| The Gambia                     | 23 (12–37)                                                                    | 0·094% (0·051–0·154)                                                                   | 9 (5–15)                                                             |
+| Ghana                          | 1870 (1239–2730)                                                              | 0·156% (0·104–0·228)                                                                   | 58 (38–84)                                                           |
+| Guinea-Bissau                  | 41 (24–64)                                                                    | 0·168% (0·099–0·263)                                                                   | 19 (11–30)                                                           |
+| Kenya                          | 890 (776–1104)                                                                | 0·067% (0·058–0·083)                                                                   | 16 (14–19)                                                           |
+| Lesotho                        | 153 (96–229)                                                                  | 0·280% (0·176–0·419)                                                                   | 64 (40–96)                                                           |
+| Liberia                        | 23 (14–35)                                                                    | 0·066% (0·040–0·103)                                                                   | 4 (3–7)                                                              |
+| Madagascar                     | 241 (152–367)                                                                 | 0·104% (0·066–0·159)                                                                   | 8 (5–12)                                                             |
+| Malawi                         | 159 (100–237)                                                                 | 0·082% (0·052–0·122)                                                                   | 7 (5–11)                                                             |
+| Mali                           | 273 (168–440)                                                                 | 0·090% (0·056–0·145)                                                                   | 12 (8–20)                                                            |
+| Mauritania                     | 100 (64–142)                                                                  | 0·080% (0·051–0·114)                                                                   | 20 (12–28)                                                           |
+| Mauritius                      | 221 (177–274)                                                                 | 0·085% (0·068–0·106)                                                                   | 175 (140–217)                                                        |
+| Mozambique                     | 307 (196–445)                                                                 | 0·095% (0·061–0·137)                                                                   | 9 (6–13)                                                             |
+| Namibia                        | 296 (190–470)                                                                 | 0·109% (0·070–0·173)                                                                   | 105 (67–167)                                                         |
+| Niger                          | 116 (74–181)                                                                  | 0·061% (0·039–0·095)                                                                   | 4 (3–7)                                                              |
+| Nigeria                        | 4977 (3052–7847)                                                              | 0·060% (0·037–0·094)                                                                   | 23 (14–36)                                                           |
+| Rwanda                         | 347 (184–604)                                                                 | 0·149% (0·079–0·259)                                                                   | 25 (13–44)                                                           |
+| Senegal                        | 254 (162–407)                                                                 | 0·058% (0·037–0·094)                                                                   | 14 (9–22)                                                            |
+| Sierra Leone                   | 47 (28–74)                                                                    | 0·065% (0·039–0·102)                                                                   | 6 (3–9)                                                              |
+| South Africa                   | 14216 (11905–16891)                                                           | 0·191% (0·160–0·227)                                                                   | 236 (198–281)                                                        |
+| Sudan                          | 2144 (1380–3703)                                                              | 0·177% (0·114–0·306)                                                                   | 46 (30–80)                                                           |
+| Tanzania                       | 887 (581–1300)                                                                | 0·076% (0·050–0·112)                                                                   | 13 (9–19)                                                            |
+| Togo                           | 129 (80–195)                                                                  | 0·133% (0·082–0·201)                                                                   | 14 (9–22)                                                            |
+| Uganda                         | 670 (390–1038)                                                                | 0·103% (0·060–0·159)                                                                   | 13 (8–20)                                                            |
+| Zambia                         | 578 (380–855)                                                                 | 0·101% (0·066–0·149)                                                                   | 29 (19–42)                                                           |
+|                                |                                                                               |                                                                                        |                                                                      |
+
+*Table 1:* **Economic burden attributable to road injuries in 2015–30, by country and World Bank region**
+
+![](_page_5_Figure_1.jpeg)
+
+*Figure 1:* **Macroeconomic burden due to road injuries in 2015–30 (in billions of US\$ with constant prices as of 2010)** Grey areas represent countries with insufficient data.
+
+![](_page_5_Figure_3.jpeg)
+
+*Figure 2:* **Macroeconomic burden due to road injuries as a percentage of total GDP in 2015–30** Grey areas represent countries with insufficient data. GDP=gross domestic product.
+
+equivalent to an annual tax of 0·12% on global output, with an average per capita burden of \$231.
+
+By World Bank region, the aggregate macroeconomic burden of road injuries is highest in east Asia and the Pacific with a total economic loss of \$560 billion (table 2). North America has the second largest aggregate total economic loss of \$515 billion, but the highest per capita loss of \$1370 (table 2). This loss corresponds to an annual tax of 0·15% on the region's aggregate output. The economic burden of road injuries increases as the income group escalates: high-income countries bear the greatest burden with a total economic loss of \$963 billion and a per capita loss of \$779 (table 2). By contrast, road injuries cost low-income countries \$11 billion in total and \$14 per person (table 2). In terms of percentage loss of (cumulative) GDP, all countries have a relatively similar burden: 0·106% of GDP for high-income countries, 0·120% for low-income countries, and 0·138–0·144% for middle-income countries (table 2). Discounted estimates by World Bank region and World Bank income group are shown in the appendix (pp 10–11).
+
+Road injuries resulted in 70 million disability-adjusted life-years (DALYs) worldwide in 2015.21 The economic burden is not distributed in proportion with population size and DALYs (table 3). For example, south Asia accounts for 23·8% of the DALYs, but only 6·7% of the economic loss, whereas North America accounts for only 3·9% of the DALYs, but 28·6% of the economic loss (table 3). Notably, despite the relatively low economic burden of road injuries in low-income and middleincome countries (46·4% of the global economic loss), the disease burden, as measured in DALYs, is very large (89% of global DALYs; table 3).
+
+We also explored the importance of treatment costs in the economic burden of road injuries. A previous empirical analysis35 produced a bell curve when plotting traffic fatalities against GDP. Given that accident and injury rates are not declining with income, the downward segment of this curve seems to be mostly due to better life-saving treatments in high-income countries. This disparity might also be evident in treatment costs, where countries with a higher income conceivably face a higher burden. Our results show that treatment costs account for a greater proportion of the total economic burden in high-income countries than in low-income countries. In high-income countries, physical capital loss (because a proportion of the costs of treating road injuries could have gone into savings if no road injury had occurred) accounts for 31·5% of the total economic burden due to road injuries, but this number decreases to 13·9% for upper-middle-income countries, 6·2% for lower-middleincome countries, and 3·9% for low-income countries (appendix p 11).
+
+# **Discussion**
+
+This study estimates the macroeconomic burden of road injuries for 166 countries and shows that between 2015 and 2030, road injuries will cost the world economy \$1·8 trillion through a combination of diversion—healthcare expenditures that would otherwise have been used for savings or investment—and losses in employment due to mortality and morbidity. This figure is more than the aggregate GDP of Canada (the world's tenth largest economy) in 2017.36 The economic burden of road injuries is equivalent to an annual tax of 0·12% on global GDP during this period.
+
+The health and economic burdens of road injuries are distributed unequally across countries and regions. Of the 70 million DALYs lost to road injuries worldwide in 2015, nearly 90% occurred in low-income and middleincome countries. This distribution might be due to a higher proportion of vulnerable road users (including pedestrians, cyclists, and riders of motorised two-wheelers and their passengers) in lower-income countries.37 Moreover, low-income countries are more likely to lack good-quality prehospital care, the mandatory use of seatbelts for drivers and helmets for motorcyclists, appropriate speed limits, and effective laws against drunk driving.37 Responsive policy strategies for low-income and middle-income countries could include improving road conditions, lighting, traffic lights, and signage, building paved and level roads with more clearly demarcated traffic lanes, installing dedicated bike lanes, pedestrian crossings, and raised and protected pavements, enforcing the mandatory use of seatbelts in cars and helmets for motorcyclists, establishing laws against drunk driving, vehicle inspection laws, and specific speed limits appropriate to the type of road, and strengthening traffic law enforcement overall.
+
+Despite the large burden in terms of DALYs, the economic burden of road injuries in low-income and middle-income countries only accounts for 46·4% of the global economic cost. The disparity relates to differences in economic development. First, the workforce in
+
+|                                    | Economic loss, billions of<br>constant 2010 US\$ | Percentage of total<br>gross domestic<br>product in 2015–30 | Per capita loss,<br>constant 2010 US\$ |
+|------------------------------------|--------------------------------------------------|-------------------------------------------------------------|----------------------------------------|
+| By World Bank region               |                                                  |                                                             |                                        |
+| East Asia and Pacific              | 560                                              | 0·123%                                                      | 240                                    |
+| Europe and central Asia            | 345                                              | 0·082%                                                      | 374                                    |
+| Latin America and Caribbean        | 115                                              | 0·116%                                                      | 184                                    |
+| Middle East and north Africa       | 103                                              | 0·166%                                                      | 227                                    |
+| North America                      | 515                                              | 0·149%                                                      | 1370                                   |
+| South Asia                         | 121                                              | 0·155%                                                      | 64                                     |
+| Sub-Saharan Africa                 | 38                                               | 0·120%                                                      | 33                                     |
+| By World Bank country income group |                                                  |                                                             |                                        |
+| Low income                         | 11                                               | 0·120%                                                      | 14                                     |
+| Lower-middle income                | 202                                              | 0·138%                                                      | 64                                     |
+| Upper-middle income                | 621                                              | 0·144%                                                      | 237                                    |
+| High income                        | 963                                              | 0·106%                                                      | 779                                    |
+| Global (166 countries)             | 1797                                             | 0·120%                                                      | 231                                    |
+
+*Table 2:* **Economic cost attributable to road injury mortality and morbidity, by World Bank region and World Bank country income group**
+
+|                                    | Population in<br>2015, million<br>(global %) | Gross domestic<br>product in 2015,<br>billions of<br>constant 2010<br>US\$ (global %) | Economic loss in<br>2015–30,<br>billions of<br>constant 2010<br>US\$ (global %) | Disability<br>adjusted life<br>years in 2015,<br>million<br>(global %) |
+|------------------------------------|----------------------------------------------|---------------------------------------------------------------------------------------|---------------------------------------------------------------------------------|------------------------------------------------------------------------|
+| By World Bank region               |                                              |                                                                                       |                                                                                 |                                                                        |
+| East Asia and Pacific              | 2251 (31·3%)                                 | 20236 (27·3%)                                                                         | 560 (31·1%)                                                                     | 21·5 (32·2%)                                                           |
+| Europe and central Asia            | 906 (12·6%)                                  | 22466 (30·3%)                                                                         | 345 (19·2%)                                                                     | 5·8 (8·7%)                                                             |
+| Latin America and Caribbean        | 584 (8·1%)                                   | 5339 (7·2%)                                                                           | 115 (6·4%)                                                                      | 5·8 (8·7%)                                                             |
+| Middle East and north Africa       | 404 (5·6%)                                   | 3146 (4·2%)                                                                           | 103 (5·8%)                                                                      | 5·8 (8·6%)                                                             |
+| North America                      | 356 (4·9%)                                   | 18500 (25·0%)                                                                         | 515 (28·6%)                                                                     | 2·6 (3·9%)                                                             |
+| South Asia                         | 1744 (24·2%)                                 | 2796 (3·8%)                                                                           | 121 (6·7%)                                                                      | 15·9 (23·8%)                                                           |
+| Sub-Saharan Africa                 | 950 (13·2%)                                  | 1621 (2·2%)                                                                           | 38 (2·1%)                                                                       | 9·5 (14·1%)                                                            |
+| By World Bank country income group |                                              |                                                                                       |                                                                                 |                                                                        |
+| Low income                         | 621 (8·6%)                                   | 374 (0·5%)                                                                            | 11 (0·6%)                                                                       | 6·8 (10·1%)                                                            |
+| Lower-middle income                | 2856 (39·7%)                                 | 5812 (7·8%)                                                                           | 202 (11·2%)                                                                     | 26·8 (40·1%)                                                           |
+| Upper-middle income                | 2521 (35·0%)                                 | 18952 (25·6%)                                                                         | 621 (34·6%)                                                                     | 26·0 (38·9%)                                                           |
+| High income                        | 1196 (16·6%)                                 | 48966 (66·1%)                                                                         | 963 (53·6%)                                                                     | 7·3 (10·9%)                                                            |
+| Global (166 countries)             | 7195 (100%)                                  | 74103 (100%)                                                                          | 1797 (100%)                                                                     | 70·0 (100%)                                                            |
+|                                    |                                              |                                                                                       |                                                                                 |                                                                        |
+
+*Table 3:* **Comparison of macroeconomic loss and lifetime disease burden by World Bank region and country income group**
+
+high-income countries is typically better educated, which implies that, for the same loss of DALYs due to road injuries, the loss of human capital will be larger. Second, high-income countries have advanced healthcare systems (eg, in terms of ambulance response times and accident and emergency departments), implying a smaller loss of DALYs due to lower morbidity and mortality associated with road injuries, but also much greater treatment costs. Our results show that physical capital loss due to diversion of savings to pay for treatment has a more important role in high-income countries than in low-income countries. More than 30% of the total economic burden due to road injuries comes from physical capital loss in high-income countries, whereas physical capital loss accounts for less than 5% of the total economic burden in low-income countries. Although the economic burden of road injuries on low-income countries is relatively light at present, it is likely to rise in the course of economic development if growth in motorisation and traffic density outpaces development of infrastructure and law enforcement levels.38–40
+
+Promotion of the use of self-driving cars might be a potential solution for reducing road accidents and lowering the burden of road injuries. Articles in *The Economist*41,42 and findings by the Boston Consulting Group43 argue that 90–94% of all accidents are due to human error and are, therefore, preventable through the use of self-driving cars. We calculated the potential cost savings from the adoption of autonomous cars by considering a conservative scenario of a 50% reduction in accidents and an optimistic scenario of a 90% reduction in accidents (as determined by *The Economist* and by the Boston Consulting Group). In the conservative scenario, autonomous cars could save \$0·9 trillion at a global level, whereas savings of \$1·6 trillion were produced in the optimistic scenario. However, because a country's infrastructure must be well developed to use self-driving vehicles successfully, promotion of their use might only be possible in high-income countries in the near future. The scientific research on autonomous cars and accident prevention is in its infancy; autonomous cars, for example, might lead to greater traffic density such that the number of accidents could increase.
+
+Our model has several limitations (appendix pp 11–13). First, we had to rely on imputations to calculate road injury-related health expenditures. This could either underestimate or overestimate the country-specific treatment cost of road injuries. However, this technique is a widely used approach to deal with lack of data and has also been adopted in other studies calculating the economic burden of other health outcomes.33,34 Second, owing to missing data, we had to impute the economic burden of road injuries for a subset of 28 of 166 countries. However, this does not substantially compromise our results, given that the 138 countries for which we had complete data cover more than 90% of the world population. Third, we did not account for the behavioural changes of family members, including their participation in the labour force when traffic accidents happen. Nevertheless, our analysis has many strengths and is a first step in understanding the global macroeconomic burden of road injuries using a simulation model rigorously grounded in dynamic macroeconomic theory.
+
+This study shows that high-income countries have the largest macroeconomic costs of road injuries, whereas low-income and middle-income countries bear sizeable health burdens. The fact that low-income and middle-income countries bear the majority of the human toll underscores the need for improvements on multiple fronts, including infrastructure, law enforcement, public awareness, and emergency response systems. Otherwise, as these countries develop, the human cost they already bear will be accompanied by economic hardship.
+
+#### **Contributors**
+
+SC, KP, MK, and DEB contributed to the study concept and design. SC did data analysis and wrote the first draft of the manuscript. SC, KP, MK, and DEB contributed to literature review and the interpretation of the data. KP, MK, and DEB critically revised the manuscript for important intellectual content. All authors approved the final version.
+
+#### **Declaration of interests**
+
+We declare no competing interests.
+
+#### **Acknowledgments**
+
+This research received funding from National Institute on Aging, National Institutes of Health (award numbers P30AG024409 and R01AG048037)
+
+#### **References**
+
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+- 27 Montenegro CE, Patrinos HA. Comparable estimates of returns to schooling around the world. Washington, DC: World Bank Group, 2014.
+- 28 Mincer J. Schooling, experience, and earnings. New York, NY: National Bureau of Economic Research, 1974.
+- 29 Heckman JJ, Lochner LJ, Todd PE. Earnings functions, rates of return and treatment effects: the Mincer equation and beyond. In: Hanushek E, ed. Handbook of the economics of education. Amsterdam: Elsevier, 2006: 307–458.
+- 30 University of Groningen and University of California. Capital stock at constant national prices for United States (RKNANPUSA666NRUG). Federal Reserve Bank of St Louis, 2017. https://fred.stlouisfed.org/series/RKNANPUSA666NRUG (accessed Aug 23, 2017).
+
+- 31 Jones CI. R&D-based models of economic growth. *J Polit Economy* 1995; **103:** 759–84.
+- 32 Centers for Disease Control and Prevention. Cost of injury data. Centers for Disease Control and Prevention, 2010. https://www.cdc.gov/injury/wisqars/cost/index.html (accessed March 20, 2018).
+- 33 Bloom DE, Cafiero E, Jané-Llopis E, et al. The global economic burden of noncommunicable diseases. Geneva: World Economic Forum, 2011.
+- 34 Ding D, Lawson KD, Kolbe-Alexander TL, et al. The economic burden of physical inactivity: a global analysis of major non-communicable diseases. *Lancet* 2016; **388:** 1311–24.
+- 35 Bishai D, Quresh A, James P, Ghaffar A. National road casualties and economic development. *Health Econ* 2006; **15:** 65–81.
+- 36 The World Bank. Canada. The World Bank, 2018. https://data. worldbank.org/country/canada (accessed Sep 3, 2019).
+- 37 WHO. 10 facts on global road safety. Geneva: World Health Organization, 2017. http://www.who.int/features/factfiles/ roadsafety/en/ (accessed June 20, 2018).
+- 38 WHO. Global status report on road safety 2013: supporting a decade of action. Geneva: World Health Organization, 2013.
+- 39 Ameratunga S, Hijar M, Norton R. Road-traffic injuries: confronting disparities to address a global-health problem. *Lancet* 2006; **367:** 1533–40.
+- 40 Chandran A, Sousa TRV, Guo Y, Bishai D, Pechansky F, Vida No Transito Evaluation Team. Road traffic deaths in Brazil: rising trends in pedestrian and motorcycle occupant deaths. *Traffic Injury Prev* 2012; **13** (suppl 1)**:** 11–16.
+- 41 Reinventing wheels. Autonomous vehicles are just around the corner. *The Economist,* March 1, 2018.
+- 42 A different world. Self-driving cars will profoundly change the way people live. Special report on autonomous cars. *The Economist*, March 1, 2018.
+- 43 Lang N, Rüßmann M, Mei-Pochtler A, et al. Self-driving vehicles, robo-taxis, and the urban mobility revolution. Boston Consulting Group, 2016. https://www.bcg.com/publications/2016/automotivepublic-sector-self-driving-vehicles-robo-taxis-urban-mobilityrevolution.aspx (accessed Sep 3, 2019).

Zotero/001_artiklid/Road Safety Indicators/forumroadsafetyannualreport2023.md

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+---
+category: literaturenote
+citekey: forumroadsafetyannualreport2023
+title: Road Safety Annual Report 2023
+authors: International Transport Forum
+year: 2023
+date: 2023-12-18 2023-12-18
+doi: 10.1787/8654c572-en
+url: "https://www.oecd.org/en/publications/road-safety-annual-report-2023_8654c572-en.html"
+zotero_key: JEBXV66X
+zotero_storage: 3Q9CYK8Y
+collections: doktoritöö / HLO
+folder: 001_artiklid/Road Safety Indicators
+firstAuthor: International Transport Forum
+status: converted
+---
+![](_page_0_Picture_0.jpeg)
+
+# **Road Safety** Annual Report 2023
+
+![](_page_0_Picture_2.jpeg)
+
+![](_page_1_Picture_0.jpeg)
+
+# **Road Safety** Annual Report 2023
+
+![](_page_2_Picture_1.jpeg)
+
+### **About this publication**
+
+This work is published under the responsibility of the Secretary‑General of the International Transport Forum. The opinions expressed and arguments employed herein do not necessarily reflect the official views of International Transport Forum member countries. This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law. Data in this report have been provided by countries to the database of the International Traffic Safety Data and Analysis Group (IRTAD). Where data in this report has not been independently validated by IRTAD, this is indicated. Additional information on individual countries is provided online at www.itf-oecd.org/irtad.
+
+Cite this work as: ITF (2023), *Road Safety Annual Report 2023*, OECD Publishing, Paris.
+
+## **About the International Transport Forum**
+
+The International Transport Forum (ITF) is an intergovernmental organisation with 66 member countries that organises global dialogue for better transport. It acts as a think tank for transport policy and hosts the Annual Summit of transport ministers. The ITF is the only global body that covers all transport modes. The ITF is administratively integrated with the OECD, yet politically autonomous.
+
+#### **International Transport Forum**
+
+2 rue André Pascal F‑75775 Paris Cedex 16 contact@itf-oecd.org www.itf-oecd.org
+
+### **About IRTAD**
+
+The International Traffic Safety Data and Analysis Group (IRTAD) is the permanent working group for road safety of the International Transport Forum. The IRTAD Group brings together road safety experts from national road administrations, road safety research institutes, international organisations, automobile associations, insurance companies, car manufacturers and others. With 80 members and observers from more than 40 countries, the IRTAD Group is a central force in promoting international co‑operation on road crash data and its analysis.
+
+### **About the IRTAD Database**
+
+The IRTAD Database includes road safety data, aggregated by country and year from 1970 onwards. It provides an empirical basis for international comparisons and more effective road safety policies.
+
+The IRTAD Group validates data for quality before inclusion in the database. At present, the database includes validated data from 35 countries: Argentina, Australia, Austria, Belgium, Canada, Chile, Colombia, Costa Rica, Czechia, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Lithuania, Luxembourg, the Netherlands, New Zealand, Norway, Poland, Portugal, Serbia, Slovenia, Spain, Sweden, Switzerland, the United Kingdom and the United States.
+
+The data in this report are valid as of 3 December 2023. The data are provided in a common format based on definitions developed and agreed by the IRTAD Group. Selected data are available for free; full online access requires IRTAD membership. Access the database via the OECD statistics portal: https://stats.oecd.org/Index.aspx?DataSetCode=IRTAD\_CASUAL\_BY\_AGE.
+
+| Table of contents | Introduction<br>Foreword                                                             | 8<br>8   |
+|-------------------|--------------------------------------------------------------------------------------|----------|
+|                   | Preface                                                                              | 9        |
+|                   | Short‑term road safety trends<br>Preliminary 2023 data                               | 10<br>10 |
+|                   | Mobility and road safety in 2022                                                     | 12       |
+|                   | Traffic volumes in 2022                                                              | 12       |
+|                   | Road deaths in 2022                                                                  | 14       |
+|                   | Mortality rates and fatality risks in 2022                                           | 28       |
+|                   | Longer-term road safety trends<br>Evolution in the number of<br>road deaths, 2012‑22 | 32<br>32 |
+|                   | Road deaths by user group                                                            | 44       |
+|                   | Road deaths by age group                                                             | 49       |
+|                   | Road deaths by road type                                                             | 50       |
+|                   | National road safety strategies                                                      | 51       |
+|                   | References                                                                           | 52       |
+|                   | Data tables                                                                          | 53       |
+|                   | Annex. Road safety strategies and targets in IRTAD countries                         | 62       |
+|                   | Acknowledgements                                                                     | 72       |
+|                   | IRTAD members and observers                                                          | 73       |
+
+### **Figures**
+
+16 Figure 1: Evolution in road deaths by user category, 2022 compared to average for 2017-19
+
+21 Figure 2: Evolution in road deaths by age group, 2022 compared to average for 2017-19
+
+22 Figure 3: Mortality rate by age group, 2022
+
+26 Figure 4: Road deaths by road type, 2022
+
+27 Figure 5: Evolution in road deaths by road type, 2022 compared to average for 2017-19
+
+29 Figure 6: Road fatalities per 100 000 inhabitants, 2022
+
+30 Figure 7: Road fatalities per 10 000 registered vehicles, 2022
+
+31 Figure 8: Road fatalities per billion vehicle-kilometres, 2021
+
+33 Figure 9: Aggregate evolution in the number of road deaths in IRTAD countries, 2012-2022
+
+35 Figure 10: Percentage change in the number of road deaths, 2012-22
+
+38 Figure 11: Road deaths compared to the linear trend since 2012 (excluding 2020 and 2021)
+
+44 Figure 12: Evolution in road deaths by user category, 2022 compared to 2012
+
+45 Figure 13: Percentage change in the number of passenger car occupants killed, 2012-22
+
+46 Figure 14: Percentage change in the number of pedestrians killed, 2012-22
+
+47 Figure 15: Percentage change in the number of cyclists killed, 2012-22
+
+48 Figure 16: Percentage change in the number of PTW killed, 2012-22
+
+49 Figure 17: Evolution in road deaths by age group, 2022 compared to 2012
+
+50 Figure 18: Evolution in road deaths by road type, 2022 compared to 2012
+
+### **Tables**
+
+11 Table 1: Road deaths, first half of 2017‑2023 Provisional data
+
+13 Table 2: Traffic volumes in 2017-22 (millions vehicle-kilometres)
+
+15 Table 3: 2022 Road fatality data compared to the 2017-19 average
+
+19 Table 4: Percentage share of e-bike users in cyclist fatalities
+
+36 Table 5: Road fatality trends, 2012-22
+
+54 Table 6: National speed limits on urban roads, rural roads and motorways, 2023 passenger vehicles (km/h)
+
+56 Table 7: Maximum authorised blood alcohol content levels, 2023, by country
+
+58 Table 8: Seat-belt laws and wearing rates in front and rear seats of passenger cars, 2022 or latest available year
+
+60 Table 9: Helmet laws and wearing rates, 2022 or latest available year
+
+63 Table A1: Road safety strategies in IRTAD countries
+
+68 Table A2: Targets on road deaths and serious injuries in IRTAD countries
+
+#### **Boxes**
+
+13 Box 1 Mobility in France after the Covid‑19 pandemic
+
+17 Box 2 Motorcycle use in Latin America and the Caribbean
+
+28 Box 3 Measuring risk and comparing countries
+
+### **Foreword**
+
+I am pleased to present to you the 2023 ITF Annual Report on Road Safety. For over a decade, this report has been a trusted source of high‑quality traffic‑crash data. This report would not have been possible without the dedicated work of the International Traffic Safety Data and Analysis Group (IRTAD), the International Transport Forum's permanent working group on road safety.
+
+The good news is that most of the 35 IRTAD countries analysed in this report recorded a reduction in road fatalities in 2022 compared to the 2017‑2019 average. That said, more must be done to reach the target of halving road deaths by 2030, which is enshrined in the 2020 UN General Assembly resolution A/RES/74/299 on "Improving Global Road Safety".
+
+Following the ITF's Safe System approach can help countries reach that goal. ITF's IRTAD working group has actively advocated the Safe System approach in various reports and is currently working on transforming it into a tool for road safety assessment, counselling, and benchmarking Safe System implementations or indicators.
+
+Better data collection and analysis are the essential first steps towards improved road safety, as the foundation for setting targets and monitoring road safety progress. This report offers a glance on the current road safety trends across IRTAD countries, highlighting challenges in front of us, from the emergence of new mobility trends to an ageing population. ITF's IRTAD working group is committed to helping policymakers in addressing these challenges and finding solutions to make our roads safer for everyone. This report offers a departing point of this discussion. I hope you will enjoy reading it.
+
+**Young Tae KIM, Secretary-General of ITF**
+
+### **Preface**
+
+At its 2022 conference in Lyon, the International Traffic Safety Data and Analysis Group (IRTAD) adopted the Lyon Declaration. The declaration's 14 recommendations focus on improving the quality and comparability of road‑safety data to inform policies to achieve the ambitious target of halving the number of road deaths and serious injuries by 2030 (IRTAD, 2022a).
+
+Figures for 2022 presented in this report, as well as the first 2023 figures, clearly show that the impact of the Covid‑19 pandemic on traffic, road crashes and deaths has abated. The bad news is that the number of road deaths between 2020‑21 and 2022 increased. The good news is that in many countries (among the 35 for which figures are presented here), the number of fatalities in 2022 continued to fall compared with 2019 and previous years. However, the ten‑year trends also show that this decrease is sometimes very small. Particular attention must therefore be paid to this issue when devising policies to reduce fatalities and serious injuries.
+
+Two sub‑groups have been set up within IRTAD. The first will focus on data harmonisation and regional road safety observatories, as reliable data are not enough to make relevant comparisons between countries. The second group will focus on national road safety strategies, in co‑operation with the European Commission initiative to develop a tool for countries to monitor the implementation of national strategies. The first results of these two groups will be reported in 2024.
+
+Data reviews have also been carried out by IRTAD members in Cameroon in 2023. Again, it is important to stress the value of these management reviews in enabling the countries concerned to support effective policies to improve their data collection.
+
+Finally, there is cause for optimism in the adoption of low emission zones, traffic limited zones and the development of 30 km/h zones by many cities. Although the decision to introduce a 30 km/h zone is often taken for environmental reasons (low‑emission mobility zones), the impact in terms of improving road safety is obvious.
+
+This shows that road safety is an integral part of mobility management policies and a contributor to sustainable territorial development. The ITF and IRTAD will continue to work for safe and sustainable mobility.
+
+### **Dominique MIGNOT, Chair, IRTAD**
+
+This section presents data on short‑term trends in road safety. It includes preliminary data for the year 2023 and mobility and road safety data for the year 2022.
+
+### **Preliminary 2023 data**
+
+Preliminary data for the first half of 2023 shows an improved situation compared to the beginning of 2022. The analysis is restricted to the 24 countries with available data.
+
+In the first half of 2023, road deaths decreased in 17 countries and increased in only seven countries compared to 2022: Colombia, Denmark, Ireland, Japan, Lithuania, Portugal and Sweden. However, in these countries, apart from Colombia and Ireland, road deaths decreased if the first six months of 2023 are compared with the 2017‑19 average for the first half of the year (see Table 1).
+
+In the first half of 2023, road deaths increased in the Netherlands (4.4%), Norway (8.5%) and the United States<sup>1</sup> (11.9%) when compared to the average 2017‑19.
+
+At the same time, 2023 data for 11 IRTAD members, including several with large populations, were unavailable at the time of writing. Including this data in future reports will influence the overall trend.
+
+1 2022 and 2023 data for the United States are statistical projections.
+
+Road deaths decreased by 2.8% in 2023 compared to 2022.
+
+**Road deaths, first half of 2017‑2023** Provisional data
+
+| Country       | Average<br>2017‑19 | 2022   | 2023   | % change in<br>2023 compared<br>to av. 2017‑19 | % change in<br>2023 compared<br>to 2022 |
+|---------------|--------------------|--------|--------|------------------------------------------------|-----------------------------------------|
+| Austria       | 189                | 191    | 179    | -5.3                                           | -6.3                                    |
+| Colombia      | 3 153              | 3 813  | 4 002  | 26.9                                           | 5.0                                     |
+| Czechia       | 265                | 252    | 241    | -9.1                                           | -4.4                                    |
+| Denmark       | 84                 | 64     | 77     | -8.3                                           | 20.3                                    |
+| Finland       | 107                | 85     | 75     | -29.9                                          | -11.8                                   |
+| France        | 1 557              | 1 536  | 1 380  | -11.4                                          | -10.2                                   |
+| Germany       | 1 502              | 1 271  | 1 264  | -15.8                                          | -0.6                                    |
+| Greece        | 309                | 288    | 281    | -9.1                                           | -2.4                                    |
+| Hungary       | 267                | 233    | 213    | -20.2                                          | -8.6                                    |
+| Iceland       | 7                  | 4      | 1      | -85.7                                          | -75.0                                   |
+| Ireland       | 72                 | 77     | 84     | 16.7                                           | 9.1                                     |
+| Italy         | 1 544              | 1 419  | 1 384  | -10.4                                          | -2.5                                    |
+| Japan         | 1 869              | 1 422  | 1 441  | -22.9                                          | 1.3                                     |
+| Lithuania     | 80                 | 49     | 73     | -8.8                                           | 49.0                                    |
+| Luxembourg    | 13                 | 13     | 13     | 0.0                                            | 0.0                                     |
+| Netherlands   | 273                | 324    | 285    | 4.4                                            | -12.0                                   |
+| New Zealand   | 192                | 182    | 171    | -10.9                                          | -6.0                                    |
+| Norway        | 47                 | 54     | 51     | 8.5                                            | -5.6                                    |
+| Poland        | 1 225              | 893    | 824    | -32.7                                          | -7.7                                    |
+| Portugal      | 299                | 280    | 286    | -4.3                                           | 2.1                                     |
+| Serbia        | 228                | 240    | 220    | -3.5                                           | -8.3                                    |
+| Slovenia      | 51                 | 51     | 39     | -23.5                                          | -23.5                                   |
+| Sweden        | 117                | 95     | 110    | -6.0                                           | 15.8                                    |
+| United States | 17 437             | 20 190 | 19 515 | 11.9                                           | -3.3                                    |
+
+### **Mobility and road safety in 2022**
+
+Data on mobility and road safety in 2022 relate to traffic volumes, road deaths, mortality rates and fatality risks.
+
+### **Traffic volumes in 2022**
+
+This report expresses the traffic volume in individual countries as the total distance travelled in vehicle‑kilometres (vkm).
+
+In 2022, traffic volumes, measured in millions of vkm, increased compared to 2020 but were not yet back to the levels of 2017‑19, before the Covid‑19 pandemic (see Table 2). This was the case for all 15 countries which provided these data, except Canada, Czechia, Denmark, Hungary and Iceland, where traffic volumes in 2022 were back to pre‑Covid 19 levels.
+
+2022 can no longer be considered an "abnormal" year. In some countries, traffic volumes did not recover to pre‑Covid 19 levels, but this was mainly due to a change in mobility behaviour.
+
+In Denmark, for example, the Danish National Travel Survey data indicate that the reduction in travel by car is due to the increase in gasoline prices and a more widespread habit of working from home.
+
+Also, in Germany, working from home could be an explanation for reduced traffic. Between 2017 and 2022, the percentage of employees teleworking some days of the week increased from 13% to 28%. In addition, new mobility routines have emerged in recent years. Walking has increased, while cycling remains stable. Cars and public transport are used less frequently but for longer distances. Box 1 presents the situation in France.
+
+Traffic volumes in 2022 had not returned to pre‑Covid levels, reflecting changes in mobility behaviour.
+
+### **Traffic volumes in 2017-22 (millions vehicle-kilometres)**
+
+| Country       | Average<br>2017-19 | 2020    | 2021    | 2022    | % change<br>in 2022<br>compared to<br>av. 2017-19 | % change<br>in 2022<br>compared to<br>2020 |
+|---------------|--------------------|---------|---------|---------|---------------------------------------------------|--------------------------------------------|
+| Australia     | 256 626            | 242 880 | 244 787 | 240 011 | -6.5                                              | -1.2                                       |
+| Canada        | 398 337            | 378 046 | 409 029 | 410 000 | 2.9                                               | 8.5                                        |
+| Czechia       | 56 240             | 52 280  | 53 742  | 58 818  | 4.6                                               | 12.5                                       |
+| Denmark       | 54 540             | 51 527  | 53538   | 54913   | 0.7                                               | 6.6                                        |
+| Finland       | 50 349             | 48 543  | 48 305  | 47 695  | -5.3                                              | -1.7                                       |
+| France        | 641 000            | 531 911 | 577 044 | 629 380 | -1.8                                              | 18.3                                       |
+| Germany       | 751 900            | 681 749 | 690 000 | 721 000 | -4.1                                              | 5.8                                        |
+| Great Britain | 539 298            | 427 914 | 478 874 | 521 093 | -3.4                                              | 21.8                                       |
+| Hungary       | 45 374             | 41 854  | 46 611  | 49 531  | 9.2                                               | 18.3                                       |
+| Iceland       | 3 981              | 3 800   | 3 942   | 4 010   | 0.7                                               | 5.5                                        |
+| Netherlands   | 135 057            | 117 853 | 123 105 | 131 510 | -2.6                                              | 11.6                                       |
+| New Zealand   | 47 482             | 45 905  | 46 550  | 47 251  | -0.5                                              | 2.9                                        |
+| Norway        | 45 836             | 43 406  | 44 968  | 45 404  | -0.9                                              | 4.6                                        |
+| Slovenia      | 21 903             | 17 612  | 19 449  | 20 508  | -6.4                                              | 16.4                                       |
+| Sweden        | 84 036             | 77 813  | 80 119  | 81 823  | -2.6                                              | 5.2                                        |
+
+#### **Mobility in France after the Covid‑19 pandemic**
+
+In France, there is no recent national survey on mobility behaviour. However, some data are available for major cities. Research lead by LVMT Laboratory (2022) shows that the pandemic increased the attractiveness of cycling and consolidated existing cyling practices due to the construction of new bike lanes. Telework reduced traffic volumes, especially for passenger cars and public transportation. The decrease is more pronounced on Fridays, Mondays and Wednesdays. The impact of telework on car use and average distance remains unclear. However, some studies show that telework is associated with more trips around home on teleworking days but does not necessarily reduce car use.
+
+According to a survey carried out by Île de France Mobilité (2022), new mobility behaviours can be identified in the Île‑de‑France region. In 2022, for all modes of transport combined, Paris region residents made 10% fewer journeys than in 2018. Teleworking and videoconferencing have developed strongly, reducing the number of home‑to‑work journeys, as well as journeys for meetings or lunch breaks". In addition, while road traffic has generally returned to pre‑Covid levels, this is not the case for public transport use, which reached a plateau in 2022, with passenger numbers at between 80% and 85% of pre‑Covid levels. This is also confirmed by public transport operators.
+
+Another research project has been launched, led by LVMT Laboratory (Dablanc et al., 2022a, 2022b), looking at accidental journeys made by delivery drivers on major platforms such as Ubereats and Deliveroo. The data are based on annual surveys conducted by the Logistics City Chair in Paris and a survey in Nantes in 2021, involving fieldwork with 600 delivery drivers. The results reveal a high crash rate reported by drivers themselves. Delivery personnel report 26‑29% of crashes on bicycles or scooters, depending on the year, half of which require a trip to the emergency room and 33% of which require medical attention.
+
+### **Road deaths in 2022**
+
+After the shock of the Covid-19 pandemic in 2020 and 2021, when mobility was restricted everywhere and road deaths showed a general decrease, 2022 was a "normal" year. There were no particular restrictions on mobility in IRTAD countries.
+
+To avoid biased results, this report compares road deaths in 2022 to the average for 2017‑19 for short‑term comparisons.
+
+On average, for the 35 IRTAD countries with validated data, road deaths increased by 3.2% in 2022 compared to the average for 2017‑19.
+
+However, the United States, the most populous country in the analysis, significantly impacts the result. When US data are not included, in 2022, road deaths decreased by 6.4% compared to the average for 2017‑19.
+
+**Evolution by country**
+
+The picture is quite varied when looking at the data for each country. Among the 35 IRTAD countries, 23 countries recorded a reduction in road deaths in 2022, compared to the average for 2017‑19. In 15 countries, the decline was greater than 10% (see Table 3).
+
+The strongest decreases were in Lithuania (-34.4%), Poland (-33.9%), followed by Iceland (-30.8%), Korea (-27.5%), Japan (-22.9%), Finland (-17.5%), Denmark (-15.4%), Sweden (-14.7%), Czechia (-14.5%), Argentina (-14.4%), Slovenia (-14.1%), Hungary (-13.7%), Belgium (-12.8%), Germany (-12%) and Austria (-10.4%).
+
+Five countries recorded an increase in road fatalities of more than 10% in 2022 compared to the average for 2017‑19: Luxembourg (28.6%), Colombia (22.2%), the United States (16%), the Netherlands (14.4%) and Switzerland (11.1%).
+
+In the Netherlands, the number of road deaths in 2022 (745) was the highest in more than ten years, while in Switzerland the number of road deaths in 2022 was higher than in any year since 2015.
+
+In the United States, even if there was an increase of 16% compared to the average for 2017‑19, the number of road deaths slightly decreased in 2022 when compared to 2021.
+
+If the US data are excluded, overall deaths in IRTAD member countries fell by 6.4%.
+
+Five countries recorded an increase of more than 10% in 2022.
+
+### **2022 Road fatality data compared to the 2017-19 average**
+
+| Country                               | 2022 road deaths | Data status | 2017-19 road deaths | % change |  |  |  |  |
+|---------------------------------------|------------------|-------------|---------------------|----------|--|--|--|--|
+| Countries with validated data         |                  |             |                     |          |  |  |  |  |
+| Argentina                             | 4 567            | provisional | 5 334               | -14.4    |  |  |  |  |
+| Australia                             | 1 188            | provisional | 1 182               | 0.5      |  |  |  |  |
+| Austria                               | 370              | final       | 413                 | -10.4    |  |  |  |  |
+| Belgium                               | 540              | final       | 619                 | -12.8    |  |  |  |  |
+| Canada                                | 1 934            | provisional | 1 852               | 4.4      |  |  |  |  |
+| Chile                                 | 2 137            | final       | 1 951               | 9.5      |  |  |  |  |
+| Colombia                              | 8 030            | final       | 6 570               | 22.2     |  |  |  |  |
+| Costa Rica                            | 786              | provisional | 820                 | -4.1     |  |  |  |  |
+| Czechia                               | 527              | final       | 617                 | -14.6    |  |  |  |  |
+| Denmark                               | 154              | final       | 182                 | -15.4    |  |  |  |  |
+| Finland                               | 189              | provisional | 229                 | -17.5    |  |  |  |  |
+| France                                | 3 267            | final       | 3 313               | -1.4     |  |  |  |  |
+| Germany                               | 2 788            | final       | 3 167               | -12.0    |  |  |  |  |
+| Greece                                | 641              | provisional | 706                 | -9.2     |  |  |  |  |
+| Hungary                               | 535              | final       | 620                 | -13.7    |  |  |  |  |
+| Iceland                               | 9                | final       | 13                  | -30.8    |  |  |  |  |
+| Ireland                               | 155              | provisional | 143                 | 8.4      |  |  |  |  |
+| Israel                                | 351              | final       | 345                 | 1.7      |  |  |  |  |
+| Italy                                 | 3 159            | final       | 3 295               | -4.1     |  |  |  |  |
+| Japan                                 | 3 216            | final       | 4 172               | -22.9    |  |  |  |  |
+| Korea                                 | 2 735            | final       | 3 772               | -27.5    |  |  |  |  |
+| Lithuania                             | 120              | final       | 183                 | -34.4    |  |  |  |  |
+| Luxembourg                            | 36               | final       | 28                  | 28.6     |  |  |  |  |
+| Netherlands                           | 745              | final       | 651                 | 14.4     |  |  |  |  |
+| New Zealand                           | 375              | provisional | 369                 | 1.6      |  |  |  |  |
+| Norway                                | 116              | final       | 107                 | 8.4      |  |  |  |  |
+| Poland                                | 1 896            | final       | 2 867               | -33.9    |  |  |  |  |
+| Portugal                              | 618              | final       | 663                 | -6.8     |  |  |  |  |
+| Serbia                                | 553              | final       | 554                 | -0.2     |  |  |  |  |
+| Slovenia                              | 85               | final       | 99                  | -14.1    |  |  |  |  |
+| Spain                                 | 1 746            | final       | 1 797               | -2.8     |  |  |  |  |
+| Sweden                                | 227              | final       | 266                 | -14.7    |  |  |  |  |
+| Switzerland                           | 241              | final       | 217                 | 11.1     |  |  |  |  |
+| United Kingdom                        | 1 766            | final       | 1 834               | -3.7     |  |  |  |  |
+| United States                         | 42 795           | provisional | 36 888              | 16.0     |  |  |  |  |
+| Observers and accession countries (a) |                  |             |                     |          |  |  |  |  |
+| Mexico                                | 15 979           | provisional | 15 371              | 4.0      |  |  |  |  |
+| Morocco                               | 3 499            | final       | 3 695               | -5.3     |  |  |  |  |
+| Uruguay                               | 431              | final       | 473                 | -8.9     |  |  |  |  |
+
+(a) Data as provided by the countries and not validated by IRTAD.
+
+### **Short‑term evolution by user group**
+
+When looking at data by road user group, data are available for 32 countries (see Figure 1). Australia, Greece, and the United States have not yet published detailed 2022 data.
+
+For the countries analysed, road fatalities decreased in 2022 compared to the average 2017‑19 for all road user types except for powered two‑wheelers (PTWs), which increased by 6.7%. Pedestrian fatalities recorded the biggest decrease (‑17.7%), followed by passenger car occupants (-8%) and cyclists (-3.3%).
+
+The increase in the number of PTW users was due mainly to the very sharp increase in Colombia (+41.1% in 2022 compared to the average for 2017‑19). When excluding Colombia, the number of PTW users killed decreased by 6.9% in 2022 compared to the average for 2017‑19.
+
+The safety of PTW users is a growing issue in Colombia as in many Latin American countries. In 2022, over 800 000 new motorcycles were registered in the country, representing the highest number of registrations of new motorcycles over the last decade (see Box 2).
+
+Road deaths decreased for all user groups in 2022, except for users of powered-two wheelers.
+
+**Evolution in road deaths by user category, 2022 compared to average for 2017-19**
+
+![](_page_15_Figure_7.jpeg)
+
+Note: Data include Argentina, Austria, Belgium, Canada, Chile, Colombia, Costa Rica, Czechia, Denmark, Finland, France, Germany, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Lithuania, Luxembourg, Netherlands, New Zealand, Norway, Poland, Portugal, Serbia, Slovenia, Spain, Sweden, Switzerland, United Kingdom.
+
+### **Motorcycle use in Latin America and the Caribbean**
+
+In Latin American and Caribbean countries, the number of motorcycle users killed exceeds the world average. According to the International Development Bank (IDB), In some countries, such as Colombia, the Dominican Republic and Uruguay, motorcycles represent more than half of road traffic (IDB, 2022). In these countries, motorcycles accounted for 73%, 56%, and 51% of the vehicle fleet, respectively (IDB, 2022).
+
+Several factors contribute to the increased use of motorcycles in the region. First, in cities where the supply of public transport does not satisfy the demand, motorcycles are considered a valid alternative (Rodríguez et al., 2015). Other contributing factors include rising income levels, lower manufacturing costs, access to financing facilities, tax incentives, ease of maintenance and lower fuel consumption. Additionally, motorcycles provide agility in congested traffic conditions, which are common in large Latin American cities.
+
+There is also a growing trend in using motorcycles as a means of work. The demand for courier, cab or delivery services aboard motorcycles offers lower fares and shorter travel times compared to other modes of transportation. People who use their motorcycles for work tend to have low education and income levels, which is a barrier to accessing employment with better working conditions. The commercial use of motorcycles should be formalised under adequate labour regulations, thus improving the quality‑of‑life standards for people who provide a service without decent conditions.
+
+The IDB report provides a set of guidelines and best practices to enhance road safety for motorcycle users in the region that should be implemented across three key dimensions: 1) drivers and passengers, 2) motorcycle safety and 3) infrastructure and operation.
+
+First, regarding the driver and passenger, the IDB recommends governments should establish
+
+minimum age requirements for motorcycle operation, considering engine power and riding proficiency, and introduce mandatory training programmes for individuals applying for a motorcycle license, starting with a basic category, and progressively advancing based on years of experience. Furthermore, personal safety elements for both the driver and passenger must be enforced.
+
+Second, concerning motorcycles, automatic braking systems (ABS) and appropriate day and night lights should be required and enforced. In addition, compulsory vehicle safety inspections and mandatory insurance coverage are essential to enhance safety.
+
+Third, regarding infrastructure and operation, it is essential to implement speed management measures and the installation of side barriers adapted to accommodate motorcycles.
+
+Source: Inter‑American Development Bank (2022).
+
+While cyclist fatalities in 2022 decreased by 3.3% compared to the average for 2017‑19, there are growing concerns regarding the safety of e‑bikes. Their use is becoming more and more common in the IRTAD countries. This results in increased trips performed by e‑bikes and consequently increased share in the fatalities among cyclists, generating new safety challenges.
+
+Data from the ten countries which reported these data for 2022 confirm this trend (see Table 4). In Israel and Switzerland, more than half of the cyclists killed in road crashes were using an e‑bike. The percentage was quite high also for Germany (44%), Denmark (39%) and Belgium (38%).
+
+This trend is growing. For example, in Switzerland in 2017 only 19% of cyclists killed were riding e‑bikes. This phenomenon particularly affected older people, attracted by the possibility of continuing to do some physical exercise. For example, in Japan in 2022 60% of e‑bikers killed were over 75, while the equivalent figures were around 40% in Belgium and Germany.
+
+Few countries record data concerning new micro‑mobility vehicles, such as e‑scooters. In the countries where these data are collected, there has been an increase in road fatalities in recent years, due mainly to the increasing use. For example, in France, the number of people killed while using these vehicles tripled between 2019 and 2022. However, they still represent a small share of total road fatalities.
+
+Recently, some countries have made efforts to collect road crash data about new mobility modes. But the same cannot be said for exposure (I.e. how many kilometres cyclists and e‑scooter users travel). Only the Netherlands has national data on cycling, based on annual ad hoc surveys. In other countries, data can be obtained at the city level from self‑service bike or scooter operators.
+
+However, even at the local level, there is little data available on user trips outside self‑service fleets. Initial work has been carried out using mobile phone data to measure trips using new mobility modes but at this stage, it has not been shared or validated. This is a major knowledge challenge for the coming years. The ITF Statistics Group has set up a task force on emerging mobility patterns data, including walking and cycling. IRTAD is a member of this group, which is due to report in 2024.
+
+There are growing concerns about e-bikes.
+
+**Percentage share of e-bike users in cyclist fatalities**
+
+| Country     | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 |
+|-------------|------|------|------|------|------|------|
+| Belgium     | 28   | 23   | 27   | 35   | 47   | 38   |
+| Denmark     |      | 21   | 30   | 30   | 12   | 39   |
+| France      |      |      | 8    | 9    | 11   | 18   |
+| Germany     | 18   | 20   | 27   | 33   | 35   | 44   |
+| Israel      |      |      | 47   | 81   | 52   | 55   |
+| Italy       |      |      |      |      | 6    | 10   |
+| Japan       | 7    | 9    | 12   | 12   | 13   | 15   |
+| Netherlands | 28   | 25   | 32   | 32   | 39   | 34   |
+| Portugal    | 4    | 0    |      |      |      | 26   |
+| Slovenia    | 25   | 0    | 0    | 0    | 0    | 13   |
+| Switzerland | 19   | 29   | 38   | 31   | 41   | 55   |
+
+### **Short-term evolution by age group**
+
+When looking at data by age group, data are available for 30 countries (see Figure 2). Australia, Canada, Costa Rica, Greece, and the United States do not yet have detailed 2022 data.
+
+In 2022, road deaths decreased for all age groups compared to the 2017‑19 average. The biggest reductions were for the youngest generation. The decrease among children under 14 amounted to 12.9%, while for teenagers between 15 and 17 years old, the decrease was 16.4%.
+
+In contrast with previous years, the senior population recorded an improvement in road safety. In 2022, road deaths decreased by 5.2% for the 65‑74 age group and 11.6% among people over 75. People aged between 21 and 24 derived fewer benefits from better road safety. Road deaths for this group decreased by only 1.7%.
+
+Road deaths in 2022 decreased for all age groups.
+
+**Evolution in road deaths by age group, 2022 compared to average for 2017-19**
+
+![](_page_20_Figure_1.jpeg)
+
+Note: Data include Argentina, Austria, Belgium, Chile, Colombia, Czechia, Denmark, Finland, France, Germany, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Lithuania, Luxembourg, Netherlands, New Zealand, Norway, Poland, Portugal, Serbia, Slovenia, Spain, Sweden, Switzerland, United Kingdom.
+
+Historically, the 18‑20 and 21‑24 age groups were the most at risk in traffic. In recent years, in many IRTAD countries, seniors aged 75 and over have become more and more at risk in traffic. In 2022, in almost two‑thirds of the countries with available data, the mortality rates of people aged 75 and over were higher than those of people aged 18‑20 or 21‑24 (see Figure 3).
+
+The are several reasons for this shift. First of all, the population is ageing in most of the developed countries. At the same time, the population is more mobile than before since the average health conditions are better and new transport modes, such as e‑bikes, suit the elderly population.
+
+Second, in the last few years, successful measures have been taken to improve the safety of young people. In addition, younger generations tend to drive less and later.
+
+While fewer seniors are dying in road crashes, they remain the most‑at‑risk age group.
+
+#### **Mortality rate by age group, 2022**
+
+Age group Total
+
+![](_page_21_Figure_6.jpeg)
+
+![](_page_21_Figure_7.jpeg)
+
+![](_page_21_Figure_8.jpeg)
+
+![](_page_21_Figure_9.jpeg)
+
+![](_page_22_Figure_0.jpeg)
+
+![](_page_22_Figure_1.jpeg)
+
+![](_page_23_Figure_0.jpeg)
+
+![](_page_23_Figure_1.jpeg)
+
+![](_page_23_Figure_2.jpeg)
+
+![](_page_23_Figure_3.jpeg)
+
+![](_page_23_Figure_4.jpeg)
+
+![](_page_23_Figure_5.jpeg)
+
+![](_page_23_Figure_6.jpeg)
+
+![](_page_23_Figure_7.jpeg)
+
+![](_page_23_Figure_8.jpeg)
+
+![](_page_24_Figure_0.jpeg)
+
+![](_page_24_Figure_1.jpeg)
+
+![](_page_24_Figure_2.jpeg)
+
+![](_page_24_Figure_3.jpeg)
+
+![](_page_24_Figure_4.jpeg)
+
+![](_page_24_Figure_5.jpeg)
+
+![](_page_24_Figure_6.jpeg)
+
+![](_page_24_Figure_7.jpeg)
+
+![](_page_24_Figure_8.jpeg)
+
+### **Short-term evolution by road type**
+
+Data disaggregated by road type are available for 25 countries in 2022 (see Figure 4). Rural roads are the deadliest roads in almost all countries. In 17 countries, more than half of the road deaths occurred on rural roads. In Finland, Ireland and New Zealand, two‑thirds of road deaths occurred in this type of road. Only in Korea, the Netherlands, Japan, and Portugal are urban roads deadlier than other road types.
+
+The reasons for the dangerousness of rural roads relate mainly to road infrastructure and inappropriate speed. Rural roads often lack physical separation of lanes, have numerous intersections and are sometimes poorly maintained. In addition, drivers tend to speed on rural roads, mainly because of a lack of enforcement.
+
+Rural roads remain the deadliest road type.
+
+### **Road deaths by road type, 2022**
+
+![](_page_25_Figure_6.jpeg)
+
+In 2022, for the 25 countries with available data, road deaths decreased by 13.5% compared to the average 2017‑19 (see Figure 5). The biggest decrease was in the number of people killed on urban roads (‑15.5%), followed by rural roads (‑7.5%) and motorways (‑6.2%).
+
+**Evolution in road deaths by road type, 2022 compared to average for 2017-19** 0% -2% -4% -6% -8% -10% -12% -14% -16% -18% Urban roads Rural roads Motorways All road types **-15.5% -7.5% -6.2% -13.5%**
+
+Note: Data include Argentina, Austria, Belgium, Czechia, Denmark, Finland, France, Germany, Great Britain, Hungary, Ireland, Italy, Japan, Korea, Lithuania, Luxembourg, Netherlands, New Zealand, Poland, Portugal, Serbia, Slovenia, Spain, Sweden, Switzerland.
+
+## **Mortality rates and fatality risks in 2022**
+
+Three common indicators are used to measure road safety performance and compare safety levels across countries: 1) the number of road deaths per population, 2) the number of road deaths per motorised vehicle, and 3) the number of road deaths per distance travelled (see Box 3). This section explores the 2022 data for the first two indicators and the 2021 data for the latter.
+
+In 2022, the mortality rate ranged from 2.1 to 15.5 fatalities per 100 000 inhabitants (see Figure 6). Norway recorded the lowest mortality rate, with 2.1 fatalities per 100 000 inhabitants. Norway also registered the lowest mortality rate from road crashes in 2021. A total of 22 IRTAD countries had a mortality rate between 3 and 9 in 2022. Four countries had a mortality rate higher than 10 fatalities per 100 000 inhabitants: Chile (10.8), the United States (12.8), Costa Rica (15.2), and Colombia (15.5).
+
+Seven countries recorded per capita mortality rate below 3 in 2022.
+
+### **Measuring risk and comparing countries**
+
+Three common indicators measure road safety performance and compare safety levels across countries. Each has pros and cons; in all cases, interpret country comparisons with great care, especially between countries with different levels of motorisation.
+
+First, the number of **fatalities per head of population** measures the mortality rate. The number of inhabitants (per 100 000 or million) is the most often‑used denominator as this figure is readily available in most countries. This rate expresses the average citizen's overall risk of being killed in traffic. It is comparable to other causes of death (e.g. coronary diseases or HIV/AIDS). It is also useful when comparing risk in countries with similar levels of motorisation. It is not very
+
+meaningful to compare safety levels between highly motorised countries and countries where the level of motorisation is low.
+
+Second, the number of **fatalities per number of registered motorised vehicles** is an alternative to measuring fatalities per distance travelled, although it does not consider actual traffic volume. It is only useful for comparing the safety performance of countries with similar traffic and vehicle‑use characteristics. It also requires reliable statistics on the number of vehicles. In some countries, scrapped vehicles are not systematically removed from registration databases, undermining the accuracy of this indicator. Equally, this indicator does not consider non‑motorised vehicles (e.g. bicycles), which represent a large part of the
+
+vehicle fleet (and fatality figures) in some countries. This indicator is usually expressed as the number of fatalities per 10 000 registered motorised vehicles.
+
+Third, the number of **fatalities per distance travelled** by motorised vehicles measures fatality risk. This indicator describes the safety quality of road traffic. Theoretically, it is the best indicator to assess the level of risk of the road network. However, it does not take into account non‑motorised vehicles (e.g. bicycles). In some countries, non‑motorised vehicles represent a large part of the vehicle fleet and of road fatalities. Furthermore, only a limited number of countries collect data on distance travelled. Fatality risk is usually expressed in road deaths per billion vehicle‑kilometres.
+
+Other six countries recorded less than 3 fatalities from road crashes per 100 000 inhabitants in 2022: Sweden (2.2), Iceland (2.4), Japan, Denmark, and the United Kingdom (2.6), and Switzerland (2.8).
+
+In the case of Switzerland, while it recorded an increase in road fatalities of 11.1% in 2022 compared to the average 2017‑19, the country nevertheless registered a relatively low mortality rate. It is also worth noting that the number of road deaths in 2019 in Switzerland was extremely low.
+
+![](_page_28_Figure_2.jpeg)
+
+Note: (a) Real data (actual numbers instead of reported numbers by the police).
+
+Fatality rates, measured against the number of motorised vehicles, ranged from 0.2 to 4.5 deaths per 10 000 motorised vehicles (see Figure 7) in 2022. Ten countries registered a mortality rate of less than 0.5: Iceland, Norway, Sweden, Japan, Switzerland, Finland, United Kingdom, Denmark, Spain, and Germany.
+
+The fatality risk was highest in Chile and Colombia, with a rate of 3.5 and 4.5 fatalities per 10 000 motorised vehicles, respectively.
+
+**Road fatalities per 10 000 registered vehicles, 2022**
+
+Ten countries recorded a mortality rate per registered vehicle below 0.5.
+
+> New Zealand Hungary (b) Argentina
+
+![](_page_29_Figure_3.jpeg)
+
+Australia Netherlands (a) Lithuania Czech Republic Luxembourg Belgium (b) Greece (b) Canada Portugal (b) Israel
+
+Note: (a) Real data (actual numbers instead of reported numbers by the police). (b) Mopeds are not included in the registered vehicles.
+
+Iceland Norway Sweden Japan Switzerland Finland United Kingdom Denmark (b) Spain Germany (b) Austria Slovenia Ireland Poland
+
+Colombia
+
+The fatality risk calculated by distance travelled is available for 22 countries in 2021 (but only 11 countries available in 2022). In 2021, the fatality risk ranged from 1.8 to 9.9 fatalities per billion vkm (see Figure 9).
+
+Four countries reported less than 3 deaths per billion vkm: Norway (1.8), Iceland (2.3), Denmark (2.4), and Sweden (2.6). Three countries registered more than 8 deaths per billion vkm: Korea (8.2), the United States (8.5) and Czechia (9.9).
+
+Four countries recorded a mortality rate per distance travelled below 3.
+
+### **Road fatalities per billion vehicle-kilometres, 2021**
+
+![](_page_30_Figure_5.jpeg)
+
+Note: (a) Real data (actual numbers instead of reported numbers by the police). (b) Data only for Great Britain.
+
+This section discusses the longer‑term evolution of specific road safety indicators for the period 2012‑22. This section discusses two broad sets of data: data on the total number of road deaths; and data on road deaths disaggregated by user group, age group and road type. The IRTAD database also covers serious injuries; details are provided in the accompanying country profiles.
+
+## **Evolution in the number of road deaths, 2012‑22**
+
+Between 2012 and 2022, road deaths increased by 1.5% in the 35 countries with validated data.
+
+When the United States's data are not included, road deaths decreased by 14.4%. This decrease needs to be accelerated to meet the target under the second Decade of Action for Road Safety 2021‑30 (WHO, 2021).
+
+Figure 9 shows the evolution in the number of road deaths between 2012 and 2022, with and without US data.
+
+In 2021, road deaths increased compared to 2020 but stayed below the pre‑Covid 19 level. In 2022, the total number of road deaths increased a further but stayed below the pre‑Covid 19 level.
+
+If US data are excluded, overall road deaths in IRTAD countries fell by 14%.
+
+#### **Aggregate evolution in the number of road deaths in IRTAD countries, 2012-2022**
+
+![](_page_32_Figure_2.jpeg)
+
+![](_page_32_Figure_3.jpeg)
+
+### **Number of road deaths (excluding the US)**
+
+![](_page_32_Figure_5.jpeg)
+
+Between 2012 and 2022, road deaths decreased in 27 of the 35 IRTAD countries (see Figure 10 and Table 5). Fatalities decreased the most in Lithuania (‑60.1%), Korea (‑49.2%) and Poland (‑46.9%). Five other countries recorded a reduction of more than 30% in 2022 compared to 2012: Japan (‑38.9%), Greece (‑35.1%), Belgium (‑34.7%), Slovenia (‑34.6%), and Austria (‑30.3%).
+
+Road deaths increased in 8 IRTAD countries and by more than 20% in five countries: Colombia (50.9%), the United States (26.7%), New Zealand (21.8%), Israel (21%) and Costa Rica (20%).
+
+Lithuania, Korea and Poland have achieved large drops in road fatalities since 2012.
+
+![](_page_34_Figure_0.jpeg)
+
+Note: (a) Real data (actual numbers instead of reported numbers by the police).
+
+#### **Road fatality trends, 2012-22**
+
+| Country                               |        |        |        |        |        |        |        |
+|---------------------------------------|--------|--------|--------|--------|--------|--------|--------|
+|                                       | 2012   | 2013   | 2014   | 2015   | 2016   | 2017   | 2018   |
+| Countries with validated data         |        |        |        |        |        |        |        |
+| Argentina                             | 5 074  | 5 209  | 5 279  |        | 5 550  | 5 611  | 5 493  |
+| Australia                             | 1 299  | 1 185  | 1 151  | 1 205  | 1 295  | 1 223  | 1 135  |
+| Austria                               | 531    | 455    | 430    | 479    | 432    | 414    | 409    |
+| Belgium                               | 827    | 764    | 745    | 762    | 670    | 609    | 604    |
+| Canada                                | 2 075  | 1 951  | 1 841  | 1 887  | 1 900  | 1 861  | 1 939  |
+| Chile                                 | 1 979  | 2 103  | 2 116  | 2 136  | 2 178  | 1 925  | 1 955  |
+| Colombia                              | 5 320  | 5 757  | 6 118  | 6 406  | 6 936  | 6 505  | 6 629  |
+| Costa Rica                            | 655    | 625    | 662    |        |        | 862    | 811    |
+| Czechia                               | 742    | 654    | 688    | 734    | 611    | 577    | 658    |
+| Denmark                               | 167    | 191    | 182    | 178    | 211    | 175    | 171    |
+| Finland                               | 255    | 258    | 229    | 270    | 258    | 238    | 239    |
+| France                                | 3 653  | 3 268  | 3 384  | 3 461  | 3 477  | 3 448  | 3 248  |
+| Germany                               | 3 600  | 3 339  | 3 377  | 3 459  | 3 206  | 3 180  | 3 275  |
+| Greece                                | 988    | 879    | 795    | 793    | 824    | 731    | 700    |
+| Hungary                               | 605    | 591    | 626    | 644    | 607    | 625    | 633    |
+| Iceland                               | 9      | 15     | 4      | 16     | 18     | 16     | 18     |
+| Ireland                               | 163    | 188    | 192    | 162    | 182    | 154    | 134    |
+| Israel                                | 290    | 309    | 319    | 356    | 377    | 364    | 316    |
+| Italy                                 | 3 753  | 3 401  | 3 381  | 3 428  | 3 283  | 3 378  | 3 334  |
+| Japan                                 | 5 261  | 5 165  | 4 838  | 4 885  | 4 698  | 4 431  | 4 166  |
+| Korea                                 | 5 392  | 5 092  | 4 762  | 4 621  | 4 292  | 4 185  | 3 781  |
+| Lithuania                             | 301    | 258    | 267    | 239    | 188    | 191    | 173    |
+| Luxembourg                            | 34     | 45     | 35     | 36     | 32     | 25     | 36     |
+| Netherlands (b)                       | 650    | 570    | 570    | 621    | 629    | 613    | 678    |
+| New Zealand                           | 308    | 252    | 292    | 317    | 326    | 377    | 379    |
+| Norway                                | 145    | 187    | 147    | 117    | 135    | 106    | 108    |
+|                                       |        |        |        |        |        |        |        |
+| Poland                                | 3 571  | 3 357  | 3 202  | 2 938  | 3 026  | 2 831  | 2 862  |
+| Portugal                              | 718    | 637    | 638    | 593    | 563    | 602    | 700    |
+| Serbia                                | 688    | 650    | 536    | 599    | 607    | 579    | 548    |
+| Slovenia                              | 130    | 125    | 108    | 120    | 130    | 104    | 91     |
+| Spain                                 | 1 903  | 1 680  | 1 688  | 1 689  | 1 810  | 1 830  | 1 806  |
+| Sweden                                | 285    | 260    | 270    | 259    | 270    | 252    | 324    |
+| Switzerland                           | 339    | 269    | 243    | 253    | 216    | 230    | 233    |
+| United Kingdom                        | 1 802  | 1 770  | 1 854  | 1 804  | 1 860  | 1 856  | 1 839  |
+| United States                         | 33 782 | 32 893 | 32 744 | 35 484 | 37 806 | 37 473 | 36 835 |
+| Observers and accession countries (a) |        |        |        |        |        |        |        |
+| Mexico                                | 17 102 | 15 853 | 15 886 | 16 039 | 16 185 | 15 866 | 15 574 |
+| Morocco                               | 4 167  | 3 832  | 3 489  | 3 776  | 3 785  | 3 726  | 3 736  |
+| Uruguay                               | 510    | 567    | 538    | 506    | 446    | 470    | 528    |
+|                                       |        |        |        |        |        |        |        |
+
+<sup>(</sup>a) Data as provided by the countries and not validated by IRTAD. (b) Real data (actual numbers instead of reported numbers by the police).
+
+|                 |                 |                 |                 | 2022 % change from |               | Annual average change |
+|-----------------|-----------------|-----------------|-----------------|--------------------|---------------|-----------------------|
+| 2019            | 2020            | 2021            | 2022            | av. 2017-19        | 2012          | 2012-22               |
+|                 |                 |                 |                 |                    |               |                       |
+| 4 898           | 3 513           | 4 481           | 4 567           | -14.4              | -10.0         | -1.0                  |
+| 1 187           | 1 097           | 1 116           | 1 188           | 0.5                | -8.5          | -0.9                  |
+| 416             | 344             | 362             | 370             | -10.4              | -30.3         | -3.5                  |
+| 644             | 499             | 516             | 540             | -12.8              | -34.7         | -4.2                  |
+| 1 756           | 1 746           | 1 768           | 1 934           | 4.4                | -6.8          | -0.7                  |
+| 1 973           | 1 794           | 2 052           | 2 137           | 9.5                | 8.0           | 0.8                   |
+| 6 577           | 5 447           | 7 238           | 8 030           | 22.2               | 50.9          | 4.2                   |
+| 787             | 570             | 707             | 786             | -4.1               | 20.0          | 1.8                   |
+| 617             | 517             | 531             | 527             | -14.6              | -29.0         | -3.4                  |
+| 199             | 163             | 130             | 154             | -15.2              | -7.8          | -0.8                  |
+| 211             | 223             | 225             | 189             | -17.6              | -25.9         | -3.0                  |
+| 3 244           | 2 541           | 2 944           | 3 267           | -1.4               | -10.6         | -1.1                  |
+| 3 046           | 2 719           | 2 562           | 2 788           | -12.0              | -22.6         | -2.5                  |
+| 688             | 584             | 624             | 641             | -9.2               | -35.1         | -4.2                  |
+| 602             | 460             | 544             | 535             | -13.7              | -11.6         | -1.2                  |
+| 6               | 8               | 9               | 9               | -32.5              | 0.0           | 0.0                   |
+| 140             | 146             | 136             | 155             | 8.6                | -4.9          | -0.5                  |
+| 355             | 305             | 364             | 351             | 1.7                | 21.0          | 1.9                   |
+| 3 173           | 2 395           | 2 875           | 3 159           | -4.1               | -15.8         | -1.7                  |
+| 3 920           | 3 416           | 3 205           | 3 216           | -22.9              | -38.9         | -4.8                  |
+| 3 349           | 3 081           | 2 916           | 2 735           | -27.5              | -49.3         | -6.6                  |
+| 186             | 175             | 148             | 120             | -34.5              | -60.1         | -8.8                  |
+| 22              | 26              | 24              | 36              | 30.1               | 5.9           | 0.6                   |
+| 661             | 610             | 582             | 745             | 14.5               | 14.6          | 1.4                   |
+| 350             | 317             | 318             | 375             | 1.7                | 21.8          | 2.0                   |
+| 108             | 93              | 80              | 116             | 8.1                | -20.0         | -2.2                  |
+| 2 909           | 2 491           | 2 245           | 1 896           | -33.9              | -46.9         | -6.1                  |
+| 688             | 536             | 561             | 618             | -6.8               | -13.9         | -1.5                  |
+| 534             | 492             | 521             | 553             | -0.1               | -19.6         | -2.2                  |
+| 102             | 80              | 114             | 85              | -14.1              | -34.6         | -4.2                  |
+| 1 755           | 1 370           | 1 533           | 1 759           | -2.1               | -7.6          | -0.8                  |
+| 221             | 204             | 210             | 227             | -14.6              | -20.4         | -2.2                  |
+| 187             | 227             | 200             | 241             | 11.2               | -28.9         | -3.4                  |
+| 1 808           | 1 516           | 1 608           | 1 766           | -3.7               | -2.0          | -0.2                  |
+| 36 355          | 39 007          | 42 939          | 42 795          | 16.0               | 26.7          | 2.4                   |
+|                 |                 |                 |                 |                    |               |                       |
+| 14 673<br>3 622 | 13 630<br>3 005 | 14 715<br>3 685 | 15 979<br>3 499 | 4.0<br>-5.3        | -6.6<br>-16.0 | -0.7<br>-1.7          |
+| 422             | 391             | 434             | 431             | -8.9               | -15.5         | -1.7                  |
+|                 |                 |                 |                 |                    |               |                       |
+
+Figure 11 illustrates the trends in road fatalities in IRTAD countries since 2012. It includes expected values for 2020 and 2021 had the trend continued without the Covid‑19 pandemic.
+
+For most of the countries there is some evidence that 2020 and 2021 were exceptional years, with values much lower than the expected trend. For a more in‑depth analysis of the reasons for this variation at the country level, see the individual country reports on the ITF website.
+
+2022 data confirm that 2020 and 2021 were exceptional years.
+
+**Road deaths compared to the linear trend since 2012 (excluding 2020 and 2021)**
+
+![](_page_37_Figure_4.jpeg)
+
+Road deaths Trend
+
+2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
+
+![](_page_37_Figure_5.jpeg)
+
+![](_page_37_Figure_6.jpeg)
+
+![](_page_37_Figure_7.jpeg)
+
+![](_page_38_Figure_0.jpeg)
+
+![](_page_38_Figure_1.jpeg)
+
+![](_page_38_Figure_2.jpeg)
+
+![](_page_38_Figure_3.jpeg)
+
+![](_page_38_Figure_4.jpeg)
+
+![](_page_38_Figure_5.jpeg)
+
+![](_page_38_Figure_6.jpeg)
+
+![](_page_38_Figure_7.jpeg)
+
+![](_page_38_Figure_8.jpeg)
+
+![](_page_38_Figure_9.jpeg)
+
+### Road deaths Trend
+
+![](_page_39_Figure_1.jpeg)
+
+![](_page_39_Figure_2.jpeg)
+
+![](_page_39_Figure_3.jpeg)
+
+![](_page_39_Figure_4.jpeg)
+
+![](_page_39_Figure_5.jpeg)
+
+![](_page_39_Figure_6.jpeg)
+
+![](_page_39_Figure_7.jpeg)
+
+![](_page_39_Figure_8.jpeg)
+
+![](_page_40_Figure_0.jpeg)
+
+![](_page_40_Figure_2.jpeg)
+
+![](_page_40_Figure_3.jpeg)
+
+![](_page_40_Figure_4.jpeg)
+
+![](_page_40_Figure_5.jpeg)
+
+![](_page_40_Figure_6.jpeg)
+
+![](_page_40_Figure_7.jpeg)
+
+![](_page_40_Figure_8.jpeg)
+
+![](_page_40_Figure_9.jpeg)
+
+### Road deaths Trend
+
+![](_page_41_Figure_1.jpeg)
+
+![](_page_41_Figure_2.jpeg)
+
+![](_page_41_Figure_3.jpeg)
+
+![](_page_41_Figure_4.jpeg)
+
+![](_page_41_Figure_5.jpeg)
+
+![](_page_41_Figure_6.jpeg)
+
+![](_page_41_Figure_7.jpeg)
+
+When looking at the trends for 2012‑22, without including 2020 and 2021, the trend in road deaths is going upward in six countries: Colombia, Costa Rica, Israel, the Netherlands, New Zealand and the United States.
+
+In some countries, such as Chile, Spain and the United Kingdom, the trend is plateauing, and except for the two exceptional years in 2020 and 2021, the number of road deaths did not show a clear decrease.
+
+The trend is downward in the rest of the countries, even if few countries reached the target of halving road deaths in the last decade.
+
+In six countries the long‑term trend in road deaths is ascending.
+
+### **Road deaths by user group**
+
+Disaggregated data by user category are available for 32 IRTAD countries (see Figure 12). For these countries, in 2022, road fatalities decreased by 14.1% compared to 2012. When looking at the evolution by user category, passenger car occupants and pedestrians recorded reductions of 26.1% and 27.3%, respectively. Cyclist fatalities decreased by 8.3% in 2022 compared to 2012, while motorcyclist fatalities recorded a strong increase of 19.9%.
+
+In the last 10 years safety for pedestrians improved significantly.
+
+![](_page_43_Figure_4.jpeg)
+
+Note: Data include Argentina, Austria, Belgium, Canada, Chile, Colombia, Costa Rica, Czechia, Denmark, Finland, France, Germany, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Lithuania, Luxembourg, Netherlands, New Zealand, Norway, Poland, Portugal, Serbia, Slovenia, Spain, Sweden, Switzerland, United Kingdom.
+
+#### **Passenger car occupants**
+
+When considering all reporting countries, the number of passenger car occupants killed in road crashes decreased by 26.1% between 2012 and 2022. In four countries, such fatalities decreased by more than 50%: Korea (‑63.8%), Costa Rica (‑59.8%), Slovenia (‑56.5%) and Lithuania (‑52.8%) (see Figure 13). However, in five countries, road deaths among passenger car occupants increased. The biggest increase was recorded in Chile (+46.5%), where the safety risk for this group has not improved in recent years.
+
+![](_page_44_Figure_2.jpeg)
+
+Note: (a) Real data (actual numbers instead of reported numbers by the police).
+
+### **Pedestrians**
+
+The number of pedestrians killed in traffic decreased by 27.3% between 2012 and 2022 for the 32 countries with available data. Four countries recorded a reduction of more than 50%: Lithuania (‑71.3%), Norway (‑60.9%), Poland (‑60.2%) and Korea (‑54%) (Figure 14). Pedestrian fatalities increased in four countries, with Ireland recording the largest increase (48.3%), not taking in consideration Luxembourg for which small variations result in big growth rates.
+
+![](_page_45_Figure_2.jpeg)
+
+Note: (a) Real data (actual numbers instead of reported numbers by the police). Data from Iceland are not included in this figure, as percentage changes in small numbers distort trends.
+
+### **Cyclists**
+
+Overall, the number of cyclists killed in traffic decreased by 8.3% in 2022 compared to 2012. In New Zealand, however, fatalities among cyclists more than doubled, from 8 to 19 people killed.
+
+In Colombia, Argentina and Israel, cyclist fatalities increased by more than 50%. In France and the Netherlands, they increased by more than 40%.
+
+The situation is particularly worrying in the Netherlands, where cycling is common. In 2022, cyclists represented 40% of all road fatalities in this country.
+
+Fatalities among cyclists decreased in 19 out of 31 countries. Robust reductions were recorded in Lithuania (‑84.4%), Hungary (‑50.6%) and Norway (‑50%) (see Figure 15).
+
+![](_page_46_Figure_5.jpeg)
+
+Note: (a) Real data (actual numbers instead of reported numbers by the police). Data from Iceland and Luxembourg are not included in this figure, as percentage changes in small numbers distort trends.
+
+#### **Motorcyclists**
+
+Motorcyclists are the only category of road users which recorded an increase in fatalities between 2012 and 2022. Fatalities among motorcyclists more than doubled in Israel and Colombia.
+
+The data are very concerning, especially in Colombia, where the number of new registrations of motorcycles is constantly increasing. In two other Latin American countries, Costa Rica and Chile, motorcyclist fatalities increased by more than 50%.
+
+The reductions in road fatalities among motorcyclists were smaller than for the other categories. Five countries recorded a decrease of more than 30% between 2012 and 2022: Japan (‑44.7%), Poland (‑38.5%), Slovenia (‑31.8%), Serbia and Switzerland (‑30.8%) (see Figure 16).
+
+![](_page_47_Figure_4.jpeg)
+
+Note: (a) Real data (actual numbers instead of reported numbers by the police).
+
+### **Road deaths by age group**
+
+Disaggregated data by age group are available in 29 IRTAD counties. In 2022, road fatalities decreased by 15.5% compared to 2012 (see Figure 17). When looking at age cohorts, road fatalities decreased for all age groups, although at different paces.
+
+The biggest reductions were recorded for children and young people (‑36.8% and ‑29.7%, respectively). Road deaths decreased less for the senior population. People aged between 65 and 74 recorded a decrease of 10.1% between 2012 and 2022, while people over 75 recorded a decrease of 9.9% in road deaths.
+
+In the last ten 10 years, 36% less children died in road crashes.
+
+**Evolution in road deaths by age group, 2022 compared to 2012**
+
+![](_page_48_Figure_5.jpeg)
+
+Note: Data include Austria, Belgium, Chile, Colombia, Czechia, Denmark, Finland, France, Germany, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Lithuania, Luxembourg, Netherlands, New Zealand, Norway, Poland, Portugal, Serbia, Slovenia, Spain, Sweden, Switzerland, United Kingdom.
+
+### **Road deaths by road type**
+
+Data disaggregated by road type are available in 23 IRTAD countries. Overall, in 2022, road fatalities decreased by 27% compared to 2012 (see Figure 18). Deaths on urban and rural roads decreased by 27.8% and 27.7%, respectively. The data confirm that rural roads are still the least‑safe roads in absolute number. In 2022, road deaths on motorways decreased by 15.5% compared to 2012.
+
+In the last 10 years, deaths on rural roads have decreased, but they are still the most dangerous road type.
+
+### **Evolution in road deaths by road type, 2022 compared to 2012**
+
+![](_page_49_Figure_5.jpeg)
+
+Note: Data include Austria, Belgium, Czechia, Denmark, Finland, France, Germany, Great Britain, Hungary, Ireland, Italy, Japan, Korea, Lithuania, Luxembourg, Netherlands, New Zealand, Poland, Portugal, Serbia, Slovenia, Sweden, Switzerland.
+
+Several countries have recently released new road safety strategies in response to the Global Plan for the Decade of Action for Road Safety 2021‑30. The Annex presents the current road safety strategies and targets.
+
+27 countries have either adopted a new strategy for 2030 or are in the process of preparing one. The texts of the national road safety strategies of 29 of the 34 countries surveyed explicitly mention the Safe System approach or Vision Zero.
+
+The ITF has long promoted the Safe System approach as the best way to improve road safety. This approach is based on the ethical perspective that no one should be killed or seriously injured in road traffic. The Safe System approach includes four principles (ITF, 2016), to which a recent ITF Working Group added a fifth (ITF, 2022b). The Safe System approach is also at the core of the Global Plan.
+
+Most countries have adopted targets to reduce the number of road deaths. Among the 34 countries surveyed, 20 have a target aligned with the UN goal to reduce by 50% the number of road deaths by 2030.
+
+The baseline for this target varies. The year 2020 would have been the natural baseline for the 2021‑2030 decade. However, due to the Covid‑19 pandemic, most countries' road deaths in 2020 were exceptionally low. Using 2020 data as the baseline would therefore make the 2030 target even more challenging.
+
+Most IRTAD countries have chosen either 2019 or the average for 2017‑19 as a baseline for their 2030 targets. Several countries have set specific targets for specific road users (focusing, for example, on children, pedestrians or cyclists).
+
+Eight countries (Australia, Belgium, Finland, Ireland, the Netherlands, New Zealand, Norway, and Spain) have explicitly referred to the long‑term target of zero road deaths by 2050 in their strategies. In 2020 the European Union adopted its "Road Safety Policy Framework 2021‑30" (EC, 2020), which aims to halve the number of fatalities and serious injuries on European roads by 2030. This aim acts as a milestone on the path towards zero fatalities and serious injuries by 2050.
+
+Reducing the number of people seriously injured in road traffic is at the core of the Safe System approach. Among the 34 countries surveyed, 22 have also set a target to reduce the number of people seriously injured in road crashes. This represents significant progress compared to the period coinciding with the First Decade of Action for Road Safety (2011‑20), when very few countries addressed the issue of serious injuries.
+
+A total of 14 of the countries surveyed have adopted a target of halving the number of serious injuries by 2030. Four countries have a slightly less ambitious reduction target of 20‑40%. Four countries set their targets in absolute numbers.
+
+Azzato, F. et al (2022), "Motorcycles in Latin America: current and recommended best practices for the protection of its users", Inter‑American Development Bank, https://publications.iadb.org/en/motorcycles-latinamerica-current-and-recommended-best-practices-protection-its-users.
+
+Dablanc, L. et al. (2022a), « Etude 2022 sur les livreurs des plateformes à Paris et en petite couronne » [2022 study on platform delivery people in Paris], Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux, https://hal.science/hal-03903591.
+
+Dablanc, L. et al. (2022b), « Enquête sur les travailleurs nantais des plateformes de livraison instantanée » [Survey of Nantes workers on instant delivery platforms], Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux, https://hal.science/hal-03897757.
+
+EC (2020), "European Union Road Safety Policy Framework 2021‑30 – Next steps towards 'Vision Zero'", European Commission, Directorate‑General for Mobility and Transport, Brussels, https://data.europa.eu/doi/10.2832/391271.
+
+Institut Paris Région (2022), « Le mass transit à l'heure du télétravail et de la sobriété énergétique » [Mass transit in the era of teleworking and energy sobriety], Note rapide Mobilité, n° 958, 9 October 2022, https://www. institutparisregion.fr/fileadmin/NewEtudes/000pack3/Etude\_2844/NR\_958\_ web.pdf.
+
+IRTAD (2023), IRTAD Road Safety Database, OECD Stats, https://stats.oecd. org/Index.aspx?DataSetCode=IRTAD\_CASUAL\_BY\_AGE.
+
+ITF (2022a), Declaration from the 7th IRTAD Conference, "Better Road Safety Data for Better Safety Outcomes", Lyon, 27‑28 September 2022, www.itf-oecd. org/7th-irtad-conference-better-road-safety-data-better-safety-outcomes.
+
+ITF (2022b), The Safe System Approach in Action, ITF Research Report, OECD Publishing, Paris, https://doi.org/10.1787/ad5d82f0-en.
+
+ITF (2016), Zero Road Deaths and Serious Injuries: Leading a Paradigm Shift to a Safe System, OECD Publishing, Paris, https://doi. org/10.1787/9789282108055-en.
+
+Rodríguez, D.A., M. Santana and C.F. Pardo (2015), "La motocicleta en América Latina: caracterización de su uso e impactos en la movilidad en cinco ciudades de la región" [The motorcycle in Latin America: Characterisation of its use and impacts on mobility in five cities in the region], Development Bank of Latin America and the Caribbean, Bogotá, https://scioteca.caf.com/ handle/123456789/754.
+
+WHO (2021), Global Plan for the Decade of Action for Road Safety 2021‑2030, 20 October 2021, www.who.int/publications/m/item/global-plan-for-thedecade-of-action-for-road-safety-2021-2030.
+
+This section summarises the national data on prevailing speed limits for passenger cars, maximum authorised blood alcohol content levels, and legislation regarding seat belt and helmet use, as well as statistics on their usage. Detailed country profiles with data on deaths and injuries, crash risk exposure and road safety policies are available at www.itf-oecd.org/irtad.
+
+### **National speed limits on urban roads, rural roads and motorways, 2023 passenger vehicles (km/h)**
+
+| Country                   | Urban areas                                                                                                                             | Rural roads                                                                         | Motorways                                                                                                                                                    |
+|---------------------------|-----------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Argentina                 | 40‑60 (Buenos Aires City has a range of 20<br>to 70 km/h)                                                                               | 110                                                                                 | 120–130                                                                                                                                                      |
+| Australia                 | 50 (default)<br>60‑80 (arterial roads - increasing use of 40<br>km/h or lower limits in urban areas with<br>high pedestrian activities) | 100, 110                                                                            | 100 km/h default although<br>often set to 110 km/h<br>(130 km/h in the Northern<br>Territory)                                                                |
+| Austria                   | 50                                                                                                                                      | 100                                                                                 | 130                                                                                                                                                          |
+| Belgium                   | 30‑50<br>20 for the "living streets" regime                                                                                             | 70‑90                                                                               | 120                                                                                                                                                          |
+| Bosnia and<br>Herzegovina | 50                                                                                                                                      | 80, 100                                                                             | 130                                                                                                                                                          |
+| Cambodia                  | 30‑40 (motorcycles, tricycles)<br>40 (passenger cars, trucks)                                                                           | 60‑70 (motorcycles)<br>90                                                           | No motorways                                                                                                                                                 |
+| Canada                    | 40‑70                                                                                                                                   | 80–90                                                                               | 100–110                                                                                                                                                      |
+| Chile                     | 50 (maximum default limit but can vary<br>according to the type of road)<br>30 (school zones)                                           | 90 (rural buses, trucks and school<br>transport)<br>100 (cars and interurban buses) | 120 (maximum default<br>speed limit but can vary in<br>some sections of the road,<br>according to the type of road<br>can be lowered to 100)                 |
+| Colombia                  | 50                                                                                                                                      | 90                                                                                  | 120                                                                                                                                                          |
+| Costa Rica                | 40 (except when there is a 50 sign)                                                                                                     | 40‑100 (60 when there is no signs)                                                  | No motorways                                                                                                                                                 |
+| Czechia                   | 50                                                                                                                                      | 90                                                                                  | 130                                                                                                                                                          |
+| Denmark                   | 50 (sections with 30, 40 or 60)                                                                                                         | 80 (sections with 60, 70 or 90)                                                     | 130 (110 for a large part of<br>the motorway network)                                                                                                        |
+| Finland                   | 30‑60                                                                                                                                   | 80, 100                                                                             | 100, 120                                                                                                                                                     |
+| France                    | 50 by default<br>30 (some urban areas)<br>70 (exceptionally and under certain<br>conditions)                                            | 80 or 90 (90 on dedicated passing slots),<br>110 on dual carriageways               | 130 (110 in wet weather and<br>for novice drivers)                                                                                                           |
+| Germany                   | 50                                                                                                                                      | 100                                                                                 | None (130 recommended)                                                                                                                                       |
+| Greece                    | 50                                                                                                                                      | 90                                                                                  | 130                                                                                                                                                          |
+| Hungary                   | 50 (sections with 30, 40, 60 and 70)                                                                                                    | 90                                                                                  | 130 (110 on "motor roads")                                                                                                                                   |
+| Iceland                   | 50                                                                                                                                      | 90 (paved roads)<br>80 (gravel roads)                                               | n.a.                                                                                                                                                         |
+| Ireland                   | <=60 (can be 60 on arterial roads, 30 in<br>built up areas)                                                                             | 80, 100                                                                             | 120                                                                                                                                                          |
+| Israel                    | 30‑ 50<br>70 (arterial roads)                                                                                                           | 80, 90                                                                              | 100, 110, 120                                                                                                                                                |
+| Italy                     | 50                                                                                                                                      | 70‑90 (110 on some main dual<br>carriageways)                                       | 130 (110 km/h in wet weather,<br>100 for novice drivers.<br>Motorway operator may<br>increase speed limit up to<br>150 if stringent requirements<br>are met) |
+
+| Country        | Urban areas                                                                                                                                                                                                                 | Rural roads                                                                                                                                                    | Motorways                                                                                                              |
+|----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
+| Japan          | 40, 50, 60                                                                                                                                                                                                                  | 50, 60                                                                                                                                                         | 100                                                                                                                    |
+| Korea          | 50                                                                                                                                                                                                                          | 60‑80                                                                                                                                                          | 110 (100 in urban areas)                                                                                               |
+| Lithuania      | 50                                                                                                                                                                                                                          | 90 (70 on gravel roads and for novice<br>drivers)                                                                                                              | 120,130 (110 in winter, 90 for<br>novice drivers)                                                                      |
+| Luxembourg     | 50                                                                                                                                                                                                                          | 90                                                                                                                                                             | 130 (110 in wet weather)                                                                                               |
+| Mexico         | 10‑80 (20 in school zones, 30 on secondary<br>and tertiary streets, 50 on primary avenues<br>without controlled access, 80 in central<br>lanes of controlled access avenues and 50<br>on state highways within urban areas) | 60‑110 (60 on collector road, 80 on state<br>highways outside urban areas; 50 within<br>urban areas; 110 on roads and motorways<br>under federal jurisdiction) | 110 (110 for car, 95 for buses<br>and 80 for freight transport<br>on roads and highways under<br>federal jurisdiction) |
+| Moldova        | 50<br>30 in school zones, near hospitals, parks<br>and historical centre<br>5 in pedestrian areas                                                                                                                           | 90                                                                                                                                                             | No motorways                                                                                                           |
+| Morocco        | 60 (30 in residential area)                                                                                                                                                                                                 | 70, 80, 90, 100 (depending on vehicle type)                                                                                                                    | 120 (maximum speed, it<br>varies by vehicle type)                                                                      |
+| Netherlands    | 30‑50                                                                                                                                                                                                                       | 60‑80                                                                                                                                                          | 100 between 6:00 and 19:00<br>100, 120, or 130 between<br>19:00 and 06:00                                              |
+| New Zealand    | 50 (sections may have higher or lower<br>limits)                                                                                                                                                                            | 100 (specific sections may have lower<br>limits)                                                                                                               | 100 (specific sections may<br>have limits of 110)                                                                      |
+| Norway         | 50 (30 on residential streets)                                                                                                                                                                                              | 80 (70 on roads with high risk and 90 on<br>roads with very low traffic volumes)                                                                               | 90,100,110                                                                                                             |
+| Poland         | 50                                                                                                                                                                                                                          | 90, 100 (120 on expressways)                                                                                                                                   | 140 (120 on expresways)                                                                                                |
+| Portugal       | 50                                                                                                                                                                                                                          | 90                                                                                                                                                             | 120                                                                                                                    |
+| Serbia         | 50                                                                                                                                                                                                                          | 80, 100                                                                                                                                                        | 130                                                                                                                    |
+| Slovenia       | 50                                                                                                                                                                                                                          | 90                                                                                                                                                             | 130 (110 on expressways)                                                                                               |
+| South Africa   | 60                                                                                                                                                                                                                          | 100                                                                                                                                                            | 120                                                                                                                    |
+| Spain          | 20 (streets with a single carriageway and<br>sidewalk platform)<br>30 (single lane streets in each direction)<br>50 (streets with two or more lanes in each<br>direction)                                                   | 90                                                                                                                                                             | 120                                                                                                                    |
+| Sweden         | 30, 40, 50                                                                                                                                                                                                                  | 60,70,80,90,100                                                                                                                                                | 110,120                                                                                                                |
+| Switzerland    | 50 (sections with 30)                                                                                                                                                                                                       | 80                                                                                                                                                             | 120 (100 on expressways)                                                                                               |
+| United Kingdom | 48 (30 mph) (20 mph in Wales)                                                                                                                                                                                               | 96, 113 (60, 70 mph)                                                                                                                                           | 113 (70 mph)                                                                                                           |
+| United States  | Set by each state                                                                                                                                                                                                           | Set by each state                                                                                                                                              | 88‑129 (55‑80 mph, set by<br>each state)                                                                               |
+
+#### **Maximum authorised blood alcohol content levels, 2023, by country**
+
+| Country                | General BAC level (g/l)                                                                                                   | Differentiated BAC level (g/l)                                                                                                                                                                      |
+|------------------------|---------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Argentina              | 0.0                                                                                                                       | 0.0 for professional drivers<br>0.0 for motorcycle and moped riders                                                                                                                                 |
+| Australia              | 0.5                                                                                                                       | 0.0 for novice drivers<br>0.2 for professional drivers                                                                                                                                              |
+| Austria                | 0.5                                                                                                                       | 0.1 for moped drivers under 20; novice drivers (first three years),<br>truck (>7.5 tons) and bus (>9 seats) drivers                                                                                 |
+| Belgium                | 0.5                                                                                                                       | 0.2 for professional drivers (since January 2015)                                                                                                                                                   |
+| Bosnia and Herzegovina | 0.3                                                                                                                       | 0.0 for professional drivers, novice drivers, drivers who perform<br>public transport, driving instructors, driving candidates, drivers<br>under 21 or with less than 3 years of driving experience |
+| Cambodia               | 0.5                                                                                                                       |                                                                                                                                                                                                     |
+| Canada                 | 0.8                                                                                                                       | administrative maximum level of 0.5 g/l or 0.4 g/l in most<br>provinces<br>0.0 g/l administrative maximum level for novice and young<br>(under 21) drivers in most provinces                        |
+| Chile                  | 0.3                                                                                                                       |                                                                                                                                                                                                     |
+| Colombia               | 0.2                                                                                                                       |                                                                                                                                                                                                     |
+| Costa Rica             | 0.5                                                                                                                       | 0.2 for novice and professional drivers                                                                                                                                                             |
+| Czechia                | 0.0                                                                                                                       |                                                                                                                                                                                                     |
+| Denmark                | 0.5                                                                                                                       |                                                                                                                                                                                                     |
+| Finland                | 0.5                                                                                                                       |                                                                                                                                                                                                     |
+| France                 | 0.5                                                                                                                       | 0.2 for bus/coach drivers, novice drivers                                                                                                                                                           |
+| Germany                | 0.5 (Drivers with a BAC between 0.3‑0.5 g/l<br>can have their licenses suspended if their<br>driving ability is impaired) | 0.0 for drivers under 21 and novice drivers, for professional<br>drivers who transport passengers or hazardous goods                                                                                |
+| Greece                 | 0.5                                                                                                                       | 0.2 for professional drivers, novice drivers, motorcycles and<br>moped riders                                                                                                                       |
+| Hungary                | 0.0                                                                                                                       |                                                                                                                                                                                                     |
+| Iceland                | 0.5                                                                                                                       |                                                                                                                                                                                                     |
+| Ireland                | 0.5                                                                                                                       | 0.2 for learner, novice and professional drivers                                                                                                                                                    |
+| Israel                 | 0.5                                                                                                                       | 0.1 for young (under 24), novice and professional drivers                                                                                                                                           |
+| Italy                  | 0.5                                                                                                                       | 0.0 for young (under 21), novice and professional drivers                                                                                                                                           |
+| Japan                  | 0.3                                                                                                                       |                                                                                                                                                                                                     |
+| Korea                  | 0.3                                                                                                                       |                                                                                                                                                                                                     |
+| Lithuania              | 0.4                                                                                                                       | 0.0 for novice, professional, moped and motorcycle drivers                                                                                                                                          |
+| Luxembourg             | 0.5                                                                                                                       | 0.2 for novice and professional drivers                                                                                                                                                             |
+| Malaysia               | 0.8                                                                                                                       |                                                                                                                                                                                                     |
+| Mexico                 | 0.5                                                                                                                       | 0.0 for professional drivers<br>0.2 for motorcycle drivers                                                                                                                                          |
+
+| Country        | General BAC level (g/l)                | Differentiated BAC level (g/l)                                                        |
+|----------------|----------------------------------------|---------------------------------------------------------------------------------------|
+| Moldova        | 0.3                                    |                                                                                       |
+| Morocco        | 0.2                                    |                                                                                       |
+| Netherlands    | 0.5 (including cyclists)               | 0.2 for novice drivers (first five years) and professional drivers                    |
+| New Zealand    | 0.5                                    | 0.0 for drivers under 20 years                                                        |
+| Nigeria        | 0.5                                    | 0.2 for novice and 0.0 g/l for professional drivers                                   |
+| Norway         | 0.2                                    |                                                                                       |
+| Poland         | 0.2                                    |                                                                                       |
+| Portugal       | 0.5                                    | 0.2 for novice (first three years) and professional drivers (since 1<br>January 2014) |
+| Serbia         | 0.2                                    | 0.0 for novice and professional drivers and for PTW operators                         |
+| Slovenia       | 0.5                                    | 0.0 for novice (first three years) and professional drivers                           |
+| South Africa   | 0.5                                    | 0.2 for professional drivers                                                          |
+| Spain          | 0.5                                    | 0.3 for novice and professional drivers<br>0.0 for drivers under 18                   |
+| Sweden         | 0.2                                    |                                                                                       |
+| Switzerland    | 0.5                                    | 0.0 for novice (first three years) and professional drivers                           |
+| United Kingdom | 0.8 (England, Wales, Northern Ireland) |                                                                                       |
+| United States  | 0.5 (Scotland)                         | 0.4 for professional drivers<br>0.0 to 0.2 for drivers < 21                           |
+
+### **Seat-belt laws and wearing rates in front and rear seats of passenger cars, 2022 or latest available year**
+
+|                        |                                                            | Front seats                                                                    |                                                                                     | Rear seats                  |
+|------------------------|------------------------------------------------------------|--------------------------------------------------------------------------------|-------------------------------------------------------------------------------------|-----------------------------|
+| Country                | Date of<br>application                                     | Wearing rate (%)<br>in 2022                                                    | Date of<br>application                                                              | Wearing rate (%)<br>in 2022 |
+| Argentina              | 1995                                                       | 57 driver (urban areas)                                                        | 1995                                                                                | 13 (urban areas)            |
+| Australia              | 1970s                                                      | 97 (2018)                                                                      | 1970s                                                                               | 96 (2019)                   |
+| Austria                | 1984                                                       | 98 drivers, 99 passengers                                                      | 1990                                                                                | 93                          |
+| Belgium                | 1975                                                       | 94 drivers and 92 passengers                                                   | 1991                                                                                | 79                          |
+| Bosnia and Herzegovina | 2006                                                       |                                                                                | 2006                                                                                |                             |
+| Cambodia               | 2007                                                       | 28 (2016)                                                                      | Law in preparation                                                                  |                             |
+| Canada                 | 1976‑1988                                                  | 97.5 (2017)                                                                    | 1976‑1988                                                                           | 95 (2015)                   |
+| Chile                  | 1985                                                       | 86 drivers, 72 passengers (2021)                                               | 2002 (for vehicles<br>manufactured from<br>2002)                                    | 21 (2021)                   |
+| Colombia               | 2002                                                       | 67 drivers; 49 passengers (2022)                                               | 2004                                                                                | No official data            |
+| Costa Rica             | 2020                                                       | 71 drivers, 63 passengers (2020,<br>national roads)                            | 2020                                                                                | 36 (2020)                   |
+| Czechia                | 1966                                                       | 94.9 (2023)                                                                    | 1975                                                                                | 87.8 (2023)                 |
+| Denmark                | 1970s                                                      | 98                                                                             | 1980s                                                                               | 93                          |
+| Finland                | 1975                                                       | 97                                                                             | 1987                                                                                | 90                          |
+| France                 | 1973 (rural), 1975 (urban<br>by night)<br>1979 (all times) | 99.3 outside built up areas<br>99.4 for small cities,<br>99.7 for major cities | 1991                                                                                | 90                          |
+| Germany                | 1976                                                       | 99 drivers, 98 passengers                                                      | 1984                                                                                | 95                          |
+| Greece                 | 1979                                                       | 72 passengers                                                                  | 1993                                                                                | 56                          |
+| Hungary                | 1976                                                       | 88 drivers, 87 passengers                                                      | 1993 outside built up<br>areas<br>2001 inside built up<br>areas                     | 57                          |
+| Iceland                |                                                            | 97 drivers                                                                     |                                                                                     | 93                          |
+| Ireland                | 1979                                                       | 99 drivers, 98 passengers (2021)                                               | 1992                                                                                | 93 (2021)                   |
+| Israel                 | 1975                                                       | 93 drivers, 91 passengers (2019)                                               | 1995                                                                                | 71 (2019)                   |
+| Italy                  | 1988                                                       | 87.4 drivers, 84 passengers                                                    | 1994                                                                                | 34.5                        |
+| Japan                  | 1985                                                       | 99 drivers, 97 passengers                                                      | 2008                                                                                | 43                          |
+| Korea                  | 1990                                                       | 85 drivers, 86 passengers                                                      | 2008, on motorways<br>only<br>Since September 2018,<br>on the whole road<br>network | 32                          |
+| Lithuania              |                                                            | 98 (2021)                                                                      |                                                                                     | 62 (2021)                   |
+| Luxembourg             | 1975                                                       | 90 (2015)                                                                      | 1992                                                                                | 76 (2015)                   |
+| Malaysia               | 1978                                                       | 87 drivers, 74 pass. (2016)                                                    | 2009                                                                                | 15 (2016)                   |
+
+|                |                                                                                                                   | Front seats                                                                                                                                  | Rear seats                                        |                                |  |
+|----------------|-------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------|--------------------------------|--|
+| Country        | Date of<br>application                                                                                            | Wearing rate (%)<br>in 2022                                                                                                                  | Date of<br>application                            | Wearing rate (%)<br>in 2022    |  |
+| Mexico         | 2022 (new law)                                                                                                    | 79 drivers, 65 general (2017)                                                                                                                | 2022 (new law)                                    | 46 (2017)                      |  |
+| Moldova        | 2009                                                                                                              | No official data<br>>90 (estimation)                                                                                                         | 2009                                              | No official data               |  |
+| Morocco        | 1977 – rural areas<br>2005 – urban areas                                                                          | 57 passengers                                                                                                                                | 2005 – rural areas                                | 36 (2018)                      |  |
+| Netherlands    | 1975                                                                                                              | 95                                                                                                                                           | 1992                                              |                                |  |
+| New Zealand    | 1972                                                                                                              | 97 drivers, 96 passengers (2016)                                                                                                             | 1979                                              | 92 (2014)                      |  |
+| Nigeria        | 1997 (enforced since<br>2002)                                                                                     | 85 (2017)                                                                                                                                    | 1997 (enforced since<br>2016)                     | 3 (2017)                       |  |
+| Norway         | 1975                                                                                                              | 98.1 drivers in rural areas,<br>97.7 drivers outside rural areas,<br>97 passengers in rural areas,<br>96.6 passengers outside rural<br>areas | 1985                                              | 96 (2014)                      |  |
+| Poland         | 1983                                                                                                              | 96                                                                                                                                           | 1991                                              | 90                             |  |
+| Portugal       | 1978                                                                                                              | 96 drivers and passengers<br>(2017)                                                                                                          | 1994                                              | 77 (2017)                      |  |
+| Serbia         | 1982                                                                                                              | 86 drivers, 81 passengers                                                                                                                    | 2009                                              | 19                             |  |
+| Slovenia       | 1977                                                                                                              | 95 drivers, 96 passengers (2018)                                                                                                             | 1998                                              | 78 adults (2018)               |  |
+| South Africa   | 2005, vehicles registered<br>after 1 January 2006                                                                 | 4.5 drivers, 5 passengers<br>(estimation 2010)                                                                                               | 2005, vehicles registered<br>after 1 January 2006 |                                |  |
+| Spain          | 1974 outside urban<br>areas<br>1992 inside urban areas                                                            | 96 driver, 95.9 passengers (2021)                                                                                                            | 1992                                              | 92.8 (2021)                    |  |
+| Sweden         | 1975                                                                                                              | 96 drivers (2021)                                                                                                                            | 1986; child restraint<br>since 1988               | 94 (2017)                      |  |
+| Switzerland    | 1981                                                                                                              | 95                                                                                                                                           | 1994                                              | 88                             |  |
+| United Kingdom | 1983                                                                                                              | 97 drivers, 97 passengers (2021<br>for Great Britain)                                                                                        | 1989 (children);<br>1991 (adults)                 | 92 (2021 for Great<br>Britain) |  |
+| United States  | Primary law in 34 states<br>and D.C., secondary<br>law in 15 states. Not<br>mandatory for adults in<br>one state. | 92                                                                                                                                           | Varies by State                                   | 76 (25‑69 year‑old)            |  |
+
+### **Helmet laws and wearing rates, 2022 or latest available year**
+
+|                        | Powered two-wheelers                                                                                                                |                                                                         | Cyclists                                                                                                         |                                                                                                              |  |
+|------------------------|-------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|--|
+| Country                | Helmet law                                                                                                                          | Wearing rate (%)<br>in 2022                                             | Helmet law                                                                                                       | Wearing rate (%) in<br>2022                                                                                  |  |
+| Argentina              | Yes                                                                                                                                 | 58 riders, 34 first pass.,<br>18 additional passengers<br>(urban areas) | Yes                                                                                                              | 8 (2018)                                                                                                     |  |
+| Australia              | Yes                                                                                                                                 | 99 riders (2018)                                                        | Yes                                                                                                              |                                                                                                              |  |
+| Austria                | Yes                                                                                                                                 | 100                                                                     | Yes, for children to age 12                                                                                      | 40 (87 for children)                                                                                         |  |
+| Belgium                | Yes                                                                                                                                 | 99.7                                                                    | No                                                                                                               | 24.8%                                                                                                        |  |
+| Bosnia and Herzegovina | Yes                                                                                                                                 |                                                                         | Yes                                                                                                              |                                                                                                              |  |
+| Cambodia               | Yes, motorcycles from 50 cc,<br>motorcycles with trailers,<br>motorised tricycles (riders<br>and passengers)                        | Low (no precise data)                                                   | No                                                                                                               |                                                                                                              |  |
+| Canada                 | Yes                                                                                                                                 |                                                                         | In some jurisdictions                                                                                            |                                                                                                              |  |
+| Chile                  | Yes                                                                                                                                 | 95 riders, 87 passengers<br>(2021)                                      | Yes in urban areas                                                                                               | 67.3 (2019)                                                                                                  |  |
+| Colombia               | Yes                                                                                                                                 | 79.2 motorcycle riders,<br>52.7 passengers (urban<br>areas)             | Yes, for children to age 18                                                                                      | 22.4 (urban areas)<br>(2022)                                                                                 |  |
+| Costa Rica             | Yes                                                                                                                                 | 97.2 riders, 90.1<br>passengers (2020)                                  | No                                                                                                               |                                                                                                              |  |
+| Czechia                | Yes                                                                                                                                 | 100 (2023)                                                              | Yes, for children to age 18                                                                                      | 87.8 (2023)                                                                                                  |  |
+| Denmark                | Yes                                                                                                                                 | 100 motorcycles<br>96.6 light mopeds (urban<br>areas)                   | No                                                                                                               | 50 (urban areas)                                                                                             |  |
+| Finland                | Yes                                                                                                                                 | 99.7 (2019)                                                             | No                                                                                                               | 54                                                                                                           |  |
+| France                 | Yes, since 1973 for<br>motorcyclists<br>1976 for moped riders<br>outside built up areas<br>1980 for moped roders in<br>urban areas  | 97 outside built up areas<br>98 in urban areas                          | Yes, for children under 12                                                                                       | Major cities: 34 weekdays,<br>33 weekends (2021)                                                             |  |
+| Germany                | Yes                                                                                                                                 | 98.5 riders, 98.9<br>passengers (inside urban<br>areas)                 | No                                                                                                               | 40.3 (inside urban areas<br>including sport bicycles)<br>34 (inside urban areas<br>excluding sport bicycles) |  |
+| Greece                 | Yes, since 1977                                                                                                                     | 80.3 riders, 65.5<br>passengers                                         | No                                                                                                               |                                                                                                              |  |
+| Hungary                | Yes since 1965 for<br>motorcyclists,<br>1997 for moped riders<br>outside built up areas<br>1998 for moped riders in<br>urban areas. | 99 Budapest area (2019)<br>97 Rural areas (2019)                        | No                                                                                                               | 18 Budapest area (2019)<br>4.5 Rural areas (2019)                                                            |  |
+| Iceland                | Yes                                                                                                                                 | n.a.                                                                    | Yes, for children to age 14                                                                                      |                                                                                                              |  |
+| Ireland                | Yes, since 1978                                                                                                                     | 99.8 (2021)                                                             | No                                                                                                               | 53                                                                                                           |  |
+| Israel                 | Yes                                                                                                                                 | n.a.                                                                    | Yes. Mandatory for all<br>ages in non-urban roads.<br>Mandatory for cyclists<br>under 18 years in urban<br>roads | 21% (2015 observational<br>survey among cyclists on<br>urban roads)                                          |  |
+| Italy                  | Yes, for all since 2000<br>Since 1986 for motorcyclists<br>and riders of moped under 18                                             | 96.5                                                                    | No                                                                                                               |                                                                                                              |  |
+| Japan                  | Yes                                                                                                                                 | 100 (2021)                                                              | Yes, since 2023                                                                                                  | 13.5                                                                                                         |  |
+|                        |                                                                                                                                     |                                                                         |                                                                                                                  |                                                                                                              |  |
+
+|                | Powered two-wheelers                                                                                                                                                                                        |                                                                                                                | Cyclists                                                                                                 |                                                             |  |
+|----------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|-------------------------------------------------------------|--|
+| Country        | Helmet law                                                                                                                                                                                                  | Wearing rate (%)<br>in 2022                                                                                    | Helmet law                                                                                               | Wearing rate (%) in<br>2022                                 |  |
+| Korea          | Yes                                                                                                                                                                                                         | 93 (2021)                                                                                                      | No                                                                                                       | 94                                                          |  |
+| Lithuania      | Yes                                                                                                                                                                                                         |                                                                                                                | Yes, for children to age 18                                                                              |                                                             |  |
+| Luxembourg     | Yes, since 1976                                                                                                                                                                                             | 100 (2021e)                                                                                                    | No                                                                                                       |                                                             |  |
+| Malaysia       | Yes, since 1973                                                                                                                                                                                             | c. 77 (2015)                                                                                                   | No                                                                                                       |                                                             |  |
+| Mexico         | Yes                                                                                                                                                                                                         | 89 riders, 82 passengers<br>(2021)                                                                             | Yes on federal roads since<br>2012                                                                       | 11 (2017)                                                   |  |
+| Moldova        | Yes                                                                                                                                                                                                         | No national data                                                                                               | Yes on road sections with a<br>speed limit above 50 km/h                                                 |                                                             |  |
+| Morocco        | Yes, since 1976                                                                                                                                                                                             | 57 riders, 31 passengers                                                                                       | No                                                                                                       |                                                             |  |
+| Netherlands    | Yes, motorcycles since 1972;<br>mopeds since 1975. Not<br>compulsory on slow mopeds<br>(max. 25 km/h) until 2022<br>As of 1 Jan 2023 all riders of<br>slow-mopeds (speed max<br>25 km./h must wear a helmet | 99 mopeds                                                                                                      | No                                                                                                       | 3% bikes, 8% e-bikes                                        |  |
+| New Zealand    | Yes, since 1956 when<br>travelling above 30 mph<br>Since 1973 at all speeds                                                                                                                                 | 100 (2021)                                                                                                     | Yes, since 1994                                                                                          | 94 (2015)                                                   |  |
+| Norway         | Yes                                                                                                                                                                                                         | 100 (2021)                                                                                                     | No                                                                                                       | 67.1 (all age groups)<br>66.7 (above 12)<br>74.5 (below 12) |  |
+| Poland         | Yes, since 1997                                                                                                                                                                                             | 100                                                                                                            | No                                                                                                       | 25                                                          |  |
+| Portugal       | Yes                                                                                                                                                                                                         | Motorcyclists: 97.6 riders,<br>100 passengers<br>Mopeds: 94 riders, 92<br>passengers<br>(2013)                 | No                                                                                                       |                                                             |  |
+| Serbia         | Yes                                                                                                                                                                                                         | Motorcyclists: 87.7 riders,<br>80.3 passengers<br>Mopeds: 69.2 riders, 70.7<br>passengers                      | No                                                                                                       | 3.7                                                         |  |
+| Slovenia       | Yes                                                                                                                                                                                                         | n.a.                                                                                                           | Yes, for children and<br>youngster under 18                                                              | 21<br>67 (children)<br>27 (young)<br>(2022)                 |  |
+| Spain          | Yes                                                                                                                                                                                                         | 99.4 riders, 96.2<br>passengers<br>99.3 in urban roads<br>(2021)<br>100 in motorways and<br>rural roads (2021) | Yes.<br>Mandatory on non-urban<br>roads for all.<br>Mandatory on urban rods<br>only for cyclists under 6 | 33 in urban roads<br>89.8 in rural roads                    |  |
+| Sweden         | Yes                                                                                                                                                                                                         | 98 for mopeds (2021)                                                                                           | Yes, for children to age 15<br>(since 2015)                                                              | 46 for all age groups<br>64 for children<br>42 for adults   |  |
+| Switzerland    | Yes, motorcycles since 1981;<br>mopeds since 1990                                                                                                                                                           | 100 motorcycles<br>95 mopeds                                                                                   | No for regular bicycles<br>Yes for e-bikes > 25km/h                                                      | 56 cyclists<br>68 e-bikes <25km/h<br>91 e-bikes >25km/h     |  |
+| United Kingdom | Yes, motorcycles 1973;<br>mopeds since 1977                                                                                                                                                                 |                                                                                                                | No                                                                                                       |                                                             |  |
+| United States  | No national law.18 states, D.C.<br>and PR require helmet use<br>by all, 29 by specific users, 3<br>have no helmet law.                                                                                      | 65 use of DOT-compliant<br>helmets                                                                             | Age-specific helmet laws in<br>21 states and D.C.                                                        |                                                             |  |
+
+| Annex. Road safety strategies and targets in IRTAD countries |  |  |  |  |  |  |  |  |
+|--------------------------------------------------------------|--|--|--|--|--|--|--|--|
+|--------------------------------------------------------------|--|--|--|--|--|--|--|--|
+
+This Annex details national road safety strategies (Table A1) and national targets on road deaths and serious injuries (Table A2).
+
+#### **Road safety strategies in IRTAD countries**
+
+| Country                | Strategy                                                                                                                                                                                                                                                                                                                                                                         |
+|------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Australia              | The Australian National Road Safety Strategy 2021-30 was adopted in 2021 following consultation and<br>review. The strategy continues Australia's commitment to the Safe System approach.<br>The Australian National Road Safety Action Plan 2023-25 sets out the key actions all governments will undertake<br>to 2025.<br>Link:<br>https://www.roadsafety.gov.au/nrss          |
+| Austria                | The Austrian Road Safety Strategy 2021-2030 refers to the Safe System.<br>Link:<br>https://www.bmk.gv.at/en/topics/transport/roads/safety/vss2030.html                                                                                                                                                                                                                           |
+| Belgium                | Belgium's federal road safety plan, the Plan Fédéral de Sécurité Routière 2021-25, is based on Vision Zero.<br>There are also three regional plans and a federal strategy, known as "All for Zero".<br>Links:<br>https://all-for-zero.be/storage/minisites/plan-federal-securite-routiere.pdf<br>https://all-for-zero.be/fr/all-for-zero/                                        |
+| Bosnia and Herzegovina | The Framework Road Safety Strategy Development for Bosnia and Herzegovina (2024-2028) is under<br>preparation and has not yet been published. The strategy's vision is the Road To Zero.                                                                                                                                                                                         |
+| Canada                 | Canada's Road Safety Strategy 2025 (RSS 2025) was first published in 2016 and adopts the Safe System<br>approach.<br>Canada also has a long-term vision of zero fatalities and serious injuries on the roads (Vision Zero).<br>Link:<br>http://roadsafetystrategy.ca/en/                                                                                                         |
+| Chile                  | Chile's Estrategia Nacional de Seguridad de Tránsito [National Road Safety Strategy] for 2021-30 was<br>published in December 2020. It specifically refers to the Safe System and Vision Zero ("Vision Zero for Chile").<br>Link:<br>https://conaset.cl/wp-content/uploads/2021/05/Estrategia-Nacional-de-Seguridad-de-Tránsito_2021-2030.pdf                                    |
+| Colombia               | Colombia's National Road Safety Strategy 2022-31 was adopted in July 2022. It officially adopted the Safe<br>System approach.<br>Link:<br>https://www.ansv.gov.co                                                                                                                                                                                                                |
+| Czechia                | Czechia's national road safety strategy for 2021-30 is titled Road Safety is Everyone's Right and<br>Responsibility. Both Vision Zero and the Safe System approach are at its core.<br>Link:<br>https://besip.cz/getattachment/Pro-odborniky/Narodni-strategie-BESIP/Aktualni-strategie/Czech-Road-Traffic<br>Safety-Strategy-2021-30_11-11.pdf                                  |
+| Denmark                | Denmark has adopted the 2021-2030 Action Plan. The plan does not refer to Vision Zero or the Safe System.<br>The current plan's vision is "Every accident is one too many", which dates back to earlier action plans created by<br>the Commission.<br>Link:<br>https://www.faerdselssikkerhedskommissionen.dk/media/eymfxr0n/fsk_resume_handlingsplaneng_2021-2030_<br>final.pdf |
+
+| Country | Strategy                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
+|---------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Finland | Finland's traffic safety strategy for 2022-2026 was published in March 2022 and was accompanied by a<br>government resolution on traffic safety. It refers to both Vision Zero and the Safe System.<br>Link:<br>https://www.fintraffic.fi/en/fintraffic/strategy-2022-2026                                                                                                                                                                                                                                                                                                                                  |
+| France  | In France, the road safety strategy is announced with each meeting of the Interministerial Road Safety<br>Committee. The last one was held on 17 July 2023.<br>Link:<br>https://www.onisr.securite-routiere.gouv.fr/en/road-safety-policy/interministerial-road-safety-committees                                                                                                                                                                                                                                                                                                                           |
+| Germany | The German road safety strategy (known as the Road Safety Pact) covers the period 2021-30. It refers to the<br>Safe System.<br>Link:<br>https://www.bmvi.de/SharedDocs/DE/Anlage/StV/road-safety-pact-en.pdf?blob=publicationFile                                                                                                                                                                                                                                                                                                                                                                           |
+| Greece  | Greece's National Road Safety Strategic Plan covers the period 2021-2030. It refers to both the Safe System<br>approach and Vision Zero.<br>Links:<br>https://www.nrso.ntua.gr/nrss2030/?lang=en<br>https://www.nrso.ntua.gr/nrss2030/wp-content/uploads/2022/10/NationalRoadSafetyStrategicPlan-eng.pdf                                                                                                                                                                                                                                                                                                    |
+| Hungary | In Hungary, road safety strategies are prepared for three-year periods. The current Road Safety Action Plan<br>covers the period 2023-25. It is built on the concept of Vision Zero and the Safe System approach.<br>Link:<br>https://www.kti.hu                                                                                                                                                                                                                                                                                                                                                            |
+| Ireland | Ireland's national road safety strategy for 2021-2030, Our Journey Towards Vision Zero, refers to both the Safe<br>System and Vision Zero.<br>The 2021-2030 strategy is supported by a Phase 1 Action Plan for 2021-24.<br>The strategy and action plan focus on seven Safe System priority intervention areas, and commit to achieving<br>Vision Zero in Ireland by 2050.<br>Links:<br>https://www.rsa.ie/about/safety-strategy-2021-2030<br>https://www.rsa.ie/docs/default-source/road-safety/action-plans/rsa_safety_strategy_action_<br>plan_2021_2024_13th_jan2022_final_online.pdf?sfvrsn=67518e36_5 |
+| Italy   | In April 2022, Italy's Interministerial Committee for Economic Planning and Sustainable Development approved<br>the National Road Safety Plan 2030.<br>The plan is based on the Safe System approach.<br>Link:<br>https://www.mit.gov.it/nfsmitgov/files/media/progetti/2022-09/20220916_Piano%20Nazionale%20Sicurezza%20<br>Stradale_Def.pdf                                                                                                                                                                                                                                                               |
+| Japan   | The Japanese government released its 11th Traffic Safety Program in March 2021. It covers the period 2021-25.<br>It does not refer to either the Safe System or Vision Zero.<br>Link:<br>https://www8.cao.go.jp/koutu/kihon/keikaku11/index.html                                                                                                                                                                                                                                                                                                                                                            |
+| Korea   | Korea's 9th National Transport Safety Plan 2022-2026 has been approved by the Ministry of Land,<br>Infrastructure and Transport. The Plan is based on Vision Zero.<br>Link:<br>http://molit.go.kr/viewer/skin/doc.html?fn=3f774e661393273f795b8c521c83a539&rs=/viewer/result/20220928                                                                                                                                                                                                                                                                                                                       |
+
+| Country     | Strategy                                                                                                                                                                                                                                                                            |
+|-------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Luxembourg  | Luxembourg has put in place a National Road Safety Action Plan for 2019-2023.                                                                                                                                                                                                       |
+|             | The plan aims to reduce the large number of serious injuries and fatalities on the roads in pursuit of the long-term<br>goal of zero deaths and zero serious injuries.                                                                                                              |
+|             | Link:<br>https://gouvernement.lu/dam-assets/documents/actualites/2019/05-mai/Plan-d-action-securite-routiere.pdf                                                                                                                                                                    |
+| Mexico      | Mexico published the new Mobility and Road Safety Strategy (ENAMOV) 2023-2042 in June 2023.                                                                                                                                                                                         |
+|             | A new General Law of Mobility and Road Safety was published in the Official Gazette of the Federation on 17 May<br>2022. Its objective is to establish the basis for guaranteeing the right to safe mobility and inclusive accessibility.<br>The law adopts a Safe System approach. |
+|             | Links:                                                                                                                                                                                                                                                                              |
+|             | https://www.dof.gob.mx/nota_detalle.php?codigo=5596042&fecha=02/07/2020                                                                                                                                                                                                             |
+|             | https://www.diputados.gob.mx/LeyesBiblio/pdf/LGMSV.pdf                                                                                                                                                                                                                              |
+|             | https://www.gob.mx/cms/uploads/attachment/file/848141/ENAMOV_2023-2042.pdf                                                                                                                                                                                                          |
+| Moldova     | Moldova is currently developing a new road safety strategy to replace the previous strategy covering the period<br>2011-20.                                                                                                                                                         |
+|             | In January 2020, the Moldovan government approved a Road Safety Action Plan for the period 2020-21. The plan<br>referred to Vision Zero and the five road safety pillars.                                                                                                           |
+|             | Link:                                                                                                                                                                                                                                                                               |
+|             | https://www.legis.md/cautare/getResults?doc_id=120102⟨=ro                                                                                                                                                                                                                           |
+| Morocco     | Morocco's current national road safety strategy covers the period 2017-2026.                                                                                                                                                                                                        |
+|             | The strategy refers to the Safe System and is based on the five road safety pillars.                                                                                                                                                                                                |
+|             | Link:                                                                                                                                                                                                                                                                               |
+|             | https://www.narsa.ma/fr                                                                                                                                                                                                                                                             |
+| Netherlands | The Netherlands' road safety strategy is called Door to Door Safety (2018-2030). The Road Safety Strategic<br>Plan 2030 is based on a joint vision on the approach to road safety policy.                                                                                           |
+|             | The strategy is based on the Safe System approach (named Sustainable Safety in the Netherlands).                                                                                                                                                                                    |
+|             | Links:                                                                                                                                                                                                                                                                              |
+|             | https://www.kennisnetwerkspv.nl/getmedia/ce0099b7-ce77-4ce2-98c8-a7810662ef10/19-093-RO-SPV-Engels_                                                                                                                                                                                 |
+|             | v2.pdf.aspx<br>https://open.overheid.nl/documenten/ronl-d55ff6bc0b5d564c03906bb54019eb485f83842e/pdf                                                                                                                                                                                |
+|             |                                                                                                                                                                                                                                                                                     |
+| New Zealand | New Zealand's road safety strategy for 2020-30 is titled Road to Zero and is based on Vision Zero and the Safe<br>System approach.                                                                                                                                                  |
+|             | Link:                                                                                                                                                                                                                                                                               |
+|             | https://www.transport.govt.nz/assets/Uploads/Report/Road-to-Zero-strategy_final.pdf                                                                                                                                                                                                 |
+|             |                                                                                                                                                                                                                                                                                     |
+| Norway      | Vision Zero was adopted by the Parliament for the first time in 2001 and is the base for all the following Road<br>Safety Strategies.                                                                                                                                               |
+|             | The existing strategy was adopted by the Parliament in 2021 as part of the National Transport Plan 2022-2033.                                                                                                                                                                       |
+|             | The National Plan of Action for Road Safety 2022-2025 was developed by the Norwegian Public Roads<br>Administration in cooperation with a wide range of other national stakeholders.                                                                                                |
+|             | Links:                                                                                                                                                                                                                                                                              |
+|             | https://www.vegvesen.no/globalassets/fag/fokusomrader/trafikksikkerhet/nasjonal-tiltaksplan-for                                                                                                                                                                                     |
+|             | trafikksikkerhet-pa-vei-2022-2025.pdf<br>https://www.vegvesen.no/globalassets/fag/fokusomrader/trafikksikkerhet/national-plan-of-action-for-road                                                                                                                                    |
+
+| Country     | Strategy                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+|-------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Poland      | Poland published its National Road Safety Programme 2021-2030 in December 2021. The document refers to<br>both Vision Zero and the Safe System approach.<br>Link:<br>https://www.krbrd.gov.pl/wp-content/uploads/2021/12/Narodowy-Program-Bezpieczenstwa-Ruchu<br>Drogowego-2021-2030.pdf                                                                                                                                                                                                                                                                                                                                                                                                                           |
+| Portugal    | Portugal's national road safety strategy 2021-30, entitled "Vision Zero to 2030", is currently under development.<br>It refers to Vision Zero and the Safe System approach.<br>Link:<br>https://visaozero2030.pt/en/                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
+| Serbia      | Serbia adopted the National Road Safety Strategy 2023-2030 in September 2023, along with the Action Plan<br>2023-2025.<br>It refers to Vision Zero and the Safe System approach.<br>Link:<br>https://abs.gov.rs/ср/propisi-71/strateski-dokumenti                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
+| Slovenia    | The new national programme for the period 2023-30 was prepared approved by the National Assembly. It will be<br>based on Vision Zero and the Safe System approach.<br>Link:<br>https://www.avp-rs.si/wp-content/uploads/2023/10/novo1_renpvcp23_30-v01-3-10-2023.pdf                                                                                                                                                                                                                                                                                                                                                                                                                                                |
+| Spain       | Spain's Road Safety Strategy 2030 (Estrategia de Seguridad Vial 2030, ESV 2030) was published and officially<br>presented by the Minister of the Interior on 9 June 2022.<br>The strategy is based on the Safe System approach. The main target is aligned with the WHO Plan for the<br>Decade of Action as well as the European Union Framework 2021-2030, namely: a 50% reduction in deaths and<br>serious injuries for 2030, and a long-term target of Vision Zero by 2050.<br>Links:<br>https://seguridadvial2030.dgt.es/inicio/<br>https://seguridadvial2030.dgt.es/export/sites/sv2030/.galleries/descargas/Road_Safety_Strategy_2030_<br>Summary_EN.pdf                                                      |
+| Sweden      | Sweden released the updated 2022-30 road safety strategy in 2023. The strategy is based on Vision Zero.<br>The Action Plan 2022-2025, developed by the Swedish Transport Administration, also describes commitments<br>from a wide range of stakeholders.<br>Links:<br>http://trafikverket.diva-portal.org/smash/record.jsf?pid=diva2%3A1657137&dswid=2597<br>https://bransch.trafikverket.se/for-dig-i-branschen/samarbete-med-branschen/Samarbeten-for-trafiksakerhet/<br>tillsammans-for-nollvisionen/gemensam-aktionsplan-for-saker-vagtrafik-2022-2025/                                                                                                                                                        |
+| Switzerland | In 2016 the Swiss Federal Roads Office (FEDRO) published a strategy that set targets for fatalities and serious<br>injuries on Swiss roads to be met by 2030.<br>The sub-strategy on road safety, published in 2020, specifies the need for action and concrete measures. It<br>does not refer either to Vision Zero or the Safe System approach.<br>Links:<br>https://www.astra.admin.ch/dam/astra/fr/dokumente/direktion/strategische-ausrichtung.pdf.download.pdf/<br>Orientation%20strat%C3%A9gique%20de%20l'OFROU.pdf<br>https://www.astra.admin.ch/dam/astra/fr/dokumente/direktion/teilstrategie-verkehrssicherheit.pdf.download.<br>pdf/Strat%C3%A9gie%20partielle%20s%C3%A9curit%C3%A9%20routi%C3%A8re.pdf |
+
+| Country        | Strategy                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
+|----------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| United Kingdom | The United Kingdom is the process of developing a new Road Safety Strategic Framework (RSSF) which will be<br>published. It is likely to be based on a Safe System approach.<br>Link:<br>https://www.gov.uk/government/publications/strategic-framework-for-road-safety                                                                                                                                                                                                                                                                                                    |
+| United States  | In January 2022, the US Department of Transportation released a National Roadway Safety Strategy (NRSS).<br>At the core of this strategy is a Department-wide adoption of the Safe System approach. This is the first step in<br>working towards an ambitious long-term goal of reaching zero roadway fatalities.<br>Links:<br>https://www.transportation.gov/NRSS<br>https://www.transportation.gov/sites/dot.gov/files/2022-04/US_DOT_FY2022-26_Strategic_Plan.pdf<br>DOT NRSS Action Tracking Dashboard<br>2023 Progress Report on the National Roadway Safety Strategy |
+
+### **Targets on road deaths and serious injuries in IRTAD countries**
+
+| Country                | Target                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           | Baseline year(s)                                                                                                                                             |
+|------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Australia              | • Reduce fatalities by 50% by 2030<br>• Reduce serious injuries by 30% by 2030.<br>As part of demonstrating a commitment to the 2050 Vision Zero target, the<br>strategy will target by 2030:<br>• Zero deaths for children 7 years and under<br>• Zero deaths in city central business district (CBD) areas<br>• Zero deaths on National highways and on high-speed roads covering<br>80% of travel across the network.<br>There are no interim targets, however, the 2030 Target of a 30 per cent<br>reduction in serious injuries by 2030 will be assessed as part of the mid-term<br>review of the Strategy. | Average for 2018-20 for<br>fatalities.<br>3-year average of hospital<br>cases for 2017-18 and 2018-19<br>and estimates for 2019-20, for<br>serious injuries. |
+| Austria                | • Reduce road deaths and serious injuries by 50% by 2030.<br>Austria also has a Vision Zero for child fatalities.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                | Average for 2017-19                                                                                                                                          |
+| Belgium                | • Reduce road deaths by 50% by 2030<br>• Reduce serious injuries, as defined by a maximum abbreviated injury<br>score of three or above (MAIS3+), by 50% by 2030<br>• Reduce road deaths by 100% by 2050<br>• Reduce serious injuries (MAIS3+) by 90% by 2050.                                                                                                                                                                                                                                                                                                                                                   | 2019                                                                                                                                                         |
+| Bosnia and Herzegovina | • Reduction of 50% in the number of deaths and serious injuries by 2030.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         |                                                                                                                                                              |
+| Canada                 | No hard quantitative targets.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |                                                                                                                                                              |
+| Chile                  | • Reduce road traffic fatalities by 30% by 2030.<br>There are specific additional targets:<br>• Reduce the share of vulnerable road users in road deaths from 49% to<br>35% of all deaths<br>• Reduce the mortality rate of young people (15 29) from 2.2 in 2019 to<br>1.5 deaths per 100 000 inhabitants in 2030.<br>• Reduce the mortality rate of elderly people (+60) from 1.9 in 2019 to<br>1.3 deaths per 100 000 inhabitants in 2030.                                                                                                                                                                    | Average for 2011-19                                                                                                                                          |
+| Colombia               | • Reduce by 50% the road mortality from 14.6 road deaths per<br>100 000 population in 2021 to 7.3 in 2030.<br>The strategy also includes three specific targets:<br>• Reduce by 47% (from 4 526 in 2021 to 2 421 in 2030) the number of<br>motorcyclists killed in road crashes<br>• Reduce by 44% (from 1 590 in 2021 to 891 in 2030) the number of<br>pedestrians killed in road crashes<br>• Reduce by 37% (from 483 in 2021 to 302 in 2030) the number of cyclists<br>killed in road crashes.                                                                                                                | 2021                                                                                                                                                         |
+| Czechia                | • Reduce road deaths and serious injuries by 50% by 2030.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        | Average for 2017-19                                                                                                                                          |
+
+| Country | Target                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | Baseline year(s) |
+|---------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|
+| Denmark | • Reduce the number road deaths to 90 or below (data from policy<br>registry)<br>• Reduce the number of serious injuries to 900 or below (data from the<br>police registry)<br>• Reduce the number of slight injures to 10 000 or below (data from the<br>Danish national patient register).<br>These figures correspond to an approximate 50% reduction of the average for<br>2017-19, which is 182 killed and 1 813 seriously injured persons per year.<br>There are no specific targets, but five focus areas have been pointed out<br>and will be monitored: single vehicle crashes, head-on collisions, crashes at<br>intersections, vulnerable road users and young car drivers. |                  |
+| Finland | • Reduce by 50% the number of road deaths and serious injuries by 2030.<br>The long-term vision is zero road deaths in 2050.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           | 2020             |
+| France  | France endorsed the road safety targets, decided at the European Union level<br>in Valetta in March 2017, to reduce by 50% the number of fatalities and severe<br>injuries on European roads by 2030.<br>France reiterated its commitment at the February 2020 Global Ministerial<br>Meeting on Road Safety in Stockholm, which concluded that these same targets<br>should be achieved globally by 2030.<br>The baseline year is 2019 since the year 2020 cannot be considered as a<br>reference, due to the Covid-19 pandemic.<br>France has also endorsed the concept of zero fatalities on the roads by 2050.                                                                      | 2019             |
+| Germany | • Reduce by 40 % the number of road deaths by 2030.<br>• "Significantly" reduce the number of serious injuries by 2030.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                | 2021             |
+| Greece  | • Reduce by 50% road deaths and serious injuries by 2030.<br>Additional specific targets:<br>• 66% reduction in motorcyclists killed by 2030<br>• 60% reduction in road fatalities on Greek islands by 2030<br>• No deaths on motorways by 2030<br>• 35% reduction in deaths in single vehicles crashes by 2030<br>• Zero fatalities in 49 cities with a population between 50 000 and<br>100 000 inhabitants<br>• Being ranked 13th among EU countries regarding deaths per<br>100 000 population.<br>There is an interim target to reduce by 30% deaths and serious injuries by 2025.                                                                                                | 2019             |
+| Hungary | Long-term targets:<br>• Reduce by 50% the number of road deaths by 2030 from 460 to 230<br>• Reduce by 50% the number of serious injuries by 2030 from 4 655 to<br>2 327<br>Short-term targets:<br>• Reach the EU average in terms of road fatalities per million inhabitants<br>by 2025<br>• Proportional reduction of the number of fatalities and serious injuries<br>to reach the 2030 target (345 fatalities and 3 491 seriously injuries by<br>2025)                                                                                                                                                                                                                             | 2020             |
+
+| Country     | Target                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    | Baseline year(s)    |
+|-------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------|
+| Ireland     | • Reduce by 50% the number of road deaths by 2030 from 144 to 72 or<br>lower<br>• Reduce by 50% the number of serious injuries by 2030, from 1 259 to<br>630 or lower.<br>The strategy is divided into three phases (Phase 1 = 2021-24, Phase 2 = 2025-27,<br>Phase 3 = 2028-30) and the targets for the end of Phase 1 are to:<br>• Reduce by 15% the number of road deaths by 2020, from 144 to 122 or<br>lower<br>• Reduce by 10% the number of serious injuries from 1 259 to 1 133 or<br>lower.<br>The strategy commits to achieving Vision Zero in Ireland by 2050. | Average for 2017-19 |
+| Italy       | • Reduce by 50 % the number of road deaths and serious injuries by 2030.<br>A linear decrease in both deaths and serious injuries is hypothesised over the<br>decade, with interim monitoring in 2024 and 2027.<br>Specific targets in terms of reduction of the total number of fatalities have<br>been set for some road users: children, young drivers, motorcyclists, cyclists,<br>pedestrians and people over 65.                                                                                                                                                    | 2019                |
+| Japan       | • Fewer than 2 000 road deaths (within 24 hours) by 2025 (corresponding<br>to a reduction by 30% compared to 2020)<br>• Fewer than 22 000 serious injuries by 2025.                                                                                                                                                                                                                                                                                                                                                                                                       |                     |
+| Korea       | • Reach less than 1 800 road deaths, is a 38% reduction from the number<br>in 2021.<br>The target is in line with the United Nations goal to halve road deaths by 2030.                                                                                                                                                                                                                                                                                                                                                                                                   |                     |
+| Luxembourg  | • Reduce road fatalities and serious injuries by 50% by 2030.<br>This target follows the objectives of the European Commission's Decade of<br>Action 2021-2030 as well as the United Nations target for the same period.                                                                                                                                                                                                                                                                                                                                                  |                     |
+| Mexico      | Not yet defined.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |                     |
+| Moldova     | Not yet defined.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |                     |
+| Morocco     | • Reduce by 50% road deaths by 2026.<br>There are specific targets for pedestrians, powered two- and three-wheelers,<br>children, single-vehicle crashes and commercial transport.                                                                                                                                                                                                                                                                                                                                                                                        | 2015                |
+| Netherlands | The 2030 road safety strategy in general aims at zero fatalities and injuries by<br>2050.<br>At this moment politicians are debating an intermediate goal of a reduction of<br>50% in serious injuries and fatalities by 2030 as well as the reference year.                                                                                                                                                                                                                                                                                                              |                     |
+| New Zealand | • A 40 % reduction in killed and serious injuries by 2030.<br>The long-term vision of the strategy is to achieve zero deaths and serious<br>injuries on the roads by 2050.                                                                                                                                                                                                                                                                                                                                                                                                | 2018                |
+| Norway      | In 2030, the number of killed or seriously injured in road traffic should be<br>maximum 350, with no more than 50 fatalities.<br>There should be zero fatality from road traffic crashes in 2050.                                                                                                                                                                                                                                                                                                                                                                         |                     |
+
+| Country        | Target                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      | Baseline year(s)    |
+|----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------|
+| Poland         | • To reduce by 50% the number of road deaths and serious injuries by<br>2030.<br>There are specific targets for vulnerable road users (pedestrians, cyclists,<br>moped and motorcyclists riders) and alcohol-related fatalities.<br>There are also interim targets for each year of the programme.                                                                                                                                                                                                                          | 2019                |
+| Portugal       | • Reduce by 50% the number of road deaths by 2030.<br>• Reduce by 50% the number of MAIS3+ serious injuries by 2030                                                                                                                                                                                                                                                                                                                                                                                                         | 2019                |
+| Serbia         | • Reduce by 50% the number of road deaths and serious injuries by 2030.<br>• 0 children killed in traffic from 2030.<br>There are specific targets per pillar, as well as interim targets for specific year<br>before 2030.                                                                                                                                                                                                                                                                                                 | 2019                |
+| Slovenia       | • Reduce by 50% the number of road deaths and serious injuries by 2030.                                                                                                                                                                                                                                                                                                                                                                                                                                                     |                     |
+| Spain          | • Reduce by 50% the number of road deaths and serious injuries by 2030.<br>There is a long term target of zero road deaths and serious injuries by 2050.<br>No intermediate targets are explicitly set, but a linear reduction up to the final<br>target is implicitly used as reference value for the year to year decrease in the<br>figures.<br>There are specific targets in terms of reduction of the total number of deaths<br>and serious injuries, for the different road users, types of roads, and age<br>groups. | 2019                |
+| Sweden         | • Reduce by 50% the number of road deaths by 2030, with a maximum of<br>133 road deaths in 2030<br>• Reduce by 25% the number of serious injuries by 2030.<br>There are some more specific targets:<br>• 25% reduction in seriously injured pedestrians falling (single) by 2030<br>• 25% reduction in seriously injured cyclists in single crashes by 2030<br>A quantification of the target to reduce road deaths due to suicides (including<br>jumping from bridges) may come at a later stage.                          | Average for 2017-19 |
+| Switzerland    | • Maximum 100 fatalities and 2 500 seriously injured per year by 2030 on<br>Swiss roads.<br>• Maximum 25 fatalities and 500 seriously injured among human‑powered<br>forms of mobility per year by 2030 on Swiss roads (e.g. pedestrians,<br>bicycles and e-bikes, scooters and e-scooters, inline skates or<br>skateboards).                                                                                                                                                                                               |                     |
+| United Kingdom | Targets not yet defined.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |                     |
+| United States  | The 2022-26 Strategic Plan includes the target to reduce by 66% motor vehicle<br>related fatalities by 2040 to demonstrate progress to achieve zero roadway<br>fatalities.<br>The national strategy includes a summary of the key actions the Department<br>will take over the next three years to work towards the ambitious long-term<br>goal of reaching zero roadway fatalities.<br>Intermediate targets also exist for 2022 and 2023.                                                                                  |                     |
+
+Rachele Poggi (ITF) prepared this report with support from the ITF Secretariat.
+
+David Prater (ITF) copy-edited this report.
+
+Renaud Madignier designed the report. It is based on data and information provided by the IRTAD Group.
+
+The ITF is grateful to all the members of the IRTAD Group for their contributions to this report.
+
+More than 80 institutes worldwide are members or observers of the IRTAD Group, representing an extensive range of public and private organisations with a direct interest in road safety.
+
+IRTAD Group Chair: Dominique MIGNOT (France)
+
+| Argentina              | National Road Safety Agency (ANSV)                                                              |
+|------------------------|-------------------------------------------------------------------------------------------------|
+| Australia              | Department of Infrastructure, Transport, Regional Development, Communications and the Arts      |
+|                        | Australian Road Research Board (ARRB)                                                           |
+| Austria                | AIT Austrian Institute of Technology GmbH                                                       |
+|                        | Kuratorium für Verkehrssicherheit (KfV)                                                         |
+|                        |                                                                                                 |
+| Belgium                | Vias Institute                                                                                  |
+| Bosnia and Herzegovina | Ministry of Communications and Transport                                                        |
+| Cambodia               | National Road Safety Committee                                                                  |
+|                        |                                                                                                 |
+| Canada                 | Transport Canada                                                                                |
+| Chile                  | Ministry of Transport and Telecommunications, Comisión Nacional de Seguridad de Tránsito        |
+| Colombia               | National Road Safety Agency (ANSV)                                                              |
+| Costa Rica             | National Road Safety Council (COSEVI)                                                           |
+| Czechia                | Transport Research Centre (CDV)                                                                 |
+| Denmark                | Road Directorate                                                                                |
+|                        | Technical University of Denmark (DTU)                                                           |
+| Finland                | Finnish Transport and Communications Agency Traficom                                            |
+|                        |                                                                                                 |
+| France                 | National Interministerial Road Safety Observatory (ONISR)                                       |
+|                        |                                                                                                 |
+|                        | Centre for Studies on Expertise and Risks, Mobility, Land Planning and the Environment (Cerema) |
+|                        | Gustave Eiffel University                                                                       |
+|                        | GIE PSA Renault                                                                                 |
+| Germany                | Federal Highway Research Institute (BASt)                                                       |
+|                        | DEKRA e.V                                                                                       |
+|                        | Fraunhofer Institute for Transportation and Infrastructure Systems                              |
+|                        | German Automobile Association (ADAC)                                                            |
+|                        | German Insurance Association(GDV)                                                               |
+|                        | German Road Safety Council (DVR)                                                                |
+|                        | Mercedes Benz AG                                                                                |
+|                        | PTV Group                                                                                       |
+|                        | Robert Bosch GmbH                                                                               |
+|                        | Traffic Accident Research Institute at University of Technology Dresden (VUFO)                  |
+|                        | Volkswagen AG                                                                                   |
+| Greece                 | National Technical University of Athens                                                         |
+|                        | EL.STAT                                                                                         |
+| Hungary                | Institute for Transport Sciences (KTI)                                                          |
+| Iceland                | Icelandic Road and Coastal Administration                                                       |
+|                        | Icelandic Transport Authority (ICETRA)                                                          |
+
+| Ireland      | Road Safety Authority                            |
+|--------------|--------------------------------------------------|
+| Israel       | National Road Safety Authority                   |
+|              | Central Bureau of Statistics                     |
+| Italy        | Centre for Transport and Logistics (CTL)         |
+|              | Italian Automobile Club (ACI)                    |
+|              | Fred Engineering                                 |
+|              | ISTAT                                            |
+|              |                                                  |
+| Japan        | National Police Agency                           |
+|              | Institute for Traffic Research and Data Analysis |
+|              | National Research Institute for Police Science   |
+|              | Kansai University                                |
+| Korea        | Korea Road Traffic Authority (KoROAD)            |
+|              | Korea Expressway Corporation                     |
+|              | Korea Transportation Safety Authority (KOTSA)    |
+|              | Korea Transport Institute (KOTI)                 |
+| Lithuania    | Ministry of Transport and Communications         |
+| Luxembourg   | STATEC                                           |
+| Mexico       | Mexican Institute of Transportation (IMT)        |
+| Moldova      | Technical University of Moldova                  |
+| Morocco      | National Road Safety Agency (NARSA)              |
+| Netherlands  | Ministry of Infrastructure and Water Management  |
+|              | Institute for Road Safety Research (SWOV)        |
+|              | VIA Software                                     |
+| New Zealand  | Ministry of Transport                            |
+| Norway       | Norwegian Public Road Administration             |
+| Poland       | Motor Transport Institute (ITS)                  |
+| Portugal     | National Road Safety Authority (ANSR)            |
+|              | National Laboratory for Civil Engineering (LNEC) |
+| Serbia       | Road Traffic Safety Agency                       |
+|              | Motor Vehicle Centre (AMSS)                      |
+| Slovenia     | Slovenian Traffic Safety Agency                  |
+| South Africa | Road Traffic Management Corporation              |
+| Spain        | General Traffic Directorate                      |
+|              |                                                  |
+
+| Sweden                      | Swedish Transport Agency                                  |
+|-----------------------------|-----------------------------------------------------------|
+|                             | Swedish Transport Administration                          |
+|                             | Swedish Road and Transport Research Institute (VTI)       |
+| Switzerland                 | Federal Roads Office (FEDRO)                              |
+|                             | Swiss Council for Accident Prevention (BfU)               |
+| United Kingdom              | Department for Transport                                  |
+|                             | Agilysis                                                  |
+|                             | Transport Research Laboratory                             |
+| United States               | National Highway Traffic Safety Administration            |
+| Uruguay                     | National Road Safety Unit (UNASEV)                        |
+| International organisations | European Commission                                       |
+|                             | European Transport Safety Council (ETSC)                  |
+|                             | Fédération Internationale de l'Automobile (FIA)           |
+|                             | FIA Foundation                                            |
+|                             | International Motorcycle Manufacturers Association (IMMA) |
+|                             | The Motorcycle Industry in Europe (ACEM)                  |
+|                             | Towards Zero Foundation                                   |
+|                             | World Bank                                                |
+|                             | World Health Organisation (WHO)                           |
+|                             |                                                           |
+
+![](_page_79_Picture_0.jpeg)
+
+# **Road Safety** Annual Report 2023
+
+The Road Safety Annual Report 2023 provides an overview of road safety performance for the 42 countries participating in the International Transport Forum's permanent working group on road safety, known as IRTAD. Based on the latest data, the report describes recent road safety developments in these countries and compares their performance against the main road safety indicators.
+
+Online country profiles complement this report: www.itf-oecd.org/irtad.
+
+![](_page_79_Picture_6.jpeg)
+
+![](_page_79_Picture_7.jpeg)

Zotero/001_artiklid/Road Safety Indicators/globalstatusreportroad2023.md

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+---
+category: literaturenote
+citekey: globalstatusreportroad2023
+title: Global Status Report on Road Safety 2023
+authors: ""
+year: 2023
+date: 2023-00-00 2023
+zotero_key: PSHYMNZB
+zotero_storage: T22HEPXX
+collections: doktoritöö / HLO
+folder: 001_artiklid/Road Safety Indicators
+status: converted
+---
+![](_page_0_Picture_0.jpeg)
+
+# Global status report on road safety 2023
+
+![](_page_0_Picture_2.jpeg)
+
+![](_page_2_Picture_0.jpeg)
+
+# Global status report on road safety 2023
+
+Made possible by funding from **Bloomberg Philanthropies**
+
+Global status report on road safety 2023
+
+ISBN 978-92-4-008651-7 (electronic version) ISBN 978-92-4-008652-4 (print version)
+
+#### **© World Health Organization 2023**
+
+Some rights reserved. This work is available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; [https://creativecommons.org/licenses/](https://creativecommons.org/licenses/by-nc-sa/3.0/igo) [by-nc-sa/3.0/igo](https://creativecommons.org/licenses/by-nc-sa/3.0/igo)).
+
+Under the terms of this licence, you may copy, redistribute and adapt the work for non-commercial purposes, provided the work is appropriately cited, as indicated below. In any use of this work, there should be no suggestion that WHO endorses any specific organization, products or services. The use of the WHO logo is not permitted. If you adapt the work, then you must license your work under the same or equivalent Creative Commons licence. If you create a translation of this work, you should add the following disclaimer along with the suggested citation: *"*This translation was not created by the World Health Organization (WHO). WHO is not responsible for the content or accuracy of this translation. The original English edition shall be the binding and authentic edition".
+
+Any mediation relating to disputes arising under the licence shall be conducted in accordance with the mediation rules of the World Intellectual Property Organization ([http://www.wipo.int/amc/en/](http://www.wipo.int/amc/en/mediation/rules/) [mediation/rules/](http://www.wipo.int/amc/en/mediation/rules/)).
+
+**Suggested citation**. Global status report on road safety 2023. Geneva: World Health Organization; 2023. Licence: [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/igo/) IGO.
+
+**Cataloguing-in-Publication (CIP) data.** CIP data are available at [https://iris.who.int/.](https://iris.who.int/)
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+
+**General disclaimers.** The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of WHO concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted and dashed lines on maps represent approximate border lines for which there may not yet be full agreement.
+
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+
+All reasonable precautions have been taken by WHO to verify the information contained in this publication. However, the published material is being distributed without warranty of any kind, either expressed or implied. The responsibility for the interpretation and use of the material lies with the reader. In no event shall WHO be liable for damages arising from its use.
+
+This document has been produced with a grant from Bloomberg Philanthropies. The contents of this document are the sole responsibility of the World Health Organization and can under no circumstances be regarded as reflecting the positions of Bloomberg Philanthropies.
+
+Design and layout by Inis Communication
+
+![](_page_4_Picture_0.jpeg)
+
+# Contents
+
+| Acknowledgements<br>List of contributors<br>Executive summary<br>Introduction<br>Section 1. The global burden of road traffic deaths<br>Fatalities by road user type<br>Fatality counts and rates, by region and country-income level<br>Section 2. How the burden and context have evolved<br>Progress toward the target of a 50% reduction in deaths<br>Section 3. Measures to mitigate the risk of death and injury<br>Multimodal transport<br>Safe road infrastructure<br>Safe vehicles<br>26<br>Road user behaviours<br>29<br>Speed management<br>30<br>Impaired and distracted driving<br>31<br>Motorcycle helmet use<br>32<br>Seat-belt use<br>Child restraint systems use<br>Post-crash response<br>Progress towards safe road use: summary<br>Section 4. Measures to strengthen road safety governance<br>Institutional management<br>Monitoring, evaluation, and data management<br>Section 5. The way forward<br>References<br>Annexes<br>Annex 1. Methodology<br>59<br>Annex 2. Progress towards the voluntary UN Performance Targets<br>Annex 3. Population covered by selected road safety-related measures<br>Annex 4. National vehicle and infrastructure laws and international<br>conventions or regulations<br>73<br>Annex 5. Example Country and territory profile template<br>74<br>Annex 6. Guide to Country and territory profiles<br>75 | Foreword | iv   |
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+
+## <span id="page-5-0"></span>Foreword
+
+![](_page_5_Picture_1.jpeg)
+
+*Our transport systems open the world to us, but they come with a tragic price.* 
+
+**Dr Tedros Adhanom Ghebreyesus** Director-General World Health Organization
+
+By the time you have read this page, at least five people will have died in road traffic crashes.
+
+Road crashes are the leading killer of children and youth, and they typically strike during our most productive years, causing huge health, social and economic harm throughout society.
+
+Yet this report offers hope, and points to a way forward.
+
+Since 2010, deaths from road crashes have fallen slightly to 1.19 million per year. More than half of all UN Member States, including some of the worst-affected countries, report a decline in deaths.
+
+These hard-won gains were made while much of the world was heading in the wrong direction.
+
+As motor vehicles proliferate, countries are doubling down on transport systems built for cars, not people, and not with safety at their core.
+
+This holds back efforts to save lives, protect the vulnerable and secure a sustainable future.
+
+Some of the greatest progress has been made where the safe system approach to road safety has been applied. This holistic approach to mobility puts people and safety front and centre.
+
+With a rapidly growing and increasingly urban population, it calls for a safe, efficient and sustainable mix of transport types, including mass public transport, while ensuring the safety of pedestrians, cyclists and other vulnerable road users, who account for half of all deaths. Building safe systems also benefits many more areas of health and development. By encouraging walking and cycling for example, we help reduce the burden of noncommunicable diseases, boost physical activity, strengthen access to jobs and education and help fight climate change.
+
+We know what works; political will must match the scale and urgency of this crisis.
+
+The Global Plan for the United Nations Decade of Action for Road Safety charts the way forward, and everyone has a role in making safe, clean, affordable and green mobility a reality.
+
+Governments must lead mobility strategies that are rooted in good data, backed by strong laws and funds, and that include all sectors of society. Businesses must put safety and sustainability at the core of their value chains. Academia and civil society must generate evidence and hold leaders to account. Youth can demand action and help take it.
+
+Safe mobility is a crucial aspect of the universal right to health, a fundamental right of every human. Mobility must not, and need not, come with a tragic cost in human lives.
+
+The decline in deaths shown in this report falls far short of what is needed to halve road traffic fatalities by 2030, which means the need for action is urgent, to realise the promise of safe and sustainable mobility, and a safer, healthier and better future.
+
+# Foreword
+
+![](_page_6_Picture_1.jpeg)
+
+Diseases and Injuries
+
+*It is encouraging to see more countries saving lives through safer street design, police enforcement, and paid media campaigns. Still, the scope of the problem is not receiving enough public attention.* 
+
+**Michael R. Bloomberg** Founder, Bloomberg L.P. & Bloomberg Philanthropies WHO Global Ambassador for Noncommunicable
+
+Our mission at Bloomberg Philanthropies is straightforward: to save and improve as many lives as possible. One of the most significant opportunities to do that is making more of the world's roads safer for drivers, passengers, cyclists, and pedestrians alike.
+
+This new report highlights how, over the course of more than a decade, we have made encouraging progress together with the World Health Organization and our road safety partners. Our focus is on low- and middleincome countries and cities, where 90 percent of traffic deaths occur. Since just 2018, 23 national governments have strengthened their laws to align with WHO's best practices.
+
+It is encouraging to see more countries saving lives through safer street design, police enforcement, and paid media campaigns. Still, the scope of the problem is not receiving enough public attention.
+
+Any life lost in a traffic crash is one too many – and, in 2021, more than one million people died on the world's roads. Road crashes are also the leading cause of death for children and young people 5 to 29 years old. As the world's population grows, and the demand for vehicles grows alongside it, ensuring that our roads are safe for all is becoming even more important.
+
+To meet our goal of cutting road deaths in half by the end of this decade, more governments need to take action. Only six countries have laws that meet WHO best practice criteria for addressing road safety's key risk factors. Fewer than 50 countries have policies that promote walking, cycling, and public transport – a glaring lack of investment in safe, sustainable mobility options. More countries also need to step up regulation of vehicle safety standards, which can protect everyone involved in a collision. Right now, nearly 80 countries have no laws at all on vehicle safety standards.
+
+As this report makes clear, faster progress on road safety requires stronger commitments from governments worldwide. Persuading more leaders of the urgent need for action will continue to be a major priority for us at Bloomberg Philanthropies – and we thank Dr. Tedros, WHO, and our global network of allies for their continued partnership in this lifesaving work.
+
+# <span id="page-7-0"></span>Acknowledgements
+
+The *Global status report on road safety 2023* benefited from the substantial intellectual contribution of many WHO staff and collaborators. At WHO headquarters´ Safety and Mobility Unit, Maria Segui-Gomez coordinated the technical concept, study design, data collection, data analysis, writing and review of the report. Fangfang Luo and Evelyn Murphy led and performed the legislation review. Kacem Iaych led the mortality estimation data analyses in collaboration with Bochen Cao, Doris Ma Fat and Wayno Retno Mahanani from the WHO Division of Data, Analytics and Delivery for Impact. Overall supervision was provided by Nhan Tran and Etienne Krug.
+
+Advisory Board members actively participated in the study design and the review of the report: Shrikant Bangdiwala, McMaster University, Canada; Said Dahdah, Global Road Safety Facility at the World Bank, Washington (DC), United States of America (USA); Jennifer Ellis, Bloomberg Philanthropies, New York, United States of America (USA); Eduard Fernandez, CITA – the International Motor Vehicle Inspection Committee, Brussels, Belgium; Floor Lieshout, Youth for Road Safety (YOURS), Culemborg, the Netherlands; John Milton, Road Safety Committee World Road Association (Permanent International Association of Road Congresses -PIARC), Paris, France; Fernanda Rivera, Road Safety and Sustainable Urban Mobility, Mexico City's Mobility Ministry; David Studdert, Stanford University, California, United States of America (USA) ; Claes Tingvall, Chalmers University of Technology, Gothenburg, Sweden, and Monash University Accident Centre in Melbourne, Australia; Geetham Tiwari, Transportation Research and Injury Prevention Centre, Delhi, India; and Nancy Vandyke, Infrastructure Global Practice, Transport at the World Bank Group, Washington (DC), USA.
+
+Data collection relied heavily on the collaboration of Member States and WHO regional personnel. Member State government officials supported the project and provided official clearance of data gathered and compiled by designated National Data Focal Points (names of National Data Focal Points are presented in the List of contributors) and approximately 800 or more collaborators. Country1 data delivery involved the use of a data entry platform and securing consensus among participants.
+
+Country-level participation was facilitated through the WHO designated Regional Data Focal Points who were responsible for training and supervision of country collaborators, and who also reviewed the report: Eunice Chomi and Idrissa Talla (African Region), Alessandra Senisse (Region of the Americas), Rania Saad (South-East Asia Region and Eastern Mediterranean Region), and Roseanne Vandermeer (Western Pacific Region). Further support at WHO regional level was provided by Binta Sako (African Region), Ricardo Pérez-Núñez (Region of the Americas), Tashi Tobgay (South-East Asia Region), Jonathon Passmore – who also acted as Regional Data Focal Point (European Region), Hala Sakr Ali (Eastern Mediterranean Region), and Fang Dan (Western Pacific Region).
+
+Additional data came from publicly available data sources and collaboration with others. WHO thanks Robert McInerney (iRoad Assessment Program London, United Kingdom of Great Britain and Northen Ireland); Uta Meesmann (VIAS Institute, Brussels, Belgium); and Susanna Zamataro (International Road Federation, Geneva, Switzerland). Walter Nissler (United Nations Economic Commission for Europe, Geneva, Switzerland) provided advice during the collection and interpreting of UN conventions and regulations.
+
+WHO also thanks the following consultants whose expert contributions made this document possible: Afef Ben Ghenaya, Aida Kaffel, and Maria Teresa Martin-Nájera for their support in reviewing and analysing legislative documents; Manuel Valdano (Universidad Pontificia de Comillas, Spain) for his assistance in data management. Angela Burton provided technical writing; Adappt provided the data entry platform and country and territory profile generation that made this document possible.
+
+WHO thanks Bloomberg Philanthropies for its generous financial support for the development of this report.
+
+<sup>1</sup> The terms "country" and "national" as used in the text of this publication should be understood to refer to countries, territories, and areas as well as national and local institutions, data, and information.
+
+# <span id="page-8-0"></span>List of contributors
+
+With thanks to the following contributors from across all WHO regions who acted as National Data Focal Points to coordinate country-level data entry to the *Global status report on road safety 2023* questionnaire:
+
+**African Region**: Alexis Abouna, Fatima Adamou, Gabriel Adu-Sarpong, Kahsay Araya, Ali Atouli, Irene Bagahirwa, Matos Celso, Ovost Chooye, Jean de Dieu Havyarimana, Fetiya Dedgba, Jean Dikiyi, Serge Elanda, Kedou Eyasema, Malick Fall, Gladwell Gathecha, Michael Gaye, Hassan Guire, Ismaël Hoteyi, Sydney Ibeanusi, Amadou Kamagate, David Kasembe, Mamoudou Keita, Abdoulaye Kone, Yankho Luwe, George Madeleine, Cristovao Manjuba, Celso Matos, Euridice Matsiengouni, Bethino Mbirimujo, Amos Motshegwe, Abdelhakim Nacef, Lee Nkala, Maria Nkalubo, Aimé Nkunku, Onwar Nyibong, Tsembayena Phakathi, Emmanuel Phasha, Maphahamiso Ralienyane, Sandra Rodrigues, Gaye Sulayman, Napoleão Sumbane, Harvindradas Sungker, Ousseynou Tall, Ambrose Tucker, Marie Venerozia, and Nina Yameogo.
+
+**Region of the Americas:** Valdimy Adolphe, Shalauddin Ahmed, Klever Almeida, Jorge Arce-Araya, Donna Bannister, Donna Barker, Paul Boase, Norberto Borba, Zane Castillo, Jesus Chaicoj, Joel Collazos-Carhuay, Jasson Cruz-Villamil, Ramona Doorgen, Erick Duron, Lloyd Hodson, Deidrie Hudson-Sinclair, Johanna Lakhisaran, Phil Leon, Kishon Leslie, Claudia Maldonado-Núñez, Carla Medina, Luiz Miranda, Silvia Moran, Paola Olmos-Rojas, Juan Palacios, Sergio Peralta-Medina, Adande Piggott, Yania Plá-Ramírez, Pablo Rojas, Mateo Terreo, Valarie Williams, Merissa Yellman.
+
+**South-East Asia Region**: Robed Amid, Dail Asri, Ramya Bandaranayaka, Sonam Choden, Nusaer Chowdhury, Heitor da Pereira, Akhmad Fais Fauzi, Shri Dinesh Kumar, Bhim Prasad Sapkota, Fathimath Shabana, Nongnuch Thanthithum, and Maung Maung Toe.
+
+**European Region**: Bayonzoda Jamalidin Bayoni, Adrian Bedaj, Sinead Bracken, Ivana Brkic, Patrick Cachia, Rute Isabel Calheiros, Tamar Chachava, Vladislav Cojuhari, Peter Csizmadia, Miroslav Djeric, Charis Evripidou, Tomas Fredlund, Álvaro Gómez-Méndez, Anders Møller Gaardbo, Stratos Georgiopoulos, Yuri Gnedko, Gunnar Geir Gunnarsson, Tolga Hakan, Bakhish Hasanli, Akmal Ikromov, Kjell Jacobs, Jānis Kalniņš, Slavomir Kral, Maria Giuseppina Lecce, Peter Mak, Milen Markov, Nurian Moldaliev, Andraz Murkovic, Artemis Olavesen, Maria Pashkevich, Riikka Rajamäki, Sergey Alexandrovich Ryzhov, Manuelle Salathe, Arman Sargsyan, Karin Schranz, Yanik Scolastici, Boranova Aktoty Sermakhankyzy, Assaf Sharon, Przemyslaw Skoczynski, Renata Slaba, Thomas Spillmann, Svetlana Stojanovic, Milan Tesic, Fimka Tozija, Matthew Tranter, Raschid Urmeew, Harry Winkler, and Ingrida Zurlyte.
+
+**Eastern Mediterranean Region**: Hayat Ahmed Mohammed Abdullah, Hameed Akhtar, Mooath Mohammed Aldossari Tasneem Alfadil, Haya Alhammad, Sana Alkhawada, , Mansour Hassan Ali, Ahmed Bardan, Henda Chebbi, Okasneem Elfadil, Amani Elkhatim, Ziad Khalid Gabar, Taufik Hasaba, Ibrahim Jabeal, Fuad Al Maaytah, Suliman Al Mahrazi, Loubana Maazouri, Mohieldin Hassan Haj Hamad Mohammed, Noha Moussa, Mohammed Qais Niazai, Farah Nuh, Hamid Qahil Al Otiby, Wafa Said, Ramzi Salamé, and Hormoz Zakeri.
+
+**Western Pacific Region**: Josephine Afuamua, Enkhbold Anjim, Jarizza Mae Biscante, Leilei Duan, Mark Ellis, Paul Graham, Joonbum Lim, Lay Tin Ong, Noor Raihan Khamal, Ean Sokoeu, Daolueang Syhaphon, Mweritonga Temareti, Huu Minh Tran, Nuhisifa Williams, Timothy Wilson, and Yukiko Yamaguchi.
+
+National Data Focal Points for the participating territories were Kishon Leslie and Imad Masri.
+
+<span id="page-9-0"></span>![](_page_9_Picture_0.jpeg)
+
+# Executive summary
+
+There were an estimated 1.19 million road traffic deaths in 2021 – a 5% drop when compared to the 1.25 million deaths in 2010. More than half of all United Nations Member States reduced road traffic deaths between 2010 and 2021. The slight overall reduction in deaths occurred despite the global motor vehicle fleet more than doubling, road networks significantly expanding, and the global population rising by nearly a billion. This shows that efforts to improve road safety are working but fall far short of what is needed to meet the target of the United Nations Decade of Action for Road Safety 2021–2030 to halve deaths by 2030.
+
+Road traffic deaths and injuries remain a major global health and development challenge. As of 2019, road traffic crashes are the leading killer of children and youth aged 5 to 29 years and are the 12th leading cause of death when all ages are considered. Two-thirds of deaths occur among people of working age (18– 59 years), causing huge health, social and economic harm throughout society.
+
+More than half of fatalities are among pedestrians, motorcyclists and cyclists. Occupants of 4-wheel vehicles account for almost one-third of fatalities. Occupants of vehicles carrying more than 10 people, heavy goods vehicles and "other" users constitute one-fifth of all deaths. Micro-mobility modes such as e-scooters account for 3% of deaths.
+
+Vulnerable road users such as pedestrians, cyclists and motorcyclists remain dangerously exposed. Nearly 80% of all roads assessed do not meet a minimum 3-star rating for pedestrian safety, and as cyclist fatalities increase, just 0.2% of all roads assessed have cycle lanes.
+
+Nine in 10 deaths occur in low- and middleincome countries, while people in low-income countries continue to face the highest risk of death per population. Globally, 28% of all fatalities occur in the WHO South-East Asia Region, 25% in the Western Pacific Region, 19% in the African Region, 12% in the Region of the Americas, 11% in the Eastern Mediterranean Region, and 5% in the European Region.
+
+The European Region reports the largest drop in deaths since 2010 – a 36% decline. The Western Pacific Region reports a 16% decline, the South-East Asia Region a 2% decline and the number of deaths has remained constant in the Region of the Americas. Reductions in the number of deaths were observed in 108 countries, including 10 where the 50% was achieved by 2021. However, in 66 countries there was a rise; 28 of these countries are in the African Region, which has seen a 17% rise in the number of deaths since 2010.
+
+Measures to mitigate the risk of death and injury, including enacting laws that meet WHO best practices, have advanced modestly. Policy-makers have known of the key risk factors that contribute to road crashes for decades, yet only six countries have reached WHO best practice legislation on five risk factors – speeding, drink driving, motorcycle helmet use, and seat-belts and child restraint systems.
+
+With a growing and increasingly urban global population, the rising demand for mobility is set to overwhelm transport systems, particularly those that rely heavily on private vehicles. Yet many countries continue to design and build their mobility systems for motor vehicles, not for people, and not with safety as the main concern. This slows efforts to save lives and to protect vulnerable road users.
+
+Some of the greatest gains have been made where the safe system approach to road safety – which puts people and safety at the core of mobility systems – is most widely applied. The European Region has the greatest concentration of countries with policies and legislation that align with this approach and reports the largest drop in deaths. The Western Pacific Region is second, both in the number of countries adopting aspects of the safe system approach and in reducing fatalities. These examples show that fatality reduction targets can be met, given a level of political will, investment and capacity that matches the scale of the road death and injury crisis.
+
+## <span id="page-12-0"></span>Introduction
+
+This *Global status report on road safety 2023* (the fifth edition since 2009) *[\(1](#page-64-1)[–4\)](#page-64-2)* presents findings from a unique vantage point on the road to safe mobility: it provides the first complete overview of progress made during the Decade of Action for Road Safety 2011–2020 *([5\)](#page-64-3)* and sets a baseline for the Decade of Action for Road Safety 2021–2030 *([6](#page-64-4))*. This report looks at how and where the burden is changing and at how we are responding. Its specific objectives are to:
+
+- describe the road safety situation in United Nations (UN) Member States and assess changes since the publication of previous versions of this report, with a particular focus on the evolution of the burden and responses since 2010;
+- evaluate gaps in road safety nationally to stimulate action;
+- inspire research on road safety implementation decision-making; and
+- strengthen the network of individuals working on road safety around the world.
+
+This report addresses the UN General Assembly Resolutions to monitor progress in the reduction of deaths and nonfatal injuries in countries *[\(2,](#page-64-5) [6\)](#page-64-4)*. Individual Country or territory profiles for all 194 countries and two territories that volunteered their data are available in a companion report to this publication *([7\)](#page-64-6)*.
+
+## **A note on methodology**
+
+The findings of this report are based mainly on a survey and review of legislation in which 170 UN Member States and two territories participated. For the 24 Member States not participating in this report, the most recent data from previous surveys are used in their Country Profiles. The methodology used is described in Annex 1. Progress against the voluntary UN Performance Targets is set out in Annex 2. The percentage of the world population covered by selected road safety laws (in 2022) is set out in Annex 3. The relationship between national legislation and adherence to related UN conventions or regulations is set out in Annex 4. Annex 5 presents the template used in the Country and Territory Profiles and Annex 6 presents the operational definitions used to produce them. This report is accompanied by a summary version *[\(8](#page-64-7))*; a Country and territory profile report; and the World Health Organization (WHO) Road Safety Data mobile application *([9\)](#page-64-8).* Documents, individual country and territory profiles, and data can be accessed in multiple languages [ht t p s : //w w w.w h o. i nt / t e a m s /s o c i a l](https://www.who.int/teams/social-determinants-of-health/safety-and-mobility/global-status-report-on-road-safety-2023)  [determinants-of-health/safety-and-mobility/](https://www.who.int/teams/social-determinants-of-health/safety-and-mobility/global-status-report-on-road-safety-2023) [global-status-report-on-road-safety-2023.](https://www.who.int/teams/social-determinants-of-health/safety-and-mobility/global-status-report-on-road-safety-2023)
+
+The report incorporates WHO generated mortality estimates; a legislation review conducted by WHO legal experts based on the survey, augmented by a review of original legislation to assess whether legislation meets WHO best practice criteria.
+
+Mortality estimates for all causes of death are updated periodically by the WHO Division of Data, Analytics and Delivery for Impact (WHO DDI) *[\(10\)](#page-64-9)*. As more data are submitted by countries and territories to WHO DDI, mortality estimates for all causes are updated retrospectively. Thus, total fatality numbers set out by year in Fig. 5 do not necessarily correspond to the estimates published in previous reports. The revised mortality estimates for the previous years are as follows: 1.21 million for 2016, 1.25 million for 2013, 1.26 million for 2011, and 1.26 million for 2007.
+
+![](_page_13_Picture_0.jpeg)
+
+<span id="page-14-0"></span>![](_page_14_Picture_0.jpeg)
+
+# The global burden of road traffic deaths
+
+![](_page_14_Picture_2.jpeg)
+
+There were an estimated 1.19 million road traffic deaths in 2021; this corresponds to a rate of 15 road traffic deaths per 100 000 population.
+
+![](_page_14_Picture_4.jpeg)
+
+As of 2019, road traffic injury remains the leading cause of death for children and young people aged 5–29 years and is the 12th leading cause of death when all ages are considered.
+
+![](_page_14_Picture_6.jpeg)
+
+Globally, 4-wheel vehicle occupants represent 30% of fatalities; followed by pedestrians who make up 23% of fatalities; and powered two- and three-wheeler users who make up 21% of fatalities.
+
+![](_page_14_Picture_8.jpeg)
+
+Cyclists account for 6% of fatalities while 3% of deaths are among users of micro-mobility devices such as e-scooters.
+
+![](_page_14_Picture_10.jpeg)
+
+92% of deaths occur in low- and middle-income
+
+![](_page_14_Picture_12.jpeg)
+
+The risk of death is three times higher in low-income countries than high-income countries despite these countries having less than 1% of all motor vehicles.
+
+## There were an estimated 1.19 million road traffic deaths in 2021; this corresponds to a rate of 15 road traffic deaths per 100 000 population.
+
+There were an estimated 1.19 million road traffic deaths in 2021; this corresponds to a rate of 15 road traffic deaths per 100 000 population. Based on 2019 data on the age distribution of all-cause mortality, road traffic injury remains the leading cause of death for children and young people aged 5–29 years and is the 12th leading cause of death when all ages are considered *[\(11\)](#page-64-10)* (Table 1).
+
+As a leading cause of death and major contributor to disability, road traffic injuries also impose an enormous economic cost on societies. Some estimates put the global macroeconomic cost of road traffic injuries as high as US\$ \$1.8 trillion<sup>2</sup> , roughly equivalent to 10–12% of global gross domestic product (GDP) *([12](#page-64-11))*. As such, road traffic injuries are an important health and development challenge.
+
+Table 1. Leading causes of death, all ages, and ages 5–29 years, 2019
+
+| Rank | All ages                                | Ages 5–29 years              |
+|------|-----------------------------------------|------------------------------|
+| 1    | Ischaemic heart disease                 | Road Injury                  |
+| 2    | Stroke                                  | Tuberculosis                 |
+| 3    | Chronic obstructive pulmonary disease   | Diarrhoeal diseases          |
+| 4    | Lower respiratory infections            | Interpersonal violence       |
+| 5    | Neonatal conditions                     | Self-harm                    |
+| 6    | Trachea, bronchus, lung cancers         | HIV/AIDS                     |
+| 7    | Alzheimer´s disease and other dementias | Lower respiratory infections |
+| 8    | Diarrhoeal diseases                     | Maternal conditions          |
+| 9    | Diabetes mellitus                       | Drowning                     |
+| 10   | Kidney diseases                         | Cirrhosis of the liver       |
+| 11   | Cirrhosis of the liver                  | Malaria                      |
+| 12   | Road injury                             | Meningitis                   |
+
+*Source:* Adapted from: *[11](#page-64-10))*
+
+<sup>2</sup> For the period 2015–2030 using 2010 constant USD\$
+
+<span id="page-16-0"></span>In addition to being the leading killer for children and young adults, road traffic deaths impact people during their most productive years. Approximately 66% of fatalities are among people aged 18–59 years and 19% are aged 60 years or above. Road traffic deaths continue to disproportionately impact men, with an overall female-to-male fatality ratio of 1 to 3.
+
+The importance of deaths among people of working ages and the disproportionate impact on males is also reflected in data on work-related driver deaths available from 21 countries. In these countries, approximately 23% of driver deaths relate to trips to or from work (e.g., commuters); 16% of deaths result from work-related driving (e.g., deliveries and appointments); and an additional 12% of deaths are among (disproportionately male) professional drivers "at work" (e.g., bus drivers).
+
+## **Fatalities by road user type**
+
+Globally, occupants of 4-wheel vehicles represent 30% of fatalities; followed by pedestrians who represent 23% of fatalities; and powered two- and three-wheeler users make up 21% of fatalities. Cyclists account for 6% of fatalities. Occupants of vehicles carrying more than 10 people, heavy goods vehicles, "other" users and "unknown" user types comprise the remaining 20% of deaths. Given the rise in powered personal micromobility modes such as e-scooters, questions on these modes of transport were newly included in the survey for this report, and reveal that globally, 3% of deaths are among users of these modes (which are included in the "other" road user category).
+
+The distribution of deaths among road users changes significantly, however, when data are disaggregated by region. As shown in Fig. 1, except for the European Region and Eastern Mediterranean Region (where occupants of 4-wheel vehicles comprise the largest share of the deaths at 49% and 33% respectively), in most regions, it is pedestrians and powered two- and three-wheelers users that make up the majority of deaths. In the Western Pacific Region, pedestrians comprise the largest share of fatalities while in the South-East Asia Region, cyclists account for 12% of all deaths. This is especially concerning given that pedestrians and cyclists tend to be the most vulnerable road users and, in most countries, represent the economically most disadvantaged *([13](#page-64-12))*.
+
+**Fig. 1. Percentage distribution of country-reported deaths by road user type and WHO region, 2021** 
+
+![](_page_17_Figure_1.jpeg)
+
+## <span id="page-18-0"></span>**Fatality counts and rates, by region and country-income level**
+
+The vast majority of road traffic deaths, 92%, occur in upper-middle, lower-middle, and low-income countries combined. Seventynine percent of road traffic deaths occur in lower-middle-income countries and uppermiddle-income countries combined (44% and 35% respectively), with low-income countries accounting for 13%, and high-income countries accounting for the remaining 8%.
+
+Relative to the size of countries' motor vehicle fleets and road networks, there is a disproportionately high number of fatalities in low- and middle-income countries compared to high-income countries. For example, highincome countries have 16% of the world's population, 28% of the world's vehicle fleet, 88% of all paved inter-urban roads, and 8% of fatalities; by contrast, low-income countries have 9% of the world's population, less than 1% of the world's powered vehicle fleet and paved inter-urban roads, yet 13% of fatalities. (Fig. 2).
+
+In terms of absolute numbers, the highest number of fatalities occur in the South-East Asia Region (330 222 deaths, or 28% of the global burden), followed by the Western Pacific Region (297 733 deaths, or 25% of the global burden); the African Region (225 482 deaths, or 19% of the global burden); the Region of the Americas (144 090 deaths, or 12% of the global burden); the Eastern Mediterranean Region (125 781 deaths, or 11% of the global burden); and the European Region (62 670 deaths, or 5% of the global burden) (Fig. 3).
+
+Fig. 2. Share of global population, road traffic deaths, paved inter-urban roads, and registered motor vehicles, by country income level, 2021
+
+![](_page_18_Figure_6.jpeg)
+
+Excludes expressways
+
+![](_page_19_Figure_0.jpeg)
+
+![](_page_19_Figure_1.jpeg)
+
+Fatality rates are highest among low-income countries, at 21 deaths per 100 000 population, and lowest in high-income countries, at eight deaths per 100 000 population (Fig. 4). Uppermiddle-income and lower-middle-income countries both have fatality rates of 16 per 100 000 population.
+
+The African Region has the highest fatality rate at 19 deaths per 100 000 population, and the European Region has the lowest fatality rate at seven deaths per 100 000 population. For the other WHO regions, fatality rates per 100 000 population are 16 in both the Eastern Mediterranean Region and in the South-East Asia Region, 15 in the Western Pacific Region, and 14 in the Region of the Americas.
+
+Within regions, the same correlation between income level and fatality rates can be observed, with fatality rates highest in lowincome countries and lowest in high-income countries in all regions. In some regions, such as in the Region of the Americas, the differences between the rates are not as significant, but in others, such as the Eastern Mediterranean Region, fatality rates in the region's low-income countries are nearly double those of its high-income countries (Fig. 4).
+
+**Fig. 4. Road traffic fatality rate per 100 000 population by WHO region and country income level, 2021**
+
+![](_page_20_Figure_1.jpeg)
+
+![](_page_21_Picture_0.jpeg)
+
+## **The voice of youth:**
+
+Raquel Barrios, Executive Director, YOURS – Youth for Road Safety
+
+Road traffic crashes have been the leading killer of youth for over a decade, and despite being the largest generation of youth in history, young people's voices are rarely heard when it comes to designing road safety policies. So it should be no surprise that many young people do not trust policy-makers.
+
+Meaningful youth participation requires a shift in mindset. Moving beyond the idea that youth are beneficiaries, we need a big change in how we work to ensure that young people's experiences, ideas, expertise and perspectives are fully and systematically integrated into all programmatic, policy-, and decision-making processes.
+
+Here are just some of the ways youth can boost road safety:
+
+As active road users, youth can ensure that their behaviours are supportive of safety as well as bring their needs to the table and support the design of effective policies around urban planning and sustainable cities.
+
+As out-of-the-box thinkers, they bring creativity and innovation to tackle the most pressing issues.
+
+As millennials and centennials, they are leading the digitalization movement and the adoption of technology for greater efficiency.
+
+As change-makers, youth bring energy and flexibility and put their time, skills, and resources into community development initiatives, which could strengthen road safety.
+
+As fearless advocates, youth can push for road safety to find a place on many agendas and be vocal about the crucial role of road safety in achieving all of the Sustainable Development Goals.
+
+Road safety is key to building a healthy, inclusive, sustainable and safe environment for everyone, so we must promote road safety in all areas of development to bring more action, more investment and more resources to help reduce road crash deaths and injuries.
+
+Youth must always be at the table; their involvement in the entire cycle of road safety policies, from design to implementation and monitoring and evaluation is essential. Governments must realize the potential of intergenerational collaboration and its dynamism to save more lives on the roads.
+
+![](_page_23_Picture_0.jpeg)
+
+<span id="page-24-0"></span>![](_page_24_Picture_0.jpeg)
+
+# How the burden and context have evolved
+
+![](_page_24_Picture_2.jpeg)
+
+Globally, the number of road traffic deaths has fallen 5% since 2010.
+
+![](_page_24_Picture_4.jpeg)
+
+The global fatality rate per 100 000 population has fallen 16% since 2010 when set against the 13% rise in global population.
+
+![](_page_24_Picture_6.jpeg)
+
+The global fatality rate per 100 000 vehicles has fallen 41% since 2010 when set against the 160% increase in the global motor vehicle fleet.
+
+![](_page_24_Picture_8.jpeg)
+
+The global share of fatalities has fallen 1% among 4-wheel vehicle users and 2% among two- and three-wheeler users since 2010 but has risen from 5% to 6% among cyclists.
+
+![](_page_24_Picture_10.jpeg)
+
+In 108 countries, reductions in fatality counts between 2010 and 2021 were observed, including, for the first time, low-income countries.
+
+![](_page_24_Picture_12.jpeg)
+
+10 countries in four regions achieved the target of a 50% reduction in road traffic deaths between 2010 and 2021.
+
+## When compared to the estimated 1.25 million road traffic deaths in 2010, the current figure of 1.19 million for 2021 represents a reduction of 5%.
+
+Since the start of the Decade of Action for Road Safety 2011–2020 there have been significant rises in the global population *[\(14](#page-64-13))*, the number of powered vehicles *[\(15\)](#page-64-14)*, and the size of the world's road networks *[\(16\)](#page-64-15)*. Rapidly evolving technology, increasing population density and growth in urban areas, along with the emergence and growing presence of micro-mobility and use of mobility services, are some of the challenges affecting the burden of road traffic injuries in the past decade.
+
+When compared to the estimated 1.25 million road traffic deaths in 2010, the current figure of 1.19 million for 2021 represents a reduction of 5%. After the start of the Decade of Action for Road Safety 2011–2020, the number of road traffic deaths peaked in 2012 (at 1.26 million). This was followed by a gradual decline that started in 2013 and continues until 2021. The predominantly steady downward trend since 2010 contrasts with the gradual upward trend during the 10-year period prior to the Decade of Action for Road Safety 2011–2020 (Fig. 5). The current estimates are now close to those in 2000, at the start of the upward trend.
+
+The only notable exception to these gradual shifts can be seen in 2020, when the Coronavirus disease of 2019 (COVID-19) related confinement policies restricted mobility, and fatalities significantly, if temporarily, declined.
+
+Fig. 5. WHO estimated number of road traffic fatalities, 2000–2021
+
+![](_page_25_Figure_6.jpeg)
+
+As discussed, the period 2010–2021 saw a 5% reduction in absolute numbers of road traffic fatalities, and it also saw the global population grow by nearly 1 billion *([14](#page-64-13))* or roughly 13%. When this growth in population is considered, the road traffic fatality rate has also declined – from nearly 18 per 100 000 people in 2010 to the current estimate of 15 per 100 000 people in 2021. This represents a 16% fall in the death rate since 2010 (Fig. 6).
+
+Similarly, the period 2011–2020 saw the global motor vehicle fleet burgeon, with countries reporting a 160% increase since 2010. Four wheel vehicles comprise 85% of the world's motor vehicle fleet, with powered twoand three-wheelers accounting for the next largest share at 12%. Powered two- and three-wheelers have Fig.6. WHO-estimated global fatality rates relative to population and powered vehicle eet, by year, 2010–2021
+
+nearly tripled in number, with a 175% increase since 2011. The global increase is driven by the South-East Asia Region with a 273% increase, the Region of the Americas with a 217% increase, the Western Pacific Region with a 155% increase and the European Region with a 142% increase. This growth corresponds to data from the International Road Federation which shows an increase in road density worldwide, but especially in the African and the Western Pacific Region *([17\)](#page-64-16).*
+
+Against this backdrop, a substantial decline can be seen in annual fatality rates per 100 000 vehicles, from 79 deaths per 100 000 vehicles in 2010 to 47 deaths per 100 000 vehicles in 2021 – a 41% reduction (Fig. 7).
+
+Fig. 6. WHO estimated global road traffic fatality rates per 100 00 population, 2010–2021
+
+![](_page_26_Figure_5.jpeg)
+
+Fig. 7. WHO estimated global road traffic fatality rates per 100 000 vehicles, 2010–2021
+
+![](_page_26_Figure_7.jpeg)
+
+<span id="page-27-0"></span>The impact of increased levels of motorization are reflected in changes in the relative shares of deaths among user types. Comparisons with the *Global status report on road safety 2013* reveal modest overall changes in the total share of road traffic deaths by user type, with reductions of 1% for 4-wheel vehicle occupants and 2% for users of powered two- and three-wheelers. These overall changes hide more significant changes by WHO region. For example, fatalities among powered two- and three-wheeler users have reduced their share of total deaths by 5% in the Eastern Mediterranean Region and 20% in the Western Pacific Region but have increased their share by 4% in the European Region; 11% in the African Region; 13% in the Region of the Americas; and 15% in the South-East Asia Region.
+
+And compared to the *Global status report on road safety 2013*, the number of cyclist deaths has risen from 5% of all fatalities in 2010 to a current estimate of 6%, representing a 20% rise. This increase is particularly prominent in the South-East Asia Region and the European Region where the proportion of cyclist road traffic deaths rose from a reported 4% in each region in the *Global status report on road safety 2013*, to current shares of 12% and 9% – an increase of 200% and 125% respectively.
+
+Emerging evidence from some countries suggests this increase in cyclist fatalities is due in part to the electrification of bicycles which has resulted in increased ridership in cities that often lack adequate cycling infrastructure. In some countries, there has been an increase in e-bike use among older populations who are especially vulnerable to serious injury and death in the event of road crashes. These examples illustrate the importance of monitoring and conducting research on how new technological innovations are adopted within the transport system and their impact on safety.
+
+## **Progress toward the target of a 50% reduction in deaths**
+
+While the global target to halve road traffic deaths from the baseline set by the Decade of Action for Road safety 2011–2020 was not met globally, at the end of 2021,3 10 countries from four different regions achieved the target reduction of at least 50% in their fatality numbers: Belarus, Brunei Darussalam, Denmark, Japan, Lithuania, Norway, Russian Federation, Trinidad and Tobago, United Arab Emirates, and Venezuela (Bolivarian Republic of) *([5\)](#page-64-3).* (For more on the impact of the COVID-19 pandemic on fatalities in Europe, see Box 1).
+
+In addition to the 10 countries where the target of a 50% reduction in deaths was met, reductions of 40–49% were observed in 15 countries, of 30–39% in 20 countries, of 20–29% in 33 countries, and of 10–19% in 19 countries. An additional 11 countries achieved reductions of 2–9%.
+
+Overall, during this period, reductions larger than 2% were observed in 108 countries – nearly half of which are high income. Reductions have been observed in eight lowincome countries (Fig. 8).
+
+<sup>3</sup> Due to the restrictions on mobility as a result of the COVID-19 pandemic, there was a temporary reduction in the number of deaths in 2020; for this reason, 2021 is the year used to assess progress towards the Decade of Action for Road Safety 2011–2020.
+
+Fig. 8. Number of countries where a change in total road traffic deaths has been observed, by region and country income level, 2010–2021<sup>4</sup>
+
+![](_page_28_Figure_1.jpeg)
+
+<sup>4</sup> This excludes small countries with a population of less than 200 000 that have 1–2 deaths annually; this small number makes it impossible to assess meaningful reductions over time.
+
+![](_page_29_Figure_0.jpeg)
+
+![](_page_29_Figure_1.jpeg)
+
+These reductions have been observed across four regions, ranging from a 36% decrease in the European Region to a 0.1% decrease in the Region of the Americas, a 2% reduction in the South-East Asia Region (even though the South-East Asia Region has the highest death rates and numbers overall); and a decrease of 16% in the Western Pacific Region. In contrast, the number of deaths rose in 66 countries, of which 28 are in the African Region (where there was an overall increase of 17% in the number of fatalities); 20 in the Region of the Americas; eight in the Eastern Mediterranean Region (where there was an overall increase of less than 1% in the number of fatalities); four in each of the European Region and the South-East Asia Region; and two in the Western Pacific Region (Fig. 9).
+
+Some of the greatest gains were made where the safe system approach to road safety – which puts people and safety at the core of mobility systems – was most widely applied. The results of this report demonstrate that the European Region saw the greatest concentration of countries with policies and legislation that align with this approach and reported the largest drop in deaths. The Western Pacific Region came second, both in the number of countries adopting aspects of the safe system approach and reducing fatalities. These examples show that fatalityreduction targets can be met, given a level of political will, investment and capacity that matches the scale of the road death and injury crisis.
+
+### Box 1: COVID-19, mobility and political decision-making
+
+## Road traffic deaths fell 13% in European Region in 2020 as consequence of rapid government COVID-19 restrictions.
+
+![](_page_30_Picture_2.jpeg)
+
+Research shows that the COVID-19 pandemic response had a significant impact on mobility *([18\)](#page-64-17).* Pandemic related restrictions on movement cut exposure to road crash risks, and this was reflected in reduced rates of road trauma. More significantly for policy-making, mobility patterns also responded to restrictions (and to fears of exposure to infection) more flexibly than might have been expected. Active mobility replaced motorized transport, with cycling in particular substituting for public transport and cars. Many local governments were quick to accommodate the change, reallocating road space to accommodate safe cycling. Many of the temporary protected cycle lanes have been retained and the stimulus to investment in infrastructure for active mobility has radically changed mobility patterns in many cities towards more sustainable mobility.
+
+The strictness of COVID-19 restrictions was monitored by the United Kingdom's Oxford University Governmental Response tracker. Its stringency index was highest for most countries near the beginning of the pandemic and fluctuated thereafter according to the number of COVID-19 cases and casualties. All countries saw a fall in traffic volumes from March 2020. In Europe, April saw traffic fall by over a third in countries reporting monthly vehicle-kilometre data.
+
+Overall for the year, the 17 countries<sup>5</sup> with consistent data recorded a 13% decrease in traffic volume compared to the average for 2017–2019. These countries recorded an overall reduction in road deaths of 16% compared to the 2017–2019 baseline. Twenty-five members of the WHO European Region also report validated data to the International Transport Forum's International Traffic Safety Data and Analysis (IRTAD) group. For these countries6 the number of road deaths decreased by an average of 18% in 2020 compared to the 2017–19 baseline. There are substantial differences between countries, but the majority saw a reduction in fatalities of around 20%.
+
+Young people and older people over the age of 75 years were the two age-groups recording the largest reductions in road deaths, with falls of 25% and 19% respectively, on average (for the 25 countries minus the Netherlands (Kingdom of the)). This relates to the closing of educational institutions for the young and particularly restricted mobility for older people who were among the most vulnerable to COVID-19.
+
+All transport modes saw reduced fatalities, 24% for pedestrians, 16% for powered two-wheelers and 20% for car occupants. The shift to cycling in lockdown periods made the reduction in the number of cyclist fatalities less than for other road users, with a decrease of only 2% for the 25 countries in 2020 compared to baseline years. Changes in fatalities should also be viewed in light of exposure to crash risks, for example in relation to kilometres driven or walked. Available data are insufficiently differentiated between modes to draw conclusions.
+
+<sup>5</sup> Austria, Czechia, Denmark, Finland, France, Germany, Hungary, Iceland, Ireland, Israel, Netherlands (Kingdom of the), Norway, Poland, Slovenia, Sweden, Switzerland, the United Kingdom.
+
+<sup>6</sup> Austria, Belgium, Czechia, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Lithuania, Luxembourg, Netherlands (Kingdom of the), Norway, Poland, Portugal, Serbia, Slovenia, Spain, Sweden, Switzerland, the United Kingdom.
+
+![](_page_31_Picture_0.jpeg)
+
+<span id="page-32-0"></span>![](_page_32_Picture_0.jpeg)
+
+# Measures to mitigate the risk of death and injury
+
+![](_page_32_Picture_2.jpeg)
+
+Most people identify as pedestrians and public transport users, yet only 47 countries have policies to promote walking, cycling, and public transport.
+
+![](_page_32_Picture_4.jpeg)
+
+Nearly 80% of the roads assessed do not meet a minimum 3-star rating for pedestrian safety and just 0.2% of the roads assessed have cycle lanes.
+
+![](_page_32_Picture_6.jpeg)
+
+Only 35 countries have legislation mandating all five core areas of vehicle safety equipment while 79 countries have no legislation on vehicle safety standards.
+
+![](_page_32_Picture_8.jpeg)
+
+As of 2022, 140 countries have legislation meeting WHO best practice for at least one of the five key risk factors,<sup>7</sup> although only six countries have legislation on all five that meet WHO best practice criteria.
+
+![](_page_32_Picture_10.jpeg)
+
+Since the *Global status report on road safety 2018,* 23 countries have modified their laws to align with WHO best practice: speeding *[\(8](#page-64-7));* drink driving *([3\)](#page-64-18),* motorcycle helmets *([5\)](#page-64-3);* seat-belts *[\(11](#page-64-10));* and child restraint systems *[\(4\)](#page-64-2).*
+
+![](_page_32_Picture_12.jpeg)
+
+131 countries have national legislation mandating thirdparty liability insurance for vehicles.
+
+![](_page_32_Picture_14.jpeg)
+
+Only 25 countries mandate provision of psychological assistance to road traffic crash victims and their families.
+
+<sup>7</sup> Speeding, drink driving, motorcycle helmet use, seat-belts, and child restraint systems.
+
+## <span id="page-33-0"></span>**Multimodal transport**
+
+About 60% of the global population is expected to live in urban settings by 2030 *[\(19\)](#page-64-19)*, meaning that increased demand for mobility will exceed the capacity of most current systems in these areas. Mobility needs and the systems to fulfil them must continue to evolve in response to opportunities created by technological innovations as well as challenges such as the impact of transport on climate change as well as road traffic death and injury (see Box 2 for an example on mobility as a right in Mexico).
+
+Information on transport mode use in a recent survey of 48 countries *[\(20\)](#page-65-0)* shows that most people in these countries see themselves, at one time or another, as pedestrians (with percentages close to 95% in all regions except the Region of the Americas, where 85% of the population recognized themselves as pedestrians). The next most common user category is public transport user (between 68% and 96%, depending on region). Around 93% of people across all regions see themselves, at one time or another, as a car passenger, while identifying as a car driver is reported by between 67% and 81% of individuals, depending on region. Identifying as a motorcycle rider or passenger is reported by between 41% and 72% of people. While these findings underscore the importance of active modes of transport, particularly considering the mental and physical health benefits associated with their use *([21\)](#page-65-1)*, the increasing proportion of deaths among pedestrians and cyclists observed over the past decade is cause for concern.
+
+Despite the potential benefits of multimodal transport and the need to ensure that vulnerable road users are equally protected as other road users (including those in passenger vehicles), few countries to date have systematically assessed multimodal transport planning as part of their road safety strategies. To assess the status of data collection on multimodal transport, countries were asked if they tracked the frequency and distribution of trips by mode of transport. About a quarter of all countries report collecting data on transport modes. Forty-two countries have data on the use of passenger (4-wheel) vehicles; 30 countries report collecting data on walking or cycling, and 10 collect data on the use of powered two- and three-wheelers and other personal mobility devices. Data on publicly operated transport is available in 54 countries.
+
+## **Legislation, policies, plans and strategies related to multimodal transport use**
+
+While no countries report legislation related to multimodal transport use, 87 report national strategies to promote access to, and use of, public transport. Forty-seven countries report national policies and strategies to promote walking and cycling. According to the 2022 WHO *Global status report on physical activity [\(21\)](#page-65-1),* approximately three quarters of all countries conduct national surveillance of physical activity – including walking and cycling among adults, adolescents and children.
+
+### <span id="page-34-0"></span>Box 2: Safe mobility as a right, Mexico
+
+In 2020 Mexico established a fundamental constitutional right: the right of everyone to safe, accessible, efficient, sustainable, inclusive and equitable mobility. This marked an important milestone in the country's approach to road safety and sustainable mobility.
+
+The General Law on Mobility and Road Safety, which sets out this new constitutional right, recognizes the need to protect vulnerable road users such as pedestrians, cyclists and motorcyclists, and defines which sectors are involved in the promotion of road safety and sustainable mobility. Reflecting this comprehensive and collaborative approach, in October 2022 the National Mobility and Road Safety System was established to coordinate related activity across Mexico's government and civil society.
+
+And in October 2023 the government published its National Strategy for Mobility and Road Safety 2023–2042, presenting a long-term vision for
+
+![](_page_34_Picture_4.jpeg)
+
+the development of mobility and road safety that embraces all of the values enshrined in the law, from accessibility to equity. The new constitutional right was made possible partly by the active and constant participation of civil society, which helped push safe mobility up the political agenda.
+
+However, there are hurdles to realizing the law, such as adequate resource allocation and the inclusion of mandatory vehicle insurance; vehicle safety (an essential aspect that was not comprehensively addressed in the Law), and the need for continuous leadership and accountability. To achieve this, the participation of all sectors and institutions linked to the issue is necessary – especially civil society, which has an essential role in the process.
+
+Finally, there is the challenge of guaranteeing state level regulations and standards, since the General Law covers all recommendations at the federal level. Municipal and state level competencies require special attention to ensure effective and homogeneous implementation of road safety policies.
+
+## **Safe road infrastructure**
+
+Safe road infrastructure is key for safety. Road infrastructure should be designed and operated to eliminate or reduce risks for all road users (see Box 3 for an example in Indonesia). In addition to improving safety, road infrastructure can enhance accessibility, including for persons with disabilities, and facilitate transfers from one transport mode to another. Infrastructure safety can be maximized for new roads as well as existing roads.
+
+Despite this, the results of the survey for this report indicate that (where audited) most roads continue to be built for the growing motor vehicle fleet. Of particular concern, many new roads being built in low- and middleincome countries fail to meet recognized safety standards. In total, reporting countries collectively account for nearly 68 million km of roads, of which 4.5 million km are paved expressway; 47 million km are paved interurban roads; and 10 million km are unpaved inter-urban roads. Only 35 countries report on the availability of cycle lanes, which account for a total length of 140 000 km, or roughly 0.2% of the total length of roads reported. This deficit in infrastructure for cyclists provides some insight as to why more cyclists are dying in recent years.
+
+Fig. 10. Proportion of paved roads with a 3-star<sup>a</sup> or higher safety rating, by user group (500 000 kms evaluated, globally), 2021
+
+![](_page_35_Figure_1.jpeg)
+
+*Source:* International Road Assessment Programme *[\(22](#page-65-2)).*
+
+### **Road safety inspections or audits**
+
+A non-representative sample of nearly 500 000 km of paved road evaluated in 82 countries across all regions and income levels was conducted using the star-based road safety scoring system developed by the International Road Assessment Programme (iRAP) which rates roads from 0 to 5 *([22\)](#page-65-2)*.
+
+A 3-star rating is widely accepted as the minimum acceptable rating for new and old roads *[\(23](#page-65-3))*. 8 Using this approach, the results of this assessment reveal that only 21% of roads meet a 3-star or higher rating in relation to pedestrians and powered two- and threewheelers; 23% for cyclists; and 40% for passenger vehicles (Fig. 10).
+
+Additionally, formal road safety evaluations9 are reported by 93 countries in the survey for this report, of which nearly 50 report the percentage of their national road network evaluated. Of these countries, most declare evaluating 20–50% of their national road network.10
+
+## **Legislation, policies, plans and standards related to safe road infrastructure**
+
+Ninety-four countries report having national legislation requiring a formal road safety inspection or assessment for existing roads. However, the legal review of documents confirms the presence of this law in only 66 countries. Of these, 55 laws contain a requirement for periodic checks (maintenance or inspection), and 51 require that the needs of all road users considered.
+
+*Out of a possible 5-star rating*
+
+<sup>8</sup> This includes voluntary UN Performance Target (4b) that calls for 75% of all travel done in roads 3 stars or more for all road users.
+
+<sup>9</sup> This corresponds to UN Voluntary Performance Target 3.
+
+<sup>10</sup> Most of these evaluations were done using unspecified methods, but six countries reported using the Global Street Design guidelines and 15 other countries used the star-rating system.
+
+#### Box 3: Inclusive school zones, Indonesia
+
+Many public spaces in Indonesia are inaccessible to vulnerable groups such as children and persons with disabilities, partly due to a lack of infrastructure and limited awareness on the part of citizens and government agencies.
+
+The Inclusive Banjarmasin Initiative, led by the Transformative Urban Mobility Initiative and Kota Kita, with support from the Asian Development Bank, aimed to improve urban mobility and accessibility in Banjarmasin, Indonesia. A central focus of the project was the creation of safe and inclusive school zones to enhance road safety.
+
+The Safe School Zone project was implemented from 2019 to 2021 in two schools in the Gadang neighborhood. The project was inclusive and involved school administrators, teachers, students, parents, and other stakeholders in co-designing and implementing road safety measures. This approach ensured that the improvements are communitydriven and cater to local needs. The results of the project related to road safety are significant.
+
+![](_page_36_Picture_4.jpeg)
+
+Firstly, the project improved the safety and accessibility of sidewalks, parking areas, and drop-off/pick-up zones for all students. Dedicated sidewalks, crossroads, and curb ramps were constructed to ensure safe and convenient movement for pedestrians, including people with disabilities. Rumble strips and guiding blocks were installed to help people with visual impairments to navigate the sidewalks. These measures created a safer environment for all pedestrians, particularly vulnerable road users.
+
+Secondly, the project focused on traffic management to enhance road safety. Speed limit signs and Safe School Zone signs were installed within a 100 metre radius of the schools to raise awareness and encourage responsible driving. This helped to mitigate speeding issues and improve traffic management around the schools.
+
+The success of the Safe School Zone project in Gadang has inspired the development of five more such zones in Banjarmasin. This success underscores the scalability and replicability of the initiative, offering a model for other urban areas seeking to simultaneously enhance mobility, road safety and accessibility.
+
+One hundred and twenty countries report using technical standards for the development of new roads that account for the safety of all road users,11 and 61 of these countries report using UN or other international conventions to inform these standards.12 In addition, 92 countries report having a systematic programme to target investments and upgrade higher-risk locations, identifying road-crash hotspots as their most common mechanism for allocating available funds.
+
+While information was not available in most countries about the investments being made in road infrastructure, according to a report
+
+<sup>11</sup> This is the first proposed sub-indicator for UN Voluntary Performance Target 3 (Annex 2).
+
+<sup>12</sup> Sixty-one Member States adhere to at least one of three existing international road conventions. The 1950 Traffic Arteries Convention, 1975 European Agreement on Main International Traffic Arteries, and the 2003 Interstate Asian Highway Convention. We have chosen this as one of two UN voluntary Performance Target 3 indicators (Annex 2). See Annex 4 for more detail on adherence to conventions and existing national legislation.
+
+<span id="page-37-0"></span>by the World Bank in 2022, more than US\$ 800 billion is being spent annually on road infrastructure development by public and private investors *([24](#page-65-4))*. Similarly, data from the International Transport Forum show that spending by some countries on transport infrastructure ranged between less than 1% to as high as 5% of GDP between 2019 and 2021 *([25](#page-65-5))*. These investments represent an enormous opportunity to build infrastructure that supports multimodal transport and ensures the safety of all road users.
+
+## **Safe vehicles**
+
+The world's motor vehicle fleet – currently exceeding one billion vehicles – is likely to double between now and 2030 *([26](#page-65-6)).* Despite this growth, many new vehicles are being produced and sold that do not meet minimum safety standards. Where legislation requiring these standards are lacking, manufacturers can "de-specify" life-saving technologies in newer models sold in countries where regulations are weak or non-existent in order to reduce costs *([27](#page-65-7)).*
+
+## **Legislation, strategies, policies and plans related to safe vehicles**
+
+Two types of laws are essential for ensuring vehicle safety: the first is legislation that specifies requirements and standards for equipment; the second is legislation on inspections or assessments.
+
+As summarized in Table 2, legislation specifying requirements and standards for core safety equipment in vehicles is absent in most countries, most notably in low- and middle-income countries. Just over half of countries (88) currently have legislation that specifies the requirements and standards for seat-belts and seat-belt anchorages and only around a third of all countries have legislation on other vehicle core safety elements, including front and side impact protection, electronic stability control, pedestrian protection, and braking systems.13
+
+Table 2. Number of countries with legislation on "core" vehicle safety standards, by income, 2022
+
+|                                                               |       | Income levelsa |                           |                           |               |
+|---------------------------------------------------------------|-------|----------------|---------------------------|---------------------------|---------------|
+|                                                               | Total | High<br>income | Upper<br>middle<br>income | Lower<br>middle<br>income | Low<br>income |
+|                                                               | N=170 | N=51           | N=43                      | N=46                      | N=27          |
+| Vehicle safety equipment:                                     |       |                |                           |                           |               |
+| National law on front and side impact protection              | 52    | 39             | 9                         | 4                         | 0             |
+| National law on seat-belt and seat-belt anchorages            | 88    | 44             | 21                        | 16                        | 7             |
+| National law on electronic stability control                  | 49    | 39             | 8                         | 2                         | 0             |
+| National law on pedestrian protection                         | 44    | 35             | 7                         | 2                         | 0             |
+| National law on braking systems                               | 56    | 38             | 11                        | 6                         | 1             |
+| National law requiring periodic vehicle inspection/assessment | 134   | 46             | 30                        | 35                        | 20            |
+
+*a Not shown by income level counted in totals are the three countries for which there is no information on income level.*
+
+<sup>13</sup> Additionally, 29 countries report legislation mandating the availability of eCall or Accident Emergency Call Systems in all vehicles to trigger an emergency response through a vehicle sensor.
+
+Currently 35 countries have legislation mandating all five core areas of safety equipment; 10 have legislation for four core areas, nine have legislation for three core areas; eight have legislation for two core areas, and 29 countries have legislation for only one of the five core areas. Seventy-nine countries report no legislation on vehicle safety at all (Fig. 11).
+
+In contrast, the number of countries requiring periodic vehicle inspections is much higher. While the presence of a national law was confirmed, few of these laws specified how the inspections should be done. Only 38 of the 134 countries specify the use of international standards for vehicle inspections, as set out in international conventions (for more on the UN road safety conventions see Box 4 and Annex 4).
+
+As well as legislation on safety standards, vehicle safety can be assured through consumer oriented safety tests. Eightyseven countries report having consumer oriented crash test programmes, such as the New Car Assessment Programme (NCAP) tests, but only 25 of these countries report disseminating the safety-rating results. Fewer than 20 countries report having requirements to ensure that customers are informed on whether the vehicles they purchase meet minimum safety standards.
+
+Restrictions on used-vehicle imports are reported by 150 countries.14 Of these, 61 indicate a vehicle safety inspection criterion with or without an additional vehicle age limit, though age limit alone is also used in several countries. That only a third of countries require vehicle safety inspections for used vehicles is especially of concern considering that the African Region accounts for the largest share of the used-vehicle market – the region where the rates of road traffic deaths are highest. According to a report published by the UN Environment Programme, between 2015 and 2020 roughly 23 million used passenger vehicles were exported, of which 66% went to low- and middle-income countries. Without regulations to ensure the safety of these vehicles, these exports at present pose a significant threat to road safety *([28](#page-65-8))*.
+
+Fig. 11. Countries with legislation on "core" vehicle safety standards, 2022
+
+![](_page_38_Figure_6.jpeg)
+
+<sup>14</sup> This relates to UN Voluntary Performance Target 5.
+
+### Box 4: UN road safety conventions
+
+United Nations (UN) road safety legal instruments provide a strong foundation upon which countries can build domestic legal frameworks and transport systems in order to contribute to road safety and facilitate international road traffic. To fully realize their benefits, countries must not only accede to the conventions that provide these instruments, but also transpose the conventions into national or regional legislation. In this way they can ensure the effective application of the conventions, and thereafter enforce them through traffic police and inspection bodies.
+
+#### Number of countries adhering to UN road safety conventions
+
+| Convention                                                                                                                                                                                                                                                                                                              | Countries |
+|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------|
+| 1957 Agreement concerning the International Carriage of Dangerous Goods by Road (ADR)                                                                                                                                                                                                                                   | 53        |
+| 1958 Agreement concerning the Adoption of Harmonized Technical United Nations<br>Regulations for Wheeled Vehicles, Equipment and Parts which can be Fitted and/or be<br>Used on Wheeled Vehicles and the Conditions for Reciprocal Recognition of Approvals<br>Granted on the Basis of these United Nations Regulations | 56        |
+| 1968 Convention on Road Traffic                                                                                                                                                                                                                                                                                         | 86        |
+| 1968 Convention on Road Signs and Signals                                                                                                                                                                                                                                                                               | 71        |
+| 1970 European Agreement concerning the Work of Crews of Vehicles Engage in<br>International Road Transport (AETR)                                                                                                                                                                                                       | 51        |
+| 1997 Agreement Concerning the Adoption of Uniform Conditions for Period Technical<br>Inspection of Wheeled Vehicles and Reciprocal Recognition of Such Inspections                                                                                                                                                      | 38a       |
+| 1998 Agreement concerning the Establishing of Global Technical Regulations for Wheeled<br>Vehicles, Equipment and Parts                                                                                                                                                                                                 | 50        |
+
+*Including EU members mandated by EU Directive 2014/45/EU*
+
+To date, 120 countries report accession to one or more of the core road safety-related UN standards (see map), although 16 countries only adhere to all seven of them *[\(29](#page-65-9)).* See Annex 4 for the relationship between adherence to conventions and national legislation.
+
+#### Countries adhering to core road safety UN conventions, 2022
+
+![](_page_39_Figure_9.jpeg)
+
+## <span id="page-40-0"></span>**Road user behaviours**
+
+While the safe system approach emphasizes the importance of system designs that facilitate safe road use, laws governing road user behaviours are essential to the prevention of crashes, injuries, and deaths.
+
+Data collected for this report indicate that approximately 10% of road traffic deaths are related to drink driving; this corresponds to self-reported rates of 16–21% of people admitting to drink driving in a survey conducted by the European Survey Research Association (ESRA). The same self-reports reveal that nearly 50% of drivers across 48 countries report exceeding the speed limit
+
+outside built-up areas, with the perceived likelihood of being penalized for such violations ranging from 30% to 46%*.* Non-use of helmets among motorcyclists was reported as 20% for drivers and 30% for passengers; this corresponds to self-reports of 26–47% motorcyclists admitting to not using a helmet despite it being the law.
+
+Similar trends exist for non-use of seat-belts, with countries reporting 20% for drivers while self-reports show between 12–47% of drivers admitting to not using seat-belts. And 11–47% of people report not using a child restraint system while more than half of people surveyed admit to using communication devices while driving (Table 3).
+
+Table 3. Self-reported road user behaviours
+
+|                                                | Global status report on road safety<br>2023 survey (114 countries reporting<br>on at least one)                     | ESRA Survey (48 countries)                            |
+|------------------------------------------------|---------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------|
+| Exceeding speed limit                          | 1–66%                                                                                                               | 50%                                                   |
+| Drink driving                                  | 10% of fatalities (77 countries)                                                                                    | 16–21%                                                |
+| Non-use of helmet (adult)                      | 20% drivers (out of 44 countries);<br>30% passengers (out of 39 Member states)                                      | 26–47%                                                |
+| Non-use of seat-belts                          | 20% drivers (57 countries);<br>30% front seat passengers (50 countries);<br>50% rear seat passengers (42 countries) | 12–47% drivers<br>36–71% passengers                   |
+| Non-use of child restraint<br>system           | Information not included                                                                                            | 11–47%a                                               |
+| Distracted driving<br>(i.e., mobile phone use) | Information not included                                                                                            | 29–52% handheld phone use<br>vs 48–65% hands-free use |
+
+*Sources:* Survey for *Global status report on road safety 2023*; and *[\(20](#page-65-0), [30\)](#page-65-10).*
+
+These risks can be mitigated through the adoption and implementation of appropriate legislation. Although many countries have such laws, those laws do not always meet WHO best practice and are not consistently implemented through regulations or enforced. In the subsequent section, existing legislation is assessed against WHO best practice criteria (Table 4).15 In the colour-coded maps, those countries with laws that meet all criteria are coloured green; those with laws meeting some but not all are coloured yellow; and those with laws that do not conform with any best practice criteria or without legislation at all are coloured red.
+
+Transport of children under 150 cm in height without using a child restraint system.
+
+<sup>15</sup> WHO best practice criteria do not exist for laws on drug driving, distracted driving, and professional driver time limits
+
+## <span id="page-41-0"></span>**Speed management**
+
+Speed management remains one of the biggest challenges facing road safety practitioners around the world and calls for a concerted, long-term, multidisciplinary response. The speed at which a vehicle travels directly influences the risk of a crash as well as the severity of injuries sustained, and the likelihood of death resulting from that crash. Reducing vehicle speeds in areas where the road user mix includes a high volume of vulnerable road users, such as pedestrians and cyclists, is especially important.
+
+Among countries surveyed for this report, 163 report having laws on speeding, of which 57 meet WHO best practice – meaning they include a national speed limit; an urban speed limit of 50 km/h or lower; and the ability of local authorities to adapt speed limits to local contexts *[\(31](#page-65-11))* (Fig. 12).16 Of these 57 countries, three have laws mandating national speed limits in urban areas of 30 km/h where there is a frequent mix of road users, as recommended in the Global Plan of Action for the Decade for Road Safety *([27\)](#page-65-7)*. This represents an additional 8 countries meeting WHO best practice since the *Global status report on road safety 2018 [\(4](#page-64-2))*.
+
+Data on enforcement levels were not collected through the survey for this report, but information on self-reported behaviour and "enforcement perception" gathered by ESRA reveals that nearly 50% of drivers (across 48 countries where the survey was implemented) admit to exceeding the speed limit outside built-up areas, with the perceived likelihood of being penalized for violation ranging from 30% to 46% *[\(20\)](#page-65-0).*
+
+Fig. 12. Status of speed laws in countries, 2022
+
+![](_page_41_Figure_6.jpeg)
+
+<sup>16</sup> This corresponds to UN Voluntary Performance Target 6.
+
+<span id="page-42-0"></span>The use of speed cameras is mentioned in the speed laws of 81 countries to help enforce speed limits while penalties in the form of fines are reported as the main means of enforcement in 154 countries. Since 2018, six countries have increased their penalties for speeding.
+
+## **Impaired and distracted driving**
+
+Drinking alcohol significantly increases the risk and severity of a crash and therefore the chance it will result in death and serious injury. In high-income countries it is estimated that about 20% of fatally injured drivers have blood alcohol concentration (BAC) levels above the legal limit. And studies in low- and middleincome countries show that between 33% and 69% of fatally injured drivers and between 8% and 29% of nonfatally injured drivers had consumed alcohol before their crash *([32\)](#page-65-12).* Drink driving legislation that is evidencedriven, context relevant, consistently enforced and well understood by enforcement officials and the public has been effective in saving lives in many jurisdictions.
+
+## **Legislation on drink driving**
+
+Among countries surveyed for this report, 18 prohibit alcohol consumption among the general population. Specific legislation on drink driving is reported by 166 countries, of which 48 meet WHO best practice – which means that the law specifies a BAC limit of ≤0.05 g/dl for the general driving population and ≤0.02 g/dl for novice drivers *([32\)](#page-65-12).* This represents an increase of three countries meeting WHO best practice since the *Global status report on road safety 2018 [\(4\)](#page-64-2)* (Fig. 13).
+
+Of note, fatally injured drivers are tested for the presence of alcohol routinely in 61 countries, whereas nonfatally injured drivers involved in a fatal road crash are tested for the presence of alcohol in 51 countries.
+
+![](_page_42_Figure_7.jpeg)
+
+![](_page_42_Figure_8.jpeg)
+
+## <span id="page-43-0"></span>**Legislation on drug driving**
+
+Among those surveyed in this report, 167 countries have legislation that prohibits driving under the influence of drugs and other psychoactive substances. There are currently no WHO best practice criteria against which to assess these laws *([33](#page-65-13))*.
+
+## **Legislation on distracted driving**
+
+Among those surveyed in this report, 162 countries have legislation that prohibits distracted driving in general, but this mostly relates to mobile phone use – 144 countries prohibit the use of hand-held phones and 35 also prohibit the use of hands-free phones. There are currently no WHO best practice criteria against which to assess these laws *([34\)](#page-65-14)*.
+
+## **Legislation on professional driving times**
+
+Given the high level of exposure to traffic among professional drivers, there is a need to ensure regulation of commercial practices, including regulating driving times and conditions. Eighty-two countries have legislation on rest periods for professional drivers.
+
+Only 30 countries report a maximum number of driving hours (most typically 4–5 hours) while 23 countries report having minimum rest periods, most frequently reported as either a 30 minute rest after maximum driving time or a minimum number of daily hours. Fifty-six of these countries are signatories of the corresponding UN Convention.17 Whether this legislation matches other international recommendations such as International Labour Organization (ILO) R616 or the EU rules for working in road transport18 was not assessed at this time.
+
+## **Motorcycle helmet use**
+
+Nearly 21% of all road traffic fatalities reported in the survey involve powered two- and threewheelers, such as motorcycles, mopeds, or scooters. Yet as the use of powered twoand three-wheelers increases, particularly in developing countries, the use of lifesaving helmets often lags far behind. Head injuries are the main cause of death in most motorcycle crashes*.* Quality helmets reduce the risk of death by over six times and reduce the risk of brain injury by up to 74% *([35](#page-65-15))*.
+
+Despite this, several challenges slow the uptake and proper use of quality helmets, particularly in developing countries. These challenges include availability and affordability of quality helmets, improperly fastened helmets, a lack of available helmets for children, hot weather, and even misinformation.
+
+Among countries surveyed for this report, 160 report having legislation on helmet use, of which 54 meet WHO best practice (Fig. 14) – meaning that the law applies to both drivers and passengers; to all roads and all engine types; specifies a particular helmet standard;<sup>19</sup> and requires that the helmet be appropriately fastened *[\(35\)](#page-65-15)*. This represents an increase of five countries meeting WHO best practice since the *Global status report on road safety 2018 ([4](#page-64-2))*.
+
+Official reports by 35 countries indicate a correct helmet use rate of approximately 80% among drivers and riders, while self-reported rates of motorcycle riders correctly using helmets range from 53% to 74% *[\(20](#page-65-0)).*
+
+<sup>17</sup> 1970 European Agreement concerning the Work of Crews of Vehicles Engaged in International Road Transport (AETR).
+
+<sup>18</sup> International Labour Organization R161, 1979 or EU Reg 561/2006.
+
+<sup>19</sup> Whether countries adhere to international helmet standards is shown in Annex 4.
+
+![](_page_44_Figure_0.jpeg)
+
+![](_page_44_Figure_1.jpeg)
+
+Table 4. WHO best practice criteria for legislation on the five key risk factors
+
+| Risk Factor |                                  | WHO Best Practice Criteria                                                                                                                                                                                                                                         |
+|-------------|----------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+|             | Speeding                         | National law exists, urban limits are set at 50 km/h or lower, and<br>local authorities can further modify this limit                                                                                                                                              |
+|             | Drink<br>driving                 | National law exists, alcohol levels are defined by BAC, alcohol limits<br>per general driving population are ≤0.05 g/dl and for novice drivers<br>≤0.02 g/dl                                                                                                       |
+|             | Motorcycle<br>helmet use         | National law exists and it covers all riders, on all road types, and<br>all engine types, and the helmet must be fastened and meet a<br>standard                                                                                                                   |
+|             | Seat-belt<br>use                 | National law exists and it applies to all seating positions in<br>vehicles                                                                                                                                                                                         |
+|             | Child<br>restraint<br>system use | National law exists, children up to the age of 10 years, or 135 cm<br>in height, must use a child restraint system meeting a standard<br>in addition to the prohibition of children of a particular age/height<br>being prohibited from sitting in the front seats |
+
+![](_page_45_Picture_0.jpeg)
+
+## **The voice of civil society:**
+
+Lotte Brondum, Executive Director, Global Alliance of NGOs for Road Safety
+
+The *Global status report on road safety 2023* provides new and crucial evidence of the performance and progress of countries in reducing road crash deaths. We, the road safety NGOs, urge all to read and act on it urgently.
+
+We cannot accept the preventable tragedies that are devastating families and communities every day. We cannot accept that our children and youth are dying on the roads. We cannot accept the unfairness – that the majority of all road traffic deaths occur in low- and middleincome countries. We need transformation on our roads and communities to put people and their rights at the centre of our mobility system. We want safe mobility to be our guaranteed right.
+
+Immediate action is required to achieve a 50% reduction in road deaths by 2030 and have a transport system that is safe for people and sustainable for our planet. Civil society is an essential partner in achieving all this, and NGOs represent civil society. We are the voice of our communities. We show the reality of people's everyday journeys; we spotlight the challenges people face to reach work or school and bring them to those who have the power to act; we hold governments to account for the safety and protection of all road users.
+
+We must proceed with evidence-based and accountable measures. NGOs, we ask you to take the lead to collect data at intersections in your cities from the perspective of a pedestrian; this will provide a reality check from the ground and help to show the experiences of communities. We ask you to obtain public acceptance of the enforcement and promotion of helmet law to reduce deaths and injuries; we ask you to foster the importance of 30 km/h where people walk, bike, live, and play to save lives. We have the knowledge, expertise, and persistence necessary to make a real impact. As politicians come and go, we remain steadfast in our mission.
+
+Governments, we are the people. We urge you to rely on our experiences, take this information, and turn it into targeted interventions to prioritize safe mobility in decision-making. We are the voice of those who use the transport systems. Use this evidence; it will save lives and is a building block to achieve the SDG agenda for peace and prosperity for people and planet. Invest in safety: it has a high return on investment economically and socially. Involve your NGOs to bridge the gap between data and experience, policy and reality.
+
+The evidence for what works to transform our vision into reality is clear and abundant. There are proven actions that can save lives. We cannot afford to wait any longer. We must act now to save lives on the road.
+
+The Decade of Action's goal is to reduce road traffic deaths and injuries by 50%. Use this report to take action with us. Together, we can make a difference, leaving no one behind.
+
+## <span id="page-47-0"></span>**Seat-belt use**
+
+Failure to use seat-belts is a major risk factor for road traffic deaths and injuries among vehicle occupants. Passengers not wearing a seat-belt at the time of a collision accounts for most occupant road traffic fatalities. The most frequent and most serious injuries to occupants that occur as a result of frontal impacts are to the head, chest and abdomen*.* Disabling injuries to the legs and neck also occur*.* A systematic review and meta-analysis found unequivocally that the risk of major trauma among seat-belt-using passengers was much lower than that among those not using one; facial, abdominal and spinal injuries were significantly reduced among seat-beltwearing passengers *[\(36\)](#page-66-0)*.
+
+Among countries surveyed for report, 170 have mandatory seat-belt use laws, of which 117 meet WHO best practice – meaning that they require all front- and rear-seat occupants to use seat-belts. This is an increase of 11 countries meeting WHO best practice since the *Global status report on road safety 2018 [\(4](#page-64-2))* (Fig. 15.) Whether countries adhere to seatbelt international standards is described in Annex 4.
+
+Sixty-three countries report having national data systems to measure appropriate use of seat-belts. Among these, 12 report a compliance level of at least 80% for all occupants in both front and rear seating positions. In contrast, self-reported seat-belt use among passenger car occupants ranges from 30% to 60%, with the rate among drivers ranging from 50% to 80% *[\(20\)](#page-65-0)*.
+
+![](_page_47_Figure_4.jpeg)
+
+![](_page_47_Figure_5.jpeg)
+
+## <span id="page-48-0"></span>**Child restraint systems use**
+
+Child restraint systems (CRS) are highly effective in reducing injury and death among child occupants – the use of CRS can lead to at least a 60% reduction in deaths *[\(36\)](#page-66-0)*. The benefits of child restraints have been shown to be greatest for younger children, particularly those under the age of 4 years. For children aged 8–12 years, booster seats are associated with a 19% reduction in the likelihood of injury compared to solely using a seat-belt. The position of children in either front or rear seats is also important, as a higher risk for injury is associated with sitting in the front *[\(36\)](#page-66-0).*
+
+Among countries surveyed for this report, 128 report having laws on the use of CRS, of which 36 meet WHO best practice – meaning that they include provisions for the minimum age and height of the child requiring a CRS (set for children under the age of 11 years and equal to or less than 135 cm tall); the presence of a CRS standard;20 and prohibition on sitting in the front seats *[\(20\)](#page-65-0)*. This represents an increase of four countries meeting WHO best practice since the *Global status report on road safety 2018 [\(4](#page-64-2))* (Fig. 16).
+
+While the survey for this report did not collect data on the use of CRS, self-reported use from the ESRA2 survey indicates that the use of CRS ranges between 11% and 47% *[\(20,](#page-65-0) [30](#page-65-10))*.
+
+**Fig. 16. Status of child restraint system laws in countries, 2022**
+
+![](_page_48_Figure_5.jpeg)
+
+<sup>20</sup> Whether countries adhere to international CRS standards is shown in Annex 4.
+
+## <span id="page-49-0"></span>**Post-crash response**
+
+Increasing the likelihood of survival following a crash requires coordination across multiple sectors including police, health, justice and finance (see Box 5 for an example from Thailand). Post-crash care and survival is extremely time sensitive: delays of minutes can make the difference between life and death. Proper and timely rehabilitation service can be critical for mitigating the long-term impact of road traffic injuries and prevent lifelong disability *([37\)](#page-66-1).* In addition to postcrash care, the justice and legal system also has an important role in ensuring financial and psychosocial protection for victims.
+
+## **Legislation, policies, plans and strategies related to post-crash care**
+
+Ensuring timely access to care is critical following a crash event, and as such, one of the most important elements of the postcrash response is an emergency number that can be used to activate the response, whether it is by an individual or through an automated system like the e-call. Of those surveyed, 97 countries report having single or multiple emergency care service numbers that guarantee total country coverage, while 18 countries have a single number but without national coverage. Additionally, 118 countries report having an agency that effectively coordinates pre-hospital and facility-based emergency medical services (EMS).
+
+In addition to having a means to activate the emergency response, there is often a need for immediate care to be provided by lay bystanders whose interventions can sometimes be lifesaving. Encouraging them to do so requires protection from civil liability. While 59 countries have national legislation requiring lay bystanders to help anyone involved in a vehicle crash, only eight of them have national laws providing protection from civil liability to these lay bystanders (i.e. Good Samaritan laws).
+
+In relation to actions to ensure the quality of care provided by health facilities, 35 countries have national laws requiring training, licencing, or other certification processes for first health responders, while 104 Member states have these certifications in place for emergency medicine physicians and 95 have them for trauma surgeons. Seventy-six countries report having a trauma registry where facility-based trauma data are aggregated nationally, while 28 countries report these systems at a subnational level and 23 additional countries report trauma registries only in selected facilities.
+
+In terms of access to rehabilitative medical care for all injured persons regardless of their ability to pay, 46 countries report having laws that mandate rehabilitative medical care. While the coverage of rehabilitative care was reported at a level of 75% for road traffic injuries by only 25 countries, the actual availability and coverage of these services is largely unknown in most countries.
+
+In relation to protection and support for victims (including the families of road traffic fatalities), 131 countries have national legislation mandating third-party liability insurance for vehicles. An even lower number – 25 countries – mandate the provision of psychological assistance to road victims and their families regardless their ability to pay.
+
+#### Box 5: Better post-crash care management, Thailand
+
+In Thailand, road crashes exact a high human and economic toll. In 2022 alone, 17 000 people died as a result of road injury and 15 000 people were left with disabilities. The economic losses totalled around 500 000 million Baht (approximately US\$12.5 million). Against this backdrop, a multidisciplinary coalition including the government, NGOs, the private sector and the media has collaborated to reduce the death toll from road traffic injury. In Khon Kaen, northeast of Bangkok, progress is being made, with the province seeing a 2% decline in preventable road fatalities.
+
+Led by the Ministry of Interior's National Directing Center for Road Safety, alongside the Ministry of Public Health and numerous road safety foundations, the coalition identified and deployed three key activities to reduce the country's fatality burden: leadership and networking; data integration and policy advocacy; and strengthening post-crash response. Consequently, a range of road safety activities, including legislation, policy advocacy, and political negotiations, were conducted nationally and implemented effectively in Khon Kaen.
+
+Khon Kaen hospital is a centre of excellence within Thailand's Emergency Care System (ECS), a system that has been systematically developed to include pre-hospital care, hospital-based emergency care, referral systems, and mass-casualty management. Health care providers have been seamlessly integrated into the ECS – from sub-district primary care clinicians through to emergency physicians in Khon Kaen hospital.
+
+Key to success in Khon Kaen was starting with small-scale implementation and building over the long-term with a consistent and coherent strategic approach to strengthen post-crash care. Khon Kaen
+
+![](_page_50_Figure_5.jpeg)
+
+hospital itself now has a robust ambulance system and a strong provincial dispatch centre for the national health emergency number, 1669.
+
+Integrating emergency care has allowed for the successful implementation of EMS medical decision-making to get patients to the right location for care, aeromedical transport, facility-based triage, and telemedicine support for both pre-hospital and referral systems. This, alongside rigorous quality control and improvement processes, has significantly reduced preventable trauma deaths by more than half – from 4% to 1%
+
+In addition to a focus on post-crash care to reduce road traffic deaths, data integration has also been prioritized. Thailand's Injury Surveillance system has been pivotal in monitoring and enhancing trauma care quality but has also been instrumental in injury prevention since 2011. Integration of data from the injury surveillance system with that of the Police and the Road Accident Victims Protection Company provides more accurate insights into mortality and injuries stemming from road traffic crashes. Accurate data has allowed clinicians in Khon Kaen to undertake effective policy advocacy and to gain trust among policy-makers and politicians.
+
+This success has benefited from the continued and concerted efforts of dedicated individuals and organizations who have monitored and championed the cause of road safety in Thailand over recent decades.
+
+## <span id="page-51-0"></span>**Progress towards safe road use: summary**
+
+Improvements have been made to legislation in 23 countries to align with existing WHO best practice criteria in relation to the five key risk factors. Since the *Global status report on road safety 2018 [\(4\)](#page-64-2)*, 29 laws in 23 countries have been updated to meet WHO best practice. Specific laws improved are described in Figure 17.
+
+As of 2022, only six countries have laws addressing all five key risk factors that meet WHO best practice. Twenty-one countries have laws that meet WHO best practice on four of the five risk factors, 25 have laws on three of the five risk factors; 35 have laws on two of the five risk factors; 53 have laws on one of them, and 54 countries have no laws meeting best practice criteria for any of the key risk factors (Fig. 18).
+
+Fig. 17. Number of countries with laws meeting WHO best practice criteria on the five key risk factors, 2022
+
+![](_page_51_Figure_4.jpeg)
+
+Fig.18. Countries with laws meeting WHO best practice on one or more of the five key risk factors, 2022
+
+![](_page_52_Figure_1.jpeg)
+
+![](_page_53_Picture_0.jpeg)
+
+<span id="page-54-0"></span>![](_page_54_Picture_0.jpeg)
+
+# Measures to strengthen road safety governance
+
+![](_page_54_Picture_2.jpeg)
+
+84 countries have a dedicated road safety agency.
+
+![](_page_54_Picture_4.jpeg)
+
+117 countries report having a national road safety strategy, while just 16 of these strategies are fully funded.
+
+![](_page_54_Picture_6.jpeg)
+
+More than half of countries use general taxes on vehicle purchases, insurance, fuel and alcoholic beverages among others, to finance road safety activities.
+
+![](_page_54_Picture_8.jpeg)
+
+About half of all countries use dedicated taxes and fines from traffic violations to finance road safety activities.
+
+![](_page_54_Picture_10.jpeg)
+
+Differences between reported counts of road traffic deaths and WHO estimated counts exist in 120 countries. In some cases the WHO estimates are 10 times higher, and in one case, 49 times higher, than self-reported figures.
+
+![](_page_54_Picture_12.jpeg)
+
+Only 114 countries report having a specific definition for injuries that result from a road traffic crash.
+
+<span id="page-55-0"></span>Experience from the Decade of Action for Road Safety 2011–2020 highlights the importance of addressing the challenge of implementation – and its complexity – through effective road safety governance. This goes beyond purely managing road safety strategies and actions: it includes coordination across sectors (including health, transport, urban planning and police, etc.), and managing the social and commercial factors that influence sustainable development and other societal practices that ultimately impact road safety.
+
+## **Institutional management**
+
+Management should not be pursued as a standalone goal but as a means to govern – through coordination, legislation, funding and resource allocation, promotion, monitoring and evaluation, research and development, and knowledge transfer. How this function is organized is each country's own decision, but it is necessary to ensure shared multisectoral responsibility for results through an integrated road safety approach.
+
+The existence of a national agency responsible for road safety is reported by 84 countries, of which 81 report that the agency has funding. A national road safety strategy is reported by 117 countries – proof that the presence of a dedicated road safety agency is not essential to the development of a national strategy. However, when assessed if active during 2021, and if the strategies align with the criteria21 of having regular updates and time-bound targets for reductions in fatalities and injuries, the actual number of countries with an up-todate national road safety strategy is 17.
+
+Sixteen countries report having full funding for their plan, while 65 others report partial funding. Most countries could not answer this question. When asked about the source of funding, most countries report not knowing.
+
+In contrast to the smaller number of countries reporting on the origin of road safety funding for their strategies, a much larger number of countries (more than half) report on whether fiscal interventions (such as taxation) are applied to aspects of road transport. More than half of all countries report having taxes on vehicle purchases, vehicle insurance, fuel, or alcoholic beverages. Similarly, half of all countries report using fines from traffic violations to finance road safety activities.
+
+## **Monitoring, evaluation, and data management**
+
+Achieving the goal of 50% reduction in road traffic deaths and injuries by 2030 requires countries to assess their road safety situations, prepare or revise their road safety action plans and implement the solutions highlighted in this document. It is important to monitor and evaluate, at the global level, the progress and outcomes of country implementation of solutions. This includes monitoring and collecting data to measure impact as well as to assess implementation progress (see Box 6 for an example from Zambia).
+
+### **Evaluating implementation**
+
+In order to assess progress towards the implementation of the recommended safe system approach for road safety, a set of voluntary performance targets and indicators was identified at the request of a World Health Assembly Resolution in 2016 *[\(38\)](#page-66-2)*. The 12 performance targets were agreed upon by consensus in 2017 and corresponding indicators were agreed upon in 2018 *([23\)](#page-65-3)*. This report is the first time an assessment has been carried out to measure progress towards these performance targets. Annex 2 summarizes progress as reported by countries for these indicators and shows that globally there remain significant gaps in achieving these targets; moreover, there are nine indicators (out of 34) for which data cannot be obtained. Nonetheless, the fact that most countries are able to respond to the majority of the indicators agreed upon is encouraging and an indication of the increased coordination across sectors working to improve road safety.
+
+<sup>21</sup> As prescribed in UN Voluntary Performance Target 1.
+
+## **Evaluating impact**
+
+While the primary indicator for the Decade of Action for Road Safety 2011–2020 is the number of road traffic deaths, not all countries have this data, and the reported fatality data from different countries are not necessarily comparable, as different definitions and timeframes have been used. For this reason, WHO estimates (both absolute numbers and rates per 100 000 population) allow for comparisons between countries.
+
+Moreover, there remain significant differences in fatality numbers reported by countries and WHO estimates. Differences between estimated and reported fatalities have been highlighted in all previous editions of the *Global status report on road safety*, with average ratios of 1.8 (2013, 2015 and 2023) and 1.7 (2018) when data for countries participating in all reports to date are evaluated (Fig. 19). For 2021, differences between reported and estimated mortality figures are observed in 120 countries. In some cases, the estimated figures are 10 times higher, and in one case, 49 times higher.
+
+While the causes of these differences vary, major contributing factors are the data sources and definitions used. WHO estimates are based on civil registration and vital statistics that consolidate data from multiple sources and include all deaths resulting from road traffic crashes in a given year, regardless of the length of time between the crash date and the death (see Annex 1). Many countries report data from only one source and only include deaths that occur at the scene, or within a limited time period from the date of the crash.
+
+Producing a global morbidity figure for road traffic crashes is challenging, because around a third of countries report no measure for nonfatal cases, while the other two thirds report using a variety of operational definitions. Only 114 countries report having a specific definition for injuries that result from a road traffic crash. More than half of these countries (57%) use either the need for hospitalization as the operational definition (or hospitalization plus another condition) or require three or more days of leave from work. The next most common definition used by more than 10% of countries relates to standardized injury definitions such as the Maximum Abbreviated Injury Scale (MAIS) *[\(39\)](#page-66-3)*, the Revised Trauma Score (RTS) *([40](#page-66-4)),* or the Mechanism/Glasgow Coma Score (Age/ Pressure (MGAP) *[\(41](#page-66-5))*. The remaining countries report using a variety of definitions.
+
+Fig. 19. Road traffic deaths reported by 146 countries collaborating in all *Global status report on road safety* surveys to date, compared to WHO estimated fatalities
+
+![](_page_56_Figure_7.jpeg)
+
+### Box 6: Harnessing fatality data through capacity building, Zambia
+
+In Zambia, three key authorities handle road traffic crash fatality data: the police, health care facilities, and the Civil Registration and Vital Statistics (CRVS) system. Together these authorities face challenges around a paper-based data collection system; lack of harmonization; non-standardized coding practices and definitions of road traffic deaths; and low CRVS registration in rural areas. So, while Zambia's official records indicate an average of just under 2000 road traffic deaths annually, WHO's global health estimates suggest that this figure is 3600 – implying an approximate 50% underestimation of road traffic fatalities in official records.
+
+### **Zambia's approach to improve data collection**
+
+*Collaboration and partnerships:* Zambia established robust partnerships with key stakeholders in road safety including the Zambia Police Service, the Road Transport and Safety Agency, the Department of National Registration, Passports and Citizenship under the Ministry of Home Affairs, University Teaching Hospitals, and the Lusaka Provincial Health Office. In addition, the Bloomberg Data for Health Initiative, various road safety NGOs, and academic institutions were also part of this collaborative effort.
+
+*Capacity building:* A series of meetings and workshops with key stakeholders served as dynamic platforms for knowledge sharing, skill enhancement, and strategic planning, sparking innovation and paving the way for the development of new policies and intervention strategies.
+
+*Business process mapping:*A comprehensive review and analysis of the processes and procedures for road traffic crash mortality data collection in Zambia was conducted. A process map was developed that helped identify bottlenecks in data collection which, if adequately addressed, would lead to enhanced efficiency in the system.
+
+*Source: [\(42\)](#page-66-6)*
+
+![](_page_57_Figure_7.jpeg)
+
+*Data collection, record-linking and estimation of completeness***:** To estimate the extent of traffic mortality underreporting in Zambia, data were gathered from police records, hospitals, and the civil registration and vital statistics databases for a one-year period from 1 January to December 30, 2020, focusing on crashes in Lusaka Province. A meticulous method was employed to link these records using specific identifiers.
+
+The initiative has led to transformative outcomes*.* A multidisciplinary team for road crash data analysis and reporting is being set up, and there has been a significant uptick in data sharing and collection, broadening the utility of road traffic crash data for policy formulation.
+
+And statistical methods have been used to estimate how complete data collection was from different sources. Specifically, data from police records were about 19% complete, hospital records were 12% complete, and vital statistics from the CRVS system were estimated to be 14% complete. Importantly, when data from all these sources were combined, completeness improved to 37%. The Zambian experience serves as both a template and a testament to the transformative impact of quality data on public health initiatives.
+
+|  | Section 4. Measures to strengthen road safety governance | 47 |
+|--|----------------------------------------------------------|----|
+
+![](_page_59_Picture_0.jpeg)
+
+<span id="page-60-0"></span>![](_page_60_Picture_0.jpeg)
+
+# The way forward
+
+Road traffic deaths fell slightly to 1.19 million in 2021 – a 5% drop since 2010. More than half of all UN Member States, including some of the worst-affected countries, reported a decline in fatalities. The slight reduction in deaths occurred despite the global motor vehicle fleet more than doubling, road networks significantly expanding, and the global population increasing by more than one billion. Though the decline in deaths falls far short of what is needed to meet the UN Decade of Action for Road Safety 2021–2030 target of halving deaths by 2030, it shows how to accelerate progress. Ten countries managed to reduce road deaths by 50% since 2010, showing that such a reduction over a 10-year period is possible.
+
+Some of the greatest gains were made where the safe system approach – which puts people and safety at the core of mobility systems – was applied. The European Region has the greatest concentration of countries with policies and legislation that align with this approach and reported the largest drop in deaths – a 36% drop since 2010. Belarus, Norway, and the United Arab Emirates, for example, adopted elements of the safe system and were among the small number of countries that reduced fatalities by 50% by 2020.
+
+With a rapidly growing and increasingly urban global population, the safe system calls for an efficient and sustainable mix of transport modalities – including mass public transport – while upholding the safety of pedestrians, cyclists and other vulnerable road users, who account for half of all deaths.
+
+Yet as motor vehicle fleets and road networks built for these vehicles expand, vulnerable road users are left dangerously exposed. Just one fifth of the world's roads meet the basic safety requirements needed for cyclists and pedestrians, and just 0.2% of the world's roads have cycle lanes. The 20% increase in deaths among cyclists is worrying.
+
+Political will must match the scale and urgency of this crisis. Road crashes are the leading killer of children and youth aged 5–29 years. There are more than 3 200 road traffic deaths each day, and nine in ten deaths occur in Iow- and middle-income countries. Two thirds of all deaths occur among people of working age, causing huge health, social and economic harm throughout societies.
+
+Measures to mitigate the risk of death an injury, including enacting laws the meet WHO best practice, have advanced modestly. Policymakers have known of the key risk factors that contribute to road crashes for decades, yet only six countries have legislation on all five – speeding, drink driving, motorcycle helmet use, and seat-belts and child restraint systems – that meet WHO best practice.
+
+The Global Plan for the United Nations Decade of Action for Road Safety 2021–2030 charts the way forward, and everyone has a role to play in making safe, inclusive, and sustainable mobility a reality. Governments must lead strategies that are rooted in good data, backed by strong laws and funds, and involve all relevant sectors. Businesses must put safety and sustainability at the core of their value chains. Academia and civil society must generate evidence and hold leaders to account and young people can demand action and help take it.
+
+This more holistic approach to mobility will bring benefits in tackling many other crucial issues. By encouraging walking and cycling for example, we can reduce the burden of noncommunicable diseases, reduce pollution and combat climate change. By prioritizing the safety of vulnerable road users, we can help reduce poverty and tackle inequalities, including access to jobs and education.
+
+The increase in motor vehicles and motor vehicle based transport systems poses serious questions around sustainability. As the global and increasingly urban population grows, the demand for mobility will outstrip the capacity of systems that rely heavily on private vehicles. With rising greenhouse gas emissions, this also poses a challenge to efforts to meet global climate targets.
+
+Greater coordination with leaders from related fields could help strengthen impact through better coordination, help raise awareness of the road safety crisis among key decisionmakers and leverage greater investment into mobility systems that are designed for people, with safety front and centre.
+
+The Global Plan of Action for the United Nations Decade of Road Safety 2021–2030 calls for a holistic, safe system approach to halve road traffic deaths by 2030. This report shows that it is possible if the right decisions are taken and measures are put in place.
+
+## **The way ahead – reflections from Jean Todt, UN Special Envoy for Road Safety**
+
+The latest *Global status report on road safety 2023*  tells two competing stories.
+
+One is a tale of hope, where the tragic tally of road crash deaths is finally falling. Where major gains are made in countries that adopt the safe system approach to road safety, and governments, businesses, civil society, citizens, and communities, come together around a crucial global plan to rethink mobility and to halve road crash deaths by 2030.
+
+The other story is a troubling tale of a world barrelling towards 'carmageddon.' Where the number of motor vehicles expands exponentially and pedestrians, cyclists and other vulnerable road users are left dangerously exposed. In this narrative, more money is invested on roads with all their dangers, rather than in safe public transport or more sustainable means of mobility; and safety is an afterthought, not a goal and guiding light.
+
+The decisions that we make now will determine how many lives are saved and will have an impact on many more areas of our future, including our fragile natural environment.
+
+Motor vehicles are set to double in number by 2030 from our starting point at the first Decade of Action. This could stretch transport systems built for private vehicles to breaking point, especially in low- and middle-income countries. It means more congestion, more pollution, and spiralling health, social and economic costs for us all to bear.
+
+With the rapid expansion of urban populations – 68 percent of humanity is projected to live in cities by 2050, compared to 54 percent in 2016 – and private vehiclebased systems becoming an inefficient waste of space, the safe system approach to road safety calls for a mix of different types of mobility, including efficient and affordable public transport.
+
+And then there is climate change. The transport sector is responsible for about one quarter of the world's greenhouse gas emissions, even as we strive to reduce these emissions in a final effort to stave off climate catastrophe and protect our planet for future generations.
+
+Electric vehicles and more energy efficient solutions are good, but they are just one part of the answer. Fossil fuelled motor vehicles are also expanding much faster than e-vehicles.
+
+The Global Plan for the second Decade of Action for Road Safety (2021–2030) calls on the world to move from drab, dirty and dangerous streets to safe, green, and vibrant spaces designed for people. With safe mobility touching on many areas of sustainable development, we must work with all relevant sectors to ensure the best possible results. We must all understand that improved sustainability leads to improved safety, while unsafe transport is unsustainable.
+
+As we work towards meeting the goal of halving road crash deaths by 2030, we need a paradigm shift in leadership, commitment, investment, and action from governments everywhere, and including everyone in society, from road users to those who design and build our infrastructure.
+
+The treasure trove of data in this report should help us refine and redouble our efforts. The United Nations is fully committed to accelerating action to save lives on the roads, reflected in the establishment of a UN Road Safety Fund, UN road safety conventions, and a Global Plan of Action for Road Safety.
+
+The future is teetering on the brink, and only we ourselves will determine which of the two stories gets told.
+
+| 52 | Global status report on road safety 2023 |  |  |
+|----|------------------------------------------|--|--|
+
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+- <span id="page-65-6"></span>26. Market research report: Automotive market size, share, growth, and global industry analysis, by type (passenger vehicle and commercial vehicle), by application (personal use, municipal use, and business use), regional insights and forecast to 2031. Business Research Insights. Maharashtra, India: Business Research Insights; 2023 ([https://](https://www.businessresearchinsights.com/market-reports/automotive-market-102183) [www.businessresearchinsights.com/market](https://www.businessresearchinsights.com/market-reports/automotive-market-102183)[reports/automotive-market-102183,](https://www.businessresearchinsights.com/market-reports/automotive-market-102183) accessed 2 November 2023).
+
+- <span id="page-65-7"></span>27. Global Plan. Decade of Action for Road Safety 2021–2030. Geneva: World Health Organization; 2021 [\(https://www.who.int/publications/m/item/](https://www.who.int/publications/m/item/global-plan-for-the-decade-of-action-for-road-safety-2021-2030) [global-plan-for-the-decade-of-action-for-road](https://www.who.int/publications/m/item/global-plan-for-the-decade-of-action-for-road-safety-2021-2030)[safety-2021–2030,](https://www.who.int/publications/m/item/global-plan-for-the-decade-of-action-for-road-safety-2021-2030) accessed 15 June 2023).
+- <span id="page-65-8"></span>28. Used vehicles and the environment: a global overview of used light duty vehicles – flow, scale and regulation. Nairobi, Kenya: United Nations Environment Programme; 2020 ([https://wedocs.](https://wedocs.unep.org/20.500.11822/34175) [unep.org/20.500.11822/34175](https://wedocs.unep.org/20.500.11822/34175), accessed 15 June 2023).
+- <span id="page-65-9"></span>29. United Nations Economic Commission for Europe. United Nations Road Safety Conventions, Geneva, 2020 ([https://unece.org/transport/publications/](https://unece.org/transport/publications/united-nations-road-safety-conventions) [united-nations-road-safety-conventions](https://unece.org/transport/publications/united-nations-road-safety-conventions), accessed 15 June 2023).
+- <span id="page-65-10"></span>30. Bloomberg Philanthropies Initiative for Global Road Safety and Johns Hopkins International Injury Research Unit. BIGRS observational studies, manuscript under preparation.
+- <span id="page-65-11"></span>31. Speed management: a road safety manual for decision-makers and practitioners, second edition. Geneva: Global Road Safety Partnership, International Federation of Red Cross and Red Crescent Societies; 2023 ([https://www.grsproadsafety.org/wp-content/](https://www.grsproadsafety.org/wp-content/uploads/2023/10/Green-Manual-Speed-revised-edition-16Oct23.pdf) [uploads/2023/10/Green-Manual-Speed-revised](https://www.grsproadsafety.org/wp-content/uploads/2023/10/Green-Manual-Speed-revised-edition-16Oct23.pdf)[edition-16Oct23.pdf,](https://www.grsproadsafety.org/wp-content/uploads/2023/10/Green-Manual-Speed-revised-edition-16Oct23.pdf) accessed 15 June 2023).
+- <span id="page-65-12"></span>32. Drink driving: a road safety manual for decisionmakers and practitioners. Geneva: Global Road Safety Partnership, International Federation of Red Cross and Red Crescent Societies; 2022 ([https://www.grsproadsafety.org/wp-content/](https://www.grsproadsafety.org/wp-content/uploads/2023/09/3094-IFRC-Drink-Driving-Management-manual-revision-Sept-2023.pdf) [uploads/2023/09/3094-IFRC-Drink-Driving-](https://www.grsproadsafety.org/wp-content/uploads/2023/09/3094-IFRC-Drink-Driving-Management-manual-revision-Sept-2023.pdf)[Management-manual-revision-Sept-2023.pdf,](https://www.grsproadsafety.org/wp-content/uploads/2023/09/3094-IFRC-Drink-Driving-Management-manual-revision-Sept-2023.pdf) accessed 15 June 2023).
+- <span id="page-65-13"></span>33. Drug use and road safety: a policy brief. Geneva: World Health Organization; 2016 ( [https://iris.who.](https://iris.who.int/handle/10665/325957) [int/handle/10665/325957,](https://iris.who.int/handle/10665/325957) accessed 15 June 2023).
+- <span id="page-65-14"></span>34. Mobile phone use: a growing problem of driver distraction. Geneva: World Health Organization; 2011 ([https://iris.who.int/handle/10665/44494,](https://iris.who.int/handle/10665/44494) accessed 15 June 2023).
+- <span id="page-65-15"></span>35. Helmets: a road safety manual for decisionmakers and practitioners, second edition. Geneva: World Health Organization; 2023 ([https://iris.who.](https://iris.who.int/handle/10665/366578)
+
+- [int/handle/10665/366578](https://iris.who.int/handle/10665/366578), accessed 15 June 2023).
+- <span id="page-66-0"></span>36. Occupant restraints: a road safety manual for decision-makers and practitioners, second edition. London: FIA Foundation; 2022 ([https://www.who.int/publications/m/item/](https://www.who.int/publications/m/item/occupant-restraints--a-road-safety-manual-for-decision-makers-and-practitioners) [occupant-restraints--a-road-safety-manual-for](https://www.who.int/publications/m/item/occupant-restraints--a-road-safety-manual-for-decision-makers-and-practitioners)[decision-makers-and-practitioners](https://www.who.int/publications/m/item/occupant-restraints--a-road-safety-manual-for-decision-makers-and-practitioners), accessed 15 June 2023).
+- <span id="page-66-1"></span>37. Global report on health equity for persons with disabilities. Geneva: World Health Organization; 2022 [\(https://iris.who.int/handle/10665/364834](https://iris.who.int/handle/10665/364834), accessed 15 June 2023).
+- <span id="page-66-2"></span>38. Resolution WHA Resolution 69.7. In: Sixty-ninth World Health Assembly, Geneva, 28 May 2016. Geneva: World Health Organization; 2016 [\(https://](https://apps.who.int/gb/ebwha/pdf_files/WHA69/A69_R7-en.pdf) [apps.who.int/gb/ebwha/pdf\\_files/WHA69/A69\\_](https://apps.who.int/gb/ebwha/pdf_files/WHA69/A69_R7-en.pdf) [R7-en.pdf](https://apps.who.int/gb/ebwha/pdf_files/WHA69/A69_R7-en.pdf), accessed 2 November 2023).
+- <span id="page-66-3"></span>39. Serious injuries. In: European Commission/ Mobility and transport – road safety [website].
+
+- Brussels: European Commission; 2022 [\(https://](https://road-safety.transport.ec.europa.eu/european-road-safety-observatory/data-and-analysis/serious-injuries_en) [road-safety.transport.ec.europa.eu/european](https://road-safety.transport.ec.europa.eu/european-road-safety-observatory/data-and-analysis/serious-injuries_en)[road-safety-observatory/data-and-analysis/](https://road-safety.transport.ec.europa.eu/european-road-safety-observatory/data-and-analysis/serious-injuries_en) [serious-injuries\\_en,](https://road-safety.transport.ec.europa.eu/european-road-safety-observatory/data-and-analysis/serious-injuries_en) accessed 2 November 2023).
+- <span id="page-66-4"></span>40. Champion HR, Sacco WJ, Copes WS. A revision of the trauma score. Journal of Trauma. 1989;29 (5):623–9 ([https://pubmed.ncbi.nlm.nih.](https://pubmed.ncbi.nlm.nih.gov/2657085/) [gov/2657085/](https://pubmed.ncbi.nlm.nih.gov/2657085/), accessed 15 June 2023).
+- <span id="page-66-5"></span>41. Baghi I, Shokrgozar L, Herfatkar MR. Mechanism of injury, Glasgow Coma Scale, age and systolic Blood pressure: A new trauma scoring system to predict mortality in trauma patients. Trauma Monthy. 2015;20(3):e24473 ([https://www.ncbi.nlm.](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4630599/) [nih.gov/pmc/articles/PMC4630599/,](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4630599/) accessed 15 June 2023).
+- <span id="page-66-6"></span>42. Mwale M, Mwangilwa K, Kakoma E, Iaych K. Estimation of completeness of road traffic mortality data in Zambia using a three source capture recapture method. Accid Anal & Prev. 2023(186);107048 ( [https://doi.org/10.1016/j.](https://doi.org/10.1016/j.aap.2023.107048) [aap.2023.107048,](https://doi.org/10.1016/j.aap.2023.107048) accessed 2 November 2023).
+
+![](_page_67_Picture_0.jpeg)
+
+<span id="page-68-0"></span>![](_page_68_Picture_0.jpeg)
+
+## Annexes
+
+## <span id="page-70-0"></span>Annex 1. Methodology
+
+Since its inception in 2009, WHO's *Global status report on road safety* series has evolved through an iterative and consultative process with participating countries and other territories, while integrating data from a variety of sources.
+
+For this report, the fifth in the series, a consultative Advisory Board was established to evaluate the structure of the four previous reports *[\(1](#page-76-0)[–4\)](#page-76-1)* and outcomes, and to discuss the focus for this report. Following the advice of the Advisory Board, the objectives for this report were broadened to better reflect the Decade of Action for Road Safety 2021–2030 framework.
+
+WHO Regional Advisors established regional networks through their respective WHO Regional Data Focal Points (RDFP) and government-designated National Data Focal Points (NDFP). In turn, NDFPs were invited to seek help from up to 10 National Data Collaborators (NDCs) to foster country-based networks of experts from a variety of backgrounds to arrive at consensual responses to the survey developed for this project and its subsequent legal review. WHO headquarters coordinated the management and data collection processes using online tools, some of which were specifically built for this report. Data validation required frequent consultation with collaborators. For the most part, all processes were handled remotely.
+
+Once the report (including the country and territory profiles) and the summary report were available, feedback was solicited from Advisory Board members, WHO Regional Advisors and Regional Data Focal Points (RDFPs). Estimated mortality figures were shared with countries and territories to enable them to respond to any changes resulting from the verification and validation process. This consultation provided countries with an opportunity to comment on WHO's estimates for road traffic fatalities, which is often much higher than countries' official statistics (see Introduction).
+
+## **Data sources**
+
+This report uses several data sources. These include:
+
+### **a) WHO latest data on modelled deaths by country.**
+
+The statistical models developed were informed by the survey data collected for this report (see point b) below), particularly in relation to the number and distribution of reported fatalities by age and sex, as well as with the vehicle fleet information. However, reported figures are not sufficient, as explained previous reports in this series, and independent publications *[\(5](#page-76-2)[–6](#page-76-3))*. A comprehensive review on mortality estimation methods used by WHO and other institutions is forthcoming.1 WHO DDI produces updated estimates periodically, the latest of which on road traffic deaths, referring to year 2021, are presented in this report. whereas the latest comprehensive estimates (2019) are accessible on the [WHO website Global Health Estimates](https://www.who.int/data/global-health-estimates) [\(who.int\)](http://who.int).
+
+To estimate road traffic deaths (all ages, both sexes), WHO uses an improved regression model as a function of a set of covariates that include measures of economic development, road transport factors and legislation, road use and safety governance/ enforcement, and health system access. In addition, the regression model uses death registration data for the period 2000–2021 that were 80% or more complete for a given year or where the average completeness for last decade was greater or equal to 80%. Death registration cause of death data are submitted to WHO regularly by the national statistics offices or Ministries of Health from around the world, and mostly coded using the 10th revision of the International Classification of Diseases (ICD-10) [\(https://www.who.int/data/data-collection-tools/](https://www.who.int/data/data-collection-tools/who-mortality-database) [who-mortality-database](https://www.who.int/data/data-collection-tools/who-mortality-database)). The regression model produces estimates using ICD-10 *([7\)](#page-76-4)* criteria, which counts all deaths within a calendar year that result from a road traffic crash, regardless of the time period in which they occur (unlike many official road traffic surveillance data sources, where road traffic death data are based on a 30-day definition following a road traffic crash).
+
+<sup>1</sup> An article on the evolution in methods used to produce this series of reports is currently under review for a forthcoming edition of *Injury Prevention*.
+
+- **b) Data collected for this report via the online survey.** Following the advice of the Advisory Board, the survey used for the last report was updated to better reflect the Decade of Action for Road Safety 2021–2030 framework. This required a broadening of the scope of questions which was partly offset by removing redundant questions or questions leading to unreliable answers. The new survey was reviewed by Advisory Board members and WHO Headquarters and Regional Advisors on Injury. The survey was machine-translated into all six official UN languages and distributed by RDFPs to NDFPs (and, where requested, to NDCs). Data collection ran from September 2022 to August 2023. A copy of the original survey in English is available.2 Training on the use of the platform was done via online meetings in all six UN official languages during the third quarter of 2022. Data validation involved verifying data against source documents where available and checking for logical inconsistencies. Using an online platform allowed for controls at several levels, from data entry limitations to higher-level approval of submitted data. Discrepancies were referred, where possible, to the NDFPs for resolution. The platform allowed for the uploading of support documents as needed. Data in the survey was requested in relation to 2021 or as close to it as possible.
+- **c) WHO review of legislation and related information collected for the** *Global status report on road safety 2023***.** The WHOgenerated survey included question on several legislation matters encompassing post-crash care, infrastructure, vehicles, and road user behaviour, and totalling 25 specific legislation areas. Using the answers to the survey (see point b) above) and support legislation documentation provided by country contributors or identified in legal libraries and/or via the Internet, a team of experienced and trained lawyers validated the existence of 17 of these 25 legislative areas. In-depth evaluation of five of the 25 was done (Annex 3 lists all 25 and whether they were: only reported, validated, or evaluated). The legal reviewers were native speakers of English, French, Spanish, Arabic and Chinese. They used translations into English of legislation written in other languages. The review lasted from January to September 2023. Legislation had to be active by December 31, 2022, to be included. The legal analysis was then shared with NDFPs, and a validation process was undertaken to resolve any data conflicts through discussion and/ or submission of new legal documents. The WHO evaluation process has evolved over time as the review itself has led to refinements to the criteria to better reflect evidence and practice, as well to the review of additional legislation. Table A1.1 presents whether there is comparability of seven legislation areas reviewed with earlier editions of the *Global status report on road safety.*
+
+Table A1.1 Comparability between all editions of the Global status report on road safety for selected legislation best practice
+
+| 2023                        | 2018 | 2015 | 2013 | 2009 |
+|-----------------------------|------|------|------|------|
+| Speed                       | Yes  | Yes  | No   | No   |
+| Seat-belts use              | Yes  | Yes  | No   | No   |
+| Child restraint systems use | Yes  | No   | No   | No   |
+| Helmets use                 | Yes  | Yes  | No   | No   |
+| Drink & drive               | Yes  | Yes  | No   | No   |
+| Drug & drive                | Yes  | No   | No   | No   |
+| Distraction                 | Yes  | No   | No   | No   |
+|                             |      |      |      |      |
+
+<sup>2</sup> For a copy of the survey in English with operational instructions, please contact [sam@who.int](mailto:sam@who.int).
+
+- **d) Data from all previous editions of WHO's** *Global status report on road safety* (2009, 2013, 2015 and 2018), including data on participation; gaps between reported and estimated road traffic fatalities; and all variables presented in these reports' statistical annexes. These data were originally gathered by government designated representatives in participating countries or territories and had undergone government clearance prior to publication, as described in original reports. In depth legal reviews for the seven legislation areas described in Table A1.1 were also compiled.
+- **e)** Data on country populations (including persons under the age of 11 years) as of 1 July 2021 and 2010 were drawn from the UN Population Division *[\(8\)](#page-77-0).*
+- **f)** Data on income level per country clustered into high-, upper-middle, lower-middle, and low- income categories were extracted from the World Bank *([9\)](#page-77-1).*
+- **g)** Data on 2010 and 2021 UN or equivalent conventions and regulations on vehicles, roads and drivers, extracted from UN Economic Commission for Europe (UNECE) *[\(10](#page-77-2))* and the UN Treaty Collection *[\(11](#page-77-3))*.
+- **h)** Data on mobility patterns, self-reported behaviours, and perceived enforcement on selected behavioural related aspects (speeding, alcohol or drug consumption, mobile phone use, use of seat-belts, child restraint systems or helmets) were drawn from the E-survey of Road users' Attitudes (ESRA) initiative coordinated by Vias institute *[\(12\)](#page-77-4)* (these data are available for 48 of countries and territories).
+- **i)** Data on road density and safety score ratings were obtained from the International Road Federation's World Road Statistics *[\(13](#page-77-5))* while data on safety scoring or roads by user type were obtained from iRAP *[\(14\)](#page-77-6)*.
+- **j)** Case studies and testimonials were collected to address areas of the Global Plan for the Decade of Action for Road Safety 2021–2030 not sufficiently covered in all other data sources. A call for case studies on targeted areas was shared with NDFPs via the Regional Advisers.
+
+## **Data management**
+
+Integrating these data sources allowed the development of a selection of indicators used in the country and territory profiles as well as an update of the mobile application. For a description of indicators used in the text of this report or the Country and territory profiles, please see Annexes 5 and 6. The next paragraphs provide more detailed explanations on the development of two selected data elements: road fatalities and the legal reviews.
+
+**Road fatalities.** Government reported fatalities and their distribution by sex, age, user type and work connection were collected through the report-specific survey. Some of these values are included in the Country and territory profiles. The reported deaths are also used in the mathematical models to estimate the number of road traffic for the reasons described above. The regression models used to estimate road traffic deaths are the same as those of the previous reports with updated Civil Registration and Vital Statistics (CRVS) data for the period 2000–2021. A time series for each covariate was used for this period for each country.
+
+As in the previous reports, countries are classified based on their CRVS data into: Group 1 (countries with death registration data), Group 2, Group 3 (countries with population less than 150 000 population), and Group 4 (countries without eligible death registration data). The novelty in this report is that former Group 2 has been subdivided into groups 2A and 2b based on the status of their data systems improvements.
+
+Group 2A: Countries that have death registration data shared with WHO but face certain limitations. These limitations could be related to the number of data observations being insufficient (not equal to or less than 5), or the data quality not being high enough to classify them in Group 1, which likely represents countries with the best data quality. In such cases, WHO has supported these countries in improving their data collection and estimation methods. Instead of relying on a single data source for the entire population, these countries have conducted a linkage of data from various stakeholders. The capture-recapture method used to estimate the number of road traffic deaths for a specific year.
+
+Group 2B: Countries that are still in the process of enhancing their systems for recording road traffic deaths. The completeness of death registration data, particularly for the causes of death related to road traffic incidents, is relatively low, at around 30%. These countries conducted a linkage of data from sources other than just police records with the support of WHO. The focus of these efforts is limited to specific geographical areas, such as the capital or a district within the capital. This may be due to resource constraints or a phased approach to improving data collection and reporting.
+
+Whether a Member State belongs to a Group, or another is shown in the Country and territory profile. The specific methodology to derive estimated road fatalities and their 95% Confidence Interval varies by Group, but the methods are those used in the previous report *([5](#page-76-2)).* As in previous reports, countries or territories in Group 4 were handled using three separate negative binominal regression models. One of two peculiarities for this report lies on the fact that due to the disruptive impact of the COVID-19 pandemic on typical trends, the estimates derived from the negative binomial regression model for the years 2020 and 2021 were not used. The second peculiarity is that in the case of China and India, the estimated road traffic deaths data from Global Health Estimates (GHE) 2020 were used to account for road traffic deaths from 2000 to 2019. Subsequently, the rate of change between reported deaths in 2020 and 2019 was used as correction coefficient to estimate the deaths for 2020 and using the rate of change between reported deaths in 2021 and 2019 as correction coefficient to estimate the deaths for 2021.
+
+**Legislation.** This report presents reviewed national legislation on 22 road-related topics. For five of these topics (urban speed control, drinking and driving, motorcycle helmet use, seat-belts and child restraint restraints), equivalent information was gathered in a comparable format in previous reports as shown in Table A1.1, and best criteria are described in corresponding sections of the report and in Annex 6. These criteria are used to qualify the legislation into one of several categories, although we acknowledge that these are, de facto "minimal criteria" for the laws to have a significant safety impact. For two other topics (drugs and driving, and distracted driving), comparable data are available from all reports since the *Global status report on road safety 2015*. However, no evaluation criteria are available for these areas. Seventeen other legislative areas are evaluated and presented for the first time in this report including professional drivers' rest periods, vehicle safety (five specific aspects),3 vehicle registration and inspection, third-party vehicle insurance, road and infrastructure, access to emergency assistance, rehabilitation assistance or psychological assistance for road traffic victims, and good Samaritan laws. Three other legislative areas were not validated or evaluated but reported answers by participated countries are presented in the report. Annex 3 presents all legislative areas and the level of validation and evaluation they underwent. There are three countries whose legislation had to be reviewed at subnational level for all or some of these legislation areas because the topics are delegated to and within the jurisdiction of the subnational authorities. These countries are Australia, Canada, and the United States of America. These countries are classified as having a law at national level if 80% of their subnational entities meet the selected criteria for best practise or the existence of legislation on the topic.
+
+The population covered by these legistlations is shown in Annex 3. Calculations use general population country figures for all legislative areas except child restraint systems, whose impact is calculated in relation to the population aged below 11 years in each country.
+
+## **Data analysis**
+
+This is a descriptive report and the primary unit of analyses are Member States themselves, which we refer to as "countries" in the text, however, in Annex 3, some indicators are based on population. The analyses are kept at global level and variations by region and income level are presented. Compared with other editions of the *Global status report on road safety*, we present more income-based analyses in following with the Plan of Action recommendation to focus on low- and middleincome countries.
+
+In addition, as part of its evolutionary focus, comparison between the findings of the fifth report and the earliest available data within the Decade of Action for Road Safety 2011–2020 are presented throughout the report and in the Country and territory profiles. This implies using revised WHO mortality estimates since 2010, other 2010 information such as population, income level, adherence to conventions or regulations, etc., and the country-generated data via the *Global status report on road safety 2013.* As stated above, for selected legislative
+
+<sup>3</sup> In previous reports, vehicle safety has been addressed through the accession to UN or equivalent safety regulations. On this occasion, national-level legislation was also reviewed.
+
+comparisons we had to rely on the Global status report on road safety 2015 or 2018 for comparability criteria, although changes since the 2018 one prioritized through the report.
+
+Where change can be documented, a quantitative value of the magnitude of change and a qualitative value have been created. Differences larger than 2% are presented as "increases" or "decreases" (depending on direction). Differences of 2% or less are presented as "no change". In other instances, change is not quantifiable, although it can be a change that implies a step forward towards "better" situations. In those cases, "change" or "advancement" are used to describe the evolution. Changes in fatality counts on rates for countries with populations less than 200 000 population are not reported.
+
+For countries not participating in the *Global status report on road safety 2023*, no evolutionary analyses are shown, and their profiles contain their latest information, including the 2021 mortality estimates.
+
+## **Participation results**
+
+All 194 countries were formally invited to collaborate in this report. In addition, two territories requested to participate.4
+
+The 194 WHO countries represent 98% of the world's population, whereas the 170 countries participating in the survey represent 97% of the world's population. Participation by WHO region and income level was even, as shown in Table A1.2.
+
+<sup>4</sup> Participating territories are: British Virgin Islands (high income, Region of the Americas) and occupied Palestinian territory, including east Jerusalem (lowermiddle-income, Eastern Mediterranean Region).
+
+Table A1.2 Number of participating countries by WHO region and income level, 2021
+
+| Participating / Member states | High-income | Upper-middle<br>income | Lower-middle<br>income | Low-income | Total        |
+|-------------------------------|-------------|------------------------|------------------------|------------|--------------|
+| African Region                | 1/1         | 5/6                    | 17/18                  | 22/22      | 45/47        |
+| Region of the Americas        | 8/9         | 17/19                  | 5/5                    | 0/0        | 32/35        |
+| South-East Asia Region        | 0/0         | 2/2                    | 8/8                    | 0/1        | 10/11        |
+| European Region               | 30/34       | 14/15                  | 3/4                    | 0/0        | 47/53        |
+| Eastern Mediterranean Region  | 6/6         | 3/3                    | 6/7                    | 5/5        | 20/21        |
+| Western Pacific Region        | 6/8         | 1/7                    | 7/11                   | 0/0        | 16/27        |
+| Total                         | 51/58       | 43/52                  | 46/53                  | 27/28      | 170a<br>/194 |
+
+*a Cook Islands, Niue and Venezuela (Bolivarian Republic of) are only listed under regional totals as their income level is unknown.*
+
+NDFPs and NDCs for the 172 participating states or territories total nearly 1000 individuals. It is worth pointing out that in 50 participating countries there was one collaborator who was also their country representative in a Regional Road Safety Observatory, as suggested in UN GA74/299 *[\(15](#page-77-7)).* Additional 100 professionals have participated in the production of this report, including WHO headquarters staff, regional advisors, RDFPs and consultants participating in data management, communications, and coordination.
+
+#### **Other**
+
+Data from their participation in *the Global status report on road safety 2018* was used for 135 of the 24 not participating in *the Global status report on road safety 2023*. Six other non-participating countries had last contributed to *the Global status report on road safety 2015*. <sup>6</sup> Among the remaining five non-participating countries, three last did in *the Global status report on road safety 2013*<sup>7</sup> and only for two did we use *the Global status report on road safety 2009* (which was their first and last participation).8 Mortality estimates for 2021 for the 24 non-participating countries are, on average 16 per 100 000 population, a figure very close to the average rate for participating countries (15 per 100 000 population).
+
+Notably, all countries have participated at least once in the *Global status report on road safety* since it was first published. One hundred and forty-six countries (plus one territory) have participated in all five of them (Fig. A1.1).
+
+<sup>5</sup> Angola, Equatorial Guinea, Fiji, Grenada, Micronesia (Federated States of), Papua New Guinea, Romania, San Marino, Solomon Islands, Tonga, Turkmenistan, Ukraine, Vanuatu.
+
+<sup>6</sup> Andorra, Djibouti, Marshall Islands, Monaco, Palau (Republic of), Saint Vincent and the Grenadines.
+
+<sup>7</sup> Brunei Darussalam, Democratic People's Republic of Korea, Saint Kitts and Nevis.
+
+<sup>8</sup> Nauru, Tuvalu.
+
+![](_page_76_Figure_0.jpeg)
+
+![](_page_76_Figure_1.jpeg)
+
+Overall, completion rates for the report survey exceeds 70% of the requested information, with more gaps occurring in the areas of work relationship of the crash, road density and financing arrangements for road safety
+
+Supporting documents, including legal documents, are in custody at WHO headquarters. All data used in the Country and territory profiles are publicly available except those of the International Road Federation.
+
+## **Annex 1 references**
+
+- <span id="page-76-0"></span>1. Global status report on road safety: time for action. Geneva: World Health Organization; 2009 [\(https://apps.who.int/iris/](https://apps.who.int/iris/handle/10665/44122?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [handle/10665/44122?search-result=true&query](https://apps.who.int/iris/handle/10665/44122?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [=global+status+report+on+road+safety&scope](https://apps.who.int/iris/handle/10665/44122?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [=&rpp=10&sort\\_by=score&order=desc&page=1,](https://apps.who.int/iris/handle/10665/44122?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) accessed 15 June 2023).
+- 2. Global status report on road safety 2013: supporting a decade of action. Geneva: World Health Organization; 2013 [\(https://apps.who.int/](https://apps.who.int/iris/handle/10665/78256?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [iris/handle/10665/78256?search-result=true&qu](https://apps.who.int/iris/handle/10665/78256?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [ery=global+status+report+on+road+safety&scop](https://apps.who.int/iris/handle/10665/78256?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [e=&rpp=10&sort\\_by=score&order=desc&page=1](https://apps.who.int/iris/handle/10665/78256?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1), accessed 15 June 2023).
+- 3. Global status report on road safety 2015. Geneva: World Health Organization; 2015 [\(https://apps.](https://apps.who.int/iris/handle/10665/189242?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [who.int/iris/handle/10665/189242?search-res](https://apps.who.int/iris/handle/10665/189242?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1)
+
+- [ult=true&query=global+status+report+o](https://apps.who.int/iris/handle/10665/189242?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [n+road+safety&scope=&rpp=10&sort\\_](https://apps.who.int/iris/handle/10665/189242?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [by=score&order=desc&page=1,](https://apps.who.int/iris/handle/10665/189242?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) accessed 15 June 2023).
+- <span id="page-76-1"></span>4. Global status report on road safety 2018. Geneva: World Health Organization; 2018 [\(https://apps.](https://apps.who.int/iris/handle/10665/276462?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [who.int/iris/handle/10665/276462?search](https://apps.who.int/iris/handle/10665/276462?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1)[result=true&query=global+status+report](https://apps.who.int/iris/handle/10665/276462?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [+on+road+safety&scope=&rpp=10&sort\\_](https://apps.who.int/iris/handle/10665/276462?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [by=score&order=desc&page=1,](https://apps.who.int/iris/handle/10665/276462?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) accessed 15 June 2023).
+- <span id="page-76-2"></span>5. Global status report on road safety 2018, explanatory note 3: Estimation of total road traffic deaths. Geneva: WHO; 2018 [https://apps.who.int/](https://apps.who.int/iris/handle/10665/276462?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [iris/handle/10665/276462?search-result=true&qu](https://apps.who.int/iris/handle/10665/276462?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [ery=global+status+report+on+road+safety&scop](https://apps.who.int/iris/handle/10665/276462?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) [e=&rpp=10&sort\\_by=score&order=desc&page=1,](https://apps.who.int/iris/handle/10665/276462?search-result=true&query=global+status+report+on+road+safety&scope=&rpp=10&sort_by=score&order=desc&page=1) accessed 15 June 2023).
+- <span id="page-76-3"></span>6. Papadimitriou E, Iaych K, Adamantiadis M. Understanding and bridging the differences between country-reported and WHO estimated road traffic fatality data. Brussels: WHO and EuroMed TSP; 2019 [http://etsp.](http://etsp.eu/?page_id=24985&mdocs-cat=mdocs-cat-74&mdocs-att=nul) [eu/?page\\_id=24985&mdocs-cat=mdocs-cat-](http://etsp.eu/?page_id=24985&mdocs-cat=mdocs-cat-74&mdocs-att=nul)[74&mdocs-att=nul,](http://etsp.eu/?page_id=24985&mdocs-cat=mdocs-cat-74&mdocs-att=nul) accessed 15 June 2023).
+- <span id="page-76-4"></span>7. International Classification of Diseases – 10th Revision. Geneva: World Health Organization; 2019 (https://icd.who.int/browse10/2019/en#/, accessed 15 June 2023).
+
+- <span id="page-77-0"></span>8. UN Population Division [online database]. New York (NY): United Nations; 2022 [\(https://](https://population.un.org/wpp/) [population.un.org/wpp/](https://population.un.org/wpp/), accessed 15 June 2023).
+- <span id="page-77-1"></span>9. World Bank Country and Lending groups [online database]. Washington (DC): World Bank; 2022 ([https://datahelpdesk.worldbank.org/](https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups) [knowledgebase/articles/906519-world-bank](https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups)[country-and-lending-groups,](https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups) accessed 15 June 2023).
+- <span id="page-77-2"></span>10. United Nations Economic Commission for Europe. United Nations Road Safety Conventions, Geneva, 2020 [\(https://unece.org/transport/publications/](https://unece.org/transport/publications/united-nations-road-safety-conventions) [united-nations-road-safety-conventions,](https://unece.org/transport/publications/united-nations-road-safety-conventions) accessed 15 June 2023).
+- <span id="page-77-3"></span>11. United Nations. Treaty Collection [online database]. New York (NY): United Nations; [no date] [\(https://treaties.un.org/Pages/](https://treaties.un.org/Pages/ViewDetails.aspx?src=TREATY&mtdsg_no=XI-B-34&chapter=11&clang=_en) [ViewDetails.aspx?src=TREATY&mtdsg\\_no=XI-B-](https://treaties.un.org/Pages/ViewDetails.aspx?src=TREATY&mtdsg_no=XI-B-34&chapter=11&clang=_en)[34&chapter=11&clang=\\_en](https://treaties.un.org/Pages/ViewDetails.aspx?src=TREATY&mtdsg_no=XI-B-34&chapter=11&clang=_en), accessed 15 February 2023).
+- <span id="page-77-4"></span>12. Meesmann U, Wardenier N, Torfs K, Pires C, Delannoy S, Van den Berghe W. A global look at road safety. Synthesis from the ESRA2 survey in 48 countries. ESRA project 2022 (E-Survey of Road users' Attitudes). Brussels: Vias institute; 2022 [\(https://www.esranet.eu/storage/minisites/](https://www.esranet.eu/storage/minisites/esra2-main-report-def.pdf) [esra2-main-report-def.pdf](https://www.esranet.eu/storage/minisites/esra2-main-report-def.pdf), accessed 15 June 2023).
+- <span id="page-77-5"></span>13. World road statistics [online database]. Geneva: International Road Federation; 2023 ([www.irfnet.](http://www.irfnet.ch) [ch](http://www.irfnet.ch) and [www.worldroadstatistics.org](http://www.worldroadstatistics.org/), accessed 28 September 2023).
+- <span id="page-77-6"></span>14. iRAP Safety Insights Explorer [Internet]. London: iRAP, 2021 [\(https://irap.org/safety-insights](https://irap.org/safety-insights-explorer/)[explorer/](https://irap.org/safety-insights-explorer/), accessed 7 November 2023).
+- <span id="page-77-7"></span>15. UN General Assembly resolution 74/299. Improving global road safety. United Nations: New York (NY); 2020 [\(https://digitallibrary.un.org/](https://digitallibrary.un.org/record/3879711) [record/3879711](https://digitallibrary.un.org/record/3879711), accessed 15 June 2023).
+
+## <span id="page-78-0"></span>Annex 2. Progress towards the voluntary UN Performance Targets
+
+Twelve Voluntary Performance Targets were set out to help direct efforts to achieve the 50% fatality and non-fatal reduction in road traffic victims worldwide. In addition, a series of indicators totalling 34 were proposed to allow monitoring progress towards the targets. Table A2.1 shows their first global assessment. Performance at country level for several of them are shown in the Country and territory profiles. Adaptation of the proposed indicators to existing data (and results) resulted in some deviations, for example that instead of counting Member states reaching 100% objectives, we count for countries reaching at least 80% objectives. Similarly, "effective enforcement" was not able to be assessed for several indicators. Albeit imperfect, the emerging picture is that there are big gaps in covering these, even among high-income member states. There nine proposed indicators that could not be assessed at this time.
+
+Table A2.1. Status of UN Voluntary Target Performance indicators, Global and by income level, 2021
+
+| Target                                                                                                                            | Indicators                                                                                                                              | Number of countries      |                |                           |                           |               |  |
+|-----------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------|--------------------------|----------------|---------------------------|---------------------------|---------------|--|
+|                                                                                                                                   |                                                                                                                                         |                          |                |                           | Income levelsa            |               |  |
+|                                                                                                                                   |                                                                                                                                         | All<br>N=(170)           | High<br>(N=51) | Upper<br>middle<br>(N=43) | Lower<br>middle<br>(N=46) | Low<br>(N=27) |  |
+| Target 1                                                                                                                          | Published national action plan                                                                                                          | 17                       | 9              | 5                         | 3                         | 0             |  |
+| By 2020, all countries establish<br>a comprehensive multisectoral<br>national road safety action<br>plan with time-bound targets. | that provides for regularly<br>updated, time-bound targets for<br>reductions in fatalities and injuries                                 |                          |                |                           |                           |               |  |
+|                                                                                                                                   | Presence of national lead agency<br>to coordinate, monitor, evaluate<br>and implement multisectoral<br>national road safety action plan | 84                       | 23             | 26                        | 24                        | 11            |  |
+| Target 2                                                                                                                          | Ratification or accession, and                                                                                                          | 128                      | 50             | 33                        | 31                        | 14            |  |
+| By 2030, all countries accede<br>to one or more of the core<br>road safety-related UN<br>legal instruments.                       | adhesion, to one or more core<br>road safety-related UN legal<br>instruments (out of seven)                                             | (only 7<br>MS<br>have 7) |                |                           |                           |               |  |
+
+| Target                                                                                                                                                                              | Indicators                                                                                                                                                                   |                          | Number of countries                                                       |                                                                          |                                                                           |                                                                          |  |
+|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------|---------------------------------------------------------------------------|--------------------------------------------------------------------------|---------------------------------------------------------------------------|--------------------------------------------------------------------------|--|
+|                                                                                                                                                                                     |                                                                                                                                                                              |                          | Income levelsa                                                            |                                                                          |                                                                           |                                                                          |  |
+|                                                                                                                                                                                     |                                                                                                                                                                              | All<br>N=(170)           | High<br>(N=51)                                                            | Upper<br>middle<br>(N=43)                                                | Lower<br>middle<br>(N=46)                                                 | Low<br>(N=27)                                                            |  |
+| Target 3<br>By 2030, all new roads achieve<br>technical standards for all road<br>users that take account of<br>road safety or meet a three                                         | Presence of technical standards<br>for new roads that take account<br>of all road-user safety, or align<br>with relevant UN Conventions and<br>regulate compliance with them | 61                       | 27                                                                        | 16                                                                       | 17                                                                        | 1                                                                        |  |
+| star rating or better.                                                                                                                                                              | Use of systematic approaches to<br>assess/audit new roads                                                                                                                    | 120                      | 38                                                                        | 31                                                                       | 33                                                                        | 18                                                                       |  |
+| Target 4<br>By 2030, more than 75% of<br>travel on existing roads is on<br>roads that meet technical                                                                                | Plan for improvement of existing<br>roads that take account of the<br>safety of all road users developed<br>and implemented                                                  | Cannot be calculated yet |                                                                           |                                                                          |                                                                           |                                                                          |  |
+| standards for all road<br>users that take account of<br>road safety.                                                                                                                | Use of systematic approaches to<br>assess/audit existing roads                                                                                                               | Cannot be calculated yet |                                                                           |                                                                          |                                                                           |                                                                          |  |
+| Target 5<br>By 2030, 100% of new (defined                                                                                                                                           | Presence of high-quality safety<br>standards for new vehicles                                                                                                                | 93                       | 38                                                                        | 22                                                                       | 25                                                                        | 8                                                                        |  |
+| as produced, sold or imported)<br>and used vehicles meet high                                                                                                                       | Use of systematic approaches for<br>vehicle assessments                                                                                                                      | 134                      | 48                                                                        | 30                                                                       | 36                                                                        | 20                                                                       |  |
+| quality safety standards,<br>such as the recommended<br>priority UN Regulations, Global<br>Technical Regulations, or<br>equivalent recognized national<br>performance requirements. | Presence of high-quality safety<br>standards for used-vehicle<br>exports                                                                                                     | 113                      | 35                                                                        | 31                                                                       | 32                                                                        | 15                                                                       |  |
+| Target 6<br>By 2030, halve the proportion<br>of vehicles travelling over the<br>posted speed limit and achieve<br>a reduction in speeding<br>related injuries and fatalities.       | Speed-control legislation been<br>strengthened since last reporting                                                                                                          |                          | 26; 3<br>since<br>Global<br>status<br>report<br>on road<br>safety<br>2018 | 9; 7<br>since<br>Global<br>status<br>report<br>on road<br>safety<br>2018 | 10; 0<br>since<br>Global<br>status<br>report<br>on road<br>safety<br>2018 | 8; 0<br>since<br>Global<br>status<br>report<br>on road<br>safety<br>2018 |  |
+|                                                                                                                                                                                     | Proportion of vehicles travelling<br>over the posted speed limit have<br>reduced by half                                                                                     | Cannot be calculated yet |                                                                           |                                                                          |                                                                           |                                                                          |  |
+|                                                                                                                                                                                     | Presence of national and, where<br>applicable, subnational data<br>systems on speeding violations<br>and speeding-related injuries and<br>fatalities                         | 154                      | 47                                                                        | 41                                                                       | 42                                                                        | 24                                                                       |  |
+|                                                                                                                                                                                     | Reductions in speeding-related<br>injuries and fatalities have been<br>achieved                                                                                              | Cannot be calculated yet |                                                                           |                                                                          |                                                                           |                                                                          |  |
+
+| Target                                                                                                                        | Indicators                                                                                                                                                 | Number of countries                                  |                        |                           |                           |                        |  |
+|-------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------|------------------------|---------------------------|---------------------------|------------------------|--|
+|                                                                                                                               |                                                                                                                                                            |                                                      | Income levelsa         |                           |                           |                        |  |
+|                                                                                                                               |                                                                                                                                                            | All<br>N=(170)                                       | High<br>(N=51)         | Upper<br>middle<br>(N=43) | Lower<br>middle<br>(N=46) | Low<br>(N=27)          |  |
+| Target 7<br>By 2030, increase the<br>proportion of motorcycle<br>riders correctly using standard<br>helmets to close to 100%. | Presence of legislation requiring<br>ADULT motorcycle riders to wear<br>a helmet properly fastened and<br>meeting appropriate standards2<br>for protection | 49                                                   | 21                     | 12                        | 14                        | 2                      |  |
+|                                                                                                                               | Effective enforcementb of helmet<br>use legislation                                                                                                        | 85                                                   | 27                     | 22                        | 23                        | 13                     |  |
+|                                                                                                                               | Regulations on safety for (child<br>and) adult helmets sold                                                                                                | 93                                                   | 37                     | 23                        | 25                        | 8                      |  |
+|                                                                                                                               | Presence of national and, where<br>applicable, subnational data<br>systems on helmet use                                                                   | 105                                                  | 40                     | 29                        | 23                        | 13                     |  |
+|                                                                                                                               | Proportion of motorcycle riders<br>correctly using helmets is close<br>to 100%c                                                                            | 32                                                   | 20                     | 7                         | 4                         | 1                      |  |
+| Target 8<br>By 2030, increase the<br>proportion of motor vehicle<br>occupants using safety belts                              | Legislative improvements made<br>since last reporting towards best<br>practice standards                                                                   | 108<br>(improvement<br>in 10 Seat-belt<br>and 4 CRS) | 46<br>(2 SB:<br>0 CRS) | 33<br>(2 SB:<br>3 CRS)    | 18<br>(3 SB:<br>1 CRS)    | 11<br>(3 SB:<br>0 CRS) |  |
+| or standard child restraint<br>systems to close to 100%.                                                                      | Presence of effectively enforced<br>b legislation requiring the use of<br>child restraint systems that meet<br>appropriate standards                       | Cannot be calculated yet                             |                        |                           |                           |                        |  |
+|                                                                                                                               | Proportion of all motor vehicle<br>occupants using safety belts is<br>close to 100% c                                                                      | 12                                                   | 12                     | 0                         | 0                         | 0                      |  |
+|                                                                                                                               | Proportion of all child motor<br>vehicle occupants using standard<br>child restraints systems is close<br>to 100% c                                        | Cannot be calculated yet                             |                        |                           |                           |                        |  |
+|                                                                                                                               | Effective enforcement b of safety<br>regulations for child restraint<br>systems sold                                                                       | cannot be calculated yet                             |                        |                           |                           |                        |  |
+|                                                                                                                               | Presence of national and, where<br>applicable, subnational data on<br>use of safety belts, as well as the<br>appropriate use of child restraint<br>systems | 63                                                   | 32                     | 16                        | 8                         | 7                      |  |
+
+| Target                                                                                                                                                                                                           | Indicators                                                                                                                                                                                                        | Number of countries                                             |                    |                           |                           |                    |  |
+|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------|--------------------|---------------------------|---------------------------|--------------------|--|
+|                                                                                                                                                                                                                  |                                                                                                                                                                                                                   |                                                                 | Income levelsa     |                           |                           |                    |  |
+|                                                                                                                                                                                                                  |                                                                                                                                                                                                                   | All<br>N=(170)                                                  | High<br>(N=51)     | Upper<br>middle<br>(N=43) | Lower<br>middle<br>(N=46) | Low<br>(N=27)      |  |
+| Target 9<br>By 2030, halve the number<br>of road traffic injuries<br>and fatalities related to<br>drivers using alcohol, and/<br>or achieve a reduction<br>in those related to other<br>psychoactive substances. | Presence of legislation (and<br>effective enforcement) on driving<br>under the influence of alcohol and/<br>or other psychoactive substances<br>(based on alcohol laws)                                           | 47                                                              | 28                 | 12                        | 6                         | 1                  |  |
+|                                                                                                                                                                                                                  | Availability of national and, where<br>applicable, subnational data on<br>driving under the influence of<br>alcohol and/or psychoactive<br>substances and related road<br>traffic-related fatalities and injuries | 114                                                             | 41                 | 32                        | 27                        | 14                 |  |
+|                                                                                                                                                                                                                  | Road traffic injuries and fatalities<br>related to driving under the<br>influence of alcohol and/or other<br>psychoactive substances have<br>reduced by half                                                      | Cannot be calculated yet                                        |                    |                           |                           |                    |  |
+| Target 10<br>By 2030, all countries have<br>national laws to restrict or                                                                                                                                         | Effectively enforcedb legislation on<br>restricting or prohibiting the use<br>of mobile phones while driving                                                                                                      | 153<br>(8 since Global<br>status report on<br>road safety 2018) | 50<br>before<br>31 | 41<br>before<br>32        | 41<br>before<br>30        | 21<br>before<br>19 |  |
+| prohibit the use of mobile<br>phones while driving.                                                                                                                                                              | Presence of national and, where<br>applicable, subnational data<br>systems on the use of mobile<br>phones while driving                                                                                           | 91                                                              | 34                 | 24                        | 22                        | 11                 |  |
+| Target 11<br>By 2030, all countries to enact<br>regulation for driving time and<br>rest periods for professional                                                                                                 | Presence of international/regional<br>regulation on driving time and<br>rest periods for professional<br>drivers                                                                                                  | 45                                                              | 28                 | 14                        | 3                         | 0                  |  |
+| drivers, and/or accede<br>to international/regional<br>regulation in this area.                                                                                                                                  | Professional drivers' driving time<br>and rest periods are regulated,<br>effectively enforced, and audited                                                                                                        | 83                                                              | 40                 | 20                        | 18                        | 5                  |  |
+| Target 12<br>By 2030, all countries<br>establish and achieve national<br>targets in order to minimize                                                                                                            | National target met for time<br>between serious crash-related<br>injury and initial provision of<br>professional emergency care                                                                                   | Cannot be calculated yet                                        |                    |                           |                           |                    |  |
+| the time interval between<br>road traffic crash and the<br>provision of first professional<br>emergency care.                                                                                                    | Presence of agencies that<br>effectively coordinate pre<br>hospital and facility-based<br>emergency medical services                                                                                              | 118                                                             | 35                 | 32                        | 33                        | 18                 |  |
+
+- a Total does not add to 170 because of the three Member States with no information on income.
+- b No assessment on effectivity of enforcement is available.
+- c Use equal or higher than 80% was considered sufficient.
+
+## **Annex 2 reference**
+
+1. Voluntary global performance targets for road safety risk factors and service delivery mechanisms and corresponding indicators. Geneva: World Health Organization; 2018 [\(https://cdn.who.int/media/](https://cdn.who.int/media/docs/default-source/documents/un-road-safety-collaboration/targets-and-indicators-visual-clean.pdf?sfvrsn=29627bde_5)
+
+[docs/default-source/documents/un-road-safety](https://cdn.who.int/media/docs/default-source/documents/un-road-safety-collaboration/targets-and-indicators-visual-clean.pdf?sfvrsn=29627bde_5)[collaboration/targets-and-indicators-visual-clean.](https://cdn.who.int/media/docs/default-source/documents/un-road-safety-collaboration/targets-and-indicators-visual-clean.pdf?sfvrsn=29627bde_5) [pdf?sfvrsn=29627bde\\_5,](https://cdn.who.int/media/docs/default-source/documents/un-road-safety-collaboration/targets-and-indicators-visual-clean.pdf?sfvrsn=29627bde_5) accessed 15 June 2023).
+
+## <span id="page-82-0"></span>Annex 3. Population covered by selected road safetyrelated measures
+
+The report focuses on Member State-based data. Table A3.1 presents the percentage of the world population that is covered by selected road safety interventions.
+
+Table A3.1 Percentage of population living in countries with selected road safety laws, by income level, 2022
+
+|                                                                                                                                                                              |        | Income levela |                 |                 |     |  |
+|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------|---------------|-----------------|-----------------|-----|--|
+|                                                                                                                                                                              | Global | High          | Upper<br>middle | Lower<br>middle | Low |  |
+| Countries                                                                                                                                                                    | 170    | 51            | 43              | 46              | 27  |  |
+| Population (Million)                                                                                                                                                         | 7 874  | 1 233         | 2 526           | 3 397           | 718 |  |
+| Legislation reported, validated and evaluated (thus percentages reflect the percentage of the population whose<br>countries have these laws meeting best practice criteria): |        |               |                 |                 |     |  |
+| Legislation setting appropriate urban speed limits for 4-wheel and<br>powered 2/3 wheelers                                                                                   | 42     | 48            | 69              | 22              | 27  |  |
+| Legislation on drink driving                                                                                                                                                 | 33     | 34            | 72              | 12              | 3   |  |
+| Legislation requiring adult motorcycle riders to wear a helmet                                                                                                               | 39     | 30            | 22              | 62              | 4   |  |
+| Legislation on the use of seat-belts                                                                                                                                         | 72     | 68            | 89              | 65              | 46  |  |
+| Legislation requiring the use of child restraint systemsb                                                                                                                    | 10     | 42            | 21              | 2               | 0   |  |
+| Legislation reported and validated, but not evaluated (Thus % reflect population whose countries have these laws<br>regardless of details):                                  |        |               |                 |                 |     |  |
+| Legislation on drug driving                                                                                                                                                  | 94     | 100           | 100             | 92              | 76  |  |
+| Legislation on distracted driving (mobile phones)                                                                                                                            | 93     | 100           | 100             | 90              | 75  |  |
+| Legislation on driver licensing requirements                                                                                                                                 | 93     | 85            | 98              | 91              | 96  |  |
+| National law on vehicle registration                                                                                                                                         | 91     | 84            | 93              | 91              | 96  |  |
+| National law requiring a formal road safety inspection/assessment                                                                                                            | 58     | 67            | 66              | 59              | 14  |  |
+| National law requiring periodic vehicle inspection/assessment                                                                                                                | 84     | 59            | 92              | 85              | 86  |  |
+| National laws on front and side impact protection                                                                                                                            | 60     | 96            | 74              | 50              | 0   |  |
+| National laws on seat-belt and seat-belt anchorages                                                                                                                          | 74     | 87            | 93              | 68              | 17  |  |
+| National law on electronic stability control                                                                                                                                 | 57     | 89            | 79              | 43              | 0   |  |
+| National law on pedestrian protection                                                                                                                                        | 53     | 63            | 77              | 43              | 0   |  |
+| National law on braking systems                                                                                                                                              | 44     | 92            | 78              | 11              | 3   |  |
+| National law on universal access to emergency care                                                                                                                           | 76     | 60            | 97              | 77              | 23  |  |
+| National law guaranteeing free-of-charge access to rehabilitative care<br>for all injured                                                                                    | 51     | 43            | 77              | 44              | 3   |  |
+
+|                                                                                                                                           |        | Income levela |                 |                 |     |
+|-------------------------------------------------------------------------------------------------------------------------------------------|--------|---------------|-----------------|-----------------|-----|
+|                                                                                                                                           | Global | High          | Upper<br>middle | Lower<br>middle | Low |
+| National law guaranteeing free-of-charge access to psychological<br>services to road traffic crash victims and their families             |        | 23            | 78              | 2               | 3   |
+| National good Samaritan law                                                                                                               | 43     | 46            | 57              | 42              | 0   |
+| National legislation mandating third-party liability insurance for powered<br>vehicles                                                    | 87     | 95            | 89              | 81              | 92  |
+| National law on driving time and rest periods for professional drivers                                                                    | 74     | 81            | 89              | 72              | 16  |
+| Legislation reported but not validated nor evaluated (Thus, % reflects population living in countries that report to<br>have these laws): |        |               |                 |                 |     |
+| National law on eCall                                                                                                                     | 13     | 32            | 13              | 8               | 6   |
+| Legislation on restrictions to import vehicles                                                                                            | 32     | 32            | 26              | 35              | 40  |
+| National prohibition on alcohol consumption                                                                                               | 10     | 4             | 3               | 17              | 15  |
+
+a Not shown in income categories but counted in Totals are the three Member states with no information on income level
+
+b Population denominator is population less than 11 years old
+
+## <span id="page-84-0"></span>Annex 4. National vehicle and infrastructure laws and international conventions or regulations
+
+Table A4.1 illustrates the relationship between national legislation and adhesion or related international conventions or regulations. It shows a number of convention- or regulation-signatory countries that do not have national legislation in place on those vehicle topics. In contrast, a number of other countries have national legislation in place, although whether these match international standards is not know as they have not signed the corresponding international standards. This report does not assess whether national legislation matches the specifications of the international regulations.
+
+Table A4.1. Member States´ vehicle national laws and/or international regulation and convention adhesion for selected safety laws, 2022
+
+|                                                                                                                           | National legislation             |                                     |                                  |                                     |                         |
+|---------------------------------------------------------------------------------------------------------------------------|----------------------------------|-------------------------------------|----------------------------------|-------------------------------------|-------------------------|
+|                                                                                                                           | Yes                              |                                     |                                  | No                                  |                         |
+|                                                                                                                           | Also<br>adheres to<br>regulation | Does not<br>adhere to<br>regulation | Also<br>adheres to<br>regulation | Does not<br>adhere to<br>regulation | Cannot be<br>determined |
+| Infrastructure                                                                                                            |                                  |                                     |                                  |                                     |                         |
+| Requirement for formal road safety inspection/<br>assessment and/or any of the 3 road conventions<br>(1950, 1975 or 2003) | 30                               | 64                                  | 7                                | 62                                  | 7                       |
+| Vehicle                                                                                                                   |                                  |                                     |                                  |                                     |                         |
+| Periodic vehicle technical inspection and/or 1997<br>Periodic Inspections Conv.                                           | 35                               | 118                                 | 0                                | 14                                  | 3                       |
+| Front and side impact protection) and/or 1958<br>Regs 94 and 1958 Regs95                                                  | 31                               | 21                                  | 6                                | 70                                  | 42                      |
+| Seat-belt and seat-belt anchorages and/or 1958<br>Reg 14 and 1958 Reg 16                                                  | 37                               | 51                                  | 2                                | 41                                  | 39                      |
+| Electronic stability control and/or 1958 Reg 140, or<br>1998 Reg 8                                                        | 38                               | 11                                  | 9                                | 71                                  | 41                      |
+| Pedestrian protection and/or 1958 Reg 127 or 1998<br>Reg 9 Pedestrians                                                    | 37                               | 7                                   | 9                                | 75                                  | 42                      |
+| Braking systems and/or 1958 Reg 13H                                                                                       | 35                               | 21                                  | 6                                | 69                                  | 39                      |
+| Helmet legislation referring to and/or specifies<br>standard  and /or 1958 Reg 22                                         | 31                               | 62                                  | 15                               | 60                                  | 2                       |
+| Child restraint law specifies standard and/or 1958<br>Reg 44                                                              | 32                               | 24                                  | 12                               | 102                                 | 0                       |
+
+## <span id="page-85-0"></span>Annex 5. Example Country and territory profile template
+
+![](_page_85_Figure_1.jpeg)
+
+## <span id="page-86-0"></span>Annex 6. Guide to Country and territory profiles
+
+This annex explains the terms used through the report and the indicators included in the country and territory9 profiles. Wherever relevant, It also connects these terms with the wording of the UN Voluntary Performance Targets indicators (UNVTI).
+
+Concepts presented in the order in which they appear in the country or territory profile (top to bottom, left to right).
+
+#### **Country name, Population:** Self explanatory
+
+**Income group**: The source of this information is the World Bank estimated 2021 Gross Domestic Product and the following are the cut off points: less or equal than US\$1 085 low-income; US\$ 1 086 to US\$ 4 355 lower-middle-income; US\$ 4 256 to US\$ 13 205 uppermiddle-income; US\$ 13 205 or more, high-income. More information in [https://databankfiles.worldbank.org/](https://databankfiles.worldbank.org/public/ddpext_download/GDP.pdf) [public/ddpext\\_download/GDP.pdf.](https://databankfiles.worldbank.org/public/ddpext_download/GDP.pdf)
+
+**WHO Region:** WHO clusters countries into six regions: the African Region, the Region of the Americas, the South-East Asia Region, the Eastern Mediterranean Region, the European Region, and the Western Pacific Region. Unless stated otherwise, countries are WHO Member States.
+
+**GSRRS participation** *(participation in the Global status report on road safety series):*The *Global status report on road safety* has been published in 2009, 2013, 2015, 2018, and 202310.
+
+**Reported fatalities (year):** Country-reported number of road traffic deaths and calendar10 year to which reported figure belongs.
+
+**Reported fatalities by sex distribution (Males; Females):** Country-reported data by sex may be from a different source to the reported fatalities (above). The proportion of deaths where sex was unknown are not show. As a result, proportions may not add up to 100. Proportions may also not add up to 100% due to rounding off.
+
+**Reported fatalities by user distribution:** Countryreported data by user type may be from a different source to those used for the indicators above. User types shown are motorized-4-wheel occupants, powered 2/3 wheel occupants, pedestrians, cyclists, and others. The proportion of deaths where user type was unknown are not show. As a result, proportions may not add up to 100. Proportions may also not add up to 100% due to rounding off.
+
+**WHO estimated road traffic fatalities (and 95% Confidence Interval (CI)) (year):** The estimated number of road traffic deaths is based on methodology described in Annex 1. Where this number is based on a negative binomial regression model, a 95% CI is also shown. Estimates are all for year 2021.
+
+## **WHO estimated rate per 100 000 population (year):**
+
+The estimated rate per 100 000 population is based on the estimated number of road traffic deaths referred to above and the July 1 population in the country as described in UN Population Division.
+
+**Total paved kilometres (year):** Country-reported number of paved kilometres, and calendar year to which reported figure belongs.
+
+**Presence of technical standards for new roads that take account of all road-user safety, or align with relevant UN Conventions and regulate compliance with them:** Country-reported information on audits or star ranting on new road infrastructure projects is reported as "yes", "no" or "partial" and contrasted (as indicated by optional footnote) with country adherence to at least one of the following international road conventions: The 1950 Traffic Arteries Convention; 1975 European Agreement on Main International Traffic Arteries; and the 2003 Interstate Asian Highway Convention.
+
+**Presence of systematic approaches to assess/ audit new roads:** Information on inspections/star ratings of existing road infrastructure projects is
+
+<sup>9</sup> In the two territory profiles the terms national/subnational are not used.
+
+<sup>10</sup> Gregorian calendar year is used through the report. Years reported in other calendars have been translated into the closest full Gregorian calendar year.
+
+reported as "yes" or "no". "Yes" responses were those where respondents answered "yes" for the existence of formal road safety inspections and/or existence of star rating assessments. Those countries for which respondents answered "yes" only for the existence of maintenance safety inspections are reported as "No". This information is treated as equivalent to "Use of systematic approaches to assess/audit new roads", UN Voluntary Global Road Safety Performance Target (UNVTI3b).
+
+**National law requiring a formal road safety inspection/assessment:** Country-reported. Its WHO validation (not evaluation) is shown in optional footnote.
+
+**Target for roads to meet technical safety standards for all users (year):** Country-reported.
+
+**Investments to upgrade high-risk locations:**  Country-reported.
+
+**Total registered vehicles [rate per 100 000 pop] (year):** Country-reported information about the total number of vehicles in the country includes only registered vehicles, and various categories of such vehicles. This is the cumulative number of vehicles in circulation in 2021 (or the most recent year for which data were available). The year is also documented. Note this is not the number of vehicles brought into circulation that year. In a few countries the number of vehicles in subcategories did not add up to the total number provided. Rate is calculated using same denominator as fatality rate described earlier in this Annex.
+
+**4-wheel vehicles:** Breakdown of total vehicle figure as reported by countries: includes cars and light vehicles (e.g., vans, sport utility vehicles (SUVs), pick-up trucks) carrying no more than nine occupants.
+
+**Powered 2- and 3-wheelers:** Breakdown of total vehicle figure; includes powered 2-wheel mobility devices.
+
+**Heavy trucks:** Breakdown of total vehicle figure: ≥3500 kg).
+
+**Buses:** Breakdown of total vehicle figure: carrying more than nine occupants.
+
+**Other:** Breakdown of total vehicle figure: excludes unknown.
+
+**Legislation on periodic vehicle technical inspection:** Country-reported and WHO validated (but not evaluated) legislation. This is contrasted (and indicated with footnote) with the country's adherence to international conventions: 1997 Periodic Technical Inspection as described by UNECE or 2014 European Union (EU) Directive 45. This information is treated as equivalent to "Use of systematic approaches for vehicle assessments", UN Voluntary Global Road Safety Performance Target (UNVTI5b)
+
+**National laws on front and side impact protection:**  Country-reported and WHO validated (but not evaluated) legislation. In addition, the footnote informs on whether the country adheres to international vehicle standards such as Frontal impact standard (UN Regulation 94 and 95 or equivalent).
+
+**National laws on seat-belts and seat-belt anchorages:** "Seat-belt anchorages" are the parts of the vehicle structure or the seat structure or any other part of the vehicle to which the safety-belt assemblies are to be secured.11 This item corresponds to countryreported and WHO validated (but not evaluated) legislation. In addition, the footnote says whether the country adheres to international vehicle standards such as Frontal impact standard (UN regulation 14 and 16, or equivalent).
+
+**National law on electronic stability control:**  Electronic stability control (ESC) is an active safety system that can be fitted to cars, buses, coaches and trucks. It is an extension of antilock brake technology, which has speed sensors and independent braking for each wheel. It aims to stabilize the vehicle and prevent skidding under all driving conditions and situations, within physical limits. It does so by identifying a critical driving situation and applying specific brake pressure on one or more wheels, as required.This item corresponds to country-reported and WHO validated (but not evaluated) legislation. In addition, the footnote says whether the country adheres to international vehicle standards such as ESC (Regulation 13H or GTR8). More information in [https://road-safety.transport.ec.europa.eu/.](https://road-safety.transport.ec.europa.eu/)
+
+**National law on pedestrian protection:** Pedestrian protection systems are in-vehicle technology systems that detect pedestrians and cyclists in close proximity to the vehicle and may give a signal when collision is imminent. For more information, visit [https://unece.org/](https://unece.org/sustainable-development/press/two-new-un-vehicle-regulations-will-increase-protection-pedestrians) [sustainable-development/press/two-new-un-vehicle](https://unece.org/sustainable-development/press/two-new-un-vehicle-regulations-will-increase-protection-pedestrians)[regulations-will-increase-protection-pedestrians](https://unece.org/sustainable-development/press/two-new-un-vehicle-regulations-will-increase-protection-pedestrians). This item corresponds to country-reported and WHO validated (but not evaluated) legislation. In addition, the footnote says whether the country adheres to international vehicle standards such as Regulation 127 or GTR9.
+
+<sup>11</sup> Adapted from the UN regulation on seatbelts and anchorages
+
+**National law on braking systems:** Anti-lock braking systems aim to prevent the locking of wheels during braking when under emergency conditions, thereby preventing the motorcyclist from falling from their vehicle. For more information, visit [https://road-safety.](https://road-safety.transport.ec.europa.eu/) [transport.ec.europa.eu/.](https://road-safety.transport.ec.europa.eu/) This item corresponds to country-reported and WHO validated (but not evaluated) legislation. In addition, the footnote says whether the country adheres to international vehicle standards such as Regulation 13H (not to be confused with newly proposed Regulation 152).
+
+**Government vehicle procurement practices include safety prerequisites:** Country-reported policies regarding the purchase of vehicles.
+
+**Presence of high-quality safety standards for used-vehicle imports:** Country-reported. This information is treated as equivalent to UN Voluntary Global Road Safety Performance Target, "Presence of high-quality safety standards for used-vehicle exports" (UNVTI5c).
+
+**National law on universal access to emergency care:** Refers to specific legislation to ensure access to care regardless of the ability to pay (i.e., payment cannot be required as a pre-requisite for receiving care). This information is country-reported and WHO validated (but not evaluated).
+
+**National law guaranteeing free-of-charge access to rehabilitative care for all injured:** Reference to laws that do not require payment as a pre-requisite to accessing rehabilitation care. This information is country-reported and WHO validated (but not evaluated).
+
+**National law guaranteeing free-of-charge access to psychological services for road-crash victims and their families:** Reference to laws that do not require payment as a pre-requisite to accessing psychological care. This information is country-reported and WHO validated (but not evaluated).
+
+**National good Samaritan law:** Good Samaritan/ bystander protection laws seeks to protect good Samaritans/bystanders from some legal claims when a recipient of the bystander emergency care is harmed in the process. This information is country-reported and WHO validated (but not evaluated).
+
+**National emergency care access number:** National emergency care access number is reported as "national, single number", "national multiple number" and "partial coverage". Countries with a "national, single number" comprise those that had one single emergency care services number with total country coverage and also those having additional numbers with partial coverage. Countries with "national, multiple numbers" comprise those that had multiple emergency care services access numbers that, taken together, provide total country coverage. Countries with "partial coverage" comprise those that had one or more emergency care services access numbers with partial country coverage overall with areas of the country remaining uncovered: this information is country-reported.
+
+**National target for time between serious crash and initial provision of professional emergency care (year):** Country-reported information
+
+**Presence of strategies to promote alternatives to individuals' use of powered vehicles:** This information is country-reported.
+
+**National road safety strategy:** Country-reported information that is combined into an indicator to characterize it as "yes" if a published national action plan exists that provides for regularly updated, time‐ bound targets for reductions in fatalities and injuries. In addition, the strategy needs to be active at the calendar year 2021. This indicator is used to inform UN Voluntary Global Road Safety Performance Target (UNVTI1a).
+
+**Fatality reduction target (year):** Country-reported percentage reduction target (if any) and calendar year in which it is to be secured.
+
+**Nonfatal reduction target (year):** Country-reported percentage reduction target (if any) and calendar year in which it is to be secured.
+
+**Funding to implement strategy:** Country-reported.
+
+**National legislation mandating third-party liability insurance for powered vehicles:** Refers to legislation requiring drivers to carry insurance that covers the driver in the event of a crash for which they are responsible for injury to a person or damage to property. This information is country-reported and WHO validated (but not evaluated).
+
+**National law on driving time and rest periods for professional drivers:** Country-reported and WHO validated (but not evaluated) legislation. In addition, the footnote says whether the country adheres to international vehicle standards such as the 1979 AETR Convention. This indicator is used to inform whether Professional drivers' driving time and rest periods are regulated, effectively enforced, and audited – this corresponds to UN Voluntary Global Road Safety Performance Target UNVTI11b.
+
+**Adherence to one or more of the seven UN road safety conventions:** External sources (see Annex 1) facilitate information on adhesion to any of the following regulations: 1949 Convention on Road Traffic, 1968 Convention on Road Traffic, 1968 Convention on Road Signs and Signals, 1958 Agreement concerning the Adoption of Harmonized Technical United Nations Regulations for Wheeled Vehicles, Equipment and Parts which can be Fitted and/or be Used on Wheeled Vehicles and the Conditions for Reciprocal Recognition of Approvals Granted on the Basis of these United Nations Regulations, 1997 Agreement concerning the Adoption of Uniform Conditions for Periodical Technical Inspections of Wheeled Vehicles, 1998 Agreement concerning the Establishing of Global Technical Regulations for Wheeled Vehicles, Equipment and Parts, or 1957 Agreement concerning the International Carriage of Dangerous Goods by Road (ADR). An indicator summarizing whether a country has adhered to at least one of these seven conventions is the basis for UN Voluntary Global Road Safety Performance Target (UNVTI12).
+
+**Presence of national lead agency to implement national road safety strategy:** Country-reported information combined into one indicator to summarize "Presence of national lead agency to coordinate, monitor, evaluate and implement multisectoral national road safety action plan", UN Voluntary Global Road Safety Performance Target (UNVTI1b).
+
+**Presence of agencies that coordinate pre hospital and emergency medical services:** Country-reported information combined to confirm the "Presence of agencies that effectively coordinate pre hospital and facility based emergency medical services" which doubles as UN Voluntary Global Road Safety Performance Target (UNVTI12b).
+
+**Legislation on urban speed limits for passenger cars and motorcycles:** Country reported and WHO validated and evaluated information. Evaluation results of below explained items allow characterization of countries into four levels (strongest to weakest): level 3) law exists, urban limits are set at 50 km/h or lower, and local authorities can further modify this limit; level 2) ) law exists, urban limits are set at 50 km/h or lower but limits cannot be lowered locally; level 1) law exists but urban limits are higher than 50 km/h or no legislation exists; and level 0) legislation was not available for validation. Whether a country has changed its legislation to meet level 3 defines a country's "Speed-control legislation been strengthened since last reporting", UN Voluntary Global Road Safety Performance Target (UNVTI6a).
+
+**National law setting a speed limit:** Speed limits are the default speed limits on urban roads, rural roads and motorways for private passenger cars. The speed limits have been, where needed, converted in kilometres per hour. "Default speed limit" was interpreted as the maximum speed limit applied in normal circumstances (regardless of weather, roadworks, special events, etc.) on the road type considered. As road classifications vary greatly from country to country, special attention was paid to confirm or correct speed limits reported in the legal analysis for the different types of roads according to the definitions used in the country concerned. In some countries, the legislation does not articulate speed limits by road type but only by vehicle type. In these countries, the speed limits provided for private passenger cars is reported in the country and territory profiles for all road types.
+
+**Maximum urban speed limit:** See above.
+
+**Maximum rural speed limit:** See above.
+
+**Maximum motorway speed limit:** See above.
+
+**Local authorities can modify limits:** The criterion "local authorities able to modify speed limit" corresponds to country answering "Yes" to whether the speed limit can be altered at a local level in any way (decreased and/or increased). The definition of local authorities is interpreted broadly as any entity that is not from the central system of government (i.e., not form a national ministry) having jurisdiction over a local area whether the local area is a region, a province, a district, a department or a city. This criterion is automatically answered "Yes" for countries in which laws are set at subnational level if at least 80% of subnational entities of the country have set their own speed limits.
+
+**Presence of targets to reduce speeds nationally (year):** Country-reported information.
+
+**Available types of enforcement:** Countryreported information.
+
+**Legislation on drink driving:** Country-reported and WHO validated and evaluated information. Evaluation of results on topics explained items allow characterization of countries into 4 levels (strongest to weakest): level 3) national legislation on drink driving exists, alcohol levels are defined by BAC, alcohol limits per general driving population are ≤0.05 g/dl and for novice drivers ≤0.02 g/dl; level 2) national legislation on drink driving exists, alcohol levels are defined by BAC, alcohol limits per general driving population BAC is between 0.05 and 0.08 g/dl or the novice/professional drivers are allowed >0.02 g/dl; level 1) legislation is not based on BAC or legal limits >0.08 g/dl or no legislation exists; and level 0) legislation was not available for validation. Whether a country has changed its legislation to meet level 3 defines a country's "Presence of legislation (and effective enforcement) on driving under the influence of alcohol substances (based on alcohol laws)", UN Voluntary Global Road Safety Performance Target (a modification, as it excludes "psychoactive substance" and "effective enforcement" from the definition of UNVTI9a).
+
+If the country has national legislation to prohibit alcohol in general population, this is noted both in the Country and territory profiles as well as the corresponding map.
+
+**National law on drink driving:** As explained above.
+
+**BAC limit – general population:** Blood alcohol concertation (BAC) limits (or breath alcohol limits (BrAC) converted to BAC limits) refer to the maximum amount of alcohol legally acceptable in the blood of a driver on the road (i.e., the blood alcohol level above which a driver may be punished by law). This figure is provided for the general population and for young/novice drivers in grams per decilitre (g/dl). This survey gathered information on drink driving laws regardless of the legal status of alcohol in the country. Where alcohol consumption was legally prohibited in a country, this is indicated by a footnote. BAC limits are reported with a dash "–" for countries that have a drink driving law that is not based on blood (or equivalent breath) alcohol concentration.
+
+**BAC limit – young or novice drivers:** As explained above.
+
+**Random breath testing carried out:** The use of random breath testing is indicated based on countries' reports on whether or not such testing is carried out. It refers to the ability or statutory authority of an enforcement officer to stop a vehicle and test the driver at random, without need to establish that the driver committed another offence, or that the driver showed any signs of impairment prior to being stopped. For more information, see [https://www.grsproadsafety.](https://www.grsproadsafety.org/wp-content/uploads/2023/09/3094-IFRC-Drink-Driving-Management-manual-revision-Sept-2023.pdf) [org/wp-content/uploads/2023/09/3094-IFRC-Drink-](https://www.grsproadsafety.org/wp-content/uploads/2023/09/3094-IFRC-Drink-Driving-Management-manual-revision-Sept-2023.pdf)[Driving-Management-manual-revision-Sept-2023.pdf](https://www.grsproadsafety.org/wp-content/uploads/2023/09/3094-IFRC-Drink-Driving-Management-manual-revision-Sept-2023.pdf).
+
+**Presence of national targets to reduce drink driving (year):** Country-reported information.
+
+**Testing carried out in case of fatal crashes:** Countryreported information.
+
+**Legislation on drug-driving:** Country-reported and WHO validated (but not evaluated) legislation. This information is used to define the "Availability of national and, where applicable, subnational data on driving under the influence of […] psychoactive substances and related road traffic‐related fatalities and injuries" a modification – as it excludes alcohol of UNVTI9a. This modification we label UNVTI\_drug.
+
+**Legislation on distracted driving (mobile phones):**  Country-reported and WHO validated (but not evaluated) legislation. This information is used to define the "Effectively enforced legislation on restricting or prohibiting the use of mobile phones while driving", which doubles as UN Voluntary Global Road Safety Performance Target (UNVTI10a).
+
+**Ban on mobile phone use:** Self explanatory.
+
+**Presence of national targets to reduce distracted driving nationally (year):** Countryreported information.
+
+**Legislation on helmets for motorcycle riders:**  Country-reported and WHO validated and evaluated information. Evaluation results of below explained items allow characterization of countries into four levels (strongest to weakest): level 3) law exists and it covers all riders, on all road types, and all engine types, and the helmet must be fastened and the helmet must meet a standard; level 2) law exists and it covers all riders, on all road types, and all engines types but fastening or standard are not required; level 1) law applies only to certain types of riders, roads or engine types or no legislation exists; and level 0) legislation was not available for validation. Meeting the level 3 definition is used to define the presence of legislation requiring adult motorcycle riders "to wear a helmet properly fastened and meeting appropriate standards for protection" which doubles as UN Voluntary Global Road Safety Performance Target (UNVTI7a).
+
+**National motorcycle helmet law:** Self explanatory.
+
+**Legislation requires helmet fastening:** Self explanatory.
+
+**Legislation applies to drivers and passengers:** A reference to "riders" in the law is understood to include both drivers and adult passengers.
+
+**Legislation applies to all road types:** Self explanatory.
+
+**Legislation applies to all engine types:** All powered 2- and 3-wheelers are covered by the law, regardless of engine power.
+
+**Legislation refers to and/or specifies helmet standard:** The criteria "law refers to and/or specifies a helmet standard" is answered "Yes" if the law refers to a specific standard (such as ECE 22 or a national standard) or an authority in charge of setting such a standard, or regulations or rules to specify or develop a standard. Information on the actual adoption of the regulations prescribing a helmet standard was not always available. Whether the country has adhered to the international standard itself is in an optional footnote.
+
+**Presence of targets to increase helmet use (year):**  Country-reported information.
+
+**Helmet wearing rate (driver; passenger):** Countryreported information. The most disaggregated data are represented here (i.e., separate figures for drivers and passengers). Note the information for drivers and passengers does not necessarily represent the same year, nor come from the same source. The data on passenger rates refer to adult passengers unless otherwise indicated. Whether rates for helmet use for drivers and passengers are above 80% is used as indicative of the "Proportion of motorcycle riders correctly using helmets close to 100%, which corresponds to UN Voluntary Global Road Safety Performance Target (UNVTI7e).
+
+**Minimum age/height children are allowed as passengers:** Country-reported and WHO validated information on whether the country restricts children as passengers on motorcycles and if "yes", for what age group.
+
+**Legislation on seat-belts for motor vehicle occupants:** Country-reported and WHO validated and evaluated information. Evaluation results of the topics explained below allow characterization of countries into four levels (strongest to weakest): level 3) law exists and it applies to all seating positions in vehicles always; level 2) law only applies to front-seat occupants; level 1) law only applies to the driver or no legislation exist; and level 0) legislation was not available for validation. Reaching the level 3 definition is used to define "Legislative improvements made since last reporting towards best practice standards" which corresponds to UN Voluntary Global Road Safety Performance Target ( UNVTI8a).
+
+**National seat-belt law:** Law applies to all roads and at all times.
+
+**Legislation applies to front and rear-seat occupants:** Self explanatory.
+
+**Presence of targets to increase seat-belt use (year):** Country-reported information.
+
+**Seat-belt wearing rate (drivers; front seat occupants; rear seat occupants):** Country-reported information. Where available, information on wearing rates disaggregated by driver, front- and rear-seat occupants were used. Note that the information provided for front-seat and rear-seat occupants does not necessarily represent the same year, nor come from the same source, Whether rates for driver, frontseat occupant and rear-seat occupants are above 80% is used as indicative of the "Proportion of all motor vehicle occupants using safety belt close to 100%, which corresponds to UN Voluntary Global Road Safety Performance Target (UNVTI8c).
+
+**Legislation on child restraint systems:** Countryreported and WHO validated and evaluated information. Evaluation results of the topics below allows characterization of countries into 4 levels (strongest to weakest): level 3) law exists, children up to 10 years of age or 135 cm of height must use a child restraint system matching a standard in addition to the prohibition of children of a particular age/height prohibited from sitting in the front seats; level 2) same as previous level except that either the age of the child is set at 4 years or there is no requirement for a standard; level 1) law not based on age/heigh criteria and no standard or no legislation exist; and level 0) legislation was not available for validation. A country is interpreted as having a child restraint law where the country requires the mandatory use of child restraint systems for an identified group of children based on either their height and/or their age and/or their weight. Countries whose laws require that children within a certain age group/ weight use either a seat-belt or a child restraint were reported as not having a child restraint law for this age group/height. Countries that referred to child restraint use for children sitting in the front only (and not in the rear) were reported as not having a child restraint law. Reaching the level 3 definition is used to define "Presence of effectively enforced legislation requiring the use of child restraint systems that meet appropriate standards" which doubles as UN Voluntary Global Road Safety Performance Target (UNVTI8b).
+
+**National child restraints use law:** Child restraints include rear-facing child restraints, forward-facing child restraints, as well as booster seats. Regular (adult) seat-belts, on their own, are not counted as appropriate child restraints.
+
+**Children seated in front seat:** The criterion "children seated in front" sets out whether a country restricts children as passengers in front seats, and if so, what the restrictions are (e.g. a complete ban, or subject to placing the child in a safety restraint system and for which age group).
+
+**Age or height specified for children requiring child restraint:** The age and/or height reported for the criteria "child restraint required" corresponds to the range of years of age for which only child restraint systems are allowed to restrain children (i.e. no other form of restraint is allowed such as seat-belts only, "other means", etc.)
+
+**Child restraint standard referred to and/or specified:** Countries that referred to either child restraint use or "other means" were considered as not meeting the "standard" criteria. The criterion "law refers to and/or specifies a standards" is answered "Yes" if the law refers to a specific standard (such as ECE 44 or ECE 120) or an authority in charge of setting such a standard, or regulations or rules to specify or develop a standard. Information on the actual adoption of the regulations prescribing a standard was not always available; in cases where the country indicated that the standard had not yet been set, a corresponding footnote was included in the Country and territory profile. Whether the country adheres to any international standard on child restraint systems is noted with a footnote.
+
+**Presence of targets to increase child restraint use (year):** Country-reported information.
+
+**Civil Registration and Vital Statistics 2021:** Source is WHO. See Annex 1 (Methods).
+
+**Frequency and distribution of journeys by modal type:** Country-reported information.
+
+**Speeding violations and speedingg related injuries and fatalities:** Country-reported information. This information is meant to capture "Presence of national and, where applicable, subnational data systems on speeding violations and speeding‐related injuries and fatalities", which is UN Voluntary Global Road Safety Performance Target (UNVTI6c).
+
+### **Driving under the influence of alcohol or drugs and related road traffic‐related fatalities and injuries:**
+
+Country-reported information. This information is meant to capture "Availability of national and, where applicable, subnational data on driving under the influence of alcohol and/or psychoactive substances and related road traffic‐related fatalities and injuries" which is UN Voluntary Global Road Safety Performance Target (UNVTI9b).
+
+**Seat-belt and child restraint systems use:** Countryreported information. This information is meant to capture "Presence of national and, where applicable, subnational data on use of safety belts, as well as the appropriate use of a-restraint systems" which is UN Voluntary Global Road Safety Performance Target (UNVTI8f).
+
+**Powered 2- and 3-wheeler helmet use:** Countryreported information. This information is meant to capture "Presence of national and, where applicable, subnational data systems on helmet use" which is UN Voluntary Global Road Safety Performance Target (UNVTI7d).
+
+**Mobile phone use while driving :**Country-reported information. This information is meant to capture "Presence of national and, where applicable, subnational data systems on the use of mobile phones while driving" which is corresponds to UN Voluntary Global Road Safety Performance Target (UNVTI10b).
+
+![](_page_95_Picture_0.jpeg)
+
+#### **World Health Organization**
+
+The Department of Social Determinants of Health, Safety and Mobility Unit
+
+20 Avenue Appia 1211 Geneva 27 Switzerland Phone: +41227912881
+
+[https://www.who.int/teams/social-determinants-of-health/](https://www.who.int/teams/social-determinants-of-health/safety-and-mobility/global-status-report-on-road-safety-2023) [safety-and-mobility/global-status-report-on-road-safety-2023](https://www.who.int/teams/social-determinants-of-health/safety-and-mobility/global-status-report-on-road-safety-2023)
+
+![](_page_95_Figure_5.jpeg)

Zotero/001_artiklid/Road Safety Indicators/harrisroadsafetyriskprediction2020.md

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+---
+category: literaturenote
+citekey: harrisroadsafetyriskprediction2020
+title: A road safety risk prediction methodology for low volume rural roads
+authors: "Harris, Dale; Durdin, Paul; Brodie, Colin; Tate, Fergus; Gardener, Robyn"
+year: 2020
+date: 2020-11-08 2020-11-08
+doi: 10.3316/informit.842810685900972
+publication: Journal of the Australasian College of Road Safety
+url: "https://search.informit.org/doi/abs/10.3316/INFORMIT.842810685900972"
+zotero_key: 4DZ6336J
+zotero_storage: 27ZX3ZG5
+collections: imporditud
+folder: 001_artiklid/Road Safety Indicators
+firstAuthor: "Harris, Dale"
+status: converted
+---
+Available under a Creative Commons Attribution Licence.
+
+- McCorry, B., & Murray, W. (1993). Reducing commercial vehicle road accident costs. *International Journal of Physical Distribution & Logistics Management, 23*(4), 35-35. doi: 10.1108/09600039310041491
+- Nævestad, T. (2009). Mapping research on high-risk organisations: Arguments for a sociotechnical understanding of safety culture. *Journal of Contingencies and Crisis Management, 7*, 126-136. doi: 10.1111/j.1468-5973.2009.00573.x
+- Short, J., Boyle, L., Shackelford, S., Inderbitzen, B., & Bergoffen, G. (2007). *Commercial truck and bus safety synthesis program: Synthesis of safety practice - Synthesis 14: The role of safety culture in preventing commercial motor vehicle crashes*. Washington: Transportation Research Board.
+- Snyder, B. H. (2012). Dignity and the Professionalized Body: Truck Driving in the Age of Instant Gratifi cation. *Hedgehog Review, 14*(3), 8-20.
+- Stake, R. E. (2005). Qualitative Case Studies. In N. K. Denzin & Y. S. Lincoln (Eds.), *The Sage Handbook of Qualitative Research* (3rd ed.). Thousand Oaks: Sage Publications, Inc.
+
+- Sully, M. (2001). *When rules are not enough: Safety regulation and safety culture in the workplace*. Paper presented at the Road Safety Conference.
+- Transport Workers' Union. (2012). *Before the road safety remuneration tribunal: Application by the Transport Workers' Union of Australia for road safety remuneration orders*. Retrieved 2nd July, 2015, from http://www.twu.com. au/Home/Campaigns/Safe-Rates/TWU-Application-for-Road-Safety-Remuneration-Order/
+- Vaughan, D. (1996). *The Challenger launch decision: Risky technology, culture, and deviance at NASA*. Chicago: University of Chicago Press.
+- Williamson, A. (2007). Predictors of Psychostimulant Use by Long-Distance Truck Drivers. *American journal of epidemiology, 166(11),* 1320-1326. doi: 10.1093/aje/ kwm205
+- Williamson, A., & Friswell, R. (2013). The effect of external non-driving factors, payment type and waiting and queuing on fatigue in long distance trucking. *Accident Analysis & Prevention*, 58, 26-34. doi: 10.1016/j.aap.2013.04.017
+
+# A road safety risk prediction methodology for low volume rural roads
+
+*Dale Harris1 , Paul Durdin1 , Colin Brodie2 , Fergus Tate2 and Robyn Gardener3*
+
+ *Abley Transportation Consultants, Christchurch New Zealand, 2 New Zealand Transport Agency, New Zealand, 3 Accident Compensation Corporation, New Zealand*
+
+*Winner of the John Kirby Award for best paper by a new researcher at the Australasian Road Safety Conference ARSC2015*
+
+# Abstract
+
+The roads of New Zealand's Eastern Bay of Plenty region have relatively low vehicle volumes and experience a number of rural road safety issues, including inappropriate speed, the use of drugs and alcohol, low levels of restraint use and young/inexperienced drivers. Over half of all rural crashes are loss-of-control crashes on curves. Due to low network traffi c volumes, crashes tend to be sporadic and diffi cult to predict using risk assessment techniques that rely on crash histories.
+
+This paper introduces a new risk prediction methodology that identifi es high-risk curves independent of crash history. Using geospatial data and innovative analysis techniques, existing methodologies for identifying curves and calculating vehicle operating speeds were modelled and automated to undertake a network-wide assessment of high risk curves.
+
+The new methodology extracted and classifi ed almost 7000 curves across 1500km of road network. When compared to the location of loss-of-control crashes, it was found that 66.6% of crashes occurred on 20.3% of curves classifi ed as 'high risk' in at least one direction. These results have been shared with road controlling authorities and will support prioritised road safety improvements targeting high risk curves.
+
+This methodology is the fi rst network screening tool that has been specifi cally developed to address road safety risk in low volume rural areas in New Zealand or Australia. The methodology demonstrates how existing research into vehicle operating speed behaviour can be applied to identify high risk road elements and support targeted improvements that have the potential to signifi cantly reduce road safety risk.
+
+# Introduction
+
+Safer Journeys, New Zealand's Road Safety Strategy 2010- 20, has a vision to provide a safe road system increasingly free of death and serious injury (Ministry of Transport, 2010). This Strategy adopts a safe system approach to road safety focused on creating safe roads, safe speeds, safe vehicles and safe road use. These four safe system pillars need to come together if the New Zealand Government's vision for road safety is to be achieved.
+
+![](_page_1_Picture_3.jpeg)
+
+**Figure 1. Eastern Bay of Plenty locality map** 
+
+Safe system signature projects are identifi ed in the Safer Journeys Action Plan 2013-2015 (New Zealand Transport Agency [NZTA], 2013) as exemplar projects that adopt a complete safe system approach to road safety. Safe systems signature projects provide a platform for trialling innovative approaches and treatments across the four safe system pillars.
+
+The Eastern Bay of Plenty region (Figure 1) was identifi ed as a candidate for a safe systems signature project as it is a region with signifi cant rural road safety issues; particularly inappropriate speed, use of alcohol/drugs, poor restraint use and inexperienced drivers. The scope of the project includes rural State highways and local roads. Most Eastern Bay of Plenty roads are low volume remote roads, where crashes tend to be sporadic and diffi cult to predict using reactive crash prediction models. Therefore a new approach to assessing road risk, independent of crash history, was required.
+
+Abley Transportation Consultants was commissioned by the New Zealand Transport Agency (the Transport Agency) to develop a risk prediction model and mapping interface "SignatureNET" to support the delivery of this signature project. This included building a vehicle speed model to identify high risk curves, assessing road risk using the urban KiwiRAP risk mapping methodology (Brodie et al., 2013), and applying rural road risk prediction models.
+
+# Methodology
+
+Many rural road crashes in Eastern Bay of Plenty occur on curves (57.9% of all fatal and serious rural road crashes 2004-2013) (NZTA, 2014). Due to the remote nature of the region's roads, fatal and serious crashes tend to occur on parts of the network where high-severity crashes have not occurred in the recent past. In these areas, relying on crash
+
+history alone to predict where future crashes will occur is unreliable. A new methodology that could identify and assess the risk of all the curves on the network that was independent of crash history was developed.
+
+The Austroads (2009) operating speed model for rural roads provides a procedure for calculating speeds along road sections based on the geometric features of the road. Using calculated speeds and horizontal curve radii, the model allows users to assess the design limit of curves.
+
+With 1500 km of rural road, manually assessing the risk of each curve in the Eastern Bay of Plenty region using the Austroads model would be time-consuming and cost-prohibitive. As the inputs to the Austroads operating speed model are available in a spatial format, the model was therefore automated using a new Geographic Information Systems (GIS) methodology. This included the development of GIS models that identify curves, predict vehicle operating speeds along road corridors, and assess curve risk using approach speeds and radius (Harris & Durdin, 2015). This methodology is discussed, in brief, below.
+
+### Curve identifi cation
+
+The fi rst step in speed modelling methodology is to identify curves using a high quality road centreline and a methodology adapted from Cenek et al. (2011). The spatial road dataset used in this methodology closely matched the actual centreline of the road. Using GIS linear referencing tools, the road centreline was divided into 10m sections and the rolling 30m average radius calculated for each arc section.
+
+Discrete curve sections were extracted by combining road segments where:
+
+- a. the radius was less than 800m;
+- b. at least one 10m section had a radius of 500m or less; and
+- c. the apex (direction) of the curve did not change.
+
+Contiguous 10m sections of road that met these criteria were dissolved into a single curved segment, with the radius (m) of the curve defi ned as the minimum radius across all the sections that make up the curve. The calculated curve radii represents a mid-road curvature value (rather than separate curve radii values for each lane or direction), noting that there are no divided carriageway roads in the Eastern Bay of Plenty region.
+
+#### Speed modelling
+
+The Austroads (2009) operating speed model predicts the operating (85th percentile) speed of cars travelling in each direction along a section of rural road. The model mimics the real-world behaviour of drivers based on a large number of car vehicle observations. As such, the model only applies to cars and cannot be used to predict the operating speeds of other types of vehicle.
+
+Available under a Creative Commons Attribution Licence.
+
+Once curves had been identifi ed, each road corridor was divided sequentially into a series of curves with known radii, and straights with known lengths. Speeds were then modelled along the road centreline in both directions. Sections of road with curves of a similar radius separated by short straights (less than or equal to 200m) were identifi ed as discrete sections with an operating speed identifi ed within a narrow range of values (minimum and maximum operating speeds). When drivers travel through a series of curves with a similar radii, their speeds stabilise to a level they feel comfortable with (Austroads, 2009). Section operating speeds for single, isolated curves were also calculated.
+
+Working along the road corridor, speed behaviour was modelled as either:
+
+- *a. Acceleration* on straights longer than 200m, or on curves where the approach speed is less than the operating speed of the curve.
+- *b. Speed maintenance* on straights less than 200m, or where the speed falls within the section operating speed range.
+- *c. Deceleration* on curves where the approach speed is higher than the operating speed for the curve (or series of curves).
+
+Rates of acceleration and deceleration were modelled using the methodology in Austroads (2009) (Figures 2 and 3). Extrapolation of values was required to estimate some acceleration and deceleration outputs, including acceleration for straights longer than 1000m (Figure 2) and deceleration where curve approach speeds are less than 60 km/h (Figure 3).
+
+The exit speed at the end of each curve or straight is applied as the approach speed for the following section of road. For each curve where deceleration is modelled, the design limit is identifi ed as either out-of-context (unacceptable or undesirable) or within context (desirable) (Figure 3). Curves where no deceleration is modelled are also considered to be 'within limit'.
+
+# Results
+
+The curve identifi cation methodology recognised 6,985 curves across the Eastern Bay of Plenty region. Each curve was classifi ed by design limit (in both directions) according to the Austroads speed model (Figure 3). The number of curves identifi ed by category are displayed in Table 1. Where curves were classifi ed differently in opposing directions, the worst (most out-of-context) classifi cation has been applied. For example, a curve that is 'undesirable' in one direction but 'within limit' in the reverse direction would be categorised as 'undesirable'.
+
+Because the curve identifi cation methodology developed for this project was new and untested, the results were compared against an existing Transport Agency curve dataset for the state highway network in the Eastern Bay of Plenty. The state highway curve dataset is based on horizontal curvature data collected in the fi eld as part of the Transport Agency's annual high speed surveys (Cenek et al., 2011).
+
+![](_page_2_Figure_14.jpeg)
+
+**Figure 2. Acceleration on straights (source: Austroads, 2009)** 
+
+![](_page_3_Figure_3.jpeg)
+
+**Figure 3. Deceleration on curves and design limits (source: Austroads, 2009)** 
+
+**Table 1. Eastern Bay of Plenty curve categorisation**
+
+| Curve Category | Total Curves | % of all Curves |
+|----------------|--------------|-----------------|
+| Unacceptable   | 600          | 8.6%            |
+| Undesirable    | 815          | 11.7%           |
+| Desirable      | 941          | 13.5%           |
+| Within Limit   | 4629         | 66.3%           |
+
+The new methodology identifi ed the location of 96.8% of curves in the state highway dataset, with a visible correlation between curve radii values (Figure 4). The two datasets met the assumptions required for linear regression, with 82% of calculated curve radii values within 20% of the Transport Agency's curve radii values. The degree of scatter between the two datasets, particularly for large-radius curves, is primarily attributed to the different collection methods. The state highway dataset is collected in-fi eld using lane-based radii, whereas the operating speed model methodology relies on radii values calculated from the centreline. Extreme outlier values are more likely to refl ect errors in the geometry and topology of the road centreline dataset.
+
+The results of the curve analysis were delivered through a mapping website ("SignatureNET"), which displayed the risk metrics alongside contextual road safety data including administrative boundaries and crash locations (Figure 5).
+
+### Correlation between curve category and loss-of-control crashes
+
+Further analysis was undertaken to identify the number and percentage of loss-of-control crashes by curve category. For this comparison, 10-years of crash data (2004-2013) was
+
+selected from New Zealand's Crash Analysis System (CAS) (NZTA, 2014a). For the purposes of this analysis, loss-ofcontrol crashes were defi ned as those with movement code 'BF' (head on - lost control on curve), 'DA' (lost control turning right) or 'DB' (lost control turning left) in CAS (NZTA, 2014b).
+
+In the 10-year period selected, there were 589 loss-ofcontrol crashes on the curves categorised using the curve risk assessment methodology. The number and percentage of loss-of-control crashes by curve category are presented in Table 2.
+
+**Table 2. Eastern Bay of Plenty loss-of-control crashes by curve category**
+
+| Curve Category | Total LOC<br>Crashes | % of all Curves |
+|----------------|----------------------|-----------------|
+| Unacceptable   | 226                  | 38.4%           |
+| Undesirable    | 166                  | 28.2%           |
+| Desirable      | 64                   | 10.9%           |
+| Within Limit   | 133                  | 22.6%           |
+
+The results show that two thirds (66.6%) of all loss-ofcontrol crashes occur on out-of-context curves i.e. those identifi ed as 'unacceptable or 'undesirable'. This is a particularly important fi nding as it means road controlling authorities in the Eastern Bay of Plenty can target efforts on 20.3% of all curves where 66.6% of all loss-of-control crashes occur.
+
+![](_page_4_Figure_3.jpeg)
+
+**Figure 4. Comparison of calculated curve radii against NZTA out-of-context dataset**
+
+#### Further analysis and model validation
+
+Since the fi rst development of the operating speed model for the Eastern Bay of Plenty, the operating speed model has been applied to the Top of the South region of New Zealand - the area encompassed by the South Island local authority districts of Marlborough, Tasman and Nelson City. It includes some 3382 km of rural roads, which is much larger than the Eastern Bay of Plenty region (approximately 1500 km).
+
+The operating speed model identifi ed a total of 21,158 curves in the Top of the South region. The results of the curve classifi cation are displayed in Table 5, showing that the proportion of curves in each classifi cation in the Top of the South region mirrored the Eastern Bay of Plenty region (Table 3) very closely.
+
+**Table 3. Top of the South curve categorisation**
+
+| Curve Category | Total Curves | % of all Curves |
+|----------------|--------------|-----------------|
+| Unacceptable   | 1772         | 8.4%            |
+| Undesirable    | 2215         | 10.5%           |
+| Desirable      | 2345         | 11.8%           |
+| Within Limit   | 14826        | 70.1%           |
+
+Analysis of loss-of-control crashes against curve category was also undertaken for the Top of the South region, identifying that 55.8% of all loss-of-control crashes occurred at 18.9% of curves identifi ed as out-of-context ('unacceptable' or 'undesirable') (Table 4). This result is similar to the analysis of the Eastern Bay of Plenty region, although the correlation is not as pronounced.
+
+**Table 4. Top of the South loss-of-control crashes by curve category**
+
+| Curve Category | Total LOC<br>Crashes | % of all LOC<br>Crashes |
+|----------------|----------------------|-------------------------|
+| Unacceptable   | 360                  | 32.3%                   |
+| Undesirable    | 262                  | 23.5%                   |
+| Desirable      | 135                  | 12.1%                   |
+| Within Limit   | 359                  | 32.2%                   |
+
+The Eastern Bay of Plenty and Top of the South data were combined so the relationship between curve categorisation and loss-of-control crashes could be better understood (Figure 6). This fi gure shows there is a strong relationship between curve category and loss-of-control crashes. The relationship indicates that focusing road safety improvement efforts on out-of-context curves is targeting to risk.
+
+![](_page_5_Picture_3.jpeg)
+
+**Figure 5. SignatureNET mapping website screenshot**
+
+# Discussion
+
+The methodology presented in this paper has been wellreceived by all the agencies involved in the delivery of the Eastern Bay of Plenty safe systems signature project. The curve risk data and SignatureNET web viewer is now available to all the local road controlling authorities to assist them in identifying and prioritising road safety interventions targeting loss-of-control crashes on curves.
+
+#### Current applications
+
+The curve assessment and automated operating speed model is currently being rolled-out across other locations in New Zealand.
+
+#### Informing speed management decisions
+
+The Transport Agency has developed a process for identifying parts of the state highway road network for speed management interventions based on road safety risk. Potential interventions include targeted enforcement, reducing speed limits, or upgrading parts of the road network to reduce the frequency and severity of crashes at current operating speeds. To determine and prioritise appropriate intervention strategies, the operating speed model was applied across the high speed state highway network to determine: (a) operating speeds under current speed limits; and (b) operating speeds under the identifi ed safe and appropriate speed limits, noting that speed limit is a factor in determining the maximum (desired) speed of a road (Austroads, 2009; Harris & Durdin, 2015).
+
+The different operating speeds are then being used to estimate the potential for death and serious injury (DSi) savings by using Nilsson's Power Model which connects changes in traffi c speeds with changes in road crashes at various levels of injury severity using a power relationship (Nilsson, as cited in Cameron & Elvik, 2008). Sections of state highway that exhibit little or no speed reduction are considered to be 'self-explaining' as the geometry and terrain of the road naturally prevents drivers from achieving higher speeds. Conversely sections with extreme differences when comparing the current operating speeds and the safe and appropriate operating speed are generally straight roads where enforcement or engineering improvements may be more appropriate, depending on potential DSi savings and the functional classifi cation of the corridor.
+
+#### Training safety practitioners
+
+As noted earlier, the methodology has been extended to the Top of the South region in New Zealand for exercises in the annual Safe Systems Engineering Workshop. The outputs were presented in a web viewer and combined with Urban KiwiRAP risk profi les for the region delivered as part of an Accident Compensation Corporation (ACC) funded road safety initiative. The web viewer was used as learning media to introduce Safe Systems Engineering Workshop attendees to the use of network screening tools to assist with the identifi cation of road safety issues across the region. By considering different risk metrics alongside one another and in combination with crash data, practitioners were able to identify potential factors contributing to highrisk locations and formulate responses at a desktop level prior to physically investigating sites.
+
+![](_page_6_Figure_3.jpeg)
+
+**Figure 6. Graph demonstrating the relationship between curve category and the location of loss-of-control crashes**
+
+#### Limitations and future enhancements
+
+The speed modelling and curve risk assessment methodology is of greatest value to road safety practitioners where it is used as a network screening tool. The methodology should be applied with care when considering individual curves. Site-specifi c factors such as roadside hazards should be taken into account when identifying or prioritising curve treatments. For this reason, the SignatureNET web viewer included aerial imagery basemaps, Google Street View and other contextual data to support users in undertaking desktop reviews.
+
+During the development and roll-out of the methodology, a number of further enhancements were suggested and are being explored. These include:
+
+- a. Enhancing the speed model by exploring the relationship between curve risk category, road surface type, carriageway width and actual road safety performance.
+- b. Exploring the relationship between curve risk category, KiwiRAP star rating and the road safety performance of state highways.
+- c. Enhancing the speed model by comparing calculated operating speeds against known operating speeds, for example data collected using GPS devices.
+- d. Exploring the feasibility of using high-resolution elevation data collected using LiDAR, (if available) to calculate super elevation and vertical curvature and incorporate these factors into the curve risk assessment models.
+
+# Conclusion
+
+The operating speed model and high risk curve assessment methodology demonstrate that innovative assessment methods and tools can be developed within a safe system signature project environment. Current applications of this methodology in New Zealand demonstrate the potential of this methodology in supporting the safe system philosophy, including the identifi cation of high risk curves for targeted safety investigation and treatment (Eastern Bay of Plenty), supporting the development of the New Zealand Transport Agency's Speed Management Guide, and being used as training media for Safe Systems Engineering Workshops. The curve identifi cation and analysis techniques presented in this paper will be of particular interest to any road controlling authorities wanting to reduce loss-of-control crashes on rural roads.
+
+# References
+
+Austroads. (2009). *Guide to road design part 3: Geometric design*. Sydney, NSW, Australia: Austroads Incorporated.
+
+Brodie, C., Durdin, P., Fleet, J., Minnema, R. & Tate, F. (2013, November). *Urban KiwiRAP road safety assessment programme*. Paper presented at the Australasian College of Road Safety Conference, Adelaide, Australia. Retrieved from http://acrs.org.au/fi les/papers/57%20Brodie\_NPR.pdf
+
+Cameron, M. H., & Elvik, R. (2008). *Nilsson's Power Model connecting speed and road trauma: Does it apply to urban roads?* Paper presented at the Australasian Road Safety Research, Policing and Education Conference, Adelaide, South Australia. Retrieved from http://acrs.org.au/fi les/ arsrpe/RS080079.pdf
+
+Available under a Creative Commons Attribution Licence.
+
+- Cenek, P. D., Brodie, C. A., Davies, R. B. & Tate, F. (2011, November). *A prioritisation scheme for the safety management of curves*. Paper presented at the 3rd International Road Surface Friction Conference, Gold Coast, Queensland, Australia. Retrieved from http://www. nzta.govt.nz/resources/safety-management-of-curves/docs/ safety-management-of-curves.pdf
+- Harris, D., & Durdin, P. (2015). *Developing a risk prediction model for a safe system signature project.* Paper presented at the IPENZ Transportation Group Conference, Christchurch, New Zealand. Retrieved from http://conf. hardingconsultants.co.nz/workspace/uploads/paper-harrisdale-developi-54f3936b2a318.pdf
+- Ministry of Transport. (2010). *Safer journeys New Zealand's road safety strategy 2010-2020*. New Zealand: Author.
+- New Zealand Transport Agency. (2013). *Safer journeys action plan 2013-2015*. New Zealand: Author.
+- New Zealand Transport Agency. (2014a). *Guide for the interpretation of coded crash reports from the crash analysis system (CAS).* New Zealand: Author. Retrieved from http://www.nzta.govt.nz/assets/resources/guide-tocoded-crash-reports/docs/guide-to-coded-crash-reports.pdf
+- New Zealand Transport Agency. (2014b). *Crash analysis system* [dataset]. Retrieved from http://www.nzta.govt.nz/resources/ crash-analysis-system-data/index.html
+
+# Laser ablated removable car seat covers for reliable deployment of side airbags
+
+*Arun Vijayan1 , Amit Jadhav1 , and Rajiv Padhye1*
+
+*School of Fashion and Textiles, RMIT University, Melbourne, arun.vijayan@rmit.edu.au* 
+
+*This paper is an extended version of an earlier conference paper that was presented at the ARSC 2015. It has undergone further extensive peer review; revised with additional material added.*
+
+# Abstract
+
+In the event of a collision, the safe and reliable deployment of side airbags which include side-torso and combination airbags through removable car seat covers that use tearseam technology has been recently questioned. It is well known that a side-torso airbag system in automotive seats can reduce injuries and prevent fatalities in the event of a collision. Removable car seat covers suitable for side airbag systems are popular accessories in the automotive industry from the perspective of upholstery protection and aesthetics. This study demonstrated a better-suited technology in which laser ablation down the side panel of removable car seat covers, produced a pre-determined strength within a weakened zone that allowed a reliable airbag deployment in the event of a collision. This paper investigates the effect of laser power as a key factor in the laser ablation process and its infl uence on the bursting strength of the car seat cover materials. The laser-ablation of the removable car seat covers can ensure the consistent airbag deployment under environmental conditions and temperatures ranging between ambient (22 ± 2°C), cold (-35 ± 2°C) and hot (85 ± 2°C). The durability and deployment performance of these car seat covers after UV exposure was also investigated.
+
+# Keywords
+
+Laser ablation, Textiles, Car seat covers, Side-torso and combination airbags, Bursting strength
+
+# Introduction
+
+Airbags in passenger vehicles are a supplementary restraint system to seat belts that further mitigates the injuries suffered in serious crashes. The use of airbags can help to minimise the chances of fatalities from an external collision, and limit passenger impact with the inside of the car. Airbags were fi rst introduced in passenger cars by Ford in 1971 to protect the driver and front passenger in frontal collisions. Since then, the number of airbags in modern cars has increased to fi ve and in some cases to nine; covering a wide range of accident scenarios. Side airbags were fi rst introduced into vehicles around 1995 to help protect passenger car occupants from serious injury in struck side crashes. International studies have shown that side airbags that include side-torso as well as head-and-torso (combination) airbags are effective in reducing the risk of death in near side impact situations, and mitigate injuries in vehicle rollovers (Braver, 2004; D'Elia, 2012). A driver involved in a side impact has twice as high a fatality risk as a driver involved in frontal impacts (Farmer 1997). In 2014 in Australia, 1299 passenger vehicles were involved in police-reported fatal crashes. These crashes resulted in 763 deaths (BITRE, 2014).
+
+Airbags in front occupant car seats are generally concealed in a moulded plastic enclosure contained within the side upholstery of the seat as either a combination or torsoonly system. The seat upholstery through which the side airbag would deploy involves a tear-seam technology that facilitates the infl ation of the airbag during a collision.

Zotero/001_artiklid/Road Safety Indicators/heroadtrafficinjurymortality2021.md

@@ -0,0 +1,241 @@
+---
+category: literaturenote
+citekey: heroadtrafficinjurymortality2021
+title: "Road traffic injury mortality and morbidity by country development status, 2011-2017"
+authors: "He, Jie-Yi; Xiao, Wang-Xin; Schwebel, David C.; Zhu, Mo-Tao; Ning, Pei-Shan; Li, Li; Cheng, Xun-Jie; Hua, Jun-Jie; Hu, Guo-Qing"
+year: 2021
+date: 2021-03-00 2021-3
+doi: 10.1016/j.cjtee.2021.01.007
+publication: Chinese Journal of Traumatology
+url: "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8071733/"
+zotero_key: T7YIZNII
+zotero_storage: PCIGGLWT
+collections: doktoritöö / HLO
+folder: 001_artiklid/Road Safety Indicators
+firstAuthor: "He, Jie-Yi"
+status: converted
+---
+![](_page_0_Picture_1.jpeg)
+
+## Chinese Journal of Traumatology
+
+journal homepage: <http://www.elsevier.com/locate/CJTEE>
+
+![](_page_0_Picture_5.jpeg)
+
+## Original Article
+
+# Road traffic injury mortality and morbidity by country development status, 2011- 2017
+
+Jie-Yi He [a](#page-0-0) , Wang-Xin Xiao [a](#page-0-0) , David C. Schwebel [b](#page-0-1) , Mo-Tao Zhu [c](#page-0-2) , Pei-Shan Ning [a](#page-0-0) , Li Li [d](#page-0-3) , Xun-Jie Cheng [a](#page-0-0) , Jun-Jie Hua [a](#page-0-0) , Guo-Qing Hu [a,](#page-0-0) [\\*](#page-0-4)
+
+- <span id="page-0-0"></span><sup>a</sup> Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, 410078, China
+- <span id="page-0-1"></span><sup>b</sup> Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
+- <span id="page-0-2"></span><sup>c</sup> Center for Injury Research and Policy, Abigail Wexner Research Institute at Nationwide Children's Hospital, Department of Pediatrics, The Ohio State University, Columbus, OH, 43205, USA
+- <span id="page-0-3"></span><sup>d</sup> Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH, 43210, USA
+
+#### article info
+
+#### Article history: Received 31 May 2020 Received in revised form 1 January 2021 Accepted 4 January 2021 Available online 19 January 2021
+
+Keywords: Road traffic injury Mortality Morbidity Socioeconomic disparity Sustainable development goals
+
+#### abstract
+
+Purpose: This research examined road traffic injury mortality and morbidity disparities across of country development status, and discussed the possibility of reducing country disparities by various actions to accelerate the pace of achieving Sustainable Development Goals target 3.6 e to halve the number of global deaths and injuries from road traffic accidents by 2020.
+
+Methods: Data for road traffic mortality, morbidity, and socio-demographic index (SDI) were extracted by country from the estimates of the Global Burden of Disease study, and the implementation of the three types of national actions (legislation, prioritized vehicle safety standards, and trauma-related post-crash care service) were extracted from the Global Status Report on Road Safety byWorld Health Organization.We fitted joinpoint regression analysis to identify and quantify the significant rate changes from 2011 to 2017.
+
+Results: Age-adjusted road traffic mortality decreased substantially for all the five SDI categories from 2011 to 2017 (by 7.52%e16.08%). Age-adjusted road traffic mortality decreased significantly as SDI increased in the study time period, while age-adjusted morbidity generally increased as SDI increased. Subgroup analysis by road user yielded similar results, but with two major differences during the study period of 2011 to 2017: (1) pedestrians in the high SDI countries experienced the lowest mortality (1.68e1.90 per 100,000 population) and morbidity (110.45e112.72 per 100,000 population for incidence and 487.48e491.24 per 100,000 population for prevalence), and (2) motor vehicle occupants in the high SDI countries had the lowest mortality (4.07e4.50 per 100,000 population) but the highest morbidity (428.74e467.78 per 100,000 population for incidence and 1025.70e1116.60 per 100,000 population for prevalence). Implementation of the three types of national actions remained nearly unchanged in all five SDI categories from 2011 to 2017 and was consistently stronger in the higher SDI countries than in the lower SDI countries. Lower income nations comprise the heaviest burden of global road traffic injuries and deaths.
+
+Conclusion: Global road traffic deaths would decrease substantially if the large mortality disparities across country development status were reduced through full implementation of proven national actions including legislation and law enforcement, prioritized vehicle safety standards and trauma-related postcrash care services.
+
+© 2021 Production and hosting by Elsevier B.V. on behalf of Chinese Medical Association. This is an open access article under the CC BY-NC-ND license [\(http://creativecommons.org/licenses/by-nc-nd/4.0/](http://creativecommons.org/licenses/by-nc-nd/4.0/)).
+
+#### Introduction
+
+"To halve the number of global deaths and injuries from road traffic accidents by 2020" was proposed by the United Nations as Sustainable Development Goals (SDGs) target 3.6[.1](#page-5-0) However, according to the Global Status Report on Road Safety 2018,[2](#page-5-1) the ambitious target is unlikely to be reached despite global improvement in key domains of legislation, vehicle standards and access to
+
+<span id="page-0-4"></span><sup>\*</sup> Corresponding author. E-mail address: [huguoqing009@gmail.com](mailto:huguoqing009@gmail.com) (G.-Q. Hu). Peer review under responsibility of Chinese Medical Association.
+
+post-crash care services. This situation raises a challenge for global health decision-makers and researchers as we move into and beyond the year 2020, how can we accelerate global progress to reduce the burden of road traffic injuries (RTIs) and deaths worldwide and achieve the SDG target belatedly?
+
+Substantial research evidence suggests that there is much heavier road traffic injury burden in underdeveloped countries compared to developed ones.[2](#page-5-1)e[6](#page-5-1) The Global Status Report on Road Safety 2018 suggested that 93% of the 1.35 million global road traffic deaths occurred in low- and middle-income countries in 2016, and age-adjusted road traffic mortality was 3 times higher in lowincome countries versus high-income countries (27.5 vs. 8.3 deaths per 100,000 population)[.2](#page-5-1) Remarkably, the report also indicated the number of road traffic deaths did not decrease in any low-income country between 2013 and 2016, but reductions were observed over that time span in 48 middle- and high-income countries[.2](#page-5-1)
+
+In light of the disproportional road traffic injury burden and slow or no progress in reducing RTIs in underdeveloped countries, a feasible and reasonable approach to address the global challenge to halve RTIs is to reduce heavier burden in countries with lower development statuses. This goal also corresponds to the global goal to offer all humans an equal opportunity to enjoy a better quality of life.[4](#page-5-2)[,6](#page-5-3)[,7](#page-5-4)
+
+The present study aims to examine the recent progress in reducing road traffic injury both mortality and morbidity disparities across country development statuses, as well as to assess how that progress corresponds to the three types of recommended national actions from the World Health Organization (WHO): legislation and enforcement, adoption of motor vehicle safety standards, and implementation of trauma-related post-crash care services. These three actions have been proven to be effective in reducing road traffic injury burden.[2](#page-5-1) In order to explore the global performance, to indicate where the weaknesses were and to offer the reference for adopting relevant actions, our analysis purposely linked and examined the implementation of WHO recommended actions with country development statuses.
+
+Morbidity rates do not always correspond to mortality rates, as an example, improved post-crash care services may lead to a crucial reduction in mortality but an increase in prevalence of hospitalization. Other prevention strategies, such as road traffic legislation and prioritized vehicle safety standards, may reduce both morbidity and mortality.
+
+We used two data sources for our analysis, the latest mortality and morbidity estimates by the Global Burden of Disease (GBD) study 201[78](#page-5-5) and implementation data concerning the three national actions from the Global Status Report on Road Safety.[2,](#page-5-1)[9,](#page-5-6)[10](#page-5-7) We examined the progress to reduce disparities in road traffic mortality and morbidity across country development status from 2011 to 2017 as well as progress in implementing the recommended three types of national actions during the study time period.
+
+## Methods
+
+### Data sources
+
+The GBD study is the only data source providing annual and comparable estimates of both fatal and non-fatal road traffic injury indicators by age group, sex, sub-cause, year, and geography at global, regional, national, and subnational levels from 1990 to 2017.[11,](#page-5-8)[12](#page-5-9) The GBD 2017 updated estimates can be freely accessed through the online data visualization tool "GBD Compare | Viz Hub" which was established and maintained by the Institute for Health Metrics and Evaluation at the University of Washington.[8](#page-5-5) Mortality and morbidity (incidence and prevalence) were both considered in our analyses.
+
+The Global Status Report on Road Safety is regularly released by the WHO to offer information concerning implementation of national actions recommended for road traffic injury prevention.[2](#page-5-1)[,9](#page-5-6)[,10](#page-5-7) We extracted data concerning three key national actions: legislation and law enforcement from 180 countries, vehicle safety standards from 183 countries, and trauma-related post-crash care services from 185 countries, and matched them with GBD estimates one country by one country for subsequent analyses. It was noted that data concerning the three types of national actions were missing for a few countries in the WHO reports.
+
+We used the socio-demographic index (SDI) to measure country development status. The SDI is a composite indicator defined by the GBD study group based on per capital income, educational attainment, and total fertility rate in each country. SDI ranges continuously from zero (the lowest developmental status) to one (the highest developmental status) and reflects the development status of a country or a region. The SDI is strongly correlated with health outcomes[.13](#page-5-10) Using the SDI values of 2017, the GBD study group divided 195 countries and territories into five development levels: high, high-middle, middle, low-middle, and low.
+
+#### Data analysis
+
+Corresponding with the time period for the Global Plan for the Decade of Action for Road Safety 2011e2020[14](#page-5-11) and the SDGs[,1](#page-5-0) we selected data from 2011 to 2017 for analyses. Line graphs were plotted to demonstrate trends in age-standardized road traffic injury mortality, incidence, and prevalence from 2011 to 2017 by country development level (SDI category). Mortality, incidence and prevalence were calculated based on the number of deaths, new cases, prevalent cases and population estimated by the GBD 2017. Joinpoint regression analysis was fitted to examine the trends in mortality and morbidity from 2011 to 2017 to describe and distinguish significant changes over time[.15](#page-5-12) The average annual percent change (AAPC) and its 95% confidence interval (CI) both from joinpoint regression analysis were used to quantify the average speed of rate change from 2011 to 2017. Subgroup analyses were conducted to explore disparities in mortality and morbidity across SDI category by road users (pedestrian, pedal cyclist, motorcyclist and motor vehicle occupant).
+
+By matching SDI data from the GBD updates and the WHO reports one country by one country, we also examined progress in the implementation of the three national actions (legislation, prioritized vehicle safety standards, and trauma-related post-crash care services)[2](#page-5-1) from 2011 to 2017 by country SDI category. Legislation involves the enactment and enforcement of five national road traffic laws (speed limit law, drink-driving law, motorcycle helmet law, seat-belt law, and child restraint law). A score from zero to ten was used to quantify the enactment and enforcement of the road traffic laws; a score of zero reflects the lack of relevant laws or the weakest enforcement and a score of ten reflects the law's presence plus the strongest enforcement.[2](#page-5-1) The implementation of the four prioritized United Nations vehicle safety standards (frontal impact protection, electronic stability control, pedestrian protection, and motorcycle anti-lock braking system)[2](#page-5-1) and three trauma-related post-crash care services (national single emergency care access phone number, formal training and certification for prehospital providers, and presence of a national trauma registry)[2](#page-5-1) were also assessed. Please note that data concerning implementation of vehicle safety standards were available for 2014 and 2018 only.
+
+Joinpoint regression analysis was conducted through Joinpoint Regression Program Desktop version 4.7.0.0. Mortality and morbidity changes with p values less than 0.05 were considered statistically significant.
+
+### Results
+
+#### Primary analysis
+
+Generally, age-adjusted road traffic mortality decreased significantly as the SDI increased, which suggested that countries with higher SDI tended to have a lower mortality rate. Mortality disparities consistently existed across the five SDI categories from 2011 to 2017 ([Fig. 1A](#page-2-0)). Age-adjusted mortality significantly decreased in all five SDI categories, with the greatest decrease in the high-middle SDI countries (AAPC: -2.7%, 95% CI: -2.9% e -2.5%, p < 0.05) and the smallest decrease in the high SDI countries (AAPC: -1.2%, 95% CI: -1.4% e -0.9%, p < 0.05).
+
+In contrast, age-adjusted morbidity showed a very different spectrum across the five SDI categories. Countries with a higher SDI tended to have a higher morbidity rate [\(Fig. 1](#page-2-0)B for incidence and [Fig. 1C](#page-2-0) for prevalence). Notably, both the incidence and prevalence gradually increased in the middle SDI countries from 2011 to 2017 (AAPC: 1.3%, p < 0.05 for incidence and 1.2%, p < 0.05 for prevalence) but decreased slightly in the other four SDI categories during the study time period (AAPC: -1.0% -0.2%, all p < 0.05 for incidence and -0.9% -0.4%, all p < 0.05 for prevalence). Although morbidity in the higher SDI countries was initially higher, high (AAPC: -1.0%, p < 0.05 for incidence and -0.9%, p < 0.05 for prevalence) and high-middle (AAPC: -0.8%, p < 0.05 for incidence and -0.9%, p < 0.05 for prevalence) SDI countries showed the decreases which were more dramatic than the decreases in low-middle (AAPC: -0.2%, p < 0.05 for incidence and -0.4%, p < 0.05 for prevalence) and low (AAPC: -0.5%, p < 0.05 for incidence and -0.8%, p < 0.05 for prevalence) SDI countries.
+
+#### Subgroup analysis by road user
+
+Subgroup analysis demonstrated generally similar results to those for overall road traffic mortality, incidence and prevalence. The two most notable differences were during the study period of 2011 to 2017: (1) pedestrians in the high SDI category generally had the lowest mortality and morbidity (incidence and prevalence) [\(Fig.1](#page-2-0)-A1, B1 and C1); and (2) the mortality and morbidity of motor vehicle occupants demonstrated quite distinct gaps across the five SDI categories e the high SDI category had the lowest mortality but the highest morbidity (incidence and prevalence) ([Fig. 1](#page-2-0)-A4, B4 and C4).
+
+<span id="page-2-0"></span>![](_page_2_Figure_9.jpeg)
+
+Fig. 1. Age-standardized road traffic injury mortality, incidence and prevalence by socio-demographic index (SDI), 2011-2017.
+
+Implementation of the three types of recommended national actions
+
+The median score of legislation and enforcement of the five types of national road traffic laws (speed limit law, drink-driving law, motorcycle helmet law, seat-belt law, and child restraint law) gradually increased as the SDI level increased ([Table 1](#page-3-0)). The highest SDI countries had median scores between seven and nine, while the lowest SDI countries had median scores between zero and four. The median scores generally remained stable for all the five SDI countries between 2011 and 2017, except for a sharp increase in child restraint laws for the high-middle SDI category. Notably, the median scores remained at zero for child restraint laws in the three lower SDI categories in both 2011 and 2017, suggesting no progress in those countries in using child restraint laws to protect child motor vehicle occupants.
+
+Implementation of the four prioritized motor vehicle safety standards increased as country SDI increased [\(Table 2](#page-3-1)). Four prioritized United Nations vehicle safety standards[2](#page-5-1) : (1) frontal impact protection ensures that cars withstand the impact of frontal impact crashes at certain speeds to protect occupants, (2) electronic stability control prevents skidding and loss of control in cases of oversteering or understeering to reduce both fatal crash deaths and non-fatal crash injuries, (3) pedestrian protection provides softer bumpers and modifies the front ends of vehicles to reduce the severity of a pedestrian impact with a car, (4) motorcycle anti-lock braking system helps motorcycle operators maintain control during an emergency braking situation and reduces the likelihood of both fatal crash deaths and non-fatal crash injuries. Almost all high SDI countries adopted these standards, while countries with highmiddle or lower SDI only partially implemented the four standards. Remarkably, no low SDI countries and very few low-middle SDI countries implemented any prioritized vehicle safety standards designed to guarantee the safety of pedestrians and occupants.
+
+As for the performance of three trauma-related post-crash care services, the higher SDI countries had comparatively higher proportions of having national and single emergency care access numbers, of providing formal training and certification for all prehospital providers, and of having a national trauma registry compared to the lower SDI countries ([Table 3\)](#page-4-0).
+
+## Discussion
+
+Key findings
+
+This study identified five key findings: (1) age-adjusted road traffic mortality significantly decreased in all the five SDI categories, but large disparities persisted from 2011 to 2017, with the higher SDI countries having lower mortality rates than the lower SDI countries, (2) age-adjusted road traffic morbidity (incidence and prevalence) presented contrary disparities across the study time period, with the higher SDI countries having higher morbidity rates than the lower SDI countries, (3) age-adjusted morbidity decreased slightly in all the SDI categories from 2011 to 2017, except for a significant increase in the middle SDI category, (4) both ageadjusted mortality and morbidity for pedestrians were the lowest in the high SDI category during 2011-2017, a contrast to the broad road traffic injury mortality and morbidity spectrum across the five SDI categories as well as the spectrum for other road users, and (5) the implementation of five national road traffic laws, four prioritized motor vehicle safety standards, and three trauma-related post-crash care services remained nearly unchanged in all five SDI categories from 2011 to 2017, but continued to be stronger in the higher SDI countries than in the lower SDI countries.
+
+#### Interpretation of findings
+
+Mortality disparities across the country SDI concord with differences reported in previous publications: mortality rates are lower in the developed countries compared to the developing countries.[2](#page-5-1),[3](#page-5-13),[16](#page-5-14) These disparities are often attributed to a range of factors, including discrepancies in road infrastructure, unsafe behaviors of road users, legislation and enforcement of road traffic laws, implementation of vehicle safety standards, and pre-hospital emergency medical services and hospital treatments.[2,](#page-5-1)[9,](#page-5-6)[10](#page-5-7),[17](#page-5-15) The
+
+<span id="page-3-0"></span>Table 1 Median and quartile range enforcement score of five types of national road traffic laws by country SDI (2011 vs. 2017).
+
+| SDI group            | Speed limit law |      |      | Drink-driving law |      |      | Motorcycle helmet law |      |      | Seat-belt law |      |      | Child restraint law |      |      |      |      |      |      |      |
+|----------------------|-----------------|------|------|-------------------|------|------|-----------------------|------|------|---------------|------|------|---------------------|------|------|------|------|------|------|------|
+|                      | 2011            |      | 2017 |                   | 2011 |      | 2017                  |      | 2011 |               | 2017 |      | 2011                |      | 2017 |      | 2011 |      | 2017 |      |
+|                      | M               | QR   | M    | QR                | M    | QR   | M                     | QR   | M    | QR            | M    | QR   | M                   | QR   | M    | QR   | M    | QR   | M    | QR   |
+| High (n ¼ 35)        | 7.00            | 1.00 | 7.00 | 2.00              | 7.00 | 3.00 | 7.00                  | 2.00 | 8.00 | 2.00          | 9.00 | 2.00 | 7.00                | 2.00 | 7.00 | 2.00 | 7.00 | 3.00 | 7.00 | 2.00 |
+| High-middle (n ¼ 35) | 6.00            | 2.00 | 6.00 | 2.00              | 7.00 | 3.00 | 7.00                  | 3.00 | 6.00 | 3.00          | 7.00 | 4.00 | 6.00                | 4.00 | 7.00 | 2.00 | 1.00 | 5.00 | 4.00 | 7.00 |
+| Middle (n ¼ 39)      | 4.00            | 4.00 | 5.00 | 3.00              | 5.00 | 3.00 | 5.00                  | 4.00 | 6.00 | 3.00          | 7.00 | 4.00 | 6.00                | 3.00 | 6.00 | 2.00 | 0    | 2.00 | 0    | 4.00 |
+| Low-middle (n ¼ 37)  | 4.00            | 2.50 | 5.00 | 2.00              | 4.00 | 3.50 | 5.00                  | 4.00 | 6.00 | 4.00          | 6.00 | 4.50 | 5.00                | 4.00 | 6.00 | 4.00 | 0    | 0    | 0    | 0    |
+| Low (n ¼ 34)         | 3.00            | 2.25 | 3.00 | 4.25              | 3.00 | 2.00 | 2.00                  | 5.00 | 2.00 | 4.25          | 4.00 | 3.50 | 3.00                | 5.00 | 4.00 | 6.00 | 0    | 0    | 0    | 0    |
+
+SDI: socio-demographic index, M: median, QR: quartile range, QR is the 3rd quartile minus the 1st quartile. Data source: global status report on road safety 2013[9](#page-5-6) and global status report on road safety 2018.[2](#page-5-1)
+
+<span id="page-3-1"></span>Table 2 Number of countries adopting four prioritized United Nations vehicle safety standards by SDI (2014 vs. 2018), n (%).
+
+| SDI group            | Frontal impact protection |            | Electronic stability control |            | Pedestrian protection |            | Motorcycle anti-lock<br>braking system |            |  |
+|----------------------|---------------------------|------------|------------------------------|------------|-----------------------|------------|----------------------------------------|------------|--|
+|                      | 2014                      | 2018       | 2014                         | 2018       | 2014                  | 2018       | 2014                                   | 2018       |  |
+| High (n ¼ 35)        | 34 (97.14)                | 34 (97.14) | 34 (97.14)                   | 34 (97.14) | 32 (91.43)            | 32 (91.43) | /                                      | 29 (82.86) |  |
+| High-middle (n ¼ 35) | 10 (28.57)                | 10 (28.57) | 7 (20.00)                    | 8 (22.86)  | 7 (20.00)             | 7 (20.00)  | /                                      | 4 (11.43)  |  |
+| Middle (n ¼ 40)      | 2 (5.00)                  | 2 (5.00)   | 2 (5.00)                     | 2 (5.00)   | 2 (5.00)              | 2 (5.00)   | /                                      | 1 (2.50)   |  |
+| Low-middle (n ¼ 39)  | 1 (2.56)                  | 2 (5.13)   | 1 (2.56)                     | 1 (2.56)   | 1 (2.56)              | 2 (5.13)   | /                                      | 1 (2.56)   |  |
+| Low (n ¼ 34)         | 0 (0)                     | 0 (0)      | 0 (0)                        | 0 (0)      | 0 (0)                 | 0 (0)      | /                                      | 0 (0)      |  |
+
+<sup>&</sup>quot;/": Data were not included in the global status report on road safety 2015.
+
+SDI:socio-demographic index.
+
+Data sources: global status report on road safety 2015[10](#page-5-7) and global status report on road safety 2018.[2](#page-5-1)
+
+<span id="page-4-0"></span>Table 3 Number of countries with trauma-related post-crash care services by SDI (2011 vs. 2017), n (%).
+
+| SDI group            | National single emergency care<br>access phone number |            | prehospital providers | Formal training and certification or | National trauma registry |            |  |  |
+|----------------------|-------------------------------------------------------|------------|-----------------------|--------------------------------------|--------------------------|------------|--|--|
+|                      | 2011                                                  | 2017       | 2011                  | 2017                                 | 2011                     | 2017       |  |  |
+| High(n ¼ 36)         | 31 (86.11)                                            | 33 (91.67) | 24 (66.67)            | 25 (69.44)                           | /                        | 20 (55.56) |  |  |
+| High-middle (n ¼ 35) | 27 (77.14)                                            | 31 (88.57) | 19 (54.29)            | 26 (74.29)                           | /                        | 13 (37.14) |  |  |
+| Middle (n ¼ 40)      | 19 (47.50)                                            | 21 (52.50) | 22 (55.00)            | 20 (50.00)                           | /                        | 13 (32.50) |  |  |
+| Low-middle (n ¼ 40)  | 16 (40.00)                                            | 16 (40.00) | 13 (32.50)            | 17 (42.50)                           | /                        | 10 (25.00) |  |  |
+| Low (n ¼ 34)         | 12 (35.29)                                            | 13 (38.24) | 3 (8.82)              | 8 (23.53)                            | /                        | 3 (8.82)   |  |  |
+
+<sup>&</sup>quot;/": Data were not included in the global status report on road safety 2013.
+
+Data sources: Global status report on road safety 2013[9](#page-5-6) and Global status report on road safety 2018.[2](#page-5-1)
+
+research also suggests that mortality risks decrease with the implementation of interventions addressing these problems, including road infrastructure improvement,[18](#page-5-16) reduction of unsafe behaviors[,2](#page-5-1) stronger legislation and enforcement of road traffic laws,[19](#page-5-17) stricter implementation of vehicle safety standards,[20](#page-5-18) and higher quality pre-hospital emergency rescue and hospital treatments.[21](#page-5-19) One challenge for safety intervention is that road users in the developing countries display higher rates of unsafe behavior than those in the developed countries, such as failing to abide by road signs and signals, not using seatbelts and helmets, reckless and speedy driving, drinking and distracted driving and walking, and failing to respect a pedestrian's right-of-way.[2](#page-5-1)[,22](#page-5-20) Continued effort to address these behaviors through cultural diversity, normative behavior, and legislation is needed worldwide, and particularly in the lower SDI countries.
+
+Our findings offer novel results to the field. First, we found inconsistent results for mortality and morbidity data across the five SDI categories. Over the course of our study, the mortality from road traffic crashes decreased but the morbidity rose. This may be partly result from higher quality emergency response and postinjury care, and motorization. Crashes may occur, but survival rates become higher. Whatever the cause, the burden of RTIs appears to be slowly transformed from deaths to non-fatal injuries, some of which lead to lifelong disability. Globally, humans may survive road traffic crashes and experience extended life, but they may also suffer disability and lost quality of life[.23](#page-5-21),[24](#page-5-22) Researchers and policy-makers should consider the consequences of these data for efforts to improve injury rehabilitation, work placements for disabled individuals, and improved quality of life for victims of serious RTIs.
+
+We also found disparities across road users among the five SDI categories. In particular, pedestrians in the high SDI category had the lowest mortality and morbidity rates while motor vehicle occupants in the high SDI countries had the lowest mortality but the highest morbidity rates. These data patterns likely reflect the effect of exposure: people may drive and ride in cars more often in the wealthy nations than in poor nations, but walk less often.
+
+The pattern of rapid global motorization is also likely contributing to our results, especially concerning increased road traffic morbidity.[2](#page-5-1),[14](#page-5-11) According to WHO reports,[2](#page-5-1) the cumulative number of total registered vehicles in circulation in 2016 was 766,060,506 (37.5%) in the high SDI countries, 532,765,962 (26.0%) in the highmiddle SDI countries, 430,922,455 (21.1%) in the middle SDI countries, 294,186,940 (14.4%) in the low-middle SDI countries, and 21,460,672 (1.0%) in the low SDI countries; the proportions of registered motor vehicles clearly differ from the proportions of populations for the five SDI categories in 2016 (15.1%, 18.3%, 27.5%, 22.3%, and 16.8%), causing large discrepancies between exposurebased metrics and population-based metrics. Equally important, however, the growth of the number of registered motor vehicles from 2010 to 2016 varied across the SDI categories (8.1%, 35.7%, 52.6%, 76.8%, and 87.3% for high, high-middle, middle, low-middle, and low SDI countries, respectively). Thus, the rapid rise of registered motor vehicles in the lower SDI countries partially influences the pattern of RTIs globally. A recent study by Cheng et al.,[25](#page-5-23) for example, reported large discrepancies in using exposure-based and population-based road traffic mortality to compare rates across countries and over time.
+
+## Implications
+
+Our findings have at least two major implications. First, we illustrated the presence of significant road traffic mortality differences across the five SDI categories between 2011 and 2017. The high SDI countries had the lowest mortality rates and the strongest prevention efforts. The global road injury deaths in 2017 would have decreased by 58% (from 1.24 million to 0.52 million, saving over 700,000 lives)[8](#page-5-5) if the four lower SDI categories had the same mortality rate as the high SDI category (9.1 per 100,000 population).[8](#page-5-5) The SDGs target to halve road traffic deaths and injuries by 2020 might be met in the upcoming years if our society implement technically feasible prevention not only to strengthen legislation and law enforcement, apply the recommended vehicle safety standards, but also to improve the pre-hospital rescue services and hospital treatments effectively. Of course, implementation of these initiatives worldwide would require substantial resources. Continued work, likely under the leadership of the United Nations and the WHO, is needed to mobilize and coordinate each country of the world to implement prevention strategies. International aid may be required to support many the low- and middle-income countries.
+
+Second, the inconsistent morbidity disparities across the five SDI categories reveal the challenge of using population-based metrics instead of exposure-based metrics to study road traffic injury rates. When exposure data are preferential and available, data patterns are easier to interpret.[25](#page-5-23) To facilitate monitoring and evaluating the SDGs progress for road traffic injury precisely, we encourage key stakeholders in the field, including the GBD study group and the WHO, to include valid exposure-based metrics in their annualized updates[8](#page-5-5) and regular reports.[2](#page-5-1) Besides this, improving the reliability and quality of existing data and integration of distinct data sources to diminish the inconsistency of various data and misreporting (including under-reporting and over-reporting) are urgently needed[.26](#page-5-24)<sup>e</sup>[28](#page-5-24)
+
+#### Limitations
+
+This study was primarily limited by the GBD estimates, which are restricted by the availability of high-quality mortality, morbidity and relevant covariates at the country level. In fact, very few countries in the world have regular and high-quality data sources for the estimation of burden of diseases, particularly for
+
+SDI:socio-demographic index.
+
+morbidity and covariate data[.29](#page-5-25)<sup>e</sup>[31](#page-5-25) Therefore, the GBD study group uses a variety of models and methods to address data challenges and estimate road traffic injury mortality and morbidity[.12](#page-5-9) Assumptions used in the GBD estimation models are optimized to the extent possible but remain sub-optimal in some cases and may yield unexpected biases to the final estimates.[32](#page-5-26) This limitation could be solved to some extent by integrating new high-quality data sources and improving the GBD models, stepping the GBD study group routinely engages in[.11](#page-5-8)[,12](#page-5-9)
+
+In conclusion, the lower SDI countries continued to have a higher mortality from road traffic injury, and weaker prevention efforts, from 2011 to 2017. Prevention efforts recommended by the United Nations and the WHO should be fully implemented in all countries globally, including but not limited to legislation and law enforcement, mandated vehicle safety standards, and improved pre-hospital rescue services & hospital treatments. International aid and cooperation are needed, as implementation of evidence-based prevention strategies could have a substantial impact on global public health. In addition, efforts to improve the reliability and validity of road traffic mortality and morbidity estimates should be expedited. Such efforts include use of exposure-based metrics, regular collection of highquality data, integration of diverse data sources, and improvment of the accuracy of models for estimating RTIs.
+
+#### Funding
+
+This work was supported by the National Natural Science Foundation of China (No. 82073672).
+
+#### Ethical statement
+
+This research used anonymous open-access data and did not involve personal information from individuals. This analysis was approved by ethics committee of Xiangya School of Public Health, Central South University, Changsha, China (NO.XYGW-2019-033).
+
+#### Declaration of competing interest
+
+The authors declare that they have no conflicts of interest.
+
+## References
+
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+- <span id="page-5-7"></span>10. World Health Organization. Global Status Report on Road Safety 2015; 2015. [https://www.who.int/violence\\_injury\\_prevention/road\\_safety\\_status/2015/en/](https://www.who.int/violence_injury_prevention/road_safety_status/2015/en/)
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+- <span id="page-5-12"></span>15. Kim HJ, Fay MP, Feuer EJ, et al. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med. 2000;19:335e351. [https://doi.org/](https://doi.org/10.1002/(sici)1097-0258(20000215)19:3<335::aid-sim336>3.0.co;2-z) [10.1002/\(sici\)1097-0258\(20000215\)19:3](https://doi.org/10.1002/(sici)1097-0258(20000215)19:3<335::aid-sim336>3.0.co;2-z)<335::aid-sim336>3.0.co;2-z.
+- <span id="page-5-14"></span>16. Ning P, Schwebel DC, Huang H, et al. Global progress in road injury mortality since 2010. PloS One. 2016;11, e0164560. [https://doi.org/10.1371/](https://doi.org/10.1371/journal.pone.0164560)
+- <span id="page-5-15"></span>17. Mock CN, Jurkovich GJ, nii-Amon-Kotei D, et al. Trauma mortality patterns in three nations at different economic levels: implications for global trauma system development. J Trauma. 1998;44:804e812. [https://doi.org/10.1097/](https://doi.org/10.1097/00005373-199805000-00011)
+- <span id="page-5-16"></span>18. World Health Organization. Save LIVES-A Road Safety Technical Package; 2017. [https://apps.who.int/iris/bitstream/handle/10665/255199/9789241511704](https://apps.who.int/iris/bitstream/handle/10665/255199/9789241511704-eng.pdf?sequence=1) [eng.pdf?sequence](https://apps.who.int/iris/bitstream/handle/10665/255199/9789241511704-eng.pdf?sequence=1)¼[1.](https://apps.who.int/iris/bitstream/handle/10665/255199/9789241511704-eng.pdf?sequence=1)
+- <span id="page-5-17"></span>19. Zhao A, Chen R, Qi Y, et al. Evaluating the impact of criminalizing drunk driving on road-traffic injuries in guangzhou, China: a time-series study. J Epidemiol. 2016;26:433e439. <https://doi.org/10.2188/jea.JE20140103>.
+- <span id="page-5-18"></span>20. Walker C, Thompson J, Stevenson M. Road trauma among young Australians: implementing policy to reduce road deaths and serious injury. Traffic Inj Prev. 2017;18:363e368. <https://doi.org/10.1080/15389588.2016.1212189>.
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Zotero/001_artiklid/Road Safety Indicators/kaselouriseuropeancommissionmainfactors.md

@@ -0,0 +1,570 @@
+---
+category: literaturenote
+citekey: kaselouriseuropeancommissionmainfactors
+title: "European Commission – Main Factors Causing Fatal Crashes Safety Report, April 2024"
+authors: "Kaselouris, Konstantinos"
+url: "https://www.nrso.ntua.gr/european-commission-main-factors-causing-fatal-crashes-safety-report-april-2024/"
+zotero_key: PFMWPKYL
+zotero_storage: IAT24KE8
+collections: doktoritöö / HLO
+folder: 001_artiklid/Road Safety Indicators
+firstAuthor: "Kaselouris, Konstantinos"
+status: converted
+---
+![](_page_0_Picture_0.jpeg)
+
+![](_page_0_Figure_1.jpeg)
+
+This document is part of a series of 20 thematic reports on road safety. The purpose is to give road safety practitioners and the general public an overview of the most important research questions and results on the topic in question. The level of detail is intermediate, with more detailed papers or reports suggested for further reading. Each report has a 1-page summary.
+
+Contract: This document has been prepared in the framework of the EC
+
+Service Contract MOVE/C2/SER/2022-55/SI2.888215 with National
+
+Technical University of Athens (NTUA), SWOV Institute for Road Safety Research and Kuratorium für Verkehrssicherheit (KFV).
+
+Version 15 April 2024
+
+Author Eleonora Papadimitriou (TU Delft)
+
+Internal Review: Anastasios Dragomanovits (NTUA)
+
+External Review: Ashleigh Filtness (Loughborough University)
+
+Referencing: Reproduction of this document is allowed with due
+
+acknowledgement. Please refer to the document as follows:
+
+*European Commission (2024). Road safety thematic report – Main factors causing fatal crashes. European Road Safety Observatory.* 
+
+*Brussels, European Commission, Directorate General for Transport*.
+
+#### **Disclaimer**
+
+Whilst every effort has been made to ensure that the matter presented in this document is relevant, accurate and up to date, the (sub)contractors cannot accept any liability for any error or omission, or reliance on part or all of the content in another context.
+
+Any information and views set out in this document are those of the author(s) and do not necessarily reflect the official opinion of the European Commission. The Commission does not guarantee the accuracy of the data included in this study. Neither the Commission nor any person acting on the Commission's behalf may be held responsible for the use that may be made of the information contained therein.
+
+© European Commission, 2023.
+
+The EU does not own the copyright in relation to the following elements:
+
+- Cover page photos, © www.shutterstock.com
+
+| 1. | Summary         |                                                        | 4  |
+|----|-----------------|--------------------------------------------------------|----|
+| 2. |                 | Identifying the main factors causing fatal crashes<br> | 5  |
+|    | 2.1             | Crash causation                                        | 5  |
+|    | 2.2             | Data on crash causation<br>                            | 7  |
+| 3. |                 | Key elements of factors causing fatal crashes<br>      | 12 |
+|    | 3.1<br>Speeding |                                                        | 12 |
+|    | 3.1.1           | Mechanism                                              | 12 |
+|    | 3.1.2           | Prevalence<br>                                         | 13 |
+|    | 3.1.3           | Safety impacts<br>                                     | 15 |
+|    | 3.1.4           | Interventions                                          | 16 |
+|    | 3.2             | Alcohol & drugs<br>                                    | 17 |
+|    | 3.2.1           | Mechanism                                              | 17 |
+|    | 3.2.2           | Prevalence<br>                                         | 18 |
+|    | 3.2.3           | Safety impacts<br>                                     | 20 |
+|    | 3.2.4           | Interventions                                          | 21 |
+|    | 3.3             | Distraction                                            | 22 |
+|    | 3.3.1           | Mechanism                                              | 22 |
+|    | 3.3.2           | Prevalence<br>                                         | 22 |
+|    | 3.3.3           | Safety impacts<br>                                     | 24 |
+|    | 3.3.4           | Interventions                                          | 25 |
+|    | 3.4             | Use of protective equipment<br>                        | 25 |
+|    | 3.4.1           | Mechanism                                              | 25 |
+|    | 3.4.2           | Prevalence<br>                                         | 26 |
+|    | 3.4.3           | Safety impacts<br>                                     | 27 |
+|    | 3.4.4           | Interventions                                          | 28 |
+| 4. |                 | Further reading                                        | 29 |
+|    |                 |                                                        |    |
+
+# <span id="page-3-0"></span>**1. Summary**
+
+Crash contributory factors include an array of human, technical and organisational factors that interact within a complex and dynamic traffic environment. The Safe System approach stipulates that system design should anticipate, prevent and forgive human errors, so that safety does not depend on the behaviour or actions of an individual driver. Infrastructure and vehicle design, traffic laws and their enforcement, and the promotion of safety culture are important layers of the safe system, together with post-impact care for the mitigation of crash consequences.
+
+In this context, addressing a number of risk factors is considered fundamental for the reduction of fatal and serious crashes: speeding, driving under the influence of alcohol, distraction and other psychoactive substances, and non-use of protective equipment. Other important contributory factors are fatigue, traffic rules violation (e.g. red light running, illegal crossing or overtaking), infrastructure deficiencies, inappropriate speed limits, unsafe vehicles, and inadequate enforcement.
+
+- Speeding is a contributory factor in ~30% of fatal crashes, and a reduction of 10 km/h of the initial speed may result in ~50% reduction in fatal accidents.
+- Alcohol is involved in ~25% of fatal crashes in Europe. The fatal crash risk of driving under the influence of drugs ranges between 1.3 and >5 times higher than that of a sober driver.
+- 2-10% of European drivers are engaged in hand-held phone use at any moment, while the self-reported frequencies of hand-held, hands-free use and texting are much higher. Distraction significantly affects lateral control of the vehicle, visual attention and reaction time. Drivers often engage in compensatory behaviours (e.g. reducing speed, increasing distance from the vehicle ahead etc.) but these are mostly ineffective in counterbalancing the impaired reaction time. Distraction plays a role in 5 - 25% of crashes in Europe. The impact of distraction on crash risk ranges from ~1.5 increase for hands-free use, to ~2.5 increase for operating vehicle systems, to 3-3.5 increase for hand-held use, and eventually to >6 increase for texting.
+- Seat belt wearing rates in rear seats and helmet use among riders of powered two-wheelers (PTWs) are still low in several EU countries. Non-use of seat belts is associated with ~25% of European fatalities; in several countries the figure is much higher. It is estimated that 900 deaths per year could be avoided in the European Union if 99% of car occupants wore seat belts.
+
+These results indicate that addressing the above causes of fatalities in Europe, through safe-by-design thinking, i.e. prevention, control and mitigation of the consequences of these errors, can contribute significantly towards the ambitious EU targets of halving fatalities by 2030 and eliminating them by 2050.
+
+# <span id="page-4-0"></span>**2. Identifying the main factors causing fatal crashes**
+
+## <span id="page-4-1"></span>**2.1 Crash causation**
+
+In the EU around 20,400 people were killed in road crashes in 2023, a 1% decrease compared to 2022 as traffic levels fully recovered after the pandemic. The EC is committed to the Vision Zero targets of halving traffic fatalities by 2030 and eliminating them by 2050. In this context, it is crucial to have a full understanding of the main factors that cause traffic fatalities.
+
+It is often identified in the literature that human factors are contributory factors to ~95% of crashes, whereas infrastructure factors and vehicle factors contribute to ~30% and ~10% of crashes. This approach is driven from a liability perspective, which focuses on the events of the crash and the actions taken by its participants; it is the approach widely taken by traffic police and insurance investigations (Hauer, 2020), both interested in 'blame attribution'. In contrast, in-depth accident investigations are largely driven by a systems perspective, in which human, technical and organisational factors interact within a complex, dynamic, and often loosely regulated traffic environment.
+
+The Safe System approach recognises that humans are imperfect drivers and at the same time vulnerable to serious traffic injuries and fatalities, and therefore postulates that the systems should be designed, maintained and operated in a way that anticipates and forgives human error. Accordingly, the pillars of a Safe System approach include safe roads and roadsides, safe speeds, safe vehicles, and safe road users, all of which must be addressed in order to eliminate fatal crashes and reduce serious injuries (WHO, 2018).
+
+The term 'human factors' encompass a number of factors including individual characteristics, including demographics, knowledge, skills, experience, personality traits, attitude /perceptual / motivational factors, disease or impairment, and the resulting observed risky driving behaviour. The latter may concern speeding (exceeding speed limits or inappropriate speed for the conditions), driving under the influence of drugs or alcohol, non-use of protective equipment, inattention or distraction, drowsiness, harsh manoeuvring, tailgating, illegal crossing or overtaking, misjudgement and observation errors, or traffic rule violations (EU-DSS, 2023).
+
+Among all the potential causes, addressing a number of specific risk factors is considered fundamental for the reduction of fatal and serious injury crashes (WHO, 2023) : speeding, driving under the influence of alcohol and other psychoactive substances, non-use of motorcycle helmets, seat belts, and child restraints, and distracted driving. These factors are not only highly prevalent in fatal crashes but are also associated with more severe safety outcomes; therefore, further efforts are needed to prevent, control and mitigate their impacts. Alongside the above key risk factors, unsafe infrastructure, unsafe vehicles, inadequate post-crash care, inappropriate speed limits and inadequate traffic laws / enforcement may trigger or exacerbate the prevalence and impacts of human behaviour. At the same time, the design of selfexplaining and forgiving road infrastructure and safety technology equipped vehicles, together with the effective education and enforcement of credible traffic laws, can prevent and mitigate human errors and foster safety awareness and positive safety culture among road users.
+
+It has been well established in safety science that many of the errors that humans make are – apart from mistakes (random or systematic, due to lack of knowledge, skills or experience) or intentional violations - in fact 'latent errors', i.e. errors resulting from systems and routines that are *designed in way that humans are disposed to making errors* (Reason, 1990). Moreover, the 'Swiss cheese' model (see Figure 1) demonstrates that accidents are a result of the alignment of several failures along sequential layers of the safety management system, where human action is the last layer of the system.
+
+*Figure 1. Swiss Cheese model of accident causation. Source: Reason (1990)*
+
+![](_page_6_Picture_2.jpeg)
+
+In this sense, human factors as crash contributor factors should be considered as causes that could have been avoided through system design and safety culture, thereby not placing a disproportionate share of responsibility on road users. More specifically, system design should anticipate, prevent and forgive human errors. This way, latent errors can be prevented, by making safety independent from the actions or choices of individual humans. This implies a highly proactive approach, in which interventions are made as early on the chain as possible.
+
+# <span id="page-6-0"></span>**2.2 Data on crash causation**
+
+In this section, data is presented aiming to demonstrate the prevalence of the main contributory factors to fatal crashes across Europe. However, it is often difficult to rank these key contributory factors in terms of importance. The share of reported contributory factors varies to some extent in different countries. Indicatively, in the OECD/ITF Road Safety country profiles (ITF, 2023), it is reported that:
+
+• In France in 2020, according to police reports and in-depth crash investigations (CEREMA, 2021), speed was one of the causes of 29% of fatal crashes. The share of alcohol-related fatalities has remained stable at around 30% since 2000. It was estimated that 21% of all road deaths occurred in a crash with a driver under the influence of illegal drugs. Moreover, at any given time during daytime, 2.5% of passenger car drivers, 6% of light-duty vehicle drivers and 4.5% of heavy vehicle drivers used a handheld or ear-mounted phone, while this was a cause in 2-4% of fatal crashes (CEREMA, 2021). Moreover, 24% of car occupants killed were not wearing a seat belt or the seat belt was not appropriately buckled when the crash occurred.
+
+- In Germany, inappropriate speed was a factor in about 34% of fatal crashes in 2020. Alcohol was cited as a contributory factor in around 4 -5.8% of fatal crashes. An assessment conducted in 2019 showed that 3% of passenger car drivers use their smartphones while driving, 2% type on their smartphone and have at least one hand off the steering wheel and the view off the road ahead.
+- In Greece in 2018, it was estimated based on police reports that about 18% of fatalities were directly related to excessive or inappropriate speeds, and almost 23% of road fatalities were attributed to drink driving.
+- In Austria in 2020, 32% of all road fatalities were caused by inappropriate speed, while alcohol was involved in 8% of fatalities. In a recent study<sup>1</sup> , it was found that distraction (lack of attention, lack of concentration and simply overlooking other road users) was the presumed leading cause of 21.5% of all road fatalities in 2020.
+- In Poland, speed remains one of the leading causes of crashes and contributes to 42% of fatalities, while 13% of traffic fatalities were alcohol-related in 2020. Based on data from 2016, around 4% of drivers in passenger cars use hand-held mobile phones.
+- In Spain in 2020, inappropriate speed contributed to 25% of fatal crashes. 61% of fatally injured drivers on interurban roads were administered drug tests, with 19% testing positive. On urban roads, 62% of fatally injured drivers were tested, with 31% testing positive. Distraction, including the use of mobile phones, radios, DVDs, witnessing a previous crash, looking at the environment, absent-mindedness and sudden illness or indisposition, was a factor in 31% of fatal crashes in 2020. Moreover, 27% of car and van fatalities aged 12 and over were not wearing seat belts on interurban roads, while this figure jumps to 37% of deaths on urban roads.
+- In Slovenia, 34% of total road fatalities were caused by excessive speed. Official data attributed around 0.4% of traffic crashes to drivers under the influence of drugs.
+- In Finland, according to reports from road crash investigation teams, speeding or inappropriate speed contributes to 30% of all fatal crashes. In 2020, 26% of casualties were injured in drinkdriving related cases. While 49% of car or van occupants killed were not wearing a seat belt.
+
+It is important to note that the reporting methods of the above data vary considerably. Most countries report on the basis of police data, which have several limitations: most importantly, no formal methods
+
+<sup>1</sup> <https://www.kfv.at/ablenkung/>
+
+to identify contributory factors are implemented. Moreover, it is not known whether multiple risk factors are recorded in a single crash, or only the main cause per crash is reported. Therefore, the above figures are not directly comparable; moreover, it is likely that the above figures are an under-estimation of the magnitude of these contributory factors in most countries. Furthermore, the lag in releasing the yearly official figures in most countries does not allow assessing the most recent situation.
+
+The pertinent method for determining crash causation is that of indepth accident investigation, led by a multi-disciplinary team of investigators, but only a few countries systematically perform such investigations, and these are only on a sample of all fatal crashes – for economic and logistics reasons. Most importantly, there are very few attempts to perform in-depth investigations at European level on the basis of a common investigation methodology. The establishment of the European Road Safety Observatory (ERSO) came with the presentation of an important methodological framework and the implementation of a pilot study of crash causation in Europe, based on data from 997 fatal crashes in 6 countries. The main results are reported in Thomas et al. (2013).
+
+In that study, it was found that, in terms of general causation factors<sup>2</sup> , timing errors, i.e. situations where the road user did not act when they should have done, or on the contrary acted too quickly, were the most common (namely 51% of car drivers, 42% of motorcyclists, 68% of pedestrians and 46% of cyclists); these timing errors may result from driver distraction, alcohol/drug influence, or fatigue resulting in late reactions. Speed errors were observed in 15% of car drivers, and in 26% of motorcyclists.
+
+Table 1 shows the more detailed analysis of specific causation factors; a temporary person-related function accounts for 25% of fatal crash causes – out of which a total of 52% is attributable to inattention (22%)/ distraction (30%), a total of 19% is attributable to fatigue or sleepiness and 17% is attributable to driving under the influence. Another 16% of fatal crash causes is accounted for by interpretation errors – out of which 44% are faulty diagnosis or error in mental model, e.g. a lack of situational awareness.
+
+One of the particularities of in-depth studies is that the attributed contributory factors are based on detailed causation models, looking
+
+<sup>2</sup> General causation factors are defined as 'nine classes of contributory factors that together are taken to describe all types of physical interaction and which characterise an action' immediately before the crash, and are separated into specific risk factors that precede both chronologically and within the causation chain.
+
+backwards at the source of the inappropriate driving behaviour – and including important factors like fatigue or mental errors that can not be identified by the police. In most cases, more than one sources of error may be involved in the manifestation of a certain risk factor (e.g. a speed error may be caused by a faulty diagnosis of the road layout, which is due to an abrupt change in infrastructure design, inexperience resulting from insufficient training, or all of these at the same time). Therefore, the shares of risk factors from crash causation data cannot always be interpreted in a straightforward way, and cannot be directly related to the key factors involved in fatal crashes as reported by the police.
+
+Nevertheless, the data and information in Table 1 clearly indicate that the five main risk factors in fatal crashes can be well distinguished as standing out from the entire pool of possible fatal crash causes, and therefore particular emphasis should be given to addressing them.
+
+*Table 1. Main contributory factors of fatal crashes in Europe (Adapted from Thomas et al., 2013)*
+
+| Contributory factor                      | Share of crashes |
+|------------------------------------------|------------------|
+| Temporary person related function        | 25%              |
+| Distraction                              | 30%              |
+| Inattention                              | 22%              |
+| Under influence                          | 17%              |
+| Stress                                   | 15%              |
+| Not illness related                      | 9%               |
+| Fatigue                                  | 12%              |
+| Circadian rhythm                         | 6%               |
+| Extensive driving                        | 1%               |
+| Other                                    | 7%               |
+| Interpretation                           | 16%              |
+| Faulty diagnosis - error in mental model | 44%              |
+| Misjudgement of time-distance            | 18%              |
+| Communication                            | 15%              |
+| Planning                                 | 13%              |
+| Design of traffic environment            | 12%              |
+| Experience and training                  | 4%               |
+
+In a French report on causes of fatal crashes (CEREMA, 2021), an exhaustive list of human, vehicle and infrastructure related contributory factors were ranked in terms of causation frequency. The results are presented in Figure 2 Similar in-depth investigation results are available for accident causes in general or for specific road user groups in particular, also in other European countries, e.g. for cyclists in the Netherlands (Boele-Vos et al., 2017), for Heavy Goods Vehicles in Germany (Schindler et al., 2022).
+
+*Figure 2. Contributory factors present in more than 2% of fatal crashes in France (Sample size N= 2878 crashes) (Source: CEREMA, 2021)*
+
+![](_page_10_Figure_3.jpeg)
+
+In the following sections, a comprehensive review of the state of the art and recent available data is given on the identified main causes of fatal crashes, with focus on: i) their mechanism of affecting driving behaviour; ii) their prevalence among road users; iii) their impact on road safety in terms of accident occurrence, severity and risk; and iv) the main interventions that can be made to prevent these causes and mitigate their consequences. The detailed description of measures for tackling them is beyond the scope of this Thematic Report; the reader is referred to ERSO (2021, 2021a, 2021b, 2021c) for more details.
+
+# <span id="page-11-0"></span>**3. Key elements of factors causing fatal crashes**
+
+## <span id="page-11-1"></span>**3.1 Speeding**
+
+#### <span id="page-11-2"></span>**3.1.1 Mechanism**
+
+There are several reasons why road safety outcomes are affected by speed (EC, 2021):
+
+- High speed results in less time to react to an unexpected event, for the same driver reaction time, because the distance covered before the reaction is greater at high speed. High speed also increases the braking distance, as the latter is proportional to the square of the speed (see Figure 3).
+- The higher the speed of any given approaching vehicle the less time there is for other road users to react and avoid a collision.; in this case, other road users may also often overestimate the time left to react.
+- High speed results in narrower field of vision for the driver. For instance, at 130 km/h, a driver has only an angle of about 30°, which limits considerably their ability to detect and assess hazards (OECD/ECMT, 2006).
+- Obviously, higher impact speed means higher amount of energy released during the crash, and more severe injuries.
+
+*Figure 3. Reaction distance and stopping distance for different driving speeds. Source: Queensland Government (2023)*
+
+![](_page_12_Figure_3.jpeg)
+
+## <span id="page-12-0"></span>**3.1.2 Prevalence**
+
+Several recent studies and reports have reported on the prevalence of speeding in Europe. Table 2 shows data collected and published by the EC project Baseline on speeding on European roads on 2023. While there is large variability in the degree to which countries monitor speed limits, as well as on the methods for monitoring, the report concludes that:
+
+- On urban roads, between 27% and 79% of observed vehicle speeds are higher than the speed limit.
+- On interurban / rural roads (non-motorways), between 7% to 71% of observed vehicle speeds are higher than the speed limit.
+- On motorways, between 11% and 60% of observed vehicle speeds on motorways are higher than the speed limit.
+
+*Table 2. Observed mean speeds (free flow) and proportion (in %) of observed speeds lower than the speed limit for cars during weekdays/daytime on urban, rural roads and motorways (Source: Van der Broek et al., 2023)*
+
+| Country | Urban roads |             | Rural roads |             | Motorways |             |
+|---------|-------------|-------------|-------------|-------------|-----------|-------------|
+|         | Mean        | % within    | Mean        | % within    | Mean      | % within    |
+|         | speed       | speed limit | speed       | speed limit | speed     | speed limit |
+| AT      | 50          | 57          | 85          | 89          | 121       | 81          |
+| BE      | -           | 40          | -           | 52          | -         | 56          |
+| BG      | 52          | 45          | 64          | 93          | 116       | 89          |
+| CY      | 56          | 26          | 69          | 46          | 98        | 47          |
+| CZ      | 50          | 57          | 89          | 55          | 134       | 40          |
+| FI      | 54          | 42          | 83          | 43          | 109       | 45          |
+| EL      | 47          | 59          | 68          | 84          | 109       | 78          |
+| IE      | 58          | 25          | 91          | 89          | 106       | 88          |
+| LV      | 52          | 41          | 97          | 29          | -         | -           |
+| LT      | 54          | 36          | 93          | 47          | 118       | 77          |
+| MT      | 45          | 70          | 60          | 74          | -         | -           |
+| PL      | 61          | 21          | 91          | 52          | 126       | 54          |
+| PT      | 44          | 73          | 97          | 36          | 124       | 44          |
+| ES      | 42          | 51          | 94          | 43          | 121       | 51          |
+| SE      | 47          | 66          | 70          | 52          | 108       | 44          |
+
+Moreover, self-reported speed limit exceedance rates are in many cases higher than the observed ones. The ESRA<sup>3</sup> survey results (Holocher & Holte, 2019) showed that in 2018, 56% of European car drivers indicated that they had deliberately driven faster than the speed limit in built-up areas at least once in the previous month (67% on rural roads and 62% on motorways). The differences between countries lie on a range between 44-80% of drivers on motorways, 55-82% of drivers on interurban / rural roads and 40-73% of drivers on urban roads (see Figure 4).
+
+<sup>3</sup> [www.esranet.eu](http://www.esranet.eu/)
+
+*Figure 4. Self-reported speeding behaviour of car drivers (at least once over the previous 30 days) (Source: Holocher & Holte, 2019)*
+
+### <span id="page-14-0"></span>**3.1.3 Safety impacts**
+
+The Safe System approach stresses the human body tolerance to a collision as a function of impact speed (see Figure 3); a pedestrian or cyclist can tolerate up to ~30 km/hour, while a car occupant can tolerate 50-70 km/h impact speed in side collisions, and 70-90 km/h in frontal or hard object collisions (Yannis & Papadimitriou, 2021 based on Tingval and Haworth, 1999).
+
+Moreover, a speed increase of 10 km/h leads to a doubling of the risk of injury crash, and even higher risk of fatal crash (see Figure 5).
+
+*Figure 5. Relationship between speed change and crash rate (left panel) – relationship between impact speed and fatality risk (right panel).* 
+
+![](_page_14_Figure_7.jpeg)
+
+*Sources: Van den Berghe & Pelssers (2020) based on coefficients of exponential model in Elvik et al. (2019); Yannis & Papadimitriou, 2021 based on Tingval and Haworth, 1999*
+
+Accordingly, it is estimated by ETSC that reducing the average speed by 1 km/h on all roads across the EU would save over 2000 lives per year (Adminaité-Fodor & Jost, 2019). WHO further suggests that a pedestrian who is hit by a car travelling at 65km/h is four times more likely to be killed compared with a car travelling at 50km/h (WHO, 2018).
+
+The impact of speed on road safety outcomes is largely estimated on the basis of the 'Power Model' (see Eq.1); this suggests that the number of fatal accidents, serious injury accidents (including fatal accidents), and all police reported injury accidents (including fatal and serious injury accidents) change in proportion to, respectively, the fourth, third and second power of the relative change in the mean speed of traffic" (Aigner-Breuss et al., 2017).
+
+$$\frac{Accidents\ after}{Accidents\ before} = \left(\frac{Speed\ after}{Speed\ before}\right)^{Exponent} \tag{1}$$
+
+A re-analysis of the Power Model (Elvik, 2013) indicates that the relationship between speed and road safety does not only depend on the relative change in speed, but also on the initial speed of traffic: a 25% speed change from 20 km/h to 15 km/h will have lower effects than the same reduction from 100 km/h to 75 km/h.
+
+Additionally, Elvik's analysis resulted in exponential functions that fitted *"the data extremely well and imply that the effect on accidents of a given relative change in speed is largest when initial speed is highest*" (Elvik, 2013, p. 854). The analyses suggest that a reduction of 10 km/h of the initial speed results in ~50% reduction in fatal accidents and a 28.9% reduction in injury accidents when reducing the initial speed by 10 km/h.
+
+#### <span id="page-15-0"></span>**3.1.4 Interventions**
+
+There are four main areas of intervention for speeding:
+
+• Speed limits and their enforcement: while speed limits balance between mobility, safety and environmental considerations, the human body's physical tolerance to traffic impacts should be the backbone of credible and safe speed limits. The Dutch Sustainable Safety approach (Wegman & Aarts, 2005) indicates that speed limits should be defined on the basis of the type of traffic conflicts that can be observed on the network (frontal, lateral or at-angle, between cars and unprotected road users etc.), so that traffic participants are not exposed to intolerable speeds. Dynamic speed limits, taking into account traffic or weather conditions are also very effective (Daniels & Focant,
+
+- 2017). At the same time, enforcement of speed limits, either by means of police patrolling or by means of speed cameras has proven to be very effective in preventing speeding and fostering a compliant culture among drivers.
+- Road infrastructure design should encourage appropriate speed selection by self-explanatory roads with clear functionality (through, distributor or access road) without abrupt changes (i.e. maintaining design consistency). Moreover, credibility of speed limits particularly in urban or semi-urban settings can be enhanced with infrastructure arrangements e.g. road narrowings, speed humps or roundabouts.
+- Vehicle technologies like Intelligent Speed Adaptation or Adaptive Cruise Control can help drivers maintain a safe speed and comply with the posted speed limits.
+- Awareness raising and education are important additional tools for a sustainable safety culture, and should be promoted not only by authorities, but also vehicle manufacturers, fleet managers, companies, schools. Rehabilitation programmes for speeding offenders are also found to be effective.
+
+# <span id="page-16-0"></span>**3.2 Alcohol & drugs**
+
+## <span id="page-16-1"></span>**3.2.1 Mechanism**
+
+Alcohol and drugs may impair several functional capabilities critical for safe driving, including reaction time, tracking ability, proper speed management, vision, divided attention, and vigilance (EC, 2021). In a general review of the effects of alcohol on cognitive driving tasks, Garrison et al. (2021) conclude that:
+
+- deficits in aspects of visual perception begin at a Blood Alcohol Concentration (BAC) of 0.3 g/L
+- impairments in vigilance start at a BAC of 0.3 g/L
+- deficits in divided attention and sustained attention start at BACs between 0.5 g/L and 0.8 g/L
+- problems with dividing attention over several tasks begin at a BAC of 0.8 g/L.
+
+The mechanisms by which alcohol and drugs (legal and illegal) affect the human body, the extent to which they impair driving, and the duration of the impairment differ greatly among drugs and among individuals (Compton, 2017).
+
+#### <span id="page-17-0"></span>**3.2.2 Prevalence**
+
+It has been estimated that about one quarter of road fatalities in Europe are alcohol related (European Commission, 2018). There is no recent overall estimate of the number of drug-related casualties in Europe.
+
+In the DRUID-project, the prevalence of alcohol (and other drug use) in the driving population was assessed in 13 European countries, by means of roadside surveys in the period between January 2007 and July 2009. In total, 50,000 blood or oral fluid samples from 50,000 consenting drivers were analysed. The results indicated that alcohol was present in 3.48% of road users and a combination of alcohol with drugs or medicines in 0.37% (Houwing et al. 2011). In the same project a cross-sectional survey was conducted to determine the prevalence of alcohol (and other drugs) in drivers seriously injured (between October 2007 and May 2010) or killed (between January 2006 and December 2009) in road traffic accidents in 9 European countries. Alcohol was detected in 14.1-30.2% of the seriously injured drivers and in 15,6 – 38,9% of the killed drivers (EMCDDA, 2012).
+
+Moreover, the BASELINE project (collected an alcohol KPI in European countries, and found that the share of drivers that are not within the legal alcohol limit range between 0.1-2.7% when calculated on the basis of random roadside breath testing, between 0.3-9.1% when calculated through questionnaire surveys, and 4% when calculated by police enforcement (not random). The latter can be explained by the fact that police may implement more targeted roadside checks focusing on high risk days, areas etc.
+
+Another indicator of alcohol use in traffic is the share of alcohol offenders per country, i.e. driver with a BAC level higher than the legal BAC limit. Table 3 provides an overview of the share of alcohol offenders among drivers that were tested for alcohol at roadside police checks in Europe (ETSC, 2022). The share of alcohol offenders that were caught by the police during roadside police checks varies between 0.6% in and 8.3%.
+
+*Table 3. Roadside alcohol breath tests per 1000 inhabitants and the proportion of those above the legal limit (Source: ETSC, 2022)*
+
+| Country | Roadside Police breath<br>tests per 1000<br>inhabitants | % above legal BAC limit |
+|---------|---------------------------------------------------------|-------------------------|
+| AT      | 155                                                     | 2.1                     |
+| CY      | 31                                                      | 8.3                     |
+| EE      | 576                                                     | 0.8                     |
+| FI      | 71                                                      | 2.3                     |
+
+| FR | 109 | 3.2 |
+|----|-----|-----|
+| HU | 185 | 1.2 |
+| IE | 18  | 0.6 |
+| SE | 33  | 2.3 |
+| PL | 219 | 1.2 |
+| PT | 160 | 2.2 |
+
+It is noted however that the comparability of this data is limited, and there is insufficient information about their accuracy; countries have very different enforcement practices in terms of frequency, spatial and temporal coverage and reporting procedures, and therefore results may not be representative of country prevalence.
+
+The self-reported driving under the influence is even higher than the above rates. The ESRA study revealed that between 5-34% of European drivers declared driving after drinking alcohol in the last month, while between 1.7-10.5% of European drivers declared driving after using drugs (other than medication) – see Figure 6.
+
+*Figure 6. Self-declared use of alcohol, drugs and medicines (Source: Achermann Stürmer et al., 2021).*
+
+![](_page_18_Figure_5.jpeg)
+
+It is also interesting to note that a higher number of controls does not necessarily imply a higher number of offenders. In fact, the increase in enforcement is expected to initially result in more offenders observed; however, as the perceived degree of apprehension increases – with systematic enforcement – an eventual behaviour change may be occurred, reflected as fewer offenders observed.
+
+#### <span id="page-19-0"></span>**3.2.3 Safety impacts**
+
+Regarding the impact of alcohol, impairment of driving skills can start from BACs as low as 0.01-0.02%. The risk for drivers with a BAC of 0.5 g/L is estimated to be about 2-10 times higher than that of a sober driver; at 1.0 g/L the risk is 5-30 times higher, and at 1.5 g/L around 20-200 times higher (see Figure 7; Voas et al., 2012; EC DG-MOVE, 2022).
+
+Generally, the risk of a crash increases considerably when a driver is impaired by a combination of alcohol and drugs. A meta-analysis of SWOV (2020) reports that a combined use of alcohol and drugs may increase crash risk by 20-200%.
+
+*Figure 7. Relative risk of fatal accident involvement at various BACs compared to zero BAC (Voas et al., 2012, 2005).*
+
+![](_page_19_Figure_5.jpeg)
+
+Regarding the impact of drugs use on road safety, Table 4 shows the crash risk increase for illegal drugs as found in several meta-analyses (SWOV, 2020), with focus on fatal crashes. The highest increase in fatal crash risk is associated with amphetamines, followed by cocaine, opiates and cannabis.
+
+For both alcohol and drugs, several confounding factors will also affect crash risk, including patterns of use, reasons for use, dose ingested, mode of administration, tolerance, and driver characteristics (Beirness et al., 2021).
+
+*Table 4. Risk increase for several groups of illegal drugs (Source: SWOV, 2020)*
+
+| Drug                           | Crash severity                                 | Risk<br>increase | 95% Confidence<br>Interval |
+|--------------------------------|------------------------------------------------|------------------|----------------------------|
+| Amphetamines                   | Fatal<br>(Elvik, 2013)                         | 5.2              | (2.6 – 10.4)               |
+| Cannabis                       | Fatal<br>(Elvik, 2013)                         | 1.3              | (0.9 – 1.8)                |
+|                                | Fatal and injuries<br>(Rogeberg & Elvik, 2016) | 1.4              | (1.1 – 1.6)                |
+|                                | Fatal and injuries<br>(Els et al., 2019)       | 2.5              | (1.7 – 3.7)                |
+|                                | Fatal and injuries<br>(Rogeberg, 2019)         | 1.3              | (1.2 – 1.4)                |
+| Cocaine                        | Fatal<br>(Elvik, 2013)                         | 3.0              | (1.2 – 7.4)                |
+| Opiates                        | Fatal<br>(Elvik, 2013)                         | 1.7              | (1.0 – 2.8)                |
+| Multiple<br>drugs              | All crashes<br>(Hels et al., 2011)             | 5 - 30           | -                          |
+| Combination<br>alcohol & drugs | All crashes<br>(Hels et al., 2011)             | 20 - 200         | -                          |
+
+### <span id="page-20-0"></span>**3.2.4 Interventions**
+
+A main direction for preventing alcohol and drug use while driving is the reduction of their consumption in the general population, through pricing, taxation or marketing regulations. Traffic measures and policies that are important include (EC, 2021):
+
+- BAC limits and their enforcement: Lowering BAC limits is found to have a positive effect on reducing alcohol related crashes. However, this is most effective when combined with systematic randomised alcohol tests.
+- Awareness campaigns and rehabilitation programmes have been found important in leading to behaviour change, especially for recidivist drivers. Organisational safety culture can play an important role among professional drivers. Providing affordable alternative means of transport (e.g. taxi or ride-sharing options) can significantly reduce drink-driving, especially in suburban or rural areas.
+- Vehicle technologies, namely alcohol interlocking, can significantly reduce the risk of recidivism. Moreover, various invehicle systems may assist in identifying signs of alcohol or drug impairment (e.g. drowsiness detection), and the mitigation of its consequences on driver performance (e.g. collision warning, lane departure warning etc.)
+
+# <span id="page-21-0"></span>**3.3 Distraction**
+
+#### <span id="page-21-1"></span>**3.3.1 Mechanism**
+
+Distracted driving is defined as a diversion of attention from the main driving tasks that are critical for safe driving, towards a competing invehicle task, or to other internal or external activities. The nature of distraction can be:
+
+- motor (e.g. holding a mobile phone)
+- visual (e.g. looking at a mobile phone or in-vehicle screen),
+- auditory (e.g. listening to loud music),
+- cognitive (e.g. conversing, daydreaming).
+
+Its source may or may not be related to technology, to something inside or outside the vehicle, self-initiated or imposed (EC, 2021).
+
+Distraction or inattention while driving leads drivers to have difficulty in lateral control of the vehicle (e.g. swerve more), have longer reaction times, and miss information from the traffic environment. At the same time, drivers implement a number of compensatory behaviours, by reducing their speed, increasing the headway from the lead vehicle – however in most cases these are not sufficient to counterbalance the impaired driving performance.
+
+The extent of the negative impact of distraction on driving behaviour depends on numerous factors. The main ones are the type or source of distraction, and the traffic context (e.g. distracted driving may be less detrimental in quiet traffic conditions). The timing, intensity, resumability, complexity, duration, frequency and residual effects of the distracting activity also play a role, together with personal characteristics such as age and driving experience (Kinnear & Stevens, 2018; SWOV, 2020).
+
+#### <span id="page-21-2"></span>**3.3.2 Prevalence**
+
+The BASELINE project estimated a KPI for distracted driving (as the percentage of drivers not holding a mobile phone whole driving) and collected data for a number of European countries. Figure 8 summarises the KPI estimates for 2022, for all transport models, all roads, on weekdays (Boets, 2023). It is shown that hand-held mobile phone use while driving ranges from 2% in Finland to 10% in Cyprus.
+
+*Figure 8. Percentage of drivers not holding a mobile phone while driving (Source: Boets, 2023)*
+
+![](_page_22_Figure_2.jpeg)
+
+According to the ESRA study, between 10-50% of European drivers self-report that they have talked on a hand-held mobile phone while driving at least a few days in a month, between 33-66% have talked on a hands-free phone and between 15-37% have texted while driving (see Figure 9).
+
+*Figure 9. Self-declared percentage of drivers who were distracted while driving at least a few days a month (Pires et al., 2019).*
+
+![](_page_22_Figure_5.jpeg)
+
+It is generally estimated that distraction plays a role in 5 - 25% of crashes in Europe. (Hurts et al., 2011 in: European Commission, 2018). This is mainly based on older studies and in-depth crash investigations in which extreme forms of distraction are documented. This is likely to be an under-representation. The in-depth study of Thomas et al. (2014) found that distraction was a contributory factor in 8.3% of fatal crashes and inattention was a contributory factor in 5% of fatal crashes.
+
+#### <span id="page-23-0"></span>**3.3.3 Safety impacts**
+
+The vast majority of studies agree that driving performance is impaired by distraction, with the main effects being the increased reaction time, the increased time with eyes-off-the-road and the lateral control variability. However, few studies have been able to quantify the effects of distraction on actual road safety outcomes.
+
+The European Road Safety Decision Support System (https://www.roadsafety-dss.eu/#/) includes in-depth reviews and meta-analyses of several sources of distraction. Their findings related specifically to the effects of distraction on crash occurrence or crash risk can be summarized as follows<sup>4</sup>:
+
+- Hand-held phone use results in significantly higher crash risk (Ziakopoulos et al, 2018). Most of the results available in the literature come from naturalistic driving studies in the US. Key figures of interest are: a 3.6 increase in accident risk (Dingus et al, 2016) and a 2.7 increase of accident risk in Norway (Elvik, 2011). Dialling and texting are associated with higher risk than simply talking.
+- Texting in particular is associated with a 6.1 increase in crash risk (Dingus et al., 2016)
+- Hands-free phone use results in potentially higher crash risk, although some studies suggest none or opposite effects (Ziakopoulos et al., 2018b). Key figures of interest are: a 1.66 increase<sup>5</sup> of accident risk in Norway (Backer Grøndahl & Sagberg; 2011).
+- Interaction with vehicle systems has been found to increased (x2.5) crash risk (Dingus et al., 2016) – however these tasks are found to be self-regulated to some extent (Perez et al., 2015). The types of activities may vary from button to touch screen or voice controls, for navigation or entertainment purposes. Voice controls and head-up displays are less impairing than manual modes.
+- Conversation with passengers has not been associated with increased crash risk (EC,2021). It is likely that this type of cognitive competing task can be self-regulated by drivers and passengers.
+- Outside factors were found to increase crash or near-crash risk by 3.9 (Klauer et al., 2014); Advertising signs in particular were found to significantly increase the occurrence of crashes in Greece (Yannis et al., 2012).
+- Inattention / daydreaming, listening to music: existing research results are inconclusive. A vote-count analysis on inattention
+
+<sup>4</sup> The reported numbers correspond to odds ratios (unless mentioned otherwise).
+
+<sup>5</sup> This number expresses a relative risk.
+
+indicated that crash risk and injury severity may vary – possibly compensatory behaviours or the cognitive nature of this distraction source lead to non-identifiable safety consequences in some cases.
+
+#### <span id="page-24-0"></span>**3.3.4 Interventions**
+
+- Education, awareness raising campaigns and training programmes in the general population are a common way of targeting distracted driving, however their effects are limited due to the large penetration of smartphones and entertainment / navigation systems in the vehicles, especially among young people. Organisational safety culture by companies or employers in general can have more positive effects among professionals / employees.
+- Vehicle technologies, namely Advanced Driver Assistance Systems (ADAS) can prevent the consequences of distraction through collision warnings, Autonomous Emergency Braking or Lane Keeping Assistance. Recently a lot of focus is placed in distraction detection systems, which use eye-tracking detect offroad gaze behaviour, but these systems are still under development.
+- Infrastructure design can play an important role in preventing distraction from roadside advertising, through regulations and avoidance of digital or highly luminous billboards. Moreover, it can contribute to the mitigation of the consequences of distracted driving, through longitudinal rumble strips that alert drivers in case of lane departure.
+
+## <span id="page-24-1"></span>**3.4 Use of protective equipment<sup>6</sup>**
+
+#### <span id="page-24-2"></span>**3.4.1 Mechanism**
+
+Seat belt and helmet wearing are generally not associated with increased crash risk, but it are significantly associated with the severity of road crashes (Anderson, 2017).
+
+#### *3.4.1.1 Seat belts*
+
+The main function of a seatbelt is to reduce the risk of injury of an occupant of a vehicle in a crash; it restrains the occupant to the vehicle, thereby enabling the occupant to "ride down" (less violently) as they are coupled to the vehicle's deceleration through the restraint system. An unrestrained occupant continues to move at the vehicle's pre-impact speed while the vehicle begins to decelerate as a result of the crash.
+
+<sup>6</sup> Child restraints are not included in this report for the economy of space. The reader is referred to the ERSO thematic report on 'Seat belts and child restraints'
+
+This uncontrolled motion will result in an uncontrolled impact with the vehicle interior, or in the worst case, an ejection from the vehicle, fully or partially (EC, 2022).
+
+#### *3.4.1.2 Helmets*
+
+Helmets aim to reduce rider injuries in the event of a motorcycle or bicycle crash, by providing additional impact and abrasion protection to the head. Despite their overall similar appearance, there is a wide range of helmets available, tailored for different users, purposes or cost – the main two categories for powered-two-wheeler (PTW) helmets are openface and full-face designs, while cycle helmets are typically open-face. The head protection concept of dissipating the energy from a blow to the head area of a motorcyclist is the same in all designs (Reed, 2018).
+
+### <span id="page-25-0"></span>**3.4.2 Prevalence**
+
+Seat belt wearing rates vary considerable among European countries. The Baseline project estimated that the KPI of the share of drivers that correctly use their seatbelts on weekdays ranges between 70% and 92%, while for Heavy Goods Vehicle drivers it ranges between 34% and 92% (Van den Broek et al., 2022).
+
+The WHO report on Road Safety (2018) includes the seat belt wearing rates shown in Table 5. It is noted that, while front seat wearing is >95% in most countries, there are several countries with lower rates. Regarding rear-seat wearing, the figures are notably lower and widely dispersed, ranging between 15-93%. Helmet wearing rates for PTW riders are generally very high, with the exception of Greece (75%) and missing data for a few countries. This data should be considered with some caution, as in most cases they are based on roadside surveys with different methodologies (sampling, measurement etc.).
+
+*Table 5. Use of protective equipment in European countries, 2016 (WHO, 2018)*
+
+| Country | % of drivers<br>wearing seat<br>belt (front) | % of passengers<br>wearing seat belt (rear) | % of PTW riders<br>wearing helmet<br>(driver) |
+|---------|----------------------------------------------|---------------------------------------------|-----------------------------------------------|
+| Austria | 95.00                                        | 93.00                                       | 100.00                                        |
+| Belgium | 92.20                                        | 85.50                                       | 99.00                                         |
+| Czechia | 98.00                                        | 72.00                                       |                                               |
+| Denmark | 96.00                                        | 91.00                                       | 98.00                                         |
+| Finland | 95.00                                        | 85.00                                       | 98.30                                         |
+| France  | 98.00                                        | 88.00                                       | 98.00                                         |
+| Germany | 98.00                                        | 99.00                                       | 99.00                                         |
+| Greece  | 74.00                                        | 23.00                                       | 75.00                                         |
+
+| Country     | % of drivers<br>wearing seat<br>belt (front) | % of passengers<br>wearing seat belt (rear) | % of PTW riders<br>wearing helmet<br>(driver) |
+|-------------|----------------------------------------------|---------------------------------------------|-----------------------------------------------|
+| Hungary     | 82.80                                        | 38.50                                       | 92.30                                         |
+| Ireland     | 94.00                                        | 74.00                                       | 99.90                                         |
+| Italy       | 61.90                                        | 15.40                                       | 98.00                                         |
+| Lithuania   | 97.00                                        | 30.00                                       |                                               |
+| Netherlands | 96.60                                        | 82.00                                       | 99.90                                         |
+| Poland      | 96.00                                        | 76.00                                       | 99.00                                         |
+| Portugal    | 95.70                                        | 77.20                                       | 97.60                                         |
+| Spain       | 90.50                                        | 80.60                                       | 99.00                                         |
+| Sweden      | 96.00                                        | 90.00                                       | 97.00                                         |
+
+In the ESRA survey (20 European countries in 2018) 83% of European respondents said they had always worn the seat belt as a driver in the previous 30 days (ranging from <70% in Greece, to 90% in Ireland). In the same study, only 63% of the European respondents say that they had always used the seat belt as a rear-seat passenger in the previous 30 days (Nakamura et al., 2020).
+
+While the percentage of non-use of seat belts is relatively small in most European countries, data from the CARE database indicate that there is still a 13.3% of car occupant fatalities where no seat belt had been worn, whereas for more than 50% of the fatalities it is not known whether a seat belt had been worn. The ERSO estimates that the share of car occupant fatalities where no seat belt had been worn is estimated between 25-50% (ERS0, 2022). A study from the United Kingdom shows that more than a quarter of car occupants killed in 2017 were not wearing seat belts (ETSC, 2019), and a Norwegian study (Ringen, 2019 in Elvik, 2020) showed that between 2005 and 2010 45% of car occupants that were killed did not wear a seat belt.
+
+### <span id="page-26-0"></span>**3.4.3 Safety impacts**
+
+#### *3.4.3.1 Seat belts*
+
+Høye (2016) estimated that the risk of having a fatal crash in Norway is more than 8 times higher for unbelted drivers compared with drivers wearing a seat belt. This difference in fatal crash risk is further explained by the fact that not using seat belts correlates with other risk factors such as drink-driving, speeding, night-time driving, and previous traffic offences.
+
+Moreover, the use of seat belt reduces the risk of being killed or severely injured by 60% among front seat occupants and by 44% among rear seat occupants. Seat belt usage among rear seat occupants significantly affects the safety of belted front seat occupants; unbelted rear seat occupants can double the fatality and injury rate for belted front seat occupants (Anderson, 2017).
+
+ETSC (2017) estimates that 900 deaths per year could be avoided in the European Union if 99% of car occupants wore seat belts.
+
+#### *3.4.3.2 Helmets*
+
+The safety effects of helmet are typically estimated in terms of fatality or injury risk, as well as in terms of head impact criteria (HIC) values in biomechanical or simulation studies (Reed, 2018).
+
+The magnitude of fatality risk between helmeted and un-helmeted PTW users varies between studies but overall helmets are found to reduce the risk of death among PTW users. The results for facial injuries sustained in a PTW crash are also positive with the exception among smaller PTW users, where the prevalence of open face helmet use is suspected to be greater.
+
+More specifically, a major meta-analysis (Hoye, 2016) estimated a significant reduction of fatal injuries with helmet wearing, ranging from 24% in light PTWs to 64% in small PTWs. Significant impacts were also estimated for head, neck, brain and face injuries.
+
+Two recent meta-analyses (see Reed, 2018) estimated a significant reduction of 44-50% in head injuries by helmet wearing on cyclists. Deck et al. (2012) compared the performance of 32 ISO-compliant helmet types in terms of their ability to prevent brain injury from frontal, rear and lateral impacts.
+
+#### <span id="page-27-0"></span>**3.4.4 Interventions**
+
+- Vehicle technology has provided important systems that can prevent non-use of seat belts. Seat belt reminders are alarm systems that detect whether a seat belt is not fastened while driving and give visual and audible warnings; they have been found to be highly effective on seat belt wearing rates. Seat belt ignition interlocks have also been tested as a very effective measure, however their acceptance among car occupants is very low and they are not deployed as of today.
+- Education campaigns and enforcement are useful tools to increase the use of protective systems.
+- Regarding helmet wearing in particular, universal helmet laws and quality standards are equally important.
+
+# <span id="page-28-0"></span>**4. Further reading**
+
+European Commission (2021) Road safety thematic report – Speeding. Euro-pean Road Safety Observatory. Brussels, European Commission, Directorate General for Transport.
+
+European Commission (2021a) Road safety thematic report – Alcohol, drugs and medicine. European Road Safety Observatory. Brussels, European Commission, Directorate General for Transport
+
+European Commission (2021b) Road safety thematic report – Driver distraction. European Road Safety Observatory. Brussels, European Commission, Directorate General for Transport
+
+European Commission (2021c) Road safety thematic report –Seat belt and child restrains systems. European Road Safety Observatory. Brussels, European Commission, Directorate General for Transport
+
+Hauer E. (2020), Crash causation and prevention, Accident Analysis & Prevention, Volume 143, 105528.
+
+Thomas P, Morris A, Talbot R, Fagerlind H. Identifying the causes of road crashes in Europe. Ann Adv Automot Med. 2013;57:13-22. PMID: 24406942; PMCID: PMC3861814.
+
+# <span id="page-28-1"></span>**5. References**
+
+Achermann Stürmer, Y., Meesmann, U. & Berbatovci, H. (2021). Driving under the influence of alcohol and drugs. ESRA2 Thematic report Nr. 5. ESRA project (E-Survey of Road users' Attitudes). Bern, Switzerland: Swiss Council for Accident Prevention.
+
+Adminaité-Fodor, D., & Jost, G. (2019). Reducing speeding in Europe. ETSC PIN Flash Report 36. Brussels: European Transport Safety Council. Retrieved from <https://etsc.eu/wp-content/uploads/PIN-flash-report-36-Final.pdf>
+
+Aigner-Breuss, E., Braun, E., Eichhorn, A., Kaiser, S. (2017), Speed of Traffic, European Road Safety Decision Support System, developed by the H2020 project SafetyCube. Retrieved from www.roadsafety-dss.eu .
+
+Andersson, M. (2017), Seatbelts, European Road Safety Decision Support System, developed by the H2020 project SafetyCube. Retrieved from [www.roadsafety](http://www.roadsafety-dss.eu/)[dss.eu.](http://www.roadsafety-dss.eu/)
+
+Beirness , D.J., Gu, K.W. , Lowe, N.J., Woodall, K.L., & Desrosiers, N.A., Cahill, B., Porath, A.J. & Peaire, A. (2021) Cannabis, alcohol and other drug findings in fatally injured drivers in Ontario. Traffic Injury Prevention, 22 (1), 1-6. <https://doi.org/10.1080/15389588.2020.1847281>
+
+![](_page_28_Picture_14.jpeg)
+
+- Blomberg, R.D., Peck, R.C., Moskowitz, H., Burns, M., et al. (2005). Crash risk of alcohol involved driving: A case-control study. Contract Number DTNH22-94-C-05001 Dunlap and Associates, Inc., Stamford, CT.
+- Boele-Vos M.J., Van Duijvenvoorde K., Doumen M.J.A., Duivenvoorden C.W.A.E., Louwerse W.J.R., Davidse R.J. (2017) Crashes involving cyclists aged 50 and over in the Netherlands: An in-depth study. Accident Analysis & Prevention Volume 105, August 2017, Pages 4-10
+- CEREMA (2021). Les facteurs d'accidents mortels en 2015 ; Exploitation de la base FLAM. Rapport d'etude Cerema, Lyon, France.
+- Compton, R. (2017). Marijuana-Impaired Driving A Report to Congress. (DOT HS 812 440). Washington, DC, National Highway Traffic Safety Administration.
+- Daniels, S., Focant, N (2017), Dynamic Speed Limits, European Road Safety Decision Support System, developed by the H2020 project SafetyCube. Retrieved from www.roadsafety-dss.eu on November 2023.
+- Deck, C., Bourdet, N., Meyer, F., & Willinger, R. (2019). Protection performance of bicycle helmets. Journal of Safety Research, 71, 67–77. https://doi.org/10.1016/j.jsr.2019.09.003 (IF : 3.487)
+- EC (2018). Alcohol. Brussels, Directorate General for Transport. [https://ec.europa.eu/transport/road\\_safety/sites/default/files/pdf/ersosynthesis20](https://ec.europa.eu/transport/road_safety/sites/default/files/pdf/ersosynthesis2018alcohol.pdf) [18alcohol.pdf](https://ec.europa.eu/transport/road_safety/sites/default/files/pdf/ersosynthesis2018alcohol.pdf)
+- European Commission, Directorate-General for Mobility and Transport, Modijefsky, M., Janse, R., Spit, W. et al., Prevention of driving under the influence of alcohol and drugs – Final report, Publications Office of the European Union, 2022
+- Elvik, R. (2020). *Control of use of personal protective equipment.* The Handbook of Road Safety Measures, Norwegian (online) version. Retrieved from [https://www.tshandbok.no/del-2/8-kontroll-og-sanksjoner/doc734/.](https://www.tshandbok.no/del-2/8-kontroll-og-sanksjoner/doc734/)
+- Elvik, R., (2013). A Re-Parameterisation of the Power Model of the Relationship between the Speed of Traffic and the Number of Accidents and Accident Victims. Accident Analysis and Prevention, 50, 854–860
+- ETSC (2017). Position paper: Revision of the General Safety Regulation 2009/661 Brussels, Belgium.
+- European Commission (2021) Road safety thematic report Speeding. Euro-pean Road Safety Observatory. Brussels, European Commission, Directorate General for Transport.
+- European Commission (2021) Road safety thematic report Alcohol, drugs and medicine. European Road Safety Observatory. Brussels, European Commission, Directorate General for Transport
+- European Road Safety Decision Support System (https://www.roadsafetydss.eu/#/risk-factor-search) [Accessed October 2023]
+
+![](_page_29_Picture_15.jpeg)
+
+- Garrisson, H., Scholey, A., Ogden, E., & Benson, S. (2021). The effects of alcohol intoxication on cognitive functions critical for driving: A systematic review. Accident Analysis & Prevention, 154, [https://doi.org/10.1016/j.aap.2021.106052.](https://doi.org/10.1016/j.aap.2021.106052)
+- Hauer E. (2020), Crash causation and prevention, Accident Analysis & Prevention, Volume 143, 105528.
+- Holocher, S., & Holte, H. (2019). Speeding. ESRA2 Thematic report Nr. 2. ESRA project (E-Survey of Road users' Attitudes). Bergisch Gladbach, Germany, Germany: BASt – Bundesanstalt für Straßenwesen. [https://www.esranet.eu/storage/minisites/esra2018thematicreportno2speeding.pd](https://www.esranet.eu/storage/minisites/esra2018thematicreportno2speeding.pdf) [f](https://www.esranet.eu/storage/minisites/esra2018thematicreportno2speeding.pdf)
+- Houwing, S., Hagenzieker, M., Mathijssen, R., Bernhoft, I. M., Hels, T., Janstrup, K. Van der Linden, T., Legrand, S.-A. & Verstraete, A. (2011). Prevalence of alcohol and other psychoactive substances in drivers in general traffic Part II: Country reports. DRUID (Driving under the Influence of Drugs, Alcohol and Medicines). 6th Framework programme. Deliverable 2.2.3 Part II.
+- Høye, A. (2016). PTW Helmets. The Handbook of Road Safety Measures, Norwegian (online) version. http://tsh.toi.no/doc685.htm#anchor\_22474-90
+- Høye, A. (2016). How would increasing seat belt use affect the number of killed or seriously injured light vehicle occupants?. *Accident Analysis & Prevention, 88*, 175-186.
+- ITF (2023). Road Safety Country Profiles. OECD International Transport Forum, Paris :<https://www.itf-oecd.org/road-safety-country-profiles> [Accessed October 2023]
+- Kinnear, D. N., & Stevens, A. (2018). The battle for attention Driver distraction a review of recent research and knowledge. UK: TRL.
+- Nakamura, H., Alhajyaseen, W., Kako, Y., Kakinuma, T. (2020): Seat belt and child restraint systems. ESRA2 Thematic report No. 7. ESRA project (E-Survey of Road users' Attitudes). International Association of Traffic and Safety Sciences (IATSS), 2-6-20 Yaesu, Chuo-ku, Tokyo 104-0028, Japan
+- Nieuwkamp, R., Martensen, H., Meesmann, U (2017), Alcohol interlock, European Road Safety Decision Support System, developed by the H2020 project SafetyCube. Retrieved from www.roadsafety-dss.eu
+- Pires, C., Areal, A., & Trigoso, J. (2019). Distraction (mobile phone use). ESRA2 Thematic report Nr. 3. ESRA project (E-Survey of Road users' Attitudes) (Issue 3). Lisbon, Portugal: Portuguese Road Safety Association
+- Poda M., Mineiro F. (2022). PROGRESS IN REDUCING DRINK-DRIVING AND OTHER ALCOHOL-RELATED ROAD DEATHS IN EUROPE. SMART Project, ETSC, Brussels.
+- Reason J. (2000) Human error: models and management. BMJ 18;320(7237):768- 70.
+- Reed, S. (2018), PTW Helmets, European Road Safety Decision Support System, developed by the H2020 project SafetyCube. Retrieved from www.roadsafetydss.eu
+
+![](_page_30_Picture_15.jpeg)
+
+- Schindler, R.; Jänsch, M.; Bálint, A.; Johannsen, H. Exploring European Heavy Goods Vehicle Crashes Using a Three-Level Analysis of Crash Data. Int. J. Environ. Res. Public Health 2022, 19, 663
+- SWOV (2020). Drugs and Medicines, Scientific Factsheet, the Hague, March 2020. <https://www.swov.nl/en/factsfigures>
+- SWOV (2020). Distraction in traffic. SWOV fact sheet, July 2020. SWOV, The Hague. <https://swov.nl/en/fact-sheet/distraction-traffic>
+- Thomas P, Morris A, Talbot R, Fagerlind H. Identifying the causes of road crashes in Europe. Ann Adv Automot Med. 2013;57:13-22. PMID: 24406942; PMCID: PMC3861814.
+- Tingvall, C., Haworth, N., 1999. 'Vision zero: an ethical approach to safety and mobility. Road safety and traffic enforcement, Institute of Transportation Engineers international conference, 6th, 1999, Melbourne, Victoria, Victoria Police, Melbourne, Vic, 7 pp.
+- Van den Broek B., Aarts, L. & Silverans, P. (2023). Baseline report on the KPI Speeding. Baseline project, Brussels: Vias institute.
+- Wegman, F., & Aarts, L. T. (2005). Door met Duurzaam Veilig Nationale Verkeersveiligheidsverkenning voor de Jaren 2005-2020. Leidschendam: Stichting Wetenschappelijk Onderzoek Verkeersveiligheid
+- WHO. (2018). Global Status Report on Road Safety 2018. Geneva: World Health Organization. Retrieved from [https://www.who.int/violence\\_injury\\_prevention/road\\_safety\\_status/2018/en/](https://www.who.int/violence_injury_prevention/road_safety_status/2018/en/)
+- WHO Fact sheet on Road Traffic Injuries [\(https://www.who.int/news-room/fact](https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries)[sheets/detail/road-traffic-injuries\)](https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries) [Accessed October 2023]
+- Yannis G., Papadimitriou E., Papantoniou P., Voulgari C. (2012). A statistical analysis of the impact of advertising signs on road safety. International Journal of Injury Control and Safety Promotion 20(2), 111-120.
+- Yannis G., Papadimitriou E., Road Safety, International Encyclopedia of Transportation 1st Edition, Editor-in-Chief: Roger Vickerman, May 2021
+- Ziakopoulos, A., Theofilatos, A., Papadimitriou, E., Yannis, G. (2018), Distraction Cell Phones - Hands Free, European Road Safety Decision Support System, developed by the H2020 project SafetyCube. Retrieved from [www.roadsafetydss.eu.](http://www.roadsafetydss.eu/)
+- Ziakopoulos, A., Theofilatos, A., Papadimitriou, E., Yannis, G. (2017), Cell Phone Use – Texting, European Road Safety Decision Support System, developed by the H2020 project SafetyCube. Retrieved from [www.roadsafety-dss.eu](http://www.roadsafety-dss.eu/)
+
+![](_page_31_Picture_14.jpeg)
+
+![](_page_33_Picture_0.jpeg)