category: literaturenote citekey: gordonintelligenttransportationsystems2016 title: Intelligent Transportation Systems authors: "Gordon, Robert" year: 2016 date: 2016-00-00 2016 doi: 10.1007/978-3-319-14768-0 url: "https://doi.org/10.1007/978-3-319-14768-0" zotero_key: WV2PN839 zotero_storage: FUQ2CER8 collections: transpordi_planeerimine folder: 001_artiklid firstAuthor: "Gordon, Robert"

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Robert Gordon

Intelligent Transportation Systems

Functional Design for Effective Traffic Management

Second Edition

Intelligent Transportation Systems

Robert Gordon

Intelligent Transportation Systems

Functional Design for Effective Traffi c Management

Second Edition

Robert Gordon Plainview , NY , USA

Additional material to this book can be downloaded from http://www.springer.com/us/ book/9783319147673

ISBN 978-3-319-14767-3 ISBN 978-3-319-14768-0 (eBook) DOI 10.1007/978-3-319-14768-0

Library of Congress Control Number: 2015936046

Springer Cham Heidelberg New York Dordrecht London

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The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made.

Printed on acid-free paper

Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www.springer.com)

Pref ace

Functional design, as described in this book, is the selection of ITS management strategies and the fi eld equipment deployments required to implement them. In most cases, functional design stops short of the selection of detailed technologies. Starting with the development of detailed objectives, functional design relates management strategies to project objectives, identifi es alternative strategies for further consideration, and evaluates these strategies. It then determines whether one or more strategies can cost effectively satisfy the objectives and recommends the most appropriate alternative.

Although considerable effort has been expended by the Federal Highway Administration and others to develop high-level systems engineering processes, in practice, ITS designers have often used a "bottom up" approach. Designers often select devices and device locations without a strong connection to project objectives or to methodologies that assess the feasibility of the project and the proposed design. This book provides guidance for adapting these systems engineering processes to freeway ITS project functional requirements. It provides the basis for selecting the types of ITS components and the management strategies employed. A number of handbooks and other resources are available to provide guidance for the detailed selection of fi eld equipment and operations to manage the equipment. This book assumes that the reader is familiar with the functions of ITS devices such as dynamic message signs, highway advisory radio, traffi c detectors, and CCTV applications.

This edition is essentially an updated version of Intelligent Freeway Transportation Systems: Functional Design . The text discusses the increased emphasis on coordination among transportation management centers and the more intensive management techniques provided by emerging active traffi c management strategies. ITS evaluation techniques are described in more detail, and examples of the communication of the results of these evaluations to decision makers and to the public are described. Several types of transportation corridors are described, and examples of corridor management strategies are included. Some material was updated and obsolete material was removed.

The book emphasizes the use of fundamental transportation planning and traffi c engineering principles to develop functional designs. It is assumed that the reader is vi Preface

somewhat familiar with this area. The book largely refl ects the author's experience in adapting these principles to ITS design. For example, the book provides models to suggest appropriate locations for such ITS devices as CCTV cameras and dynamic message signs and describes methodologies for estimating the benefi ts of proposed functional designs. The models enable the designer to estimate the performance differences among alternatives and estimate benefi ts for functional design purposes. Approximations are introduced to expedite the use of these models by practitioners. While the author has found these models to be useful, readers are encouraged to modify and enhance them to better suit their needs. The web site http://www. springer.com/us/book/9783319147673 provides worksheets that facilitate the use of some of the models. The worksheets are provided in an unprotected format to enable users to modify them as required.

I give particular thanks to my wife, Norma, who provided support and encouragement to complete the effort.

Plainview, NY, USA Robert Gordon

1			Introduction	1
	1.1		Purpose of Book	1
	1.2		Development of ITS Design Practices	2
	1.3		Summary of Contents and Organization	3
			References	6
2			Cost Effective Design Processes	7
	2.1		Systems Engineering	7
		2.1.1	Systems Engineering Requirements for Federal
			Aid Projects	7
		2.1.2	Systems Engineering as a Life-Cycle Process	8
		2.1.3	ITS Project Development	12
	2.2		Goals, Objectives and Requirements	12
	2.3		Evaluation Methodologies	18
			References	18
3			Functional ITS Design Issues	19
	3.1		Relationship of ITS Design to General Transportation
			Planning Principles	19
		3.1.1	General Traffi c Flow Relationships	19
		3.1.2	Shock Waves	21
		3.1.3	Classifi cation of Congestion	21
		3.1.4	Diversion for Non-Recurrent Congestion	22
		3.1.5	Recurrent Congestion	26
	3.2		Performance and Benefi t Assessment	27
		3.2.1	Performance Measures to Facilitate System Design	28
		3.2.2	Performance Measures and ITS Planning	31
	3.3		Alternatives for Functional Design	33
		3.3.1	Design Constraints	34
		3.3.2	Relationship of ITS Management Concepts
			to Objectives	35
			References	39

viii Contents

4			Non-Recurrent Congestion: Improvement of Time
			to Clear Incidents	41
	4.1		Defi nition of an Incident for ITS Design Purposes	41
		4.1.1	Effect of Incidents on Capacity	42
		4.1.2	Secondary Accidents	42
		4.1.3	Work Zone Accidents	43
	4.2		Models of the Effects of Freeway Incidents	43
		4.2.1	Frequency and Severity of Incidents	46
		4.2.2	Data Collection for Development of Incident Model	47
	4.3		Relationship of Reduction in Delay to Reduction
			in Incident Clearance Time	49
	4.4		Interaction of Capacity Restrictions and Traffi c Conditions	51
		4.4.1	Cohort Model	51
		4.4.2	Time Saved Per Incident	54
		4.4.3	Classifi cation of Incidents	55
		4.4.4	Incident Management Approaches	56
		4.4.5	Distribution of Traffi c for Incident Conditions	56
		4.4.6	Geographic Levels of Diversion	60
	4.5		Functional Requirements for Improving Incident Response
			and Relationship of Improvement Techniques	68
		4.5.1	Improving Incident Detection and Verifi cation	69
		4.5.2	Improving Incident Response, Clearance
			and Recovery Through ITS	79
	4.6		Measuring Incident Management Effectiveness	84
		4.6.1	Degree of Attainment for Recommended Management
			Functions, Operations and Technologies	84
		4.6.2	General Measures	85
		4.6.3	Model for Evaluating Incident Management
			Effectiveness	86
			References	89
5			Non-recurrent Congestion: Incident Information to Motorists	91
	5.1		Motorist Diversion	92
		5.1.1	Motorist Messaging Techniques	92
		5.1.2	Operational Diversion Policies and Strategies	95
		5.1.3	Strategic Network Management	97
		5.1.4	Diversion Strategies	100
		5.1.5	Reduction in Freeway Delay Resulting From Diversion	103
		5.1.6	Effect of Diversion on Arterial Traffi c	105
		5.1.7	Reduction in Corridor Delay Resulting from Diversion
			for Incidents	107
	5.2		Design Considerations for DMS Locations	108
		5.2.1	Basic Considerations for DMS Functional Placement	108
		5.2.2	Simple Models to Assist in DMS Functional Placement	108

ix Contents

	5.3	Quality of Motorist Information	114
	5.4	ITS and Technology Applications in Emergency Evacuations	114
		5.4.1 Introduction	114
		5.4.2 ITS and Technology Applications	115
		References	117
6		Recurrent Congestion: Information to Motorists	119
	6.1	Nature of Recurrent Congestion	119
	6.2	Motorist Information During Recurrent Congestion	119
	6.3	Variations During Periods of Recurrent Congestion	120
	6.4	Diversion During Recurrent Congestion	122
		Reference	123
7		Ramp Metering	125
	7.1	Introduction	125
	7.2	Background	126
		7.2.1 Early Metering Projects	126
		7.2.2 Ramp Meter Installation Requirements	127
	7.3	Flow Characteristics and Freeway Capacity	128
		7.3.1 Flow Characteristics for Near-Capacity Conditions	128
		7.3.2 Effective Capacity Improvement Through
		Ramp Metering	132
		7.3.3 Freeway Service Improvement Through Ramp Metering	133
	7.4	Ramp Metering Strategies	136
		7.4.1 Overview of Metering Strategies	136
		7.4.2 Pretimed Restrictive Ramp Metering	138
		7.4.3 Local Traffi c Responsive Restrictive Ramp Metering	139
		7.4.4 System-Wide Traffi c Responsive Restrictive
		Ramp Metering	145
		7.4.5 Design Issues	145
	7.5	Ramp Metering and the Motorist	151
		7.5.1 Motorist Benefi ts and Disbenefi ts Resulting
		from Ramp Metering	151
		7.5.2 Public Acceptance of Ramp Metering	152
	7.6	Benefi ts Model for Ramp Metering	153
		References	154
8		Transportation Management Centers	157
	8.1	Transportation Management Center Functions	157
		8.1.1 Support of Emergency Management Services	157
		8.1.2 Provision of Information to Motorists	158
		8.1.3 Operation of Ramp Meters	158
		8.1.4 Operation of Service Patrols	159
		8.1.5 Coordination of Traffi c Signal Operation
		with Freeway and Corridor Requirements	160
		8.1.6 Provision of Weather Information Related
		to Roadway Conditions	160

x Contents

	8.2	Example of Transportation Management Center
		in Major Urban Location	161
	8.3	Interconnection and Coordination of TMCs	163
		8.3.1 Regional Coordination	164
		8.3.2 Statewide Coordination	168
		References	175
9		Evaluation of System Design and Operation	177
	9.1	Evaluation of Design Alternatives and Project Feasibility	177
		9.1.1 Benefi t and Cost Analysis	177
		9.1.2 Alternatives Evaluation and Project Feasibility	180
	9.2	Project Evaluation	181
		9.2.1 Role and Function of Evaluation	181
		9.2.2 Functions and Measures to Consider for Evaluation	183
		9.2.3 Data Structures for Evaluation	184
		9.2.4 Description of Measures	187
		References	191
10		Active Traffic Management (ATM)	193
	10.1	Defi nition and Concept	193
	10.2	Speed Harmonization	195
	10.3	Temporary Shoulder Use	196
	10.4	Queue Warning	199
	10.5	Dynamic Merge Control	201
	10.6	Dynamic Lane Markings	202
	10.7	Implementation Considerations	202
	10.8	Planning for Active Traffi c Management	204
		References	204
11		Corridor Management	207
	11.1	Coordinated Freeway and Arterial Operation	207
		11.1.1 Management Strategies	208
		11.1.2 Operational Plans and Procedures
		for Coordinating Freeways and Arterials	208
	11.2	Integrated Corridor Management	210
	11.3	Special Corridors	214
		11.3.1 Types of Special Corridors	214
		11.3.2 Example of Special Corridor	214
		References	219
12		Website Support	221
	12.1	Introduction	221
	12.2	System Delay per Incident	221
	12.3	Relative Effectiveness of CCTV Coverage	222
	12.4	Incident Management Effectiveness Potential	222
	12.5	Delay Reduced on Freeway Due to Queue Reduction
		Resulting from Diversion	222

xi Contents

	12.6	Probability that the Motorist Encounters DMS Prior
		to Incident (P34)	222
	12.7	Queue Storage Requirement for Ramp Meter	223
		Reference	223
13		ITS and the Connected Vehicle	225
	13.1	The Connected Vehicle	225
	13.2	Connected Vehicle Data Links	226
	13.3	Cellular/Internet Based Services	227
	13.4	In-Vehicle Displays	229
	13.5	The Traffi c Management Dilemma	230
	13.6	USDOT Connected Vehicle Program	230
		References	235

		Appendix A: Travel Time, Delay and Travel Time
		Reliability Measures	237
		Appendix B: Relative Effectiveness of CCTV Coverage	249
		Appendix C: Example of Benefits for Incident Management	253
		Appendix D: Message Display Software for Southern State Parkway	257
		Appendix E: Washington State Fuzzy Logic Ramp Metering Algorithm	261
		Appendix F: Benefits Model for Motorist Assistance Patrols	265
		Appendix G: National Incident Management System and Incident Classification	267
		Appendix H: Special Corridor Traffic Decision Support and Demand Management System Concept	271
		Index	277

List of Symbols, Abbre viations, and Acronyms

The following table defi nes the symbols, abbreviation, and acronyms that are most commonly used in the book. Parameters and variables used in the equations are defi ned in the discussion of the equations. Defi nitions for the appendices are provided in the appendix.

Acronym	Defi nition
AADT	Annual average daily traffi c
ACCR	Accident rate
ACR	Accident rate for section
ADD	Average vehicle delay (diversion)
ADM	Active demand management
ADMS	Archived data monitoring system
ADMS	Arterial dynamic message sign
ADND	Average vehicle delay (no diversion)
ADOT	Arizona Department of Transportation
ADUS	Archived Data Use Service
AID	Automatic incident detection
ALINEA	A local ramp metering algorithm
ANPRM	Advanced notice of proposed rulemaking
APM	Active parking management
AR	Accidents reduced
ARI	Accident rate in interchange area
ARNI	Accident rate in non-interchange area
ARTEMIS	Advanced Regional Traffi c Interactive Management and Information System
ATDM	Active traffi c and demand management
ATM	Active traffi c management
ATSMR	Average time per mile per vehicle saved by metering

Acronym	Defi nition
B1	Timely detection probability for a range of scenarios for different detector spacing
B J	Total mainline traffi c in section J
BSM	Basic safety message
C	Capacity
C2C	Center-to-center
CAD	Computer aided dispatch
CALTRANS	California Department of Transportation
CCTV	Closed circuit television
CD	Capacity defi cit
CDS	Total corridor delay reduction
CFA	Coordinated freeways and arterials
CFR	Code of Federal Regulations
CMS	Changeable message sign (also known as dynamic message sign)
CO	Carbon monoxide
CONOPS	Concept of operations
crf	Capital recovery factor
CS	Capacity along arterial with signal
CVF	Commercial vehicle fraction
CVRIA	Connected Vehicle Reference Implementation Architecture
DAR	Additional delay incurred by pre-diversion traffi c on diversion route
DC	Delay from TC to T
DD	Delay prior to TC
DF	Public diversion fraction for no major arterial congestion
D I	Delay from the start of the incident up to incident clearance
DIF	Delay for non-diverted freeway traffi c
DOT	Department of Transportation
DMS	Dynamic message sign
D Q	Delay from incident clearance to queue dissipation
DQC	Delay after incident clearance
DSRC	Direct short range communication
DSS	Decision support system
D T	Total delay
DTA	Dynamic traffi c assignment
E511	Emergency telephone response service provided by PSAP
ER	Emission rate
FE	Excess fuel consumption
FHWA	Federal Highway Administration
FRM	Fraction of roadway segment infl uenced by metering
FRR	Fraction of ramps in roadway segment that contain ramp meters
G	Gini coeffi cient
GE	Excess fuel consumption rate

Acronym	Defi nition
GPS	Global positioning system
GS	Green split along arterial
H	Potential ability for ITS to provide incident management support
HAR	Highway advisory radio
HC	Hydrocarbons
i	Interest rate
ICM	Integrated corridor management
ICS	Incident command system
IDI	Duration of incidents and accidents in interchange areas
IDN	Duration of incidents and accidents in non-interchange areas
IDV	Time saved by non-diverting vehicles

IEEE	Institute of Electrical and Electronics Engineers
ILD	Inductive loop detector
INCOSE	International Council on Systems Engineering
INFORM	Information for motorists
ITS	Intelligent Transportation Systems
IVI	In-vehicle infotainment system
k	Density or concentration
K	Parameter
KD	Constant for utility calculation
KS	Satisfaction rating
L1	Distance in the section in the vicinity of the upstream interchange for the section. Midpoint of the interchange that encompasses most of the accidents
L2	Distance in the section in the vicinity of the downstream interchange
LCS	Lane control signal
LD	Length of detector sensing area
LOS	Level of service
LRT	Light rail transit
LS	Section length
LV	Length of vehicle
MAC	Machine access control
M(J)	Mainline AADT for Section J
MCO	Maintenance and Construction Operations Center
M D	Mainline AADT for section with upstream DMS closest to section being analyzed
MDF	Maximum divertible freeway fl ow without major arterial congestion
MF	Maximum fl ow without major arterial congestion
MOVES	Motor vehicle emission simulator
MTF	Fraction of planned metering period that freeway is at level of service E or worse
MTTSV	Average delay reduced per assisted vehicle
MU	Multivariate utility value

Acronym	Defi nition
MUTCD	Manual of uniform traffi c control devices
MV	Utility for message type
MVMPY	Motor vehicle miles per year
n	Project useful life
NAIR	Non-accident incident rate
NCHRP	National Cooperative Highway Research Program
ND	Total number of diverted vehicles until incident clearance
NFA	Normal background traffi c
NHTSA	National Highway Traffi c Safety Administration
NIMS	National Incident Management System
NMV	Utility for other than message type
NND	Total number of vehicles served until incident clearance
NOX	Oxides of nitrogen
NT	Number of travelers
NTCIP	National Transportation Communications for ITS Protocol
NYSDOT	New York State Department of Transportation
OBU	On-board unit
OREMS	Oak ridge emergency evacuation system
P	Probability of functional capability
P(x)	Cumulative probability distribution
P10	Probability incident is managed if TMC is staffed
P21	Probability TMC staffed when incidents occur
P3	Probability motorist receives and understands message from all media
P34	Probability that motorist encounters CMS prior to reaching diversion location
P35	Probability that motorist will read and understand CMS message
P4	Probability that qualifying motorist receiving and understanding the message diverts
PC	Capital equipment cost
PD	Propensity to divert
PDF	Private component of diversion fraction
PDSL	Priced dynamic shoulder lane
PeMS	Performance measurement system
PennDOT	Pennsylvania Department of Transportation
PHV	Peak hour volume
PORTAL	Portland Oregon Regional Transportation Archive Listing
PSAP	Public service access point
q	Volume
q/C	Volume-to-capacity ratio
q 1	Volume at incident
q 2	Volume entering incident
q 3	Volume when incident is present

Acronym	Defi nition
QUAL	Relative quality of information
QWS	Queue warning system
R	Annualized cost with interest
R(j)	Meter rate after time j
R(J)	Residual volume for section J after exit ramps
RC	One direction arterial capacity
RE	Residual capacity
RI	Project class
RI A	Relative importance of attribute A
RITA	Research and Innovative Technology Administration
RSU	Roadside unit
RTV	Relative coverage of incidents
S j	Speed of vehicle j
sppwf	Single payment present worth factor
SWARM	System wide adaptive ramp metering algorithm
T	Time from start of incident to incident clearance
TA	Total number of accidents in section
TC	Time from incident occurrence until diversion is implemented
TCIP	Transit communications interface profi les
TD	Time for queue to dissipate after incident starts
TDD	Time period after incident clearance until queue clears under diversion
TDF	Total diversion fraction
TIP	Transportation improvement plan
t j	Occupancy period sensed by detector for vehicle j
TMC	Transportation (or traffi c) management center
TNA	Test for presence of non-interchange area in section
TO	Metering hours per year
TOND	Improvement in delay on diversion route
TS	Delay reduced
TSI	Delay reduced per incident
TSDV	Time saved by diverting vehicles
TVI	Fraction of roadway visible to CCTV at interchanges
TVN	Fraction of roadway visible to CCTV away from interchanges
U	Utility value or difference in utility values
u	Mean-space-speed
u T	Mean-time-speed
V	Volume
V2I	Vehicle to infrastructure communication
V2V	Vehicle to vehicle communications
VA	Mainline volume upstream of queue formed by incident
VA1	Entry volume downstream of DMS and upstream of incident
VD	Diversion volume

Acronym	Defi nition
VDS	Vehicle detector station
V ED	Exit ramp volume when diversion is implemented
V EW	Exit ramp volume when diversion is not implemented
VMT	Vehicle miles traveled
VPN	Virtual private network
VSD	Vehicle system delay
VSLS	Variable speed limit sign
W AB	Velocity of shock wave propagation. A is downstream boundary, B is upstream boundary
WAN	Wide area network
x	Queue discharge volume
X(J)	Sum of exit ramp AADT for Section J
Y	Fraction of incident management operation represented by timely assistance to emergency responder function
511	Telephone number for public service answering point
α	Shape parameter
β	Scale parameter
θ	Occupancy
θI	Filter input data
θM	Mainline detector occupancy
θO	Filter output data
θS	Occupancy setpoint

Chapter 1 Introduction

Abstract Intelligent Freeway Transportation Systems: Functional Design for Effective Traffi c Management was written to provide engineers engaged in the functional design of freeway intelligent transportation systems with the background and tools to develop effective systems that are properly scaled to traffi c conditions, and that use project resources effi ciently. This chapter describes the migration of ITS from its initial technology constraints to its current ability to support additional functions that can be integrated into a system that better satisfi es stakeholders' needs. A guide to the book's chapters is also provided.

1.1 Purpose of Book

The purpose of this book is to provide engineers engaged in the functional design of freeway ITS with the background and tools to develop effective systems that are properly scaled to traffi c conditions and that use project resources effi ciently. The major functions provided by freeway ITS include

Assisting emergency service providers in detecting and clearing incidents more rapidly. Supporting rapid response reduces the queues on the freeway with corresponding reduction in motorist delay and secondary accidents.
Providing information on incidents and other travel conditions to motorists. Benefi ts accrue to motorists that choose to alter their route, trip initiation time or travel mode. The resulting reduction in the queue on the freeway mainline also reduces the delay for motorists that do not alter their trip plan.
Controlling access to the freeway mainline or controlling lane use. Ramp metering improves the capability of the mainline to service traffi c and redistributes it on the network to reduce overall delay. Lane control signals and dynamic speed control signs may be used to improve traffi c fl ow under incident conditions and improve lane allocations during normal traffi c conditions. Dynamically managing lane use and use of the shoulders may improve traffi c fl ow.

2 1 Introduction

• Managing information and controls to support a broad array of transportation needs, including transit, optimization of passenger throughput in transportation corridors and traffi c management to support responses to emergencies and evacuations.

• Providing information on traffi c conditions and incidents to private traffi c information services.

This book provides guidance on functional design for a number of these topics.

1.2 Development of ITS Design Practices

The freeway management systems that were designed in the 1960s and 1970s were often single purpose or limited function systems. Examples include ramp metering systems, incident management in tunnels, and systems that provided limited levels of motorist information. The operational constraints on these early systems were often determined by limitations in computing and communications capability.

With improvements in computing and communications, freeway ITS were designed to provide a more comprehensive capability to manage traffi c. CCTV coverage was extensively employed. Comprehensive system-wide imagery is currently often available in major metropolitan areas, and transportation management centers often operate 24 h per day, 7 days per week. In some cases, service was extended to provide priority to high occupancy vehicles through management of lanes and ramp meter by-passes for high occupancy vehicles.

During the late 1990s, greater emphasis was placed on the introduction of systems engineering principles into freeway ITS design. These principles are embodied in the National ITS Architecture [ 1 ]. Guidance is also provided by an California Department of Transportation and FHWA report [ 2 ]. Systems engineering principles include:

A systematic life cycle process for establishing needs and objectives, developing a set of design alternatives, evaluating the alternatives, designing the system and installing it, providing the logistic services necessary to support the system, operating the system, and evaluating its performance for the purpose of improving future ITS designs and operations.
Provision of a process to integrate the freeway system into the overall transportation system including support of transit, corridor operations, other regional traffi c and transportation management systems. The process emphasizes interaction with other stakeholders.
Employing approved standards to enable interchangeability of fi eld equipment and to support the interchange of communication among stakeholders and communication with fi eld equipment.

Systems engineering is discussed further in Sect. 2.1.

More recently, increased emphasis has been placed on more intensive management of freeway lane use and vehicle speeds under incident and congestion conditions. With the reduced availability of federal aid and, in some cases, state matching funds, issues such as whether it is more cost effective to cover a wider geographic area with ITS treatments or to deploy ITS devices more intensively in a smaller area are important considerations for project planning and scoping.

1.3 Summary of Contents and Organization

This book describes the application of system engineering principles and cost effective design methodologies to the selection of management strategies and placement for fi eld equipments for commonly employed ITS techniques. The relationship of traffi c conditions to project scoping and preliminary design is extensively discussed.

System engineering methodologies employ "top-down" functional design processes. Figure 1.1 illustrates the process described in the book.

The following discussion relates the book's contents to Fig. 1.1 .

The fi rst task group in the fi gure identifi es objectives and evaluation measures. Chapter 2 describes system engineering techniques as applied to ITS and identifi es goals and objectives. It relates evaluation measures to objectives, and discusses the rationale for evaluating design alternatives and project performance.

Chapter 3 prepares the groundwork for describing ITS treatments later in the book. The chapter discusses traffi c conditions as they affect ITS, including traffi c volume, speed, density and capacity. Congestion and diversion are also explored. A section describing performance and benefi t assessment recommends certain performance measures for assessing design alternatives. Project evaluation techniques are introduced.

The second task group in Fig. 1.1 identifi es management concepts, strategies, and classes of technologies that lead to functional design. Management concepts that directly provide benefi ts to motorists include

• Reduction of time to clear incidents (Chap. 4). Models of delay caused by incidents are presented, and a relationship for the delay reduced by lowering the incident clearance time is discussed. ITS techniques for improving emergency vehicle response time, such as the use of CCTV and traffi c detectors, 1 are described. Procedures for maximizing the cost effectiveness of camera deployments and a trade-off of the effectiveness of traffi c detector deployment and reduced incident detection time are provided. The role of the transportation management center in assisting incident responders and a model for evaluating the effect of incident management is presented.

The terms " detectors or traffi c detectors " are used in this book for devices that provide indications of volume, speed or occupancy at a point on the roadway. These devices are also often called sensors or traffi c sensors.

4 1 Introduction

Fig. 1.1 Functional ITS design process

• Motorist information for non-recurrent congestion (Chap. 5). The role of motorist diversion and its implementation is described. The chapter discusses the capability to control the level of diversion through altering the types of messages and presents a model to assist in obtaining the desired diversion fraction. Strategies to control the diversion fraction in real time are introduced and the effect of the diverted traffi c on the alternate routes is explored. The chapter covers methods for communicating incident information to the motorist and models to optimize the placement of changeable message signs. A model to estimate the quality of information provided to the motorist is described.

Motorist information to address recurrent congestion (Chap. 6). In addition to supplying information on non-recurrent congestion, some agencies choose to provide information on recurrent congestion. In many cases, little or no additional equipment is required to support this capability. The chapter addresses the methodologies for generating this information, and discusses how it provides a modest level of benefi ts that result from knowledge of traffi c variations during normal capacity conditions.
Entry ramp control. Management approaches include entry ramp closure and bypass of entry ramp meters by high-occupancy vehicles. Chapter 7 covers ramp metering, the most commonly used entry ramp control strategy. Guidance is provided to determine whether ramps are suitable for metering. The ability of metering to improve merge characteristics and increase capacity is covered as it the use of metering to control access to the freeway's mainline. Basic strategies include restrictive and non-restrictive metering and their effects on ramp queues and diversion. Sub-strategies include pretimed and traffi c-responsive metering as well as isolated and system-wide metering. Design issues, impacts of traffi c diversion and accommodations that may be necessary to achieve motorist acceptance of ramp metering are described and a model for obtaining benefi ts is provided.
Active transportation and demand management. Strategies to more intensively control lane use and vehicle speeds during incident or congested periods of operation have recently been the focus of a number of ITS projects and are discussed in Chap. 10.
Chapter 11 discusses transportation corridor management and operations. Managed corridors better utilize all of the highway facilities and modes available, particularly under incident or weather related conditions.

Functional design alternatives may differ in the following ways:

Different selections of the management strategies identifi ed above and different choices of sub-strategies (e.g. type of ramp metering and ramps to be metered and motorist messaging strategies).
Intensity of implementation (e.g. average number of CCTV cameras, detector stations and changeable message signs per mile of roadway).
Types of services provided by the transportation management center such as hours of operation, and interaction with other agencies such as transit and emergency responders.

Chapter 8 discusses the support provided for the following functions by transportation management centers:

Support of emergency management services.
Provision of information to motorists.
Operation of ramp meters.
Operation of service patrols.
Coordination of traffi c signals with freeway and corridor operations.
Provision of weather related information to motorists.
Coordination of traffi c management centers on a regional and statewide basis.

6 1 Introduction

The chapter describes methods for establishing information pathways among stakeholders, and provides an example of how the fl ows that are required by a regional ITS architecture may be implemented. The functions of the INFORM Traffi c Management Center, a TMC in a major metropolitan area, illustrates the application of the concepts in the chapter. Methodologies for coordinating the activities of TMCs and other management centers are described.

The third task group in Fig. 1.1 leads to a recommendation for functional design. Benefi t vs. cost analysis is, in many cases, the key to recommending further continuation of the project, and the design alternative to be implemented. Chapter 9 describes the steps required by this type of evaluation. Chapter 9 also discusses how traffi c detector and safety information obtained by traffi c management centers may be used to estimate ITS benefi ts.

A website containing worksheets to support several methodologies discussed in the book is available. The use of these worksheets is described in the relevant chapters. Chapter 12 identifi es these worksheets and provides a brief description of their application.

Chapter 13 discusses the relationship of ITS to connected vehicles. ITS related connected vehicle data links, services and motorist displays are described. The USDOT connected vehicle program is introduced.

References

1. National ITS Architecture V7.0.http://www.iteris.com/itsarch/Online 3 Sept 2014
2. California Department of Transportation and Federal Highway Administration (2009) Systems engineering guidebook for ITS, version 3.0

Chapter 2 Cost Effective Design Processes

Abstract This chapter discusses the following processes in the design and lifecycle operation of a freeway ITS project:

Systems engineering requirements for federal aid projects, and the adaptation of these requirements to the design and project development process used by many agencies.
Objectives for freeway management systems and their relationship to project benefi ts.
Methodologies for the evaluation of design alternatives, project feasibility and project life-cycle evaluation.

2.1 Systems Engineering

2.1.1 Systems Engineering Requirements for Federal Aid Projects

Part 940 of Title 23 of the Code of Federal Regulations (23CFR940) describes the requirements for receiving federal aid. Key provisions include the availability of a Regional ITS Architecture and a project-based systems engineering analysis. The regulation states that the regional ITS architecture comprises a regional framework for insuring institutional agreement and technical integration for the implementation of ITS projects or groups of projects. To qualify for federal aid, ITS projects must conform to the National ITS Architecture [ 1 ], a framework on which the Regional ITS Architecture is based. The Regional ITS Architecture includes:

Development of operational concepts and agreements among the participating regional agencies and stakeholders.
System functional requirements.
Interface requirements and information exchanges with planned and existing systems.
Identifi cation of ITS standards.
Sequence of projects required for implementation.

A project-level ITS architecture that is coordinated with the Regional ITS Architecture is also required by 23CFR940. The systems engineering analysis for the project level architecture includes as a minimum:

Identifi cation of the portions of the Regional ITS architecture being implemented, and identifi cation of cognizant agencies and responsibilities.
Defi nition of requirements.
Analysis of alternative system confi gurations and technologies.
Procurement options.
Identifi cation of applicable ITS standards and testing procedures.
Procedures and resources necessary for operation and management of the system.

2.1.2 Systems Engineering as a Life-Cycle Process

The concept of systems engineering developed signifi cantly in the 1960s with the advent of large military and space systems. It represents the amalgamation of a number of engineering disciplines together with economics, human factors, goal setting and evaluation techniques [ 2 ].

The International Council on Systems Engineering (INCOSE) defi nes Systems Engineering as follows [ 3 ]:

Systems Engineering is an interdisciplinary approach and means to enable the realization of successful systems. It focuses on defi ning customer needs and required functionality early in the development cycle, documenting requirements, then proceeding with design synthesis and system validation while considering the complete problem.

Systems engineering practices differ considerably depending on the application. Advanced military systems, for example emphasize development of technology, while ITS design decisions principally utilize existing components and adaptations of existing software. The Systems Engineering Guidebook for ITS [ 4 ] provides project guidance for implementation by applying the Vee technical development model (Fig. 2.1 ). The Guidebook indicates that the items in the Vee diagram ranging from Concept Exploration through System Requirements are infl uenced by the Regional ITS Architecture.

A key element in the Vee diagram is the Concept of Operations (CONOPS). The objectives of the CONOPS are to document the total environment and use of the system from the point of view of the stakeholders. The Guidebook provides the template shown in Table 2.1 to assist in CONOPS development.

Fig. 2.1 Vee technical development model

Table 2.1 Template for concept of operations

Section	Contents
Title page	The title page should follow the Transportation Agency procedures or style guide At a minimum, it should contain the following information: • CONCEPT OF OPERATIONS FOR THE [insert name of project] AND [insert name of transportation agency] • Contract number • Date that the document was formally approved • The organization responsible for preparing the document • Internal document control number, if available • Revision version and date issued
1.0 Purpose of document	This section is a brief statement of the purpose of this document. It is a description and rationale of the expected operations of the system under development. It is a vehicle for stakeholder discussion and consensus to ensure that the system that is built is operationally feasible. This will briefl y describe contents, intention, and audience. One or two paragraphs will suffi ce
2.0 Scope of project	This short section gives a brief overview of the system to be built. It includes its purpose and a high-level description. It describes what area will be covered and which agencies will be involved, either directly or through interfaces. One or two paragraphs will suffi ce
3.0 Referenced documents	This optional section is a place to list any supporting documentation used and other resources that are useful in understanding the operations of the system. This could include any documentation of current operations and any strategic plans that drive the goals of the system under development
4.0 Background	Here is a brief description of the current system or situation, how it is used currently, and its drawbacks and limitations. This leads into the reasons for the proposed development and the general approach to improving the system. This is followed by a discussion of the nature of the planned changes and a justifi cation for them
5.0 Concept for the proposed system	This section describes the concept exploration. It starts with a list and description of the alternative concepts examined. The evaluation and assessment of each alternative follows. This leads into the justifi cation for the selected approach. The operational concept for that selected approach is described here. This is not a design, but a high-level, conceptual, operational description. It uses only as much detail as needed to be able to develop meaningful scenarios. In particular, if alternative approaches differ in terms of which agency does what, that will need to be resolved and described. An example would be the question of whether or not a regional signal system will have centralized control
6.0 User oriented operational description	This section focuses on how the goals and objectives are accomplished currently. Specifi cally, it describes strategies, tactics, policies, and constraints. This is where the stakeholders are described. It includes who users are and what the users do. Specifi cally, it covers when, and in what order, operations take place, personnel capabilities, organizational structures, personnel and inter-agency interactions, and types of activities. This may also include operational process models in terms of sequence and interrelationships
7.0 Operational needs	Here is a description of the vision, goals and objectives, and personnel needs that drive the requirements for the system. Specifi cally, this describes what the system needs to do that it is not currently doing

Table 2.1 (continued)

Section	Contents
8.0 System overview	This is an overview of the system to be developed. This describes its scope, the users of the system, what it interfaces with, its states and modes, the planned capabilities, its goals and objectives, and the system architecture. Note that the system architecture is not a design [that will be done later]. It provides a structure for describing the operations, in terms of where the operations will be carried out, and what the lines of communication will be
9.0 Operational environment	This section describes the physical operational environment in terms of facilities, equipment, computing hardware, software, personnel, operational procedures and support necessary to operate the deployed system. For example, it will describe the personnel in terms of their expected experience, skills and training, typical work hours, and other activities [e.g., driving] that must be or may be performed concurrently
10.0 Support environment	This describes the current and planned physical support environment. This includes facilities, utilities, equipment, computing hardware, software, personnel, operational procedures, maintenance, and disposal. This includes expected support from outside agencies
11.0 Operational scenarios	This is the heart of the document. Each scenario describes a sequence of events, activities carried out by the user, the system, and the environment. It specifi es what triggers the sequence, who or what performs each step, when communications occur and to whom or what [e.g., a log fi le], and what information is being communicated. The scenarios will need to cover all normal conditions, stress conditions, failure events, maintenance, and anomalies and exceptions. There are many ways for presenting scenarios, but the important thing is that each stakeholder can clearly see what his expected role is to be
12.0 Summary of impacts	This is an analysis of the proposed system and the impacts on each of the stakeholders. It is presented from the viewpoint of each, so that they can readily understand and validate how the proposed system will impact their operations. Here is where any constraints on system development are documented. Metrics for assessing system performance are also included here
13.0 Appendices	This is a place to put a glossary, notes, and backup or background material for any of the sections. For example, it might include analysis results in support of the concept exploration

Relevant standards are the ANSI/AIAA G-043-1992 standard and IEEE Standard 1362

2.1.3 ITS Project Development

While the Vee model provides a basis for project development, many of the agencies that acquire and operate ITS traditionally use procedures that are largely based on those used for highway construction. For example, the New York State Department of Transportation (NYSDOT) develops projects, including ITS projects through a process described in the New York State Department of Transportation Project Development Manual [ 5 ]. This manual describes the following stages of project development:

• Initial Project Proposal—A preliminary description of the problem, project objectives, schedule and cost estimate. For ITS projects this is usually a brief document.

Project Scoping Stage—Identifi es conditions, needs, objectives, design criteria, feasible alternatives and cost. For ITS projects the stage usually results in a functional design for a recommended alternative and a plan for general deployment of major devices such as DMS.
Design Stage—This stage is broken into a number of phases. A design document is prepared to summarize the results of the preliminary design phases, and the fi nal design phases result in a set of plans, specifi cations and estimates (PS&E) for the project.

In order to adapt the NYSDOT project development process to ITS needs and facilitate the incorporation of federal system engineering requirements, Appendix 6 (Intelligent Transportation Systems Scoping Guidance) was incorporated into the Project Development Manual. Figure 2.2 shows an overview of the scoping guidance provided in that appendix.

Table 2.2 shows the relationship of the major NYSDOT project stages and operations functions to the Vee diagram. The identifi cation numbers in the scoping column correspond to the processes in Fig. 2.2 .

2.2 Goals, Objectives and Requirements

Systems for various technical fi elds are often developed to satisfy a specifi c set of objectives or requirements. For example, the acceptance of a newly designed airplane by an airline is often based on its performance to a set of previously agreed on specifi cations such as the attainment of a speed vs. altitude envelope.

ITS objectives or requirements are usually formulated from a more general set of goals established by stakeholders. The National ITS Architecture [ 1 ] defi nes goals in a broad manner for all ITS applications. These goals are:

Improve the safety of the nation's surface transportation system.
Increase the operational effi ciency and capacity of the surface transportation system.
Reduce energy consumption and environmental costs.
Enhance present and future economic productivity of individuals, organizations and the economy as a whole.
Enhance the personal mobility and the convenience and comfort of the surface transportation system.
Create an environment in which the development and deployment of ITS can fl ourish.

For the purpose of scoping advanced traffi c management systems, these general goals may be focused into general objectives for a project. An example of a candidate set of general objectives for both freeway and surface street systems is shown in Table 2.3 [ 5 ]. The objectives for a project should be selected by the stakeholders, and related to the Regional ITS Architecture. To be effectively employed, objectives should be measurable. Thus the table includes a set of possible evaluation measures. A freeway management project will typically employ a subset of these objectives.

Fig. 2.2 ITS project scoping process overview [ 5 ]

Table 2.2 Relationship of NYSDOT project development and operation to systems engineering life cycle [ 5 ]

	NYSDOT engineering project develop	ment and operations functions
WA VEE FH		minary Preli	Detailed		Operations and
diagram process	Scoping	design	design	Construction	maintenance
Concept of operations	Traffi c conditions and safety inventory (1)
	Stakeholders, participating agencies (3)
	Objectives (4)
	Measures of effectiveness (4)
ments High level require	Future service life (2)
	Constraints (5)
	ment (6) mprove Selection of functions for i
	ment of alternatives (7) Develop
	Other considerations (8)
	ment (10) mmendations for project develop Benefi ts (9) Reco
ments Detailed require		√
High level design		√
Detailed design			√
mentation mple I				√
Integration and test				√
m verifi cation Subsyste				√
m verifi cation Syste				√
Operations and maintenance					√
ment Assess					m step 4 Performance measures fro

Table 2.3 General candidate objectives [ 5 ]

	Objective	Possible evaluation measure
1.	Reduce congestion and improve travel time
	(a) Recurrent congestion/travel time—signifi cant section	Vehicle hours per year saved, person hours per year saved
	(b) Recurrent congestion—spot	Vehicle hours per year saved, person hours per year saved
	(c) Non-recurrent congestion— signifi cant section	Vehicle hours per year saved, person hours per year saved
	(d) Non-recurrent congestion—spot	Vehicle hours per year saved, person hours per year saved
2.	Reduce accident rate
	(a) Over signifi cant section	Reduction in accidents per year
	(b) Spot	Reduction in accidents per year
3.	Reduce emissions and fuel consumption	Reduction in grams of HC, NOX, CO per year
4.	Serve as a corridor link in a wider area highway system	Provide capability for this roadway to offer meaningful diversion opportunity for incidents on another freeway that carries interregional traffi c
5.	Serve as a diversion route in local corridor	Provide capability for this roadway to offer meaningful diversion opportunity for incidents on another freeway or surface street that carries local or intraregional traffi c
6.	Special traffi c management functions
	(a) Traffi c monitoring for major roadway reconstruction	Provision of capability to assist in management of traffi c during construction
	(b) Traffi c monitoring for minor roadway construction	Provision of capability to assist in management of traffi c during construction
	(c) High occupancy vehicles	Provision of ITS support for HOV operations
	(d) Signal preemption for railroad or emergency vehicles	Reduction in accidents per year
	(e) Priority for transit	Reduction in total traveler hours per year. Reduction in total grams of HC, NOX, CO per year
	(f) Traffi c information on roadway construction	Increase in motorists notifi ed
	(g) Motorist information on travel conditions, parking, special events, roadway weather	Increase in motorists notifi ed
	(h) Pedestrian and bicycle movement	Reduction in total traveler hours per year. Reduction in accidents per year
	(i) Mobility and safety for the disabled	Annual volume of trips for the disabled. Average travel time for trip for disabled. Number of accidents per year for disabled
	(j) Traffi c management for future major roadway reconstruction	Provision of capability to assist in management of traffi c during construction
	(k) Motorist information about detour routes	Increase in motorists notifi ed

Table 2.3 (continued)

Objective		Possible evaluation measure
7.	Interoperability of ITS
	(a) Operating effi ciency	Regional vehicle hours per year saved, person hours per year saved. Regional reduction in accidents per year
	(b) Stakeholder involvement	Regional vehicle hours per year saved, person hours per year saved. Regional reduction in accidents per year
8.	Improvement of NYSDOT operations
	(a) Planning and/or evaluation data collection	Annual dollar savings by elimination of other forms of data collection. Provision of data not previously available
	(b) ITS equipment monitoring	Vehicle hours per year saved, person hours per year saved, reduction in accidents per year as a result of faster maintenance. Cost savings to operating agency
	(c) Effi ciency of operations	Annual cost reduction to operating agency in dollars
	(d) Reduction of maintenance cost	Annual cost reduction to operating agency in dollars
	(e) Ability to operate signals during power outages	Vehicle hours per year saved, person hours per year saved, reduction in accidents per year as a result of reduced signal outage time
	(f) Operational availability of ITS	% of time TMC available, % of fi eld devices available, monitorable and controllable
9.	Provide assistance to disabled motorists	Vehicle hours per year saved, person hours per year saved, reduction in accidents per year
	10. Provide travel information related to tourism	Increase in motorists notifi ed
11. Security
	(a) Transportation system security	Reduction in cost of vandalized equipment
	(b) Emergency operation	Vehicle hours per year saved, person hours per year saved, reduction in accidents per year as a result of increased number of operating hours per year
	(c) Information system security	Reduction in number of unauthorized operations per year, amount of data lost per year
	12. Commercial vehicle operations	Annual cost savings to industry Annual cost savings to operating authority

In establishing general project objectives, stakeholders should be aware of the relative levels of benefi ts that ITS treatments are likely to provide. For example, Fig. 2.3 shows the relative benefi ts achieved by several ITS treatments for a typical freeway whose peak period volume-to-capacity ratio is generally between 0.93 and 0.96. It is seen that objectives that result in the in the reduction of non-recurrent congestion through improvement of incident clearance time are likely to provide the greatest benefi ts.

To assist in evaluating design alternatives, after selection of the subset of general objectives used for the project, it is useful to further tailor this subset to the project,

Fig. 2.3 Typical relative improvement for several ITS measures

and to provide additional detail. Accordingly specifi c evaluation measures are selected and objectives are quantifi ed to the extent possible. Exploiting quantitative benefi t values to express objectives is important because it provides both system designers as well as decision makers with a means to identify expectations, estimate the scale and scope of the project and determine its utility relative to other candidate projects. It also provides a basis for assessing the effectiveness of the design. The values should be suffi ciently high to make a meaningful impact, but must also be achievable by technologies and resources available for the project. Many of the models described in this book and the RITA ITS benefi ts data base [ 6 ] provide guidance for the selection of values for objectives. We use the term detailed project objectives instead of requirements in order to provide some fl exibility for stakeholder review and reassessment based on project evaluation. Other features of detailed objectives include the following [ 7 ]:

Detailed objective should stand alone, i.e. it should not require the reader to look at additional text.
Detailed objective should be open to only one interpretation.
Detailed objective should be verifi able through inspection, analysis or test.

2.3 Evaluation Methodologies

Evaluation methodologies may be employed for the following major functions in the life cycle process:

Design evaluations to select the most appropriate design alternatives and to estimate the expected performance of these alternatives relative to the detailed objectives. These prospective evaluations (Sect. 3.2) may be performed using the models discussed in this book and by ITS evaluation models.
Project performance evaluations are retrospective evaluations (Sect. 3.2) performed to determine actual system performance and cost relative to expectations. They may be executed by fi eld measurements, measurements made by system detectors, accident statistics and actual cost information. In some cases simulation is used. These evaluations not only evaluate the system design and operation but also provide feedback for improving the operation of the current project and provide guidance for the functional design of future projects.

References

1. National ITS architecture V7.0, Iteris, 9 May 2013. Online available at www.iteris.com/ itsarch/. Accessed 4 Sept 2014
2. Gordon RL (2003) Systems engineering processes for developing traffi c signal systems, NCHRP synthesis 307. Transportation Research Board, Washington, DC
3. International Council on Systems Engineering (INCOSE), Seattle, WA. Online available at www.incose.org. Accessed 4 Sept 2014
4. Systems engineering guidebook for intelligent transportation systems, version 3.0 (2009) Federal Highway Administration and California Department of Transportation
5. New York State Department of Transportation Project Development Manual (2004) New York State Department of Transportation, Albany, NY
6. Intelligent transportation systems benefi ts database. Research and Innovative Technology Administration. Online available at http://www.benefi tcost.its.dot.gov/its/benecost.nsf/ Benefi tsHome. Accessed 3 April 2015
7. Developing functional requirements for ITS projects (2002) Mitretek Systems

Chapter 3 Functional ITS Design Issues

Abstract This chapter discusses a number of topics that form the conceptual framework and the building blocks for developing ITS designs as described in the chapters that follow. Topics include:

Relationship of ITS design approaches to general transportation planning principles. The impacts of volume, speed, density, capacity issues, recurrent and non-recurrent congestion are introduced and discussed. Insights into the decisions that influence how motorists make diversion choices to alternate routes are presented. The effect of message strength on diversion probability is described.
Performance and benefit assessment. Performance measures for evaluation of ITS design alternatives are needed. Marginal analysis and multi-attribute utility analysis are described and illustrated as examples of alternatives to the use of traditional cost benefit analysis.
Alternatives for functional analysis. The need for an alternatives analysis is presented along with constraints on the selection of alternatives is described. A matrix identifying the relationship of ITS management concepts to project objectives is presented in order to facilitate consideration of the appropriate ITS treatment to achieve these objectives.

3.1 Relationship of ITS Design to General Transportation Planning Principles

ITS functions and designs must be consistent with general traffic engineering and transportation planning principles. The following sections describe a number of these principles that affect ITS concept design.

3.1.1 General Traffic Flow Relationships

3.1.1.1 Relationship of Volume, Speed and Traffic Density

This relationship is provided in various texts (for example see May [1]) as

$$q = k \cdot u \tag{3.1}$$

where

q=volume (vehicles per hour per lane)

k=density or concentration (vehicles per mile per lane)

u=space-mean-speed (miles per hour)

Space-mean-speed-is the average speed of vehicles measured over a short distance, for example by converting the travel times of the vehicles measured over the distance. Probe traffic detection techniques (see Sect. 4.5.1.3) measure space-meanspeed. Time-mean-speed (uT) is the average speed of vehicles measured at a point, and may be measured by point detectors (Sect. 4.5.1.3). These quantities are statistically related [2]. An empirical relationship is [3]:

$$u = 1.026 \cdot u_{T} - 1.89 \tag{3.2}$$

where u and uT are in miles per hour. Time-mean-speed exceeds space-mean-speed with the largest divergence at low speeds.

3.1.1.2 Capacity

Capacity is defined as "the maximum sustained 15-min flow rate, expressed in passenger cars per hour per lane, that can be accommodated by a uniform freeway segment under prevailing traffic and roadway conditions in one direction of flow [4]." HCM 2000 [4] presents the suggested speed-flow relationship shown in Fig. 3.1.

The figure shows three flow regimes for basic freeway segments. In the undersaturated regime, as traffic volume increases, speed decreases slightly until the capacity is reached (2,250–2,400 passenger vehicles per hour per lane (pc/h/ln) depending on the free flow speed). Chapter 7 discusses the possibility of increasing this capacity by smoothing ramp entry flows. The queue discharge regime represents

Fig. 3.1 Speed vs. flow rate [4]

the flow resulting from a bottleneck (when freeway demand exceeds capacity). Flow rates of from 2,000 to 2,300 pc/h/ln are usually experienced in this regime for basic freeway sections.

Oversaturated flow is influenced by the effects of a downstream bottleneck (i.e. by flow into existing congested conditions). Low speeds and high values of density characterize the congestion in this regime.

3.1.2 Shock Waves

Shock waves are defined as boundary conditions in the time-space domain that demark a discontinuity in flow-density conditions [1]. The propagation speeds of shock waves often determine the time it takes to detect an incident with ITS devices. Section 4.5.1.3 discusses these issues.

3.1.3 Classification of Congestion

Congestion is travel time or delay in excess of that normally incurred under light or free-flow travel conditions. Unacceptable congestion is travel time or delay in excess of an agreed-upon norm. The agreed-upon norm may vary by type of transportation facility, travel mode, geographic location, and time of day, and should be derived taking into account the expectations for each portion of the transportation system as influenced by community input and technical considerations [5]. Many transportation agencies use a "D" level of service during peak hours in urban areas as the basis for acceptable operation and therefore as the baseline for defining delay.

Congestion is often classified as either recurrent or non-recurrent. The type of congestion depends on whether the capacity or the demand factor is out of balance.

Recurrent congestion occurs when demand increases beyond the normally available capacity. It usually is associated with the morning and afternoon work commutes, when demand reaches a level that overwhelms the freeway and traffic flow deteriorates to unstable stop-and-go conditions [5]. The role of ITS in reducing recurrent congestion is discussed in Sect. 3.1.5 and in Chap. 6.
Non-recurrent congestion results from a temporary decrease in capacity while the demand remains unchanged. This kind of congestion usually results when the freeway capacity becomes temporarily restricted. A stopped vehicle, for example, can take a lane out of service, however the same number of vehicles require passage. Speed and volume drop until the lane is reopened, and then they return to full capacity. Capacity can also be decreased by weather events and events near the travel way (i.e., "rubber necking"), leading to non-recurrent congestion and reduced reliability of the entire transportation system [1]. ITS techniques to reduce the effect of non-recurrent information include reducing the time to clear an incident (Chap. 4) and motorist diversion (Sect. 3.1.4 and Chap. 5).

3.1.4 Diversion for Non-Recurrent Congestion

3.1.4.1 Diversion Decisions by Motorists

The motorist normally selects a route based on the comparative utility (travel time and other factors) of alternative route choices. Traffic assignment models estimate the choices by user class. Other factors being equal, the freeway route is selected by most users under normal conditions.

When an incident has happened on the freeway and motorists are aware of a problem, some percentage of motorists using the freeway will choose to divert to an alternate route.

Individual diversion decisions are made on the basis of perceived time saved or other factors such as trip reliability based on information available to the motorists from various sources, along with their perception of the traffic environment. Studies show that the propensity for a motorist to divert depends on the "strength" of the message. Table 3.1 shows an example of increasing message strength [6].

Operating agencies may consider the degree of diversion desired in formulating message displays (see Chap. 5).

Estimates and models have been developed that show the probability of diversion based on the perception of time saved. An early example of an assignment curve is shown in Fig. 3.2.

Using data from Ullman et al. [8], Fig. 3.3 depicts the diversion percentage from a freeway to a surface street for motorists receiving a message of strength 8 in Table 3.1 for a particular set of circumstances. The slope of the curve for time savings for less than 20 min is approximately 6 % diversion increase per minute of time saved.

Another example of the use of message strength to result in diversion is provided by Jindahra and Choocharukul [9]. Their survey considered the following types of message combinations:

Quantitative delay (e.g. 15 min)
Cause
Suggested route
Quantitative delay plus suggested route

Table 3.1 Example of increasing message strength [6]

Message type	Message content
1	Occurrence of accident only
2	Location of the accident only
3	Expected delay only
4	The best detour strategy only
5	Location of the accident and the best detour strategy
6	Location of the accident and the expected delay
7	Expected delay and the best detour strategy
8	Location of the accident, expected delay and the best detour strategy

Source: Ref. [6]. Reproduced with permission of the Transportation Research Board

Fig. 3.2 Bureau of Public Roads diversion curve [7]

Fig. 3.3 Diversion from freeway to surface street [8] (redrawn)

Qualitative delay (e.g. expected long delay)
Cause plus quantitative delay
Quantitative delay plus suggested route
Cause plus qualitative delay
Cause plus suggested route

The responses were placed into three categories:

Motorist likely to stay on current route
Motorist is indecisive
Motorist likely to divert

Figure 3.4 shows a re-plotting of the data in the reference and indicates the substantial effect of message content on diversion.

Schroeder and Demetsky [10] correlated the effects of message strength with diversion fraction by using traffic detector stations to measure diversion fraction. Table 3.2 shows an example of their results.

Deeter [11] reports on surveys that examined the effect of posted travel times longer than normal as the basis for diversion. An example of the results of a survey in the Seattle area is shown in Table 3.3.

Fig. 3.4 Effect of message strength on diversion probability

Table 3.2 Percent diversion for message types

Message type	Example of message	% diversion
0: No incident
1: No guidance provided	"ACCIDENT AT EXIT 73, EXPECT DELAYS"	5.0
2: Alternate route recommended	"ACCIDENT AT EXIT 75, EXPECT DELAYS, USE ALT ROUTE"	9.3
3: Specific major alternate route recommended	"ACCIDENT AT EXIT 75, THRU TRAFFIC USE I-295 SOUTH"	11.3

Minutes over the typical travel time	Percent of survey respondents that described each threshold (%)
5	16
10	37
15	26
20	11
30	11

Table 3.3 Minutes over the typical travel time that drivers divert

Different results may be obtained depending on the spacing of the dynamic message signs used to convey this information. Diversion fraction DF at an exit ramp may be defined as follows:

$$DF = (V{ED} - V{EW}) / V_{A}$$ (3.3)

where

VA is the volume upstream of the exit ramp when VED is the exit ramp volume when diversion is implemented at this ramp VEW is the exit ramp volume when diversion is not implemented at this ramp

Diversion is discussed further in Chap. 5. Although the research indicates that the diversion fraction increases with increasing message strength, the diversion fractions for a particular message strength appear to vary among installations. They also vary with time of day and season for a single location [10]. Section 5.1.3 further discusses the control of diversion fraction.

3.1.4.2 System-Wide Impacts of Diversion

If traffic information on an incident is provided before the start of the trip or early in the trip, motorists may choose to:

Select an alternate route
Select an alternative time for the trip
Select a different mode

For most incidents, information reaching the motorist during his trip on the freeway will provide the motivation to divert, most often to a surface street. The previous section discussed likely motorist responses to this information. This section discusses system considerations in providing motorist information.

From a transportation system perspective, the objective of diversion is to minimize delay in the corridor and/or maximize mobility (throughput) in the corridor. While diversion, if properly implemented, will reduce delay to the vehicles diverting and reduce delay to the freeway vehicles that do not divert, it will incur additional delay to the vehicles that normally use the diversion route. Some of these vehicles may, in turn, divert to a roadway with a lower classification rating (e.g. from a principal arterial street to a minor arterial street) generally increasing the delay to these vehicles.

Most traffic management centers manage the provision of motorist information by means of operating procedures. These procedures reflect the policies of the agency and contain message structure guidelines as well as the circumstances that require messages. Dudek [12] provides a comprehensive discussion of these factors as well as a number of examples of policy statements for various aspects of message development and changeable message sign operation. For example, when explicit route guidance is provided:

The DMS operator has current and continuously-updated knowledge of the traffic conditions on the alternative route; and
The alternative route will result in a significant savings in time for the diverted motorists.

This policy is designed to apply to explicit diversion messages (e.g. message types 4, 5, 7, and 8 in Table 3.1). Although the other message types do not explicitly recommend diversion, they do, in fact, result in diversion, and the TMC operating procedures should reflect this.

Improvements in delay to non-diverting freeway traffic may be significant, even for relatively low levels of diversion. This is further discussed in Chap. 5.

Even low levels of freeway diversion may cause significant increase in the volume-to-capacity ratio on surface street alternates. When this volume-to-capacity ratio exceeds 0.9, the delay increases exponentially as shown in Fig. 3.5. Operating procedures must ensure that arterial delay does not become excessive.

3.1.5 Recurrent Congestion

Recurrent congestion is characterized by congestion that repeats on a day-to-day basis at the same locations, usually during peak traffic periods. Most motorists are familiar with traffic conditions on the freeway and on its alternates during these periods. Under these conditions, traffic distribution on the network is determined by Wardrop's Principles [13]. These principles are summarized as follows:

Wardrops's First Principle (user equilibrium) indicates that the trip costs on all routes actually used are less than those that would occur if a vehicle used any unused route. Thus users choose the route that minimizes their own travel time.
Wardrop's Second Principle (system equilibrium) indicates that cost of using the system is at a minimum. Users distribute themselves so that the average travel time on each origin-destination pair is equal for all users.

The costs include travel time and fuel consumption as well as other costs that might be perceived by drivers. According to these principles, there is nothing to be gained by selecting an alternate route, as such a selection will lead to a higher cost. These principles are based on the assumption that motorists are generally familiar with the alternate routes and the general traffic conditions associated with these routes. Knowledge of traffic conditions under recurrent congestion is markedly different from non-recurrent congestion. In the latter case, and without ITS motorist information provisions, the motorist has incomplete knowledge of network traffic conditions.

In recent years, traffic management centers have increasingly used travel time messages on DMS. These messages are supplemented by others when incidents occur.

Measures may be considered to increase traveler throughput under recurrent congestion by biasing the delays or motorists' cost in the network. Measures such as restrictive ramp metering and lane or roadway use controls provide motorists with an altered set of link travel times, and in some cases altered out of pocket cost. The application of Wardrop's principles to this new configuration will alter the travel pattern.

3.2 Performance and Benefit Assessment

Two types of evaluations may be conducted:

Prospective Evaluations—During the project scoping process, prospective evaluations assist in deciding whether the system should be implemented, and provide the basis for the evaluation of design alternatives. As described in Chap. 2, Title 23 Section 940.11 of the Code of Federal Regulations (CFR) requires the consideration of design alternatives for a project to be considered for federal aid.
Retrospective Evaluations—Performed after system installation and operation, retrospective evaluations provide the basis for developing "lessons learned" and for the future improvement of system design and operation.

Reference [14] provides an in-depth discussion of the issues concerning the selection of measures for freeway applications. Table 3.4 [15] provides a set of recommended measures for highway applications. Gordon [16] describes methodologies for developing many of the measures that are used for ITS evaluations.

3.2.1 Performance Measures to Facilitate System Design

This book is primarily concerned with development and evaluation of design alternatives, Therefore it emphasizes economic benefits and costs for design and prospective evaluation purposes.

Many of the measures in Table 3.4 represent different ways of expressing the same economic benefit to be achieved by ITS. In order to be useful for the purposes

| Table 3.4 | | Recommended performance measures for highways [15] | | |-----------|--|----------------------------------------------------|--| |-----------|--|----------------------------------------------------|--|

	Outcomes (operational) performance measures
•	Quantity of travel (users' perspectives)
	– Person-miles traveled
	– Truck-miles traveled
	– VMT
	– Persons moved
	– Trucks moved
	– Vehicles moved
•	Quality of travel (users' perspectives)
	– Average speed weighted by person-miles traveled
	– Average door-to-door travel time
	– Travel time predictability
	– Travel time reliability ( of trips that arrive in acceptable time)
	– Average delay (total, recurring, and incident-based)
	– Level of Service (LOS)
•	Utilization of the system (agency's perspective)
	– Percent of system heavily congested (LOS E or F)
	– Density (passenger cars per hour per lane)
	– Percentage of travel heavily congested
	– V/C ratio
	– Queuing (frequency and length)
	– Percent of miles operating in desired speed range
	– Vehicle occupancy (persons per vehicle)
	– Duration of congestion (lane-mile-hours at LOS E or F)
•	Safety
	– Incident rate by severity (e.g., fatal, injury) and type (e.g., crash, weather)
•	Incidents
	– Incident induced delay
	– Evacuation clearance time
	Outputs (agency performance)
•	Incident response time by type of incident
•	Toll revenue
•	Bridge condition
•	Pavement condition
•	Percent of ITS equipment operational

of evaluating alternatives and developing recommendations for design implementation, it is necessary to select a subset of these measures that facilitates the evaluation of the following categories:

Economic benefits. For evaluation purposes, delay reduction, safety and fuel consumption will be considered in this category.
Environmental Benefits (emissions).
Mobility. This represents the quantity of service provided.
Public satisfaction with ITS treatments.

To provide a basis evaluating alternatives and developing recommendations, it is necessary that the measures selected include all of the benefits in a category, but do not include the benefit more than once. For example, the measures selected for economic evaluations should include an estimate of all of the economic benefits but should not include the same effect (e.g. travel time and delay) more than once. Table 3.5 suggests a reduced set of measures that may be used to evaluate system designs.

Measures intended for design evaluations are often based on analytic or simulation processes, whereas ongoing evaluations or before and after studies generally utilize measured parameters. Economic benefit analysis for transportation systems is often the key component of a design evaluation. It usually features a benefit vs. cost analysis [17]. The benefit to cost ratio is often a key indicator for the selection of the design alternative and for the decision to implement the project. Cost benefit analysis is discussed in Chap. 9.

Simple benefit to cost ratio comparisons, however, often fail to provide a complete basis for decision making. For example, consider Alternative 1 and Alternative 2 in the hypothetical example of Table 3.6. Although the benefit-to-cost ratio for Alternative 1 is better, if the project objective is to save 600,000 vehicle hours, Alternative 2 comes much closer to satisfying this objective while maintaining a

Category	Measure	Possible units
Economic benefits	Reduction in passenger vehicle delay	Vehicle hours per year
	Reduction in commercial vehicle delay	Vehicle hours per year
	Reduction in commercial vehicle inventory delay	Vehicle hours per year
	Reduction in fuel consumption	Gallons per year
	Reduction in accidents	Accidents per year
Environmental	Carbon monoxide	Pounds per year
	Oxides of nitrogen	Pounds per year
	Volatile organic compounds	Pounds per year
	Carbon dioxide	Pounds per year
User satisfaction	Satisfaction with ITS treatment	KS·NT

Table 3.5 Measures suggested for prospective ITS evaluation

Where

KS is a satisfaction rating on a scale of −1.0 to +1.0

NT is the number of travelers to whom the issue applies

			Marginal parameters of alternative 2 relative
	Alternative 1	Alternative 2	to alternative 1
Annual vehicle hours saved	250,000	500,000	250,000
Annual benefit	\$5 M	\$10 M	\$5 M
Annualized project cost	\$1 M	\$2.5 M	\$1.5 M
Benefit-to-cost ratio	5:1	4:1	3.33:1
Net benefit	\$4 M	\$7.5 M	\$3.5 M
% of project objective satisfied	41.6	83.3	Not applicable

Table 3.6 Example of marginal analysis

satisfactory marginal benefit to cost ratio (i.e. significantly in excess of 1) for the additional investment. The introduction of the concepts of marginal values and percentage of objective satisfied provides an important basis for project evaluation.

Travel time variation is an increasing popular ITS measure, however because of the difficulty in obtaining this quantity in a manner other than direct measurement, it is more suitable for retrospective evaluation rather than prospective evaluation.

While some projects or agencies ascribe monetary values to environmental benefits, these benefits may also be a key project objective, as they reduce emissions. This is particularly important in locations that do not conform to the national ambient air quality standard.

The economic and environmental measures do not account for the change in manifest demand that results from some ITS treatments. Throughput measures the facility's capability to service demand [18]. Sometimes termed productivity [19], it represents the vehicle miles that a facility can accommodate during a peak hour or peak period. The effect of the project on the change in this measure is difficult to anticipate in advance of implementation thus the measure is best used for retrospective evaluations.

Since the user is the ultimate judge of the perception of ITS effectiveness and value, the system designer must consider the factors that the user deems important. While these factors may be difficult to estimate on a prospective basis, previous studies provide some indication as to how user satisfaction may be rated. While Chaps. 5–7 discuss user satisfaction for different ITS treatments, some general issues are discussed below.

ITS treatments such as motorist information and motorist service patrols are generally well received by the public because no class of motorists is penalized by these ITS treatments. Motorists feel that these treatments improve their trip reliability and their sense of control [20]. Rating scales based on surveys may be used to quantify user satisfaction for this these types of ITS treatments.

Other treatments such as ramp metering and road pricing or restricted road use may provide improved mobility for some users, and on balance for the whole system, while providing reduced mobility for other users. The transportation system operator must consider how prospective treatments affect different users. Levinson et al. [19] describe an approach to measuring equity. The Lorenz Curve (Fig. 3.6)

Fig. 3.6 Example of Lorenz Curve for a metered freeway entry ramp

identifies the relationship between the proportion of delay and the proportion of vehicles incurring the delay. Thus area AD in the figure identifies the users that are relatively disbenefitted by the treatment. The Gini coefficient is computed as

$$G = AD/(AD + AT)$$ (3.4)

It quantifies the level of inequality among users. Levinson et al. [19] describes a methodology for computing the Gini coefficient.

As an example of the importance of user satisfaction in ITS design and operation, the control strategy for ramp meter rates in Minnesota was revised in order to provide lower delays to entering vehicles, even at the expense of overall increases in delay [19].

3.2.2 Performance Measures and ITS Planning

Planning agencies such as metropolitan planning organizations (MPOs) are required to select and prioritize projects from a number of alternatives that may include different types of projects and, perhaps, different traveler classes. These projects may affect benefit categories such as those shown in Table 3.5 in different ways. Multiattribute utility analysis is one methodology for comparing such projects [21, 22]. It enables stakeholders with different interests and responsibilities to proactively participate in the planning process. A simple example that compares and depicts the benefits from a candidate set of ITS projects is discussed below.

	Attribute (RIA)
Alternative ITS project classes (S)a	1. Traveler cost reduced (0.6)	2. Emissions reduced (0.2)	3. Traveler satisfaction (0.2)
1. Improved incident clearance	High reduction (0.9)	Proportional to fuel reduced (0.9)	Little effect observed by motorists (0.2)
2. Restrictive ramp metering	Moderate to high reduction (0.6)	Proportional to fuel reduced (0.6)	May be significant opposition because of ramp delays and local impacts resulting from diverted traffic (0.1)
3. Non-restrictive ramp metering	Lower than candidate 2 (.3)	Proportional to fuel reduced (0.3)	Reduced opposition compared to Candidate B (0.3)
4. Motorist information	Moderate (0.4)	Proportional to fuel reduced (0.4)	Generally well accepted by public (0.8)
5. Motorist service patrol	Moderate (0.3)	Proportional to fuel reduced (0.3)	Well accepted by public (0.9)
6. Real time on-board and transit stop information	Little impact (0.1)	Little impact (0.0)	Well accepted by transit passengers (0.5)
7. Transit signal priority	Modest impact (0.3)	Little impact (0.1)	Transit time reliability improvement appreciated by transit users. Little impact on motorists (0.3)

Table 3.7 Utility values for selected ITS classes

This analysis uses two types of variables. RIA denotes the relative importance of attribute A and UAS represents the utility of alternative S for attribute A. RIA may be developed by stakeholder consensus. The sum of these values for all attributes must equal unity. The attributes in the example are described by the categories shown in Table 3.5.

Table 3.7 lists the parameter values in parentheses under the attribute and utility designations. The first row of the table identifies examples of the attribute value. The following rows show examples of the utility values.

The first attribute column in Table 3.7 represents the reduction in traveler cost. Delay, fuel cost, and accidents are major components of this cost. The second attribute column represents emission reduction. As described in Chap. 4, for many ITS treatments emission reduction is proportional to motorist delay. The third attribute column is the utility for traveler satisfaction with the treatment.

The candidate alternatives, except for candidates 6 and 7 are discussed in later chapters

Alternative ITS project classes (S)	Multivariate utility value (MUs)
Improved incident clearance	0.76
2. Restrictive ramp metering	0.42
3. Non-restrictive ramp metering	0.30
4. Motorist information	0.48
5. Motorist service patrol	0.42
6. Real time on-board and transit stop information	0.16
7. Transit signal priority	0.26

Table 3.8 Multivariate utility values for example

Examples of utility values (U_AS) are shown in parentheses in the cells that denote the ITS treatments. Values for these measures may be obtained by simulation techniques or inferred from evaluations performed by other ITS projects. Maccubbin et al. [23] provides a compilation of ITS benefits.

The multivariate utility values for each alternative S (MU_S) are given by

$$MU{S} = \sum{A=1}^{3} RI{A} \cdot U{AS}$$ (3.5)

The multivariate utility analysis values for each alternative for the example are given in Table 3.8.

In most cases the utilities for alternatives selected for this analysis may be added if more than one alternative is chosen for inclusion, in some cases (e.g. candidates 2 and 3) a choice between alternatives is required.

The cost of alternatives may be treated in the following ways in connection with utility analysis:

As an attribute. This can be done by the addition of a column in Table 3.7
As a divisor for the MU_s values in Eq. (3.5)
· As an abscissa value in a utility vs. cost plot

In a number of cases, the alternatives may share certain ITS components, thus the cost for a combination of alternatives may be lower than for each alternative taken separately. Thus it is often desirable to define alternatives that take advantage of this. For example alternatives 1 and 4 in Table 3.8 share components such as communications and management centers.

3.3 Alternatives for Functional Design

Design alternatives are required because

Systems engineering methodologies [23] generally require an alternatives analysis to insure that the design options are considered in the context of project objectives and constraints. A "do nothing" alternative is also usually considered and often constitutes the baseline for of benefits for the various design alternatives.

To obtain federal aid for a project, Title 23, Section 940.11 of the Code of Federal Regulations requires the completion of a systems engineering analysis that includes alternative systems configurations and technology options to meet requirements.
Many of the states and other agencies responsible for the design and operation of highway projects and ITS require an alternatives analysis in their project design process (see Ref. [24] for example).

Two classes of alternatives may be considered:

Alternative high level ITS project classes As discussed in Sect. 3.2.2, constraints on regional ITS budgets may require the selection of a subset of projects from the set of alternatives. The first column of Table 3.8 describes the alternatives that were considered for the example.
Project class design alternatives Alternatives may include the types of technologies to be included, the intensity of implementation (e.g. how many point detectors to include in a roadway section) and functional equipment placements (e.g. the best location for a dynamic message sign).

3.3.1 Design Constraints

Design constraints limit the selection of components and operations that are suitable for the project. Reference [25] provides the following discussion of constraints:

"The fulfillment of goals and the approaches to satisfy specific functional requirements are often constrained by resource, institutional and legacy issues. In some cases the necessity to resolve problems may justify the relaxation of constraints. Absent this situation, the use of constraint analysis has the potential to simplify the selection of design alternatives by eliminating alternatives lying outside constraint boundaries". Some of the more common constraints are:

Resource Constraints

Capital funding.
Funding for operations.
Funding for maintenance.
Staffing levels and capabilities.

Reference [24] identifies constraints as part of the project development process. Federal regulations require that both long range and short range plans be financially constrained to reflect revenues reasonably expected to be available over the time period they cover [26].

Institutional Constraints

Funding through long term planning processes.
Requirements to use agency specific standard specifications.
Requirements to use National ITS Architecture standards and protocols.
Requirements to provide interoperability with other ITS in the same jurisdiction or other jurisdictions.
General design constraints.
Preservation of existing utilities.
Right-of-way constraints.
Economic, social, environmental and community considerations.

Legacy Constraints

Requirements to use existing equipment to the extent possible.
Requirements for new equipment to be compatible with existing equipment.

Early identification will result in either of the following situations:

The potential benefits of the project or design approach indicate that a serious attempt be made to relieve the constraint.
The project must be subject to the constraints. These constraints may eliminate some alternatives from further consideration.

3.3.2 Relationship of ITS Management Concepts to Objectives

Chapter 2 described general objectives that may be considered as candidates for a project. Table 3.9 shows how these objectives are related to a number of ITS freeway management concepts. This table may assist in developing candidate concepts and alternatives for the project.

While Table 3.9 shows the types of management concepts available to address objectives, another key functional design issue is the intensity of deployment for ITS treatment. Delay increases with volume-to-capacity ratio (e.g. Fig. 4.4) and the capability for a particular ITS treatment to reduce this delay also increases with volume-to-capacity ratio (q/C). Because higher q/C situations provide greater benefits for a given cost, deployments for those cases will provide higher benefit-to cost ratios. This is conceptually illustrated in Fig. 3.7, which shows that as the volumeto-capacity ratio increases, a given investment not only provides greater benefits but also a level of benefits that cannot be obtained at any investment level for lower a lower volume-to-capacity ratio.

Reference [24] describes an approach to categorizing traffic levels so that ITS deployment intensities may be selected to implement the concepts of Fig. 3.7. These levels are defined as follows:

• Level 3—A continuous section of roadway in one direction that includes peak hour level of service D or worse traffic for at least one half of the section.

Table 3.9 Relationship of ITS freeway management concepts to general objectives

| security
performance
evaluation
√
√
√
√
√
√
√
√
√
√
assistance
Motorist
√
√
√
√
√
√
√
Information
system
√
√
√
√
√
metering
Ramp
√
√
√
√
√
√
√
information
Traveler
√
√
√
√
√
√
√
√
√
√
√
√
√
incident
tracking
√
√
√
√
√
√
√
√
√
√
√
techniques
detection
√
√
√
√
√
√
√
√
√
√
—significant
Special traffic management functions
—spot
Traffic information on roadway
Serve as a corridor link in a wider
Serve as a diversion route in local
Major roadway reconstruction
Minor roadway construction
—spot
—
Non recurrent congestion
Non recurrent congestion
High occupancy vehicles
Reduce congestion/improve
Over significant section
Reduce emissions and fuel
Recurrent congestion
Recurrent congestion
significant section
area highway system
Reduce accident rate
construction
consumption
section
travel time
Spo |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | t
corridor
Objective
(b)
(d)
(b)
(b)
(d)
(a)
(c)
(a)
(a)
(c)
1.
2.
3.
4.
5.
6. | Management concept | Recurrent | Non-recurrent
congestion | | Road | and management
Data collection | ITS equipment
Monitoring of | --------------------|------------|-----------------------------|--|---------|-----------------------------------|--------------------------------| | congestion | detection and | | weather | for planning and | and inventory
management, | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |

	(e)Information on weather conditions, parking, special events, road weather		√	√		√		√
	Traffic management for future major roadway reconstruction (f)	√	√	√				√
	Motorist information about detour routes (g)			√
7.	Interoperability of ITS
	Operator efficiency (a)	√	√	√		√
	Stakeholder involvement (b)	√	√	√	√	√	√	√	√
8.	Improvement of NYSDOT operations
	Planning and/or evaluation data collection (a)	√			√	√		√
	(b) ITS equipment monitoring							√	√
	Efficiency of operations (c)					√			√
	Reduction of operating and/or maintenance cost (d)					√		√	√
9.	Provide assistance to disabled motorists		√				√
10.	Provide travel information related to tourism			√		√
11.	Security
	Transportation system security (a)								√
	Emergency operation (b)		√	√		√			√
	(c) Information system security								√
12.	Commercial vehicle operations			√

Table 3.10 Representative implementation characteristics for freeway ITS

Capability	Level 1—minimal	Level 2—moderate	Level 3—intensive
TMC site and staffing	Minimal site cost. May be part time or partial permanent staff	Moderate site cost. May be part time or full time staffing	Full time staffing
Computer system for central management of key ITS functions	May be a computer to provide a low level of management capability	Usually	Yes
CCTV coverage	Minimal	Significant	Full
Roadway mainline detector complement (point or probe detectors)	Typically none	Not continuous	Usually continuous
Dynamic message signs	Appropriate locations, possibly at major diversion points	Diversion locations and other key locations	Diversion locations, periodic intervals, possibly at key entry locations
Service patrols	Sometimes	Often	Yes
Ramp metering	None	Rarely	Frequently

Level 2—A continuous section of roadway in one direction that includes peak hour level of service C or worse traffic for at least one half of the section. Conditions worse than level of service C may be present at scattered spot locations or for small sections. In this case, it may be appropriate to increase the concentration of field equipment at these locations.
Level 1—Traffic conditions better than Level 2.

Table 3.10 [24] indicates the general deployment intensity of ITS devices or operations commonly implemented by many ITS and that generally conform to the benefit-cost concepts of Fig. 3.7.

Chapters 4 and 5 provide more detailed application factors for equipment deployment as a function of traffic level.

References

1. May AD (1990) Traffic flow fundamentals. Prentice-Hall, Englewood Cliffs, NJ
2. Wardrop JG (1952) Some theoretical aspects of road traffic research, Road Paper 36. Proc Instn Civ Engrs Pt 2(1): 325–378
3. Drake JS, Shofer JL, May AD Jr (1967) A statistical analysis of speed-density hypotheses. Highway Research Record 154. Transportation Research Board, National Research Council, pp 53–87
4. Highway capacity manual (2000) Transportation Research Board, National Research Council, Washington, DC
5. Lomax T, Turner S, Shunk G (1997) Quantifying congestion. NCHRP Report 398. National Academy Press, Washington, DC
6. Peeta S et al (2000) Content of variable message signs and on-line driver behavior. In: 79th annual meeting of the Transportation Research Board, Washington, DC
7. Traffic assignment manual (1964) Bureau of Public Roads, U.S. Department of Commerce, U.S. Government Printing Office
8. Ullman GL, Dudek CL, Balke KN (1994) Effect of freeway corridor attributes upon motorist diversion responses to travel-time information. Transportation Research Record No. 1464. Transportation Research Board, pp 19–27
9. Jindahra P, Choocharukul K (2013) Short-run route diversion: an empirical investigation into variable message sign design and policy experiments. IEEE Trans Intell Transport Syst 14(1):388–397
10. Schroeder JL, Demetsky MJ (2010), Evaluation of driver reactions for effective use of dynamic message signs in Richmond, Virginia. Virginia Transportation Research Council Report VTRC 10-R16
11. Deeter D (2013) A sign of the times. ITS International, July/Aug 2013
12. Dudek CL (2004) Changeable message sign operation and messaging handbook. Federal Highway Administration Report No. FHWA-OP-03-070. Federal Highway Administration, Washington, DC
13. Wardrop JG (1952) Some theoretical aspects of road traffic research. In: Proceedings of the institute of civil engineers, part II, vol 1, pp 325–378
14. Neudorff LG et al (2003) Freeway management and operations handbook. Federal Highway Administration Report FHWA-OP-04-003. Federal Highway Administration, Washington, DC
15. Performance measures of operational effectiveness for highway segments and systems—a synthesis of highway practice (2003) NCHRP Synthesis 311. Transportation Research Board, Washington, DC
16. Gordon R (2012) Methodologies to measure and quantify transportation management center benefits. Report FHWA-HRT-12-054. Federal Highway Administration, Washington, DC
17. Lee DB Jr (2004) Making the case for ITS investment. In: Gillen D, Levinson D (eds) Assessing the benefits and costs of ITS. Kluwer Academic, Norwell, MA
18. Gordon RL, Tighe, W (2005) Traffic control systems handbook. Federal Highway Administration Report FHWA-HOP-06-006. Federal Highway Administration, Washington, DC
19. Levinson D et al (2004) Measuring the equity and efficiency of ramp meters. University of Minnesota, Minneapolis, MN
20. Brand D (2004) Benefit measures, values, and future impacts of ITS. In: Gillen D, Levinson D (eds) Assessing the benefits and costs of ITS. Kluwer Academic, Norwell, MA
21. Wang Z, Walton CM (2008) A multi-attribute utility theory approach for ITS planning. In: 87th annual meeting. Transportation Research Board, Washington, DC
22. Levine J, Underwood SE (1996) A multiattribute analysis of goals for intelligent transportation systems planning. Transport Res C 4(2):97–111
23. Maccubin RP et al (2003) Intelligent transportation systems benefits and costs: 2003 update. FHWA Report FHWA-OP-03-075. Mitretek Systems, Inc., Washington, DC
24. Project development manual, Appendix 6. New York State Department of Transportation, Appendix 6https://www.nysdot.gov/portal/page/portal/divisions/engineering/design/dqab/pdm
25. Gordon RL (2003) Systems engineering processes for developing traffic signal systems. NCHRP Synthesis 307. Transportation Research Board, Washington, DC
26. Smith SA (1998) Integrating intelligent transportation systems within the planning process: an interim handbook. Report FHWA-SA-98-048. Federal Highway Administration, Washington, DC

Chapter 4 Non-Recurrent Congestion: Improvement of Time to Clear Incidents

Abstract The greatest benefit that freeway ITS can provide is to assist in the reduction of the time that it takes emergency responders to clear incidents and restore normal traffic operations. This chapter describes the ways that ITS can facilitate these operations and the benefits that result. Guidance for the field location of ITS components is provided. The chapter covers the following:

• Stages of an incident
• Effects of incident on roadway capacity and models of delay resulting from an incident
• Relationship of incident clearance time to delay
• Adaptation of delay models to local traffic data
• Design functions and technologies to assist in incident management
• CCTV coverage requirements and camera placement guidelines
• Traffic detector technologies and placement guidelines
• Improvement of traffic management center support of incident management
• Evaluation of incident management effectiveness

4.1 Definition of an Incident for ITS Design Purposes

A traffic incident is an unplanned, non-recurring activity on or near the roadway that causes a reduction of roadway capacity or an abnormal increase in demand. Such events include traffic accidents, disabled vehicles and spilled cargo. Highway maintenance and reconstruction projects are sometimes considered as incidents, but our definition excludes these activities. Emergencies such as natural disasters and terrorist attacks are also unplanned; and they can cause a reduction of capacity or an abnormal increase in demand. Their impacts and management requirements, however, extend well beyond the roadway.

The National Incident Management System (NIMS) is a comprehensive, national approach to incident management that is applicable at all jurisdictional levels and across functional disciplines. Appendix G summarizes the NIMS approach to managing incidents and provides a commonly used incident classification scheme.

Figure 4.1 shows the periods for the various incident phases [1]. Table 4.1 provides the definitions for the phases [1].

The ITS issues for incident management are discussed in Sect. 4.5.

Fig. 4.1 Incident timeline

Table 4.1 Key incident times

Incident phase	Duration	Definition
Detection time	T1−T0	The time between the incident occurring and the incident being reported. Detection time is typically not reported because the actual time the incident occurred is often unknown
Verification time	T2−T1	The time between the incident being reported and the incident being verified
Response time	T4−T2	The time between the incident being verified and the responder arriving on scene. Law enforcement may not be the first party to arrive on scene. Response time depends on the incident location and each responding party's proximity to the incident
Roadway clearance time	T5−T1	The time between the first incident report and the first confirmation that all lanes are available for traffic flow
Incident clearance time	T6−T1	The time between the first incident report and the time that the last responder left the scene

4.1.1 Effect of Incidents on Capacity

The effect of capacity reduction on a freeway is far greater than the physical reduction of roadway width. This effect is shown by Lindley [2] in Table 4.2.

4.1.2 Secondary Accidents

Secondary accidents are accidents that result from an existing primary incident. Many times these accidents occur at the end of queues that result from the primary incident. Raub [3] estimates that more than 15 % of the crashes reported by the police may be secondary accidents. Reducing the duration of queues resulting from incidents not

			Lanes blocked
Number of freeway lanes in each direction	Shoulder disablement	Shoulder accident	One	Two	Three
2	.95	.81	.35	0	N/A
3	.99	.83	.49	.17	0
4	.99	.85	.58	.25	.13
5	.99	.87	.65	.40	.20
6	.99	.89	.71	.50	.25
7	.99	.91	.75	.57	.36
8	.99	.93	.78	.63	.41

Table 4.2 Fraction of freeway section capacity available under incident conditions

Source: From Transportation Research Record 1132, Trransportation Research Board, National Research Council, Washington, DC 1987. Table 1

only reduces delay to motorists due to the incident but also results in a reduced rate of secondary accidents and consequent reduction in the total accident rate.

The Virginia Department of Transportation Operations Manual [4] identifies an incident as a secondary incident when it occurs within 4.5 miles upstream of the primary incident and in the same direction. The secondary incident also must occur within 30 min of the end time of the primary incident.

According to a study of 3,425 incident records by Murthy et al. [5], when incidents are not identified by TMCs and messages are not posted on DMS, secondary incidents are 2.33 times more likely to occur as compared to when these ITS management concepts are employed.

4.1.3 Work Zone Accidents

The difference between normal driving conditions and the conditions that the driver experiences when approaching and travelling in work zones provides the opportunity for additional accidents. In 2003 there were 1,028 fatalities and more than 40,000 injuries in work zone crashes in the U.S. [6]. Antonucci et al. [6] indicate that ITS related strategies and demand management programs to reduce to reduce volumes through work zones will reduce the number of crashes. The diversion strategies, motorist information, lane control and speed management strategies discussed in this book provide the basis for implementing these strategies.

4.2 Models of the Effects of Freeway Incidents

Deterministic queuing models are often used to analyze the delay and timeline associated with freeway incidents that restrict the capacity to below the demand volume. An example of a simple model is shown in Fig. 4.2. While models of this type do

Fig. 4.2 Delay and timeline model for incidents

not capture all of the details of the dynamic traffic flow characteristics, they provide approximations that are sufficiently accurate for design and evaluation purposes.1

The time for the queue to dissipate after the incident is cleared is given by:

$$T{D} = (q{2} - q{3}) \cdot T / (q{1} - q_{2})$$ (4.1)

where

q1=Volume at incident clearance (roadway capacity)

q2=Volume entering incident location (demand volume)

q3=Volume when incident is present (restricted capacity resulting from incident)

T=Time from start of incident to incident clearance

The line q2 in the figure represents the number of vehicles that enter the incident location while q1 and q3 depict the number of vehicles that are released from the incident location. The vertical distance between q2 and either q3 or q1 represents the number of vehicles in the queue. QC is the queue length at the time the incident is cleared. DI, the delay until incident clearance, is calculated as

$$D{1} = (q{2} - q_{3}) \cdot T^{2} / 2 \tag{4.2}$$

The delay from incident clearance to queue dissipation is given by

$$D{Q} = (q{2} - q{3})^{2} \cdot T^{2} / (2 \cdot (q{1} - q_{2}))$$ (4.3)

¹The model and the related model discussed in Sect. 4.3 do not incorporate the delay resulting from the additional vehicles delayed by the upstream propagation of the tail of the queue.

Fig. 4.3 Vehicle hours of delay vs. time to clear incident

Total delay is

$$\begin{split} D{T} &= D{T} + D{Q} \ D{T} &= (q{2} - q{3}) \cdot T^{2} / 2 + (q{2} - q{3})^{2} \cdot T^{2} / (2 \cdot (q{1} - q{2})) \end{split} \tag{4.4}$$

A more complex model that includes a period of total closure is provided by Morales [7].

Figure 4.3 shows an example of incident delay as a function of the time to clear an incident blocking one lane of a roadway with three lanes in one direction for a typical peak hour condition without recurrent congestion. Figure 4.4 shows incident delay as function of volume to capacity ratio for the freeway upstream of that incident

There is considerable variation in the accident clearance time data provided by different agencies. Osbay and Kachroo [8] provide data obtained in Northern Virginia for different types of incidents. For example, an analysis of lane blocking incident data on freeways in Long Island, NY prior to the installation of ITS showed that the average time to clear as 49.6 min, and data for similar conditions in the Atlanta area prior to ITS installation showed a 64 min period [9].

Sections 4.1 and 4.2 show that the delay corresponding to an incident varies significantly with the number of lanes that the facility has, the lane blocking effects of the incident, the time for the incident to be cleared and the demand volume in the absence of an incident. The practical evaluation of ITS improvements requires a relatively simple model that embeds these variations. Sections 4.3 and 4.4 describe an approach to the development of such a model.

Fig. 4.4 Delay vs. volume to capacity ratio upstream of incident

4.2.1 Frequency and Severity of Incidents

The evaluation model described in Sect. 4.4 requires a value for the blockage time and severity (capacity reduction) of a representative incident. It also requires a value for the frequency of the incident (number of incidents per million vehicle miles). A model is shown in Fig. 4.5 that provides some of the required information.

The model does not contain information on incident frequency. Furthermore, the model shows wide variations in incident duration. While a good deal of this variation is likely due to differences in reporting styles, and even in the definition of an incident, a more appropriate approach for practitioners is to provide a model and procedure that may be calibrated on a local or area-wide basis. The model structure in Fig. 4.6 was developed by the New York State Department of Transportation (NYSDOT), and provides a framework for agencies responsible for freeway management operations to calibrate the model using locally obtained data [11]. The model treats accidents and non-accident incidents separately, thus enabling the widely reported accident rate data to be used directly. The model considers a section as the roadway portion between the centers of two interchanges. The data shown in the figure is based on observations in several upstate New York metropolitan areas. Since lane-specific data for incident blockage duration was not available from the NYSDOT incident data, Fig. 4.6 employs data from Kittleson and Vandehey [12] for this purpose.

Fig. 4.5 Composite profile of reported incidents by type [10]

4.2.2 Data Collection for Development of Incident Model

Experience has shown that in many cases, historic data from the incident logs commonly provided by traffic management systems are often not provided with sufficient fidelity to enable non-accident incident rates and durations to be obtained. For example, the development of Fig. 4.6 required the documentation of data in more detail and in a different format than that provided by normal operation of the traffic management system. It is therefore recommended that a separate data set be collected for this purpose by traffic management center operators who have been

Fig. 4.6 Incident model structure

briefed on the model and its data collection requirements. This data set should be based on CCTV observations.

Data collection will be required for a number of sections to provide a sufficient data sample for analysis. The parameters required for analysis are:

· Roadway Section ID
· Incident ID
· Roadway direction
Date
· Time incident detected
· Time incident cleared
• Accident or non-accident incident
• Shoulder or moving-lane incident
• Number of lanes closed
• Duration of lane closure

4.3 Relationship of Reduction in Delay to Reduction in Incident Clearance Time

The area abcd in Fig. 4.7 shows the effect on delay of a reduction in the time to clear the incident.

Equation (4.4) shows that the total delay is proportional to the square of the time interval from the start of the incident until incident clearance. Thus, (4.4) may be rewritten as:

$$D_{T} = K \cdot T^{2} \tag{4.5}$$

The effect on delay of small changes in the time to clear the incident is given by the derivative of DT with respect to T as

$$dD_{T} / dT = 2 \cdot K \cdot T \tag{4.6}$$

The ratio of change in delay to incident clearance time is

$$(1/T) \cdot (dD_T/dT) = 2 \cdot K \tag{4.7}$$

From this equation it is seen that a small percentage change in the reduction in the time to clear the incident results in twice that percentage of delay reduced.

Fig. 4.7 Delay reduction resulting from reduction in incident clearance time

rapid incident clearance

Fig. 4.8 Example of peak period reduction in delay as a result of reduction in time to clear incident

Fig. 4.9 Example of off-peak period reduction in delay as a result of reduction in time to clear incident

An example of the reduction in delay due to reduction in incident clearance time is shown in Fig. 4.8. It was computed using (4.4) by taking the difference of the delay prior to and after the reduction in incident clearance time. A similar graph for off-peak period incidents is shown in Fig. 4.9.

4.4 Interaction of Capacity Restrictions and Traffic Conditions

Because an incident may occur at any time, the impact on delay will depend on the volume at that time and the residual capacity as shown in Table 4.2.

Incident models of the types shown in Figs. 4.5 and 4.6 provide the basis for assigning a probability of occurrence to each blockage time. A general plan for developing a model for average incident delay is shown in Fig. 4.10. The plan depicts an approach that groups the likelihood of incidents into volume to capacity ratio based groups or "cohorts" that represent the effect of various types of incidents. Delay is computed for each cohort, and then the cohorts are assembled into the final delay estimate. Sections 4.4.1 and 4.4.2 discuss the details of the approach.

4.4.1 Cohort Model

In order to estimate the percentage of traffic at each volume to capacity level, the representative hourly traffic volumes may be classified into "cohorts" designed to capture the effect of the various lane blockage scenarios [11]. For example, for a freeway with three lanes in each direction, the cohorts for a single lane blockage

Fig. 4.10 Flow diagram to develop incident delay for freeway with three lanes in each direction

Cohort number	Volume to capacity ratio range in cohort	Representative volume to capacity ratio used in analysis
1	0.7	0.8	0.8
2	0.7≥q/C≥0.49	0.6
3	0.49≥q/C≥0.17	0.33
4	0.17≥q/C≥0	0.1

Table 4.3 Cohorts for freeway with three lanes in each direction

Fig. 4.11 Relationship of cohorts to volume profile

may be classified as shown in Table 4.3. Notice that the cohort range definitions (.49 and .17) correspond to the blocked lane capacities shown in Table 4.2.

The last column of the table provides a volume to capacity ratio characteristic of the cohort and that will be used in the computation of delay. Figure 4.11 shows the relationship of these cohorts to a typical weekday freeway volume characteristic. To develop the model, the hourly volumes are assigned to the proper cohort and summed. The data are then used to identify the fraction of the AADT that is present when different lane blockages occur.

Figure 4.12 shows an example of the worksheet used to develop the fraction of the AADT that is in each cohort. The figure shows the computation for a three-lane roadway.

Hourly volume for each roadway direction is entered into the worksheet along with the capacity for the roadway segment. The volume to capacity ratio is computed by the worksheet. The worksheet then sorts the volumes into cohorts using the cohort definitions in Table 4.2. The sorted volumes for each hour are then summed over the day to determine the daily volume for each cohort.

							COMPUTATION OF COHORT FRACTIONS (THREE LANE ROADWAY)

	Data entry required

		Roadway Segment				I-490 from I-390 to Mt. Read Blvd.									Cohort Volumes for
Beginning		Direction		Est Cap	eastbound	westbound		Cohort Volumes for Lane Blocking Incidents							Shoulder Accidents
Hour	Eastbound	Westbound	Total	way 1	v/c	v/c	eb	eb	eb	eb	wb	wb	wb	wb	eb	wb
							cohort 1	cohort 2	cohort 3	cohort 4	cohort 1	cohort 2	cohort 3	cohort 4	v/c>= .83	v/c>= .83
12:00 AM	284	671	955	6300	0.045	0.107	0	0	0	284	0	0	0	671	0	0
1:00 AM	164	519	683	6300	0.026	0.082	0	0	0	164	0	0	0	519	0	0
2:00 AM	164	490	654	6300	0.026	0.078	0	0	0	164	0	0	0	490	0	0
3:00 AM	222	468	690	6300	0.035	0.074	0	0	0	222	0	0	0	468	0	0
4:00 AM	441	519	960	6300	0.070	0.082	0	0	0	441	0	0	0	519	0	0
5:00 AM	1550	842	2392	6300	0.246	0.134	0	0	1550	0	0	0	0	842	0	0
6:00 AM	3831	2088	5919	6300	0.608	0.331	0	3831	0	0	0	0	2088	0	0	0
7:00 AM	5830	2769	8599	6300	0.925	0.440	5830	0	0	0	0	0	2769	0	5830	0
8:00 AM	4714	2300	7014	6300	0.748	0.365	4714	0	0	0	0	0	2300	0	0	0
9:00 AM	2751	1869	4620	6300	0.437	0.297	0	0	2751	0	0	0	1869	0	0	0
10:00 AM	2182	1832	4014	6300	0.346	0.291	0	0	2182	0	0	0	1832	0	0	0
11:00 AM	2142	2031	4173	6300	0.340	0.322	0	0	2142	0	0	0	2031	0	0	0
12:00 PM	2143	2180	4323	6300	0.340	0.346	0	0	2143	0	0	0	2180	0	0	0
1:00 PM	2201	2170	4371	6300	0.349	0.344	0	0	2201	0	0	0	2170	0	0	0
2:00 PM	2591	3064	5655	6300	0.411	0.486	0	0	2591	0	0	0	3064	0	0	0
3:00 PM	2869	4472	7341	6300	0.455	0.710	0	0	2869	0	4472	0	0	0	0	0
4:00 PM	2956	5282	8238	6300	0.469	0.838	0	0	2956	0	5282	0	0	0	0	5282
5:00 PM	2988	5148	8136	6300	0.474	0.817	0	0	2988	0	5148	0	0	0	0	0
6:00 PM	2151	2896	5047	6300	0.341	0.460	0	0	2151	0	0	0	2896	0	0	0
7:00 PM	1514	1905	3419	6300	0.240	0.302	0	0	1514	0	0	0	1905	0	0	0
8:00 PM	1261	1789	3050	6300	0.200	0.284	0	0	1261	0	0	0	1789	0	0	0
9:00 PM	1222	1659	2881	6300	0.194	0.263	0	0	1222	0	0	0	1659	0	0	0
10:00 PM	870	1207	2077	6300	0.138	0.192	0	0	0	870	0	0	1207	0	0	0
11:00 PM	505	1067	1572	6300	0.080	0.169	0	0	0	505	0	0	0	1067	0	0

Total =	47546	49237	96783			Total	10544	3831	30521	2650	14902	0	29759	4576	5830	5282
							cohort	fraction		Frac shoulder accidents with V/C>= .83			0.115
							1	0.263

							2 3	0.040
								0.623
							4	0.075

Fig. 4.12 Worksheet for computation of cohort fractions

Table 4.2 depicting the percentage of freeway capacity under incident conditions on the shoulder, shows that for three lane freeways, a q/C of .99 must be present for the incident to have an effect. Since this condition is uncommon for the volume profile of Fig. 4.11, that type of incident was not considered in the development of Fig. 4.12. The table does, however, show that shoulder accidents may develop congestion under some conditions in Fig. 4.11. Thus the analysis shown in Fig. 4.12 also identifies the fraction of the AADT for which shoulder accidents will influence delay. The volumes in the example represent a situation with no recurrent congestion.

The website http://www.springer.com/us/book/9783319147673contains the worksheet file Cohort Factors 3 Lanes file for Fig. 4.12.

4.4.2 Time Saved Per Incident

The cohort fraction data, such as that shown in Fig. 4.12 may be used in conjunction with the incident delay model in (4.4) to compute the delay for lane blocking incidents for each lane blocked scenario. These may then be used in conjunction with the percentage of incidents for which the lane groups are blocked (Fig. 4.6) to arrive at the average delay per lane blocking incident and shoulder accident. Building on the previous example, a worksheet example for this calculation is shown in Fig. 4.13. The website http:// www.springer.com/us/book/9783319147673 contains the worksheet file Average delay resulting from incident.xls with the parameters of Fig. 4.13 for the three-lane case.

Each of the four rows for each set of computations provides the delay computation for a cohort. The worksheet columns are described as follows. The data to be entered by the analyst is indicated by an asterisk.

• Column B*—The incident duration from inception to clearance. An incident duration of approximately 53 min (0.88 h) was used for this example.
• Column C*—Roadway capacity in one direction is 6,300 vph
• Column D*—Demand volume fraction is the representative q/C associated with the cohort. These were obtained from Table 4.3.
• Column E—Demand volume is the product of roadway capacity (Column C) and demand volume fraction (Column D).
• Column F*—The incident capacity fractions were obtained from Table. 4.2.
• Column G—The incident capacity is the product of the roadway capacity (Column C) and incident capacity fraction (Column F).
• Column H—The delay per incident is provided by the application of (4.4) to the data in the previous columns.
• Column I*—The fraction of the traffic in the cohort is obtained from the cohort fraction analysis (Fig. 4.12).
• Column J—The delay per incident for the cohort fraction is the product of the delay per incident (Column H) and the fraction of the traffic in the cohort (Column I). These are then summed over all cohorts for the type of incident to provide total weighted delay for the incident type.
• Column K*—The lane weighting represents the fraction of lane blocking incidents for the data set. It was obtained from Fig. 4.6 and must be entered by the user if changes are desired.

		AVERAGE DELAY RESULTING FROM INCIDENTS - 3 LANE ROADWAY
	Data Entry Required
Section		490	Section 61
A	B	C	D	E	F	G	H	I	J	K	L
	Duration	Capacity	Demand	Demand	Inc Cap	Inc.	Delay per Frac in		Del per	Lane	Weighted
	Hr		Vol	Vol	Fraction	Cap	incident	Cohort	inc. for	weighting for Delay
			Fraction				Veh hr		coh fraction this type		for
											Incidents
											Veh hr
	3Lanes 1 Lane Blocked

	0.88	6300	0.8	5040	0.49	3087	1928	0.263	507.1
	0.88	6300	0.6	3780	0.49	3087	342	0.039	13.3
	0.88	6300	0.33	2079	0.49	3087	0	0.623	0.0
	0.88	6300	0.2	1260	0.49	3087	0	0.075	0.0

							Total weighted delay		520.5	0.82	427
							per inc. type

	3Lanes - 2 Lanes Blocked

	0.88	6300	0.8	5040	0.17	1071	6378	0.263	1677.3
	0.88	6300	0.6	3780	0.17	1071	2177	0.039	84.9
	0.88	6300	0.33	2079	0.17	1071	484	0.623	301.2
	0.88	6300	0.2	1260	0.17	1071	76	0.075	5.7

							Total weighted delay		2069.1	0.14	290
							per inc. type
	3Lanes - 3 Lanes Blocked

	0.88	6300	0.8	5040	0	0	9757	0.263	2566.2
	0.88	6300	0.6	3780	0	0	3659	0.039	142.7
	0.88	6300	0.33	2079	0	0	1201	0.623	748.5
	0.88	6300	0.2	1260	0	0	610	0.075	45.7

							Total weighted delay		3503.2	0.04	140
							per inc. type





								Delay for average incident			857

Fig. 4.13 Worksheet for calculation of average delay resulting from incident

• Column L—The weighted delay for incidents is the product of the delay per incident for the cohort fraction (Column J) and the lane weighting (Column K).

The delay for the average incident is the sum of the weighted delays for each incident type. The saving in delay due to ITS measures may be computed by taking the difference in the worksheet computation for which incident duration (Column B) is entered prior to ITS project implementation and after its implementation. ITS measures that result in more rapid incident clearance are discussed in Sect. 4.4.4.

4.4.3 Classification of Incidents

Agencies commonly employ severity classifications for responses to incidents. For example, The Chattanooga Urban Area Metropolitan Planning Organization and the Chattanooga-Hamilton County Regional Planning Agency have devised a classification system [13] that is based on traffic flow, impact/delay, incident characteristics and types of responders. A Level 4 incident is one that typically is causing traffic delays of less than 30 min where traffic is only slightly impacted and can be relatively easily routed around the incident. A Level 3 incident is one lasting more than 30 min but less than an hour, and a moderate impact on traffic flow. Typically a Level 3 incident involves a collision without or with just minor injuries. A Level 2 incident is one lasting more than 30 min, but less than 2 h. In a Level 2 incident, the impacts on the flow of traffic are significant, and the incident probably involves injuries to motorists. With a Level 2 incident, traffic management is essential and site management involves significant interagency cooperation. A Level 1 incident generally tends to represent major events that close the roadway and cause major area-wide congestion. This classification system is typical of those employed by operating agencies.

4.4.4 Incident Management Approaches

Incident management by TMCs may employ the following approaches:

• Assist emergency service providers by improving their access to the incident, reducing incident clearance time and protecting the safety of emergency service providers. Many of the policies implemented by agencies responsible for incident management focus on this objective. FHWA provides guidance [14] and many state DOTs and other agencies have developed plans that address their needs. TMCs provide congestion and lane access information to emergency responders, provide lane information to motorists and assist emergency responders to establish incident related traffic control measures.
• Provide incident location and lane guidance to motorists to smooth necessary lane changes and to avoid secondary accidents. Active transportation and demand management techniques (Chap. 10) support this management measure).
• Reduction of demand at the incident location by encouraging the use of alternative modes such as parallel transit services under incident conditions. Managed transportation corridors (Chap. 11) may be used to implement this management measure.
• Reducing traffic demand at the incident by encouraging diversion at the geographic level that is appropriate to the management of the incident, depending on the severity of its impacts (Sect. 4.4.6).

Many agencies have developed a formal management structure for managing incidents. Table 4.4 [15] shows the classification of incident levels by Delaware DOT and Table 4.5 [15] shows the TMC incident management responsibilities and action items for the incident levels.

4.4.5 Distribution of Traffic for Incident Conditions

Traffic diversion is commonly used by operating agencies to manage non-recurrent congestion resulting from such incidents as crashes, vehicle disablements, spilled loads, roadway surface problems, construction, weather related issues and security concerns.

Figure 4.14 shows a simplified example of volumes on a freeway (solid line) and an alternate route (dashed line) under normal conditions and incident conditions. V5 represents the volume for the diverting traffic.

Table 4.4 Delaware DOT levels of response for planned/unplanned incidents/events

Level	mpact Area of i	Resources	(EOC) activation for unplanned mergency Operation Centers events E	Highest level of decision making	Examples
1	Site/area specific	Normal staffing.	No EOC Normal interagency — mmunication activation co	Normal operations	Day-to-day operations
2	District wide or multi-district	— mary agencies ment of ment greater expertise may be personnel and equip notified or activated mited re-assign needed. Pri Li	county EOCs may or may not be partially or fully activated. State mmunications, local/ EOC on notice Elevated co	chief traffic engineer/ operations managers District managers/	MAT incident; power road); major accident; closing of a other roads (i.e. blockage on main Traffic may need to be diverted to outage; bridge structural damage; large planned events (i.e., Dover road; injuries; isolated road flooding; HAZ Downs Races)
3	Multi-districts	agencies activated. Support US ACE). Contractors may ment of personnel mary WA, agencies notified. Federal —greater agencies notified (FH expertise needed. Pri ment be activated and equip Reassign	to county EOC and may be to state mmunications, mpacted local/county EOCs may DelDOT liaison required (i.e. shelter, mass care). man needs are State EOC may be partially or Higher elevated co EOC, if activated be activated if hu — fully activated i	department secretary Division director or	mes of rain MAT incident; Coastal storm; high volu or snow; major HAZ mited evacuation li
4	Statewide/ multi-state	Total activation of personnel agencies activated. Ongoing mary, contract, and support federal coordination ment. Pri and equip	DelDOT liaison to county EOC and state EOC if mpacted local/county and state state EOC activated — EOCs activated I	MA, or mbers Governor, DE Me Cabinet	m MAT incident; mass destruction; acts of terroris biological incident; weapons of Hurricanes; floods; blizzards; catastrophic HAZ

Table 4.5 Delaware DOT TMC responsibilities for incident management

		MC T
Level	Notification	Control	Monitor	Information	Resources/personnel	Preparedness/staging
1	and coordination mmunication Normal co	with districts to determine mmunicate ment, ms Normal operations ment syste (personnel, equip alternate routes transportation materials). Co manage	ment transportation manage Normal monitoring ms syste	Exchange Network [IEN]) media, and neighboring transportation agencies agencies, departments, mination to other Normal information (via the Information disse	ments Daily assign	Normal transportation m ment syste checks, SOPs followed manage
2	MC bridge/conference call requested and/ SOPs. Possible personnel per T or initiated, if Appropriate required	m based mmunicate with mpacted routes. Adjust mpact of incident/ districts to determine Set up and control of ment syste alternate routes transportation event. Co manage on i i	m ment activities of statewide syste event. Normal monitoring ms to concentrate on Redirect monitoring of transportation manage continues syste	MS), kiosks, website, variable message signs agencies, departments, mination to other Public relations, and Normal information MC, WT media via disse IEN (V	handle short and long Evaluate status to term events	tested and confirmed. m Staffing reviewed ment/syste Transportation ment manage equip
3	MC bridge/conference call requested and/ SOPs. Possible personnel per T or initiated, if Appropriate required	m based mmunicate with mpacted routes. Adjust Districts to determine mpact of incident/ Set up and control of ment syste alternate routes transportation event. Co manage on i i	m ment activities of statewide syste Monitoring and event. Normal monitoring m ms to concentrate on re-directing requests fro Redirect monitoring of transportation manage EOC and 911 centers continues. syste	MS), kiosks, website, variable message signs agencies, departments, mination to other public relations, and Normal information MC, WT media via disse IEN (V	handle short and long accountability; assess term wants events mpacts of Evaluate status to personnel and situation on resources further i	mmunications with supervisors Co
4	MC bridge/conference call requested and/ SOPs. Possible personnel per T or initiated, if Appropriate required	m based mmunicate with mpacted routes. Adjust Districts to determine mpact of incident/ Set up and control of ment syste alternate routes transportation event. Co manage on i i	m ment activities of statewide syste Monitoring and ms to concentrate on event. Normal monitoring m re-directing requests fro Redirect monitoring of Manage EOC and 911 centers Transportation continues. Syste	station, variable message MC radio agencies, departments, mination to other MS), kiosks, public relations, and Normal information WT website, IEN media via signs (V disse	handle short and long accountability; assess term wants events mpacts of Evaluate status to personnel and situation on resources further i	and data safeguarded. MC, ms Prepare to evacuate ment syste and/or relocate T Transportation if necessary manage

Fig. 4.14 Volumes on freeway and alternate routes

Volumes on freeway and alternate route under normal conditions

Volumes on freeway and alternate under incident conditions

The lower drawing in Fig. 4.14 shows diversion under incident conditions. The heavy line section on the freeway indicates a possible region of queuing resulting from the loss of capacity. The diverted traffic volume V5 is subtracted from the freeway route and added to the diversion route.

A travel cost² may be associated with each travel link. The travel cost for an incident can be represented as the sum the travel times for all vehicles on the network from the start of the incident until normal traffic flow is restored. For the mainline link on which the incident occurs (Link AB), travel cost may be expressed as follows:

$$T{AB} = \sum{n=1}^{N} f(V1 - V5), RC)$$ (4.8)

$$C{AB} = K \cdot T{AB} \tag{4.9}$$

where

CAB is the cost of travel on link AB during the incident period

f is a function that depends on link inflow (V1-V5) during the incident period and on RC, the residual capacity of the freeway prior to incident clearance. Table 4.2 shows an example of RC.

K represents the value of time

n is the vehicle sequence on link AB during the incident period

N is the total number of vehicles on the link until incident clearance

$T_{AB}$ is the total travel time on Link AB during the incident period

The other links have similar cost functions, but without the residual capacity term. Figure 4.15 shows an example of the cost on the links and for the network under (a) incident free (normal) conditions, (b) an incident where the diversion has been excessive and (c) where the diversion is approximately optimum. In the latter case, less traffic has been diverted from the freeway, resulting in a higher cost on link AB

^<sup>2

Travel cost is usually taken to be the sum of travel time cost and out of pocket cost. For the current example, out of pocket cost is assumed to be largely independent of route choice.

Fig. 4.15 Example of costs under incident conditions resulting from diversion

but a lower overall network cost. The network cost under incident conditions is seen to vary significantly with diversion.

The diversion fraction DF at an exit ramp may be defined as follows:

$$DF = V{ED} / V{AD} - V{EW} / V{AW}$$ (4.10)

where

VAD is the volume upstream of the exit ramp when diversion is implemented at this ramp. VAW is the volume upstream of the exit ramp exit ramp volume when diversion is not implemented at this ramp. For diversion at a single ramp, VAW = VAD.

VED is the exit ramp volume when diversion is implemented at this ramp.

VEW is the exit ramp volume when diversion is not implemented at this ramp.

4.4.6 Geographic Levels of Diversion

The incident management levels such as those described in Sect. 4.4.4 are related to the severity and expected duration of the effects of the incident, construction or weather. It is also useful to classify diversion routes by levels that generally represent the geographical extent of the diversion route and the diversion location in advance of the incident. The type of information provided to motorists may be related to the geographic diversion level.

Three geographic levels of diversion are described, starting at the local level (Level 1), progressing to the area level (Level 2) and extending to the regional level (Level

3). By diverting the largest number of vehicles possible before they reach the location at which the local level comes into play, congestion and queuing at the incident site are minimized, as is overall corridor delay. This is conceptually shown in Fig. 4.16.

Figure 4.17 shows the conceptual relationship among diversion levels. Regional level diversion roadways are usually freeways, local level diversion roadways are usually surface streets, and area level diversion roadways may be either. At the area level, a significant traffic volume may not complete the trip on the diversion route, as other routes may be more convenient.

The following sections describe the characteristics of the three diversion levels.

Fig. 4.17 Relationship among diversion levels

4.4.6.1 Local Diversion (Geographic Level 1)

Diversion at this level is usually accomplished by diverting to surface streets at the exit ramp just upstream of the incident and returning to the freeway at the next entry opportunity. The diversion route is usually in close proximity to the freeway. While this diversion level is commonly associated with the actions of emergency service providers that may be needed to manage severe incidents including roadway closures, most incidents do not involve closures or other highly aggressive forms of management.

Because emergency service providers often participate at this level, police, traffic management agencies and other stakeholders are often active in the development of formal diversion plans. Figure 4.18 shows an example of a Level 1 traffic diversion operation requiring inter-agency cooperation.

Figure 4.19 shows an example of a formal diversion plan of this type for a freeway in Connecticut.

The Connecticut plan includes:

• Diversion route identification and location. In some cases trucks may require a separate route.
• Diversion signs at turns.
• Location of traffic signals.
• Location of police monitors.
• Emergency contact information.
• Special requirements.

Fig. 4.18 Example of traffic diversion operation (Source: Washington State DOT)

Fig. 4.19 Example of Level 1 diversion plan

Fig. 4.20 Permanent DMS with moderate strength message

Fig. 4.21 Example of alternate route trailblazers

Since the majority of incidents do not require this level of intervention, diversion is often implemented by ITS devices alone, with little or no police activity to implement diversion.

The most common methodology employed by operating agencies to influence diversion is the dynamic message sign (DMS). An example of a moderate strength message on a permanent DMS is shown in Fig. 4.20 [16]. Permanent DMS are sometimes supplemented with portable DMS for prolonged incidents or construction.

Diversion signs (trailblazers) may be used as shown in Fig. 4.19 to identify alternate routes. Figure 4.21 [17] shows a graphic of alternate route trailblazers. Colored markers are sometimes used to distinguish among multiple alternate routes.

Dynamic trailblazers are static signs with a section that may illuminated or otherwise changed to modify the message when diversion is in effect. Figure 4.22 [18] shows an example of a dynamic trailblazer. Under a "bypass" condition as shown in the upper variable panel, motorists are directed to the diversion route as indicated by the variable arrow. Under normal conditions, the "bypass" panel is blank and the arrow is pointed in the same direction as would a standard static route marker.

Fig. 4.22 Typical dynamic trailblazer assembly

4.4.6.2 Area Level Diversion (Geographic Level 2)

Characteristics of Area Level Diversion

Diversion routes at this level are often identified by the operating agency to enable diversion strategies and formats for motorist messages to be developed in advance of the diversion need. Diversion routes may consist, in whole or in part, of freeway routes, or may consist entirely of surface street routes. Multiple diversion routes may be employed. The motorist may be advised by means of highway information devices such as dynamic message signs (DMS) and highway advisory radio (HAR) as well as by private traffic information services. The state's 511 services may also be used for pre-trip and en-route information. A portion of the planned alternate route network may be used for a particular incident as shown in Fig. 4.23. The portion of the alternate route selected for diversion may change during the incident period as the queue changes.

The figure shows the portion of the diverted traffic that does not return to the freeway downstream of the incident.

Examples of Area Level Diversion Routes

An example of area level diversion routes in a section of an eastbound limited access highway corridor is shown in Fig. 4.24. This corridor section is in a suburban environment and consists of the eastbound sections of the Long Island Expressway (I-495) and the Northern State Parkway that lie between NY 135 and the Sagtikos

Fig 4.23 Example of Level 2 motorist diversion routing

Fig. 4.24 Area level diversion route alternatives in the Long Island Expressway Corridor

Parkway. The corridor section also has direct crossovers between the major eastbound routes and is approximately 11 miles long. The figure shows those movements that may be influenced by the diversion requirements. Similar Level 2 corridor sections are present to the west of the section shown.

An example of area level diversion that uses surface street alternate routes is shown in Fig. 4.25. It consists of a contiguous set of Level 1 sections. In the event of an incident, information may be used to divert motorists to the frontage road as

Fig. 4.25 Example of area level diversion routes using surface streets

an alternate (in any case, it is an obvious choice to motorists.) Incident management may call for a change in the signal timing plan on the frontage road to support diversion. Changes in the location of the end of the queue will result in diversion at different exit points. The appropriate diversion location will be described or implied by motorist information. As delays resulting from diverted traffic build up on the frontage road, motorists who are familiar with the local street system may choose de facto diversion routes such as the one shown by dashed lines, as well as others that are not shown.

Coordination of Area Level Diversion Plans

In some cases, area level diversion may require coordinated measures by more than one transportation management center (TMC) or more than one agency. Concepts of operation often provide the functional basis for such coordination. In certain locations, operating agencies may be members of a central agency charged with compiling, coordinating, and distributing traffic and incident data among member agencies as well as recommending coordinated response plans. For example in the New York City area TRANSCOM (Transportation Operations Coordinating Committee) operates an Operations Information Center for this purpose.

4.4.6.3 Regional Level Diversion (Geographic Level 3)

Major incidents are likely to cause long delays on the facility on which the incident occurs and on the area level alternates associated with this facility. Travelers whose destinations extend past the locations in the affected corridor may find their travel time reduced and travel reliability improved if they divert sufficiently upstream of the incident, even if such diversion adds considerably to the trip's distance. Limited access highways often constitute the diversion routes. An example of such a diversion is shown in Fig. 4.26. In this example, in the event of a major incident on

Fig. 4.26 Example of regional level diversion routes

westbound I-88, diversion of traffic originating or passing through the Albany/ Schenectady area and destined for the Binghamton, NY area or beyond might be appropriate. Although the diversion route consisting of I-90, I-481 and I-81increases the trip length from 104 to 169 miles, the congestion resulting from a major incident will, in many cases, result in greater travel time by remaining on I-88 than the additional time required for the diversion routing.

As with area level diversion, regional level diversion often requires the knowledge of traffic conditions from a number of operating agencies. In some cases regional organizations such as the I-95 Corridor Coalition provide traffic condition information to operating agencies and to the public.

4.5 Functional Requirements for Improving Incident Response and Relationship of Improvement Techniques

Traffic management centers implement the functions shown in Fig. 4.1 and discussed in Sect. 4.1.

Incident management is a multi-agency function involving a number of emergency responders. ITS and traffic management centers can assist in incident management by helping to plan management of incident, by providing surveillance and monitoring capability and by facilitating communication among incident responders. Table 4.6 describes a number of functions that can be provided by ITS and traffic management centers.

√

Stages of incident management Incident management function Detection and verification Response Clearance Recovery Coordinate development, archiving and update of incident response plans √ √ √ √ Integrate traffic incident management needs into operations planning and ITS design √ √ √ √ Detect an incident and identify its properties (lanes blocked, location) √ Classify incident into type and severity √ Notify responding agencies of location and character of incident √ Improve conventional traffic operations √ √ Select response plan. Implement: • Lane and ramp controls • Emergency signal timing plans • Motorist information √ √ √ Facilitate operations for emergency responders √ √ √ Provide traffic conditions and/or route guidance to emergency responders √ √ √ Provide incident information to motorists (see Chap. 5) √ √ √ Provide tail of queue detection √ √ √

Table 4.6 ITS and TMC related incident management functions

The relationship between incident management functions and a number of traffic operations and ITS technologies is shown in Table 4.7. Sections 4.5.1 and 4.5.2 discuss the effective application of certain of these operations and technologies. Chapter 5 discusses motorist information.

4.5.1 Improving Incident Detection and Verification

The following sections discuss commonly used approaches to incident detection and verification.

4.5.1.1 Public Service Access Points

Terminate incident management

functions

Most freeway incidents are detected by motorist cellular telephone calls to public service access points (PSAPs) providing 911 service. In many cases, this information is provided to traffic management centers on a data channel using filters to restrict the

Table 4.7 Traffic operations and ITS technologies for incident response

	Functions
	Incident			mergency E	Traffic information	Tail of	Termination
	detection and	Incident	Response plan	responder	mergency for e	queue	of incident
Operations and technologies	verification	classification	mentation mple i	operations	responders	detection	ment manage
CCTV	√	√	√	√	√	√	√
Traffic detectors	√		√		√	√	√
911 service	√	√
Traffic reporting service	√		√		√
Service patrols	√	√		√
Police services	√	√	√	√
MC information displays T	√	√	√
Lane controls			√
Ramp meters			√
ming plans mergency signal ti E			√
m mmand syste Incident co		√	√	√
me Surveillance and travel ti			√	√	√
on alternate routes
Traffic information for				√	√
mergency service providers e
In vehicle information for				√	√
mergency service providers e

Fig. 4.27 Benefit and cost of CCTV coverage

information to traffic related incidents. When the call originates from a vehicle involved in an incident, position information is automatically available. In some cases the information is suitable for verification, but in other cases other verification techniques (usually CCTV observation, police responses or motorist service patrols) are required.

4.5.1.2 CCTV

CCTV and traffic detectors may detect incidents more rapidly than other techniques such as 911 calls. CCTV provides the capability to identify the type of incident and its properties, thus providing verification as well as detection. This information may be used to determine the types of emergency services required. Verification by CCTV is often the fastest way to accomplish this function. In many cases, the number of CCTV cameras on the freeway far exceeds the number of monitors available in the traffic management center. When this occurs, automated camera "tours" are commonly employed to allow the operator to rapidly monitor large sections of the roadway.

Incidents that are not the result of accidents are generally distributed evenly along the roadway. Accidents more frequently occur within or near interchanges. Furthermore accidents generally require more time to clear. Thus the benefits for cameras are greatest when they are placed in the interchange area. Figure 4.27 shows the general relationship for cost and benefits of CCTV placement. Curve A in this figure represents the benefit as a function of percent coverage for the case where demand volumes are high. The concave shape results from the higher benefits of the cameras at or near the interchange area where the accident rate is generally higher than in the roadway portion away from the interchange. Curve B shows the benefits when the demand volume is lower (see Fig. 4.4 as an example of incident delay sensitivity). Curve C is the cost of installing CCTV cameras. Curve C is convex because as the percentage of the roadway covered increases, the likelihood of overlapping camera coverage increases. This increases the number of cameras employed per mile of roadway. For each deployment alternative (represented by a value for the roadway percent covered) the line segment between the benefits curve and the cost curve represents the net benefits. The net benefit can possibly become negative when excessive CCTV coverage is provided for low demand volume situations.

Reference [11] provides guidance for the initial consideration of camera locations as a function of traffic conditions. As discussed in Chap. 3, it defines traffic conditions in terms of deployment "levels" as follows:

• Level 3—A continuous section of roadway in one direction that includes peak hour level of service D or worse traffic for at least one half of the section.
• Level 2—A continuous section of roadway in one direction that includes peak hour level of service C or worse traffic for at least one half of the section. Conditions worse than level of service C may be present at scattered spot locations or for small sections. In this case, it may be appropriate to increase the concentration of field equipment at these locations.
• Level 1—Traffic conditions better than Level 2.

Guidance for the initial consideration of camera placement is shown in Table 4.8 [19]. Because the classification levels and application factors cover broad ranges of conditions, the consideration of deployment alternatives is recommended.

Appendix B describes a measure for the relative effectiveness (RTV) of CCTV coverage based on the fraction of incident periods observable by CCTV. An example of this measure for a particular roadway section is shown in Fig. 4.28. A worksheet (RTV) for computing RTV from section accident data is described in Appendix B and is provided on the website http://www.springer.com/us/book/9783319147673.

4.5.1.3 Traffic Detectors

Traffic flow at any point on the roadway is governed by the general traffic equation discussed in Sect. 3.1.1.1 and repeated below:

$$q = k \cdot u \tag{3.1}$$

where

q=volume (vehicles per hour per lane).

k=density or concentration (vehicles per mile per lane).

u=space mean speed (miles per hour).

Table 4.8 Considerations for preliminary location of CCTV cameras

Deployment level	Application factor
1	High accident rate locations. Other locations as deemed necessary
2	High accident rate locations, freeway-to-freeway interchanges, spot congestion locations. Other locations as deemed necessary
3	Continuous coverage (average 1.5–2.0 cameras per centerline mile)

Fig. 4.28 Incident periods covered vs. number of cameras

Point and probe detectors are discussed in the following sections. Point detectors can sense a sufficient complement of variables in each lane to enable the application of (3.1) to each sensed lane of traffic. Probe detectors essentially provide a sample of travel times from which speed may be computed for the sensed section. The probe technologies discussed in this section are generally not lane specific.

Point detectors

Point detectors sense lane volume, speed and lane occupancy at a particular location. All detector types do not necessarily sense all variables. Most point detectors can provide data for each traffic lane. Aggregation of detector data into the traffic parameters is performed periodically.

Detector technologies that are commonly used for freeway monitoring include:

• Inductive loop detectors (ILDs). The ILD provides measurements of lane volume and lane occupancy (the fraction of time that the vehicle occupies the loop in the pavement.) ILDs may be used in pairs or singly in a lane. When used in pairs, time mean speed may be accurately measured by the time between activations of each detector in the pair. This may be converted to space mean speed by means of (3.2) and density may be computed from (3.1). When used singly, in addition to volume, the ILDs sense lane volume and lane occupancy (the fraction of time that the vehicle spends over the inductive loop). When a single detector in each lane is used, in order to calculate speed an assumption must be made about the average vehicle length and the average apparent loop length. While many agencies use a constant coefficient for this value, Caltrans uses a "g" factor to relate occupancy to speed for each detector as a function of time of day as shown in (4.11) [20]. The following relationship of the g factor to speed is given by Jia et al. [21].

$$v(t) = g(t) \times \frac{c(t)}{o(t) \times T}$$ (4.11)

where

v(t) is the average time-mean-speed.
c(t) is the number of vehicles crossing the detector during the averaging period.
o(t) is the fraction of time that a vehicle is sensed.

T is the averaging period.

While probably the most accurate point detector type, the difficulty of maintaining inductive loop detectors over long periods of time has led some agencies to use non-pavement-invasive technologies that do not require lane closures for maintenance.

Frequency modulated continuous wave radar detectors. This type of detector has found increasing use because of its adequate performance and non-pavement\ninvasive feature. Volume and time-mean speed are usually detected quite accurately, however very slow speeds may affect performance.
Magnetometer detectors. Recent improvements in technology have resulted in a type of detector consisting of a battery powered magnetic sensor that is installed flush with the pavement and a wireless link to a roadside processor. Battery life\nis a function of traffic volume. Maintenance includes installing another sensor\nunit when the battery life is exceeded.
Video processing detectors. The need to clean and readjust these detectors from time to time as well as lighting, sun glint and weather considerations has encouraged some agencies to select alternative technologies for freeway applications.

Klein [22] discusses detector technologies in detail. Detector data is most commonly displayed in the traffic management center as a map presentation that is color coded according to speed. Closer detector spacing improves the location of the lower speed indications that may result from an incident. Using historical experience, operators often infer the presence of a potential incident, and use other means such as CCTV, 911 information, service patrols and police reports to confirm the incident and to provide additional information. Point detectors also provide information for other than incident detection functions as described in Chaps. 5–7. Reference [19] provides guidance for point detector spacing. For urban freeways with significant congestion, spacing of 0.3–0.4 miles (0.48–0.64 km) is recommended. A general approach for placing detectors is:

Identify sites for mainline stations required for ramp meters if they are to be employed.
Add additional stations so that mainline roadway portions between each entry and exit location has a station.
Add detectors so that gaps do not exceed 0.33 miles (0.53 km).
Modify detector locations to avoid very short spacing.

Typical spacing on freeways with ramp metering may average 0.25–0.33 directional miles (0.40–0.53 directional kilometers).

Traffic detectors often malfunction or provide data that is not accurate. In order to maintain the functionality of the applications requiring this data, freeway management systems often include techniques that identify malfunctioning detectors and synthesize data to replace the bad or missing data. List et al. [23] provide a detailed discussion of imputation concepts that use data from surrounding detectors.

Point detectors may be used for incident detection as described in the following sections.

4.5.2 Point Detectors For Incident Detection Without Incident-Detection Algorithms

Although other techniques such as CCTV, 911 calls and police reports are the primary sources on incident detection, many agencies use point detectors to help assist in incident detection. For example, map displays show the speed for zones in the roadway. The zone is usually defined as the approximate midpoint between the locations of two detector stations. While the display does not directly indicate an incident in the zone, an experienced operator, using his historical knowledge of expected traffic conditions, may often infer the possible presence of an incident, particularly when the incident occurs in off-peak periods. This tentative detection requires confirmation by other means.

When a traffic incident occurs that results in the demand upstream of the incident exceeding the remaining capacity of the roadway, a queue begins to form at the incident site, thus increasing density and reducing the speed upstream of the incident. The queue builds with time and causes a shock wave to propagate upstream of the incident. The time required for this shock wave to reach the traffic detector determines, in large measure, the time delay in the operator's ability to detect the incident in this way. The following discussion provides an example of how this time may be estimated. The equation for the velocity of propagation of the shock wave is [24]

$$W_{AB} = (q_A - q_B)/(k_A - k_B)$$ (4.12)

where k and q are as defined above. Subscript A identifies the conditions in the queue downstream of the shock wave boundary and subscript B describes the conditions upstream of the boundary.

The following is an example of the average incident detection time for point detectors when applied in this way. Figure 4.29 diagrams the propagation of the shock wave and describes the conditions found in the example.

The following parameters were used for the volume and density upstream and downstream of the incident

qA =1100 vehicles per hour.

qB =1600 vehicles per hour.

kA =110 vehicles per mile.

kB =26.7 vehicles per mile.

Fig. 4.29 Shock wave propagation for a bottleneck caused by an incident

Applying (4.12), a shock wave propagates upstream of the incident at a speed of 6 mph. If detector stations are spaced at intervals of 0.25 miles, the wave will take 2.5 min to travel that distance. Assuming that incidents are randomly spaced between detectors, an average propagation time of half of this value will result. To this must be added the time to smooth and process the detector data (typically 1 min). Figure 4.30 shows the average detection times for different detector spacing based on this example.

Since detection time depends on the incident scenario, it is useful to define a parameter B1 to represent the timely detection probability for a range of scenarios for different detector spacing. The models for incident management effectiveness discussed in Sect. 4.6.3 employ parameter B1. An example of a value set for B1 is provided by the following expression based on average point detector spacing.

0.4 mi≥spacing, B1=0.9.
0.7 mi≥spacing>0.4 mi, B1=0.7.
1.0 mi≥spacing>0.7 mi, B1=0.5.
2.0 mi≥spacing>1.0 mi, B1=0.3.
Spacing>2 mi, B1=0.1.
No detectors, B1=0.0.

4.5.3 Point Detectors With Automatic Incident-Detection (Aid) Algorithms

The previous section describes a manual technique for incident detection. Although not employed by most agencies, techniques that process point detector data have been used, with varying degrees of success, to alert the operator to the possible presence of an

Fig. 4.30 Example of average detection time

incident [4, 25, 26]. Criteria for assessing the quality of AID algorithms include detection rate, false alarm rate and time to detect. Based on these criteria, the performance of these algorithms has generally not measured up to that achievable by other means. Martin [25] concludes that "the use of video coverage on the freeway systems and everexpanding use of cell phones has made the need for AID algorithms less important."

Probe detection. Probe detection consists of determining the difference in arrival times of a vehicle at two pre-established locations. Some technologies use roadway equipment to establish these locations, other technologies may provide virtual locations. This process has been termed vehicle matching or vehicle re-identification. Common probe detection technologies include:

– Toll tags and toll tag readers. A high percentage of vehicles are equipped with toll tags in locations where toll facilities are commonly used. Vehicle matching techniques employed by public agencies protect the identity of the vehicle. The TRANSMIT system is a probe system based on the use of toll tag readers is an example of this approach. Test results showed the probability of incident detection to be approximately 89 % on the New York State Thruway and 72 % on the Garden State Parkway. False alarm probabilities ranged from 10–22 % on the New York State Thruway and from 16–32 % on the Garden State Parkway. In recent years the TRANSMIT system has been extended in the New York City metropolitan area, and to other locations on the New York State Thruway [27]. Incident detection time, and the precision with which an incident may be located depends on the distance between the locations used to estimate the travel times. In the case of infrastructure based readers, reducing this distance requires significant expenditure.

Private traffic information services based on GPS technology. With the motorist's permission and cooperation, cellular telephone communication or other communication techniques transmit the vehicle's location to a privately operated center for re-identification, development of speed, travel time and routing information. Cooperating motorists may also provide other information such as incidents, construction and weather conditions. In some cases, the firm combines the probe information with information from TMCs and other sources.
Bluetooth readers. Bluetooth is an open, wireless communication platform used to connect myriad electronic devices. Many computers, car radios and dashboard systems, PDAs, cell phones, headsets, or other personal equipment are, or can be, Bluetooth-enabled to streamline the flow of information between devices. The interconnection between Bluetooth devices is achieved through the transmission and acceptance of a 48-bit Machine Access Control, or "MAC", address between inquiring and receiving devices. A small transceiver is constantly transmitting its device-specific MAC address in an effort to find other devices with which to communicate. Once a Bluetooth device is connected to another, the transmission of this MAC address continues. Although duplicates may exist, manufacturers typically assign unique MAC addresses to Bluetooth-equipped devices. These unique addresses are not tracked or readily available when devices are sold within the marketplace, making them a personal informationfree identifier. The constant broadcast of these MAC addresses is detectable and measurable without establishing a relationship to personal or otherwise sensitive information, keeping the traveling public and their information anonymous. Matching the MAC addresses between two locations establishes the travel time between these locations. A general rule of thumb is to achieve three matched pairs every 5 min, or nine matched pairs per 15 min, 36 matched pairs an hour, or 864 per day [28]. Match rates ranging from 3.5 to 4.7 % were experienced on I-76 in Philadelphia [28].

While probe detection is most commonly used to provide travel times, it can provide incident detection capability through a comparison of current and historic travel time.

4.5.3.1 Motorist Service Patrols and Police

Motorist service patrols are available in many locations during significant portions of the work-week. They may be available at other times as well. Motorist service patrols not only detect and confirm incidents but also help clear minor incidents and assist other responders in incident clearance and traffic management.

Police patrols also detect and confirm accidents. Police are often the first responders when incidents have been detected.

In some cases, logs from other agencies may be used to assist in traffic management. Figure 4.31 [29] shows an example of an incident management log provided by the California Highway Patrol. Detailed information is shown in the lower portion of the figure for a particular incident.

Communication Centers	Se one ( GR	Resources ONE IT OK ated as of 3/15/201
Center No.	umber of Incidents:	6:49:08 A
☐ Auto Refresh Off List Map	16
Auto Reliesii Oli V List V Map
No. Time Type	Location	TBM/LATLON A
Details 003556:45 AM Trfc Collision-Unkn Inj	Sr121 / Sr128	38.445540 -122.1964
Details 000116:43 AM Trfc Collision-No Inj	Us101 S / Us101 S Lucky Dr Ofr	37.939346 -122.5163
Details 003526:41 AM Trfc Collision-No Inj	Us101 S / Us101 S Lucky Dr Ofr	37.939346 -122.5163
Details 000106:39 AM Reporting Car Fire	I280 S / I280 S Alemany Blvd Ofr	37.732277 -122.4149
Details 003506:38 AM Hit and Run No Injuries	3839 Emery St	37.828943 -122.2804
Details 000096:38 AM Traffic Hazard	1680 S / 1680 S Gold Hill Rd Ofr	38.185908 -122.1361
Details 00346 6:37 AM Car Fire	1280 S / I280 S Alemany Blvd Ofr	37.732277 -122.4149
Details 003456:34 AM Traffic Hazard	1680 S / 1680 S Gold Hill Rd Ofr	38.185908 -122.1361
Details 00007 6:26 AM Traffic Hazard	1880 N / 1880 N High St Ofr	37.763330 -122.2161 37.763330 -122.2161 -
Details 00333 6:24 AM Traffic Hazard	1880 N / 1880 N High St Ofr
Tris Callisian No Ini	Location: Us101 S / Us101 S Luc	kv Dr Ofr TBM/LatLon:
Incident: 00352 Type: Trfc Collision-No Inj	Location. Os10137031013 Euc	ky Di Oil TOWILGILOII.

Detail Information	-13
6:51 AM 9 [14] A34-010 4 LNS BLKD [Share	al	DV TV IS NOT
	IG RIG IS MOVEABLE,BUT DELIVE IS AT THIS TIME—PLZ KEEP CHP I	ROLLING [Shared]
6:44 AM 7 [12] 1039 MARIN CO FIRE [Share	ed]
6:44 AM 6 [11] LL FIRE [Shared]
6:43 AM 5 [3] UNK IF DELIVERY TK CAN M	OVE OO RDWY
6:43 AM 4 [2] BLKG SLOW LN
6:43 AM 3 [8] [2] BLKG LN # 3 [Shared]
6:43 AM 2 [1] BLU/WHI BIG RIG VS WHI DE	ELIVERY TK
6:42 AM 1 [7] [1] BIG RIG VS LARGE BOX M	MOVING TK [Shared]
Unit Information

Fig. 4.31 California Highway Patrol traffic incident information page

4.5.4 Improving Incident Response, Clearance and Recovery Through ITS

Agencies often classify incidents by severity and provide response measures according to these classifications.

4.5.4.1 Incident Response Plans

The coordination of incident response planning is generally accomplished by the stakeholders, often through a group or committee established for that purpose. The traffic management center's responsibilities typically include:

• Development a coordinated set of motorist information messages.

• Identification of suitable alternate routes and development of emergency signal timing plans to support diverted traffic.
• Operation of ancillary controls and displays such as lane control signals, blank out signs and dynamic trail-blazers.

Figure 4.32 [30] shows how a selection of a response plan is influenced by the incident classification level and by expected traffic conditions.

			Lanes Impacted / Action Level
Time of Day	Estimated Duration	0 Lanes	1 Lane	2 Lanes	>2 Lanes
0000 - 0600	< 2 hours	0	0	1*	3*
	2-4 hours	0	0	2*	3*
	>4 hours	0	0	2*	3*

0600 - 1000	< .5 hours	1	1	2	3
	.5 - 2 hours	1	1	2	4
	> 2 hours	1	2	3	4

1000 - 1500	< 2 hours	1	1	2	3
	2-4 hours	1	1	2	3
	> 4 hours	1	2	3	3

1500 - 1900	< .5 hours	1	1	2	3
	.5 - 2 hours	1	1	2	4
	> 2 hours	1	2	3	4

1900 - 2400	< 2 hours	0	0	1*	3*
	2-4 hours	0	0	2*	3*
	> 4 hours	0	0	2*	3*

Level 0 No special action required

Level 1 Implement Response Plan to notify appropriate PSAs Turn on Level 1 CMS and HAR

Level 2 Implement Response Plan to notify appropriate PSAs Turn on Level 2 CMS and HAR Turn HAR flashing lights on a level 2

Level 3 Implement Response Plan to notify appropriate PSAs Turn on Level 3 CMS and HAR Turn HAR flashing lights on a level 3 Provide Advisory Alternate Routing

Level 4 Implement Response Plan to notify appropriate PSAs Turn on Level 4 (and above) CMS and HAR Turn HAR flashing lights on a level 4 Provide Mandatory Alternate Routing

Level n CMS n = number of decision points prior to the incident corridor

Level n HAR n = number of times the related advisory is repeated in a HAR cycle (e.g. within a 3 minute cycle) Level n* * = notification of operations personnel may be required to implement outside normal duty hours

Fig. 4.32 ARTEMIS incident response plan selection

4.5.4.2 Improved Interagency Communication

Many of the states structure their incident response approach according to the guidelines provided by the National Incident Management System (NIMS) and the Incident Command system (ICS). Appendix G provides a discussion of these systems.

Cooperation and coordination among agencies that provide incident responders are important to the success and efficiency of the incident management and clearance process. Important elements of this process include the following:

• Concept of Operations. The Conops defines the roles and responsibilities of the participating agencies. An example of this is shown in Table 4.9 from the Concept of Operations for the Philadelphia area [31]. The agencies and their responsibilities are summarized in the chart.

Table 4.9 Philadelphia area incident management roles and responsibilities

Area	Stakeholders	Roles and responsibilities
Traffic	NJDOT STMC/TOC South	• Conduct traffic surveillance, identify incidents
management	PennDOT District 6-0 RTMC	• Notify 9-1-1 center that an incident has occurred
centers	BCBC TOC	• Dispatch ESP vehicles for traffic control
	DRJTBC Offices	• Post information on VMS signs • Enter incident information into 511
	DRPA TPC	• Notify other entities via RIMIS
	NJ County TOCs	• Modify traffic signal timings on detour routes
	NJTA TMC	• Request maintenance crews for clean up
	Philadelphia TOC	• Provide information to ISPs and media
	PTCOCC	• Develop/implement traffic control plan for
	SJATOC	special events
9-1-1 call	NJ County 9-1-1 s	• Receive 9-1-1 call from the public
centers	NJSP Troop Dispatch	• Dispatch first responders
Emergency responders	PA County 9-1-1 s	• Verify incident from traffic management video
	PPD Radio Room Dispatch	• Dispatch additional police, fire, EMS resources
	PSP Norristown CDC
	NJSP	• Determine first responder resources needed
	PSP	• Conduct traffic investigation, traffic control
	BCBC Police	• Implement ICS procedures
	DRPA Police	• Request additional resources as needed
	Municipal Police, Fire, EMS
	PPD Philadelphia Fire Dept.
Information	NJDOT 511/Traveler Info	• 511 systems update their databases and maps
service	PennDOT 511/Traveler Info	• Update ISP/TMAs databases and maps
providers	NJTA 511/Traveler Info	• Issue traveler alerts to people signed up for
	PTC Traveler Info	them
	SJTA 511/Traveler Info
	ISPs
	NJ and PA TMAs

Area	Stakeholders	Roles and responsibilities
Maintenance offices	NJDOT Maintenance PennDOT District 6-0 County maintenance DRPA Bridge Maintenance BCBC Maintenance DRJTBC Offices	Receives request for assistance from 9-1-1, police, or traffic management Dispatched maintenance crew
	NJTA Maintenance NJ County Public Works Departments
	Philadelphia Streets Department PTC Maintenance Offices
	SJTA Maintenance
Special events operators	Event operators	Notify traffic management about upcoming special events

Table 4.9 (continued)

Interagency agreements that may be needed to implement these responsibilities.
A center-to-center communications plan and architecture for sharing text, voice and video. Figure 4.33 shows the incident related communications flow for the Illinois Tollway [32].

Improved sharing of information and coordination of response operations may be facilitated by the following:

Co-location of management centers. Those which are most commonly co-located include operations centers for freeway traffic management, traffic signal control, police operations and emergency management centers.
Use of ITS standards protocols. These protocols facilitate the migration of information among management centers. Management centers commonly support the National Transportation Communications for ITS Protocol (NTCIP) [33] and the IEEE 1512 standards suites [34].

4.5.4.3 Provision of Traffic Information to Responders

The detector technologies described in Sect. 4.5.1.3 may be used to provide speed, travel time or routing to emergency responders and to motorists. Private traffic information services may also be used. If the information for the freeways and major surface streets is provided to emergency service providers, they often have the capability to alter their access routes to the incident, or to use vehicles located more favorably with respect to congestion patterns. This information is best provided in the form of speed or congestion maps, or by instructions depicting the quickest route. Updated traffic information may be provided by in-vehicle visual and audio displays. Provision of this capability to emergency responders requires knowledge of travel times on the freeway and on the alternate routes that may be employed to access the incident.

Fig. 4.33 Incident communication flow for Illinois Tollway

4.5.4.4 Definition and Management of Major Response Routes

The following emergency route management measures will facilitate more rapid access.

• Traffic signal preemption. Techniques include preemption of individual traffic signals by the use of wireless, optical or sonic communication links to the intersection. Traffic signals may also be preempted along pre-planned routes from designated dispatch centers such as fire department facilities.
• Establishment of priorities for roadway maintenance operations that benefit emergency response vehicles. Lane closures or other capacity reducing maintenance activities along routes commonly used by emergency responders may increase travel time on these routes. Planning maintenance activities so that lane closure time is minimized, and coordinating maintenance and construction so that alternate routes used by emergency vehicles are not simultaneously impacted is an important step to improving emergency vehicle access. Similarly, providing priority treatment for snow and ice removal along these routes will improve response time. Input from emergency service responders can assist in identifying specific locations for priority treatment.
• Emergency vehicle turnarounds on freeways. Travel times from emergency vehicle locations to high incident rate freeway sections may be improved by the use of appropriately located emergency vehicle turnarounds. Access to these turnarounds may be protected, if necessary, by the use of gates that are remotely operated by emergency vehicles.
• Coordination of construction planning with emergency vehicle route requirements.

• Coordination of traffic calming plans with emergency vehicle route requirements. Traffic calming treatments often have an adverse effect on the speed and accessibility of emergency service vehicles. It is important for the agencies involved in developing traffic calming plans to coordinate with emergency service providers. Atkins and Coleman [35] discuss the effect of traffic calming measures on emergency vehicle speeds. This research has led Portland, Oregon to classify a number of streets as major emergency response streets. Traffic preemption devices are emphasized and traffic-slowing devices are avoided on these streets. Other locations [36] have also addressed this issue.

4.5.4.5 Tail of Queue Detection

During the progress of an incident, the tail of the queue progresses upstream. The tail may be at a considerable distance from the incident site, thus making its location difficult to identify by on-site personnel. Point detectors and CCTV may be used to provide this information (CCTV provides a labor intensive solution that may be inappropriate when a number of incidents must be simultaneously monitored). Detecting the tail of the queue serves the following functions:

• Assists on site personnel to adopt appropriate traffic management measures.
• Assists emergency vehicles to find the best route to the incident.
• Assists in the selection of appropriate motorist information messages and routing plans. As the tail of the queue continues to build after the incident has been cleared, this function continues even after the emergency responders have left the scene. Section 10.4 provides additional descriptions of queue warning systems.
• Termination of queue. It is important to detect this event so that motorist information messages do not indicate the presence of an incident after the queue is cleared. Point detectors and CCTV may be employed for this purpose.

4.6 Measuring Incident Management Effectiveness

Incident management effectiveness may be viewed from a number of perspectives as described in the following sections.

4.6.1 Degree of Attainment for Recommended Management Functions, Operations and Technologies

FHWA has established a Traffic Incident Management Self-Assessment program for this purpose. An example of the type of issues covered and the score from responders is shown in Table 4.10.

Table 4.10 Example of Self-assessment questions and responses [37]

Question		% of assessments
number	Question	scoring 3 or higher
4.2.1.1.	Have established criteria for what is a "major incident"— incident levels or codes?	17 %
4.2.1.2.	Identify high ranking agency members available on 24/7 basis to respond to a major incident?	77 %
4.2.1.3.	Have a pre-identified (approved) contact list of resources (including special equipment) for incident clearance and hazardous materials response?	66 %
4.2.1.4.	Have the response equipment pre-staged for timely response?	44 %
4.2.2.1.	Train all responders in traffic control procedures?	30 %
4.2.2.2.	Utilize on-scene traffic control procedures for various levels of incidents in compliance with MUTCD?	29 %
4.2.2.3.	Utilize traffic control procedures for the end of the incident traffic queue?	14 %
4.2.2.4.	Have mutually understood equipment staging and emergency lighting procedures on-site to maximize traffic flow past an incident while providing responder safety?	16 %
4.2.3.1.	Utilize the Incident Command System?	54 %
4.2.3.2.	Have specific policies and procedures for fatal accident investigation?	51 %
4.2.3.3.	Have specific policies and procedures for hazardous materials response?	69 %
4.2.3.4.	Have quick clearance policies?	36 %
4.2.3.5.	Have a pre-qualified list of available and contracted towing and recovery operators (to include operators' capabilities)?	74 %
4.2.3.6.	Use motorist assist service patrols?	70 %

4.6.2 General Measures

While general ITS performance measures such as reduction in delay and crashes also pertain to incident management, measures that have been identified as directly pertinent to incident management include [38]:

• Roadway clearance time (the time between first recordable awareness of an incident and the time that all lanes are available).
• Incident clearance time (time between the first recordable awareness of an incident and the time that the last responder leaves).
• Secondary crashes.

4.6.3 Model for Evaluating Incident Management Effectiveness

The following sections discuss a model for evaluating alternative ITS design concepts as applied to incident management. The model computes a parameter (H) ranging from 0.0 to 1.0 that represents the potential ability of the ITS to effectively provide incident management support. The model is discussed below.

4.6.3.1 Relationship of Incident Management Functions to Techniques and Technologies

The parameter H considers the following functional requirements:

1. Timely detection of incidents (H1).
2. Timely confirmation and classification of incidents (H2).
3. Timely assistance provided by the TMC in managing incident response and clearance (H3).
4. Timely detection of the tail of the queue and the termination of the queue (H4).

The probability that each of the above events has the potential to be satisfied depends on the technologies and operations employed.

Table 4.11 uses the index g to represent these functional requirements. Vng is a value that represents the potential ability of the technology or operation to satisfy requirement g. Representative values are provided in Table 4.12.

Technologies and operations	Probability that requirement is satisfied
1. 911/PSAP information availability	V1g
2. Police operations	V2g
3. CCTV	V3g · RTV
4. Motorist service patrols	V4g · K35 · K40
5. Electronic traffic detection (point or probe)	V5g · B1

Table 4.11 Probability of satisfying functional requirement

Table 4.12 Default Values for Vng

	Technologies
Functional requirements (g)	V1g	V2g	V3g	V4g	V5g
1. Timely detection	0.6	0.3	0.9	0.5	0.4
2. Timely conf. and class.	0.3	0.6	.9	0.5	0.2
3. Timely assistance	0	0.9	.8	0.5	0.2
4. Tail of queue and termination	0	0.1	0.5	0.2	0.8

In the table

B1=timely detection probability for a range of scenarios for different detector spacing (Sect. 4.5.1.3).

RTV=Fraction of roadway incidents observed by CCTV (Appendix B).

K35=Correction factor for level of service patrols (Appendix F).

K40=Scaling factor for service patrols (Appendix F).

The user may choose to modify these values based on experience or based on special considerations pertaining to the application.

4.6.3.2 Model for Incident Management Effectiveness Potential

A value Hg is required to represent the effectiveness potential for each of the incident management functional requirements. Since the contributions of the technologies towards supporting incident management overlap, a technique is required to model these interactions. The technique employed uses a combination of probability theory and Bayesian inference (for example see Klein [22]). To compute Hg

Hg=1–probability that no technology satisfies function g.

Probability that no technology satisfies the function=(1−probability of satisfaction by technology 1) • ⋯⋯⋯.• (1−probability of satisfaction by technology 5).

Thus Hg is provided by

$$H{g} = 1 - (1 - V{1g}) \cdot (1 - V{2g}) \cdot (1 - V{3g} \cdot RTV) \cdot (1 - V{4g} \cdot K40 \ K35) \cdot (1 - V{5g} \cdot BI)$$ (4.13)

Incident management effectiveness potential includes the following operations:

• Timely detection of incidents (H1).
• Timely confirmation and classification of incidents (H2).
• Management of incidents (HM).
- Timely assistance to emergency responders (H3).
- Timely detection of tail of queue and termination of queue (H4).

Since H3 and H4 contribute to incident management, a measure of HM may be provided by

$$H{M} = Y \cdot H{3} + (1 - Y) \cdot H_{4}$$ (4.14)

Where Y represents the timeliness of incident management operations (on a scale of zero to 1.0. A value of 0.8 or higher may be used for metropolitan areas that feature good response services.

The value of H is provided by

$$\mathbf{H} = \mathbf{H}_1 \cdot \mathbf{H}2 \cdot \mathbf{H}{\mathbf{M}} \tag{4.15}$$

4.6.3.3 Benefits for ITS Incident Management Treatment

Reduction in incident clearance time produces the following benefits:

• Reduction in overall vehicle delay.
• Reduction in secondary accidents as a result of reduction in the time that the queue is present.
• Reduction in fuel consumption.
• Reduction in vehicle emissions.

The reduction in delay and accidents depends on a number of the parameters discussed earlier in Sect. 4.6.3 as well as others. A model describing the relationships for these benefits is shown in Fig. 4.34.

Representative values for certain of the parameters in the model are shown in Table 4.13.

P10 – Probability incident managed if TMC manned

P21 – Probability TMC manned when incidents occur

H – Incident management effectiveness potential

MVMPY – Millions of vehicle miles per year IR – Incidents per million vehicle miles

TSI – Time saved peer incident

K5 – Accident reduction factor

ACCR – Accident rate

Fig. 4.34 Model for delay and accident reduction benefits

Table 4.13 Representative parameter values for delay and accident reduction benefits model

Symbol	Parameter	Representative value
P10	Probability incident is managed if TMC is staffed	1.0 if TMC operations manual or operating direction requires support of incidents.
P21	Probability TMC staffed when incidents occur	1.0 if TMC operates around the clock. If TMC is staffed on weekdays from 6 AM to 7 PM, 58.6 % of the vehicle miles traveled and accidents will occur during this period [11]
K5	Accident reduction factor (fraction of accidents reduced by ITS support of incident operations)	0.10 is used as the default factor

89 References

The computations for (4.13) through (4.15) are provided by the Inc mgt effectiveness potential worksheet on the website http://www.springer.com/us/book/ 9783319147673. An example of a design tradeoff to obtain benefits for alternative CCTV camera and detector deployments and an illustration of a worksheet is provided in Appendix C.

Procedures for the estimation of fuel consumption and emissions are described in Schrank et al. [38] and are based on the EPA's MOVES model [39].

References

1. Conklin CA, Bahler SJ, Belmore KL, Hallenbeck M, Ishamura J, Schnell GM, Clark JE, Cathleen E, Kandarpa R, Hill D, But A (2013) Transportation management center data capture for performance and mobility measures guidebook. Joint Program Office, Report FHWA-JPO-13-062, Washington, DC
2. Lindley JA (1987) A methodology for quantifying urban freeway congestion. Transportation Research Record 1132. Transportation Research Board, Washington, DC
3. Raub RA (1997) Secondary crashes: an important component of roadway incident management. Transport Q 51(3):93–104
4. Traffic Operations Center (TOC) manual (2008) Virginia Department of Transportation
5. Murthy G, Lu JJ, Rajaram L (2013) Evaluation of intelligent transportation systems operations using logistic regression models. ITE J
6. Antonnucci ND, Hardy KK, Bryden JE, Neuman TR, Pfefer R, Slack K (2005) Guidance for implementation of the AASHTO Strategic Highway Safety Plan, Volume 17: A guide for reducing work zone collisions, NCHRP Report 500. Transportation Research Board, Washington, DC
7. Morales JM (1986) Analytical procedures for estimating freeway traffic congestion. Public Roads 50(2):55–61
8. Ozbay K, Kachroo P (1999) Incident management in intelligent transportation systems. Artech House, Boston, MA
9. Presley MW, Wyrosdick KG, Sulbaran TA (2000) Calculating benefits for NAVIGATOR, Georgia ITS. 79th annual meeting of the transportation research board, Washington, DC
10. Traffic Incident Management Handbook (2000) PB Farradyne
11. Region 4 ATMS local evaluation report (2005) Dunn Engineering Associates
12. Kittelson W, Vandehey M (2013) SHRP 2- incorporation of travel time reliability into the HCM, Kittelson and Associates. August 2013
13. Chattanooga urban area incident management plan. Chattanooga Urban Area Metropolitan Planning Organization and Chattanooga – Hamilton County Regional Planning Agency, May 2010
14. Owens N et al (2010) Traffic incident management handbook, Report FHWA-HOP-10-013. Federal Highway Administration, Washington, DC
15. Transportation incident and event management plan. Delaware Department of Transportation (2004) Edwards and Kelcey
16. Online 08/22/14 http://www.bing.com/images/search?q=dynamic+message+signs+traffic+ill ustrations&qs=n&form=QBIR&pq=dynamic+message+signs+traffic+illustrations&sc=0-0& sp=1&sk=#view=detail&id=4D19201188287BC363EAF0A59342CDC4B8E43756&selecte dIndex=43
17. Alternate route handbook (2006) Dunn Engineering Associates Federal Highway Administration Report No. FHWA-HOP-06-092, Washington, DC
1. Intelligent Transportation Systems (ITS) design manual (2000) Wisconsin Department of Transportation
19. Project development manual, Appendix 6. New York State Department of Transportation, Appendix 6.https://www.nysdot.gov/portal/page/portal/divisions/engineering/design/dqab/pdm
1. PeMS user guide, Caltrans, May 2013
1. Jia Z, Chao C, Coifman B, Varaiya P (2014) The PeMS algorithms for accurate, real-time estimates of g-factors and speeds from single-loop detectors, online April 25, 2014, http:// robotics.eecs.berkeley.edu/~varaiya/papers\_ps.dir/gfactoritsc.pdf
1. Klein LA (2001) Sensor technologies and data requirements for ITS. Artech House, Boston, MA
1. List GF, Williams B, Rouphail N (2014) Guide to establishing monitoring programs for travel time reliability, SHRP 2 Report S2-LO2-RR2. Transportation Research Board, Washington, DC
1. May AD (1990) Traffic flow fundamentals. Prentice-Hall, Englewood Cliffs, NJ
1. Martin PT et al (2001) Incident detection algorithm evaluation. University of Utah, Salt Lake City, UT
1. Automatic incident detection algorithms. ITS Decision Report, Partners for Advanced Transportation and Highways (PATH), University of California at Berkeley, 27 Feb 2001
1. Mouskos KC et al (1999) Transportation operations and coordinating committee system for managing incidents and traffic: evaluation of the incident detection system. Transport Res Rec 1679:50–57
1. Bluetooth travel time technology evaluation using the BlueTOAD™. KMJ Consulting Inc., 4 Jan 2010
1. California highway patrol online 03/15/2013. http://cad.chp.ca.gov/gov/traffic.aspx
1. ARTIMIS operations plan (1997) The advanced regional traffic interactive management & information system
1. Regional ITS architecture for the Delaware Valley, Delaware valley regional planning commission executive summary, Version 2.0, June 2012
1. Incident management operating information and procedures guide. Illinois Tollway, Jan 2013
1. The NTCIP guide updated version 4 (2009) American Association of State Highway and Transportation Officials, Institute of Transportation Engineers, National Electrical Manufacturers Association
1. Guide for implementing IEEE STD 1512 using a systems engineering process (2008) The Institute of Electrical and Electronics Engineers, Inc.
1. Atkins C, Coleman M (1997) The influence of traffic calming on emergency response times. ITE J 67(8):42–46
1. Guidelines on traffic calming devices. Street and Traffic Division, Public Works Department (2006) City of Kansas, MO
1. Traffic incident management (TIM) self assessment national executive summary report (2003) Federal Highway Administration
1. Schrank D, Eisele B, Lomax T (2012) TTI's 2012 urban mobility report. Texas A&M University System, December, 2012
1. MOVES (Motor Vehicle Emission Simulator). Environmental Protection Agency, online 3 Sept 2014. http://www.epa.gov/otaq/models/moves/

Chapter 5 Non-recurrent Congestion: Incident Information to Motorists

Abstract Chapter 4 discussed delay reduction resulting from reduction in the response time to incidents. This chapter describes the other significant ITS approach to mitigating non-recurrent congestion, namely providing motorists with information. Since messaging policies and diversion effects for recurrent and non-recurrent congestion may be different, these subjects are covered in two different chapters.

Motorist information can mitigate non-recurrent congestion in the following ways:

• Induce a motorist traveling on the freeway to divert in the event of an incident. Circumstances that induce diversion include:
- Capacity reducing incidents on the freeway on which the motorist is traveling or on freeways that are accessed by the freeway on which the motorist is traveling.
- Capacity reducing incidents and construction for special events on remote facilities. Avoiding the incident on the remote facility may require the motorist to modify his route on the facility that he is currently using.
• Prior to the start of a trip or early in the trip, induce a motorist to change his travel mode or the start time of his trip.
• Make the motorist aware of unusual conditions such as incidents, lane blockages and lane closures. Accidents are reduced by facilitating the motorists' earlier preparation for these events.

Section 3.1.4 discusses the general issues relating to diversion resulting from non-recurrent congestion and shows several diversion curves. It also discusses policy issues related to motorist information for non-recurrent congestion. The following topics are covered this chapter in connection with diversion to avoid incidents:

• The techniques for communicating with motorists.
• Strategies and policies or developing messages and the use of the content and the strength of the message to influence the percentage of motorists diverting.
• Semi-automatic and manually implemented strategies for controlling diversion.
• The effect of diverted traffic on alternate routes.
• Models for delay reduction resulting from diversion for the diverted traffic, nondiverted traffic remaining on the freeway and corridor traffic.
• The effect of diverted traffic on alternate routes and the necessity for controlling the impact.

The chapter provides guidance and some simple models to assist the engineer in locating dynamic message signs. The importance of the quality of motorist information is discussed, and a simple evaluation measure is provided. The use of ITS for emergency evacuation is introduced and a model for generating and disseminating information is discussed.

5.1 Motorist Diversion

5.1.1 Motorist Messaging Techniques

5.1.1.1 Technologies for Communicating with Motorists

Traffic information is often developed by the agencies operating the highway facility. In some cases, the agency contracts with a private service to provide this information. Private services may also supply this information directly to motorists or to the vehicle. Table 5.1 identifies a number of technologies that provide communication with motorists.

Information dissemination techniques may be provided by the operating agency directly to the motorist through dynamic message signs (DMS) and by using highway advisory radio (HAR) transmitters in combination with vehicle radios. Other operating agency initiatives include 511 telephone information service that may be accessed in the vehicle or prior to the trip. These services, provided by many state departments of transportation, offer detailed traffic and roadway condition information along with transit related information.

Privately provided traffic information includes commercial radio station traffic broadcasts, satellite radio, television traffic condition reports and in-vehicle GPS based navigation systems that provide real-time traffic conditions and routing information. The traffic information updates for these navigation systems may be provided by cellular telephone or by satellite radio. The connected vehicle program [1] provides an emerging technology for distributing in-vehicle information using both roadside equipment and information from other vehicles.

Communication of traffic information may result in the motorist changing his lane, route, mode or the time he initiates his trip. Most mode and trip initiation time changes occur prior to starting the trip. This book primarily discusses route diversion issues that occur when the trip is already in progress.

5.1.1.2 Diversion Messages

Dudek indicates that operating agencies should only provide messages that contain information that the motorist does not already know [2]. According to this policy, messages should only deal with non-recurring events. FHWA, however, favors the policy of posting travel time on DMS even during non-incident periods [3].

93 5.1 Motorist Diversion

Table 5.1 Techniques for providing motorist information

Technique	Message coverage characteristics	Limitations	Speed of response to incidents	Source of data
Dynamic message sign (DMS)	Coverage of roadway and possibly nearby roadways as generally used	Message length limited by readability considerations	Good	Agency ITS equipment based information may be augmented by private traffic information services
Highway advisory radio (HAR)	Coverage radius typically 3–5 miles	Message length limited by transmission coverage	Good	Agency ITS equipment based information may be augmented by private traffic information services
Commercial radio television	Wide area. May be used for pre-trip planning	Completeness of conventional radio incident coverage often limited by broadcast time allocation. Satellite radio generally provides better coverage	Fair	Private helicopters. Agency ITS equipment based information may be augmented by private traffic information services
Commercial television	Wide area. Useful for pre-trip planning		Fair	Agency ITS equipment based information may be augmented by private traffic information services
GPS in-vehicle navigation system (original vehicle or aftermarket based equipment or smartphone based)	Wide area	Visual information presentations may result in driver distraction	Varies depending on traffic information source	Private traffic information services may be enhanced by public based ITS information
E 511 service (public agency)	Wide area. Many states provide information organized by roadway section or other means to obtain specific information. May be used for pre-trip planning	In-vehicle selection of desired information may cause motorist distraction	Varies depending on traffic information source	Cellular telephone service cost

Table 5.1 (continued)

Technique	Message coverage characteristics	Limitations	Speed of response to incidents	Source of data
Private website	Wide area	Useful for pre-trip planning. In-vehicle information must be used safely	Varies depending on traffic information source	Private information services may be enhanced by public based ITS information

Fig. 5.1 Alternative routes

Messages that describe abnormal traffic conditions often result in the motorist diverting to another route. Diversion messages may be of either of the following types:

• Explicit diversion—Sometimes called active diversion, these messages indicate the need to divert, and may suggest an alternate route. In Table 3.1, the messages related to message strengths 4, 5, 7 and 8 are active diversion messages, and generally induce larger diversion levels than do implicit (or passive messages). Dudek [2] suggests that the policy described in Sect. 3.1.4.2 be implemented in the case of explicit diversion.

In recent years several smartphone and internet based services offer instructions for the fastest route, thus contributing to the explicit diversion traffic level. For

95 5.1 Motorist Diversion

Fig. 5.2 Map based depiction of alternative routes

example, WAZE (https://www.waze.com/) provides fastest route directions for the measured traffic conditions. Figures 5.1 and 5.2 show representative WAZE displays of alternate routes with travel times (these are best used for pre-trip planning). Note the inclusion of a toll-free route. For the selected route, en-route turn by turn guidance is provided audibly at the appropriate location in the trip. Because explicit route guidance is provided based on the fastest route, this type of information may be considered as a component of explicit diversion.

• Implicit diversion—Messages that describe such events on the roadway as accidents, lane blockages and closures, construction, special events, delay and travel time above expectations may, depending on the delay that the motorist perceives, result in diversion. They are implicit or passive diversion messages. Messages 1, 2, 3 and 6 in Table 3.1 are implicit diversion messages. Travel time messages may also be considered as implicit diversion messages.

5.1.2 Operational Diversion Policies and Strategies

When an incident occurs on a freeway, diversion options include:

• Diversion around the incident and return to the freeway downstream of the incident.
• Diversion to alternate local routes when these more conveniently access the motorist's destination.

While in some cases direct diversion to another freeway may be possible, most diversion opportunities require use of the surface streets for some, or all, of the diversion route. During peak periods, diversion routes may have little spare capacity.

During non-peak periods, even modest diversion levels may also have the potential to congest surface street arterials that may serve as alternates. A simple example is shown by the midday scenario in Fig. 5.3 and in Table 5.2.

Figure 5.3 depicts a single lane freeway blockage during a midday period. A medium capacity arterial alternate is directly accessible from the freeway and returns to the freeway downstream of the incident. There is a DMS upstream of the incident that has the capability of diverting traffic. The residual capacity of the freeway under incident conditions is 49 % of the basic capacity (see Table 4.2). This results in a capacity deficit of 913 VPH.

With the signal, the alternate roadway has a capacity of 1,980 VPH. Figure 3.5 indicates that significant congestion on the surface street alternate is likely when the volume to capacity ratio exceeds 0.9. If a policy is adopted that does not permit excessive congestion on the alternate during non-peak periods, then only 1,782 total VPH may be accommodated, and only 412 VPH may be diverted from the freeway. Such a policy may be needed to

• Maintain a lower travel time on the alternate route than on the route with an incident.
• Preserve acceptable conditions for traffic that normally uses the alternate route.

The strategy to implement this policy requires the diversion messages to limit the diversion volume to 412 VPH or a diversion fraction of approximately 10 %. Section 3.1.4.1 indicates that the propensity to divert can be controlled through the "strength" of the message. The low diversion fraction required for this example implies that only a low strength message (Table 3.1) would be appropriate. The example illustrates the need for closely monitoring traffic conditions on the alternate route to assure that the strategy is being properly implemented.

Fig. 5.3 Flow diversion during a non-peak period

97 5.1 Motorist Diversion

Parameter	Symbol or relationship	Value
Three lane freeway (one direction)
Normal capacity	C	6,300 VPH
Number of lanes blocked		1
Residual capacity	RE=0.49·C	3,087 VPH
Normal freeway volume	q	4,000 VPH
Capacity deficit	CD=q−RE	913 VPH
Arterial alternate (two moving lanes)
One direction roadway capacity	RC	3,600 VPH
Green signal split along arterial	G	0.55
Capacity along arterial with signal	CS=G·RC	1,980 VPH
Maximum flow without major arterial congestion	MF=.9·CS	1,782 VPH
Normal arterial volume	qA	1,370 VPH
Maximum divertible freeway flow without major arterial congestion	MDF=MF−qA	412 VPH
Maximum diversion fraction for no major arterial congestion	DF=MDF/q	0.103

Table 5.2 Parameters for non-peak period diversion example

5.1.3 Strategic Network Management

Possible policies to manage the component of diversion controlled by the TMC include the following:

• Accept considerable congestion on alternate. In the example in Sect. 5.1.2 the strategy to implement this policy could result in raising the acceptable volume to capacity ratio to 0.96, resulting in a diversion volume of 531 VPH, corresponding to a diversion fraction of approximately 13 %. Transit on the arterial is also likely to experience considerable delay.
• Favor reducing delay on the freeway to the extent possible. Further increase in the diversion fraction will considerably increase delay on the arterial.
• Implement a strategy that minimizes traveler delay in the corridor.
• Avoid explicit diversion messages except for road closures or hazardous conditions.

By providing messages to motorists, agencies employ one or more of these policies. In some cases the agency has made a decision to adopt a policy while in other cases the selection of message formats implicitly defines a policy.

Policies may be supported by the traffic assignment and distribution models that are traditionally used for transportation planning. These models have a demand component (trip generation and traveler behavior) and a supply component (network characteristics). A model to optimize flow under changing network conditions requires more rapid adaptation of both the demand and supply component to short term changes. Dynamic traffic assignment (DTA) models address this need.

For example, DynaMIT [4] models short-term changes in traveler demand and network characteristics. In addition, it accepts real-time inputs from field surveillance data and from traffic controls.

5.1.3.1 Diversion Fraction

The diversion fraction is a key variable in diversion strategies that implement these policies. Diversion may be viewed as possessing a component (PDF) that is provided by private organizations through traffic information services and a public component (DF) managed by TMCs and influenced by messages provided by the TMC. Both contribute to the total diversion fraction (TDF) as follows:

$$TDF = PDF + DF (5.1)$$

Rewriting Equation 4.10, the public component of diversion fraction (DF) at an exit ramp may be defined as follows:

$$DF = (V{E2} - V{E1}) / V_{M}$$ (5.2)

where

VE1=Exit ramp volume before instituting diversion message

VE2=Exit ramp volume after instituting diversion message

VM =Mainline volume upstream of exit ramp

From an operational standpoint DF is best determined by measurements of mainline and exit ramp traffic flow changes in response to different types of messages. DF for a DMS message may be measured in response to a message and this same value may be used for that message type (as defined for example in Table 3.1) when suitable conditions require this diversion fraction. Figure 5.4 shows volume detection configurations that are appropriate for obtaining DF. Two of the three detection stations shown in the figure are required for this purpose.

The public diversion fraction includes the use of other public agency operated media such as highway advisory radio (HAR) and 511 sites that provide coordinated information.

By compiling historic public component diversion fractions, this database may be used to select the message strength appropriate to the incident. These databases may also be used as a starting point for operations when a new DMS is added.

Fig. 5.4 Detection location configurations

99 5.1 Motorist Diversion

5.1.3.2 Diversion Fraction Model

If it is not feasible to use the measurement process described in Sect. 5.1.3.1, an analytic approach may be considered to estimate diversion probability. Peeta et al. [5] suggest that DMS message strength may be used to control the level of diversion by this means and provides the following binomial logit model as a basis for this control.

$$PD = 1/(1 + e^{-U})$$ (5.3)

where

PD is the diversion probability

U is the difference in utility between diverting and not diverting motorists

In Peeta's formulation

$$U = KD + NMV + MV (5.4)$$

where

KD is a constant

NMV is a value that represents a set of variables that relate to factors other than the message type

MV is a value that represents the message type (presentation strength)

Based on the message types of Table 3.1, Table 5.3 [5] shows a set of model parameters for a particular set of motorist characteristics and the accompanying diversion probability.

Parameter	Message characteristics	Parameter value	Presentation factor (provided by author)
KD		−1.88
NMV		+0.54
following rows	MV for different messages shown in the	Message type parameter (MV)
Message 1	Occurrence of accident	0	0.20
Message 2	Location of the accident	−0.09	0.19
Message 3	Expected delay	+0.61	0.32
Message 4	The best detour strategy	+0.82	0.37
Message 5	Location of the accident and the best detour strategy	+2.08	0.67
Message 6	Location of the accident and the expected delay	+2.49	0.75
Message 7	Expected delay and the best detour strategy	+2.73	0.80
Message 8	Location of the accident, expected delay and the best detour strategy	+3.55	0.89

The Peeta study is based on a stated preference survey. "Real world" factors such as driver comprehension, DMS visibility and driver reaction time generally reduce the actual diversion probability. Mansoureh and Ardshirri [6] indicate a significant discrepancy between the diversion probability when determined by a stated preference survey and a driving simulator.

Because of the limitations of the results from stated preference surveys, the data shown in this section should be considered as an example in the technical literature of the effects of message strength on diversion.

5.1.3.3 Operational Considerations in System Design

The preceding sections discuss the parameters that influence the diversion fraction through motorist information. System designs that consider these issues are more likely to result in more effective performance. The relationships leading to the diversion fraction are, however, complex, and the parameters that result in diversion are difficult to establish with certainty and vary among roadway facilities.

5.1.4 Diversion Strategies

Diversion policies may be implemented by use of diversion strategies. Diversion strategies include open loop control (little or no capability for monitoring the controlled freeway and its alternate) and closed loop control. The following sections describe these strategies.

5.1.4.1 Open Loop Control

Strategy selection is based on policies that prescribe specific strategies corresponding to events such as incidents and their severity. Strategies may consist of diversion through motorist messages and may be supported by traffic controls such as ramp metering, special signal timing plans and lane use changes. Different pre-stored strategies may apply during different traffic periods. Simulation may assist in the development of these strategies. Open loop control provides little capability to adjust the control strategy (either manually or automatically) in response to actual traffic conditions that develop during the operation. It may occur when operating procedures are inadequate to respond to current conditions or when the TMC workloads exceed the capability to provide timely responses.

5.1.4.2 Closed Loop Control

Closed loop control implies the adjustment of the diversion fraction and other traffic controls based on traffic observations by the system operator or by measurement by means of traffic detectors. In some cases, detector data and/or CCTV images are

101 5.1 Motorist Diversion

available for both the roadway with the incident and for the major alternate route. In other cases, particularly when the alternate route is a surface street, appropriate information on the alternate is not available. The following sections describe several variations of closed loop control.

Closed Loop Manual Control

Figure 5.5 schematically shows this type of control. The operator, observing traffic conditions on displays of traffic detector data, CCTV displays and using incident information obtained from other sources implements messages according to established policies.

Information from traffic detectors is often shown as a color-coded map display to simplify its interpretation by the operator. This is the most commonly used form of control when traffic surveillance equipment is available.

TMCs are often able to change surface street timing plans in response to diversion messages that increase surface street demand. Adaptive traffic signal control systems provide this capability automatically.

In recent years, traffic detection capability in the form of CCTV coverage and probe based information has increased. Commonly used sources of probe information for this purpose include Bluetooth readers, toll tag readers and privately developed GPS based probe information that is used by operating agencies.

Closed Loop Semi-Automatic Control

Examples of traffic condition states that may be used include speed, delay or traffic density. Implementing the control strategy automatically recommends a set of messages and controls based on policy rules and constraints. The message or controls may be modified by the operator based on additional information available to him such as CCTV observations and information from other sources. As with closed

Fig. 5.6 Closed loop semi-automatic control

loop manual control, traffic condition information may be available on both the freeway being controlled as well as on the alternate route.

Figure 5.6 shows this type of control. Traffic detector information may be processed (possibly including the use of prediction) to include the traffic state(s) that may be employed by the control strategy. Traffic condition information may be available on the freeway being controlled as well as on the alternate route.

Since closed loop semi-automatic control is implemented by traffic detector data, it is generally employed for both recurrent and non-recurrent congestion. An example of closed loop semi-automatic control where the controlled freeway is monitored but the alternate route is not monitored is provided in Appendix D. An example with alternate route monitoring is described below.

Highway 401 in the Toronto, Ontario area features a set of express lanes and a set of collector lanes, with transfer opportunities between these lane groups every few miles. The COMPASS system provides dynamic message signs located on each roadway upstream of the transfer points. The DMS describe general traffic speed conditions on both routes. These speeds are measured by detector stations downstream of the transfer point. Figure 5.7 shows the general character of the control loop [7].

The diversion fraction between roadways is altered by providing messages on each DMS that indicate the conditions on both roadways. Table 5.4 shows the general COMPASS message structure for displaying these conditions on each roadway.

103 5.1 Motorist Diversion

Fig. 5.7 Illustration of DMS feedback control loop (from Transportation Research Record: No. 2047, Transportation Research Board of the National Academies, Washington, DC, 2008, Fig. 5, p. 16. Reproduced with permission of the Transportation Research Board)

Table 5.4 Speed thresholds to determine message display where free flow speed is 100 km/h (62.1 miles/h) [7]

Current message	New message	Threshold speed
Moving well	Moving slowly	80 km/h (49.7 mph)
Moving well or moving slowly	Very slow	40 km/h (24.8 mph)
Very slow	Moving slowly	45 km/h (27.9mph)
Very slow or moving slowly	Moving well	85 km/h (52.8 mph)

The COMPASS control strategy is a relatively simple example of closed loop semiautomatic control. Closed loop control does not require an explicit knowledge of diversion fraction resulting from the message because this type of control changes the strength of the message in response to measured traffic conditions. In the case of COMPASS, the control strategy approximately equalizes the speeds on the controlled roadways.

Closed loop control for other traffic management applications may be achieved by changing the message types. The design of closed loop systems requires an analysis to assure stability and satisfactory performance.

This type of control may also be implemented with strategies that employ more detailed traffic control models. For example, Kachroo and Ozbay [8] provide mathematical models for dynamic traffic routing. They discuss the use of feedback activated controls to optimize travel time and assure system stability.

5.1.5 Reduction in Freeway Delay Resulting From Diversion

The most significant reduction in overall system delay resulting from diversion often accrues to the freeway traffic that does not divert under incident conditions. Section 5.1.6 provides an example that illustrates this.

Figure 4.2 shows the effect of an incident on delay. Figure 5.8 is a similar figure that depicts the effect of diversion on the queues resulting in delay. It adds a line representing the new demand volume after diversion. The area enclosed by points a,

Fig. 5.8 Delay and timeline model under diversion conditions

b, c and O represents delay under diversion conditions. Diversion commences after incident detection and confirmation (TC). The vertical distance between the lines Oab and Ocb represents the number of vehicles in the queue at a given time.

The following definitions apply to Fig. 5.8 and to the following equations:

q₁—Volume at incident clearance (roadway capacity)
q₂—Volume entering incident location (prior to diversion)
q₃—Volume when incident is present (capacity under incident conditions)
q₄-Volume entering incident location after diversion
T-Time from incident occurrence until incident is cleared
TC-Time from the occurrence of the incident occurrence until diversion is implemented
TDD—Time period after incident clearance until queue clears under diversion conditions

Analysis of the geometrical relationships in Fig. 5.8 leads to the following equations:

Delay reduced prior to TC

$$DD = 0.5 \cdot TC^2 \cdot (q_2 - q_3)$$ (5.5)

Delay (DC) from TC to T

$$DC = 0.5 \cdot q_4 \cdot \left(T - TC\right)^2 + \left(T - TC\right) \cdot TC \cdot \left(q_2 - q_3\right) - 0.5 \cdot q_3 \cdot \left(T - TC\right)^2 \ (5.6)$$

Time (TDD) from incident clearance to queue clearance

$$TDD = (q_4 \cdot (T - TC) + q_2 \cdot TC - q_3 \cdot T) / (q_1 - q_4)$$

$$(5.7)$$

105 5.1 Motorist Diversion

Delay (DQC) after incident clearance

$$DQC = 0.5 \cdot TDD^2 \cdot (q_1 - q_4)$$ (5.8)

Total delay for non-diverted freeway traffic (DIF) is given by

$$DIF = DD + DC + DQC (5.9)$$

Equation (4.4) describes the total delay, DT, with no diversion. The total time for the queue to clear is T+TD where

T=Time from start of incident to incident clearance

TD =Time for queue to dissipate after incident clearance (see Eq. (4.1))

The total number of vehicles served during this period (NND) is given by

$$NND = q_2 \cdot (T + T_D) \tag{5.10}$$

and the average vehicle delay during this period (ADND) is

$$ADND = D_{T} / NND (5.11)$$

Similarly, for the case where vehicles are diverted, the number of diverted vehicles served until queue clearance is given by

$$ND = q_2 \cdot (T + TDD - TC)$$ (5.12)

and the average vehicle delay during this period (ADD) is

$$ADD = DIF / ND (5.13)$$

Figure 5.9 shows an example of a worksheet Delay improvement on freeway (included in the website http://www.springer.com/us/book/9783319147673) to compute the key variables as well as DIF and the per-vehicle reduction in delay for non-diverting vehicles (IDV).

5.1.6 Effect of Diversion on Arterial Traffic

Preferred diversion policies and strategies require that:

• Motorists choosing to divert as a result of information explicitly or implicitly provided must benefit from such a diversion. Otherwise, the motorist may perceive that the information lacks credibility and may not use it in the future.
• The overall network must benefit from the diversion.

DELAY SAVINGS ON FREEWAY DUE TO QUEUE REDUCTION RESULTING FROM DIVERSION

Required data entry
			No Diversion With Diversion
Capacity (Veh/hr)	q1 =	6000	6000
Demand Vol (Veh/hr)	q2=	4500
Demand vvolume after diversion (veh/hr)	q4		4050
Residual Capacity After Incident (Veh/hr)	q3 =	3500	3500
Diversion Fraction	F	0.1	0.1
1-F	G	0.9	0.9
Blocked Time (hr)	T	1	1
Time to Detect & Confirm Incident (hr)	TC	0.07	0.07
Time after Incident Clearance Until Queue Clears (hr)	TD	0.67
Delay Until Incident Clearance (veh hr)	DT	500
Delay Clearance to Queue Dissipation (veh hr)	DQ	333
Delay Until Detection (veh hr)	DD		2
Delay - Detection to Clearance (veh hr)	DC		303
Time after Incident Clearance Until Queue Clears (hr)	TDD		0.30
Delay after Clearance (veh hr)	DQC		87
Total Freeway Delay (veh hr)		833	392
Average Delay/Veh for Non-Diverting Vehicles (hr)		0.111	0.074
Improvement in Delay for Non-Diverting Vehicles (veh hr)	DIF		441
Improvement in Delay per Vehicle for Non-Diverting Vehicles (hr)	IDV		0.037
Improvement % for Non-Diverting Vehicles			33.3
Volume Diverted (veh/hr)	VD		450

Fig. 5.9 Worksheet computing delay reduced on freeway resulting from diversion

• The effects of diversion, particularly to surface streets, resulting from traveler information, must not exceed impacts that are agreed to in advance by the local stakeholders. Special signal timing plans may be used to facilitate diversion and reduced the impact of diversion.

A simplified example using a single diversion route may be used to illustrate these concepts. Using the freeway data in Fig. 5.9, a freeway diversion fraction of 0.1 results in a diversion volume of 450 vehicles per hour. Table 5.5 provides the parameters for the example.

The policy constraint in this example restricts diversion to 396 VPH unless the signal timing is changed. In order to achieve the desired diversion level of 450 VPH, the use of an alternative signal timing plan is required.

The time saved by each diverting vehicle is the time saved by non-diverting vehicles (IDV) plus the additional improvement in delay on the diversion route (TOND). The total time saved by diverting vehicles (TSVD) is the product of this value and the number of diverting vehicles (ND). The expressions for these relationships are provided below.

$$ND = VD \cdot (T + TDD - TC)$$ (5.14)

$$TSVD = ND \cdot (IDV + TOND)$$ (5.15)

where VD is the diversion volume.

107 5.1 Motorist Diversion

Parameter	Symbol or relationship	Normal green signal split	Diversion plan green signal split
Roadway capacity (VPH)	RC	3,600	3,600
Green split on arteriala	G	0.4	0.5
Signal controlled capacity (VPH)	CS=G·RC	1,440	1,800
Policy requirement	No significant off-peak additional congestion
Maximum flow without significant congestion (VPH)	MF=0.9·CS	1,296	1,620
Normal background traffic (VPH)	NFA	900
Maximum acceptable diversion flow without significant congestion	MDF=MF−NFA	396	720

Table 5.5 Example of surface street diversion impacts for off-peak period

Figure 3.3 shows that for the assumed diversion fraction of 10 % the example, the delay saved by the diverting vehicles as compared with the non-diverting vehicles (TOND) is approximately 5 min. Using the example parameters yields

ND=572 diverted vehicles

TSVD=68.6 vehicle hours of delay reduction for diverting vehicles

The delay to non-diverting vehicles is reduced by 441 vehicle hours (difference between no diversion delay and diversion delay in Fig. 5.9). Since TSVD is considerably less than this value, the major system benefit for diversion results from benefits to non-diverting vehicles. This benefit results from the shorter queue on the facility with the incident. For this example the individual diverting vehicle benefits considerably more than the non-diverting vehicle.

5.1.7 Reduction in Corridor Delay Resulting from Diversion for Incidents

Total corridor delay reduction (CDS) includes the sum of the delay reduced by nondiverting vehicles and diverting vehicles less the additional delay incurred by the pre-diversion traffic on the diversion route (DAR). This may be expressed as:

$$CDS = DIF + TSVD - DAR (5.16)$$

This simplified model assumes that all traffic diverting from an incident will utilize the planned diversion route, and that pre-diversion traffic on the diversion

Green split shown excludes lost time (queue start up+clearance lost time)

route will also continue to use that route. A traffic assignment model will provide a better estimate of the traffic actually using this route.

As diversion volume approaches the capacity of the alternate route, Fig. 3.5 shows that DAR begins to increase exponentially, and the value of CDS may be significantly reduced.

5.2 Design Considerations for DMS Locations

Dynamic message signs may take a number of forms ranging from simple blank-out signs and portable signs to large installations. Figure 5.10 shows some examples of the larger signs used for informing motorists of non-recurrent traffic conditions such as construction, incidents and weather conditions.

A DMS of this type requires a significant capital investment, and these DMS often incur a large portion of the cost of an ITS project. It is therefore important that the number and location of these DMS be selected based on cost effective principles. The exact location of a DMS depends on a number of factors such as the sight distance considerations, constraints on installation due to roadway construction features, nearby environmental issues, power access availability and maintenance considerations. A number of these issues are discussed in Dudek [2]. The following sections treat the selection of DMS sites from a functional point of view, i.e. the effect of the DMS on notifying the motorist of incidents and other traffic related issues.

5.2.1 Basic Considerations for DMS Functional Placement

The key functional objective for locating DMS is to place them so that the maximum number of viewers will be exposed to the DMS for incidents downstream of the DMS. An example of a methodology for implementing this principle on a network-wide basis is described by Abbas and McCoy [9].

5.2.2 Simple Models to Assist in DMS Functional Placement

Many ITS projects are of limited scope and address the requirements of a single freeway or a portion of that freeway. This section describes two simplified models that may assist in determining the functional placement requirements for DMS for that purpose. The discussion adapts concepts from Ref. [9]. The general concept is illustrated in Fig. 5.11. The figure illustrates the simple case of a DMS located upstream of the last diversion opportunity prior to encountering the incident. The

Fig. 5.10 (a) Dynamic message sign displaying construction information (Source: Parsons Brinckerhoff, Inc.). (b) Small dynamic message sign displaying incident information (Source: Daktronics, Inc.). (c) Dynamic message sign displaying weather information and controlling speed (Source: Daktronics, Inc.)

Fig. 5.11 DMS just upstream of traffic entering mainline before incident queue

double-circled symbol in the illustration denotes the incident location and the checkered region represents the congestion building back from that point.

The probability that the motorist encounters a DMS prior to the section containing the incident (P34) for Section A is given by the fraction of motorists that become candidates for diversion as a result of the DMS and prior to encountering the congestion and incident. In this case the value is:

$$P34 = (VA - VA1) / VA$$ (5.17)

where

VA=Mainline volume upstream of queue formed by incident VA1=Entry volume downstream of DMS and upstream of incident

Sections 5.2.2.1 and 5.2.2.2 discuss the simplified models for the following cases:

• Origin-destination data are available.
• Origin-destination data are not available.

5.2.2.1 Computation of P34 when Origin-Destination Data are Available

This section provides a model for computing P34 for a single freeway when origindestination trip distribution information is available. This data may be obtained from the following sources:

• Planning models.
• Computer models that synthesize origin destination data (trip tables) data from traffic volumes.
• Special surveys employed for the collection of this data.

Consider the case where only one DMS is provided in the study roadway, and where no DMS is present upstream of the study roadway. This case is represented by the example shown in Fig. 5.12. The solid rectangle shows the DMS location.

Each of the E and X symbols represents a node at which the traffic enters or exits the roadway. Thus t23 represents the volume of traffic entering at node E2 and leav-

Roadway being analyzed

Fig. 5.12 Single roadway with one DMS

Roadway being analyzed

Fig. 5.13 Single roadway with multiple DMS

ing at node X3. E0 and X6 are the mainline volumes entering and exiting the study roadway. A DMS is shown as a shaded rectangle in Section 2. For an incident in a section, diversion will take place for traffic normally destined to exit at that section and beyond. Motorists destined for exits downstream of the section containing the DMS are candidates for diversion. The computation for P34 for Section J for the case shown is of the form:

$$P34(J) = \left( \frac{\text{Sum of the traffic volumes passing the DMS}}{\text{and exiting at or downstream of Section J}} \right) / M(D)$$ (5.18)

where D is the section containing the DMS.

For the example shown:

$$P34(3) = (t{03} + t{04} + t{05} + t{06} + t{13} + t{14} + t{15} + t{16} + t{23} + t{24} + t{25} + t{26}) / M(2) (5.19)$$

$$P34(4) = (t{04} + t{05} + t{06} + t{14} + t{15} + t{16} + t{24} + t{25} + t_{26}) / M(2)$$ (5.20)

$$P34(5) = (t{05} + t{06} + t{15} + t{16} + t{25} + t{26}) / M(2)$$ (5.21)

When roadways being analyzed contain more than one DMS, each DMS provides diversion capability for incidents in the sections downstream of that DMS, until another DMS is encountered. This case is represented by Fig. 5.13, which show DMS in mainline sections 1 and 3.

For the last DMS in the study area, diversion will occur for incidents in the sections downstream of that DMS. Qualifying traffic volumes are identified as follows:

• Origin node—All entering nodes between the upstream DMS and the subject DMS.
• Destination node—All exiting nodes starting with the section analyzed. Start with section downstream of the DMS.

In terms of the example

$$P34(4) = (t{24} + t{25} + t{26} + t{34} + t{35} + t{36}) / M(3)$$ (5.22)

$$P34(5) = (t{25} + t{26} + t{35} + t{36}) / M(3)$$ (5.23)

For DMS upstream of the last DMS in the study area, qualifying traffic volumes are identified as follows:

• Origin node—All entering nodes upstream of the DMS.If there is a DMS upstream of this one, limit the origin nodes to nodes that are downstream of that DMS.
• Destination node—All exiting nodes starting with the section analyzed (downstream of the DMS) and extending to and including the section with the downstream DMS.

In terms of the example

$$P34(2) = (t{12} + t{13} + t{14} + t{15} + t{02} + t{03} + t{04} + t{05}) / M(1)$$ (5.24)

$$P34(3) = (t{13} + t{14} + t{15} + t{03} + t{04} + t{05}) / M(1)$$ (5.25)

5.2.2.2 Computation of P34 for a Single Roadway When Origin-Destination Data are not Available

This section describes the probability that the motorist encounters a DMS prior to a diversion point for an incident when origin-destination data are not available. It uses a simple trip assignment process based on freeway mainline and exit ramp volumes. The computation of P34 is based on a recursive process and is illustrated by the following example of Fig. 5.14.

The diagram shows a DMS in Section 2. Definitions are as follows:

M(J) is the mainline AADT for Section J (volume between entry and exit locations.

X(J) is the sum of the exit ramp AADT for Section J.

R(J) is the residual volume after the exit ramps for Section J.

MD is the mainline AADT for the section with the upstream DMS closest to the section being analyzed.

Fig. 5.14 Example of single roadway with single DMS when no origin-destination data are available

| PROBABILITY THAT MOTORIST ENCOUNTERS DMS PRIOR TO INCIDENT (P34) | | | | | | | | | | |------------------------------------------------------------------|--------------|---------------------------------------------------|------|-------|-------|-------|----------|-------|--| | | | Required entry deoending on roadway configuration | | | | | | | | | SECTION DMS ON | | MAINLINE EXIT | | B | R | Basis | Intermed | P34 | | | n | SECTION AADT | | RAMP | | | | Comp | | | | | | | AADT | | | | | | | | -2 | 0 | 0 | 0 | 0.000 | 0 | 0 | | | | | -1 | 0 | 0 | 0 | 0.000 | 0 | 0 | | | | | 0 | 0 | 0 | 0 | 0.000 | 0 | 0 | | | | | 1 | 0 | 41800 | 4200 | 0.900 | 0 | 0 | 0.000 | 0.000 | | | 2 | 1 | 57200 | 5500 | 0.904 | 51700 | 57200 | 0.000 | 0.000 | | | 3 | 0 | 57150 | 5600 | 0.902 | 46634 | 57200 | 0.904 | 0.904 | | | 4 | 0 | 59750 | 5500 | 0.908 | 42341 | 57200 | 0.815 | 0.815 | | | 5 | 0 | 54700 | | | | | 0.740 | 0.740 | |

Fig. 5.15 Worksheet showing computation of P34

In addition to the sections in the roadway under analysis (section numbers higher than zero in Fig. 5.14), provision is made in the model for the possible location of the DMS in sections that are upstream of the roadway being analyzed. These are represented by sections numbered less than 1 in the figure.

For sections following the DMS, the distribution model computes the traffic that has been exposed to the DMS after the section's exit point (denoted as P34(J)) as the product of the exposed traffic entering the section, R(J) and the ratio of the total remaining mainline traffic after the exit point to the total mainline traffic in the section (BJ). The equations that express this relationship are:

$$B_{J} = 1 - X(J) / M(J)$$

$$(5.26)$$

$$R(J) = R(J-1) \cdot B_{J} \tag{5.27}$$

$$P34(J) = R(J-1)/M_D$$ (5.28)

Figure 5.15 shows an example of the computation of P34. This worksheet, Computation of P34, is provided on the website http://www.springer.com/us/ book/9783319147673. A "1" must be entered in the "DMS ON SECTION" column for each DMS on the roadway. Mainline volumes for a section containing a DMS upstream of the study roadway must be entered, along with volumes from that

section to the study roadway. Exit ramp volumes for all sections upstream of the study region and in the study region (except for the last section) must be entered.

Using these equations or the worksheet, it is possible to determine the most effective placement for DMS (based on the probability that the motorist passes a DMS prior to the section containing the incident) by analyzing various numbers and locations of DMS.

5.3 Quality of Motorist Information

Support for ITS rests, in large measure, on its ultimate customers, i.e. the motorists and their perceptions of the value of the service. Customer satisfaction is traditionally measured by stated preference surveys. Some states proactively solicit feedback on ITS as well as on other transportation services. Delaware DOT, for example, solicits information on the importance of a service. In 2009, the survey reported performance on "information on when to expect delay, road closings" as 5.1 on a scale of 1–7 [10].

In some cases studies are conducted to identify the quality and value of particular services. Evaluation of 511 systems resulted in a customer satisfaction rate of 71 % in Arizona, 68 % in Washington State [11], 92 % in the San Francisco Bay Area and 90 % in Montana [12].

From the system designer's perspective, the quality or perceived benefit of motorist information depends on the following:

• Availability of technology and services to detect and confirm incidents and congestion related to incidents.
• Availability of traffic management center staff to implement messages at the time of the incident (a number of centers do not provide full time coverage).
• The ability of the motorist to receive and understand the message.

5.4 ITS and Technology Applications in Emergency Evacuations

5.4.1 Introduction

Many agencies at all levels of government participate in emergency evacuation planning and operations. Successful culmination of these efforts involves interagency coordination and appropriate use of the assets available to the participating organizations.

Situations that may arise include:

• Evacuations for which affected locations may or may not be anticipated in advance.
• The approximate time for the evacuation may or may not be anticipated in advance.

The types of situations that typically require evacuation include:

• Weather related incidents such as hurricanes.
• Hazardous material related incidents.
• Nuclear power plant incidents.
• Homeland security related events.

Emergency evacuations typically require planning and coordination by a number of agencies at all levels of government. The Freeway Management and Operations Handbook [13] provides an introduction to the subject.

5.4.2 ITS and Technology Applications

The principal role of ITS and ITS related technology to support emergency evacuations includes planning, traffic controls, and highway and traffic related information.

5.4.2.1 Planning

The following are commonly used tools to assist in the planning of multi-agency responses to emergency management and evacuation situations:

• By providing a common mapping reference for different agencies, the use of GIS systems facilitates the organization of emergency evacuations. Functions include disaster forecasts, vulnerability analysis, resource inventories, existing infrastructure inventory, shelter identification and status [14].
• Simulations to model traffic evacuation routes, demands, capacities and emergency response traffic control measures. An example of a simulation available for this purpose is the Oak Ridge Evaluation Modeling System (OREMS) [15].

5.4.2.2 Traffic Controls

Elements of the evacuation plan may include traffic controls. Examples of the use of traffic controls include:

• Special timing provisions for traffic signals. Provisions may include signal timing plans that support evacuation routes, usually by means of longer green split periods along the evacuation route and longer cycle lengths. In some cases it may be appropriate to provide a constant green indication along the route.
• Contra-flow lanes on freeways. HOV lanes and reversible lanes may be used for this purpose, or conventional lanes may be reversed in support of an overall traffic management plan. In some cases ancillary traffic controls such as lane control signals and ramp access gates may be used to support the plan.

Fig. 5.16 Information dissemination model

Static signing is often used to identify emergency evacuation routes to motorists.
CCTV is used to assist traffic management centers to support clearance of traffic incidents along emergency routes.

5.4.2.3 Highway and Traffic Related Information

The motorist information delivery technologies listed in Table 5.1 are used to provide information during evacuations. During these events, the traffic management center serves as one element in the overall evacuation management process. The following discussion and Fig. 5.16 depicts an information dissemination model. It is abstracted from Ref. [16].

The information flows depicted in Fig. 5.16 are intended to illustrate the full range of information that is generated and communicated to the public throughout a disaster situation. There are elements of timing and dependency relationships that come into play as a disaster unfolds, as participants enter or exit the picture and as information evolves. Moreover, the information flow embodies a continuous feedback loop which incorporates the response of the public to the information received and the outcome of disaster mitigation.

References

1. Connected Vehicle Applications, Research and Innovative Technology Administration, U.S. Department of Transportation. http://www.its.dot.gov/connected\_vehicle/connected\_vehicle\_ apps.htm Online 14 Sept 2014
2. Dudek CL (2004) Changeable message sign operation and messaging handbook. Federal Highway Administration Report No. FHWA-OP-03-070, Federal Highway Administration, Washington, DC
3. Travel Time Messages on Dynamic Message Signs, Federal Highway Administration. http:// ops.fhwa.dot.gov/travelinfo/dms/signs.htm Online 14 Sept 2014
4. DTA System Enhancement and Evaluation of Traffic Management Center, Task P: Framework for the Use of DynaMIT-P (2000) Massachusetts Institute of Technology
5. Peeta S et al (2000) Content of variable message signs and on-line driver behavior. In: 79th annual meeting of the Transportation Research Board, Washington, DC
6. Mansoureh J, Ardshirri A (2013) Exploring travelers' behavior in response to dynamic message signs (DMS) using a driving simulator. Report No. MD-13-SP209B4K, Morgan State University, Oct 2013
7. Foo S et al (2008) Impacts of changed CMS messages on traffic diversion rates. In: 87th annual meeting of the Transportation Research Board, Washington, DC
8. Kachroo P, Ozbay K (1999) Feedback control theory for dynamic traffic assignment. Springer, London
9. Abbas MM, McCoy PT (1999) Optimizing variable message sign locations on freeways using genetic algorithm. In: 78th annual meeting of Transportation Research Board, 10–14 Jan 1999, Washington, DC
10. 2009 report on customer satisfaction. Delaware Department of Transportation
11. Intelligent transportation systems for traveler information—deployment benefits and lessons learned. U.S. Department of Transportation. http://www.its.dot.gov/jpodocs/repts\_te/14319. htm. Accessed 27 May 2008
12. Americas travel information number—implementation and operational guidelines for 511 services, version 3.0 (2005) 511 Deployment Coalition, Washington, DC
13. Neudorff LG et al (2003) Freeway management and operations handbook. Federal Highway Administration Report FHWA-OP-04-003, Federal Highway Administration, Washington, DC
14. Pal A et al (2005) Enhancements to emergency evacuation procedures. UTCA Final Report 01105, University of Alabama, Tuscaloosa, Alabama, Aug 2005
15. Oak Ridge evaluation modeling system (OREMS), Center for Transportation Analysis, Oak Ridge National Laboratory. http://cta.ornl.gov/cta/One\_Pagers/OREMS.pdf. Accessed 27 May 2008
16. Communicating with the public using ATIS during disasters—concept of operations (2006) Batelle and PBSJ, Columbus, OH

Chapter 6 Recurrent Congestion: Information to Motorists

Abstract Section 3.1.3 briefl y describes the differences between recurrent congestion and non-recurrent congestion. This chapter further elaborates on recurrent congestion. Discussion includes practices employed by traffi c management centers and others in the provision of motorist information. The time periods when recurrent congestion is experienced, along with the variations in these periods, is discussed. The chapter covers diversion under recurrent congestion conditions, and describes the opportunities for diversion during shoulder periods.

6.1 Nature of Recurrent Congestion

Non-recurrent congestion, discussed in Chaps. 4 and 5, is generally caused by a temporary reduction in the normal capacity of the roadway. Recurrent congestion generally occurs when demand for the facility use exceeds the facility's capacity and results in low average travel speeds, poor levels of service, and possible diffi culty in access to and egress from the freeway. The demand trends and the resulting congestion are, within limits, generally repetitive. Severe recurrent congestion in major metropolitan areas is often experienced during peak commuting periods. Weekend shopping and recreation travel also often generate recurrent congestion. Congestion caused by special events is treated by some traffi c engineers as recurrent congestion and by others as non-recurrent congestion.

6.2 Motorist Information During Recurrent Congestion

Section 5.1.1.1 describes the techniques and technologies commonly employed for providing motorist information. While the same technologies are used for providing information for recurrent and non-recurrent congestion, the types of information displayed may be somewhat different. Table 6.1 shows the types of information often provided by messaging technologies.

Figure 6.1 shows a typical recurrent congestion message. Travel time information, as recommended by FHWA is also often displayed [ 1 ]. When no congestion is present, the DMS may be left blank or a default message such as that shown in

Technology	Recurrent congestion messages	Non-recurrent congestion messages
Information provided by state
DMS	Travel time, delays, no delays, default messages, or blank sign representing no delays a	Location and nature of incident, delays, possible alternate route information, construction information
HAR	Rarely used	Location and nature of incident, delays, possible alternate route information, construction, weather, evacuation information
State website/511 website	Delays, travel time, traffi c condition status map, travel time reliability	Location and nature of incident, construction, weather, evacuation information
511 telephone	Delays, travel time b	Location and nature of incident, weather, evacuation information
Information provided by others
Conventional and satellite commercial radio	Delays, limited travel time information. Reports often emphasize common congestion locations such as water crossings. Estimates of delays are sometimes provided	Location and nature of incident, construction information, weather, evacuation information
Real time GPS based information service	Quickest route, travel condition map	Quickest route, travel condition map, location of incident and construction

Table 6.1 Message content for recurrent and non-recurrent congestion

Fig. 6.2 may be used (motorists familiar with the system understand that such messages indicate that no congestion is present).

Semi-automatic message strategies of the type described in Sect. 5.1.4.2 based on point or probe detector information or on information from suppliers of traffi c information may be displayed. Messages for these strategies are generally developed without any consideration of the cause of the congestion and thus they frequently provide recurrent congestion related information. When an incident occurs, in most cases the operator will replace the automatically developed message with another message that describes the incident, its location, and possible recommended remediation recommendations.

6.3 Variations During Periods of Recurrent Congestion

Recurrent congestion is common and pervasive during peak periods in major metropolitan areas, and is generally characterized by low speeds. Variations in day-ofweek demands, monthly demands, and random demands result in day-to-day speed and travel time variations for the same trip made at the same time of day.

If policy requires provision of recurrent congestion information on DMS

b Some sites may indicate when conditions are clear

Fig. 6.1 Typical recurrent congestion message

Fig. 6.2 Typical default message implying lack of congestion

As an example of these variations, the horizontal tics in Fig. 6.3 show the mean speed measured at a location in Portland, Oregon for weekdays from April 1, 2008 until April 11, 2008. The vertical bars represent the range of speeds encompassing one standard deviation above and one standard deviation below the mean. Thus, for the hour ending at 4 PM, the northbound detector station at milepost 304.4 reported

Fig. 6.3 Average speed and standard deviation for I-5 NB milepost 304.4. Data for this fi gure were developed using the Portland Oregon Regional Transportation Archive Listing (PORTAL). PORTAL was developed by Portland State University under the direction of Dr. Robert Bertini

a mean speed of 19.6 mph for this period and a standard deviation of 6.3 mph. This peak period also extends into the next hour. Although the mean speed is above 30 mph for the hour preceding and the hour following the peak period, the standard deviation is also high for these shoulder periods.

Standard deviation is a measure of travel time reliability. Provision of congestion, speed or travel time information enables the motorist to reduce his/her anxiety level by providing an indication, at least in some cases, of his anticipated delay. In some cases it provides diversion opportunities. Figure 6.4 is an example of travel time reliability information provided by the Washington State DOT 511 website.

6.4 Diversion During Recurrent Congestion

Congestion patterns in major urban areas generally follow Wardrop's principles (see Sect. 3.1.5). These principles indicate that although recurrent congestion delays may be signifi cant, diversion in the absence of non-recurrent congestion is not likely to be productive for either the individual motorist or for the entire system.

Wardrop's principles are, however, predicated on the assumption that conditions are invariant, and therefore that the motorist is aware of conditions on the routes in

123 Reference

Fig. 6.4 Internet message for travel time reliability

the travel corridor. Figure 6.3 and similar data, however, show signifi cant levels of variation during these periods. This variation may present opportunities to reduce delay under some conditions.

Although speeds may be low during peak periods, speeds on the alternates are usually also low during these periods, so that signifi cant diversion opportunities are relatively rare. During shoulder periods, however, there are times when the freeway speed is low, as shown in Fig. 6.3 , and since volume-to-capacity ratios on the alternate routes are generally lower than during peak periods, there may be opportunities for diversion during these periods.

Because diversion opportunities are limited and delay savings resulting from DMS recurrent congestion messages generally amount to only a few minutes per trip, system-wide savings are usually modest. The savings are, however, generally achieved at little or no marginal cost.

Reference

Travel time messages on dynamic message signs. Federal Highway Administration. http://ops. fhwa.dot.gov/travelinfo/dms/signs.htm Online 14 Sept 2014

Chapter 7 Ramp Metering

Abstract Ramp metering is commonly used in major metropolitan areas to reduce freeway delay and improve safety. It does this by 1) smoothing the flow of traffic at the merge and thereby increasing effective freeway capacity and safety and 2) reducing the traffic entering the freeway which reduces the volume to capacity ratio. Topics covered by this chapter include:

• Ramp meter physical installation requirements and ranges of metering rates.
• Traffic flow breakdown models and the role of ramp metering in improving breakdown.
• Ramp metering strategies including pretimed, traffic responsive, isolated and systemwide ramp metering.
• Ramp storage requirements and ramp queue control strategies.
• Ramp metering acceptance by the public.
• Ramp metering benefits model.

7.1 Introduction

Entry ramp control strategies include

• Ramp metering.
• Ramp closure.
• Special treatments including bus by-pass lanes on metered ramps.

Use of these treatments is described in the Freeway Management and Operations Handbook [1] and the Ramp Management Handbook [2]. These references provide guidance in the implementation of these treatments. Ramp metering is the most commonly used of these treatments and is the subject of this chapter.

Ramp metering is implemented by a traffic signal on a freeway entry ramp (Fig. 7.1). By smoothing the flow at the merge with the mainline, it increases the service rate (bottleneck capacity) of the mainline, and reduces the accident rate. If the metering rate is established at a value that is below the average arrival rate at the ramp (restrictive ramp metering), a queue will build on the ramp causing additional delay to the arriving vehicles. As a result, some of these vehicles will seek alternate routes, thereby reducing the demand volume at the entry ramp merge with the mainline.

Fig. 7.1 Ramp meter signal display

This, in turn, reduces the demand volume-to-capacity ratio at the merge and downstream of the merge, and reduces the delay to the vehicles on the freeway mainline. Metering rates that are equal to the average vehicle arrival rate (nonrestrictive ramp metering) build much smaller queues and generally do not result in significant volumes of traffic seeking alternate routes.

7.2 Background

7.2.1 Early Metering Projects

One of the first projects to establish the ability of metering to increase lane flow was conducted in the Lincoln Tunnel [3]. Lane changes are not permitted in the tunnel and bottleneck flows are frequently experienced at the foot of the upgrade in the tunnel. Early experiments showed that using fixed rate metering improved lane throughput from 1,200 cars per lane per hour to 1,320 cars per lane per hour. Once congestion set in, the higher throughput could not be sustained. A later experiment provided control based on volume and speed measurements. The results of the experiment are shown in Table 7.1.

Ramp metering projects started in the 1960s in Chicago, Detroit, Los Angeles and Houston These projects included pretimed metering and traffic-responsive metering have been expanded over the years. 28 metropolitan areas in the United States currently operate ramp metering systems, and other parts of the world also use this technology.

127 7.2 Background

Table 7.1 Results of Lincoln tunnel metering experiment [3]

	Uncontrolled	Controlled
Average throughput (cars/lane/hour)	1,210	1,290
Maximum throughput over a half-hour period	1,260	1,430
Average speed (feet/second)	27.2	40.9
Average density (cars/mile)	75.8	47.5

7.2.2 Ramp Meter Installation Requirements

Several types of metering installations are employed depending on the metering rates to be used and the configuration of vehicle storage capability on the ramp. For example, a single lane or multiple lanes may be metered. Metering may permit only one vehicle to pass the stop line per signal cycle or may permit multiple vehicles to pass (platoon metering).

Figure 7.2 [1] depicts a common deployment for a single lane, single vehicle meter. A standard 3-section (red-yellow-green), or 2-section (red-green) signal display is provided. The signals may be either mast arm or pole mounted. A sign or beacon is often used to indicate that metering is in effect.

For single vehicle meters, the metering rate is established by defining a metering cycle equal to the reciprocal of the desired metering rate. If the previous cycle has timed out (turning the signal to red), the signal will change to green when a vehicle is detected by the check-in (or demand) detector. When the vehicle is sensed by the check-out or passage detector the green interval is then terminated. The signal will remain in red until the traffic cycle times out, at which time it will respond to the next arriving vehicle detected by the check-in detector.

Some ramp metering installations use merge detectors. The merge detector senses the presence of vehicles in the primary merging area of the ramp and freeway mainlines. When the merge detector senses a stopped vehicle blocking the merge area, the signal may be held in red for some preset maximum time in order not to congest the area and to reduce the possibility of a rear end collision [1].

One or more queue detectors are commonly used to prevent the queue from spilling back into the surface street traffic stream. Detection of vehicles by the queue detector increases the metering rate or terminates the ramp metering. Strategies for accomplishing this are described in Sect. 7.4.5.2. In some cases the queue detector may be used to limit ramp waiting time to a specified value [1]. As discussed in Sect. 7.4.5.1, the lack of adequate vehicle storage capacity often limits the effectiveness of restrictive ramp metering.

Mainline detector placement is closely related to the particular control strategy implemented (see Sect. 7.4). To be meterable, the physical and traffic demand characteristics of ramps must lie within certain values. Deployment requirements for ramp metering are listed in Sect. 7.4.5. Acceptable ramp meter rates are shown in Table 7.2.

Fig. 7.2 Single-lane entry ramp metering system layout

7.3 Flow Characteristics and Freeway Capacity

7.3.1 Flow Characteristics for Near-Capacity Conditions

As traffic demand (i.e., volume) increases, density increases with a corresponding decrease in speed. As vehicle demand approaches highway capacity, traffic flow begins to deteriorate. Traffic flow is interrupted by periods of turbulence that disrupt efficiency. Traffic flow then begins to break down rapidly, followed by further deterioration of operational efficiency. An example of the breakdown in stable flow is shown in Fig. 7.3.

Table 7.2 Ranges of ramp metering rates [4]

Types of metering	Number of metered lanes	Approximate range of metering rates (v/h)	Comments
Single vehicle entry per green interval	1	240–900 v/h	Full stop at the meter usually not achieved at 900 v/h metering rate
Tandem metering— single vehicle entry	2	400–1,700 v/h	Applies when required metering rate exceeds 900 v/h
per green interval per lane			Requires two lanes for vehicle storage
			Vehicles may be released from each lane simultaneously or sequentially
Platoon metering— single lane multiple	1	240–1,100 v/h	Platoon lengths permit passage of 1–3 vehicles per green interval
vehicle entry per green interval geometrics			Principally used to increase metered volumes when geometrics do not permit use of more than one metered lane
			Requires changeable sign indicating permitted number of vehicles in green interval

Fig. 7.3 Time trends for speed and flow during AM peak period. From, Transportation Research Record: Journal of the Transportation Research Board, No. 1748, Transportation Research Board of the National Academies, Washington, D.C., 2001, Figure 1, p. 111. Reproduced with the permission of the Transportation Research Board

Fig. 7.4 Conceptual volume vs. density diagram

There has been considerable research (e.g. References [5] and [6]) into identifying the properties of transitions between non-congested, stable flow and congested, unstable flow. Banks [6] suggests the models shown in Fig. 7.4. Line segments OAC constitute the inverted V model and line segment AB is added for the reversed lambda model. The dotted ovals indicate that considerable variation in the values of the actual data points is experienced. Jam density is the value of density when the traffic is stopped.

As volume increases, average density increases in an approximately linear relationship until the volume reaches the approximate location of Point A. This near linear relationship implies little speed change. When volume nears this point, the probability of the flow transitioning to an unstable state arises. This is generally characterized by lower volume, lower speed and higher density. The location in a section of highway at which this transition first occurs is termed a bottleneck location. Bottlenecks typically occur at or near entry ramps as a result of merged traffic volumes that exceed roadway capacity. Line segment AC depicts the general trend in the unstable state, however the actual data may vary widely from this trend. In Fig. 7.5 Shawki and Nakamura [7] show the best data point fit for the cumulative distribution for the maximum pre-breakdown flow and outflow rates (discharge flow from the queue after flow breakdown) on a section of a freeway in Tokyo.

Shawki and Nakamura [7] represent the cumulative probability distribution P(x) by the Weibull Logistic and Normal functions of the form

$$P(x) = 1 - \exp(-(x/\beta)^{\alpha})$$ (7.1)

where

x=outflow (queue discharge volume in passenger cars per hour per lane) α=shape parameter

β=scale parameter

For the location used for Fig. 7.5.

α=28.7 β=2,256

An example of the flow breakdown probability in the Toronto area is shown in Fig. 7.6.

Fig. 7.5 Cumulative probability of distributions (redrawn). From, Transportation Research Record: Journal of the Transportation Research Board, No. 2012, Transportation Research Board of the National Academies, Washington, D.C., 2007, Figure 6b, p. 14. Reproduced with the permission of the Transportation Research Board

Fig. 7.6 Probability of flow breakdown for 1-min periods. From, Transportation Research Record: Journal of the Transportation Research Board, No. 1748, Transportation Research Board of the National Academies, Washington, D.C., 2001, Figure 5, p. 113. Reproduced with the permission of the Transportation Research Board

7.3.2 Effective Capacity Improvement Through Ramp Metering

This section describes the effect of ramp metering on the flow breakdown characteristics described in the previous section. The discussion uses the concepts and data described in Zhang and Levinson [8]. That reference examines the traffic flow characteristics at 27 PM peak period active bottlenecks in the Twin Cities area with and without ramp metering. The motivation for the test is discussed in Sect. 7.5.2.

Figure 7.7 shows the model used by Zhang and Levinson to analyze flow breakdown situations. As volume increases during the peak period and crosses the queue discharge flow level, a pre-queue transition period commences. The steady state queue discharge flow is shown by the dashed lines in the figure. The pre-queue transition period lasts until the flow equals the steady state queue discharge flow. During this period, several instances of flow breakdown and restoration to pre-breakdown conditions may occur. In time, the flow decreases below the values shown in the figure shown as a result of the decrease in demand. Ramp metering delays flow breakdown and results in higher discharge rates after breakdown.

Fig. 7.7 Flow profiles at a bottleneck with and without ramp metering

While the results vary considerably from ramp to ramp, Zhang and Levinson's results revealed the following average improvements:

• Ramp metering increased the average pre-queue transition period from 60 min to nearly 2 h, a 73 % increase.
• The average flow during the steady state queue discharge period is 5.8 % lower than during the pre-queue transition period. Thus the extension of the pre-queue transition period results in a considerable reduction in delay.
• The average value of the flow during the pre-queue transition period is 3 % higher with ramp metering.
• The average value of the flow during the steady state queue discharge period is 2 % higher with metering.
• The average number of flow breakdown occurrences per afternoon peak period reduced from 1.2 without metering to 0.4 with metering. This occurs in part because of the elimination of flow breakdown at approximately half of the locations studied.
• Reducing the number of queues and their duration reduces the probability of spillback of these queues to the next upstream entry ramp.

In a subsequent paper, Zhang and Levinson [9] identify the following types of capacity increases resulting from ramp metering.

• Type 1—Capacity upstream of the bottleneck is improved because the queue formed by the bottleneck is shorter and flow remains stable for a longer period.
• Type 2—Capacity is increased at the bottleneck as described above.

7.3.3 Freeway Service Improvement Through Ramp Metering

Both non-restrictive and restrictive ramp metering improve freeway throughput, delay and safety in the following ways:

• Smoothing the merge flow through ramp metering has been shown to reduce the crash rate. A survey of management centers in eight cities found that ramp metering reduced the accident rate by 24–50 % [10]. The accident rate improvement includes the reduction of secondary accidents and the delays resulting from both primary and secondary accidents.
• A large number of studies report significantly reduced travel time resulting from ramp metering. For example, non-restrictive ramp metering on Long Island provided an improvement of 20 % [10]. Restrictive ramp metering may provide additional benefits as described below.
• Ramp metering may provide throughput increases. For example, system-wide restrictive ramp metering resulted in a 10 % increase in freeway volumes in the Minneapolis-St. Paul, Minnesota area [11].

Fig. 7.8 Example of local restrictive ramp metering

Restrictive ramp metering provides an additional benefit resulting from the reassignment of traffic resulting in a decreased demand for the ramp. This concept is illustrated by the following simple example showing restrictive metering at a single ramp. Figure 7.8 shows a freeway (line FBD) and an alternate route (EACD). Prior to metering, the volume entering the ramp at location B exceeds the 5,000 vph capacity and causes a queue to build as shown in the figure, resulting in a delay of 400 vehicle hours during the 2 h peak period. Prior to metering, most of the vehicles on link EA that are destined for location D and beyond choose to use the freeway because the trip is 2.75 min shorter. The downstream merge volume of reassigned traffic with the freeway traffic at location D results in a volume that is below the freeway capacity at this point.

VEHICLE HOURS FOR	TRAFFIC WI	TH
ROUTE CHOICES AT E
AND BACKROUND TRA
7.11.2 27.101.11.1001.12 11.11
Unmetered entry ramp v	olume (UFRV)		800
Metered entry ramp volu			400
Base alternate traffic (B			400
Diverted alternate traffic			400
Traffic entering alternate		Δ)	1000
Traine critering anomate	at point o (o i	, , , , , , , , , , , , , , , , , , ,	1000
SEGMENT	Unmetered	Unmetered	Metered	Metered
	Alternative	Alternative	Alternative	Alternative
	Trav time	Vehicle	Trav time	Vehicle
	(min)	Hours	(min)	Hours
	` ′		,
AC	3.0	40.0	3.0	80.0
BD	3.0	80.0	3.0	40.0
CD	3.0	140.0	4.0	240.0
AB	0.3	6.7	4.8	63.3

Subtotal		266.7		423.3

Vehicle hours in mainline	e queue	400.0		0.0
		666.7
	Total - Travel time on alternate +			423.3
mainline queue delay

System delay reduced by metering		243.3	vehicle ho	urs
Travel time for vehicles at point A with metering (minutes)
By freeway	7.8		uies j
By alternate	7.0
by alternate	7.0	l	1

Fig. 7.9 Worksheet for restrictive ramp metering example

Figure 7.9 contains the pertinent data for the metered and unmetered situations. With the initiation of ramp metering at an entry rate of 400 vehicles per hour, the queue builds on the entry ramp until the travel time via the freeway route and the alternate route are approximately equal.

The vehicle hours traveled for the segments (other than the mainline queue) were computed by the relationship:

Restrictive metering of this ramp results in a significant reduction in system delay. These benefits are typically not, however, evenly distributed among all motorists. In this example, improvements resulting from the elimination of the mainline queue accrue to motorists on the mainline upstream of the ramp at location A.

Motorists on the alternate route destined for location D and beyond, whether entering the freeway ramp, remaining on the alternate route, or entering the alternate route at a location downstream of the metered ramp experience a longer trip time.

7.4 Ramp Metering Strategies

The previous sections provide the general background on ramp metering and describe the mechanisms that ramp metering provides for relieving congestion. There are, however, potential negative effects that may result from ramp metering. These include:

• Additional delay to motorists that normally enter the ramp, even if they elect to use an alternate route.
• Additional delay to motorists that do not normally use the ramp but that do use an alternate route.
• Possible spillback of traffic onto the surface street network.
• Motorist dissatisfaction resulting from the above.

The success of a ramp metering project depends, in part, on planning efforts to determine if metering is, in fact, feasible, and to select the metering strategy that best addresses the specific issues. Simulation is often a valuable tool for estimating the effects on the alternate routes, on the highway system in the vicinity of the metered ramp and on the additional travel time that the ramp users and divertees will experience. It may assist in selecting the ramp metering strategy to be employed.

7.4.1 Overview of Metering Strategies

The metering rate for non-restrictive ramp meters is established at a higher level than the average arrival rate. The ramp queues are relatively short, consisting essentially of vehicle platoons released from an upstream signal or small vehicle platoons where the surface street upstream of the ramp is not signal controlled. The queue usually clears before the arrival of the platoon released by the subsequent signal cycle. The instrumentation requirements are relatively low (no mainline detectors are required) and communication with the traffic management center is not essential.

Restrictive ramp metering strategies include local metering strategies, systemwide metering strategies and pretimed and traffic responsive metering strategies. Successful restrictive ramp metering treatments usually depend on detailed planning efforts. Table 7.3 provides a summary of the major characteristics of restrictive ramp metering strategies.

Restrictive ramp metering provides a higher level of overall system benefits than does non-restrictive ramp metering. As discussed in Sect. 7.5, restrictive ramp metering may result in perceived disbenefits to a significant number of motorists. Where agencies have encountered this issue or expect that the introduction of

Table 7.3 Characteristics of restrictive ramp metering strategies

	Pretimed		Traffic-responsive
	Local metering	System-wide metering	Local metering	System-wide metering
Functions
Safety improvements through flow smoothing	Useful	Useful	Useful	Useful
Capacity improvements through flow smoothing	Useful	Useful	Useful	Useful
Congestion at a bottleneck that can be mitigated by metering at a single ramp	Useful	Not required	Useful	Not required
Significant number of non-meterable ramps between metered ramps	Useful	Can possibly improve local metering performance	Useful	Can possibly improve local metering performance
Congestion at a bottleneck requiring metering at a number of upstream ramps	Not useful	Useful	Not useful	Useful
Traffic reassignment on a long term (strategic) basis	Useful	Useful	Can possibly improve pretimed metering performance	Can possibly improve pretimed metering performance
Traffic reassignment on a short term basis (including non recurrent events)	Not useful	Not useful	Useful	Useful
Implementation issues
Manual data collection	Usually required	Usually required	Not usually required	Not usually required
Mainline detectors	Not required but may be used to establish data base	Not required but may be used to establish data base	Required	Required
Management by TMC and field communication with TMC	Useful but not required	Useful but not required	Required	Required
High level of vehicle storage capability	Required	Required	Required	Required
Ramp queue spillback protection	Required	Required	Required	Required
Capital and maintenance cost	Relatively low	Relatively low	Higher per metered ramp	Highest per metered ramp

restrictive ramp metering may result in adverse publicity, the increased capacity and reduction in accident rate provided by non-restrictive ramp metering may provide a viable alternative. Ramp delays associated with non-restrictive ramp metering are usually minimal, and motorists often recognize the benefit of the smoother merge. Non-restrictive ramp metering may also be useful when sufficient storage space for restrictive ramp metering is not available.

7.4.2 Pretimed Restrictive Ramp Metering

Pretimed restrictive local ramp metering is appropriate for mitigation of recurrent congestion when the alternate routes downstream of the meter can accommodate the reassigned traffic and:

• Control of upstream ramps is not required to relieve congestion at the ramp merge or in the downstream section fed by the merge or
• It is not possible to meter upstream ramps.

A typical application is the mitigation of congestion at a single bottleneck as illustrated by the example in Sect. 7.3.3.

Pretimed restrictive system-wide ramp metering may be used to relieve recurrent congestion when:

• Metering a single ramp cannot provide a sufficient reduction in freeway volume. The lowest feasible metering rate at a ramp upstream of the bottleneck may not be sufficient to reduce demand to a level that is below bottleneck capacity. Metering of additional upstream ramps may be able to achieve or more closely approach this objective.
• The presence of multiple bottlenecks requires the consideration of metering at a number of ramps.

May [12] formulates relationships (termed demand-supply analysis) for a series of ramps in a manner that is generally similar to that shown in the example of Sect. 7.3.3. He describes the optimal control strategy for system-wide ramp metering as a linear programming procedure that maximizes mainline volume. His analysis treats the traffic diverted to the alternate route in a simple fashion.

Constraints in the linear programming formulation include the following:

• Volumes on each freeway link must be below capacity.
• Metering rates must fall within practical limits.
• It may not be possible to control some entry ramps. In this case the freeway entry volume equals the arrival volume at the ramp.
• There may be additional constraints such as limitations on the size of the ramp queue and limitations on the volume of re-assignable traffic resulting from capacity limitations on the alternates.

The design of this system-wide pretimed ramp metering strategies may be facilitated by the use of simulation [13].

7.4.3 Local Traffic Responsive Restrictive Ramp Metering

Local traffic responsive ramp metering provides the capability to adjust the metering rate to real time traffic conditions in the vicinity of the metered ramp. Local traffic responsive metering is also employed as a component of a number of system wide traffic responsive metering strategies.

7.4.3.1 Occupancy

By accommodating to day-to-day variations and shorter term variations in mainline traffic volume, local traffic responsive ramp metering can improve performance relative to pretimed metering. Many ramp metering control algorithms use occupancy as the key parameter to establish metering rates.

Occupancy is the ratio of the time that vehicles occupy the detection zone of a traffic detector to a specified time period. It is sometimes used in ITS as a surrogate for traffic density (vehicles per lane per mile).

Different types of traffic detectors provide different vehicle sensing distances on the lane, that is, the occupancy time of a vehicle as sensed by a detector is:

$$t{j} = (LV + LD) / S{j}$$

$$(7.3)$$

where

$t_j$ =occupancy period sensed by detector for vehicle j LV=length of vehicle LD=length of detector sensing area $S_i$ =speed of vehicle j

The values of t are summed over a time period and divided by that time period to obtain the occupancy as indicated by that type of detector according to:

$$\theta = (1/T) \cdot \sum_{j=1}^{m} t_j \tag{7.4}$$

where:

$\theta$ =occupancy over averaging period T as indicated by the detector m=number of vehicles passing the detector during time period T

Shawky and Nakamura [7] relate flow breakdown probability to occupancy in the same way that they did for volume (Fig. 7.5). Figure 7.10 shows the best fit to the data points for a particular ramp merge. Shawshy and Nakamura indicate that the relationship between flow breakdown probability and occupancy is more consistent among different ramp locations than is the relationship to volume, and therefore may be more preferable to use as a control variable. This observation is reinforced by the Australian Freeway Ramp Signal Handbook which notes that the critical volume point (o_cr in Fig. 7.11 [14]) is more stable and consistent under varying weather and lighting conditions.

Fig. 7.10 Cumulative probability of flow breakdown vs. occupancy (redrawn). From, Transportation Research Record: Journal of the Transportation Research Board, No. 2012, Transportation Research Board of the National Academies, Washington, D.C., 2007, Figure 8a, p. 16. Reproduced with the permission of the Transportation Research Board

Fig. 7.11 Flow vs. occupancy regimes

Figure 7.12 shows a plot of volume vs. occupancy data for 1 min periods taken prior to the start of the PM peak period and continuing into that period. The trend lines in the figure may be compared to the trend lines in the volume vs. density plot of Fig. 7.4. The zero volume intercept of the congested condition trend line in

Fig. 7.12 Volume vs. occupancy data (Developed from Portland Oregon Regional Transportation Archive Listing—PORTAL)

Fig. 7.12 corresponds to the jam density point of Fig. 7.4. Its value is less than 100 % occupancy because, for most detectors, the apparent length that the detector itself contributes when each vehicle is sensed is less than the space between vehicles at jam density. For example, the sensed distance for the commonly used 6 ft square inductive loop detector is approximately 6 ft. The inter-vehicle distance at jam density is longer. Thus the average spacing between vehicles at jam density is greater than the detector's sensed distance along the of the roadway and an occupancy value of 100 % will not be obtained even under highly congested conditions.

7.4.3.2 Explicit Scheduling of Metering Rate

One commonly used control approach is to schedule the metering rate as a function of the occupancy measured during the previous time interval as shown in Table 7.4 [15]. Occupancy is measured by means of mainline detectors situated near the ramp merge with the mainline as shown in Fig. 7.2.

Occupancy data, however, exhibits considerable minute-to-minute variation, particularly when operation is in the transition region between the non-congested flow regime and congested flow. Figure 7.13 shows a portion of the data for 1-min intervals at the same location as for Fig. 7.12. This data encompasses the transition period between uncongested and congested flow as well as a portion of the congested flow period.

Table 7.4 Example of metering rate schedule Occupancy (%)

	Metering rate (vehicles/minute)
≤10	12
11–16	10
17–22	8
23–28	6
29–34	4
>34	3

Fig. 7.13 Occupancy data vs. time for 1-min intervals (Developed from Portland Oregon Regional Transportation Archive Listing—PORTAL)

If control were to be implemented using raw data, the current occupancy might be considerably different from the value during the previous interval, i.e. the interval whose data are used to set the parameters for the current interval's metering rate. This would result in considerable variation in the metering rate during successive intervals. In order to mitigate this problem, many ITS use occupancy data that is processed by a filtering or smoothing process. The relationship for a first order linear filter that is commonly used [4] is:

$$\theta{O}(j) = \theta{O}(j-1) + K \cdot (\theta{I}(j) - \theta{O}(j-1))$$ (7.5)

where:

θO(j)=Filter output after the jth instant

θI(j)=Filter input data value (average value of variable between j−1 and j instants) K=Filter coefficient in the range 0–1.0; (K=1.0 represents no filtering)

Fig. 7.14 Effect of filter coefficient

Figure 7.14 shows the large minute-to-minute variations in the unfiltered data plot to be considerably reduced as filtering is increased (reduced value of K). However, the time lag in the filtered data increases is the level of filtering is increased. Thus the selection of K is a compromise between the need to reduce the random variation in occupancy, and the requirement to closely track the secular trend.

Similar filtering considerations apply to the other traffic variables (e.g. volume, speed) that may be used for other purposes such as the geographical display of data in the traffic management center, use of data for DMS messages and communication of this information to traffic service providers.

Other data filtering techniques such as Kalman filtering [16] have also been employed in traffic systems. Kalman filters automatically adjust the filter coefficients based on the random variation in the sensed value of occupancy and in the detection error.

7.4.3.3 Closed Loop Control

The technique described in Sect. 7.4.3.2 for scheduling the local metering rate by occupancy measurements does not control the metering rate to achieve a specific objective. Closed loop control systems compare a desired objective function with an estimate of the function derived from measured traffic parameter(s). The metering rate is then adjusted to resolve the discrepancy. ALINEA is a commonly used closed loop control system. The ALINEA strategy controls the metering rate to a desired level

Fig. 7.15 ALINEA model

of occupancy based on the principles of linear control theory [17]. The desired level of occupancy (occupancy set-point) may be established based on capacity or flow breakdown probability. The equation used for the metering rate computation is:

$$R(j) = R(j-1) + K_R \cdot (\theta_S - \theta_M(j))$$ (7.6)

where

R(j)=meter rate (ramp volume) after time j

KR =adjustable parameter

θS=occupancy set-point

θM(j)=occupancy measured by mainline detector (usually somewhat downstream of ramp merge with mainline) between time intervals j−1 and j

Figure 7.15 describes the operation of the control loop. The meter rate is added to the volume upstream of the meter (qU). The model includes a physical time delay in the merged volume when sensed at the detector. This time delay is equal to the travel time between the ramp meter and the detector station. The detector station sensing this traffic provides the value of occupancy as determined by Eqs. (7.3) and (7.4). As shown in Eq. (7.6), this occupancy θM is subtracted from the set-point occupancy value θS, and the difference is multiplied by parameter KR. This product constitutes the change in metering rate from the prior computation interval. Because these changes are relatively small for each interval, the filtering of occupancy data as described in the previous section is not required. ALINEA has been deployed at a number of sites in the U.S. and Europe.

SWARM 2 is a set of local traffic responsive algorithms. As described by Chu and Liu [18], SWARM 2a uses a density function to compute local metering rates based on headway theory. Theoretically, it attempts to maintain headway at the detector station upstream of metered ramp by optimizing density to maintain maximum flow. SWARM 2b introduces the concept of storage zone, which starts from the mainline upstream vehicle detector station (VDS) to the next downstream mainline VDS. The number of vehicles stored within this storage zone will be calculated. Then, SWARM 2b computes metering rates to maintain demand such that LOS D is maintained as along as possible. If there are on-ramps and off ramps between the two VDSs, detectors are required to be placed at on-ramps and off ramps for counting traffic volumes. This algorithm depends on accurate loop detector data.

7.4.4 System-Wide Traffic Responsive Restrictive Ramp Metering

System-wide traffic responsive ramp meter strategies adjust the rates of ramp meters as a group to optimize some objective function. A commonly employed objective is to minimize the probability of demand exceeding capacity at any bottleneck location within the controlled section of roadway based on current sensed traffic conditions. This may entail reducing the metering rate at a number of ramps upstream of the bottleneck. Advantages of these strategies include the ability to respond to current changes in traffic demand, and the ability to respond to changes in roadway capacity resulting from weather conditions and incidents. Table 7.5 provides a summary of the key features of these strategies.

In general, these strategies examine detector data in a zone downstream of the meter. Occupancy or density from one or more critical downstream detector locations is compared with criteria (usually at or somewhat less than a value which represents capacity, or the variable's flow breakdown value). In some cases, density is computed by a count-in, count-out process for a zone.

The metering rates of one or more upstream ramp meters are established to adjust the occupancy or density values at the detectors so that the critical value is not exceeded. Many strategies incorporate a local metering algorithm in addition to the system-wide algorithm, and the more restrictive rate computed by these algorithms is implemented.

The ramp is usually instrumented with one or more detector stations upstream of the meter in order to adjust the rates so that the queue does not spill back onto the surface street so as to obstruct traffic flow (this topic is discussed in Sect. 7.4.5.2).

7.4.5 Design Issues

7.4.5.1 Ramp Design Considerations

Metered ramps may be configured in a variety of ways to service signal display, safety and storage requirements. The number of metered lanes and the use of single vehicle metering or platoon metering depends on the maximum metering rate to be

Table 7.5 Examples of system wide traffic responsive ramp metering strategies

Strategy	Example of location used	Reference	Key properties of strategy
Stratified zone metering	Twin Cities, Minnesota	[19]	Freeway divided into zones. Strategy sets metering rate to keep the number of vehicles entering zone less than the number leaving
			Zones are organized into groupings (layers) which serve as the basis for meter rate calculations
			Strong emphasis given to constraint on maximum ramp waiting times. Ramp queues are monitored to assure that waiting time is not exceeded
Fuzzy logic	Seattle, Washington	[20]	See Appendix E
Helper	Denver, Colorado	[21]	Local algorithm initially sets metering rates
			If a ramp is metered at its minimum rate, the rates of upstream ramps are reduced
System wide adaptive ramp metering algorithm (SWARM)	Orange County, California, other locations	[22]	Selects lower of SWARM 1 and SWARM 2
			SWARM 1
			Forecasts density and measures excess density at each detector station
			Calculates target density and required volume reduction at each detector station
			Assigns volume reduction to upstream meters
			SWARM 2 (see Sect. 7.4.3.3)
Metaline	Paris	[23, 24]	Generalizes ALINEA for system wide metering
			Establishes an occupancy setpoint for critical downstream detectors and measures the error between the set-points and the occupancy value
			Provides incremental changes to each meter's metering rate based on weighted downstream occupancy error

employed (see Table 7.2). Where one lane is metered, vehicles may be stored in one lane or in two lanes and merged prior to the meter. In some cases an additional lane may be employed to permit buses or high occupancy vehicles to by-pass the ramp meter. The California Department of Transportation (CALTRANS) provides a ramp meter design manual that recommends design criteria for metered ramps and provides examples of designs [25].

Restrictive ramp metering often requires considerable storage space for vehicles. Caltrans describes a method for computing the ramp storage space required. The process is illustrated in Fig. 7.16 [25]. The figure consists of a grid divided horizontally into 10-min time increments and vertically into 100 vehicle per hour volume increments. The figure is based on an estimate of metering rates such as would be developed for a pre-timed metering schedule. Hourly volumes (in hundreds) are entered into the first row of the table below the figure when the arrival rate exceeds the metering rate. The second row represents the discharge rate which is the metering rate for the period that the queue is present. The third row represents the queue in tens of vehicles, and is computed as the difference between the first row and the second row plus the residual queue remaining from the preceding interval. Thus, in the example in Fig. 7.16, the maximum queue is computed as 60.4 vehicles, and occurs between 40 and 50 min after the demand first exceeds the metering rate as shown by the vertical profile rate. Caltrans recommends that 9 m of ramp lane length be allocated for each vehicle stored, thus the minimum storage requirement is 540 lane meters (60•9) in the example. Caltrans recommends additional storage where there are significant percentages of trucks, buses or recreational vehicles. The website http://www.springer. com/us/book/9783319147673 contains a data free image of this chart as shown in Fig. 7.17 that may be used to assist in establishing ramp meter schedules.

In many cases, the ramps cannot accept or be modified to accept the storage requirement. When this occurs, it may be advisable to consider non-restrictive metering.

7.4.5.2 Control of Ramp Queue Length

During the course of a control period that uses restrictive ramp metering, the queue will build and wane in the general way shown by the vertical length in the shaded area of Fig. 7.16. Short term variations in this general profile result from random traffic arrivals or by vehicle platoons released by traffic signals upstream of the ramp. Most operating agencies limit the maximum queue length on the ramp for one or both of the following reasons:

• Extending the queue past the physical ramp or past the space set aside for the storage of vehicles destined for the ramp entry will interfere with general surface street traffic operations.
• Some agencies may choose to limit the ramp waiting time (see Sect. 7.5.2).

Thus, most ramp meter controller systems provide a means for limiting the length of the queue, the technique usually utilizing signals from the ramp queue detector shown in Fig. 7.2. The following describes a number of techniques that may be used to control the queue. The first four techniques use the periodic occupancy measurement commonly developed by freeway management systems to determine the presence of the queue over the queue detector. Because the queue continues to build even after the metering control has been changed to compensate for the queue presence over the detector, that detector must be located somewhat

Fig. 7.16 Ramp queue computation chart

Fig. 7.17 Ramp computation chart (data free)

downstream on the ramp from the maximum expected end of the queue. The fifth technique utilizes additional queue detector data from each vehicle to estimate the end of the queue and control the metering rate accordingly. The sixth technique uses volume and occupancy estimates.

Termination of ramp metering when the queue is sensed by a high value of occupancy at the queue detector. Metering is resumed when the queue is no longer over the queue detector This is an early approach that is still sometimes used. It is not recommended because termination of ramp metering has a severe adverse effect on mainline traffic flow.

2. Increase of ramp metering rate to a higher value than the ramp arrival rate when the queue is sensed by a high value of occupancy at the queue detector. The rate may be increased to the maximum ramp metering rate. The planned metering rate is restored when the queue is no longer over the queue detector. This type of control results in a limit cycle (oscillation of the queue) in the vicinity of the queue detector, thus requiring the detector to be placed upstream of the location to be protected from queue spillback. The effect is to reduce the available queue storage space on the ramp.
3. When the queue is sensed by a high value of occupancy at the queue detector the metering rate may be incremented. This incrementation process continues with each sampling period until the queue is no longer over the queue detector, at which time the planned metering rate is restored. This control process, used by many of the ramp meters in California is slower than Method 2, and may lead to instability in controlling the queue [26].
4. In order to minimize the queue buildup after detection, Gordon [27] describes a technique which uses a combination of a faster than conventional sampling period for the occupancy detector (10 s is recommended) in conjunction with a data processing technique that anticipates the presence of the queue at the location of the detector by including the rate of change of occupancy. This technique results in a limit cycle that has a lower amplitude compared with Method 2, resulting in lower queue storage space requirements.
5. Sun and Horowitz [26] describe a technique that is used when the queue is close to the queue detector. At this point it adjusts the metering rate to maintain a prescribed queue length. Queue length is estimated by comparing the speed of each vehicle passing over the detector to a stored profile of vehicle speed vs. distance from the tail of the queue. This profile is developed beforehand based on observed measurements fitted to a curve that represents the vehicle's deceleration profile.
6. Spiliopoulou et al. describe a technique that estimates the number of vehicles in the queue by taking the difference of count measurements at the ramp entry and exit locations. This difference is then calibrated using occupancy measurements taken at the middle of the ramp [28].

7.4.5.3 Freeway-to-Freeway Ramp Metering

Traffic patterns on a freeway in major metropolitan areas are often dominated by traffic merging from another freeway. Often the effect is to create excessive delays to motorists on the first freeway upstream of the merge point. To mitigate these delays, the ramp leading from the merging freeway may be metered to induce some motorists to enter the freeway at a downstream entry ramp. Jacobson and Landsman

Table 7.6 Guidelines for freeway-to-freeway ramp metering [29]

Consider locations where recurrent congestion is a problem or where route diversion should be encouraged

Consider route diversion only where suitable alternative routes exist

Avoid metering twice within a short distance

Avoid metering single lane freeway-to-freeway ramps that feed traffic into an add-lane

Do not install meters on any freeway-to-freeway ramp unless analysis ensures that mainline flow will be improved so that freeway-to-freeway ramp users are rewarded

Install meters on freeway-to-freeway ramps where more than one ramp merges together before feeding onto the mainline, and congestion on the ramp occurs regularly (four or more times a week during the peak period)

If traffic queues that impede mainline traffic develop on the upstream mainline because of a freeway-to-freeway ramp meter, then the metering rate should be increased to minimize the queues on the upstream mainline, or additional storage capacity should be provided

Freeway-to-freeway ramp meters should be monitored and be controllable by the appropriate traffic management center

Whenever possible, install meters at locations on roadways that are level or have a slight downgrade, so that heavy vehicles can easily accelerate. Also, install meters where the sight distance is adequate for drivers approaching the meter to see the queue in time to safety stop

offer guidelines for the selection of appropriate sites [29]. These are summarized in Table 7.6.

Meters on freeway-to-freeway connectors have been extensively deployed on ramps leading to I-210 in California [30].

7.5 Ramp Metering and the Motorist

7.5.1 Motorist Benefits and Disbenefits Resulting from Ramp Metering

A review of ramp metering projects in North America indicates that significant overall benefits in the travel time in the corridor controlled by ramp meters and in the accident rate on the freeways controlled by ramp meters are obtained [10]. However, unlike other ITS treatments that are often characterized by benefits to all users, ramp metering, and especially restrictive ramp metering provides benefits to some motorists and exacts penalties on others.

Beneficiaries of ramp metering generally include motorists whose ramp waiting time is short compared to their trip length on the freeway. In some cases, motorist may enter the freeway upstream of the metered section and experience no waiting time. Other beneficiaries may include transit passengers in buses that utilize a ramp meter by-pass lane. Motorists penalized by ramp metering include the following:

• Motorists whose ramp waiting time is relatively long compared to the travel time on the mainline. These motorists often enter the freeway in the central city closer

to the central business district. In other cases, the waiting time is considerably different at different ramps. These equity issues have been addressed in the following ways:

Metering may be primarily utilized on the suburban ramps rather than in the central city.
Queue waits may be limited to an acceptable maximum (Sect. 7.5.2).
Metering may be implemented only in the outbound direction. Section 3.2.1 discusses the Gini coefficient that may be used as a measure of equity.
• Motorists who divert from the freeway and motorists on the alternate routes whose trips do not utilize the freeway will generally experience longer trip times than they experienced before the freeway was metered. These issues may be mitigated in the following ways:
- Preplanning by means of simulation or other techniques to provide metering rates that will limit diversion to a level that is acceptable to stakeholders concerned with surface street impacts. For example, when metering was first implemented in Portland, Oregon it was agreed to limit diversion so that surface street volumes would not increase by more than 25 % [1].
- Detectors in traffic signal systems and CCTV and probe readers on surface streets may be monitored in real time, and metering rates adjusted to assure that an acceptable level of service is maintained on the alternates.

Issues such as these require the stakeholders to agree to the planned ramp metering operations and their estimated impacts. It is recommended that these be included in the Concept of Operations for the system (Sect. 2.1.2).

7.5.2 Public Acceptance of Ramp Metering

When ramps are restrictively metered, motorists waiting in the daily queue rapidly become aware of a delay that they had not previously experienced. The benefits in terms of reduced mainline travel time and more safe merges may not be as easily perceived. The motoring public, political leaders and law enforcement agencies should be made aware of the potential benefits before they experience ramp metering. Public outreach techniques include brochures, use of the print and electronic media and outreach to local leaders and law enforcement officials [1, 2]. In many cases these techniques have resulted in positive public attitudes towards and compliance with ramp meter signals.

As an example of the type of difficulty that acceptance of ramp metering may experience, because of perceived long ramp waiting times, the Minnesota legislature in 1990 required a study to be conducted to assess the benefits of ramp metering at the behest of the public and political leaders. The study involved measuring delay with and without ramp metering, the ramp meters being turned off for a period of approximately 2 months.

The results showed that the ramp meters made considerable improvement in travel time reliability, mainline throughput and in crash reduction. A user survey indicated that while respondents now had an increased appreciation of the role of ramp meters, they felt that there was too much metering under free flow conditions and that there were too many meters in general. The study recommended a new principal for ramp meter operation namely Balance the efficiency of moving as much traffic during the rush hours as possible, consistent with safety concerns and public consensus regarding the queue length at meters [31].

As a result of the study, ramp metering policy was modified to limit ramp meter wait time to less than 4 min for local ramps and less than 2 min for freeway to freeway connector ramps. Implementation of this plan resulted in system-wide benefits that were better than the no metering situation, but worse that the previously employed ramp metering strategy [32].

7.6 Benefits Model for Ramp Metering

When demand is sufficiently close to capacity, ramp metering can reduce overall corridor delay and provide savings in fuel consumption and emissions in the roadway segment affected. It also reduces the accident rate near metered ramps. Figure 7.18 shows the relationships for a simple benefits model. The model estimates annual delay and accident reduction in a segment of the highway influenced by ramp metering.

The symbols in the model are defined in Table 7.7.

Fig. 7.18 Simple ramp metering benefits model

Symbol	Definition	Representative default value
LS	Length of roadway segment influenced by ramp metering (miles)	Default not applicable
PHV	Peak hour volume	Default not applicable
TO	Metering hours per year	Default not applicable
FRM	Fraction of roadway segment improved by metering	Default not applicable
ATSMR	Average time per mile per vehicle saved by metering	.00476 h per mile per vehicle
K19	Ramp metering benefit factor	K19=1.0 for restrictive metering
		K19=0.4 for non-restrictive metering
MTF	Fraction of planned metering period that freeway is at level of service E or worse	Default not applicable
ACCR	Accident rate per million	Default not applicable
K7	Accident reduction factor	0.2
FRR	Fraction of ramps in roadway segment that contain ramp meters	Default not applicable

Table 7.7 Symbols for ramp metering benefits model

References

1. Neudorff LG et al (2003) Freeway management and operations handbook. Federal Highway Administration Report FHWA-OP-04-003. Federal Highway Administration, Washington, DC
2. Jacobson L et al (2006) Ramp management and control handbook. Federal Highway Administration Report FHWA-HOP-06-001. Federal Highway Administration, Washington, DC
3. Gazis D, Foote R (1967) Surveillance and control of tunnel traffic by an on-line digital computer. 32nd Natl Meeting Operations Research Soc. Am
4. Gordon RL et al (1995) Traffic control systems handbook. Federal Highway Administration Report FHWA-SA-95-032. Federal Highway Administration, Washington, DC
5. Banks J (2002) Review of empirical research on congested freeway flow. Presented at the 81st Annual Meeting of the Transportation Research Board. Transportation Research Board, Washington, DC
6. Persaud B et al (2001) Study of breakdown-related capacity for a freeway with ramp metering. 80th Annual Meeting of the Transportation Research Board. Transportation Research Board, Washington, DC
7. Shawky M, Nakamura H (2007) Characteristics of breakdown phenomena in Japan urban expressway merging sections. Transportation Research Board 2007 Annual Meting. Transportation Research Board, Washington, DC
8. Zhang L, Levinson D (2004) Ramp metering and the capacity of active freeway bottlenecks. 83rd Annual Meeting of the Transportation Research Board. Transportation Research Board, Washington, DC
9. Zhang L, Levinson D (2010) Ramp metering and freeway bottleneck capacity. Transp Res A 44:218–235
10. Piotrowics G, Robinson J (1995) Ramp metering status in North America 1995 update. Federal Highway Administration, Washington, DC
11. Twin Cities ramp meter evaluation (2001) Cambridge, MA: Cambridge Systematics Inc.
1. May AD (1990) Traffic flow fundamentals. Prentice Hall, Englewood Cliffs, NJ
13. Imada T, May AD (1985) FREQ8PE - a freeway corridor simulation and ramp metering optimization model. Report UCB-ITS-RR-85-10. University of California, Berkley, CA
1. Managed freeways freeway ramp signals handbook (2013) Kew, VIC: Vic Roads
1. Blumentritt CW et al (1981) Guidelines for selection of ramp control systems. NCHRP Report 232. NCHRP, Washington, DC
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1. Papageorgiou M et al (1991) ALINEA: a local feedback control law for on-ramp metering. Transp Res Rec 1320:58–64
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1. Executive summary twin cities ramp meter evaluation (2001) Cambridge, MA: Cambridge Systematics Inc.
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Chapter 8 Transportation Management Centers

Abstract This chapter describes the functions of a transportation management center (TMC) and provides examples of the services that TMCs provide. Information fl ows among stakeholders, how they relate to the Regional ITS Architecture and how they may be implemented are discussed. Statewide TMC architectures and statewide databases are described.

8.1 Transportation Management Center Functions

The control and management of ITS operations is performed in a transportation management center (TMC), sometimes called a traffi c management center or traffi c operations center. The TMC provides a focal point for implementing the Regional ITS Architecture and the Concept of Operations (CONOPS) [ 1 ] developed from the project's systems engineering processes (Sect. 2.1.2). TMCs often house operations for a number of transportation related agencies and emergency service providers.

TMCs provide general management services to support transportation related functions provided by agencies responsible for freeway operations, surface street operations, emergency management and police services. TMCs facilitate interagency communication and coordination, implement the provision of traffi c information to the media and to the public, coordinate with transit agencies and provide a point of contact for the public and for organizations with special information needs. Major freeway management functions supported by the TMC are described below.

8.1.1 Support of Emergency Management Services

TMCs support emergency management service providers that respond to traffi c related incidents. They make available information and traffi c conditions to responders and help them identify the need for emergency services while identifying the quickest route for emergency service providers to reach the incident site. Specifi c information such as CCTV images, lanes affected and the location of the tail of the queue may be afforded in response to requests by emergency service providers. The TMC generates, stores and implements incident management plans and provides the incident support services discussed in Sect. 4.5.2.

CCTV is a key tool to assist in incident management as it supports the following functions:

Identifying the types of response services required.
Assisting responders in fi nding the quickest route to the incident.
Assisting responders in managing traffi c in the vicinity of the incident and its queue.

CCTV images are often shared with other TMCs, agencies and emergency responders.

8.1.2 Provision of Information to Motorists

The TMC provides information to the agency's fi eld devices such as dynamic message signs (DMS), highway advisory radio, HAR beacons and perhaps kiosks in agency operated locations or in private venues. Traffi c information is also offered by private agencies such as independent service providers and the media. The TMC may provide messages requested by other TMCs. Information generated by the TMC typically makes a signifi cant contribution to the information base for the state's 511 motorist information service.

The types of information provided to the motorist by the TMC may include:

Non-recurrent congestion and related problems such as police activity and roadway surface related problems.
Recurrent congestion in the form of travel time or travel movement information (depending on the agency's policy).
Construction scheduling and traffi c impact.
Special event scheduling and traffi c impact.
Major events or incidents on other facilities.
AMBER alerts.
Roadway or traffi c conditions related to weather events.
Transit and corridor related information including park-and-ride facility status.
Default messages related to motorist safety (depending on the agency's policy).

8.1.3 Operation of Ramp Meters

TMCs support the following operations associated with ramp meters:

Daily operations—Operating personnel select metering modes and may alter metering rates based on observations of mainline traffi c fl ow and ramp queues. Incident management plans and corridor management functions may also require the modifi cation of ramp metering rates.
Data archiving and mining—Traffi c detector data is stored and analyzed by computer programs. These programs provide information showing distribution of

traffi c data at a site by time (e.g. Fig. 6.3). Daily profi les showing speed for a section of roadway such as those displayed in Fig. 8.1 [ 2 ] and the volume data that accompany them are useful in determining and revising meter rates, schedules and traffi c responsive metering parameters. Data archiving and mining also support other TMC functions.

• Revision of metering plans—Meter rates, schedules and traffi c responsive metering parameters may be modifi ed based on archived data as described above. Revisions may be facilitated by the use of traffi c simulation programs [ 3 ].

8.1.4 Operation of Service Patrols

Freeway service patrols, also known as motorist assistance patrols and courtesy patrols may be operated by a highway agency or a private company. The TMC usually coordinates and supervises service patrol operations. Most service patrol vehicles follow pre-established beats or routes. Their primary function is to mitigate congestion or potential congestion by clearing minor incidents from travel lanes. They generally provide the following services:

Assist immobile vehicles by providing fl uids, performing minor mechanical repairs and calling towing services. Push bumpers may be used to clear stalled vehicles from travel lanes.
Clear debris from the moving lanes and from the shoulders.

Fig. 8.1 Daily speed profi le for roadway section

Assist police in the tagging and removal of abandoned vehicles.
Assist response providers in the management of traffi c during incidents.

The benefi ts provided by service patrols to the freeway system include reduction of delay and reduction in secondary accidents by improving the clearance time for incidents. They are popular with the motoring public.

8.1.5 Coordination of Traffi c Signal Operation with Freeway and Corridor Requirements

Implementation of traffi c diversion plans in the event of incidents may require the TMC to instigate alternative signal timing plans. In some cases, another agency implements the timing plans requested by the freeway TMC. Alternative signal timing plans may be used for the following purposes:

Diversion along preplanned routes in the event of a freeway incident.
Support of operations to improve throughput in a transportation corridor.
Implementation of freeway and surface street traffi c plans to support special events.
Implementation of freeway and surface street traffi c plans to support emergency evacuations.

8.1.6 Provision of Weather Information Related to Roadway Conditions

TMCs provide weather information related to roadway conditions. This information may be provided by systems operated by the TMC, or the TMC may receive this information from a statewide system. Roadway weather information systems (RWIS) utilize measurements made at fi eld stations that may include:

Air temperature, pressure and humidity.
Wind speed and direction.
Precipitation type and amount.
Visibility.
Pavement and subsurface temperature.
Pavement condition, e.g. dry, damp, wet, ice, snow, residual salt and water fi lm.

This knowledge is utilized by models that, together with National Weather Service and private weather service data, provide information on visibility and precipitation related conditions. This information warns motorists of hazardous conditions and may infl uence route selection. The information is also used to deploy snowplows and sanders to the most likely incident prone locations.

8.2 Example of Transportation Management Center in Major Urban Location 1

Figure 8.2 shows The New York State Department of Transportation's INFORM transportation management center (TMC) which manages traffi c on the limited access highways and on a number of surface streets on Long Island. The TMC operates 24-h a day, 365 days a year. A major function of the TMC is to assist emergency responders in the management and clearance of incidents. Figure 8.3 shows a commercial vehicle that illegally entered a Long Island parkway and became trapped under one of the parkway's low overpasses.

Figure 8.4 displays the facility's control room. Services performed by the INFORM TMC include:

Notice of traffi c conditions on dynamic message signs These DMS provide indications of both recurrent and non-recurrent congestion events.
Information dissemination to the media, the NYSDOT 511 system and to other transportation agencies.
Monitoring of roadway conditions via closed circuit television cameras. A number of these cameras are located on surface streets and near special event venues. Public access to the camera displays is available through the INFORM web site [ 4 ] as well as others.

Fig. 8.2 INFORM Traffi c Management Center. Source: Parsons Brinckerhoff, Inc.

Much of the information in this section was provided by Messrs. Emilio Sosa of the New York State Department of Transportation and Richard Knowlden of Parsons Brinckerhoff, Inc.

Fig. 8.3 Incident on a Long Island parkway. Source: Parsons Brinckerhoff, Inc.

Fig. 8.4 INFORM control room. Source: Parsons Brinckerhoff, Inc.

• Collection of information from over traffi c detectors including inductive loop detectors, video detectors, radar based detectors and acoustic detectors. This information assists in incident management and development of motorist information. The system also operates sites providing weather information.

Fig. 8.5 INFORM ramp meter. Source: Parsons Brinckerhoff, Inc.

Operation of entry ramp meters. Figure 8.5 shows a typical ramp meter installation. These ramp meters are generally operated in a non-restrictive fashion (Sect. 7.1).
Dedicated travel time signs at key locations on the Northern State Parkway and state surface street arterials. Travel time is also displayed on the overhead, shared purpose DMS.
Coordination of traffi c signals on surface streets that support the limited access highway network. In the event of incidents or construction on the limited access highways, emergency signal timing plans facilitate diversion to these facilities.
Motorist assistance during morning and evening peak travel periods.

8.3 Interconnection and Coordination of TMCs

In earlier years, freeway TMCs were primarily stand-alone entities. Coordination with other TMCs and emergency services were primarily telephonic and often informal. Subsequent experience revealed the benefi ts of intensifying and formalizing the relationships and improving connectivity among freeway TMCs and between freeway TMCs and other agencies. TMCs are important facilities for implementing the Regional ITS Architecture.

Fig. 8.6 Information fl ow requirements for emergency response

8.3.1 Regional Coordination

8.3.1.1 Functions of Regional Coordination

The following sections discuss the functions and purposes of coordinating TMCs in a region.

Facilitate Interagency Emergency Response

Agencies responding to emergencies and contributing to clearance of incidents typically operate management centers. Data exchanges among these agencies insure that the most appropriate agencies, equipment, and routes are employed. Interagency emergency response functions may become quite complex as illustrated in Fig. 8.6 [ 5 ].

Coordinate Traffi c Management Strategies Among Agencies [ 6 ]

Management of traffi c may require traffi c management measures that are required by or implemented by other agencies. These may, for example include:

Control of traffi c signals by other agencies to support coordinated traffi c management strategies.
Coordination of DMS or HAR messages that utilize equipment that is managed by other agencies.
Responses to weather emergencies and other emergencies.

Support Traveler Mode Choice Decisions

Decisions by motorists to retain or alter their current mode in response to the current situation may require information from other agencies. This information may be displayed on the agency's DMS or on the 511 website. Typical requirements include:

Information on transit schedules.
Information on parking availability.
Information on congestion as a result of special events.
Signifi cant problems at another location that may cause a traveler to alter the character of his trip.

8.3.1.2 Implementation of Regional Coordination

Regional coordination may be implemented through the following measures.

Regional ITS Architecture

TMCs are key instruments for implementing the Regional ITS Architecture. This section illustrates how the information fl ows identifi ed in the Regional Architecture may be implemented by TMCs. The Regional ITS Architecture represents a longrange view of the region's ITS needs.

The Regional ITS Architecture emphasizes the use of common communication standards among the stakeholders and management centers. Computer-to-computer data transfers may be performed using ITS protocol families such as NTCIP, TCIP or IEEE 1512 protocol families, or with other standard data transfer protocols.

In contrast, projects that install fi eld equipment or establish or modify TMCs satisfy a subset of these needs. These projects must identify the particular information fl ows to be incorporated into the project and must defi ne the methodology for accomplishing these information fl ows. As an example of how this is accomplished, Table 8.1 shows a methodology for implementing information fl ows for a TMC in Binghamton, NY in conformance with the Regional ITS Architecture.

Source element	Destination element	Flow description	Implementation methodology
NYSDOT Regional TMC	NYSDOT Regional TMC Roadside Equipment	Roadway information system data	DMS NTCIP protocol for controls and message delivery
			HAR voice audio fi le standard
			HAR beacon control signal
		Signal control data	NYSDOT standard signal system
		Traffi c sensor control	NTCIP protocol for data request
		Video surveillance control	NTCIP protocol for camera controls
	Broome County Emergency	Incident information	NYSDOT TMC workstation, telephone
	Management Center	Road network conditions	NYSDOT TMC workstation, telephone
	NYSDOT Regional MCO Center	Field equipment status	NYSDOT TMC workstation
		Road network conditions	NYSDOT TMC workstation
		Work plan feedback	Telephone, email
NYSDOT Regional TMC	NYSDOT Regional TMC	Freeway control status	DMS Status—NTCIP protocol
Roadside Equipment			HAR Status— proprietary protocol
			HAR beacon status— simple switch indication
		Traffi c fl ow	Detector data—NTCIP protocol
		Traffi c images	CCTV camera images— MPEG standard

Table 8.1 Implementation of information links

Shared Facilities and ITS Equipment

The following general methods of sharing information for incident management and other purposes are utilized:

• Face-to-face information sharing—This usually takes place when facilities are shared by stakeholders. Improvement in operations results when stakeholder management centers are co-located, as co-location provides opportunities for close collaboration in planning operations involving multiple stakeholders. In some cases equipment may be shared among stakeholders. For example, the Regional Traffi c Operations Center in the Rochester, NY region (Fig. 8.7 ) houses

the operations centers for NYSDOT freeway operations, the Monroe County traffi c signal system (which operates signals in the City of Rochester, Monroe County and interconnected state signals), and the New York State Police. NYSDOT and Monroe County CCTV cameras are controlled by a single system. Every camera may be accessed by either agency and displayed either on workstations or on shared large screen displays. Similarly, a single system for controlling DMS is shared by both agencies.

Other resource sharing opportunities include the following [ 6 ]:

Sharing of the same computer aided dispatch (CAD) system by emergency responders.
Text message interfaces between CAD systems and the freeway management system.
Sharing communication facilities among stakeholders. This may facilitate display of CCTV at stakeholders facilities or in emergency response vehicles.
Remote voice—Telephones and land mobile radio are examples of this method.
Electronic text—Examples include paging, facsimile, email and text access to traffi c incident-related data systems.
Other media and advanced systems such as video and traffi c management systems.

This type of data transfer may require reprogramming of legacy systems. The modifi cation cost might be signifi cant, particularly for metropolitan areas with limited resources. Alternatively, remote workstations offer a relatively inexpensive way to share information. For example, placing a TMC workstation or workstation software in another management center will enable that center to view road network conditions, equipment status and incident status.

Regional Management

In some locations, a regional data clearing house provides coverage that enables the agency to "see" beyond its geographical or functional operating limits. For example, in the New York Metropolitan Area, TRANSCOM serves as an agency that coordinates transportation data (including transit information) and management of emergency responses.

TRANSCOM [ 7 ] was created in 1986 to facilitate construction coordination among agencies throughout the New York, New Jersey, and Connecticut metropolitan region. Subsequently, its role expanded to include multi-agency, regional incident management 24 h a day. In serving its 17 member agencies, TRANSCOM has developed and now operates a number of Intelligent Transportation Systems (ITS). TRANSCOM collects and disseminates up-to-the-minute regional incident, construction, and special events information, 24 h a day, through an extensive notifi cation network. Member agencies contribute traffi c condition and incident information, and transit agencies contribute schedule variance information. Each notifi cation is distributed to affected agencies in the tri-state area. Recipients include highway and transit agencies; state, county, and local police departments; and media traffi c services. During major incidents, construction, and special events, TRANSCOM helps to marshal regional resources for incident response. These resources include its member agencies' dynamic message signs and highway advisory radio, which get the word out to travelers. Sharing these resources allows information to reach a much wider public.

8.3.2 Statewide Coordination

Many states operate a number of TMCs. Although many were originally designed as stand-alone facilities, a number of states have taken steps to coordinate their design and operation.

8.3.2.1 Functions of Statewide Coordination

The purposes of statewide coordination of operations and facility management among the state DOT's divisions or regions include the following.

Seamless Operation Among Adjacent Divisions or Regions

Incident management and motorist messaging in response to recurrent or nonrecurrent congestion that involves more than one TMC must be coordinated. Similarly, requirements for selection of traffi c signal timing plans that may cross TMC boundaries must also be coordinated.

Economies of Operation

TMCs that manage smaller regions or those with less intense traffi c may be operated by another, larger TMC, particularly during evening hours, thus achieving staffi ng economies. Implementation requires this requirement to be included during the design or modifi cation of the facilities involved.

Response to Disruption of TMC Operation

Environmental or other events may disrupt TMC service. In some cases, provision may be made for an alternate facility. In other cases, it may be more feasible to conduct operations from another state region or division.

Logistics Economies

Uniform design may lead to economies in personnel and maintenance training and in the maintenance of TMCs. Uniform design also facilitates shared learning and management experience.

8.3.2.2 Implementation of Statewide Coordination

Statewide coordination may be implemented through the following measures.

Statewide ITS Architecture

The statewide ITS architecture provides a vehicle for coordinating both the physical and functional requirements of TMCs. Figure 8.8 [ 8 ] shows a depiction of a statewide architecture while Fig. 8.9 [ 9 ] shows a small portion of the traffi c management responsibilities.

Fig. 8.8 Arizona Statewide ITS Architecture concept

Shared Center-to-Center (C2C) Communications

Some state architectures utilize a highly developed level of center-to-center information sharing. An example of such an architecture is shown in Fig. 8.10 [ 10 ].

Figure 8.10 provides an illustration of the interface of several existing component systems via their individual C2C Interface Modules. DMS and CCTV operate through a peer-to-peer approach. For example, when a given jurisdiction desires to

| Stakeholder | Role and Responsibility | | | |----------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--|--| | ADOT | Coordinate road closures with other agencies and notify appropriate information service providers of road closure schedules. | | | | | Collect, process, store and disseminate weather information to travelers. | | | | | Gather information from stakeholders and Maintain Statewide ITS Architecture every 3-5 years or as needed. | | | | | Use systems polling feature to provide fault data | | | | | Provide snowplow operations support and availability information for other agencies. | | | | | Remotely control dynamic message signs for dissemination of traffic and other information to drivers. | | | | | Maintain field equipment. | | | | | Implement traffic control response to incidents. | | | | | Monitor traffic on ADOT controlled highways and on-ramps. | | | | | Collect and share information collected by the service patrol with traffic, maintenance and construction, and traveler information systems for incident management, incident notification to travelers and incident cleanup. | | | | | Dispatch and track location of roadway service patrol vehicles to identified incident locations. | | | | | Provide resources when requested by emergency management agencies. | | | | | Provide information on traffic conditions, environment conditions, weather and event information from the requested voice activated phone system. | | | | | Remotely monitor video images and surveillance data collected in secure areas on facilities and in traffic. | | | | | Collect, process, store and disseminate traffic and highway condition information to travelers, including incident information, detours and road closures, event information, recommended routes and current speed on specific routes. | | | | | Share control of field equipment with ADOT Districts, other transportation and emergency agencies. | | | | | Monitor traffic on highways, on-ramps, and ADOT controlled highways. Provide traffic and incident information to drivers. Share traffic information with other emergency and transportation agencies. | | | | Arizona Department of
Public Safety (DPS) | Coordinate road closures with other agencies and notify appropriate information service providers of road closure schedules. | | |

Fig. 8.9 Portion of Arizona Statewide ITS Architecture

Fig. 8.10 Arizona C2C diagram

place a message on a neighboring jurisdiction's DMS, it places the request through its own software, which is then translated by the C2C Interface Module to the standard protocol. Next, it is passed over the C2C System (through the "cloud"), translated to the neighboring jurisdiction's input format by the receiving C2C Interface Module, and then passed to the receiving system for processing. At no point will an "outside" system have direct control over or communications with that DMS because all inputs and outputs will pass through the local "owning" system. The "owning" system retains the ability to permit or restrict access to any and all users, both internally and externally, and also retains the ability to log all actions by all users [ 10 ].

Statewide ITS Standards and Specifi cations

By including ITS standards in their standard specifi cations many states ensure that data may be easily transmitted among TMCs. Some of the more commonly employed standards sets are identifi ed in Sect. 8.3.1.2 . The National ITS Architecture identifi es standards sites that are commonly used [ 11 ].

Single Supplier for ITS Management System Software

In the past, many states implemented ITS management software separately for each region or division. The disadvantages of this arrangement include diffi culty in migrating data and in coordinating operations between adjacent TMCs, inability to share maintenance and training resources among TMCs and reduced effi ciency in sharing "lessons learned". To improve these limitations, a number of states have decided to consolidate TMC software through the use of a single supplier. Because of resource limitations, this process may take some time to complete.

Remote Operation of TMCs

Larger TMCs often are equipped with backup management facilities in the event that circumstances render the primary site inoperative. This approach might not be effective for smaller TMCs. In addition, it may be more effi cient, particularly during off hours, to operate smaller TMCs from larger TMCs. The architecture shown in Fig. 8.10 may be adapted to implement this approach. An alternative architecture, shown in Fig. 8.11 may also be employed for this purpose. Using this approach under normal conditions, the local TMC normally manages the operation. In off hours or under emergency conditions, the fi eld devices may be managed by the remote TMC through a communication channel that does not require the local TMC to be available. The use of internet communications protocols facilitates this concept. A link between the TMCs is used to keep the remote TMC up to date on the

Fig. 8.11 Architecture for remote control of TMC

system status prior to handover, and to assist in the handover and return to local operation. An architecture of this type is being implemented by the New York State Department of Transportation.

Statewide Traffi c Databases

An increasing number of states have the capability to collect and archive traffi c and incident data in real time and in near real time for such purposes as data exchange among TMCs, use in the development of 911 websites, use by commercial traffi c services, researchers and use by motorists. One such system is the Performance Measurement System (PeMS) employed by Caltrans. It is the centralized repository for all of Caltrans' real-time traffi c data, enabling easy access to these data that might otherwise be dispersed across multiple districts and more diffi cult to obtain. PeMS provides a consolidated database of traffi c data collected by Caltrans as well as partner agency data sets. The data collected by vehicle detectors are relayed from the fi eld to Caltrans Transportation Management Centers (TMCs) and then sent to PeMS. PeMS is a real-time Archive Data Management System (rt-ADMS) that collects, stores, and processes raw data in real-time. It can be accessed via a standard Internet browser and contains a series of built-in analytical capabilities to support a variety of uses [ 12 ]. Figure 8.12 provides an overview of PeMS [ 12 ].

Fig. 8.12 Overview of PeMS

References

1. Transportation management center concepts of operation—implementation guide (1999) Federal Highway Administration, Washington, DC
2. Ishimaru JM et al (1999) Central Puget Sound freeway network usage and performance, 1999 update, vol 1. Report WA-RD 493.1. Washington State Transportation Center
3. Beaulieu M et al (2007) A guide to documenting VISSIM-based microscopic traffi c simulation models. Report WA-RD 678.1. Washington State Transportation Center
4. INFORM. www.informny.com/ Accessed 7 July 2014
5. Owens N, Armstrong A, Sullivan P, Mitchell C, Newton D, Brewster R, Trego T (2010) Traffi c incident management handbook. Report FHWA-hop-10-013. Federal Highway Administration, Washington, DC, Jan 2010
6. Brooke K et al (2004) Sharing information between public safety and transportation agencies for traffi c incident management. NCHRP Report 520. Transportation Research Board, Washington, DC
7. Transcom Transportation Management. http://www.nymtc.org/ITS/080904TRANSCOM%20 history.pdf Online 8 June 2014
1. Statewide ITS Architecture Development—a case study (1999) Arizona's Rural Statewide Architecture, Sept 1999
9. Arizona Statewide ITS Architecture. http://wwwa.azdot.gov/ITS-Architecture/html/opscon/ rr2.html Online 9 June 2014
1. AZTech C2C Program. http://www.aztech.org/docs/c2c/AZTechC2C\_FINAL.pdf Online 9 June 2014
1. National ITS Architecture, v 7.0, ITS Standards. http://www.iteris.com/itsarch/html/standard/ standard.htm Online 7 July 2014
1. PeMS User Guide, Caltrans, May 2013

Chapter 9 Evaluation of System Design and Operation

Abstract Prospective evaluations (evaluations prior to system installation) and retrospective evaluations (evaluations after system operation commences) are necessary to ensure that implemented systems satisfy the stakeholders' requirements upon which they are based. To be effective, these evaluations require methods for performing annualized benefit and cost analyses. Selection of parameters for assessing benefits, and identification of key parameters associated with for benefits estimation are important for these evaluations. These topics along with planning requirements for project evaluations after operation commences are covered. The impact of evaluation requirements on system design are discussed. Methodologies that may be used to implement retrospective evaluations with emphasis on the use of traffic management systems may be used to automatically collect data and compute the measures are included.

9.1 Evaluation of Design Alternatives and Project Feasibility

Prospective evaluations are used to evaluate design alternatives and project feasibility during the project's planning and design phases. These evaluations usually utilize benefit and cost analysis as well as qualitative factors that are important but that do not lend themselves to this type of analysis.

9.1.1 Benefit and Cost Analysis

Benefit and cost analysis has been the principal tool that is traditionally used during the initial project planning and later design phases for highway related projects. As used in prospective assessments, benefit and cost analysis assists with the evaluation of candidate design alternatives and in establishing the feasibility of the project (possibly in relation to other projects that compete for resources). It is also used to establish priorities among projects competing for available funding. As applied to retrospective assessments, benefit and cost analysis assists in evaluating the improvements to system operations, establishing lessons learned, providing inputs to reports to the public, and improving and selecting future designs and projects. The following sections describe the application of benefit and cost analysis to freeway ITS projects.

9.1.1.1 Methodology for Cost Estimation

A commonly used methodology is an annual cost comparison [1]. This entails converting capital costs to an equivalent annual cost and adding the annual maintenance and operating expenses.

A useful life for the project must be established. For ITS projects it is often considered to be in the range of 20–25 years. Although much equipment will likely be replaced before this period, these replacements may be generally considered as a maintenance expense for the purpose of this analysis.

Several techniques to annualize capital cost are available. The frequently applied capital recovery with a rate-of return method is described below [2]. This approach converts the cost of a design alternative into an equivalent uniform series of annual costs. The salvage value after the project's useful life is generally considered as zero. The conversion is provided by the following equation:

$$R = PC \cdot crf \tag{9.1}$$

where R is the annualized cost with interest, PC the capital equipment cost, and crf is the capital recovery factor.

The capital recovery factor is a function of the interest rate (i) and the project useful life in years (n). It is provided in tables in engineering economics texts and its expression is shown below:

$$\operatorname{crf} = i \cdot (1+i)^{n} / ((1+i)^{n} - 1)$$ (9.2)

The annualized life cycle cost is the sum of Eq. (9.1) and the annual maintenance and operating expenses.

9.1.1.2 Implementing Benefit and Cost Analysis

Prospective benefit estimations may be performed by using the RITA ITS data base for benefits [3], by analytical methods such as those described in this book, by ITS evaluation programs or by extension from previous experience. Figure 9.1 shows the results of a benefits analysis for a number of functional design alternatives for a project.

Although the-benefit-to-cost ratio is a commonly used measure of the relative value of a project or of alternative designs, this ratio must be applied in conjunction with other factors, including the ability to achieve project objectives. It is helpful to depict the benefits and costs in a more general way, such as is conceptually shown in Fig. 9.2. The annualized benefits and life cycle costs are shown for alternatives A, B and C. Each of these alternatives has a benefit to cost ratio considerably in excess of 1.0. While Alternative B has the highest benefit-to-cost ratio (depicted in the

Fig. 9.1 Benefits analysis

Fig. 9.2 Monetary benefits and costs for design alternatives

figure as the slope of the dashed line), Alternative C more closely approaches the detailed objective.

Selection between Alternatives B and C may be assisted by performing a of marginal benefit to cost analysis as discussed in Sect. 3.2.1. The example shown in that section may be generalized to include all monetary benefits.

Table 9.1 Year that 50 % of total project benefits are achieved

Interest rate (%)	Year after project initiation
4	8.1
6	7.2
8	6.5

9.1.1.3 Selection of Parameters for Estimation of Benefits

As shown in Fig. 4.4, delay is very sensitive to the parameters assumed for the evaluation scenario. In order to improve the credibility of the analysis, it may be constructive to conduct the analysis using a range of volume inputs. The cohort model technique described in Sect. 4.4.1 is a systematic way of selecting volumes for benefits estimation.

To obtain the present worth of future year benefits, each future year benefit must be multiplied by the single payment present worth factor (sppwf) [1]. This is given by Eq. (9.3)

sppwf = $$1/(1+i)^{n-0.5}$$ (9.3)

where i is the interest rate and n is the year for which the sppwf is computed. Equation (9.3) uses the term n-0.5 instead of the more commonly used n in order to represent the average annual benefit more closely. Although it is more accurate to conduct the analysis by employing each year's volumes to compute the benefits for that year, a commonly applied approximation is to select a single appropriate future year and utilize the volumes for that year.

Because the benefits for the more distant years are more lightly weighted, the appropriate set of volumes to use for the benefits evaluation should be more heavily biased toward the early years for the project. As an aid to selecting the most appropriate year's volumes to employ, Table 9.1 identifies the year that 50 % of the total life cycle benefits are accumulated after operation commences. The table is based on a 20 year project life.

9.1.2 Alternatives Evaluation and Project Feasibility

The development of the Transportation Improvement Plan (TIP)1 requires the consideration of candidate ITS projects relative to other candidate transportation improvement projects. Similarly, the development of the Regional ITS Architecture and the selection of actual projects to implement the architecture requires

¹To qualify for federal aid funding, the project must be included in the Transportation Improvement Plan prepared by the metropolitan planning organization.

consideration of alternative projects. Stakeholders and decision makers are key contributors to the project selection process. The benefit and cost considerations described in Sect. 9.1.1 usually play a significant role in the process, but there are other considerations as well. Section 3.2.1 identifies the following considerations that are common to ITS projects described in this book:

Economic benefits. For evaluation purposes, delay reduction, safety and fuel consumption are considered in this category.
Environmental benefits (emissions).
Mobility. This represents the ease with which people and goods move [4]. Measures may include delay and variation in delay [5].
Public satisfaction with ITS treatments.

Section 3.2.2 describes multi-attribute utility analysis as an evaluation tool that facilitates the participation of stakeholders and decision makers in the selection of projects and functional alternative project designs.

9.2 Project Evaluation

9.2.1 Role and Function of Evaluation

Project evaluations are retrospective evaluations, i.e. they are implemented after the design of the project. Portions of the evaluation may be conducted prior to or during project installation. The reasons for performing project evaluations include:

Improvement of operations. Lessons learned during the evaluation may provide the basis for improved operations.
Reports to the public and to officials responsible for resource planning for the project. Support for ITS is crucial for its continued success. Figures 9.3 and 9.4 show how the Houston TranStar project accomplishes this [6].
Improvement of future designs.
Assistance in the selection of future projects [4].

ITS project operations are generally envisioned to continue for an indefinite time period. The evaluation process should therefore be considered as a continuous or at least periodic function, in order to keep the project in tune with evolving objectives, requirements and technologies. This is schematically illustrated in Fig. 9.5 by the addition of an evaluation feedback function to the simplified Vee diagram of Fig. 2.1.

Evaluation planning should be considered during the system design process. If "before" conditions are to be measured in the field, the plan may require data collection prior to project installation. Primary methods of data collection include: field observation, automatic data collection devices, simulations and surveys [5]. It may be useful to use traffic system detectors as a means of collecting volume data, speed data and day-to-day variation in speed. After project operation commences, some

Fig. 9.3 Houston Transtar benefit/cost ratios 1997–2012

Fig. 9.4 Average annual incident clearance time 2004–2012

Fig. 9.5 Vee diagram with evaluation feedback

period of time is required for traffic conditions to stabilize. This occurs when the benefits do not change significantly over short periods of time. This time period is usually considerably less than 1 year [5].

Evaluation may be facilitated by including data mining software into the system design. The archived data user service (ADUS) has been incorporated into the National ITS Architecture [7] and guidelines for its use have been developed [8]. For example, the PORTAL ADUS system, developed by Portland State University is extensively used for evaluation in Portland, Oregon [9]. It archives and analyzes inductive loop detector data to create a variety of reports.

9.2.2 Functions and Measures to Consider for Evaluation

The material in this section and in the following sections borrows extensively from Ref. [10].

Table 9.2 identifies functions and classes of functions that TMCs that manage freeways commonly provide. A number of references (e.g. [11–13]) describe measures that are useful for the evaluation of ITS functions. Table 9.3 provides a more tightly focused subset of these measures that are further described in this book. The measures shown in the table relate to the outcomes of the management measures as sensed by the freeway users. Another class of functions termed output functions and associated measures are sometimes used to evaluate the performance of activities that lead to the outcomes. Measures such as incident clearance time and the number of service patrol assists are examples of output measures.

Section 9.2.3 discusses ways that detector data might be structured to facilitate the computation of measures that use this data. Using these data structures, Appendix A provides representative algorithms and computational processes for developing a number of the measures identified in Table 9.3.

Table 9.2 Freeway TMC functions and functional classes

TMC functions and classes of functions
Active traffic and demand management
Speed harmonization
Temporary shoulder use
Queue warning
Dynamic truck restrictions
Dynamic routing
Dynamic lane markings
Incident response
Development of incident management plans
Selection of incident management plan
Assistance to emergency service providers
Motorist information
Management of information for ITS field devices and traffic information service providers
Provision of information to external services
Ramp management and conventional lane management
Ramp metering
Ramp closure
Conventional lane controls
Service patrol
Weather monitoring

9.2.3 Data Structures for Evaluation

Freeway management systems commonly include the following set of data collection, storage and data manipulation capabilities.

Collection and storage of traffic flow data. Data may come from point detector stations (in which case archiving is generally performed at this level), from probe detectors, or from services that provide this data. Point detector data may consist of volume, speed, occupancy, and vehicle classification. Provision is usually made in the freeway management system for the identification and correction of flawed data and missing data. Probe data is comprised of travel time information between physical or virtual probe reading locations.
Collection and storage of incident management reports developed by the TMC. Some states provide this capability on a statewide basis.
Link data structures to provide for the agency's TMC functions (e.g. traffic condition map displays, ramp metering, incident management and motorist information).

Table 9.3 Subset of evaluation measures

| Type of measure | Measure | | | |--------------------------------|--------------------------------------------------------------|--|--| | System delay measures | Vehicle system delay | | | | | Private passenger vehicle occupant delay | | | | | Commercial vehicle occupant delay | | | | | Goods inventory delay | | | | | Transit vehicle occupant delay | | | | Safety | Freeway crashes | | | | | Secondary crashes | | | | | Work zone related crashes | | | | | Pedestrian crashes | | | | | Safety performance index | | | | Fuel consumption | Gallons | | | | Throughput | Freeway throughput | | | | Emissions | See Ref. [13] | | | | Service quality/user | Level of service | | | | perceptions | Route travel time | | | | | Route travel time reliability | | | | | User satisfaction | | | | | User satisfaction | | | | Equity | User perception | | | | | Gini coefficient or Lorenz curve | | | | Quality of assistance to | Service patrol assists | | | | motorists | Quality of service—Periods of patrol coverage | | | | | Quality of service—Average motorist waiting time | | | | | Quality of service—Extent of roadway serviced | | | | | Rating by public | | | | Response to weather situations | Response time to provide actionable information to motorists | | |

9.2.3.1 Spatial Data Structures

A data structure concept is required to relate the data sources (e.g., detector data, crash reports, incidents) to a construct that may be used for evaluation purposes. Figure 9.6 shows an example of a data structure based on freeway links that provides this capability. A link represents a section of the mainline between vehicle access or egress points. The concept of a domain is introduced in the figure to relate data from freeway surveillance stations to mainline links. Domains relate links to the roadway locations receiving information from a particular point detector station. As shown in the figure, each domain is related to a particular detector station. Domain boundaries are established at link nodes, at locations where the roadway characteristics may change or where the link is sufficiently long to encompass more than one detector station. In that case (e.g., Link 4) domain boundaries are used to separate the regions for which each detector station will be employed. Note that no detector in Fig. 9.6 lies within the physical boundaries of Domain 4; that domain obtains its information from Detector Station 4.

Fig. 9.6 Example of link, domain and detector station relationships

Fig. 9.7 Example of link, domain and probe site relationships

Figure 9.7 shows a similar diagram for probe-based surveillance. The asterisks identify locations for probe travel-time measurements. These boundaries may be established by physical equipment locations (such as toll tag reader locations or locations of Bluetooth readers) or may be virtual boundaries for other types of probe detection systems such as those based on GPS. While it is sometimes possible to co-locate virtual or actual boundaries with link boundaries, this is not always the case. The probe-measured travel times are converted to speeds, and these speeds, in conjunction with link lengths, are used to estimate travel link travel times. Probebased detection does not provide volume estimates, so supplementing this data with other information is required for certain measures and for benefit-cost analysis. In order to obtain system-wide delay and travel time measures with probe detection, at least one source of volume data per link is required.

Fig. 9.8 Data accumulation methodology

9.2.3.2 Temporal Data Structures

For archiving purposes, freeway management system volume, speed, and occupancy data from point detectors are often stored at 5-min intervals and aggregated into 15-min and 1-h intervals. The 5 and 15-min intervals provide convenient processing intervals for many of the computations developed from traffic detector data as described in Appendix A and in Sect. 9.2.4. Building on these concepts, a methodology using the spatial/temporal relationship shown in Fig. 9.8 may be used to develop these measures. The methodology uses the domain concept (Figs. 9.6 and 9.7) as the basis for freeway mainline data accumulation.

Detector data is used to obtain these measures at the domain level for 5-min periods and is accumulated at the link level. The 15-min period at the link level is a convenient building block for many of the evaluation measures. The path to computing this level for the 15-min period is shown by the solid trace in Fig. 9.8. The dashed traces show the paths to other spatial levels and time periods. Depending on the particular measure to be computed, and on the purpose (reports, etc.), the 15-min data may be aggregated by time according to the particular spatial relationship required for the purpose. The spatial data structure described in Sect. 9.2.3.1 and the temporal data structure discussed in this section are examples of the types of data structures that may be employed.

9.2.4 Description of Measures

This section describes ways in which a number of the measures in Table 9.4 that are used to identify benefits may be developed. Travel time measures, delay measures route travel time reliability measures and through put measures in the table are discussed in Appendix A. Other measures are discussed in the following sections.

9.2.4.1 Safety

Chapter 4 discusses the management techniques that ITS employs to reduce the number of crashes. A worksheet for use during project design to estimate the potential benefits is provided in Appendix C.

MC functions to measures of effectiveness



Relationship of T
Table 9.4

		Active traffic ment manage	Incident response	information Motorist	and conventional ment Ramp metering lane manage	monitoring Weather	Motorist service patrols
me Travel ti	me (Appendix A, Eq. 1.1. Route travel ti (A.18))	√	√	√	√	√	√
	me reliability (Appendix A, Eqs. (A.21) and (A.22)) 1.2. Route travel ti	√	√	√	√	√	√
m delay Syste	m delay (Appendix A, Eq. 2.1. Vehicle syste (A.7))	√	√	√	√	√	√
	delay (Appendix A, Eqs. (A.8), (A.21) and (A.22)) 2.2. Private passenger vehicle occupant system	√	√	√	√	√	√
	m mmercial vehicle occupant syste delay (Appendix A, Eq. (A.9)) 2.3. Co	√	√	√	√	√	√
Safety	3.1. Freeway crash rate (Sect. 9.2.4.1)	√	√	√	√	√	√
	3.2. Secondary crash rate (Sect. 9.2.4.1)	√	√	√	√	√	√
mption Fuel consu	4. Gallons/year (Sect. 9.2.4.2, Eq. (9.4))	√	√	√	√	√	√
Throughput	5. Vehicle miles during peak hour	√	√	√	√	√	√
User satisfaction	Measure based on survey 6.1.	√	√	√	√	√	√
	mplaints Measure based on co 6.2.	√	√	√	√	√	√
Equity	Measure based on — mplaints 7.1. User perception survey or co				√
	7.2. Gini coefficient (Sect. 3.2.1)				√
Perceived quality	8.1. Hours of coverage per year						√
to of assistance	me 8.2. Average motorist waiting ti						√
motorists	8.3. Centerline miles of roadway served						√
missions E	9. Lb. per year for each pollutant	√	√	√	√	√	√

Retrospective evaluations of safety determine whether the project objectives have been realized and enable the results of ongoing operational improvements to be evaluated. The crash rate (crashes per million vehicle miles) is a key measure used by agencies for this purpose. Police accident reports are generally used as the basis for this determination, and the results are generally included in state accident reporting systems. They may be supplemented by data from TMC logs.

ITS motorist communication techniques identify incident locations to motorists to enable them to perform proper lane adjustments prior to entering the incident location, or to avoid the affected route.

Secondary accidents (Sect. 4.1.2) constitute an important problem that ITS functions can significantly address. Moore et al. [14] describe a complex process for identifying them. An alternative approach is to enter secondary accidents as a descriptor in the TMC's incident management log entry classification (Sect. 4.5.1.4).

9.2.4.2 Fuel Consumption

The estimation of fuel consumption under congestion conditions is a complex process that involves a number of variables. Schrank et al. [13] provides a description of this process. The model used is the product of delay time and the excess fuel consumption rate during periods of delay as provided by Eq. (9.4).

$$FE = GE \cdot VSD \tag{9.4}$$

where

FE=Excess fuel consumption (gallons)

GE=Excess fuel consumption rate (gallons/h of congestion delay)

VSD=Vehicle system delay (provided by Appendix A, Eq. (A.7))

Schrank et al. [13] provides statistics for fuel consumption for the metropolitan areas in the U.S. These data may be used to estimate the excess fuel consumption rate. For example, for the 15 largest metropolitan areas in the U.S., the excess fuel consumption rate varies from 0.41 gallons per vehicle hour of congestion delay to 0.57 gallons per hour, with an average of 0.46 gallons per hour.

9.2.4.3 User Satisfaction

User satisfaction may be measured in terms of rating scales associated with user surveys. As an example, Georgia DOT conducted a detailed motorist mail survey [15]. The measure used for this survey was a simple satisfaction scale ranging from 0.0 to 4.0. The survey response rate was approximately 13 %. The survey was detailed and evaluated specific ITS functions as shown in Fig. 9.9.

Fig. 9.9 Georgia DOT survey results

The year-over-year trends in the number of complaints provide a basis for determining changes in the quality of ITS management provided by the agency. An unusual number of complaints that focus on a location or an operation at that location may highlight a need for remediation.

9.2.4.4 Equity

While most ITS functions provide benefits to all freeway users, other functions provide benefits to some users and may inconvenience others. Surveys and complaints may provide feedback that may result in modification of the function. Where warranted, quantitative measures of the users benefitted and inconveniences such as the Gini coefficient described in Sect. 3.2.1 may be employed.

9.2.4.5 Quality of Assistance to Motorists

By assisting motorists to resolve vehicle problems or aiding them in getting such assistance, motorist service patrols reduce the congestion that might have resulted from the incident. Several measures identified in Table 3.4 may be used to evaluate the effect of motorist service patrols on the quality and quantity of travel.

191 References

References

Maccubin RP et al (2003) Intelligent transportation systems benefits and costs: 2003 update. Report FHWA-0P-03-075. Mitretek Systems, Inc., Washington, DC

2. Taylor GA (1975) Managerial and engineering economy, 2nd edn. D. Van Nostrand Company, New York
3. ITS Benefits Database. www.itsbenefits.its.dot.gov Online 23 Oct 2014
4. Highway mobility operations manual (2005) Oregon Department of Transportation
5. Development of a project evaluation methodology framework for Canadian Intelligent Transportation Systems (2007) Delcan
6. Houston TranStar 2012 Annual Report. houstontranstar.org. Accessed 4 Dec 2013
7. ITS data archiving: five-year program description (2000) U.S. DOT
8. Turner S (201) Guidelines for developing ITS data archiving systems. Report 2127-3. Texas Department of Transportation, Texas Transportation Institute, U.S. DOT
9. Bertini RL et al (2005) Experience implementing a user service for archived intelligent transportation systems data. Transport Res Rec 1817:90–99
10. Gordon R (2012) Methodologies to measure and quantify transportation management center benefits. FHWA Report FHWA-HRT-12-054, Washington, DC
11. Park B (2005) Transportation management system performance monitoring, evaluation and reporting—a technical handbook. FHWA Report FHWA-HOP-07-142. University of Virginia
12. Shaw T (2003) Performance measurements of operational effectiveness for highway segments and systems. NCHRP Synthesis 311, Transportation Research Board
13. Schrank D, Eisele B, Lomax T (2012) TTI's 2012 urban mobility report. Texas A&M Transportation Institute, Dec 2012
14. Moore JE, Giuliano G, Cho S (2004) Secondary accident rates on Los Angeles freeways. J Transp Eng 130(3):280–285
15. Poister TH, Berryman AF, Roberts A, Xu J (2006) Motorist survey pilot statewide results. Georgia State University, 2007, Online 31 Oct 2014

Chapter 10 Active Traffi c Management (ATM)

Abstract Active traffi c management (ATM) is defi ned and ATM strategies and their potential benefi ts are identifi ed. Each of the ATM strategies is described and illustrated. Planning and implementation considerations are summarized.

10.1 Defi nition and Concept

"Active Traffi c and Demand Management (ATDM) is the dynamic management, control, and infl uence of travel demand, traffi c demand, and traffi c fl ow of transportation facilities. Through the use of available tools and assets, traffi c fl ow is managed and traveler behavior is infl uenced in real-time to achieve operational objectives, such as preventing or delaying breakdown conditions, improving safety, promoting sustainable travel modes, reducing emissions, or maximizing system effi ciency. Under an ATDM approach the transportation system is continuously monitored. Using archived data and/or predictive methods, actions are performed in real-time to achieve or maintain system performance" [ 1 ]. ATDM actions can be classifi ed into:

Active Demand Management (ADM). Strategies focused on managing the trip demand on the network.
Active Traffi c Management (ATM). Strategies focused on managing the fl ow of vehicle traffi c on the network.
Active Parking Management (APM). Strategies focused on managing the parking requirements of vehicles.

This chapter focuses on several ATM strategies. Table 10.1 [ 2 ] identifi es a class of strategies that are commonly included in ATM. The strategies in the table are often used in combination and several are discussed in the following sections. Although not included in Table 10.1 , certain more traditional ITS strategies such as ramp metering are sometimes included as ATM strategies.

Table 10.1 ATM strategies and potential benefi ts

	Potential benefi ts
							More		Delay
Active traffi c			Decrease	Decrease in	Decrease	More	uniform	Increased	onset of	Reduction	Reduction	Reduction
ment strategy manage	throughput Increased	Increased capacity	mary incidents in pri	secondary incidents	in incident severity	uniform speeds	behavior driver	reliability trip	breakdown freeway	in traffi c noise	missions in E	mption in fuel consu
harmonization Speed	√		√	√	√	√	√	√	√	√	√	√
shoulder use mporary Te	√	√						√	√
warning Queue			√	√	√	√	√	√		√	√	√
merge control Dynamic	√	√	√			√	√	√	√	√	√	√
Dynamic lane markings	√	√						√
Construction ment manage site	√	√						√		√	√	√
restrictions Dynamic truck	√	√				√	√	√			√	√
rerouting and information Dynamic traveler	√		√	√			√	√			√	√
ment mated enforce speed Auto			√		√	√	√	√			√	√

10.2 Speed Harmonization

The concept of speed harmonization, also called variable speed limits or dynamic speed limits, is already in place in many countries and in several states in the United States. The intent is to minimize the differences among vehicle speeds and to bring the average speed closer to a safe speed for the current conditions. The most common reasons for deploying speed harmonization are for weather related conditions and congestion management under recurrent and non-recurrent congestion conditions. Depending on the goals of the agency, the speed can either be mandatory or advisory [ 3 ]. Figure 10.1 [ 4 ] shows an example of the speed control signs used on I-5 in the Seattle area in conjunction with a DMS that describes the reason for the speed reduction. As shown in Fig. 10.2 [ 4 ], speed harmonization is often used in conjunction with other traffi c management techniques such as lane control signals and other ATM measures such as queue warning and shoulder running. The project shown in these fi gures employs gantries supporting the signs at an approximate spacing of 0.5 miles.

Recommended criteria for the inclusion of speed harmonization include [ 3 ]:

Level of service E or F for a minimum of 3 h for at least one peak period and at least 5 h per day;
Right of way for overhead gantries and DMS;
At least one location every 2 miles where queues form and warning is warranted; and
At least fi ve incidents related to queuing, merging, and/or diverging per week.

The success of speed harmonization is closely linked to the extent to which drivers comply with the signing. The strategy should be success-oriented with a fair and reasonable plan for the majority of users. Speed harmonization should be utilized in response to an issue that is actually present. If users do not believe the system is

Fig. 10.1 Speed control signs for speed harmonization

Fig. 10.2 Lane control with speed harmonization

legitimate, compliance rates will be low. Therefore, if the reason for the new speed limit is not apparent, it should be explained through appropriate signing [ 3 ].

When speed harmonization is used to manage recurrent congestion, an automatic algorithm to display speed messages is often employed. Measured speed is commonly used as the primary variable. In the Netherlands, the control algorithm reduces the speed as the volume increases. This avoids an abrupt transition into congested fl ow [ 5 ].

Table 10.2 [ 6 ] provides spacing characteristics and operating results for a project in the St. Louis area.

One algorithm to control variable speed limit signs (VSLS) examines data from several point detector locations, both upstream and downstream of each VSLS location. The values of measured speed and their variations among locations are used to determine the posted speed [ 7 ].

10.3 Temporary Shoulder Use

Shoulder use, also known as hard shoulder running (HSR), is a measure designed to temporarily increase the capacity of a facility by opening one or sometimes both shoulders to traffi c. Shoulder running may be used for a variety of applications including:

Use of shoulders for transit buses only. The Minneapolis–St. Paul area uses this approach extensively;
Use during peak periods to increase capacity;
Use during peak periods to provide additional storage for exiting vehicles when exit ramp capacity is limited by a traffi c signal at the exit ramp intersection;
Use during peak periods to maintain capacity and permit another lane to be used as a toll lane (Fig. 10.3 [ 8 ]); and
Use as an evacuation route [ 9 ].

	Segment number
	1	2	3	4
Number of signs	8	4	7	5
Distance between signs	0.6–1.9 miles	1.3–2.3 miles	1.1–2.9 miles	0.9–2.0 miles
Change in average delay (peak)	Much lower	Much lower	Much lower	Much lower
Change in reliability (peak)	Improvement	Improvement (3–11 %)	Improvement	Improvement
Change in speed standard deviation (peak)	Decreased	Decreased (5.5 %)	No change	Decreased slightly

Table 10.2 Summary of evaluation of side mounted variable speed limit signs in St. Louis

Change is relative to the pre-VSL (variable speed limit) system

Reliability measured by travel time index, buffer time index, and planning time index

Reduction in standard deviation indicates an increase in speed homogeneity No conclusive fi ndings on safety due to there being only 1 year of post VSL data

Fig. 10.3 Shoulder use with toll lane

Figure 10.4 shows a display concept for the hard shoulder running lanes and Fig. 10.5 shows a concept for DMS displays upstream of the lane [ 10 ].

Shoulder use increases the effective capacity of the freeway and reduces congestion. The essential criteria for considering implementation of shoulder use are [ 11 ]:

Fig. 10.4 Instrumentation concept for hard shoulder running (inactive and active)

Fig. 10.5 Upstream entrance DMS for hard shoulder running

Level of service E or F for at least 2 h in at least one peak period; Length of the facility suffi cient to alleviate a series of bottlenecks should be at least 3 miles;
No expected bottleneck downstream of the shoulder use segment;
Low volume of entering/exiting vehicles if crossing multiple interchanges;
Minimum shoulder width of 10 ft, with ability to add emergency refuge areas; and
Pavement strength to accommodate increased traffi c load.

Guidelines for consideration of shoulder use that is restricted to transit vehicles include the following [ 3 ]

Fig. 10.6 Queue warning system display

Predictable congestion delays, Level of service D for 2 h per day;
Minimum 10 ft shoulder width available;
Suffi cient pavement strength to sustain bus load; and
Minimum service of 50 buses/h (freeway) or 25 buses/h (arterial).

10.4 Queue Warning

Differences in speed often cause vehicle confl icts and increase the potential for crashes. The basic principle of queue warning is to inform travelers of the presence of downstream queues, based on dynamic traffi c detection and using warning signs and fl ashing lights. This strategy allows the traveler to anticipate a requirement for emergency braking and to limit the extent of speed differentials, erratic behavior, and queuing-related collisions. Queue warning can be used on its own with DMS placed on overhead gantries or on roadside mounted DMS that show when a queue is close. It can also be included with speed harmonization and lane control signals to provide incident management capabilities. To improve traffi c management under incident conditions, the speed between gantries is measured and incrementally reduced. Traffi c is shifted among lanes as appropriate. The system can be automated or controlled by a TMC operator. Work zones also benefi t from queue warning with portable DMS units placed upstream of expected queue points [ 3 ].

Figure 10.6 shows an example of a dynamic message sign for a stand-alone queue warning system (QWS) in Ontario, Canada [ 12 ]. The beacons on the sign fl ash when a queue is present. Figure 10.7 [ 12 ] shows the deployment plan for the major components comprising a portion of the system. Information to develop the message is provided by inductive loop detectors.

Fig. 10.7 Overview of components

The QWS in Ontario employs the three major traffi c parameters that might be sensed by traffi c detectors (i.e., volume, speed and occupancy). All admissible traffi c patterns are defi ned in a library. The set of traffi c data collected from the detectors is matched to the patterns in the library. The matched pattern determines whether a queue exists in the zone. When a queue has been identifi ed, the system identifi es the upstream queue-end location among travelled lanes, and activates the corresponding QWS signs with fl ashing beacons in a coordinated manner. It automatically chooses the appropriate messages to be displayed on the DMS. The system is close to a border crossing, and the algorithm is designed to detect all types of queue conditions, especially the slow moving traffi c and standing truck queues formed near the border [ 12 ].

Essential guidelines for the need to implement queue warning include [ 3 ]:

Level of service E or F for at least 2 h per peak period;
Presence of queues in predictable locations;
Sight distance restricted by vertical grades, horizontal curves, or inadequate illumination;
Right of way for overhead gantries and DMS; and
At least fi ve incidents related to queuing merging and diverging per week.

10.5 Dynamic Merge Control

Dynamic merge control is used to meter or close specifi c lanes upstream of the interchange to manage access based on current traffi c demand. It is an operational treatment that addresses the geometric condition when the sum of both freeway general purpose lanes and merging lanes at an interchange is higher than the number of downstream general purpose lanes. A typical U.S. application of this condition would be a lane drop for one of the outside lanes or a merging of two inside lanes, both of which are static solutions. The intent is to provide dynamic priority access to the higher traffi c stream. It is a practical approach to handling varying demand on the mainline lanes and the merging lanes to effectively utilize existing capacity. This concept is implemented by lane control signals and is illustrated in Fig. 10.8 [ 3 ].

Essential criteria for dynamic merge control include the following [ 3 ]:

Signifi cant merging volumes (>900 vph);
Available capacity on general purpose lanes upstream of the interchange that can be borrowed with no worse than LOS E after implementation; and
Non-simultaneous peak traffi c upstream on the general purpose lanes and merging lanes.

Fig. 10.8 Dynamic merge control concept

10.6 Dynamic Lane Markings

Dynamic lane markings may be used to assist in implementing strategies such as shown in Fig. 10.8 . They may also be used to manage lane use for other functions. In Minnesota, a lane may sometimes be used to implement a priced dynamic shoulder lane (PDSL) as shown in Fig. 10.9 [ 8 ]. Lane marking changes are used to highlight the use requirement as shown in Fig. 10.10 [ 8 ].

10.7 Implementation Considerations

Lane control signals such as shown in Fig. 10.2 may display a variety of characters and symbols. A set of options employed in Minnesota is shown in Fig. 10.11 [ 8 ]. These signals are used to support incident management, speed harmonization and the priced dynamic shoulder lane. They are spaced at half mile intervals.

Motorist displays for lane use and lane speed vary with time and with distance along the roadway. Measurements of speed, occupancy and volume are usually

Fig. 10.9 Priced dynamic shoulder lane

Fig. 10.10 In pavement lighting when priced dynamic shoulder lane is open

provided by point detectors that are located in each roadway section that is separated by overhead lane control displays.

Equipment deployment plans for ATM installations are infl uenced by the following:

Roadway geometrics including entry and exit ramps, lane additions and drops, sight distance problems resulting from rapid changes in roadway alignment.
The presence of existing ITS equipment. Since ATM is often employed for roadway sections that experience volumes that approach or exceed roadway capacity,

Fig. 10.11 Options for intelligent lane control signals in Minnesota

in many cases these sections are equipped with freeway management systems and ATM strategies provide more precise control at the lane management level. Existing equipment should be considered for use when applicable.

• Legislation and public attitudes on automatic speed limit enforcement.

10.8 Planning for Active Traffi c Management

ATM strategies generally provide for more intensive speed and lane management treatments than do conventional ITS designs. They are often installed in locations that are equipped with conventional ITS. The existing ITS, however, often provides considerable underlying infrastructure support in the form of communications, traffi c surveillance and motorist information systems thus facilitating ATM implementation. ATM is also often introduced concurrently with a major highway facility upgrade or change in the roadway's use characteristics.

Refs. [ 3 , 13 ] provide descriptions of ATM strategies and concepts. Ref. [ 14 ] is an interactive guide to assist in the selection of ATM strategies to address traffi c management objectives.

References

1. ADTM program brief: an introduction to active transportation and demand management. Publication #: FHWA-HOP-12-032, June 2012
2. Yelchuru B, Singuluri S, Rajiwade S (2013) Active transportation and demand management (ATDM) foundational research, analysis, modeling, and simulation (AMS) concept of operations

205 References

(CONOPS). Joint Project Offi ce Report No. FHWA-JPO-13-020. US Department of Transportation, 27 June 2013

3. Levecq C, Kuhn B, Jasek D (2011) General guidelines for active traffi c management deployment. Report UTCM 10-01-54-1. Texas Transportation Institute, Aug 2011
4. WSDOT-I-5-active traffi c management-complete, Washington State Department of Transportation, Aug 2010
5. American Trade Initiatives for Federal Highway Administration (1997) FHWA scanning report on traffi c management and traveler information systems. Report No. FHWA-PL-98-010, Alexandria, VA
6. Evaluation of variable speed limits on I-270/I-255 in St. Louis; Civil, Architectural and Environmental Engineering, Missouri University of Science and Technology, Oct 2010
7. Active traffi c management: innovative techniques for the future. Washington State Department of Transportation, Sept 2007
8. Kary B (2012) Active traffi c management in Minnesota, online 2012 ATM Minnesota Overview(1).pdf. Accessed 4 Feb 2014
9. Effi cient use of highway capacity. Report to Congress. FHWA-HOP-10-023
10. Active traffi c management—concept of operations. Washington State Department of Transportation, Dec 2008
11. Ungemah D, Kuhn B (2008) Strategy screening criteria for managed use lane projects. Report for New York State Department of Transportation. Texas Transportation Institute and Parsons Brinckerhoff, College Station, TX, July 2008
12. Browne R, Byrne A (2014) Highway 402 queue warning system. http://conf.tac-atc.ca/english/ resourcecentre/readingroom/conference/conf2008/docs/e1/Browne.pdf Online 13 Feb 2014
13. Neudorff L (2014) State of the practice for ATM feasibility and screening guidance. FHWA
14. Tech Memo traffi c management screening tool, version 1.0. http://mltooldev.tamu.edu Accessed 1 July 2014

Chapter 11 Corridor Management

Abstract Management strategies for traffi c corridors consisting of coordinated freeways and arterials (CFA) are described. The USDOT Integrated Corridor Management (ICM) program and its inclusion of other than private vehicle based modes is described. The chapter discusses the strategies and approaches employed in the San Diego and Dallas ICM corridors. Special corridors that address issues that are unique to particular locations are described and an example is discussed.

11.1 Coordinated Freeway and Arterial Operation

Prior chapters discuss many of the components employed for freeway management including ramp metering, incident management and motorist information technology and diversion strategies. This chapter discusses the integration of those strategies with arterials and with other components of the transportation system, and the operations required to implement this integration. Figure 11.1 [ 1 ] depicts a managed corridor.

Freeway corridors are often defi ned in terms of a freeway and the connecting and parallel arterials that serve to move traffi c in the same direction. The arterials may serve as an alternative to the freeway. Coordinated freeways and arterials (CFA) operations is the implementation of policies, strategies, plans, procedures, and technologies that enable traffi c on freeway and adjacent arterials to be managed jointly as a single corridor and not as individual, separate facilities. These policies, strategies, etc. should have an end goal of improving the mobility, safety, and environment of the overall corridor as well as traffi c on individual facilities [ 2 ]. This implies a proactive mindset to corridor management that emphasizes planning and operational cooperation and coordination among the agencies involved.

Urbanik et al. [ 2 ] identifi es the following sources of congestion that may be managed by the CFA approach.

Traffi c incident management
Work zone management
Planned special event management
Day-to-day or recurring operations

Goals and objectives are similar to those for the management of freeways, but with extension to the corridor.

Fig. 11.1 Example of development of corridor operations plans

11.1.1 Management Strategies

The strategies employed for CFA management are generally adaptations of freeway and surface street arterial ITS strategies, but with the emphasis on optimizing operation for the corridor. Strategies for coordinated operation are shown in Table 11.1 .

11.1.2 Operational Plans and Procedures for Coordinating Freeways and Arterials

CFA operation requires a single coordinated management approach to be employed by the agencies involved. One approach for managing incidents is illustrated in Fig. 11.2 [ 2 ]. It employs the following steps:

Defi nition of background scenarios (the set of normal traffi c conditions that may be expected).
Use of an activation matrix , the relationship between the lane blockage and incident clearance activity and criteria such as traffi c fl ow characteristics that may help to differentiate response requirements.
Selection of operations plans based on corridor operating strategies . Examples of these strategies include:
- DMS messages and arterial DMS messages
- Use of alternative signal timing plans
- Lane use strategies
- Function related real time communication requirements among agencies

Table 11.1 Examples of management strategies for coordinated corridors

Category	Strategies	Real time strategy	Every-day strategy
	Traffi c management and control
Freeway	Ramp metering	Traffi c responsive metering	Pretimed metering
management	HOV bypass at metered ramps	Not applicable	Encourage HOV use
	Active traffi c management	See Chap. 10	Not applicable
	Ramp closure	For incident management	Certain ramps may be closed to improve safety and mobility
Arterial management	Changeable lane use	Active lane controls	Pretimed lane controls
	Road closures	For incident management	Time of day controls
	On-street parking restrictions	For incident or special events management	Permanent or time of day
	Trailblazers	Dynamic trailblazers	Static trailblazers
	Parking management systems	Reduces circulating traffi c	Not applicable
	Arterial dynamic message signs	Incident and congestion management	Not applicable
Intersection traffi c control	Traffi c signal timing and coordination	Traffi c responsive and traffi c adaptive,	Pretimed signal control
		Operator selection of diversion timing plan
		Transit vehicle signal priority
		Preemption for emergency vehicles
	Access and turn restrictions	Only if safety considerations permit	Improves safety and mobility
Traveler information
Pretrip traveler information	Provision of information by public agencies (e.g.	Real time traffi c conditions, incidents, weather	Construction information
	511 services), provision	Trip reliability	Transit schedules
	by internet, smartphone and the media	Transit vehicle arrival time
	Provision of information by private organizations, provision by internet, smartphone and the media	Real time traffi c conditions and incidents, construction, route planning	Not applicable

(continued)

Table 11.1 (continued)

Category	Strategies	Real time strategy	Every-day strategy
En route traveler information	Provision of information by public agencies	Incident, congestion and travel time provided by DMS, arterial DMS, portable DMS, HAR, 511 services	Static signing
		Provision of incident and congestion information to private services and to the media
	Provision of information by private organizations. Provision of information by smartphone and by in-vehicle displays	Traffi c information obtained from public sources and by private agencies. Provision of traffi c conditions, routing information, lane and speed advisory information, anticipatory traffi c signal signal display information	Not applicable
	Incident management and safety initiatives
Traffi c and incident surveillance, incident management	Surveillance with CCTV, traffi c detectors, 911 reports, police reports	Find shortest route for emergency responders to incidents, help to manage traffi c and locate tail of queue, implement traffi c management incident response plans, provide information to media and traffi c service providers	Not applicable
	Motorist service patrols	Expedite clearance of minor incidents	Not applicable
Connected vehicle techniques (emerging)	In vehicle safety messages and vehicle controls	Provision of corridor information using in-vehicle displays	Not applicable

Figure 11.3 [ 2 ] shows the procedures that are required by this approach to transform the operations plans into action steps .

11.2 Integrated Corridor Management

The concepts described in Sect. 11.1 have been broadened by the USDOT Incident Corridor Management (ICM) program [ 3 ] to emphasize the employment of additional assets and strong corridor management initiatives to enhance corridor mobility. The listing below identifi es these corridor assets.

Freeways
HOV
Tolling
Value pricing
Arterials
Real time control
Bus
Fixed route
Express bus
Bus rapid transit
Rail
Commuter rail
Light rail
Subway/heavy rail

A USDOT project established Dallas, TX and San Diego, CA as sites to demonstrate ICM principles. In order to effi ciently use corridor resources and assets these sites incorporate decision support systems (DSS). The San Diego site's rule based DSS concept is shown in Fig. 11.4 [ 4 ] (redrawn) with examples of the rules for various conditions. Stakeholders defi ned a high-level decision support framework for ICM as part of their concept of operations. They organized their response plans, their "Response Posture," around a combination of demand conditions on the network ('X' axis), i.e., "light," "moderate," or "heavy;" and predicted 'event impact' ('Y' axis), assessed as "low," "medium," or "high." Within this framework (organized as a matrix), they then determined whether they would be likely to take "conservative," "moderate," or "aggressive," measures to manage the impacts. They then coded their joint response plans accordingly, and associating fi nely-tuned response actions with a host of scenarios.

Highlights of the Integrated Corridor Management system for the US 75 Corridor in Dallas include the following concepts [ 5 ]:

Congestion is monitored along I-75 and travel time is monitored on key surface streets using Bluetooth readers.
A predictive model determining corridor response is employed to assist in selecting corridor management strategies.
For minor incidents (one lane and shoulder blocked with less than a 2 mile queue) traffi c is diverted to the Frontage Road.
For major incidents (two or more lanes blocked or a 2–4 mile queue) traffi c is diverted to the Frontage Road, Greenville Ave and to the Red Line LRT.
Travel time assists in the selection of the appropriate signal timing plan are provided for appropriate surface streets in the corridor.
Parking availability is monitored for fi ve park and ride lots for the Red Line LRT and messages are provided on the DMS.

Table 11.2 provides an overview of US 75 ICM strategies [ 6 ].

Fig. 11.2 Example of development of corridor operations procedures

city signal engineer.

Fig. 11.3 Example of integrated managed corridor

Table 11.2 Overview of US 75 ICM strategies

Strategies	Scenarios
	Daily no incident	operations—	Minor incident			Major incident
Demand	Med	High	Med	High	Low	Med	High
Traveler information
Comparative, multi-modal travel time information (pre-trip and en-route)	●	●	●	●	●	●	●
Traffi c management
Incident signal retiming plans for frontage roads			●	●	●	●	●
Incident signal retiming plans for arterials			●	●	●	●	●
HOV lane a	○	○	○	○	○	○	○
HOT lane (congesting pricing)	●	●
Express toll lane (congestion pricing)	●	●
Light rail transit management
Smart parking system						●	●
Red line capacity increase						●	●
Station parking expansion (private parking)						●	●
Station parking expansion (valet parking)						●	●

HOV lane 2+ is currently in operation, thus is not considered an ICM strategy but is part of all scenarios

11.3 Special Corridors

11.3.1 Types of Special Corridors

The coordinated freeway and arterial corridors (Sect. 11.1 ) and the integrated corridors (Sect. 11.2 ) address issues that are common to many major urban areas. Many urban areas require special consideration of issues that are unique to a particular traffi c corridor. Examples of special corridors include:

Long term construction causing signifi cant traffi c congestion. Section 11.3.2 provides an example of a corridor of this type.
Emergency evacuations. ITS may assist police in providing support to such measures as reversing lanes, closing access points, and providing additional capacity on supporting alternate routes.
Special events. Lane management techniques, permanent or portable DMS and management messages on existing DMS in conjunction with intensive parking management techniques may be employed.
Limited access highways with no shoulders or sub-standard shoulders. While these problems may be addressed by the more intensive incident management operations commonly employed by bridge and tunnel operators, active traffi c and demand management strategies (Chap. 10) may also be employed to address these defi ciencies.

The concept of operations for projects containing special corridors should emphasize the unique issues involved and how the management concepts address these issues.

11.3.2 Example of Special Corridor [ 7 ]

Construction on ramps connecting the Betsy Ross Bridge to I-95 and Aramingo Ave. (a major surface street arterial) in Philadelphia will develop congestion for extended periods of time on I-95 and on Aramingo Ave. from Bridge St. to Allegheny Ave. The special corridor shown in Fig. 11.5 was defi ned to address this need.

The special corridor is a portion of the I-95 Corridor in Philadelphia. It is managed by the Pennsylvania Department of Transportation (PennDOT). Key ITS assets in the special corridor prior to any improvement include:

CCTV and point detectors on I-95.
CCTV and Bluetooth probe detectors on Aramingo Ave.
DMS on I-95. Arterial DMS (ADMS) on certain surface street locations in and near the corridor.
Interconnected signals on Aramingo Ave. Signals are controlled by the Philadelphia Department of Streets during working hours and by PennDOT at other times.
Extensive fi ber optics communications cable on I-95 and on key surface streets.

Fig. 11.4 Decision support logic for San Diego ICM project

A series of major reconstruction projects in the region encompassed by Fig. 11.5 is planned. The objective of the special corridor is to improve response to construction related congestion or incidents in the special corridor. In addition to a more rapid response to incidents it will provide detailed motorist information on congestion avoidance in the special corridor. A managed roadway network for the special corridor was defi ned (Fig. 11.6 ) and is consistent with the emergency detour routes developed under a prior project.

Requirements for managing the special corridor include the following:

Enhancement of incident detection and management capability by additional CCTV cameras at key locations.
Retention of currently employed motorist information messaging when no incidents or construction related delays are present in the special corridor.
Provision of detailed motorist information when incidents or construction related delays are detected in the special corridor. A decision support system (Appendix H) assists TMC operators to select detailed messages to be provided on DMS on arterial I-95 and on arterial ADMS at special corridor entry points, denoted as A, B, C, D and E in Fig. 11.7 . Additional ADMS will be provided at these points as necessary. Figure 11.8 shows an example of a message to be provided on a northbound DMS on I-95 prior to corridor entry. The DMS indicates conditions on both I-95 and on the Aramingo Ave. alternate.

Fig. 11.5 Special corridor in Philadelphia

Fig. 11.6 Managed roadway network in special corridor

Fig. 11.7 Corridor entry points

219 References

Fig. 11.8 Example of detailed DMS message

Interconnection and coordination of signals other than those on Aramingo Ave. (which are currently coordinated). Provision of signal timing plans to support the diversion introduced by the detailed motorist messaging.
Addition of fi ber optics communication cable to support the additional ITS devices and signal coordination.

References

1. Thompson D (2011) Integrated Corridor Management (ICM) overview, APTA Transit Tech Conference, Miami, FL, March 30, 2011
2. Urbanik T, Humphries D, Smith B, Levine S (2006) Coordinated freeway and arterial operations handbook. Report No. FHWA-HRT-06-095. Federal Highway Administration, Washington, DC, May 2006
3. Integrated Corridor Management Systems, Research and Innovative Technology Administration. http://www.its.dot.gov/icms/Online 3 Aug 2014
4. Applying decision support systems to integrated corridor management. ITE J, vol 84 No 7, July 2013
5. Dallas integrated corridor management (ICM) update. North Central Council of Governments, 26 Apr 2013
6. Stage 2, US-75 integrated corridor management analysis, modeling and simulation. http:// www.its.dot.gov/icms/pdf/ICMStage2AMS.pdf Online 9 Aug 2014
7. I-95 corridor intelligent transportation system. Systems Engineering Report, version 4.0. STV, Incorporated, Aug 2014

Chapter 12 Website Support

Abstract This chapter provides short descriptions of the fi les on the website that support this book (http://www.springer.com/us/book/9783319147673). The fi les implement models that are described in more detail in earlier chapters.

12.1 Introduction

In order to facilitate the reader's use of several of the models described in the text, several worksheets are provided in the form of Microsoft ® Excel workbook fi les and a Microsoft ® Word fi le on the website. The contents of these fi les are described in the following sections. In order to facilitate modifi cations or adaptations that the reader deems appropriate, the Excel workbook fi les are not protected and are populated with data to illustrate the type of data needed. Readers must substitute their own data to obtain results specifi c to their applications.

Because the Excel fi les are provided as "read only" fi les, the user must copy these fi les to a suitable folder and rename them prior to use.

12.2 System Delay per Incident

Since incidents may occur under a variety of traffi c conditions, the model offers a methodology to apportion the appropriate fraction of daily volume to the capacity conditions that apply and to then compute the resulting delay. Two worksheets are used to estimate the delay resulting from an incident on a roadway section with three lanes in one direction.

As described in Sect. 4.4.1 and illustrated in Fig. 4.12, the fi rst worksheet (CD Excel fi le Cohort Factors 3 Lane ) Titled "COMPUTATION OF COHORT FRACTIONS (THREE LANE ROADWAY)" generates fractions for the relative occurrence of incidents for groups of volume-to-capacity ratios (cohorts). This fi le is applicable where the roadway section under analysis consists of three lanes in one direction. The user must supply appropriate hourly volumes in columns 2 and 3, appropriate roadway section titles and an appropriate capacity. The data from the fi le are utilized as input to the Excel fi le Average delay resulting from incident . Figure 4.13 illustrates the worksheet and Sect. 4.4.2 describes the inputs to the fi le.

222 12 Website Support

12.3 Relative Effectiveness of CCTV Coverage

Section 4.5.1.2 describes the considerations for providing CCTV coverage. Appendix B presents a model for the effectiveness of this coverage. The measure, RTV represents the probable capability of CCTV to observe an incident on a section of roadway. Figure 4.28 shows an application of this model to a particular case. The Excel fi le RTV on the website provides one data point for this fi gure. The shaded cells require data input by the analyst.

12.4 Incident Management Effectiveness Potential

A model for assessing the effectiveness of ITS in enhancing the management of the response to incidents is described in Sect. 4.6.3.2. Figure C.1 in Appendix C illustrates an application of the model to evaluate candidate system design alternatives. Computations for this fi gure are shown in Fig. C.2. The Excel fi le Inc mgt effectiveness potential was used to compute the data for the 3 camera, 5 detector alternative for Fig. C.1. The value of RTV was obtained from Fig. 4.28.

12.5 Delay Reduced on Freeway Due to Queue Reduction Resulting from Diversion

Section 5.1.5 describes a model that provides approximate values for the reduction of freeway delay resulting from diversion. Figure 5.9 shows the results of the Excel worksheet fi le Delay improvement on freeway . The shaded cells in the workbook represent required data entries. The non-shaded cells perform the worksheet calculations.

12.6 Probability that the Motorist Encounters DMS Prior to Incident (P34)

Section 5.2.2.2 illustrates the computation of the parameter P34 when origindestination data is not available. This parameter represents the probability that the motorist encounters a DMS prior to the section containing the incident, thus providing the capability for diversion. The worksheet shown in Fig. 5.15 was computed by the Excel fi le Computation of P34 .

223 Reference

12.7 Queue Storage Requirement for Ramp Meter

Section 7.4.5.1 describes Caltrans' approach to estimating the storage space required for metered ramps. Figure 7.16 illustrates a typical computation chart [ 1 ]. The reference also provides a chart that is not populated with data (Fig. 7.17). For convenient use, that chart is reproduced in the jpeg fi le Ramp storage empty computation chart .

Reference

Ramp meter design manual (2000) Traffi c operations program. California Department of Transportation, Sacramento, CA

Chapter 13 ITS and the Connected Vehicle

Abstract Section 13.1 describes one view of a connected vehicle architecture that encompasses both the USDOT connected vehicle architecture and non-government entities and Sect. 13.2 covers the components of this architecture. Section 13.3 covers cellular telephone based techniques and Sect. 13.4 describes in-vehicle displays. Section 13.5 considers a key ITS operational issue related to connected vehicles and Sect. 13.6 discusses the USDOT connected vehicle program.

13.1 The Connected Vehicle

A connected vehicle is defi ned as any vehicle connected to an external network. At this writing, connected vehicle technology is evolving quite rapidly in both the private and public sectors. As the technology is rapidly changing, this chapter provides an overview of the status in 2015, and subsequent developments that may reasonably be foreseen. Private sector technology includes "infotainment", a category that includes vehicle and driver functions (the focus of this chapter) as well as others. While unsafe cellular telephone techniques are often employed to deliver this information, this chapter focuses on the current and emerging safe methodologies that may be employed.

Traditional methodologies for providing the motorist with ITS information include freeway based dynamic message signs (DMS), lane control signals (LCS) and variable speed limit signs (VSLS). In-vehicle display methodologies may be used to advantage to present this information.

Vehicle provided displays may reduce the future need for non-regulatory roadway information devices such as DMS. For example, A. Prasad, Secretary of Florida DOT, states "Ten years ago, VMS 1 made sense because the space was empty and there was a need for traveler information. State DOTs were the only ones providing this. Now there's so much information out there, we are starting to question whether we as a DOT, still need to provide traveler information…They probably make sense for the next few years, but long term we need to seriously think about whether this is something we should be investing in". Prasad envisages DOTs collecting data,

VMS (variable message sign) is an alternative acronym for dynamic message signs (DMS).

entering into public–private partnerships to share the publicly and privately collected data, and to provide that data to the public [ 1 ]. Reduced emphasis on DMS is also anticipated by Hendrickson et al. [ 2 ]. With the emphasis on motorist information shifting to the private sector, the role of transportation management centers in providing motorist information is changing.

13.2 Connected Vehicle Data Links

Figure 13.1 shows one perspective of the types of data links that may be used for connected vehicles.

The fi gure includes the following data link types:

Conventional ITS communication links—These links typically connect the traffi c management center (TMC) with fi eld equipment such as vehicle detector stations and roadway motorist information displays such as dynamic message signs (DMS), These connections typically use fi ber optic cable, cellular connections or owned wireless equipment. Communications with other centers are typically implemented by cellular telephone service, often over virtual private networks (VPNs).
Cellular/internet telephone based services—Cellular/internet telephone based service connects most of the currently available public and private applications to the vehicle. The fi gure shows an architecture that facilitates a safe and convenient methodology for smartphone based services. From the user's smartphone, a physical or Wi-fi connection is established to an appropriately adapted vehicle infotainment system (IVI). The IVI may be supplied by the vehicle manufacturer or by an aftermarket supplier. This architecture is further discussed in Sect. 13.3 .
USDOT connected vehicle architecture links—Fig. 13.1 includes a simplifi ed overview of the USDOT connected vehicle communication links. The connected vehicle architecture and its applications are discussed in Sect. 13.6 . Vehicles exchange basic safety messages (BSMs) through their on-board units (OBUs) and provide these messages to roadside units (RSUs) as well. RSUs are provided at certain freeway locations and at certain traffi c signal controllers. Communication among OBUs and between OBUs and RSUs is provided by dedicated short range wireless communications (DSRC) in the 5.9 GHz band. Information from central sources such as traffi c management centers may be sent to RSUs for transmission to vehicles.
Proprietary communication channels—These channels may carry special services provided in cooperation with vehicle manufacturers or aftermarket equipment suppliers. An example of a proprietary communication service is Sirius XM radio. Using satellite communications in the S band (2.32–2.345 MHz), this service provides traffi c and weather information in addition to entertainment channels. Proprietary connection capability using smartphones is also employed.
Conventional ITS roadway displays and AM/FM radio. Dynamic message signs, lane controls, highway advisory radio and conventional radio traffi c information reports are examples of currently available ITS applications.

Fig. 13.1 Data links for connected vehicles

13.3 Cellular/Internet Based Services

Most of the connected vehicle applications provided to date utilize this approach. Section 13.4 describes techniques for safely providing this information to motorists. A wide variety of mapping, route fi nding and navigation services are currently available with no subscription cost to the motorist. Information may be delivered in text, map and oral formats. In some cases, the information may be downloaded directly from the internet. In other cases, an application program must fi rst be

Fig 13.2 Traffi c signal state display

installed in the cell phone. Major limitations of cellular/internet information delivery include:

Latency limitations—Latency is a measure of the communications response time. It is usually defi ned as the average time to transmit a message and receive a response. Rapid response requirements for certain safety related messages may prevent the use of this approach for those applications.
Cellular telephone charges. Continuous connection requirements may result in charges that are unacceptable to the driver.

Travel related functions commonly provided by cellular/internet technology include:

Traffi c information and navigation
State 511 systems
Parking availability
Specialized services. One specialized service is the provision of traffi c signal state countdown information. A system implemented by Connected Signals Technology provides displays such as that shown in Fig. 13.2 in certain locations.

The information must be provided to the motorist in a safe and convenient manner, and at this writing, vehicular technology is moving rapidly in this direction.

Currently, internet/cellular information may be provided in three ways:

1. Vehicle manufacturer supplied equipment and software . The Ford Sync system is an example of this technique. The interface with the smartphone is through a Bluetooth connection. The screen can be controlled by voice activated commands as well as by screens. Travel related functions such as those described above may be accessed. In addition other internet provided infotainment functions are available as well as vehicle supplier functions such as vehicle health reports.
2. Cellular telephone providers . Major providers of cellular telephone operating systems have developed interfaces to head units similar to those described above. Android Auto and Apple CarPlay are examples of this approach. Selected applications are supported. Travel related features are generally similar to those described above.
3. Non proprietary standards . The Car Connectivity Consortium comprised of a number of auto and electronics manufacturers has established an industry standard for certifying applications and devices that are both safe and useful for drivers called MirrorLink [ 4 ]. It displays the smartphone screen from a number of mobile operating systems. It is available for both vehicle manufacturers and aftermarket suppliers.

13.4 In-Vehicle Displays

Typical in-vehicle components include the cellular telephone and the infotainment system head unit including the visual display and a method of control. Controls may consist of a touch screen integrated with the dashboard display or alternatively a head-up display (HUD) may be employed. Head-up augmented reality displays have been introduced. In one implementation, the head unit connects to the cellular phone with a cable or wireless connection. The screen of the head unit essentially replicates the cell phone display. Voice replication and voice command capability are also provided. Commands on the screen and by voice provide for the selection of all infotainment systems.

Traffi c information, roadway conditions and regulatory information may be presented in a variety of display techniques and provided by vehicle suppliers or by aftermarket suppliers. HUDs may result in less driver distraction than dashboard displays.

NHTSA has developed guidelines for avoiding driver distraction [ 5 ]. These guidelines recommend that glances away from the roadway should be completed in two seconds or less and that the cumulative time spent in glancing away from the roadway should be 12 seconds or less.

13.5 The Traffi c Management Dilemma

As the provision of motorist information becomes increasingly privatized, a consequence is that the capability of government agencies to provide the traditional traffi c management and assignment functions may become signifi cantly impacted. Privatized traffi c assignment is ad hoc, does not conform either to theoretical traffi c assignment principles or to traffi c assignment practices desired by the TMC. This may result in unfavorable impacts on traffi c distribution. Although private fi rms do not explicitly try to manage traffi c on an area-wide basis, their messages, in effect and at least in part, perform this function. While private fi rms have the advantage of access to both private and publicly available traffi c information, their ability to properly manage traffi c is limited by:

The inability to provide CCTV based traffi c information as well as the personal supervision and judgement such as provided by TMC managers and operators.
The business models of private fi rms focus on providing automated information to individual motorists. Turn-by-turn route guidance information is the most popular form of presentation. These fi rms generally have no mandate or motivation to implement corridor-wide or area-wide traffi c management strategies, nor to inject human supervision. The individual strategies for responding to non- recurrent congestion may prove counter-positive from a system-wide viewpoint.
The route optimization models of private fi rms may contrast with the traffi c assignment emphasis and constraints employed by public agencies.

Possible techniques to address these issues include:

Provision of traffi c information such as that presented on state 511 websites and their mobile applications to enable safe, in-vehicle presentation of corridor management information.
Provision of detailed traffi c conditions and traffi c management messaging to private traffi c services.

13.6 USDOT Connected Vehicle Program

This is a very large scale program whose basic objectives are the improvement of safety, mobility and the environment by the use of connected vehicle technology. USDOT indicates that connected vehicles have the potential to address approximately 80 % of vehicle crash scenarios involving unimpaired drivers [ 6 ]. The

Fig. 13.3 Basic safety message descriptors

-- Part I, sent at all times
msgID DSRCmsgID, -- App ID value, 1 byte
msgCnt MsgCount, -- 1 byte
id TemporaryID, -- 4 bytes
secMark DSecond, -- 2 bytes
-- pos PositionLocal3D,
lat Latitude, -- 4 bytes
long Longitude, -- 4 bytes
elev Elevation, -- 2 bytes
accuracy PositionalAccuracy, -- 4 bytes
-- motion Motion,
speed TransmissionAndSpeed, -- 2 bytes
heading Heading, -- 2 bytes
angle SteeringWheelAngle, -- 1 bytes
accelSet AccelerationSet4Way, -- 7 bytes
-- control Control,
brakes BrakeSystemStatus, -- 2 bytes
-- basic VehicleBasic,
size VehicleSize, -- 3 bytes

fundamental premise of the connected vehicle initiative is that enabling wireless connectivity among vehicles, the infrastructure, and mobile devices will bring about transformative changes in safety, mobility, and the environmental impacts in the transportation system [ 7 ]. Key elements of the program include:

Vehicle to vehicle (V2V) communication. In 2014 NHTSA published an advanced notice of proposed rulemaking (ANPRM) that would require light motor vehicles to contain a vehicle to vehicle short-range communication (DSRC) capability in the 5.9 GHz band [ 8 ]. The communications and data formatting are provided by an on board unit (OBU).
NHTSA's study recommended transmission of a basic safety message (BSM). The contents of the BSM are shown in Fig. 13.3 [ 9 ]. Position and motion messages are broadcast at a rate of ten times per second. The ANPRM cites the following applications that would signifi cantly improve safety:
- Intersection Movement Assist (IMA)
- Left Turn Assist (LTA)

The safety applications using this technology would be developed by industry.

• Vehicle to infrastructure (V2I) communication. Roadside units (RSU) communicate with vehicle OBUs in the 5.9 GHz band and may exchange information with information sources such as TMCs as shown in Fig. 13.1 . They may also provide information from intersection traffi c controllers to vehicles. Since USDOT does not currently plan to mandate installation of RSUs, their availability is not assured. A key application envisioned by USDOT is the signal phase and timing (SPaT) message which identifi es the current traffi c signal state. This message is transmitted by an RSU in a traffi c signal controller cabinet to vehicle OBUs. Software in the vehicle may use this data, in conjunction with information from the vehicle's own sensors to determine whether additional action is required to enable the vehicle to obey the signal. This type of information, when coupled with BSM information from other vehicles may possibly be used to determine whether additional action is required to avoid a crash with another vehicle that is not going to slow or stop when required.

The USDOT Connected Vehicle Program is engaged in research covering a large number of applications. While some of these applications are unique to connected vehicles, others are modifi cations of existing ITS or non-USDOT based connected vehicle services.

The Connected Vehicle Reference Implementation Architecture (CVRIA) is being developed as the basis for identifying the key interfaces across the connected vehicle environment that will support further analysis to identify and prioritize standards development activities. CVRIA will also support policy considerations for certifi cation, standards, core system implementation, and other elements of the connected vehicle environment [ 10 ]. CVRIA is developed in four viewpoints:

Enterprise—The relationships between organizations and the roles those organizations play within the connected vehicle environment.
Functional—Abstract functional elements (processes) and their logical interactions (data fl ows) that satisfy the system requirements.
Physical—Physical objects (systems and devices) and their application objects as well as the high-level interfaces between those physical objects.
Communications—The layered sets of communications protocols that are required to support communications among the physical objects that participate in the connected vehicle environment.

A key standard included in the CVRIA is the SAE J 2735 Standard [ 10 ]. This standard essentially provides the message sets used for V2V and V2I communications. Table 13.1 shows proposed message priorities based on safety impacts and latency (urgency) for applications [ 10 ]. Higher priority numbers represent greater safety impacts.

Table 13.1 Message priorities (proposed values) and latency

Reception latency

Importance level from FCC

policy description	Description (when to apply a specifi c urgency level)	Example(s)	ms) (urgency) (
Messages and 1 = Safety of Life Those	mpact mitigation and injury avoidance/ mergency i mitigation E	Crash-Pending Notifi cation	<10
Message Sets requiring mmediate or urgent	mpact and/or injury mitigation mergency potential-event i and avoidance E	Pre-Crash	<10
mission trans	Warning Events (using Event Flags) Urgent	Warning, EEBL, Anti-Lock, etc.) and Control Loss Hard-Brake (Collision	<10
	mpending local situation Urgent warning of i	mergency Vehicle Approaching E	10–20
	Situation-based status information of uninvolved local interest	mergency Vehicle, Situation Ahead (e.g., E Accident)	10–20
	Situation-based status information of uninvolved local interest	mergency Vehicle, Situation Ahead (e.g., E Accident)	10–20
	Potential-situation information of uninvolved local interest	Probable-situation (e.g., Rapidly deteriorating dangerous conditions)	10–20
	Possible-situation information of uninvolved high-latency local interest	Possible-situation (e.g., Deteriorating dangerous conditions)	>20
			(continued)

Table 13.1 (continued)

m FCC mportance level fro I			Reception latency
policy description	Description (when to apply a specifi c urgency level)	Example(s)	ms) (urgency) (
2 = Public Safety (Safety	Urgent public safety downloads (Intersection Information)	ming) SPAT (Signal Phase and Ti	<10
not in 1)	Urgent public safety data transactions, exchanges	Electronic Toll Collection	<10
Roadside Units (RSUs) and	Periodic public safety status information	Heartbeat message	<10
operated by state or local On-Board Units (OBUs)	Public safety geospatial context information	GID message (Geospatial Context)	<10
mental entities that govern	ment mi-urgent public safety link establish Se	Lane Coordination; Cooperative ACC	<10
mptively engaged are presu	Public safety GPS correction information	GPSC message (GPS Correction)	<10
in public safety priority	Periodic less frequent public safety status information	Heartbeat (at lower frequency)	<10
mmunications (Includes Mobility and Traffi c co	m enabler mi-urgent public safety syste Se	metric Intersection Defi nition Localized Geo Download	10–20
ment Features) Manage	mi-urgent public safety data and application enabler Se	Map Download Services Table, Digital	>20
	ment status information enabler Manage mportant Traffi c I	Highway Closed Ahead	>20
	ment of Services mportant Announce I	ment) Wave Service Announce WSA message (	>20
	ment enabler Manage mportant Traffi c mi-i Se	General Traffi c Information Download	>20
	ment Foundational Data Manage Non-urgent Traffi c	Messages, Localized warning zones update Probe	>20
3 = Non-Priority	Urgent, private mobility message	Off-Board Navigation Reroute Instructions	<10
mmunications (not in 1 Co	mmercial electronic transactions Urgent, private and co	ments Electronic Pay	<10
ment of Traveler Information Manage Fleet or 2)	mi-urgent, private mobility data exchange Se	Private mobility applications (e.g., GPS based driving instructions)	10–20
Services and Convenience	mmercial electronic transactions mi-urgent, private and co Se	mmerce applications mmerciai and private e-co Co	10–20
ms or Private Syste	mmercial electronic transactions mportant, private and co I	mmerce) mmercial transactions (E-Co Large co	10–20
	mportant, private mobility data exchange I	mmercial and private offers, directions Co	10–20
	Background, private mobility data exchange	Area map download or upgrade	>20

Background, private data downloads and upgrades Database download >20

235 References

References

1. "The Death of VMS", Traffi c Technology International, January 2015
2. Hendrickson C, Biehler A, Mashayekh Y (2014) Connected and autonomous vehicles-2040 Vision, Pennsylvania Department of Transportation, July 10, 2014
3. EnLighten Users Guide, Connected Signals, Inc., Online. http://connectedsignals.com/ enlighten\_Android\_users\_guide.php, July 19, 2015
4. Car Connectivity Consortium, online, July 19, 2015. http://www.mirrorlink.com/
5. Visual-Manual NHTSA Driver Distraction Guideline for In-Vehicle Electric Devices, Docket No. NHTSA-2010-0053National Highway Traffi c Safety Administration, 2012, online 061215, http://www.distraction.gov/downloads/pdfs/visual-manual-nhtsa-driver-distraction guidelines-for-in-vehicle-electronic-devices.pdf
6. Lister M, Schagrin M, Fehr W, Pol J (2013) Connected Vehicle Program 101, April 21, 2013
7. Wright J, Garrett JK, Hill CJ, Krueger GD, Evans JH, Andrews S, Wilson CK, Rajbhandari, Burkhard B (2014) National Connected Vehicle Infrastructure Footprint Analysis, American Association of State Highway and Transportation Offi cials, Federal Highway Administration Report No FHWA-JPO-14-125, June 27, 2014
8. Federal Register Vol. 79, No. 161/Wednesday, August 20, 2014
9. DSRC Implementation Guide (2010) SAE International, February 2010
10. Connected Vehicle Reference Implementation Architecture, Research and Innovative Technology Administration, 12/03/14, online 03/20/15. http://www.iteris.com/cvria/

Appendix A Travel Time, Delay and Travel Time Reliability Measures

This appendix describes the techniques and algorithms that may be used to compute a number of the measures described in Table 9.3. This appendix provides the computations for obtaining the 5 min and 15 min values for travel time, delay and travel time reliability (see Fig. 9.8). The 15 min values must be further aggregated by the user to obtain the specific time period desired for the measure. This appendix is largely based on Gordon [1]. Table A.1 summarizes the notation employed in the appendix.

Freeway Delay and Travel Time

Many freeway management systems are equipped with point-based, and in some cases probe-based, traffic detectors to perform normal traffic management functions. Since these detectors provide a basis for automatic data collection for performance evaluation purposes, the manual effort to obtain measures based on speed and travel time is minimal.

Several measures in Table 9.3 require the computation of travel time and delay. System delay is the sum of freeway mainline delay and freeway ramp delay for all vehicles. System travel time has a similar relationship. Vehicle travel time, delay and travel time reliability consider these quantities on an individual trip basis.

The relationships provided below describe the requirements for obtaining freeway mainline data.

| Table A.1 | List of symbols, variables and parameters for Appendix A | | | | |-----------|----------------------------------------------------------|--|--|--| |-----------|----------------------------------------------------------|--|--|--|

a, b denote domain end points for link level computations

D=System mainline delay for measurement interval (vehicle hours)

DO=Domain ID

FC=Commercial vehicle fraction of traffic volume

FD=Freeway system delay

FP=Private passenger vehicle fraction of traffic volume

K1=Average number of travelers in private passenger vehicle

K2=Average number of occupants in commercial vehicle

L=Link ID

L1=Start of link range under evaluation

LE=Length of link, domain or probe sensing region (mi)

LN=Last link in range under evaluation

LPP=Traveler system delay in private passenger vehicles (person hours)

LPT=Occupant delay in commercial vehicles (person hours)

LV=Link volume

M=Mean travel time of a set of sample trips for the period

N=number of sample trips

N15=15-min evaluation period index number

N5=5-min evaluation period index number

NF=Freeway evaluation time period index number (used for freeway and entry ramps)

P=15-min period index

PHT=Peak hour throughput

PR=Probe sensing region ID

RI=Link on start of selected route

RO=Link on end of selected route

ROD=Freeway route delay (hours)

RRT=Reference ramp travel time

RTT=Route travel time (hours)

s=Standard deviation

SD=Domain speed (mph)

SP=Probe sensing region speed (mph)

SR=Reference speed (reference speed for delay) (mph)

T=Time measurement interval (hours)

T15=15 min (.25 h) for intersection signals and surface streets

T5=5 min (.06777 h) for mainline and ramps

Tj=Travel time of jth trip on a specific route

TP=Travel time as sensed by probe vehicles (hours)

TT=System mainline travel time (veh h)

V=Roadway volume (vph)

VD=Vehicle delay (hours)

VSD=Vehicle system delay (hours)

VT=Vehicle travel time (hours)

x denotes the number of vehicles in 5- or 15-min probe vehicle sample

Mainline Delay and Travel Time Evaluation for Point Detectors

The values for these measures are built up using the structure and relationships shown in Figs. 9.6, 9.7, and 9.8. The domain is the basic spatial structure for the computation scheme. Its boundaries are determined by the following:

• Freeway entry and exit locations
• Location of DMS and other traffic management and control devices
• Detector locations

Domain System Travel Time

Equation (A.1) computes domain travel time for all vehicles in a domain in a 5 min period.

$$TT(DO,N5) = T5 \cdot V(DO,N5) \cdot LE(DO) / SD(DO,N5)$$ (A.1)

where

TT=System mainline travel time (veh h)

DO=Domain ID

N5=5-min evaluation period index number

T5=5 min (.06777 h) for mainline and ramps

V=Roadway volume (vph)

LE=Length of link, domain or probe sensing region (mi)

SD=Domain speed (mph)

In some systems traffic management systems SD represents weighted speed [2]. Since speeds and volumes are different in different lanes, weighted speed is the product of lane volume and lane speed divided by total volume.

Domain System Delay

Domain system delay removes the vehicle hours of vehicles travelling at or above a reference speed which is considered to be an acceptable value.

$$If (TT(DO,N5)-T5\cdot V(DO,N5)\cdot LE(DO)/SR(DO))>0 \text{ then } D(DO,N5)$$

$$= (TT(DO,N5)-T5\cdot V(DO,N5)\cdot LE(DO)/SR(DO)) \text{ else} D(DO,N5)=0$$ (A.2)

where

D=System mainline delay for measurement interval (vehicle hours)

SR=Reference speed (reference speed for delay) (mph)

Link System Travel Time

Travel links (distance between each freeway exit or entry location and the next downstream location) are commonly used to provide the geographical structure for expressing measures. Equation (A.3) sums the system travel times for the domains in a link.

$$TT(L,N5) = \sum_{DO=a}^{b} TT(DO,N5)$$ (A.3)

where

L=Link ID

a=domain that begins link

b=domain that terminates link

Link System Travel Time for 15-Min Periods

Equation (A.4) aggregates the 5-min period link travel time to 15 min.

$$TT(L,P) = \sum_{NF}^{NF+3} TT(L,N5)$$ (A.4)

where

P=15-min period index

NF=NF 5-min index at the beginning of the 15-min period

Link System Delay

$$D(L,N5) = \sum_{DO=a}^{b} D(DO,N5)$$ (A.5)

System Delay for 15-Min Periods

$$D(L,P) = \sum_{N5=NF}^{NF+3} D(L,N5)$$ (A.6)

Vehicle System Delay

Equation (A.7) sums Eq. (A.6) over a daily period and over the set of links under evaluation (for example, a freeway or the entire freeway system)

$$VSD = \sum{L=L}^{LN} \sum{P=1}^{96} D(L, P)$$ (A.7)

where

L1=the start of start of the link range under evaluation LN=the last link in the link range under evaluation VSD is vehicle system delay

By modifying Eq. (A.7), Eqs. (A.8) and (A.9) provide values for private passenger vehicle occupant system delay and commercial vehicle occupancy system delay.

Private Passenger Occupancy System Delay

$$LPP(L,P) = K1 \cdot \sum{L=L}^{LN} \sum{P=1}^{96} D(L,P) \cdot FP(L,P)$$ (A.8)

where

K1=Average number of travelers in private passenger vehicles FP=Private passenger vehicle fraction of traffic volume

Commercial Vehicle Occupant System Delay

$$LPT(L,P) = K2 \cdot \sum{l=l}^{LN} \sum{P=1}^{96} D(L,P) \cdot FD(L,P)$$ (A.9)

where

K2=Average number of occupants in commercial vehicle FC=Commercial vehicle fraction of traffic volume LPT=Occupant delay in commercial vehicles (person hours)

Domain Vehicle Travel Time

Equation (A.10) provides the travel time for an individual vehicle in a domain computed for each 5-min interval.

$$VT(DO, N5) = T5 \cdot LE(DO) / SD(DO, N5)$$ (A.10)

where

VT=Vehicle travel time (hours)

Domain Vehicle Delay

$$If (VT(DO,N5) - T5 \cdot LE(DO) / SR(DO) > 0) \text{ then } VD(DO,N5)$$

$$= (VT(DO,N5) - T5 \cdot LE(DO) / SR(DO)) \text{ else } VD(DO,N5) = 0$$ (A.11)

where

VD=Vehicle delay (hours)

Link Vehicle Travel Time

$$VT(L, N5) = \sum_{DO=a}^{b} VT(DO, N5)$$ (A.12)

Link Vehicle Travel Time for Each 15-Min Period

$$VT(L,P) = \sum_{NS+NF}^{NF+3} VT(L,N5)$$ (A.13)

Link Vehicle Delay

$$VD(L,NF) = \sum_{DO=a}^{b} VD(DO,N5)$$ (A.14)

Link Vehicle Delay for Each 15-Min Period

$$VD(L,P) = \sum_{NS+NF}^{NF+3} VD(L,N5)$$ (A.15)

Mainline Delay and Travel Time Evaluation for Probe Detectors

Probe detectors provide the basis for developing link delay and link travel time. Because the boundaries of probe sensing regions may not directly correspond to link boundaries, a domain structure, such as shown in Fig. 9.7, or an equivalent relationship is required. The basic concept requires determining the speed in the set of domains included in the probe sensing region by dividing the region's length by the travel time measured by the probe vehicles, as shown in Eqs. (A.16) and (A.17). This speed (SP) represents the speed for all domains encompassed by the probesensing region and is employed to compute domain and link vehicle travel time and delay in Eqs. (A.8)–(A.13) at the 5-min level. It is used for probe detection in place of SD in Eqs. (A.1) and (A.10).

$$TP(PR,T5) = \frac{1}{x} \cdot \sum_{i=1}^{x} TP(i)$$ (A.16)

$$SP(PR) = LE(PR)/TP(PR,T5)$$ (A.17)

where

TP=Travel time as sensed by probe vehicles (hours)

PR=Probe sensing region ID

x denotes the number of vehicles in 5 or 15 min probe vehicle sample

SP=Probe sensing region speed (mph)

LE=Length of probe sensing region

In order to develop system delay and system travel time measures, the volume variable required by Eqs. (A.1) and (A.2) must be obtained. A source of link volume data such as a point-detector station is required. Only one volume data source per link is required.

Route Travel Time, Route Travel Time Reliability and Throughput

Route Travel Time

Route travel time is commonly provided to the motorist by DMS on the freeway mainline as well as by web sites. Designated routes are often provided for this purpose, and these routes are convenient to use for evaluation [3].

Route travel time is the sum of route link travel times (VT) and may be computed as follows.

$$RTT = \sum_{L=RI}^{RO} VT(L, N5)$$ (A.18)

where

RTT=Route travel time (hours)

RI=Link on start of selected route

RO=Link on end of selected route

If the trip starts at 7 AM, the travel time for the first link on the route (designated as RI) becomes VT for the time period starting at 7 AM. N5 for the first link in this case is 73 (12 5-min periods for the period from midnight until 7 AM plus the current evaluation period). It is designated as NSTART.

Recognizing that the links on the route might be traveled during different time periods, and consequently at different speeds, a laddered concept for computing route travel times (RTT) is discussed by Ishimaru and Hallenbeck [3]. Route travel time is the sum of route link travel times (VT) and is computed for the appropriate time period for that link as follows.

If VT for this link<5 min, then the travel time for the next link uses the same 5-min time period. If VT≥5 min, then the travel time for the next link uses the subsequent 5-min time period. Higatani et al. [4] indicate that this approach is more accurate than the summation of link travel times computed for a single time period. Figure A.1 depicts a flow chart that implements this concept.

Similarly, freeway route delay (ROD) may be computed as follows.

$$ROD = RTT - \sum_{L=RI}^{RO} LE(L) / SR(L)$$ (A.19)

Route Travel Time Reliability

Travel time reliability measures the extent of this unexpected delay. A formal definition for travel time reliability is: the consistency or dependability in travel times, as measured from day-to-day and/or across different times of the day [5].

Travel time variability may be measured by comparing travel times for a specified route for a given time period (for example for a peak hour starting at 7 AM). Shaw [6] recommends a minimum data collection period of 4 weeks at 15 min intervals. Coupling this criterion with the previous discussion of route travel time, if a "trip" is considered to be a calculation of three 5-min travel times for each 15-min period in a weekday peak hour, eliminating holidays and other non-representative days, a 1 month data collection cycle provides a sufficiently representative data cycle.

The basis for travel time variability and the measures that are used to express it is the standard deviation of the travel time measurements. This is given by Martin and Wu [7] as:

$$s^{2} = \frac{\sum (T_{j} - M)^{2}}{n - 1}$$ (A.20)

Fig. A.1 Time periods for travel time computation

where

s=estimate of travel time standard deviation

Tj=the travel time of the jith trip on a specific route

M=the mean travel time of a set of sample trips for the period (e.g. 15 min) n=the number of sample trips

Commonly used measures of route travel time reliability are the completion of 90 % or 95 % of the trips within a given time. Statistical tables indicate that the relationship between the sample of travel times and the mean are as follows:

A 90 % reliability corresponds to 1.28 standard deviations A 95 % reliability corresponds to 1.64 standard deviation

Fig. A.2 Relationships among travel time reliability measures

Measures that are commonly used [5] include:

*Buffer time*—The extra time required (i.e., calculated as the difference between the 95th percentile travel time and the average travel time) as provided by Eq. (A.21).

$$Buffertime = 1.64 \cdot s \tag{A.21}$$

*Planning time*—The total travel time, which includes buffer time (i.e., calculated as the 95th percentile travel time).

$$Planningtime = RouteTravelTime + Buffertime$$ (A.22)

*Planning time index*—How much larger the total travel time is than the ideal or free-flow travel time calculated as the ratio of the planning time to the ideal.

*Buffer index*—The size of the buffer time as a percentage of the average route travel time calculated as the planning time minus the average, divided by the average route travel time.

The relationship among these measures is shown in Fig. A.2 [5].

The basis for all of the reliability measures is route or point-to-point travel times. There are four basic ways in which these travel times can be developed [7]:

1. Directly calculated from continuous probe vehicle data;
1. Estimated from continuous point-based detector data;
3. Collected in periodic special studies (e.g., floating car runs); and,
1. Estimated using computer simulation, sketch planning, or demand forecasting models.

List et al. [8] provide a detailed discussion travel time reliability along with examples of deployments.

Throughput

One measure of throughput is the vehicle miles for a link for the peak hour. For each 5 min of the peak hour identify the lowest volume for each domain in the link (LV). Peak hour throughput (PHT) is provided by Eq. (A.23)

$$PHT(L) = \sum_{N5=\text{ five minute period identifier for peak hour starr}}^{N5+12} T5 \cdot LE(L) \cdot LV(L, N5)$$ (A.23)

References

1. Gordon R (2012) Methodologies to measure and quantify transportation management center benefits. FHWA Report FHWA-HRT-12-054, Washington, DC
2. Park B (2005) Transportation management system performance monitoring, evaluation and reporting—a technical handbook. University of Virginia, FHWA Report FHWA-HOP-07-142
3. Ishimaru JM, Hallenbeck ME (1999) Flow evaluation design technical report. University of Washington Report No. WA-RD-466.2, Mar 1999
4. Higatani A, Kitazawa T, Tanabe J, Suga Y, Sekhar R, Asakura Y (2009) Empirical analysis of travel time reliability measures in Hanshin Expressway network. J Intell Transport Syst 13(1): 28–38
5. Travel time reliability: making it there on time, all the time. http://www.ops.fhwa.dot.gov/ publications/tt\_reliability/ttr\_report.htm. Accessed 23 Dec 2013
6. Shaw T (2003) Performance measurements of operational effectiveness for highway segments and systems. NCHRP Synthesis 311, Transportation Research Board
7. Martin PT, Wu P (2003) Automated data collection, analysis and archival. University of Utah Traffic Lab, Nov 2003
8. List GF, Williams B, Rouphail N (2014) Guide to establishing monitoring programs for travel time reliability. SHRP 2 Report S2-LO2-RR2, Transportation Research Board, Washington, DC

Appendix B Relative Effectiveness of CCTV Coverage

Most of the accidents on urban and suburban freeways occur in the vicinity of interchanges. These accidents often take longer to clear than non-accident-related incidents. Thus, ITS designs that do not provide for complete or near-complete CCTV coverage usually place most of the cameras in the vicinity of the interchanges. The incident-hours covered by these cameras provide a larger fraction than would be experienced if the accidents were distributed evenly along the roadway (non-accident-related incidents are assumed to be evenly distributed along the roadway). This appendix describes a measure (RTV) for evaluating the relative coverage of incidents by CCTV. RTV approximately represents the fraction of incident periods in the section that is observable by the CCTV cameras.

Figure B.1 provides the physical layout for the RTV computation. The section shown in the figure represents one direction of the roadway between two interchanges. For convenience, half the distance within the interchange is attributed to the section (the other half is assigned to the adjacent section).

The following parameters are used for the computation of RTV:

ACR	Accident rate for section
ARI	Accident rate in interchange area
ARNI	Accident rate in non-interchange area
IDI	Duration of incidents and accidents in interchange areas
IDN	Duration of incidents and accidents in non-interchange areas
LS	Section length
L1	Distance in the section in the vicinity of the upstream interchange for the section midpoint of the interchange that encompasses most of the accidents
L2	Distance in the section in the vicinity of the downstream interchange; the values L1 and L2 represent half the distance centered at the midpoint of the interchange that encompasses the highest accident rate portion of the section
NAIR	Non-accident incident rate
TVI	Fraction of roadway visible to CCTV at interchanges
TVN	Fraction of roadway visible to CCTV away from interchanges
TNA	Test for presence of non-interchange area in section
WE	Ratio of accident rate in interchange area to accident rate in non-interchange area

Fig. B.1 Physical relationship for RTV equation

Accident data may be available in the following ways:

• Accident rate summary for the section.
• Detailed accident rate data may be available by milepost (usually 0.1 mile intervals) or by geodetic reference.

Accident rate data for the section (identified above as ACR) may be disaggregated into the high accident rate portion near the interchanges (ARI) and the lower accident portion away from the interchanges (ARNI). The model expresses the approximate relationship.

$$ARI = WE \cdot ARNI \tag{B.1}$$

An estimated value for WE is required. The total number of annual accidents (TA) in the section may be expressed as

$$TA = ACR \cdot LS = (L1 + L2) \cdot ARI + (LS - L1 - L2) \cdot ARNI$$ (B.2)

Substituting (B.1) into (B.2) yields

$$TA = ACR \cdot LS = (L1 + L2) \cdot WE \cdot ARNI + (LS - L1 - L2) \cdot ARNI$$ (B.3)

Simplifying (B.3) yields

$$ARNI / ACR = LS / (LS + (L1 + L2) \cdot (WE - 1))$$ (B.4)

In some cases detailed accident data at tenth of mile intervals is available, thus providing WE directly from (B.1).

The computations for the relative coverage of incidents by CCTV are as follows:

$$IDI = (ARNI \cdot WE + NAIR) \cdot (L1 + L2)$$ (B.5)

Fig. B.2 CCTV coverage for camera development alternatives

$$IDN = (LS - (L1 + L2)) \cdot (ARNI + NAIR)$$ (B.6)

$$RTV = (TVI \cdot IDI + TVN \cdot IDN) / (IDI + IDN)$$ (B.7)

Figure B.2 illustrates a simplified case study for evaluating RTV. Here each CCTV camera is assumed to cover one half mile of roadway. A distance of one half mile centered at the midpoint of the interchange is also assumed to represent the accident clustering region. The boundaries for the section under evaluation extend from the midpoint of the upstream interchange to the midpoint of the downstream interchange. Three alternate deployments providing less than 100 % CCTV coverage are shown in Fig. B.2, along with the CCTV camera count. The cameras at the interchanges are each counted as one half of a camera because 50 % of their

Fig. B.3 Relative effectiveness of CCTV coverage

coverage extends into another section. Other parameters for the case study example include the following:

• Non-accident incident rate=7.03 incidents per mile per year
• Accident rate for section=2.1 accidents per mile per year
• Ratio of accidents in interchange area to accidents in non-interchange area=2.4

The worksheet RTV on the website http://www.springer.com/us/book/ 9783319147673 and shown in Fig. B.3 was used to compute the values shown in Fig. 4.28. If the milepost based accident data is available, the value WE may be computed from this data (B.1) and entered into the worksheet. If only section summary accident rate data is available, the default value of WE=2.4 may be retained or another value may be substituted.

Appendix C

Example of Benefits for Incident Management

This appendix provides an example of an alternatives analysis for the computation of the reduction in vehicle delay and accidents for ITS support of incident management.

The traffic parameters in the travel direction for the example are described in Table C.1, The parameters for the ITS treatments are shown in Table C.2. Two alternatives are considered for CCTV camera placements and two alternatives for detector deployment are examined in the example.

Equations (4.13)–(4.17) were applied to the parameters described above for the example for alternatives ac, ad, bc and bd. Figure C.1 shows a plot of the results for the alternatives shown in Table C.2 as well as the alternative of no detectors and no CCTV camera. The Inc mgt effectiveness potential worksheet on the website http:// www.springer.com/us/book/9783319147673 (shown in Fig. C.2) was used to develop the data for the three camera and five detector alternative designs in Fig. C.1.

Table C.1 Traffic parameters for example

Symbol	Definition	Value	Comments
	Number of lanes	3
AADT	Average annual daily traffic (vehicles/day)	75,000
ACCR	Accident rate (accidents per million vehicle miles)	2.1	Based on New York State average for freeway accidents
CS	Capacity (vehicles/h)	6,300
IR	Capacity reducing incidents in incidents per million vehicle miles	9.01	Based on data for upstate New York metropolitan areas
LS	Section length (miles)	1.7
MVMPY	Million vehicle miles per year	46.54	Based on MVMPY=AADT ⋅ LS ⋅ 365/1,000,000
PHV	Peak hour volume (vehicles/h)	6,000
TSI	Time reduced per incident in vehicle miles for high level of ITS deployment and intensive incident management by the TMC	271.8	Table 4.3 for three lanes and traffic condition level 3
K35	Correction factor for level of service	1.0	See Appendix F for further details

| Table C.2 | ITS parameters for example | | |-----------|----------------------------|--| |-----------|----------------------------|--|

Technology or operation	Alternative	Deployment	Comments
911/PSAP information availability		Included in project
Police operations		Included in project
CCTV	a	3 cameras	RTV=0.89 (example in Appendix B and Fig. 4.28)
	b	2 cameras	RTV=0.62 (example in Appendix B and Fig. 4.28)
Motorist service patrols		Not included
Electronic traffic detection	c	5 detector stations	Average spacing=1.7/5=0.34 miles/ detector
			B1=0.9 (see Sect. 4.5.1.3)
	d	None	No detectors
			B1=0 (see Sect. 4.5.1.3)
TMC operational support		TMC assists in incident management	P10=1.0 K5=0.1 (see Table 4.13)
		TMC staffed around the clock	P21=1.0

Fig. C.1 Reduction in vehicle hours of delay per year for design alternatives

INCIDENT		MANAGEMENT EFFECTIVENESS POTENTIAL

		Must enter data to obtain results following data entry
		May be optionally entered or changed by user

Alterfnative:					0 CCTV cameras in section, 0 detector stations in
	section, no service patrols
RTV =	0.89
K40 =	1
K41 =	1
B1 =	0.9

		V1g	V2g	V3g	V4g	V5g
Functions (g)
1		0.6	0.3	0.9	0.5	0.4
2		0.3	0.6	0.9	0.5	0.2
3		0	0.9	0.8	0.5	0.2
4		0	0.1	0.5	0.2	0.8

		Cumulative Probability for Each Function (Hg)
Functions Symbol
1	H1 =	0.982
2	H2 =	0.977
3	H3 =	0.988
4	H4 =	0.888
		Fraction of benefits obtained by assistance in clearing incident
Y =	0.8
		Incident Management Effectiveness Potential
H =	0.929

IR	9.01
P10	1
P21	1
TSI	271.8
MVMPY	46.54
ACCR	2.1
K5	0.1

		Vehicle hours and accidents reduced
	Vehicle hours of delay reduced			105902 per year
Accidents reduced				9.1 per year

Fig. C.2 Inc mgt effectiveness potential example

Appendix D Message Display Software for Southern State Parkway

This appendix describes the DMS semi-automatic control software employed in the freeway management system for the Southern State Parkway on Long Island in New York State [1].

The software performs the following functions:

• Provides DMS messages that display congestion conditions measured by system point detectors. Messages for several levels of congestion may be displayed.
• When congestion conditions are present on different sections of the roadway, the software prioritizes the messages to be displayed by location and severity condition. The priority scheme enables the limited messaging capability of the DMS to provide the most relevant information to the largest number of motorists.
• Provides the capability for the operator to alter the message.

Relationships Involving Geometry. Travel Time and Delay

The message generation technique is based on travel time and delay between certain key locations. Travel time is obtained from estimated speed from detector stations on the mainline of the freeway. A set of definitions and geometrical relationships to support the computation was defined and is discussed below.

As shown in Fig. D.1, a link represents a section of the mainline between vehicle access or egress points. The concept of a domain, discussed in Sect. 9.2.3.1 and illustrated in Fig. 9.6 is employed to relate data from freeway surveillance stations to mainline links. Domains relate links and DMS to the roadway locations receiving speed information from a particular detector station. Speed information from detector stations is filtered to remove short term fluctuations. In some cases the detector station may not physically be in the domain. As shown in the figure, each domain is assigned to a particular detector station.

Figure D.2 introduces the geometry and definitions used by the technique. In urban areas, DMS are often deployed at spatial intervals that encompass more than

Fig. D.1 Link, domain and detector station relationships [1]

Fig. D.2 Definitions for dynamic message sign software [1]

one exit ramp. Thus, a "near zone" is defined in Fig. D.2 as the distance from the DMS to the exit ramp just downstream of the subsequent DMS. This distance is serviced by one or more exit ramps Eq(e). The "far zone", which is user defined, may encompass a number of subsequent DMS. A near zone and far zone is established for each DMS. As described later, the software develops different messages for the two zones.

Figure D.2 defines another data type, the "element" which is the distance between exit ramps. Each element includes one or more of the domains shown in Fig. D.1. Travel time for each domain is the quotient of domain length (Rq(e)) and the speed provided by the detector station associated with each domain. Element travel time is the sum of the domain travel times within the element.

The system operator must establish a nominal travel time for each element. Element delay, the difference between element travel time and nominal travel time is the basic component used for building the message.

Message Development

The following describes the message development capability of the software. The software provides two levels of congestion messages (delay and long delay) and a default message. For each element, the operator defines a delay threshold value that may trigger the message. Similarly, a long delay threshold value is also defined. A tentative delay indication or tentative long delay indication is declared for the element where prescribed thresholds are exceeded. The message is confirmed by the software if the declaration is valid for several computation intervals.

If the last element in the near zone (element m+1 in Fig. D.2) exceeds the delay criterion for that zone, it is possible that the next downstream element is also congested. In this case the software modifies the near zone boundary downstream to encompass those adjacent elements that experience delays.

Candidate Message Set Identification and Message Selection

Each candidate message is characterized by two factors:

• Intensity of delay (delay or long delay message classes).
• Freeway exits for which the delay condition applies.

When the appropriate delay or long delay thresholds are exceeded, a set of candidate congestion messages is developed for each zone. Each candidate message identifies a contiguous group of elements experiencing congestion.

Because the DMS are limited in their message display capability, more candidate messages may be developed than can actually be displayed. Table D.1 identifies the

Table D.1 Message priority classes

	Near zone	Far zone
Long delay message set	a	c
Delay message set	b	d

priority classes for each DMS. The system operator may select the priorities. A commonly used priority order is a, b, c, d.

Within each priority class the messages are ordered geographically, the first message being closest to the motorist. DMS on the freeway mainline commonly display three or four lines of information. The software provides messages according to the priority selected within the DMS display constraints.

Reference

Southern State Parkway ITS Early Implementation Project, Nassau County and Suffolk County (1997) New York State Department of Transportation

Appendix E Washington State Fuzzy Logic Ramp Metering Algorithm

Fuzzy logic has the ability to address multiple objectives (by weighing the rules that implement these objectives) and to implement the tuning process in a more userfriendly fashion (by the use of linguistic variables rather than numerical variables). This algorithm employs fuzzy logic to provide ramp metering rates.

There are six inputs to the fuzzy logic controller (FLC). These include:

• Speed and occupancy from the mainline detector station located just upstream of the on-ramp merge
• Occupancy and speed from a downstream detector station. The station selected exhibits the maximum occupancy of selected downstream stations that have historically exhibited high flow breakdown rates
• Occupancy from a ramp queue detector typically located halfway between the ramp metering stop bar and the end of ramp storage
• Occupancy from the advanced queue occupancy detector at the upstream end of the ramp storage location

"Fuzzification" translates each numerical input into a set of fuzzy classes. For local occupancy and local speed, the fuzzy classes used are very small (VS), small (S), medium (M), big (B), and very big (VB). The degree of activation indicates how true that class is on a scale of 0 to 1. For example, if the local occupancy is 20 %, the medium class would be true to a degree of 0.3, and the big class would be true to a degree of 0.8, while the remaining classes would be zero (Fig. E.1). The downstream occupancy only uses the very big class, which begins activating at 11 %, and reaches full activation at 25 % (Fig. E.2). The downstream speed uses the very small class, which begins activating at 64.4 km/h and reaches full activation at 88.5 km/h. The queue occupancy and advance queue occupancy use the very big class. For ramps with proper placement of ramp detectors, the parameter defaults are for activation to begin at 12 %, and reach full activation at 30 %. The dynamic range, distribution and shape of these fuzzy classes can be tuned for each input at each location.

Fig. E.1 Fuzzy classes for local occupancy, redrawn. Presented at the 79th annual meeting of the Transportation Research Board, January 11, 2000, Washington, DC. Reproduced with permission of the Transportation Research Board

Fig. E.2 Fuzzy class for downstream occupancy [1], redrawn. Presented at the 79th annual meeting of the Transportation Research Board, January 11, 2000, Washington, DC. Reproduced with permission of the Transportation Research Board

Rule	Default rule weight	Rule premise	Rule outcome
6	3.0	If local speed is VS AND local occupancy is VB	Metering rate is VS
10	4.0	If downstream speed is VS AND downstream occupancy is VB	Metering rate is VS
12	4.0	If advance queue occupancy is VB	Metering rate is VB

Table E.1 Examples of fuzzy logic rules in the Washington state algorithm [1]

The last step, called defuzzification, generates a single valued numerical metering rate based on the rule outcomes and the degree of activation.

After the fuzzy states have been developed, weighted rules are then applied to develop the metering rate. Examples of weighted rules are shown in Table E.1.

References

1. Taylor C et al (2000) Results of the on-line implementation and testing of a fuzzy logic ramp metering algorithm. In: 79th annual meeting of the Transportation Research Board, Washington, DC
2. Neudorff LG et al (2003) Freeway management and operations handbook. Report FHWA-0P-04-003. Federal Highway Administration, Washington, DC
3. Klein LA (2001) Sensor technologies and data requirements fror ITS. Artech, Boston, MA

Appendix F

Benefits Model for Motorist Assistance Patrols

A possible model for delay reduction for motorist assistance patrols is provided by the following expression:

TS = × K K 12 17× × K K 35 40 × × MTSSV LS

TS=Motorist time saved

K12=Annual service patrol stops per directional mile. The default value of 119 is based on INFORM ITS data and is based on an annual service patrol period of 2,600 h

K17=Fraction of stops for which assistance is provided. The default value of 0.46 is based on INFORM ITS data

K35=Correction factor. Possible default values are:

K35=1.0 where peak hour level of service is D or worse

K35=0.7 where peak hour level of service is C

K35=0.0 where peak hour level of service is B or better

K40=Number of annual hours for which service is provided/2600

MTSSV=Average delay reduced per assisted vehicle. A representative default value is 95 h [1]. It is based on a freeway with level of service D or worse

Reference

Wohlschlaeger SD, Balke KN (1992) Incident response and clearance in the State of Texas: case studies of four motorist assistance patrols. Report No. FHWA/TX-92/1232-15, Texas Transportation Institute, College Station, TX

Appendix G National Incident Management System and Incident Classification

This appendix describes the basics of the National Incident Management System and a commonly used incident classification system. The appendix contains material from the document Emergency Traffic Control and Scene Management Guidelines, Version 2.0 Wisconsin Department of Transportation, Feb. 12, 2012.

National Incident Management System and Incident Command System

• Be applicable across a full spectrum of potential incidents and hazard scenarios, regardless of size or complexity.
• Improve coordination and cooperation between public and private entities in a variety of domestic incident management activities. One of the key features of NIMS is the Incident Command System (ICS). ICS is a standardized, on-scene, all-hazards incident management concept that allows its users to adopt an integrated organizational structure to match the complexities and demands of single or multiple incidents without being hindered by jurisdictional boundaries. ICS consists of procedures for controlling personnel, facilities, equipment and communications. It is also a system designed to be used or applied from the time an incident occurs until the requirement for management and operations no longer exists. ICS should be established and used for every incident.

ICS has an Incident Commander who has complete responsibility for incident management. The Incident Commander must account for all personnel working at the scene. This includes those that arrived on the scene initially (law enforcement, fire, emergency medical services, etc.) as well as those who arrive later to assist with the scene (highway department personnel, insurance investigators, engineers, etc.).

When incidents require a multi-jurisdictional or multi-agency response, the guidelines of Unified Command should be followed. Unified Command allows agencies with different legal, geographic, and functional authorities and responsibilities to work together effectively without affecting individual agency authority, responsibility or accountability. Unified Command enables all responsible agencies to manage an incident together by establishing a common set of incident objectives and strategies. Use of Unified Command helps minimize duplication of efforts and confusion on the scene.

It is recommended that when command is established or transferred from one person to another, this information, as well as the location of the command post, be communicated for all responders to hear. In many instances, and for a variety of reasons, there are challenges with on-scene responder communication. In such cases, it is necessary that the Incident Commander ensure that all parties have been made aware of any pertinent information.

Additionally, ambiguous codes and acronyms have proven to be a major obstacle in communications at incidents that involve multiple agencies. As such, ICS requires that all responders use plain English, or clear text, when responding to an incident, which means that radio codes, agency-specific codes or jargon should not be used.

Incident Response Priorities

Incident objectives should be established based on the following incident response priorities:

• Priority 1: Life safety
• Priority 2: Incident stabilization
• Priority 3: Preservation of property and the environment

Incident Classification

All traffic incidents will be classified based on the expected incident duration as outlined in Chapter 6I of the MUTCD. The three incident classes to be used are as follows:

• Major—expected duration of more than 2 h
- Major traffic incidents typically involve closing all or part of a roadway facility for a period exceeding 2 h. During major incidents, motorists are usually diverted through lane shifts or directed around the incident using an emergency alternate route.

– Examples include:

Fatal crashes or incidents that require a crash investigation Incidents involving a hazardous materials spill Overturned truck or tractor-trailer Structural damage Wildfires near the roadway

• Intermediate—expected duration of 30 min to 2 h

Intermediate traffic incidents usually require traffic control on the scene to divert motorists past the blockage. Full roadway closures might be needed for short periods during incident clearance to allow responders to accomplish their tasks.
Examples include:

Rollover or multi-vehicle crashes Crashes involving personal injury Truck or tractor-trailer crashes

• Minor—expected duration under 30 min

For minor traffic incidents, it is not generally possible or practical to set up a lane closure with traffic control devices.
Examples include:

Disabled vehicles Minor crashes (e.g., property damage only) Roadway debris

Appendix H Special Corridor Traffic Decision Support and Demand Management System Concept

This appendix provides further detail for the detailed motorist information that assists the system operator to provide displays of traffic conditions for the special corridor described in Sect. 11.3.2.

Concept

Section 11.3.2 describes a special corridor (Fig. 11.5) in Philadelphia that is managed by the Pennsylvania Department of Transportation. When congestion occurs resulting from incidents or construction in the special corridor, the decision support system advises the TMC operators to take additional remedial actions including the provision of additional detailed motorist messages. These messages apply to the major alternate routes in the corridor (I-95 and Aramingo Ave.). In addition, recommendations are provided to implement appropriate signal timing plans to help accommodate traffic volume increases on the arterials to which traffic is diverted. The principal alternates include I-95 and Aramingo Ave. Other alternates include portions of Delaware Avenue, Richmond Street and Tacony Street (see Fig. 11.6).

I-95 contains existing point detectors and travel time tag readers and Aramingo Ave. has Bluetooth probe detectors. Some Bluetooth detectors are present on the other arterials. These detectors, together with sufficient traffic volumes enable detection of abnormal traffic conditions on I-95 and on Aramingo Ave. to provide displays and to identify the need for dynamic message sign (DMS) and arterial dynamic message sign (ADMS) messages. The traffic information is also used to identify the type of message to be provided. CCTV is also used to detect abnormal traffic conditions.

The operator display and messaging support concepts notify the operator of "abnormal" traffic conditions. The management concept does not seek the fastest route, but is based on the premise that on a "normal" day the traffic balances itself optimally, although recurrent congestion may be present. This premise is in accord with Wardrop's principles (Sect. 3.1.5). To determine what is "abnormal", the concept of travel time reliability (Appendix A) is used. Thus the operators' displays and suggested DMS and ADMS messages are targeted towards conditions that are not within the range of expected normality and that originate from conditions inside the special corridor.

Travel time reliability is a measure of how much current travel time deviates from historic, non-incident travel times for that time of day. This variation is measured in terms of a standard deviation that is compiled from historic data. Recommended operator displays and DMS and ADMS messaging recommendations are provided for the major routes (I-95 and Aramingo Ave.). I-95 has point detectors and Aramingo Ave. often has sufficient traffic volume to support enable its Bluetooth detectors to provide timely information. Algorithmic guidance for the remaining alternate routes (Richmond Street, Delaware Avenue) is not provided by this software.

Traffic Condition Development

Traffic conditions on I-95 are best identified by existing point detectors. Rapid detection is feasible during daytime periods. Analysis shows that the Bluetooth data on Aramingo Avenue is likely to provide appropriate response times for many traffic conditions. The Bluetooth data on the other arterials in the special corridor (Delaware Ave., Tacony St., Richmond St.) is slower to respond and must be considered as supplemental. No display or messaging assistance is provided for those arterials by the software.

The management approach, based on travel time reliability compares measured travel times with archived historic travel times. A historic statistic, the standard deviation (SD) is developed for each time period. If the measured travel time is outside of some upper boundary, the travel time is not "normal". The operator display indicates this abnormal travel time (ATT) condition, and a message is advised. An example of such a boundary is where 85 % of the trips do not exceed the historic travel time.

On the section of I-95 in the corridor,

If $$ATT > TAA + K1*SD$$ then the $I=95$ section is abnormal $(AB)$ (20.1)

where

ATT=measured travel time TTA=average historic travel time K1=a parameter that establishes the threshold SD=standard deviation of historic travel time

For example for an 85 % threshold, K1=1.04. If the situation is worse (e.g. where K is significantly greater than K1), the situation might be classified as "unusually long delay". An equation for this situation, called "unusually long delay" (ULD), is

If $$ATT > TTA + K2 \times SD$$ then $I - 95$ section is $ULD$ (20.2)

where

K2 is a larger multiplier (e.g. 1.8)

Similar considerations apply to the Aramingo Ave. section in the corridor.

Diversions between the I-95 and Aramingo Ave. routes require the use of connector arterials (Bridge St., Allegheny Ave., Castor Ave.) that may not have sufficient traffic volume to provide reliable and timely Bluetooth detection. The operation requires that these links be monitored by CCTV to identify incidents or unusual congestion that might affect the messages to be provided.

Operator Displays

A graphical display shows congestion levels on I-95 and parallel arterials using level of service (LOS) conditions.

LOS on I-95 is developed by using either speed and volume (to compute density) or occupancy from point detectors. LOS definitions are provided in Exhibit 10-7 of HCM 2010 [2]. The display shows the current congestion level using LOS as follows in Table H.1.

The display shows conditions for each segment as well as for the entire route in the corridor. Historic conditions are shown by a dashed line, current conditions by a solid line. When abnormal conditions are experienced, the solid line flashes. When long unusual travel time conditions are experienced, the solid line flashes quickly.

Similarly, the screen displays the Aramingo Ave. segments represented by the Bluetooth pairs and the entire route. Arterial LOS criteria are provided by HCM 2010 Exhibit 16-4 [2].

The screen displays will assist operators to identify the relative traffic conditions on both routes and to request the appropriate signal timing plan.

Congestion level	LOS (consistent with Pa 511 site)	Display color
Free flowing	LOS A, B, C	Green
Moderate	LOS D	Yellow
Heavy traffic	LOS E	Red
Stop and go	LOS F	Black

Table H.1 Congestion level conditions and corresponding operator display colors

DMS/ADMS Messaging Recommendations

The DMS and ADMS messages describe exception conditions on I-95 and on Aramingo Ave. They cover the entire section of the roadways between Allegheny Ave. and Bridge St. Thus the surveillance data, standard deviation and computations for AB and ULD apply to the entire section. The messages are described below by message content The recommended messaging is confined to these two routes. Since the Richmond St. alternate may not have sufficient volume to support rapid condition identification. In addition, its capacity limitations will likely limit the capability to support significant diversion. Diversions to this route will be entirely operator controlled.

Message Development

The conditions to be displayed that are unique to this algorithm are long delays (LD) and unusually long delays (ULD). Long delays are represented by abnormal (AB) conditions. The DMS have sufficient display capability to indicate abnormal congestion on both routes (using a message for each route on a single display page). Space limitations on the ADMS limit the message display to congestion on one route. ADMS can also display congestion on both routes when the types of congestion on both routes are the same. The software provides the capability to implement the following message types.

• Message Type 0—Conventional RTMC message (e.g. travel time)
• Message Type 1—Unusual delay on interstate
• Message Type 2—Unusually long delay on arterial
• Message Type 3—Long delay on interstate
• Message Type 4—Long delay on arterial
• Message Type 5—Unusually long delay on both routes
• Message Type 6—Long delay on both routes

Table H.2 below provides on possible set of message formulations that may be employed.

Messages are targeted to motorists familiar with the corridor.

Interstate (I-95) DMS message		Arterial (Aramingo Ave.) ADMS message
Interstate condition	Arterial condition	Message type	Arterial condition	Interstate condition	Message type
UD	UD	1 and 2	UD	UD	5
UD	LD	1 and 4	UD	LD	2
UD	ND	1 and 0	UD	ND	2
LD	UD	3 and 2	LD	UD	1
LD	LD	3 and 4	LD	LD	6
LD	ND	3	LD	ND	4
ND	UD	0	ND	UD	1
ND	LD	0	ND	LD	3
ND	ND	0	ND	ND	0

Table H.2 Possible DMS/ADMS message formulations

References

1. I-95 Corridor Intelligent Transportation System, Systems Engineering Report, Version 4.0, STV, Incorporated, Aug 2014
2. HCM 2010 highway capacity manual (2010) Transportation Research Board, Washington, DC

A	C
AADT , 52, 53, 112, 113, 241	California Department of Transportation
Accident, accident statistics , 18	(CALTRANS) , 2, 73, 146–147,
Active traffi c and demand management	174, 223
(ATDM) , 184, 193, 214	Capacity
ALINEA , 143–144, 146	capacity reducing incidents , 91
Alternate route(s) , 4, 19, 22–25, 27, 56, 58,	freeway capacity , 21, 54, 125, 128–136
59, 62, 64–66, 80, 82, 83, 91, 94–96,	residual capacity , 51, 59, 96
101, 102, 108, 123, 125, 126, 135, 136,	roadway capacity , 41, 44, 54, 104, 130,
138, 152, 214, 260	145, 203
Alternatives analysis, alternatives evaluation ,	Carbon dioxide , 29
180–181	Carbon monoxide , 29
Archived data user service (ADUS) , 183	CCTV , 2, 3, 5, 48, 70–75, 84, 86, 87, 89,
Area level diversion , 61, 65–68	100–102, 116, 152, 157, 158, 167,
Arterial traffi c , 105–107	170, 214, 215, 222, 237–242,
Assessment , 3, 19, 27–33, 177	259, 261
Attribute , 32, 33, 181	Cellular telephone , 69, 78, 92, 93
Automatic incident-detection (AID)	Center-to-center , 82, 170, 172
algorithms , 76	Changeable message signs (CMS) , 4, 5, 26, 27, 80, 158, 246
	Classifi cation of incidents , 55, 56, 79, 86, 87,
B	255–257
Bayesian inference , 87	Closed loop control
Benefi ts	closed loop manual control , 101
and cost analysis , 6, 29, 177–180	closed loop semi-automatic control ,
model , 125, 153–154, 253	101–103
economic benefi t , 28–29, 181	Code of Federal Regulations (CFR)
Benefi t to cost ratio , 29	23CFR940 , 7–8
Binomial logit model , 99	Part 940 of Title 23 , 7, 27, 34
Blank out signs , 80, 108	Cohort(s) , 51–55, 180, 221
Bluetooth , 78, 101, 211, 214, 259–261	Commercial radio , 92, 93, 120
Bottleneck , 21, 76, 126, 130, 132, 133, 138,	Commercial vehicle delay , 29
145, 198	Commercial vehicle inventory delay , 29
capacity , 20, 125, 138	Commercial vehicles , 16, 29, 37, 161, 185,
Buffer time , 197, 234	188, 226, 229

Communication(s)	Diversion
channel(s) , 173	explicit diversion , 26, 94, 95, 97
links , 83	fraction probability(ies) , 98–100
standards , 165	messages , 26, 92–98, 102
COMPASS , 103	policy(ies) , 95–97, 106
Computer aided dispatch (CAD) , 167	route , 14, 25, 56, 59, 60, 62, 63, 65–68, 92,
Concept of Operations (CONOPS) , 8, 9, 13,	94, 95, 106–108
81, 152, 157, 211, 214	strategy(ies) , 43, 65, 98, 100–103, 207
Congestion	volume , 96, 97, 106–108
non-recurrent congestion , 4, 5, 14, 16,	Dudek, C.L. , 26, 92, 94, 108
21–27, 41–89, 91–116, 119, 120, 122,	Dynamic merge control , 201–202
158, 161, 195	Dynamic message sign (DMS) , 11, 25, 26, 38,
recurrent congestion , 5, 14, 21, 26–27, 45,	43, 62, 63, 65, 92, 93, 96, 103, 108,
119–123, 138, 158, 196, 259	109, 119, 123, 161, 165, 167, 170, 172,
Constraint(s) , 2, 10, 19, 33–35, 102, 107, 108,	195, 197–199, 201, 214, 215, 222, 231,
138, 248	246–248, 259, 260
Construction , 11, 13–15, 56, 62, 77, 83, 84,	locations , 108–113
91, 95, 108, 109, 120, 158, 163, 168,	message , 98–100, 143, 211, 219, 245, 262
208, 214, 215, 259	Dynamic traffi c assignment, dynamic traffi c
Contra-fl ow lanes , 115	routing , 97
Corridor, corridor delay reduction , 108, 153
Cost benefi t analysis , 19, 29, 177–180
Costs, motorists' cost , 27	E
	E 511 , 92, 93, 120, 165
	Effective capacity improvement , 132–133
D	Emergency evacuation(s), evacuation plan ,
Data archiving, (data) mining , 158–159, 183	114–116
Data structures , 183–187	Emergency management services
Delay , 1, 3, 21, 22, 24–29, 31, 32, 35, 41,	emergency service providers , 1, 55, 60–61,
43–45, 49–55, 60, 66, 67, 71, 75, 85,	83, 84, 157
88, 91, 95, 97, 99, 100, 102–108, 113,	emergency services , 71, 83, 163
120, 122, 123, 125, 126, 132–136, 138,	Emergency vehicle(s) , 3, 14, 83, 84
144, 150, 152, 153, 160, 180, 181,	Emergency vehicle turnarounds , 84
186–189, 193, 199, 215, 221, 222,	Emissions, vehicle emissions , 88
225–235, 241, 242	Energy , 11
Demand-supply analysis , 138	Environment(al) , 8, 10, 11, 14, 22, 29, 30, 35,
Demand volume , 43–45, 54, 71, 103, 125, 126	66, 108, 169, 181, 207
Density , 3, 19–21, 73, 75, 102, 128, 130,	Equity , 30, 152, 185, 190
139–141, 144–146, 261	Evacuation route(s) , 115, 196
Design constraints , 34–35	Evaluation
Design ITS , 2–4, 8, 19–38, 41–43, 86, 88,	prospective evaluation , 17, 27, 28, 30, 177
204, 237	retrospective evaluation , 17, 27, 30,
Detector(s)	181, 189
acoustic detectors , 162
detector spacing , 74–76, 87
inductive loop detectors , 73–74, 141, 162,	F
183, 199	False alarm , 77
point (traffi c) detector(s) , 3, 20, 24, 41,	Federal aid , 3, 7–8, 27, 34, 180

69–78, 84, 101–103, 139, 158, 162,	Federal Highway Administration (FHWA) ,
184, 185, 187, 196, 201, 203, 214, 225,	2, 13, 55, 85, 92, 119
227–230, 259–261	Feedback , 17, 103, 104, 113, 115, 181,
probe traffi c detection , 20	183, 190
radar detectors , 74	Filter(ing) , 69, 142–144, 245
video processing detectors , 74	Filter coeffi cient , 142, 143

Fire department , 83 Flow breakdown , 125, 130–133, 139, 140, 144, 145, 249 characteristics , 44, 128–136, 209 rate , 20, 21 smoothing , 125, 133, 137 Free fl ow speed , 20, 104 Freeway-to-freeway ramp metering , 150–151 Fuel consumption , 14, 27, 29, 88, 89, 153, 181, 185, 189 Functional placement, DMS functional placement , 108–113 Fuzzy logic , 146, 249–251	management , 2, 3, 41, 55–56, 58, 59, 66, 68, 69, 75, 78, 81, 157, 158, 162, 166, 168, 169, 184, 189, 199, 202, 207–209, 214, 241–243 management effectiveness , 41, 75, 84–89, 222, 243 model , 47–49, 51 recovery , 69, 78–84 response , 68–84, 86, 168, 184, 188, 256 stages of an incident , 41, 69 Intensity of deployment, deployment intensity , 35, 38 Interchangeability , 2 Interoperability , 15, 35, 37
G g factor , 73 Geographic levels , 56, 59–68 Gini coeffi cient , 31, 152, 188, 190 Goals , 3, 8–17, 34, 195, 207 GPS , 77, 92, 93, 102, 120, 186 Green signal split , 97, 107	J Jam density , 130, 141 K Kalman fi lter(s) , 143
H Hazardous materials , 85, 114, 257 High accident rate locations , 72 Highway advisory radio (HAR) , 65, 80, 92, 93, 98, 120, 158, 165, 166, 168, 209 I IEEE 1512 standards , 83, 165 Implicit diversion , 95	L Lane closures , 49, 74, 83, 91, 257 Lane control signals , 1, 79, 195, 199, 201, 202, 204 Level of service (LOS) , 21, 28, 35, 38, 71, 72, 87, 119, 145, 152, 195, 198, 199, 201, 253, 261 Life cycle costs , 178 Linear programming , 138 Local diversion , 60–65 Lorenz Curve , 30–31
Incident clearance , 32, 33, 44, 49, 55, 56, 59, 78, 85, 104, 105, 209, 257 clearance time , 3, 16, 42, 49–50, 55, 86, 88, 182, 183 command system , 70, 80, 255–256 delay , 45, 51, 53, 71, 120 detection , 3, 68–78, 103, 215 detection time , 3, 42, 75, 77 dissemination model , 115, 116 duration , 45, 46, 50, 54, 55, 256 frequency , 46–47 incident-detection algorithm(s) , 46, 54, 55, 256 incident-response plans , 69, 78–80, 209 information , 4, 69, 79, 81, 91–116, 166, 168 Interagency communication , 80–83 ITS standards , 83 lane blocking incident , 45, 52–55	M Management concepts , 3, 19, 35–38, 43, 214, 255, 259 Marginal analysis , 19, 30 Marginal values , 30 Merge detector(s) , 127 Message content , 22, 24, 100, 120, 262 Message set(s) , 247–248 Message strength , 19, 22, 24, 25, 62, 63, 94, 96, 98–100 Metaline , 146 Metropolitan planning organizations (MPOs) , 31, 55, 180 Mobility , 14, 15, 25, 29, 30, 181, 207, 208, 211 Mode , 1, 5, 10, 21, 25, 56, 91, 92, 158, 165, 193

Models , 3–5, 8, 9, 11, 16, 17, 22, 41, 43–49,
51–53, 75, 86–89, 91, 92, 97–100, 104,
108–113, 115, 116, 125, 130, 132, 144,
153–154, 160, 180, 189, 213, 221, 222,
235, 238, 253
Motorist information
information to motorists , 2, 4, 5, 25–27,
30, 32, 33, 43, 66, 68, 69, 79, 84,
91–93, 100, 113–115, 119–120, 158,
162, 204, 207, 215, 259
motorist messaging , 92–95
Motorist satisfaction, traveler satisfaction , 32
Motorist service patrols , 30, 32, 69, 78, 86,
190, 242
Multi-attribute utility analysis , 19, 31, 181
N
National ambient air quality standard , 30
National Incident Management System
(NIMS) , 41, 80, 255–257
National ITS Architecture , 2, 7, 11, 35, 172, 183
National Transportation Communications for
ITS Protocol (NTCIP) , 83, 165, 166
New York State Department of Transportation
(NYSDOT) , 11, 46, 161, 173
New York State Department of Transportation
Project Development Manual , 11
Node , 110–112, 185, 246
Non-diverting vehicle(s) , 106–107
Non-recurrent congestion , 4, 5, 16, 19,
21–25, 27, 41–89, 91–116, 119,
120, 122, 161, 195

Percentage of objective satisfi ed , 30
Performance Measurement System (PeMS) , 174
Performance measures , 3, 14, 19, 28–33, 85
Point detector , 20, 73–79, 84, 184, 185, 187,
196, 203, 214, 227–230, 259–261
Point detector data , 76, 184
Police , 42, 62, 64, 70, 71, 74, 75, 78, 81, 82, 86,
157, 158, 160, 168, 189, 210, 214, 242
Police patrols , 78
Policy , 26, 91, 92, 94, 96, 97, 101, 107, 153, 158
Presentation factor , 99
Probability of incident detection , 77
Probability theory , 87
Probe detector , 73, 120, 184, 214, 231, 259
Probe detector data , 184
Productivity , 12, 30
Project-level ITS architecture , 8
Propensity to divert , 96
Prospective evaluation(s) , 18, 27, 28, 30, 177
Public acceptance , 152–153
Public satisfaction , 29, 181
Public service access points (PSAPs) ,
69, 86, 242
Q
Quality of motorist information , 92, 114
Queue , 1, 5, 20, 42, 44, 65–67, 69, 70, 75,
76, 84, 86–88, 103–107, 110, 125–127,
130–138, 145, 147–153, 157, 158, 195,
222, 223, 249
detector(s) , 127, 128, 147, 149, 150, 249
discharge , 20–21, 130, 132, 133
warning , 84, 195, 199–201

O
Oak Ridge Evaluation Modeling System
(OREMS) , 115
Objectives , 2–4, 8, 10–17, 25, 29, 30, 33,
35–38, 56, 108, 138, 143, 145, 178, 179,
181, 189, 193, 204, 207, 215, 249, 256
Open loop control , 100
Operating procedure , 26, 100
Origin-destination , 27, 110–112
Oxides of nitrogen (NOX) , 15, 29

R
Ramp meter(s) , 2, 5, 31, 70, 74, 125–128, 136,
144–147, 150–154, 158–159, 163, 223
Ramp metering
isolated (ramp) metering , 5, 125
local (ramp) metering , 136–138, 143–145
metering rate(s) , 125–127, 129, 136, 138,
139, 141–147, 149, 150, 152, 158, 251
metering strategies , 125–151, 153
non-restrictive (ramp) metering , 5, 32, 33,

P Passenger vehicle delay , 20, 28, 29, 130 Peak hour , 21, 30, 35, 38, 45, 72, 188, 232, 235, 241, 253 Peak period , 16, 30, 50, 95, 120, 122, 123, 129, 132–135, 140, 195, 196, 198, 201 Peeta, S. , 99, 100

non-restrictive (ramp) metering , 5, 32, 33, 133, 136, 138, 147, 154 platoon metering , 127, 129, 145 pretimed (metering) , 5, 126, 136–139, 209 ramp metering benefi ts model , 153–154 (ramp) metering plans , 159 ramp meter installation , 127–128, 163 restrictive (ramp) metering , 5, 27, 32, 33, 125, 127, 133–145, 151, 152

system-wide ramp metering , 2, 5, 25, 133,	Standards, ITS standards , 7, 8, 82, 173
137, 138, 145	Stated preference survey(s) , 100, 114
traffi c-responsive (metering) , 5, 126, 137,	Static sign(ing) , 64, 116, 210
139–145, 149, 159, 209	Strategic network management , 97–100
Ramp storage , 125, 147, 223, 249	Strategy , 5, 10, 22, 31, 96, 97, 99–103, 127,
Recurrent congestion , 5, 15, 21, 26–27, 45,	136, 138, 143, 146, 153, 194, 195, 199,
119–123, 138, 158, 196, 260	208–209, 213, 214
Regional ITS Architecture , 6–8, 12, 157, 163,	Stratifi ed zone metering , 146
165, 180	Systems engineering , 2, 7–12, 33,
Regional level diversion , 61, 67–68	34, 157
Requirements , 7–8, 10, 12–17, 34, 35, 41, 48,	International Council on Systems
62, 66, 68–84, 86, 87, 108, 127, 136,	Engineering (INCOSE) , 8
143, 145, 147, 150, 160, 164, 165, 169,	System Wide Adaptive Ramp Metering
181, 193, 202, 208, 215, 223, 225, 255	Algorithm (SWARM) , 144–146
Restricted road use , 30
Retrospective evaluation(s) , 18, 27, 30, 181, 189
RITA ITS , 17, 178	T
Road pricing , 30	Tail of queue , 69, 70, 84, 86, 87, 210
Roadway weather information systems	Tandem metering , 129
(RWIS) , 160	Television traffi c , 92
Route guidance , 26, 95	Temporal data structures , 187
	Temporary shoulder use , 196–199
	Throughput , 2, 25, 27, 30, 126, 127, 133, 153,
S	160, 185, 188, 231–235
Safety , 6, 12, 14, 28, 29, 56, 85, 133, 137, 145,	Time saved , 22, 54–55, 106
153, 158, 181, 185, 187–189, 193,	Toll tag readers , 77, 101, 186
207–209, 210, 256	Toll tags , 77
Satellite radio , 92, 93	Traffi c assignment , 22, 97, 108
Saturated fl ow, oversaturated fl ow , 21	Traffi c calming , 84
Scoping , 3, 12–14, 27	Traffi c levels , 35, 38, 94
Secondary accidents , 1, 42–43, 56, 88, 133,	Traffi c management center , 5, 6, 26, 41, 47,
160, 189	68, 69, 71, 74, 78, 79, 114–116, 136,
Service patrol , 5, 30, 74, 78, 87, 159–160,	143, 157, 161
183, 190, 253	Traffi c signal(s), signal timing , 5, 62, 67, 79,
Service rate , 125	83, 101, 106, 115, 125, 147, 152, 160,
Set-point , 144, 146	163, 165, 167, 169, 196, 209, 211, 219,
Shock wave(s), shock wave boundaries , 21, 75	259, 261
Shoulder accidents , 43, 53, 54	Traffi c signal preemption , 83
Shoulder periods , 122, 123	Trailblazers , 64, 65
Simulation , 18, 29, 33, 100, 115, 136, 138,	Transmit , 77
152, 159, 181, 235	Transportation management center (TMC) ,
Smoothing , 20, 56, 76, 125, 133, 137, 138, 142	2, 3, 5, 6, 16, 26, 38, 43, 56, 58, 67, 69,
Spatial data structures , 185–186	70, 78, 81, 86, 97, 98, 100, 101, 137,
Special events , 15, 37, 81, 82, 91, 95, 119,	157–174, 183, 184, 188, 189, 199, 215,
158, 160, 161, 165, 168, 207, 209, 214	241, 242, 259
Speed	traffi c management center , 5, 6, 26, 41, 47,
average speed , 20, 28, 122, 127, 195	68, 69, 71, 74, 79, 114, 116, 136, 143,
harmonization , 195–196, 199, 202	157, 161
space-mean-speed , 20, 72, 73	Traveler behavior , 97, 193
time-mean-speed , 20, 73, 74	Travel time(s) , 15, 20–22, 24, 25, 27, 28, 30,
Spillback , 133, 136, 137, 150	36, 56, 59, 67, 68, 70, 73, 77, 78, 82,
Stable fl ow , 128, 130	83, 92, 95, 96, 103, 119, 120, 122, 123,
Stakeholder(s) , 1, 2, 6–12, 14, 16, 17, 31, 32, 37, 62, 79, 81, 82, 106, 152, 165–167,	133, 135, 136, 144, 151–153, 158, 163, 184, 186–188, 213, 225–235, 245–247,

259–262

181, 211

Travel time reliability , 28, 120, 122, 123, 153, 185, 187, 188, 225–235, 260 Travel time variation , 30, 120 Trip generation , 97 196, 198, 201–203, 221, 226, 227, 229, 231, 235, 259–262 Volume-to-capacity ratio , 16, 26, 35, 123, 126, 221

U Undersaturated regime , 20 Unstable fl ow , 130 User satisfaction , 29–31, 188–190 Utility , 11, 17, 22, 31–33, 35, 99, 181

V Vee diagram , 8, 12, 14, 181, 183 Verifi cation , 14, 42, 69–75 Volatile organic compounds , 29 Volume , 3, 15, 16, 19–21, 25, 26, 35, 43–46, 51–54, 56, 57, 59, 71–74, 96–98, 103, 104, 106, 108, 110–113, 125, 126, 128, 130, 132–135, 138–141, 144, 145, 147,

149, 151, 159, 180, 181, 184, 186, 187,

Waiting time , 127, 146, 147, 151, 152, 185, 188 Wardrops's Principles , 27 Wardrops's First Principle , 27 Wardrops's Second Principle , 27 Weather , 5, 15, 21, 28, 56, 60, 78, 77, 108, 109, 115, 139, 145, 158, 160, 162, 165, 195 Wireless , 74, 78, 83 Worksheet , 6, 52–55, 72, 89, 105, 106, 113, 135, 187, 221, 222, 240, 242

Z Zone(s) , 43, 75, 139, 145, 146, 155, 199, 201, 207, 247, 248

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Intelligent Transportation Systems

Intelligent Transportation Systems

Robert Gordon

Intelligent Transportation Systems

Pref ace

Contents

List of Symbols, Abbre viations, and Acronyms

Chapter 1 Introduction

1.1 Purpose of Book

1.2 Development of ITS Design Practices

1.3 Summary of Contents and Organization

References

Chapter 2 Cost Effective Design Processes

2.1 Systems Engineering

2.1.1 Systems Engineering Requirements for Federal Aid Projects

2.1.2 Systems Engineering as a Life-Cycle Process

2.1.3 ITS Project Development

2.2 Goals, Objectives and Requirements

2.3 Evaluation Methodologies

References

Chapter 3 Functional ITS Design Issues

3.1 Relationship of ITS Design to General Transportation Planning Principles

3.1.1 General Traffic Flow Relationships

3.1.1.1 Relationship of Volume, Speed and Traffic Density

3.1.1.2 Capacity

3.1.2 Shock Waves

3.1.3 Classification of Congestion

3.1.4 Diversion for Non-Recurrent Congestion

3.1.4.1 Diversion Decisions by Motorists

3.1.4.2 System-Wide Impacts of Diversion

3.1.5 Recurrent Congestion

3.2 Performance and Benefit Assessment

3.2.1 Performance Measures to Facilitate System Design

3.2.2 Performance Measures and ITS Planning

3.3 Alternatives for Functional Design

3.3.1 Design Constraints

Resource Constraints

Institutional Constraints

Legacy Constraints

3.3.2 Relationship of ITS Management Concepts to Objectives

References

Chapter 4 Non-Recurrent Congestion: Improvement of Time to Clear Incidents

4.1 Definition of an Incident for ITS Design Purposes

4.1.1 Effect of Incidents on Capacity

4.1.2 Secondary Accidents

4.1.3 Work Zone Accidents

4.2 Models of the Effects of Freeway Incidents

4.2.1 Frequency and Severity of Incidents

4.2.2 Data Collection for Development of Incident Model

4.3 Relationship of Reduction in Delay to Reduction in Incident Clearance Time

4.4 Interaction of Capacity Restrictions and Traffic Conditions

4.4.1 Cohort Model

4.4.2 Time Saved Per Incident

4.4.3 Classification of Incidents

4.4.4 Incident Management Approaches

4.4.5 Distribution of Traffic for Incident Conditions

4.4.6 Geographic Levels of Diversion

4.4.6.1 Local Diversion (Geographic Level 1)

4.4.6.2 Area Level Diversion (Geographic Level 2)

Characteristics of Area Level Diversion

Examples of Area Level Diversion Routes

Coordination of Area Level Diversion Plans

4.4.6.3 Regional Level Diversion (Geographic Level 3)

4.5 Functional Requirements for Improving Incident Response and Relationship of Improvement Techniques

4.5.1 Improving Incident Detection and Verification

4.5.1.1 Public Service Access Points

4.5.1.2 CCTV

4.5.1.3 Traffic Detectors

4.5.2 Point Detectors For Incident Detection Without Incident-Detection Algorithms

4.5.3 Point Detectors With Automatic Incident-Detection (Aid) Algorithms

4.5.3.1 Motorist Service Patrols and Police

4.5.4 Improving Incident Response, Clearance and Recovery Through ITS

4.5.4.1 Incident Response Plans

4.5.4.2 Improved Interagency Communication

4.5.4.3 Provision of Traffic Information to Responders

4.5.4.4 Definition and Management of Major Response Routes

4.5.4.5 Tail of Queue Detection

4.6 Measuring Incident Management Effectiveness

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