Fatal road accidents have become one of the risks of deaths in the world. Increasing road safety is crucial to save lives and achieve the UN Sustainable Development Goals (UN, 2015). Road traffic crashes cost most countries 3% of their gross domestic product. Therefore, to measure road safety, evaluating the indicators plays a crucial role in comparing countries and trends by considering fatality rate (number of deaths on roads) and fatal road accident rate (number of accidents with deaths).

Measuring road safety has remained challenging. The paper explores the indicators of road safety and proposes ways to measure it. The random events theory was used to assume that the distribution of fatal road accidents is almost perfectly random, and the Poisson model gives a good description of the random process. Chi-square test was used to fit the data and to predict the number of fatal road accidents. The results aim to predict road safety from sustainability perspective. Better data-based planning of road systems helps to reduce the fatalities on roads.

Keywords: road safety, UN development goals, smart cities, fatal accidents, Poisson distribution.
