Analysis of the speed distribution of vehicles involved in accidents on urban roads

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Authors: Oleksandr Riabushenko, Serhii Danets, Vitalii Kashkanov
Cited by: 0

Abstract

The aim of this study is to conduct a comprehensive statistical analysis of the speed distribution of vehicles involved in road traffic accidents (RTAs) with casualties on the urban road network of the city of Kharkiv (Ukraine). The empirical basis of the research consists of official police investigation materials covering 294 recorded RTA cases. Within the scope of the study, empirical speed distributions were constructed and the main statistical characteristics were analyzed, including the mean value, mode, as well as the coefficients of skewness and kurtosis. The results indicate that the highest concentration of RTA cases occurs within the speed interval of 50–60 km/h, with an average speed of 53 km/h. It was found that in 61% of the cases the legally established urban speed limit of 50 km/h was exceeded; in 13% of the cases the speed exceeded 70 km/h, and in 4% of the cases it exceeded 100 km/h. The analysis of the empirical distribution shape revealed pronounced right-sided skewness, significant kurtosis, and a high modal frequency, which prevents an adequate approximation by the normal distribution or other closely related theoretical models. A comparative analysis of speed distributions for specific types of road traffic accidents, such as vehicle-to-vehicle collisions and pedestrian impacts, demonstrated statistical characteristics similar to those of the overall sample. The observed features of the shape and structure of the speed distributions may be attributed both to imperfections in the existing urban speed enforcement system and to the specific methodologies used to estimate vehicle speeds during accident investigations. The findings of this study have both scientific and practical significance, as they may be used to further investigate the impact of speed as a factor in road traffic safety and to provide an additional analytical tool for assessing the probability of road traffic accidents as a function of vehicle speed.

Fields of Study & Subjects

Traffic and Road Safety Transportation Systems and Logistics IoT and GPS-based Vehicle Safety Systems

Publication details

Journal / source
Journal of Mechanical Engineering and Transport
Volume
21
Issue
1
Pages
76–86
Publication date
9 February 2026
Language
EN