Citation

Jin J, Huang H, Zhou R, Chen J, Liu P. Traffic Injury Prev. 2024; ePub(ePub): ePub.

Copyright

(Copyright © 2024, Informa - Taylor and Francis Group)

DOI

10.1080/15389588.2024.2312517

PMID

38346208

Abstract

OBJECTIVE: The dynamic characteristics of vehicles involved in crashes may be an important factor affecting the crash severity. This study investigates the relationship between the dynamic characteristics of vehicles involved in crashes in the five seconds before the occurrence and the crash severity. The findings aim to offer insights for preventing severe crashes and advancing autonomous vehicle technology.

METHODS: This study aims to investigate the impact of dynamic features, such as speed, acceleration, and relative distance of vehicles involved in the crash in the five seconds before the crash, on the crash severity. Five hundred ninety-six crash samples from the China In-depth Mobility Safety Study-Traffic Accident database were selected for crash reconstruction. A random parameters logit model was used to extract and analyze the effect of dynamic features of the vehicles involved in the crash on the crash severity.

RESULTS: The random parameters logit model demonstrated a satisfactory fit. Analysis of the parameter estimation results of the model showed that the variables of speed, acceleration, and relative distance between vehicles involved in the crash at some time points during the five seconds before the crash significantly affected the crash severity. Notably, the coefficient of variation of relative distance over 5 s emerged as the most influential positive determinant of the crash severity.

CONCLUSIONS: Certain dynamic characteristics of vehicles involved in a crash in the five seconds before a crash significantly impact the crash severity. The study's findings can serve as a reference for preventing severe crashes and advancing the development of autonomous vehicles.

Language: en

Keywords

Crash severity; dynamic precursors; factor analysis; random parameters logit model; vehicles involved in crash