Differential Analysis of Factors Influencing the Severity of Single-Vehicle and Multi-Vehicle Crashes

To investigate the factors influencing crash severity for different numbers of vehicles involved, this paper selected 10 years (2013–2022) of road traffic crash data from a city in Shandong Province, China, and divided the crash types into two categories: single-vehicle and multi-vehicle crashes. The crash severity was divided into three categories according to no injury, minor injury, and severe injury, and the potential heterogeneity of the influencing factors in the two crash types was analyzed using marginal effects by comparing the performance of random parameter logit models, and random parameter logit model with means and variances heterogeneity in estimating the crash injury severity of different crash types. The results show that the random parameters logit model with means and variances can fully represent the heterogeneity and effectively describe the differences between variables and has a good goodness-of-fit. The factors affecting the severity of single-vehicle and multiple-vehicle crashes show obvious differences. The results of the study could provide reference countermeasures for traffic safety management to implement more targeted countermeasures to mitigate traffic crashes.