Objective: The objectives of this study are (1) to examine the effects of different rule-violating behaviors on the risk of bus drivers being at fault in crashes, and (2) to identify the randomness and heterogeneity generated by the significant factors.
Methods: This study proposes a random parameter logit model based on the bus crash data obtained from the bus safety management system in Xi'an, China. The model considers crashes where bus drivers were at fault as the dependent variables and 16 factors as independent variables. These factors include a history of previous rule violations, a history of past crashes, the characteristics of the driver, the route length, and the characteristics of crashes.
Results: According to the results of the study, irregular behavior when entering and exiting bus stations had a significant effect on the likelihood of being at fault, as well as the driver's gender, during the probationary period, any complaints received, and reports of crashes. Moreover, the unobserved heterogeneity is determined by considering three variables, such as return trips, crashes at the intersection, and crash records of non-at-fault bus drivers.
Conclusions: The study results offer empirical evidence for the relationship between bus driver violations and being at fault in the crash, which has only previously been obtained through stated questionnaires. Further, we found that there was heterogeneity across cases in terms of the effect of previous crashes, meaning that following some crashes, drivers might be more cautious, while following others they may not. The findings provide additional insight into crashes and driver differences. Additionally, In light of our findings, we recommend practical measures to improve the safety management of bus companies.
Keywords: Traffic safety; at-fault crash; bus driver; random parameter logit model; rule-violating behavior.