Abstract
Fatal traffic crashes involving commercial vehicles exhibit distinct characteristics and mechanisms compared to general traffic crashes, influenced by numerous factors that impact the resulting fatalities. This study presents a comprehensive analysis of significant commercial vehicle crashes in China over a nine‐year period (2014–2022), exploring an extensive range of factors including driver behavior, road conditions, vehicle characteristics, and environmental aspects. Utilizing a hierarchical Bayesian ordered probit model that incorporates both categorical and random effects, the research offers nuanced insights into the probabilistic outcomes of fatal traffic crashes. The model’s hierarchical structure enables the exploration of unobserved heterogeneities at individual and group levels. Key findings indicate that driver’s behaviors like speeding and overloading significantly escalate the likelihood of fatal traffic crashes, particularly those resulting in 10 or more fatalities. The study also highlights the role of road class in fatal crashes, with primary and secondary roads being associated with higher risks of more severe fatal crashes. The analysis extends to the impact of vehicle type, noting a distinct increase in the probabilities of fatal crashes with passenger vehicles, while freight vehicles exhibit a more complex relationship with fatal crashes severity. The insights from this study underscore the urgent need for enhanced enforcement of speed limit and vehicle weight regulations, particularly through the deployment of advanced monitoring technologies on highways frequented by commercial vehicles, and targeted infrastructure improvements on primary and secondary roads. This approach offers a novel analytical framework for evaluating commercial traffic crashes, assisting policymakers in devising targeted safety interventions to reduce the incidence of commercial vehicle crashes.
Funder
Ministry of Transport of the People's Republic of China