Injury severity analysis of highway-rail grade crossing crashes in non-divided two-way traffic scenarios : a random parameters logit model

Abstract

Highway-rail grade crossing (HRGC) crashes in non-divided two-way traffic scenarios have caused numerous fatalities and injuries over the years. Although crucial to the safety of multimodal transportation systems, these crossings have received little attention and previous studies did not fully account for the unobserved heterogeneity and its potential interactive effects. To bridge these gaps, the HRGC crashes occurring between 2019 and 2020 in the United States were collected from the Federal Railroad Administration's Office of Safety Analysis System. A random parameters logit model with heterogeneity in means was developed to investigate the impact of multiple factors associated with crossings, crashes, drivers, vehicles, and the environment. The present study indicates that did not stop behavior generates the random parameter with heterogeneity in means that is influenced by the dark and land with commercial power indicators. Furthermore, the findings show that factors such as estimated vehicle speed > 25 MPH, train speed > 45 MPH, going around the gate, old driver, female driver, motorcycle, and the driver was in vehicle indicators would increase the likelihood of more severe injury outcomes in HRGC crashes. Notably, the adverse crossing surface and truck indicators demonstrate unexpected marginal effects by reducing the likelihood of severe injury outcomes at non-divided two-way traffic HRGCs. This study emphasizes the importance of considering unobserved heterogeneity in the context of HRGC crashes. The findings can serve as a foundation for developing targeted interventions aimed at enhancing road and railway safety.