Risky User Behavior at Highway–Rail Grade Crossings: A Systematic Literature Review with Empirical Insights

Highway–rail grade crossings (HRGCs) remain a critical safety problem despite decades of infrastructure investment. Moreover, the relationship between specific driver behaviors and crash severity across different geographic contexts remains poorly quantified. This study aimed to conduct a systematic review to (1) synthesize existing evidence on behavior-specific crash outcomes at HRGCs and (2) empirically validate findings from crash datasets. The study was conducted following PRISMA 2020 guidelines, identifying peer-reviewed studies (2015–2025) through structured searches of electronic databases. Inclusion criteria required studies to report quantitative associations between driver behavior and crash severity at HRGCs. In addition, crash records from two U.S. states (New Jersey and Texas; 2013 to 2022) were analyzed using multinomial logistic regression to assess empirical validity. Multinomial logistic regression analysis reveals that highway user action (HAU = 1) “going around gates” significantly increase the fatal risk. Empirical analysis confirmed these trends but revealed geographic variation: New Jersey showed a fatality odds ratio of 4.490 versus Texas’s 3.686 for a fatal risk, i.e., severity level 1. In addition, gender emerged as a significant factor in fatal crash risk, with female drivers facing elevated odds of fatal injury compared to male drivers: 1.464 in New Jersey and 1.817 in Texas. Despite these findings, three critical gaps remain in HRGCs: (1) predictive models focus on crash frequency rather than behavior forecasting, (2) data quality issues compromise of risk predictions, and (3) machine learning approaches lack interpretability for practitioners. This review demonstrates that identical driver behaviors produce different crash outcomes across geographic regions. Effective safety interventions need to address local risk factors instead of relying on a uniform national approach.