Is there any association of local characteristics with traffic signal and stop sign violation induced crashes? A Hierarchical Modeling based study from Alabama, USA

Abstract

Traffic violations are one of the major causes of road crashes. This study investigates traffic crashes involving traffic sign or signal violations at intersections in Alabama, USA by exploiting a statewide crash database with nearly 60,000 sign or signal violation crashes to inform mitigation strategies. This study aims to identify factors contributing to traffic sign or signal violation crashes at intersections, with a particular focus on local characteristics, including the built environment and socioeconomic factors. Due to the multi-level data structure, this study employs a hierarchical modeling approach to explore the correlates of intersection crashes and develop models by integrating hierarchical modeling with the binary logit model and negative binomial model separately to explain factors contributing to both types of crashes. The modeling results reveal that signal violation and stop sign violation crashes occur more frequently at intersections close to open spaces. Both violation crashes are more likely to occur in block groups with more low-income or under-educated households. Further, the crash frequencies are positively related to the distance from an intersection to its nearest law enforcement agency and negatively related to the number of police officers in an area.