Exploring traffic safety climate with driving condition and driving behaviour: a random parameter structural equation model approach

Abstract

Abstract This study aimed to explore traffic safety climate by quantifying driving conditions and driving behaviour. To achieve the objective, the random parameter structural equation model was proposed so that driver action and driving condition can address the safety climate by integrating crash features, vehicle profiles, roadway conditions and environment conditions. The geo-localized crash open data of Las Vegas metropolitan area were collected from 2014 to 2016, including 27 arterials with 16 827 injury samples. By quantifying the driving conditions and driving actions, the random parameter structural equation model was built up with measurement variables and latent variables. Results revealed that the random parameter structural equation model can address traffic safety climate quantitatively, while driving conditions and driving actions were quantified and reflected by vehicles, road environment and crash features correspondingly. The findings provide potential insights for practitioners and policy makers to improve the driving environment and traffic safety culture.