Analyzing the Injury Severity in Overturn Crashes Involving Sport Utility Vehicles: Latent Class Clustering and Random Parameter Logit Model

Abstract

The fatal or incapacitating injury caused by overturn crashes involving sport utility vehicles (SUVs) is irreparable. The purpose of this study is to identify potential factors that affect the injury severity of overturn crashes involving SUVs and develop adequate preventive strategies. Given the unobserved heterogeneity existing in the data set, crash data in North Carolina from Highway Safety Information System (HSIS) is analyzed and separated by Latent Class Clustering into six relatively homogeneous groups. To further explore the heterogeneity, random parameter logit models are developed for each cluster, and the impacts of significant factors are estimated with marginal effects. The results reveal the heterogeneity across the clusters and the homogeneity within the same cluster. Variables (including females, people over fifty years old, improper or aggressive behavior, rural areas, high-speed limit, curved roadway, rolling and mountainous terrain, adverse weather, and poor light conditions) are associated with the injury severity of the overturn crashes involving SUVs. The findings of this study can further provide decision makers with insightful countermeasures to improve transportation safety and mitigate the injuries of overturn crashes involving SUVs.