Modeling Pedestrian Injury Severity in Pedestrian-Vehicle Crashes in Rural and Urban Areas: Mixed Logit Model Approach

Abstract

Pedestrian-vehicle crashes are more likely to result in severe pedestrian incapacitating injuries and fatalities than other types of crashes. In this study, mixed logit models are developed to investigate and identify significant contributing factors to the pedestrian injury severity in pedestrian-vehicle crashes in both rural and urban areas in North Carolina, United States. Pedestrian-vehicle crash data from the Highway Safety Information System database from 2005 to 2012 are collected and used in this study. Crash injury severities are classified into five categories: fatality; injury class 1 (disabling injury); injury class 2 (evident injury); injury class 3 (possible injury); and no injury (property damage only). The estimation results show that factors such as a bad driver’s physical condition, heavy trucks, dark light condition, speed limit between 35 and 50 mph and speed limit above 50 mph will significantly increase pedestrian injury severities in both rural and urban areas. The developed model and analysis results provide insights on developing effective countermeasures to reduce pedestrian injury severities in pedestrian-vehicle crashes and improve traffic system safety performance.