Analysis of Factors Affecting Crash Severity of Pedestrian and Bicycle Crashes Involving Vehicles at Intersections

Alshehri, Abdulaziz; Eustace, Deogratias; Hovey, Peter · 2020 · OpenAlex-citations

DOI: 10.1061/9780784483152.005

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Summary

This thesis investigates the factors influencing crash severity for vulnerable road users (VRUs), specifically pedestrians and bicyclists, involved in collisions with motor vehicles at intersections. The research is motivated by the heightened vulnerability of non-motorists due to a lack of physical protection and increased exposure to conflict points at intersections. The study aims to identify significant predictor variables to inform countermeasures that reduce injury severity for these users. The analysis utilized a three-year crash database (January 2013 to December 2015) obtained from the Ohio Department of Public Safety. The dataset was merged from crash, unit, and people records, resulting in 4,019 intersection-related crashes involving VRUs and motor vehicles. Of these, 53.2% involved pedestrians and 46.8% involved bicyclists. Crash severity was categorized as a binary dependent variable, combining fatal and injury outcomes against property damage only (PDO), as fatal crashes constituted a small minority (1.9%) of the data. A binary logistic regression model with stepwise selection was employed to evaluate fourteen independent variables, including environmental, traffic, road geometry, and human factors. The model identified five statistically significant predictors that increase the likelihood of severe outcomes (fatal or injury) compared to PDO crashes. These factors are: whether the VRU was a pedestrian (as opposed to a bicyclist), road contour (non-level or curved roads), gender, light conditions, and the unit in error. Notably, variables often cited in other studies as significant, such as posted speed limits, alcohol involvement, and age, were not statistically significant in this specific dataset. Speed-related factors were excluded from the analysis due to insufficient data reporting. The findings indicate that pedestrian status, complex road geometries, and specific lighting conditions are critical determinants of injury severity in these intersection crashes. The significance of this study lies in its identification of specific, data-driven factors affecting VRU safety in Ohio, providing a basis for targeted engineering and policy interventions. By highlighting that pedestrian status and road contour are significant predictors while others like alcohol and speed limits were not in this context, the research suggests that countermeasures should focus on intersection design and visibility improvements rather than solely on speed enforcement or alcohol prevention for this specific crash subset. The results offer empirical evidence to support the development of safer intersection environments for non-motorized road users.

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Topics

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• vru crash typology
• cyclist safety
• demographic disparities

Information type

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• Empirical Findings: crash risk outcomes