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Analysis of Pedestrian–Motor Vehicle Crashes in San Antonio, Texas

Department of Civil and Environmental Engineering, University of Texas at San Antonio, San Antonio, TX 78249, USA
Author to whom correspondence should be addressed.
Academic Editors: Aleksander Król and Małgorzata Król
Sustainability 2021, 13(12), 6610;
Received: 3 May 2021 / Revised: 4 June 2021 / Accepted: 7 June 2021 / Published: 10 June 2021
(This article belongs to the Special Issue Transportation Safety Management: Perspectives for Sustainability)
Pedestrian safety is becoming a global concern and an understanding of the contributing factors to severe pedestrian crashes is crucial. This study analyzed crash data for San Antonio, TX, over a six-year period to understand the effects of pedestrian–vehicle crash-related variables on pedestrian injury severity based on the party at fault and to identify high-risk locations. Bivariate analysis and logistic regression were used to identify the most significant predictors of severe pedestrian crashes. High-risk locations were identified through heat maps and hotspot analysis. A failure to yield the right of way and driver inattention were the primary contributing factors to pedestrian–vehicle crashes. Fatal and incapacitating injury risk increased substantially when the pedestrian was at fault. The strongest predictors of severe pedestrian injury include the lighting condition, the road class, the speed limit, traffic control, collision type, the age of the pedestrian, and the gender of the pedestrian. The downtown area had the highest crash density, but crash severity hotspots were identified outside of the downtown area. Resource allocation to high-risk locations, a reduction in the speed limit, an upgrade of the lighting facilities in high pedestrian activity areas, educational campaigns for targeted audiences, the implementation of more crosswalks, pedestrian refuge islands, raised medians, and the use of leading pedestrian interval and hybrid beacons are recommended. View Full-Text
Keywords: pedestrian; motor vehicle; crashes; fatalities; logistic regression; bivariate analysis pedestrian; motor vehicle; crashes; fatalities; logistic regression; bivariate analysis
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MDPI and ACS Style

Billah, K.; Sharif, H.O.; Dessouky, S. Analysis of Pedestrian–Motor Vehicle Crashes in San Antonio, Texas. Sustainability 2021, 13, 6610.

AMA Style

Billah K, Sharif HO, Dessouky S. Analysis of Pedestrian–Motor Vehicle Crashes in San Antonio, Texas. Sustainability. 2021; 13(12):6610.

Chicago/Turabian Style

Billah, Khondoker, Hatim O. Sharif, and Samer Dessouky. 2021. "Analysis of Pedestrian–Motor Vehicle Crashes in San Antonio, Texas" Sustainability 13, no. 12: 6610.

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