Urban Transportation Infrastructure and Cyclist and Pedestrian Safety

Sharif, Hatim; Dessouky, Samer · 2021 · ROSA P / Transportation Consortium of South-Central States

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Summary

This study, conducted by the University of Texas at San Antonio in cooperation with the City of San Antonio, addresses the critical need to improve safety for vulnerable road users—specifically pedestrians and bicyclists—in alignment with the city’s Vision Zero goals. Motivated by the high economic costs of traffic crashes and San Antonio’s ranking as one of the most dangerous metro areas for pedestrians, the research aims to identify root causes of crashes, determine risk factors, and recommend effective countermeasures. The study focuses on the period from 2013 to 2017, analyzing crash data to support the Federal Highway Administration’s designation of San Antonio as a Bicycle and Pedestrian Safety Focus City. The methodology involved a comprehensive evaluation of crash data from the Crash Record Information System. Researchers developed a database of bicycle and pedestrian crash reports, calculating crash counts and rates while identifying high-concentration locations through geospatial analysis, including heat maps and hotspot analysis. The study utilized bivariate analysis and logistic regression to identify significant predictors of severe crashes. Variables analyzed included driver characteristics (age, gender), road-related factors (road class, speed limit, traffic control), environmental conditions (weather, lighting, time of day), and collision types. The analysis also explored the relationship between pedestrian/bicyclist crashes and other Strategic Highway Safety Plan emphasis areas, such as distracted driving, impaired driving, and speeding. Key findings indicate that pedestrian crashes were significantly more likely to result in fatal or severe injuries compared to bicyclist crashes. During the study period, pedestrian crashes accounted for 18.0% of all fatal and serious injury crashes, despite representing only 1.8% of total crashes. The strongest predictors of severe injury included lighting conditions, road class, speed limits, traffic control, collision type, and the age and gender of the pedestrian or bicyclist. Geospatial analysis revealed that while the downtown area had the highest crash density, crash severity hotspots were located outside the downtown core. Notably, the risk of fatal and incapacitating injuries increased substantially when the pedestrian or bicyclist was determined to be at fault. Distracted and impaired driving were also identified as significant contributors to crash frequency and severity. The study concludes with specific recommendations to enhance safety and allocate resources effectively. Proposed countermeasures include reducing speed limits, upgrading lighting facilities in high-activity areas, and implementing infrastructure improvements such as additional crosswalks, pedestrian refuge islands, raised medians, and leading pedestrian intervals. The authors also recommend targeted educational campaigns, automated speed enforcement, and the promotion of ridesharing services. These findings provide policymakers with evidence-based strategies to reduce fatalities and serious injuries, supporting the broader goal of achieving Vision Zero in San Antonio and similar urban environments.

Key finding

The strongest predictors of severe pedestrian and bicyclist injury are lighting conditions, road class, speed limit, traffic control, collision type, and the age and gender of the road user, with fatal and incapacitating injury risk increasing substantially when the pedestrian or bicyclist is at fault.

Methodology

dataset

Sample size: 442074

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• cyclist safety
• vru crash typology
• incidence prevalence
• demographic disparities
• fatality injury trends
• comparative international

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: crash risk outcomes