Application of demographic analysis to pedestrian safety : final report.

Lin, Pei-Sung; Kourtellis, Achilleas; Zhang, Yu; Guo, Rui; Bialkowska-Jelinska, Elzbieta · 2017 · ROSA P / University of South Florida. Center for Urban Transportation Research

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Summary

This research addresses the disproportionate risk of pedestrian fatalities in low-income areas, where fatality rates are approximately twice those of affluent neighborhoods. Motivated by the need to systematically address pedestrian safety in these vulnerable communities, the study aimed to develop a demographics-based methodology to identify pre-conditions for pedestrian hazards, quantify relationships between crash frequency/severity and various factors, and provide targeted recommendations for engineering and educational countermeasures. The researchers, from the University of South Florida’s Center for Urban Transportation Research, conducted a comprehensive literature review and developed a methodological flowchart integrating geographic analysis and statistical modeling. They tested this methodology using data from Florida Department of Transportation (FDOT) District 4, specifically focusing on low-income census block groups in Broward and Palm Beach Counties. The analysis utilized FDOT GIS databases, Census data, and other available sources to model pedestrian crash frequency and injury severity. The study examined five categories of variables: demographic and social factors, road environment factors, neighborhood land use attributes, individual characteristics, and environmental conditions. Key findings revealed that pedestrian crashes are more frequent in low-income areas with higher populations, minority dominance, zero-car ownership, and lower education levels. Notably, a smaller proportion of older adults was associated with higher crash frequency, while the proportion of commuters using public transit or biking increased risk. Road environment factors significantly influenced crash frequency, with the number of traffic signals per block group being the most influential variable, followed by bus stop density and the proportion of higher-speed roads. Land use analysis indicated that higher densities of discount stores, convenience stores, and fast-food restaurants correlated with increased crash frequency. Regarding injury severity, dark (unlighted) conditions were the most influential factor, followed by impaired pedestrians and aggressive drivers. Additionally, impaired pedestrian crashes were found to cluster near alcohol retail locations. The study concludes that a combined approach of engineering, education, and enforcement is essential for improving pedestrian safety in low-income areas. Recommended engineering countermeasures include improved roadway lighting, midblock pedestrian crossing signals (such as HAWK and RRFB), high-visibility crosswalks, bus stop improvements, and speed reduction treatments like road diets and roundabouts. Educational strategies include WalkWise safety programs, distribution of tip cards, social media outreach, and community networking. The research provides a validated framework for transportation agencies to identify high-risk areas and implement targeted interventions that resonate with local demographics, ultimately aiming to reduce pedestrian fatalities and injuries in underserved communities.

Key finding

Pedestrian crash frequency is significantly higher in low-income areas characterized by zero-car ownership, lower education levels, and high densities of discount stores, while severe injury risk is most strongly driven by dark-unlighted conditions and pedestrian impairment.

Methodology

dataset

Provenance

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

Topics

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• demographic disparities
• incidence prevalence
• vru crash typology
• comparative international

Information type

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• Empirical Findings: crash risk outcomes