Social and Infrastructure Factors Shaping Road Safety: A Multi-Level Analysis of Crashes in Ohio, Texas, and Washington

AAA Foundation for Traffic Safety · 2025 · AAA Foundation for Traffic Safety

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Summary

This study addresses the persistent disparities in traffic safety, specifically the higher rates of fatalities and injuries experienced by marginalized communities. Motivated by the need to understand the unique contexts and challenges of different populations, the research employs a multi-level analysis to examine crash severity outcomes, crash likelihood, and infrastructure characteristics. The primary goal is to identify evidence-based recommendations using a Safe System approach to mitigate these inequities. The methodology involved analyzing crash, census, and roadway data across Ohio, Texas, and Washington. The researchers utilized a variety of statistical techniques, including intersectional analysis, binary logit models, Bayesian models, and structural equation models, to quantify disparities at three distinct levels: individual, neighborhood, and roadway segments. At the individual level, the study examined injury severities among pedestrians, bicyclists, and motor vehicle occupants. The neighborhood-level analysis compared pre-COVID (2018–2019) and post-COVID (2021–2022) periods to identify persistent and emerging crash rates linked to sociodemographic and infrastructure factors. Additionally, the roadway segment-level analysis developed an interactive tool to visualize safety scores across road segments in Cleveland, Austin, and Seattle. Key findings reveal that minority populations experienced the highest fatalities and incapacitating injury rates, often exceeding statewide averages. Disparities in traffic safety were evident across race and ethnicity for all road user types. Intersectional analysis highlighted the overrepresentation of specific demographic groups in traffic fatalities. At the neighborhood level, disparities were driven by sociodemographic and infrastructure factors. Roadway analysis indicated that socioeconomic disadvantaged areas lacked readiness to prevent fatal crashes, as measured by Safe System scores. Specifically, high poverty and unemployment in Cleveland contributed to poor safety alignment, whereas Austin’s early adoption of equity-focused Vision Zero policies resulted in comparatively better alignment. In Seattle, demographic factors were strongly associated with lower safety alignment. The study concludes that targeted interventions must recognize the multifaceted nature of traffic safety inequities. Recommendations include expanding analysis to include complex, intersecting factors such as human experiences, developing place-based analyses to uncover inequities, and applying a Safe System approach with an equity-lens framework. Specific state-level recommendations include culturally relevant messaging campaigns, urban pedestrian infrastructure improvements like traffic calming and enhanced visibility, bike-friendly infrastructure such as protected lanes and subsidy programs for safety equipment, and rural roadway safety enhancements including rumble strips and improved emergency response access. These findings aim to guide other regions in designing safer, more equitable transportation systems.

Key finding

Minority populations in Ohio, Texas, and Washington experience disproportionately higher rates of traffic fatalities and incapacitating injuries compared to statewide averages, driven by sociodemographic and infrastructure disparities.

Methodology

mixed_methods

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_aaa_foundation on 2026-05-23 (6 acquisition events logged).

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

Topics

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

• demographic disparities
• comparative international
• cyclist safety
• incidence prevalence
• fatality injury trends
• traffic safety culture

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