Research Utilizing SHRP2 Data to Improve Highway Safety: Development of Speed—Safety Relationships

Hutton, Jessica M.; Cook, Daniel J.; Grotheer, J.; Conn, M. · 2020 · ROSA P / United States. Federal Highway Administration. Office of Safety Research and Development

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Summary

This study investigates the relationship between driving speed and crash safety on urban and suburban arterials, addressing a significant limitation in current highway safety management tools like the Highway Safety Manual (HSM). Existing models rely on posted speed limits rather than actual traffic speeds, leading to multicollarity issues that obscure the true impact of speed on crash frequency and severity. The research aims to develop empirical speed–safety relationships using high-resolution naturalistic driving data to determine if incorporating speed terms improves safety prediction models. The researchers utilized data from the second Strategic Highway Research Program (SHRP2), specifically the Naturalistic Driving Study (NDS) for vehicle speed data and the Roadway Inventory Database (RID) for roadway characteristics. The study focused on 114 roadway segments: 60 two-lane undivided (2U) and 54 four-lane divided (4D) arterials across five states. Site selection prioritized segments with consistent cross-sections, sufficient length for free-flow speeds, and high volumes of NDS trips. Researchers collected detailed site characteristics, including lane width, shoulder width, and driveway density, using aerial and street-view imagery to supplement RID data. Statistical analyses examined correlations between various speed measures—such as mean space-mean speed, speed variance, and the difference between maximum and minimum trip speeds—and crash frequency and severity, while controlling for roadway design features. The findings indicate that roadway characteristics significantly influence both speed choice and crash experience. Crucially, the study found that higher variance in mean speed across trips on a given segment was frequently correlated with increased crash frequency, particularly for multivehicle crashes. Conversely, most other speed metrics, including mean speed and the 85th percentile speed relative to the posted limit, showed no correlation or a negative correlation with crash frequency. Despite identifying these relationships, the research concluded that adding a speed term to existing HSM safety performance functions or developing speed-based crash modification factors (CMFs) did not substantially improve the predictive accuracy of crash models for urban and suburban arterials. The significance of this work lies in its clarification of the complex role of speed in highway safety. While confirming that speed variance is a risk factor, the study demonstrates that current safety prediction models are not significantly enhanced by the inclusion of actual speed data. This suggests that the existing HSM methodologies, which rely on surrogate variables like speed limits and roadway geometry, remain robust for safety analysis. The results provide transportation professionals with evidence that while speed variance matters, integrating complex speed metrics into standard safety tools may not yield practical improvements in crash prediction for these roadway types.

Key finding

Crash likelihood increases as the variance of mean speed increases for a given roadway segment, while adding a speed term to existing Highway Safety Manual models does not improve prediction accuracy.

Methodology

naturalistic

Sample size: 100

Provenance

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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.

• incidence prevalence
• speed choice
• roadway lighting effects
• urban rural setting
• comparative international
• speed management

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, observational prevalence
• Methodological Resource: dataset resource