Safety Index for Evaluation of Two-Lane Rural Highways

Cafiso, Salvatore; La Cava, Grazia; Montella, Alfonso · 2007 · OpenAlex-citations

DOI: 10.3141/2019-17

archive: archived pipeline: cataloged verified

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Summary

This paper presents a methodological approach for evaluating the safety of two-lane rural highway segments, specifically addressing the challenge of assessing safety on roads where crash data are unavailable or unreliable. The authors propose a Safety Index (SI) that integrates two complementary analytical procedures: alignment design consistency models and Road Safety Inspections (RSI). This systematic procedure aims to identify hazardous locations and rank safety issues quantitatively, allowing for proactive remedial treatments before accidents occur. The research was conducted as part of the IASP project, funded by the European Commission and the Province of Catania, Italy. The Safety Index is formulated by combining three risk components: the Exposure factor, the Accident Frequency factor, and the Accident Severity factor. The Exposure factor is calculated based on segment length and Average Annual Daily Traffic (AADT). The Accident Frequency factor is derived from two sources: RSI scores and Geometric Design (GD) evaluations. RSI involves inspecting specific safety issues—such as accesses, cross-sections, delineation, markings, pavement, roadside hazards, sight distance, and signs—at 200-meter intervals. These issues are scored based on defined criteria for high or low-level problems, with weights assigned based on literature-derived Accident Modification Factors. The GD evaluation assesses design consistency using operating speed models and checks against Italian design standards for tangents and curves. The Accident Severity factor accounts for operating speed relative to a base speed and the presence of roadside hazards, weighted by their potential to cause injury or fatality. To validate the procedure, the authors applied the SI to 30 homogeneous segments of two-lane rural highways in the Province of Catania. The validation involved comparing the risk rankings produced by the SI against accident history estimates refined using the Empirical Bayes (EB) procedure. The EB estimates were derived from a negative binomial regression model predicting accident frequency based on segment length and AADT, which corrected for regression-to-mean bias. The agreement between the SI rankings and the EB estimates was measured using Spearman’s rank-correlation analysis. The results demonstrated a strong correlation between the two methods, with a correlation coefficient of 0.87. The rankings agreed at the 99.9% level of significance, validating the Safety Index as an effective tool for safety evaluation. The study concludes that the proposed SI provides a replicable and systematic method for assessing road safety performance without relying solely on historical crash data. This approach allows agencies to effectively identify and prioritize safety improvements on rural highways, particularly where data scarcity has previously hindered accurate safety assessments.

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• induced exposure

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• Empirical Findings: crash risk outcomes