Surrogate Safety Measures from Traffic Simulation Models

Gettman, Douglas; Head, Larry · 2003 · OpenAlex-citations

DOI: 10.3141/1840-12

archive: archived pipeline: cataloged verified

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Summary

This report, produced by the Federal Highway Administration (FHWA), addresses the challenge of assessing safety for new or modified traffic intersections where historical crash data is unavailable. The primary research question investigates the potential for deriving surrogate safety measures from existing microscopic traffic simulation models. The motivation stems from the limitations of traditional safety assessment methods, which rely on crash statistics that are difficult to predict accurately for new facilities and often require long observation periods. By utilizing surrogate measures, the project aims to provide a methodology for evaluating traffic engineering alternatives for both signalized and unsignalized intersections prior to construction. The study employed a comprehensive approach involving five main activities. First, it reviewed previous literature on safety modeling and surrogate measures, focusing on the traffic conflicts technique. Second, it surveyed commercially available microscopic traffic simulation models to determine their capabilities for supporting safety measure derivation. Third, the researchers identified use cases and functional requirements for a Surrogate Safety Assessment Methodology (SSAM) tool designed to interact with simulation outputs. Fourth, the report specifies computational algorithms for calculating specific surrogate measures appropriate for intersections. Finally, it outlines suggestions for validating these surrogate measures against field data and previous safety studies. The analysis covered various simulation platforms, examining their behavior modeling, data extraction capabilities, and calibration parameters. The findings include a detailed specification of algorithms for calculating surrogate measures based on conflict events. The report defines conflicts as situations where road users approach each other with a risk of collision if movements remain unchanged. It categorizes conflicts into crossing flows (conflict points), merging flows (conflict lines), and following flows (rear-end conflict lines). Specific surrogate measures defined and algorithmically specified include Time to Collision (TTC), Post-Encroachment Time (PET), Deceleration Rate (DR), and Gap Time (GT). The report provides computational methods for deriving these metrics from simulation event files, detailing how to calculate severity and frequency for different conflict types. It also identifies limitations, noting that certain collision types, such as those involving pedestrians or U-turns, are not fully represented in the proposed surrogate measures. The significance of this work lies in establishing a standardized framework for using traffic simulation models as a proxy for safety assessment. By defining the SSAM and specifying algorithms for surrogate measures, the report enables traffic engineers to evaluate the safety implications of design alternatives without relying solely on post-construction crash data. This approach supports more informed decision-making in transportation planning and design. The report concludes by recommending validation activities to correlate simulation-derived surrogate measures with actual traffic conflicts and crash reductions, thereby strengthening the link between simulated safety metrics and real-world safety outcomes. This methodology represents a shift toward proactive safety analysis, allowing for the identification and mitigation of safety risks before infrastructure is built.

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

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• induced exposure
• naturalistic crash near crash
• exposure measurement
• incidence prevalence
• regulatory evaluation

Information type

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• Empirical Findings: crash risk outcomes
• Methodological Resource: validation psychometrics
• Theoretical Contribution: computational model