Surrogate Safety Assessment Model and Validation: Final Report
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Summary
This report details the development and validation of the Surrogate Safety Assessment Model (SSAM), a software tool designed to evaluate traffic facility safety using conflict analysis rather than historical crash data. Traditional safety assessments rely on police-reported crashes, which are infrequent, random, and retrospective, making them unsuitable for evaluating new designs or flow-control strategies before implementation. SSAM addresses this limitation by analyzing narrowly averted vehicle-to-vehicle collisions—traffic conflicts—as a surrogate measure of safety. The tool processes vehicle trajectory data exported from traffic simulation software, allowing engineers to compare the relative safety of different design alternatives statistically. The SSAM software was developed to interface with four major traffic simulation platforms: VISSIM, AIMSUN, Paramics, and TEXAS. An open-standard vehicle trajectory data format was established to ensure compatibility across these vendors. The model identifies, classifies, and evaluates conflicts based on specific algorithms that calculate metrics such as Time to Collision (TTC) and post-enclosure time. The validation process comprised three main components: theoretical validation, field validation, and sensitivity analysis. Theoretical validation involved eleven case studies comparing pairs of simulated design alternatives, such as protected versus permitted left turns, roundabouts versus signalized intersections, and various interchange configurations. These tests assessed whether SSAM could correctly discriminate between designs known to have different safety profiles. Field validation compared SSAM outputs against real-world crash records from 83 intersections in British Columbia, Canada. These intersections were modeled in VISSIM and simulated under AM-peak traffic conditions. The study employed five statistical tests, including ranking intersections by total incidents and incident types, developing a conflicts-based crash-prediction regression model, and identifying incident-prone locations. Results indicated that SSAM could effectively rank intersections by safety and identify high-risk locations consistent with historical crash data. Sensitivity analysis further examined differences in SSAM outputs across the four simulation platforms for identical intersection designs, providing guidance on the relative reliability of surrogate measures from each system. The findings demonstrate that conflict analysis via SSAM is a viable alternative to crash-based safety assessment, particularly for pre-construction evaluation of traffic facilities. The tool successfully distinguished between safer and less safe design alternatives in theoretical tests and correlated with real-world crash data in field tests. The report concludes that while SSAM provides valuable insights, further research is needed to improve driver behavior modeling in simulations, develop a composite safety index, and investigate the underlying nature of conflicts in real-world data. The SSAM software and user manual are made available to the public to support transportation engineers, safety researchers, and simulation designers in assessing traffic safety proactively.
Key finding
SSAM conflict metrics successfully ranked intersections by safety and predicted crash frequencies when compared against real-world crash records from 83 Canadian sites.
Methodology
mixed_methods
Sample size: 83
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_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
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
- naturalistic crash near crash
- crash typology
- intersection design
- regulatory evaluation
- comparative international
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
- Methodological Resource: dataset resource