Implementation of the AASHTO Highway Safety Manual
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Summary
This report details a scoping study conducted by the University Transportation Center for Alabama (UTCA) and the Center for Advanced Public Safety to develop a cost-effective implementation plan for the AASHTO Highway Safety Manual (HSM) within the Alabama Department of Transportation (ALDOT). The HSM, published in 2010, represents a significant shift in roadway safety science, introducing rigorous Empirical Bayes methodologies, new terminology, and data-intensive procedures. However, its complexity, lack of standardized implementation protocols, and the absence of dedicated software created substantial barriers for state agencies. ALDOT initiated this study to avoid inefficient adoption, aiming to customize the HSM to fit Alabama’s existing resources, data infrastructure, and organizational structure. The research team executed a multi-task scoping project to evaluate implementation strategies. Key activities included identifying HSM users across ALDOT bureaus and local agencies, assessing national implementation experiences, and evaluating software capabilities. The team specifically analyzed two primary tools: SafetyAnalyst (SA), adapted by FHWA and AASHTO for HSM computations, and the Interactive Highway Safety Design Model (IHSDM). They also conducted a comprehensive data-needs assessment to identify gaps between ALDOT’s current datasets and the extensive geometric, operational, and crash-history data required by HSM Safety Performance Functions (SPFs). Additionally, the researchers investigated the potential integration of ALDOT’s legacy software, CARE and CORRECT, with SafetyAnalyst to determine the most viable analytical platform. Findings revealed that while SafetyAnalyst produces high-quality outputs and handles complex HSM computations, its implementation is resource-intensive, requiring significant data transformation and dedicated staff for maintenance. A nationwide survey indicated that only one-third of state DOTs were implementing SA, with many encountering substantial data migration and processing issues. IHSDM was deemed less viable for general HSM computations due to labor-intensive data entry and poor integration with existing Computer-Aided Design (CADD) systems. The study highlighted that ALDOT’s existing CARE software offers robust screening and analysis capabilities but lacks the Empirical Bayes methodology central to the HSM. Consequently, the report outlines a phased implementation strategy divided into short-, mid-, and long-term actions, emphasizing the need for calibrated Alabama-specific SPFs, targeted training, and strategic software selection to balance computational rigor with operational feasibility. The significance of this work lies in providing ALDOT with a structured roadmap to transition from traditional safety programs to HSM-based practices without incurring unnecessary costs or delays. By identifying specific data gaps and software limitations, the report enables ALDOT to prioritize critical data collection and select an analytical framework that leverages existing institutional knowledge. The proposed flexible implementation plan ensures that Alabama can adopt advanced safety methodologies effectively, accommodating future updates to the HSM while addressing the unique constraints of state and local transportation agencies.
Key finding
The study developed a phased implementation roadmap for ALDOT that recommends evaluating the integration of existing CARE software with HSM methodologies rather than immediately replacing it with SafetyAnalyst, due to the high data and staffing requirements of the latter.
Methodology
mixed_methods
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
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| 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.
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- Applied Guidance: countermeasure evaluation
- Empirical Findings: crash risk outcomes
- Methodological Resource: dataset resource