Screening methodology for needs of roadway lighting.
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Summary
This paper addresses the inadequacy of existing screening methods for determining the need for fixed roadway lighting, specifically those established by the American Association of State Highway and Transportation Officials (AASHTO) and the National Cooperative Highway Research Program (NCHRP). These legacy methods, unchanged since the 1970s, fail to account for modern traffic volumes, automotive technology, and roadway design. Furthermore, they dilute the influence of critical factors, lack a traceable theoretical foundation, and are ineffective for locations lacking crash history data. The study aims to develop an updated, principle-based screening methodology to help engineers and planners prioritize lighting installations for crash reduction. The authors developed a two-phase screening method grounded in risk assessment and benefit-cost analysis. The first phase, exposure assessment, utilizes a streamlined benefit-cost ratio to evaluate individual and population vulnerability to crashes. This assessment plots average daily traffic (exposure) against the night-to-day crash rate ratio (severity) to categorize locations into accepted, marginal, or rejected zones. The second phase, site-parameters assessment, refines the selection by evaluating eight specific engineering criteria: traffic mix, veiling luminance, curvature and grade, lane configuration, section/intersection geometry, posted speed, level of service, and intermodal transactions. Each parameter has defined thresholds; meeting a high threshold in any single parameter indicates that lighting would likely provide a safety benefit. This approach simplifies the complex scoring systems of previous methods. The methodology was tested using night crash histories from over eighty unlighted road sections across three regions in Virginia. The study demonstrated the application of the two-phase method to individual locations, validating its ability to screen needs even when precise crash data is unavailable by using indirect estimation methods. The results confirmed that the new method provides a more objective and theoretically sound basis for decision-making compared to the arbitrary thresholds of the AASHTO and NCHRP approaches. The significance of this work lies in providing highway agencies with a robust tool for resource allocation and lighting master planning. The authors recommend that agencies designate funds for lighting based on this screening method, provide training on its principles, and consider replacing older methods after a testing phase. They also advise performing annual regional data analysis and incorporating the method into holistic visibility enhancement plans. By establishing a clear link between risk assessment and lighting needs, the study offers a framework that can be adapted for other visibility improvements, such as pavement markings, ultimately enhancing nighttime highway safety.
Key finding
The developed two-phase screening method, validated against crash data from over eighty unlighted Virginia road sections, provides a theoretically grounded alternative to outdated AASHTO and NCHRP warranting systems for prioritizing roadway lighting investments.
Methodology
dataset
Sample size: 80
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 | partial | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified_with_issues.
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- Empirical Findings: crash risk outcomes