Public Roads: A Journal of Highway Research and Development, Vol. 54 No. 4

Tignor, Samuel; Paniati, Jeffrey F.; Council, Forrest M.; Hansen, Allen; Lum, Harry · 1991 · ROSA P / United States. Government Printing Office

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Summary

This document comprises two primary articles from the March 1991 issue of *Public Roads*, a journal of the Federal Highway Administration (FHWA). The first article, "Highway Safety in the Nineties" by Samuel C. Tignor, outlines the strategic direction for highway safety research and implementation during the 1990s. The second article, by Jeffrey F. Paniati and Forrest M. Council, details the capabilities and applications of the Highway Safety Information System (HSIS), a new database linking accident, roadway, and traffic data. Tignor’s article addresses the projected increase in highway fatalities, which were estimated to rise from 47,000 to 65,000 annually by the year 2000 if the fatality rate remained at 2.2 per 100 million vehicle miles. The paper identifies key safety challenges, noting that rural fatalities are disproportionately high compared to travel volume, nighttime fatalities occur at twice the rate of nighttime travel, and work zone fatalities had increased by over 40% in the early 1980s. To address these issues, the FHWA prioritized several research areas: highway safety information management, driver behavior research, enhanced highway simulators, highway design management, pedestrian safety, and improved traffic control methods. Specific initiatives included developing the HSIS to better utilize accident data, investigating mismatches between driver capabilities and highway design, and deploying Intelligent Vehicle-Highway Systems (IVHS) for real-time safety warnings and traffic management. The second article describes the HSIS, a microcomputer-based system developed by the FHWA and the University of North Carolina Highway Safety Research Center. Using five years of data (1985–1989) from Illinois, Maine, Michigan, Minnesota, and Utah, the system allows analysts to merge accident, geometric, and traffic data for detailed problem identification. The authors illustrate the system’s utility through four case studies. First, an analysis of crest vertical curves showed that accidents cluster near curve crests, with higher grade differentials correlating to increased accident proportions. Second, an examination of older drivers revealed that those aged 65 and older were overrepresented in intersection accidents, particularly at two-way stop-controlled intersections, suggesting a need for improved sight distance and intersection controls. Third, the system was used to estimate median crossover accident rates on divided highways, helping engineers weigh the safety trade-offs of installing median barriers. Finally, the HSIS facilitated a rapid assessment of head-on accidents to identify conditions contributing to severe injuries. The significance of these works lies in their shift toward data-driven safety improvements. Tignor emphasizes that existing technologies, such as microcomputer traffic control and IVHS, must be more widely implemented to meet public demand for safety. The HSIS article demonstrates how integrated data systems can isolate specific safety problems, such as those affecting older drivers or specific roadway geometrics, thereby guiding targeted engineering countermeasures and research efforts. Together, these articles advocate for a more systematic, evidence-based approach to reducing highway fatalities and injuries in the coming decade.

Key finding

The Highway Safety Information System enables the integration of accident, roadway, and traffic data to identify specific safety problems, such as the higher proportion of intersection accidents involving older drivers and the clustering of accidents near crest vertical curves with high grade differentials.

Methodology

dataset

Provenance

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Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• roadway lighting effects
• incidence prevalence
• rail grade crossings
• comparative international
• fatality injury trends
• naturalistic crash near crash

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, observational prevalence
• Methodological Resource: dataset resource