Improving driver decisions and performance in high-speed, multilane, complex conditions.

NHTSA · 2009 · ROSA P / California. Department of Transportation

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Summary

This 2009 Preliminary Investigation by the Caltrans Division of Research and Innovation addresses the challenge of reducing fatalities caused by improper driver decisions regarding right-of-way and turning in high-speed, multilane environments. Motivated by California’s Strategic Highway Safety Plan, specifically Challenge Area 5, the study aims to identify strategies and technologies that improve driver performance and decision-making in complex infrastructure conditions. The investigation focuses on five priorities: developing systematic approaches to identify high-crash locations, exploring technologies used elsewhere to reduce severe collisions, expanding tools to minimize abrupt lane-changing crashes, and supporting in-vehicle communication technologies for collision warning. The methodology involved a comprehensive review of completed domestic and international research, as well as research in progress. The authors summarized literature across seven topic areas: multidisciplinary crash investigations, driver behavior, crash-contributing factors, countermeasures, tools for improving traffic operating conditions, collision avoidance for lane changing, and in-vehicle technologies. Additionally, the team surveyed transportation agencies to identify best practices for multidisciplinary crash investigations and contacted five state departments of transportation (Arizona, Illinois, Massachusetts, Nevada, and Texas) to gather information on countermeasures used in complex operating conditions. Key findings reveal that multidisciplinary crash investigations involving medical and behavioral specialists are rare in the United States, with only Virginia’s Multidisciplinary Crash Investigation Team actively employing psychologists and physicians. In contrast, Finland utilizes the VALT 2003 Method, which mandates multidisciplinary teams for all fatal crashes. Regarding driver behavior, studies indicate that information load rates significantly impact crash frequency; for example, increased sign frequency correlates with higher accident rates on freeways with fewer lanes, while optimal driver responses occur at middle-range information loads. Behavioral modeling highlights distinct lane-changing patterns across different freeway lanes and the influence of exclusive lanes like HOV lanes. Countermeasures identified include variable speed limits, overhead guide signage changes, and continuous flow lanes. Technological findings highlight the development of sensor-based collision avoidance systems, side blind zone alerts, and vehicle-to-vehicle communication systems designed to warn drivers of potential collisions during lane changes. The significance of this investigation lies in its identification of gaps in current U.S. practices, particularly the lack of multidisciplinary expertise in crash investigations and the need for further validation of initial research findings through real-world scenarios. The report concludes with recommendations for Caltrans to follow up with Virginia’s investigation team, attend human factors training, identify specific areas for further research, and conduct field tests of the identified tools and strategies. By synthesizing existing knowledge and international best practices, the document provides a foundational scope for future research aimed at mitigating crashes associated with complex driving environments.

Methodology

review

Provenance

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Topics

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

• perceptual countermeasures
• rail grade crossings
• lane changing
• traffic density
• incidence prevalence
• work zones

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