Examination of Backing Crashes and Potential IVHS Countermeasures

Tijerina, Louis; Hendricks, Donald; Pierowicz, John; Everson, Jeff; Kiger, Steve · 1993 · ROSA P / United States. Joint Program Office for Intelligent Transportation Systems

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Summary

This 1993 report by Battelle, sponsored by the National Highway Traffic Safety Administration (NHTSA), examines the potential for Intelligent Vehicle Highway System (IVHS) technology to prevent backing crashes. The study was motivated by the prevalence of these incidents, which accounted for approximately 182,000 police-reported crashes and 185 fatalities in 1990. Because backing maneuvers typically involve low closing speeds, the authors hypothesized that vehicle-based warning systems could significantly enhance crash avoidance capabilities. The research methodology combined causal factor analysis with analytical modeling. Researchers analyzed 100 General Estimates System (GES) police accident reports from 1991–1992 and 49 case reports from the 1986 National Automotive Sampling System (NASS). This analysis identified four primary crash subtypes: parallel path (23.1%), straight crossing path (53.4%), curved path (15.1%), and pedestrian/pedalcyclist (1.4%). Causal assessments revealed that 60.8% of crashes occurred because drivers did not see the struck object, while 26.6% resulted from improper backing. To estimate countermeasure effectiveness, the study employed factorial and stochastic modeling for a proposed rear-zone object detection system. The model incorporated variables such as driver reaction times, vehicle acceleration, and gap distances, assuming a system with a 15-foot effective range. The findings indicate that a functional rear-zone object detection system would be approximately 70% effective in preventing parallel path, curved path, and pedestrian/pedalcyclist crashes. However, when applied to all backing crash subtypes, the estimated effectiveness drops to 28%. This reduction is primarily due to the straight crossing path subtype, which constitutes over half of all backing crashes. In these scenarios, a vehicle backs into the path of a faster-moving perpendicular vehicle; the study concluded that a rear-zone detection system offers minimal benefit for this specific subtype because the threat originates from the side rather than directly behind the vehicle. The report concludes that while rear-zone object detection is a viable near-term countermeasure for specific crash types, significant research and development needs remain. Key gaps include understanding driver responses to false alarms, determining appropriate system interfaces, and collecting data on kinematic variables. Furthermore, the study highlights the need for alternative IVHS countermeasures specifically designed to address straight crossing path crashes, which current rear-zone sensors cannot effectively mitigate.

Key finding

A rear-zone object detection system is estimated to be approximately 70 percent effective in avoiding parallel path, curved path, and pedestrian/pedalcyclist crash subtypes, but only 28 percent effective across all backing crash subtypes.

Methodology

dataset

Sample size: 149

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• perception reaction time
• naturalistic crash near crash
• incidence prevalence
• crash typology
• driver post crash behavior

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