Dimensions of Motor Vehicle Crash Risk

Blincoe, Lawrence J.; Knipling, R R; Wang, Jing-Shiarn · 2011 · OpenAlex-citations

DOI: 10.21949/1501486

archive: archived pipeline: cataloged verified

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Summary

This paper addresses the need for a precise, multi-dimensional assessment of motor vehicle crash risks to evaluate the potential impact of safety interventions. The authors argue that valid assessments require disaggregating crash statistics by crash involvement type, subject vehicle body type, metric type, and problem-size referent. This granularity is essential for regulators and system developers to assess cost-benefit ratios for specific technologies, such as Intelligent Transportation Systems (ITS) or vehicle-based sensors, which often target specific crash scenarios or vehicle fleets. The study analyzes U.S. police-reported (PR) motor vehicle crashes using data from the General Estimates System (GES) for the five-year period of 1989–1993. The analysis is structured around four dimensions: crash involvement types (e.g., single-vehicle roadway departure, rear-end, left-turn-across-path); subject vehicle body types (passenger cars, light trucks/vans, combination-unit trucks, single-unit trucks, and motorcycles); metrics (crashes, involved vehicles, persons injured/killed, monetary costs, and fatal equivalents); and referents (annual national totals, per crash, per mile traveled, per vehicle, and per driver career). Monetary costs were calculated using both economic (E) criteria, covering direct losses, and comprehensive (C) criteria, which include valuations for pain, suffering, and loss of life. These costs were adjusted to 1997 price levels and discounted at 4% annually for long-term projections. Key findings reveal significant variations in crash risk and cost across vehicle types and crash scenarios. For instance, while passenger cars account for the highest absolute number of crashes (5.3 million annually), motorcycles exhibit the highest crash involvement rate per 100 million vehicle-miles traveled (927.65) and the highest average comprehensive cost per crash ($206,460). Combination-unit trucks (CUTs) also show high costs, with an average comprehensive cost of $89,400 per crash. The study calculates that the total annual comprehensive cost of all U.S. crashes is $431.9 billion, equivalent to 139,699 fatal equivalents. When projected over a vehicle’s operational life, the expected comprehensive monetary cost ranges from $10,230 for motorcycles to $162,040 for CUTs. Over a driver’s expected 58-year career, the discounted comprehensive cost is estimated at $81,630. The significance of this work lies in providing a standardized framework for quantifying crash consequences across different dimensions. By offering detailed statistics on per-unit costs and risks, the paper enables more accurate cost-benefit analyses for safety interventions. It highlights that national aggregates mask critical differences in risk profiles among vehicle types and crash geometries, which is crucial for targeting safety technologies effectively. The inclusion of comprehensive costs and fatal equivalents allows for a more holistic comparison of the societal harm caused by crashes, supporting better-informed regulatory and market decisions.

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Topics

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• incidence prevalence
• vru crash typology
• crash typology
• motorcycle crash typology
• induced exposure
• exposure measurement

Information type

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• Empirical Findings: crash risk outcomes