Evaluating the Relationship Between Near-Crashes and Crashes: Can Near-Crashes Serve as a Surrogate Safety Metric for Crashes?

The number of crashes observed in naturalistic driving studies is typically small; thus, there is a need to use crash surrogates. This study evaluated the use of near-crashes as a surrogate measure when assessing the safety impacts of driver behaviors and other risk factors. Two metrics, the precision and bias of the risk estimation, were used to assess whether near-crashes could be combined with crashes. The principles and exact conditions for improved precision and unbiased estimation were proposed and applied to the 100-Car data. The analyses indicated that, in general, there is a strong relationship between the frequencies of contributing factors for crashes and for near-crashes. The study also indicated that analyses based on combined crash and near-crash data consistently underestimate the risk of contributing factors compared to using crash data alone. At the same time, the precision of the estimation will increase. This consistent pattern allows investigators to identify the truly high risk factors while qualitatively assessing the potential bias. In summary, the study concluded that there is a benefit to the use of near-crashes as a crash surrogate for risk assessment when naturalistic studies are not large enough to generate sufficient numbers of crashes.

• Record URL:
  http://www.nhtsa.gov/DOT/NHTSA/NVS/Human Factors/Safety Problem Identification/DOT HS 811 382.pdf
• 
• Supplemental Notes:
  • Cover date: October 2010. Alternate title: Task 3-Evaluating the Relationship Between Near-Crashes and Crashes: Can Near-Crashes Serve as a Surrogate Safety Metric for Crashes?
• Corporate Authors:

  Virginia Polytechnic Institute and State University, Blacksburg

  Virginia Tech Transportation Institute
  3500 Transportation Research Plaza
  Blacksburg, VA  United States  24061

  National Highway Traffic Safety Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Guo, Feng
  • Klauer, Sheila G
  • McGill, Michael T
  • Dingus, Thomas A
• Publication Date: 2010-9

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Draft Final Report
• Features: Appendices; Figures; Glossary; Photos; References; Tables;
• Pagination: 73p

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Behavior; Crash data; Data analysis; Drivers; Metrics (Quantitative assessment); Near crashes; Risk analysis; Traffic crashes
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; I83: Accidents and the Human Factor;

Filing Info

• Accession Number: 01563556
• Record Type: Publication
• Files: HSL, TRIS, ATRI, USDOT
• Created Date: May 18 2015 11:03AM