Informing the Selection of Countermeasures by Evaluating, Analyzing, and Diagnosing Contributing Factors that Lead to Crashes

Successful safety management practices require a thorough understanding of the factors contributing to crashes. The continuous advancements in the science of data-driven safety analysis, as well as the countermeasures and technologies available for addressing crashes, create challenges in maintaining a safety workforce that is always proficient in the state of the practice. In many cases, agencies continue to use approaches, such as descriptive statistics and anecdotal information to perform this diagnostic assessment without a thorough understanding of what should be expected for a given context or road type. A secondary issue is that once the nature of the crashes at a location are assessed, choosing an effective countermeasure requires an examination of the human factors, behavioral factors, future development, prevailing or predicted crash type(s) or mix of road users to determine the most appropriate treatments to apply. Doing so allows the selected countermeasure to reduce crashes to the greatest extent possible. However, in many cases, practitioners have limited experience and background to assess these contributing factors, reducing the likelihood of safety investment success. Further, the practitioner may have limited understanding of the potential for a treatment to increase exposure to the more vulnerable road users. For instance, installing a turn lane might also increase vehicle speeds or crossing distance. By having a better understanding of these tradeoff, changes can be made in the design and operations of facilities upfront, rather than waiting for crashes to occur before addressing the less than optimal road design. The objective of this research is to assess best practices in crash diagnosis across crash types in modal diverse contexts, recognizing that vehicle and mode mix matters in the success of investment strategies. The research will then develop additional diagnostic tools that leverages the availability of crash, roadway, traffic volume, human factors, behavioral, socioeconomic, and demographic data to advance the art of the practice in crash diagnostics that consider both modal priority and facility context.


  • English


  • Status: Proposed
  • Funding: $690000
  • Contract Numbers:

    Project BTS-14

  • Sponsor Organizations:

    Behavioral Traffic Safety Cooperative Research Program

    Transportation Research Board
    500 Fifth Street, NW
    Washington, DC  United States  20001

    Governors Highway Safety Association

    444 N. Capitol Street, NW, Suite 722
    Washington, DC  United States  20001

    National Highway Traffic Safety Administration

    1200 New Jersey Avenue, SE
    Washington, D.C.  United States  20590
  • Project Managers:

    Rogers, William

  • Start Date: 20200204
  • Expected Completion Date: 0
  • Actual Completion Date: 0

Subject/Index Terms

Filing Info

  • Accession Number: 01708755
  • Record Type: Research project
  • Source Agency: Transportation Research Board
  • Contract Numbers: Project BTS-14
  • Files: TRB, RiP
  • Created Date: Jun 24 2019 3:27PM