Understanding and Communicating Reliability of Crash Prediction Models

The current Highway Safety Manual (HSM), published in 2010, provides models for predicting crashes for several common roadway facilities and methods for calibrating the models and some qualitative guidance on model reliability. However, the manual does not include methods to consistently convey model reliability. Transparency and credibility are essential to any form of analysis being performed for the public welfare. During initial implementation of the HSM, model results have been generated and often utilized to make major capital improvement decisions without fully understanding and communicating the accuracy of the model results, which can erode the credibility of this new and rapidly growing field. The state of the art of safety analysis has progressed and more has been learned about the impact on accuracy of assumptions made during the development of crash prediction models using HSM procedures. Reliability, accuracy, and appropriateness of safety models may not always conform to necessary requirements relative to facility type. Practitioners also appear to be struggling to fully understand and appropriately communicate the benefits of the HSM and results derived from the included methods. There are many factors that affect reliability, for example model accuracy. Case studies presented at various conferences, including the Transportation Research Board (TRB) Annual Meeting, and through other initiatives demonstrate that some practitioners are utilizing the models incorrectly or in ways not recommended, and are also displaying crash prediction results without properly understanding the model reliability. Some crash prediction models have been reported with measures of model reliability while others have not. Understanding and communicating consistently reliable crash prediction results is critical to credible analysis and a barrier for some transportation agencies or professionals utilizing these models. The objectives of this research are to develop guidance for: (1) the quantification of the reliability of crash prediction models including crash modification factors and/or functions (CMFs) and safety performance functions (SPFs) for practitioner use; (2) user interpretation of model reliability; and (3) the application of crash prediction models accounting for, but not limited to assumptions, data ranges, and intended and unintended uses. The guidance should address the following, at a minimum: (1) Methods to improve the reliability of crash prediction models; (2) Implications of assumptions; (3) Crash Prediction Model validation; (4) Data quality; (5) Use and reliability of calibrations; (6) Combining CMFs; (7) Enhanced accuracy and reliability as a result of increased model complexity; (8) Implications of crash prediction model limitations on safety programs and policy; and (9) Effective communication of crash prediction model outputs to a variety of audiences. The guidance should include a number of case studies or illustrative examples that demonstrate the quantification and user interpretation of crash prediction models reliability. Examples may illustrate the application of crash prediction models accounting for, but not limited to assumptions, data ranges, and intended and unintended uses. The guidance is intended to assist practitioners and researchers in addressing the application and understanding and communicating the model outcomes. The research results may be incorporated in a future edition of the American Association of State Highway and Transportation Officials (AASHTO) Highway Safety Manual (HSM).

Language

  • English

Project

  • Status: Active
  • Funding: $300000
  • Contract Numbers:

    Project 17-78

  • Sponsor Organizations:

    Federal Highway Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590

    American Association of State Highway & Transportation Officials (AASHTO)

    444 North Capitol Street, NW, Suite 225
    Washington, DC  United States  20001

    National Cooperative Highway Research Program

    Transportation Research Board
    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Project Managers:

    Bush, Mark

  • Performing Organizations:

    University of North Carolina, Chapel Hill

    Chapel Hill, NC  United States  27514
  • Principal Investigators:

    Srinivasan, Raghavan

  • Start Date: 20160920
  • Expected Completion Date: 20190319
  • Actual Completion Date: 0
  • Source Data: RiP Project 40218

Subject/Index Terms

Filing Info

  • Accession Number: 01572382
  • Record Type: Research project
  • Source Agency: Transportation Research Board
  • Contract Numbers: Project 17-78
  • Files: TRB, RiP
  • Created Date: Aug 7 2015 1:01AM