Development and Application of Crash Severity Models for the Highway Safety Manual

As the Highway Safety Manual (HSM) continues to evolve, determining the potential crash severity at a location becomes an increasingly vital component in predicting safety performance. For safety performance functions (SPFs) to be reliable, they must be consistent. Consistency in how states apply stand-alone severity or severity with frequency based tools and estimates are a fundamental requirement for the adoption and use of the HSM and its associated tools. Consistency is a function of several factors: (1) results that are in general agreement from a multitude of analytical techniques available to practitioner; (2) availability of data sources that allow for broad state and interstate analysis; and (3) interpretability of results for policy application at the national, state, and local agency levels. Severity analysis tools, as currently available in the HSM, do not fully meet this definition of consistency–for various reasons, but primarily originating from the fact that the analytical techniques available in the published literature are not consistent in their estimation of crash severity probabilities and frequencies. The differences in severity estimations can be significant–from the methods currently in use that adopt the observed severity ratios to emerging methods which analyze the severity aspects at multiple scales–from spot location, to corridor and network levels. Three factors are critical to adoption of safety analysis techniques–integrity with network screening methods (Part B of the HSM), data availability and requirements, and model predictive performance (Part C of the HSM). The HSM provides methods for model calibration and qualitative guidance on the model reliability, but lacks methods to identify which crash severity levels and crash types need to be modeled to ensure consistency. The default approach recommends using observed crash severity ratios for a facility type and using those factors to obtain severity specific expected values. Data quality, crash severity reporting, and how to model crash severity level combinations are significant challenges in terms of crash prediction reliability. Crash prediction model results are currently used to make planning and project-level decisions without complete understanding of their reliability. Specific examples include: (1) lack of understanding of confounding factors due to inaccuracy of severity estimations; (2) poor understanding of models and their limitations; (3) use of models at or near their limits; and (4) inappropriate transfer of severity ratios and severity level definitions without consideration of location specific temporal and spatial factors. Continuing the use of models in this way may lead to suboptimal design of projects, degradation of model credibility, and open concerns of liability and public trust. The objectives of this project were to: (1) assess the current HSM approaches to severity estimation and prediction using SPFs; (2) identify gaps and opportunities in the current severity prediction/estimation procedures within the HSM; (3) develop and validate new severity models to address the gaps and opportunities; and (4) develop a guidance document that includes protocols for the use and application of severity based models in a format suitable for possible adoption in the HSM.  


  • English


  • Status: Completed
  • Funding: $600000
  • Contract Numbers:

    Project 17-85

  • Sponsor Organizations:

    National Cooperative Highway Research Program

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

    American Association of State Highway and Transportation Officials (AASHTO)

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

    Federal Highway Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Project Managers:

    Jared, David

  • Performing Organizations:

    University of Connecticut, Storrs

    Storrs, CT  United States  06268-5202
  • Principal Investigators:

    Ivan, John

  • Start Date: 20181115
  • Expected Completion Date: 20220630
  • Actual Completion Date: 0
  • Source Data: RiP Project 41639

Subject/Index Terms

Filing Info

  • Accession Number: 01634970
  • Record Type: Research project
  • Source Agency: Transportation Research Board
  • Contract Numbers: Project 17-85
  • Files: TRB, RIP
  • Created Date: May 19 2017 9:31AM