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The National Academies

NCHRP 17-78 [Completed]

Understanding and Communicating Reliability of Crash Prediction Models

  Project Data
Funds: $300,000
Research Agency: University of North Carolina - Chapel Hill
Principal Investigator: Dr. Raghavan Srinivasan
Effective Date: 12/1/2016
Completion Date: 8/31/2020

The objectives of this research were to develop guidelines 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 guidelines were to address the following, at a minimum:
  • Methods to improve the reliability of crash prediction models
  • Implications of assumptions
  • Crash Prediction Model validation
  • Data quality
  • Use and reliability of calibrations 
  • Combining CMFs 
  • Enhanced accuracy and reliability as a result of increased model complexity 
  • Implications of crash prediction model limitations on safety programs and policy 
  • Effective communication of crash prediction model outputs to a variety of audiences
The guidelines were to 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 guidelines were 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 AASHTO HSM.

STATUS: Research is complete, and publication of final report is pending. 

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