Developing CMFs from Probability Analyses

Since the advent of the Highway Safety Manual (HSM), crash frequency is the basis for safety evaluations of countermeasures where ample crash data are available. One of the goals for safety analyses is estimating Crash Modification Factors (CMFs). The HSM defines a CMF as “the ratio between the number of crashes per unit of time expected after a modification or measure is implemented and the number of crashes per unit of time estimated if the change does not take place”. In other words, the change in expected crash frequency due to a countermeasure. The success of applying methods such as the cross-sectional, and before-after analyses to estimate CMFs is highly dependent on the size of the data available. Significant challenges are present when evaluating the safety performance of improvements with limited crash data. It is generally accepted that a representative sample of locations is needed for a robust crash frequency safety analysis, but when crash frequency is significantly low, most sites in such a representative sample have zero crashes. Fortunately, probability-based analysis is applicable as long as the dataset contains an appropriate number of sites with and without crashes. Probability-based analysis (otherwise known as risk analysis) is therefore a promising alternative to overcome the issue of limited crash data for safety evaluations. However, it is not completely clear how a safety effect estimated from probability analysis relates to the crash-frequency-based definition of CMF in the HSM. Therefore, it is desirable to determine if reliable CMFs for countermeasures can be estimated using risk analysis in cases where crash data is significantly scarce, and thus non-representative samples are used. This research is important because it will determine if developing reliable CMFs using probability-based analysis is a viable option in situations when crash frequency is very low. The goal is to develop a methodology to obtain reliable CMFs and their standard errors from probability-based safety evaluations. The objectives of this research are; to establish the relationship between the outcomes of frequency-based (FB) and probability-based (PB) safety evaluations; to develop a methodology to construct CMFs from PB safety evaluations; and to test and validate the methodology on one or two real-world datasets.

  • Supplemental Notes:
    • Contract to a Performing Organization has not yet been awarded.


  • English


  • Status: Proposed
  • Funding: $58881
  • Contract Numbers:


  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Start Date: 20170501
  • Expected Completion Date: 20171231
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01634571
  • Record Type: Research project
  • Source Agency: Center for Advancing Transportation Leadership and Safety (ATLAS Center)
  • Contract Numbers: DTRT13-G-UTC54
  • Files: UTC, RiP
  • Created Date: May 5 2017 8:28AM