Development of Crash Prediction Models for Short-Term Durations

Current crash prediction methods—such as those in the AASHTO Highway Safety Manual (HSM)—consist of safety performance functions (SPF), crash modification factors (CMF), and severity distribution functions (SDF). These tools use annual average daily traffic (AADT) data along with geometric and operational characteristics to predict annual average crash frequency of roadway sites. While these models have statistical merit, they do not allow users to accurately predict crashes for variable, short-term periods (e.g., peak periods, special events). This can be an issue for agencies wanting to assess the safety impacts of temporary works zones or time-of-day capacity changes (e.g., lane configuration or speed limit). The existing annual prediction convention also limits the models’ ability to quantify the effects of variables that fluctuate throughout the day (e.g., operating speeds, or operating speed variance). State departments of transportation require the ability to more accurately assess daily or hourly changes that could affect crash outcomes. The objectives of this research were to: (1) develop short-term crash prediction models to estimate the safety performance of roadways. Consideration should be given to specific geometric, operational, and exposure characteristics (e.g., detours, variable speed limits), and routes that experience short-term capacity changes (e.g., hard shoulder running, reversible lanes). (2) Identify explanatory variables measured over short durations. Include more precise measures of exposure other than AADT (e.g., peak hour volume, special event volume), and factors such as speed (including speed variability) to help predict crashes for varied periods of time. (3) Develop an implementation tool suitable for practitioner use.

• Record URL:
  • http://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4780

Language

• English

Project

• Status: Completed
• Funding: $650000
• Contract Numbers:

  Project 22-48

• 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:

  Crichton-Sumners, Camille

• Performing Organizations:

  University of Central Florida, Orlando

  12201 Research Parkway, Suite 501
  Orlando, FL  United States  32826-0150
• Principal Investigators:

  Abdel-Aty, Mohamed

• Start Date: 20200720
• Expected Completion Date: 20230116
• Actual Completion Date: 20230116

Subject/Index Terms

• TRT Terms: Annual average daily traffic; Crash rates; Crash risk forecasting; Highway safety; Methodology; Predictive models; Time periods; Traffic speed
• Subject Areas: Highways; Planning and Forecasting; Safety and Human Factors;

Filing Info

• Accession Number: 01707549
• Record Type: Research project
• Source Agency: Transportation Research Board
• Contract Numbers: Project 22-48
• Files: TRB, RIP
• Created Date: Jun 5 2019 12:55PM