Development of Crash Prediction Models for Short-Term Durations
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 annual average daily traffic (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.
Language
- English
Project
- Status: Completed
- Funding: $650000
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Contract Numbers:
Project 22-48
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Sponsor Organizations:
National Cooperative Highway Research Program
Transportation Research Board
500 Fifth Street, NW
Washington, DC United States 20001American Association of State Highway and Transportation Officials (AASHTO)
444 North Capitol Street, NW
Washington, DC United States 20001Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC United States 20590 -
Project Managers:
Crichton-Sumners, Camille
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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