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Crash prediction methods, which are used to identify crash hotspots or crash severity, consist of safety performance functions (SPFs), crash modification factors, and severity distribution functions. These tools use annual average daily traffic data along with geometric and operational characteristics to predict the annual average crash frequency.

NCHRP Research Report 1073: Development of Crash Prediction Models for Short-Term Durations, from TRB's National Cooperative Highway Research Program, provides roadway safety practitioners within state departments of transportation with short-term crash prediction models to be used for estimating safety performance.

Supplemental to the report are a Training Materials Presentation, a Webinar Presentation, crash-prediction data on Github, and a crash prediction tool and guide at AASHTO.

RESOURCES AT A GLANCE

Suggested Citation

National Academies of Sciences, Engineering, and Medicine. 2023. Development of Crash Prediction Models for Short-Term Durations. Washington, DC: The National Academies Press. https://doi.org/10.17226/27402.

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Publication Info

214 pages |  8.5 x 11 |  Paperback
ISBN: 978-0-309-70917-0
DOI: https://doi.org/10.17226/27402
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