This research sought to identify a process to improve long-range planning prioritization by using forecasted safety metrics in place of the existing Utah Department of Transportation Safety Index—a metric based on historical crash data. The research team developed a Safety Forecast Model using Highway Safety Manual Safety Performance Functions and Crash Modification Factors. The research team obtained existing roadway characteristics that served as inputs for the Safety Forecast Model from uPlan. The research team also collected future condition data—such as forecast volumes and lanes—from the Utah Statewide Travel Model, a travel demand forecasting model. The Safety Forecast Model compared crashes predicted based on the current 2015–2040 UDOT Long-Range Plan (LRP) Build scenario to crashes predicted based on the No-Build scenario. The research team determined, through a case study of 15 LRP widening projects, that the project prioritization ranking changes if the ranking considers future safety impacts rather than relying solely on historical crash data. The research team also determined that the Safety Forecast Model could be used to recommend safety projects and perform systemic safety analyses.


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    DRIVE SAFETY FORECAST FOR FUTURE DRIVES

    UDIPI RAHUL ANANTHA PADMANABHA / YU CHRISTOPHER / WHEELER MAXON REAVE | Europäisches Patentamt | 2021

    Freier Zugriff

    Drive safety forecast for future drives

    UDIPI RAHUL ANANTHA PADMANABHA / YU CHRISTOPHER / WHEELER MAXON REAVE | Europäisches Patentamt | 2023

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    Fuzzy surrogate safety metrics

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    Highway Safety -- A Review and Forecast

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    NASA System Wide Safety (SWS) Project: Safety Metrics Research

    Richard H Mogford / Pam Munro | NTRS | 2018