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Mid-America Transportation Center

Statistical Modeling to Identify Heavy Truck Critical Crash Locations in Kansas

Final Report
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Researchers

  • Principal Investigator: Steven Schrock (schrock@ku.edu (785) 864-3418)
  • Project Status
    Complete
    Sponsors & Partners
  • Kansas Department of Transportation
  • Kansas University Transportation Research Institute
  • About this Project
    Brief Project Description & Background
    A disproportionate number of crashes and fatalities involve heavy trucks, making them a key consideration in any efforts to improve highway safety. The Kansas Department of Transportation (KDOT) has placed transportation safety at the top of their priorities with special emphasis on work zones, heavy vehicles, and other strategic highway safety planning measures. To address transportation safety across the state, safety data analysis must occur wherein models are developed to identify critical locations where crashes are occurring. This data mining includes analysis by route, by vehicle type, by severity and by other factors deemed critical by KDOT employees. The results of the research would be the identification of critical sections across the state where crash frequency exceeds the statistical average and acceptable confidence bands. These locations can then be targeted for safety improvements consistent with the types of crashes occurring therein.
    Research Objective
    Develop a list of locations across the state where crash frequency exceeds the statistical average and acceptable confidence bands in an effort to identify locations for targeted safety improvements. This safety data analysis will include analysis by route, by vehicle type, by severity, and by other factors deemed critical through consultation with KDOT personnel.
    Potential Benefits
    By providing a comprehensive analysis of statewide crash data, locations with a high number of crashes can be identified and local conditions taken into account when making safety improvements.
    Abstract
    Transportation safety has been, and continues to be, a critical component emphasized by the United States Department of Transportation (USDOT). The number of deaths on highways in the United States has remained steady over the past 15 years at approximately 40,000 fatalities per year. Although the total number of fatalities is relatively constant, the fatality rate is dropping due to an increase in the total number of vehicle miles traveled (VMT) in the nation (NHTSA 2009). Transportation funding bills have continually addressed the importance of reducing highway crashes, particularly fatalities, across the nation (USDOT 2009). The Kansas Department of Transportation (KDOT) has also placed transportation safety at the front of their priorities with special emphasis on work zones, heavy vehicles, and other strategic highway safety planning measures. To be able to truly address transportation safety across the state of Kansas, safety data analysis must occur wherein models are developed to identify critical locations where crashes are occurring. This data mining includes analysis by route, by vehicle type, by severity, and by other factors deemed critical by KDOT employees. The results of the research would be to identify critical sections across the state where crash frequency exceeds the statistical average and acceptable confidence bands. These locations can then be targeted for safety improvements consistent with the types of crashes occurring therein.
    Project Amount
    $ 125,876.40