Severe injury involvements on arterial roads account for a quarter of the total severe injuries reported statewide. Crash severity analysis was conducted and consisted of six road entity models and twenty crash type models. The data preparation and sampling was successful in allowing a robust dataset. The overall model was a good candidate for the analysis of driver injury severity on high-speed multilane roads. Driver injury severity resulting from angle and left turn crashes were best modeled by separate unsignalized intersection crash analysis. Injury severity from rear-end and fixed object crashes was best modeled by combined analysis of pure segment and unsignalized intersection crashes. The most important contributing factors found in the overall analysis included driver-related variables such as age, gender, seat belt use, at-fault driver, physical defects and speeding. Crash and vehicle-related contributing factors included driver ejection, collision type (harmful event), contributing cause, type of vehicle and off-roadway crash. Multivehicle crashes and interactions with intersection and off road crashes were also significant. The most significant roadway-related variables included speed limit, adt per lane, access class, lane width, roadway curve, sidewalk width, non-high mast lighting density, type of friction course and skid resistance. Two additional models of crashes for urban and rural areas were successfully developed. The land use models goodness of fit was substantially better than any other combination by road entity or the overall model.


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    Title :

    Reducing Fatalities and Severe Injuries on Florida's High-Speed Multi-Lane Arterial Corridors. Part I: Preliminary Severity Analysis of Driver Crash Involvements


    Contributors:
    M. Abdel-Aty (author) / A. Pande (author) / C. Lee (author) / A. Das (author) / A. Nevarez (author)

    Publication date :

    2009


    Size :

    367 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English