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Analysis of FARS data on state highways in Oklahoma.

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  • Abstract:
    Analysis of fatality automobile accident data can be challenging in rural areas where a relatively small number of

    such accidents occurs on specific sections of highways. Combining crash data for 1998 to 2011 from the Fatality

    Analysis Reporting System (FARS) and highway networks and design specifications from the Oklahoma

    Department of Transportation (ODOT), this project employs Poisson regression analysis to determine what

    roadway characteristics (e.g., grade, geometry, and design) are most associated with fatal crashes on

    predominantly rural segments of highways in Oklahoma.

    A state-wide model found that median width and type, terrain type, surface type and thickness, grade, and outside

    shoulder width were all significant predictors of fatality crashes. Vertical grade was the most significant variable in

    the state model, with uphill grades contributing to significantly more fatal crashes while flat roads modestly reduce

    the risk. Terrain type was also very significant, both flat and rolling terrain categories having higher contributions to

    fatality crash rates than baseline levels in residential areas. Outside shoulder width significantly negatively

    correlated with fatalities, as wider shoulders mean more room for drivers to recover or at least shed speed.

    Median width was also significant with the expected negative sign as wider medians result in fewer fatalities.

    Surprisingly, median type was only moderately significant, though as expected most other median types did

    contribute to higher crash rates compared to cable barriers.

    The results provide information about what combinations of highway design traits have contributed most to past

    crashes and therefore can identify potentially dangerous road segments system-wide. This information will help

    transportation engineers evaluate current construction practice and seek ways to address design issues that are

    shown to contribute significantly to serious crashes.

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    urn:sha256:56c47e8ee19faafbedd68d039bf0f61e82106d70b77a818f53aaed76561758bf
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File Language:
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