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Pavement markings and safety.

File Language:
English


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  • Edition:
    Final report.
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  • Abstract:
    Previous research on pavement markings from a safety perspective tackled various issues such as pavement marking retroreflectivity

    variability, relationship between pavement marking retroreflectivity and driver visibility, or pavement marking improvements and

    safety. A recent research interest in this area has been to find a correlation between retroreflectivity and crashes, but a significant

    statistical relationship has not yet been found.

    This study investigates such a possible statistical relationship by analyzing five years of pavement marking retroreflectivity data

    collected by the Iowa Department of Transportation (DOT) on all state primary roads and corresponding crash and traffic data. This

    study developed a spatial-temporal database using measured retroreflectivity data to account for the deterioration of pavement markings

    over time along with statewide crash data to attempt to quantify a relationship between crash occurrence probability and pavement

    marking retroreflectivity.

    First, logistic regression analyses were done for the whole data set to find a statistical relationship between crash occurrence probability

    and identified variables, which are road type, line type, retroreflectivity, and traffic (vehicle miles traveled). The analysis looked into

    subsets of the data set such as road type, retroreflectivity measurement source, high crash routes, retroreflectivity range, and line types.

    Retroreflectivity was found to have a significant effect in crash occurrence probability for four data subsets—interstate, white edge line,

    yellow edge line, and yellow center line data. For white edge line and yellow center line data, crash occurrence probability was found to

    increase by decreasing values of retroreflectivity.

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    urn:sha-512:e33463d5b8f38f5a5cffd165b90bc8471f80f823e7b2d18fc4665d84823c266f3752f09c4c5277f7f865b4f29a6de3e10e64ab2bd0364018f0f9a191d4031f16
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    Filetype[PDF - 1.96 MB ]
File Language:
English
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