This study is intended to focus on the major factors affecting traffic crash rates and severity levels, in addition to identifying crash-prone locations (i.e., black spots) based on the two indicators. The available crash data for different road segments used for the analysis were obtained from the Washington state database provided by the Highway Safety Information System (HSIS) for the years 2006 to 2011. A Random Forest (RF) classifier was used to predict the outcome level of crash severity, while crash rates were predicted by applying RF regressor. Certain features were selected for each model besides the abstraction of new features to check if there are unobserved correlations affecting the independent variables, such as accounting for the number and weight of crashes within 1 km2 area by implementing the Getis-Ord Gi∗ index. Moreover, to calculate the collective risk (CR) score, crash rates were adjusted to incorporate crash severity weights (cost per severity type) and regression-to-the-mean (RTM) bias via Empirical Bayes (EB) method. Finally, segments were ranked according to their CR score.


    Access

    Download


    Export, share and cite



    Title :

    Collective Risk Ranking of Highway Segments on the Basis of Severity-Weighted Crash Rates


    Contributors:


    Publication date :

    2020




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Alternative Crash Severity Ranking Measures and the Implications on Crash Severity Ranking Results

    Campbell, J. R. / Knapp, K. K. / Institute of Transportation Engineers | British Library Conference Proceedings | 2006


    Identifying High Crash Risk Highway Segments Using Jerk-Cluster Analysis

    Mousavi, Seyedeh Maryam / Zhang, Zhao / Parr, Scott A. et al. | TIBKAT | 2019


    Identifying High Crash Risk Highway Segments Using Jerk-Cluster Analysis

    Mousavi, Seyedeh Maryam / Zhang, Zhao / Parr, Scott A. et al. | ASCE | 2019



    Highway Work Zone Risk Factors and Their Impact on Crash Severity

    Li, Y. / Bai, Y. | British Library Online Contents | 2009