Traffic safety is one of the most important goals for roadway design and traffic system operations. Collision hotspot identification serves as a major fundamental component for traffic safety performance measurements. With identified collision hotspots, limited resources can be better allocated to improve roadway safety. There has been a significant amount of studies on collision hotspots identification over the past decades. However, most studies only considered crash counts as the sole roadway safety performance indicator. In this study, a new cluster-based method is proposed to quantify roadway safety conditions. This method is able to incorporate more heterogeneous safety-related factors for clustering, such as crash fatality, injuries, and average collision duration. Compared with the prevailing Empirical Bayes methods, our cluster-based method demonstrates its improved accuracy and efficiency, and can be easily implemented in practice.


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    Title :

    Developing a Cluster-Based Algorithm for Collision Hotspot Identification


    Contributors:
    Bi, Chaofan (author) / Ma, Xiaolei (author) / Zhang, Yingying (author) / Wang, Yinhai (author)

    Conference:

    14th COTA International Conference of Transportation Professionals ; 2014 ; Changsha, China


    Published in:

    CICTP 2014 ; 2381-2395


    Publication date :

    2014-06-24




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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