Highlights Procedure for the identification of hazardous road locations is proposed. Only two sets of data are necessary to complete the analysis. Our approach can be used in cases where there are no values of AADT for a road.

    Abstract This paper proposes a procedure which evaluates clusters of traffic accident and organizes them according to their significance. The standard kernel density estimation was extended by statistical significance testing of the resulting clusters of the traffic accidents. This allowed us to identify the most important clusters within each section. They represent places where the kernel density function exceeds the significance level corresponding to the 95th percentile level, which is estimated using the Monte Carlo simulations. To show only the most important clusters within a set of sections, we introduced the cluster strength and cluster stability evaluation procedures. The method was applied in the Southern Moravia Region of the Czech Republic.


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    Title :

    Identification of hazardous road locations of traffic accidents by means of kernel density estimation and cluster significance evaluation


    Contributors:

    Published in:

    Publication date :

    2013-03-03


    Size :

    9 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English