Previous researches have made great efforts on predicting freeway crashes real-timely in advanced traffic management and information systems (ATMIS) environment. However, a comprehensive literature review of crash likelihood prediction model research is lacking. To outline a conceptual framework for developing crash likelihood prediction model using real-time traffic flow variables, this study reviewed the state-of-the-art researches on real-time crash prediction estimation in relation to freeway safety. A systematic literature search was conducted. Researches were summarized and comparatively analyzed from the following four aspects: data sources, the selection of normal and disruptive traffic, the determination of indicator, and the prediction model. It is concluded that traffic flow parameters have a considerable potential for increasing road safety by means of real-time crash risk prediction. The links between traffic flow and real-time crash risk were confirmed. In the end, some suggestions were proposed on development tendency of real-time crash risk prediction model research.


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    Titel :

    Real-Time Crash Prediction Estimation of Freeway Safety: A Review


    Beteiligte:
    Chu, Wenhui (Autor:in) / Zhang, Hui (Autor:in)

    Kongress:

    17th COTA International Conference of Transportation Professionals ; 2017 ; Shanghai, China


    Erschienen in:

    CICTP 2017 ; 4475-4482


    Erscheinungsdatum :

    2018-01-18




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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