The purpose of this article is to present insights into the relationship between complex traffic flow phenomena on urban motorways and crash risk. Unstable or congested flow can trigger low speed/high density clusters (e.g. nucleations or shockwaves) creating ‘surprise elements’, therefore sharply increasing the cognitive workload for motorists. When combined with reduced road space and freedom to perform needed manoeuvres (e.g. lane changes), conditions can exceed the physical or mental capability and hence increase the likelihood of human error. There is overwhelming evidence that high traffic density drastically increases the crash risk. Some density concentrations can be avoided through appropriate planning and real-time traffic control, resulting in a reduction in crashes. Modern measurement devices allow for the analysis of individual vehicle behaviours such as ‘Brake’, ‘Speed alert’ or ‘Lane change’ events and show promise in providing robust data to further exploring what makes dense traffic complex. This allows establishing relationships between “events as elementary units of exposure” and crash occurrence resulting in a new way of understanding crash rates. These relationships are important to predict crashes, identify high-risk locations, and establish suitable measures for crash reduction.


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    Titel :

    Towards linking driving complexity to crash risk


    Beteiligte:
    Hendrik Zurlinden (Autor:in) / Anita Baruah (Autor:in) / John Gaffney (Autor:in)


    Erscheinungsdatum :

    2020




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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