The goal of this project is to demonstrate the quantitative relationship between weather patterns and surface traffic conditions. The aviation and maritime industries use weather measurements and predictions as a normal part of operations, and this can be extended to surface transportation. While it is generally asserted that there is a causal relationship between weather and transportation system delays, this relationship has not been quantified in a way that allows the effects on surface transportation systems to be predicted. This research has the potential to accomplish two very important things: (1) prediction of non-recurring traffic congestion and (2) prediction of conditions under which incidents or accidents can have a significant impact on the freeway system. This linkage of weather to traffic may be one of the only non-recurring congestion phenomena that can be accurately predicted. If the research is successful, it will create a report that describes an algorithm and implementation to correlate weather and traffic congestion. Furthermore, it may provide a means for traffic management to proactively place resources to clear incidents.


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    Titel :

    Use of Weather Data to Predict Non-Recurring Traffic Congestion


    Beteiligte:
    D. J. Dailey (Autor:in)

    Erscheinungsdatum :

    2006


    Format / Umfang :

    23 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




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