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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    Title :

    Use of Weather Data to Predict Non-Recurring Traffic Congestion


    Contributors:

    Publication date :

    2006


    Size :

    23 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




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