Travel time is one of the most desired variables for Advanced Traveler Information Systems (ATIS). Travel time prediction on urban traffic network, however, is a very challenging issue due to the nature of interrupted flows as well as the randomness of vehicle arrivals. Therefore, most online ATIS provide no information on urban street travel time despite the needs of travelers. Most existing travel time prediction algorithms were designed specifically for freeway applications. With the increasing deployment of traffic detectors and the growing availability of traffic signal event data on urban traffic network, predicting urban arterial travel time becomes feasible. In this research, an arterial travel time prediction algorithm will be developed and implemented in an interactive online platform based on Google Map. The proposed algorithm uses both historical and real-time traffic and signal control data as inputs.


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    Title :

    Real-Time Travel Time Prediction on Urban Traffic Network


    Contributors:
    Y. Wagt (author) / Y. J. Wu (author) / X. Ma (author) / J. Corey (author)

    Publication date :

    2010


    Size :

    80 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




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