Prediction of the traffic information such as flow, density, speed, and travel time is important for traffic control systems, optimizing vehicle operations, and the individual driver. Prediction of future traffic information is a challenging problem due to many dynamic contributing factors. In this paper, macroscopic and kinetic traffic modeling approaches are investigated. We present a speed prediction algorithm, KTM-SP, based on gas-kinetic traffic modeling. Experimental results show that the proposed algorithm gave good prediction results on real traffic data.


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    Title :

    Real time vehicle speed predition using gas-kinetic traffic modeling


    Contributors:
    Ruoqian Liu, (author) / Shen Xu, (author) / Jungme Park, (author) / Murphey, Y. L. (author) / Kristinsson, J. (author) / McGee, R. (author) / Ming Kuang, (author) / Phillips, T. (author)


    Publication date :

    2011-04-01


    Size :

    368467 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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