This research presents a local signal optimization system that integrates a neural network prediction model with a dynamic programming algorithm. With the reliable prediction function, the proposed system can perform real proactive rather than responsive control. Since the developed neural network model is capable of performing a reliable prediction 3-time-steps ahead under various surveillance environments, our proposed integrated control system offers the potential for use in practice. The preliminary results from extensive simulation tests have proved the promising properties of our proposed system.


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    Title :

    An Integrated Model for Adaptive Intersection Signal Control


    Contributors:

    Published in:

    Publication date :

    1996-01-01


    Size :

    24 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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