The present investigation considers deep learning algorithm on urban intelligent transportation to enhance the smart level of urban transportation system. Utilized is a deep learning-based urban intelligent transportation algorithm model, which is generated through comprehensive analysis of principles and characteristics of deep learning algorithms. Of Interests are traffic congestion prediction, traffic signal optimization, intelligent path planning and other functions. Overall, the model show excellent potential for technological advancement through improved effectiveness of urban traffic management verifying both numerically and experimentally.


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    Title :

    An Urban Intelligent Transportation Model Based Deep Learning Algorithm


    Contributors:
    Luo, Xiao (author) / Zheng, Guimei (author)


    Publication date :

    2023-09-08


    Size :

    322969 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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