Intelligent network connection was expected to completely break the existing rules and orders of transportation system. The theoretical peak speed of 5G wireless bandwidth could reach more than 10 Gb per second, which enables cars to exchange information such as location, speed, and destination. It would provide a technical basis for real-time information sharing among vehicles. Based on the formal study of Neural Networks, we added Gaussian noise in the RBM top-level connecting regression, constructing a CDSHybird model that could predict traffic flow in the urban intersections. The results showed that the model proposed in this paper could reflect the movement of vehicles passing through urban intersections in various situations. Further development of interconnection would probably realize the control of traffic flow without a traffic light, which could maximize the efficiency of traffic.


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    Title :

    Impact of Intelligent Networking on Vehicles Exiting at Urban Intersections


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Wang, Wuhong (editor) / Chen, Yanyan (editor) / He, Zhengbing (editor) / Jiang, Xiaobei (editor) / Liu, Jun (author) / Li, Shu-Bin (author)


    Publication date :

    2021-12-14


    Size :

    23 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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