A variety of scholars have developed the properties of traffic flow jams, while most of the research are limited to the basic assumption of the operating independently for vehicles. In this paper, coupled with the interactive impacts from the surrounding vehicles, the multiple traffic flow model is presented with the aid of neural networks. Through the application of the graph theory and multi-weighted Lyapunov functions, the authors analyze the vehicle synchronized system, and verify the stability condition for the hybrid system. It is proved that the weighted Lyapunov functions are feasible to assess the stability evaluation of the hybrid systems. Also, the expansion of the previous methods is carried out. This work provides a stability guidance of the coupled network system which can be applied in the reality test of the unconstructed and constructed coupled traffic system.


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    Titel :

    Synchronization Analysis of Coupled Network Systems with Multi-Weights Lyapunov Functions in Traffic Flow Networks


    Beteiligte:
    Xu, Mengqing (Autor:in) / Fan, Yingfei (Autor:in)

    Kongress:

    Sixth International Conference on Transportation Engineering ; 2019 ; Chengdu, China


    Erschienen in:

    ICTE 2019 ; 141-150


    Erscheinungsdatum :

    13.01.2020




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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