With the continuous improvement of people's daily living standard and the acceleration of urbanization, smart city transportation planning and smart city planning have been promoted. Relevant departments are committed to creating a healthy, stable and sustainable urban planning scheme, providing more quality and comprehensive services for people's daily life and social improvement. At present, in the improvement of smart city planning in China, urban transportation planning is a vital foundation to ensure the sound improvement of smart cities, and the transportation planning of smart cities has vital significance for the coordination of smart city planning. In this paper, particle swarm optimization (PSO) algorithm is adopted, and according to the traffic flow message of major road intersections and sections, real-time dynamic prediction is made by appropriate methods, which provides basic basis for travelers to provide the best driving route, balance traffic flow, optimize traffic administration scheme and improve traffic control. From the study in this paper, it is concluded that the algorithm in this paper is effective, and it is suitable to be widely put into practice.


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    Titel :

    Simulation Algorithm of Virtual Reality Urban Road Traffic Flow Based on Particle Swarm Optimization


    Beteiligte:
    Lu, Yingfeng (Autor:in) / Liu, Haiyan (Autor:in)


    Erscheinungsdatum :

    2023-05-01


    Format / Umfang :

    1052381 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch