Due to the complexity and dynamic nature of urban road networks, it is difficult to directly interpret the relationships between various roads, and the uncertainty of direct connectivity also affects the accuracy of predictions. Existing research still faces challenges in practical applications, especially in large-scale road networks and real-time traffic information requirements, where the speed of intelligent algorithms solving dynamic programming path often fails to meet the urgency of rescue time. Therefore, this paper proposes a multi-factor integrated emergency dispatch model, which considers traffic flow prediction, highway network flow calculation, emergency resources, and time constraints. To solve the speed problem, this paper adopts the ACSPGA improved genetic algorithm, with the aim of improving speed while ensuring solution quality. The experimental results show that the digital twin visual analysis system achieves the effects of traffic congestion recognition, traffic scene simulation, and traffic change comparison, providing decision support for traffic planners.


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    Titel :

    Research on visual application of route planning for emergency rescue vehicles based on digital twin


    Beteiligte:
    Feng, Zhengang (Herausgeber:in) / Mikusova, Miroslava (Herausgeber:in) / Wu, Tieqiang (Autor:in) / Li, Yurong (Autor:in) / Huang, Xu (Autor:in)

    Kongress:

    International Conference on Smart Transportation and City Engineering (STCE 2024) ; 2024 ; Chongqing, China


    Erschienen in:

    Proc. SPIE ; 13575


    Erscheinungsdatum :

    28.04.2025





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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