In response to the practical difficulties faced by current urban cargo distribution, in order to effectively solve the problems of timeliness, accuracy, and sustainability of cargo distribution, a joint distribution method of trucks and drones is proposed. A mathematical model is established, and a task planning algorithm based on K-means clustering analysis and GA is designed. And a comparison was made in terms of time and travel distance between the joint delivery method of vehicles and drones and three types of goods circulation methods: truck separate delivery, drone separate delivery, and truck drone independent delivery. The results showed that using the joint delivery method of vehicles and drones better reflects transportation advantages and is easier to optimize goals.


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    Titel :

    Research on task planning for truck and drone joint cargo distribution based on K-means cluster analysis and genetic algorithm


    Beteiligte:
    Feng, Zhengang (Herausgeber:in) / Mikusova, Miroslava (Herausgeber:in) / Liu, Shen (Autor:in) / Zeng, Yong (Autor:in) / Xu, Xiaobo (Autor:in) / He, Wenhui (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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