With the continuous growth of market demand and express delivery business, logistics enterprises must build a more intelligent logistics system. This article adopted a deep learning based AI (Artificial Intelligence) method to plan the route of automobiles. The optimization module of the automobile logistics transportation path planning system can continuously adjust the results of path planning based on real-time data and actual needs, thereby improving transportation efficiency and reducing costs. On this basis, this article studied the trajectory planning results of deep learning based trajectory planning algorithms and traditional algorithms under different load conditions. Method 3 (medium load+traditional method) Path length: 12km, transportation time: 20min; Method 4 (medium load+deep learning method) Path length: 11 km, transportation time: 17 minutes. In view of an AI based automotive logistics transportation path planning system, This article’ system is beneficial for improving logistics transportation speed and shortening logistics transportation time.


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    Title :

    Automotive Logistics Transportation Path Planning System on Basis of Artificial Intelligence


    Contributors:
    Yu, Qianying (author) / Xiang, Chengjiu (author) / Su, Li (author)


    Publication date :

    2024-10-18


    Size :

    137379 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English