In order to solve the problem that the uncertainty of prediction information in traditional path planning algorithm might easily cause the fluctuation of planned path, the concept of mutual assistance in travel was introduced. A path planning algorithm based on Mutual Assistance Trip (MAP) was proposed for traffic congestion. Based on the proposed MAP system framework, this paper took vehicles participating in MAP as research subjects, a MAP-based path planning objective function with optimal travel time was established. Based on BPR function, a road resistance function with mixed link penalty function is designed by introducing the obedience coefficient μ and the intensity coefficient θ of mutual assistance information. Using the greedy policy and the roulette mechanism, a heuristic path planning algorithm was proposed for the proposed MAP strategy, and the algorithm flow chart was given. The algorithm took the personalized differences of travel into account, and selected the travel direction with historical experience. Based on the analysis, the proposed MAP-based path planning algorithm has better convergence speed and optimization performance. The algorithm can realize the balanced distribution of time and space of road network traffic flow, and improve the overall travel efficiency by 20.79%. According to the sensitivity analysis of MAP characteristic parameters, as μ increases and θ decreases, the proposed path planning algorithm has better guidance performance.


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    Titel :

    A Path Planning Algorithm Based on Mutual Assistance Trip in Traffic Congested Network


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Zhang, Zhenyuan (Herausgeber:in) / Yang, Guojun (Autor:in) / Wang, Jiangfeng (Autor:in) / Zeng, Zhaohui (Autor:in) / Sun, Jianping (Autor:in) / Xian, Kai (Autor:in)

    Kongress:

    International Conference on Intelligent Transportation Engineering ; 2021 ; Beijing, China October 29, 2021 - October 31, 2021



    Erscheinungsdatum :

    2022-06-01


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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