With the acceleration of urbanization, the optimization of public transport systems has become the key to solving urban traffic problems. However, due to the huge road network lines of the public transportation system and the changing road conditions, it is not easy for passengers to find a good public transportation route quickly. In this paper, a bus route generation method based on key road sections is proposed, which mainly focuses on congestion avoidance and route selection efficiency improvement in bus route selection scenarios, and mainly contains three aspects: firstly, the bus route search map is established, and the congestion coefficient is calculated by characterizing the congestion with the speed, so as to achieve the purpose of congestion avoidance; secondly, the neighboring station transfer strategy is proposed to improve the effectiveness of congestion avoidance; finally, the Yen algorithm is combined with the Dijkstra algorithm, and the Dijkstra algorithm is combined with the Dijkstra algorithm. Yen algorithm and Dijkstra algorithm into the bus routing scenario to form a bus route routing algorithm, and use the critical path method to improve the efficiency of the algorithm. The experimental results prove that before and after using the critical path method, the algorithm improves the running time, congestion time, and congestion avoidance; after using the neighboring station transfer strategy, the congestion coefficient is reduced by 12% in the mixed mode of bus and subway, and by 15% in the separate bus mode.


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    Title :

    Public Transport Route Generation Method Based on Critical Path


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yin, Guangqiang (editor) / Liu, Xiaodong (editor) / Su, Jian (editor) / Yang, Yangzhao (editor) / Li, Ye (author) / Yin, Hang (author) / Pu, Yuanyuan (author) / Shang, Xiaolei (author) / Yasen, Kamil (author)

    Conference:

    International Conference on Computer Engineering and Networks ; 2024 ; Kashi, China October 18, 2024 - October 21, 2024



    Publication date :

    2025-05-16


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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