The train operation scheme is the basis of urban rail transport organization. During peak hours, metro operations are characterized by overcrowded and unevenly distributed passenger demand. In this paper, a short-turning strategy is proposed to optimize train operations in combination with passenger flow variations to address the problem of concentrated traffic congestion on long metro lines. Firstly, an optimization model is developed for minimizing the total passenger waiting for time cost and train operating cost, taking into account the actual passing capacity of the line and the current constraints of train operations. Simultaneously, a genetic algorithm is designed to optimize the locations of the turn-back stations and the optimal ratio of different routings during the morning peak hours. Finally, the validity of the model is verified using Nanning Metro Line 1 as a case study, and the sensitivity of positions of turn-back stations is also analyzed. The results showed that the opening of short-turning routing during peak hours is conducive to accelerating train turnover, reducing the number of vehicles employed, and balancing passenger flow. It saved passenger waiting time by 4% and reduced vehicle kilometers traveled by 7% compared with full-length routing. This strategy improves the uneven spatial load of trains during peak passenger flows and provides theoretical support and technical reference for the optimized travel commissioning of urban rail transit line networks.


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    Title :

    Train Operation Scheme of Short-Turning Routing in Urban Rail Transit Based on Passenger Travel


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    He, Deqiang (author) / He, Yan (author) / Zhang, Lang (author) / Chen, Yanjun (author) / Sun, Zheng (author) / Miao, Jian (author)


    Publication date :

    2023-05-05




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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