In recent years, with the rapid growth of urban residents' travel demand, especially during rush hours, urban rail transit faces a huge challenge of serious mismatch between transportation capacity and passenger demand. To solve this problem, this paper analyzes the relationship among passenger demand, train timetables and price, tries to adjust the passenger demand distribution using a dynamic pricing strategy, and based on this, constructs a train timetable optimization model with the objective of minimizing the passengers’ waiting time at stations and designs a corresponding genetic algorithm to solve it. The practicality of the model and algorithm is verified by an example. The results of the example prove that the passenger demand during the rush hour decreases significantly based on the dynamic pricing strategy, and the optimized train timetable also adapts to the passenger demand better, effectively shortens the passenger waiting time at the station and relieves the crowded situation of the station during the rush hours.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Train timetable optimization of urban rail transit in rush hours based on the dynamic pricing strategy


    Contributors:
    Zhao, Xiaoli (author) / Li, Dewei (author) / Zhao, Yaqiong (author)

    Conference:

    International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022) ; 2022 ; Lanzhou,China


    Published in:

    Proc. SPIE ; 12340


    Publication date :

    2022-11-21





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Train timetable optimization of urban rail transit in rush hours based on the dynamic pricing strategy

    Zhao, Xiaoli / Li, Dewei / Zhao, Yaqiong | British Library Conference Proceedings | 2022


    Urban rail transit train timetable optimization method and system considering passenger flow distribution

    SUN YUANGUANG / ZHOU WEITENG / YANG RUIXIA et al. | European Patent Office | 2023

    Free access

    Integrated energy‐efficient optimization for urban rail transit timetable

    Lianbo Deng / Ming Chen / Keyi Duan et al. | DOAJ | 2023

    Free access


    Train timetable adjusting method under sudden interruption scene of urban rail transit

    JIA BIN / WANG HUI / LI FENG et al. | European Patent Office | 2023

    Free access