Volume 22 Issue 4
Aug.  2022
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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2022  >  22(4): 285-294
ZHANG Song-liang, LI De-wei, YIN Yong-hao. Trip reservation and train operation plan optimization method of urban rail transit under demand responsive mechanism[J]. Journal of Traffic and Transportation Engineering, 2022, 22(4): 285-294. doi: 10.19818/j.cnki.1671-1637.2022.04.022
Citation: ZHANG Song-liang, LI De-wei, YIN Yong-hao. Trip reservation and train operation plan optimization method of urban rail transit under demand responsive mechanism[J]. Journal of Traffic and Transportation Engineering, 2022, 22(4): 285-294. doi: 10.19818/j.cnki.1671-1637.2022.04.022
shu

Trip reservation and train operation plan optimization method of urban rail transit under demand responsive mechanism

doi: 10.19818/j.cnki.1671-1637.2022.04.022
  • 1.

    School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

  • 2.

    Frontiers Science Center for Smart High-Speed Railway System, Beijing Jiaotong University, Beijing 100044, China

  • 3.

    School of Traffic and Transportation Engineering, Central South University, Changsha 410075, Hunan, China

Funds:

National Natural Science Foundation of China 71971019

Fundamental Research Funds for the Central Universities 2020JBZD007

Fundamental Research Funds for the Central Universities 2022JBQY006

Natural Science Foundation of Hunan Province 2022JJ40651

More Information
  • Author Bio:

    ZHANG Song-liang(1997-), male, doctoral student, 21114041@bjtu.edu.cn

    LI De-wei(1982-), male, professor, PhD, lidw@bjtu.edu.cn

  • Received Date: 2022-03-13
    Available Online: 2022-10-08
  • Publish Date: 2022-08-25
    Abstract
  • In rail transit systems, the planning of the supply side conflicts with the time-varying characteristics of the demand side. Therefore, an optimization method of trian operation plan for urban rail transit under a demand responsive mechanism was proposed to coordinate the supply and demand relationship. The optimization method includes two steps: trip reservation and demand response. A collaborative optimization model of demand response and train operation plan was established to minimize passenger trip cost and train operation cost, and the delay cost of passengers due to trip reservation was emphasized. The factors such as train operation, transport capacity, train marshalling and passenger distribution were considered, and an adaptive large-scale neighborhood search algorithm based on passenger priority was designed. It was featured with an outer layer optimizing the train operation plan and an inner layer optimizing the passenger allocation, which realizes the matching between the supply and demand of passenger flows. With Beijing Subway Batong Line as an example, a numerical experiment was carried out on its all-day demand management and transportation organization based on the demand responsive mechanism. The results were analyzed from three aspects including locomotive application, passenger waiting time and load rate distribution. Analysis results show that the optimization method can reduce the number of operation trains by 13.8%, and 29.8% of units can be saved by the multi-group mode, which can effectively reduce the operating miles of trains and cut down corporate expenses. Furthermore, the method can shorten the average passenger waiting time at stations by up to 35.3% while ensuring the basic trip of passengers, and the increase in the proportion of reservations has an obvious effect on the reduction of passenger waiting time. The optimized operation plan can make the train load rate maintain at a set level and effectively reduce personnel density to avoid large-scale gathering of passengers, which is a useful exploration and can effectively prevent and control the pandemic appearing in urban rail transit. 2 tabs, 8 figs, 31 refs.

     

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