Optimization of the Suburban Railway Train Operation Plan Based on the Zonal Mode

  • Yongbin Yang China Railway Engineering Design and Consulting Group Co., Ltd., Beijing, China
  • Peng Du Beijing Jiaotong University, Beijing, China
Keywords: suburban railway, centripetal travel, train stop plan, zonal operation mode, integer program

Abstract

Traditional all-stop train operation mode cannot meet the demand of long travel distance and centralized travel of commuters very well. To meet this special travel demand, a zonal train operation mode based on “many-to-many” train stops is proposed. The coefficient of passenger exchange is used to locate suburban areas by depicting travel characteristics of commuters. Operational separating points within the suburban area are used as decision variables to analyze the combined cost components of this model, including passenger travel costs and railway operating costs. An integer programming model with the lowest overall cost is established, and the genetic algorithm is employed to solve it. The results proved good relative benefits in operation costs and travel time. And the sensitivity analysis of both coefficient of passenger exchange and passenger intensity has shown that the zonal operation mode is suitable for suburban railways with centralized travelers. However, the research also shows that when the passenger volume rose to a very high level, the number of zones would be limited by the maximized capacity of railway lines, which may cause the decline of the relative operational efficiency.

References

Qi J, Yang L, Di Z, et al. Integrated optimization for train operation zone and stop plan with passenger distributions. Transportation Research Part E: Logistics and Transportation Review. 2018;109: 151-173.

Yang L, Qi J, Li S, et al. Collaborative optimization for train scheduling and train stop planning on high-speed railways. Omega. 2016;64: 57-76.

Vuchic VR. Urban Transit: Operation, Planning and Economics. New Jersey, USA: John Wiley & Sons, Inc.; 2005.

Shang P, Li R, Yang L. Demand-driven timetable and stop pattern cooperative optimization on an urban rail transit line. Transportation Planning and Technology. 2020;43(1): 78-100.

Yin J, Yang L, Tang T, et al. Dynamic passenger demand-oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches. Transportation Research Part B: Methodological. 2017;97: 182-213.

Xiong Y. Research on the express/slow train of the zonal rail line. Graduate thesis. Southwest Jiaotong University; 2012. p. 32-40.

Gao Y, Yang L, Gao Z. Energy consumption and travel time analysis for metro lines with express/local mode. Transportation Research Part D. 2018;60: 7-27.

Lee E, Lee I, Cho S, et al. A Travel Behavior-Based Skip-Stop Strategy Considering Train Choice Behaviors Based on Smartcard Data. Sustainability. 2019;11(10): 2791.

Luo Q, Hou Y, Li W, et al. Stop Plan of Express and Local Train for Regional Rail Transit Line. Journal of Advanced Transportation. 2018;2018(3): 1-11.

Wang Y, De S, Van D, Ning B. Efficient bi-level approach for urban rail transit operation with stop-skipping. IEEE Transactions on Intelligent Transportation Systems. 2014;15(6): 2658-2670.

Yang A, Huang J, Wang B, et al. Train Scheduling for Minimizing the Total Travel Time with a Skip-stop Operation in Urban Rail Transit. IEEE Access. 2019;99(7): 81956-81968.

Jamili A, Aghaee M. Robust stop-skipping patterns in urban railway operations under traffic alteration situation. Transportation Research Part C: Emerging Technologies. 2015;61: 63-74.

Xu Z. Study on Job-Housing Relationship and Characteristic of Commuting in Shanghai: Based on the Perspective of Rail Transit Passenger Flow Data. Shanghai Urban Planning Review. 2016;(2): 114-121.

Salzborn F. Timetables for a suburban rail transit system. Transportation Science. 1969;3: 279-316.

Wang D, Li B. An Optimization Model of Elevators Group Zoning Dispatching and Its Application. CDEE. 2010;1: 18-21.

Zhang X. Urban rail transit operation management. Beijing: Higher Education Press; 2017.

Ghoneim N, Wirasinghe S. Optimum zone structure during peak periods for existing urban rail lines. Transportation Research Part B: Methodological. 1986;20(1): 7-18.

Ingvardson J, Nielsen O, Raveau S, et al. Passenger arrival and waiting time distributions dependent on train service frequency and station characteristics: A smart card data analysis. Transportation Research Part C: Emerging Technologies. 2018;90: 292-306.

Du P, Yang Y. Optimization of suburban train operation plan in mixed arrival mode. Journal of Transportation Systems Engineering and Information Technology. 2018;18(06): 92-98.

Published
2021-06-04
How to Cite
1.
Yang Y, Du P. Optimization of the Suburban Railway Train Operation Plan Based on the Zonal Mode. Promet [Internet]. 2021Jun.4 [cited 2024Dec.22];33(3):425-36. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/3608
Section
Articles