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Intermodal Transit System Coordination

Author

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  • Shoaib M. Chowdhury
  • Steven I-Jy Chien

Abstract

In urban areas where transit demand is widely spread, passengers may be served by an intermodal transit system, consisting of a rail transit line (or a bus rapid transit route) and a number of feeder routes connecting at different transfer stations. In such a system, passengers may need one or more transfers to complete their journey. Therefore, scheduling vehicles operating in the system with special attention to reduce transfer time can contribute significantly to service quality improvements. Schedule synchronization may significantly reduce transfer delays at transfer stations where various routes interconnect. Since vehicle arrivals are stochastic, slack time allowances in vehicle schedules may be desirable to reduce the probability of missed connections. An objective total cost function, including supplier and user costs, is formulated for optimizing the coordination of a general intermodal transit network. A four-stage procedure is developed for determining the optimal coordination status among routes at every transfer station. Considering stochastic feeder vehicle arrivals at transfer stations, the slack times of coordinated routes are optimized, by balancing the savings from transfer delays and additional cost from slack delays and operating costs. The model thus developed is used to optimize the coordination of an intermodal transit network, while the impact of a range of factors on coordination (e.g., demand, standard deviation of vehicle arrival times, etc) is examined.

Suggested Citation

  • Shoaib M. Chowdhury & Steven I-Jy Chien, 2002. "Intermodal Transit System Coordination," Transportation Planning and Technology, Taylor & Francis Journals, vol. 25(4), pages 257-287, January.
    • Handle: RePEc:taf:transp:v:25:y:2002:i:4:p:257-287
    DOI: 10.1080/0308106022000019017
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    Cited by:

    1. Liang, Jinpeng & Wu, Jianjun & Qu, Yunchao & Yin, Haodong & Qu, Xiaobo & Gao, Ziyou, 2019. "Robust bus bridging service design under rail transit system disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 132(C), pages 97-116.
    2. Morton O’Kelly, 2010. "Routing Traffic at Hub Facilities," Networks and Spatial Economics, Springer, vol. 10(2), pages 173-191, June.
    3. Bo Sun & Ming Wei & Chunfeng Yang & Zhihuo Xu & Han Wang, 2018. "Personalised and Coordinated Demand-Responsive Feeder Transit Service Design: A Genetic Algorithms Approach," Future Internet, MDPI, vol. 10(7), pages 1-14, July.
    4. Wu, Weitiao & Liu, Ronghui & Jin, Wenzhou & Ma, Changxi, 2019. "Stochastic bus schedule coordination considering demand assignment and rerouting of passengers," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 275-303.
    5. Liang, Jinpeng & Wu, Jianjun & Gao, Ziyou & Sun, Huijun & Yang, Xin & Lo, Hong K., 2019. "Bus transit network design with uncertainties on the basis of a metro network: A two-step model framework," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 115-138.
    6. Xuan Li & Toshiyuki Yamamoto & Tao Yan & Lili Lu & Xiaofei Ye, 2020. "First Train Timetabling for Urban Rail Transit Networks with Maximum Passenger Transfer Satisfaction," Sustainability, MDPI, vol. 12(10), pages 1-22, May.
    7. Kim, Myungseob (Edward) & Schonfeld, Paul, 2014. "Integration of conventional and flexible bus services with timed transfers," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 76-97.
    8. Herbon, Avi & Hadas, Yuval, 2015. "Determining optimal frequency and vehicle capacity for public transit routes: A generalized newsvendor model," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 85-99.
    9. Liu, Tao & Ceder, Avishai (Avi), 2018. "Integrated public transport timetable synchronization and vehicle scheduling with demand assignment: A bi-objective bi-level model using deficit function approach," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 935-955.
    10. Manser, Patrick & Becker, Henrik & Hörl, Sebastian & Axhausen, Kay W., 2020. "Designing a large-scale public transport network using agent-based microsimulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 1-15.
    11. Wu, Weitiao & Liu, Ronghui & Jin, Wenzhou, 2016. "Designing robust schedule coordination scheme for transit networks with safety control margins," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 495-519.
    12. Sun, Yanshuo & Schonfeld, Paul, 2016. "Holding decisions for correlated vehicle arrivals at intermodal freight transfer terminals," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 218-240.
    13. Mohammad Hadi Almasi & Ali Sadollah & Seungmo Kang & Mohamed Rehan Karim, 2016. "Optimization of an Improved Intermodal Transit Model Equipped with Feeder Bus and Railway Systems Using Metaheuristics Approaches," Sustainability, MDPI, vol. 8(6), pages 1-27, June.

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