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A Modeling Framework for Passenger Assignment on a Transport Network with Timetables

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  • Sang Nguyen

    (Département d'informatique et de recherche opérationnelle and Centre de recherche sur les transports, Université de Montréal, c.p. 6128, succ. centre ville, Montréal, Canada H3C 3J7)

  • Stefano Pallottino

    (Dipartimento di Informatica, Università di Pisa, 40 corso Italia, 56125 Pisa, Italy)

  • Federico Malucelli

    (Dipartimento di Elettronica e Informazione, Politecnico di Milano, P. le L. da Vinci 32, Milano, Italy)

Abstract

This paper presents a new graph theoretic framework for the passenger assignment problem that encompasses simultaneously the departure time and the route choice. The implicit FIFO access to transit lines is taken into account by the concept of available capacity. This notion of flow priority has not been considered explicitly in previous models. A traffic equilibrium model is described and a computational procedure based on asymmetric boarding penalty functions is suggested.

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  • Sang Nguyen & Stefano Pallottino & Federico Malucelli, 2001. "A Modeling Framework for Passenger Assignment on a Transport Network with Timetables," Transportation Science, INFORMS, vol. 35(3), pages 238-249, August.
    • Handle: RePEc:inm:ortrsc:v:35:y:2001:i:3:p:238-249
    DOI: 10.1287/trsc.35.3.238.10152
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    Cited by:

    1. Cats, Oded & Koutsopoulos, Haris N. & Burghout, Wilco & Toledo, Tomer, 2013. "Effect of real-time transit information on dynamic path choice of passengers," Working papers in Transport Economics 2013:28, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    2. Khani, Alireza, 2019. "An online shortest path algorithm for reliable routing in schedule-based transit networks considering transfer failure probability," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 549-564.
    3. Mohamed Wahba & Amer Shalaby, 2011. "Large-scale application of MILATRAS: case study of the Toronto transit network," Transportation, Springer, vol. 38(6), pages 889-908, November.
    4. Yu, Liping & Liu, Huiran & Fang, Zhiming & Ye, Rui & Huang, Zhongyi & You, Yayun, 2023. "A new approach on passenger flow assignment with multi-connected agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    5. Alireza Khani & Mark Hickman & Hyunsoo Noh, 2015. "Trip-Based Path Algorithms Using the Transit Network Hierarchy," Networks and Spatial Economics, Springer, vol. 15(3), pages 635-653, September.
    6. S. Mahmassani, Hani & F. Hyland, Michael, 2016. "Gap-based transit assignment algorithm with vehicle capacity constraints: Simulation-based implementation and large-scale applicationAuthor-Name: Verbas, Ömer," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 1-16.
    7. Guangming Xu & Shuo Zhao & Feng Shi & Feilian Zhang, 2017. "Cell transmission model of dynamic assignment for urban rail transit networks," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-31, November.
    8. Codina, Esteve & Rosell, Francisca, 2017. "A heuristic method for a congested capacitated transit assignment model with strategies," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 293-320.
    9. Peftitsi, Soumela & Jenelius, Erik & Cats, Oded, 2022. "Modeling the effect of real-time crowding information (RTCI) on passenger distribution in trains," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 354-368.
    10. Binder, Stefan & Maknoon, Yousef & Bierlaire, Michel, 2017. "Exogenous priority rules for the capacitated passenger assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 19-42.
    11. Zhaoqi Zang & Xiangdong Xu & Anthony Chen & Chao Yang, 2022. "Modeling the α-max capacity of transportation networks: a single-level mathematical programming formulation," Transportation, Springer, vol. 49(4), pages 1211-1243, August.
    12. Donghyung Yook & Kevin Heaslip, 2015. "The effect of crowding on public transit user travel behavior in a large-scale public transportation system through modeling daily variations," Transportation Planning and Technology, Taylor & Francis Journals, vol. 38(8), pages 935-953, December.
    13. Jiang, Y. & Szeto, W.Y., 2016. "Reliability-based stochastic transit assignment: Formulations and capacity paradox," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 181-206.
    14. Younes Hamdouch & Siriphong Lawphongpanich, 2010. "Congestion Pricing for Schedule-Based Transit Networks," Transportation Science, INFORMS, vol. 44(3), pages 350-366, August.
    15. Shang, Pan & Li, Ruimin & Guo, Jifu & Xian, Kai & Zhou, Xuesong, 2019. "Integrating Lagrangian and Eulerian observations for passenger flow state estimation in an urban rail transit network: A space-time-state hyper network-based assignment approach," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 135-167.
    16. Poon, M. H. & Wong, S. C. & Tong, C. O., 2004. "A dynamic schedule-based model for congested transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 38(4), pages 343-368, May.
    17. Shang, Pan & Xiong, Yufan & Guo, Jifu & Xian, Kai & Yu, Yun & Xu, Han, 2024. "A modeling framework to integrate frequency - and schedule-based passenger assignment approaches for coordinated path choice and space-time trajectory estimation based on multi-source observations," Transportation Research Part B: Methodological, Elsevier, vol. 183(C).
    18. Hamdouch, Younes & Ho, H.W. & Sumalee, Agachai & Wang, Guodong, 2011. "Schedule-based transit assignment model with vehicle capacity and seat availability," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1805-1830.
    19. Liu, Jiangtao & Zhou, Xuesong, 2016. "Capacitated transit service network design with boundedly rational agents," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 225-250.
    20. Hamdouch, Younes & Szeto, W.Y. & Jiang, Y., 2014. "A new schedule-based transit assignment model with travel strategies and supply uncertainties," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 35-67.
    21. Linzhong Liu & Haibo Mu & Juhua Yang, 2017. "Toward algorithms for multi-modal shortest path problem and their extension in urban transit network," Journal of Intelligent Manufacturing, Springer, vol. 28(3), pages 767-781, March.
    22. Mo, Baichuan & Koutsopoulos, Haris N. & Shen, Zuo-Jun Max & Zhao, Jinhua, 2023. "Robust path recommendations during public transit disruptions under demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 169(C), pages 82-107.

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