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Multi-agent transit operations and assignment model

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Abstract

Transit systems exercise complex dynamics and evolve through the interaction of various agents. The analysis of transit performance requires emulating the dynamic loading of travellers and their interaction with the underlying transit system. Multi-agent simulations aim to mimic the emergence of global spontaneous order from numerous inter-dependent local decisions. This paper presents a framework for a multi-agent transit operations and assignment model which captures supply uncertainties and adaptive user decisions. An iterative day-to-day learning process consisting of a within-day dynamic network loading loop simulates the interaction between transit supply and demand. The model requires the development and integration of several modules including traffic simulation, transit operations and control, dynamic path choice model and real-time information generator. BusMezzo, a transit simulation model, is used as the platform for implementation.

Suggested Citation

  • Cats, Oded, 2013. "Multi-agent transit operations and assignment model," Working papers in Transport Economics 2013:24, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    • Handle: RePEc:hhs:ctswps:2013_024
    Note: Published in Procedia Computer Science, Vol. 19, 2013, pp 809–814, proceedings from the The 4th International Conference on Ambient Systems, Networks and Technologies (ANT 2013),and the 3rd International Conference on Sustainable Energy Information Technology (SEIT-2013). DOI: 10.1016/j.procs.2013.06.107
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    File URL: http://www.transportportal.se/swopec/CTS2013-24.pdf
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    References listed on IDEAS

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    1. Dominik Grether & Yu Chen & Marcel Rieser & Kai Nagel, 2009. "Effects of a Simple Mode Choice Model in a Large-Scale Agent-Based Transport Simulation," Advances in Spatial Science, in: Aura Reggiani & Peter Nijkamp (ed.), Complexity and Spatial Networks, chapter 0, pages 167-186, Springer.
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    Cited by:

    1. Oded Cats & Zafeira Gkioulou, 2017. "Modeling the impacts of public transport reliability and travel information on passengers’ waiting-time uncertainty," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 247-270, September.
    2. Hörcher, Daniel & Tirachini, Alejandro, 2021. "A review of public transport economics," Economics of Transportation, Elsevier, vol. 25(C).
    3. Cats, Oded & Jenelius, Erik, 2015. "Planning for the unexpected: The value of reserve capacity for public transport network robustness," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 47-61.
    4. Oded Cats & Erik Jenelius, 2014. "Dynamic Vulnerability Analysis of Public Transport Networks: Mitigation Effects of Real-Time Information," Networks and Spatial Economics, Springer, vol. 14(3), pages 435-463, December.
    5. Jesper Bláfoss Ingvardson & Jonas Kornerup Jensen & Otto Anker Nielsen, 2017. "Analysing improvements to on-street public transport systems: a mesoscopic model approach," Public Transport, Springer, vol. 9(1), pages 385-409, July.
    6. 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.
    7. Caterina Malandri & Luca Mantecchini & Filippo Paganelli & Maria Nadia Postorino, 2021. "Public Transport Network Vulnerability and Delay Distribution among Travelers," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    8. Zoi Christoforou & Etienne Corbille & Nadir Farhi & Fabien Leurent, 2016. "Managing planned disruptions of mass transit systems," Post-Print hal-01240155, HAL.
    9. Yu Shen & Jinhua Zhao, 2017. "Capacity constrained accessibility of high-speed rail," Transportation, Springer, vol. 44(2), pages 395-422, March.
    10. Cats, Oded & West, Jens & Eliasson, Jonas, 2015. "Appraisal of increased public transport capacity: the case of a new metro line to Nacka, Sweden," Working papers in Transport Economics 2015:2, CTS - Centre for Transport Studies Stockholm (KTH and VTI).

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    More about this item

    Keywords

    Agent-based Simulation; Public Transport; Assignment; Operations;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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