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METROPOLIS2: Bridging Theory and Simulation in Agent-Based Transport Modeling

Author

Listed:
  • Lucas javaudin
  • André de Palma

    (Université de Cergy-Pontoise, THEMA)

Abstract

Transport simulators can be used to compute the equilibrium between transporta- tion demand and supply within complex transportation systems. However, despite their theoretical foundations, there is a lack of comparative analysis between simula- tor results and theoretical models in the literature. In this paper, we bridge this gap by introducing METROPOLIS2, a novel mesoscopic transport simulator capable of simulating agents’ travel decisions (including mode, departure-time, and route choice), based on discrete-choice theory within a dynamic, continuous-time framework. We demonstrate METROPOLIS2’s functionality through its application to the single-road bottleneck model and validate its ability to replicate analytical results. Furthermore, we provide a comprehensive overview of METROPOLIS2 in large-scale scenarios. Fi- nally, we compare METROPOLIS2’s results with those of the original METROPOLIS1 simulator in a simulation of Paris, highlighting its speed and ability to converge to an equilibrium.

Suggested Citation

  • Lucas javaudin & André de Palma, 2024. "METROPOLIS2: Bridging Theory and Simulation in Agent-Based Transport Modeling," THEMA Working Papers 2024-03, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    • Handle: RePEc:ema:worpap:2024-03
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    References listed on IDEAS

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    5. André Palma & Lucas Javaudin & Patrick Stokkink & Léandre Tarpin-Pitre, 2024. "Ride-sharing with inflexible drivers in the Paris metropolitan area," Transportation, Springer, vol. 51(3), pages 963-986, June.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    transport simulation; agent-based modeling; bottleneck; dynamic traffic assignment; discrete-choice models;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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