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Analysis of travel cost components using large-scale dynamic traffic models

Author

Listed:
  • A. de Palma
  • F. Marchal
Abstract
This paper extends research in dynamic traffic modeling using METROPOLIS, a dynamic simulation tool. We briefly present an overview of the original departure time choice model introduces by W. Vickrey (1969) for a single O-D pair. Using this framework for our analysis, we explore how the aggregation of the commuters travel cost for large-scale dynamic networks extends the results obtained by Vickrey for the basic-single O-D pair model. The paper provides a test-site application for the network of the city of Geneva and a policy example (extension of staggered hours).
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Suggested Citation

  • A. de Palma & F. Marchal, 1999. "Analysis of travel cost components using large-scale dynamic traffic models," THEMA Working Papers 99-12, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    • Handle: RePEc:ema:worpap:99-12
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    Cited by:

    1. Lindsey, Robin & Daniel, Terry & Gisches, Eyran & Rapoport, Amnon, 2014. "Pre-trip information and route-choice decisions with stochastic travel conditions: Theory," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 187-207.
    2. de Palma, André & Lindsey, Robin, 2020. "Tradable permit schemes for congestible facilities with uncertain supply and demand," Economics of Transportation, Elsevier, vol. 21(C).
    3. A. de Palma & F. Marchal, 2001. "Real Cases Applications of the Fully Dynamic METROPOLIS Tool-Box: an Advocacy for Large-scale Mesoscopic Transportation Systems," THEMA Working Papers 2001-18, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    4. A. de Palma & F. Marchal, 2000. "Dynamic traffic analysis with static data: some guidelines with an application to Paris," THEMA Working Papers 2000-55, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.

    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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