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Marginal Congestion Cost Pricing in a Multi-agent Simulation Investigation of the Greater Berlin Area

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  • Ihab Kaddoura

Abstract

In this paper, an innovative agent-based marginal congestion cost-pricing approach was applied successfully to the real-world case study of Greater Berlin. To the best of the author's knowledge, the general principles of marginal congestion cost pricing have never been applied to a real-world city model on such a sophisticated level of detail. Link-specific marginal delay costs are computed for each simulated time step at a microscopic, truly agent-based level. The simulation experiments indicate a great potential to reduce congestion by means of intelligent pricing and reconsiderations of route choice decisions. © 2015 LSE and the University of Bath

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  • Ihab Kaddoura, 2015. "Marginal Congestion Cost Pricing in a Multi-agent Simulation Investigation of the Greater Berlin Area," Journal of Transport Economics and Policy, University of Bath, vol. 49(4), pages 560-578, October.
    • Handle: RePEc:tpe:jtecpo:v:49:y:2015:i:4:p:560-578
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    Cited by:

    1. Joseph Molloy & Alberto Castro & Thomas Götschi & Beaumont Schoeman & Christopher Tchervenkov & Uros Tomic & Beat Hintermann & Kay W. Axhausen, 2023. "The MOBIS dataset: a large GPS dataset of mobility behaviour in Switzerland," Transportation, Springer, vol. 50(5), pages 1983-2007, October.
    2. Thi Ngoc Nguyen & Felix Muesgens, 2024. "Fuel tax loss in a world of electric mobility: A window of opportunity for congestion pricing," Papers 2409.20033, arXiv.org.
    3. Ihab Kaddoura & Kai Nagel, 2018. "Simultaneous internalization of traffic congestion and noise exposure costs," Transportation, Springer, vol. 45(5), pages 1579-1600, September.
    4. Kaddoura, Ihab & Bischoff, Joschka & Nagel, Kai, 2020. "Towards welfare optimal operation of innovative mobility concepts: External cost pricing in a world of shared autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 48-63.
    5. Kaddoura, Ihab & Nagel, Kai, 2019. "Congestion pricing in a real-world oriented agent-based simulation context," Research in Transportation Economics, Elsevier, vol. 74(C), pages 40-51.
    6. Maggi,Elena & Vallino,Elena, 2017. "An Agent-Based Simulation of Urban Passenger Mobility and Related Policies. The Case Study of an Italian Small City," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201708, University of Turin.

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