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A dynamic cordon pricing scheme combining the Macroscopic Fundamental Diagram and an agent-based traffic model

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  • Zheng, Nan
  • Waraich, Rashid A.
  • Axhausen, Kay W.
  • Geroliminis, Nikolas

Abstract

Pricing is considered an effective management policy to reduce traffic congestion in transportation networks. In this paper we combine a macroscopic model of traffic congestion in urban networks with an agent-based simulator to study congestion pricing schemes. The macroscopic model, which has been tested with real data in previous studies, represents an accurate and robust approach to model the dynamics of congestion. The agent-based simulator can reproduce the complexity of travel behavior in terms of travelers’ choices and heterogeneity. This integrated approach is superior to traditional pricing schemes. On one hand, traffic simulators (including car-following, lane-changing and route choice models) consider travel behavior, i.e. departure time choice, inelastic to the level of congestion. On the other hand, most congestion pricing models utilize supply models insensitive to demand fluctuations and non-stationary conditions. This is not consistent with the physics of traffic and the dynamics of congestion. Furthermore, works that integrate the above features in pricing models are assuming deterministic and homogeneous population characteristics. In this paper, we first demonstrate by case studies in Zurich urban road network, that the output of a agent-based simulator is consistent with the physics of traffic flow dynamics, as defined by a Macroscopic Fundamental Diagram (MFD). We then develop and apply a dynamic cordon-based congestion pricing scheme, in which tolls are controlled by an MFD. And we investigate the effectiveness of the proposed pricing scheme. Results show that by applying such a congestion pricing, (i) the savings of travel time at both aggregated and disaggregated level outweigh the costs of tolling, (ii) the congestion inside the cordon area is eased while no extra congestion is generated in the neighbor area outside the cordon, (iii) tolling has stronger impact on leisure-related activities than on work-related activities, as fewer agents who perform work-related activities changed their time plans. Future work can apply the same methodology to other network-based pricing schemes, such as area-based or distance-traveled-based pricing. Equity issues can be investigated more carefully, if provided with data such as income of agents. Value-of-time-dependent pricing schemes then can also be determined.

Suggested Citation

  • Zheng, Nan & Waraich, Rashid A. & Axhausen, Kay W. & Geroliminis, Nikolas, 2012. "A dynamic cordon pricing scheme combining the Macroscopic Fundamental Diagram and an agent-based traffic model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1291-1303.
  • Handle: RePEc:eee:transa:v:46:y:2012:i:8:p:1291-1303 DOI: 10.1016/j.tra.2012.05.006
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Daganzo, Carlos F & Lehe, Lewis J, 2014. "Distance-dependent Congestion Pricing for Downtown Zones," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt9vz1b9rs, Institute of Transportation Studies, UC Berkeley.
    2. Gayah, Vikash V. & Gao, Xueyu (Shirley) & Nagle, Andrew S., 2014. "On the impacts of locally adaptive signal control on urban network stability and the Macroscopic Fundamental Diagram," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 255-268.
    3. Gonzales, Eric J., 2016. "Demand responsive transit systems with time-dependent demand: User equilibrium, system optimum, and management strategyAuthor-Name: Amirgholy, Mahyar," Transportation Research Part B: Methodological, Elsevier, vol. 92(PB), pages 234-252.
    4. Daganzo, Carlos F. & Lehe, Lewis J., 2015. "Distance-dependent congestion pricing for downtown zones," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 89-99.
    5. van den Berg, Vincent A.C., 2014. "Coarse tolling with heterogeneous preferences," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 1-23.
    6. repec:eee:transb:v:100:y:2017:i:c:p:255-283 is not listed on IDEAS
    7. Zheng, Nan & Geroliminis, Nikolas, 2016. "Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 36-58.
    8. Geroliminis, Nikolas, 2015. "Cruising-for-parking in congested cities with an MFD representation," Economics of Transportation, Elsevier, vol. 4(3), pages 156-165.

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