IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this article

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

Listed author(s):
  • Zheng, Nan
  • Waraich, Rashid A.
  • Axhausen, Kay W.
  • Geroliminis, Nikolas
Registered author(s):

    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.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 46 (2012)
    Issue (Month): 8 ()
    Pages: 1291-1303

    in new window

    Handle: RePEc:eee:transa:v:46:y:2012:i:8:p:1291-1303
    DOI: 10.1016/j.tra.2012.05.006
    Contact details of provider: Web page:

    Order Information: Postal:

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    in new window

    1. Arnott, R. & de Palma, A. & Lindsey, R., 1990. "Departure time and route choice for the morning commute," Transportation Research Part B: Methodological, Elsevier, vol. 24(3), pages 209-228, June.
    2. Arnott, Richard, 2007. "Congestion tolling with agglomeration externalities," Journal of Urban Economics, Elsevier, vol. 62(2), pages 187-203, September.
    3. Arnott, Richard & Inci, Eren, 2010. "The stability of downtown parking and traffic congestion," Journal of Urban Economics, Elsevier, vol. 68(3), pages 260-276, November.
    4. Lei Zhang & David Levinson, 2005. "Balancing Efficiency and Equity of Ramp Meters," Working Papers 200508, University of Minnesota: Nexus Research Group.
    5. D. Helbing & M. Treiber & A. Kesting & M. Schönhof, 2009. "Theoretical vs. empirical classification and prediction of congested traffic states," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 69(4), pages 583-598, June.
    6. Verhoef, Erik T., 2002. "Second-best congestion pricing in general networks. Heuristic algorithms for finding second-best optimal toll levels and toll points," Transportation Research Part B: Methodological, Elsevier, vol. 36(8), pages 707-729, September.
    7. Yang, Hai & Huang, Hai-Jun, 1998. "Principle of marginal-cost pricing: how does it work in a general road network?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(1), pages 45-54, January.
    8. Daganzo, Carlos F., 2007. "Urban gridlock: Macroscopic modeling and mitigation approaches," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 49-62, January.
    9. Geroliminis, Nikolas & Sun, Jie, 2011. "Properties of a well-defined macroscopic fundamental diagram for urban traffic," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 605-617, March.
    10. May, A. D. & Milne, D. S., 2000. "Effects of alternative road pricing systems on network performance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(6), pages 407-436, August.
    11. Small, Kenneth A. & Yan, Jia, 2001. "The Value of "Value Pricing" of Roads: Second-Best Pricing and Product Differentiation," Journal of Urban Economics, Elsevier, vol. 49(2), pages 310-336, March.
    12. Geroliminis, Nikolas & Daganzo, Carlos F., 2008. "Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 759-770, November.
    13. de Palma, André & Lindsey, Robin, 2006. "Modelling and evaluation of road pricing in Paris," Transport Policy, Elsevier, vol. 13(2), pages 115-126, March.
    14. Vickrey, William S, 1969. "Congestion Theory and Transport Investment," American Economic Review, American Economic Association, vol. 59(2), pages 251-260, May.
    15. Nikolas Geroliminis & David Levinson, 2008. "Cordon pricing consistent with the physics of overcrowding," Working Papers 000038, University of Minnesota: Nexus Research Group.
    16. Axhausen, Kay, 2008. "Accessibility: Long Term Perspectives," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 1(2), pages 5-22.
    17. Lei Zhang & David M. Levinson & Shanjiang Zhu, 2008. "Agent-Based Model of Price Competition, Capacity Choice, and Product Differentiation on Congested Networks," Journal of Transport Economics and Policy, University of Bath, vol. 42(3), pages 435-461, September.
    18. de Palma, André & Kilani, Moez & Lindsey, Robin, 2005. "Congestion pricing on a road network: A study using the dynamic equilibrium simulator METROPOLIS," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 588-611.
    19. Geroliminis, Nikolas & Sun, Jie, 2011. "Hysteresis phenomena of a Macroscopic Fundamental Diagram in freeway networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 966-979, November.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:46:y:2012:i:8:p:1291-1303. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.