IDEAS home Printed from https://ideas.repec.org/p/cdl/itsrrp/qt85g9p36h.html
   My bibliography  Save this paper

City-wide traffic control: modeling impacts of cordon queues

Author

Listed:
  • Ni, Wei
  • Cassidy, Michael J

Abstract

Optimal cordon-metering rates are obtained using Macroscopic Fundamental Diagrams in combination with flow conservation laws. A model-predictive control algorithm is also used so that time-varying metering rates are generated based on their forecasted impacts. Our scalable algorithm can do this for an arbitrary number of cordoned neighborhoods within a city. Unlike its predecessors, the proposed model accounts for the constraining effects that cordon queues impose on a neighborhood's circulating traffic. It does so at every time step by approximating a neighborhood's street space occupied by cordon queues, and re-scaling the MFD downward to describe the state of circulating traffic that results. The model is also unique in that it differentiates between saturated and under-saturated cordon-metering operations. Computer simulations show that these enhancements can substantially improve the predictions of both, the trip completion rates in a neighborhood and the rates that vehicles cross metered cordons. Optimal metering policies generated as a result are similarly shown to do a better job in reducing the Vehicle Hours Traveled in a city. The VHT reductions stemming from the proposed model and from its predecessors differed by as much as 18%.

Suggested Citation

  • Ni, Wei & Cassidy, Michael J, 2018. "City-wide traffic control: modeling impacts of cordon queues," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt85g9p36h, Institute of Transportation Studies, UC Berkeley.
  • Handle: RePEc:cdl:itsrrp:qt85g9p36h
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/85g9p36h.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ramezani, Mohsen & Haddad, Jack & Geroliminis, Nikolas, 2015. "Dynamics of heterogeneity in urban networks: aggregated traffic modeling and hierarchical control," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 1-19.
    2. Daganzo, Carlos F., 2007. "Urban gridlock: Macroscopic modeling and mitigation approaches," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 49-62, January.
    3. Haddad, Jack, 2017. "Optimal perimeter control synthesis for two urban regions with aggregate boundary queue dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 1-25.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haddad, Jack & Zheng, Zhengfei, 2020. "Adaptive perimeter control for multi-region accumulation-based models with state delays," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 133-153.
    2. Batista, S.F.A. & Leclercq, Ludovic & Geroliminis, Nikolas, 2019. "Estimation of regional trip length distributions for the calibration of the aggregated network traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 192-217.
    3. Yildirimoglu, Mehmet & Sirmatel, Isik Ilber & Geroliminis, Nikolas, 2018. "Hierarchical control of heterogeneous large-scale urban road networks via path assignment and regional route guidance," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 106-123.
    4. Dantsuji, Takao & Takayama, Yuki & Fukuda, Daisuke, 2023. "Perimeter control in a mixed bimodal bathtub model," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 267-291.
    5. Mohajerpoor, Reza & Saberi, Meead & Vu, Hai L. & Garoni, Timothy M. & Ramezani, Mohsen, 2020. "H∞ robust perimeter flow control in urban networks with partial information feedback," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 47-73.
    6. Mariotte, Guilhem & Leclercq, Ludovic & Laval, Jorge A., 2017. "Macroscopic urban dynamics: Analytical and numerical comparisons of existing models," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 245-267.
    7. Zhong, R.X. & Chen, C. & Huang, Y.P. & Sumalee, A. & Lam, W.H.K. & Xu, D.B., 2018. "Robust perimeter control for two urban regions with macroscopic fundamental diagrams: A control-Lyapunov function approach," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 687-707.
    8. Ampountolas, Konstantinos & Zheng, Nan & Geroliminis, Nikolas, 2017. "Macroscopic modelling and robust control of bi-modal multi-region urban road networks," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 616-637.
    9. Ding, Heng & Di, Yunran & Feng, Zhongxiang & Zhang, Weihua & Zheng, Xiaoyan & Yang, Tao, 2022. "A perimeter control method for a congested urban road network with dynamic and variable ranges," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 160-187.
    10. Xu, Guanhao & Gayah, Vikash V., 2023. "Non-unimodal and non-concave relationships in the network Macroscopic Fundamental Diagram caused by hierarchical streets," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 203-227.
    11. Laval, Jorge A. & Aghamohammadi, Rafegh, 2022. "Network-wide Emissions Estimation Using the Macroscopic Fundamental Diagram," Institute of Transportation Studies, Working Paper Series qt8670m9jh, Institute of Transportation Studies, UC Davis.
    12. Zhong, R.X. & Huang, Y.P. & Chen, C. & Lam, W.H.K. & Xu, D.B. & Sumalee, A., 2018. "Boundary conditions and behavior of the macroscopic fundamental diagram based network traffic dynamics: A control systems perspective," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 327-355.
    13. Saeedmanesh, Mohammadreza & Geroliminis, Nikolas, 2017. "Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 193-211.
    14. Paipuri, Mahendra & Leclercq, Ludovic, 2020. "Bi-modal macroscopic traffic dynamics in a single region," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 257-290.
    15. Yang, Lei & Yin, Suwan & Han, Ke & Haddad, Jack & Hu, Minghua, 2017. "Fundamental diagrams of airport surface traffic: Models and applications," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 29-51.
    16. Guo, Qiangqiang & Ban, Xuegang (Jeff), 2020. "Macroscopic fundamental diagram based perimeter control considering dynamic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 87-109.
    17. Haddad, Jack & Mirkin, Boris, 2020. "Resilient perimeter control of macroscopic fundamental diagram networks under cyberattacks," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 44-59.
    18. Su, Z.C. & Chow, Andy H.F. & Fang, C.L. & Liang, E.M. & Zhong, R.X., 2023. "Hierarchical control for stochastic network traffic with reinforcement learning," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 196-216.
    19. Alonso, Borja & Ibeas, Ángel & Musolino, Giuseppe & Rindone, Corrado & Vitetta, Antonino, 2019. "Effects of traffic control regulation on Network Macroscopic Fundamental Diagram: A statistical analysis of real data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 136-151.
    20. Anupriya, & Bansal, Prateek & Graham, Daniel J., 2023. "Congestion in cities: Can road capacity expansions provide a solution?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).

    More about this item

    Keywords

    Engineering; Traffic control; Traffic models; Algorithms; Urban transportation;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:itsrrp:qt85g9p36h. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucbus.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.