IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v38y2004i3p251-270.html
   My bibliography  Save this article

A flow-maximizing adaptive local ramp metering strategy

Author

Listed:
  • Smaragdis, Emmanouil
  • Papageorgiou, Markos
  • Kosmatopoulos, Elias

Abstract

An extension of the feedback local ramp metering strategy ALINEA is proposed that allows the automatic tracking of the critical occupancy to help maximize the mainstream flow. The developed AD-ALINEA strategy may be valuable whenever the critical occupancy cannot be estimated beforehand or is subject to real-time change due to changing environmental conditions or traffic composition (e.g. trucks). An upstream-measurement based version of the adaptive strategy (AU-ALINEA) is also developed. Both strategies are successfully tested in a stochastic macroscopic simulation environment under various scenarios.

Suggested Citation

  • Smaragdis, Emmanouil & Papageorgiou, Markos & Kosmatopoulos, Elias, 2004. "A flow-maximizing adaptive local ramp metering strategy," Transportation Research Part B: Methodological, Elsevier, vol. 38(3), pages 251-270, March.
    • Handle: RePEc:eee:transb:v:38:y:2004:i:3:p:251-270
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(03)00012-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shengnan Li & Hu Yang & Minglun Li & Jianjun Dai & Pu Wang, 2023. "A Highway On-Ramp Control Approach Integrating Percolation Bottleneck Analysis and Vehicle Source Identification," Sustainability, MDPI, vol. 15(16), pages 1-15, August.
    2. Reilly, Jack & Martin, Sébastien & Payer, Mathias & Bayen, Alexandre M., 2016. "Creating complex congestion patterns via multi-objective optimal freeway traffic control with application to cyber-security," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 366-382.
    3. Michael L. Anderson & Lucas W. Davis, 2018. "Two Empirical Tests of Hypercongestion," NBER Working Papers 24469, National Bureau of Economic Research, Inc.
    4. Schmitt, Marius & Ramesh, Chithrupa & Lygeros, John, 2017. "Sufficient optimality conditions for distributed, non-predictive ramp metering in the monotonic cell transmission model," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 401-422.
    5. Čičić, Mladen & Johansson, Karl Henrik, 2022. "Front-tracking transition system model for traffic state reconstruction, model learning, and control with application to stop-and-go wave dissipation," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 212-236.
    6. Sheu, Jiuh-Biing, 2007. "Stochastic modeling of the dynamics of incident-induced lane traffic states for incident-responsive local ramp control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 365-380.
    7. van Erp, Paul B.C. & Knoop, Victor L. & Hoogendoorn, Serge P., 2018. "Macroscopic traffic state estimation using relative flows from stationary and moving observers," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 281-299.
    8. Jovanović, Aleksandar & Kukić, Katarina & Stevanović, Aleksandar, 2021. "A fuzzy logic simulation model for controlling an oversaturated diverge diamond interchange and ramp metering system," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 165-181.
    9. Rudjanakanoknad, Jittichai, 2005. "Increasing Freeway Merge Capacity Through On-Ramp Metering," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3js9x18d, Institute of Transportation Studies, UC Berkeley.
    10. Changle Sun & Hongyan Gao, 2019. "Traffic Model and On-Ramp Metering Strategy under Foggy Weather Conditions Using T-S Fuzzy Systems," Complexity, Hindawi, vol. 2019, pages 1-12, December.
    11. Anupriya & Daniel J. Graham & Daniel Horcher & Prateek Bansal, 2021. "Revisiting the empirical fundamental relationship of traffic flow for highways using a causal econometric approach," Papers 2104.02399, arXiv.org.

    More about this item

    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:eee:transb:v:38:y:2004:i:3:p:251-270. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    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.