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A flow-maximizing adaptive local ramp metering strategy

Author

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  • 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
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    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. Pengsen Yang & Minghui Ma & Chaoteng Wu, 2024. "Ecologically Oriented Freeway Control Methods Integrated Speed Limits and Ramp Toll Booths Layout," Sustainability, MDPI, vol. 16(11), pages 1-14, May.
    12. 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.

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