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Optimal Freeway Ramp Control without Origin-Destination Information

Author

Listed:
  • Lei Zhang
  • David Levinson

    (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)

Abstract

This paper develops an analytical framework for ramp metering, under which various ramp control strategies can be viewed as ramifications of the same most-efficient control logic with different threshold values, control methods, and equity considerations. The most-efficient control logic only meters the entrance ramps nearest critical freeway mainline sections so as to eliminate freeway internal queues, which is derived from a new formulation of the optimal ramp control problem. Instead of assuming the availability of real-time origin-destination information, the new formulation takes advantages of the stability and predictability of off-ramp exit percentages. Those properties of the off-ramp exit percentages are supported by empirical data, and allow us to formulate the optimal ramp control problem as a linear program whose input variables are all directly measurable by detectors in real-time. The solution is also tested on a real-world freeway section in a microscopic traffic simulator for demonstration. Time-dependent origin/destination tables and off-ramp exit percentages are compared as two alternative ways to represent the true real-time demand patterns that are important to freeway ramp metering.

Suggested Citation

  • Lei Zhang & David Levinson, 2004. "Optimal Freeway Ramp Control without Origin-Destination Information," Working Papers 200404, University of Minnesota: Nexus Research Group.
  • Handle: RePEc:nex:wpaper:optimalrampmetering
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    File URL: http://hdl.handle.net/11299/179904
    File Function: First version, 2007
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    Cited by:

    1. Sheu, Jiuh-Biing & Yang, Hai, 2008. "An integrated toll and ramp control methodology for dynamic freeway congestion management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4327-4348.
    2. Wu, Jiaming & Kulcsár, Balázs & Ahn, Soyoung & Qu, Xiaobo, 2020. "Emergency vehicle lane pre-clearing: From microscopic cooperation to routing decision making," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 223-239.
    3. Zheng, Liang & Xue, Xinfeng & Xu, Chengcheng & Ran, Bin, 2019. "A stochastic simulation-based optimization method for equitable and efficient network-wide signal timing under uncertainties," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 287-308.
    4. Zhang, Lei & Levinson, David, 2010. "Ramp metering and freeway bottleneck capacity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(4), pages 218-235, May.
    5. Levinson, David & Zhang, Lei, 2006. "Ramp meters on trial: Evidence from the Twin Cities metering holiday," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(10), pages 810-828, December.
    6. 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.
    7. Kontorinaki, Maria & Karafyllis, Iasson & Papageorgiou, Markos, 2019. "Local and coordinated ramp metering within the unifying framework of an adaptive control scheme," Transportation Research Part A: Policy and Practice, Elsevier, vol. 128(C), pages 89-113.
    8. Daniel Hörcher & Ramandeep Singh & Daniel J. Graham, 2022. "Social distancing in public transport: mobilising new technologies for demand management under the Covid-19 crisis," Transportation, Springer, vol. 49(2), pages 735-764, April.
    9. 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.
    10. Liang Zheng & Ji Bao & Zhen Tan, 2025. "Robust simulation-based optimization for multiobjective problems with constraints," Annals of Operations Research, Springer, vol. 346(2), pages 1897-1927, March.
    11. He, Sheng-Xue, 2016. "Will a higher free-flow speed lead us to a less congested freeway?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 17-38.
    12. Pu Wang & Bin Wang & Rihong Ke & Hu Yang & Shengnan Li & Jianjun Dai, 2024. "Uncovering the Spatiotemporal Patterns of Regional and Local Driver Sources in a Freeway Network," Sustainability, MDPI, vol. 16(8), pages 1-17, April.
    13. Dong, Sheng & Li, Xiaonan & Ding, Wenlong & Chen, Feng & Zhang, Ning, 2024. "A method for estimating vehicle delays at parking lot exits in urban networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 656(C).

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    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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