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Optimal freeway ramp control without origin-destination information

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  • Zhang, Lei
  • Levinson, David

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

  • Zhang, Lei & Levinson, David, 2004. "Optimal freeway ramp control without origin-destination information," Transportation Research Part B: Methodological, Elsevier, vol. 38(10), pages 869-887, December.
  • Handle: RePEc:eee:transb:v:38:y:2004:i:10:p:869-887
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    References listed on IDEAS

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    1. Alan L. Erera & Carlos F. Daganzo & David J. Lovell, 2002. "The Access-Control Problem on Capacitated FIFO Networks With Unique O-D Paths is Hard," Operations Research, INFORMS, vol. 50(4), pages 736-743, August.
    2. Bogenberger, Klaus & May, Adolf D., 1999. "Advanced Coordinated Traffic Responsive Ramp Metering Strategies," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3pq977ts, Institute of Transportation Studies, UC Berkeley.
    3. Lei Zhang & David Levinson, 2005. "Balancing Efficiency and Equity of Ramp Meters," Working Papers 200508, University of Minnesota: Nexus Research Group.
    4. Lovell, David J. & Daganzo, Carlos F., 2000. "Access control on networks with unique origin-destination paths," Transportation Research Part B: Methodological, Elsevier, vol. 34(3), pages 185-202, April.
    5. Zhang, H. M. & Recker, W. W., 1999. "On optimal freeway ramp control policies for congested traffic corridors," Transportation Research Part B: Methodological, Elsevier, vol. 33(6), pages 417-436, August.
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    Citations

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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. 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.
    9. 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.

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    JEL classification:

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

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