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Convexity and robustness of dynamic traffic assignment and freeway network control

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  • Como, Giacomo
  • Lovisari, Enrico
  • Savla, Ketan

Abstract

We study the use of the System Optimum (SO) Dynamic Traffic Assignment (DTA) problem to design optimal traffic flow controls for freeway networks as modeled by the Cell Transmission Model, using variable speed limit, ramp metering, and routing. We consider two optimal control problems: the DTA problem, where turning ratios are part of the control inputs, and the Freeway Network Control (FNC), where turning ratios are instead assigned exogenous parameters. It is known that relaxation of the supply and demand constraints in the cell-based formulations of the DTA problem results in a linear program. However, solutions to the relaxed problem can be infeasible with respect to traffic dynamics. Previous work has shown that such solutions can be made feasible by proper choice of ramp metering and variable speed limit control for specific traffic networks. We extend this procedure to arbitrary networks and provide insight into the structure and robustness of the proposed optimal controllers. For a network consisting only of ordinary, merge, and diverge junctions, where the cells have linear demand functions and affine supply functions with identical slopes, and the cost is the total traffic volume, we show, using the Pontryagin maximum principle, that variable speed limits are not needed in order to achieve optimality in the FNC problem, and ramp metering is sufficient. We also prove bounds on perturbation of the controlled system trajectory in terms of perturbations in initial traffic volume and exogenous inflows. These bounds, which leverage monotonicity properties of the controlled trajectory, are shown to be in close agreement with numerical simulation results.

Suggested Citation

  • Como, Giacomo & Lovisari, Enrico & Savla, Ketan, 2016. "Convexity and robustness of dynamic traffic assignment and freeway network control," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 446-465.
  • Handle: RePEc:eee:transb:v:91:y:2016:i:c:p:446-465
    DOI: 10.1016/j.trb.2016.06.007
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    References listed on IDEAS

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    Cited by:

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    2. 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.
    3. Schmitt, Marius & Lygeros, John, 2018. "An exact convex relaxation of the freeway network control problem with controlled merging junctions," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 1-25.
    4. Krešimir Kušić & Edouard Ivanjko & Filip Vrbanić & Martin Gregurić & Ivana Dusparic, 2021. "Spatial-Temporal Traffic Flow Control on Motorways Using Distributed Multi-Agent Reinforcement Learning," Mathematics, MDPI, vol. 9(23), pages 1-28, November.
    5. Schmitt, Marius & Lygeros, John, 2020. "On convexity of the robust freeway network control problem in the presence of prediction and model uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 167-190.

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