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Adjoint-Based Optimization on a Network of Discretized Scalar Conservation Laws with Applications to Coordinated Ramp Metering

Author

Listed:
  • Jack Reilly

    (University of California)

  • Samitha Samaranayake

    (University of California)

  • Maria Laura Delle Monache

    (Inria Sophia Antipolis - Méditerranée)

  • Walid Krichene

    (University of California)

  • Paola Goatin

    (Inria Sophia Antipolis - Méditerranée)

  • Alexandre M. Bayen

    (University of California)

Abstract

The adjoint method provides a computationally efficient means of calculating the gradient for applications in constrained optimization. In this article, we consider a network of scalar conservation laws with general topology, whose behavior is modified by a set of control parameters in order to minimize a given objective function. After discretizing the corresponding partial differential equation models via the Godunov scheme, we detail the computation of the gradient of the discretized system with respect to the control parameters and show that the complexity of its computation scales linearly with the number of discrete state variables for networks of small vertex degree. The method is applied to the problem of coordinated ramp metering on freeway networks. Numerical simulations on the I15 freeway in California demonstrate an improvement in performance and running time compared with existing methods. In the context of model predictive control, the algorithm is shown to be robust to noise in the initial data and boundary conditions.

Suggested Citation

  • Jack Reilly & Samitha Samaranayake & Maria Laura Delle Monache & Walid Krichene & Paola Goatin & Alexandre M. Bayen, 2015. "Adjoint-Based Optimization on a Network of Discretized Scalar Conservation Laws with Applications to Coordinated Ramp Metering," Journal of Optimization Theory and Applications, Springer, vol. 167(2), pages 733-760, November.
    • Handle: RePEc:spr:joptap:v:167:y:2015:i:2:d:10.1007_s10957-015-0749-1
    DOI: 10.1007/s10957-015-0749-1
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    References listed on IDEAS

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    1. Samitha Samaranayake & Walid Krichene & Jack Reilly & Maria Laura Delle Monache & Paola Goatin & Alexandre Bayen, 2018. "Discrete-Time System Optimal Dynamic Traffic Assignment (SO-DTA) with Partial Control for Physical Queuing Networks," Transportation Science, INFORMS, vol. 52(4), pages 982-1001, August.

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