An Adjoint State Method for Numerical Approximation of Continuous Traffic Congestion Equilibria

被引:7
作者
Luo, Songting [1 ]
Leung, Shingyu [2 ]
Qian, Jianliang [1 ]
机构
[1] Michigan State Univ, Dept Math, E Lansing, MI 48824 USA
[2] Hong Kong Univ Sci & Technol, Dept Math, Hong Kong, Hong Kong, Peoples R China
基金
美国国家科学基金会;
关键词
Traffic congestion; adjoint state method; gradient descent; fast sweeping method; factored eikonal equation; HAMILTON-JACOBI EQUATIONS; FAST SWEEPING METHOD; VISCOSITY SOLUTIONS; EIKONAL EQUATIONS; CONVERGENCE; COST;
D O I
10.4208/cicp.020210.311210a
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The equilibrium metric for minimizing a continuous congested traffic model is the solution of a variational problem involving geodesic distances. The continuous equilibrium metric and its associated variational problem are closely related to the classical discrete Wardrop's equilibrium. We propose an adjoint state method to numerically approximate continuous traffic congestion equilibria through the continuous formulation. The method formally derives an adjoint state equation to compute the gradient descent direction so as to minimize a nonlinear functional involving the equilibrium metric and the resulting geodesic distances. The geodesic distance needed for the state equation is computed by solving a factored eikonal equation, and the adjoint state equation is solved by a fast sweeping method. Numerical examples demonstrate that the proposed adjoint state method produces desired equilibrium metrics and out-performs the subgradient marching method for computing such equilibrium metrics.
引用
收藏
页码:1113 / 1131
页数:19
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