Distributed Stochastic MPC Traffic Signal Control for Urban Networks

In this paper, the authors design a stochastic model predictive control (MPC)-based traffic signal control method for urban networks when the uncertainties of the traffic model parameters (including the exogenous traffic flows and the turning ratios of downstream traffic flows) are taken into account. Considering that the traffic model parameters are random variables with known expectations and variances, the traffic signal control and coordination problem is formulated as a quadratic program with linear and second-order cone constraints. In order to reduce computational complexity, they suggest a way to decompose the optimization problem corresponding to the whole network into multiple subproblems. By applying an Alternating Direction Method of Multipliers (ADMM) scheme, the optimal stochastic traffic signal splits are found in a distributed manner. The effectiveness of the designed control method is validated via some simulations using VISSIM and MATLAB.

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 01891203
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Aug 28 2023 9:19AM