Model Predictive Control for Urban Traffic Signals with Stability Guarantees

Tong Liu, Qichao Wang, Hong Wang, Zhong Ping Jiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Traditional traffic signal control focuses more on the optimization aspects whereas the stability and robustness of the closed-loop system are less studied. This paper aims to establish the stability properties of traffic signal control systems through the analysis of a practical model predictive control (MPC) scheme, which models the traffic network with the conservation of vehicles based on a store-and-forward model and attempts to balance the traffic densities. More precisely, this scheme guarantees the exponential stability of the closed-loop system under state and input constraints when the inflow is feasible and traffic demand can be fully accessed. Practical exponential stability is achieved in case of small uncertain traffic demand by a modification of the previous scheme. Simulation results of a small-scale traffic network validate the theoretical analysis.

Original languageEnglish (US)
Title of host publication2023 SIAM Conference on Control and Its Applications, CT 2023
PublisherSociety for Industrial and Applied Mathematics Publications
Pages64-71
Number of pages8
ISBN (Electronic)9781611977745
StatePublished - 2023
Event2023 SIAM Conference on Control and Its Applications, CT 2023 - Philadelphia, United States
Duration: Jul 24 2023Jul 26 2023

Publication series

Name2023 SIAM Conference on Control and Its Applications, CT 2023

Conference

Conference2023 SIAM Conference on Control and Its Applications, CT 2023
Country/TerritoryUnited States
CityPhiladelphia
Period7/24/237/26/23

ASJC Scopus subject areas

  • Control and Systems Engineering

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