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 language | English |
|---|---|
| Title of host publication | 2023 SIAM Conference on Control and Its Applications, CT 2023 |
| Publisher | Society for Industrial and Applied Mathematics Publications |
| Pages | 64-71 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781611977745 |
| State | Published - 2023 |
| Event | 2023 SIAM Conference on Control and Its Applications, CT 2023 - Philadelphia, United States Duration: Jul 24 2023 → Jul 26 2023 |
Publication series
| Name | 2023 SIAM Conference on Control and Its Applications, CT 2023 |
|---|
Conference
| Conference | 2023 SIAM Conference on Control and Its Applications, CT 2023 |
|---|---|
| Country/Territory | United States |
| City | Philadelphia |
| Period | 07/24/23 → 07/26/23 |
Funding
∗This work has been supported in part by the U.S. Department of Energy under Contract DE-AC05-00OR22725 and in part by the National Science Foundation under Grant ECCS-2210320. †Department of Electrical and Computer Engineering, New York University, Brooklyn, NY 11201. Email: [email protected] ‡National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 804011. Email: [email protected] §Oak Ridge National Laboratory, Oak Ridge, TN 37831. Email: [email protected] ¶Department of Electrical and Computer Engineering, New York University, Brooklyn, NY 11201. Email: [email protected]
