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Title: Model Predictive Control for Urban Traffic Signals with Stability Guarantees
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.  more » « less
Award ID(s):
2210320
NSF-PAR ID:
10513224
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Society for Industrial and Applied Mathematics
Date Published:
Journal Name:
2023 Proceedings of the Conference on Control and its Applications (CT)
Page Range / eLocation ID:
64-71
Subject(s) / Keyword(s):
Model Predictive Control Stability traffic signal control
Format(s):
Medium: X
Location:
Society for Industrial and Applied Mathematics
Sponsoring Org:
National Science Foundation
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