Adaptive Parameterized Control for Coordinated traffic Management Using Reinforcement Learning

Adaptive Parameterized Control for Coordinated traffic Management Using Reinforcement Learning

Sun, D. (TU Delft Transport and Planning)
Jamshidnejad, A. (TU Delft Control & Simulation)
De Schutter, B.H.K. (TU Delft Delft Center for Systems and Control)

Delft Center for Systems and Control

2023

Traffic control is essential to reduce congestion in both urban and freeway traffic networks. These control measures include ramp metering and variable speed limits for freeways, and traffic signal control for urban traffic. However, current traffic control methods are either too simple to respond to complex traffic environment, or too sophisticated for real-life implementation. In this paper, we propose an adaptive parameterized control method for traffic management by using reinforcement learning algorithms. This method takes advantage of the simple structure of parameterized state-feedback controllers for traffic; meanwhile, a reinforcement learning agent is employed to adjust the parameters of the controllers on-line to react to the varying environment. Therefore, the proposed method requires limited real-time computational efforts, and is adaptive to external disturbances. Furthermore, the reinforcement learning agent can coordinate multiple local traffic controllers when adjusting their parameters. The method is validated by a numerical case study on a freeway network. Results show that the proposed method outperforms conventional controllers when the system is exposed to a changing environment.

Parameterized control
adaptive control
reinforcement learning
coordinated control
traffic network system

http://resolver.tudelft.nl/uuid:5d5621c8-d102-4f74-b41e-efe3507dd769

https://doi.org/10.1016/j.ifacol.2023.10.198

1474-6670

IFAC-PapersOnLine, 56 (2), 5463-5468

22nd IFAC World Congress, 2023-07-09 → 2023-07-14, Yokohama, Japan

Institutional Repository

journal article

© 2023 D. Sun, A. Jamshidnejad, B.H.K. De Schutter