Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing

• Main Authors: Haibo Zhang, Xiaoming Liu, Honghai Ji, Zhongsheng Hou, Lingling Fan
• Format: Article
• Language: English
• Published: MDPI AG 2019-04-01
• Series: Energies
• Subjects: D²ITS; data-driven control; multi-agent systems; adaptive cooperative control; queuing strength balance; urban traffic signal timing
• Online Access: https://www.mdpi.com/1996-1073/12/7/1402
• ISSN: 1996-1073

Data-driven intelligent transportation systems (D²ITSs) have drawn significant attention lately. This work investigates a novel multi-agent-based data-driven distributed adaptive cooperative control (MA-DD-DACC) method for multi-direction queuing strength balance with changeable cycle in urban traffic signal timing. Compared with the conventional signal control strategies, the proposed MA-DD-DACC method combined with an online parameter learning law can be applied for traffic signal control in a distributed manner by merely utilizing the collected I/O traffic queueing length data and network topology of multi-direction signal controllers at a single intersection. A Lyapunov-based stability analysis shows that the proposed approach guarantees uniform ultimate boundedness of the distributed consensus coordinated errors of queuing strength. The numerical and experimental comparison simulations are performed on a VISSIM-VB-MATLAB joint simulation platform to verify the effectiveness of the proposed approach.