期刊
ENERGIES
卷 12, 期 7, 页码 -出版社
MDPI
DOI: 10.3390/en12071402
关键词
(DITS)-I-2; data-driven control; multi-agent systems; adaptive cooperative control; queuing strength balance; urban traffic signal timing
资金
- North China University of Technology Scientific Research Foundation
- National Natural Science Foundation of China [61803036]
- Scientific Research Common Program of Beijing Municipal Commission of Education [KM201911232015]
- Supplementary and Supportive Project for Teachers at Beijing Information Science and Technology University [5029011103(5111911129)]
- Service Ability Construction of Science and Technology Innovation - Construction of High-end Disciplines [PXM2019_014212_000020]
Data-driven intelligent transportation systems (D(2)ITSs) 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.
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