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

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 traff...

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Bibliographic Details
Published in:Energies (Basel) 2019-04, Vol.12 (7), p.1402
Main Authors: Zhang, Haibo, Liu, Xiaoming, Ji, Honghai, Hou, Zhongsheng, Fan, Lingling
Format: Article
Language:English
Subjects:
adaptive cooperative control
Artificial intelligence
Automation
Collaboration
Control systems
Controllers
Cooperative control
D2ITS
data-driven control
Distance learning
Dynamic programming
Fuzzy sets
International conferences
Modular structures
multi-agent systems
Network topologies
Neural networks
Nonlinearity
Optimization
Queues
queuing strength balance
Roads & highways
Sensors
Strength
Supersaturation
Time varying control
Topology
Traffic congestion
Traffic control
Traffic flow
Traffic signals
urban traffic signal timing
Vehicles
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Summary: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.
ISSN:1996-1073
1996-1073
DOI:10.3390/en12071402