ICEC '05 Proceedings of the 7th international conference on Electronic commerce
Urban Trunk Road Traffic Signal Coordinated Control Based on Multi-Objective Immune Algorithm
CAR '09 Proceedings of the 2009 International Asia Conference on Informatics in Control, Automation and Robotics
Agent-based architecture for designing hybrid control systems
Information Sciences: an International Journal
A novel self-tuning feedback controller for active queue management supporting TCP flows
Information Sciences: an International Journal
A review of the applications of agent technology in traffic and transportation systems
IEEE Transactions on Intelligent Transportation Systems
Type-2 fuzzy logic based urban traffic management
Engineering Applications of Artificial Intelligence
Multi-agent system in urban traffic signal control
IEEE Computational Intelligence Magazine
An automated signalized junction controller that learns strategies from a human expert
Engineering Applications of Artificial Intelligence
Study of traffic flow controlled with independent agent-based traffic signals
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part II
ACM SIGAPP Applied Computing Review
An ontology-based semantic service for cooperative urban equipments
Journal of Network and Computer Applications
A market-inspired approach for intersection management in urban road traffic networks
Journal of Artificial Intelligence Research
Engineering Applications of Artificial Intelligence
Engineering e-Collaboration Services with a Multi-Agent System Approach
International Journal of Systems and Service-Oriented Engineering
A Hybrid Cooperative Behavior Learning Method for a Rule-Based Shout-Ahead Architecture
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Expert Systems with Applications: An International Journal
Holonic multi-agent system for traffic signals control
Engineering Applications of Artificial Intelligence
Hierarchical control of traffic signals using Q-learning with tile coding
Applied Intelligence
Hi-index | 0.00 |
This paper presents a new hybrid, synergistic approach in applying computational intelligence concepts to implement a cooperative, hierarchical, multiagent system for real-time traffic signal control of a complex traffic network. The large-scale traffic signal control problem is divided into various subproblems, and each subproblem is handled by an intelligent agent with a fuzzy neural decision-making module. The decisions made by lower-level agents are mediated by their respective higher-level agents. Through adopting a cooperative distributed problem solving approach, coordinated control by the agents is achieved. In order for the multiagent architecture to adapt itself continuously to the dynamically changing problem domain, a multistage online learning process for each agent is implemented involving reinforcement learning, learning rate and weight adjustment as well as dynamic update of fuzzy relations using an evolutionary algorithm. The test bed used for this research is a section of the Central Business District of Singapore. The performance of the proposed multiagent architecture is evaluated against the set of signal plans used by the current real-time adaptive traffic control system. The multiagent architecture produces significant improvements in the conditions of the traffic network, reducing the total mean delay by 40% and total vehicle stoppage time by 50%.