Q-learning for intersection traffic flow Control based on agents

  • 주선 (전북대학 전자정보공학과) ;
  • 정길도 (전북대학 전자정보공학과)
  • Published : 2009.05.07

Abstract

In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of multi-agent technology. The structure is composed of sixphase agents and one intersection agent. Wireless communication network provides the possibility of the cooperation of agents. As one kind of reinforcement learning, Q-learning is adopted as the algorithm of the control mechanism, which can acquire optical control strategies from delayed reward; furthermore, we adopt dynamic learning method instead of static method, which is more practical. Simulation result indicates that it is more effective than traditional signal system.

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