Study on Traffic Signal Control Based on Q-Learning

In order to reduce the delay of vehicles passing through junction, the signal timing of agent controlled intersection was optimized by Q-Learning approach. On the basis of fuzzy rule set, the effect of signal control was improved through optimizing the combination of control rules with Q-Learning. The result of simulation illustrates that the signal control method based on Q-Learning is better than fixed-time control, actuated control and signal control based on genetic algorithms. The result of this research indicates that the signal control method based on Q-Learning is adapted to the urban traffic control.