To accelerate the convergence speed of iterative learning control in traffic signal control and solve the problem of low utilization of historical information in iterative learning control,a traffic signal control method based on iterative learning control of historical information was proposed.Similar historical data were found from the historical information database using Euclidean distance,and the data were weighted to give greater weights to the data with high similarity.The suitable initial iterative control signal was subsequently calculated based on the signal timing and weights corresponding to the data and applied to PD-type itera-tive learning control.Compared with the PD-type iterative learning control that sets the initial iterative control signal autono-mously,it achieves higher speed to equalize the queue length of each intersection,fully utilizes the green light duration of one cycle,and improves the traffic efficiency of the road network.The effectiveness of the algorithm is verified using simulation ex-periments.
关键词
城市交通/交通信号控制/迭代学习控制/收敛速度/历史信息/欧氏距离/初次迭代控制信号
Key words
urban traffic/traffic signal control/iterative learning control/convergence speed/historical information/Euclidean distance/initial iterative control signal
维普
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