关键词: 城市交通, 迭代学习, 模糊控制, 数据驱动, 自适应, 交通信号控制

Abstract: Iterative learning control (ILC), as a branch of data-driven control, has obtained plentiful achievements both at theoretical research and practical application over the past two decades. Taking the traffic signal control system as a plant system, the paper introduces the idea of the ILC and fuzzy logic to design an adaptive data-driven traffic signal controller to improve the capacity of the intersection. The key rule of the signal control logic is described by fuzzy iterative theory, and the control strategy can adapt itself to the changing of traffic flow by iterative learning and handle the uncertainty and randomness in traffic system by fuzzy logic, so as to avoid the modeling of complex transport system and take advantages of data-driven on non-model control. Finally, the proposed method is testified to be applicable and effective based on the simulation results by VISSIM. The simulation result indicates that the effect of the proposed method is more effective than the fixed and actuated control approaches.

Key words: urban traffic, iterative learning, fuzzy control, data-driven, adaptive, traffic signal control