基于改进GA 的城市交通模糊控制研究

提出了基于相序优化的城市交通信号模糊控制算法,并用改进的遗传算法(GA)对模糊控制规则进行优化.以现实中常用的四相位交通信号控制为例,通过研究发现,在不改变原来四相位相序的前提下,通过灵活的相位优化,可以获得更好的控制效果,采用改进的GA对模糊规则进行优化,可以减少因专家经验的主观性而导致的模糊规则的不完备性.以典型的十字路口为对象,选择不同时段的交通流状况进行仿真实验,仿真结果表明,与传统交叉路口信号模糊控制的方法相比,文中提出的控制算法能有效避免交通流不平衡引起的拥挤堵塞,提高系统的实时性和控制精度,从而减少了车辆平均延误时间,是进行城市交通信号自适应控制的一种实用且有效的算法.

Research of Urban Traffic Fuzzy Control Based on Improved GA

The paper presents signal fuzzy control algorithm for urban traffic based on optimization of phases' order and uses improved genetic algorithm(GA) to optimize fuzzy control rules.Take example for four-phase traffic signal control used commonly in real world,research discovers that flexible optimization of phases can acquire better control results under the premise of unchanged old order of four phases,it can reduce the inadequacy of fuzzy control rules brought by the subjectivity of expert's experiences to optimize fuzzy control rules by the improved GA.Compared with traditional signal fuzzy control method for single intersection,the control algorithm presented in the paper can avoid congestion caused by unbalanced traffic flow effectively and improve the real-time character and control precision,so it can reduce the vehicles' average delay time,the proposed algorithm is a practicable and effective algorithm for urban traffic signal self-adaptive control.