摘要
一般模糊控制器控制规则依赖于专家经验,量化因子固定,不能随交通流的变化而动态改变,针对这种情况,提出了基于遗传算法的模糊控制器的优化控制,对模糊控制器所作出的决策进行动态调整,文章介绍了控制过程、染色体的编码及遗传算子的实现方法。以车辆平均延误为目标函数,在模糊控制器作出判决的基础上,对控制规则的调整量进行全局寻优,加快了收敛速度。通过对某一4相位交叉口进行仿真的结果表明,控制效果有明显的改善。
Conventional traffic signal fuzzy control rules depend on experiences. And the quantificational factors can not change dynamically with variety of vehicles. In this paper, an optimized design of traffic signal fuzzy controller based on genetic algorithm is proposed. The output of fuzzy controller is ad）usted dynamically, and the control process, chromosome codes, and genetic operators are introduced. The average delay of vehicles is employed as objective function. The genetic algorithm optimizes the adjustment of fuzzy control rules based on the output of fuzzy controller. This method speeds up the convergence. The computer simulation results show that the effect is improved obviously by a simulation experiment of a four-phase intersection.
出处
《交通与计算机》
2005年第6期95-98,共4页
Computer and Communications
关键词
交叉口
交通控制
模糊控制器
遗传算法
traffic intersection
traffic signal control
fuzzy controller
genetic algorithm
