基于GA的多相位交通信号模糊控制器优化方法

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,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了全局寻优,加快了收敛速度.通过对一个四相位交叉口进行仿真,结果表明控制效果有明显的改善.

Optimized Method of Multiphase Traffic Signal Fuzzy Controller Based on Genetic Algorithm

Conventional traffic signal fuzzy control rules depend on experience,and the quantificational factors can not be changed dynamically with variety of vehicles.In this paper,the optimized designation of traffic signal fuzzy controller based on genetic algorithm is proposed,the output of fuzzy controller is adjusted dynamically,and the control process,chromosome codes,genetic operators are introduced.The average delay of vehicles is employed as objective function,the genetic algorithm optimizes the adjustion of fuzzy control rules based on the output of fuzzy controller,and 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.