基于神经网络模糊控制的单交叉口信号控制

在分析城市交通信号控制研究现状的基础上,提出一种基于神经网络模糊控制的单路口交通信号灯控制方法,通过检测当前相位的排队长度和下一相位的排队长度得出当前相位以及下一相位的车流密度,进而判断是否进行相位变换.以每个周期内交叉口的车辆平均延误作为控制指标,来判断该控制器的控制性能.计算机仿真结果表明,该方法能够降低车辆在交叉路口的平均延误.

Single intersection signal control based on fuzzy neural network control

Based on the analysis of current situation of urban traffic signal control,a method of single intersection signal control was presented based on fuzzy neural network control.Density of vehicle flow of current and next phase was determined by detecting the queue length of the current and next phase,so that it was further determined whether the phase should be changed or not.The average delay of the vehicles passing through the intersection in a period was taken as performance index in order to estimate the p...