交叉口交通信号灯的模糊控制及优化研究  

Research on Fuzzy Control and Optimization for Traffic Lights at Single Intersection

作　　者：刘佳佳[1] 左兴权[2] Liu Jiajia;Zuo Xingquan(Beijing University of Posts and Telecommunications,Beijing 100876,China;Key Laboratory of Trusted Distributed Computing and Services of Ministry of Education,Beijing 100876,China)

机构地区：[1]北京邮电大学,北京100876 [2]可信分布式计算与服务教育部重点实验室,北京100876

出　　处：《系统仿真学报》2020年第12期2401-2408,共8页Journal of System Simulation

基　　金：国家自然科学基金(61873040)。

摘　　要：针对城市单交叉口的交通信号控制问题,提出一种交通灯信号的模糊控制方法。该方法基于四相位定相序对单交叉口交通灯进行控制,模糊控制系统输入为车辆排队数和车辆到达率,输出为当前绿灯相位的绿灯延长时间。利用遗传算法(GeneticAlgorithm,GA)优化模糊控制系统的模糊规则和隶属度函数,提升模糊控制系统性能。利用Sumo(Simulation of Urban Mobility)仿真软件,实现了该模糊控制方法。将Sumo自带的控制方法、模糊控制方法、以及基于GA的模糊控制方法进行仿真对比。结果表明,基于GA的模糊控制方法能有效减少车辆的平均延误时间,提高了交叉口的通行能力。Aiming at the traffic signal control at urban single intersection,a fuzzy control method for traffic lights is presented.The method is based on a four-phase phasing sequence to control the traffic lights at a single intersection.Inputs of the fuzzy controller are the number of vehicles in line and the arrival rate of vehicles,and the output is the green light extension time of the current green light phase.A genetic algorithm(GA)is used to optimize fuzzy rules and membership functions of the fuzzy control system to improve the performance of the fuzzy controller.The fuzzy control method is realized by using Sumo(Simulation of Urban Mobility)simulation software.The Sumo’s own control method,the fuzzy control method,and GA based fuzzy control method are simulated and compared.The results show that the GA based fuzzy control method can effectively reduce the average delay time of vehicles and improve the traffic capacity of the intersection.

关 键 词：交通信号控制 模糊控制 遗传算法 Sumo仿真 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]