5G智能交通背景下交通信号灯配时优化研究——基于灰色预测模型和遗传算法

Research on Timing Optimization of Traffic Signals in 5G Intelligent Transport System——timing optimization of traffic signals based on grey prediction model and genetic algorithm

交通信号是交通管理的重要部分,其中智能化交通信号配时系统是智能交通系统不可或缺的组成部分。针对交通信号灯配时问题,采用灰色预测模型GM(1,1)和遗传算法的思想,进行信配优化算法的编写,并用MATLAB语言实现。算法以进道口15min流率来计算优化配时,通过遗传算法实现干线交叉口配时的协调。使用VISSIM5.3-03学生版仿真平台进行环境仿真,通过优化前后两组信号配时数据进行仿真模拟,对比前后结果,证明算法的可行性和优越性。

5G has been put into commercial use in 2020.Its characteristics such as fast speed,lowdelay,and high connection density will greatly help the development of intelligent transportation systems.Traffic lights are an important part of traffic management,and intelligent traffic signal timing systems are also a significant part of the intelligent transportation systems.Aiming at solving the traffic signal timing problem,the grey prediction model GM(1,1)and the idea of genetic algorithm were used to compile the algorithm of timing optimization and implemented in MATLAB.The algorithm uses the 15 min flowrate of the entrance to calculate the optimal timing,and the genetic algorithm is used to achieve the coordination of the timing of the main intersection.The environmental simulation platform of VISSIM 5.3-03 student version is used to simulate the environment,and the two sets of time-matching data of the two sets of signals are optimized to simulate the results,which proves the feasibility and superiority of the algorithm.