基于云遗传算法的信号交叉口相序相位优化  

Optimization of signal sequence phase sequence based on cloud genetic algorithm

作　　者：唐秋生[1] 张笑语 TANG Qiusheng;ZHANG Xiaoyu(College of Transportation,Chongqing Jiaotong University,Chongqing 400041,China)

机构地区：[1]重庆交通大学交通运输学院,重庆400041

出　　处：《交通科技与经济》2021年第1期19-25,共7页Technology & Economy in Areas of Communications

基　　金：国家自然科学基金资助项目(51508061)。

摘　　要：交叉口是影响通行效率的关键场所,为更好地提高路网通行能力,提出利用云遗传算法对信号控制交叉口的相序相位及信号配时组成方案进行优化。首先,运用MATLAB构造出交叉口的相序相位优化模型;其次,利用云模型改进的遗传算法计算得到最小总延误,同时输出最小总延误下的配时方案;最后,将得出的结果与现状和传统遗传算法得出的信号配时方案进行对比验证,并运用VISSIM对3种信号配时方案进行仿真验证。结果表明,云遗传算法得出的优化方案能更好地减小交叉口延误,提高交叉口通行效率。Intersection is a key place that affects traffic efficiency.In order to improve the road network capacity,a cloud genetic algorithm is proposed to optimize the phase sequence phase and signal timing scheme of signal control intersections.Firstly,MATLAB is used to construct the phase sequence phase optimization model of the intersection;secondly,the genetic algorithm improved by the cloud model is used to calculate the minimum total delay;at the same time,the timing scheme under the minimum total delay is output;finally,the result obtained is compared and verified with the current situation and the signal timing schemes obtained by traditional genetic algorithms.VISSIM is used to simulate and verify the three signal timing schemes.The result shows that the optimized solution obtained by cloud genetic algorithm can better reduce the delay of the intersection and improve the traffic efficiency of the intersection.

关 键 词：相序相位优化 信号配时方案 云遗传算法 信号交叉口 交叉口延误 

分 类 号：U491.54[交通运输工程—交通运输规划与管理]