摘要
由于信号配时方案影响交叉口的通行效率,为改善交叉口的运行现状,构建了以车辆延误、停车次数和延误不均衡度为优化目标的交叉口信号配时优化模型,并以改进人工鱼群算法进行求解。在改进算法中引入衰减函数,获得可变步长和可变视野;在人工鱼移动策略中结合遗传算法的交叉、变异操作,利用云模型生成新的交叉变异概率优化交叉与变异操作。选取重庆市某交叉口作为案例,利用VISSIM软件进行实验仿真,对比分析现状配时方案和优化后的方案对交叉口运行效率的影响。结果表明,应用本文中方法可以使车辆延误、停车次数、排队长度均得到降低,可以有效提升道路交叉口的通行效率。
Due to the impact of signal timing schemes on the traffic efficiency of intersections,in order to improve the operation status of intersections,this paper constructs an intersection signal timing optimization model with the optimization objectives of vehicle delay,number of stops and delay imbalance,and uses an improved artificial fish swarm algorithm to solve the problem.It introduces attenuation functions in the improved algorithm to obtain variable step size and variable field of view.By combining the crossover and mutation operations genetic algorithm in artificial fish movement strategy,a cloud model is used to generate new crossover and mutation probabilities to optimize crossover and mutation operations.Finally,a certain intersection in Chongqing is selected as a case study,and VISSIM software is used for experimental simulation to compare and analyze the impact of the current timing scheme and the optimized scheme on the operational efficiency of the intersection.The results show that the application of this method can reduce vehicle delay,parking times and queue length,effectively improving the traffic efficiency of road intersections.
作者
陈玉如
张容
唐秋生
CHEN Yuru;ZHANG Rong;TANG Qiusheng(College of Traffic and Transportation,Chongqing Jiaotong University,Chongqing 400074,China)
出处
《重庆理工大学学报（自然科学）》
北大核心
2023年第7期25-33,共9页
Journal of Chongqing University of Technology：Natural Science
基金
国家自然科学基金项目(51208538)。
关键词
多目标优化
人工鱼群算法
云遗传算法
信号交叉口配时方案优化
multi-objective optimization
artificial fish swarm algorithm
cloud genetic algorithm
signal intersection timing scheme optimization
