摘要
根据我国城市交通的特点,提出一种基于三群协同粒子群优化算法的城市区域交通自适应协调控制方法。采用两层递阶分布式结构,分阶段优化控制参数(周期、相位差和绿信比),每个阶段长10-3O分钟,周期、相位差由区域控制级每阶段优化一次,绿信比由交叉口控制级每周期优化一次。采用车辆延误为性能指标,周期、相位差和绿信比均采用三群协同粒子群算法进行优化。仿真结果表明该方法是可行而有效的。
A Three Swarms Cooperative-Particle Swarm Optimization algorithm （TSC-PSO） based adaptive control method for urban traffic network signal is proposed.A two-level hierarchical distributed construction is adopted.The parameters are optimized hierarchically with an interval of 10-30 minutes.Cycle and offsets are optimized by central controller in each interval and splits are optimized by intersection controller in each cycle.For a given performance index,such as minimizing the mean vehicle delay and number of stops etc.TSC-PSO is used to optimize the cycle,offsets and splits.Simulation results show that the new method proposed in this paper is feasible and efficient.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第14期187-189,共3页
Computer Engineering and Applications
基金
教育部博士学科科研基金(No.20050732002)项目
甘肃省2006科技攻关计划项目(No.2GS064-A52-037)
关键词
城市区域交通控制
三群协同粒子群优化算法
信号优化配时
车辆延误
urban traffic signal control
Three Swarms Cooperative-Particle Swarm Optimization（TSC-PSO）
signal timing opti- mization
average delay per vehicle
