基于双向并行灾变粒子群算法的区域交通控制

计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (34): 229-232.

基于双向并行灾变粒子群算法的区域交通控制

王春雷,钱勇生

兰州交通大学交通运输学院，兰州 730070

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-12-01 发布日期:2007-12-01
通讯作者: 王春雷

Urban traffic signal control based on bidirectional parallel catastrophic-particle swarm optimization algorithm

WANG Chun-lei,QIAN Yong-sheng

School of Traffic and Transportation Engineering，Lanzhou Jiaotong University，Lanzhou 730070，China

Received:1900-01-01 Revised:1900-01-01 Online:2007-12-01 Published:2007-12-01
Contact: WANG Chun-lei

摘要/Abstract

摘要： 针对基本粒子群优化算法易陷入局部极值点、搜索精度低等缺点，引入灾变模型，采用双向并行策略，提出一种双向并行灾变粒子群优化算法（BPC-PSO），并将其成功应用于城市区域交通控制信号参数配时优化。仿真结果表明：双向并行灾变粒子群算法相对于基本粒子群算法大大提高了寻找全局最优解的能力，使车辆平均延误和平均停车率都比基本粒子群算法有明显地降低。

关键词: 双向并行灾变粒子群优化算法, 城市区域交通控制, 尖点灾变模型, 信号优化配时, PI值

Abstract: In order to overcome the drawback of basic PSO，such as being subject to falling into local optimization and being poor in performance of precision，a Bidirectional Parallel Catastrophic-Particle Swarm Optimization（BPC-PSO） has been developed through introducing bidirectional parallel tactics and a cusp catastrophic model in panicle swarm optimization algorithm，and the algorithm has been effectively used in dealing with the optimization of signal timing to urban traffic.Simulation data shows that the new method proposed in this paper is feasible and efficient.

Key words: Bidirectional Parallel Catastrophic-Particle Swarm Optimization（BPC-PSO）, urban traffic signal control, cusp catastrophic model, signal timing optimization, PI value

王春雷,钱勇生. 基于双向并行灾变粒子群算法的区域交通控制[J]. 计算机工程与应用, 2007, 43(34): 229-232.

WANG Chun-lei,QIAN Yong-sheng. Urban traffic signal control based on bidirectional parallel catastrophic-particle swarm optimization algorithm[J]. Computer Engineering and Applications, 2007, 43(34): 229-232.