期刊文献+

基于改进粒子群算法的单交叉口信号配时仿真 被引量:7

Simulation of Signal Timing for Single Intersection Based on Improved-PSO Algorithm
下载PDF
导出
摘要 研究城市交通信号控制系统中的单交叉口优化交通流问题,由于交通流具有非线性和不确定性特点,很难建立精确模型。为解决上述问题,提出把每一相位的排队长度都作为优化的目标,采用多目标信号配时模型以满足不同交通需求,并采用改进粒子群(PSO)算法进行求解。在深入研究分析PSO算法的基础上,引入变异因子和惯性权重自适应策略对该算法进行改进,既发挥了PSO算法随机优化收敛速度快的优点,又克服了算法易陷入局部最优点的缺点,显著提高了优化算法的性能指标。仿真结果验证了方法的有效性和合理性。 With the development of economic and urbanization process,the contradiction between road capacity and traffic demands has become more and more severe.This paper took a single intersection as research object,took queue length of each phase as the optimization objectives,and used multi-objective signal timing model to satisfy diffident traffic demands,and introduced improved-PSO algorithm to solve the problem.On the basis of the research and analysis for PSO,the variability factor and inertia weight self-adaptability strategy were introduced to improve the PSO algorithm.The improved PSO algorithm not only has the advantage of fast convergence speed,but also overcomes the shortcoming of PSO algorithm which easily falls into the local minimums,and improves the performance of optimization greatly.The simulation experiments verify the effectiveness and rationality of the control method.
作者 邢广成 石磊
出处 《计算机仿真》 CSCD 北大核心 2012年第5期348-351,共4页 Computer Simulation
关键词 单交叉口 改进粒子群算法 多目标信号配时 Single intersection Improved-PSO algorithm Multi-objective signal timing
  • 相关文献

参考文献6

  • 1徐建闽,严新平.智能交通技术研究与应用[c].2006第一届智能交通与人工智能学术研究会论文集),广州:华南理工大学出版社.2006-12.
  • 2J Kennedy, R C Eberhart, Y Shi. Swarm intelligence [ M ]. San Francisco: Morgan Kaufmann Publishers, 2001.
  • 3王亚利,王宇平.基于混合的GA-PSO神经网络算法[J].计算机工程与应用,2007,43(2):38-40. 被引量:9
  • 4M Clerc. The swarm and the queen: towards a deterministic and a- daptive particle swarm optimization [ C 1. Proceedings of the 1999Congress on Evolutionary Computation. Washington, USA, 1999:1951-1957.
  • 5丁爱萍.平面交叉口交通信号控制研究[D].上海大学硕士研究生论文.2006—3.
  • 6万伟,陈锋.基于遗传算法的单交叉口信号优化控制[J].计算机工程,2007,33(16):217-219. 被引量:13

二级参考文献18

  • 1高海兵,高亮,周驰,喻道远.基于粒子群优化的神经网络训练算法研究[J].电子学报,2004,32(9):1572-1574. 被引量:93
  • 2Rumelhart D E,Hinton G E,Williams R J.Learning representations by back propagating errors[J].Nature,1986,323(11):533-536.
  • 3Whitley D.Genetic algorithm and neural networks[C]//Winter G,Periaux J,Galan M,et al.Genetic Algorithm Engineering and Computer Science,New York:Wiley,1995:191-201.
  • 4Zhang C,Shao H,Li Y.Particle swarm optimization for evolving artifical Network[C]//IEEE Int Chnf Man,Cyber,2000,4:2487-2490.
  • 5Franchini M.Use of a genetic algorithm combined with a local search method for the automatic calibration of conceptual rainfallrunoff models[J].Hydrological Science Journal,1996,41 (1):21-39.
  • 6Kennedy J,Eberhart R C.Particle swarm optimization[C]//Proceedings of IEEE International Conference on Neutral Networks,Australia.IEEE,1995:1942-1948.
  • 7Yoshida H,Kawata K,Yoshikazu F.A particle swarm optimization for reactive power and voltage control considering voltage security assessment[J].IEEE Transaction on Power System,2000,15(4):1232-1239.
  • 8Eberhart R C,Hu X.Human tremor analysis using particle swarm optimization[C]//IEEE Congress on Evolutionary Computation,Piscataway.NJ:IEEE Service Center,1999:1927-1930.
  • 9Kennedy J,Eberhart R C,Shi Y.Swarm intelligence[M].San Francisco:Morgan Kaufmann Publishers,2001.
  • 10Shi Y,Eberhart R C.A modified swarm optimizer[C]//IEEE International Conference of Evolutionary Computation,An chorage,Alaska,1998.

共引文献21

同被引文献71

  • 1许伦辉,衷路生,徐建闽.基于神经网络的交叉口多相位模糊控制[J].华南理工大学学报(自然科学版),2004,32(6):67-70. 被引量:9
  • 2郑长江,王炜.混合交通流条件下信号交叉口配时优化设计[J].公路交通科技,2005,22(4):116-119. 被引量:23
  • 3臧利林,贾磊,杨立才,林忠琴.基于改进GA的城市交通模糊控制研究[J].系统工程理论与实践,2006,26(10):113-118. 被引量:3
  • 4顾榕,曹立明,王小平.免疫遗传算法在交叉口信号配时优化中的应用[J].同济大学学报(自然科学版),2007,35(2):208-212. 被引量:7
  • 5FABRE M G,PULIDO G T,COELLO C A C.Two Novel Approaches for Many-Objective Optimization[C] // 2010 IEEE Congress on Evolutionary Computation.Barcelona,Spain:IEEE,2010.
  • 6HUANG V I,SUGANTHAN P N,QIN A K.Multi-objective Differential Evolution with External Archive and Harmonic Distance Based Diversity Measure[R].Singapore:Nanyang Technological University,2005.
  • 7Rodrigo C Carlson.Optimal mainstream traffic flow control of large-scale motorway networks[J].Transportation Research Part C,2010,18(2):193-212.
  • 8Al-Kaisy A F,Stewart J A.New approach for developing warrants of protected left-turn phase at signalized intersections[J].Transportation Research Part A:Policy and Practice,2001,35(6):561-574.
  • 9Husch D,Albeck J.Trafficware SYNCHRO 6 user guide[J].Traffic Ware,Albany,California,2004,11:1493-1499.
  • 10KOSCH T,KUL P I,BECHLER M,et al.Communication Architecture for Cooperative Systems in Europe[J].IEEE Communications Magazine,2009,47(5):116-125.

引证文献7

二级引证文献37

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部