期刊文献+

基于模糊控制的双交叉口相序可变信号配时方法 被引量:3

Study of Variable Phase Sequence Fuzzy Coordinated Control Algorithm on Adjacent Intersections
原文传递
导出
摘要 为优化交叉口信号配时,降低车辆平均延误,提出了一种相序可变的干线双交叉口模糊协调控制方法。提出的模糊协调控制方法包括候选相位选择控制器、绿灯相位观测控制器、相位切换控制器和两个交叉口协调控制模块共五个控制模块。相序可变的干线双交叉口模糊协调控制方法基于对当前上下游交叉口交通紧迫程度的判断,以及对未来交通状态演变的估计,采用相序可变的模糊控制方法实时、动态调整交叉口信号配时方案。利用MATLAB对VISSIM二次开发搭建仿真平台,对所提出的模糊控制方法进行了验证。结果表明,所提出的模糊控制方法在单交叉口和双交叉口两个控制层面均优于传统定时控制方法,可以显著降低车辆平均延误,提高交叉口通行效率。 In order to optimize the signal control of intersections and decrease the average vehicle delay,a variable phase sequence coordinated fuzzy control algorithm on adjacent intersections is proposed.The algorithm included five control modules:Candidate phase choosing controller,greenlight observing controller,phase-switching controller and two intersection-coordinated modules.Based on the current traffic condition of adjacent intersections and prediction of future traffic fluctuation,the proposed algorithm is able to adjust signal control parameters timely and dynamically.Then MATLAB is used for VISSIM secondary development to build a simulation platform to verify this model.The result indicates that the variable phase sequence threestage fuzzy coordinated control algorithm is able to decrease average vehicle delay significantly both on single intersection and adjacent intersections compared with timing control.
作者 乌兰娜仁 罗霞 WU Lannaren;LUO Xia(School of Transportation and Logistics,Southwest Jiaotong University,Chengdu 610031 Sichuan,China;National United Engineering Laboratory of Integrated and Intelligent Transportation,Southwest Jiaotong University,Chengdu 610031 Sichuan,China)
出处 《综合运输》 2019年第7期77-82,共6页 China Transportation Review
基金 四川省科技计划项目(2017JY0072)
关键词 交叉口 信号控制 协调控制 模糊控制 VISSIM二次开发 Intersections Signal control Coordinated control Fuzzy control VISSIM secondary development
  • 相关文献

参考文献4

二级参考文献20

  • 1陈丹,高孝洪,张本.城市道路交叉口交通信号控制系统的发展及现状[J].交通科技,2005,15(6):76-78. 被引量:9
  • 2李水友,刘智勇.城市交通感应控制综述[J].城市交通,2006,4(6):64-69. 被引量:10
  • 3解菲,陈珺.浅析我国城市交通管理与控制[J].中国市场,2007(15):18-19. 被引量:5
  • 4HAWAS Y E. A fuzzy-based system for incident detection in urban street networks[ J]. Trans on Research Part C: Emerging Technologies, 2007,15(2) :69-95.
  • 5PAPPIS C P, MAMDANI E H. A fuzzy logic controller for a traffic junction[J]. IEEE Trans on Systems, Man, and Cybernetics, 1977 ,SMC-7(10) :707-717.
  • 6HSING-HAN L, PAU-LO H. Design and simulation of adaptive fuzzy control on the traffic network[ C ]//Pore of SICE-ICASE International Joint Conference. Korea: [ s. n. ] , 2006:4961-4966.
  • 7NAIR B M, CAI Jin-hai. A fuzzy logic controller for isolated signalized intersection with traffic abnormality considered [ C ]//Proc of IEEE Intelligent Vehicles Symposium. Turkey: IEEE press, 2007: 1229-1233.
  • 8ALCALA R, ALCALA-FDEZ J, HERRERA F, et al. Genetic learning of accurate and compact fuzzy rule based systems based on the 2- tuples linguistic representation [ J ]. International Journal of Approximate Reasoning, 2007,44( 1 ) :45-64.
  • 9CHEN S M, HUANG C M. A new approach to generate weighted fuzzy rules using genetic algorithms for estimating null values[ J]. Expert Systems with Applications, 2007,5 (3) :905- 917.
  • 10BEGUM M, MANN G K, GOSINE R G. Integrated fuzzy logic and genetic algorithmic approach for simultaneous localization and mapping of mobile robots [ J ]. Applied Soft Computing, 2008,8 ( 1 ) : 150- 165.

共引文献23

同被引文献20

引证文献3

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