Simulation of a vehicle traffic control network using a fuzzy classifier system

被引:7
|
作者
Clymer, JR [1 ]
机构
[1] Calif State Univ Fullerton, Fullerton, CA 92634 USA
关键词
D O I
10.1109/SIMSYM.2002.1000165
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
A Complex Adaptive System (CAS) is a network of communicating, intelligent agents where each agent adapts its behavior in order to collaborate with other agents to achieve overall system goals. Further, the overall system often exhibits emergent behavior that cannot be achieved by any proper subset of agents alone. A graphical simulation library called Operational Evaluation Modeling for Context-Sensitive Systems (OpEMCSS) has been developed to simulate complex systems, including CAS. This simulation library includes a Classifier Event Action block that is a forward chaining, expert system controller. The Classifier Event Action block can implement both crisp and fuzzy rules. A network of traffic light controller agents, one at each intersection, is simulated for a city traffic grid. Each traffic controller agent uses a fuzzy classifier block to make decisions about traffic light timing in order to minimize local vehicle wait time. Out of the co-evolutionary interaction of these agents, emerges the global minimization of vehicle wait time in the network.
引用
收藏
页码:285 / 291
页数:7
相关论文
共 50 条
  • [1] Simulation of traffic flow system and control using fuzzy logic
    Taskin, H
    Gumustas, R
    [J]. PROCEEDINGS OF THE 1997 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL, 1997, : 325 - 330
  • [2] Simulation of vehicle stability control system using fuzzy PI control method
    De Li, Y
    Liu, W
    Li, J
    Ma, ZM
    Zhang, JC
    [J]. 2005 IEEE International Conference on Vehicular Electronics and Safety Proceedings, 2005, : 165 - 170
  • [3] Design and simulation of adaptive fuzzy control on the traffic network
    Liu, Hsing-Han
    Hsu, Pau-Lo
    [J]. 2006 SICE-ICASE INTERNATIONAL JOINT CONFERENCE, VOLS 1-13, 2006, : 2604 - +
  • [4] An Efficient Technique to Control Road Traffic Using Fuzzy Neural Network System
    Aggarwal, Apoorva
    Purwar, Archana
    Gulati, Shubham
    [J]. 2014 3RD INTERNATIONAL CONFERENCE ON RELIABILITY, INFOCOM TECHNOLOGIES AND OPTIMIZATION (ICRITO) (TRENDS AND FUTURE DIRECTIONS), 2014,
  • [5] Design of a traffic junction controller using classifier system and fuzzy logic
    Cao, YJ
    Ireson, N
    Bull, L
    Miles, R
    [J]. COMPUTATIONAL INTELLIGENCE: THEORY AND APPLICATIONS, 1999, 1625 : 342 - 353
  • [6] Traffic signal control using fuzzy and neural network
    Wei, W
    Wang, MJ
    [J]. 8TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING, VOLS 1-3, PROCEEDING, 2001, : 305 - 310
  • [7] Traffic Sign Recognition System for Autonomous Vehicle Using Cascade SVM Classifier
    Wahyono
    Kurnianggoro, Laksono
    Hariyono, Joko
    Jo, Kang-Hyun
    [J]. IECON 2014 - 40TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2014, : 4081 - 4086
  • [8] Optimization of Urban Vehicle Traffic Using Genetic Fuzzy Logic Control
    Letia, Tiberiu S.
    Hulea, Mihai
    Dinga, Florin
    [J]. PROCEEDINGS OF THE 2ND WSEAS INTERNATIONAL CONFERENCE ON URBAN PLANNING AND TRANSPORTATION: RECENT ADVANCES IN URBAN PLANNING AND TRANSPORTATION, 2009, : 171 - 176
  • [9] A Simulation System and Speed Guidance Algorithms for Intersection Traffic Control Using Connected Vehicle Technology
    Shuai Liu
    Weitong Zhang
    Xiaojun Wu
    Shuo Feng
    Xin Pei
    Danya Yao
    [J]. Tsinghua Science and Technology, 2019, 24 (02) : 160 - 170
  • [10] A Simulation System and Speed Guidance Algorithms for Intersection Traffic Control Using Connected Vehicle Technology
    Liu, Shuai
    Zhang, Weitong
    Wu, Xiaojun
    Feng, Shuo
    Pei, Xin
    Yao, Danya
    [J]. TSINGHUA SCIENCE AND TECHNOLOGY, 2019, 24 (02) : 160 - 170