Type-2 fuzzy logic based urban traffic management

被引:47
|
作者
Balaji, P. G. [1 ]
Srinivasan, D. [1 ]
机构
[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 119260, Singapore
关键词
Type-2 fuzzy logic; Multi-agent system; PARAMICS; Distributed architecture; Traffic signal control; SIGNAL; SYSTEM; TRANSPORTATION;
D O I
10.1016/j.engappai.2010.08.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a multi-agent system based on type-2 fuzzy decision module for traffic signal control in a complex urban road network. The distributed agent architecture using type-2 fuzzy set based controller was designed for optimizing green time in a traffic signal to reduce the total delay experienced by vehicles. A section of the Central Business District of Singapore simulated using PARAMICS software was used as a test bed for validating the proposed agent architecture for the signal control. The performance of the proposed multi-agent controller was compared with a hybrid neural network based hierarchical multi-agent system (HMS) controller and real-time adaptive traffic controller (GLIDE) currently used in Singapore. The performance metrics used for evaluation were total mean delay experienced by the vehicles to travel from source to destination and the current mean speed of vehicles inside the road network. The proposed multi-agent signal control was found to produce a significant improvement in the traffic conditions of the road network reducing the total travel time experienced by vehicles simulated under dual and multiple peak traffic scenarios. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:12 / 22
页数:11
相关论文
共 50 条
  • [31] Parallel type-2 fuzzy logic co-processors for engine management
    Lynch, Christopher
    Hagras, Hani
    Callaghan, Victor
    [J]. 2007 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-4, 2007, : 905 - 910
  • [32] Design of stable type-2 fuzzy logic controllers based on a fuzzy Lyapunov approach
    Castillo, Oscar
    Cazarez, Nohe
    Melin, Patricia
    [J]. 2006 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5, 2006, : 2331 - +
  • [33] An Adaptive Type-2 Input Based Nonsingleton Type-2 Fuzzy Logic System for Real World Applications
    Sahab, Nazanin
    Hagras, Hani
    [J]. IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011), 2011, : 509 - 516
  • [34] A survey-based type-2 fuzzy logic system for energy management in hybrid electrical vehicles
    Martinez, Javier Solano
    John, Robert I.
    Hissel, Daniel
    Pera, Marie-Cecile
    [J]. INFORMATION SCIENCES, 2012, 190 : 192 - 207
  • [35] Interval type-2 fuzzy logic based radio resource management in multi-radio WSNs
    Peng, Wei
    Chen, Dongyan
    Sun, Wenhui
    Li, Chengdong
    Zhang, Guiqing
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2018, 35 (02) : 2525 - 2536
  • [36] Restricted crossing U-turn traffic control by interval Type-2 fuzzy logic
    Jovanovic, Aleksandar
    Kukic, Katarina
    Stevanovic, Aleksandar
    Teodorovic, Dus an
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2023, 211
  • [37] Type-2 fuzzy logic systems: Type-reduction
    Karnik, NN
    Mendel, JM
    [J]. 1998 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5, 1998, : 2046 - 2051
  • [38] Type-n fuzzy logic - the next level of type-1 and type-2 fuzzy logic
    Maity, Saikat
    Chakraborty, Sanjay
    Pandey, Saroj Kumar
    De, Indrajit
    Nath, Sourasish
    [J]. INTERNATIONAL JOURNAL OF INTELLIGENT ENGINEERING INFORMATICS, 2023, 11 (04) : 353 - 389
  • [39] On the Monotonicity of Interval Type-2 Fuzzy Logic Systems
    Li, Chengdong
    Yi, Jianqiang
    Zhang, Guiqing
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 22 (05) : 1197 - 1212
  • [40] Type-2 Fuzzy Logic Grammars in Language Evolution
    Paulo Alvarado-Magana, Juan
    Rodriguez-Diaz, Antonio
    Castro, Juan R.
    Castillo, Oscar
    [J]. SOFT COMPUTING APPLICATIONS IN OPTIMIZATION, CONTROL, AND RECOGNITION, 2013, 294 : 265 - 286