• DocumentCode
    3728259
  • Title

    Design of an Optimal ANFIS Traffic Signal Controller by Using Cuckoo Search for an Isolated Intersection

  • Author

    Sahar Araghi;Abbas Khosravi;Doug Creighton

  • Author_Institution
    Center for Intell. Syst. Res., Deakin Univ., Waurn ponds, VIC, Australia
  • fYear
    2015
  • Firstpage
    2078
  • Lastpage
    2083
  • Abstract
    An optimal design of Adaptive Neuro-Fuzzy Inference System (ANFIS) traffic signal controller is presented in this paper. The proposed controller aims to adjust a set of green times for traffic lights in a single intersection with the purpose of minimizing travel delay time and traffic congestion. The ANFIS controller is trained, to learned how to set green times for each traffic phase. This intelligent controller uses the Cuckoo Search (CS) algorithm to tune its parameters during the learning pried. Evaluating the performance of the proposed controller in comparison with the performance of a FLS controller (FLC) with predefined rules and membership functions, and also three fixed-time controllers, illustrates the better performance of the optimal ANFIS controller against the other benchmark controllers.
  • Keywords
    "Delays","Vehicles","Adaptation models","Genetic algorithms","Detectors","Decision making"
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/SMC.2015.363
  • Filename
    7379495