• DocumentCode
    3466916
  • Title

    Approaches to control acyclic traffic lights in an exemplary urban road network

  • Author

    Ruchaj, M. ; Stanislawski, Rafal

  • Author_Institution
    Dept. of Electr., Opole Univ. of Technol., Opole, Poland
  • fYear
    2011
  • fDate
    22-25 Aug. 2011
  • Firstpage
    387
  • Lastpage
    392
  • Abstract
    This paper presents a comparison of five algorithms used to control acyclic traffic lights at intersections of roads in an urban road network. The following algorithms are selected: Most Cars characterized by low computational complexity, the author´s algorithm called In-and-Outbound Lane Control, which is an efficient modification of the Most Cars, Local Hill-Climbing algorithm (LHC), the reinforcement learning RL 1 Bucket 2.0 algorithm and the neural network GenNeural algorithm.
  • Keywords
    learning (artificial intelligence); neural nets; road traffic; traffic control; RL 1 Bucket 2.0 algorithm; acyclic traffic light control; computational complexity; in-and-outbound lane control; local hill climbing algorithm; neural network GenNeural algorithm; reinforcement learning; urban road network; Algorithm design and analysis; Green products; Junctions; Learning; Roads; Traffic control; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Methods and Models in Automation and Robotics (MMAR), 2011 16th International Conference on
  • Conference_Location
    Miedzyzdroje
  • Print_ISBN
    978-1-4577-0912-8
  • Type

    conf

  • DOI
    10.1109/MMAR.2011.6031378
  • Filename
    6031378