• DocumentCode
    226860
  • Title

    Fuzzy Adaptive Cruise Control system with speed sign detection capability

  • Author

    Rizvi, Raazi ; Kalra, Sandeep ; Gosalia, Chirag ; Rahnamayan, Shahryar

  • Author_Institution
    Dept. of the Electr., Univ. of Ontario Inst. of Technol., Oshawa, ON, Canada
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    968
  • Lastpage
    976
  • Abstract
    Advanced Driver Assistance System (ADAS) is one of latest innovations in the auto-mobile industry and has become a premium feature in many luxury vehicles. ADAS assists drivers by integrating multiple safety and convenience features into a single system. Current ADAS technology usually comprises of an Adaptive Cruise Control (ACC) system in combination with one or more warning/prevention systems. Such as lane departure, collision avoidance, and parking assist systems. This paper outlines a fuzzy logic based ADAS with integrated speed sign detection (SSD) capability. The described system improves safety of the vehicle by dynamically adjusting the speed of the ACC in accordance with the speed limit of the road. The proposed ADAS system will be helpful in reducing speeding violations and enhancing smoother cruise control in heavy traffic conditions. All system design, implementation and testing was done using the MATLAB development environment, and TORCS virtual car simulator.
  • Keywords
    adaptive control; automobiles; collision avoidance; control engineering computing; digital simulation; driver information systems; fuzzy control; object detection; ACC; MATLAB development environment; SSD; TORCS virtual car simulator; advanced driver assistance system; auto-mobile industry; collision avoidance; cruise control; fuzzy adaptive cruise control system; fuzzy logic based ADAS; heavy traffic conditions; integrated speed sign detection capability; lane departure; luxury vehicles; parking assist systems; speed sign detection capability; speeding violations; warning-prevention systems; Acceleration; Adaptive systems; Artificial neural networks; Fuzzy logic; Roads; Sensors; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-2073-0
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2014.6891748
  • Filename
    6891748