• DocumentCode
    2580067
  • Title

    Developing adaptive driving route guidance systems based on fuzzy neural network

  • Author

    Lin, I-Cheng ; Chou, Shuo-Yan ; Hsu, Hsin-Yin

  • Author_Institution
    TFT-LCD Manuf. Div., Production Planning Dept., TFT BU, Taipei, Taiwan
  • fYear
    2009
  • fDate
    11-14 Oct. 2009
  • Firstpage
    4293
  • Lastpage
    4298
  • Abstract
    This paper proposes a route guidance system which can be moldable by drivers based on using fuzzy neural network. The self-learning system has become a hot issue in the field of Driving Route Guidance. However, most of the researches didn´t pay attention to the relationship between the route choice and the driver´s vague perception. Even though with the same starting and destination points, different drivers typically do not go through the same path as they make choices of routes based on different attributes and weighting of the attributes. The adaptive-network-based fuzzy inference system (ANFIS) is used to learn the decision logic with vague attributes from the past driving records of the drivers to make the guidance system adaptive. By integrating this intelligent adaptive capability, a driving route guidance system should be able to adapt to driver´s behavior in generating routes teller-made for individual drivers.
  • Keywords
    adaptive systems; fuzzy neural nets; road traffic; unsupervised learning; adaptive network based fuzzy inference system; decision logic; drivers vague perception; fuzzy neural network; past driving records; route guidance systems; routes teller made; self learning system; Adaptive control; Adaptive systems; Cybernetics; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Production planning; Shortest path problem; Thin film transistors; USA Councils; ANFIS; TSK inference system; fuzzy inference system; intelligent adaptive system; route choice criteria; route guidance system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • ISSN
    1062-922X
  • Print_ISBN
    978-1-4244-2793-2
  • Electronic_ISBN
    1062-922X
  • Type

    conf

  • DOI
    10.1109/ICSMC.2009.5346804
  • Filename
    5346804