• DocumentCode
    2608538
  • Title

    Fatigue driving detecting model based on momentum indices and neural-fuzzy approach

  • Author

    Liu, C.L. ; Uang, S.T.

  • Author_Institution
    Vanung Univ., Taoyuan
  • fYear
    2007
  • fDate
    2-4 Dec. 2007
  • Firstpage
    500
  • Lastpage
    504
  • Abstract
    Driver fatigue is recognized as an important factor in road accidents in worldwide. The fatigue-tracking technologies to prevent fatigue-related accidents have been widely discussed in the last decade. There is some evidence to suggest that subjective measures of fatigue do indeed correlate with performance decrements associated with fatigue. However, it is difficult to measure on-line. The study investigated the effect of tendency indices for actual driving performance measuring. A fatigue driving detecting model was proposed based on neural-fuzzy approach integrating driving performance measuring variables and tendency indices. This study has been performed using experimental data coming from 50 drivers. Results show that the model could achieve the same effect as subjective ratings.
  • Keywords
    accident prevention; fuzzy neural nets; mechanical engineering computing; momentum; motorcycles; road accidents; vehicle dynamics; accident prevention; driving performance measurement; fatigue driving detecting model; fatigue-tracking technology; momentum indices; motor vehicles; neural-fuzzy approach; road accident; Alarm systems; Engineering management; Fatigue; Life estimation; Road accidents; Technology management; Vehicle crash testing; Vehicle driving; Vehicle safety; Wheels; Fatigue; momentum indices; neuro-fuzzy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management, 2007 IEEE International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-1529-8
  • Electronic_ISBN
    978-1-4244-1529-8
  • Type

    conf

  • DOI
    10.1109/IEEM.2007.4419240
  • Filename
    4419240