• DocumentCode
    2517089
  • Title

    Risk indicators anticipation based on the vehicle dynamics anticipation to avoid accidents

  • Author

    Ghandour, Raymond ; Victorino, Alessandro ; Charara, Ali ; Lechner, Daniel

  • Author_Institution
    Heudiasyc Lab., Univ. de Technol. de Compiegne, Compiègne, France
  • fYear
    2012
  • fDate
    3-7 June 2012
  • Firstpage
    93
  • Lastpage
    98
  • Abstract
    This article leads to the challenging problem of increasing vehicle driving security by applying on boarded intelligent diagnosis systems; it presents a methodology of evaluating, in an anticipated way, the risk of having an accident (skid and rollover). The methodology consists in adopting assumptions about the trajectory, the longitudinal velocity and the longitudinal acceleration in future instants and use these assumptions, allied to previous road information to calculate the future vehicle dynamics parameters. Once calculated, the risk indicators based on these parameters could be predicted in order to expect and avoid possible dangerous situations. These indicators are the lateral load transfer (LTR) based on vertical forces, and the lateral skid indicator (LSI) based ont the maximum friction coefficient and the used friction coefficient. A sliding window system is used to apply the method on the whole trajectory to take into account the vehicle dynamics updates by the driver.
  • Keywords
    friction; knowledge based systems; risk analysis; road accidents; road safety; traffic engineering computing; vehicle dynamics; LSI; LTR; intelligent diagnosis system; lateral load transfer; lateral skid indicator; longitudinal acceleration; longitudinal velocity; maximum friction coefficient; risk indicator anticipation; road accident; road information; rollover; sliding window system; trajectory; vehicle driving security; vehicle dynamics anticipation; vehicle dynamics parameter; vertical forces; Friction; Large scale integration; Roads; Trajectory; Vehicle dynamics; Vehicles; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium (IV), 2012 IEEE
  • Conference_Location
    Alcala de Henares
  • ISSN
    1931-0587
  • Print_ISBN
    978-1-4673-2119-8
  • Type

    conf

  • DOI
    10.1109/IVS.2012.6232224
  • Filename
    6232224