• DocumentCode
    1847
  • Title

    Rollover Risk Prediction of Heavy Vehicle Using High-Order Sliding-Mode Observer: Experimental Results

  • Author

    imine, hocine ; Benallegue, A. ; Madani, T. ; Srairi, Salim

  • Author_Institution
    Lab. for Road Oper., Perception, Simulators & Simulations, French Inst. of Sci. & Technol. for Transp., Dev. & Networks, Marne la Vallée, France
  • Volume
    63
  • Issue
    6
  • fYear
    2014
  • fDate
    Jul-14
  • Firstpage
    2533
  • Lastpage
    2543
  • Abstract
    In this paper, an original method about heavy-vehicle rollover risk prediction is presented and validated experimentally. It is based on the calculation of the load transfer ratio (LTR), which depends on the estimated vertical forces using high-order sliding-mode (HOSM) observers. Previously, a tractor model is developed. The validation tests were carried out on an instrumented tractor rolling on the road at various speeds and lane-change maneuvers. Many scenarios have been experienced: driving tests in a straight line, a curve, and a zigzag line, and brake tests to emphasize the rollover phenomenon and its prediction to set off an alarm to the driver. In this paper, the vehicle dynamic parameters (masses, inertia, stiffness, etc.) and the static-force infrastructure characteristics (road profile, radius of curvature, longitudinal and lateral slopes, and skid resistance) are measured or calculated before the tests.
  • Keywords
    braking; mechanical testing; observers; risk analysis; road traffic control; variable structure systems; vehicle dynamics; HOSM observers; LTR; brake tests; curve; driving tests; estimated vertical forces; heavy-vehicle rollover risk prediction; high-order sliding-mode observer; instrumented tractor; lane-change maneuvers; load transfer ratio; rollover phenomenon; static-force infrastructure characteristics; straight line; tractor model; vehicle dynamic parameters; zigzag line; Acceleration; Agricultural machinery; Gravity; Observers; Roads; Vehicles; Wheels; Estimation; Heavy vehicle modeling; Prediction; Rollover; Sliding mode observer; heavy-vehicle modeling; prediction; rollover; sliding-mode observer;
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2013.2292998
  • Filename
    6675869