• DocumentCode
    635034
  • Title

    Data-based modeling of vehicle collision by LPV-ARMAX model approach

  • Author

    Qiugang Lu ; Pawlus, Witold ; Karimi, Hamid Reza ; Robbersmyr, K.G.

  • Author_Institution
    Dept. of Eng., Univ. of Agder, Grimstad, Norway
  • fYear
    2013
  • fDate
    23-26 June 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Vehicle crash are considered to be events with high complexity from the mathematical points of view. The high experiment cost and huge time-consumption make the establishment of a mathematical model of vehicle crash which can simplify the analysis process in great demand. In this work, we present the application of LPV-ARMAX model to simulate the car-to-pole collision with different initial impact velocities. The parameters of the LPV-ARMAX are assumed to be functions of the initial impact velocities. Instead of establishing a set of LTI models for vehicle crashes with various impact velocities, the LPV-ARMAX model is comparatively simple and applicable to predict the responses of new collision situations different from those used for identification. The comparison between the predicted response and the real test data is conducted, which shows the high fidelity of the LPV-ARMAX model.
  • Keywords
    automobiles; autoregressive moving average processes; collision avoidance; control engineering computing; data models; impact testing; mathematical analysis; road safety; traffic engineering computing; vehicle dynamics; velocity control; LPV-ARMAX model; LPV-ARMAX parameter; car-to-pole collision simulation; collision situations; data-based modeling; impact velocities; mathematical model; vehicle collision; vehicle crash; Acceleration; Autoregressive processes; Data models; Mathematical model; Predictive models; Vehicle crash testing; Vehicles; LPV-ARMAX model; data-based modeling; time series analysis; vehicle crash;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ASCC), 2013 9th Asian
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-1-4673-5767-8
  • Type

    conf

  • DOI
    10.1109/ASCC.2013.6606138
  • Filename
    6606138