• DocumentCode
    3737521
  • Title

    Model predictive cooperative cruise control in mixed traffic

  • Author

    Hyuntai Chin;Hiroyuki Okuda;Yuichi Tazaki;Tatsuya Suzuki

  • Author_Institution
    Graduate School of Engineering Department of Mechanical Science and Engineering, Nagoya University, Furo-cho, Nagoya, Aichi, Japan
  • fYear
    2015
  • Firstpage
    3199
  • Lastpage
    3205
  • Abstract
    This paper presents cooperative adaptive cruising control of multiple cars in automated/un-automated mixed traffic. In order to take account of un-automated cars, the vehicle maneuver is expressed as a PrARX model that is a continuous approximation of hybrid dynamical system. The PrARX model describes the driver´s logical decision making as well as continuous maneuver in a uniform manner. The acceleration inputs of automated vehicles are computed in model predictive control framework where the state equation includes a platoon of automated and un-automated cars coupled with PrARX driver models. For computing assisting outputs in real time, a fast computation method for nonlinear model predictive control based on the continuation technique is employed. Simulation studies of the proposed CACC system indicates that explicit prediction of un-automated cars improves the overall stability of the platoon.
  • Keywords
    "Automobiles","Mathematical model","Acceleration","Computational modeling","Predictive models","Adaptation models"
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, IECON 2015 - 41st Annual Conference of the IEEE
  • Type

    conf

  • DOI
    10.1109/IECON.2015.7392593
  • Filename
    7392593