IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/3108589.html
   My bibliography  Save this article

Research on Curved Path Tracking Control for Four-Wheel Steering Vehicle considering Road Adhesion Coefficient

Author

Listed:
  • Runqiao Liu
  • Minxiang Wei
  • Nan Sang
  • Jianwei Wei

Abstract

Curved path tracking control is one of the most important functions of autonomous vehicles. First, small turning radius circular bends considering bend quadrant and travel direction restrictions are planned by polar coordinate equations. Second, an estimator of a vehicle state parameter and road adhesion coefficient based on an extended Kalman filter is designed. To improve the convenience and accuracy of the estimator, the combined slip theory, trigonometric function group fitting, and cubic spline interpolation are used to estimate the longitudinal and lateral forces of the tire model (215/55 R17). Third, to minimize the lateral displacement and yaw angle tracking errors of a four-wheel steering (4WS) vehicle, the front-wheel steering angle of the 4WS vehicle is corrected by a model predictive control (MPC) feed-back controller. Finally, CarSim® simulation results show that the 4WS autonomous vehicle based on the MPC feed-back controller can not only significantly improve the curved path tracking performance but also effectively reduce the probability of drifting or rushing out of the runway at high speeds and on low-adhesion roads.

Suggested Citation

  • Runqiao Liu & Minxiang Wei & Nan Sang & Jianwei Wei, 2020. "Research on Curved Path Tracking Control for Four-Wheel Steering Vehicle considering Road Adhesion Coefficient," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-18, January.
    • Handle: RePEc:hin:jnlmpe:3108589
    DOI: 10.1155/2020/3108589
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2020/3108589.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2020/3108589.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2020/3108589?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhe Zhang & Haitao Ding & Konghui Guo & Niaona Zhang, 2022. "A Hierarchical Control Strategy for FWID-EVs Based on Multi-Agent with Consideration of Safety and Economy," Energies, MDPI, vol. 15(23), pages 1-18, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:3108589. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.