IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i12p2259-d121823.html
   My bibliography  Save this article

Longitudinal Control for Mengshi Autonomous Vehicle via Gauss Cloud Model

Author

Listed:
  • Hongbo Gao

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100083, China)

  • Xinyu Zhang

    (Information Technology Center,Tsinghua University, Beijing 100083, China)

  • Yuchao Liu

    (The Institute of Electronic System Engineering, Beijing 100039, China)

  • Deyi Li

    (The Institute of Electronic System Engineering, Beijing 100039, China)

Abstract

Dynamic robustness and stability control is a requirement for self-driving of autonomous vehicle. Longitudinal control technique of autonomous vehicle is basic theory and one key complex technique which must have the reliability and precision of vehicle controller. The longitudinal control technique is one of the foundations of the safety and stability of autonomous vehicle control. In our paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle. The longitudinal control algorithm mainly uses cloud model generator to control the acceleration of the autonomous vehicle to achieve the goal that controls the speed of Mengshi autonomous vehicle. The proposed longitudinal control algorithm based on cloud model is verified by real experiments on Highway driving scene. The experiments results of the acceleration and speed show that the algorithm is validity and stability.

Suggested Citation

  • Hongbo Gao & Xinyu Zhang & Yuchao Liu & Deyi Li, 2017. "Longitudinal Control for Mengshi Autonomous Vehicle via Gauss Cloud Model," Sustainability, MDPI, vol. 9(12), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:12:p:2259-:d:121823
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/12/2259/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/9/12/2259/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Yanwei Zhang & Hualin Xie, 2019. "Welfare Effect Evaluation of Land-Lost Farmers’ Households under Different Livelihood Asset Allocation," Land, MDPI, vol. 8(11), pages 1-41, November.

    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:gam:jsusta:v:9:y:2017:i:12:p:2259-:d:121823. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.