IDEAS home Printed from https://ideas.repec.org/a/igg/jaci00/v10y2019i4p25-44.html
   My bibliography  Save this article

A Lane Identifying Approach of the Intelligent Vehicle in Complex Condition: Intelligent Vehicle in Complex Condition

Author

Listed:
  • Botao Wu

    (Hebei Institute of Machinery and Electricity, Hebei, China)

  • Huijuan Wang

    (North China Institute of Aerospace Engineering, Langfang, China)

Abstract

Lane identification by intelligent vehicles in some common complicated conditions is a key technique. The parabola model of lane boundary is established first for fitting the curved lane boundary, and the objective function is used to estimate the fitting quality of the lane boundary is designed with the grayness character and grads character of the lane boundary in a gray image. To improve the speed of the identifying algorithm, the ant colony algorithm is applied to lane identifying, and with the guidance of the designed objective function, the positive feedback of hormone will consistently allow the search the best path within the searching region of interest as soon as possible, thus, the lane boundary is found. The method can effectively eliminate the negative effect of illumination conditions or shadows of trees, etc., and identify linear or curving lane boundaries exactly. The pretreatment to image is found and the searching region of interest is set, so the real-time identifying is greatly improved.

Suggested Citation

  • Botao Wu & Huijuan Wang, 2019. "A Lane Identifying Approach of the Intelligent Vehicle in Complex Condition: Intelligent Vehicle in Complex Condition," International Journal of Ambient Computing and Intelligence (IJACI), IGI Global, vol. 10(4), pages 25-44, October.
    • Handle: RePEc:igg:jaci00:v:10:y:2019:i:4:p:25-44
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJACI.2019100102
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Neeraj Gupta & Saurabh Gupta & Mahdi Khosravy & Nilanjan Dey & Nisheeth Joshi & Rubén González Crespo & Nilesh Patel, 2021. "RETRACTED ARTICLE: Economic IoT strategy: the future technology for health monitoring and diagnostic of agriculture vehicles," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1117-1128, April.

    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:igg:jaci00:v:10:y:2019:i:4:p:25-44. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.