With the development of intelligent driving technology, the progress of hardware technology. Visual perception technology based on deep learning has been applied more and more in the field of intelligent driving. Vision, as the main part of information acquisition, is the core of automatic assisted driving technology. Based on the intelligent vehicle as the research platform, the use of ROS combined the technology of deep learning design implements a lane detection algorithm, in the car on the road ahead uninterrupted detection, extraction of the road lane information, to guide the car driving direction, effectively improve the security and intelligent vehicle driving process, to achieve the function of unmanned vehicle automated driving laid the foundation.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Research on lane detection algorithm of intelligent vehicle


    Contributors:
    Liu, Biao (author) / Liu, Guohao (author) / Qiao, Junchao (author)

    Conference:

    International Conference on Algorithms, Microchips and Network Applications ; 2022 ; Zhuhai,China


    Published in:

    Proc. SPIE ; 12176


    Publication date :

    2022-05-06





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Research on lane detection algorithm of urban road

    He, Lulu | British Library Conference Proceedings | 2023


    A two-wheeled vehicle oriented lane detection algorithm

    Nava, Dario / Panzani, Giulio / Zampieri, Pierluigi et al. | IEEE | 2018


    Algorithm on lane changing and tracking control technology for intelligent vehicle

    You, Feng / Wang, Rongben / Zhang, Ronghui | Tema Archive | 2007


    AN EFFICIENT LANE DETECTION ALGORITHM FOR LANE DEPARTURE DETECTION

    Jung, H. / Min, J. / Kim, J. et al. | British Library Conference Proceedings | 2013


    An efficient lane detection algorithm for lane departure detection

    Jung, Heechul / Min, Junggon / Kim, Junmo | IEEE | 2013