In this study, we worked on an efficient lane keeping assist system. Lane keeping is one of the most concerning things in Automated Automobile Industries in recent times. Lane keeping assist system is a key feature of autonomous driving. Keeping the vehicle in its designated lane is one of the most important things in order to reduce road accidents. Research on this area is important in making the system suitable for real-world road conditions which are quite challenging. In order to achieve an efficient lane keeping system, first we need to detect the lane lines automatically. We did it using an image dataset by two image processing algorithms: Canny edge detection and Hough transformation. The proposed system has two stages: the detection of lane lines and the calculation of the offset value. Basically, the offset value means how much the vehicle deviates from its lane or if the vehicle is in the center line of the lane. We use Sliding Window Algorithm for the offset value calculation. The proposed system’s performance is evaluated using the IROADS database in this work.


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    Titel :

    A Lane Detection Framework for Automated Vehicle Using Computer Vision


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Shrivastava, Vivek (Herausgeber:in) / Bansal, Jagdish Chand (Herausgeber:in) / Panigrahi, Bijaya Ketan (Herausgeber:in) / Islam, Yumna (Autor:in) / Azad, Farhana (Autor:in) / Ruslan, Ch Zakauddin Md. (Autor:in) / Marma, C. Aye Mong (Autor:in) / Kalpoma, Kazi A. (Autor:in)

    Kongress:

    International Conference on Power Engineering and Intelligent Systems (PEIS) ; 2023 ; Delhi, India June 24, 2023 - June 25, 2023



    Erscheinungsdatum :

    2024-01-23


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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