Open AccessDriving Assistance System with Lane Change Detection
Author(s) -
Jia-Shing Sheu,
Chun-Kang Tsai,
Po-Tong Wang
Publication year - 2021
Publication title -
advances in technology innovation
Language(s) - English
Resource type - Journals
eISSN - 2518-2994
pISSN - 2415-0436
DOI - 10.46604/aiti.2021.7109
Subject(s) - grayscale , computer vision , artificial intelligence , thresholding , offset (computer science) , computer science , intersection (aeronautics) , lane departure warning system , dilation (metric space) , mathematics , image (mathematics) , geography , geometry , cartography , programming language
In this study, a simple technology for a self-driving system called “driver assistance system” is developed based on embedded image identification. The system consists of a camera, a Raspberry Pi board, and OpenCV. The camera is used to capture lane images, and the image noise is overcome through color space conversion, grayscale, Otsu thresholding, binarization, erosion, and dilation. Subsequently, two horizontal lines parallel to the X-axis with a fixed range and interval are used to detect left and right lane lines. The intersection points between the left and right lane lines and the two horizontal lines can be obtained, and can be used to calculate the slopes of the left and right lanes. Finally, the slope change of the left and right lanes and the offset of the lane intersection are determined to detect the deviation. When the angle of lanes changes drastically, the driver receives a deviation warning. The results of this study suggest that the proposed algorithm is 1.96 times faster than the conventional algorithm.