Volume 11, Number 4/5/6

Implementation of Lane Tracking by using Image Processing Techniques in
Developed Prototype Autonomous Vehicle


Sertap Kamçı, Dogukan Aksu and Muhammed Ali Aydin, Istanbul University-Cerrahpasa, Turkey


Today, unmanned vehicle technologies are developing in parallel with increasing interest in technological developments. These developments aim to improve people's quality of life. Transportation, which is a part of human life, has taken its share from this developing technology. With the development of artificial intelligence, it is aimed to provide the necessary assistance to the driver in transportation and to provide ease of driving. This development has been increased with ADAS (Advanced Driver Assistance Systems) in vehicles, but it is not possible to experience a completely driverless and comfortable road. With all these demands and conditions, autonomous vehicles have quickly attracted attention. While ADAS is a warning system, all accident risks that may arise from the driver rather than the warning to the driver in autonomous vehicles are minimized by the vehicle.

In this paper, we present an autonomous vehicle prototype that follows lanes via image processing techniques, which are a major part of autonomous vehicle technology. Autonomous movement capability is provided by using various image processing algorithms such as canny edge detection, Sobel filter, etc. We implemented and tested these algorithms on the vehicle. The vehicle detected and followed the determined lanes. By that way, it went to the destination successfully.


Autonomous Vehicle, Lane Detection, Image Processing, HSV Color, RGB Color, Canny Edge Detection, DC Motor, Region of Interest (ROI), Vanishing Point, Sobel Filter