Abstract
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.
Highlights
We present an autonomous vehicle prototype that follows lanes via image processing techniques, which are a major part of autonomous vehicle technology
If an autonomous vehicle is not traveling, the driver should: After providing the road and traffic control without deciding to pass the vehicle, first to check the mirrors according to the direction of departure, to check whether there is a vehicle in the blind spot and wait for the vehicles to pass, to give the appropriate signal to the direction of exit, not to get too close to the passing vehicle and after passing the vehicle to pass immediately, to overtake in cases where overtaking is prohibited, service vehicles and buses minibuses briefly public transport vehicles to pay attention to the superiority of the transition
It is more convenient to use HSV color space when we want to differentiate an object of a certain color in any computer vision/image processing application [3]
Summary
In order for the vehicles to be able to watch safely in a series, the part of the vehicle path separated by lines is called lane. It is important to not leave the current lane and center the lane Because in this case the accident is inevitable and people in other vehicles have added to the risk of having an accident. The algorithm of autonomous vehicles allows the protection of the lane. Gets an idea with the algorithm written about the lanes to be traveled according to the route of the vehicle and determines the path . The vehicle has an idea about the lanes to be traveled according to the route of the vehicle and determines its path . With the operation of the autonomous vehicle, the image on the road is taken through the camera.
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