This project was designed and implemented with a focus on Computer Vision, aiming to simulate certain capabilities of autonomous vehicles. The system employed image processing algorithms to detect the environment and identify components of the driving path.
Specifically, the Hough Transformation algorithm was used for lane detection, enabling the system to recognize the vehicle’s path. This approach serves as a fundamental basis for motion control decisions in autonomous vehicles and plays a key role in safe and automated navigation.
The project is a practical example of integrating image processing, artificial intelligence, and intelligent transportation systems, demonstrating that even at a laboratory scale, some complex capabilities of autonomous vehicles can be successfully implemented.