The development of autonomous vehicles is crucial for enhancing driving safety, comfort, and efficiency. This research presents the design of a self-driving Remote Controlled (RC) car at a 1:10 scale, equipped with a lane-keeping system and a pure pursuit controller. The primary objective is to evaluate the effectiveness of integrating computer vision techniques with trajectory tracking control to maintain lane stability. Lane detection was achieved using a sliding windows algorithm, while polynomial fitting estimated the lane centerline. A stereo camera provided spatial perception, capturing images that were processed to determine the steering angle needed to minimize deviation between the lookahead point and the viewpoint of the vehicle. Experimental results show that the system-maintained lane position with minimal deviation, achieving an average steering angle of 90.44° on straight paths, 65.4° on right turns, and 113.1° on left turns. These results demonstrate the feasibility of combining vision-based lane detection with a pure pursuit controller to improve path-tracking accuracy and stability in autonomous vehicles.