This work focuses on the assembly of a 1:10 scale autonomous driving vehicle to develop and implement a data-driven navigation methodology for a controlled environment. The objective is that the vehicle can Lane-keeping, overtake and pass other vehicles also at 1:10 scale. Necessary components were selected to autonomously drive such a platform. The vehicle was tested at the Mexican Robotics Tournament 2024, in the Automodel Car category, held at the Universidad Autónoma de Nuevo León in Monterrey, Mexico. The competition included, for a given circuit, lane keeping, traffic sign recognition, passing other vehicles, and automatic parking. The lane keeping test on the test track was addressed by image processing, with all communication managed from ROS and Jetson Xavier. The lane detection algorithm achieved 97% accuracy, evaluated on 2967 images captured per lap of the track with an Intel D457 camera. The vehicle completed the course in four out of six possible attempts. Real-time tuning of the adaptive PID controller implemented in the ESP significantly improved departure angle (steering) accuracy. However, there were approximately 79 false detections per lap, indicating the need for additional adjustments especially at zebra crossings. The next phase will focus on optimizing the algorithm for higher speeds and improving robustness to variations in lighting and traffic signals.