The AutoTenth project is a student-led project centered around the design and development of a fully autonomous 1/10th-scale F1 race car. The autonomous vehicle is capable of navigating competitive race tracks with high-speed precision and efficiency. Through a combination of LiDAR sensing, the NVIDIA Jetson Orin Nano, the VESC 6 speed and motor controlling, along with advanced control algorithms such as Simultaneous Localization and Mapping (SLAM), disparity extender, and the Model Predictive Control (MPC); the vehicle operates with the Robot Operating System (ROS) to make fast and real-time navigation decisions. Our goal is to minimize lap times and maximize autonomy across the different race track conditions. This project serves as a scaled testbed for developing and refining autonomous driving technologies.