This project focuses on the development of a high-performance autonomous 1/10th-scale race car for the F1TENTH competition. The vehicle is designed to reach speeds up to 30 mph while maintaining stability through a lightweight and low center-of-gravity design. It uses LiDAR and encoder feedback for real-time perception and state estimation, supported by a custom powertrain with hub motors and an embedded system architecture. The autonomy stack progresses from a baseline Follow-the-Gap (FTG) algorithm to a Model Predictive Path Integral (MPPI) controller with simultaneous localization and mapping (SLAM), enabling both reliable obstacle avoidance and predictive, high-speed navigation. MPPI allows the system to evaluate control actions over a short horizon while accounting for vehicle dynamics and environmental constraints. With a high-frequency control loop and low-latency communication over a CAN-based network, the system is designed for fast and responsive operation. This project demonstrates the integration of advanced control, sensing, and mechanical design to achieve robust autonomous racing performance.