Our project focuses on the development and implementation of autonomous driving algorithms on a 1/10 scale open-source self-driving vehicle designed for education and research. Utilizing Robot Operating System (ROS), our project integrates modules for sensing, decision-making, and control to enable real-time navigation and obstacle avoidance. A key component of our project is the LiDAR-based reactive obstacle avoidance algorithm such as disparity extender which is able to quickly navigate almost any given track. The culmination of our project involves testing the vehicle's performance in competitive racing scenarios, emphasizing the practical application of autonomous systems in dynamic environments. Through iterative development and real-world testing, our project provides a comprehensive platform for exploring and learning autonomous vehicle technologies.