Autonomous Vehicles (AVs) depend on various sensors to understand their surroundings, determine their location, and make instantaneous choices. This paper describes a detailed sensor configuration for a self-driving vehicle, including cameras, radar, IMU, and GNSS. The sensors are positioned strategically to offer a complete \(360^\circ \) perspective of the vehicle’s environment and provide precise localization and navigation information. Combining these sensors with the Robot Operating System (ROS 2) and the Gazebo simulator allows for accurate control and testing of the vehicle in simulated settings. The simulation imitates actual circumstances, enabling the assessment of vehicle performance, sensor fusion techniques, and decision-making algorithms. This configuration improves object detection, path planning, and motion control, showing strong performance in challenging and unfavorable circumstances. This paper looks into how sensor setup and placement impact the safety and functionality of autonomous vehicles.