Obstacle Detection Using 24 GHz mmWave Radar Module For Collision Avoidance In Autonomous Vehicle Applications

Abstract

The goal of this project is to design and develop an obstacle detection system for collision avoidance in autonomous vehicle applications using a 24 GHz mmWave radar module. The proposed system employs a radar module to detect objects in the vehicle's path and then classifies them based on their distance and relative speed. The system also estimates the position and velocity of detected objects. The effectiveness of the proposed system is demonstrated through simulations and experiments on a test bench. The results show that the proposed system can accurately detect and classify obstacles in real time and issue warnings to the vehicle control system in time, which can be used for collision avoidance. This system provides a robust and reliable solution for obstacle detection in autonomous vehicle applications, especially in adverse weather conditions where other sensor systems may not be effective. The proposed system has the potential to improve the safety and reliability of autonomous vehicles, ultimately leading to safer and more efficient transportation systems.