Autonomous driving refers to the capability of a vehicle to operate independently, without human intervention through the integration of both hardware and software systems. Radar technology is crucial in hardware detection. This essay seeks to thoroughly examine radar integration technology in self-driving cars and offers comprehensive reviews of technology and future directions. It will encompass an overview of radar components, various detection methodology, and their practical application in autonomous vehicles. Additionally, the type of radar and its approach of measurement are also mentioned briefly in the text. In the last section, two models are applied to test the performance of radar object detection. Based on the calculation of accuracy, precision and recall from the nuScenes dataset, The RCS-based model and machine learning based are designed for virtual testing. The results evaluate the performance of two radar models, indicating the great performance and accuracy of identification of the machine learning model yet over-optimization of RCS model.
