An overview of the development of key technologies in autonomous driving technology

Abstract

Technological advances in each of the smaller fields of automated driving technology have collectively advanced the maturity of automated driving technology. This paper describes some of the technological advances in the development of automated driving of automobiles. Firstly, it introduces the improvement of 3D target detection algorithms, the problem of 3D target detection from LIDAR point cloud, and the proposed control network to address the lack of human driving logic in the existing driverless strategy. Next, the convenience of virtual simulation technology in testing self-driving cars is presented as well as the use of high-definition maps by self-driving cars to understand the road and surroundings. Then the solution to the problem of weak feature extraction and low training efficiency when extracting data in the self-driving learning model, the path planning technology for self-driving cars, and the understanding of the scene when self-driving cars are traveling at night are presented. Finally, image target recognition based on synthetic aperture radar, image color recognition method based on deep learning, and how deep learning can be applied to the field of image recognition are presented.