Design and analysis of convolutional neural network in assisted driving of unmanned vehicles

Abstract

In recent years, with the arrival of the AI era, AI technology is widely used in various industries, and in recent years, the research of unmanned driving technology is also the most. With the rise of technology such as unmanned driving, as a key part of safe driving, various auxiliary driving systems on the car can real-time warning car, active intervention, to avoid the occurrence of various accidents. Based on the above analysis, this paper proposes a high-performance embedded platform based on Jetson Nano, which includes the classification and recognition of circular traffic signs and pedestrian detection, through the use of machine vision and deep learning and other technologies to achieve an assisted driving system.