Studies Advanced in Traffic Sign Detection in Autonomous Driving Scenarios

Abstract

Traffic sign detection and recognition is a hot research topic in the environmental awareness module of autonomous driving, which aims to build a model of road traffic information and provide a decision basis for driving scheme design. Early traffic sign recognition methods were mostly based on color features, shape features, or multi feature fusion. Thanks to the rapid development of convolutional neural networks, traffic sign recognition methods based on deep learning have continuously made breakthroughs in both accuracy and speed. In this paper, focusing on the four major types of mainstream frameworks mentioned above, we will introduce the latest research progress in traffic sign detection and recognition technology, including the principles, steps, advantages and disadvantages of representative algorithms. In addition, we quantitatively compared the performance of different recognition methods on common data sets. Finally, we discussed the existing problems in traffic sign recognition and its future development direction.