THE ORETICAL APPROACHES TO THE DETECTION AND RECOGNITION OF TRAFFIC SIGNS IN AUTONOMOUS DRIVING AND DRIVER ASSISTANCE SYSTEMS

The transportation sector is being transformed by the arrival of autonomous driving and advanced driver assistance systems (ADAS). The correct function of many of these systems relies heavily on detecting traffic signs which can be a life saver. In this article, different theoretical approaches to the detection and recognition of traffic signs are addressed. It covers the classical image processing methods, machine learning-based methods, and the state-of-the-art deep learning models. It also documents the difficulties which are encountered by systems in real world and gives the solution to increase the system potential to make it more robust and accurate. Keywords: traffic signs, driver assistance systems, technique, equalization.