Deit Model for Iranian Traffic Sign Recognition in Advanced Driver Assistance Systems

Abstract

Due to the important relationship between the impact of accurate detection of traffic signs in self-driving cars and driver assistance during car movement, it is very challenging and necessary to create a high-accuracy system for interpretation and immediate decision-making. In this research, by applying the new vision transformer Deit approach, a system is designed that can recognize Iranian traffic signs. We trained our model with two collections of traffic sign images (GTSRB and PTSD) that reached higher accuracy levels of 99.5% and 98.8%, respectively, in optimal conditions.