Analysis of Traffic Sign Recognition for Automated Transportation Systems Using Neural Networks

Recently, numerous applications of Intelligent Transportation Systems (ITS) have gained increasingly more focus. One of the most crucial functions of ITS is Traffic Signs Detection and Recognition (TSDR) by notifying drivers of the status of road signs and providing helpful information regarding safety procedures which helps to improve safety. This paper analyzes the different deep learning algorithms implemented for TSDR along with discrete optimization functions used, Image conditions of the datasets, and accuracy attained during the training and testing of Traffic Sign Detection algorithms (TSD) in recent research. A comparison of all the approaches is presented in the study with the help of tables. In the paper, a list of publicly accessible datasets is also mentioned, along with a discussion that can be very useful for future TSDR research work.