TSR Traffic Sign Recognition System

Abstract

The vast majority of the recent traffic accidents are caused due to distractions and lack of attention while driving. Traffic signs play a critical role in the transportation sector. Due to the distraction of drivers, the odds of not noticing these traffic signs have been tremendously expanded. In order to address these issues such as lack of recognisability of traffic signs and not noticing them by drivers, on-road applications known as advanced driver-assistance systems were introduced with the feature of traffic sign recognition. Traffic sign recognition is the third eye for the drivers. It is a fantastically simple, yet amazingly valuable piece of innovation. Traffic sign recognition is aimed at detecting and classifying all traffic signs ahead. Despite the fact that this innovation was presented as assistance for the drivers, as of now it has been utilized in autonomous driving vehicles and robot navigations. There are numerous approaches to implement a traffic sign recognition system. In this research, detection based on machine learning approach has been selected and deep learning model based on Convolutional Neural Networks (CNN) prompted promising outcomes concerning the accuracy of 95.78% is produced. The exploratory outcomes affirmed high precision and efficiency of the developed system.