Intelligent Road Sign Recognition and Autnomous Driving
Neha Janu, Neha Shrotriya, Aditi Goel · 2025
In the modern times, with increasing population and technological advancements,driving has become an important part of the lives of a large amount of population and their Good Health and Well-Being. As every driver’s major focus is on the road, they might some times misread signals or signs. This is a huge problem as it poses an issue on driver’s safety. To resolve this issue, various methods have been proposed. One such development,to overcome this concern, has been the road sign recognition systems that provide drivers information about traffic rules and road signs. Several deep learning algorithms and machine learning (ML) are used to make road sign recognition system efficient and reliable.Notable advancements have been made in the fields of deep learning and machine learning. Numerous models and methods, such as Random Forest, Support Vector Machine (SVM), Con-volutional Neural Network (CNN), and Histogram of Orientated Gradients (HOG), are used for road sign recognition. In order to build a traffic sign identification system, this study uses the Deep Convolutional Neural Network (CNN), a dependable deep learning model that has shown outstanding results in the past, and the German Traffic Sign identification Benchmark (GTSRB) as a dataset for data preprocessing. Procedures like preprocessing, feature extraction, classification, and performance evaluation were used to achieve high accuracy and aesthetically acceptable outcomes.