Building a Predictive Model for Traffic Sign Recognition in Vietnam for Safe Driving Assistance.

Abstract

With the increasingly crowded and frequent traffic jams on roads in Vietnam, the accurate recognition of traffic signs has become extremely important to enhance safety and reduce accidents. This study introduces a new approach, building a predictive model to recognize traffic signs in Vietnam by using modern machine learning techniques, combined with deep learning, especially convolutional neural networks (CNN). This model is designed to classify and recognize signs effectively. The experimental results show that the model achieves high accuracy, opening up the prospect of application in safe driving assistance systems, contributing to improving traffic safety. The article also mentions the challenges when applying the model in real traffic conditions in Vietnam and proposes solutions to improve recognition efficiency.