Research and Development of a Traffic Sign Recognition Module in Vietnam
Received: 22 November 2023 | Revised: 4 December 2023 | Accepted: 6 December 2023 | Online: 8 February 2024
Corresponding author: Nguyen Luong Thien
Abstract
Automatic traffic sign recognition is essential in researching and developing driver assistance systems and autonomous vehicles. This paper presents the research and development of an automated traffic sign recognition module in Vietnam. The recognition model is developed based on the deep learning model YOLOv5 and incorporates architectural modifications to reduce computational complexity, increase inference speed, and meet real-time requirements for embedded system applications. The model is trained using a custom dataset collected by the research team from real-world street environments in Vietnam, encompassing diverse locations, times, and weather conditions. The trained recognition model is deployed on the Jetson embedded system, yielding high-quality recognition results and meeting real-time recognition needs.
Keywords:
traffic sign recognition, YOLOv5, embedded system, image processing, deep learningDownloads
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Copyright (c) 2023 Pham Xuan Tung, Nguyen Luong Thien, Pham Van Bach Ngoc, Minh Hung Vu
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