Design and Analysis of an Autonomous Road Sign Recognition System | ||||
| Advanced Sciences and Technology Journal | ||||
| Volume 2, Issue 1, June 2025, Page 1-34 PDF (1.83 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/astj.2025.347656.1047 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Adham Hassan Sayed; Athanasious Nashaat Rasmy; Eithar Reda Ebrahim; Gannah Mohamed Youssef; Mohamed Ahmed Salah; Mohamed Ahmed Mohamed; Omar Mohamed Elsadawy; Veronia Medhat Sabry; Youssef Emad Salib; Abo M. Elhady 
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| Mechatronics Engineering Department, Faculty of Engineering and Technology, Egyptian Chinese University, Cairo, Egypt. | ||||
| Abstract | ||||
| To ensure efficient and safe traffic flow, it is essential that all drivers should follow the road sign strictly. Car industrial technology is heading towards autonomous driving. And to make auto driving safe, it should be flawless and fault-free. Therefore, the system must read all road signs correctly. There must be an awareness competent that makes the system able to comprehend and interpret those road signs. The problem of our matter is that if we want to ensure safe flow effectively, our system must read and interpret all road signs correctly. Our current state acknowledges that there is a driver who has lost concentration while driving. So, we create a system that recognizes road signs and interprets them into voice alerting the driver. The system completely depends on the You Only Look Once V8 NANO and German Traffic Sign Recognition Benchmark Dataset. We have chosen the German Traffic Sign Recognition Benchmark because it's the most similar to what is actually on Egyptian roads. | ||||
| Keywords | ||||
| Road sign detection YOLO V8; GTSDB Dataset; Convolution Neural Network; Deep learning | ||||
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