Intelligent Traffic Sign Detection using CNN

Author(s)	Kottam Vishal Reddy, Bumpelli Rohith, Mamindla Rahul Sai, D Saidulu
Country	India
Abstract	With the rise of autonomous driving and smart transportation, traffic sign detection is key to road safety and efficient navigation. Traditional methods struggle with lighting, weather, and occlusions, so we propose an Intelligent Traffic Sign Detection System using CNNs for accurate, real-time classification. Trained on the GTSRB dataset with over 50,000 images across 43 categories, our CNN model reduces manual preprocessing and improves accuracy. Data augmentation ensures robustness to real-world conditions. Achieving 92-95% accuracy, the system integrates with autonomous vehicles, providing real-time detection and alerts to enhance road safety and navigation.
Keywords	Traffic Sign Detection, Convolutional Neural Networks, Autonomous Vehicles.
Field	Engineering
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-04-24
DOI	https://doi.org/10.71097/IJSAT.v16.i2.3300
Short DOI	https://doi.org/g9gp4p

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International Journal on Science and Technology