Road Sign Detection for Automated Vehicles

Real-time detection · YOLO · Autonomous driving · Diverse environments

Overview

Real-time traffic and road sign detection system for automated vehicle use-cases. Robust performance across diverse lighting conditions and environmental variations for safe autonomous navigation.

🚗 Autonomous Driving 🚦 Traffic Signs ⚡ Real-time Python PyTorch 🎯 YOLO OpenCV

Problem

  • Safety-critical application requiring real-time detection.
  • Diverse lighting conditions (day, night, rain, fog).
  • Various sign types, sizes, and viewing angles.
  • Occluded or partially visible signs must be detected.

Solution

  • YOLO-based object detection for real-time sign recognition.
  • Improved performance in diverse lighting/environment conditions.
  • Multi-scale detection for signs at various distances.
  • Robust training with extensive data augmentation.

My Role

  • Designed object detection pipeline for road sign recognition.
  • Improved performance in diverse lighting/environment conditions.
  • Optimized for real-time inference on edge devices.

Implementation

Language: Python

Libraries:

PyTorch YOLO OpenCV

Results Gallery

Images to be added

End Result

  • Reliable road sign detection with real-time inference capability.
  • Robust performance across diverse environmental conditions.
  • Suitable for deployment in autonomous vehicle systems.