Computer Vision for Autonomous Vehicles

The Challenge

An automotive manufacturer needed Level 4 autonomous driving capabilities requiring real-time processing of multiple sensor inputs (LiDAR, radar, cameras) with high accuracy in all weather conditions. Safety was the absolute priority.

Our Solution

We developed advanced computer vision systems using deep learning models for multi-modal sensor fusion. The system processes LiDAR, radar, and camera data in real-time to perform object detection, semantic segmentation, and path prediction with exceptional accuracy.

Results & Achievements

  • 99.9% accuracy in adverse weather conditions
  • Real-time processing with <100ms latency
  • Successfully tested in 15+ countries
  • Zero accidents in 1M+ miles of testing
  • Level 4 autonomy certification achieved

Impact

The system enabled the manufacturer to launch Level 4 autonomous vehicles, positioning them as a leader in autonomous driving technology. It has the potential to revolutionize transportation and reduce accidents significantly.

Technologies Used

OpenCV TensorFlow LiDAR Processing Sensor Fusion Real-time Systems C++ ROS

Client Information

Client: Automotive Manufacturer

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