Autonomous Vehicle Perception System Design
Design a real-time, 3D object detection system for an autonomous vehicle fleet. The system must process multi-camera feeds at <30ms latency on edge hardware. Detail the end-to-end ML lifecycle, focusing on a scalable 'Data Engine' for active learning, an auto-labeling pipeline using offline multi-sensor fusion, and strategies for ensuring temporal consistency and safety-critical reliability. Explain your choices for model architecture (e.g., BEV-based vs. image-space) and how you handle the transition from cloud training to edge deployment including quantization and shadow mode validation.
TransformersBEVFormerYOLOTensorRTResNetFPNKafkaSparkPyTorchQuantizationActive LearningCenterNet
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