Radar combined with machine learning is redefining vehicle perception systems, delivering a robust environmental model critical to automated driving. Unlike cameras and lidar, radar performs reliably across poor weather and lighting conditions, offers accurate range and speed detection, and can be discretely embedded behind vehicle surfaces. Machine learning augments radar's raw data, improving object classification, edge detection, and accuracy in complex scenarios like occlusions, tunnels, and low-reflectivity surfaces. Aptiv’s centralized Satellite Architecture further reduces system cost and power needs, enabling scalable safety features across all vehicle classes.

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