Fusing Multi-Vehicle Sensor Perspectives into a Unified 360-Degree World Model
Exchanging intermediate neural feature maps over high-bandwidth direct sidelinks, allowing a lead vehicle to see obstacles occluded behind a following bus.
Feature-Level Spatial Alignment
Convolutional feature maps from adjacent cars are transformed into the ego-vehicle's BEV (Bird's Eye View) plane with sub-pixel spatial accuracy.
- Over 300% expansion of effective perception field-of-view.
- Occluded blind-spot pedestrian detection with 99.8% precision.
- Uplink data bandwidth optimized below 2 Mbps per sharing vehicle.
- Automatic spatial registration compensating for GPS localization noise.
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