CarlaNCAP framework and 11k-frame dataset show infrastructure collective perception achieves up to 100% accident avoidance in EuroNCAP scenarios versus 33% for vehicle-only sensors.
Dair-v2x: A large-scale dataset for vehicle- infrastructure cooperative 3d object detection
2 Pith papers cite this work. Polarity classification is still indexing.
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A survey comparing classical multi-agent systems with large foundation model-enabled multi-agent systems, showing how the latter enables semantic-level collaboration and greater adaptability.
citing papers explorer
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CarlaNCAP: A Framework for Quantifying the Safety of Vulnerable Road Users in Infrastructure-Assisted Collective Perception Using EuroNCAP Scenarios
CarlaNCAP framework and 11k-frame dataset show infrastructure collective perception achieves up to 100% accident avoidance in EuroNCAP scenarios versus 33% for vehicle-only sensors.
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Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures
A survey comparing classical multi-agent systems with large foundation model-enabled multi-agent systems, showing how the latter enables semantic-level collaboration and greater adaptability.