MDrive benchmark shows multi-agent cooperative driving systems generally outperform single-agent ones in closed-loop settings but perception sharing does not always improve planning and negotiation can harm performance in complex traffic.
F-cooper: Feature based cooperative perception for autonomous vehicle edge computing system using 3d point clouds
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A new online attack framework manipulates object poses in shared CAV perception data below detection thresholds, propagating errors to cause unsafe trajectory predictions and behaviors in up to 50% of tested scenarios while evading defenses.
BOLT is a 0.9M-parameter plug-and-play module that uses ego-as-teacher distillation on high-confidence predictions to align neighbor features online, raising AP@50 by up to 32.3 points over unadapted fusion while beating ego-only baselines on DAIR-V2X and OPV2V.
citing papers explorer
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MDrive: Benchmarking Closed-Loop Cooperative Driving for End-to-End Multi-agent Systems
MDrive benchmark shows multi-agent cooperative driving systems generally outperform single-agent ones in closed-loop settings but perception sharing does not always improve planning and negotiation can harm performance in complex traffic.
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From Stealthy Data Fabrication to Unsafe Driving: Realistic Scenario Attacks on Collaborative Perception
A new online attack framework manipulates object poses in shared CAV perception data below detection thresholds, propagating errors to cause unsafe trajectory predictions and behaviors in up to 50% of tested scenarios while evading defenses.
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BOLT: Online Lightweight Adaptation for Preparation-Free Heterogeneous Cooperative Perception
BOLT is a 0.9M-parameter plug-and-play module that uses ego-as-teacher distillation on high-confidence predictions to align neighbor features online, raising AP@50 by up to 32.3 points over unadapted fusion while beating ego-only baselines on DAIR-V2X and OPV2V.