Search Results for author:
Found 4 papers, 1 papers with code
AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning
In addition, the single-vehicle autonomous driving systems lack of the ability of collaboration and negotiation with other vehicles, which is crucial for the safety and efficiency of autonomous driving systems.
Collaborative Perception for Connected and Autonomous Driving: Challenges, Possible Solutions and Opportunities
Autonomous driving has attracted significant attention from both academia and industries, which is expected to offer a safer and more efficient driving system.
Towards Full-scene Domain Generalization in Multi-agent Collaborative Bird's Eye View Segmentation for Connected and Autonomous Driving
To address these challenges, we propose a unified domain generalization framework applicable in both training and inference stages of collaborative perception.
Adaptive Communications in Collaborative Perception with Domain Alignment for Autonomous Driving
To address these issues, we propose ACC-DA, a channel-aware collaborative perception framework to dynamically adjust the communication graph and minimize the average transmission delay while mitigating the side effects from the data heterogeneity.
