3 papers
cs.RO2026
Defer to Plan: Adaptive Multi-Agent Fusion for End-to-End V2X Driving
Nuoran Li, Zhang Zhang, Yueran Zhao +2
Vehicle-to-everything-aided autonomous driving (V2X-AD) significantly enhances driving performance through information sharing. However, existing collaborative perception methods o…
cs.CV2025
HeatV2X: Scalable Heterogeneous Collaborative Perception via Efficient Alignment and Interaction
Yueran Zhao, Zhang Zhang, Chao Sun +3
Vehicle-to-Everything (V2X) collaborative perception extends sensing beyond single vehicle limits through transmission. However, as more agents participate, existing frameworks fac…
cs.CV2025
RoadMamba: A Dual Branch Visual State Space Model for Road Surface Classification
Tianze Wang, Zhang Zhang, Chao Yue +2
Acquiring the road surface conditions in advance based on visual technologies provides effective information for the planning and control system of autonomous vehicles, thus improv…