6 citations · 7 across the 4 of their papers we have counts for
4 papers
STDA: Spatio-Temporal Dual-Encoder Network Incorporating Driver Attention to Predict Driver Behaviors Under Safety-Critical Scenarios
Dongyang Xu, Yiran Luo, Tianle Lu +3
Accurate behavior prediction for vehicles is essential but challenging for autonomous driving. Most existing studies show satisfying performance under regular scenarios, but most n…
AHMF: Adaptive Hybrid-Memory-Fusion Model for Driver Attention Prediction
Dongyang Xu, Qingfan Wang, Ji Ma +2
Accurate driver attention prediction can serve as a critical reference for intelligent vehicles in understanding traffic scenes and making informed driving decisions. Though existi…
Risk-Aware Vehicle Trajectory Prediction Under Safety-Critical Scenarios
Qingfan Wang, Dongyang Xu, Gaoyuan Kuang +3
Trajectory prediction is significant for intelligent vehicles to achieve high-level autonomous driving, and a lot of relevant research achievements have been made recently. Despite…
M2DA: Multi-Modal Fusion Transformer Incorporating Driver Attention for Autonomous Driving
Dongyang Xu, Haokun Li, Qingfan Wang +3
End-to-end autonomous driving has witnessed remarkable progress. However, the extensive deployment of autonomous vehicles has yet to be realized, primarily due to 1) inefficient mu…