33 citations · 85 across the 9 of their papers we have counts for
9 papers
nuTruck: Benchmarking Autonomous Driving Planning for Distributed Electric-drive Trucks
Jinyu Miao, Pu Zhang, Yifei He +5
The dominance of traditional rule-based methods in autonomous driving has gradually been replaced by learning-based approaches. While learning-based planners have achieved consider…
Physics-informed Deep Mixture-of-Koopmans Vehicle Dynamics Model with Dual-branch Encoder for Distributed Electric-drive Trucks
Jinyu Miao, Pu Zhang, Rujun Yan +8
Advanced autonomous driving systems require accurate vehicle dynamics modeling. However, identifying a precise dynamics model remains challenging due to strong nonlinearities and t…
MetaDAT: Generalizable Trajectory Prediction via Meta Pre-training and Data-Adaptive Test-Time Updating
Yuning Wang, Pu Zhang, Yuan He +2
Existing trajectory prediction methods exhibit significant performance degradation under distribution shifts during test time. Although test-time training techniques have been expl…
Enhancing Mapless Trajectory Prediction through Knowledge Distillation
Yuning Wang, Pu Zhang, Lei Bai +1
Scene information plays a crucial role in trajectory forecasting systems for autonomous driving by providing semantic clues and constraints on potential future paths of traffic age…
FEND: A Future Enhanced Distribution-Aware Contrastive Learning Framework for Long-tail Trajectory Prediction
Yuning Wang, Pu Zhang, Lei Bai +1
Predicting the future trajectories of the traffic agents is a gordian technique in autonomous driving. However, trajectory prediction suffers from data imbalance in the prevalent d…
Heterogeneous Trajectory Forecasting via Risk and Scene Graph Learning
Jianwu Fang, Chen Zhu, Pu Zhang +2
Heterogeneous trajectory forecasting is critical for intelligent transportation systems, but it is challenging because of the difficulty of modeling the complex interaction relatio…
Trajectory Forecasting from Detection with Uncertainty-Aware Motion Encoding
Pu Zhang, Lei Bai, Jianru Xue +3
Trajectory forecasting is critical for autonomous platforms to make safe planning and actions. Currently, most trajectory forecasting methods assume that object trajectories have b…
BLVD: Building A Large-scale 5D Semantics Benchmark for Autonomous Driving
Jianru Xue, Jianwu Fang, Tao Li +4
In autonomous driving community, numerous benchmarks have been established to assist the tasks of 3D/2D object detection, stereo vision, semantic/instance segmentation. However, th…
SR-LSTM: State Refinement for LSTM towards Pedestrian Trajectory Prediction
Pu Zhang, Wanli Ouyang, Pengfei Zhang +2
In crowd scenarios, reliable trajectory prediction of pedestrians requires insightful understanding of their social behaviors. These behaviors have been well investigated by plenty…