4 citations · 4 across the 3 of their papers we have counts for
5 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The dominance of traditional rule-based methods in autonomous driving has gradually been replaced by learning-based approaches.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…
COME: Adding Scene-Centric Forecasting Control to Occupancy World Model
Yining Shi, Kun Jiang, Qiang Meng +6
World models are critical for autonomous driving to simulate environmental dynamics and generate synthetic data. Existing methods struggle to disentangle ego-vehicle motion (perspe…
PanoSSC: Exploring Monocular Panoptic 3D Scene Reconstruction for Autonomous Driving
Yining Shi, Jiusi Li, Kun Jiang +4
Vision-centric occupancy networks, which represent the surrounding environment with uniform voxels with semantics, have become a new trend for safe driving of camera-only autonomou…
EFFOcc: Learning Efficient Occupancy Networks from Minimal Labels for Autonomous Driving
Yining Shi, Kun Jiang, Jinyu Miao +8
3D occupancy prediction (3DOcc) is a rapidly rising and challenging perception task in the field of autonomous driving. Existing 3D occupancy networks (OccNets) are both computatio…