4 papers
FutureX: Enhance End-to-End Autonomous Driving via Latent Chain-of-Thought World Model
Hongbin Lin, Yiming Yang, Yifan Zhang +10
In autonomous driving, end-to-end planners learn scene representations from raw sensor data and utilize them to generate a motion plan or control actions. However, exclusive relian…
UrbanWorld2.0: A Multimodal Agentic Framework for Reality-Aligned 3D World Generation at City-Scale
Shengyuan Wang, Zhiheng Zheng, Yu Shang +6
The automated generation of high-fidelity, city-scale 3D environments remains a formidable challenge with profound academic and industrial implications. However, existing methods s…
LHPF: Look back the History and Plan for the Future in Autonomous Driving
Sheng Wang, Yao Tian, Xiaodong Mei +5
Decision-making and planning in autonomous driving critically reflect the safety of the system, making effective planning imperative. Current imitation learning-based planning algo…
DragTraffic: Interactive and Controllable Traffic Scene Generation for Autonomous Driving
Sheng Wang, Ge Sun, Fulong Ma +5
Evaluating and training autonomous driving systems require diverse and scalable corner cases. However, most existing scene generation methods lack controllability, accuracy, and ve…