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cs.RO2026
Ego-Dynamics-Augmented World Model for Autonomous Driving with Zero-Shot Cross-Chassis Adaptation
Zhidong Wang, Jingsong Liang, Zirui Li +3
World model (WM)-based reinforcement learning enables sample-efficient end-to-end autonomous driving learning by imagining long-horizon trajectories in latent space. However, most…
cs.RO2025
A Human-Oriented Cooperative Driving Approach: Integrating Driving Intention, State, and Conflict
Qin Wang, Shanmin Pang, Jianwu Fang +4
Human-vehicle cooperative driving serves as a vital bridge to fully autonomous driving by improving driving flexibility and gradually building driver trust and acceptance of autono…
cs.RO2024
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…