Long-horizon planning enables autonomous vehicles to anticipate scene evolution and potential risks, supporting safe and stable decisions in complex interactions. However, existing methods struggle to propagate motion trends from observed history into the future. Long rollouts based on a single latent state may further...
Zi-Ying Song, Sheng-Kai Zhang, Lei Yang et al.· 0 citations
PV-WM, a history-only world model over structured post-perception tracks, recurrently advances pedestrian root motion, 15-joint articulation, and learned vehicle states within a synchronized heterogeneous state while preserving type-specific pedestrian and vehicle dynamics.
Hao-Zhuang Chi, Jing-Song Liang, Zi-Ying Song et al.· 2 citations
A World Model-based Risk-aware Mixture-of-Experts (WM-RMoE) framework is proposed, which uniquely exhibits the ability to generate foresighted and semantically distinct overtaking maneuvers across diverse traffic densities.
Yongzhi Liu, Su-Nan Zhang, Jin-Chang Xu et al.· 0 citations
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