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Preprint Sep 2026

MomWorld: Momentum-Aware Latent World Model for Long-Horizon Autonomous Driving

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
#artificial intelligence Preprint Sep 2026

PV-WM: A Heterogeneous Micro-Macro World Model for Articulated Pedestrian-Vehicle Co-Rollout

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
#artificial intelligence Preprint Jul 2026

Risk-Aware Decision-Making for Autonomous Overtaking: A World Model-Based Mixture-of-Experts Framework

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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