AI RESEARCH
Latent World Models for Automated Driving: A Unified Taxonomy, Evaluation Framework, and Open Challenges
arXiv CS.AI
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ArXi:2603.09086v1 Announce Type: cross Emerging generative world models and vision-language-action (VLA) systems are rapidly reshaping automated driving by enabling scalable simulation, long-horizon forecasting, and capability-rich decision making. Across these directions, latent representations serve as the central computational substrate: they compress high-dimensional multi-sensor observations, enable temporally coherent rollouts, and provide interfaces for planning, reasoning, and controllable generation.