PLAN-S decodes a style-conditioned four-channel semantic cost map from latent representations to bridge world models and planners in autonomous driving, reporting 0.55 m average L2 and 42% collision reduction on nuScenes plus PDMS gains on NAVSIM.
Drive my way: Preference alignment of vision-language-action model for personalized driving,
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PLAN-S: Bridging Planning with Latent Style Dynamics for Autonomous Driving World Models
PLAN-S decodes a style-conditioned four-channel semantic cost map from latent representations to bridge world models and planners in autonomous driving, reporting 0.55 m average L2 and 42% collision reduction on nuScenes plus PDMS gains on NAVSIM.