PlanWAM: Planning-Shaped Future Representations for End-to-End Autonomous Driving

Key points

• To this end, we propose PlanWAM, a Planning-Shaped World Action Model.1
• We then introduce a privileged future posterior branch that observes ground-truth future frames, and shape its future latent representation with trajectory-planning objectives to obtain a planning-shaped future latent representation.1
• The predicted future latent representation serves as planning context and guides trajectory generation and selection.1
• Extensive experiments further demonstrate that planning-shaped future representations provide an effective and deployable form of foresight for world-action models.1

Sources (1)

• [1]PlanWAM: Planning-Shaped Future Representations for End-to-End Autonomous Driving
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 8, 07:13 AM

  World models in end-to-end autonomous driving predict future scene evolution to provide foresight for trajectory planning.

  To this end, we propose PlanWAM, a Planning-Shaped World Action Model.

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