PlanWAM: Planning-Shaped Future Representations for End-to-End Autonomous Driving
World models in end-to-end autonomous driving predict future scene evolution to provide foresight for trajectory planning.
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Key points
- To this end, we propose PlanWAM, a Planning-Shaped World Action Model.
- 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.
- The predicted future latent representation serves as planning context and guides trajectory generation and selection.
- Extensive experiments further demonstrate that planning-shaped future representations provide an effective and deployable form of foresight for world-action models.
Sources (1)
- [1]PlanWAM: Planning-Shaped Future Representations for End-to-End Autonomous DrivingarXiv (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.
Extractive summary: sentences quoted from the sources.
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