# Dream2Assist: Intent-Conditioned World Models for Shared Vehicle Control

- Source: arXiv cs.RO
- Published: 2026-10-27T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/jc2mf7gscivbjq7imyi69i2yd
- Original: https://arxiv.org/abs/2610.34650

## Summary

The authors propose Dream2Assist, a model-based reinforcement learning framework that adds intent inference to a recurrent state-space world model, enabling an assistive policy to anticipate and support discrete human goals without taking over human control. The work also presents a complete deployment pipeline from world-model policy to a safe human-machine system, addressing the sim-to-real-human gap through policy down-selection and reward restructuring, and validates it in two human-subjects studies, high-speed racing (N=30) and urban driving (N=10), plus a preliminary on-vehicle deployment, where intent conditioning produced measurable improvements in torque alignment and collision rate.