Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving
Human driving behavior is inherently personal, which is shaped by long-term habits and influenced by short-term intentions. Individuals differ in how they accelerate, brake, merge, yield, and overtake across diverse situations. However, existing end-to-end autonomous driving systems either optimize for generic objectives or rely on fixed driving modes, lacking the ability to adapt to individual preferences or interpret natural language intent. To address this gap, we propose Drive My Way (DMW), a personalized Vision-Language-Action (VLA) driving framework that aligns with users' long-term driving habits and adapts to real-time user instructions. DMW learns a user embedding from our person...
| Authors | Zehao Wang, Huaide Jiang, Shuaiwu Dong et al. |
|---|---|
| Primary category | cs.RO |
| Published | 26 March 2026 |
| Last updated at source | 26 March 2026 |
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