BATON: A Multimodal Benchmark for Bidirectional Automation Transition Observation in Naturalistic Driving
Existing driving automation (DA) systems on production vehicles rely on human drivers to decide when to engage DA while requiring them to remain continuously attentive and ready to intervene. This design demands substantial situational judgment and imposes significant cognitive load, leading to steep learning curves, suboptimal user experience, and safety risks from both over-reliance and delayed takeover. Predicting when drivers hand over control to DA and when they take it back is therefore critical for designing proactive, context-aware HMI, yet existing datasets rarely capture the multimodal context, including road scene, driver state, vehicle dynamics, and route environment. To fill ...
| Authors | Yuhang Wang, Yiyao Xu, Chaoyun Yang et al. |
|---|---|
| Primary category | cs.HC |
| Published | 8 April 2026 |
| Last updated at source | 27 July 2026 |
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