Abstract
The inclusion of in-vehicle sensors and increased intention and state recognition capabilities enable implicit in-vehicle interaction. Starting from a systematic literature review (SLR) on implicit in-vehicle interaction, which resulted in 82 publications, we investigated state and intention recognition methods based on (1) their used modalities, (2) their underlying level of automation, and (3) their considered interaction focus. Our SLR revealed a research gap addressing implicit interaction in highly automated vehicles (HAVs). Therefore, we discussed how the requirements for implicit state and intention recognition methods and interaction based on them are changing in HAVs. With this, open questions and opportunities for further research in this area were identified.
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