Affiliation:
1. Ulm University, Ulm, Germany
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.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)
Cited by
5 articles.
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1. Effects of 3D Displays on Mental Workload, Situation Awareness, Trust, and Performance Assessment in Automated Vehicles;Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia;2023-12-03
2. What and When to Explain?;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2023-09-27
3. I’ve Got the Power: Exploring the Impact of Cooperative Systems on Driver-Initiated Takeovers and Trust in Automated Vehicles;Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications;2023-09-18
4. A Demonstration of AutoVis: Enabling Mixed-Immersive Analysis of Automotive User Interface Interaction Studies;Adjunct Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications;2023-09-18
5. Effects of Urgency and Cognitive Load on Interaction in Highly Automated Vehicles;Proceedings of the ACM on Human-Computer Interaction;2023-09-11