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Multimodal Technologies Interact. 2019, 3(1), 21; https://doi.org/10.3390/mti3010021

Improving Driver Emotions with Affective Strategies

1
BMW Group Research, New Technologies, Innovations, 85748 Garching, Germany
2
LMU Munich, 80337 Munich, Germany
3
Eindhoven University of Technology, 5612 Eindhoven, The Netherlands
4
CODE Research Institute, Bundeswehr University, 81739 Munich, Germany
*
Author to whom correspondence should be addressed.
Received: 15 February 2019 / Revised: 19 March 2019 / Accepted: 20 March 2019 / Published: 25 March 2019
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Abstract

Drivers in negative emotional states, such as anger or sadness, are prone to perform bad at driving, decreasing overall road safety for all road users. Recent advances in affective computing, however, allow for the detection of such states and give us tools to tackle the connected problems within automotive user interfaces. We see potential in building a system which reacts upon possibly dangerous driver states and influences the driver in order to drive more safely. We compare different interaction approaches for an affective automotive interface, namely Ambient Light, Visual Notification, a Voice Assistant, and an Empathic Assistant. Results of a simulator study with 60 participants (30 each with induced sadness/anger) indicate that an emotional voice assistant with the ability to empathize with the user is the most promising approach as it improves negative states best and is rated most positively. Qualitative data also shows that users prefer an empathic assistant but also resent potential paternalism. This leads us to suggest that digital assistants are a valuable platform to improve driver emotions in automotive environments and thereby enable safer driving. View Full-Text
Keywords: affective computing; automotive user interfaces; emotions; human–computer interaction; ambient light; driver state; voice assistants affective computing; automotive user interfaces; emotions; human–computer interaction; ambient light; driver state; voice assistants
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Braun, M.; Schubert, J.; Pfleging, B.; Alt, F. Improving Driver Emotions with Affective Strategies. Multimodal Technologies Interact. 2019, 3, 21.

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