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.
Highlights
Affective automotive user interfaces show potential for an improvement of driver safety through the detection of performance-influencing states, such as anger, and their mitigation through strategic interaction [1]
We take the viability of psychophysiological sensing of emotions as a given prerequisite for affective in-car systems and focus on interaction techniques to mitigate the effects of negative emotional states
We present strategies to counteract negative emotional states from related work and evaluate four approaches which we deem promising for an in-car application
Summary
Affective automotive user interfaces show potential for an improvement of driver safety through the detection of performance-influencing states, such as anger, and their mitigation through strategic interaction [1]. We take the viability of psychophysiological sensing of emotions as a given prerequisite for affective in-car systems and focus on interaction techniques to mitigate the effects of negative emotional states. We present strategies to counteract negative emotional states from related work and evaluate four approaches which we deem promising for an in-car application. Sixty participants experienced these interface concepts and provided us with insights on their effects on driving behavior, physiological data, and user experience. The presented study focusses on the Multimodal Technologies and Interact. 2019, 3, 21; doi:10.3390/mti3010021 www.mdpi.com/journal/mti
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