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Book ChapterDOI

User Experience of Driver State Visualizations: A Look at Demographics and Personalities

TLDR
The impact of demographics and personality traits on the user experience of driver state visualizations is investigated to support professionals and researchers designing affective in-car information systems.
Abstract
Driver state detection is an emerging topic for automotive user interfaces. Motivated by the trend of self-tracking, one crucial question within this field is how or whether detected states should be displayed. In this work we investigate the impact of demographics and personality traits on the user experience of driver state visualizations. 328 participants experienced three concepts visualizing their current state in a publicly installed driving simulator. Driver age, experience, and personality traits were shown to have impact on visualization preferences. While a continuous display was generally preferred, older respondents and drivers with little experience favored a system with less visual elements. Extroverted participants were more open towards interventions. Our findings lead us to believe that, while users are generally open to driver state detection, its visualization should be adapted to age, driving experience, and personality. This work is meant to support professionals and researchers designing affective in-car information systems.

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Citations
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Journal ArticleDOI

Improving Driver Emotions with Affective Strategies

TL;DR: Results of a simulator study 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.
Journal ArticleDOI

Affective Automotive User Interfaces–Reviewing the State of Driver Affect Research and Emotion Regulation in the Car

TL;DR: In this article, the authors review the current literature regarding the impact of emotions on driver behavior and analyze the state of emotion regulation approaches in the car, summarizing challenges for affective interaction in the form of technological hurdles and methodological considerations, as well as opportunities to improve road safety by reinstating drivers into an emotionally balanced state.

Zombies on the road: A holistic design approach to balancing gamification and safe driving [poster]

TL;DR: In this paper, the authors explore novel driving experiences that make use of gamification and augmented reality in the car and discuss their design considerations, which are grounded in road safety psychology and video game design theory.
Journal ArticleDOI

A Spontaneous Driver Emotion Facial Expression (DEFE) Dataset for Intelligent Vehicles: Emotions Triggered by Video-Audio Clips in Driving Scenarios

TL;DR: In this article , a new dataset, the driver emotion facial expression (DEFE) dataset for drivers' spontaneous emotions analysis is introduced, which includes facial expression recordings from 60 participants during driving.
Journal ArticleDOI

CogEmoNet: A Cognitive-Feature-Augmented Driver Emotion Recognition Model for Smart Cockpit

TL;DR: In this paper , a cognitive-feature-augmented driver emotion detection method was proposed based on emotional cognitive process theory and deep networks. But the proposed method is not suitable for the task of driving safety, comfort, and acceptance of intelligent vehicles.
References
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Journal ArticleDOI

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Journal ArticleDOI

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TL;DR: This personal historical article traces the development of the Big-Five factor structure, whose growing acceptance by personality researchers has profoundly influenced the scientific study of individual differences.
Book

What the face reveals : basic and applied studies of spontaneous expression using the facial action coding system (FACS)

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