Towards Understanding Emotional Reactions of Driver-Passenger Dyads in Automated Driving

Alyüz, Neşe; Aslan, Sinem; Healey, Jennifer; Álvarez, Ignacio; Esme, Asli Arslan

doi:10.1109/fg.2018.00093

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…A post-hoc review of positive and negative emotion induction in higher fidelity automated (2) and manual (1) driving experiments indicate greater robustness for negative emotion inductions: greater number of inductions [37], range of induction [38] and inter-rater reliability [39]. A broad literature review indicates that scenario based methods for emotional induction are more robust in negative than positive cases [40].…”

Section: Discussionmentioning

confidence: 99%

Extrapolating significance of text-based autonomous vehicle scenarios to multimedia scenarios and implications for user-centered design

Robinson

Robert

Eglash

2021

2021 30th IEEE International Conference on Robot &Amp; Human Interactive Communication (RO-MAN)

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Extrapolation from low-fidelity design iterations is especially critical in HRI. An initial proposal for low-fidelity to higher fidelity extrapolation is developed using insights from cognitive multimedia learning theory to account for the effects of prototype medium and three types of cognitive demands. Inspired by Donald Norman and others, our proposal leverages tightly controlled and multi-authored scenarios through crowdsourcing to create additional potential evidence as a kind of experimental "stress test." We motivate our proposal by investigating the intersection of emotion and human control, which is understudied outside of autonomous vehicles (AV) and HRI research. Evidence for positively moderated emotional effects in text-based AV scenarios as well as tentative evidence for our extrapolation proposal are identified.

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Section: Discussionmentioning

confidence: 99%

Extrapolating significance of text-based autonomous vehicle scenarios to multimedia scenarios and implications for user-centered design

Robinson

Robert

Eglash

2021

2021 30th IEEE International Conference on Robot &Amp; Human Interactive Communication (RO-MAN)

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“…While advances in group emotion recognition have been made, existing approaches have shortcomings, such as assuming the group to share one common emotion, largely relying on just one modality and not considering the evolution of emotions over time [127]. Group affect in the car is rarely investigated, one such work being a study of Alyuz et al, who examine the emotions of driver-passenger dyads in simulated autonomous driving [131].…”

Section: Group Affect and Priorisationmentioning

confidence: 99%

Audiovisual Affect Recognition for Autonomous Vehicles: Applications and Future Agendas

Karas,

Schuller,

Schuller

2024

IEEE Trans. Intell. Transport. Syst.

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Emotion and a broader range of affective and cognitive states play an important role on the road. While this has been predominantly investigated in terms of driver safety, the approaching advent of autonomous vehicles (AVs) is expected to bring a fundamental shift in focus for emotion recognition in the car, from the driver to the passengers. This work presents a number of affect-enabled applications, including adapting the driving style for an emotional experience or tailoring the infotainment to personal preferences. It attempts to foresee upcoming challenges and provides suggestions for multimodal affect modelling, with a focus on the audio and visual modalities. In particular, this includes context awareness, reliable diarisation of multiple passengers, group affect, and personalisation. Finally, we provide some recommendations on future research directions, including explainability, privacy, and holistic modelling.

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The SKYNIVI Experience: Evoking Startle and Frustration in Dyads and Single Drivers

Álvarez

Healey

Lewis

2019

2019 IEEE Intelligent Vehicles Symposium (IV)

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Towards Understanding Emotional Reactions of Driver-Passenger Dyads in Automated Driving

Cited by 4 publications

References 22 publications

Extrapolating significance of text-based autonomous vehicle scenarios to multimedia scenarios and implications for user-centered design

Extrapolating significance of text-based autonomous vehicle scenarios to multimedia scenarios and implications for user-centered design

Audiovisual Affect Recognition for Autonomous Vehicles: Applications and Future Agendas

The SKYNIVI Experience: Evoking Startle and Frustration in Dyads and Single Drivers

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