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extended-abstract

Emotion GaRage Vol. II:: A Workshop on Affective In-Vehicle Display Design

Published:21 September 2020Publication History

ABSTRACT

Driver performance and behavior can be partially predicated based on one's emotional state. Through ascertaining the emotional state of passengers and employing various mitigation strategies, empathic cars can show potential in improving user experience and driving performance. Challenges remain in the implementation of such strategies, as individual differences play a large role in mediating the effect of affective intervention. Therefore, we propose a workshop that aims to bring together researchers and practitioners interested in affective interfaces and in-vehicle technologies as a forum for the development of targeted emotion intervention methods. During the workshop, we will focus on a common set of use cases and generate approaches that can suit different user groups. By the end of this short workshop, researchers will determine ideal intervention methods for prospective user groups. This will be achieved through the method of insight combination to generate and discuss ideas.

References

  1. M. Jeon, 2015.“Towards affect-integrated driving behaviour research,” Theor. Issues Ergon. Sci., vol. 16, no. 6, pp. 553–585, 2015, doi: 10.1080/1463922X.2015.1067934.Google ScholarGoogle ScholarCross RefCross Ref
  2. G. Underwood, P. Chapman, S. Wright, and D. Crundall, 1999.“Anger while driving,” Transp. Res. Part F Traffic Psychol. Behav., vol. 2, no. 1, pp. 55–68, 1999, doi: 10.1016/S1369-8478(99)00006-6.Google ScholarGoogle ScholarCross RefCross Ref
  3. M. Jeon, 2017.“Emotions and affect in human factors and human–computer interaction: Taxonomy, theories, approaches, and methods,” in Emotions and Affect in Human Factors and Human-Computer Interaction, Elsevier, 2017, pp. 3–26.Google ScholarGoogle Scholar
  4. H. Sanghavi, 2020.“Exploring the Influence of anger on takeover performance in semi-automated vehicles,” Virginia Polytechnic Institute and State University, 2020.Google ScholarGoogle Scholar
  5. E. R. Dahlen and R. P. White, 2006.“The Big Five factors, sensation seeking, and driving anger in the prediction of unsafe driving,” Pers. Individ. Dif., vol. 41, no. 5, pp. 903–915, 2006, doi: 10.1016/j.paid.2006.03.016.Google ScholarGoogle ScholarCross RefCross Ref
  6. D. C. Schwebel, J. Severson, K. K. Ball, and M. Rizzo, 2006.“Individual difference factors in risky driving: The roles of anger/hostility, conscientiousness, and sensation-seeking,” Accid. Anal. Prev., vol. 38, no. 4, pp. 801–810, 2006, doi: 10.1016/j.aap.2006.02.004.Google ScholarGoogle ScholarCross RefCross Ref
  7. A. Shahar, 2009.“Self-reported driving behaviors as a function of trait anxiety,” Accid. Anal. Prev., vol. 41, no. 2, pp. 241–245, 2009, doi: 10.1016/j.aap.2008.11.004.Google ScholarGoogle ScholarCross RefCross Ref
  8. J. E. Taylor, M. J. Connolly, R. Brookland, and A. Samaranayaka, 2018.“Understanding driving anxiety in older adults,” Maturitas, vol. 118, no. September, pp. 51–55, 2018, doi: 10.1016/j.maturitas.2018.10.008.Google ScholarGoogle ScholarCross RefCross Ref
  9. E. R. Dahlen, R. C. Martin, K. Ragan, and M. M. Kuhlman, 2005.“Driving anger, sensation seeking, impulsiveness, and boredom proneness in the prediction of unsafe driving,” Accid. Anal. Prev., vol. 37, no. 2, pp. 341–348, 2005, doi: 10.1016/j.aap.2004.10.006.Google ScholarGoogle ScholarCross RefCross Ref
  10. M. Jeon, B. N. Walker, and J. Bin Yim, 2014.“Effects of specific emotions on subjective judgment, driving performance, and perceived workload,” Transp. Res. Part F Traffic Psychol. Behav., vol. 24, pp. 197–209, 2014, doi: 10.1016/j.trf.2014.04.003.Google ScholarGoogle ScholarCross RefCross Ref
  11. S. Jansen, A. Westphal, M. Jeon, and A. Riener, 2013.“Detection of Drivers’ Incidental and Integral Affect Using Physiological Measures,” Proc. 5th Int. Conf. Automot. User Interfaces Interact. Veh. Appl. (AutomotiveUI ’13), no. June 2014, pp. 97–98, 2013, [Online]. Available: http://www.researchgate.net/publication/257985342_Detection_of_Drivers’_Incidental_and_Integral_Affect_Using_Physiological_Measures/file/3deec528080a401cd0.pdf.Google ScholarGoogle Scholar
  12. K. Ngamsomphornpong and Y. Punsawad, 2019.“Development of Hybrid EEG-fEMG-based Stress Levels Classification and Biofeedback Training System,” ACM Int. Conf. Proceeding Ser., pp. 25–28, 2019, doi: 10.1145/3332340.3332349.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. S. M. Fakhrhosseini, S. Landry, Y. Y. Tan, S. Bhattarai, and M. Jeon, 2014.“If you're angry, turn the music on: Music can mitigate anger effects on driving performance,” AutomotiveUI 2014 - 6th Int. Conf. Automot. User Interfaces Interact. Veh. Appl. Coop. with ACM SIGCHI - Proc., no. September, 2014, doi: 10.1145/2667317.2667410.Google ScholarGoogle Scholar
  14. C. Jones and I. M. Jonsson, 2008.“Using paralinguistic cues in speech to recognise emotions in older car drivers,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 4868 LNCS, pp. 229–240, 2008, doi: 10.1007/978-3-540-85099-1_20.Google ScholarGoogle Scholar
  15. K. Ihme, C. Dömeland, M. Freese, and M. Jipp, 2018.“Frustration in the face of the driver: a simulator study on facial muscle activity during frustrated driving,” Interact. Stud., vol. 19, no. 3, pp. 487–498, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  16. I.-M. Jonsson, M. Zajicek, H. Harris, and C. Nass, 2005.“Thank you, I did not see that: in-car speech based information systems for older adults,” in CHI’05 Extended Abstracts on Human Factors in Computing Systems, 2005, pp. 1953–1956.Google ScholarGoogle Scholar
  17. B. Donmez, L. N. Boyle, and J. D. Lee, 2006.“The impact of distraction mitigation strategies on driving performance,” Hum. Factors, vol. 48, no. 4, pp. 785–804, 2006, doi: 10.1518/001872006779166415.Google ScholarGoogle ScholarCross RefCross Ref
  18. F. Steinberger, R. Schroeter, and C. N. Watling, 2017.“From road distraction to safe driving: Evaluating the effects of boredom and gamification on driving behaviour, physiological arousal, and subjective experience,” Comput. Human Behav., vol. 75, pp. 714–726, 2017, doi: 10.1016/j.chb.2017.06.019.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. L. M. Lundqvist and L. Eriksson, 2019.“Age, cognitive load, and multimodal effects on driver response to directional warning,” Appl. Ergon., vol. 76, no. December 2018, pp. 147–154, 2019, doi: 10.1016/j.apergo.2019.01.002.Google ScholarGoogle ScholarCross RefCross Ref
  20. L. Kourkouta, C. Iliadis, and A. Monios, 2015.“Psychosocial issues in elderly,” Prog. Heal. Sci., vol. 5, no. 1, pp. 232–237, 2015.Google ScholarGoogle Scholar
  21. H. J. Foy, P. Runham, and P. Chapman, 2016.“Prefrontal cortex activation and young driver behaviour: A fNIRS study,” PLoS One, vol. 11, no. 5, pp. 1–18, 2016, doi: 10.1371/journal.pone.0156512.Google ScholarGoogle ScholarCross RefCross Ref
  22. J. Li, A. Butz, M. Braun, and F. Alt, 2019.“Designing emotion-aware in-car interactions for unlike markets,” Adjun. Proc. - 11th Int. ACM Conf. Automot. User Interfaces Interact. Veh. Appl. AutomotiveUI 2019, pp. 352–357, 2019, doi: 10.1145/3349263.3351324.Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. E. Bosch ., 2018.“Emotional GaRage: A workshop on in-car emotion recognition and regulation,” Adjun. Proc. - 10th Int. ACM Conf. Automot. User Interfaces Interact. Veh. Appl. AutomotiveUI 2018, pp. 44–49, 2018, doi: 10.1145/3239092.3239098.Google ScholarGoogle ScholarDigital LibraryDigital Library

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  • Published in

    cover image ACM Conferences
    AutomotiveUI '20: 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
    September 2020
    116 pages
    ISBN:9781450380669
    DOI:10.1145/3409251

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    • Published: 21 September 2020

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