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Digital Contents Society (한국디지털콘텐츠학회)
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A Study on Driver Experience in Autonomous Car Based on Trust and Distrust Model of Automation System

자율주행 자동차 환경에서의 운전자 경험에 대한 연구: 신뢰와 불신 형성 모형 중 심으로

  • 이지인 (연세대학교 일반대학원 인지과학협동과정 HCI 전공) ;
  • 김나은 (연세대학교 일반대학원 인지과학협동과정 HCI 전공) ;
  • 김진우 (연세대학교 경영학과 HCI 전공)
  • Received : 2017.06.16
  • Accepted : 2017.07.23
  • Published : 2017.07.31
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Abstract

Recently technological drive on autonomous vehicle is on the rush. Along with the trend, researches on driver's perspective are increasing. However, previous studies have limitations in terms of study period and rich experience. In this paper, we conducted an ethnographically inspired fieldwork to observe human-autonomous car interaction. We had six participants to ride a prototype autonomous car on the real road for six days. After, we generated trust, distrust factors according to Lee & See's categorization of trust dimension: process, performance, and purpose. We derived eight distrust factors that saliently influences passenger's experience in autonomous vehicle. Our research broadens trust model into autonomous driving context based on real road field study and contributes to automotive community with design guidelines to increase trust toward autonomous vehicle.

최근 자율주행 자동차에 대한 관심이 높아짐에 따라 자율주행 자동차 관련 기술 개발에 대한 활발한 연구가 진행되고 있다. 이에 따라 자율주행 환경에서의 운전자 관점에 대한 연구도 조금씩 늘어나고 있는 추세이다. 그러나 일부 연구들은 자율주행 자동차에 대한 낙관적인 입장만을 보이고 있다. 하지만, 선행 연구에서는 실제 자율주행 자동차를 태우지 않았다는 한계가 있다. 따라서, 본 연구에서는 자율주행 자동차를 기반으로 인간과 차량 간 상호작용을 알아보고자 에스노그라피 접근을 통한 질적 연구를 진행하였다. 그 결과, 자율주행 환경에서 운전자의 경험에 영향을 미치는 8개의 불신 요소를 도출하였다. 결과적으로 본 연구는 기존 신뢰 모형을 통해 자율주행 맥락에 적용하여 확장하였다는 점과 결과를 바탕으로 자율주행 환경에서 불신을 낮추고 신뢰를 높여줄 디자인 가이드를 제시했다는 점에서 이론적 및 실용적 의의가 있다.

Keywords

References

  1. B. Schettle and M. Sivak, "A Survey of Public Opinion about Autonomous and Self-Driving vehicles in the US, the UK and Australia,"Transportation Research Institute, Ann Arbor, MI, Rep. UMTRI-2014-21, 2014.
  2. Beale, R., & Creed, C. (2009). Affective interaction: How emotional agents affect users. International Journal of Human-Computer Studies, 67(9), 755-776. https://doi.org/10.1016/j.ijhcs.2009.05.001
  3. Carter, L., & Belanger, F. (2005). The utilization of e-government services: Citizen trust, innovation and acceptance factors. Information Systems Journal, 15, 5-25. https://doi.org/10.1111/j.1365-2575.2005.00183.x
  4. Choi, J. K., & Ji, Y. G.2015. Investigating the Importance of Trust on Adopting an Autonomous Vehicle. International Journal of Human-Computer Interaction, 31(10), 692-702. https://doi.org/10.1080/10447318.2015.1070549
  5. Christensen, L. B., Johnson, B., & Turner, L. A. (2011). Research methods, design, and analysis (pp. 1-539). Allyn & Bacon.
  6. Deutsch, M. 1958. "Trust and Suspicion,"Journal of Conflict Resolution (2), pp. 265-279. https://doi.org/10.1177/002200275800200401
  7. Dimoka A., Pavlou, P. A., and Davis, F. 2010. "NeuroIS: The Potential of Cognitive Neuroscience for Information Systems Research," Information Systems Research, forthcoming.
  8. Dixon, S. R., Wickens, C. D., & McCarley, J. S. (2007). On the independence of compliance and reliance: Are automation false alarms worse than misses?.Human Factors: The Journal of the Human Factors and Ergonomics Society,49(4), 564-572 https://doi.org/10.1518/001872007X215656
  9. E. Adell, A. Varhelyi, and M. Fontana, "The effects of a driver assistance system for safe speed and safe distance-A real life field study,"Transportation research p1. art C: emerging technologies, vol.19, no.1, 2011, pp. 145-155. https://doi.org/10.1016/j.trc.2010.04.006
  10. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27, 51-90. https://doi.org/10.2307/30036519
  11. Ghazizadeh, M., Peng, Y., Lee, J. D., & Boyle, L. N. (2012, September). Augmenting the technology acceptance model with trust: Commercial drivers' attitudes towards monitoring and feedback. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 56, No. 1, pp. 2286-2290). Sage Publications.
  12. Grovier T. 1994. "An Epistemology of Trust," International Journal of Moral Social Studies (8), pp. 155-174
  13. Rhiu, I., Kwon, S., Bahn, S., Yun, M. H., & Yu, W. (2015). Research Issues in Smart Vehicles and Elderly Drivers: A Literature Review. International Journal of Human-Computer Interaction, 31(10), 635-666. https://doi.org/10.1080/10447318.2015.1070540
  14. K. Cho and J. Moon, "Direction for Support of MOTIE R&D in Autonomous Driving Vehicle,"Journal of KSAE, vol. 36, no. 7, 2014, pp. 20-25
  15. Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors: The Journal of the Human Factors and Ergonomics Society, 46(1), 50-80. https://doi.org/10.1518/hfes.46.1.50.30392
  16. Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors: The Journal of the Human Factors and Ergonomics Society, 46(1), 50-80. https://doi.org/10.1518/hfes.46.1.50.30392
  17. Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors: The Journal of the Human Factors and Ergonomics Society, 46(1), 50-80. https://doi.org/10.1518/hfes.46.1.50.30392
  18. Lee, J., & Moray, N. (1992). Trust, control strategies and allocation of function in human-machine systems. Ergonomics, 35, 1243-1270. https://doi.org/10.1080/00140139208967392
  19. LuhmannN. 1979. Trust and Power, Chichester, UK: Wiley
  20. Merriam, S. B. (1988). Case study research in education: A qualitative approach. Jossey-Bass.
  21. Meyer, J., Wiczorek, R., & Gunzler, T. (2014). Measures of Reliance and Compliance in Aided Visual Scanning. Human Factors: The Journal of the Human Factors and Ergonomics Society, 56(5), 840-849 https://doi.org/10.1177/0018720813512865
  22. Parasuraman R, Riley V. Humans and automation: Use, misuse, disuse, abuse. Human Factors: The Journal of the Human Factors and Ergonomics Society. 1997;39(2):230-53 https://doi.org/10.1518/001872097778543886
  23. Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2008). Situation awareness, mental workload, and trust in automation: Viable, empirically supported cognitive engineering constructs. Journal of Cognitive Engineering and Decision Making, 2, 140-160. https://doi.org/10.1518/155534308X284417
  24. Payre, W., Cestac, J., & Delhomme, P. (2014). Intention to use a fully automated car: Attitudes and a priori acceptability. Transportation research part F: traffic psychology and behaviour, 27, 252-263. https://doi.org/10.1016/j.trf.2014.04.009
  25. Rhiu, I., Kwon, S., Bahn, S., Yun, M. H., & Yu, W. 2015. Research Issues in Smart Vehicles and Elderly Drivers: A Literature Review. International Journal of Human-Computer Interaction, 31(10), 635-666. https://doi.org/10.1080/10447318.2015.1070540
  26. Sheridan, T. B. (1975). Considerations in modeling the human supervisory controller. International Federation of Automatic Control, Triennial World Congress, 6th, 40.
  27. Sheridan, T. B., & Hennessy, R. T. (1984). Research and modeling of supervisory control behavior. Report of a workshop. Washington DC: National Research Council, Committee on Human Factors
  28. Silverman, D. (2013). Doing qualitative research: A practical handbook. SAGE Publications Limited.
  29. Ullmann-Margalit, E. 2004. "Trust, Distrust, and in Between," in Distrust, R. Hardin (ed.), New York: Russell Sage Foundation, pp. 60-82.
  30. Y. Kong, "Trends and direction of Google Car,"KISDI., JinChon, Korea, 2013, vol. 25.

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