Influencing Factors on Social Acceptance of Autonomous Vehicles and Policy Implications

자율주행자동차의 사회 수용에 미치는 영향 요인과 정책적 시사점

  • 이지혜 (이화여자대학교 융합콘텐츠학과) ;
  • 장형식 (연세대학교 기술정책협동과정) ;
  • 박영일 (이화여자대학교 융합콘텐츠학과)
  • Received : 2018.05.08
  • Accepted : 2018.06.11
  • Published : 2018.06.30

Abstract

The introduction of autonomous vehicles will bring about not only changes in existing automotive ecosystem but also widespread changes in our lives, society, economy, and culture. Social acceptance is one of important influencing factors for the commercialization of autonomous vehicles. The purpose of this study analyzes influencing factors in the acceptance of autonomous vehicles in terms of consumers. Autonomous vehicles in this study were defined as PAV (Partial Autonomous Vehicles) and FAV (Full Autonomous Vehicles) by drivers' intervention or not. The survey was conducted over 20 years old including not only drivers but also non-drivers. The results showed that the factors affecting acceptance of PAV and FAV were different. Factors directly related to drivers influenced PAV acceptance while external environmental factors influenced FAV acceptance. This study is proved that is should need different strategies between PAV and FAV for increasing those acceptance

자율주행자동차의 도입은 자동차의 산업생태계 변화뿐만 아니라 사회적, 문화적, 경제적 변화를 가져올 것이다. 사회적 수용성은 자율주행자동차 상용화가 성공하기 위한 중요한 영향 요인 중 하나이다. 본 연구는 수요자 관점에서 자율주행자동차의 수용에 영향을 주는 요인들이 무엇인지 분석하였다. 본 연구에서는 운전자의 개입 여부에 따라 부분자율주행자동차(PAV)와 완전자율주행자동차(FAV)로 정의하였다. 설문은 운전자뿐만 아니라 비운전자도 포함하여 20세 이상을 대상으로 수행되었다. 그 결과 PAV와 FAV 수용에 영향을 미치는 요인들은 다르게 나타났다. PAV의 경우 운전자와 직접적인 관련이 있는 요인들이 수용성에 영향을 미쳤고, FAV의 경우 외부 환경 요인들이 자율주행자동차의 수용에 영향을 미치는 것으로 나타났다. 이러한 결과는 PAV와 FAV의 수용 확산을 위해서는 서로 다른 전략이 필요하다는 것을 보여주었다.

Keywords

References

  1. 강선준.김민지 (2017), 자율주행자동차 활성화를 위한 법제 개선방안 및 입법(안) 제안, 서울 : 한국과학기술기획평가원.
  2. 국토교통부 (2016), 제5차 규제개혁장관회의-드론.자율주행차 등 신산업규제혁신, 세종 : 국토교통부.
  3. 국토교통부 (2017), "국토교통부 자율차 정책과 미래전략", 2017 대국국제미래자동차엑스포 발표
  4. 김지윤 (2018), "공유경제를 향한 완성차 업체들의 자율주행차 개발", KOTRA해 외시장뉴스 https://news.kotra.or.kr/user/globalAllBbs/kotranews/album/2/globalBbsDataAllView.do?dataIdx=165724&column=&search=&searchAreaCd=&searchNationCd=&searchTradeCd=&searchStartDate=&searchEndDate=&searchCategoryIdxs=&searchIndustryCateIdx=&page=1&row=10 (2018.04.25.).
  5. 박준환 (2017), 자율주행자동차 관련 국내외 입법.정책 동향과 과제, 서울 : 국회입법조사처.
  6. 박형근 (2016), 자율주행자동차를 둘러싼 논란-긍정적 효과 vs. 뛰어넘어야할 허들, 서울 : POSCO 경영연구원.
  7. 아주대학교 산학협력단 (2016), 자율주행자동차 상용화 대비 도로교통법 개정 방안 연구, 서울 : 경찰청.
  8. 오원석 (2016), "구글자율주행차, 첫 사고 기록 책임인정", http://www.bloter.net/archives/251067/ (2018.04.11.).
  9. 이기영.김수희 (2016), "자율주행시대 도로교통검지체계 구상", 대한토목학회 학술대회, 15-16.
  10. 이병윤 (2016), "국내외 자율주행자동차 기술개발 동향과 전망", 한국통신학회지, 33(4): 10-16.
  11. 이재관 (2017), "자율주행, 진화를 앞둔 자동차산업", 오토저널, 39(6): 56-60.
  12. 이중기 (2016), "자율주행차 운행의 법적 이슈", 월간교통, 2-4.
  13. 정경오 (2016), 자율주행자동차의 법적 쟁점, 서울 : Hanjoong LLP.
  14. 정보통신기술진흥센터(IITP) (2016), 해외 자율주행자동차 정책동향-미국, 유럽 일본, 대전 : 정보통신기술진흥센터.
  15. 최남호.김효창.최종규.지용구 (2015), "미래형 자율주행자동차의 정책수립을 위한 연구", 대한산업공학회지, 41(1): 5-58.
  16. 트렌드모니터(Trend Monitor) (2010), 자동차 관련 조사 : 경차 vs 전기차 vs 하이브리드(한, 중, 대만 3개국 공동조사), 서울 : 트렌드모니터.
  17. 한국과학기술기획평가원(KISTEP) (2013), 2013 KISTEP 10대 미래유망기술 선정에 관한 연구 : 미래 한국사회의 '스마트 에이징'선도를 위한 유망기술, 서울 : 한국과학기술기획평가원.
  18. 한상희 (2018), "우버 자율주행차 첫 보행자 사망사고, 자동차, IT업계 깊어지는 고민", http://www.ekn.kr/news/article.html?no=350352/ (2018.04.11.).
  19. 허건수 (2017), "자율주행자동차의 상용화는 언제?", 오토저널, 39(6): 61-64.
  20. 호드 립슨.멜바 컬만 (2017), 넥스트모바일: 자율주행혁명 (박세연 옮김), 서울 : 더퀘스트.
  21. 황상규.조선아 (2016), "미래형 자동차의 수용성 분석을 통한 정책적 시사점", 월간교통, 5-13.
  22. 황승환 (2017), "모델S 사망사고, 경고 수 차례 무시한 운전자 과실 결론", http://thegear.co.kr/14710/ (2018.04.11.).
  23. Adell, E. (2009), "Driver Experience and Acceptance of Driver Support Systems: A Case of Speed Adaption", Ph.D. thesis, Lund University, Lund, Sweden.
  24. Alm, C. and Lindberg, E. (2000), "Perceived Risk, Feelings of Safety and Worry Associated with Different Travel Modes. Pilot study", KFB (Kommunikationsforskningsberedningen, Sweden), Linkoping University.
  25. Banuls Eseda, R., Carbonell Vaya, E., Casonoves, M. and Chisvert, M. (1996), "Different Emotional Responses in Novice and Professional Drivers", In Proceedings of the International Conference on Traffic and Transport Psychology, 343-352.
  26. Beggiato, M., Hartwich, F., Schleinitz, K., Krems, J., Othersen, I. and Petermann-Stock, I. (2015), "What Would Driver Like to Know During Automated Driving? Information Needs at Different Levels of Automation", In Proceedings of the 7th Conference on Driver Assistance, Munich, Germany, 1-5.
  27. Brookhuis, K., and de Waard, D. (2006), "The Consequences of Automation for Driver Behavior and Acceptance", In Proceedings of the 16th Triennial Congress of the International Ergonomics Association, Maastricht, Netherlands, 10-14.
  28. Choi, J. K. and 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
  29. Davis, F. D. (1989), "Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Theory", MIS Quarterly, 13: 319-340. https://doi.org/10.2307/249008
  30. European Road Transport Research Advisory Council (ERTRAC) (2015), Automated Driving Roadmap Version 5.0, ERTRAC.
  31. Fagnant, D. J. and Kockelman, K. (2015), "Preparing a Nation for Autonomous Vehicles: Opportunities, Barriers and Policy Recommendations", Transportation Research Part A: Policy and Practice, 77: 167-181. https://doi.org/10.1016/j.tra.2015.04.003
  32. Fagnant, D. J., Kockelman, K. M. and Bansal, P. (2015), "Operations of Shared Autonomous Vehicle Fleet for the Austin, Texas, Market", present at 94th TRB Annual Meeting.
  33. Fishbein, M. (1967), A behavioral theory approach to the relations between beliefs about an object and attitude toward that object, in M. Fishbein (Ed.), Readings in attitude theory and measurement, 389-400, New York: Wiley.
  34. Helldin, T., Falkman, G., Riveiro, M. and Davidsson, S. (2013), "Presenting System Uncertainty in Automotive UIs for Supporting Trust Calibration in Autonomous Driving", In Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Eindhoven, Netherlands, Oct. 28-30, 210-217.
  35. Kaan, J. (2017), "User Acceptance of Autonomous Vehicles: Factors and Implications", M.S. thesis, Delft University of Technology, Delft, Netherlands.
  36. Knapp, T. R. (1991), "Coefficient alpha: Conceptualizations and anomalies", Research in Nursing and Health, 14: 457-480. https://doi.org/10.1002/nur.4770140610
  37. Lewis, P., Rogers, G. and Turner, S. (2017), Beyond Speculation: Automated Vehicles and Public Policy: An Action Plan for Federal, State, and Local Policymakers, The Eno Center for Transportations.
  38. Lipson, H. and Kurman, M. (2017), Driverless: Intelligent Cars and the Road Ahead, The MIT Press.
  39. Litman, T. (2017), Autonomous Vehicle Implementation Predictors - Implications for Transport Planning, Victoria Transport Policy Institute.
  40. Madigan, R., Louw, T., Dziennus, M. and Graindorge, T. (2016), "Acceptance of Automated Road Transport Systems (ARTS): An Adaptation of the UTAUT Model", Transportation Research Procedia, 14: 2217-2226. https://doi.org/10.1016/j.trpro.2016.05.237
  41. Madigan, R., Louw, T., Wilbrink, M., Schieben, A. and Merat, N. (2017), "What Influences the Decision to Use Automated Public Transport? Using UTAUT to Understand Public Acceptance of Automated Road Transport Systems", Transportation Research Part F, 50: 55-64. https://doi.org/10.1016/j.trf.2017.07.007
  42. Ministry of Land, Infrastructure and Transport (2017), "MOLIT Policy and Future Strategy of Autonomous Vehicles", (in Korean) presented at Daegu International Future Auto EXPO, Daegu, Korea.
  43. Nees, M. A. (2016), "Acceptance of Self-driving Cars: An Examination of Idealized versus Realistic Portrayals with a Self-driving Car Acceptance Scale", presented at the Proceedings of the Human Factors and Ergonomics Society Annual Meeting.
  44. OECD (2014), Urban Mobility: System Upgrade, OECD.
  45. Osswald, S., Wurhofer, D., Trosterer, S., Beck, E. and Tscheligi, M. (2012), "Predicting Information Technology Usage in the Car: Towards a Car Technology Acceptance Model", In Proceedings of the 4th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Portsmouth, NH, USA, 51-58.
  46. Van de Ven, A. H. and Ferry, D. L. (1980), Measuring and Assessing Organization, New York: John Wiley&Sons.
  47. Venkatesh, V. and Davis, F. D. (2000), "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies", Management Science, 46: 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
  48. Venkatesh, V., Morris, M. G. and Davis, F. D. (2003), "User Acceptance of Information Technology: Toward a Unified View", MIS Quarterly, 27(3): 425-478. https://doi.org/10.2307/30036540
  49. Venkatesh, V., Thong, J. Y. L. and Xu, X. (2012), "Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology", MIS Quarterly, 36: 157-178. https://doi.org/10.2307/41410412
  50. Victoria Transport Policy Institute (2018), Autonomous Vehicle Implementation Predictions, Victoria Transport Policy Institute.
  51. Warrendale, P. (2016), "U.S. Department of Transportation's New Policy on Automated Vehicles Adopts SAE International's Levels of Automation for Defining Driving Automation in On-Road Motor Vehicles", https://www.sae.org/news/3544/, (10 Jan. 2018)
  52. Weyer, J., Fink, R. D. and Adelt, F. (2015), "Human-machine cooperation in smart cars. An empirical investigation of the loss-of-control thesis", Safety Science, 72: 199-208. https://doi.org/10.1016/j.ssci.2014.09.004