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Fluid Interface Concept for Automated Driving

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HCI in Mobility, Transport, and Automotive Systems. Automated Driving and In-Vehicle Experience Design (HCII 2020)

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Abstract

The biggest challenge for a human-machine interface in highly automated vehicles is to provide enough information to the potentially unaware human operator to induce an appropriate response avoiding cognitive overload. Current interface design struggles to provide timely and relevant information tailored for future driver’s needs. Therefore, a new human-centered approach is required to connect drivers, vehicles and infrastructures and account for non-driving related activities in the forthcoming automated vehicles. A viable solution derives from a holistic approach that merges technological tools with human factors knowledge, to enable the understanding and resolution of potential usability, trust and acceptance issues. In this paper, the human factors challenges introduced by automated driving provide the starting point for the conceptualization of a new Fluid interface. The requirements for the new concept are derived from a systematic analysis of the necessary interactions among driver, vehicle and environment. Therefore, the characteristics, components and functions of the interface are described at a theoretical level and compared to alternative solutions.

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References

  1. Oliveira, L., Proctor, K., Burns, C.G., Birrell, S.: Driving style: how should an automated vehicle behave? Information 10(6), 219 (2019). https://doi.org/10.3390/info10060219

    Article  Google Scholar 

  2. Lu, Z., Happee, R., Cabrall, C.D.D., Kyriakidis, M., de Winter, J.C.F.: Human factors of transitions in automated driving: a general framework and literature survey. Transp. Res. Part F Traffic Psychol. Behav. 43, 183–198 (2016). https://doi.org/10.1016/j.trf.2016.10.007

    Article  Google Scholar 

  3. Kyriakidis, M., et al.: A human factors perspective on automated driving. Theor. Issues Ergon. Sci. 20(3), 2017 (2019). https://doi.org/10.1080/1463922X.2017.1293187

    Article  Google Scholar 

  4. Nordhoff, S., de Winter, J., Kyriakidis, M., van Arem, B., Happee, R.: Acceptance of driverless vehicles: results from a large cross-national questionnaire study. J. Adv. Transp. (2018). https://www.hindawi.com/journals/jat/2018/5382192/. Accessed 04 June 2018

  5. Cunningham, M., Regan, M.A.: Autonomous vehicles: human factors issues and future research. ResearchGate (2015). https://www.researchgate.net/publication/310327242_Autonomous_Vehicles_Human_Factors_Issues_and_Future_Research. Accessed 17 Feb 2020

  6. de Winter, J.C.F., Happee, R., Martens, M.H., Stanton, N.A.: Effects of adaptive cruise control and highly automated driving on workload and situation awareness: a review of the empirical evidence. Transp. Res. Part F Traffic Psychol. Behav. 27, 196–217 (2014). https://doi.org/10.1016/j.trf.2014.06.016

    Article  Google Scholar 

  7. Parasuraman, R., Sheridan, T.B., Wickens, C.D.: A model for types and levels of human interaction with automation. IEEE Trans. Syst. Man Cybern. Part Syst. Hum. Publ. IEEE Syst. Man Cybern. Soc. 30(3), 286–297 (2000). https://doi.org/10.1109/3468.844354

    Article  Google Scholar 

  8. Skottke, E.-M., Debus, G., Wang, L., Huestegge, L.: Carryover effects of highly automated convoy driving on subsequent manual driving performance. Hum. Factors 56(7), 1272–1283 (2014). https://doi.org/10.1177/0018720814524594

    Article  Google Scholar 

  9. Diels, C., Bos, J.E.: User interface considerations to prevent self-driving carsickness, pp. 14–19 (2015). https://doi.org/10.1145/2809730.2809754

  10. Iskander, J., et al.: From car sickness to autonomous car sickness: a review. Transp. Res. Part F Traffic Psychol. Behav. 62, 716–726 (2019). https://doi.org/10.1016/j.trf.2019.02.020

    Article  Google Scholar 

  11. Kennedy, R.S., Frank, L.H.: A Review of Motion Sickness with Special Reference to Simulator Sickness. Defense Technical Information Center, Fort Belvoir (1985)

    Book  Google Scholar 

  12. Wada, T. (ed.): Motion sickness in automated vehicles. Advanced Vehicle Control AVEC 2016: Proceedings of the 13th International Symposium on Advanced Vehicle Control (AVEC 2016), Munich, Germany, 13–16 September 2016, CRC Press/Balkema (2016). P.O. Box 11320, 2301 EH Leiden, The Netherlands, e-mail: Pub.NL@taylorandfrancis.com, www.crcpress.com – www.taylorandfrancis.com: Crc Press

  13. Salter, S., Diels, C., Herriotts, P., Kanarachos, S., Thake, D.: Motion sickness in automated vehicles with forward and rearward facing seating orientations. Appl. Ergon. 78, 54–61 (2019). https://doi.org/10.1016/j.apergo.2019.02.001

    Article  Google Scholar 

  14. Haspiel, J., et al.: Explanations and expectations: trust building in automated vehicles. In: Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction - HRI 2018, Chicago, IL, USA, 2018, pp. 119–120 (2018). https://doi.org/10.1145/3173386.3177057

  15. Fridman, L.: Human-centered autonomous vehicle systems: principles of effective shared autonomy. ArXiv181001835 Cs, October 2018

    Google Scholar 

  16. Boelhouwer, A., van Dijk, J., Martens, M.H.: Turmoil behind the automated wheel. In: Krömker, H. (ed.) HCII 2019. LNCS, vol. 11596, pp. 3–25. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22666-4_1

    Chapter  Google Scholar 

  17. Carsten, O., Martens, M.H.: How can humans understand their automated cars? HMI principles, problems and solutions. Cogn. Technol. Work 21(1), 3–20 (2019). https://doi.org/10.1007/s10111-018-0484-0

    Article  Google Scholar 

  18. Portouli, E., et al.: Methodologies to understand the road user needs when interacting with automated vehicles. In: Krömker, H. (ed.) HCII 2019. LNCS, vol. 11596, pp. 35–45. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22666-4_3

    Chapter  Google Scholar 

  19. Audi Experience Ride. audi.com (2019). https://www.audi.com/en/experience-audi/mobility-and-trends/digitalization/experience-ride.html. Accessed 12 Dec 2019

  20. Audi Immersive In-Car Entertainment. Audi MediaCenter (2019). https://www.audi-mediacenter.com:443/en/audi-at-the-2019-ces-11175/audi-immersive-in-car-entertainment-11180. Accessed 12 Dec 2019

  21. Toyota Concept-i | The Car of the Future (2019). https://www.toyota.com/concept-i/. Accessed 12 Dec 2019

  22. Nissan unveils Invisible-to-Visible technology concept at CES. 日産自動車ニュースルーム, 03 January 2019. https://global.nissannews.com/ja-JP/releases/nissan-unveils-invisible-to-visible-technology-concept-at-ces. Accessed 25 Feb 2020

  23. Consumer Electronics Show (CES) 2020: In collaboration with the AVATAR films, Mercedes-Benz is developing a vision for the future of mobility: the VISION AVTR. marsMediaSite (2020). https://media.daimler.com/marsMediaSite/en/instance/ko/Consumer-Electronics-Show-CES-2020-In-collaboration-with-the-AVATAR-films-Mercedes-Benz-is-developing-a-vision-for-the-future-of-mobility-the-VISION-AVTR.xhtml?oid=45322778. Accessed 10 Jan 2020

  24. The Mercedes-Benz F 015 Luxury in Motion (2015). https://www.mercedes-benz.com/en/innovation/autonomous/research-vehicle-f-015-luxury-in-motion/. Accessed 25 Feb 2020

  25. BMW i Interaction EASE technology unveiled at CES 2020 in Las Vegas. BMW BLOG, 07 January 2020. https://www.bmwblog.com/2020/01/07/bmw-i-interaction-ease-technology-unveiled-at-ces-2020-in-las-vegas/. Accessed 25 Feb 2020

  26. #IAA2017 Renault SYMBIOZ: the vision of the future of mobility - Groupe Renault (2017). https://group.renault.com/en/news-on-air/news/renault-symbioz-the-vision-of-the-future-of-mobility/. Accessed 25 Feb 2020

  27. Faurecia: When Driving Becomes the Distraction: Faurecia to Explore Future of Autonomous Driving, Share Research at Connected Car Expo (2017). https://www.prnewswire.com/news-releases/when-driving-becomes-the-distraction-faurecia-to-explore-future-of-autonomous-driving-share-research-at-connected-car-expo-300180095.html. Accessed 01 Mar 2020

  28. Diaper, D., Stanton, N.: The Handbook of Task Analysis for Human-Computer Interaction, p. 568 (2003)

    Google Scholar 

  29. Doignon, J.-P., Falmagne, J.-C.: Spaces for the assessment of knowledge. Int. J. Man-Mach. Stud. 23(2), 175–196 (1985). https://doi.org/10.1016/S0020-7373(85)80031-6

    Article  MATH  Google Scholar 

  30. Schöner, H.-P., Pretto, P., Sodnik, J., Kaluza, B., Komavec, M., Varesanovic, D.: Driving style score based on statistical driving behaviour. In: Presented at the FISITA world congress (2020, in press)

    Google Scholar 

  31. Abe, R.: Introducing autonomous buses and taxis: quantifying the potential benefits in Japanese transportation systems. Transp. Res. Part Policy Pract. 126, 94–113 (2019). https://doi.org/10.1016/j.tra.2019.06.003

    Article  Google Scholar 

  32. de Winkel, K.N., Pretto,P., Nooij, S.A.E., Cohen, I., Bülthoff, H.H.: Efficacy of peripheral and anticipatory visual cues for reducing sickness in autonomous vehicles. Displays, submitted

    Google Scholar 

  33. Adaptive User Interfaces, Principles and Practice. https://www.elsevier.com/books/adaptive-user-interfaces/schneider-hufschmidt/978-0-444-81545-3. Accessed 27 Feb 2020

  34. Dix, A., et al.: Intelligent context-sensitive interactions on desktop and the web 2006, 23–27 (2006). https://doi.org/10.1145/1145706.1145710

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Acknowledgments.

HADRIAN has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875597. The publication was written at VIRTUAL VEHICLE Research GmbH in Graz, Austria and partially funded by the COMET K2 – Competence Centers for Excellent Technologies Programme of the Federal Ministry for Transport, Innovation and Technology (bmvit), the Federal Ministry for Digital, Business and Enterprise (bmdw), the Austrian Research Promotion Agency (FFG), the Province of Styria and the Styrian Business Promotion Agency (SFG).

The authors would like to thank Bernd Fachbach for insightful discussions during the preparation of the manuscript.

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Authors and Affiliations

  1. Virtual Vehicle Research GmbH, 8010, Graz, Austria

    Paolo Pretto, Peter Mörtl & Norah Neuhuber

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  1. Paolo Pretto
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  2. Peter Mörtl
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Correspondence to Paolo Pretto .

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  1. Institute of Media Technology, Ilmenau University of Technology, Ilmenau, Germany

    Heidi Krömker

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Pretto, P., Mörtl, P., Neuhuber, N. (2020). Fluid Interface Concept for Automated Driving. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. Automated Driving and In-Vehicle Experience Design. HCII 2020. Lecture Notes in Computer Science(), vol 12212. Springer, Cham. https://doi.org/10.1007/978-3-030-50523-3_9

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  • DOI: https://doi.org/10.1007/978-3-030-50523-3_9

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