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Anthropomorphising driver-truck interaction: a study on the current state of research and the introduction of two innovative concepts

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Abstract

The general role of personal assistants in form of anthropomorphised conversational, virtual or robotic agents in cars is subject to research since a few years and the first results indicate numerous positive effects of these anthropomorphised interfaces. However, no comprehensive review of the conducted studies has been comprised yet. Furthermore, existing studies on the effect of anthropomorphism mainly focus on passenger cars. This article provides a comprehensive review and summary of the conducted studies and investigates the applicability to commercial transportation, in particular to anthropomorphised interaction between truck driver and truck. In the first part of the article, a literature review describes the details, aspects and various forms of anthropomorphism as well as its observed positives effects. The review focusses on studies referring to anthropomorphism in passenger cars, complemented by relevant research results from non-automotive disciplines. The second part of this article aims to derive innovative and applicable concepts for the anthropomorphised driver-truck interfaces using the Design-Thinking approach: building on a comprehensive literature review to identify user needs and problems, an interdisciplinary expert workshop developed the two first anthropomorphised driver-truck interaction concepts. The paper finishes with carving out the differences between anthropomorphised car-driver and truck-driver interaction. The next step of research will then be the implementation of the developed interaction concepts in a first prototype followed by the respective user evaluation.

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Notes

  1. https://www.nio.io/en_DE/es8.

  2. https://www.nio.io/en_DE/es8.

References

  1. Admoni H, Datsikas C, Scassellati B (2014) Speech and gaze conflicts in collaborative human-robot Interactions. In: 36th Annual conference of the Cognitive Science Society, Quebec City, Canada

  2. Aggarwal P, McGill AL (2007) Is that car smiling at me? Schema congruity as a basis for evaluating anthropomorphized products. J Consum Res 34(4):468–479

    Article  Google Scholar 

  3. Araújo R, Anjos E, Silva DR (2015) Trends in the use of design thinking for embedded systems. In: 15th International conference on computational science and its applications, Banff, Canada

  4. Audi (2017) Audi Elaine concept car highly automated at level 4. Press Release. https://bit.ly/2ED2MXm

  5. BAG (2016) Marktbeobachtung Güterverkehr: Auswertung der Arbeitsbedingungen in Güterverkehr und Logistik 2016-I. https://bit.ly/2tzALej

  6. BAG (2017) Marktbeobachtung Güterverkehr: Auswertung der Arbeitsbedingungen in Güterverkehr und Logistik 2017-I. https://bit.ly/2AaVwNN

  7. Benford S, Bowers J, Fahlén LE, Greenhalgh C, Snowdon D (1995) User embodiment in collaborative virtual environments. In: Proceedings of the SIGCHI conference on human factors in computing systems 1995, New York, USA

  8. Brave S, Nass C (2003) Emotion in human-computer interaction. The human-computer interaction handbook. ACM, Hillsdale, pp 81–96

    Google Scholar 

  9. Breazeal C (2002) Designing sociable robots. MIT Press, Cambridge

    MATH  Google Scholar 

  10. Cacilo A, Schmidt S, Wittlinger P, Herrmann F, Bauer W, Sawade O, Doderer H, Hartwig M, Scholz V (2015) Hochautomatisiertes Fahren auf Autobahnen—industriepolitische Schlussfolgerungen. Studie im Auftrag des Bundesministeriums für Wirtschaft und Energie (BMWi)

  11. Calo R (2010) Robots and privacy. In: Robot ethics: the ethical and social implications of robotics, MIT Press, Cambridge

  12. Casner SM, Hutchins EL, Norman D (2016) The challenges of partially automated driving. Commun ACM 59(5):70–77

    Article  Google Scholar 

  13. Cassell J (2000) Embodied conversational interface agents. Commun ACM 43(4):70–78

    Article  Google Scholar 

  14. Dacey M (2017) Anthropomorphism as cognitive bias. Philos Sci 84(5):1152–1164

    Article  Google Scholar 

  15. Damasio AR (1994) Descartes’ error. Emotion, reason and the human brain. Avon Books, New York

    Google Scholar 

  16. Darling K (2015) Whos Johnny? Anthropomorphic framing in human robot interaction, integration, and policy. In: Robot ethics 2.0: from autonomous cars to artificial intelligence. Oxford University Press

  17. Darling K, Nandy P, Breazeal C (2015) Empathic concern and the effect of stories in human-robot interaction. In: 24th IEEE international symposium on robot and human interactive communication, pp 770–775

  18. Dautenhahn K (1997) I could be you: the phenomenological dimension of social understanding. Cybern Syst 28(5):417–453

    Article  Google Scholar 

  19. Deci EL, Ryan RM (1995) Efficacy, agency, and self-esteem. Human autonomy. Springer, Boston, pp 31–49

    Google Scholar 

  20. Delgado-Ballester E, Palazn M, Pelaez-Muoz J (2017) This anthropomorphised brand is so loveable: the role of self-brand integration. Spanish J Market 21(2):89–101

    Article  Google Scholar 

  21. Derryberry D, Tucker DM (1992) Neural mechanisms of emotion. J Consult Clin Psychol 60(3):329–338

    Article  Google Scholar 

  22. Duffy BR (2003) Anthropomorphism and the social robot. Rob Auton Syst 42(3):177–190

    Article  MATH  Google Scholar 

  23. Ekman P (1957) A methodological discussion of nonverbal behavior. J Psychol 43(1):141–149

    Article  Google Scholar 

  24. Ekman P, Friesen WV, O’Sullivan M, Diacoyanni-Tarlatzis I, Krause R, Pitcairn T, Scherer K, Chan A, Heider K, LeCompte WA, Ricci-Bitti PE, Tomita M, Tzavaras A (1987) Universals and cultural differences in the judgments of facial expressions of emotion. J Personal Soc Psychol 53(4):712–717

    Article  Google Scholar 

  25. Ellinghaus D, Steinbrecher J (2002) Lkw im Strassenverkehr Eine Untersuchung ber Beziehungen zwischen Lkw- und Pkw-Fahrern. Köln/Hannover. https://bit.ly/2tIV3B6

  26. Endsley MR (1995) Toward a theory of situation awareness in dynamic systems. Hum Factors J Hum Factors Ergon Soc 37(1):32–64

    Article  Google Scholar 

  27. Endsley MR, Kiris EO (1995) The out-of-the-loop performance problem and level of control in automation. Hum Factors 37(2):381–394

    Article  Google Scholar 

  28. Epley N, Waytz A, Cacioppo JT (2007) On seeing human: a three-factor theory of anthropomorphism. In: Psychological review, 114(4)

  29. Evers C (2009) Auswirkungen von Belastungen und Stress auf das Verkehrsverhalten von Lkw-Fahrern. In: Berichte der Bundesanstalt für Strassenwesen

  30. Eyben F, Wöllmer M, Poitschke T, Schuller B, Blaschke C, Färber B, Nguyen-Thien N (2010) Emotion on the road: necessity, acceptance, and feasibility of affective computing in the car. Adv Hum Comput Interaction 2010:1–17

    Article  Google Scholar 

  31. Thomas F, Johnston O (1981) Disney animation: the illusion of life. Abbeville Press, New York

    Google Scholar 

  32. Fank J, Knies C, Diermeyer F, Prasch L, Reinhardt J, Bengler K (2017) Factors for user acceptance of cooperative assistance systems: a two-step study assessing cooperative driving. In: 8. Tagung der Fahrerassistenz, Munich, Germany

  33. Fank J, Lienkamp M (2019) “I’m your personal co-driver how can I assist you?” Assessing the potential of personal assistants for truck drivers. In: Proceedings of the 2nd international conference on intelligent human systems integration, San Diego, USA

  34. Fiske DW (1949) Consistency of the factorial structures of personality ratings from different sources. J Abnorm Soc Psychol 44(3):329–344

    Article  Google Scholar 

  35. Flemisch FO, Bengler K, Bubb H, Winner H, Bruder R (2014) Towards cooperative guidance and control of highly automated vehicles: H-mode and conduct-by-wire. Ergonomics 57(3):343–360

    Article  Google Scholar 

  36. Fogg BJ (2003) Computers as persuasive social actors. In: Persuasive technology: using computers to change what we think and do. Morga Kaufmann Puplishers, pp 89–120

  37. Fogg BJ, Nass C (1997) How users reciprocate to computers: an experiment that demonstrates behavior change. In: Conference human factors in computing systems. ACM, New York, USA, pp 331–332

  38. Fong T, Nourbakhsh I, Dautenhahn K (2003) A survey of socially interactive robots. Rob Auton Syst 42(3–4):143–166

    Article  MATH  Google Scholar 

  39. Forster Y, Naujoks F, Neukum A (2017) Increasing anthropomorphism and trust in automated driving functions by adding speech output. In: 2017 IEEE intelligent vehicles symposium (IV), pp 365–372

  40. GDV (2017) Müdigkeit und hochautomatisiertes Fahren: Unfallforschung kompakt. Studienbericht

  41. Goetz J, Kiesler S, Powers A (2003) Matching robot appearance and behavior to tasks to improve human-robot cooperation. In: The 12th IEEE international workshop on robot and human interactive communication. Millbrae, USA, pp 55–60

  42. Goldberg LR (1993) The structure of phenotypic personality traits. Am Psychol 48(1):26–34

    Article  Google Scholar 

  43. Gordon G, Spaulding S, Westlund JK, Lee JJ, Plummer L, Martinez M, Das M, Breazeal C (2016) Affective personalization of a social robot tutor for children’s second language skills. In: Proceedings of the thirtieth AAAI conference on artificial intelligence, pp 3951–3957

  44. Grodal T (1997) Moving pictures a new theory of film genres, feelings, and cognitions. Clarendon Press, University of Michigan

    Google Scholar 

  45. Guthrie SE (1993) Faces in the clouds: a new theory of religion. Oxford University Press, Oxford

    Google Scholar 

  46. Ham J, Midden CJH (2014) A persuasive robot to stimulate energy conservation: the influence of positive and negative social feedback and task similarity on energy-consumption behavior. Int J Soc Rob 6(2):163–171

    Article  Google Scholar 

  47. Ham J, Cuijpers RH, Cabibihan JJ (2015) Combining robotic persuasive strategies: the persuasive power of a storytelling robot that uses gazing and gestures. Int J Soc Rob 7(4):479–487

    Article  Google Scholar 

  48. Hampson SE, John OP, Goldberg LR (1986) Category breadth and hierarchical structure in personality: studies of asymmetries in judgments of trait implications. J Personal Soc Psychol 51(1):37–54

    Article  Google Scholar 

  49. Häuslschmid R, von Bülow M, Pfleging B, Butz A (2017) Supporting trust in autonomous driving. In: Proceedings of the 22nd international conference on intelligent user interfaces, ACM, New York, USA, pp 319–329

  50. Heckman CE, Wobbrock JO (2000) Put your best face forward: anthropomorphic agents, e-commerce consumers, and the law. In: Proceedings of the 4th international conference on autonomous agents, ACM, New York, USA, pp 435–442

  51. Heerink M, Krse B, Evers V, Wielinga B (2009) Influence of social presence on acceptance of an assistive social robot and screen agent by elderly users. Adv Rob 23(14):1909–1923

    Article  Google Scholar 

  52. Hock P, Kraus J, Walch M, Lang N, Baumann M (2016) Elaborating feedback strategies for maintaining automation in highly automated driving. In: Proceedings of the 8th international conference on automotive user interfaces and interactive vehicular applications, ACM, New York, USA, pp 105–112

  53. Hofmann H, Tobisch V, Ehrlich U, Berton A (2015) Evaluation of speech-based HMI concepts for information exchange tasks: a driving simulator study. In: Computer speech & language, vol 33, no 1, pp 109–135

  54. Holz T, Dragone M, O’Hare GMP (2009) Where robots and virtual agents meet. Int J Soc Rob 1(1):83–93

    Article  Google Scholar 

  55. Institut für Nachhaltigkeit in Verkehr und Logistik (ed) (2012) ZF-Zukunftsstudie Fernfahrer: Der Mensch im Transport- und Logistikmarkt. EuroTransportMedia Verlags- und Veranstaltungs-GmbH. https://bit.ly/2EEDjgn

  56. John OP (1990) The big five factor taxonomy: dimensions of personality in the natural language and in questionnaires. Handbook of personality: theory and research. Guilford Press, New York, pp 66–100

    Google Scholar 

  57. Jonsson IM, Dahlbäck N (2014) Driving with a speech interaction system: effect of personality on performance and attitude of driver. Human-computer interaction. Springer International Publishing, Advanced Interaction Modalities and Techniques, pp 417–428

  58. Jonsson IM, Zajicek M, Harris H, Nass C (2005) Thank you, I did not see that: in-car speech based information systems for older adults. In: Human factors in computing systems, pp 1953–1956

  59. Karatas N, Yoshikawa S, De Silva PRS, Okada M (2015) NAMIDA: multiparty conversation based driving agents in futuristic vehicle. In: Human-computer interaction: users and contexts. Springer International Publishing, pp 198–207

  60. Kiesler S, Powers A, Fussell SR, Torrey C (2008) Anthropomorphic interactions with a robot and robot-like agent. Soc Cognit 26(2):169–181

    Article  Google Scholar 

  61. Klowait N (2017) The quest for appropriate models of human-likeness: anthropomorphism in media equation research. AI Soc 33(4):527–536

    Article  Google Scholar 

  62. Kozima H, Yano H (2001) A robot that learns to communicate with human caregivers. In: The first international workshop on epicgenetic robotics, pp 47–52

  63. Kraus JM, Sturn J, Reiser JE, Baumann M (2015) Anthropomorphic agents, transparent automation and driver personality: towards an integrative multi-level model of determinants for effective driver-vehicle cooperation in highly automated vehicles. In: The 7th international conference on automotive user interfaces and interactive vehicular applications. ACM, New York, USA, pp 8–13

  64. Kraus JM, Nothdurft F, Hock P, Scholz D, Minker W, Baumann M (2016) Human after all: effects of mere presence and social interaction of a humanoid robot as a co-driver in automated driving. In: The 8th international conference on automotive user interfaces and interactive vehicular applications. ACM, New York, USA, pp 129–134

  65. Landwehr JR, McGill AL, Herrmann A (2011) It’s got the look: the effect of friendly and aggressive “Facial” expressions on product liking and sales. J Mark 75(3):132–146

    Article  Google Scholar 

  66. Large DR, Burnett GE, Antrobus V, Skrypchuk L (2017) Stimulating conversation: engaging drivers in natural language interactions with an autonomous digital driving assistant to counteract passive task-related fatigue. In: International conference on driver distraction and inattention

  67. Lee KM, Jung Y, Kim J, Kim SR (2006) Are physically embodied social agents better than disembodied social agents?: The effects of physical embodiment, tactile interaction, and people’s loneliness in humanrobot interaction. Int J Hum Comput Stud 64(10):962–973

    Article  Google Scholar 

  68. Luchs MG (2015) A brief introduction to design thinking. In: Luchs MG, Scott Swan K, Griffin A (eds) Design thinking. Wiley, Hoboken, pp 1–12

    Chapter  Google Scholar 

  69. Lugano G (2017) Virtual assistants and self-driving cars. In: 15th International conference on ITS telecommunications, pp 1–5

  70. Luger E, Sellen A (2016) “Like having a really bad PA”: the Gulf between user expectation and experience of conversational agents. Conference on human factors in computing systems. ACM, New York, pp 5286–5297

    Google Scholar 

  71. Luo J, McGoldrick P, Beatty S, Keeling KA (2006) Onscreen characters: their design and influence on consumer trust. J Serv Mark 20(2):112–124

    Article  Google Scholar 

  72. Martin A, O’Hare GMP, Duffy BR, Schön B, Bradley JF (2005) Maintaining the identity of dynamically embodied agents. In: Intelligent virtual agents. Springer, Berlin, pp 454–465

  73. McDonnell R, Breidt M, Bülthoff HH (2012) Render me real?: Investigating the effect of render style on the perception of animated virtual humans. ACM Trans Graph 31(4):1–11

    Article  Google Scholar 

  74. McNeill D (1992) Hand and mind: what gestures reveal about thought. University of Chicago Press, Chicago

    Google Scholar 

  75. Mead GH (2015) Mind, self, and society: the definitive edition. University of Chicago Press, Chicago

    Book  Google Scholar 

  76. Moon Y, Nass C (1996) How real are computer personalities?: Psychological responses to personality types in human-computer interaction. Commun Res 23(6):651–674

    Article  Google Scholar 

  77. Morris MW, Keltner D (2000) How emotions wWork: the social functions of emotional expression in negotiations. Res Organ Behav 22:1–50

    Article  Google Scholar 

  78. Mueller F (1888) Das Denken im Lichte der Sprache. abc, Leipzig

  79. Murray IR, Arnott JL (1993) Toward the simulation of emotion in synthetic speech: a review of the literature on human vocal emotion. J Acoust Soc Am 93(2):1097–1108

    Article  Google Scholar 

  80. Nass C, Lee KM (2001) Does computer-synthesized speech manifest personality? Experimental tests of recognition, similarity-attraction, and consistency-attraction. J Exp Psychol Appl 7:171–181

    Article  Google Scholar 

  81. Nass C, Steuer J, Tauber ER (1994) Computers are social actors. In: Conference on human factors in computing systems. ACM, New York, USA, pp 72–78

  82. Nass C, Moon Y, Fogg BJ, Reeves B, Dryer CD (1995) Can computer personalities be human personalities? Int J Hum Comput Stud 43(2):223–239

    Article  Google Scholar 

  83. Nass C, Jonsson IM, Harris H, Reaves B, Endo J, Brave S, Takayama L (2005a) Improving automotive safety by pairing driver emotion and car voice emotion. In: Human factors in computing systems. ACM, New York, USA, pp 1973–1976

  84. Nass C, Jonsson IM, Harris H, Reaves B, Endo J, Brave S, Takayama L (2005b) Improving automotive safety by pairing driver emotion and car voice emotion. In: Human factors in computing systems. ACM, New York, USA, pp 1973–1976

  85. Naujoks F, Forster Y, Wiedemann K, Neukum A, (2016) Speech improves human-automation cooperation in automated driving. In: Mensch und computer (2016) Workshopband. Gesellschaft fr Informatik e.V, Aachen

  86. Nicolescu MN, Mataric MJ (2001) Learning and interacting in human-robot domains. IEEE Trans Syst Man Cybern A Syst Hum 31(5):419–430

    Article  Google Scholar 

  87. Niculescu AI, Lim MQ, Wibowo SA, Yeo KH, Lim BP, Popow M, Chia D, Banchs RE (2015) Designing IDA—an intelligent driver assistant for smart city parking in Singapore. In: 15th Human-computer interaction, pp 510–513

  88. Niculescu AI, Dix A, Yeo KH (2017) Are you ready for a drive?: User perspectives on autonomous vehicles. In: Human factors in computing systems. ACM, New York, USA, pp 2810–2817

  89. Nissan (2007) Pivo concept car. Press Release. https://bit.ly/2IHWRoi

  90. Nissan (2015) Nissan IDS concept: Nissans vision for the future of EVs and autonomous driving. Press Release. https://bit.ly/2tKtk2E

  91. Okamoto S, Sano S (2017) Anthropomorphic AI agent mediated multimodal interactions in vehicles. In: 9th International conference on automotive user interfaces and interactive vehicular. ACM, New York, USA, pp 110–114

  92. Pak R, Fink N, Price M, Bass B, Sturre L (2012) Decision support aids with anthropomorphic characteristics influence trust and performance in younger and older adults. Ergonomics 55(9):1059–1072

    Article  Google Scholar 

  93. Parise S, Kiesler S, Sproull L, Waters K (1996) My partner is a real dog: cooperation with social agents. In: Proceedings of the 1996 ACM conference on computer supported cooperative work, ACM, New York, USA, pp 399–408

  94. Premack D, Premack AJ (1995) Origins of human social competence. In: The cognitive neurosciences. The MIT Press, Cambridge, US, pp 205–218

  95. Reeves B, Nass C (1996) The media equation: how people treat computers, television, and mew media like real people and places. Cambridge University Press, New York

    Google Scholar 

  96. Resnick M, Myers B, Nakakoji K, Shneiderman B, Pausch R, Selker T, Eisenberg M (2005) Design principles for tools to support creative thinking. In: Proceedings of the NSF workshop on creativity support tools, pp 25–36

  97. Richardson N, Doubek F, Kuhn K, Stumpf A (2017) Assessing truck drivers’ and fleet managers’ opinions towards highly automated driving. In: Advances in human aspects of transportation. Springer International Publishing, pp 473-484

  98. Richardson NT, Lehmer C, Lienkamp M, Michel B (2018) Conceptual design and evaluation of a human machine interface for highly automated truck driving. In: 2018 IEEE intelligent vehicles symposium (IV), pp 2072–2077

  99. Rijkswaterstaat (2016) European truck platooning challenge 2016: creating next generation mobility. Challenge network. https://bit.ly/2VpBR7d, storybook

  100. Scassellati B (2002) Theory of mind for a humanoid robot. Auton Robots 12(1):13–24

    Article  MATH  Google Scholar 

  101. Schallmo DRA (2017) Design Thinking erfolgreich anwenden: So entwickeln Sie in 7 Phasen kundenorientierte Produkte und Dienstleistungen. Springer Fachmedien Wiesbaden, Wiesbaden

    Book  Google Scholar 

  102. Seifert CM, Gonzalez R, Yilmaz S, Daly S (2015) Boosting creativity in idea generation using design heuristics. In: Design thinking: new product development essentials from the PDMA, pp 71–85

  103. Sirkin D, Fischer K, Jensen L, Ju W (2016) Eliciting conversation in robot vehicle interactions. In: Association for the advancement of artificial intelligence spring symposium series, pp 164–171

  104. Smith M (1995) Engaging characters—fiction, emotion, and the cinema. Oxford University Press, Oxford

    Google Scholar 

  105. Takayama L, Nass C (2008) Driver safety and information from afar: an experimental driving simulator study of wireless versus in-car information services. Int J Hum Comput Stud 66(3):173–184

    Article  Google Scholar 

  106. Takeuchi A, Nagao K (1993) Communicative facial displays as a new conversational modality. In: Conference on human factors in computing systems. ACM, New York, USA, pp 187–193

  107. Terwogt MM, Hoeksma JB (1995) Colors and emotions: preferences and combinations. J Gen Psychol 122(1):5–17

    Article  Google Scholar 

  108. Thomas S, Michael M, Martin B (2016) Global truck study 2016. Deloitte

  109. Toyota (2017) Toyota concept-i makes the future of mobility human. Press Release. https://toyota.us/2kbTvci

  110. Urquiza-Haas EG, Kotrschal K (2015) The mind behind anthropomorphic thinking: attribution of mental states to other species. Anim Behav 109:167–176

    Article  Google Scholar 

  111. Vandenberghe B, Slegers K (2016) Anthropomorphism as a strategy to engage end-users in health data ideation. In: The 9th Nordic conference on human-computer interaction. ACM, New York, USA, pp 1–4

  112. de Visser EJ, Krueger F, McKnight P, Scheid S, Smith M, Chalk S, Parasuraman R (2012) The world is not enough: trust in cognitive agents. In: The human factors and ergonomics society annual meeting, vol 56, no 1, pp 263–267

  113. Volkswagen (2017) Individual mobility redefined: autonomous driving at the touch of a button. Press Release. https://bit.ly/2VkJDiG

  114. Vossen S, Ham J, Midden C (2010) What makes social feedback from a robot work? Disentangling the effect of speech, physical appearance and evaluation. Persuasive technology. Springer, Berlin Heidelberg, pp 52–57

  115. de Waal F (2009) The age of empathy: natures lessons for a kinder society. Broadway Books, Berkeley

    Google Scholar 

  116. Wang W (2017) Smartphones as social actors? Social dispositional factors in assessing anthropomorphism. Comput Hum Behav 68:334–344

    Article  Google Scholar 

  117. Waytz A, Heafner J, Epley N (2014) The mind in the machine: anthropomorphism increases trust in an autonomous vehicle. J Exp Soc Psychol 52:113–117

    Article  Google Scholar 

  118. Williams K, Breazeal C (2013) Reducing driver task load and promoting sociability through an Affective Intelligent Driving Agent (AIDA). In: Human-computer interaction—INTERACT 2013. Springer, Berlin Heidelberg, pp 619–626

  119. Williams K, Flores JA, Peters J (2014) Affective robot influence on driver adherence to safety, cognitive load reduction and sociability. In: The 6th international conference on automotive user interfaces and interactive vehicular applications. ACM, New York, USA, pp 1–8

  120. Williams KJ, Peters JC, Breazeal CL (2013) Towards leveraging the driver’s mobile device for an intelligent, sociable in-car robotic assistant. In: 2013 IEEE intelligent vehicles symposium (IV), pp 369–376

  121. Windhager S, Hutzler F, Carbon CC, Oberzaucher E, Schaefer K, Thorstensen T, Leder H, Grammer K (2009) Laying eyes on headlights: eye movements suggest facial features in cars. Coll Antropol 34(3):1075–1080

    Google Scholar 

  122. Yang JY, Jo YH, Kim JC, Kwon DS (2013) Affective interaction with a companion robot in an interactive driving assistant system. In: 2013 IEEE intelligent vehicles symposium (IV), pp 1392–1397

  123. Zimmermann M, Bauer S, Ltteken N, Rothkirch IM, Bengler K (2014) Acting together by mutual control: evaluation of a multimodal interaction concept for cooperative driving. In: 2014 International conference on collaboration technologies and systems, pp 227–235

  124. Złotowski J, Proudfoot D, Yogeeswaran K, Bartneck C (2015) Anthropomorphism: opportunities and challenges in human-robot interaction. Int J Soc Robot 7(3):347–360

    Article  Google Scholar 

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Acknowledgements

This research was conducted with basic research funds of the Institute of Automotive Technology at Technical University of Munich. We would like to thank the participants of the interdisciplinary workshop Rafael Hostettler, Marcus Novotny (10 Days of Design), Markus Rickert (Fortiss GmbH), and Christiane Wölfel for their contributions.

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JF is the initiator of this article’s research idea and contributed to the literature review, workshop design, development and data analysis. NTR has supported the research idea, contributed to the workshop design and revised the manuscript. FD revised the manuscript critically for important intellectual content.

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Correspondence to Jana Fank.

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Fank, J., Richardson, N.T. & Diermeyer, F. Anthropomorphising driver-truck interaction: a study on the current state of research and the introduction of two innovative concepts. J Multimodal User Interfaces 13, 99–117 (2019). https://doi.org/10.1007/s12193-019-00296-w

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