Journal on Multimodal User Interfaces

, Volume 13, Issue 2, pp 99–117 | Cite as

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

  • Jana FankEmail author
  • Natalie T. Richardson
  • Frank Diermeyer
Original Paper


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.


Anthropomorphism Driver-vehicle interaction Car drivers Truck drivers Conversational agent Virtual agent Robotic agent Design thinking 



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.

Author Contributions

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.


  1. 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, CanadaGoogle Scholar
  2. 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):468–479Google Scholar
  3. 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, CanadaGoogle Scholar
  4. 4.
    Audi (2017) Audi Elaine concept car highly automated at level 4. Press Release.
  5. 5.
    BAG (2016) Marktbeobachtung Güterverkehr: Auswertung der Arbeitsbedingungen in Güterverkehr und Logistik 2016-I.
  6. 6.
    BAG (2017) Marktbeobachtung Güterverkehr: Auswertung der Arbeitsbedingungen in Güterverkehr und Logistik 2017-I.
  7. 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, USAGoogle Scholar
  8. 8.
    Brave S, Nass C (2003) Emotion in human-computer interaction. The human-computer interaction handbook. ACM, Hillsdale, pp 81–96Google Scholar
  9. 9.
    Breazeal C (2002) Designing sociable robots. MIT Press, CambridgezbMATHGoogle Scholar
  10. 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)Google Scholar
  11. 11.
    Calo R (2010) Robots and privacy. In: Robot ethics: the ethical and social implications of robotics, MIT Press, CambridgeGoogle Scholar
  12. 12.
    Casner SM, Hutchins EL, Norman D (2016) The challenges of partially automated driving. Commun ACM 59(5):70–77Google Scholar
  13. 13.
    Cassell J (2000) Embodied conversational interface agents. Commun ACM 43(4):70–78Google Scholar
  14. 14.
    Dacey M (2017) Anthropomorphism as cognitive bias. Philos Sci 84(5):1152–1164Google Scholar
  15. 15.
    Damasio AR (1994) Descartes’ error. Emotion, reason and the human brain. Avon Books, New YorkGoogle Scholar
  16. 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 PressGoogle Scholar
  17. 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 770–775Google Scholar
  18. 18.
    Dautenhahn K (1997) I could be you: the phenomenological dimension of social understanding. Cybern Syst 28(5):417–453Google Scholar
  19. 19.
    Deci EL, Ryan RM (1995) Efficacy, agency, and self-esteem. Human autonomy. Springer, Boston, pp 31–49Google Scholar
  20. 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):89–101Google Scholar
  21. 21.
    Derryberry D, Tucker DM (1992) Neural mechanisms of emotion. J Consult Clin Psychol 60(3):329–338Google Scholar
  22. 22.
    Duffy BR (2003) Anthropomorphism and the social robot. Rob Auton Syst 42(3):177–190zbMATHGoogle Scholar
  23. 23.
    Ekman P (1957) A methodological discussion of nonverbal behavior. J Psychol 43(1):141–149Google Scholar
  24. 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):712–717Google Scholar
  25. 25.
    Ellinghaus D, Steinbrecher J (2002) Lkw im Strassenverkehr Eine Untersuchung ber Beziehungen zwischen Lkw- und Pkw-Fahrern. Köln/Hannover.
  26. 26.
    Endsley MR (1995) Toward a theory of situation awareness in dynamic systems. Hum Factors J Hum Factors Ergon Soc 37(1):32–64Google Scholar
  27. 27.
    Endsley MR, Kiris EO (1995) The out-of-the-loop performance problem and level of control in automation. Hum Factors 37(2):381–394Google Scholar
  28. 28.
    Epley N, Waytz A, Cacioppo JT (2007) On seeing human: a three-factor theory of anthropomorphism. In: Psychological review, 114(4)Google Scholar
  29. 29.
    Evers C (2009) Auswirkungen von Belastungen und Stress auf das Verkehrsverhalten von Lkw-Fahrern. In: Berichte der Bundesanstalt für StrassenwesenGoogle Scholar
  30. 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 2010:1–17Google Scholar
  31. 31.
    Thomas F, Johnston O (1981) Disney animation: the illusion of life. Abbeville Press, New YorkGoogle Scholar
  32. 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, GermanyGoogle Scholar
  33. 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, USAGoogle Scholar
  34. 34.
    Fiske DW (1949) Consistency of the factorial structures of personality ratings from different sources. J Abnorm Soc Psychol 44(3):329–344Google Scholar
  35. 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):343–360Google Scholar
  36. 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 89–120Google Scholar
  37. 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 331–332Google Scholar
  38. 38.
    Fong T, Nourbakhsh I, Dautenhahn K (2003) A survey of socially interactive robots. Rob Auton Syst 42(3–4):143–166zbMATHGoogle Scholar
  39. 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 365–372Google Scholar
  40. 40.
    GDV (2017) Müdigkeit und hochautomatisiertes Fahren: Unfallforschung kompakt. StudienberichtGoogle Scholar
  41. 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 55–60Google Scholar
  42. 42.
    Goldberg LR (1993) The structure of phenotypic personality traits. Am Psychol 48(1):26–34Google Scholar
  43. 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 3951–3957Google Scholar
  44. 44.
    Grodal T (1997) Moving pictures a new theory of film genres, feelings, and cognitions. Clarendon Press, University of MichiganGoogle Scholar
  45. 45.
    Guthrie SE (1993) Faces in the clouds: a new theory of religion. Oxford University Press, OxfordGoogle Scholar
  46. 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):163–171Google Scholar
  47. 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):479–487Google Scholar
  48. 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):37–54Google Scholar
  49. 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 319–329Google Scholar
  50. 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 435–442Google Scholar
  51. 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):1909–1923Google Scholar
  52. 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 105–112Google Scholar
  53. 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 109–135Google Scholar
  54. 54.
    Holz T, Dragone M, O’Hare GMP (2009) Where robots and virtual agents meet. Int J Soc Rob 1(1):83–93Google Scholar
  55. 55.
    Institut für Nachhaltigkeit in Verkehr und Logistik (ed) (2012) ZF-Zukunftsstudie Fernfahrer: Der Mensch im Transport- und Logistikmarkt. EuroTransportMedia Verlags- und Veranstaltungs-GmbH.
  56. 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 66–100Google Scholar
  57. 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 417–428Google Scholar
  58. 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 1953–1956Google Scholar
  59. 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 198–207Google Scholar
  60. 60.
    Kiesler S, Powers A, Fussell SR, Torrey C (2008) Anthropomorphic interactions with a robot and robot-like agent. Soc Cognit 26(2):169–181Google Scholar
  61. 61.
    Klowait N (2017) The quest for appropriate models of human-likeness: anthropomorphism in media equation research. AI Soc 33(4):527–536Google Scholar
  62. 62.
    Kozima H, Yano H (2001) A robot that learns to communicate with human caregivers. In: The first international workshop on epicgenetic robotics, pp 47–52Google Scholar
  63. 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 8–13Google Scholar
  64. 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 129–134Google Scholar
  65. 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):132–146Google Scholar
  66. 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 inattentionGoogle Scholar
  67. 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):962–973Google Scholar
  68. 68.
    Luchs MG (2015) A brief introduction to design thinking. In: Luchs MG, Scott Swan K, Griffin A (eds) Design thinking. Wiley, Hoboken, pp 1–12Google Scholar
  69. 69.
    Lugano G (2017) Virtual assistants and self-driving cars. In: 15th International conference on ITS telecommunications, pp 1–5Google Scholar
  70. 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 5286–5297Google Scholar
  71. 71.
    Luo J, McGoldrick P, Beatty S, Keeling KA (2006) Onscreen characters: their design and influence on consumer trust. J Serv Mark 20(2):112–124Google Scholar
  72. 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 454–465Google Scholar
  73. 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):1–11Google Scholar
  74. 74.
    McNeill D (1992) Hand and mind: what gestures reveal about thought. University of Chicago Press, ChicagoGoogle Scholar
  75. 75.
    Mead GH (2015) Mind, self, and society: the definitive edition. University of Chicago Press, ChicagoGoogle Scholar
  76. 76.
    Moon Y, Nass C (1996) How real are computer personalities?: Psychological responses to personality types in human-computer interaction. Commun Res 23(6):651–674Google Scholar
  77. 77.
    Morris MW, Keltner D (2000) How emotions wWork: the social functions of emotional expression in negotiations. Res Organ Behav 22:1–50Google Scholar
  78. 78.
    Mueller F (1888) Das Denken im Lichte der Sprache. abc, LeipzigGoogle Scholar
  79. 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):1097–1108Google Scholar
  80. 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 7:171–181Google Scholar
  81. 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 72–78Google Scholar
  82. 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):223–239Google Scholar
  83. 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 1973–1976Google Scholar
  84. 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 1973–1976Google Scholar
  85. 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, AachenGoogle Scholar
  86. 86.
    Nicolescu MN, Mataric MJ (2001) Learning and interacting in human-robot domains. IEEE Trans Syst Man Cybern A Syst Hum 31(5):419–430Google Scholar
  87. 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 510–513Google Scholar
  88. 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 2810–2817Google Scholar
  89. 89.
    Nissan (2007) Pivo concept car. Press Release.
  90. 90.
    Nissan (2015) Nissan IDS concept: Nissans vision for the future of EVs and autonomous driving. Press Release.
  91. 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 110–114Google Scholar
  92. 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):1059–1072Google Scholar
  93. 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 399–408Google Scholar
  94. 94.
    Premack D, Premack AJ (1995) Origins of human social competence. In: The cognitive neurosciences. The MIT Press, Cambridge, US, pp 205–218Google Scholar
  95. 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 YorkGoogle Scholar
  96. 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 25–36Google Scholar
  97. 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 473-484Google Scholar
  98. 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 2072–2077Google Scholar
  99. 99.
    Rijkswaterstaat (2016) European truck platooning challenge 2016: creating next generation mobility. Challenge network., storybook
  100. 100.
    Scassellati B (2002) Theory of mind for a humanoid robot. Auton Robots 12(1):13–24zbMATHGoogle Scholar
  101. 101.
    Schallmo DRA (2017) Design Thinking erfolgreich anwenden: So entwickeln Sie in 7 Phasen kundenorientierte Produkte und Dienstleistungen. Springer Fachmedien Wiesbaden, WiesbadenGoogle Scholar
  102. 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 71–85Google Scholar
  103. 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 164–171Google Scholar
  104. 104.
    Smith M (1995) Engaging characters—fiction, emotion, and the cinema. Oxford University Press, OxfordGoogle Scholar
  105. 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):173–184Google Scholar
  106. 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 187–193Google Scholar
  107. 107.
    Terwogt MM, Hoeksma JB (1995) Colors and emotions: preferences and combinations. J Gen Psychol 122(1):5–17Google Scholar
  108. 108.
    Thomas S, Michael M, Martin B (2016) Global truck study 2016. DeloitteGoogle Scholar
  109. 109.
    Toyota (2017) Toyota concept-i makes the future of mobility human. Press Release.
  110. 110.
    Urquiza-Haas EG, Kotrschal K (2015) The mind behind anthropomorphic thinking: attribution of mental states to other species. Anim Behav 109:167–176Google Scholar
  111. 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 1–4Google Scholar
  112. 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 263–267Google Scholar
  113. 113.
    Volkswagen (2017) Individual mobility redefined: autonomous driving at the touch of a button. Press Release.
  114. 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 52–57Google Scholar
  115. 115.
    de Waal F (2009) The age of empathy: natures lessons for a kinder society. Broadway Books, BerkeleyGoogle Scholar
  116. 116.
    Wang W (2017) Smartphones as social actors? Social dispositional factors in assessing anthropomorphism. Comput Hum Behav 68:334–344Google Scholar
  117. 117.
    Waytz A, Heafner J, Epley N (2014) The mind in the machine: anthropomorphism increases trust in an autonomous vehicle. J Exp Soc Psychol 52:113–117Google Scholar
  118. 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 619–626Google Scholar
  119. 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 1–8Google Scholar
  120. 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 369–376Google Scholar
  121. 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):1075–1080Google Scholar
  122. 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 1392–1397Google Scholar
  123. 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 227–235Google Scholar
  124. 124.
    Złotowski J, Proudfoot D, Yogeeswaran K, Bartneck C (2015) Anthropomorphism: opportunities and challenges in human-robot interaction. Int J Soc Robot 7(3):347–360Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Technical University of Munich, Institute of Automotive TechnologyGarchingGermany

Personalised recommendations