Nilsson T, Crabtree A, Fischer J, Koleva B (2019) Breaching the future: understanding human challenges of autonomous systems for the home. Pers Ubiquit Comput 23:287–307. https://doi.org/10.1007/s00779-019-01210-7
Streitz N, Charitos D, Kaptein M, Böhlen M (2019) Grand challenges for ambient intelligence and implications for design contexts and smart societies. Journal of Ambient Intelligence and Smart Environments 11:87–107
Farooq U, Grudin J (2016) Human computer integration. ACM Interactions 23(6):26–32
[+]
Nilsson T, Crabtree A, Fischer J, Koleva B (2019) Breaching the future: understanding human challenges of autonomous systems for the home. Pers Ubiquit Comput 23:287–307. https://doi.org/10.1007/s00779-019-01210-7
Streitz N, Charitos D, Kaptein M, Böhlen M (2019) Grand challenges for ambient intelligence and implications for design contexts and smart societies. Journal of Ambient Intelligence and Smart Environments 11:87–107
Farooq U, Grudin J (2016) Human computer integration. ACM Interactions 23(6):26–32
Waytz, A.: How humans and machines can live and work together (May 2019),
Gams, M., Yu-Hua Gu, I., Härmä, A., Muñoz, A., Tam, V.: Artificial intelligence and ambient intelligence, Tenth Anniversary Issue, Journal of Ambient Intelligence and Smart Environments 11 (2019), 71–86. IOS Press
Streitz, N., Privat, G.: Ambient intelligence. Final section “Looking to the future”, in: The Universal Access Handbook, C. Stephanidis, ed., CRC Press, 2009, pp. 60.1–60.17
Gil M, Albert M, Fons J, Pelechano V (2019) Designing human-in-the-loop autonomous cyber physical systems. Int J Hum Comput Stud 130:21–39
Gil M, Albert M, Fons J, Pelechano V (2020) Engineering human-in-the-loop interactions in cyber physical systems. Information Software Technology 126:106349
Fitts, P. M: Human engineering for an effective air-navigation and traffic-control system, National Research Council (1951)
Sheridan, T. B: On how often the supervisor should sample, IEEE Transactions on Systems Science and Cybernetics 6 (2) (1970) 140–145
Lee JD, See KA (2004) Trust in automation: designing for appropriate reliance. Hum Factors 46(50–80):50–80
Stanton, N. A., Young, M. S: Vehicle automation and driving performance, Ergonomics 41 (7) (2010) 1014–1028
Cámara, J., Moreno, G., Garlan, D.: Reasoning about human participation in self- adaptive systems. In: 2015 IEEE/ACM 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. pp. 146–156 (May 2015)
Dorn, C., Taylor, R. N. “Coupling software architecture and human architecture for collaboration-aware system adaptation,” in Proceedings of the 2013 International Conference on Software Engineering, ser. ICSE ’13. Piscataway, NJ, USA: IEEE Press, 2013, pp. 53–62
Evers, C., Kniewel, R., Geihs, K., Schmidt, L.: “The user in the loop: enabling user participation for self-adaptive applications,” Futur Gener Comput Syst, vol. 34, no. 0, pp. 110–123, 2014
Cranor, L., A framework for reasoning about the human in the loop, in UPSEC'08 conference on usability, psychology, and security (2008)
Nothwang WD, McCourt MJ, Robinson RM, Burden SA, Curtis JW (2016) The human should be part of the control loop? In: Resilience week (RWS)
Nunes DS, Zhang P, Silva JS (2015) A survey on human-in-the-loop applications towards an internet of all. IEEE Communications Surveys and Tutorials 17(2):944–965
Weiser M (1991) The computer for the 21st century. Sci Am:66–75
Gibson JJ (1986) The ecological approach to visual perception. Lawrence Erlbaum Associates, London (first published in 1979)
Norman, D.A.: Affordance, conventions and design, Interactions 6(3) (1999), 38–43. ACM Press
Christakis N (2010) The face and others: issues of communication and social psychology. Papazisis Publications, Athens
Chin, J., Callaghan, V., Allouch, S.B.: The Internet of things: reflections on the past, present and future from a user centered and smart environments perspective, Tenth Anniversary Issue, Journal of Ambient Intelligence and Smart Environments 11 (2019), 45–69. IOS Press
Langley, P: Machine learning for adaptive user interfaces. pp. 53–62. Annual Conference on Artificial Intelligence. 1997
Garcia-Ceja E, Riegler M (2019) Kvernberg. A. K., Torresen, J.: User-adaptive models for activity and emotion recognition using deep transfer learning and data augmentation, User Modeling and User-Adapted Interaction
Miller, C.A., Parasuraman, R.: Designing for flexible interaction between humans and automation: delegation interfaces for supervisory control, The Journal of the Human Factors and Ergonomics Society 49(1), pp. 57–75, March 2007
Cheng, B.H., et al.: Software engineering for self-adaptive systems. pp. 1–26. Springer-Verlag (2009)
Mirnig AG, Gärtner MA, Laminger A, Meschtscherjakov S, Trösterer M, Tscheligi R, McCall F (2016) McGee: control transition interfaces in semiautonomous vehicles: a categorization framework and literature analysis. In: International conference on automotive user interfaces and interactive vehicular applications (AutomotiveUI ’17)
Dey AK (2001) Understanding and using context. Personal Ubiquitous Comput 5(1):4–7
Eskins D, Sanders WH (2011) The multiple-asymmetric-utility system model: a framework for modeling cyber-human systems, in: proceedings of the 2011 Eighth International Conference on Quantitative Evaluation of SysTems. IEEE Computer Society, Washington, DC, USA, pp 233–242
Buxton, B.: Integrating the periphery and context: A new model of telematics, in: Proceedings of Graphics Interface, 1995, pp. 239–246
Horvitz E, Kadie C, Paek T, Hovel D (2003) Models of attention in computing and communication: from principles to applications. Commun ACM 46(3):52–59
Ju W, Leifer L (2008) The design of implicit interactions: making interactive systems less obnoxious. Des Issues 24(3):72–84
Beruscha, F., Augsburg, K., Manstetten, D., Schwieberdingen, R. B. G.: Haptic warning signals at the steering wheel: a literature survey regarding lane departure warning systems (short paper) (2011)
Chun J, Lee I, Park G, Seo J, Choi S, Han S (2013) H. Efficacy of haptic blind spot warnings applied through a steering wheel or a seatbelt. Transport Res F: Traffic Psychol Behav 21:231–241
Trivedi MM, Cheng SY (2007) Holistic sensing and active displays for intelligent driver support systems. Computer 40(5):60–68
Winkler, S., Kazazi, J., Vollrath, M.: Distractive or supportive – how warnings in the head-up display affect drivers’ gaze and driving behavior, in: 2015 IEEE 18th International Conference on Intelligent Transportation Systems, 2015, pp. 1035–1040
Basili, V., Caldiera, G., Rombach, H. Goal question metrics paradigm, in: J. Marciniak (Ed.), Encyclopedia of Software Engineering, Wilely, 1994, pp. 528–532
Cao Y, Theune M, Nijholt A (2009) Modality effects on cognitive load and performance in high-load information presentation, in: proceedings of the 14th international conference on intelligent user interfaces, IUI ’09. ACM, New York, NY, USA, pp 335–344
Lemmelä S, Vetek A, Mäkelä K, Trendafilov D (2008) Designing and evaluating multimodal interaction for mobile contexts, in: proceedings of the 10th international conference on multimodal interfaces, ICMI ’08. ACM, New York, NY, USA, pp 265–272
Obrenovic Z, Abascal J, Starcevic D (2007) Universal accessibility as a multimodal design issue. Commun ACM 50(5):83–88
Bernsen NO (1994) Foundations of multimodal representations: a taxonomy of representational modalities. Interact Comput 6(4):347–371
Reeves LM, Lai J, Larson JA, Oviatt S, Balaji TS, Buisine S, Collings P, Cohen P, Kraal B, Martin J-C, McTear M, Raman T, Stanney KM, Su H, Wang QY (2004) Guidelines for multimodal user interface design. Commun ACM 47:57–59
Savio, N., Braiterman, J.: Design sketch: the context of mobile interaction, in: Proceedings of MobileHCI 2007, 2007, pp. 248–286
Mohri M, Rostamizadeh A, Talwalkar A (2012) Foundations of machine learning. The MIT Press
Nair V (2010) Hinton. G. Rectified Linear Units Improve Restricted Boltzmann Machines, ICML
Goodfellow, I., Bengio, Y., Courville, A. 6.2.2.3 Softmax Units for Multinoulli Output Distributions. Deep Learning. MiT Press. pp. 180–184 (2016)
Diederik P (2015) Kingma and Jimmy Ba. Adam, A Method for Stochastic Optimization, International Conference on Learning Representations
de Lemos, R., Giese, H., Hausi A. Müller, Mary Shaw, Jesper Andersson, Marin Litoiu, Bradley Schmerl, Gabriel Tamura, Norha M. Villegas, Thomas Vogel, Danny Weyns, Luciano Baresi, Basil Becker, Nelly Bencomo and Yuriy Brun, Software Engineering for Self-Adaptive Systems: A second Research Roadmap, in Software Engineering for Self-Adaptive Systems II, LNCS, Springer, January 2013, vol. 7475, pp. 1–32
IBM, An architectural blueprint for autonomic computing, Autonomic Computing,White Paper 2005
Kitchenham B, Pickard L, Pfleeger SL (1995) Case studies for method and tool evaluation. IEEE Softw 12(4):52–62
Wohlin C, Runeson P, Host M, Ohlsson MC, Regnell B (2000) Wesslen. A. Experimentation in Software Engineering, An Introduction, Springer US
Davis FD (1989) Perceived usefulness. Perceived ease of use and user acceptance of information technology, MIS Quarterly 13(3):319–340
Jamieson S (2005) Likert scales: how to (ab) use them. Med Educ 38:1217–1218
Runeson, P. Using students as experiment subjects – an analysis on graduate and freshmen student data, in: Proceedings 7th International Conference on Empirical Assessment & Evaluation in Software Engineering, 2003, pp. 95–102
Litman, T.: Autonomous vehicle implementation predictions: implications for transport planning (2013)
Muller J No hands, no feet: my unnerving ride in Google’s driverless car. Forbes
Gil M, Giner P, Pelechano V (2012) Personalization for unobtrusive service interaction. Personal Ubiquitous Computing 16:543–561
Vastenburg, M., Keyson, D.V., de Ridder, H. Considerate home notification systems: a user study of acceptability of notifications in a living room laboratory. International Journal of Human-ComputerStudies 67(9):814–826
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