Abstract
Driving automation is radically changing the role of the driver. The proliferation of driving assistance systems is increasingly transforming driver’s tasks from vehicle control operations to supervising activities. However, the process of turning the driver into a passenger is far from being accomplished. This paper describes an innovative interaction approach developed in the framework of EU funded project AutoMate. The overarching aim of AutoMate is to build a “TeamMate System”, in which the human and the automation cooperate with each other to achieve a safe, pleasant and efficient driving. Through an effective interaction, and by sharing perception, decision and action, they can negotiate specific behaviors and maneuvers in order to build a team based on trust. In order to measure the effectiveness of this concept, a driving simulator experiment has been conducted: findings suggest that the concept of Human-Machine Team can increase the trust in automation and improve the efficiency in specific conditions.
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Karush, S.: They’re working: Insurance claims data show which new technologies are preventing crashes. Status report of the insurance institute for highway safety—highway loss data institute, vol. 52, no. 5 (2012)
Buehler, M., Iagnemma, K., Singh, S. (eds.): The DARPA Urban Challenge: Autonomous Vehicles in City Traffic. (Series Springer Tracts in Advanced Robotics), vol. 56. Springer, Heidelberg (2009)
Wei, J., Snider, J., Kim, J., Dolan, J., Rajkumar, R., Litkouhi, B.: Towards a viable autonomous driving research platform. In: Proceeding of the IEEE Intelligent Vehicles Symposium, Gold Coast, Australia, June 2013, pp. 763–770 (2013)
Wachtel, J.: By what hubris? The readiness of the human operator to take over when the automation fails or hands over control. In: Proceeding of DDI 2018, 6th International Conference on Driver Distraction and Inattention, Gothenborg (2018)
Kaber, D.B., Endsley, M.R.: Out-of-the-loop performance problems and the use of intermediate levels of automation for improved control system functioning and safety. Process Saf. Prog. 16, 126–131 (1997)
Stanton, N.A., Marsden, P.: From fly-by-wire to drive-by-wire: Safety implications of automation in vehicles. Saf. Sci. 24, 35–49 (1996)
Rudin-Brown, C.M., Parker, H.A.: Behavioural adaptation to adaptive cruise control (ACC): implications for preventive strategies. Transp. Res. Part F Traffic Psychol. Behav. 7, 59–76 (2004)
Saffarian, M., De Winter, J.C.F., Happee, R.: Automated driving: human-factors issues and design solutions. In: Proceedings of the Human Factors and Ergonomics Society 56th Annual Meeting, pp. 2296–2300 (2012)
Poulin, C., Stanton, N.A., Cebon, D.: Response to: autonomous vehicles. Ingenia Online (62) (2015)
Eriksson, A., Stanton, N.A.: The chatty co-driver: a linguistics approach to human-automation-interaction. In: Human Factors in Organizational Design and Management – XI (1997)
Koo, J., et al.: Why did my car just do that? Explaining semi-autonomous driving actions to improve driver understanding, trust, and performance. Int. J. Interact. Des. Manuf. (IJIDeM) 9(4), 269–275 (2015)
Castellano, A., et al.: Is your request just this? New automation paradigm to reduce the requests of transition without increasing the effort of the driver. In: 25th ITS World Congress, Copenhagen, Denmark (2018)
Körber, M.: Theoretical considerations and development of a questionnaire to measure trust in automation. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds.) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018): Volume VI: Transport Ergonomics and Human Factors (TEHF), Aerospace Human Factors and Ergonomics, 1st edn, pp. 13–30. Springer (2019)
Van der Laan, J.D., Heino, A., De Waard, D.: A simple procedure for the assessment of acceptance of advanced transport telematics. Transp. Res.-Part C Emerg. Technol. 5, 1–10 (1997)
Hart, S.G., Staveland, L.E.: Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. In: Hancock, P.A., Meshkati, N. (eds.) Human Mental Workload. Advances in Psychology (1988)
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The paper has been written in the framework of AutoMate Project. This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme, under Grant Agreement No. 690705.
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Castellano, A., Fossanetti, M., Landini, E., Tango, F., Montanari, R. (2020). Automation as Driver Companion: Findings of AutoMate Project. In: Ahram, T., Karwowski, W., Vergnano, A., Leali, F., Taiar, R. (eds) Intelligent Human Systems Integration 2020. IHSI 2020. Advances in Intelligent Systems and Computing, vol 1131. Springer, Cham. https://doi.org/10.1007/978-3-030-39512-4_159
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DOI: https://doi.org/10.1007/978-3-030-39512-4_159
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