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Russwinkel, N. (2013). Modellierung von Zeitkognition bei der Fahrzeugführung [13]. In Jürgensohn, T. and Kohlrep, H. (Eds.), Fahrermodellierung in Wissenschaft und Wirtschaft.- 4. Berliner Fachtagung Fahrermodellierung, Berlin, 13./14. Juni 2013, p. 80-90.


Russwinkel, N. and Prezenski, S. (2014). ACT-R Meets Usability [14]. In Proceedings of the Sixth International Conference on Advanced Cognitive Technologies and Applications COGNITIVE, 2014. (Best Paper Award)


Russwinkel, N. (2020). Antizipierende interaktiv lernende autonome Agenten [15]. In Buxbaum, HJ. (Eds.), Mensch-Roboter-Kollaboration, p. 193-207.


Russwinkel, N., Prezenski, S., Joeres, F., Lindner, S. and Halbrügge, M. (2014). Introduction to cognitive modelling with ACT-R [16]. Cognitive Processing, 15(Suppl. 1), p. S25. (Tutorial im Rahmen der KogWis 2014)


Russwinkel, N., Prezenski, S., Lindner, S., Halbrügge, M., Schulz, M. and Wirzberger, M. (2014). Modeling of cognitive aspects of mobile interaction [17]. Cognitive Processing, 15(Suppl. 1), p. S22-S24. doi: 10.1007/s10339-014-0632-2 (Symposium im Rahmen der KogWis 2014)


Russwinkel, N., Vernaleken, C. and Klaproth, O. (2020). Towards Cognitive Assistance and Teaming in Aviation by Inferring Pilot's Mental State [18]. In Ahram, T. and Karwowski, W. and Vergnano, A. and Leali, F. and Taiar, R. (Eds.), Proceedings of the Intelligent Human Systems Integration 2020. Advances in Intelligent Systems and Computing, p. 1021-1027.


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Scharfe, M. and Russwinkel, N. (2019). Towards a Cognitive Model of the Takeover in Highly Automated Driving for the Improvement of Human Machine Interaction [19]. In Proceedings of the 17th International Conference on Cognitive Modelling.


Scharfe, M. and Russwinkel, N. (2019). A Cognitive Model for Understanding the Takeover in Highly Automated Driving Depending on the Objective Complexity of Non-Driving Related Tasks and the Traffic Environment [20]. In Proceedings of the 41th Annual Cognitive Science Society Meeting.


Scharfe, M., Zeeb, K. and Russwinkel, N. (2020). The Impact of Situational Complexity and Familiarity on Takeover Quality in Uncritical Highly Automated Driving Scenarios [21]. Information, 11, p. 115.


Scharfe, M. (2020). How are Eye Tracking Patterns in Takeover Situations related to Complexity, Takeover Quality and Cognitiive Model Predictions? [22]. In Zachaeus, Carolin (Eds.), Proceedings of the AMAA2020 Intelligent System Solutions for Auto Mobility and Beyond.


Scharfe, M. and Russwinkel, N. (2018). Towards a Cognitive Model for the Adaption of Cooperative Takeover Systems [23]. Poster presented at the HUFACO - Human Factors Aspects of Cooperative Systems Design.


Scharfe, M. and Russwinkel, N. (2019). A Cognitive Model for the Takeover Task in Complex Environments for Highly Automated Driving [24]. Poster presented at the EuroCogSci2019. TU Bochum.


Scharfe, M. and Russwinkel, N. (2021). Familiarity and Complexity during a Takeover in Highly Automated Driving [25]. International Journal of Intelligent Transportation Systems Research, .


Schuhmacher, J. (2017). Machine Learning for User Learning [26]. In Hess, Steffen and Fischer, Holger (Eds.), Mensch und Computer 2017 - Usability Professionals, p. 275-280.


Smieszek, H., Joeres, F. and Russwinkel, N. (2015). Workload of Airport Tower Controllers: Empirical Validation of a Macro-cognitive Model [27]. In Soeffker, D.; Kluge, A. (Eds.), Online Journal Kognitive Systeme, Heft 1(Vol. 2), 2015.


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