TU Berlin

Cognitive Modeling in dynamic Human-Machine SystemsAlexander Lotz

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M.Sc. Alexander Lotz

Lupe
© Alexander Lotz

External Researcher


 

Telephone: +49 (0)711-17-59925

 

 

 

As the successive improvement of driver assistant systems is closing the gap towards implementing autonomous driving on a large scale, the human-machine-interaction is becoming of a primary focus. New systems allowing the driver to activate conditional autonomous driving temporarily, turn the driving task into a sequential handling between human and machine. When forced to take-over control of the vehicle, the driver has to process his/her surrounding to create an adequate situation awareness. This requires time as well as cognitive and perceptual resources. In this work, behavioural patterns are identified during the take-over situations through machine learning algorithms, in order to determine current and future situation awareness.

 

Research interests

  • Driver modeling in human-machine interaction
  • Take-over behaviour for autonomous driving
  • Classification methods through machine learning algorithms

 

Talks

  • Lotz, A. & Russwinkel, N. (2016). The Role of Familiarity in Spatial Competence. Presentation at Kognitive Systeme in Bochum, Germany, 14.03.-16.03.2016.
  • Lotz, A. & Russwinkel, N. (2016). Modelling different strategies in mental rotation. Presentation at KogWis in Bremen, Germany, 26.09.-30.09.2016.

Publications

Lotz, A. and Russwinkel, N. (2016). Modeling different strategies in mental rotation. In Proceedings of the 13th Biannual Conference of the German Cognitive Science Society (KogWis 2016).

Lotz, A. (2018). Take-over behavior for truck drivers in time critical situations. In 2nd Winter School Human Factors Aspects of Cooperative Systems Design. Link to publication

Lotz, A. and Weissenberger, S. (2019). Predicting take-over times of truck drivers in conditional autonomous driving. In Stanton, N. (Eds.), Advances in Intelligent Systems and Computing. Advances in Human Aspects of Transportation 2018, p. 329–338. Link to publication Link to original publication

Lotz, A. and Russwinkel, N. and Wohlfarth, E. (2019). Response Times and Gaze Behavior of Truck Drivers in Time Critical Conditional Automated Driving Take-overs. Transportation Research Part F: Traffic Psychology and Behaviour, 64, p. 532-551. Link to original publication

Fuhl, W. and Castner, N. and Kuebler, T. and Lotz, A. and Rosenstiel, W. and Kasneci, E. (2019). Ferns for area of interest free scanpath classification. In ACM (Eds.), Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications. Link to original publication

Wiese, S. and Lotz, A. and Russwinkel, N. (2019). SEEV-VM: ACT-R Visual Module based on SEEV theory. In Proceedings of the 17th International Conference on Cognitive Modeling. Link to publication

Lotz, A. and Russwinkel, N. and Wohlfarth, E. (2020). Take-over expectation and criticality in Level 3 automated driving: a test track study on take-over behavior in semi-trucks. Cognition, Technology and Work, (2020). Link to original publication

Lotz, A. and Russwinkel, N. and Wagner, T. and Wohlfarth, E. (2020). An adaptive assistance system for subjective critical driving simulation: understanding the relationship between subjective and objective complexity. In D. de Waard et al. (Eds.), Proceedings of the Human Factors and Ergonomics Society Europe Chapter 2019 Annual Conference. Nantes, France, p. 97-108. Link to publication Link to original publication

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