Publication

Goldbach, C., Sickmann, J., Pitz, T., & Zimasa, T. (2022). Towards autonomous public transportation: Attitudes and intentions of the local population. Transportation Research Interdisciplinary Perspectives, 13, 100504. https://doi.org/10.1016/j.trip.2021.100504

Goldbach, C., Kayar, D., Pitz, T., & Sickmann, J. (2022). Driving, Fast and Slow: An Experimental Investigation of Speed Choice and Information. SAGE Open, 12(2), 21582440221091708.

Ferraz, V., & Pitz, T. (2022). Analyzing the Impact of Strategic Behavior in an Evolutionary Learning Model Using a Genetic Algorithm. Computational Economics, 1-39.

DOI: 10.3389/fncom.2022.939202

DOI: 10.1007/978-3-030-85099-9_6 Abstract This paper investigates the effects of the training process on the classification accuracy for a steady-state motion visual evoked potentials (SSMVEP)-based brain-computer interface (BCI) paradigm. An SSMVEP-based BCI works similar to SSVEP with the main difference that the stimulus is smoothly changing its appearance, with a continuous motion, leading to less user fatigue. Typical SSMVEP classification utilises correlation algorithms to compare the incoming Electroencephalography (EEG) data with a sine-cosine template.

DOI: https://doi.org/10.1016/j.trip.2020.100190.

Goldbach, C., Sickmann, J., Pitz, T., & Zimasa, T. (2022). Towards autonomous public transportation: Attitudes and intentions of the local population. Transportation Research Interdisciplinary Perspectives, 13, 100504. https://doi.org/10.1016/j.trip.2021.100504

Goldbach, C., Kayar, D., Pitz, T., & Sickmann, J. (2022). Driving, Fast and Slow: An Experimental Investigation of Speed Choice and Information. SAGE Open, 12(2), 21582440221091708.

Ferraz, V., & Pitz, T. (2022). Analyzing the Impact of Strategic Behavior in an Evolutionary Learning Model Using a Genetic Algorithm. Computational Economics, 1-39.

Minguillon, J., Volosyak, I., Guger, C., Tangermann, M., & Lopez, M. A. (2022). Brain-Computer Interfaces: Novel applications and interactive technologies. Frontiers in Computational Neuroscience, 16, 939202.

Stawicki, P., Rezeika, A., & Volosyak, I. (2021, June). Effects of Training on BCI Accuracy in SSMVEP-based BCI. In International Work-Conference on Artificial Neural Networks (pp. 69-80). Springer, Cham.

Ribeiro, P., Krause, A. F., Meesters, P., Kural, K., van Kolfschoten, J., Büchner, M. A., … & Essig, K. (2021). A VR Truck Docking Simulator Platform for Developing Personalized Driver Assistance. Applied Sciences, 11(19), 8911.

Wild-Wall, N. (2020). Kap. 6: Kompensation und erfolgreiches Altern: Neurokognitive und psychosoziale Grundlagen und die Relevanz für das Arbeitsleben. In M. Falkenstein & C. Kardys (Hrsg.): Arbeit, Kognition und Alter (84-100). Stuttgart: W. Kohlhammer GmbH.

Fenneman, A., Sickmann, J., Pitz, T. & Stanfey, A. (2020). Two distinct and separable processes underlie individual differences in algorithm adherence: differences in predictions and differences in trust thresholds, Journal of Behavioral Decision making.

Pitz, T., Kayar, D., Gardian, W., Sickmann, J. and Alkaş, H. (2020). “Comparison of competing market mechanisms with reinforcement learning in a carpooling scenario.” Transportation Research Interdisciplinary Perspectives, 7, 2020: 100190.