Publication

Ciuffo, B.. et al. (2023). Robotic Competitions to Design Future Transport Systems: The Case of JRC AUTOTRAC 2020.

Ciuffo, B., Makridis, M., Padovan, V., Benenati, E., Boriboonsomsin, K., Chembakasseril, M. T., Daras, P., Das, V., Dimou, A., Grammatico, S., Hartanto, R., Hoelscher, M., Jiang, Y., Krilasevic, S., Liu, S., Nguyen Le, Q. N., Rosier, C., Ruan, P., Wei, Z., … Zhao, Z. (2023). Robotic Competitions to Design Future Transport Systems: The Case of JRC AUTOTRAC 2020. Transportation Research Record, 2677(2), 1165–1178. https://doi.org/10.1177/03611981221110566{.broken_link}

Sikder, N., Esfahani, M. J., van Bakel, M., Idesis, S., Bovy, L., Weber, F., … & Dresler, M. (2022, October). The quantified scientist: a longitudinal study to explore the interdependencies between sleep, stress, the gut and other bodily functions. In JOURNAL OF SLEEP RESEARCH (Vol. 31). 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY.

Sikder, N., Esfahani, M. J., van Bakel, M., Idesis, S., Bovy, L., Weber, F., … & Dresler, M. (2022, October). The quantified scientist: a longitudinal study to explore the interdependencies between sleep, stress, the gut and other bodily functions. In JOURNAL OF SLEEP RESEARCH (Vol. 31). 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY.

Stawicki, P., & Volosyak, I. (2022). cVEP Training Data Validation—Towards Optimal Training Set Composition from Multi-Day Data. Brain Sciences, 12(2), 234.

DOI: 10.3390/brainsci12020234 Abstract This paper investigates the effects of the repetitive block-wise training process on the classification accuracy for a code-modulated visual evoked potentials (cVEP)-based brain–computer interface (BCI). The cVEP-based BCIs are popular thanks to their autocorrelation feature. The cVEP-based stimuli are generated by a specific code pattern, usually the m-sequence, which is phase-shifted between the individual targets. Typically, the cVEP classification requires a subject-specific template (individually created from the user’s own pre-recorded EEG responses to the same stimulus target), which is compared to the incoming electroencephalography (EEG) data, using the correlation algorithms.

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).

Abstract This study aimed to investigate the role of information and individual determinants on speed choice in a controlled laboratory setting in order to improve the general understanding of individual speeding behavior. A novel and interactive speed choice experiment was designed where participants repeatedly had to choose between fast or slow driving. Results showed that additional information had an effect on speeding choice if it contains quantitative instead of qualitative information.

Viswanathan, A., Titze, M., Nissing, D. (2022). Untersuchungen zur Nutzerakzeptanz eines aktiven Gaspedals für V2X-Szenarien. Investigations on User Acceptance of an Active Gas Pedal for V2X. Fachtagung VDI-Mechatronik 2022.

Abstract The possibility to provide the driver with V2X (vehicle to everything) information only by utilizing haptic feedback on the gas pedal (“active pedal) as the HMI (human machine interface) is investigated. A user acceptance study is carried out to determine the suitability of an active pedal as the HMI along with the relationship between the strength of haptic feedback on the driver’s response as well as the determination of side effects from such feedback.

Krause, A. F., & Essig, K. (2022). Protecting Privacy Using Low-Cost Data Diodes and Strong Cryptography. In Science and Information Conference (pp. 776-788). Springer, Cham.

https://doi.org/10.1007/978-3-031-10467-1_47 Abstract Compromised near-body electronic devices, like an eye tracker or a brain-computer interface, can leak private, highly sensitive biometric or medical data. Such data must be protected at all costs to avoid mass-surveillance and hacking attempts. We review the current, dire state of network security caused by complex protocols, closed-source software and proprietary hardware. To tackle the issue, we discuss a concept that protects privacy by combining three elements: data diodes, strong encryption and true random number generators.