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PublicationAre Drivers Allowed to Sleep?( 2023)Higher levels of automated driving may offer the possibility to sleep in the driver’s seat in the car, and it is foreseeable that drivers will voluntarily or involuntarily fall asleep when they do not need to drive. Post-sleep performance impairments due to sleep inertia, a brief period of impaired cognitive performance after waking up, is a potential safety issue when drivers need to take over and drive manually. The present study assessed whether sleep inertia has an effect on driving and cognitive performance after different sleep durations. A driving simulator study with n = 13 participants was conducted. Driving and cognitive performance were analyzed after waking up from a 10-20 min sleep, a 30-60 min sleep, and after resting without sleep. The study’s results indicate that a short sleep duration does not reliably prevent sleep inertia. After the 10-20 min sleep, cognitive performance upon waking up was decreased, but the sleep inertia impairment faded within 15 min. Although the driving parameters showed no significant difference between the conditions, participants subjectively felt more tired after both sleep durations compared to resting. The small sample size of 13 participants, tested in a within-design, may have prevented medium and small effects from becoming significant. In our study, take-over was offered without time pressure, and take-over times ranged from 3.15 min to 4.09 min after the alarm bell, with a mean value of 3.56 min in both sleeping conditions. The results suggest that daytime naps without previous sleep deprivation result in mild and short-term impairments. Further research is recommended to understand the severity of impairments caused by different intensities of sleep inertia.
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PublicationEliciting potential for positive UX using psychological needs: Towards a user-centered method to identify technologies for UX in the car interior( 2022)Positive user experiences (PUX) in the vehicle interior will be enabled by choosing the technologies with the potential to provide such experiences. Design for PUX in general exists, but methods to assess and compare technologies regarding their PUX potential are missing. Building on the insight that fulfillment of basic psychological needs may lead to PUX (Hassenzahl et al., 2010), this paper presents the first iteration of the user-centered method Tec4UXNeeds. Tec4UXNeeds combines VR representations of technologies and half-structured interviews to identify PUX potential of technologies: which basic psychological needs a technology may fulfill and in which use cases the technology could be used to enable need fulfillment. The method is applied for two display technologies in a standardized within-subjects study (n = 27). The study investigates whether the method Tech4UX enables participants to describe whether a technology has a potential to fulfill psychological needs for them and whether the method is specific enough to find differences in need fulfillment potential between technologies described by participants.Preliminary results identified distinct levels of need fulfillment for the first and second display technology (Display on Demand & Holography). Data will be analyzed further using qualitative content analysis. The method will be optimized iteratively in the future.
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PublicationPersonalAIzation - Exploring concepts and guidelines for AI-driven personalization of in-car HMIs in fully automated vehicles( 2022)
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PublicationKlassifikation von Fahrerzuständen und Nebentätigkeiten über Körperposen bei automatisierter Fahrt( 2016)Durch die fortschreitende Automatisierung von Fahrzeugen, besonders des Fahrvorgangs selbst, verändert sich die Rolle des Fahrers mehr und mehr hin zum Passagier. Damit steigt die Bedeutung von Nebenaufgaben und fahrfremden Tätigkeiten. Solange jedoch mit Rückübergaben der Fahraufgabe an den Fahrer während der Fahrt gerechnet werden muss, müssen aus Sicherheits- und Komfortgründen die Aktivitäten des Fahrers erfasst werden. Eine Möglichkeit hierfür ist die optische Erfassung und Klassifikation der Körperhaltung. In diesem Beitrag präsentieren wir ein System zur manuellen Analyse der Körperhaltung für Simulator-Studien sowie einen Ansatz zur automatischen Erfassung der Körperhaltung im Fahrzeug.
