In automated driving, getting ready to drive after a take-over is one of the most crucial topics. Whereas previous research mainly focuses on behavioral data, little is known about the driver’s experience. In this simulator study, the participants are asked retrospectively when they felt ready to drive again after the take-over. The results suggest that driver availability is a subjectively and situationally influenced concept determined by motoric, temporal, visual, or cognitive factors. Identifying the relevant factors contributes to the development of tailored support during the transition.
Funding source: Bundesministerium für Wirtschaft und Energie
Award Identifier / Grant number: 19A16006A
Funding statement: This work was funded by the German Federal Ministry for Economic Affairs and Energy (ID: 19A16006A).
About the authors
Lara Scatturin is a doctoral student at Robert Bosch GmbH in the department HMI Solutions for Display Products. She studied Cognitive Science at the University of Tübingen (M. Sc.). Her research is focused on the cognitive psychological foundations of take-over situations during automated driving.
Rainer Erbach, Senior Manager HMI at Robert Bosch GmbH, studied electrical engineering at the University of Karlsruhe and did there also his doctorate. He began his professional career as a systems engineer and software project manager. This was followed by several years in a leading position in IT consulting. In 2006, he joined the Bosch Group and took over responsibility for the HMI series development at Car Multimedia. Since 2016, his focus is in the area of HMI R&D for automated driving.
Martin Baumann received his Ph. D. in 2001 from Chemnitz University of Technology. From 2007 to 2014, he led the teams “Driver Cognition and Modeling” and “System ergonomics and interaction design” at the Institute of Transportation Systems at German Aerospace Center (DLR). Since February 2014, Martin Baumann is Professor for Human Factors at Ulm University. His main research interests are the cognitive processes underlying human behavior in human-machine systems.
The authors thank Ramona Schmid and Harald Schröder for their help with programming the experiment and analyzing the data.
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