Key Learnings
- How to setup a field studiy and which challanges can appear
- Learn how to measure more than 3 interaction patterns at the same time
- How to measure trust and acceptance in semi-automated driving
The state-of-the-art on interaction between drivers and advanced driver assistance systems (ADAS) lacks studies in the field instead of a simulated context. Beyond that, studies explicitly respecting diversity of drivers – e.g., age, gender, experience with ADAS – are underrepresented. Most studies infer their results from participant groups consisting of relatively young, technology-affine, male persons.
The GENDrive project makes use of the recent possibility to conduct field studies with recently introduced commercial ADAS (Level 2). For this purpose, a set of heterogeneous variables coming from various data sources are recorded. Such interaction patterns are assumed to be measurable by various sensors aiming at gathering data from subjects as well as objectified vehicle data. These sensors range from qualitative data (e.g., interviews) to psycho-physiological measurements (e.g., skin conductance) to eye-tracking to data acquired from the vehicle itself (e.g., speed). Using methods of data science, these measurements are combined and synchronized in order to obtain a comprehensive view on drivers.
Date: Wednesday, October 21st
Norah Neuhuber
Research Scientist for Human-Centered Systems, Virtual Vehicle Research GmbH
I hold a Master’s Degree in Psychology from the University of Graz, specializing in Work & Organizational Psychology (Human Factors). During the past four years I had the opportunity to deepen my understanding of Human Factors. Within that time I gained experience in topics such as Human-Automation Interaction, Human-Centered Design, Data Analysis, Task Analysis & Psychophysiology. My current research focus is on trust in automation.
My goal is to further develop my skills as a Human Factors Specialist and to contribute to the development of human-centered systems.
Alexander Stocker
Key Researcher, Virtual Vehicle Research GmbH
Interested in Information Systems, Digitalisation, Digital Transformation, Data Science, Automotive, Information & Knowledge Management, Web 2.0 and Enterprise 2.0, Semantic Web, Web of Data
