Trust in technology is an important factor to be considered for safety-critical systems. Of particular interest today is the transport domain, as more and more complex information and assistance systems find their way into vehicles. Research in driving automation / automated driving systems is in the focus of many research institutes worldwide. On the operational side, active safety systems employed to save lives are frequently used by non-professional drivers that neither know system boundaries nor the underlying functional principle. This is a serious safety issue, as systems are activated under false circumstances and with wrong expectations. At least some of the recent incidents with advanced driving assistance systems (ADAS) or automated driving systems (ADS; SAE J3016) could have been prevented with a full understanding of the driver about system functionality and limitations (instead of overreliance). Drivers have to be trained to accept and use these systems in a way, that subjective trust matches objective trustworthiness (cf. “appropriate trust”) to prevent disuse and / or misuse. In this article, we present an interaction model for trust calibration that issues personalized messages in real time. On the showcase of automated driving we report the results of two user studies related to trust in ADS and driving ethics. In the first experiment (N = 48), mental and emotional states of front-seat passengers were compared to get deeper insight into the dispositional trust of potential users of automated vehicles. Using quantitative and qualitative methods, we found that subjects accept and trust ADSs almost similarly as male / female drivers. In another study (N = 40), moral decisions of drivers were investigated in a systematic way. Our results indicate that the willingness of drivers to risk even severe accidents increases with the number and age of pedestrians that would otherwise be sacrificed. Based on our initial findings, we further discuss related aspects of trust in driving automation. Effective shared vehicle control and expected advantages of fully / highly automated driving (SAE levels 3 or higher) can only be achieved when trust issues are demonstrated and resolved.
About the authors
Philipp Wintersberger is a research assistant at the research center CARISSMA (Center of Automotive Research on Integrated Safety Systems and Measurement Area) at the University of Applied Sciences Ingolstadt (THI). After finishing the Federal Higher Technical College for Informatics in Leonding, he studied Computer Science and obtained his diploma at the Johannes Kepler University Linz specializing in Human-Computer-Interaction and Computer Vision. He worked 10 years as software engineer / architect in professional software development (in the field of Business Process Management and Mobile Computing) and was repeatedly invited to give talks about mobile and software development. In January 2016, he decided to accept a position as PHD candidate in the area of Human Factors and & Driving Ergonomics at THI. His research interests focus on human factors in automated driving, especially trust in automation, ethics and driver state assessment.
Andreas Riener is professor for Human-Machine Interaction and Virtual Reality in the Faculty for Electrical Engineering and Computer Science at the University of Applied Sciences Ingolstadt (THI). He has a co-appointment in the research center CARISSMA (Center of Automotive Research on Integrated Safety Systems and Measurement Area) in the area of Human Factors & Driving Ergonomics. Riener is leading the degree program User Experience Design and the head of several labs at THI (UXD, Driving simulator).
His research interests include driving ergonomics, driver state assessment from physiological measures, human factors in driver-vehicle interfaces and topics related to (over)trust, user acceptance, and ethics in automated driving. His focus is hypothesis-driven experimental research in the area of driver and driving support systems at various levels (simulation, simulator studies, field operational tests, naturalistic driving studies). One particular interest is in the methodological investigation of human factors in driving (emotional state recognition: detection of stress, fatigue, cognitive overload, situation awareness; trust in and acceptance of technology, etc.). Furthermore, his research interests include cyber-physical (automotive) systems, augmented reality (AR) applications and virtual reality (VR) environments, and novel interaction concepts for automated driving including communication strategies, ethical and legal aspects, and safety and security issues (hacking, identity preservation).
Prof. Riener’s research has yielded more than 100 publications across various journals and conference proceedings in the broader field of sensor / actuator (embedded) systems, (implicit) human-computer interaction, human vital state recognition, or context-sensitive data processing. He has presented his research findings in more than 50 conference talks, was invited to teach courses at universities in Austria, Germany and US and to give keynote talks at several conferences. He was further invited as expert, consultant and key contributor to various workshops. Furthermore, he was engaged in several EU- (FP7 SOCIONICAL, FP7 OPPORTUNITY) and industrial funded (SIEMENS P2P, FACT) research projects and has been long-time reviewer for conferences (including PERVASIVE, UBICOMP, CHI, ISWC, AmI, EuroSSC) and journals (such as IEEE PCM, IEEE ITS, Springer PUC, etc.) in the pervasive / ubiquitous / automotive / embedded / networking domain. In June 2016 he was one of the co-organizers of the Dagstuhl seminar 16262 on “Automotive User Interfaces in the Age of Automation”.
This work is based, in part, on discussions with participants of the Dagstuhl Seminar 16262 “Automotive User Interfaces in the Age of Automation”, http://www.dagstuhl.de/16262.
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