Trust in Automation – Before and After the Experience of Take-over Scenarios in a Highly Automated Vehicle☆

Highly automated vehicles (Level 3, [1]) are likely to enter the market within the next decade. By removing the driver from the driver-vehicle system, positive impacts, for instance on road-safety or fuel consumption, are expected. These predicted effects can only arise if automated vehicles are accepted by society. Trust as well as the attitude towards technology has been found to be a precursor in the acceptance formation process. Therefore, we conducted a driving simulator experiment within the interdisciplinary research group at the Munich Center of Technology in Society (MCTS) in order to investigate how the experience of automated driving will change trust in automation and the attitude of the driver towards automation. The sample consisted of 72 participants between 19 and 79 years (M = 44.97, SD = 22.16). Participants completed a questionnaire before and after the driving simulator experience to assess trust in automation, safety gain, intention to use and other constructs in order to analyze the change caused by the driving simulation experience. Besides participants’ ratings from the questionnaires, their gaze behavior was recorded in order to measure a change of trust by a change in scanning behavior. The participants drove highly automated on a three lane highway at a speed of 120 km/h. As critical situations are expected to have a significant impact on trust in automation, the participants experienced three take-over scenarios (system limits). Results indicate that the driving experience increased self-reported trust in automation and lead to a decrease in other measured constructs like safety gain. Older participants rated the vehicle automation more positively than younger drivers. Horizontal gaze behavior could not be confirmed as a metric for measuring trust in automation, although this measure behaved as expected and analogous to the self-reported level of trust.

[1]  Raj M. Ratwani,et al.  Single operator, multiple robots: an eye movement based theoretic model of operator situation awareness , 2010, HRI 2010.

[2]  Klaus Bengler,et al.  How Traffic Situations and Non-Driving Related Tasks Affect the Take-Over Quality in Highly Automated Driving , 2014 .

[3]  Leo Gugerty,et al.  Development of a Novel Measure of Situation Awareness: The Case for Eye Movement Analysis , 2010 .

[4]  Stephanie Arndt,et al.  Evaluierung der Akzeptanz von Fahrerassistenzsystemen , 2011 .

[5]  Klaus Bengler,et al.  Why Should I Use ADAS? Advanced Driver Assistance Systems and the Elderly: Knowledge, Experience and Usage Barriers , 2017 .

[6]  Ying Wang,et al.  The sensitivity of different methodologies for characterizing drivers’ gaze concentration under increased cognitive demand , 2014, Transportation Research Part F: Traffic Psychology and Behaviour.

[7]  Donald L. Fisher,et al.  Verbal and Spatial Loading Effects on Eye Movements in Driving Simulators: A Comparison to Real World Driving , 2002 .

[8]  Bonnie M. Muir,et al.  Trust Between Humans and Machines, and the Design of Decision Aids , 1987, Int. J. Man Mach. Stud..

[9]  Michela Terenzi,et al.  Using the Distribution of Eye Fixations to Assess Pilots' Mental Workload , 2006 .

[10]  Jason S. McCarley,et al.  Mind Wandering Behind the Wheel , 2011, Hum. Factors.

[11]  Jaap Ham,et al.  Trust in Smart Systems , 2012, Hum. Factors.

[12]  N Moray,et al.  Trust, control strategies and allocation of function in human-machine systems. , 1992, Ergonomics.

[13]  Klaus Bengler,et al.  “Take over!” How long does it take to get the driver back into the loop? , 2013 .

[14]  Neville Moray Are Observers Ever Really Complacent When Monitoring Automated Systems? , 2000 .

[15]  Klaus Bengler,et al.  Potential Individual Differences Regarding Automation Effects in Automated Driving , 2014, Interacción '14.

[16]  Alexander Pollatsek,et al.  Using Eye Movements To Evaluate Effects of Driver Age on Risk Perception in a Driving Simulator , 2005, Hum. Factors.

[17]  Neville A Stanton,et al.  Driver behaviour with adaptive cruise control , 2005, Ergonomics.

[18]  Bonnie M. Muir,et al.  Trust in automation. I: Theoretical issues in the study of trust and human intervention in automated systems , 1994 .

[19]  John D. Lee,et al.  Trust in Automation: Designing for Appropriate Reliance , 2004 .

[20]  Klaus Bengler,et al.  Taking Over Control from Highly Automated Vehicles , 2014 .

[21]  Raja Parasuraman,et al.  Humans and Automation: Use, Misuse, Disuse, Abuse , 1997, Hum. Factors.

[22]  Colin G. Drury,et al.  Foundations for an Empirically Determined Scale of Trust in Automated Systems , 2000 .

[23]  Masooda Bashir,et al.  Trust in Automation , 2015, Hum. Factors.

[24]  A. Fisk,et al.  Reliability and Age-Related Effects on Trust and Reliance of a Decision Support Aid , 2004 .

[25]  Charles T. Scialfa,et al.  Age differences in trust and reliance of a medication management system , 2005, Interact. Comput..