Calibration of Trust Expectancies in Conditionally Automated Driving by Brand, Reliability Information and Introductionary Videos: An Online Study

The design of a priori information about a conditionally automated driving (CAD) function influences the extent of effective usage of this function. The present online study investigated the effects of preliminary reliability and brand information on trust and acceptance for CAD. N = 519 participants were randomly assigned to (1) a reliability condition (high or low) and (2) an original equipment manufacturer (OEM) reputation condition (i.e., above average, average, below average, baseline). To measure the effect of CAD experience, participants were additionally exposed to four short videos of a driver interacting with a CAD function. Study results provide first evidence for an influence of OEM branding and reliability on CAD evaluation. We observed a trend towards more favorable attitudes for high compared to low reliability. This effect depends on the respective OEM reputation. The findings hold implications for the design of communication on automated vehicles to calibrate a priori assessment.

[1]  S. Turner,et al.  The SAGE Handbook of Social Science Methodology , 2007 .

[2]  Daniele Ruscio,et al.  Limitations and automation: the role of information about device-specific features in ADAS acceptability , 2016 .

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

[4]  Klaus Bengler,et al.  It's Out of Our Hands Now! Effects of Non-Driving Related Tasks During Highly Automated Driving on Drivers' Fatigue , 2017 .

[5]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[6]  R. Shprintzen,et al.  What's in a name? , 1990, The Cleft palate journal.

[7]  Markus Maurer,et al.  Rechtsfolgen zunehmender Fahrzeugautomatisierung , 2012 .

[8]  Jacob Cohen,et al.  A power primer. , 1992, Psychological bulletin.

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

[10]  M. König,et al.  Users’ resistance towards radical innovations: The case of the self-driving car , 2017 .

[11]  David C. Howell,et al.  The Treatment of Missing Data , 2007 .

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

[13]  Alexandra Neukum,et al.  Improving Usefulness of Automated Driving by Lowering Primary Task Interference through HMI Design , 2017 .

[14]  Linda Ng Boyle,et al.  Extending the Technology Acceptance Model to assess automation , 2011, Cognition, Technology & Work.

[15]  Kasper Hornbæk,et al.  Current practice in measuring usability: Challenges to usability studies and research , 2006, Int. J. Hum. Comput. Stud..

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

[17]  Frederik Naujoks,et al.  Testing Scenarios for Human Factors Research in Level 3 Automated Vehicles , 2017 .

[18]  J. Krems,et al.  The evolution of mental model, trust and acceptance of adaptive cruise control in relation to initial information , 2013 .

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

[20]  Alexandra Neukum,et al.  Driver compliance to take-over requests with different auditory outputs in conditional automation. , 2017, Accident; analysis and prevention.

[21]  Alexandra Neukum,et al.  A Human-Machine Interface for Cooperative Highly Automated Driving , 2017 .

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

[23]  Moritz Körber,et al.  Introduction matters: Manipulating trust in automation and reliance in automated driving. , 2018, Applied ergonomics.

[24]  G. Hofstede Cultural dimensions in management and planning , 1984 .

[25]  Josef F. Krems,et al.  Keep Your Scanners Peeled , 2016, Hum. Factors.

[26]  Josef F. Krems,et al.  Prior Familiarization With Takeover Requests Affects Drivers’ Takeover Performance and Automation Trust , 2017, Hum. Factors.

[27]  Guy H. Walker,et al.  Human Factors in Automotive Engineering and Technology , 2017 .

[28]  Bryan Reimer,et al.  What's in a Name: Vehicle Technology Branding & Consumer Expectations for Automation , 2017, AutomotiveUI.

[29]  R. Lewicki,et al.  Developing and Maintaining Trust in Work Relationships , 1996 .

[30]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[31]  Lesley Strawderman,et al.  Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. , 2017, Accident; analysis and prevention.

[32]  Mark R. Lehto,et al.  Foundations for an Empirically Determined Scale of Trust in Automated Systems , 2000 .