Trust Repair Strategies with Self-Driving Vehicles: An Exploratory Study. (September 2018)

• Record Type: Journal Article
• Authors: Kohn, Spencer C.; Quinn, Daniel; Pak, Richard; de Visser, Ewart J.; Shaw, Tyler H.
• Is Part Of: Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Volume 62:Part 1(2018)
• Page Start: 1108
• Page End: 1112
• Publication Date: 2018-09
• Subjects: Human engineering -- Congresses; 620.8205
• DOI: 10.1177/1541931218621254
• Languages: English
• ISSNs: 1541-9312

Abstract

Trust is important for any relationship, especially so with self-driving vehicles: passengers must trust these vehicles with their life. Given the criticality of maintaining passenger's trust, yet the dearth of self-driving trust repair research relative to the growth of the self-driving industry, we conducted two studies to better understand how people view errors committed by self-driving cars, as well as what types of trust repair efforts may be viable for use by self-driving cars. Experiment 1 manipulated error type and driver types to determine whether driver type (human versus self-driving) affected how participants assessed errors. Results indicate that errors committed by both driver types are not assessed differently. Given the similarity, experiment 2 focused on self-driving cars, using a wide variety of trust repair efforts to confirm human-human research and determine which repairs were most effective at mitigating the effect of violations on trust. We confirmed the pattern of trust repairs in human-human research, and found that some apologies were more effective at repairing trust than some denials. These findings help focus future research, while providing broad guidance as to potential methods for approaching trust repair with self-driving cars.