Prior Familiarization With Takeover Requests Affects Drivers' Takeover Performance and Automation Trust. (May 2017)

• Record Type: Journal Article
• Authors: Hergeth, Sebastian; Lorenz, Lutz; Krems, Josef F.
• Is Part Of: Human factors. Volume 59:Number 3(2017)
• Page Start: 457
• Page End: 470
• Publication Date: 2017-05
• Subjects: human–automation interaction -- trust in automation -- experimental design -- analysis and evaluation -- autonomous driving; Human engineering -- Periodicals; 620.82
• DOI: 10.1177/0018720816678714
• Languages: English
• ISSNs: 0018-7208

Abstract

Objective: The objective for this study was to investigate the effects of prior familiarization with takeover requests (TORs) during conditional automated driving on drivers' initial takeover performance and automation trust. Background: System-initiated TORs are one of the biggest concerns for conditional automated driving and have been studied extensively in the past. Most, but not all, of these studies have included training sessions to familiarize participants with TORs. This makes them hard to compare and might obscure first-failure-like effects on takeover performance and automation trust formation. Method: A driving simulator study compared drivers' takeover performance in two takeover situations across four prior familiarization groups (no familiarization, description, experience, description and experience) and automation trust before and after experiencing the system. Results: As hypothesized, prior familiarization with TORs had a more positive effect on takeover performance in the first than in a subsequent takeover situation. In all groups, automation trust increased after participants experienced the system. Participants who were given no prior familiarization with TORs reported highest automation trust both before and after experiencing the system. Conclusion: The current results extend earlier findings suggesting that prior familiarization with TORs during conditional automated driving will be most relevant for takeover performance in the first takeover situation and that it lowers drivers' automation trust. Application: Potential applications of this research include different approaches to familiarize users with automated driving systems, better integration of earlier findings, and sophistication of experimental designs.