Paper Info
Title
Acceptance of Full Driving Automation: Personally Owned and Shared-Use Concepts.
Abstract
Objective: This study aims to develop user acceptance models for two concepts of full driving automation: personally owned and shared use. Background: Many manufacturers have been investing considerably in and actively developing full driving automation. However, factors influencing user acceptance of full driving automation are not yet fully understood. Method: This study consisted of two parts: focus group discussions and online surveys. A total of 30 potential users participated in focus groups to discuss their perception of full driving automation acceptance. Based on the findings from focus group discussions, theoretical foundations, and empirical evidence, we hypothesized the acceptance models for both personally owned and shared-use concepts. We tested the models with 310 and 250 participants, respectively, online. Results: The results of focus groups indicated that users' concerns are centered around safety, usefulness, compatibility, trust, and ease of use. The survey results revealed the important roles of perceived usefulness and perceived safety in both models, whereas the direct impact of perceived ease of use was found to be insignificant. The indirect impact of perceived ease of use was less significant in the personally owned than in the shared-use model, whereas usefulness, trust, and compatibility played more important roles in the personally owned when compared with the shared-use model. Conclusion: The findings uncovered a chain of constructs that affect behavioral intention to use for both full driving automation concepts. Application: The framework and outcome of this study provide valuable guidelines that allow better understanding for government agencies, manufacturers, and automation designers regarding users' acceptance of full driving automation.
Year
DOI
Venue
2020
10.1177/0018720819870658
HUMAN FACTORS
Keywords
Field
DocType
adaptive automation,automation,expert systems,human-automation interaction,intelligent systems,technology acceptance,usability,acceptance measurement and research,human-computer interaction,computer systems
Social psychology,Intelligent decision support system,Engineering management,Expert system,Automation,Engineering
Journal
Volume
Issue
ISSN
62.0
SP2.0
0018-7208
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Sanaz Motamedi100.34
Pei Wang200.34
Tingting Zhang300.34
Ching-Yao Chan47923.48