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Journal Article

Citation

Motamedi S, Wang P, Zhang T, Chan CY. Hum. Factors 2019; ePub(ePub): ePub.

Affiliation

University of California, Berkeley, Richmond, USA.

Copyright

(Copyright © 2019, Human Factors and Ergonomics Society, Publisher SAGE Publishing)

DOI

10.1177/0018720819870658

PMID

31469591

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.


Language: en

Keywords

adaptive automation; automation; computer systems; expert systems; human–automation interaction; human–computer interaction; intelligent systems; technology acceptance; usability/acceptance measurement and research

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