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Individual Differences and Expectations of Automated Vehicles.

Authors :
Zhang, Qiaoning
Yang, X. Jessie
Robert Jr., Lionel P.
Source :
International Journal of Human-Computer Interaction. Jun2022, Vol. 38 Issue 9, p825-836. 12p. 3 Charts, 2 Graphs.
Publication Year :
2022

Abstract

Despite the benefits of automated vehicles (AVs), there are still barriers to their widespread adoption. Expectations about AVs have been identified as one of the most important factors in understanding AV adoption. Therefore, by understanding the public's expectations of AVs, we can better understand whether or when AVs are likely to be adopted on a wide scale. Individual differences, including demographics and personality, have been identified as factors that impact technology expectations and adoption. However, it is not clear whether and how individual differences can influence expectations of AVs. To examine this, we conducted an online survey with 443 U.S. drivers who were recruited and divided into subpopulations by age, gender, ethnicity, census region, educational level, marital status, income, driving frequency, driving experience, and personality traits. Results revealed that drivers' expectations of AVs differ significantly by age, gender, ethnicity, education levels, marital status, drive frequency, drive experience, and personality. More specifically, higher expectations are more often generated by drivers who are younger, men, White non-Hispanic, more highly educated, never married, with a higher frequency of driving, with less driving experience, and who are high in extraversion, agreeableness, conscientiousness, and emotional stability. The results of this study provide a foundation for future research related to expectations and have important implications on future design and development of AVs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10447318
Volume :
38
Issue :
9
Database :
Academic Search Index
Journal :
International Journal of Human-Computer Interaction
Publication Type :
Academic Journal
Accession number :
156553951
Full Text :
https://doi.org/10.1080/10447318.2021.1970431