The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
Investigating the Importance of Trust on Adopting an Autonomous Vehicle
Abstract
The objective of this study is to examine the user’s adoption aspects of autonomous vehicle, as well as to investigate what factors drive people to trust an autonomous vehicle. A model explaining the impact of different factors on autonomous vehicles’ intention is developed based on the technology acceptance model and trust theory. A survey of 552 drivers was conducted and the results were analyzed using partial least squares. The results demonstrated that perceived usefulness and trust are major important determinants of intention to use autonomous vehicles. The results also show that three constructs—system transparency, technical competence, and situation management—have a positive effect on trust. The study identified that trust has a negative effect on perceived risk. Among the driving-related personality traits, locus of control has significant effects on behavioral intention, whereas sensation seeking did not. This study investigated that the developed model explains the factors that influence the acceptance of autonomous vehicle. The results of this study provide evidence on the importance of trust in the user’s acceptance of an autonomous vehicle.
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Cites
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Cited by
Trust in AI and Its Role in the Acceptance of AI Technologies
Choung, H., David, P., & Ross, A. (2023) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2050543 · Cited by 963
“The finding is in line with studies that have tested the impact of these constructs on the adoption of various forms of technology (e.g., Beldad & Hegner, 2018; Choi & Ji, 2015).”
ResultThe roles of initial trust and perceived risk in public’s acceptance of automated vehicles
Zhang, T., Tao, D., Qu, X., Zhang, X., Lin, R., & Zhang, W. (2019) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2018.11.018 · Cited by 837
What drives people to accept automated vehicles? Findings from a field experiment
Xu, Z., Zhang, K., Min, H., Wang, Z., Zhao, X., & Liu, P. (2018) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2018.07.024 · Cited by 631
User acceptance of virtual reality: An extended technology acceptance model
Sagnier, C., Loup-Escande, E., Lourdeaux, D., Thouvenin, I., & Valléry, G. (2020) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2019.1708612 · Cited by 493
Introduction matters: Manipulating trust in automation and reliance in automated driving
Körber, M., Baseler, E., & Bengler, K. (2018) · Applied Ergonomics · doi:10.1016/j.apergo.2017.07.006 · Cited by 418
Metadata
- Authors
- Choi, J. K., & Ji, Y. G.
- Venue
- International Journal of Human-Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2015-07-09
- Volume
- 31
- Issue
- 10
- Pages
- 692-702
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W2286247980
- Cited by
- 1,203
- References
- 69
- FWCI
- 30.24
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
