The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
What drives people to accept automated vehicles? Findings from a field experiment
Abstract
Abstract This field study aims at understanding the influence of direct experience of an automated vehicle (AV, Level 3) and explaining and predicting public acceptance of AVs through a psychological model. The model includes behavioral intention (BI) to use self-driving vehicles (SDVs, Level 5), willingness to re-ride (WTR) in our AV (Level 3), and their four potential determinants, namely perceived usefulness (PU), perceived ease of use (PEU), trust related to SDVs, and perceived safety (PS) while riding in our AV. The last two determinants are largely ignored, but we consider them critical in the context of AVs. Three-hundred students were invited as participants (passengers) to experience the AV. The trust, PU, PEU, and BI of the participants were recorded prior to their experiencing the AV; after this experience, all the constructs of the psychological model were recorded. The participants’ experience with the AV was found to increase their trust, PU and PEU (but not BI), the consistency between PU/PEU and BI, and the explanatory power of BI. The model explained 55% of the variance in BI and 40% in WTR. PU, trust, and PS were found to be steady and direct predictors of both the acceptance measures; PEU predicted BI only after the participants’ AV experience. Mediation analysis showed that trust also can indirectly affect AV acceptance through other determinants. Out-of-sample prediction confirmed the model’s predictive capability for AV acceptance. The theoretical contributions and practical implications of the findings are discussed.
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The 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
Garrow, L. A., German, B. J., & Leonard, C. E. (2021) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2021.103377 · Cited by 488
The determinants of public acceptance of autonomous vehicles: An innovation diffusion perspective
Yuen, K. F., Wong, Y. D., Ma, F., & Wang, X. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.121904 · Cited by 298
Examining public acceptance of autonomous mobility
Rezaei, A., & Caulfield, B. (2020) · Travel Behaviour and Society · doi:10.1016/j.tbs.2020.07.002 · Cited by 72
Liu, P., Du, Y., & Xu, Z. (2019) · Accident Analysis & Prevention · doi:10.1016/j.aap.2019.02.012 · Cited by 65
Self-citation
Metadata
- Authors
- Xu, Z., Zhang, K., Min, H., Wang, Z., Zhao, X., & Liu, P.
- Venue
- Transportation Research Part C: Emerging Technologies
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 95
- Pages
- 320-334
- ISSN
- 0968-090X (ISSN-L)
- OpenAlex
- W2886300831
- Cited by
- 631
- References
- 68
- FWCI
- 53.17
- Type
- journal article
- Language
- en
- Open access
- closed
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- Xu, Z., Zhang, K., Min, H., Wang, Z., Zhao, X., & Liu, P. (2018). What drives people to accept automated vehicles? Findings from a field experiment. Transportation Research Part C: Emerging Technologies. https://doi.org/10.1016/j.trc.2018.07.024
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.