Driver’s Age and Automated Vehicle Explanations
dc.contributor.author | Zhang, Qiaoning | |
dc.contributor.author | Yang, X. Jessie | |
dc.contributor.author | Robert, Lionel + "Jr" | |
dc.date.accessioned | 2021-02-05T12:33:33Z | |
dc.date.available | 2021-02-05T12:33:33Z | |
dc.date.issued | 2021-02-05 | |
dc.identifier.citation | Zhang, Q., Yang, X. J. and Robert, L. P. (2021). Driver’s Age and Automated Vehicle Explanations, Sustainability, accepted | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/166295 | en |
dc.identifier.uri | https://doi.org/10.3390/su13041948 | |
dc.description.abstract | Automated Vehicles (AV) have the potential to benefit our society. However, a lack of trust is a major barrier to the adoption of AVs. Providing explanations is one approach to facilitating AV trust by decreasing uncertainty about AV's decision-making and action. However, explanations might increase drivers’ cognitive effort and anxiety. Because of differences in cognitive ability across age groups, it is not clear whether explanations are equally beneficial for drivers across age groups in terms of trust, effort, and anxiety. To examine this, we conducted a mixed-design experiment with 40 participants divided into three age groups (i.e., younger, middle-age, and older). Participants were presented with: (1) no explanation, or (2) explanation given before or (3) after the AV took action, or (4) explanation along with a request for permission to take action. Results suggest that the explanations provided before AV take actions produced the highest trust and lowest effort for all drivers regardless of age group. The request-for-permission condition led to the highest trust and lowest effort only for older drivers. Younger drivers had the lowest anxiety and effort under the AV-explanation-after-action condition; however, this condition produced the highest level of anxiety and effort in middle-age and older drivers, respectively. These results have important implications in designing AV explanations and promoting trust. | en_US |
dc.description.sponsorship | University of Michigan Mcity | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Sustainability | en_US |
dc.subject | Automated Vehicles | en_US |
dc.subject | explanations | en_US |
dc.subject | Automated Vehicles explanations | en_US |
dc.subject | autonomous vehicle explanations | en_US |
dc.subject | autonomous vehicle | en_US |
dc.subject | autonomous vehicle trust | en_US |
dc.subject | Automated Vehicles trust | en_US |
dc.subject | Human-Machine Interface | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Artificial Intelligence Transparency | en_US |
dc.subject | Older Drivers | en_US |
dc.subject | Automated Driving | en_US |
dc.subject | Artificial Intelligence Explainability | en_US |
dc.subject | Driver's Age | en_US |
dc.subject | Automation | en_US |
dc.subject | self driving car | en_US |
dc.subject | Explainable Artificial Intelligence | en_US |
dc.subject | Artificial Intelligence trust | en_US |
dc.subject | advance driving automation | en_US |
dc.subject | Advanced Driver Assistance Systems | en_US |
dc.subject | Automated Driving Systems | en_US |
dc.subject | human computer interaction | en_US |
dc.subject | human robot interaction | en_US |
dc.title | Driver’s Age and Automated Vehicle Explanations | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Information and Library Science | |
dc.subject.hlbtoplevel | Social Sciences | |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Information, School of | en_US |
dc.contributor.affiliationum | College of Engineering | en_US |
dc.contributor.affiliationum | Robotics Institute | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/166295/1/Zhang et al. 2021 [Final paper]-sustainability-0202.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/166295/3/Zhang et al. 2021.pdf | en |
dc.identifier.doi | https://dx.doi.org/10.7302/218 | |
dc.identifier.doi | 10.3390/su13041948 | |
dc.identifier.source | Sustainability | en_US |
dc.identifier.orcid | 0000-0002-1410-2601 | en_US |
dc.description.filedescription | Description of Zhang et al. 2021 [Final paper]-sustainability-0202.pdf : Preprint | |
dc.description.depositor | SELF | en_US |
dc.identifier.name-orcid | Robert, Lionel P.; 0000-0002-1410-2601 | en_US |
dc.working.doi | 10.7302/218 | en_US |
dc.owningcollname | Information, School of (SI) |
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