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Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems
Trust is critical for human-automation collaboration, especially under safety-critical tasks such as driving. Providing explainable information on how the automation system reaches decisions and predictions can improve system transparency, which is believed to further facilitate driver trust and use...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232983/ https://www.ncbi.nlm.nih.gov/pubmed/37275735 http://dx.doi.org/10.3389/fpsyg.2023.1121622 |
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author | Taylor, Skye Wang, Manhua Jeon, Myounghoon |
author_facet | Taylor, Skye Wang, Manhua Jeon, Myounghoon |
author_sort | Taylor, Skye |
collection | PubMed |
description | Trust is critical for human-automation collaboration, especially under safety-critical tasks such as driving. Providing explainable information on how the automation system reaches decisions and predictions can improve system transparency, which is believed to further facilitate driver trust and user evaluation of the automated vehicles. However, what the optimal level of transparency is and how the system communicates it to calibrate drivers’ trust and improve their driving performance remain uncertain. Such uncertainty becomes even more unpredictable given that the system reliability remains dynamic due to current technological limitations. To address this issue in conditionally automated vehicles, a total of 30 participants were recruited in a driving simulator study and assigned to either a low or a high system reliability condition. They experienced two driving scenarios accompanied by two types of in-vehicle agents delivering information with different transparency types: “what”-then-wait (on-demand) and “what + why” (proactive). The on-demand agent provided some information about the upcoming event and delivered more information if prompted by the driver, whereas the proactive agent provided all information at once. Results indicated that the on-demand agent was more habitable, or naturalistic, to drivers and was perceived with faster system response speed compared to the proactive agent. Drivers under the high-reliability condition complied with the takeover request (TOR) more (if the agent was on-demand) and had shorter takeover times (in both agent conditions) compared to those under the low-reliability condition. These findings inspire how the automation system can deliver information to improve system transparency while adapting to system reliability and user evaluation, which further contributes to driver trust calibration and performance correction in future automated vehicles. |
format | Online Article Text |
id | pubmed-10232983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102329832023-06-02 Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems Taylor, Skye Wang, Manhua Jeon, Myounghoon Front Psychol Psychology Trust is critical for human-automation collaboration, especially under safety-critical tasks such as driving. Providing explainable information on how the automation system reaches decisions and predictions can improve system transparency, which is believed to further facilitate driver trust and user evaluation of the automated vehicles. However, what the optimal level of transparency is and how the system communicates it to calibrate drivers’ trust and improve their driving performance remain uncertain. Such uncertainty becomes even more unpredictable given that the system reliability remains dynamic due to current technological limitations. To address this issue in conditionally automated vehicles, a total of 30 participants were recruited in a driving simulator study and assigned to either a low or a high system reliability condition. They experienced two driving scenarios accompanied by two types of in-vehicle agents delivering information with different transparency types: “what”-then-wait (on-demand) and “what + why” (proactive). The on-demand agent provided some information about the upcoming event and delivered more information if prompted by the driver, whereas the proactive agent provided all information at once. Results indicated that the on-demand agent was more habitable, or naturalistic, to drivers and was perceived with faster system response speed compared to the proactive agent. Drivers under the high-reliability condition complied with the takeover request (TOR) more (if the agent was on-demand) and had shorter takeover times (in both agent conditions) compared to those under the low-reliability condition. These findings inspire how the automation system can deliver information to improve system transparency while adapting to system reliability and user evaluation, which further contributes to driver trust calibration and performance correction in future automated vehicles. Frontiers Media S.A. 2023-05-18 /pmc/articles/PMC10232983/ /pubmed/37275735 http://dx.doi.org/10.3389/fpsyg.2023.1121622 Text en Copyright © 2023 Taylor, Wang and Jeon. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Taylor, Skye Wang, Manhua Jeon, Myounghoon Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems |
title | Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems |
title_full | Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems |
title_fullStr | Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems |
title_full_unstemmed | Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems |
title_short | Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems |
title_sort | reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232983/ https://www.ncbi.nlm.nih.gov/pubmed/37275735 http://dx.doi.org/10.3389/fpsyg.2023.1121622 |
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