An Online Study to Explore Trust in Highly Automated Vehicle in Non-Critical Automated Driving Scenarios

Haoyu Dong; Bastian Pfleging; Marieke H. Martens

doi:10.1145/3473682.3480259

An Online Study to Explore Trust in Highly Automated Vehicle in Non-Critical Automated Driving Scenarios

Haoyu Dong, Bastian Pfleging, Marieke H. Martens

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

While using highly automated systems, various non-critical automated driving scenarios can be identified in which trust plays a role. In this study, we investigated the change of trust in these scenarios with a digital “Feeling of Trust” indicator, through video-based online experiments simulating automated driving. Initial results show that trust even changes in these scenarios and revealed multiple influential factors. While trust seems to drop consistently in certain cases, we found individual differences in other events. With our experimental setup and findings, we provide a tool to examine trust aspects in an online study. This contributes to the understanding of how to design human-vehicle interactions in highly automated cars with the goal to calibrate trust under ordinary non-critical events.

Original language	English
Title of host publication	13th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI 2021)
Publisher	Association for Computing Machinery, Inc
Pages	34–38
Number of pages	5
ISBN (Electronic)	9781450386418
DOIs	https://doi.org/10.1145/3473682.3480259
Publication status	Published - 9 Sept 2021
Event	13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2021 - Virtual, Virtual, Online, United Kingdom Duration: 9 Sept 2021 → 14 Sept 2021 Conference number: 13 https://www.auto-ui.org/21/

Conference

Conference	13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2021
Abbreviated title	AutomotiveUI 2021
Country/Territory	United Kingdom
City	Virtual, Online
Period	9/09/21 → 14/09/21
Internet address	https://www.auto-ui.org/21/

Keywords

Trust calibration
highly automated vehicles
video study

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10.1145/3473682.3480259Licence: Unspecified

Cite this

Dong, H., Pfleging, B., & Martens, M. H. (2021). An Online Study to Explore Trust in Highly Automated Vehicle in Non-Critical Automated Driving Scenarios. In 13th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI 2021) (pp. 34–38). Association for Computing Machinery, Inc. https://doi.org/10.1145/3473682.3480259

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title = "An Online Study to Explore Trust in Highly Automated Vehicle in Non-Critical Automated Driving Scenarios",

abstract = "While using highly automated systems, various non-critical automated driving scenarios can be identified in which trust plays a role. In this study, we investigated the change of trust in these scenarios with a digital “Feeling of Trust” indicator, through video-based online experiments simulating automated driving. Initial results show that trust even changes in these scenarios and revealed multiple influential factors. While trust seems to drop consistently in certain cases, we found individual differences in other events. With our experimental setup and findings, we provide a tool to examine trust aspects in an online study. This contributes to the understanding of how to design human-vehicle interactions in highly automated cars with the goal to calibrate trust under ordinary non-critical events.",

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publisher = "Association for Computing Machinery, Inc",

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note = "13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2021, AutomotiveUI 2021 ; Conference date: 09-09-2021 Through 14-09-2021",

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Dong, H, Pfleging, B & Martens, MH 2021, An Online Study to Explore Trust in Highly Automated Vehicle in Non-Critical Automated Driving Scenarios. in 13th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI 2021). Association for Computing Machinery, Inc, pp. 34–38, 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2021, Virtual, Online, United Kingdom, 9/09/21. https://doi.org/10.1145/3473682.3480259

An Online Study to Explore Trust in Highly Automated Vehicle in Non-Critical Automated Driving Scenarios. / Dong, Haoyu; Pfleging, Bastian; Martens, Marieke H.
13th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI 2021). Association for Computing Machinery, Inc, 2021. p. 34–38.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N2 - While using highly automated systems, various non-critical automated driving scenarios can be identified in which trust plays a role. In this study, we investigated the change of trust in these scenarios with a digital “Feeling of Trust” indicator, through video-based online experiments simulating automated driving. Initial results show that trust even changes in these scenarios and revealed multiple influential factors. While trust seems to drop consistently in certain cases, we found individual differences in other events. With our experimental setup and findings, we provide a tool to examine trust aspects in an online study. This contributes to the understanding of how to design human-vehicle interactions in highly automated cars with the goal to calibrate trust under ordinary non-critical events.

AB - While using highly automated systems, various non-critical automated driving scenarios can be identified in which trust plays a role. In this study, we investigated the change of trust in these scenarios with a digital “Feeling of Trust” indicator, through video-based online experiments simulating automated driving. Initial results show that trust even changes in these scenarios and revealed multiple influential factors. While trust seems to drop consistently in certain cases, we found individual differences in other events. With our experimental setup and findings, we provide a tool to examine trust aspects in an online study. This contributes to the understanding of how to design human-vehicle interactions in highly automated cars with the goal to calibrate trust under ordinary non-critical events.

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An Online Study to Explore Trust in Highly Automated Vehicle in Non-Critical Automated Driving Scenarios

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