Literature DB >> 24745204

Improving the driver-automation interaction: an approach using automation uncertainty.

Johannes Beller, Matthias Heesen, Mark Vollrath.   

Abstract

OBJECTIVE: The aim of this study was to evaluate whether communicating automation uncertainty improves the driver-automation interaction.
BACKGROUND: A false system understanding of infallibility may provoke automation misuse and can lead to severe consequences in case of automation failure. The presentation of automation uncertainty may prevent this false system understanding and, as was shown by previous studies, may have numerous benefits. Few studies, however, have clearly shown the potential of communicating uncertainty information in driving. The current study fills this gap.
METHOD: We conducted a driving simulator experiment, varying the presented uncertainty information between participants (no uncertainty information vs. uncertainty information) and the automation reliability (high vs.low) within participants. Participants interacted with a highly automated driving system while engaging in secondary tasks and were required to cooperate with the automation to drive safely.
RESULTS: Quantile regressions and multilevel modeling showed that the presentation of uncertainty information increases the time to collision in the case of automation failure. Furthermore, the data indicated improved situation awareness and better knowledge of fallibility for the experimental group. Consequently, the automation with the uncertainty symbol received higher trust ratings and increased acceptance.
CONCLUSION: The presentation of automation uncertaintythrough a symbol improves overall driver-automation cooperation. APPLICATION: Most automated systems in driving could benefit from displaying reliability information. This display might improve the acceptance of fallible systems and further enhances driver-automation cooperation.

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Mesh:

Year:  2013        PMID: 24745204     DOI: 10.1177/0018720813482327

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  4 in total

1.  Research on the use intention of potential designers of unmanned cars based on technology acceptance model.

Authors:  Tianyang Huang
Journal:  PLoS One       Date:  2021-08-20       Impact factor: 3.240

2.  Transitions Between Highly Automated and Longitudinally Assisted Driving: The Role of the Initiator in the Fight for Authority.

Authors:  Davide Maggi; Richard Romano; Oliver Carsten
Journal:  Hum Factors       Date:  2020-08-31       Impact factor: 2.888

3.  Examining Senior Drivers' Attitudes Toward Advanced Driver Assistance Systems After Naturalistic Exposure.

Authors:  Dan Liang; Nathan Lau; Stephanie A Baker; Jonathan F Antin
Journal:  Innov Aging       Date:  2020-06-18

4.  Component-Based Interactive Framework for Intelligent Transportation Cyber-Physical Systems.

Authors:  Sangsoo Jeong; Youngmi Baek; Sang H Son
Journal:  Sensors (Basel)       Date:  2020-01-02       Impact factor: 3.576

  4 in total

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