Previous studies indicate that, if an automated vehicle communicates its system status and intended behaviour, it could increase user trust and acceptance. However, it is still unclear what types of interfaces will better portray this type of information. The present study evaluated different configurations of screens comparing how they communicated the possible hazards in the environment (e.g. vulnerable road users), and vehicle behaviours (e.g. intended trajectory). These interfaces were presented in a fully automated vehicle tested by 25 participants in an indoor arena. Surveys and interviews measured trust, usability and experience after users were driven by an automated low-speed pod. Participants experienced four types of interfaces, from a simple journey tracker to a windscreen-wide augmented reality (AR) interface which overlays hazards highlighted in the environment and the trajectory of the vehicle. A combination of the survey and interview data showed a clear preference for the AR windscreen and an animated representation of the environment. The trust in the vehicle featuring these interfaces was significantly higher than pretrial measurements. However, some users questioned if they want to see this information all the time. One additional result was that some users felt motion sick when presented with the more engaging content. This paper provides recommendations for the design of interfaces with the potential to improve trust and user experience within highly automated vehicles.
|Number of pages||17|
|Journal||Transportation Research Part F: Traffic Psychology and Behaviour|
|Early online date||30 Jun 2020|
|Publication status||Published - Jul 2020|
Bibliographical noteNOTICE: this is the author’s version of a work that was accepted for publication in Transportation Research Part F: Traffic Psychology and Behaviour. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Transportation Research Part F: Traffic Psychology and Behaviour, 72, (2020)
© 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
FunderInnovate UK Grant competition code: 1407_CRD1_TRANS_DCAR.
- Automated vehicles
- System transparency
- Trust in automation
- User experience
ASJC Scopus subject areas
- Civil and Structural Engineering
- Automotive Engineering
- Applied Psychology