Li, Y. orcid.org/0000-0001-7100-8040, Lee, Y.M. orcid.org/0000-0003-3601-4191, Yang, Y. orcid.org/0000-0001-5876-6576 et al. (5 more authors) (2023) Do Drivers have Preconceived Ideas about an Automated Vehicle's Driving Behaviour? In: Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. AutomotiveUI '23: 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 18-21 Sep 2023, Ingolstadt, Germany. ACM , New York, New York , pp. 291-299. ISBN 9798400701054
Abstract
This study investigated drivers' preconceived notions about manoeuvres of Automated Vehicles (AVs) compared to manually driven vehicles (MVs) using a pseudo-coupled driving simulator. The simulator displayed a message indicating the state of approaching vehicles (AV/MV) in a bottleneck scenario, while participants were informed that the MV was controlled by an experimenter using another simulator, despite all trials having the same preprogrammed behaviours. Results showed that the types of AV/MV did not impact participants' subjective responses. Communication through kinematic cues of the AV/MV was effective, with higher perceived safety, comprehension, and trust reported for approaching vehicles that yielded with an offset away from participants. Perceived safety and trust of the AV were also higher for trials with a light-band external Human Machine Interface (eHMI). This study highlights the value of both explicit and implicit cues for the communication of AVs with other drivers.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | AV-MV communication, AV behaviour, Implicit communication, eHMI, Bottleneck Road |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Safety and Technology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Jan 2024 11:59 |
Last Modified: | 09 Jan 2024 11:59 |
Published Version: | https://dl.acm.org/doi/10.1145/3580585.3607155 |
Status: | Published |
Publisher: | ACM |
Identification Number: | 10.1145/3580585.3607155 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:207287 |