The University of Southampton
University of Southampton Institutional Repository

Handover assist in highly automated vehicles: how vocal communication guides visual attention

Handover assist in highly automated vehicles: how vocal communication guides visual attention
Handover assist in highly automated vehicles: how vocal communication guides visual attention

Automated vehicles that require human intervention will inevitably require the transition of control and responsibility between driver and automation. These ‘handovers’ represent a vulnerability in the driving system due to factors such as reduced situation awareness. As a solution, handover assistants have been proposed to alleviate these drawbacks and facilitate better communication between vehicle and driver. We present findings from a vocal-handover task between two drivers, conducted in a driving simulator, to explore how visually scanning the environment can be encouraged using different vocal interactions. The data revealed trends such as how mentioning location may encourage more efficient visual gaze. Conversely, no vocal interaction may result in little-to-no visual gaze towards certain areas of the driving environment. Further study could explore how vocal interaction can work in conjunction with visual displays to guide visual attention during the handover task.

Automation, Eye-Tracking, Handover, Human communication
2194-5357
295-306
Springer
Clark, Jediah
5d82ac6c-58be-4366-9b11-5e3179d85b33
Stanton, Neville
351a44ab-09a0-422a-a738-01df1fe0fadd
Revell, Kirsten
e80fedfc-3022-45b5-bcea-5a19d5d28ea0
Clark, Jediah
5d82ac6c-58be-4366-9b11-5e3179d85b33
Stanton, Neville
351a44ab-09a0-422a-a738-01df1fe0fadd
Revell, Kirsten
e80fedfc-3022-45b5-bcea-5a19d5d28ea0

Clark, Jediah, Stanton, Neville and Revell, Kirsten (2019) Handover assist in highly automated vehicles: how vocal communication guides visual attention. In Advances in Human Aspects of Transportation - Proceedings of the AHFE 2018 International Conference on Human Factors in Transportation, 2018. vol. 786, Springer. pp. 295-306 . (doi:10.1007/978-3-319-93885-1_27).

Record type: Conference or Workshop Item (Paper)

Abstract

Automated vehicles that require human intervention will inevitably require the transition of control and responsibility between driver and automation. These ‘handovers’ represent a vulnerability in the driving system due to factors such as reduced situation awareness. As a solution, handover assistants have been proposed to alleviate these drawbacks and facilitate better communication between vehicle and driver. We present findings from a vocal-handover task between two drivers, conducted in a driving simulator, to explore how visually scanning the environment can be encouraged using different vocal interactions. The data revealed trends such as how mentioning location may encourage more efficient visual gaze. Conversely, no vocal interaction may result in little-to-no visual gaze towards certain areas of the driving environment. Further study could explore how vocal interaction can work in conjunction with visual displays to guide visual attention during the handover task.

This record has no associated files available for download.

More information

e-pub ahead of print date: 28 June 2018
Published date: 2019
Venue - Dates: AHFE International Conference on Human Factors in Transportation, 2018, Loews Sapphire Falls Resort at Universal Studios, Orlando, United States, 2018-07-21 - 2018-07-25
Keywords: Automation, Eye-Tracking, Handover, Human communication

Identifiers

Local EPrints ID: 422528
URI: http://eprints.soton.ac.uk/id/eprint/422528
ISSN: 2194-5357
PURE UUID: 9efa896c-c6e0-4020-b72a-c2085ef90d75
ORCID for Jediah Clark: ORCID iD orcid.org/0000-0002-1356-2462
ORCID for Neville Stanton: ORCID iD orcid.org/0000-0002-8562-3279

Catalogue record

Date deposited: 25 Jul 2018 16:30
Last modified: 18 Mar 2024 03:13

Export record

Altmetrics

Contributors

Author: Jediah Clark ORCID iD
Author: Neville Stanton ORCID iD
Author: Kirsten Revell

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×