The chatty co-driver: A linguistics approach applying lessons learnt from aviation incidents
The chatty co-driver: A linguistics approach applying lessons learnt from aviation incidents
Drivers of contemporary vehicles are now able to relinquish control of the driving task to the vehicle, essentially allowing the driver to be completely hands and feet free. However, changes to legislation taking effect in 2016 will require the driver to be able to override the automated driving systems or switch them off completely. Initially this functionality is likely to be limited to certain areas, such as motorways. This creates a situation where the driver is expected to take control of the vehicle after being removed from the driving control-loop for extended periods of time, which places high demand on coordination between driver and automation. Resuming control after being removed from the control-loop have proven difficult in domains where automation is prevalent, such as aviation. Therefore the authors propose the Gricean Maxims of Successful Conversation as a means to identify, and mitigate flaws in Human-Automation-Interaction. As automated driving systems have yet to penetrate the market to a sufficient level to apply the Maxims, the authors applied the Maxims to two accidents in aviation. By applying the Maxims to the case studies from a Human-Automation-Interaction perspective, the authors were able to identify lacking feedback in different components of the pilot interface. By applying this knowledge to the driving domain, the authors argue that the Maxims could be used as a means to bridge the gulf of evaluation, by allowing the automation to act like a chatty co-driver, thereby increasing system transparency and reducing the effects of being out-of-the-loop.
Automated Driving, Communication, Common Ground, Human Automation Collaboration, Transfer of Control, Learning from Incidents
Eriksson, Alexander
75015c12-48a6-41ac-8fc4-15b1d71237f3
Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Eriksson, Alexander
75015c12-48a6-41ac-8fc4-15b1d71237f3
Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Eriksson, Alexander and Stanton, Neville A.
(2017)
The chatty co-driver: A linguistics approach applying lessons learnt from aviation incidents.
Safety Science.
(doi:10.1016/j.ssci.2017.05.005).
Abstract
Drivers of contemporary vehicles are now able to relinquish control of the driving task to the vehicle, essentially allowing the driver to be completely hands and feet free. However, changes to legislation taking effect in 2016 will require the driver to be able to override the automated driving systems or switch them off completely. Initially this functionality is likely to be limited to certain areas, such as motorways. This creates a situation where the driver is expected to take control of the vehicle after being removed from the driving control-loop for extended periods of time, which places high demand on coordination between driver and automation. Resuming control after being removed from the control-loop have proven difficult in domains where automation is prevalent, such as aviation. Therefore the authors propose the Gricean Maxims of Successful Conversation as a means to identify, and mitigate flaws in Human-Automation-Interaction. As automated driving systems have yet to penetrate the market to a sufficient level to apply the Maxims, the authors applied the Maxims to two accidents in aviation. By applying the Maxims to the case studies from a Human-Automation-Interaction perspective, the authors were able to identify lacking feedback in different components of the pilot interface. By applying this knowledge to the driving domain, the authors argue that the Maxims could be used as a means to bridge the gulf of evaluation, by allowing the automation to act like a chatty co-driver, thereby increasing system transparency and reducing the effects of being out-of-the-loop.
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Chatty Co-Driver_prepub
- Accepted Manuscript
More information
Accepted/In Press date: 18 May 2017
e-pub ahead of print date: 24 May 2017
Keywords:
Automated Driving, Communication, Common Ground, Human Automation Collaboration, Transfer of Control, Learning from Incidents
Organisations:
Transportation Group, Southampton Marine & Maritime Institute
Identifiers
Local EPrints ID: 410097
URI: http://eprints.soton.ac.uk/id/eprint/410097
ISSN: 0925-7535
PURE UUID: 65fc2be7-8636-46f1-84a0-21aedd371ca3
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Date deposited: 03 Jun 2017 04:02
Last modified: 16 Mar 2024 05:22
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Author:
Alexander Eriksson
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