Conversational Voice Agents are Preferred and Lead to Better Driving Performance in Conditionally Automated Vehicles

dc.contributor.authorWang, M.en
dc.contributor.authorLee, S. C.en
dc.contributor.authorMontavon, G.en
dc.contributor.authorQin, J.en
dc.contributor.authorJeon, Myounghoonen
dc.date.accessioned2024-01-22T17:32:07Zen
dc.date.available2024-01-22T17:32:07Zen
dc.date.issued2022-09-17en
dc.description.abstractIn-vehicle intelligent agents (IVIAs) can provide versatile information on vehicle status and road events and further promote user perceptions such as trust. However, IVIAs need to be constructed carefully to reduce distraction and prevent unintended consequences like overreliance, especially when driver intervention is still required in conditional automation. To investigate the effects of speech style (informative vs. conversational) and embodiment (voice-only vs. robot) of IVIAs on driver perception and performance in conditionally automated vehicles, we recruited 24 young drivers to experience four driving scenarios in a simulator. Results indicated that although robot agents received higher system response accuracy and trust scores, they were not preferred due to great visual distraction. Conversational agents were generally favored and led to better takeover quality in terms of lower speed and smaller standard deviation of lane position. Our findings provide a valuable perspective on balancing user preference and subsequent user performance when designing IVIAs.en
dc.description.versionSubmitted versionen
dc.format.extentPages 86-95en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1145/3543174.3546830en
dc.identifier.isbn9781450394154en
dc.identifier.orcidJeon, Myounghoon [0000-0003-2908-671X]en
dc.identifier.urihttps://hdl.handle.net/10919/117543en
dc.language.isoenen
dc.publisherACMen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleConversational Voice Agents are Preferred and Lead to Better Driving Performance in Conditionally Automated Vehiclesen
dc.title.serialMain Proceedings - 14th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2022en
dc.typeConference proceedingen
dc.type.dcmitypeTexten
dc.type.otherConference Proceedingen
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/Engineering/Industrial and Systems Engineeringen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Engineering/COE T&R Facultyen

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
AutoUI2022_1014.pdf
Size:
684.68 KB
Format:
Adobe Portable Document Format
Description:
Submitted version
License bundle
Now showing 1 - 1 of 1
Name:
license.txt
Size:
1.5 KB
Format:
Plain Text
Description: