Teaching Drivers about ADAS using Spoken Dialogue: A Wizard of Oz Study
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| Titel: | Teaching Drivers about ADAS using Spoken Dialogue: A Wizard of Oz Study |
|---|---|
| Autoren: | Rukonic, Luka, Marie-Anne Pungu Mwange, Kieffer, Suzanne, 6th International Conference on Human Computer Interaction Theory and Applications (HUCAPP) |
| Weitere Verfasser: | UCL - SSH/ILC/PCOM - Pôle de recherche en communication |
| Verlagsinformationen: | SCITEPRESS |
| Publikationsjahr: | 2022 |
| Bestand: | DIAL@USL-B (Université Saint-Louis, Bruxelles) |
| Schlagwörter: | Interactive Driver Tutoring, Mental Models, Car Voice Assistant, Wizard of Oz, Advanced Driver Assistance |
| Beschreibung: | Understanding the limitations and capabilities of the advanced driver-assistance systems (ADAS) is a prerequisite for their safe and comfortable use. This paper presents a formative user study on the use of a dialogue-based system, implemented using the Wizard of Oz (WOz) technique, to help drivers learn about the correct use of driving assistance. We investigated whether drivers would build the correct mental model of the driving assistance systems through natural language dialogue. We describe the evolution of the prototype over four iterations of formative evaluation with older and younger drivers. Using a mixed-method approach, combining the WOz, interviews, questionnaires, and a knowledge quiz, we evaluated the prototype of a voice assistant and identified the teaching content objectives. Participants’ mental model about ADAS was assessed to evaluate the efficacy of the teaching approach. The results show that the teaching goals need to be clearly communicated to the drivers to ensure the adoption of the VA. |
| Publikationsart: | conference object |
| Sprache: | English |
| Relation: | boreal:257993; http://hdl.handle.net/2078.1/257993 |
| Verfügbarkeit: | http://hdl.handle.net/2078.1/257993 |
| Rights: | info:eu-repo/semantics/openAccess |
| Dokumentencode: | edsbas.5D110CAB |
| Datenbank: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: http://hdl.handle.net/2078.1/257993# Name: EDS - BASE (s4221598) Category: fullText Text: View record from BASE – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Rukonic%20L Name: ISI Category: fullText Text: Nájsť tento článok vo Web of Science Icon: https://imagesrvr.epnet.com/ls/20docs.gif MouseOverText: Nájsť tento článok vo Web of Science |
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| Items | – Name: Title Label: Title Group: Ti Data: Teaching Drivers about ADAS using Spoken Dialogue: A Wizard of Oz Study – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rukonic%2C+Luka%22">Rukonic, Luka</searchLink><br /><searchLink fieldCode="AR" term="%22Marie-Anne+Pungu+Mwange%22">Marie-Anne Pungu Mwange</searchLink><br /><searchLink fieldCode="AR" term="%22Kieffer%2C+Suzanne%22">Kieffer, Suzanne</searchLink><br /><searchLink fieldCode="AR" term="%226th+International+Conference+on+Human+Computer+Interaction+Theory+and+Applications+%28HUCAPP%29%22">6th International Conference on Human Computer Interaction Theory and Applications (HUCAPP)</searchLink> – Name: Author Label: Contributors Group: Au Data: UCL - SSH/ILC/PCOM - Pôle de recherche en communication – Name: Publisher Label: Publisher Information Group: PubInfo Data: SCITEPRESS – Name: DatePubCY Label: Publication Year Group: Date Data: 2022 – Name: Subset Label: Collection Group: HoldingsInfo Data: DIAL@USL-B (Université Saint-Louis, Bruxelles) – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Interactive+Driver+Tutoring%22">Interactive Driver Tutoring</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+Models%22">Mental Models</searchLink><br /><searchLink fieldCode="DE" term="%22Car+Voice+Assistant%22">Car Voice Assistant</searchLink><br /><searchLink fieldCode="DE" term="%22Wizard+of+Oz%22">Wizard of Oz</searchLink><br /><searchLink fieldCode="DE" term="%22Advanced+Driver+Assistance%22">Advanced Driver Assistance</searchLink> – Name: Abstract Label: Description Group: Ab Data: Understanding the limitations and capabilities of the advanced driver-assistance systems (ADAS) is a prerequisite for their safe and comfortable use. This paper presents a formative user study on the use of a dialogue-based system, implemented using the Wizard of Oz (WOz) technique, to help drivers learn about the correct use of driving assistance. We investigated whether drivers would build the correct mental model of the driving assistance systems through natural language dialogue. We describe the evolution of the prototype over four iterations of formative evaluation with older and younger drivers. Using a mixed-method approach, combining the WOz, interviews, questionnaires, and a knowledge quiz, we evaluated the prototype of a voice assistant and identified the teaching content objectives. Participants’ mental model about ADAS was assessed to evaluate the efficacy of the teaching approach. The results show that the teaching goals need to be clearly communicated to the drivers to ensure the adoption of the VA. – Name: TypeDocument Label: Document Type Group: TypDoc Data: conference object – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: boreal:257993; http://hdl.handle.net/2078.1/257993 – Name: URL Label: Availability Group: URL Data: http://hdl.handle.net/2078.1/257993 – Name: Copyright Label: Rights Group: Cpyrght Data: info:eu-repo/semantics/openAccess – Name: AN Label: Accession Number Group: ID Data: edsbas.5D110CAB |
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| RecordInfo | BibRecord: BibEntity: Languages: – Text: English Subjects: – SubjectFull: Interactive Driver Tutoring Type: general – SubjectFull: Mental Models Type: general – SubjectFull: Car Voice Assistant Type: general – SubjectFull: Wizard of Oz Type: general – SubjectFull: Advanced Driver Assistance Type: general Titles: – TitleFull: Teaching Drivers about ADAS using Spoken Dialogue: A Wizard of Oz Study Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rukonic, Luka – PersonEntity: Name: NameFull: Marie-Anne Pungu Mwange – PersonEntity: Name: NameFull: Kieffer, Suzanne – PersonEntity: Name: NameFull: 6th International Conference on Human Computer Interaction Theory and Applications (HUCAPP) – PersonEntity: Name: NameFull: UCL - SSH/ILC/PCOM - Pôle de recherche en communication IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2022 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa |
| ResultId | 1 |
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