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Authors: Luka Rukonić 1 ; Marie-Anne Mwange 2 and Suzanne Kieffer 1

Affiliations: 1 Institute for Language and Communication, Université catholique de Louvain, Louvain-la-Neuve, Belgium ; 2 AISIN Europe, Braine-L’Alleud, Belgium

Keyword(s): Interactive Driver Tutoring, Mental Models, Car Voice Assistant, Wizard of Oz, Advanced Driver Assistance.

Abstract: 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. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Rukonić, L.; Mwange, M. and Kieffer, S. (2022). Teaching Drivers about ADAS using Spoken Dialogue: A Wizard of Oz Study. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - HUCAPP, ISBN 978-989-758-555-5; ISSN 2184-4321, pages 88-98. DOI: 10.5220/0010913900003124

@conference{hucapp22,
author={Luka Rukonić. and Marie{-}Anne Mwange. and Suzanne Kieffer.},
title={Teaching Drivers about ADAS using Spoken Dialogue: A Wizard of Oz Study},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - HUCAPP,},
year={2022},
pages={88-98},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010913900003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - HUCAPP,
TI - Teaching Drivers about ADAS using Spoken Dialogue: A Wizard of Oz Study
SN - 978-989-758-555-5
IS - 2184-4321
AU - Rukonić, L.
AU - Mwange, M.
AU - Kieffer, S.
PY - 2022
SP - 88
EP - 98
DO - 10.5220/0010913900003124