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Maneuver and Parameter Interventions in Automated Driving to Enhance User Satisfaction: A Kano Method Application

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HCI International 2023 – Late Breaking Papers (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14057))

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Abstract

This paper investigates participants’ perceptions and preferences regarding different cooperative intervention features for automated driving with level 2 driving automation. The experiment conducted involved 40 participants. A Kano questionnaire and a semi-standardized interview were employed to collect participants’ feedback on features for interventions in different maneuvers (e.g., initiating a lane change) and parameter settings (e.g., changing target speed). The results revealed a positive influence of most features on user satisfaction. Certain features were rated as essential requirements, while others were perceived as exciting additions. The response distributions show a high variance, indicating the existence of multiple user groups with different needs. The interviews conducted subsequently to the experiment provide qualitative insights, emphasizing the significance of implementation and the varying relevance between different maneuver and parameter interventions regarding satisfaction. The findings contribute to the design of experience-oriented human-machine interfaces (HMIs) in automated driving, highlighting the importance of cooperative features. The results can be used to prioritize the integration of distinct features. Future research should consider larger and more diverse samples to further enhance generalizability.

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Acknowledgments

We thank all those involved in the implementation of the experiment for their support.

Funding

This work was funded by the BMW Group.

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Authors and Affiliations

  1. Chair of Ergonomics, Technical University of Munich, Garching, Germany

    Lorenz Steckhan & Klaus Bengler

  2. BMW Group, Munich, Germany

    Wolfgang Spiessl

Authors
  1. Lorenz Steckhan
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  2. Wolfgang Spiessl
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  3. Klaus Bengler
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Corresponding author

Correspondence to Lorenz Steckhan .

Editor information

Editors and Affiliations

  1. Purdue University, West Lafayette, IN, USA

    Vincent G. Duffy

  2. Technische Universitat Ilmenau, Ilmenau, Germany

    Heidi Krömker

  3. Smart Future Initiative, Frankfurt am Main, Germany

    Norbert A. Streitz

  4. Kyushu University, Fukuoka, Japan

    Shin'ichi Konomi

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Steckhan, L., Spiessl, W., Bengler, K. (2023). Maneuver and Parameter Interventions in Automated Driving to Enhance User Satisfaction: A Kano Method Application. In: Duffy, V.G., Krömker, H., A. Streitz, N., Konomi, S. (eds) HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14057. Springer, Cham. https://doi.org/10.1007/978-3-031-48047-8_26

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  • DOI: https://doi.org/10.1007/978-3-031-48047-8_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48046-1

  • Online ISBN: 978-3-031-48047-8

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