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

Lorenz Steckhan, Wolfgang Spiessl, Klaus Bengler

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationHCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings
EditorsVincent G. Duffy, Heidi Krömker, Norbert A. Streitz, Shin'ichi Konomi
PublisherSpringer Science and Business Media Deutschland GmbH
Pages390-404
Number of pages15
ISBN (Print)9783031480461
DOIs
StatePublished - 2023
Event25th International Conference on Human-Computer Interaction, HCII 2023 - Copenhagen, Denmark
Duration: 23 Jul 202328 Jul 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14057 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th International Conference on Human-Computer Interaction, HCII 2023
Country/TerritoryDenmark
CityCopenhagen
Period23/07/2328/07/23

Keywords

  • automated driving
  • driver vehicle cooperation
  • kano model
  • maneuver control
  • parameter control
  • user experience
  • user preference
  • user satisfaction

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