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Explainable Automation: Personalized and Adaptive UIs to Foster Trust and Understanding of Driving Automation Systems

Published: 20 September 2020 Publication History

Abstract

Recent research indicates that transparent information on the behavior of automated vehicles positively affects trust, but how such feedback should be composed and if user trust influences the amount of desired feedback is relatively unexplored. Consequently, we conducted an interview study with (N=56) participants, who were presented different videos of an automated vehicle from the ego-perspective. Subjects rated their trust in the vehicle in these situations and could arbitrarily select objects in the driving environment that should be included in augmented reality feedback systems, so that they are able to trust the vehicle and understand its actions. The results show an inverse correlation between situational trust and participants’ desire for feedback and further reveal reasons why certain objects should be included in feedback systems. The study also highlights the need for more adaptive in-vehicle interfaces for trust calibration and outlines necessary steps for automatically generating feedback in the future.

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cover image ACM Conferences
AutomotiveUI '20: 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
September 2020
300 pages
ISBN:9781450380652
DOI:10.1145/3409120
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 20 September 2020

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Author Tags

  1. augmented reality
  2. automated driving
  3. explainable artificial intelligence
  4. feedback systems
  5. interview studies
  6. trust in automation
  7. user centered design

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Cited By

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  • (2024)TimelyTale: A Multimodal Dataset Approach to Assessing Passengers' Explanation Demands in Highly Automated VehiclesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785448:3(1-60)Online publication date: 9-Sep-2024
  • (2024)Explaining Away Control: Exploring the Relationship between Explainable AI and Passengers' Desire for Control in Automated VehiclesAdjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3641308.3685040(155-160)Online publication date: 22-Sep-2024
  • (2024)Customized HMI as a Key to increased Acceptance? Implications of an Online Survey assessing Relationships of Experience, Trust and Information InterestAdjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3641308.3685034(117-122)Online publication date: 22-Sep-2024
  • (2024)Effects of Uncertain Trajectory Prediction Visualization in Highly Automated Vehicles on Trust, Situation Awareness, and Cognitive LoadProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314087:4(1-23)Online publication date: 12-Jan-2024
  • (2024)One Size Does Not Fit All: Designing and Evaluating Criticality-Adaptive Displays in Highly Automated VehiclesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642648(1-15)Online publication date: 11-May-2024
  • (2024)Designing User Interfaces for Automated Driving: A Simulator Study on Individual Information PreferencesIEEE Transactions on Intelligent Vehicles10.1109/TIV.2023.33222619:1(338-346)Online publication date: Jan-2024
  • (2024)Evaluating the Influence of Characteristics on the Acceptance of Artificial Intelligence Application: An Empirical StudyHeliyon10.1016/j.heliyon.2024.e39460(e39460)Online publication date: Oct-2024
  • (2023)A Framework of Vehicle-Human Communication Features at Traffic Intersections to Enhance Trust and Situation AwarenessProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/2169506723119292767:1(1154-1160)Online publication date: 25-Oct-2023
  • (2023)We're in This Together: Exploring Explanation Needs and Methods in Shared Automated Shuttle BusesProceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia10.1145/3626705.3627798(145-151)Online publication date: 3-Dec-2023
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