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Explainability in Automated Parking: The Effect of Augmented Reality Visualizations on User Experience and Situation Awareness

Published: 03 December 2023 Publication History

Abstract

Although automated driving is becoming a more widespread technology, there is still a lack of understanding about how to best communicate information to drivers in the specific situation of automated parking. This mixed-method user study aimed to address this gap by evaluating the preferences of users for information about the vehicle’s behavior in automated parking and the impact on user experience and situation awareness. An explainable concept displayed as augmented visualizations in the vehicle’s windshield was prototyped and evaluated in a driving simulation study and a qualitative interview. N = 25 participants provided insights into the development of more effective and user-centered interface designs for automated parking. As a result, the explainable concept was preferred by the participants and led to a higher user experience and explainability. This work contributes to the design and evaluation of future automated parking systems and provides a step towards more user-friendly automated driving experiences.

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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)Agents preserving privacy on intelligent transportation systems according to EU lawArtificial Intelligence and Law10.1007/s10506-024-09391-0Online publication date: 12-Feb-2024

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    cover image ACM Other conferences
    MUM '23: Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia
    December 2023
    607 pages
    ISBN:9798400709210
    DOI:10.1145/3626705
    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: 03 December 2023

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    Author Tags

    1. Automated Driving
    2. Explainable AI
    3. Human Factors
    4. Parking
    5. User Interfaces
    6. User Study

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    • Refereed limited

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    • German Federal Ministry of Education and Research (BMBF)

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    View all
    • (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)Agents preserving privacy on intelligent transportation systems according to EU lawArtificial Intelligence and Law10.1007/s10506-024-09391-0Online publication date: 12-Feb-2024

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