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Driving Hotzenplotz: A Hybrid Interface for Vehicle Control Aiming to Maximize Pleasure in Highway Driving

Published: 24 September 2017 Publication History

Abstract

A prerequisite to foster proliferation of automated driving is common system acceptance. However, different users groups (novice, enthusiasts) decline automation, which could be, in turn, problematic for a successful market launch. We see a feasible solution in the combination of the advantages of manual (autonomy) and automated (increased safety) driving. Hence, we've developed the Hotzenplotz interface, combining possibility-driven design with psychological user needs. A simulator study (N=30) was carried-out to assess user experience with subjective criteria (Need Scale, PANAS/-X, HEMA, AttrakDiff) and quantitative measures (driving behavior, HR/HRV) in different conditions. Our results confirm that pure AD is significantly less able to satisfy user needs compared to manual driving and make people feeling bored/out of control. In contrast, the Hotzenplotz interface has proven to reduce the negative effects of AD. Our implication is that drivers should be provided with different control options to secure acceptance and avoid deskilling.

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      cover image ACM Conferences
      AutomotiveUI '17: Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
      September 2017
      317 pages
      ISBN:9781450351508
      DOI:10.1145/3122986
      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 ACM 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: 24 September 2017

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      Author Tags

      1. Automated Driving
      2. Joy of Driving
      3. Need Scale
      4. Playful Interaction
      5. User Acceptance
      6. User Experience
      7. User Studies

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      AutomotiveUI '17 Paper Acceptance Rate 29 of 85 submissions, 34%;
      Overall Acceptance Rate 248 of 566 submissions, 44%

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      Cited By

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      • (2024)Improving Driver Engagement with Level 2 Automated Systems: The Impact of Fully Shared Longitudinal ControlProceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3640792.3675708(43-52)Online publication date: 22-Sep-2024
      • (2024)Supporting Task Switching with Reinforcement LearningProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642063(1-18)Online publication date: 11-May-2024
      • (2023)Evaluation of User Interfaces for Cooperation Between Driver and Automated Driving System*2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC53992.2023.10394584(2913-2920)Online publication date: 1-Oct-2023
      • (2023)Unequally Yoked [Skilled]: Transformative Views on Human-Automation Skilfulness2023 International Conference on Electrical, Computer and Energy Technologies (ICECET)10.1109/ICECET58911.2023.10389238(1-8)Online publication date: 16-Nov-2023
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      • (2022)Two Heads Are Better Than One: A Dimension Space for Unifying Human and Artificial Intelligence in Shared ControlProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517610(1-21)Online publication date: 29-Apr-2022
      • (2022)Designing for Continuous Interaction with Artificial Intelligence SystemsExtended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491101.3516409(1-4)Online publication date: 27-Apr-2022
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