Work in Progress

In-Vehicle Interface Adaptation to Environment-Induced Cognitive Workload

Authors:

Alexandra Alles,

Guillermo ReyesAuthors Info & Claims

AutomotiveUI '22: Adjunct Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

Pages 83 - 86

https://doi.org/10.1145/3544999.3552533

Published: 17 September 2022 Publication History

Abstract

Many car accidents are caused by human distractions, including cognitive distractions. In-vehicle human-machine interfaces (HMIs) have evolved throughout the years, providing more and more functions. Interaction with the HMIs can, however, also lead to further distractions and, as a consequence, accidents. To tackle this problem, we propose using adaptive HMIs that change according to the mental workload of the driver. In this work, we present the current status as well as preliminary results of a user study using naturalistic secondary tasks while driving (i.e., the primary task) that attempt to understand the effects of one such interface.

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Cited By

Tan ZWang JDai NZhang R(2025)Qualitative Research of the Multimodal In-Vehicle Interaction Systems Latency PerceptionProceedings of the ACM on Human-Computer Interaction10.1145/37012049:1(1-25)Online publication date: 10-Jan-2025
https://dl.acm.org/doi/10.1145/3701204
Sriranga ALu QBirrell S(2023)A Systematic Review of In-Vehicle Physiological Indices and Sensor Technology for Driver Mental Workload MonitoringSensors10.3390/s2304221423:4(2214)Online publication date: 16-Feb-2023
https://doi.org/10.3390/s23042214
Gomaa AFeld M(2023)Towards Adaptive User-centered Neuro-symbolic Learning for Multimodal Interaction with Autonomous SystemsProceedings of the 25th International Conference on Multimodal Interaction10.1145/3577190.3616121(689-694)Online publication date: 9-Oct-2023
https://dl.acm.org/doi/10.1145/3577190.3616121

Index Terms

In-Vehicle Interface Adaptation to Environment-Induced Cognitive Workload
1. Applied computing
  1. Law, social and behavioral sciences
    1. Psychology
2. Human-centered computing
  1. Interaction design
    1. Interaction design process and methods
      1. User centered design

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Published In

cover image ACM Conferences

AutomotiveUI '22: Adjunct Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 2022

225 pages

ISBN:9781450394284

DOI:10.1145/3544999

General Chairs:
Yong Gu Ji
Yonsei University, South Korea
,
Myounghoon Jeon
Virginia Tech, USA

Copyright © 2022 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 September 2022

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Work in progress
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Refereed limited

Funding Sources

Bundesministerium für Bildung und Forschung

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AutomotiveUI '22

Sponsor:

SIGCHI

AutomotiveUI '22: 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 17 - 20, 2022

Seoul, Republic of Korea

Acceptance Rates

Overall Acceptance Rate 248 of 566 submissions, 44%

Upcoming Conference

AutomotiveUI '25

Sponsor:
sigchi

17th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 21 - 25, 2025

Brisbane , QLD , Australia

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Cited By

Tan ZWang JDai NZhang R(2025)Qualitative Research of the Multimodal In-Vehicle Interaction Systems Latency PerceptionProceedings of the ACM on Human-Computer Interaction10.1145/37012049:1(1-25)Online publication date: 10-Jan-2025
https://dl.acm.org/doi/10.1145/3701204
Sriranga ALu QBirrell S(2023)A Systematic Review of In-Vehicle Physiological Indices and Sensor Technology for Driver Mental Workload MonitoringSensors10.3390/s2304221423:4(2214)Online publication date: 16-Feb-2023
https://doi.org/10.3390/s23042214
Gomaa AFeld M(2023)Towards Adaptive User-centered Neuro-symbolic Learning for Multimodal Interaction with Autonomous SystemsProceedings of the 25th International Conference on Multimodal Interaction10.1145/3577190.3616121(689-694)Online publication date: 9-Oct-2023
https://dl.acm.org/doi/10.1145/3577190.3616121

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