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An Adaptive and Personalized In-Vehicle Human-Machine-Interface for an Improved User Experience

Author:

Guillermo ReyesAuthors Info & Claims

IUI '20 Companion: Companion Proceedings of the 25th International Conference on Intelligent User Interfaces

Pages 35 - 36

https://doi.org/10.1145/3379336.3381882

Published: 17 March 2020 Publication History

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Abstract

Human Machine Interfaces (HMIs) enable the communication between humans and machines. In the automotive domain, all in-vehicle systems used to be independent. Today they are more and more interconnected and interdependent. However, they still don't act in unison to help drivers achieve their individual goals. More specifically, even though, some current HMIs provide a certain degree of personalization, they don't adapt dynamically to the situation and don't learn driver-specific nuances in order to improve the driver's user experience.

References

[1]

Angelos Amditis, Luisa Andreone, Aris Polychronopoulos, and Johan Engström. 2005. Design and development of an adaptive integrated driver-vehicle interface: overview of the AIDE project. IFAC Proceedings Volumes 38, 1 (2005), 103--108.

Crossref

Google Scholar

[2]

Alexander Gepperth and Barbara Hammer. 2016. Incremental learning algorithms and applications. In European Symposium on Artificial Neural Networks (ESANN).

Google Scholar

[3]

Farzan Yazdi Motlagh and Peter Göhner. 2014. Adaptive Human-Machine-Interface of Automation Systems. In Doctoral Conference on Computing, Electrical and Industrial Systems. Springer, 175--182.

Google Scholar

[4]

Mahasivam Nivethika, Ilanthalaisingam Vithiya, Sebastiankularatnam Anntharshika, and Sampath Deegalla. 2013. Personalized and adaptive user interface framework for mobile application. In 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 1913--1918.

Crossref

Google Scholar

Cited By

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Patel ALjepava N(2024)How Will Autonomous Vehicles Increase Ease of Life?Human-Centric Smart Computing10.1007/978-981-99-7711-6_51(655-665)Online publication date: 18-Feb-2024
https://doi.org/10.1007/978-981-99-7711-6_51
Khorsandi PJones LDavoodnia VLampen TConrad AEtemad ANabil S(2023)FabriCar: Enriching the User Experience of In-Car Media Interactions with Ubiquitous Vehicle Interiors using E-textile SensorsProceedings of the 2023 ACM Designing Interactive Systems Conference10.1145/3563657.3595988(1438-1456)Online publication date: 10-Jul-2023
https://dl.acm.org/doi/10.1145/3563657.3595988
Gomaa AAlles AMeiser ERupp LMolz MReyes GJi YJeon M(2022)What’s on your mind? A Mental and Perceptual Load Estimation Framework towards Adaptive In-vehicle Interaction while DrivingProceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3543174.3546840(215-225)Online publication date: 17-Sep-2022
https://dl.acm.org/doi/10.1145/3543174.3546840
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An Adaptive and Personalized In-Vehicle Human-Machine-Interface for an Improved User Experience

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Published In

IUI '20 Companion: Companion Proceedings of the 25th International Conference on Intelligent User Interfaces

March 2020

153 pages

ISBN:9781450375139

DOI:10.1145/3379336

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 March 2020

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Extended-abstract
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Refereed limited

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IUI '20

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SIGAI
SIGCHI

IUI '20: 25th International Conference on Intelligent User Interfaces

March 17 - 20, 2020

Cagliari, Italy

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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IUI '25

Sponsor:
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30th International Conference on Intelligent User Interfaces

March 24 - 27, 2025

Cagliari , Italy

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Cited By

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Patel ALjepava N(2024)How Will Autonomous Vehicles Increase Ease of Life?Human-Centric Smart Computing10.1007/978-981-99-7711-6_51(655-665)Online publication date: 18-Feb-2024
https://doi.org/10.1007/978-981-99-7711-6_51
Khorsandi PJones LDavoodnia VLampen TConrad AEtemad ANabil S(2023)FabriCar: Enriching the User Experience of In-Car Media Interactions with Ubiquitous Vehicle Interiors using E-textile SensorsProceedings of the 2023 ACM Designing Interactive Systems Conference10.1145/3563657.3595988(1438-1456)Online publication date: 10-Jul-2023
https://dl.acm.org/doi/10.1145/3563657.3595988
Gomaa AAlles AMeiser ERupp LMolz MReyes GJi YJeon M(2022)What’s on your mind? A Mental and Perceptual Load Estimation Framework towards Adaptive In-vehicle Interaction while DrivingProceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3543174.3546840(215-225)Online publication date: 17-Sep-2022
https://dl.acm.org/doi/10.1145/3543174.3546840
Gopinath DDeCastro JRosman GSumner EMorgan AHakimi SStent S(2022)HMIway-env: A Framework for Simulating Behaviors and Preferences to Support Human-AI Teaming in Driving2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW56347.2022.00480(4341-4349)Online publication date: Jun-2022
https://doi.org/10.1109/CVPRW56347.2022.00480
Reguera-Bakhache DGaritano IUribeetxeberria RCernuda C(2021)An Industrial HMI Temporal Adaptation based on Operator-Machine Interaction Sequence Similarity2021 22nd IEEE International Conference on Industrial Technology (ICIT)10.1109/ICIT46573.2021.9453580(1021-1026)Online publication date: 10-Mar-2021
https://doi.org/10.1109/ICIT46573.2021.9453580
Zhu RZhang ZCai Z(2021)Enabling Pointing Assistance in Adaptive Interfaces Using Mouse Pointing Intention Prediction2021 China Automation Congress (CAC)10.1109/CAC53003.2021.9727601(4808-4813)Online publication date: 22-Oct-2021
https://doi.org/10.1109/CAC53003.2021.9727601

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