Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/3473682.3477435acmconferencesArticle/Chapter ViewAbstractPublication PagesautomotiveuiConference Proceedingsconference-collections
extended-abstract

To Customize or Not to Customize - Is That the Question?

Published: 22 September 2021 Publication History

Abstract

As automated vehicles become more prevalent, designing interfaces that best fit all users, especially ones in minority populations, is a pressing but difficult goal. System-driven adaptation is a commonly used approach as it is easier and created by experts but, has innate flaws. Customization, on the other hand, allows users to consciously alter the interface to appear and operate in a manner most suited to their needs and wants. However, various components of the interface have different constraints, capabilities, and requirements with the amount of customization appropriate. In this workshop, we will dissect an expansive taxonomy for customization and develop a series of levels in order to get the full benefits from customization, which in turn can help engineers and designers in creating more user-centered systems.

References

[1]
Sasha Barab and Kurt Squire. 2004. Design-based research: Putting a stake in the ground. The journal of the learning sciences 13, 1 (2004), 1–14.
[2]
Zoe M Becerra, Nadia Fereydooni, Andrew L Kun, Angus McKerral, Andreas Riener, Clemens Schartmüller, Bruce N Walker, and Philipp Wintersberger. 2021. Interactive Workshops in a Pandemic: The Real Benefits of Virtual Spaces. IEEE Pervasive Computing 20, 1 (2021), 35–39.
[3]
Jen Cardello and Jakob Nielsen. [n.d.]. Customization Features Done Correctly for the Right Reasons 46 Design Guidelines To Improve Web-based Interface and Product Customization HOW TO SHARE. Technical Report. http://www.nngroup.com/reports/customization
[4]
Jenna E Cotter, Andrew Atchley, Barbara C Banz, and Nathan L Tenhundfeld. 2021. Is my User Impaired? Designing Adaptive Automation that Monitors the User’s State. (2021).
[5]
Paul Dourish and Scott D Mainwaring. 2012. Ubicomp’s colonial impulse. In Proceedings of the 2012 ACM conference on ubiquitous computing. 133–142.
[6]
Frédéric Fonsalas. 2019. Holistic HMI Architecture for Adaptive and Predictive Car Interiors. In Electronic Components and Systems for Automotive Applications. Springer, 217–227.
[7]
Krzysztof Z Gajos and Krysta Chauncey. 2017. The influence of personality traits and cognitive load on the use of adaptive user interfaces. In Proceedings of the 22nd International Conference on Intelligent User Interfaces. 301–306.
[8]
Connor C Gramazio, David H Laidlaw, and Karen B Schloss. 2016. Colorgorical: Creating discriminable and preferable color palettes for information visualization. IEEE transactions on visualization and computer graphics 23, 1(2016), 521–530.
[9]
Donna Haraway. 1988. Situated knowledges: The science question in feminism and the privilege of partial perspective. Feminist studies 14, 3 (1988), 575–599.
[10]
SAE International. 2018. SAE MOBILUS. saemobilus.sae.org/content/J3016_201806
[11]
Anthony Jameson. 2007. Adaptive interfaces and agents. In The human-computer interaction handbook. CRC Press, 459–484.
[12]
Wendy E Mackay. 1990. Patterns of sharing customizable software. In Proceedings of the 1990 ACM conference on Computer-supported cooperative work. 209–221.
[13]
Brent Daniel Mittelstadt, Patrick Allo, Mariarosaria Taddeo, Sandra Wachter, and Luciano Floridi. 2016. The ethics of algorithms: Mapping the debate. Big Data & Society 3, 2 (2016), 2053951716679679.
[14]
Carson Reynolds. 1999. Generalization in User Interface Design.
[15]
Andreas Riener, Myounghoon Jeon, and Ignacio Alvarez (Eds.). 2022. User Experience Design in the Era of Automated Driving | Andreas Riener | Springer. Springer. https://www.springer.com/gp/book/9783030777258
[16]
SM Sarala, DH Sharath Yadav, and Asadullah Ansari. 2018. Emotionally adaptive driver voice alert system for advanced driver assistance system (adas) applications. In 2018 International Conference on Smart Systems and Inventive Technology (ICSSIT). IEEE, 509–512.
[17]
Ben Shneiderman. 1994. Dynamic queries for visual information seeking. IEEE software 11, 6 (1994), 70–77.
[18]
Kate Starbird, Ahmer Arif, and Tom Wilson. 2019. Disinformation as collaborative work: Surfacing the participatory nature of strategic information operations. Proceedings of the ACM on Human-Computer Interaction 3, CSCW(2019), 1–26.
[19]
S Shyam Sundar and Sampada S Marathe. 2010. Personalization versus customization: The importance of agency, privacy, and power usage. Human Communication Research 36, 3 (2010), 298–322.
[20]
Gabriel Urzaiz, Sergio F Ochoa, Jose Bravo, Liming Luke Chen, and Jonice Oliveira. 2013. Ubiquitous Computing and Ambient Intelligence: Context-awareness and Context-driven Interaction: 7th International Conference, UCAmI 2013, Carrillo, Costa Rica, December 2-6, 2013, Proceedings. Vol. 8276. Springer.
[21]
Jenny Van Doorn and Janny C Hoekstra. 2013. Customization of online advertising: The role of intrusiveness. Marketing Letters 24, 4 (2013), 339–351.
[22]
Daniel Weld, Corin Anderson, Pedro Domingos, Oren Etzioni, Krzysztof Z Gajos, Tessa Lau, and Steve Wolfman. 2003. Automatically personalizing user interfaces. (2003).
[23]
Philipp Wintersberger, Hannah Nicklas, Thomas Martlbauer, Stephan Hammer, and Andreas Riener. 2020. Explainable Automation: Personalized and Adaptive UIs to Foster Trust and Understanding of Driving Automation Systems. In 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. 252–261.

Cited By

View all
  • (2023)Analyzing Consumer Experience of Autonomous Vehicles Using Topic ModelingHCI International 2023 Posters10.1007/978-3-031-36001-5_8(61-67)Online publication date: 9-Jul-2023

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
AutomotiveUI '21 Adjunct: 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
September 2021
234 pages
ISBN:9781450386418
DOI:10.1145/3473682
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.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 September 2021

Check for updates

Author Tags

  1. automated vehicles
  2. customization
  3. standardization
  4. user interface

Qualifiers

  • Extended-abstract
  • Research
  • Refereed limited

Conference

AutomotiveUI '21
Sponsor:

Acceptance Rates

Overall Acceptance Rate 248 of 566 submissions, 44%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)20
  • Downloads (Last 6 weeks)3
Reflects downloads up to 18 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2023)Analyzing Consumer Experience of Autonomous Vehicles Using Topic ModelingHCI International 2023 Posters10.1007/978-3-031-36001-5_8(61-67)Online publication date: 9-Jul-2023

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media