Personalized In-Car User Interfaces Using Machine Learning and Variable Fonts

Published by Kushtrim Hamzaj
July 10, 2025

As vehicles become more digitized, the demand for intelligent, adaptive in-car interfaces is growing. This use case proposes a personalized in-car interface that updates its visual elements, especially variable fonts, based on the driver’s identity. The project’s main goal is to enhance the personalization of modern cars’ ML-driven user interfaces by integrating variable font technology. The use case was also presented at the 9th International Conference on Design and Digital Communication.

Conclusion and Future Work

With the final implementation of the use case, it can be stated that the proposed synergy of variable fonts and machine learning can significantly improve the personalization of digital interfaces in a practical context. While initial feedback on the use case was positive, further research is required to evaluate the effectiveness of variable fonts in adaptive design environments. This includes techniques such as, usability testing, A/B testing, task performance analysis, think-aloud protocols, eye-tracking studies, semi-structured interviews and diary studies to gather insights about each case independently. These tests could further reveal user perceptions and contextual usage insights on how designers perceive each use case.

References:

Tarnowski, T., Haidenthaler, R., Pohl, M., & Pross, A. (2022). Mercedes-Benz MBUX
Hyperscreen Merges Technologies into Digital Dashboard Application. Informa-
tion Display, 38 (3), 12–17. doi: 10.1002/msid.1300

Geyer, J., Kassahun, Y., Mahmudi, M., Ricou, X., Durgesh, R., Chung, A. S., . . .
Schuberth, P. (2020). A2D2: Audi Autonomous Driving Dataset. arXiv. doi:
10.48550/arXiv.2004.06320

AITYDE – Artificial Intelligence in Typography and Design
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