Computational Models for In-Vehicle User Interface Design: A Systematic Literature Review

In-Vehicle Haptic, Audio & Multimodal FeedbackUser Research Methods (Interviews, Surveys, Observation)Prototyping & User TestingAutomotive Manufacturers & Vehicle DesignersUI/UX Designers

In this review, we analyze the current state of the art of computational models for in-vehicle User Interface (UI) design. Driver distraction, often caused by drivers performing Non Driving Related Tasks (NDRTs), is a major contributor to vehicle crashes. Accordingly, in-vehicle UI s must be evaluated for their distraction potential. Computational models are a promising solution to automate this evaluation, but are not yet widely used. limit their real-world impact. We systematically review the existing literature on computational models for NDRTs to analyze why current approaches have not yet found their way into practice. We found that while many models are intended for UI evaluation, they focus on small and isolated phenomena that are disconnected from the needs of automotive UI designers. In addition, very few approaches make predictions detailed enough to inform current design processes. Our analysis of the state of the art, the identified research gaps, and the formulated research potentials can guide researchers and practitioners towards computational models that improve the automotive UI design process.

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https://hci.top/en/papers/auto_ui/168464/2024

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Source
AutoUI
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Year
2024
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Authors
5 authors
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Subtopics
In-Vehicle Haptic, Audio & Multimodal Feedback, User Research Methods (Interviews, Surveys, Observation), Prototyping & User Testing
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Professions
Automotive Manufacturers & Vehicle Designers, UI/UX Designers
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Abstract only
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