Vehicle Display Configuration via Eye Tracking Analysis
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Solution Overview
Problem
Users face difficulties in locating important buttons or information on vehicle display configurations due to aesthetically pleasing but poorly optimized layouts, which can be influenced by their eyesight and experience.
Innovation Solution
A vehicle display configuration system employing an eye tracker and electronic controller to analyze user eye movement and sequentially display sets of images for comparison, allowing the system to designate a preferred display configuration based on eye tracking data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Shape
If the display configuration is optimized for aesthetic appeal, then the visual appearance is improved, but the findability of important buttons and information deteriorates
Solution Approach 1:
The system performs preliminary eye tracking analysis and user preference assessment before finalizing the display configuration. By analyzing eye movement patterns during the setup phase and comparing multiple configuration options, the system pre-determines the optimal layout that balances aesthetics with findability, rather than relying on post-deployment adjustments
Solution Approach 2:
The system incorporates real-time feedback loops where eye tracking data continuously monitors user interaction with the display. This feedback is used to iteratively refine the display configuration, adjusting element positions and sizes based on actual user gaze patterns and interaction difficulty, thereby resolving the conflict between aesthetic design and operational ease
2Ease of manufacture
If the button size and information display are standardized, then the manufacturing and implementation is simplified, but the adaptability to different users' eyesight and experience deteriorates
Solution Approach 1:
The system transforms static, standardized display configurations into dynamic, adaptive layouts. By incorporating eye tracking technology and machine learning algorithms, the display automatically adjusts button sizes, information density, and element positioning based on individual user characteristics such as eyesight acuity and interaction experience, maintaining ease of implementation through automated adaptation
Solution Approach 2:
The system systematically varies display parameters including font size, button dimensions, spacing, and information hierarchy based on measured user characteristics. Eye tracking metrics and user feedback serve as inputs that trigger parameter adjustments, enabling the same hardware platform to deliver customized display configurations tailored to different users' visual capabilities and experience levels
3Ease of operation
If manual user selection of display configuration is used, then the user preference is captured, but the time required for configuration and adjustment deteriorates
Solution Approach 1:
The system enables self-service configuration by automatically capturing user preferences through non-intrusive eye tracking analysis. Users naturally interact with display options during normal viewing, and the system autonomously analyzes gaze patterns, fixation durations, and scanning behaviors to infer preferences, eliminating the need for time-consuming manual surveys or iterative adjustments while still capturing genuine user preferences
Data Source
AI summary
A vehicle display configuration system and method employs a display, an eye tracker and a controller. The eye tracker is configured to track eye movement of a user viewing the display. The controller is configured to control the display to sequentially display sets of a plurality of images for comparison and selection by the user, to receive selection information representing a respective selected image from each of the sets being displayed on the display as selected by the user, to analyze eye tracker eye movement information received from the eye tracker representing eye movement of the user while the user is viewing each of the sets being displayed on the display, and to designate a vehicle display image based on the selection information and a result of the analysis of the eye movement information.