Adaptive Head-Up Display Eyebox Alignment for AR Image Clarity
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Solution Overview
Problem
Existing augmented-reality head-up displays (AR HUDs) in vehicles project images onto a single virtual image plane, leading to misalignment and low quality for different vehicle occupants due to varying heights, seat positions, vision acuity, and weather conditions, resulting in unsuitable appearance and unclarity of the AR images.
Innovation Solution
A vehicle computer adjusts the virtual image plane based on occupant eyebox data, using sensors and machine learning to perform adjustments along multiple axes and account for individual occupant characteristics and weather conditions, ensuring the image is optimally projected for each occupant.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single virtual image plane is used for all occupants, then the device complexity is reduced, but the image alignment and quality deteriorate for different occupants
Solution Approach 1:
The patent implements dynamic adjustment of the virtual image plane parameters based on detected occupant characteristics. The system transitions from a static single plane configuration to a dynamic multi-plane configuration, adjusting the virtual image plane position and orientation in real-time according to sensor data about occupant eyebox location, thereby maintaining high image quality without requiring complex hardware for each occupant
Solution Approach 2:
The system changes the parameters of the virtual image plane (position, orientation, distance) based on detected occupant characteristics such as eyebox location, height, and seat position. By adjusting these parameters dynamically, the system adapts the projection to match each occupant's viewing geometry, resolving the contradiction between simple device configuration and precise image alignment
2Device complexity
If the virtual image plane is fixed, then the device complexity is reduced, but the adaptability to different occupants deteriorates
Solution Approach 1:
The system employs feedback from sensors that detect occupant characteristics (eyebox location, seat position, height) to dynamically adjust the virtual image plane parameters. This closed-loop feedback mechanism enables the fixed projection hardware to adapt to different occupants by modifying the virtual image plane configuration based on real-time sensor data, achieving high adaptability without complex mechanical adjustment mechanisms
Solution Approach 2:
The system performs self-adjustment by automatically detecting occupant characteristics and modifying its own virtual image plane parameters without requiring manual intervention or complex external control mechanisms. The projection system serves itself by adapting to each occupant's unique viewing geometry through automated sensor-based parameter adjustment
Data Source
AI summary
A virtual image plane is determined with respect to a reference eyebox. A virtual image projected into the virtual image plane is visible in the reference eyebox. An occupant eyebox is determined from sensor data. A first adjustment is performed of the virtual image plane based on the occupant eyebox so that the virtual image projected into the virtual image plane is visible in the occupant eyebox.