Vehicle Window HUD Optics Discrete Calculation Method
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Solution Overview
Problem
Current methods for assessing the suitability of vehicle windows as reflection surfaces for head-up displays (HUDs) are prone to errors due to surface reconstruction, which can affect the imaging quality and accuracy of beam path calculations.
Innovation Solution
A method that bypasses surface reconstruction by directly calculating HUD beam paths based on discrete measurement points on the vehicle pane, using a measurement grid defined by human resolution criteria, and determining local actual normal vectors and viewing rays to assess the pane's suitability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If surface reconstruction is used to capture the vehicle pane, then the entire surface can be examined, but additional error sources are generated that affect imaging quality assessment
Solution Approach 1:
The patent extracts only the necessary measurement points from the complete surface reconstruction, selecting discrete points that are sufficient for accurate beam path calculation without requiring the entire surface to be reconstructed. This eliminates the error sources introduced by reconstructing the complete surface while maintaining adequate measurement coverage.
Solution Approach 2:
The patent segments the vehicle pane surface into discrete measurement points arranged in a measurement grid, rather than treating the surface as a continuous reconstructed model. This segmentation approach allows direct calculation of beam paths at specific points without introducing reconstruction errors.
2Adaptability or versatility
If numerical simulations with reconstructed surfaces are carried out, then comprehensive optical assessment is possible, but the reconstruction process introduces errors relevant for imaging quality assessment
Solution Approach 1:
The patent extracts the essential measurement data (discrete measurement points with normal vectors) from the surface reconstruction process and uses these extracted points directly for beam path calculation, bypassing the need for complete surface reconstruction and the associated reconstruction errors.
Solution Approach 2:
Instead of using a reconstructed surface model that introduces errors, the patent creates a discrete copy of the actual measured surface points and their normal vectors, which accurately represents the real surface without the artifacts of mathematical reconstruction.
3Measurement precision
If the measurement grid is defined by human resolution criteria, then the discretization is optimized for perceived image quality, but the grid density must be carefully controlled to balance accuracy and computational efficiency
Solution Approach 1:
The patent changes the parameter of measurement point density based on human resolution criteria, optimizing the grid density to match the perceptual capabilities of the observer. This ensures that measurements are sufficient for accurate assessment without excessive computational complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces error sources associated with surface reconstruction, providing a more accurate assessment of the vehicle pane's suitability for HUD applications and improving the imaging quality by directly utilizing actual measurement data.
Implementation Method 1
a deflectometric capture of local actual normal vectors Ni = (N0, N1, N2 . . . N(n-1)) for a set of discrete measurement points Pi = (P0, P1, P2 . . . P(n-1)) on the actual vehicle pane (5) to be examined is carried out
Data Source
AI summary
A method for examining the suitability of a vehicle window for use in a head-up display device includes defining, in relation to human resolution capability, a measuring grid by specifying measuring point distances between discrete measuring points in an actual vehicle window surface to be used as a reflection surface for the head-up display device; acquiring, using deflectrometry, local actual normal vectors of this reflection surface for the specified discrete measuring grid; determining an accompanying local actual line of vision of the head-up display device for each acquired local actual normal vector; and evaluating the actual vehicle window according to a deviation of the determined local actual lines of vision from ideal target lines of vision of the head-up display device, which are each reflected at corresponding surface points of a predetermined ideal target vehicle window.