A method for detecting the polarization matching between HUD virtual image and real environment
By detecting the polarization matching between the virtual image in the HUD and the real ambient light, and using a polarization matching degree evaluation model to identify and locate polarization conflicts, the image quality problem caused by the polarization mismatch between the virtual image and the real ambient light is solved, thereby improving driving safety and user experience.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SUZHOU METROLOGY & TESTING INSTITUTE CO LTD
- Filing Date
- 2026-04-22
- Publication Date
- 2026-06-30
AI Technical Summary
Existing technologies cannot effectively detect the polarization matching between HUD virtual images and real ambient light, leading to problems such as image dimming, disappearance, glare, and visual fatigue.
By collecting polarization parameters of HUD virtual images and real ambient light at multiple preset test points, a polarization matching degree evaluation model is used to calculate the matching degree score, identify and locate polarization conflicts, and trigger audible and visual alarms.
During the research and development phase, polarization design defects can be identified and corrected to prevent image darkening, disappearance, and glare, thereby improving driving safety and user experience.
Smart Images
Figure CN122089726B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of automotive head-up display system testing technology, and in particular to a method for detecting the polarization matching between the HUD virtual image and the real environment. Background Technology
[0002] Head-up display (HUD) systems are widely used in modern automobiles to project key information such as vehicle speed and navigation onto the windshield as virtual images, allowing drivers to obtain driving information without looking down, thus improving driving safety. Current HUD polarization-related technologies mainly focus on polarizer fabrication, virtual image rendering algorithm optimization, and real-scene fusion display optimization. All of these technologies aim to improve the optical performance or display effect of the HUD itself.
[0003] In the process of developing the existing technology, the inventors discovered that:
[0004] In practical applications, drivers often wear polarized sunglasses to reduce glare. When the polarization direction of the virtual image in a HUD does not match that of the polarized sunglasses, the virtual image may become darker, partially missing, or even disappear completely, severely affecting information acquisition. Furthermore, augmented reality head-up displays (AR-HUDs) require a natural visual integration between the virtual image and the real ambient light. If there is a significant difference in their polarization characteristics, it can easily lead to glare, visual fatigue, and other problems, reducing user experience and driving safety.
[0005] Therefore, this application provides a method for detecting the polarization matching between the virtual image of a HUD and the real environment to solve the technical problems of image darkening, disappearance, glare, and visual fatigue caused by the inability to detect the polarization matching between the virtual image and the ambient light in the prior art. Summary of the Invention
[0006] This application provides a method for detecting the polarization matching between the virtual image of a HUD and the real environment to solve the technical problems of image darkening, disappearance, glare, and visual fatigue caused by the inability to detect the polarization matching between the virtual image and the ambient light in the prior art.
[0007] Specifically, a method for detecting the polarization matching between a HUD virtual image and the real environment includes the following steps:
[0008] When projecting a virtual image into the HUD, a set of virtual polarization parameters for multiple preset test points in the HUD virtual image is collected.
[0009] Simultaneously acquire the real ambient light polarization parameter set in the directions corresponding to multiple preset test points;
[0010] The virtual polarization parameter set and the real environment polarization parameter set are input into a preset polarization matching degree evaluation model to calculate the matching degree score for each preset test point;
[0011] When at least one of the matching scores of each preset test point is lower than the preset threshold, it is determined that there is a polarization conflict at that test point, and the polarization conflict type and conflict location information are output.
[0012] Furthermore, the virtual polarization parameter set and the real environment polarization parameter set each include at least one of the following polarization parameters: polarization state, polarization intensity, degree of polarization, polarization azimuth angle, and polarization uniformity.
[0013] Furthermore, the multiple preset test points are multiple feature points in the HUD virtual image screen, and the feature points include at least the center point of the screen, the four corner points, and the midpoints of the four sides.
[0014] Furthermore, the polarization matching degree evaluation model includes at least:
[0015] The first evaluation score is determined by evaluating the consistency of polarization direction;
[0016] The second evaluation score is determined by evaluating polarization intensity compatibility.
[0017] Based on the first evaluation score and the second evaluation score, a matching score is calculated;
[0018] The matching score is obtained by weighted summation of the first evaluation score and the second evaluation score, respectively.
[0019] Furthermore, the polarization matching degree evaluation model also includes polarization uniformity evaluation.
[0020] Furthermore, the polarization direction consistency evaluation is used to characterize the deviation between the polarization azimuth angle of the virtual image and the polarization azimuth angle of the real ambient light at the same test point, and the polarization intensity adaptability evaluation is used to characterize the ratio of the polarization intensity of the virtual image to the polarization intensity of the real ambient light.
[0021] Furthermore, the polarization conflict types include at least one of the following: polarization direction deviation exceeding a preset direction threshold, polarization intensity ratio exceeding a preset intensity threshold, and local polarization uniformity deviation exceeding a preset uniformity threshold.
[0022] Furthermore, the conflict location information is output in the form of coordinates in a virtual image, or in the form of a region location on the windshield of the HUD under test.
[0023] Furthermore, an audible and visual alarm is triggered when a polarization conflict occurs.
[0024] Furthermore, the acquisition frequency of the virtual polarization parameter set and the real environment polarization parameter set is adjustable, with an adjustment range of 1Hz to 100Hz.
[0025] Compared with the prior art, the present invention has the following beneficial effects:
[0026] This invention provides a novel concept: by simultaneously acquiring the polarization parameter sets of the HUD virtual image and the real ambient light in the corresponding directions at the same preset test point, and introducing a polarization matching degree evaluation model, it evaluates the polarization direction consistency and polarization intensity adaptability. A matching degree score is calculated through weighted summation and compared with a threshold to identify conflict types such as polarization direction deviation, intensity ratio mismatch, and uniformity degradation, and to pinpoint the specific location of the conflict in the virtual image or on the windshield. This allows HUD products to identify and correct polarization design defects during the R&D stage, preventing quality issues such as image dimming and disappearance from entering the market. It ensures the visibility of the virtual image under polarized sunglasses and the visual consistency between the virtual image and the real ambient light, thereby avoiding image dimming, disappearance, glare, and visual fatigue, significantly improving driving safety and user experience. Attached Figure Description
[0027] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:
[0028] Figure 1 This is a flowchart illustrating a method for detecting the polarization matching between a HUD virtual image and the real environment, provided in an embodiment of this application.
[0029] Figure 2 This is a schematic diagram of the detection device for implementing the method provided in an embodiment of this application.
[0030] Figure label:
[0031] Optical platform-1; Position adjustment component-2; Polarization detection unit-3; Data fusion unit-4; Display and feedback module-5; HUD-6; Windshield-7; Virtual image-8; Real ambient light-9; Detailed Implementation
[0032] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0033] This embodiment provides a method for detecting the polarization matching between the virtual image of a HUD and the real environment. This method can be applied to the laboratory testing environment during the R&D stage of automotive HUD products, and also to the factory testing stage on the production line. The following is a combination of... Figure 1 The flowchart shown below provides a detailed explanation of the method in this embodiment.
[0034] A method for detecting the polarization matching between a HUD virtual image and the real environment, characterized by comprising the following steps:
[0035] S101: When projecting a virtual image into the HUD, collect the virtual polarization parameter set of multiple preset test points in the HUD virtual image screen.
[0036] When projecting a virtual image into a HUD, it is first necessary to determine multiple preset test points within the HUD virtual image. In this embodiment, these preset test points are nine feature points within the HUD virtual image, including the center point, four corner points, and the midpoints of the four sides. These feature points can comprehensively cover the key areas of the virtual image, effectively evaluating the polarization uniformity at different locations on the screen.
[0037] For each preset test point, a virtual polarization parameter set is collected. The virtual polarization parameter set includes at least one of polarization state, polarization intensity, degree of polarization, polarization azimuth angle, and polarization uniformity. In this embodiment, it is preferable to collect all of the above parameters simultaneously to obtain complete polarization information. The acquisition frequency can be adjusted according to actual detection needs, with a typical adjustment range of 1Hz to 100Hz. In this embodiment, it is set to 60Hz to capture the dynamic changes in polarization during the HUD refresh process.
[0038] S102: Synchronously acquire the real ambient light polarization parameter set in the directions corresponding to the multiple preset test points.
[0039] While acquiring the virtual polarization parameter set, the real ambient light polarization parameter set in the corresponding directions of the multiple preset test points is simultaneously acquired. Here, "corresponding direction" means: for a certain test point in the virtual image, the real ambient light polarization information in the real world direction corresponding to that point is acquired.
[0040] The collected real-world polarization parameter set and the virtual polarization parameter set contain parameters of the same type, including at least one of polarization state, polarization intensity, degree of polarization, polarization azimuth angle, and polarization uniformity, for comparison item by item. To ensure the accuracy of the matching degree evaluation, the acquisition of virtual polarization parameters and real-world optical polarization parameters must be performed synchronously under the control of the same clock signal to ensure consistent acquisition timing.
[0041] S103: Input the virtual polarization parameter set and the real environment polarization parameter set into the preset polarization matching degree evaluation model, and calculate the matching degree score for each preset test point.
[0042] Furthermore, the polarization matching degree evaluation model includes at least: determining a first evaluation score through polarization direction consistency evaluation; determining a second evaluation score through polarization intensity adaptability evaluation; calculating a matching degree score based on the first evaluation score and the second evaluation score; the matching degree score is obtained by weighted summation of the first evaluation score and the second evaluation score respectively.
[0043] Furthermore, the polarization direction consistency evaluation is used to characterize the deviation between the polarization azimuth angle of the virtual image and the polarization azimuth angle of the real ambient light at the same test point. The smaller the deviation, the higher the first evaluation score. For example, when the deviation is 0°, the first evaluation score is 1; when the deviation is 90°, the first evaluation score is 0; intermediate values are calculated using linear interpolation. The polarization intensity adaptability evaluation is used to characterize the ratio of the polarization intensity of the virtual image to the polarization intensity of the real ambient light. The closer this ratio is to 1, the higher the second evaluation score. For example, when the ratio is 1, the second evaluation score is 1; when the ratio is greater than 2 or less than 0.5, the second evaluation score is 0; intermediate values are calculated using logarithmic interpolation.
[0044] Furthermore, the polarization matching evaluation model also includes polarization uniformity evaluation. Polarization uniformity evaluation characterizes the degree of deviation between the polarization parameters of each preset test point and the overall average level of the image. The specific calculation method is as follows: First, calculate the average value of the same polarization parameter (such as polarization degree or polarization azimuth angle) at all preset test points; then, for each test point, calculate the deviation between the parameter at that point and the average value; finally, determine the third evaluation score for that test point based on this deviation. The smaller the deviation, the higher the third evaluation score. When the parameter at a certain test point is consistent with the overall level of the image, it indicates that the polarization uniformity at that point is good; conversely, it indicates that there is localized uniformity degradation at that point.
[0045] Taking polarization degree as an example, let the average polarization degree of all test points be P_avg, and the polarization degree of a certain test point be P_i. Then the deviation ΔP = |P_i - P_avg|, and the third evaluation score = 1 - ΔP (when ΔP ≤ 1) or 0 (when ΔP > 1). In this way, each test point obtains an independent third evaluation score, which reflects the uniformity of that point in the overall image.
[0046] Specifically, the formula for calculating the match score is as follows:
[0047] Match score = α × first evaluation score + β × second evaluation score + γ × third evaluation score;
[0048] In this model, α, β, and γ are weighting coefficients. The first evaluation score is calculated based on the deviation between the polarization azimuth angle of the virtual image at the test point and the polarization azimuth angle of the real ambient light. The second evaluation score is calculated based on the ratio of the polarization intensity of the virtual image at the test point to the polarization intensity of the real ambient light. The third evaluation score is calculated based on the deviation of the polarization parameter of the test point from the average value of all test points. In this embodiment, α, β, and γ are set to 0.5, 0.3, and 0.2, respectively, to highlight the importance of polarization direction consistency. The data fusion unit calculates the matching degree score for each of the nine test points, resulting in nine score values.
[0049] S104: When at least one of the matching scores of each preset test point is lower than the preset threshold, it is determined that there is a polarization conflict at the test point, and the polarization conflict type and conflict location information are output.
[0050] The matching score of each test point is compared with a preset threshold. When the matching score of any test point is lower than the preset threshold, it is determined that the test point has a polarization conflict. In a preferred embodiment provided in this application, the preset threshold is set to 0.6. When the matching score of a test point is lower than the preset threshold, it is considered that the test point has a polarization conflict.
[0051] Specifically, polarization conflict types include at least one of the following: polarization direction deviation exceeding a preset direction threshold, polarization intensity ratio exceeding a preset intensity threshold, and local polarization uniformity deviation exceeding a preset uniformity threshold.
[0052] Specifically, when the polarization direction deviation exceeds the preset direction threshold by about ±15°, it is considered a polarization conflict; when the polarization intensity ratio exceeds the preset intensity threshold by more than 2 or less than 0.5, it is considered a polarization conflict; when the local polarization uniformity deviation exceeds the preset uniformity threshold, such as when the difference between the maximum and minimum values exceeds 20%, it is considered a polarization conflict.
[0053] Furthermore, the conflict location information is output in the form of coordinates in a virtual image, or in the form of a region location on the windshield of the HUD under test.
[0054] Specifically, in this embodiment, the conflict location information is output in the form of coordinates in the virtual image, such as "the polarization direction deviation of the upper left corner of the image (-10°, +5°) is 25°", or in the form of the location of the area on the windshield of the HUD under test, such as "the polarization intensity ratio of the left side of the windshield is mismatched".
[0055] It should also be noted that, after performing the above-mentioned matching detection method, the method also includes: triggering an audible and visual alarm when a polarization conflict exists.
[0056] Specifically, when the matching score of all test points is higher than the threshold, the test is displayed as passed; when polarization conflict exists, an audible and visual alarm is triggered, such as a buzzer sound and a red indicator light, and an electronic test report is output. The test report includes test parameter settings, virtual polarization parameters and real-world polarization parameters for each test point, a matching score table, and a diagram of conflict locations.
[0057] Furthermore, the above-mentioned detection methods can be implemented using relevant detection devices, such as... Figure 2 As shown, in a preferred embodiment provided in this application, the detection device includes: an optical platform 1, a position adjustment component 2, a polarization detection unit 3, a data fusion unit 4, and a display and feedback module 5. It also includes a car windshield 7 for simulating the detection environment, and real ambient light 9. The HUD projects a virtual image 8 onto the windshield.
[0058] Optical platform 1 is a vibration-isolated optical platform used to provide a stable horizontal reference plane. During polarization detection, external vibrations directly affect the accuracy of polarization measurements. The optical platform eliminates environmental vibration interference through vibration isolation design, ensuring the accuracy of the detection results.
[0059] The position adjustment component 2, placed on the optical platform, is mainly used for adjusting the position of the polarization detection unit. For those skilled in the art, the position adjustment component can consist of an X-axis module, a Y-axis module, and a Z-axis module connected together. Through electric drive, it adjusts the position and angle of the polarization detection unit to ensure precise alignment of its acquisition end face with the test area of the HUD virtual image, meeting the requirements for positioning and acquisition at multiple preset test points.
[0060] The polarization detection unit 3 adopts an integrated design, incorporating a Stokes polarization sensor and a spectroradiometer, enabling precise acquisition of polarization parameters such as the polarization state, degree of polarization, polarization intensity, polarization azimuth angle, and polarization uniformity of light. This unit can be configured as a dual-probe structure: the first probe faces the HUD virtual image to acquire virtual image polarization parameters; the second probe faces the environment in front of the vehicle to acquire real-world environmental polarization parameters. Both probes operate synchronously under the control of the same clock signal, achieving the synchronous acquisition requirements of steps S101 and S102.
[0061] The acquisition frequency of the polarization detection unit can be adjusted by the data fusion unit, with an adjustment range of 1Hz to 100Hz, to adapt to the detection needs of different dynamic scenarios.
[0062] The data fusion unit 4 is an industrial control computer or embedded processing module with a built-in polarization matching degree evaluation model. It is used to receive the virtual polarization parameter set and the real environment polarization parameter set collected by the polarization detection unit, execute the matching degree calculation in step S103 and the conflict determination in step S104, and output the determination result to the display and feedback module.
[0063] The display and feedback module 5 includes an LCD touchscreen, a buzzer, and a tri-color LED indicator. The LCD touchscreen displays the testing process, parameter settings, and test report; the buzzer and tri-color LED indicator provide audible and visual alarms for each step. After testing, the module automatically generates an electronic test report in PDF format and supports export via USB.
[0064] This application achieves collaborative detection of polarization between the virtual image and the real ambient light by simultaneously acquiring the polarization parameter sets of the HUD virtual image and the real ambient light in the corresponding directions at the same preset test point. By introducing a polarization matching degree evaluation model, it can identify conflict types such as polarization direction deviation, intensity ratio mismatch, and uniformity degradation, and accurately locate the conflict position. This allows polarization design defects to be identified and corrected during the HUD product development stage, preventing quality issues such as image dimming and disappearance from entering the market. It ensures the visibility of the virtual image under polarized sunglasses and the visual consistency between the virtual image and the real ambient light, thereby avoiding image dimming, disappearance, glare, and visual fatigue, significantly improving driving safety and user experience.
[0065] It should be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0066] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.
Claims
1. A method for detecting polarization matching between a HUD virtual image and a real environment, characterized in that, Includes the following steps: When projecting a virtual image into the HUD, a set of virtual polarization parameters for multiple preset test points in the HUD virtual image is collected. Simultaneously acquire the real ambient light polarization parameter set in the directions corresponding to multiple preset test points; The virtual polarization parameter set and the real environment polarization parameter set are input into a preset polarization matching degree evaluation model to calculate the matching degree score for each preset test point; When at least one of the matching scores of each preset test point is lower than the preset threshold, it is determined that there is a polarization conflict at the test point, and the polarization conflict type and conflict location information are output. The polarization matching degree evaluation model includes at least the following: The first evaluation score is determined by evaluating the consistency of polarization direction; The second evaluation score is determined by evaluating polarization intensity compatibility. Based on the first evaluation score and the second evaluation score, a matching score is calculated; The matching score is obtained by weighted summation of the first evaluation score and the second evaluation score, respectively.
2. The method according to claim 1, characterized in that, The virtual polarization parameter set and the real environment polarization parameter set each include at least one of the following polarization parameters: polarization state, polarization intensity, degree of polarization, polarization azimuth angle, and polarization uniformity.
3. The method according to claim 1, characterized in that, The multiple preset test points are multiple feature points in the HUD virtual image screen, and the feature points include at least the center point of the screen, the four corner points, and the midpoints of the four sides.
4. The method according to claim 1, characterized in that, The polarization matching degree evaluation model also includes polarization uniformity evaluation.
5. The method according to claim 1, characterized in that, The polarization direction consistency evaluation is used to characterize the deviation between the polarization azimuth angle of the virtual image and the polarization azimuth angle of the real ambient light at the same test point, and the polarization intensity adaptability evaluation is used to characterize the ratio of the polarization intensity of the virtual image to the polarization intensity of the real ambient light.
6. The method according to claim 1, characterized in that, The polarization conflict types include at least one of the following: polarization direction deviation exceeding a preset direction threshold, polarization intensity ratio exceeding a preset intensity threshold, and local polarization uniformity deviation exceeding a preset uniformity threshold.
7. The method according to claim 1, characterized in that, The conflict location information is output in the form of coordinates in the virtual image screen, or in the form of the area location on the windshield of the HUD under test.
8. The method according to claim 1, characterized in that, When a polarization conflict occurs, an audible and visual alarm is triggered.
9. The method according to claim 1, characterized in that, The acquisition frequencies of the virtual polarization parameter set and the real environment polarization parameter set are adjustable, with an adjustment range of 1Hz to 100Hz.