Camera-aided configuration of a headlight setting tester

Abstract

A method for configuring a headlight setting tester (10), SEP, is proposed, the method comprising: generating, by means of a camera (30), a real-time image (210) of an actual light distribution of a headlight (2) of a vehicle (1); providing a plurality of target images (220), wherein each target image (220) comprises a target light distribution and each target image (220) is assigned a headlight setting test algorithm from a plurality of headlight setting test algorithms; displaying, by means of a display device (40; 140), the real-time image (210); displaying, by means of the display device (40; 140), at least one target image (220) of the plurality of target images (220); and receiving a setting command of a selected headlight setting test algorithm of the plurality of headlight setting test algorithms for the headlight setting tester on the basis of a selected target image (220) of the plurality of target images (220).

Description

[0001] Hella Gutmann Solutions GmbH

[0002] P149130PC00

[0003] Camera-based configuration of a headlight aiming test device

[0004] The present invention relates to a method for configuring a headlight aiming test device (SEP), a method for adjusting and / or testing a vehicle headlight using an SEP, an SEP and an SEP system, and finally, a computer program for carrying out the respective method and a computer-readable medium on which the program is stored. Modern vehicle headlight systems, in particular AFS (Advanced Frontlight System) headlights, are characterized by a multitude of light settings adapted to the vehicle's environment and, in some cases, dynamically adjustable. Thus, the headlight system of a single vehicle can comprise up to seven or more different light settings, such as symmetrical and asymmetrical low beam, high beam, cornering light, city light, motorway light, parking light, bad weather light, etc.These are typically provided by LED, matrix LED, and / or laser headlight systems and are characterized by distinctive light distributions generated by the vehicle headlight, which can illuminate the road in different ways. Accordingly, the requirements for the calibration or adjustment of such systems also increase, which can typically be done with a SEP (System Optimizer). For this purpose, the SEP is first positioned in a predetermined position relative to the headlight to be calibrated, as specified by the manufacturer, and then the calibration is carried out according to the manufacturer's instructions. An example SEP is described in EP application number 23 213 106.0.

[0005] A SEP (Spotlight Adjustment Testing Algorithm) comprises a camera and lens system for capturing the instantaneous light distribution produced by the headlight, an actual light distribution. This distribution can then be compared with a predefined, correct target light distribution stored in the SEP and calibrated accordingly. For the calibration itself, the SEP must therefore be correctly positioned relative to the headlight and configured. Specifically, the correct headlight adjustment test algorithm (SEP algorithm) must be set for the calibration process. This algorithm includes the test and adjustment parameters as well as the commands for performing the calibration.For the correct calibration of a headlight using a SEP (Lighting Evaluation Panel), it is therefore essential to set the correct SEP algorithm. This algorithm depends not only on the lighting system being calibrated but also on the light distribution to be calibrated on the vehicle. The SEP algorithm is typically set without reference to the actual light distribution produced by the headlight, by selecting from a simple list stored in the SEP. This list merely contains various vehicle makes, models, and their corresponding light distributions, and is therefore regularly prone to incorrect selection, especially incorrect selections that cannot be traced later. This can ultimately lead to faulty calibration and thus endanger the vehicle's road safety.

[0006] Against this background, the present invention aims to provide an alternative and / or improved solution for configuring a SEP. The improvement may, in particular, consist of minimizing the risk of incorrectly selecting the SEP algorithm and / or simplifying the correct selection process.

[0007] According to the invention, this problem is solved by a method for configuring a SEP, a method for adjusting and / or testing a vehicle headlight using an SEP, an SEP and an SEP system, a computer program for carrying out the respective method, and a computer-readable medium on which the program is stored, with the features of the corresponding independent claims. Possible embodiments and further developments are described in the dependent claims, the following description, and the figures.

[0008] The proposed procedure for configuring a SEP includes:

[0009] Generating, using a camera, a real-time image of the actual light distribution of a vehicle's headlight;

[0010] Providing a multitude of target images, each target image comprising a target light distribution and each target image being assigned a headlight aiming test algorithm from a multitude of headlight aiming test algorithms;

[0011] Display of the real-time image using a display device;

[0012] Displays, by means of the display device, at least one target image of the plurality of target images;

[0013] Receiving a setting command for a selected headlight adjustment test algorithm from among the many headlight adjustment test algorithms for the SEP (Headlight Adjustment Testing System) based on a selected target image from among the many target images. By configuring the SEP algorithm based on a selected target image from among the many target images and using the real-time image, the risk of incorrect SEP algorithm selection can be minimized. Furthermore, additional work steps, such as an extra trip to the vehicle and checking the headlight setting on the vehicle, can be eliminated.

[0014] The setting command can be issued by a user. The user can be supported and / or guided in selecting the correct SEP algorithm by the provided and displayed target images and their comparison with the displayed real-time image. Alternatively or additionally, the selection of the SEP algorithm can be guided and / or supported by a machine learning (ML) classification based on a comparison of the real-time image and the multitude of target images. It can be provided that the set SEP algorithm and at least the real-time image, optionally supplemented by the multitude of target images on which the SEP algorithm setting was based, are automatically logged. This allows the process to be traced retrospectively, e.g., for the purpose of service documentation of a completed headlight calibration.

[0015] A light distribution is fundamentally characterized by providing a characteristic illumination of a roadway, adapted, for example, to specific environmental conditions. Therefore, every image, such as the real-time image captured by the camera and / or the provided target images, is characteristic of the respective actual and / or desired light distribution. This can relate to the geometry of the light distribution, in particular the shape of the depicted light cone, the position of its vertical and / or horizontal light-dark boundary(s) – i.e., the transition between illuminated and unilluminated areas – the presence of additional lighting spots, and / or the intensity of the light distribution, especially a glare value and / or an illuminance of the light distribution. In the relevant technical terminology, a light distribution as such is sometimes also referred to as a reference element.This should not be confused with the term "reference segment" used below, which in this context refers to a characteristic feature of a light distribution. Examples of possible reference segments are listed further below.

[0016] The method can further include displaying one or more target light distribution reference segments in at least one or each of the multiple target images, wherein each target light distribution reference segment corresponds to a light distribution characteristic. The target light distribution reference segment(s) can be requested from and retrieved from a database or storage device. Alternatively or additionally, the method can include generating and displaying one or more actual light distribution reference segments in the real-time image, wherein each actual light distribution reference segment corresponds to a light distribution characteristic. Each of these measures can reduce the complexity of a light distribution and / or highlight a key parameter of a light distribution relevant for light adjustment.The light distribution characteristic can be a light-dark boundary, especially a vertical light-dark boundary, or a characteristic shape of the light distribution, a luminous center, a predefined pixel, and the like. These are regularly particularly important characteristics for the geometry of the light distribution. Selected light distribution characteristics can be generated in real-time imaging using simple image processing methods, such as contrast analysis. Additionally, one or more identical light distribution characteristics from the target image and the real-time image can be compared. For example, the respective vertical light-dark boundaries of a real-time image and one or more target images from a multitude of target images can be displayed and compared.

[0017] Each target image among the multitude of target images can correspond to a different light setting from a variety of headlight settings. The number and type of light settings can be specific to the headlight system, i.e., dependent on the vehicle make and model. The light settings can include, but are not limited to, symmetrical and asymmetrical low beam, high beam, parking lights, fog lights, cornering lights, bad weather lights, motorway lights, city lights, and / or diagnostic lights. Diagnostic lights can correspond to a characteristic light distribution predetermined by the manufacturer specifically for diagnostics and / or calibration. In particular, diagnostic lights can be provided for vehicle headlight systems with adaptive light control. In these systems, the headlight light distribution is automatically adjusted to different environmental conditions.The procedure can also include sending a diagnostic light command to the vehicle to generate a diagnostic light as the actual light distribution of the headlight.

[0018] Each target image can be associated with characteristic target information, and the procedure can include selective display of this target information. The target information can further reduce the complexity of a light distribution and / or highlight a key parameter of the light distribution relevant for light setting. The target information can be requested from and retrieved from a database or storage device. The target information can include information on the target light distribution, in particular its geometry, glare value, and / or illuminance. The target information can also include information on the light distribution algorithm associated with the target image, particularly as a function of vehicle data, headlight data, and / or headlight setting.

[0019] The method can further include generating and displaying test information for real-time imaging. This test information can further reduce the complexity of a light distribution and / or highlight a key parameter of the light distribution relevant for light setting. The test information can include details of the actual light distribution, in particular its geometry, glare value, and / or illuminance. This test information can also be generated using image processing methods, such as contrast analysis or illuminance measurement.

[0020] A method for adjusting and / or testing a vehicle's headlight using a headlight aiming tester (SEP) is also proposed. This method includes the features of the SEP configuration procedure described above, plus the adjustment and / or testing of the headlight according to the selected headlight aiming test algorithm. In other words, after setting the SEP algorithm based on a selected target image, the headlight is calibrated as intended, particularly using the configured SEP algorithm. This may include calibrating, i.e., adjusting, the actual light distribution to the selected target light distribution.

[0021] Finally, a computer program and a computer-readable medium on which the computer program is stored are also proposed. The computer program comprises instructions that cause the SEP or the SEP system to execute one of the methods according to the invention. The program can be provided on the SEP or the SEP system.

[0022] Several embodiments have been disclosed herein. Further embodiments of the present invention will become apparent to those skilled in the art from the following detailed description, which shows and describes an exemplary embodiment. Accordingly, the drawings and the detailed description are to be considered exemplary and not limiting. Recurring features are identified in the figure description by the same reference numerals.

[0023] They show

[0024] Fig. 1 shows a schematic representation of an embodiment of a SEP,

[0025] Fig. 2 shows a schematic representation of an embodiment of a SEP system in front of a vehicle,

[0026] Fig. 3 shows a schematic representation of a display of real-time mapping and target mapping.

[0027] Fig. 4 shows another schematic representation of the display from Fig. 3 and

[0028] Figures 5 to 8 each show an example of light distribution under different lighting conditions. Recurring features are described once for all figures below. References to individual figures are made only when relevant.

[0029] Fig. 1 shows a SEP 10 with an integrated display device 40. Fig. 2 shows a SEP system 100, which, in addition to the SEP 10, includes a mobile device 150 with a display device 140. The mobile device 150 with the display device 140 can be provided as an alternative or additional to the display device 40 integrated in the SEP 10 and can be, for example, a smartphone or a tablet. The SEP 10 includes a camera 30, which is arranged behind an input lens 20, here a Fresnel lens. The SEP 10 is configured, when oriented as intended towards a headlight 2 of a vehicle 1, to use the camera 30 to capture light emitted by the headlight 2 of an actual light distribution and to generate a real-time image 210 of the actual light distribution. The camera 30 is, in this case, a CMOS camera. Furthermore, the SEP 10 includes an alignment device 90, here a line laser, for the intended alignment of the SEP 10 relative to a headlight 2 to be calibrated.Further details regarding the SEP 10 and its orientation can be found, for example, in EP application number 23 213 106.0. The headlight 2 can be a low beam, high beam, fog, or auxiliary headlight. The headlight 2 can be a DE, FF, LED, or xenon headlight. Both the SEP 10 and the SEP system 100 are configured to perform the procedure described below. The SEP 10 and / or the mobile terminal 150 include a control device configured to execute a computer program containing commands that cause the SEP 10 and / or the SEP system 100 to execute and / or implement the procedure. The computer program can, for example, be provided from a computer-readable medium.

[0030] First, the SEP 10 is aligned relative to a headlight 2 of a vehicle 1 for the headlight calibration to be performed, in such a way that the SEP 10 can detect the actual light distribution produced by the headlight 2 and generate a real-time image 210 of the actual light distribution based on this. This alignment can include a predetermined distance, a predetermined height, and / or a predetermined orientation of the SEP 10 relative to the headlight 2 to be calibrated. Subsequently, the configuration of the SEP 10 can be carried out, which in this case involves setting the appropriate or correct SEP algorithm for the calibration. The correct SEP algorithm depends on the headlight system and the selected light setting from, for example, a multitude of light settings available to the headlight system. Each light setting produces a predetermined actual light distribution of the headlight, such as...Symmetrical and asymmetrical low beam, high beam, parking lights, fog lights, cornering lights, bad weather lights, motorway lights, city lights and / or diagnostic lights. The headlight system is typically assigned to a specific vehicle make and model.

[0031] Configuring the SEP comprises generating, by means of the camera 30, a real-time image 210 of the actual light distribution of the headlight 2 of the vehicle 1; providing a plurality of target images 220, wherein each target image 220 comprises a target light distribution and each target image 220 is assigned a headlight adjustment test algorithm from a plurality of headlight adjustment test algorithms; displaying, on a display 200, the real-time image 210, cf. Figs. 3 and 4 right, and at least one target image 220 of the plurality of target images 220, cf. Figs. 3 and 4 left, by means of the display device 40 integrated in the SEP 10 and / or the display device 140 of the terminal device 150; and finally, receiving a setting command of a selected headlight setting test algorithm from the multitude of headlight setting test algorithms for the SEP 10 based on a selected target image 220 from the multitude of target images 220.

[0032] The configuration command is issued by a user, who is supported and / or guided in selecting the correct SEP algorithm by the provided and displayed target images 220 and their comparison with the displayed real-time image 210. Alternatively or additionally, the selection of the SEP algorithm can be guided and / or supported by a machine learning classification based on a comparison of the real-time image 210 and the multitude of target images 220. It can be provided that the configured SEP algorithm and at least the real-time image 210, optionally supplemented by the multitude of target images 220 on which the SEP algorithm was based, are automatically logged.

[0033] As explained above, each target image 220 corresponds to a different light setting from a multitude of light settings of the headlight 2. The number and type of light settings are headlight system-specific and can therefore depend on the vehicle make and model. Thus, in a preconfiguration of the SEP 10 (not shown in detail here), the number of possible SEP algorithms may be reduced by preselecting the relevant headlight system—e.g., from a list of vehicle makes and models—according to the light distributions that the headlight 2 can produce. The light settings can include, in a non-exhaustive and headlight system-dependent list, symmetrical and asymmetrical low beam, high beam, parking light, fog light, cornering light, bad weather light, motorway light, city light, and / or diagnostic light.Diagnostic light can correspond to a characteristic light distribution predetermined by the manufacturer specifically for diagnosis and / or calibration. Such a light distribution is shown in Figures 3 and 4 for glare-free high beam and can be provided, for example, by sending a diagnostic light command to the vehicle 1 to generate the diagnostic light as the actual light distribution of the headlight 2. Alternative light distributions, in this case possible target light distributions, can be seen in Figures 5 to 8. These include the asymmetric low beam BX of a bi-xenon headlight in Figure 5, high beam FL in Figure 6, asymmetric low beam with a light spot AL in Figure 7, and fog light NL in Figure 8. This illustration makes it clear that each light distribution and the resulting target image 220 has a very characteristic geometry. The x and y axes form the horizontal and vertical axes, respectively.the vertical reference axis or center axis of the respective figure.

[0034] Furthermore, in the respective target image 220 shown in Figures 3 and 4, a target light distribution reference segment 221 is displayed, wherein the target light distribution reference segment 221 corresponds to a light distribution characteristic. The target light distribution reference segment 221 can be requested from and retrieved from a database or storage device. Additionally, in the real-time image 210 shown in Figure 4, an actual light distribution reference segment 211 is generated and displayed, wherein the actual light distribution reference segment 211 corresponds to a light distribution characteristic. In this case, the light distribution characteristic is a vertical light-dark boundary, but it can also be a characteristic shape of the light distribution (here, for example, a rectangle characteristic of the light distribution shown), a luminous center, a predefined pixel, and the like.Therefore, the respective vertical light-dark boundaries of the real-time image 210 and the displayed target image 220 are shown and compared for the multitude of target images. The generation of selected light distribution characteristics in the real-time image 210 can be achieved using simple image processing methods, such as contrast analysis.

[0035] As shown in Fig. 4, characteristic target information 222 can be assigned to the target image 220 and selectively displayed. This information can be requested from and retrieved from a database or storage device. The target information 222 can include information on the target light distribution, in particular its geometry (e.g., as shown here, characterized as a "rectangular characteristic" and provided with the additional reference to the inner vertical light-dark boundary), glare value, and / or illuminance of the target light distribution. The target information 222 can also include information on the light distribution algorithm assigned to the target image 220, in particular as a function of vehicle data, headlight data, and / or headlight setting. Additionally, test information 212 is generated and displayed in the real-time image 210.The test information 212 can include information on the actual light distribution, in particular its geometry, glare value, and / or illuminance. Here, the distance of the inner light-dark boundary of the current actual / target distribution to the vertical reference axis y is displayed in arcminutes. The test information 212 can also be generated using image processing methods, such as contrast analysis or luminous intensity measurement. After the SEP algorithm has been set based on a selected target image 220, the intended calibration of the headlight 2 can be carried out using the set SEP algorithm, i.e., the headlight 2 can be adjusted and / or tested according to the selected headlight adjustment / test algorithm. In this process, the actual light distribution can be calibrated to the selected target light distribution, i.e., adjusted to it.

[0036] Another embodiment of the method for configuring the SEP 10 or SEP system 100 can include the following sequence. First, target settings are selected. For this purpose, settings for calibrating or adjusting the respective light distributions are entered in a menu on the display device 40; 140 (not shown). These can relate, for example, to the test standard, the vehicle type of vehicle 1, a forward tilt of the headlight 2, the direction of travel, or the presence of adaptive lighting control. A selection assistant can then be provided as an option. If, for example, an operator or user is unsure which type of light distribution to expect or which must be selected, a button allows them to view all target light distributions available in the SEP 10 or SEP system 100 (possibly vehicle- and / or headlight system-specific), e.g.,to display a high-beam assist function for glare-free high beams. This leads the operator to the display 200 shown in Figures 3 and 4, a menu for selecting the light distribution. On the right side of display 200, the real-time image 210 is shown, i.e., the live image of the light distribution emitted by the headlight 2 into the SEP and recorded by the camera 30. On the left side of display 200, all light distributions, e.g., of the brand-specific high-beam assist systems (glare-free high beams), are listed. A selection by vehicle brand can be made using the "Manufacturer" selection field. Then only the light distributions of that vehicle brand are displayed. Here, the operator can use a scroll function to view all target images 220 stored in the SEP 10 or SEP system 100 and compare them with the real-time image 210. To the right, next to the heading, is a button labeled "i".Pressing the button activates it and displays additional, relevant target information 222 below the graphic regarding the target image 220 and the associated light distribution, the corresponding algorithm, and / or the corresponding setting of the headlight 2. Pressing the button again deactivates it and hides the information. This is achieved through a comparison between the target image 220 and the real-time image 210, as well as the textual target information.

[0037] The operator can select the correct algorithm at 222. Each target image 220 has a heading with the respective name of the displayed light distribution. To the left of the name is a checkbox; checking this box selects the corresponding algorithm.

[0038] Further embodiments of the described invention will be obvious to a person skilled in the art.

Claims

Hella Gutmann Solutions GmbH P149130PC00 Claims 1. Method for configuring a headlight aiming test device (10), SEP, the method comprising: Generating, using a camera (30), a real-time image (210) of an actual light distribution of a headlight (2) of a vehicle (1); Providing a plurality of target images (220), wherein each target image (220) includes a target light distribution and each target image (220) is associated with a headlight adjustment test algorithm from a plurality of headlight adjustment test algorithms; Display of the real-time image (210) by means of a display device (40; 140); Displays, by means of the display device (40; 140), at least one target image (220) of the plurality of target images (220); Receiving an adjustment command from a selected headlight adjustment test algorithm of the multitude of headlight adjustment test algorithms for the SEP based on a selected target image (220) of the multitude of target images (220).

2. Method according to claim 1, further comprising displaying one or more light distribution target reference segments (221) in at least one or each target image (220) of the plurality of target images (220), wherein each light distribution target reference segment (221) corresponds to a light distribution characteristic.

3. Method according to claim 1 or 2, further comprising generating and displaying one or more actual light distribution reference segments. (211) in the real-time image (210), wherein each light distribution actual reference segment (211) corresponds to a light distribution characteristic.

4. Method according to claim 2 or 3, wherein the light distribution characteristic is a light-dark boundary, in particular an inner vertical light-dark boundary, or a characteristic shape of the light distribution.

5. Method according to any of the preceding claims, wherein each target image (220) of the plurality of target images (220) corresponds to a different light setting from a plurality of light settings of the headlight (2), wherein the light settings optionally include low beam, high beam, parking, fog, cornering, bad weather, motorway, city and / or diagnostic light.

6. Method according to one of the preceding claims, wherein each target image (220) is assigned characteristic target information (222), and wherein the method comprises selectively displaying the target information (222).

7. Method according to claim 6, wherein the target information (222) includes information on the target light distribution, in particular geometry, glare value and / or illuminance of the target light distribution, information on the light distribution algorithm associated with the target image (220), in particular depending on vehicle data, headlight data and / or headlight light setting.

8. Method according to one of the preceding claims, further comprising generating and displaying test information (212) for the real-time image (210), wherein test information (212) includes information on the actual light distribution, in particular geometry, glare value and / or illuminance.

9. Method according to one of the preceding claims, further comprising sending a diagnostic light command to the vehicle to generate a diagnostic light as the actual light distribution of the headlight (2).

10. Method according to one of the preceding claims, wherein a selection of the headlight adjustment test algorithm is carried out and / or supported on the basis of a comparison of the real-time image (210) and the plurality of target images (220) by means of an ML classification.

11. Method for adjusting and / or testing a headlight (2) of a vehicle using a headlight aiming tester (10), SEP comprising the features according to any of the preceding claims, and additionally: Adjusting and / or checking the headlight (2) according to the selected headlight adjustment / checking algorithm.

12. Headlight aiming test device (10), SEP, comprising a camera (30) and a display device (40), wherein the SEP (10) is configured to perform the method according to any one of claims 1 to 11.

13. SEP system (100) comprising a headlight aiming test device (10), SEP, with a camera (30) and further comprising a mobile terminal (150) with a display device (140), in particular a smartphone or a tablet, wherein the SEP system (100) is configured to perform the method according to any one of claims 1 to 11.

14. Computer program comprising instructions that cause the device of claim 12 or the system of claim 13 to execute the method according to any one of claims 1 to 11.

15. Computer-readable medium on which the computer program according to claim 14 is stored.

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