A method and device for testing glare coordination of adaptive high beams, and an electronic device

Abstract

The embodiment of the specification discloses a kind of adaptive high beam's glare collaborative test method, device and electronic equipment.The method includes by first obtaining the test data of target vehicle in field test, and based on the bus data in test data, darkroom light test is carried out to target vehicle, the light shape data corresponding to each target time is obtained, then the target illumination range corresponding to each light shape data is determined according to the inertial navigation data in test data, finally, the glare test result of adaptive high beam is determined by the comparison result of each two two matching target illumination range and theoretical glare affected range.The test data obtained in field test is backfilled to darkroom light test scene by data, the glare collaborative test of adaptive high beam is carried out, it is guaranteed that real road driving condition environment can be simulated, and the target illumination range of each target time can be accurately and efficiently determined in darkroom test environment, the accuracy and efficiency of adaptive high beam glare test are improved.

Description

Technical Field

[0001] This specification relates to the field of automotive lighting testing technology, and more particularly to a method, apparatus, and electronic device for testing the glare coordination of adaptive high beams. Background Technology

[0002] With the rapid development of autonomous driving technology, the performance requirements for adaptive driving beams (ADB) in automobiles are becoming increasingly stringent. These ADB systems must automatically adjust their high beams in various driving scenarios to prevent glare from other vehicles. Therefore, a comprehensive, accurate, and efficient testing method for adaptive high beams is needed to evaluate the performance of vehicle headlights' ADB. However, current traditional ADB testing methods are mostly limited to laboratory or darkroom environments, lacking simulations of complex scenarios under real road conditions. They often focus only on the performance of the headlight itself, neglecting the impact of vehicle dynamics, road conditions, and the position of surrounding objects on ADB performance. This leads to significant discrepancies between test results and actual usage, making it difficult to accurately reflect the anti-glare effect of adaptive high beams. Summary of the Invention

[0003] This specification provides an embodiment of a method, apparatus, and electronic device for testing the glare coordination of adaptive high beam headlights, the technical solution of which is as follows:

[0004] In a first aspect, embodiments of this specification provide a method for testing the glare coordination of adaptive high beam headlights, the method comprising:

[0005] Acquire test data of the target vehicle during field testing. The test data includes inertial navigation data and bus data. The inertial navigation data is used to characterize the position information of the target vehicle and the excitation vehicle at each test moment. The bus data is used to characterize the working information of the adaptive high beam of the target vehicle at each test moment.

[0006] Based on the bus data, a darkroom lighting test is performed on the target vehicle to obtain light pattern data corresponding to at least two target times, wherein the working information corresponding to the target times is in the on state.

[0007] Based on the inertial navigation data, construct a three-dimensional model of the high beam illumination corresponding to each target time, and determine the target illuminance range corresponding to each light pattern data based on each three-dimensional model of the high beam illumination.

[0008] The theoretical glare-affected range of the excitation vehicle at each of the target times is determined, and the target illuminance range and the theoretical glare-affected range are compared in pairs. Based on the comparison results, the glare test results of the adaptive high beam are determined.

[0009] Secondly, an adaptive high beam glare coordination testing device is provided, the device comprising:

[0010] The acquisition module is used to acquire test data of the target vehicle in the field test. The test data includes inertial navigation data and bus data. The inertial navigation data is used to characterize the position information of the target vehicle and the excitation vehicle at each test moment. The bus data is used to characterize the working information of the adaptive high beam of the target vehicle at each test moment.

[0011] The testing module is used to perform a darkroom lighting test on the target vehicle based on the bus data, and obtain light pattern data corresponding to at least two target times, wherein the working information corresponding to the target times is in the on state;

[0012] The construction module is used to construct a three-dimensional model of the high beam illumination corresponding to each target time based on the inertial navigation data, and to determine the target illuminance range corresponding to each light pattern data based on each three-dimensional model of the high beam illumination.

[0013] The determination module is used to determine the theoretical glare-affected range of the excitation vehicle at each of the target times, and compare the target illuminance range and the theoretical glare-affected range that are paired up in each pair, and determine the glare test result of the adaptive high beam based on the comparison results.

[0014] Thirdly, an electronic device is provided, including a device processor and a memory;

[0015] The device processor is connected to the memory;

[0016] The memory is used to store executable program code;

[0017] The device processor runs a program corresponding to the executable program code stored in the memory to perform the steps of the method provided as in the first aspect or any possible implementation thereof.

[0018] Fourthly, a computer-readable storage medium is provided having a computer program stored thereon, the computer-readable storage medium storing instructions that, when executed on a computer or device processor, cause the computer or device processor to perform the method provided as in the first aspect or any possible implementation thereof.

[0019] The beneficial effects of the technical solutions provided in some embodiments of this specification include at least the following:

[0020] In one or more embodiments of this specification, test data of the target vehicle during field testing can be acquired first. Based on the bus data in the test data, a darkroom lighting test is performed on the target vehicle to obtain the light pattern data corresponding to each target moment. Then, the target illuminance range corresponding to each light pattern data is determined based on the inertial navigation data in the test data. Finally, the glare test result of the adaptive high beam is determined by comparing the paired target illuminance ranges with the theoretical glare-affected range. By feeding the test data acquired in the field test back into the darkroom lighting test scenario to conduct adaptive high beam glare coordination testing, it is ensured that both real road driving conditions can be simulated, and the target illuminance range at each target moment can be accurately and efficiently determined in the darkroom test environment, thus improving the accuracy and efficiency of adaptive high beam glare testing. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart illustrating a glare coordination test method for adaptive high beams provided in this specification's embodiments;

[0023] Figure 2 A schematic diagram of the structure of an adaptive high beam glare coordination testing device provided in the embodiments of this specification;

[0024] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this specification. Detailed Implementation

[0025] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0026] The terms "first," "second," "third," etc., in the description, claims, and accompanying drawings are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0027] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of this specification. Various processes or components may be appropriately omitted, substituted, or added to the examples. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.

[0028] Please see Figure 1 , Figure 1 This document presents an overall flowchart of a method for testing the glare coordination of adaptive high beams, as provided in an embodiment of this specification.

[0029] like Figure 1 As shown, the glare coordination test method for adaptive high beams may include at least the following steps:

[0030] Step 101: Obtain test data of the target vehicle during the field test.

[0031] The test data includes inertial navigation data and bus data. The inertial navigation data is used to characterize the position information of the target vehicle and the excitation vehicle at each test moment, and the bus data is used to characterize the working information of the adaptive high beam of the target vehicle at each test moment.

[0032] In the embodiments of this specification, in order to conduct glare coordination testing on the adaptive high beams of the target vehicle, it is necessary to simulate it under real road conditions. However, it is difficult to obtain the light pattern data of the high beams under real road conditions. Therefore, it is necessary to first simulate the real driving environment in the test site and then import the obtained test data into a darkroom test environment where the light pattern data is easier to capture. Specifically, site testing requires preparation, including installing inertial navigation systems, ADB robots, and other equipment, and preheating and calibrating the test vehicle to ensure the normal operation of the test equipment. Next, the site test is conducted, using an autonomous driving robot to drive the target vehicle and the trigger vehicle in specified scenarios within the site, including following, oncoming traffic, overtaking, cutting in from the vehicle ahead, and cutting out from the vehicle ahead. Simultaneously, the inertial navigation systems on both the target vehicle and the trigger vehicle record driving information, obtaining the test data of the target vehicle during the site test. The test data includes inertial navigation data and bus data. The inertial navigation data includes the target vehicle speed V1, the target vehicle pitch angle φ, the target vehicle position coordinates L1 (x1, y1), and the trigger vehicle coordinates L2 (x2, y2), etc. The bus data includes the operating information of the target vehicle's adaptive high beam at each test moment. The inertial navigation data and bus data box are synchronized via I / O ports, while the inertial navigation systems of the target vehicle and the triggering vehicle are synchronized via GPS. The response of the ADB system is monitored and recorded in real time. Therefore, the obtained inertial navigation data and bus data are paired at each test moment.

[0033] Optionally, after conducting field tests, the acquired test data can be professionally organized and aligned. First, scenarios are finely categorized based on driving characteristics, such as straight roads, curves, and oncoming traffic. Second, data is summarized and classified according to inertial navigation (INS) data and bus data. For example, each scenario's data is identified as TEST-Name and the corresponding data for each scenario; bus data is identified as Test-CAN-ID, and INS data as Test-RT-ID.

[0034] Step 102: Perform a darkroom lighting test on the target vehicle based on the bus data to obtain light pattern data corresponding to at least two target times.

[0035] The working information corresponding to the target time is in an "on" state.

[0036] In the embodiments of this specification, after obtaining test data through field testing, a data feedback architecture can be built first. Specifically, the headlight bus is disconnected from the body bus, and the two buses are bridged to CANoe (headlight H / L to CH1 and CH2, body H / L to CH3 and CH4). A feedback script is written, including instructions such as pause, injection, reset, and time selection, so that data feedback can be paused at any time, and all signals are kept in the state of that moment during the pause, ensuring the flexibility and continuity of the test. Next, data feedback is started, and the bus data is input to the headlight controller using the built data feedback architecture. Darkroom lighting tests are then performed, and the adaptive high beam is controlled using the bus data. Multiple target times are randomly selected within the time period when the adaptive high beam is in the on state, and the light pattern data corresponding to each target time is obtained through the light pattern sensor.

[0037] In one possible implementation, the step of performing a darkroom lighting test on the target vehicle based on the bus data to obtain light pattern data corresponding to at least two target times includes:

[0038] Based on the bus data, determine the high beam operation commands corresponding to at least two target times;

[0039] According to the high beam operation commands, a darkroom lighting test is performed on the target vehicle to obtain the light pattern data corresponding to each target time.

[0040] In the embodiments of this specification, the acquired bus data includes the operating information of the adaptive high beam of the target vehicle at each test moment, i.e., the light sensor control commands at each test moment. Therefore, to conduct a darkroom lighting test on the target vehicle, the time period during which the adaptive high beam is in the on state can be determined through the bus data, and this time period can be divided into three equal parts. A target moment can be determined in each part of the time period using a random method. Then, by querying the three different target moments T1, T2, and T3 in the bus data, the high beam operating commands corresponding to each target moment can be obtained. Further, the lighting test on the target vehicle is conducted in a darkroom environment using each high beam operating command. An illuminance probe is used to scan the main glare potential area, and an imaging luminance meter is used to take pictures and measure the remaining areas. Finally, the two sets of data are combined to obtain the light pattern data corresponding to each target moment.

[0041] Step 103: Construct a three-dimensional model of the high beam illumination corresponding to each target time based on the inertial navigation data, and determine the target illuminance range corresponding to each light pattern data based on each three-dimensional model of the high beam illumination.

[0042] In the embodiments of this specification, after acquiring the inertial navigation data from the field test and the light pattern data at each target moment from the cue light test, the illuminance range at the location of the stimulating vehicle at each target moment can be determined by first using the acquired inertial navigation data to determine the corresponding location information at each target moment. This information may include the target vehicle coordinates, the stimulating vehicle coordinates, and the surrounding geographical environment. Next, a 3D model of the high beam illumination corresponding to each different target moment is constructed using 3D modeling software based on the location information. The light pattern data is then input into the corresponding 3D model of the high beam illumination to simulate the target illuminance range generated at the corresponding stimulating vehicle coordinate location after the light pattern data is emitted at the target vehicle coordinate location.

[0043] In one possible implementation, constructing a three-dimensional model of the high beam illumination corresponding to each target time based on the inertial navigation data includes:

[0044] An initial illumination 3D model is constructed, and the position information corresponding to each target at each time point is determined based on the inertial navigation data;

[0045] The location information is input into the initial illumination 3D model to obtain the high beam illumination 3D model corresponding to each target time.

[0046] In the embodiments of this specification, the illumination area can first be divided into meshes using fixed physical location information such as the position of the target vehicle's headlights and its driving direction. Based on the results of ray tracing, the brightness, color, and other information of each mesh are rendered. A geometric 3D model is constructed using 3D modeling software such as Blender or 3ds Max, and a high beam source is added to it, setting its initial position and defining initial parameters such as the initial intensity, color, illumination angle, and range of the light source to construct an initial illumination 3D model. Next, the acquired inertial navigation data is filtered using each target time as a timestamp to obtain the location information corresponding to each target time, including the target vehicle coordinates, the excitation vehicle coordinates, and the surrounding geographical environment. Further, each location information is input into the initial illumination 3D model to update the position and direction information of the high beam in the initial illumination 3D model. A ray tracing algorithm is used to calculate the propagation path of the light emitted from the high beam source in the scene, and the intersection points of the light with objects in the scene are rendered to display the illumination effect, thus obtaining the high beam illumination 3D model corresponding to each target time.

[0047] In one possible implementation, determining the target illuminance range corresponding to each of the light pattern data based on each of the three-dimensional models of the high beam illumination includes:

[0048] Determine the coordinates of the excitation vehicle in each of the aforementioned location information;

[0049] Based on the three-dimensional model of each high beam illumination, the target illuminance range corresponding to the coordinates of each excitation vehicle is determined.

[0050] In the embodiments of this specification, the coordinates of the excitation vehicle included in the location information corresponding to each target time can be determined first. Then, each light pattern data is input into its corresponding three-dimensional model of high beam illumination, and adaptive adjustments are made to the tilt angle and light intensity of the high beam to simulate high beam illumination. Simulated illumination points are set at the coordinates of the excitation vehicle to receive the high beam illumination of the target vehicle, thereby obtaining the target illuminance range corresponding to each light pattern data.

[0051] Step 104: Determine the theoretical glare-affected range of the excitation vehicle at each of the target times, and compare the target illuminance range and the theoretical glare-affected range that are paired up in each pair. Based on the comparison results, determine the glare test results of the adaptive high beam.

[0052] In the embodiments of this specification, during actual driving, the theoretical glare-affected range of the excitation vehicle varies at different target times due to differences in the distance between it and the target vehicle, as well as the different driving scenarios of the two vehicles. Specifically, when the target illuminance range received by the excitation vehicle at a target time exceeds the theoretical glare-affected range, it indicates that the excitation vehicle will be affected by glare from the high beams of the target vehicle. Therefore, the theoretical glare-affected range of the excitation vehicle at each target time is first determined using a historical test database. Next, the obtained paired target illuminance ranges and theoretical glare-affected ranges are compared, and the glare test result of the adaptive high beam is determined based on the comparison results. Generally, it is necessary to judge the comparison results corresponding to all target times; only when all of them meet the preset values ​​can the glare test result of the adaptive high beam be determined to meet the requirements.

[0053] In one possible implementation, determining the theoretical glare impact range of the excitation vehicle at each of the target times includes:

[0054] The driving scenario type for each target time point is determined based on the test data.

[0055] The theoretical glare range of the excitation vehicle at each of the target times is determined based on the type of driving scenario.

[0056] In the embodiments of this specification, the test data includes various driving scenarios. Since the theoretical glare impact range differs for different driving scenarios, for example, when the target vehicle and the stimulating vehicle are traveling in the same direction, the theoretical glare impact range for the stimulating vehicle is the positions of the left and right rearview mirrors and the driver's side rearview mirror; when the target vehicle and the stimulating vehicle are traveling in opposite directions, the theoretical glare impact range for the stimulating vehicle is the position of the windshield. Therefore, it is necessary to first determine the type of driving scenario corresponding to each target time from the acquired test data. Then, a historical test database is constructed using historical test data. By inputting the type of driving scenario corresponding to each target time and the relative positions of the target vehicle and the stimulating vehicle at that target time into this database, the corresponding theoretical glare impact range can be output.

[0057] In one possible implementation, comparing the paired target illuminance ranges with the theoretical glare-affected ranges includes:

[0058] The similarity between the target illuminance range and the theoretical glare influence range is calculated based on a similarity algorithm.

[0059] Each similarity is compared with a preset similarity value to obtain a comparison result.

[0060] In the embodiments of this specification, the target illuminance range and the theoretical glare influence range can first be converted into set form, with each range defined as a set containing numerical values. Next, the Jaccard similarity algorithm is used to calculate the ratio of the intersection to the union of the two sets, obtaining the similarity J between each pair of paired target illuminance ranges and theoretical glare influence ranges. Further, a preset similarity J0 is determined, and the calculated similarity J between each pair of pairs is compared with J0 using difference calculations to obtain the comparison results.

[0061] In one possible implementation, determining the glare test result of the adaptive high beam based on each comparison result includes:

[0062] When all the comparison results indicate that the similarity is less than the preset similarity value, the glare test result of the adaptive high beam is determined to meet the preset requirements;

[0063] When at least one of the comparison results indicates that the similarity is not less than the preset similarity value, the glare test result of the adaptive high beam is determined to be unsatisfactory.

[0064] In the embodiments of this specification, when determining the glare test results of the adaptive high beam based on various comparison results, it is generally necessary to ensure that the adaptive high beam of the target vehicle does not cause glare to the exciting vehicle at all target times. That is, there should be as little overlap as possible between the target illuminance range and the theoretical glare influence range, and the similarity should be as small as possible below a preset similarity value. Therefore, when all the difference comparison results are negative, indicating that the corresponding similarities are all less than the preset similarity value, the glare test results of the adaptive high beam can be determined to meet the preset requirements. Conversely, if even one difference comparison result is not negative, indicating that the similarity is not less than the preset similarity value, the glare test results of the adaptive high beam can be determined to not meet the preset requirements.

[0065] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0066] Please refer to the following. Figure 2 , Figure 2 A schematic diagram of the structure of an adaptive high-beam glare coordination testing device provided in an embodiment of this specification is shown. It should be noted that... Figure 2 The adaptive high beam glare coordination test device shown is used to perform the test of this application. Figure 1 The methods shown in the embodiments are illustrated for ease of explanation, showing only the parts relevant to the embodiments of this application. For specific technical details not disclosed, please refer to this application. Figure 1 The example shown.

[0067] like Figure 2 As shown, the glare coordination testing device for adaptive high beams may include at least:

[0068] The acquisition module 201 is used to acquire test data of the target vehicle in the field test. The test data includes inertial navigation data and bus data. The inertial navigation data is used to characterize the position information of the target vehicle and the excitation vehicle at each test moment. The bus data is used to characterize the working information corresponding to the adaptive high beam of the target vehicle at each test moment.

[0069] Test module 202 is used to perform a darkroom lighting test on the target vehicle based on the bus data, and obtain light pattern data corresponding to at least two target times, wherein the working information corresponding to the target times is in the on state;

[0070] The construction module 203 is used to construct a three-dimensional model of the high beam illumination corresponding to each target time based on the inertial navigation data, and to determine the target illuminance range corresponding to each light pattern data based on each three-dimensional model of the high beam illumination.

[0071] The determination module 204 is used to determine the theoretical glare-affected range of the excitation vehicle at each of the target times, and compare the target illuminance range and the theoretical glare-affected range that are paired up in each pair, and determine the glare test result of the adaptive high beam based on each comparison result.

[0072] In one possible implementation, the test module 202 is specifically used for:

[0073] Based on the bus data, determine the high beam operation commands corresponding to at least two target times;

[0074] According to the high beam operation commands, a darkroom lighting test is performed on the target vehicle to obtain the light pattern data corresponding to each target time.

[0075] In one possible implementation, the construction module 203 is specifically used for:

[0076] An initial illumination 3D model is constructed, and the position information corresponding to each target at each time point is determined based on the inertial navigation data;

[0077] The location information is input into the initial illumination 3D model to obtain the high beam illumination 3D model corresponding to each target time.

[0078] In one possible implementation, the construction module 203 is further configured to:

[0079] Determine the coordinates of the excitation vehicle in each of the aforementioned location information;

[0080] Based on the three-dimensional model of each high beam illumination, the target illuminance range corresponding to the coordinates of each excitation vehicle is determined.

[0081] In one possible implementation, the determining module 204 is specifically used for:

[0082] The driving scenario type for each target time point is determined based on the test data.

[0083] The theoretical glare range of the excitation vehicle at each of the target times is determined based on the type of driving scenario.

[0084] In one possible implementation, the determining module 204 is further configured to:

[0085] The similarity between the target illuminance range and the theoretical glare influence range is calculated based on a similarity algorithm.

[0086] Each similarity is compared with a preset similarity value to obtain a comparison result.

[0087] In one possible implementation, the determining module 204 is further configured to:

[0088] When all the comparison results indicate that the similarity is less than the preset similarity value, the glare test result of the adaptive high beam is determined to meet the preset requirements;

[0089] When at least one of the comparison results indicates that the similarity is not less than the preset similarity value, the glare test result of the adaptive high beam is determined to be unsatisfactory.

[0090] Those skilled in the art will clearly understand that the technical solutions of the embodiments of this application can be implemented by means of software and / or hardware. In this specification, "unit" and "module" refer to software and / or hardware that can independently complete or cooperate with other components to complete a specific function, wherein the hardware may be, for example, a field-programmable gate array (FPGA), an integrated circuit (IC), etc.

[0091] Each processing unit and / or module in the embodiments of this application can be implemented by an analog circuit that implements the functions described in the embodiments of this application, or by software that executes the functions described in the embodiments of this application.

[0092] Please refer to the following. Figure 3 , Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of this specification is shown.

[0093] like Figure 3 As shown, the electronic device 300 may include: at least one device processor 301, at least one network interface 303, user interface 303, memory 305, and at least one communication bus 302.

[0094] The communication bus 302 can be used to realize the connection and communication of the above components.

[0095] The user interface 303 may include buttons, and the optional user interface may also include a standard wired interface or a wireless interface.

[0096] The network interface 304 may include, but is not limited to, Bluetooth modules, NFC modules, Wi-Fi modules, etc.

[0097] The device processor 301 may include one or more processing cores. The device processor 301 connects to various parts within the electronic device 300 using various interfaces and lines. It executes various functions and processes data of the electronic device 300 by running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling data stored in the memory 305. Optionally, the device processor 301 may be implemented using at least one hardware form of DSP, FPGA, or PLA. The device processor 301 may integrate one or more of the following: CPU, GPU, and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the device processor 301 and may be implemented as a separate chip.

[0098] The memory 305 may include RAM or ROM. Optionally, the memory 305 may include a non-transitory computer-readable medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned device processor 301. Figure 3 As shown, the memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.

[0099] Specifically, the device processor 301 can be used to call the adaptive high beam glare coordination test application stored in the memory 305, and specifically perform the following operations:

[0100] Acquire test data of the target vehicle during field testing. The test data includes inertial navigation data and bus data. The inertial navigation data is used to characterize the position information of the target vehicle and the excitation vehicle at each test moment. The bus data is used to characterize the working information of the adaptive high beam of the target vehicle at each test moment.

[0101] Based on the bus data, a darkroom lighting test is performed on the target vehicle to obtain light pattern data corresponding to at least two target times, wherein the working information corresponding to the target times is in the on state.

[0102] Based on the inertial navigation data, construct a three-dimensional model of the high beam illumination corresponding to each target time, and determine the target illuminance range corresponding to each light pattern data based on each three-dimensional model of the high beam illumination.

[0103] The theoretical glare-affected range of the excitation vehicle at each of the target times is determined, and the target illuminance range and the theoretical glare-affected range are compared in pairs. Based on the comparison results, the glare test results of the adaptive high beam are determined.

[0104] As an optional embodiment of this specification, the step of performing a darkroom lighting test on the target vehicle based on the bus data to obtain light pattern data corresponding to at least two target times includes:

[0105] Based on the bus data, determine the high beam operation commands corresponding to at least two target times;

[0106] According to the high beam operation commands, a darkroom lighting test is performed on the target vehicle to obtain the light pattern data corresponding to each target time.

[0107] As an optional embodiment of this specification, the step of constructing a three-dimensional model of the high beam illumination corresponding to each target time based on the inertial navigation data includes:

[0108] An initial illumination 3D model is constructed, and the position information corresponding to each target at each time point is determined based on the inertial navigation data;

[0109] The location information is input into the initial illumination 3D model to obtain the high beam illumination 3D model corresponding to each target time.

[0110] As an optional embodiment of this specification, determining the target illuminance range corresponding to each of the light pattern data based on each of the three-dimensional models of the high beam illumination includes:

[0111] Determine the coordinates of the excitation vehicle in each of the aforementioned location information;

[0112] Based on the three-dimensional model of each high beam illumination, the target illuminance range corresponding to the coordinates of each excitation vehicle is determined.

[0113] As an optional embodiment of this specification, determining the theoretical glare range affected by the excitation vehicle at each of the target times includes:

[0114] The driving scenario type for each target time point is determined based on the test data.

[0115] The theoretical glare range of the excitation vehicle at each of the target times is determined based on the type of driving scenario.

[0116] As an optional embodiment of this specification, the comparison of the paired target illuminance ranges and the theoretical glare-affected ranges includes:

[0117] The similarity between the target illuminance range and the theoretical glare influence range is calculated based on a similarity algorithm.

[0118] Each similarity is compared with a preset similarity value to obtain a comparison result.

[0119] As an optional embodiment of this specification, determining the glare test result of the adaptive high beam based on the comparison results includes:

[0120] When all the comparison results indicate that the similarity is less than the preset similarity value, the glare test result of the adaptive high beam is determined to meet the preset requirements;

[0121] When at least one of the comparison results indicates that the similarity is not less than the preset similarity value, the glare test result of the adaptive high beam is determined to be unsatisfactory.

[0122] This specification also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0123] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0124] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0125] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0126] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0127] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0128] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0129] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0130] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

Claims

1. A method for testing the glare coordination of adaptive high beam headlights, characterized in that, The method includes: Acquire test data of the target vehicle during field testing. The test data includes inertial navigation data and bus data. The inertial navigation data is used to characterize the position information of the target vehicle and the excitation vehicle at each test moment. The bus data is used to characterize the working information of the adaptive high beam of the target vehicle at each test moment. Based on the bus data, a darkroom lighting test is performed on the target vehicle to obtain light pattern data corresponding to at least two target times, wherein the working information corresponding to the target times is in the on state. Based on the inertial navigation data, construct a three-dimensional model of the high beam illumination corresponding to each target time, and determine the target illuminance range corresponding to each light pattern data based on each three-dimensional model of the high beam illumination. The theoretical glare-affected range of the excitation vehicle at each of the target times is determined, and the target illuminance range and the theoretical glare-affected range are compared in pairs. Based on the comparison results, the glare test results of the adaptive high beam are determined. The step of comparing the paired target illuminance ranges with the theoretical glare-affected ranges includes: The similarity between the target illuminance range and the theoretical glare-affected range is calculated based on a similarity algorithm. Each of the aforementioned similarities is compared with a preset similarity value to obtain the comparison results; The determination of the glare test results of the adaptive high beam based on each comparison result includes: When all the comparison results indicate that the similarity is less than the preset similarity value, the glare test result of the adaptive high beam is determined to meet the preset requirements; When at least one of the comparison results indicates that the similarity is not less than the preset similarity value, the glare test result of the adaptive high beam is determined to be unsatisfactory.

2. The method according to claim 1, characterized in that, The step of performing a darkroom lighting test on the target vehicle based on the bus data to obtain light pattern data corresponding to at least two target times includes: Based on the bus data, determine the high beam operation commands corresponding to at least two target times; According to the high beam operation commands, a darkroom lighting test is performed on the target vehicle to obtain the light pattern data corresponding to each target time.

3. The method according to claim 1, characterized in that, The construction of a three-dimensional model of the high beam illumination corresponding to each target time based on the inertial navigation data includes: An initial illumination 3D model is constructed, and the position information corresponding to each target at each time point is determined based on the inertial navigation data; The location information is input into the initial illumination 3D model to obtain the high beam illumination 3D model corresponding to each target time.

4. The method according to claim 3, characterized in that, The determination of the target illuminance range corresponding to each of the light pattern data based on the three-dimensional model of each high beam illumination includes: Determine the coordinates of the excitation vehicle in each of the aforementioned location information; Based on the three-dimensional model of each high beam illumination, the target illuminance range corresponding to the coordinates of each excitation vehicle is determined.

5. The method according to claim 1, characterized in that, Determining the theoretical glare range affected by the excitation vehicle at each of the target times includes: The driving scenario type for each target time point is determined based on the test data. The theoretical glare range of the excitation vehicle at each of the target times is determined based on the type of driving scenario.

6. A glare coordination testing device for adaptive high beam headlights, characterized in that, The device includes: The acquisition module is used to acquire test data of the target vehicle in the field test. The test data includes inertial navigation data and bus data. The inertial navigation data is used to characterize the position information of the target vehicle and the excitation vehicle at each test moment. The bus data is used to characterize the working information of the adaptive high beam of the target vehicle at each test moment. The testing module is used to perform a darkroom lighting test on the target vehicle based on the bus data, and obtain light pattern data corresponding to at least two target times, wherein the working information corresponding to the target times is in the on state; The construction module is used to construct a three-dimensional model of the high beam illumination corresponding to each target time based on the inertial navigation data, and to determine the target illuminance range corresponding to each light pattern data based on each three-dimensional model of the high beam illumination. The determination module is used to determine the theoretical glare-affected range of the excitation vehicle at each of the target times, and compare the target illuminance range and the theoretical glare-affected range that are paired up in each pair, and determine the glare test result of the adaptive high beam based on the comparison results. Specifically, the determination module is also used for: The similarity between the target illuminance range and the theoretical glare influence range is calculated based on a similarity algorithm. Each of the aforementioned similarities is compared with a preset similarity value to obtain the comparison results; The module is also specifically used for: When all the comparison results indicate that the similarity is less than the preset similarity value, the glare test result of the adaptive high beam is determined to meet the preset requirements; When at least one of the comparison results indicates that the similarity is not less than the preset similarity value, the glare test result of the adaptive high beam is determined to be unsatisfactory.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, the computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform the steps of the method as claimed in any one of claims 1-5.

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