Intelligent vehicle lamp dark area size verification system and method
By arranging photosensitive sensors and simulation testing systems around the vehicle, automated verification of dark area size is achieved, solving the problem of inaccurate dark area coverage in the ADB system, and improving driving safety and testing accuracy.
Patent Information
- Application Number
- CN202411123347.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-15
- Publication Date
- 2024-12-20
AI Technical Summary
When the existing ADB system generates dark areas, due to signal transmission and processing delays, the dark areas cannot accurately cover the vehicles in front of them, which may cause dazzling phenomena and affect driving safety. Moreover, conventional testing methods cannot accurately verify the size of the dark areas.
The intelligent light dark area size verification system is adopted. By arranging a photosensitive sensor around the vehicle, combining a simulation test system and an assisted driving module, the dark area size is automatically judged and verified, and the photosensitive sensor is used to collect actual lighting data in real time and output test reports.
Accurate automated testing and verification of dark area size is achieved, avoiding the inaccuracy of driver subjective judgments and improving vehicle driving safety and testing reliability.
Smart Images
Figure CN119172907A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of simulation test technology, and more specifically, to an intelligent vehicle lamp dark area size verification system and method. Background Art
[0002] ADB (Adaptive Driving Beam) is a technology that can adaptively control the vehicle's high beam according to the vehicle's driving status and driving environment. The ADB system is an advanced lighting system that uses advanced sensors, control units and actuators to automatically adjust the lighting range, brightness and angle according to factors such as the vehicle's driving status, road conditions and weather conditions to adapt to different driving environments. This technology can identify the distance, angle and other position information between the vehicle in front and the vehicle based on the camera sensor, and control the vehicle's high beam based on this position information to generate a dark area in the area where the vehicle in front is located to prevent dazzling the vehicle in front.
[0003] In the process of collecting the position information of the vehicle in front, both signal transmission and signal processing require a certain amount of time, which will cause a certain lag between the time when the dark area is generated and the time when the position information of the vehicle in front is collected. As a result, the generated dark area cannot accurately cover the area where the vehicle in front is located. Therefore, it may still cause dazzling problems to the vehicle in front, affecting the driving safety of the vehicle.
[0004] Therefore, in practical applications, in order to ensure the safety and reliability of the system, it needs to be fully and effectively tested. At present, ADB tests are divided into real vehicle and simulation tests. The simulation test method is mainly based on the scene simulation software to establish a scene library test and evaluation. However, conventional test methods cannot test and verify the size of the dark area of the real target vehicle. It can only be judged subjectively by the driver's naked eye, and the size of the dark area cannot be accurately verified.
[0005] To this end, in combination with the above requirements and the defects of the prior art, the present application proposes an intelligent vehicle headlight dark area size verification system and method. Summary of the invention
[0006] The present invention provides an intelligent vehicle lamp dark area size verification system and method, which can automatically determine the size of the dark area through photosensitive sensors arranged around the vehicle, thereby completing the test verification of the dark area size of the real target vehicle.
[0007] The primary purpose of the present invention is to solve the above technical problems. The technical solution of the present invention is as follows:
[0008] The first aspect of the present invention provides an intelligent vehicle headlight dark area size verification system, comprising: a simulation test system, an auxiliary driving module, a light controller and a photosensitive sensor module; the simulation test system constructs a simulation environment, performs automated testing according to the parameters of the vehicle to be tested, and outputs Ethernet data, bus data and video data to the auxiliary driving module; the auxiliary driving module integrates an adaptive high beam software algorithm, sends a light control signal to the light controller according to the received data, the light controller is connected to the left and right headlights of the vehicle to be tested, and transmits the parameter data and light control signal of the headlights to the simulation test system through the bus; the photosensitive sensor module is composed of a plurality of photosensitive sensors arranged around the vehicle to be tested, and is used to transmit the actual light data emitted by the headlights of the vehicle to be tested to the simulation test system.
[0009] Furthermore, the simulation test system includes a scene simulation system, a vehicle dynamics system and an automated test system; the scene simulation system is used to construct road scenes and vehicle scenes in virtual scenes, and to construct a joint simulation with a light controller; the vehicle dynamics system simulates the acceleration, braking and steering of the vehicle by collecting or presetting the parameters of the vehicle to be tested; the automated test module performs automated testing on the size of the dark area of the headlights of the vehicle to be tested according to the parameter data returned by the light controller, and automatically determines the automated test results of the dark area size according to the actual light data collected by the photosensitive sensor module, and outputs a test report.
[0010] Furthermore, the simulation test system transmits the data in the simulation scene constructed by the scene simulation system to the assisted driving module through a video board, an Ethernet board or a bus board. The assisted driving module integrates an ADB algorithm and sends a lighting control signal to the lighting control system through a bus board according to the data in the simulation scene. The lighting control system controls the left and right headlights of the vehicle to be tested to turn on according to the lighting control signal, and sends the lighting angle and illumination value data to the simulation test system through the bus board.
[0011] Furthermore, the photosensitive sensor module is set according to the joint simulation scene constructed by the scene simulation system, and the collected data is transmitted to the simulation test system via an Ethernet board or a bus board.
[0012] A second aspect of the present invention provides a method for verifying the size of a dark area of an intelligent vehicle headlight, which is used in the intelligent vehicle headlight dark area verification system. The method comprises the following steps:
[0013] S1. A test scenario is constructed in a simulation test system according to the parameters of the vehicle to be tested. The auxiliary driving module controls the light controller to perform corresponding operations according to the test scenario and returns a light control signal to the simulation test system.
[0014] S2. Develop an automated test script and set up the photosensitive sensor module according to the test requirements of the test scenario.
[0015] S3. Execute the automated test script, compare the test result with the actual light data collected by the photosensitive sensor module, and output a test report.
[0016] Furthermore, the test scene includes a meeting and overtaking scene, and the process of setting the photosensitive sensor module is to set a number of photosensitive sensors around the vehicle to be tested, and 2n photosensitive sensors are evenly arranged horizontally at a distance of s1 from the vehicle to be tested in the driving direction of the vehicle to be tested, and the setting range is to take the central axis of the vehicle to be tested as the origin, , where D1 represents the width of the vehicle to be tested, and s represents the preset dark area size deviation value; the photosensitive sensor collects the actual light emitted by the headlights of the vehicle to be tested, and transmits the actual light data to the simulation test system.
[0017] Furthermore, the specific process of step S2 is:
[0018] S21. Configure the lighting effects of the test scene based on the IES file of the actual lighting.
[0019] S22. The simulation test system performs a scene dynamic simulation according to the configured lighting effects, and outputs the photosensitive sensor layout requirements, and sets the photosensitive sensors around the vehicle to be tested according to the layout requirements.
[0020] S23. Write the ADB algorithm to be verified into the assisted driving module, use the test scene data output by the simulation test system as the input signal of the assisted driving module, build a joint simulation, and return the actual light data collected by the photosensitive sensor module in real time.
[0021] Furthermore, the parameters in the IES file of the actual light include: effective light emitting angle, brightness limit curve, regional luminous flux and spatial light intensity distribution curve; the lighting effect of the test scene includes: number of light sources, light value and light emitting angle; the value of the light data returned by the photosensitive sensor when sensing light is I n =1, when no light is sensed, the value of the light data returned is I n =0.
[0022] Furthermore, the development of automated test scripts specifically includes: conducting a demand analysis on the test requirement specification, specifying a test plan and test scheme, setting up a test environment and designing test cases according to the test requirements, writing test scripts, and inputting them into the test scenario constructed by the joint simulation for automated testing, and determining whether the test passes according to preset conditions. If so, analyzing the test results and outputting a test report; otherwise, outputting the error type and error content, and performing a corrected regression automated test on the automated test script.
[0023] Furthermore, in step S3, the set photosensitive sensors are numbered, wherein the value of the light data returned by the xth photosensitive sensor is 1, and the value of the light data returned by the x+1th photosensitive sensor is 0, then the actual dark area size angle calculation process is as follows:
[0024]
[0025] Wherein, D1 represents the width of the vehicle to be tested, s represents the preset dark area size deviation value, and s1 represents the vertical distance between the photosensitive sensor and the vehicle to be tested.
[0026] According to the actual dark area angle a' and the dark area angle a output by the simulation test system, the actual angle error Δa of the algorithm is calculated. The calculation process is:
[0027]
[0028] Among them, when the actual error of the algorithm is less than or equal to the preset dark area size deviation value, the test result is passed, and when the actual error of the algorithm is greater than the preset dark area size deviation value, the test result is failed.
[0029] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:
[0030] The present invention provides an intelligent vehicle lamp dark area size verification system and method. Based on a constructed simulation environment, photosensitive sensors are arranged around the vehicle to be tested. The actual light data transmitted back in real time by the photosensitive sensors is used to automatically determine whether the dark area size calculation is accurate through automated testing. The dark area size can be determined through intelligent light testing without the need for subjective judgment by the driver's naked eyes. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] Figure 1 The figure is a schematic diagram of an intelligent vehicle light dark area size verification system according to the present invention.
[0032] Figure 2 The present invention is a flow chart of a method for verifying the size of a dark area of an intelligent vehicle lamp.
[0033] Figure 3 The present invention is a flowchart of an automated test in an embodiment of the present invention.
[0034] Figure 4 A flowchart of developing an automated test script in an embodiment of the present invention.
[0035] Figure 5 It is a schematic diagram of configuring the lighting effect of a test scene according to an IES file of actual lighting in an embodiment of the present invention. DETAILED DESCRIPTION
[0036] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.
[0037] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.
[0038] Example 1
[0039] like Figure 1 As shown, the present invention provides an intelligent vehicle lamp dark area size verification system, comprising: a simulation test system, an auxiliary driving module, a light controller and a photosensitive sensor module; the simulation test system constructs a simulation environment, performs automatic testing according to the parameters of the vehicle to be tested, and outputs Ethernet data, bus data and video data to the auxiliary driving module; the auxiliary driving module integrates an adaptive high beam software algorithm, sends a light control signal to the light controller according to the received data, the light controller is connected to the left and right headlights of the vehicle to be tested, and transmits the parameter data and light control signal of the headlights to the simulation test system through the bus; the photosensitive sensor module is composed of a plurality of photosensitive sensors arranged around the vehicle to be tested, and is used to transmit the actual light data emitted by the headlights of the vehicle to be tested to the simulation test system.
[0040] Furthermore, the simulation test system includes a scene simulation system, a vehicle dynamics system and an automated test system; the scene simulation system is used to construct road scenes and vehicle scenes in virtual scenes, and to construct a joint simulation with a light controller; the vehicle dynamics system simulates the acceleration, braking and steering of the vehicle by collecting or presetting the parameters of the vehicle to be tested; the automated test module performs automated testing on the size of the dark area of the headlights of the vehicle to be tested according to the parameter data returned by the light controller, and automatically determines the automated test results of the dark area size according to the actual light data collected by the photosensitive sensor module, and outputs a test report.
[0041] Furthermore, the simulation test system transmits the data in the simulation scene constructed by the scene simulation system to the assisted driving module through a video board, an Ethernet board or a bus board. The assisted driving module integrates an ADB algorithm and sends a lighting control signal to the lighting control system through a bus board according to the data in the simulation scene. The lighting control system controls the left and right headlights of the vehicle to be tested to turn on according to the lighting control signal, and sends the lighting angle and illumination value data to the simulation test system through the bus board.
[0042] Furthermore, the photosensitive sensor module is set according to the joint simulation scene constructed by the scene simulation system, and the collected data is transmitted to the simulation test system via an Ethernet board or a bus board.
[0043] According to the above technical features, the present invention develops a photosensitive sensor in a virtual scene, which is arranged around the target vehicle. It can detect the light value sent by the vehicle in real time, so as to judge whether the size of the dark area given by the algorithm is reasonable, solving the problem that the size of the dark area cannot be accurately judged in the industry.
[0044] Example 2
[0045] Based on the above embodiment 1, combined with Figure 2-Figure 4 , this embodiment describes in detail the second aspect of the present invention.
[0046] like Figure 2 As shown, the second aspect of the present invention provides a method for verifying the size of a dark area of an intelligent vehicle headlight, which is used in the intelligent vehicle headlight dark area verification system. The method comprises the following steps:
[0047] S1. A test scenario is constructed in a simulation test system according to the parameters of the vehicle to be tested. The auxiliary driving module controls the light controller to perform corresponding operations according to the test scenario and returns a light control signal to the simulation test system.
[0048] S2. Develop an automated test script and set up the photosensitive sensor module according to the test requirements of the test scenario.
[0049] S3. Execute the automated test script, compare the test result with the actual light data collected by the photosensitive sensor module, and output a test report.
[0050] Furthermore, the test scene includes a meeting and overtaking scene, and the process of setting the photosensitive sensor module is to set a number of photosensitive sensors around the vehicle to be tested, and 2n photosensitive sensors are evenly arranged horizontally at a distance of s1 from the vehicle to be tested in the driving direction of the vehicle to be tested, and the setting range is to take the central axis of the vehicle to be tested as the origin, , where D1 represents the width of the vehicle to be tested, and s represents the preset dark area size deviation value; the photosensitive sensor collects the actual light emitted by the headlights of the vehicle to be tested, and transmits the actual light data to the simulation test system.
[0051] Furthermore, if Figure 3 As shown, the specific process of step S2 is:
[0052] S21. Configure the lighting effects of the test scene based on the IES file of the actual lighting.
[0053] S22. The simulation test system performs a scene dynamic simulation according to the configured lighting effects, and outputs the photosensitive sensor layout requirements, and sets the photosensitive sensors around the vehicle to be tested according to the layout requirements.
[0054] S23. Write the ADB algorithm to be verified into the assisted driving module, use the test scene data output by the simulation test system as the input signal of the assisted driving module, build a joint simulation, and return the actual light data collected by the photosensitive sensor module in real time.
[0055] Furthermore, the parameters in the IES file of the actual light include: effective light emitting angle, brightness limit curve, regional luminous flux and spatial light intensity distribution curve; the lighting effect of the test scene includes: number of light sources, light value and light emitting angle; the value of the light data returned by the photosensitive sensor when sensing light is I n =1, when no light is sensed, the value of the light data returned is I n =0.
[0056] Furthermore, if Figure 4 As shown, the development of automated test scripts specifically includes: conducting a demand analysis on the test requirement specification, specifying a test plan and test scheme, setting up a test environment and designing test cases according to the test requirements, writing a test script, and inputting it into the test scenario constructed by the joint simulation for automated testing, and judging whether the test passes according to preset conditions. If so, analyzing the test results and outputting a test report; otherwise, outputting the error type and error content, and performing regression automated testing on the automated test script after correction.
[0057] Furthermore, in step S3, the set photosensitive sensors are numbered, wherein the value of the light data returned by the xth photosensitive sensor is 1, and the value of the light data returned by the x+1th photosensitive sensor is 0, then the actual dark area size angle calculation process is as follows:
[0058]
[0059] Wherein, D1 represents the width of the vehicle to be tested, s represents the preset dark area size deviation value, and s1 represents the vertical distance between the photosensitive sensor and the vehicle to be tested.
[0060] According to the actual dark area angle a' and the dark area angle a output by the simulation test system, the actual angle error Δa of the algorithm is calculated. The calculation process is:
[0061]
[0062] When the actual error of the algorithm is less than or equal to the preset dark area size deviation value, the test result is passed; when the actual error of the algorithm is greater than the preset dark area size deviation value, the test result is failed.
[0063] Example 3
[0064] Based on Example 1 and Example 2, the present invention describes in detail the process of performing automated testing of the present invention.
[0065] a. First, the simulation test system includes the scenario simulation system VTD, the vehicle dynamics system CARSIM and the automated test system ECUTEST.
[0066] VTD software: In this software, you can build the traffic participation elements required in the ADB function, such as roads, vehicles, LSC-GUI interface, VIG interface photosensitive sensors, etc.
[0067] CARSIM dynamics software: This software can simulate the acceleration, braking, steering and other vehicle parameters of the actual vehicle.
[0068] ECUTESU: This automation software can receive the bus data of the actual lighting, the angle and light value data from the scene simulation system, and the data of the photosensor, and then compare the input and output data to produce a test report.
[0069] b. The ADB software algorithm is integrated into the ADAS controller.
[0070] c. The lighting controller integrates the real lighting controller and left and right lighting actuators.
[0071] First, build the scenarios that need to be tested in the simulation system, such as meeting and overtaking scenarios, install photosensitive sensors around the vehicle, and send the data in the scene to the ADAS controller through the video board, Ethernet board, and bus board. The ADAS controller then controls the light controller and actuator in the dark area based on the scene information. Finally, through the collection of bus data, the actual results are fed back to the ECUTESU automated testing tool in the test system. ECUTEST automatically tests the data of the photosensitive sensor and the bus data and quickly gives a test report.
[0072] In order to restore the optical effect of real lights 100%, the LSC-GUI interface is configured according to the parameters such as the effective light angle, brightness limit curve, regional luminous flux, and spatial light intensity distribution curve defined in the IES file of the actual lights. In the LSC interface, 100 LED configuration options are set on the left and right, and the light angle, brightness and other parameters of each LED can be controlled individually. According to the lighting value and the number of street lights, a virtual simulation test scene is built using scene simulation software, including OPENDRIVE static road creation and OPENSCENARIO dynamic scene creation. For example, at night, in a two-lane scene, an experiment of a two-car meeting scene is conducted to form a scene such as Figure 5 The light VIG visualization interface is shown.
[0073] Then, the software of the ADAS controller is flashed, the ADB algorithm that needs to be verified is downloaded to the controller, the signal request of the input end of the control algorithm is given to the controller through the scenario software, a joint simulation is established, the photosensitive sensor model value is returned in real time, and automated testing is performed through the ECUTEST automated testing software.
[0074] In the embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium, which, when executed, executes the steps of the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media capable of storing program codes.
[0075] Alternatively, if the above-mentioned embodiments of the present invention are implemented in the form of software function modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media capable of storing program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.
[0076] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. The icons describing the structural positional relationships in the accompanying drawings are only used for exemplary purposes and are not to be construed as limiting the present invention. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and is not possible to list all the embodiments here. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the claims of the present invention.
Claims
1. An intelligent vehicle headlight dark area size verification system, characterized in that: The invention comprises: a simulation test system, an auxiliary driving module, a light controller and a photosensitive sensor module; the simulation test system constructs a simulation environment, performs automatic testing according to the parameters of the vehicle to be tested, and outputs Ethernet data, bus data and video data to the auxiliary driving module; the auxiliary driving module integrates an adaptive high beam software algorithm, sends a light control signal to the light controller according to the received data, the light controller is connected to the left and right headlights of the vehicle to be tested, and transmits the parameter data and light control signal of the headlights to the simulation test system through the bus; the photosensitive sensor module is composed of a plurality of photosensitive sensors arranged around the vehicle to be tested, and is used to transmit the actual light data emitted by the headlights of the vehicle to be tested to the simulation test system.
2. The intelligent vehicle headlight dark area size verification system according to claim 1, characterized in that: The simulation test system includes a scene simulation system, a vehicle dynamics system and an automated test system; the scene simulation system is used to construct a road scene and a vehicle scene in a virtual scene, and to construct a joint simulation with a lighting controller; The vehicle dynamics system simulates the acceleration, braking and steering of the vehicle by collecting or presetting the parameters of the vehicle to be tested; The automated testing module performs automated testing on the size of the dark area of the headlights of the vehicle to be tested according to the parameter data returned by the lighting controller, and automatically determines the automated testing result of the size of the dark area according to the actual lighting data collected by the photosensitive sensor module, and outputs a test report.
3. The intelligent vehicle headlight dark area size verification system according to claim 2, characterized in that: The simulation test system transmits the data in the simulation scene constructed by the scene simulation system to the auxiliary driving module through a video board, an Ethernet board or a bus board. The auxiliary driving module integrates an ADB algorithm and sends a light control signal to the light control system through a bus board according to the data in the simulation scene. The light control system controls the left and right headlights of the vehicle to be tested to turn on according to the light control signal, and sends the light angle and illumination value data to the simulation test system through the bus board.
4. The intelligent vehicle headlight dark area size verification system according to claim 3, characterized in that: The photosensitive sensor module is set according to the joint simulation scene constructed by the scene simulation system, and the collected data is transmitted to the simulation test system via an Ethernet board or a bus board.
5. An intelligent vehicle light dark area size verification method, characterized in that: The following steps are involved: S1. Construct a test scenario in a simulation test system according to the parameters of the vehicle to be tested. The auxiliary driving module controls the light controller to perform corresponding operations according to the test scenario and returns a light control signal to the simulation test system. S2. Develop automated test scripts and set up light sensor modules according to the test requirements of the test scenario; S3. Execute the automated test script, compare the test result with the actual light data collected by the photosensitive sensor module, and output a test report.
6. The method for verifying the size of the dark area of an intelligent vehicle headlight according to claim 5, characterized in that: The test scenarios include meeting and overtaking scenarios. The process of setting the photosensitive sensor module is to set a number of photosensitive sensors around the vehicle to be tested. 2n photosensitive sensors are evenly set horizontally at a distance of s1 from the vehicle to be tested in the driving direction of the vehicle to be tested. The setting range is to take the central axis of the vehicle to be tested as the origin. , where D1 represents the width of the vehicle to be tested, and s represents the preset dark area size deviation value; the photosensitive sensor collects the actual light emitted by the headlights of the vehicle to be tested, and transmits the actual light data to the simulation test system.
7. The method for verifying the size of the dark area of an intelligent vehicle headlight according to claim 6, characterized in that: The specific process of step S2 is: S21, configure the lighting effects of the test scene based on the IES file of the actual lighting; S22, the simulation test system performs a scene dynamic simulation according to the configured lighting effects, and outputs the photosensitive sensor layout requirements, and sets the photosensitive sensors around the vehicle to be tested according to the layout requirements; S23. Write the ADB algorithm to be verified into the assisted driving module, use the test scene data output by the simulation test system as the input signal of the assisted driving module, build a joint simulation, and return the actual light data collected by the photosensitive sensor module in real time.
8. The intelligent vehicle light dark area size verification method according to claim 7, characterized in that: The parameters in the IES file of the actual light include: effective light emitting angle, brightness limit curve, regional luminous flux and spatial light intensity distribution curve; the lighting effect of the test scene includes: number of light sources, light value and light emitting angle; the value of the light data returned by the photosensitive sensor when sensing light is I n =1, when no light is sensed, the value of the light data returned is I n =0.
9. The intelligent vehicle light dark area size verification method according to claim 8, characterized in that: The development of automated test scripts specifically includes: conducting a requirements analysis on the test requirements specification, specifying a test plan and test scheme, building a test environment and designing test cases according to the test requirements, writing a test script, inputting it into the test scenario constructed by the joint simulation for automated testing, judging whether the test is passed according to preset conditions, and if so, analyzing the test results and outputting a test report; Otherwise, output the error type and error content, and perform regression automated testing on the corrected automated testing script.
10. The intelligent vehicle light dark area size verification method according to claim 9, characterized in that: In step S3, the set photosensitive sensors are numbered, wherein the value of the light data returned by the xth photosensitive sensor is 1, and the value of the light data returned by the x+1th photosensitive sensor is 0, and the actual dark area size angle calculation process is as follows: Wherein, D1 represents the width of the vehicle to be tested, s represents the preset dark area size deviation value, and s1 represents the vertical distance between the photosensitive sensor and the vehicle to be tested; According to the actual dark area angle a' and the dark area angle a output by the simulation test system, the actual angle error Δa of the algorithm is calculated. The calculation process is: Among them, when the actual error of the algorithm is less than or equal to the preset dark area size deviation value, the test result is passed, and when the actual error of the algorithm is greater than the preset dark area size deviation value, the test result is failed.