Vehicle lamp control method, vehicle and storage medium

Abstract

The invention discloses a vehicle lamp control method, a vehicle and a storage medium. The method comprises the following steps: acquiring an environment image; identifying a passive reflective area in the environment image, and obtaining the reflection intensity of the passive reflective area; according to the reflection intensity, obtaining the position and the area of the passive light reflection area so as to generate a vehicle lamp control instruction corresponding to the environment image; and controlling the matrix type vehicle lamp according to the vehicle lamp control instruction. By detecting the passive reflective area on the road surface according to different complex road conditions and then generating the corresponding vehicle lamp control instruction according to the position and the area of the passive reflective area, vehicle lamp control can be effectively achieved under the condition that the reflective area exists in front of the vehicle, and then driving safety is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a vehicle light control method, a vehicle and a storage medium. Background Art

[0002] With the development of society and the advancement of technology, the high beam, low beam and directional headlights of vehicles can no longer meet people's growing demand for driving safety. Therefore, intelligent and efficient headlights came into being. This type of headlight can provide a larger lighting range and distance, while also improving the lighting blind spots of traditional headlights, thereby significantly improving driving safety.

[0003] However, in severe weather conditions, if there are reflective areas such as water accumulation areas, ice and snow covered roads, glass and mirrors, traffic signs, road markings, etc. on the road, reflections will be generated when the vehicle headlights shine on these reflective areas, which may dazzle the vehicle driver, making driving more difficult and reducing driving safety. Summary of the invention

[0004] The main technical problem solved by the present application is to provide a vehicle light control method, a vehicle and a storage medium, which can effectively realize the vehicle light control when there is a reflective area in front of the vehicle, thereby improving driving safety.

[0005] In order to solve the above technical problems, a technical solution adopted by the present application is: a vehicle light control method, the method is applied to a vehicle, the vehicle includes a matrix type vehicle light, the method includes:

[0006] Collect environmental images;

[0007] Identifying a passive reflective area in the environmental image and obtaining a reflection intensity of the passive reflective area;

[0008] According to the reflection intensity, the position and area of ​​the passive reflective area are obtained to generate a vehicle light control instruction corresponding to the environmental image;

[0009] The matrix type vehicle lights are controlled according to the vehicle light control instruction.

[0010] Optionally, the step of identifying the passive reflective area in the environmental image includes:

[0011] Extracting features from the environment image to determine a road surface profile;

[0012] identifying a light source region within the road surface contour;

[0013] Filtering and edge detection are performed on the light source area to determine the passive reflective area.

[0014] Optionally, the step of extracting features from the environment image to determine the road surface contour includes:

[0015] Performing color extraction on the environment image based on a preset color model to determine the color characteristics of the road surface; wherein the color model is created by using a dimensionality reduction method;

[0016] Using a texture extraction method to extract texture from the environment image to determine road surface texture features;

[0017] The road surface profile is obtained according to the road surface color characteristics and the road surface texture characteristics.

[0018] Optionally, the step of filtering and edge detecting the light source area to determine the passive reflective area includes:

[0019] Performing morphological filtering on the light source area to obtain a filtered image;

[0020] A multi-level edge search is performed on the filtered image to obtain the passive reflective area.

[0021] Optionally, the step of obtaining the reflection intensity of the passive reflective area includes:

[0022] Binarizing the environment image to obtain a binary image;

[0023] The grayscale of the binary image is adjusted to obtain the reflection intensity of the passive reflection area.

[0024] Optionally, the step of calculating the position and area of ​​the passive reflective area according to the reflection intensity to generate a vehicle light control instruction corresponding to the environmental image includes:

[0025] Determining the center coordinates of the passive reflective area according to the reflection intensity;

[0026] Calculating at least one side length parameter of an equivalent figure of the passive reflective area according to the center coordinates;

[0027] The position and area of ​​the passive reflective region are determined according to the side length parameter to generate a vehicle light control instruction corresponding to the environmental image.

[0028] Optionally, the step of controlling the matrix headlight according to the headlight control instruction includes:

[0029] parsing the headlight control instruction to obtain at least one headlight identification of the matrix headlight;

[0030] According to the vehicle lamp identifier, the vehicle lamps in the matrix vehicle lamps are controlled to be turned off and / or the brightness is adjusted.

[0031] Optionally, the step of collecting the environment image includes:

[0032] The current weather data is acquired, so as to capture the environment image when it is detected that the current weather data meets a preset danger threshold.

[0033] In order to solve the above technical problems, another technical solution adopted by the present application is: a vehicle, the vehicle comprising:

[0034] A memory for storing executable program codes;

[0035] A processor is used to call and run the executable program code from the memory, so that the vehicle executes the vehicle light control method as described in any one of the above.

[0036] In order to solve the above technical problems, another technical solution adopted in the present application is: a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed, the vehicle light control method as described in any one of the above items is implemented.

[0037] Different from the prior art, an embodiment of the present application provides a vehicle light control method, the method comprising: collecting an environmental image; identifying a passive reflective area in the environmental image, and obtaining a reflection intensity of the passive reflective area; obtaining a position and an area of ​​the passive reflective area based on the reflection intensity to generate a vehicle light control instruction corresponding to the environmental image; and controlling the matrix vehicle light based on the vehicle light control instruction.

[0038] The beneficial effect of the embodiments of the present application is that: for different complex road conditions, the passive reflective area on the road surface is detected, and then the corresponding headlight control instructions are generated according to the position and area of ​​the passive reflective area. The headlight control can be effectively realized when there is a reflective area in front of the vehicle, thereby improving driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is a flow chart of the first embodiment of the vehicle light control method of the present application;

[0040] Figure 2 is a flow chart of a second embodiment of the vehicle light control method of the present application;

[0041] Figure 3 is a flow chart of a third embodiment of the vehicle light control method of the present application;

[0042] Figure 4 is an exemplary structural block diagram of a vehicle of the vehicle light control method of the present application;

[0043] Figure 5It is an exemplary structural block diagram of a computer-readable storage medium of the vehicle light control method of the present application. DETAILED DESCRIPTION

[0044] The present application is described in detail below with reference to the accompanying drawings and implementation methods.

[0045] See also Figure 1 , Figure 1 is a flowchart of the first embodiment of the vehicle light control method of the present application. It should be noted that if there is substantially the same result, the method of the present application is not limited to Figure 1 The process sequence shown is limited. Figure 1 As shown, the method is applied to a vehicle, the vehicle includes a matrix headlight, and the method includes:

[0046] Step S110, collecting environment images;

[0047] This embodiment takes into account that in severe weather conditions, if there are reflective areas such as water accumulation areas, ice and snow covered roads, glass and mirrors, traffic signs, road markings, etc. on the road surface, reflections will be generated when the vehicle headlights shine on these reflective areas, which may dazzle the vehicle driver, making driving more difficult for the driver and reducing driving safety.

[0048] Therefore, this embodiment detects the passive reflective area on the road surface for different complex road conditions, and then generates corresponding headlight control instructions according to the position and area of ​​the passive reflective area. It can effectively realize headlight control when there is a reflective area in front of the vehicle, thereby improving driving safety.

[0049] Specifically, the matrix headlight may be a headlight system composed of a plurality of independently controllable light sources (such as LED lights), and the brightness and switching state of each light source in the matrix headlight may be controlled to achieve complex lighting effects.

[0050] In order to ensure that the vehicle light control can be adjusted according to the current actual road environment, the vehicle can collect real-time environmental images through a camera or sensor installed in the front. The environmental image can be used to analyze and judge the current road conditions and environmental status.

[0051] Step S120, identifying a passive reflective area in the environmental image, and obtaining a reflection intensity of the passive reflective area;

[0052] Specifically, the passive reflective area can be an area that reflects light back by utilizing the illumination of an external light source, such as a water-logged area, road signs, reflective clothing, vehicles, ice-covered roads, glass mirrors, traffic signs, road markings, etc.

[0053] Step S130, obtaining the position and area of ​​the passive reflective area according to the reflection intensity, so as to generate a vehicle light control instruction corresponding to the environmental image;

[0054] Specifically, the position of the passive reflective area may be a minimum recognition distance between the current vehicle and the passive reflective area, and the area of ​​the passive reflective area may be a maximum area of ​​the passive reflective area that the current vehicle recognizes.

[0055] Since the passive reflective area can reflect light from the light source, this embodiment can draw a reflective intensity distribution diagram of the passive reflective area according to the reflection intensity by measuring and analyzing at least one reflection intensity of the passive reflective area. Then, according to the distribution of the reflective intensity, the position and area of ​​the reflective area can be determined.

[0056] Step S140: controlling the matrix headlights according to the headlight control instructions.

[0057] Specifically, the headlight control instructions can be used to adjust the brightness, angle, illumination range, etc. of the light source in the rectangular headlights. The lighting route of the rectangular headlights can be controlled to avoid reflective areas on the road surface, effectively reducing the interference of reflected and refracted light in the environment, and improving the active safety factor of the vehicle headlights, thereby improving the driving safety of the entire vehicle.

[0058] See also Figure 2 , Figure 2 1 is a flow chart of a second embodiment of the vehicle light control method of the present application. In this embodiment, the method includes the following steps:

[0059] Step S201, obtaining current weather data, and capturing the environment image when it is detected that the current weather data meets a preset danger threshold.

[0060] This embodiment takes into account that the road traffic situation in bad weather is more complicated than that in sunny days. For example, there is a water area in front of the vehicle, and the vehicle headlights shining on the water area will dazzle the vehicle driver, thereby increasing the risk of driving. Therefore, it is necessary to propose a method for effectively realizing the control of the headlights when there is a reflective area in front of the vehicle, thereby improving driving safety.

[0061] Specifically, the vehicle of this embodiment may further include a central control module, an image acquisition module, a central processing module and a light control module. The image acquisition module acquires an environmental image of the vehicle's current driving environment and sends the environmental image to the central processing module.

[0062] Weather data can be current rainfall, haze concentration, visibility and other data. These weather data may affect driving safety. For example, heavy rain, dense fog and other conditions may cause reduced visibility on the road. The danger threshold is used to determine whether the current road environment requires the light control function to be turned on. For example, when the haze concentration reaches a certain range, the light control function is turned on. Therefore, as an implementation solution, when the central control module detects that the weather data meets a certain danger threshold, it can instruct the image acquisition module to collect the current environment image in order to further analyze the road and environmental information.

[0063] As another implementation scheme, the vehicle driver can actively choose whether to turn on the headlight control function according to weather data. When the driver chooses to turn on the headlight control function, he can perform relevant operations on the headlight control function in the vehicle's central control module, such as clicking a button for the headlight control function. At this time, the central control module responds to the user's relevant operations on the headlight control function and instructs the image acquisition module to acquire the current environment image.

[0064] Step S202, extracting features from the environment image to determine the road surface profile;

[0065] Specifically, after acquiring the environmental image, the contour of the road surface can be identified by performing feature extraction on the environmental image through a deep learning model.

[0066] Step S203, identifying a light source area within the road surface contour;

[0067] Specifically, the light source area refers to the active reflective area and the passive reflective area on the road surface. This example mainly takes into account that there may be active light sources and passive light sources on the road surface. Passive light sources may cause glare in actual driving, thereby affecting the driving field of vision. Therefore, by identifying the light source area within the road surface contour, the active light source and the passive light source are further distinguished to determine the passive reflective area.

[0068] Step S204: filtering and edge detection are performed on the light source area to determine the passive reflection area.

[0069] Specifically, this embodiment takes into account that there are active light sources and passive light sources on the road surface, so it is necessary to distinguish the difference between active light sources and passive light sources for classification. By filtering and edge detection of the light source area, the noise in the light source area can be reduced and the boundary of the object can be determined, and the passive reflective area can be accurately identified and determined. These reflective areas may be caused by the reflection of car lights in the water area on the road surface.

[0070] Among them, the reflection of the road at night mainly comes from car lights, which are generally light sources with high color temperature and high brightness. The illumination characteristics of reflective light sources and active light sources are different. Therefore, the different characteristics of the light sources can be determined and the active light sources and passive light sources can be screened.

[0071] Step S205, binarizing the environment image to obtain a binarized image;

[0072] Specifically, this embodiment takes the environment image obtained by the Advanced Driver Assistance Systems (ADAS) camera in the image acquisition module as an example, and the ADAS camera sets the image region of interest (ROI) and copies the image to obtain a cropped image. Then, the grayscale value of the pixel point of the cropped image is set to 0 or 255, that is, the entire image presents an obvious black and white effect, so that the outline of the reflective area can be highlighted.

[0073] Step S206, grayscale adjustment is performed on the binary image to obtain the reflection intensity of the passive reflection area.

[0074] Specifically, since the passive reflective areas on the road surface may have different brightness conditions, it is necessary to implement adaptive grayscale adjustment of the image binarization. Based on the binary image, the grayscale is adaptively adjusted to obtain the reflection intensity data of these passive reflective areas.

[0075] Step S207, determining the center coordinates of the passive reflective area according to the reflection intensity;

[0076] Specifically, the central processing module determines the center coordinates of the passive reflective areas through the reflection intensity data, and the center coordinates can locate the specific positions of these passive reflective areas in the image.

[0077] Step S208, calculating at least one side length parameter of the equivalent figure of the passive reflective area according to the center coordinates;

[0078] Specifically, the equivalent figure can be a figure similar to the passive reflective area, and the central processing module can calculate the side length parameter of the equivalent figure of the passive reflective area according to the center coordinates of the passive reflective area. The side length parameter can characterize the shape and size of the passive reflective area.

[0079] Step S209: determining the position and area of ​​the passive reflective region according to the side length parameter to generate a vehicle light control instruction corresponding to the environmental image.

[0080] Specifically, the edge length parameter is used to determine the position and area of ​​the passive reflective area, and then the impact range and degree of the passive reflective area can be estimated to provide data for subsequent lighting control strategies.

[0081] Step S210, parsing the headlight control instruction to obtain at least one headlight identification of the matrix headlight;

[0082] Specifically, in order to determine the headlight to be controlled in the matrix headlight, the headlight to be controlled may be an LED headlight to be adjusted or turned off. The at least one headlight identification carried in the headlight control instruction is identification information corresponding to the controlled headlight in the matrix headlight.

[0083] Step S211, according to the vehicle lamp identifier, controlling the vehicle lamps in the matrix vehicle lamps to turn off and / or adjust the brightness.

[0084] Specifically, the headlight control module can determine the corresponding headlight to be controlled from the multiple headlights of the matrix headlight according to at least one headlight identifier, and then control these headlights to turn off and / or adjust the brightness. Therefore, when the headlights irradiating the passive reflective area are turned off or the brightness is adjusted, the headlight illumination route avoids the passive reflective area on the driving road surface, which can effectively reduce the interference of reflected and refracted light in the environment, improve the active safety factor of the vehicle headlights, and thus improve the driving safety of the entire vehicle.

[0085] This embodiment detects the road surface contour ahead in real time through features, determines the passive reflective area according to the road surface contour, and further determines the center position information and area of ​​the passive reflective area. The visual perception module uses the position information of the passive reflective area to achieve real-time adaptive reflection weakening control of the passive reflective area to prevent the strong reflection in the passive reflective area from dazzling the oncoming vehicle drivers. The brightness and pixels are used to judge the road conditions on complex roads, and identification and judgment are performed, so as to achieve adaptive weakening of the passive reflective area by the headlights to prevent the strong reflection caused by the passive reflective area from dazzling the vehicle drivers.

[0086] See also Figure 3 , Figure 3 1 is a flow chart of the third embodiment of the vehicle light control method of the present application. In this embodiment, the method includes the following steps:

[0087] Step S310, performing color extraction on the environment image based on a preset color model to determine the color characteristics of the road surface; wherein the color model is created by using a dimensionality reduction method;

[0088] Specifically, the material of the road surface is mainly asphalt, so the road type can be identified by extracting color feature values ​​under various road conditions based on the observed color of the road surface. More specifically, the color model can be a red-green-blue model (RGB model), a hue-saturation-intensity model (HIS model), and a hue-saturation-value model (HSV model). Since color models have a large amount of data, the principal component analysis method can be used to reduce the dimension of the data in the color model, thereby reducing the amount of calculation while maintaining important color information.

[0089] Step S320, extracting texture from the environment image using a texture extraction method to determine road surface texture features;

[0090] Specifically, since the road surface state is affected by the temperature and humidity of the ground layer and the atmosphere, it may be difficult to determine the road surface area only by color features. Therefore, the present embodiment can also identify the road surface by acquiring the texture of the road surface image. The method for extracting the road surface texture in the present embodiment can be gray level co-occurrence matrix, Gabor wavelet transform method, etc.

[0091] Step S330, obtaining the road surface profile according to the road surface color characteristics and the road surface texture characteristics.

[0092] Specifically, because pavement surfaces often have specific texture patterns, such as the granular texture of asphalt or the striations of concrete, these features can be used to distinguish between pavement areas and non-pavement areas.

[0093] Step S340, identifying a light source area within the road surface contour;

[0094] The above step S203 may be performed and will not be described in detail here.

[0095] Step S350, performing morphological filtering on the light source area to obtain a filtered image;

[0096] Specifically, the morphological processing of this embodiment can be to use digital morphology as a tool to extract image components or features for expressing and depicting the shape of the passive reflective area from the environmental image, such as the boundary, skeleton and convex hull of the passive reflective area, and also includes morphological filtering, thinning and pruning for pre-processing or post-processing. This embodiment takes Gauss filtering as an example, and in other embodiments, other filtering methods for characterizing the passive reflective area can also be used.

[0097] Step S360, performing a multi-level edge search on the filtered image to obtain the passive reflective area.

[0098] Specifically, the light sources of road traffic scenes are complex, and the reflective area of ​​​​the accumulated water mainly comes from the road surface. Therefore, it is necessary to determine the reflective area of ​​the reflective road surface. The road surface can be identified by its color and surface texture, and the edge area can be extracted.

[0099] Performing a multi-level edge search on the filtered image can more accurately detect the edge of the passive reflective area. The passive reflective area usually has obvious brightness changes in the image. These details can be captured through multi-level edge search, thereby identifying the passive reflective area. Among them, the multi-level edge search can identify as many actual edges in the image as possible, and the probability of missing the real edge and the probability of falsely detecting non-edges are as small as possible; then, the position of the detected edge point is closest to the position of the actual edge point, or the degree to which the detected edge deviates from the real edge of the object due to noise is minimized; the edge points detected by the operator correspond one-to-one to the edge points of the actual passive reflective area. Among them, this embodiment takes Canny edge detection as an example, and it can also be used to search for the edge of the passive reflective area in other embodiments.

[0100] This embodiment extracts the texture and color features of the road from the environmental image to determine the contour of the road. At the same time, through morphological filtering and multi-level edge search, passive reflective areas can be identified, which can help accurately identify and segment the road and its related areas in the image, providing important image processing support for applications such as autonomous driving and road monitoring, thereby improving the accuracy of headlight control.

[0101] See also Figure 4 , Figure 4 is an exemplary structural block diagram of a vehicle of the vehicle light control method of the present application. Figure 4 As shown, the vehicle 400 of the present application may include a processor 401 and a memory 402, wherein the processor 401 and the memory 402 communicate with each other via a bus. The memory 402 stores program instructions for controlling the headlights. When the program instructions are executed by the processor 401, the method steps described in the above text in combination with the accompanying drawings are implemented: collecting an environmental image; identifying a passive reflective area in the environmental image, and obtaining the reflection intensity of the passive reflective area; obtaining the position and area of ​​the passive reflective area according to the reflection intensity to generate a headlight control instruction corresponding to the environmental image; and controlling the matrix headlight according to the headlight control instruction.

[0102] Optionally, the processor 401 performs the step of identifying the passive reflective area in the environmental image, including:

[0103] Extracting features from the environment image to determine a road surface profile;

[0104] identifying a light source region within the road surface contour;

[0105] Filtering and edge detection are performed on the light source area to determine the passive reflective area.

[0106] Optionally, the processor 401 performs the step of extracting features from the environment image to determine the road surface contour, including:

[0107] Performing color extraction on the environment image based on a preset color model to determine the color characteristics of the road surface; wherein the color model is created by using a dimensionality reduction method;

[0108] Using a texture extraction method to extract texture from the environment image to determine road surface texture features;

[0109] The road surface profile is obtained according to the road surface color characteristics and the road surface texture characteristics.

[0110] Optionally, the processor 401 performs filtering and edge detection on the light source area to determine the passive reflection area, including:

[0111] Performing morphological filtering on the light source area to obtain a filtered image;

[0112] A multi-level edge search is performed on the filtered image to obtain the passive reflective area.

[0113] Optionally, the processor 401 executes the step of obtaining the reflection intensity of the passive reflective area, including:

[0114] Binarizing the environment image to obtain a binary image;

[0115] The grayscale of the binary image is adjusted to obtain the reflection intensity of the passive reflection area.

[0116] Optionally, the processor 401 executes the step of calculating the position and area of ​​the passive reflective area according to the reflection intensity to generate a headlight control instruction corresponding to the environmental image, including:

[0117] Determining the center coordinates of the passive reflective area according to the reflection intensity;

[0118] Calculating at least one side length parameter of an equivalent figure of the passive reflective area according to the center coordinates;

[0119] The position and area of ​​the passive reflective region are determined according to the side length parameter to generate a vehicle light control instruction corresponding to the environmental image.

[0120] Optionally, the processor 401 executes the step of controlling the matrix headlight according to the headlight control instruction, including:

[0121] parsing the headlight control instruction to obtain at least one headlight identification of the matrix headlight;

[0122] According to the vehicle lamp identifier, the vehicle lamps in the matrix vehicle lamps are controlled to be turned off and / or the brightness is adjusted.

[0123] Optionally, the processor 401 executes the step of collecting the environment image including:

[0124] The current weather data is acquired, so as to capture the environment image when it is detected that the current weather data meets a preset danger threshold.

[0125] See also Figure 5 , Figure 5 is an exemplary structural block diagram of a computer-readable storage medium of the vehicle light control method of the present application. Figure 5 As shown, the computer-readable storage medium 500 stores a computer program 501. When the computer program 501 is executed on a computer, the computer executes the above-mentioned related method steps to implement a vehicle light control method in the above-mentioned embodiment.

[0126] The above scheme collects environmental images; identifies the passive reflective area in the environmental images to obtain the reflection intensity of the passive reflective area; obtains the position and area of ​​the passive reflective area according to the reflection intensity to generate the headlight control instruction corresponding to the environmental image; and controls the matrix headlight according to the headlight control instruction. By detecting the passive reflective area on the road surface for different complex road conditions, and then generating the corresponding headlight control instruction according to the position and area of ​​the passive reflective area, the headlight control can be effectively realized when there is a reflective area in front of the vehicle, thereby improving driving safety.

[0127] In the several embodiments provided in the present application, it should be understood that the disclosed methods, vehicles and storage media can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0128] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0129] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0130] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially 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, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a vehicle, a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

[0131] The above description is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A vehicle light control method, characterized in that: The method is applied to a vehicle, the vehicle comprising a matrix headlight, and the method comprises: Collect environmental images; Identifying a passive reflective area in the environmental image and obtaining a reflection intensity of the passive reflective area; According to the reflection intensity, the position and area of ​​the passive reflective area are obtained to generate a vehicle light control instruction corresponding to the environmental image; The matrix type vehicle lights are controlled according to the vehicle light control instruction.

2. The vehicle light control method according to claim 1, characterized in that: The step of identifying the passive reflective area in the environmental image comprises: Extracting features from the environment image to determine a road surface profile; identifying a light source region within the road surface contour; Filtering and edge detection are performed on the light source area to determine the passive reflective area.

3. The vehicle light control method according to claim 2, characterized in that: The step of extracting features from the environment image to determine the road surface contour comprises: Performing color extraction on the environment image based on a preset color model to determine the color characteristics of the road surface; wherein the color model is created by using a dimensionality reduction method; Using a texture extraction method to extract texture from the environment image to determine road surface texture features; The road surface profile is obtained according to the road surface color characteristics and the road surface texture characteristics.

4. The vehicle light control method according to claim 2, characterized in that: The step of filtering and edge detecting the light source area to determine the passive reflective area comprises: Performing morphological filtering on the light source area to obtain a filtered image; A multi-level edge search is performed on the filtered image to obtain the passive reflective area.

5. The vehicle light control method according to claim 1, characterized in that: The step of obtaining the reflection intensity of the passive reflective area comprises: Binarizing the environment image to obtain a binary image; The grayscale of the binary image is adjusted to obtain the reflection intensity of the passive reflection area.

6. The vehicle light control method according to claim 1, characterized in that: The step of calculating the position and area of ​​the passive reflective area according to the reflection intensity to generate a vehicle light control instruction corresponding to the environmental image comprises: Determining the center coordinates of the passive reflective area according to the reflection intensity; Calculating at least one side length parameter of an equivalent figure of the passive reflective area according to the center coordinates; The position and area of ​​the passive reflective region are determined according to the side length parameter to generate a vehicle light control instruction corresponding to the environmental image.

7. The vehicle light control method according to claim 1, characterized in that: The step of controlling the matrix headlight according to the headlight control instruction comprises: parsing the headlight control instruction to obtain at least one headlight identification of the matrix headlight; According to the vehicle lamp identifier, the vehicle lamps in the matrix vehicle lamps are controlled to be turned off and / or the brightness is adjusted.

8. The vehicle light control method according to claim 1, characterized in that: The step of collecting the environment image comprises: The current weather data is acquired, so as to capture the environment image when it is detected that the current weather data meets a preset danger threshold.

9. A vehicle, characterized in that: The vehicle comprises: A memory for storing executable program codes; A processor is used to call and run the executable program code from the memory, so that the vehicle executes the vehicle light control method as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, the vehicle light control method according to any one of claims 1 to 8 is implemented.

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