Vehicle control method, electronic equipment, vehicle, storage medium and computer product

Abstract

The invention discloses a vehicle control method, electronic equipment, a vehicle, a storage medium and a computer product, and relates to the technical field of vehicles, the vehicle control method is applied to the vehicle comprising an image acquisition device, and specifically comprises the steps that target image data comprising a road in front of the vehicle is shot through the image acquisition device; determining a transmissivity parameter corresponding to each pixel point in the target image data; determining a target weather type corresponding to the vehicle in combination with each transmissivity parameter; when it is detected that the target weather type is a foggy weather type, determining a current visibility grade corresponding to the foggy weather type; and determining a first speed regulation proportion according to the current visibility grade, and executing vehicle speed regulation operation according to the first speed regulation proportion. By adopting the method and the device, the electronic equipment can screen the speed regulation proportion matched with the visibility, and the running speed of the vehicle is controlled according to the speed regulation proportion.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle control method, electronic equipment, vehicle, storage medium, and computer program product. Background Art

[0002] With the continuous development of the automobile industry, vehicles have become the preferred means of transportation for more and more users in their daily travel.

[0003] In related technologies, a vehicle usually relies on its own configured image acquisition device to capture the surrounding environment to obtain image data, and then determines the weather type of the current environment based on the brightness changes of the image data.

[0004] However, when the ambient light around the vehicle changes significantly, the vehicle is likely to identify the wrong weather type after acquiring image data, resulting in a lag in safety control strategies and significantly increasing driving safety risks. Summary of the Invention

[0005] The main purpose of this application is to provide a vehicle control method, electronic equipment, vehicle, storage medium and computer program product, aiming to solve the technical problem in related technologies that vehicles are prone to increase driving safety risks due to incorrect weather type identification.

[0006] To achieve the above objectives, the present application proposes a vehicle control method, which is applied to a vehicle including an image acquisition device, and includes:

[0007] capturing target image data containing the road ahead of the vehicle through the image acquisition device, and determining the transmittance parameter corresponding to each pixel point in the target image data;

[0008] Determining a target weather type corresponding to the vehicle by combining the transmittance parameters;

[0009] When the target weather type is detected to be a heavy fog weather type, determining a current visibility level corresponding to the heavy fog weather type;

[0010] A first speed adjustment ratio is determined according to the current visibility level, and a vehicle speed adjustment operation is performed according to the first speed adjustment ratio.

[0011] In one embodiment, the step of determining the target weather type corresponding to the vehicle by combining the transmittance parameters includes:

[0012] Obtaining a preset transmittance threshold, and comparing each of the transmittance parameters with the transmittance threshold to obtain a plurality of comparison results;

[0013] Determining the number of low-transmittance pixels based on the plurality of comparison results, and determining a low-visibility area and a drivable area included in the target image data when it is detected that the number of low-transmittance pixels reaches a preset threshold;

[0014] The target weather type corresponding to the vehicle is determined in combination with the low visibility area and the drivable area.

[0015] In one embodiment, the step of determining the target weather type corresponding to the vehicle based on the low visibility area and the drivable area includes:

[0016] Determining the coordinates of each first pixel included in the low-visibility area, and determining the coordinates of each second pixel included in the drivable area;

[0017] traversing each of the first pixel coordinates and each of the second pixel coordinates to determine each overlapping pixel coordinate, and determining an overlapping area ratio according to each of the overlapping pixel coordinates;

[0018] When it is detected that the overlapping area ratio reaches a preset overlapping ratio threshold, it is determined that the target weather type corresponding to the vehicle is a heavy fog weather type.

[0019] In one embodiment, the step of determining the target weather type corresponding to the vehicle by combining the transmittance parameters further includes:

[0020] Determining each cluster area included in the target image data, and determining a transmission change parameter between each cluster area based on each transmittance parameter;

[0021] determining a low visibility area and a drivable area included in the target image data when detecting that at least one transmission change parameter reaches a preset change parameter threshold;

[0022] The target weather type corresponding to the vehicle is determined in combination with the low visibility area and the drivable area.

[0023] In one embodiment, the step of determining the current visibility level corresponding to the heavy fog weather type includes:

[0024] determining a plurality of preset overlap ratios and a preset visibility level corresponding to each of the plurality of preset overlap ratios;

[0025] screening the plurality of preset overlapping ratios in combination with the overlapping area ratio to determine a target preset overlapping ratio that matches the overlapping area ratio;

[0026] The preset visibility level corresponding to the target preset overlap ratio is determined as the current visibility level corresponding to the heavy fog weather type.

[0027] In one embodiment, the step of determining the current visibility level corresponding to the heavy fog weather type further includes:

[0028] determining a front vehicle contour line contained in the target image data;

[0029] The integrity of the outline of the preceding vehicle is detected, and a current visibility level corresponding to the heavy fog weather type is determined based on the integrity.

[0030] In one embodiment, after the step of performing the vehicle speed adjustment operation according to the first speed adjustment ratio, the method further includes:

[0031] Obtaining location information corresponding to the vehicle, and determining a current road grade corresponding to the vehicle based on the location information;

[0032] Determining a second speed regulation ratio corresponding to the current road grade, and calculating a third speed regulation ratio based on the second speed regulation ratio and the first speed regulation ratio;

[0033] The vehicle speed adjustment operation is performed according to the third speed adjustment ratio.

[0034] In one embodiment, after the step of performing the vehicle speed adjustment operation according to the first speed adjustment ratio, the method further includes:

[0035] Determining driver identification information corresponding to the vehicle, and determining a vehicle speed change parameter triggered by the vehicle, wherein the vehicle speed change parameter is a vehicle speed change parameter generated when the driver of the vehicle actively adjusts the vehicle speed;

[0036] The first speed regulation ratio is updated in combination with the vehicle speed change parameter to obtain a fourth speed regulation ratio, and the vehicle speed adjustment operation is performed according to the fourth speed regulation ratio.

[0037] In addition, to achieve the above-mentioned purpose, the present application also proposes an electronic device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the vehicle control method as described above.

[0038] In addition, to achieve the above objectives, the present application also proposes a vehicle, which includes the electronic device as described above.

[0039] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium. A computer program is stored on the storage medium, and when the computer program is executed by the processor, the steps of the vehicle control method described above are implemented.

[0040] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the vehicle control method described above.

[0041] The vehicle control method provided in an embodiment of the present application is applied to a vehicle including an image acquisition device, wherein the image acquisition device captures target image data including a road in front of the vehicle and determines the transmittance parameters corresponding to each pixel point in the target image data; the target weather type corresponding to the vehicle is determined in combination with each of the transmittance parameters; when it is detected that the target weather type is a heavy fog weather type, the current visibility level corresponding to the heavy fog weather type is determined; a first speed regulation ratio is determined based on the current visibility level, and a vehicle speed adjustment operation is performed according to the first speed regulation ratio.

[0042] In this embodiment, when the electronic device is running, it first controls the image acquisition device configured on the vehicle to capture target image data containing the road in front of the vehicle through the image acquisition device. The electronic device then processes each pixel in the target image data to determine the transmittance parameter corresponding to each pixel. Afterwards, the electronic device identifies the target weather type corresponding to the vehicle's environment based on each transmittance parameter. Afterwards, if the electronic device determines that the target weather type is a heavy fog weather type, it determines the visibility level corresponding to the heavy fog weather type based on each transmittance parameter. Finally, the electronic device filters and obtains a matching first speed regulation ratio based on the current visibility level, and performs a vehicle speed adjustment operation on the vehicle according to the first speed regulation ratio.

[0043] In this way, the present application solves the technical problem in the related art that vehicles are prone to increase driving safety risks due to incorrect identification of weather types. That is, the present application calculates the transmittance parameters of each pixel point in the image data, so that the electronic device can fully consider the physical attenuation characteristics of fog to light, avoid determining the wrong weather type based on the overall brightness of the image data, and accurately identify whether the vehicle is in foggy weather and determine the visibility level in foggy weather, and then enable the electronic device to screen the matching speed regulation ratio based on the visibility level, control the vehicle's driving speed according to the speed regulation ratio, and reduce the driving safety risk of the vehicle during driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0046] Figure 1 A flow chart of the first embodiment of the vehicle control method of the present application is provided;

[0047] Figure 2 This is a schematic diagram of target image data involved in an embodiment of the vehicle control method of the present application;

[0048] Figure 3 A brief flowchart of the vehicle control method of this application;

[0049] Figure 4 This is a schematic diagram of the module structure of the vehicle control device according to an embodiment of the present application;

[0050] Figure 5 This is a schematic diagram of the device structure of the hardware operating environment involved in the vehicle control method in the embodiment of the present application.

[0051] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0052] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0053] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0054] In this embodiment, for ease of description, the following description will be made using an electronic device that is configured in a vehicle and has an image processing module inside, or a mobile terminal, data storage control terminal, PC or other terminal connected to an electronic control unit that is compatible with the electronic device as the execution subject.

[0055] Based on the above electronic equipment, the overall concept of the vehicle control method of the present application is proposed here.

[0056] With the continuous development of the automotive industry, vehicles have become the preferred means of transportation for an increasing number of users. In related technologies, vehicles typically rely on their own image acquisition devices to capture the surrounding environment and obtain image data, thereby determining the current weather type based on changes in the brightness of the image data. However, when the ambient light around the vehicle experiences significant changes, the vehicle is prone to identifying the wrong weather type after acquiring the image data, resulting in a lag in safety control strategies and significantly increasing driving safety risks.

[0057] In response to the above phenomenon, the present application provides a vehicle control method, which is applied to a vehicle including an image acquisition device, and the method includes: capturing target image data including the road in front of the vehicle through the image acquisition device, and determining the transmittance parameters corresponding to each pixel point in the target image data; determining the target weather type corresponding to the vehicle in combination with each of the transmittance parameters; when it is detected that the target weather type is a heavy fog weather type, determining the current visibility level corresponding to the heavy fog weather type; determining a first speed regulation ratio according to the current visibility level, and performing a vehicle speed adjustment operation according to the first speed regulation ratio.

[0058] In this way, the present application solves the technical problem in the related art that vehicles are prone to increase driving safety risks due to incorrect identification of weather types. That is, the present application calculates the transmittance parameters of each pixel point in the image data, so that the electronic device can fully consider the physical attenuation characteristics of fog to light, avoid determining the wrong weather type based on the overall brightness of the image data, and accurately identify whether the vehicle is in foggy weather and determine the visibility level in foggy weather, and then enable the electronic device to screen the matching speed regulation ratio based on the visibility level, control the vehicle's driving speed according to the speed regulation ratio, and reduce the driving safety risk of the vehicle during driving.

[0059] Based on the overall concept of the vehicle control method of the present application, the embodiment of the present application provides a vehicle control method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the vehicle control method of the present application. In this embodiment, the vehicle control method is applied to a vehicle including an image acquisition device, and the vehicle control method includes steps S10 to S40:

[0060] Step S10: capturing target image data including the road ahead of the vehicle through an image acquisition device, and determining the transmittance parameter corresponding to each pixel point in the target image data;

[0061] In this embodiment, while the vehicle is driving, the electronic device configured on the vehicle first controls the image acquisition device configured on the vehicle to capture target image data containing the road ahead through the image acquisition device. The electronic device inputs the target image data into the image processing module configured on the vehicle, and the image processing module processes the target image data to calculate the transmittance parameters corresponding to each pixel point.

[0062] For example, see Figure 2 , Figure 2 This is a schematic diagram of target image data involved in an embodiment of the vehicle control method of the present application. When the vehicle is driving, the electronic device configured on the vehicle first controls the camera configured on the vehicle to make the camera capture a frame such as Figure 2 As shown, the electronic device includes target image data of the road ahead of the vehicle. The target image data is input into the image processing module configured therein. The image processing module performs denoising and white balance adjustment on the target image data to obtain a standardized RGB matrix, and calls a preset transmittance calculation formula:

[0063]

[0064] The standardized RGB matrix is ​​processed to determine the transmittance parameter t(x) corresponding to each pixel point on the target image data.

[0065] It should be noted that in the transmittance calculation formula, I c is the color channel of the observed image, A c is the atmospheric light intensity, ω is the angle parameter, and Ω is the adjustment parameter, ranging from 0.9 to 0.95, which is used to enhance the authenticity of the processing results (i.e., retain some fog for detection).

[0066] It is understandable that the electronic device can first obtain the atmospheric scattering model:

[0067] I(x)=J(x)t(x)+A(1-t(x)), where I(x) is the foggy image and J(x) is the fog-free image;

[0068] After obtaining the atmospheric scattering model, the electronic device determines, based on the atmospheric scattering model and the preset foggy image I(x) and fog-free image J(x), that the foggy image I(x) is composed of the light reflected by the object after being attenuated by the fog and the atmospheric light reflected by the fog.

[0069] At the same time, the electronic device processes the fog-free image J(x) to determine that the dark channel of the non-sky area of ​​the fog-free image J(x) is close to zero, that is:

[0070] J dark (x) = min y∈Ω(x)(min c∈(r,g,b) J c (y))→0;

[0071] Therefore, electronic devices can combine the dark channel prior algorithm and the atmospheric scattering model and then perform normalization processing to obtain a transmittance calculation formula.

[0072] In this way, the electronic device can process the target image data to determine the transmittance parameters corresponding to each pixel in the target image data, thereby fully considering the physical attenuation characteristics of fog on light, to determine the clear areas and low visibility areas in the image data, and then determine the target weather type corresponding to the vehicle's environment based on the clear areas and low visibility areas.

[0073] Step S20: Determine the target weather type corresponding to the vehicle based on the transmittance parameters;

[0074] In this embodiment, after determining each transmittance parameter, the electronic device further determines a plurality of abnormal pixels with low transmittance in the target image data based on each transmittance parameter, and determines the number of low transmittance pixels based on the plurality of abnormal pixels. When the number of low transmittance pixels is combined to identify that the vehicle is in a low visibility environment, the target image data is processed to determine a low visibility area and a drivable area, and then, based on the low visibility area and the drivable area, it is determined whether the target weather type corresponding to the environment in which the vehicle is located is a heavy fog weather type.

[0075] Exemplarily, for example, after determining the transmittance parameter t(x) corresponding to each pixel point, the electronic device first identifies abnormal pixel points with low transmittance in the target image data based on each transmittance parameter t(x), and determines the number of low-transmittance pixel points based on each abnormal pixel point. When the electronic device detects that the number of low-transmittance pixel points reaches a preset threshold, it can determine that the vehicle is in a low-visibility environment. At this time, the electronic device processes the target image data to determine the low-visibility area and the drivable area contained in the target image data. The electronic device thereby determines the ratio of overlapping areas between the low-visibility area and the drivable area, and determines whether the target weather type corresponding to the vehicle's environment is a heavy fog weather type based on the overlapping area ratio.

[0076] In this way, the electronic device can fully consider the physical attenuation characteristics of fog on light based on various transmittance parameters to determine the clear areas and low visibility areas in the image data, and then determine the target weather type corresponding to the vehicle's environment based on the clear areas and low visibility areas.

[0077] In a feasible implementation manner, the above step S20 may specifically include steps S201 to S203:

[0078] Step S201: obtaining a preset transmittance threshold, and comparing each transmittance parameter with the transmittance threshold to obtain a plurality of comparison results;

[0079] Step S202: determining the number of low-transmittance pixels based on the plurality of comparison results, and determining the low-visibility area and the drivable area included in the target image data when it is detected that the number of low-transmittance pixels reaches a preset threshold;

[0080] Step S203: Determine a target weather type corresponding to the vehicle based on the low visibility area and the drivable area.

[0081] In this embodiment, after determining the transmittance parameter corresponding to each pixel point, the electronic device can first read the storage module configured by itself to obtain a preset transmittance threshold value, and compare each transmittance parameter with the transmittance threshold value to obtain multiple comparison results. Thereafter, the electronic device traverses the multiple comparison results, and thereby determines, in each pixel point, a plurality of abnormal pixel points whose transmittance parameters do not reach the transmittance threshold value based on the multiple comparison results. The electronic device determines the number of low-transmittance pixels of the multiple abnormal pixels and obtains a preset pixel number threshold value. When the electronic device detects that the number of low-transmittance pixels reaches the pixel number threshold value, it determines that the vehicle is in low visibility. environment, at this time, the electronic device calls the preset deep learning model to process the target image data to extract the image features contained in the target image data, and then identifies the key elements such as lane lines, road boundaries, obstacles contained in the target image data according to the image features, and then identifies the drivable area contained in the target image data according to each key element. At the same time, the electronic device clusters each abnormal pixel point to determine the low-visibility area contained in the target image data. Finally, the electronic device traverses the low-visibility area and the drivable area to determine the overlapping ratio between the low-visibility area and the drivable area, and then determines the target weather type corresponding to the vehicle according to the overlapping ratio.

[0082] Exemplarily, for example, after determining the transmittance parameter t(x) corresponding to each pixel point, the electronic device may first read the above-mentioned storage module to obtain a preset transmittance threshold α, and the electronic device then compares each transmittance parameter t(x) with the transmittance threshold α to obtain multiple comparison results. Afterwards, the electronic device traverses the multiple comparison results, and thereby determines, based on the multiple comparison results, abnormal pixels whose transmittance parameter t(x) is less than the transmittance threshold α in each pixel point, the electronic device determines the number of low-transmittance pixels of the abnormal pixels, and determines 70% of the total number of pixels in the target image data as the pixel number threshold. The electronic device then determines that the vehicle In a low-visibility environment, the electronic device calls the preset semantic segmentation network U-Net to process the target image data to extract the image features of the target image data, and identifies the key elements such as lane lines, road boundaries, obstacles, etc. contained in the target image data based on the image features. The semantic segmentation network U-Net models each key element and converts the 2D image into a drivable area in 3D space through BEV technology. At the same time, the electronic device clusters each abnormal pixel point to obtain the low-visibility area. Finally, the electronic device traverses the low-visibility area and the drivable area to generate the ratio of overlapping areas between the low-visibility area and the drivable area, thereby determining the target weather type corresponding to the vehicle's environment based on the ratio of overlapping areas.

[0083] In this way, the electronic device can fully consider the physical attenuation characteristics of fog on light based on various transmittance parameters to determine the clear areas and low visibility areas in the image data, and then determine the target weather type corresponding to the vehicle's environment based on the clear areas and low visibility areas.

[0084] In a feasible implementation manner, the above step S203 may specifically include steps S2031 to S2034:

[0085] Step S2031: determining the coordinates of each first pixel included in the low visibility area, and determining the coordinates of each second pixel included in the drivable area;

[0086] Step S2032: traversing each of the first pixel coordinates and each of the second pixel coordinates to determine each overlapping pixel coordinate, and determining an overlapping area ratio according to each of the overlapping pixel coordinates;

[0087] Step S2033: When it is detected that the overlapping area ratio reaches a preset overlapping ratio threshold, it is determined that the target weather type corresponding to the vehicle is a heavy fog weather type.

[0088] In this embodiment, after determining the low visibility area and the drivable area contained in the target image data, the electronic device first traverses the low visibility area to determine the first pixel coordinates in the low visibility area. At the same time, the electronic device traverses the drivable area to determine the second pixel coordinates in the drivable area. Afterwards, the electronic device traverses the first pixel coordinates and the second pixel coordinates to determine the overlapping pixel coordinates, and determines the overlapping area ratio between the low visibility area and the drivable area based on the number of overlapping pixel coordinates. Finally, the electronic device reads the above-mentioned storage module to obtain a preset overlapping ratio threshold, and when it is detected that the overlapping area ratio reaches the overlapping ratio threshold, it determines that the target weather type is a heavy fog weather type.

[0089] Exemplarily, for example, when the electronic device determines the low visibility area and the drivable area in the target image data, the electronic device first traverses the low visibility area to determine the first pixel coordinates contained therein, and traverses the drivable area to determine the second pixel coordinates contained therein. Afterwards, the electronic device compares each first pixel coordinate with each second pixel coordinate respectively to determine the first pixel coordinate that overlaps with the second pixel coordinate as the overlapping pixel coordinate, and determines the number of overlapping coordinates of the overlapping pixel coordinates. At the same time, the electronic device detects the number of target coordinates of the second pixel coordinates, and calculates the overlapping area ratio based on the number of overlapping coordinates and the number of target coordinates. Finally, the electronic device reads the above-mentioned storage module to obtain a preset overlapping ratio threshold, and when it is detected that the overlapping area ratio reaches the overlapping ratio threshold, determines that the target weather type is a heavy fog weather type.

[0090] It should be noted that in this embodiment and another embodiment, when the electronic device detects that the overlapping area ratio does not reach the overlapping ratio threshold, it can further identify whether the target weather type is freezing rain, hail, and other extreme weather types with higher visibility than foggy weather but lower than clear weather based on the vibration wave sensor, rain sensor, temperature sensor, etc. configured on the vehicle. It can be understood that this application does not limit the process of the vehicle identifying other extreme weather types.

[0091] In this way, the electronic device can fully consider the physical attenuation characteristics of fog on light based on various transmittance parameters to determine the clear areas and low-visibility areas in the image data, and then determine the target weather type corresponding to the vehicle's environment based on the clear areas and low-visibility areas, avoiding the misjudgment of weather types due to shadows or partial occlusions.

[0092] In a feasible implementation manner, the above step S20 may further include steps S204 to S206:

[0093] Step S204: determining each cluster area included in the target image data, and determining a transmittance variation parameter between each cluster area based on each transmittance parameter;

[0094] Step S205: determining the low visibility area and the drivable area included in the target image data when detecting that at least one transmission change parameter reaches a preset change parameter threshold;

[0095] Step S206: Determine the target weather type corresponding to the vehicle based on the low visibility area and the drivable area.

[0096] It should be noted that the transmission change parameter is an indicator for quantifying the visibility difference between adjacent areas. It can be understood that the larger the transmission change parameter is, the greater the visibility difference between adjacent cluster areas is.

[0097] In this embodiment, after determining the transmittance parameters corresponding to each pixel point, the electronic device may first call an image segmentation algorithm to divide the target image data into different cluster areas, and calculate the mean value of the transmission parameters corresponding to each cluster area based on each transmittance parameter. The electronic device then calculates the transmission change parameter generated between any two adjacent cluster areas based on each transmittance mean value. After that, the electronic device reads the above-mentioned storage module to obtain a preset change parameter threshold, and when it is detected that at least one transmission change parameter reaches the change parameter threshold, it determines that the vehicle is in a low visibility environment. At this time, the electronic device calls a preset deep learning model to analyze the target image. The data is processed to extract image features contained in the target image data, so as to identify key elements such as lane lines, road boundaries, obstacles contained in the target image data according to the image features, and then identify the drivable area contained in the target image data according to each key element. At the same time, the electronic device determines the above-mentioned abnormal pixel points contained in the target image data based on each transmittance parameter, and clusters the abnormal pixel points to determine the low-visibility area contained in the target image data. Finally, the electronic device traverses the low-visibility area and the drivable area to determine the overlapping area ratio between the low-visibility area and the drivable area, and then determines the target weather type corresponding to the vehicle according to the overlapping area ratio.

[0098] Exemplarily, for example, after determining the transmittance parameter t(x) corresponding to each pixel point, the electronic device can also call an image segmentation algorithm to divide the target image data into multiple cluster areas, and the electronic device calculates the transmittance mean corresponding to each cluster area according to the transmittance parameters t(x) contained in each cluster area, and the electronic device calculates the transmittance change parameter generated between any two adjacent cluster areas according to the transmittance mean. Afterwards, the electronic device reads the above-mentioned storage module to obtain a preset change parameter threshold, and compares each transmission change parameter with the change parameter threshold respectively, so that when it is detected that at least one transmission change parameter reaches the change parameter threshold, the two cluster areas with larger changes are determined to be transition areas between different media in the air (such as fog and clear air), thereby determining that the vehicle is in a low visibility environment, and the electronic device calls the preset semantic segmentation network U-Net to process the target image data to extract the image features of the target image data, and identifies the key elements such as lane lines, road boundaries, obstacles, etc. contained in the target image data according to the image features. The semantic segmentation network U-Net Each key element is modeled, and the 2D image is converted into a drivable area in a 3D space using BEV technology. At the same time, the electronic device determines abnormal pixel points whose transmittance parameters t(x) are less than the above-mentioned transmittance threshold α in the target image data based on each transmittance parameter t(x), and clusters each abnormal pixel point to obtain a low visibility area. Finally, the electronic device traverses the low visibility area to determine each first pixel coordinate contained therein, and traverses the drivable area to determine each second pixel coordinate contained therein. The electronic device compares each first pixel coordinate with each second pixel coordinate respectively to determine the first pixel coordinate that overlaps with the second pixel coordinate as the overlapping pixel coordinate, and determines the number of overlapping coordinates of the overlapping pixel coordinates. At the same time, the electronic device detects the number of target coordinates of the second pixel coordinates and calculates the overlapping area ratio based on the overlapping coordinate number and the target coordinate number. The electronic device reads the above-mentioned storage module to obtain a preset overlapping ratio threshold. When it is detected that the overlapping area ratio reaches the overlapping ratio threshold, the electronic device determines that the target weather type is a heavy fog weather type, and determines the visibility level corresponding to the heavy fog weather type based on the overlapping area ratio.

[0099] In this way, the electronic device can fully consider the physical attenuation characteristics of fog on light based on various transmittance parameters to determine the clear areas and low visibility areas in the image data, and then determine the target weather type corresponding to the vehicle's environment based on the clear areas and low visibility areas.

[0100] Step S30: When the target weather type is detected to be a heavy fog weather type, determining a current visibility level corresponding to the heavy fog weather type;

[0101] In this embodiment, when the electronic device detects that the vehicle is in heavy fog, it further reads the storage module configured therein to obtain a preset overlapping ratio-visibility level mapping relationship. The electronic device then traverses the low-visibility area and the drivable area contained in the target image data, determines the overlapping area ratio between the low-visibility area and the drivable area, and queries the overlapping ratio-visibility level mapping relationship based on the overlapping area ratio to determine the current visibility level.

[0102] Exemplarily, for example, when the electronic device detects that the vehicle is in foggy weather based on various transmittance parameters, it further identifies the drivable area extracted by the semantic segmentation network U-Net and the low visibility area obtained by itself based on various transmittance parameters. The electronic device traverses the low visibility area to determine the first pixel coordinates contained therein, and traverses the drivable area to determine the second pixel coordinates contained therein. The electronic device compares each first pixel coordinate with each second pixel coordinate respectively to determine the number of overlapping coordinates, and calculates the overlapping area ratio based on the number of overlapping coordinates. The electronic device reads the above-mentioned storage module to obtain a preset overlapping ratio-visibility level mapping relationship, thereby determining the current visibility level based on the overlapping ratio-visibility level mapping relationship.

[0103] In this way, the electronic device can quantify the actual impact of foggy weather on driving based on the overlap ratio between the low visibility area and the drivable area, and then determine the current visibility level that matches the actual impact.

[0104] In a feasible implementation manner, the above step S30 may specifically include steps S301 to S303:

[0105] Step S301: determining a plurality of preset overlap ratios and preset visibility levels corresponding to the plurality of preset overlap ratios;

[0106] Step S302: screening the plurality of preset overlapping ratios in combination with the overlapping area ratio to determine a target preset overlapping ratio that matches the overlapping area ratio;

[0107] Step S303: determining the preset visibility level corresponding to the target preset overlap ratio as the current visibility level corresponding to the heavy fog weather type.

[0108] In this embodiment, when the electronic device detects that the vehicle is in a heavy fog weather type, it first reads the above-mentioned storage module to obtain the preset overlap ratio-visibility level mapping relationship, and reads multiple preset overlap ratios contained in the overlap ratio-visibility level mapping relationship, and the preset visibility levels that each of the multiple preset overlap ratios matches in the overlap ratio-visibility level mapping relationship. Afterwards, the electronic device queries the overlap ratio-visibility level mapping relationship based on the overlapping area ratio to determine the target preset overlap ratio that matches the current visibility level. Finally, the electronic device determines the preset visibility level corresponding to the target preset overlap ratio in the overlap ratio-visibility level mapping relationship as the current visibility level that matches the heavy fog weather type.

[0109] In this way, the electronic device can quantify the actual impact of foggy weather on driving based on the overlap ratio between the low visibility area and the drivable area, and then determine the current visibility level that matches the actual impact.

[0110] In a feasible implementation manner, the above step S30 may further include steps S304 to S305:

[0111] Step S304: determining the contour lines of the preceding vehicle contained in the target image data;

[0112] Step S305: Detecting the completeness of the outline of the preceding vehicle, and determining the current visibility level corresponding to the heavy fog weather type according to the completeness.

[0113] In this embodiment, when the electronic device detects that the vehicle is in heavy fog weather, it can also process the above-mentioned target image data to extract the contour lines of the front vehicle contained in the target image data. Afterwards, the electronic device evaluates the contour lines of the front vehicle to determine the completeness of the contour lines of the front vehicle, and determines the current visibility level corresponding to the heavy fog weather type based on the completeness of the contour lines of the front vehicle.

[0114] Exemplarily, for example, when the electronic device detects that the vehicle is in heavy fog, in addition to querying the above-mentioned overlapping ratio-visibility level mapping relationship to determine the current visibility level, it can also identify the above-mentioned target image data to locate the front vehicle model of other vehicles in front of the vehicle contained in the target image data, and perform continuous line drawing processing on the target boundary of the front vehicle model to obtain the minimum boundary that can wrap the front vehicle model as the front vehicle contour line. Afterwards, the electronic device calls the Laplacian gradient operator to perform grayscale gradient evaluation on each boundary point on the front vehicle contour line to determine the contour completeness of the front vehicle. At the same time, the electronic device reads the storage module to obtain the preset contour completeness-visibility level mapping relationship, and queries the contour completeness-visibility level mapping relationship based on the contour completeness to determine the current visibility level.

[0115] It should be noted that since the Laplacian gradient operator processes each boundary point based on the second-order derivative information of the image, the Laplacian gradient operator is very sensitive to the edges and mutation points of the targets in the image, so it can evaluate the integrity of the vehicle contour lines. In addition, it can be understood that the specific process of querying the preset contour completeness-visibility level mapping relationship is similar to the process of querying the overlap ratio-visibility level mapping relationship in the above embodiment, so it will not be repeated here.

[0116] In this way, the electronic device can quantify the actual impact of foggy weather on driving based on the completeness of the contour lines of the vehicle in front, and then determine the current visibility level that matches the actual impact.

[0117] Step S40: determining a first speed adjustment ratio according to the current visibility level, and performing a vehicle speed adjustment operation according to the first speed adjustment ratio;

[0118] In this embodiment, after determining the current visibility level, the electronic device further reads the storage module to obtain a preset visibility level-speed regulation ratio mapping relationship, and then queries the visibility level-speed regulation ratio mapping relationship based on the current visibility level to determine a first speed regulation ratio that matches the current visibility level. The electronic device controls the vehicle to perform a vehicle speed adjustment operation based on the first speed regulation ratio.

[0119] For example, after determining the current visibility level, if the electronic device detects that the current visibility level is a blue warning, it first reads the above-mentioned storage module to obtain the visibility level-speed regulation ratio mapping relationship shown in Table 1:

[0120] Visibility level Blue Alert Orange alert Red Alert Speed ​​regulation ratio 5％ 10％ 25％

[0121] Table 1: Visibility level-speed ratio mapping relationship

[0122] The electronic device then queries the visibility level-speed regulation ratio mapping relationship based on the current visibility level to determine that when the current visibility level is a blue warning, the first speed regulation ratio is determined to be 5%. At the same time, the electronic device determines the current speed of the vehicle and calculates the first target speed based on the first speed regulation ratio of 5% and the current speed. The electronic device then controls the vehicle to adjust the current speed of the vehicle to the first target speed.

[0123] It should be noted that, in this embodiment and another embodiment, after determining the first speed regulation ratio, the electronic device can also control the fog lights configured for the vehicle to enter the on state. At this time, the electronic device pushes the preset light-on authorization content "We have recognized that you are accustomed to turning on the fog lights in an environment with insufficient visibility. Will the vehicle automatically turn on the fog lights for you in the future?" and receives the authorization feedback of "agree" or "reject" triggered by the user based on the light-on authorization content. When the electronic device detects that the authorization feedback is "agree", it modifies the light-on authorization content to "The visibility of the road ahead is reduced, and the fog lights have been turned on for you". Similarly, when the electronic device detects that the authorization feedback is "reject", it identifies the ID identifier corresponding to the user and performs a control function sleep operation on the ID identifier, so that when the ID identifier is detected to be logged in the vehicle, it stops adjusting the driving speed and keeps the fog lights off when the vehicle is in foggy weather.

[0124] In this embodiment, when the vehicle is traveling, the electronic device configured on the vehicle first controls the image acquisition device configured on the vehicle to capture target image data containing the road ahead through the image acquisition device. The electronic device inputs the target image data into the image processing module configured by itself, and the image processing module processes the target image data to calculate the transmittance parameters corresponding to each pixel point. Thereafter, the electronic device determines multiple abnormal pixels with low transmittance in the target image data based on each transmittance parameter, and determines the number of low-transmittance pixels based on the multiple abnormal pixels. In this way, when the vehicle is identified as being in a low-visibility environment in combination with the number of low-transmittance pixels, the target image data is processed to determine the low-visibility area and the drivable area, and then the vehicle is detected to be in a low-visibility environment. The low visibility area and the drivable area determine whether the target weather type corresponding to the vehicle's environment is a heavy fog weather type. After that, the electronic device obtains a preset overlapping ratio-visibility level mapping relationship. The electronic device then traverses the low visibility area and the drivable area contained in the target image data, determines the overlapping area ratio between the low visibility area and the drivable area, and queries the overlapping ratio-visibility level mapping relationship based on the overlapping area ratio to determine the current visibility level. Finally, the electronic device obtains a preset visibility level-speed regulation ratio mapping relationship, and then queries the visibility level-speed regulation ratio mapping relationship based on the current visibility level to determine a first speed regulation ratio that matches the current visibility level. The electronic device controls the vehicle to perform a vehicle speed adjustment operation based on the first speed regulation ratio.

[0125] In this way, the present application solves the technical problem in the related art that vehicles are prone to increase driving safety risks due to incorrect identification of weather types. That is, the present application calculates the transmittance parameters of each pixel point in the image data, so that the electronic device can fully consider the physical attenuation characteristics of fog to light, avoid determining the wrong weather type based on the overall brightness of the image data, and accurately identify whether the vehicle is in foggy weather and determine the visibility level in foggy weather, and then enable the electronic device to screen the matching speed regulation ratio based on the visibility level, control the vehicle's driving speed according to the speed regulation ratio, and reduce the driving safety risk of the vehicle during driving.

[0126] Based on the first embodiment of the present application, a second embodiment of the present application is proposed. In the second embodiment of the present application, the same or similar contents as those of the above embodiments can be referred to above and will not be described in detail. On this basis, after the step of "determining the first speed adjustment ratio according to the current visibility level" in the above step S40, the vehicle control method of the present application can also include steps A10 to A30:

[0127] Step A10: Acquire location information corresponding to the vehicle, and determine the current road grade corresponding to the vehicle based on the location information;

[0128] Step A20: determining a second speed regulation ratio corresponding to the current road grade, and calculating a third speed regulation ratio based on the second speed regulation ratio and the first speed regulation ratio;

[0129] Step A30: Execute the vehicle speed adjustment operation according to the third speed adjustment ratio.

[0130] It should be noted that the road grade is grade data that can reflect the degree of road adhesion. It can be understood that the higher the road grade, the higher the road adhesion, and the lower the risk of the vehicle losing control on the road. Similarly, the lower the road grade, the lower the road adhesion, and the higher the risk of the vehicle losing control on the road.

[0131] In this embodiment, after determining the current visibility level, the electronic device can also detect the vehicle's location information and determine the road grade corresponding to the road where the vehicle is located based on the location information. Afterwards, the electronic device queries the second speed regulation ratio corresponding to the road grade, and superimposes the second speed regulation ratio and the above-mentioned first speed regulation ratio to obtain a third speed regulation ratio. Finally, the electronic device controls the vehicle to perform a speed adjustment operation based on the third speed regulation ratio.

[0132] For example, after determining that the current visibility level is a blue warning and that the first speed adjustment ratio corresponding to the blue warning is 5%, the electronic device may further detect the current location information of the vehicle and determine the road grade of the road currently located by the vehicle based on the current location information. Thereafter, if the electronic device detects that the road grade is level 3, the electronic device reads the storage module to obtain a road grade-speed adjustment ratio mapping relationship as shown in Table 2, which includes multiple road grades and speed adjustment ratios corresponding to each of the multiple road grades:

[0133] Road grade Level 3 Level 2 Level 1 Speed ​​regulation ratio 5％ 10％ 25％

[0134] Table 2: Road grade-speed regulation ratio mapping relationship

[0135] The electronic device determines, based on the road grade-speed adjustment ratio mapping relationship, that the second speed adjustment ratio corresponding to the grade 3 road is 5%, and further calculates the fourth speed adjustment ratio of 10% based on the first speed adjustment ratio of 5% and the second speed adjustment ratio of 5%.

[0136] Finally, the electronic device determines the current speed of the vehicle and calculates a second target speed based on the fourth speed adjustment ratio 10% and the current speed. The electronic device then controls the vehicle to adjust the current speed of the vehicle to the second target speed.

[0137] In this way, the electronic equipment can identify the road conditions corresponding to the vehicle's location information and determine the potential driving risks under such road conditions, thereby flexibly adjusting the speed reduction ratio under different roads and different visibility levels. This allows the vehicle control strategy in foggy weather to be more closely matched to the weather type and road conditions, further improving the safety of the vehicle during driving.

[0138] Based on the first and / or second embodiments of the present application, a third embodiment of the present application is proposed. In the third embodiment of the present application, the same or similar contents as those of the above embodiments can be referred to above and will not be described in detail. On this basis, after the above step S40, the vehicle control method of the present application may further include steps B10 to B20:

[0139] Step B10: determining the driver identification information corresponding to the vehicle, and determining a vehicle speed change parameter triggered by the vehicle, wherein the vehicle speed change parameter is a vehicle speed change parameter generated when the driver of the vehicle actively adjusts the vehicle speed;

[0140] Step B20: updating the first speed regulation ratio in combination with the vehicle speed change parameter to obtain a fourth speed regulation ratio, and performing a vehicle speed adjustment operation according to the fourth speed regulation ratio.

[0141] In this embodiment, after the electronic device adjusts the vehicle speed to the above-mentioned first target speed, it can also first identify the driver identification information logged by the driver on the vehicle. At the same time, the electronic device detects the speed change parameters generated when the driver actively adjusts the speed. Afterwards, the electronic device calculates the adjusted third target speed based on the speed change parameters and the first target speed, and updates the above-mentioned first speed regulation ratio according to the third target speed to update the first speed regulation ratio to the fourth speed regulation ratio, and then directly controls the vehicle according to the fourth speed regulation ratio under the foggy weather type with the same visibility level.

[0142] Exemplarily, for example, after the electronic device adjusts the current speed of the vehicle to the above-mentioned first target speed, it can also first identify the control system in the vehicle to determine the driver ID information logged on the control system. At the same time, the electronic device detects the vehicle and, when it detects that the driver actively adjusts the first target speed, determines the speed change parameters generated during the speed change process. Afterwards, the electronic device calculates the changed third target speed based on the speed change parameters and the first target speed, and determines the speed regulation ratio update parameter based on the third target speed and the initial speed before entering the speed regulation state (i.e., the above-mentioned current speed). The electronic device then updates the first speed regulation ratio by 5% according to the speed regulation ratio update parameter to obtain a fourth speed regulation ratio, and stores the fourth speed regulation ratio in the storage module. Then, when it is detected that the vehicle is in foggy weather with a visibility level of blue warning, the speed of the vehicle is directly adjusted according to the fourth speed regulation ratio.

[0143] In this way, the electronic device can detect the active speed adjustment process triggered by the user after adjusting the speed of the vehicle, and then modify the speed adjustment ratio based on the active speed adjustment process, so that the speed adjustment ratio is closer to the driver's driving habits, further enhancing the driver's driving experience.

[0144] For example, in order to help understand the implementation process of the vehicle control method obtained by combining this embodiment with the above embodiments, please refer to Figure 3 , Figure 3 This is a brief flowchart of the vehicle control method of this application, specifically:

[0145] In this embodiment, while a vehicle is traveling, an electronic device configured on the vehicle first controls an image acquisition device configured on the vehicle to capture target image data including a road ahead through the image acquisition device. The electronic device processes the target image data to determine a transmittance parameter corresponding to each pixel in the target image data. The electronic device then reads a memory module configured therein to obtain a preset transmittance threshold value and compares each transmittance parameter with the transmittance threshold value. Based on multiple comparison results, the electronic device identifies abnormal pixels whose transmittance parameters do not meet the transmittance threshold value. The electronic device then determines whether the vehicle is in a low-visibility environment based on the number of abnormal pixels. If the electronic device determines that the vehicle is in a low-visibility environment, the electronic device further processes the target image data to identify low-visibility areas and drivable areas within the target image data. The electronic device detects an overlap ratio between the low-visibility area and the drivable area. If the overlap ratio is detected to reach a preset overlap ratio threshold value, the electronic device determines that the weather type corresponding to the vehicle's environment is heavy fog. The electronic device determines the visibility level corresponding to the heavy fog type based on the overlap ratio.

[0146] Then, the electronic device obtains a preset visibility level-speed regulation ratio mapping relationship, and determines a first speed regulation ratio that matches the current visibility level based on the visibility level-speed regulation ratio mapping relationship. At the same time, the electronic device detects the vehicle's position information, and determines the road level corresponding to the road on which the vehicle is located based on the position information. The electronic device determines a second speed regulation ratio corresponding to the road level, and superimposes the first speed regulation ratio and the second speed regulation ratio to obtain a third speed regulation ratio. The electronic device detects the vehicle's current speed, and calculates a target speed based on the current speed and the third speed regulation ratio. The electronic device controls the vehicle to travel at the target speed.

[0147] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the vehicle control method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0148] This application also provides a vehicle control device, please refer to Figure 4 The vehicle control device is applied to a vehicle including an image acquisition device, and the device includes:

[0149] a transmittance detection module 10 for capturing target image data including the road ahead of the vehicle through the image acquisition device and determining a transmittance parameter corresponding to each pixel point in the target image data;

[0150] A weather recognition module 20 is configured to determine a target weather type corresponding to the vehicle based on each of the transmittance parameters;

[0151] The visibility recognition module 30 is configured to determine a current visibility level corresponding to the heavy fog weather type when detecting that the target weather type is the heavy fog weather type;

[0152] The speed adjustment determining module 40 is configured to determine a first speed adjustment ratio according to the current visibility level and perform a vehicle speed adjustment operation according to the first speed adjustment ratio.

[0153] In a feasible implementation manner, the weather identification module 20 is further configured to:

[0154] Obtaining a preset transmittance threshold, and comparing each transmittance parameter with the transmittance threshold to obtain a plurality of comparison results;

[0155] Determining the number of low-transmittance pixels based on the plurality of comparison results, and determining a low-visibility area and a drivable area included in the target image data when it is detected that the number of low-transmittance pixels reaches a preset threshold;

[0156] The target weather type corresponding to the vehicle is determined in combination with the low visibility area and the drivable area.

[0157] In a feasible implementation manner, the weather identification module 20 is further configured to:

[0158] Determining the coordinates of each first pixel included in the low-visibility area, and determining the coordinates of each second pixel included in the drivable area;

[0159] traversing each of the first pixel coordinates and each of the second pixel coordinates to determine each overlapping pixel coordinate, and determining an overlapping area ratio according to each of the overlapping pixel coordinates;

[0160] When it is detected that the overlapping area ratio reaches a preset overlapping ratio threshold, it is determined that the target weather type corresponding to the vehicle is a heavy fog weather type.

[0161] In a feasible implementation manner, the weather identification module 20 is further configured to:

[0162] Determining each cluster area included in the target image data, and determining a transmission change parameter between each cluster area based on each transmittance parameter;

[0163] determining a low visibility area and a drivable area included in the target image data when detecting that at least one transmission change parameter reaches a preset change parameter threshold;

[0164] The target weather type corresponding to the vehicle is determined in combination with the low visibility area and the drivable area.

[0165] In a feasible implementation manner, the visibility recognition module 30 is further configured to:

[0166] determining a plurality of preset overlap ratios and a preset visibility level corresponding to each of the plurality of preset overlap ratios;

[0167] screening the plurality of preset overlapping ratios in combination with the overlapping area ratio to determine a target preset overlapping ratio that matches the overlapping area ratio;

[0168] The preset visibility level corresponding to the target preset overlap ratio is determined as the current visibility level corresponding to the heavy fog weather type.

[0169] In a feasible implementation manner, the visibility recognition module 30 is further configured to:

[0170] determining a front vehicle contour line contained in the target image data;

[0171] The integrity of the outline of the preceding vehicle is detected, and a current visibility level corresponding to the heavy fog weather type is determined based on the integrity.

[0172] In a feasible implementation manner, the speed adjustment determination module 40 is further configured to:

[0173] Obtaining location information corresponding to the vehicle, and determining a current road grade corresponding to the vehicle based on the location information;

[0174] Determining a second speed regulation ratio corresponding to the current road grade, and calculating a third speed regulation ratio based on the second speed regulation ratio and the first speed regulation ratio;

[0175] The vehicle speed adjustment operation is performed according to the third speed adjustment ratio.

[0176] In a feasible implementation manner, the speed adjustment determination module 40 is further configured to:

[0177] Determining driver identification information corresponding to the vehicle, and determining a vehicle speed change parameter triggered by the vehicle, wherein the vehicle speed change parameter is a vehicle speed change parameter generated when the driver of the vehicle actively adjusts the vehicle speed;

[0178] The first speed regulation ratio is updated in combination with the vehicle speed change parameter to obtain a fourth speed regulation ratio, and the vehicle speed adjustment operation is performed according to the fourth speed regulation ratio.

[0179] The vehicle control device provided in this application, utilizing the vehicle control method of the aforementioned embodiment, can resolve the technical issue in the related art whereby vehicles are susceptible to increased driving safety risks due to incorrectly identifying the weather type. Compared to the prior art, the beneficial effects of the vehicle control device provided in this application are the same as those of the vehicle control method provided in the aforementioned embodiment, and the other technical features of the vehicle control device are the same as those disclosed in the aforementioned embodiment and are not further described here.

[0180] The present application provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the vehicle control method in the above-mentioned embodiment one.

[0181] Reference below Figure 5 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic device in the embodiments of the present application may include, but is not limited to, an electronic device configured in a vehicle and equipped with an image processing module, or a mobile terminal, data storage control terminal, PC, or other terminal connected to an electronic control unit of the electronic device. Figure 5 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0182] like Figure 5 As shown, the electronic device may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory 1002 or programs loaded from a storage device 1003 into a random access memory 1004. The random access memory 1004 also stores various programs and data required for the operation of the electronic device. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are connected to each other via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems may be connected to the input / output interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape or a hard disk; and a communication device 1009. The communication device 1009 may allow the electronic device to communicate with other devices wirelessly or wired to exchange data. Although the figures show electronic devices with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0183] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0184] The electronic device provided in this application, utilizing the vehicle control method of the aforementioned embodiment, can resolve the technical issue in related art where vehicles are prone to incorrectly identifying weather types, leading to increased driving safety risks. Compared to the prior art, the beneficial effects of the electronic device provided in this application are the same as those of the vehicle control method provided in the aforementioned embodiment, and the other technical features of the electronic device are the same as those disclosed in the aforementioned embodiment, and are not further elaborated here.

[0185] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0186] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0187] The present application provides a vehicle having the electronic device as described above, and the electronic device is used to execute the vehicle control method in the above embodiment.

[0188] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer program) stored thereon, and the computer-readable program instructions are used to execute the vehicle control method in the above-mentioned embodiment.

[0189] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0190] The computer-readable storage medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0191] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by an electronic device, the electronic device: captures target image data containing the road in front of the vehicle through the image acquisition device, and determines the transmittance parameters corresponding to each pixel point in the target image data; determines the target weather type corresponding to the vehicle in combination with each of the transmittance parameters; when it is detected that the target weather type is a heavy fog weather type, determines the current visibility level corresponding to the heavy fog weather type; determines a first speed regulation ratio according to the current visibility level, and performs a vehicle speed adjustment operation according to the first speed regulation ratio.

[0192] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0193] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0194] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0195] The computer-readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned vehicle control method. This computer-readable storage medium can address the technical issue in related art where vehicles are prone to incorrectly identifying weather types, leading to increased driving safety risks. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the vehicle control method provided in the aforementioned embodiments, and are not further elaborated here.

[0196] The present application also provides a computer program product, comprising a computer program, which implements the steps of the vehicle control method as described above when the computer program is executed by a processor.

[0197] The computer program product provided in this application can address the technical issue in related art where vehicles are prone to incorrectly identifying weather conditions, leading to increased driving safety risks. Compared to the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the vehicle control method provided in the aforementioned embodiment, and are not further elaborated here.

[0198] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A vehicle control method, characterized in that: The vehicle control method is applied to a vehicle including an image acquisition device, and the method includes: capturing target image data containing the road ahead of the vehicle through the image acquisition device, and determining the transmittance parameter corresponding to each pixel point in the target image data; Determining a target weather type corresponding to the vehicle by combining the transmittance parameters; When the target weather type is detected to be a heavy fog weather type, determining a current visibility level corresponding to the heavy fog weather type; A first speed adjustment ratio is determined according to the current visibility level, and a vehicle speed adjustment operation is performed according to the first speed adjustment ratio.

2. The vehicle control method according to claim 1, wherein: The step of determining the target weather type corresponding to the vehicle in combination with each of the transmittance parameters includes: Obtaining a preset transmittance threshold, and comparing each of the transmittance parameters with the transmittance threshold to obtain a plurality of comparison results; Determining the number of low-transmittance pixels based on the plurality of comparison results, and determining a low-visibility area and a drivable area included in the target image data when it is detected that the number of low-transmittance pixels reaches a preset threshold; The target weather type corresponding to the vehicle is determined in combination with the low visibility area and the drivable area.

3. The vehicle control method according to claim 2, wherein: The step of determining the target weather type corresponding to the vehicle by combining the low visibility area and the drivable area includes: Determining the coordinates of each first pixel included in the low-visibility area, and determining the coordinates of each second pixel included in the drivable area; traversing each of the first pixel coordinates and each of the second pixel coordinates to determine each overlapping pixel coordinate, and determining an overlapping area ratio according to each of the overlapping pixel coordinates; When it is detected that the overlapping area ratio reaches a preset overlapping ratio threshold, it is determined that the target weather type corresponding to the vehicle is a heavy fog weather type.

4. The vehicle control method according to claim 1, wherein: The step of determining the target weather type corresponding to the vehicle in combination with each of the transmittance parameters further includes: Determining each cluster area included in the target image data, and determining a transmission change parameter between each cluster area based on each transmittance parameter; determining a low visibility area and a drivable area included in the target image data when detecting that at least one transmission change parameter reaches a preset change parameter threshold; The target weather type corresponding to the vehicle is determined in combination with the low visibility area and the drivable area.

5. The vehicle control method according to any one of claims 1 to 4, characterized in that: The step of determining the current visibility level corresponding to the heavy fog weather type includes: determining a plurality of preset overlap ratios and a preset visibility level corresponding to each of the plurality of preset overlap ratios; screening the plurality of preset overlapping ratios in combination with the overlapping area ratio to determine a target preset overlapping ratio that matches the overlapping area ratio; The preset visibility level corresponding to the target preset overlap ratio is determined as the current visibility level corresponding to the heavy fog weather type.

6. The vehicle control method according to any one of claims 1 to 4, characterized in that: The step of determining the current visibility level corresponding to the heavy fog weather type further includes: determining a front vehicle contour line contained in the target image data; The integrity of the outline of the preceding vehicle is detected, and a current visibility level corresponding to the heavy fog weather type is determined based on the integrity.

7. The vehicle control method according to claim 1, wherein: After the step of performing the vehicle speed adjustment operation according to the first speed adjustment ratio, the method further includes: Obtaining location information corresponding to the vehicle, and determining a current road grade corresponding to the vehicle based on the location information; Determining a second speed regulation ratio corresponding to the current road grade, and calculating a third speed regulation ratio based on the second speed regulation ratio and the first speed regulation ratio; The vehicle speed adjustment operation is performed according to the third speed adjustment ratio.

8. The vehicle control method according to claim 1, wherein: After the step of performing the vehicle speed adjustment operation according to the first speed adjustment ratio, the method further includes: Determining driver identification information corresponding to the vehicle, and determining a vehicle speed change parameter triggered by the vehicle, wherein the vehicle speed change parameter is a vehicle speed change parameter generated when the driver of the vehicle actively adjusts the vehicle speed; The first speed regulation ratio is updated in combination with the vehicle speed change parameter to obtain a fourth speed regulation ratio, and the vehicle speed adjustment operation is performed according to the fourth speed regulation ratio.

9. An electronic device, characterized in that: The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the vehicle control method according to any one of claims 1 to 8.

10. A vehicle, characterized in that: The vehicle includes the electronic device according to claim 9.

11. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the vehicle control method according to any one of claims 1 to 8 are implemented.

12. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the vehicle control method according to any one of claims 1 to 8 are implemented.

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