Vehicle windscreen wiper control method and device, vehicle and storage medium

Abstract

The invention relates to the technical field of intelligent cabins, in particular to a vehicle windscreen wiper control method and device, a vehicle and a storage medium, and the method comprises the steps that a current rainfall image of the vehicle can be collected, the rainfall image is preprocessed to obtain image information, then the image information is input into a pre-constructed rainfall analysis model, and the rainfall analysis model is used for analyzing the rainfall of the vehicle. The rainfall information of the current environment is output, the windscreen wiper action of the vehicle windscreen wiper is matched according to the rainfall information, a corresponding control instruction is generated according to the windscreen wiper action, and the vehicle windscreen wiper is controlled to respond to the control instruction. Therefore, the problems of hardware redundancy, increase of the cost of the whole vehicle, reduction of rainfall detection reliability in extreme weather and the like due to dependence on a special rainfall sensor in the prior art are solved.

Description

Technical Field

[0001] This application relates to the field of windshield wiper control technology, and in particular to a vehicle windshield wiper control method, device, vehicle, and storage medium. Background Technology

[0002] In related technologies, automotive environmental perception systems typically rely on dedicated physical sensors to achieve rain detection. Among these, rain sensors are a common implementation method. They often employ the principle of infrared optical reflection and are installed inside the vehicle's windshield to detect rainfall, providing basic environmental information support for vehicle wiper control and other functions.

[0003] However, in related technologies, the reliance on dedicated rain sensors leads to hardware redundancy in vehicles, which not only increases the overall vehicle BOM (Bill of Materials) cost, but also requires additional space for sensor layout. Furthermore, under extreme weather conditions such as heavy fog and strong light, the sensors are prone to malfunction, thereby reducing the reliability and accuracy of detection, lowering the user experience, failing to meet usage needs, and reducing user stickiness. These issues urgently need to be addressed. Summary of the Invention

[0004] This application provides a vehicle windshield wiper control method, device, vehicle, and storage medium to solve the problems existing in related technologies, such as hardware redundancy, increased vehicle cost, and decreased reliability of rain detection under extreme weather conditions due to reliance on dedicated rain sensors.

[0005] The first aspect of this application provides a vehicle windshield wiper control method, comprising the following steps: acquiring a current rainfall image of the vehicle; preprocessing the rainfall image to obtain image information; inputting the image information into a pre-constructed rainfall analysis model to output rainfall information of the current environment; and matching the vehicle windshield wiper action according to the rainfall information, and generating a corresponding control command according to the wiper action to control the vehicle windshield wiper to respond to the control command.

[0006] Through the above technical means, the embodiments of this application can obtain accurate rainfall information by utilizing rainfall images and rainfall analysis models, thereby matching the wiper action of the vehicle's windshield wipers according to the rainfall information. Compared with setting up a dedicated sensor, it not only eliminates the need for redundant hardware and hardware space, but also makes rainfall detection more accurate and reliable, effectively improving the precision of control, ensuring the user's driving visibility, effectively improving the user experience, meeting the user's needs, and increasing user stickiness.

[0007] Optionally, in one embodiment of this application, the preprocessing of the rainfall image to obtain image information includes: enhancing the rainfall image to obtain an enhanced image; extracting at least one region of interest from the enhanced image and performing motion compensation on the at least one region of interest to obtain a compensated image; and extracting multiple raindrop features from the compensated image as the image information.

[0008] Through the above technical means, the embodiments of this application can enhance the rainfall image, highlight the raindrop features, and then extract the region of interest, reduce the interference of redundant information, reduce the computational complexity, improve the real-time performance of wiper control, and at the same time use motion compensation to eliminate inter-frame offset of the image, avoid misjudgment of raindrop features, thereby extracting multiple raindrop features, comprehensively reflecting the rainfall information, and providing a high-quality data foundation for the subsequent level judgment of the rainfall analysis model.

[0009] Optionally, in one embodiment of this application, the step of inputting the image information into a pre-constructed rainfall analysis model to output the rainfall information of the current environment includes: fusing the multiple raindrop features based on the weights corresponding to each raindrop feature according to the rainfall analysis model to obtain fused features; and matching the actual rainfall level of the current environment according to the fused features as the rainfall information.

[0010] Through the above technical means, the embodiments of this application can obtain fused features based on multiple raindrop features, integrate multi-dimensional rainfall information, avoid the one-sidedness of a single feature, improve the accuracy of rainfall level determination, provide accurate basis for subsequent wiper control, and ensure the effectiveness and intelligence of wiper control of vehicles in different rainfall scenarios.

[0011] Optionally, in one embodiment of this application, the plurality of raindrop features include at least one of raindrop spatial features, raindrop temporal features, and raindrop frequency features.

[0012] Through the above technical means, the embodiments of this application can avoid the limitations of a single feature by offering multiple raindrop features as options, thereby improving the accuracy of rainfall analysis and ensuring its reliability. Even if a certain feature is interfered with, other features still provide support, thus improving the reliability of wiper control.

[0013] Optionally, in one embodiment of this application, the method further includes: receiving a user's manual correction instruction; adjusting the control instruction according to the manual correction instruction; and updating the rainfall analysis model based on the manual correction instruction.

[0014] Through the above technical means, the embodiments of this application can receive manual correction commands from users to adjust control commands, so as to quickly respond to users' needs for adjusting the wiper effect, avoid deviation between automatic control commands and actual usage preferences, and update the rainfall analysis model according to the manual correction commands to continuously optimize the rainfall analysis model, gradually reduce the deviation between automatic commands and user expectations, reduce the frequency of subsequent manual corrections, make automatic control more accurate and more in line with user habits, and improve the intelligence and humanization level of wiper control.

[0015] Optionally, in one embodiment of this application, before acquiring the current rainfall image of the vehicle, the method further includes: obtaining the confidence level of the image acquisition device corresponding to the current rainfall image; obtaining the current processing confidence interval of the confidence level; if the current processing confidence interval is a first interval, controlling the vehicle to enter the automatic wiper control mode; if the current processing confidence interval is a second interval, detecting whether the image acquisition device is obstructed, and issuing an obstruction reminder when obstruction is detected, so that after clearing the obstruction, the vehicle is controlled to enter the automatic wiper control mode; if the current processing confidence interval is a third interval, controlling the vehicle to enter the manual wiper mode.

[0016] Through the above technical means, the embodiments of this application can dynamically switch the control mode according to the confidence level of the device. When the reliability is high, the accuracy of automatic control is guaranteed. When the reliability is medium, the recoveryable interference is eliminated through the occlusion reminder to maintain the availability of the automatic function. When the reliability is low, it is promptly downgraded to manual mode to avoid miscontrol caused by device abnormality. It comprehensively ensures clear driving visibility and operational safety in rainy weather, and improves the adaptability of device status changes and the reliability of wiper control.

[0017] A second aspect of this application provides a vehicle windshield wiper control device, comprising: a data acquisition module for acquiring a current rainfall image of the vehicle and preprocessing the rainfall image to obtain image information; an output module for inputting the image information into a pre-built rainfall analysis model to output rainfall information of the current environment; and a first control module for matching the wiper action of the vehicle windshield wipers according to the rainfall information and generating corresponding control commands according to the wiper action to control the vehicle windshield wipers to respond to the control commands.

[0018] Through the above technical means, the embodiments of this application can obtain accurate rainfall information by utilizing rainfall images and rainfall analysis models, thereby matching the wiper action of the vehicle's windshield wipers according to the rainfall information. Compared with setting up a dedicated sensor, it not only eliminates the need for redundant hardware and hardware space, but also makes rainfall detection more accurate and reliable, effectively improving the precision of control, ensuring the user's driving visibility, effectively improving the user experience, meeting the user's needs, and increasing user stickiness.

[0019] Optionally, in one embodiment of this application, the acquisition module includes: an enhancement unit for enhancing the rainfall image to obtain an enhanced image; a compensation unit for extracting at least one region of interest from the enhanced image and performing motion compensation on the at least one region of interest to obtain a compensated image; and an extraction unit for extracting multiple raindrop features from the compensated image as image information.

[0020] Through the above technical means, the embodiments of this application can enhance the rainfall image, highlight the raindrop features, and then extract the region of interest, reduce the interference of redundant information, reduce the computational complexity, improve the real-time performance of wiper control, and at the same time use motion compensation to eliminate inter-frame offset of the image, avoid misjudgment of raindrop features, thereby extracting multiple raindrop features, comprehensively reflecting the rainfall information, and providing a high-quality data foundation for the subsequent level judgment of the rainfall analysis model.

[0021] Optionally, in one embodiment of this application, the output module includes: a fusion unit, configured to fuse the multiple raindrop features based on the weights corresponding to each raindrop feature according to the rainfall analysis model, to obtain fused features; and a matching unit, configured to match the actual rainfall level of the current environment according to the fused features, as the rainfall information.

[0022] Through the above technical means, the embodiments of this application can obtain fused features based on multiple raindrop features, integrate multi-dimensional rainfall information, avoid the one-sidedness of a single feature, improve the accuracy of rainfall level determination, provide accurate basis for subsequent wiper control, and ensure the effectiveness and intelligence of wiper control of vehicles in different rainfall scenarios.

[0023] Optionally, in one embodiment of this application, the plurality of raindrop features include at least one of raindrop spatial features, raindrop temporal features, and raindrop frequency features.

[0024] Through the above technical means, the embodiments of this application can avoid the limitations of a single feature by offering multiple raindrop features as options, thereby improving the accuracy of rainfall analysis and ensuring its reliability. Even if a certain feature is interfered with, other features still provide support, thus improving the reliability of wiper control.

[0025] Optionally, in one embodiment of this application, it further includes: a receiving module, configured to receive a user's manual correction instruction; and an updating module, configured to adjust the control instruction according to the manual correction instruction and update the rainfall analysis model based on the manual correction instruction.

[0026] Through the above technical means, the embodiments of this application can receive manual correction commands from users to adjust control commands, so as to quickly respond to users' needs for adjusting the wiper effect, avoid deviation between automatic control commands and actual usage preferences, and update the rainfall analysis model according to the manual correction commands to continuously optimize the rainfall analysis model, gradually reduce the deviation between automatic commands and user expectations, reduce the frequency of subsequent manual corrections, make automatic control more accurate and more in line with user habits, and improve the intelligence and humanization level of wiper control.

[0027] Optionally, in one embodiment of this application, before acquiring the current rainfall image of the vehicle, the system further includes: a first acquisition module, configured to acquire the confidence level of the image acquisition device corresponding to the current rainfall image; a second acquisition module, configured to acquire the current processing confidence interval of the confidence level; a second control module, configured to control the vehicle to enter the automatic wiper control mode when the current processing confidence interval is a first interval; a third control module, configured to detect whether the image acquisition device is obstructed when the current processing confidence interval is a second interval, and to issue an obstruction reminder when obstruction is detected, so as to control the vehicle to enter the automatic wiper control mode after the obstruction is cleared; and a fourth control module, configured to control the vehicle to enter the manual wiper mode when the current processing confidence interval is a third interval.

[0028] Through the above technical means, the embodiments of this application can dynamically switch the control mode according to the confidence level of the device. When the reliability is high, the accuracy of automatic control is guaranteed. When the reliability is medium, the recoveryable interference is eliminated through the occlusion reminder to maintain the availability of the automatic function. When the reliability is low, it is promptly downgraded to manual mode to avoid miscontrol caused by device abnormality. It comprehensively ensures clear driving visibility and operational safety in rainy weather, and improves the adaptability of device status changes and the reliability of wiper control.

[0029] A third aspect of this application provides a vehicle, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle wiper control method as described in the above embodiments.

[0030] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle windshield wiper control method described above.

[0031] A fifth aspect of this application provides a computer program product, including a computer program that, when executed, implements the vehicle windshield wiper control method described above.

[0032] This application embodiment can acquire current rainfall images of a vehicle, preprocess the rainfall images to obtain image information, and then input the image information into a pre-built rainfall analysis model to output the rainfall information of the current environment. Based on the rainfall information, the vehicle's windshield wiper actions are matched, and corresponding control commands are generated based on the wiper actions to control the vehicle's wipers. This achieves vehicle wiper control. Compared to setting up a dedicated sensor, this not only eliminates redundant hardware and saves hardware space, but also makes rainfall detection more accurate and reliable, effectively improving control precision, ensuring the driver's visibility, and enhancing the user experience, meeting user needs, and increasing user stickiness. Therefore, it solves the problems of related technologies that rely on dedicated rain sensors, leading to hardware redundancy, increased vehicle costs, and decreased reliability of rainfall detection in extreme weather conditions.

[0033] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0034] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a schematic diagram of the structure of a vehicle wiper control system provided in one embodiment of this application; Figure 2 This is a flowchart of a vehicle windshield wiper control method according to an embodiment of this application; Figure 3 This is a schematic diagram of a rainfall level determination process based on the fusion of multiple raindrop features according to an embodiment of this application; Figure 4 This is a flowchart illustrating camera failure protection according to one embodiment of this application; Figure 5 This is a schematic diagram illustrating the working principle of a vehicle windshield wiper control method according to an embodiment of this application; Figure 6 This is a block diagram of a vehicle windshield wiper control device according to an embodiment of this application; Figure 7 This is a schematic diagram of the vehicle structure provided in an embodiment of this application.

[0035] Reference numerals: 101-Camera, 102-Smart Cockpit Domain Controller, 103-Windshield Wiper Actuator; 60-Vehicle Windshield Wiper Control Device, 100-Acquisition Module, 200-Output Module, 300-First Control Module; 701-Memory, 702-Processor, 703-Communication Interface. Detailed Implementation

[0036] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0037] The following description, with reference to the accompanying drawings, outlines a vehicle windshield wiper control method, apparatus, vehicle, and storage medium according to embodiments of this application. Addressing the problems mentioned in the background art, such as hardware redundancy, increased vehicle costs, and decreased reliability of rainfall detection in extreme weather conditions due to reliance on dedicated rain sensors, this application provides a vehicle windshield wiper control method. In this method, a current rainfall image of the vehicle is acquired, preprocessed to obtain image information, and then input into a pre-built rainfall analysis model to output rainfall information of the current environment. The method then matches the vehicle's windshield wiper actions based on the rainfall information and generates corresponding control commands based on the wiper actions. This controls the vehicle's windshield wipers in response to the control commands, achieving vehicle windshield wiper control. Compared to using dedicated sensors, this method eliminates redundant hardware and saves hardware space, while also making rainfall detection more accurate and reliable, effectively improving control precision, ensuring the driver's visibility, enhancing the user experience, meeting user needs, and increasing user engagement. Therefore, it solves the problems of hardware redundancy, increased vehicle costs, and decreased reliability of rainfall detection in extreme weather conditions inherent in related technologies due to reliance on dedicated rain sensors.

[0038] Before explaining the vehicle wiper control method provided in the embodiments of this application, the vehicle wiper control system involved in the embodiments of this application will be illustrated first.

[0039] like Figure 1 As shown, the vehicle's windshield wiper control system includes: a camera 101, a smart cockpit domain controller 102, and a wiper actuator 103.

[0040] Among them, the camera 101 can collect image information in front of the car and transmit the image data to the smart cockpit domain controller 102 through CSI (Camera Serial Interface).

[0041] The intelligent cockpit domain controller 102 may include, but is not limited to, an image processor, a neural network processor, and an implementation processor. The image processor can preprocess the image data transmitted from the camera 101, such as image enhancement and image filtering, to provide effective data for rainfall analysis. The neural network processor can extract raindrop features based on the preprocessed image and determine the current rainfall level through model fusion and quantization. The implementation processor can generate corresponding wiper control signals based on the rainfall level.

[0042] The wiper actuator 103 can receive wiper control signals via CAN / LIN (Controller Area Network / Local Interconnect Network) and execute corresponding wiper actions.

[0043] Specifically, Figure 2 This is a flowchart of a vehicle windshield wiper control method provided according to an embodiment of this application.

[0044] like Figure 2 As shown, the vehicle wiper control method includes the following steps: In step S201, the current rainfall image of the vehicle is acquired, and the rainfall image is preprocessed to obtain image information.

[0045] In the embodiments of this application, rainfall images can be understood as images obtained through a vehicle-mounted camera (such as...). Figure 1 Images captured by the vehicle's camera (or similar camera) that reflect rainfall conditions around the vehicle include the distribution of raindrops, the morphological characteristics of the rain curtain, and visual information related to rainfall. These images serve as the foundational data source for subsequent analysis and processing of rainfall, thereby enabling vehicle wiper control.

[0046] In actual implementation, the embodiments of this application can use an in-vehicle camera to capture the current rainfall image in front of the car, and then process the rainfall image through image preprocessing technology to obtain image information.

[0047] Specifically, in one embodiment of this application, preprocessing a rainfall image to obtain image information includes: enhancing the rainfall image to obtain an enhanced image; extracting at least one region of interest from the enhanced image and performing motion compensation on the at least one region of interest to obtain a compensated image; and extracting multiple raindrop features from the compensated image as image information.

[0048] Understandably, in rainy conditions, light levels are prone to being too low, too high, or obscured by fog, leading to low contrast and color imbalance in rainfall images. In practical implementation, this application embodiment can employ techniques such as image denoising, contrast enhancement, and defogging to improve image clarity and strengthen the visual difference between raindrops and the background, thereby obtaining an enhanced image.

[0049] Furthermore, since the rainfall image covers a wide area and contains a large amount of redundant information unrelated to rainfall detection, this embodiment can filter out regions of interest (ROIs) strongly correlated with rainfall detection (such as the main field of view of the windshield and the core area covered by the wipers) from the enhanced image, and remove irrelevant areas such as the vehicle body and the sky, thereby reducing redundant computation. Simultaneously, this embodiment can use motion compensation technology to eliminate inter-frame shifts caused by vehicle vibration and camera shake, ensuring the stability of raindrop positions and trajectories to obtain a compensated image. Subsequently, this embodiment can extract multiple raindrop features reflecting rainfall intensity based on the compensated image, forming structured image information.

[0050] This application embodiment can enhance rainfall images to highlight raindrop features, thereby extracting regions of interest, reducing interference from redundant information, lowering computational complexity, and improving the real-time performance of wiper control. At the same time, motion compensation is used to eliminate inter-frame offset in the image, avoiding misjudgment of raindrop features, thus extracting multiple raindrop features to comprehensively reflect rainfall information and provide a high-quality data foundation for subsequent rainfall analysis model level judgment.

[0051] Optionally, in one embodiment of this application, the multiple raindrop features include at least one of raindrop spatial features, raindrop temporal features, and raindrop frequency features.

[0052] In the embodiments of this application, raindrop spatial features can be understood as features extracted from a single frame of rainfall image that reflect the static distribution state of raindrops in the spatial dimension. These features may include, but are not limited to, the number of raindrops (the number of raindrops in a unit area), spatial coverage (the proportion of the effective area of ​​the image occupied by raindrops), raindrop size (the pixel size of a single raindrop), and spatial distribution density (the degree of aggregation or dispersion of raindrops in the area).

[0053] In addition, raindrop temporal features can be extracted by comparing multiple consecutive rainfall images and extracting the dynamic changes of raindrops in the time dimension. These features may include, but are not limited to, raindrop falling speed (the amount of displacement of raindrops in the image per unit time), consistency of motion trajectory (the stability of raindrop motion paths in multiple frames), and changes in raindrop occurrence frequency (the increasing or decreasing trend of the number of raindrops in different time segments).

[0054] In addition, raindrop frequency domain features can be understood as features extracted after converting a single frame of rainfall image from the spatial domain to the frequency domain through algorithms such as Fourier transform. These features may include, but are not limited to, the proportion of high-frequency components (corresponding to the texture of small and dense raindrops), the energy of low-frequency components (corresponding to the texture of large and sparse raindrops), and the peak value of characteristic frequency bands (typical frequency signals under specific rainfall intensities).

[0055] In actual implementation, the embodiments of this application can extract multiple raindrop features from rainfall images. Using multiple raindrop features as image information can cover raindrop spatial features, raindrop temporal features, and raindrop frequency features, providing a comprehensive basis for judgment of rainfall analysis models and avoiding correlation bias caused by a single feature.

[0056] The embodiments of this application can avoid the limitations of a single feature by offering multiple raindrop features as options, thereby improving the accuracy of rainfall analysis and ensuring its reliability. Even if a certain feature is interfered with, other features can still provide support, thus improving the reliability of wiper control.

[0057] In step S202, the image information is input into a pre-built rainfall analysis model to output the rainfall information of the current environment.

[0058] In the embodiments of this application, the rainfall analysis model can be understood as an intelligent computing tool built based on machine learning or deep learning algorithms. It takes image information as input and transforms visual features into actual rainfall results through pre-learned association rules between image information and rainfall information.

[0059] In addition, rainfall information can be understood as standardized data reflecting the current rainfall intensity in the environment. It can be presented using rainfall status, specific rainfall values ​​and rainfall levels, and used to support functions such as windshield wiper control.

[0060] In actual implementation, the embodiments of this application can be trained with massive amounts of image information and rainfall information samples, and the association rules between image information and rainfall information can be mastered with the help of machine learning or deep learning algorithms. A rainfall analysis model can be pre-built, and then new image information can be input. The rainfall analysis model can call parameters to perform calculations, and the mapping between image information and rainfall information can be completed according to the association rules, thereby outputting the rainfall information of the current environment.

[0061] Specifically, in one embodiment of this application, image information is input into a pre-built rainfall analysis model to output rainfall information of the current environment, including: based on the rainfall analysis model, multiple raindrop features are fused according to the weights corresponding to each raindrop feature to obtain fused features; the fused features are matched with the actual rainfall level of the current environment as rainfall information.

[0062] In the embodiments of this application, the fusion feature can be understood as a feature that comprehensively reflects the rainfall status after weighting and fusing multiple raindrop features according to preset weights. The preset weights can be understood as the weights corresponding to the raindrop features determined through training during the construction of the rainfall analysis model, reflecting the contribution of raindrop features to the determination of rainfall level in different rainfall scenarios. For example, in heavy rain scenarios, the weight of raindrop movement speed is higher, while in light rain scenarios, the weight of raindrop coverage is higher.

[0063] In addition, the actual rainfall level can be understood as the actual rainfall intensity level in the current environment, determined according to the fusion characteristics and the rainfall level classification rules. The rainfall level classification rules can be understood as the rules for classifying rainfall levels according to the rainfall state, such as classifying the five rainfall states of no rain, light rain, moderate rain, heavy rain, and rainstorm into five rainfall levels of 0, 1, 2, 3, and 4 respectively.

[0064] In practical implementation, this embodiment of the application can determine the weights corresponding to raindrop features based on a rainfall analysis model. When image information is input into the rainfall analysis model, that is, when multiple raindrop features are input into the rainfall analysis model, the multiple raindrop features can be weighted and fused according to preset weights to obtain a fused feature that comprehensively reflects the rainfall status. Subsequently, according to the correspondence rules between the fused feature and the actual rainfall level, the matching between the fused feature and the actual rainfall level is completed to output the rainfall information of the current environment. For example, such as Figure 3 As shown, this embodiment of the application can extract four raindrop features from a rainfall image: raindrop count, raindrop coverage, raindrop movement speed, and raindrop texture intensity. Subsequently, preset weights can be assigned to each of the four raindrop features to reflect the importance of each raindrop feature in determining the rainfall level. Then, through feature fusion, the four weighted raindrop features can be comprehensively calculated to obtain a fused feature that can comprehensively reflect the rainfall state. Thus, based on the fused feature, the actual rainfall level of the current environment can be matched from five rainfall levels: 0, 1, 2, 3, and 4.

[0065] The embodiments of this application can obtain fused features based on multiple raindrop features, integrate multi-dimensional rainfall information, avoid the one-sidedness of a single feature, improve the accuracy of rainfall level determination, provide accurate basis for subsequent wiper control, and ensure the effectiveness and intelligence of wiper control of vehicles in different rainfall scenarios.

[0066] In step S203, the wiper action of the vehicle is matched according to the rainfall information, and a corresponding control command is generated according to the wiper action to control the vehicle wipers to respond to the control command.

[0067] In the embodiments of this application, the control command can be understood as the wiper action control command generated by the cockpit domain controller based on the rainfall information. It is an abstract logical command that does not have a physical form. When executed, it can be converted into a specific control signal and transmitted to the wiper actuator.

[0068] In actual implementation, the embodiments of this application can match the wiper action of the vehicle's wipers according to the rainfall information, that is, the actual rainfall level of the current environment, and then generate a control signal, which is transmitted to the wiper actuator to drive the wipers to perform the corresponding wiper action according to the control signal.

[0069] Specifically, as shown in the table below, the mapping relationship between rainfall level, rainfall status, control signal, and wiper action is illustrated. The rainfall level categorizes rainfall into five levels—0, 1, 2, 3, and 4—based on intensity, serving as a digital identifier for rainfall. The rainfall status corresponds to the actual rainfall conditions within the rainfall level, categorized as no rain, light rain, moderate rain, heavy rain, and torrential rain. The control signal controls the wiper actuator through the duty cycle of PWM (Pulse Width Modulation); a larger duty cycle results in stronger wiper action. Wiper action refers to the specific operating mode executed by the wipers based on the control signal, categorized as off, intermittent low speed, continuous low speed, continuous medium speed, and continuous high speed.

[0070]

[0071] Optionally, in one embodiment of this application, the method further includes: receiving a user's manual correction instruction; adjusting the control instruction according to the manual correction instruction; and updating the rainfall analysis model based on the manual correction instruction.

[0072] Understandably, although rainfall analysis models can automatically generate rainfall information based on image data, and this rainfall information can be converted into control commands, special interferences (such as glass smudges) may exist in real-world scenarios, causing deviations between the control commands and the user's desired wiper performance. At the same time, different users have different preferences for wiper speed (such as some users prefer slightly faster wipers in moderate rain). Therefore, by receiving manual correction commands from users, the system can adapt to user needs in real time and optimize the model using the correction data, thus compensating for the limitations of automatic control.

[0073] In actual implementation, this application embodiment can receive manual correction commands from users through interactive components such as the wiper control lever and the central control touch screen. On the one hand, this application embodiment can directly convert and adjust logic using manual correction commands, modifying the current wiper control command in real time (e.g., adjusting the original 50% duty cycle PWM signal to an 80% duty cycle PWM signal, corresponding to the wiper switching from continuous low speed to continuous medium speed). On the other hand, this application embodiment can automatically associate the scene data at the time the manual correction command is generated, which may include, but is not limited to, the image information, rainfall information, and the original control command at that time. The scene data and the manual correction command are used as new labeled samples input into the rainfall analysis model, and the model parameters are updated through iterative training (e.g., adjusting raindrop feature weights and optimizing rainfall level matching rules) to generate control commands that better fit the user's correction logic.

[0074] This application embodiment can receive manual correction commands from users to adjust control commands, so as to quickly respond to users' needs for adjusting the wiper effect, avoid deviation between automatic control commands and actual usage preferences, and update the rainfall analysis model according to the manual correction commands to continuously optimize the rainfall analysis model, gradually reduce the deviation between automatic commands and user expectations, reduce the frequency of subsequent manual corrections, make automatic control more accurate and more in line with user habits, and improve the intelligence and humanization level of wiper control.

[0075] Optionally, in one embodiment of this application, before acquiring the current rainfall image of the vehicle, the method further includes: obtaining the confidence level of the image acquisition device corresponding to the current rainfall image; obtaining the current processing confidence interval of the confidence level; if the current processing confidence interval is a first interval, controlling the vehicle to enter the automatic wiper control mode; if the current processing confidence interval is a second interval, detecting whether the image acquisition device is obstructed, and issuing an obstruction reminder when obstruction is detected, so that after clearing the obstruction, the vehicle is controlled to enter the automatic wiper control mode; if the current processing confidence interval is a third interval, controlling the vehicle to enter the manual wiper mode.

[0076] It is understandable that the condition of image acquisition equipment (such as a camera) directly affects the reliability of rainfall images. When the equipment malfunctions, is obstructed, or has insufficient acquisition accuracy, the input data of the rainfall analysis model may be distorted, leading to automatic wiper control errors (such as misjudging rainfall and causing abnormal wiper operation). Therefore, the embodiments of this application can first assess the equipment confidence level and divide it into intervals, and dynamically switch the control mode according to the reliability level, so as to ensure the accuracy of wiper control while avoiding the impact of equipment problems on driving safety.

[0077] In some cases, embodiments of this application can pre-set a confidence threshold to divide the confidence level of the image acquisition device into three intervals corresponding to different data reliability levels: the first interval, the second interval, and the third interval. The first interval is the high reliability interval, referring to a range where the device's acquired data has high reliability, no significant interference, and can provide accurate input for the rainfall analysis model; an example value is "confidence level ≥ 80%". The second interval is the medium reliability interval, referring to a range where the device's acquired data has moderate reliability, but recoverable interference exists, allowing for the elimination of interference before use; an example value is "50% ≤ confidence level < 80%". The third interval is the low reliability interval, referring to a range where the device's acquired data has low reliability, contains anomalies that cannot be quickly recovered, and cannot support automatic control; an example value is "confidence level < 50%".

[0078] In actual implementation, this embodiment of the application can obtain the confidence level of the image acquisition device and the current interval before acquiring the rainfall image. Further, when the current interval is the first interval, this embodiment of the application can control the vehicle to enter the automatic wiper control mode; when the current interval is the second interval, this embodiment of the application first detects whether the device is obstructed, and if obstruction exists, reminds the driver to clear it before entering automatic mode; when the current interval is the third interval, this embodiment of the application can control the vehicle to switch to manual wiper mode.

[0079] For example, such as Figure 4 As shown, the specific steps in camera failure protection are as follows: Step S401: Obtain camera confidence level.

[0080] Step S402: Is it in the first interval?

[0081] In this embodiment of the application, it can be determined whether the confidence level of the camera is in the first interval. If it is in the first interval, it indicates that the reliability of the rainfall image collected by the camera is high, and step S403 can be executed. If it is not in the first interval, step S404 is executed.

[0082] Step S403: Execute automatic mode.

[0083] Step S404: Is it in the second interval?

[0084] In this embodiment of the application, it can determine whether the camera is in the second interval. If it is in the second interval, step S405 can be executed; if it is not in the second interval, step S407 can be executed.

[0085] Step S405: Detect whether the camera is obstructed.

[0086] In this embodiment of the application, step S406 can be executed when the camera is blocked.

[0087] Step S406: Remind the driver to remove the obstacle.

[0088] Step S407: Downgrade to manual mode.

[0089] This application embodiment can dynamically switch control modes according to the device confidence level. When the reliability is high, it ensures the accuracy of automatic control. When the reliability is medium, it eliminates recoverable interference through occlusion reminders to maintain the availability of automatic functions. When the reliability is low, it promptly degrades to manual mode to avoid miscontrol caused by device malfunctions. It comprehensively ensures clear driving visibility and operational safety in rainy weather, and improves the adaptability of device status changes and the reliability of wiper control.

[0090] The vehicle wiper control method proposed in this application will be described below with reference to a specific embodiment.

[0091] Figure 5 This is a schematic diagram illustrating the working principle of a vehicle windshield wiper control method according to an embodiment of this application.

[0092] Step S501: Acquire images.

[0093] In this embodiment, the current rainfall image of the vehicle's environment can be captured by a camera.

[0094] Step S502: Enhance the image.

[0095] In this embodiment of the application, image enhancement processing can be used to improve the recognizability of raindrop features after image acquisition.

[0096] Step S503: Select the region of interest.

[0097] In this embodiment of the application, after image enhancement, a region of interest in the image can be selected to filter out irrelevant background information.

[0098] Step S504: Compensate the image.

[0099] In this application embodiment, motion compensation can be performed to eliminate image distortion caused by vehicle movement or camera shake.

[0100] Step S505: Extract and fuse multiple raindrop features.

[0101] Among them, multiple raindrop features include spatial features, temporal features, and frequency domain features.

[0102] Step S506: Generate image information.

[0103] In this embodiment, image information can be generated based on the features of multiple raindrops after fusion.

[0104] Step S507: Match rainfall levels.

[0105] In this embodiment of the application, the rainfall level of the current environment can be matched with the image information through a rainfall analysis model to reflect no rain, light rain, moderate rain, heavy rain and rainstorm as rainfall information.

[0106] Step S508: Generate control commands.

[0107] In this embodiment, the wiper actions of the vehicle are matched with rainfall information, and control commands are generated based on the wiper actions. These control commands are then transmitted to the wiper actuator to control the vehicle's wipers to perform corresponding actions, achieving precise adaptation between the wiper operating status and real-time rainfall, thus ensuring clear visibility while driving in rainy weather. It should be noted that the control commands are specifically manifested as control signals, namely PWM signals with different duty cycles.

[0108] The vehicle wiper control method proposed in this application can acquire the current rainfall image of the vehicle, preprocess the rainfall image to obtain image information, and then input the image information into a pre-built rainfall analysis model to output the rainfall information of the current environment. Based on the rainfall information, the wiper action of the vehicle is matched, and corresponding control commands are generated according to the wiper action to control the vehicle wipers in response to the control commands, thus realizing vehicle wiper control. Compared with setting up a dedicated sensor, this method not only eliminates redundant hardware and saves hardware space, but also makes rainfall detection more accurate and reliable, effectively improving control precision, ensuring the driver's visibility, effectively improving the user experience, meeting user needs, and increasing user stickiness. Therefore, it solves the problems of related technologies that rely on dedicated rainfall sensors, leading to hardware redundancy, increased vehicle costs, and decreased reliability of rainfall detection in extreme weather conditions.

[0109] Next, the vehicle windshield wiper control device according to an embodiment of this application is described with reference to the accompanying drawings.

[0110] Figure 6 This is a block diagram of a vehicle windshield wiper control device provided according to an embodiment of this application.

[0111] like Figure 6 As shown, the vehicle wiper control device 60 includes: a data acquisition module 100, an output module 200, and a first control module 300.

[0112] The acquisition module 100 is used to acquire the current rainfall image of the vehicle and preprocess the rainfall image to obtain image information.

[0113] The output module 200 is used to input image information into a pre-built rainfall analysis model to output rainfall information of the current environment.

[0114] The first control module 300 is used to match the wiper action of the vehicle's wipers according to the rainfall information, and generate corresponding control commands according to the wiper action to control the vehicle's wipers to respond to the control commands.

[0115] Optionally, in one embodiment of this application, the acquisition module 100 includes: an enhancement unit, a compensation unit, and an extraction unit.

[0116] The enhancement unit is used to enhance the rainfall image to obtain an enhanced image.

[0117] The compensation unit is used to extract at least one region of interest from the enhanced image and perform motion compensation on the at least one region of interest to obtain the compensated image.

[0118] The extraction unit is used to extract multiple raindrop features from the compensated image as image information.

[0119] Optionally, in one embodiment of this application, the output module 200 includes a fusion unit and a matching unit.

[0120] The fusion unit is used to fuse multiple raindrop features based on the weights corresponding to each raindrop feature, according to the rainfall analysis model, to obtain the fused features.

[0121] The matching unit is used to match the actual rainfall level of the current environment based on the fusion features, as rainfall information.

[0122] Optionally, in one embodiment of this application, the multiple raindrop features include at least one of raindrop spatial features, raindrop temporal features, and raindrop frequency features.

[0123] Optionally, in one embodiment of this application, it further includes a receiving module and an updating module.

[0124] The receiving module is used to receive manual correction commands from users.

[0125] The update module is used to adjust control commands based on manual correction instructions and update the rainfall analysis model based on manual correction instructions.

[0126] Optionally, in one embodiment of this application, before acquiring the current rainfall image of the vehicle, the system further includes: a first acquisition module, a second acquisition module, a second control module, a third control module, and a fourth control module.

[0127] The first acquisition module is used to acquire the confidence level of the image acquisition device corresponding to the current rainfall image.

[0128] The second acquisition module is used to acquire the current confidence interval of the confidence level.

[0129] The second control module is used to control the vehicle to enter the automatic wiper control mode when the current information interval is the first interval.

[0130] The third control module is used to detect whether the image acquisition device is obstructed when the current processing information interval is the second interval, and to issue an obstruction reminder when obstruction is detected, so as to control the vehicle to enter the automatic wiper control mode after the obstruction is cleared.

[0131] The fourth control module is used to control the vehicle to enter manual wiper mode when the current signal interval is the third interval.

[0132] It should be noted that the foregoing explanation of the vehicle wiper control method embodiment also applies to the vehicle wiper control device of this embodiment, and will not be repeated here.

[0133] The vehicle wiper control device proposed in this application can acquire current rainfall images of the vehicle, preprocess the rainfall images to obtain image information, and then input the image information into a pre-built rainfall analysis model to output the rainfall information of the current environment. Based on the rainfall information, the wiper actions of the vehicle are matched, and corresponding control commands are generated according to the wiper actions to control the vehicle wipers in response to the control commands, thus achieving vehicle wiper control. Compared with setting up a dedicated sensor, this not only eliminates the need for redundant hardware and saves hardware space, but also makes rainfall detection more accurate and reliable, effectively improving control precision, ensuring the driver's visibility, effectively improving the user experience, meeting user needs, and increasing user stickiness. Therefore, it solves the problems of related technologies that rely on dedicated rain sensors, leading to hardware redundancy, increased vehicle costs, and decreased reliability of rainfall detection in extreme weather conditions.

[0134] Figure 7 A schematic diagram of the structure of a vehicle provided in an embodiment of this application. The vehicle may include: The memory 701, the processor 702, and the computer program stored on the memory 701 and executable on the processor 702.

[0135] When processor 702 executes the program, it implements the vehicle windshield wiper control method provided in the above embodiments.

[0136] Furthermore, the vehicle also includes: Communication interface 703 is used for communication between memory 701 and processor 702.

[0137] The memory 701 is used to store computer programs that can run on the processor 702.

[0138] The memory 701 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0139] If the memory 701, processor 702, and communication interface 703 are implemented independently, then the communication interface 703, memory 701, and processor 702 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized into address buses, data buses, control buses, etc. For ease of representation, Figure 7 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0140] Optionally, in a specific implementation, if the memory 701, processor 702, and communication interface 703 are integrated on a single chip, then the memory 701, processor 702, and communication interface 703 can communicate with each other through an internal interface.

[0141] The processor 702 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0142] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the vehicle windshield wiper control method described above.

[0143] This application also provides a computer program product, including a computer program that, when executed, implements the vehicle windshield wiper control method described above.

[0144] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0145] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0146] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0147] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0148] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0149] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0150] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0151] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for controlling vehicle windshield wipers, characterized in that, Applied to intelligent cockpit domain controllers, the method includes the following steps: The current rainfall image of the vehicle is acquired, and the rainfall image is preprocessed to obtain image information; The image information is input into a pre-built rainfall analysis model to output rainfall information for the current environment; and The vehicle's windshield wiper actions are matched with the rainfall information, and corresponding control commands are generated based on the wiper actions to control the vehicle's windshield wipers to respond to the control commands.

2. The method according to claim 1, characterized in that, The preprocessing of the rainfall image to obtain image information includes: The rainfall image is enhanced to obtain an enhanced image; At least one region of interest is extracted from the enhanced image, and motion compensation is performed on the at least one region of interest to obtain a compensated image; Multiple raindrop features are extracted from the compensated image and used as the image information.

3. The method according to claim 2, characterized in that, The step of inputting the image information into a pre-built rainfall analysis model to output the rainfall information of the current environment includes: Based on the rainfall analysis model, the multiple raindrop features are fused according to the weights corresponding to each raindrop feature to obtain the fused features; The actual rainfall level of the current environment is matched with the fusion features to obtain the rainfall information.

4. The method according to claim 3, characterized in that, The plurality of raindrop features include at least one of raindrop spatial features, raindrop temporal features, and raindrop frequency features.

5. The method according to claim 3 or 4, characterized in that, Also includes: Receive manual correction commands from users; The control command is adjusted according to the manual correction command, and the rainfall analysis model is updated based on the manual correction command.

6. The method according to claim 1, characterized in that, Before acquiring the current rainfall image of the vehicle, the following is also included: Obtain the confidence level of the image acquisition device corresponding to the current rainfall image; Obtain the current processed confidence interval of the confidence level; If the currently processed information interval is the first interval, control the vehicle to enter the automatic wiper control mode; When the currently processed information interval is the second interval, the system detects whether the image acquisition device is obstructed and issues an obstruction reminder when obstruction is detected, so that after the obstruction is cleared, the system controls the vehicle to enter the automatic wiper control mode. If the currently processed information interval is the third interval, control the vehicle to enter the windshield wiper manual mode.

7. A vehicle windshield wiper control device, characterized in that, include: The acquisition module is used to acquire the current rainfall image of the vehicle and preprocess the rainfall image to obtain image information; The output module is used to input the image information into a pre-built rainfall analysis model to output the rainfall information of the current environment; as well as The control module is used to match the wiper action of the vehicle's windshield wipers according to the rainfall information, and generate corresponding control commands according to the wiper actions, so as to control the vehicle's windshield wipers to respond to the control commands.

8. A vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the vehicle wiper control method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the vehicle windshield wiper control method as described in any one of claims 1-6.

10. A computer program product, characterized in that, When the computer program is executed, it is used to implement the vehicle windshield wiper control method as described in any one of claims 1-6.

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