Adaptive control method and system for windshield wiper of vehicle, device, and vehicle

Abstract

An adaptive control method and system for a windshield wiper of a vehicle, an electronic device and computer-readable storage medium for implementing the method, and a vehicle comprising the system or the electronic device. The adaptive control method comprises: acquiring the current field-of-view blur score, windshield wiper working state, dynamic blur threshold and vehicle data of a target vehicle, wherein the vehicle data includes at least one of vehicle speed data, vehicle spacing data, or behavior data of an adjacent vehicle; performing dynamic threshold updating on the dynamic blur threshold on the basis of the vehicle data to obtain an updated dynamic blur threshold; performing windshield wiper state prediction on the current field-of-view blur score on the basis of the updated dynamic blur threshold to obtain a target working state; and updating the current windshield wiper working state on the basis of the target working state. The adaptive control method can improve the timeliness and accuracy of windshield wiper control, thereby improving the driving experience and driving safety of drivers.

Description

Self-adaptive control method, system, device and vehicle for vehicle wiper TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, and in particular to a self-adaptive control method, system, device and vehicle for vehicle wiper. BACKGROUND

[0002] There are two ways to adjust the vehicle wiper, namely manual control and automatic control. The automatic control is increasingly concerned by people because it can assist the driver to control the vehicle wiper, reduce the interference of wiper control on the driver, and improve the driving attention.

[0003] The traditional automatic control method usually adjusts the speed or working state of the wiper based on the rainfall data obtained by the rainfall sensor. However, the timeliness and accuracy of the wiper adjustment are not satisfactory, and the driving experience and safety of the driver are not good.

[0004] Therefore, the technical problems in the related art need to be improved.

[0005] SUMMARY

[0006] The present application aims to at least partially solve one of the technical problems in the related art.

[0007] The main purpose of the embodiments of the present application is to provide a self-adaptive control method, system, device and vehicle for vehicle wiper, which can improve the timeliness and accuracy of wiper control, and improve the driving experience and safety of the driver.

[0008] To achieve the above-mentioned purpose, one aspect of the embodiments of the present application provides a self-adaptive control method for vehicle wiper, comprising:

[0009] obtaining the current visual field blur score, wiper working state, dynamic blur threshold and vehicle data of the target vehicle, wherein the vehicle data includes at least one of vehicle speed data, vehicle distance data or adjacent vehicle behavior data;

[0010] According to the vehicle data, the dynamic blur threshold is dynamically updated to obtain an updated dynamic blur threshold;

[0011] According to the updated dynamic blur threshold, the current visual field blur score is predicted to obtain a target working state, wherein the target working state includes any one of high-speed continuous state, low-speed continuous state, intermittent state or off state;

[0012] According to the target working state, the current wiper working state is updated.

[0013] In addition, the adaptive control method of the vehicle wiper according to the above-mentioned embodiments of the present application can further have the following additional technical features.

[0014] In some embodiments, the field of view blur score is obtained by the following steps:

[0015] obtaining a field of view image from the target vehicle windshield;

[0016] preprocessing the field of view image to obtain a field of view intermediate image;

[0017] based on a preset Laplacian operator, performing image evaluation on the field of view intermediate image to obtain the field of view blur score.

[0018] In some embodiments, the dynamic threshold updating of the dynamic blur threshold according to the vehicle data to obtain the updated dynamic blur threshold comprises:

[0019] obtaining a preset steady-state blur threshold and a vehicle adaptive adjustment coefficient corresponding to the vehicle data;

[0020] performing dynamic transformation on the steady-state blur threshold according to the vehicle adaptive adjustment coefficient to obtain a dynamic transformation threshold;

[0021] performing threshold replacement on the dynamic blur threshold according to the dynamic transformation threshold to obtain the updated dynamic blur threshold.

[0022] In some embodiments, the vehicle adaptive adjustment coefficient is obtained by the following steps:

[0023] obtaining at least one of a vehicle speed adjustment coefficient corresponding to the vehicle speed data, a distance adjustment coefficient corresponding to the vehicle distance data, or a behavior adjustment coefficient corresponding to the behavior data of the adjacent vehicle;

[0024] generating the vehicle adaptive adjustment coefficient according to at least one of the obtained vehicle speed adjustment coefficient, the distance adjustment coefficient, or the behavior adjustment coefficient;

[0025] wherein the vehicle speed adjustment coefficient is negatively correlated with the vehicle speed data, the distance adjustment coefficient is positively correlated with the vehicle distance data, and the behavior adjustment coefficient is negatively correlated with the behavior data of the adjacent vehicle.

[0026] In some embodiments, the dynamic blur threshold comprises a first blur threshold, a second blur threshold, and a third blur threshold, and the wiper state prediction of the field of view blur score according to the dynamic blur threshold to obtain the target working state comprises:

[0027] comparing the dynamic blur threshold and the field-of-view blur score to obtain a blur comparison result;

[0028] If the blur comparison result is that the field-of-view blur score is less than the first blur threshold, it is determined that the target working state of the target vehicle wiper is a high-speed continuous state; or, if the blur comparison result is that the field-of-view blur score is greater than or equal to the first blur threshold and less than the second blur threshold, it is determined that the target working state of the target vehicle wiper is a low-speed continuous state; or, if the blur comparison result is that the field-of-view blur score is greater than or equal to the second blur threshold and less than the third blur threshold, it is determined that the target working state of the target vehicle wiper is an intermittent state; or, if the blur comparison result is that the field-of-view blur score is greater than or equal to the third blur threshold, it is determined that the target working state of the target vehicle wiper is a closed state.

[0029] In some embodiments, the adaptive control method further comprises:

[0030] obtaining a current system sensitivity, the system sensitivity being used to represent an update frequency of the current wiper working state and a threshold adjustment amplitude of the dynamic blur threshold;

[0031] performing a sensitive threshold update on the dynamic blur threshold according to the current system sensitivity to obtain an updated dynamic blur threshold.

[0032] In some embodiments, the system sensitivity is updated by the following steps:

[0033] obtaining current vehicle data and environmental data, and a preset sensitive update amplitude, environmental sensitive conditions and vehicle sensitive conditions;

[0034] performing an environmental condition determination on the current environmental data according to the environmental sensitive conditions to obtain an environmental sensitive determination result, and performing a vehicle condition determination on the current vehicle data according to the vehicle sensitive conditions to obtain a vehicle sensitive determination result;

[0035] if the environmental sensitive determination result is an environmental high risk or the vehicle sensitive determination result is a vehicle high risk, performing a sensitive update on the current system sensitivity according to the sensitive update amplitude; or, if the environmental sensitive determination result is an environmental low risk and the vehicle sensitive determination result is a vehicle low risk, performing a sluggish update on the current system sensitivity according to the sensitive update amplitude.

[0036] In some embodiments, the vehicle sensitivity condition comprises at least one of a vehicle speed condition, a vehicle distance condition, or a neighboring vehicle behavior condition, the vehicle condition determination on the current vehicle data according to the vehicle sensitivity condition comprises:

[0037] The vehicle speed condition is determined according to the vehicle speed data to obtain a vehicle speed determination result, or the vehicle distance condition is determined according to the vehicle distance data to obtain a distance determination result, or the neighboring vehicle behavior condition is determined according to the neighboring vehicle behavior data to obtain a behavior determination result.

[0038] At least one of the vehicle speed determination result, the distance determination result, or the behavior determination result is integrated to obtain the vehicle sensitivity determination result.

[0039] In some embodiments, the environmental sensitivity condition comprises an environmental luminosity condition and an environmental rainfall condition, the environmental data comprises luminosity data and rainfall data, and the environmental condition determination on the current environmental data according to the environmental sensitivity condition comprises:

[0040] The luminosity condition is determined according to the luminosity data to obtain a luminosity determination result, and the rainfall condition is determined according to the rainfall data to obtain a rainfall determination result.

[0041] The luminosity determination result and the rainfall determination result are integrated to obtain the environmental sensitivity determination result.

[0042] To achieve the above object, another aspect of the embodiment of the present application proposes a self-adaptive control system of a vehicle wiper, comprising:

[0043] An acquisition unit is configured to acquire a current visual field blur score of a target vehicle, a wiper working state, a dynamic blur threshold, and vehicle data, wherein the vehicle data comprises at least one of vehicle speed data, vehicle distance data, or neighboring vehicle behavior data.

[0044] A threshold updating unit is configured to perform dynamic threshold updating on the dynamic blur threshold according to the vehicle data to obtain an updated dynamic blur threshold.

[0045] A state prediction unit is configured to perform wiper state prediction on the current visual field blur score according to the updated dynamic blur threshold to obtain a target working state, wherein the target working state comprises any one of a high-speed continuous state, a low-speed continuous state, an intermittent state, or an off state.

[0046] a state updating unit configured to update the current wiper working state according to the target working state.

[0047] To achieve the above object, another aspect of the embodiments of the present application provides an electronic device, which comprises a memory and a processor, the memory stores a computer program, and the processor implements the above method when executing the computer program.

[0048] To achieve the above object, another aspect of the embodiments of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above method.

[0049] To achieve the above object, another aspect of the embodiments of the present application provides a vehicle, which comprises the above vehicle lamp control system or the above electronic device.

[0050] The embodiments of the present application at least have the following beneficial effects:

[0051] The present application provides a vehicle wiper adaptive control method, system, device and vehicle, wherein the adaptive control method obtains the current visual field blur score of the target vehicle, the wiper working state, the dynamic blur threshold and the vehicle data, the vehicle data comprises at least one of the vehicle speed data, the vehicle distance data or the adjacent vehicle behavior data; according to the vehicle data, the dynamic blur threshold is dynamically updated to obtain the updated dynamic blur threshold; according to the updated dynamic blur threshold, the current visual field blur score is predicted to obtain the target working state, the target working state comprises any one of the high-speed continuous state, the low-speed continuous state, the intermittent state or the closed state; according to the target working state, the current wiper working state is updated. The adaptive control method dynamically updates the dynamic blur threshold by real-time acquisition of the vehicle data, which can make the dynamic blur threshold adaptively change according to the actual situation, and the wiper state prediction based on the adaptively changed dynamic blur threshold and the real-time acquired visual field blur score can make the wiper control more flexible to cope with different situations, improve the response speed and accuracy of the wiper control (i.e. improve the timeliness and accuracy of the wiper control), thereby improving the driving experience and driving safety of the driver. BRIEF DESCRIPTION OF DRAWINGS

[0052] Fig. 1 is a flow diagram of a vehicle wiper adaptive control method provided by the embodiments of the present application;

[0053] Fig. 2 is a flow diagram of a visual field blur score provided by the embodiments of the present application;

[0054] FIG. 3 is a detailed flowchart of step S120 according to an embodiment of the present application;

[0055] FIG. 4 is a detailed flowchart of acquiring the adaptive adjustment coefficient of the vehicle according to an embodiment of the present application;

[0056] FIG. 5 is a detailed flowchart of step S130 according to an embodiment of the present application;

[0057] FIG. 6 is a flowchart of an optional adaptive control method of the vehicle wiper according to an embodiment of the present application;

[0058] FIG. 7 is a flowchart of acquiring the system sensitivity according to an embodiment of the present application;

[0059] FIG. 8 is a detailed flowchart of step F2 according to an embodiment of the present application;

[0060] FIG. 9 is a structural diagram of an adaptive control system of the vehicle wiper according to an embodiment of the present application;

[0061] FIG. 10 is a hardware structural diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0062] The present application will be further described in detail. It should be understood that the specific examples described herein are intended to explain the present application and are not intended to limit the present application. When the following description refers to the accompanying drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with some aspects of the present embodiments, but are merely examples of apparatuses / devices and methods consistent with some aspects of the present embodiments as detailed in the appended claims.

[0063] It can be understood that the terms "first", "second", and the like as used herein can be used to describe various concepts, but unless specifically stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information, without departing from the scope of the present embodiments. Depending on the context, the word "if" as used herein can be interpreted as "when" or "upon" or "in response to determining" as used herein.

[0064] The terms "at least one", "multiple", "each", "any", and the like used herein include one, two, or more than two, multiple includes two or more than two, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0065] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to be limiting of this application.

[0066] At present, the traditional automatic control wiper mode is usually to adjust the wiper speed or working state based on the rainfall data obtained by the rainfall sensor, and this mode is specifically realized by setting a specific rainfall threshold. However, in the driving process of the vehicle, the rainfall sensor needs to be in contact with the rainwater to identify the rainfall size, and in special cases (such as water mist caused by adjacent vehicle tires, dirty windshield of the vehicle, etc.), the timeliness and accuracy of the wiper control are not satisfactory, which makes the driving vision of the driver not clear, and the driving safety and driving experience are not high.

[0067] Therefore, in the embodiments of the present application, a self-adaptive control method, system, device and vehicle for vehicle wiper are provided, wherein the self-adaptive control method can dynamically update the dynamic blur threshold by real-time acquisition of target vehicle data, so that the dynamic blur threshold can be self-adaptively changed according to the actual situation, and the wiper state can be predicted based on the self-adaptively changed dynamic blur threshold and the real-time acquired vision blur score, so that the wiper control can more flexibly cope with different situations, improve the response speed and accuracy of the wiper control (i.e. improve the timeliness and accuracy of the wiper control), and keep the driving vision clear more timely, thereby improving the driving experience and driving safety of the driver.

[0068] In addition, the self-adaptive control method also updates the wiper working state based on the real-time acquired system sensitivity, and / or updates the dynamic blur threshold based on the real-time acquired system sensitivity, which can timely and accurately control the wiper according to the actual situation, so as to make the driving vision of the driver clear and improve the driving safety, and further improve the matching degree between the wiper working state and the actual situation (i.e. vision blur score, vehicle data, etc.) in the driving process, thereby improving the driving experience of the driver.

[0069] The adaptive control method of the vehicle wiper provided in the embodiments of the present application can be applied to a terminal, can be applied to a server, and can also be software running in the terminal or the server. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a vehicle-mounted terminal, and the like, but is not limited thereto. The server end can be configured as a stand-alone physical server, can be configured as a server cluster or a distributed system formed by multiple physical servers, can be configured as a cloud server providing basic cloud computing services such as cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN, and big data and artificial intelligence platform, and the server can also be a node server in a blockchain network. The software can be an application that implements the method, but is not limited to the above forms.

[0070] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present application can also be practiced in a distributed computing environment, in which tasks are performed by remote processing devices connected by a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0071] Referring to FIG. 1, FIG. 1 is an optional flowchart of the adaptive control method of the vehicle wiper provided in the embodiments of the present application. The method in FIG. 1 can include, but is not limited to, steps S110 to S140.

[0072] Step S110, obtaining the current visual field blur score of the target vehicle, the wiper working state, the dynamic blur threshold, and the vehicle data, the vehicle data including at least one of the vehicle speed data, the vehicle distance data, or the adjacent vehicle behavior data;

[0073] In the embodiments of the present application, the current field of view blur score, the wiper working state, the dynamic blur threshold and the vehicle data can be real-time related data of the target vehicle, that is, the wiper working state can be the state of the vehicle data wiper at the current time, and the state includes any one of a high-speed continuous state, a low-speed continuous state, an intermittent state and an off state; and the dynamic blur threshold is a self-adaptive threshold, which is used to represent the blur threshold corresponding to the wiper working state under the current field of view blur score and the vehicle data of the target vehicle at the current time.

[0074] Specifically, the vehicle speed data in the vehicle data can be the vehicle speed of the target vehicle (i.e., the vehicle driven by the driver) at the current time, the vehicle distance data can be the distance between the target vehicle and the front vehicle, the adjacent vehicle behavior data can be the traffic flow around the target vehicle, and the driving behavior data of the adjacent vehicle, which includes adjacent lane changing, straight driving, adjacent far lane changing, etc., wherein the adjacent lane changing indicates that the adjacent vehicle changes lane to the side of the target vehicle, and the adjacent far lane changing indicates that the adjacent vehicle changes lane to the opposite side of the target vehicle.

[0075] Referring to FIG. 2, in some embodiments, the field of view blur score is obtained by the following steps:

[0076] A1, obtaining a field of view image from the windshield of the target vehicle;

[0077] A2, preprocessing the field of view image to obtain a field of view intermediate image;

[0078] A3, based on a preset Laplacian operator, performing image evaluation on the field of view intermediate image to obtain the field of view blur score.

[0079] In the embodiments of the present application, the field of view image at the windshield can be captured by setting a camera device at a proper position inside or outside the vehicle; then, the preprocessing of the field of view image can be image enhancement, denoising processing, grayscale, binarization, image augmentation and the like to obtain the field of view intermediate image; and then, based on the preset Laplacian operator, the field of view blur degree of the field of view intermediate image is evaluated by calculating the Laplacian transform of the field of view image, so as to obtain the field of view blur score.

[0080] It should be noted that the field of view blur score can be used to evaluate the blur degree of the field of view image, or to evaluate the un-blur degree of the field of view image. In the embodiments of the present application, the field of view blur score is used as an example to evaluate the un-blur degree of the field of view image, and the higher the field of view blur score is, the clearer the corresponding field of view image is.

[0081] Step S120, dynamically updating the dynamic blur threshold according to the vehicle data to obtain an updated dynamic blur threshold;

[0082] Referring to FIG. 3, in some embodiments, the step S120 dynamically updates the dynamic blur threshold according to the vehicle data, to obtain an updated dynamic blur threshold.

[0083] B1, obtaining a preset steady-state blur threshold and a vehicle adaptive adjustment coefficient corresponding to the vehicle data;

[0084] B2, dynamically transforming the steady-state blur threshold according to the vehicle adaptive adjustment coefficient to obtain a dynamically transformed threshold;

[0085] B3, replacing the dynamic blur threshold with the dynamically transformed threshold to obtain the updated dynamic blur threshold.

[0086] In the embodiments of the present application, the steady-state blur threshold can be a preset basic blur threshold, which is used as a fixed reference threshold for dynamic threshold updating. Specifically, the dynamic transformation can be calculating the product of the steady-state blur threshold and the vehicle adaptive adjustment coefficient to obtain the dynamically transformed threshold; then, the current dynamic blur threshold is replaced with the dynamically transformed threshold to obtain the updated dynamic blur threshold.

[0087] For example, in the embodiments of the present application, the steady-state blur threshold can include a low steady-state blur threshold 50, a medium steady-state blur threshold 100 and a high steady-state blur threshold 150, and the vehicle adaptive adjustment coefficient is 0.4. The dynamic transformation can be calculating the product of the low steady-state blur threshold 50, the medium steady-state blur threshold 100 and the high steady-state blur threshold 150 and the vehicle adaptive adjustment coefficient 0.4, respectively, to obtain the updated dynamic blur threshold, which includes a low dynamic blur threshold 20, a medium dynamic blur threshold 40 and a high dynamic blur threshold 60.

[0088] Referring to FIG. 4, further, the vehicle adaptive adjustment coefficient is obtained by the following steps:

[0089] C1, obtaining at least one of a speed adjustment coefficient corresponding to the vehicle speed data, a distance adjustment coefficient corresponding to the vehicle distance data, or a behavior adjustment coefficient corresponding to the behavior data of the adjacent vehicle;

[0090] C2, generating the vehicle adaptive adjustment coefficient according to at least one of the obtained speed adjustment coefficient, the distance adjustment coefficient or the behavior adjustment coefficient;

[0091] Wherein, the speed adjustment coefficient is negatively correlated with the vehicle speed data, the distance adjustment coefficient is positively correlated with the vehicle distance data, and the behavior adjustment coefficient is negatively correlated with the behavior data of the adjacent vehicle.

[0092] In the embodiments of the present application, the vehicle speed adjustment coefficient, the distance adjustment coefficient and the behavior adjustment coefficient can be preset in the target vehicle in advance and obtained according to the real-time vehicle data of the target vehicle. For example, for the vehicle speed adjustment coefficient, when the target vehicle is at a low speed (for example, 20 km / h), the corresponding vehicle speed adjustment coefficient is 1; when the target vehicle is at a high speed (for example, 100 km / h), the corresponding vehicle speed adjustment coefficient is 0.5. The vehicle speed adjustment coefficient is negatively correlated with the vehicle speed data, so that the higher the speed of the target vehicle, the smaller the corresponding dynamic fuzzy threshold, thereby improving the sensitivity of the wiper control.

[0093] Specifically, for the behavior adjustment coefficient, the difference from the vehicle speed adjustment coefficient is that the behavior adjustment coefficient is negatively correlated with the adjacent vehicle behavior data, that is, the smaller the behavior adjustment coefficient, the greater the traffic flow of the target vehicle and the more the number of lane changing behaviors of the adjacent vehicles. For the distance adjustment coefficient, the difference from the vehicle speed adjustment coefficient is that the smaller the distance between the target vehicle and the front vehicle, the smaller the distance adjustment coefficient, and the greater the distance between the target vehicle and the front vehicle, the greater the distance adjustment coefficient (that is, the distance adjustment coefficient is positively correlated with the vehicle distance data).

[0094] It can be understood that the specific values of the behavior adjustment coefficient, the distance adjustment coefficient and the vehicle speed adjustment coefficient can be set according to actual conditions, and the examples in the present application are only for illustration and do not limit the present application. In addition, for step C2, the vehicle adaptive adjustment coefficient can be generated according to at least one of the vehicle speed adjustment coefficient, the distance adjustment coefficient and the behavior adjustment coefficient. For example, when the vehicle data only includes the vehicle speed data, the vehicle adaptive adjustment coefficient can be determined directly according to the obtained vehicle speed adjustment coefficient; when the vehicle data includes the vehicle speed data, the vehicle distance data and the adjacent vehicle behavior data, the vehicle adaptive adjustment coefficient can be determined according to the product of the vehicle speed adjustment coefficient, the distance adjustment coefficient and the behavior adjustment coefficient, or the vehicle adaptive adjustment coefficient can be determined according to the weighted sum of the vehicle speed adjustment coefficient, the distance adjustment coefficient and the behavior adjustment coefficient.

[0095] It should be noted that, by implementing the dynamic threshold updating of the dynamic blur threshold value by acquiring the vehicle data, the dynamic blur threshold value can be adaptively changed according to the actual situation (that is, the threshold value when the wiper enters different working states is changed), so that the wiper can enter different working states according to the actual situation, thereby more flexibly coping with different situations. Specifically, for the vehicle speed data, when the target vehicle speed is greater, in order to ensure safe driving, the driver has a higher requirement for the field of view clarity during driving. Based on the adaptive change of the dynamic blur threshold value, the wiper can be more timely and accurately controlled, thereby improving the field of view clarity of the driver during driving, improving the driving experience and safety, and the vehicle spacing data and the behavior data of the adjacent vehicle are the same. Therefore, the present application will not be repeated here.

[0096] In step S130, the wiper state prediction is performed on the current field of view blur score according to the updated dynamic blur threshold value, and a target working state is obtained, wherein the target working state includes any one of a high-speed continuous state, a low-speed continuous state, an intermittent state or a closed state.

[0097] Referring to FIG. 5, in some embodiments, the dynamic blur threshold value includes a first blur threshold value, a second blur threshold value and a third blur threshold value, and the step S130 of performing wiper state prediction on the field of view blur score according to the dynamic blur threshold value to obtain a target working state includes:

[0098] D1, comparing the dynamic blur threshold value and the field of view blur score to obtain a blur comparison result;

[0099] D2, if the blur comparison result is that the field of view blur score is less than the first blur threshold value, it is determined that the target working state of the wiper of the target vehicle is a high-speed continuous state; or, if the blur comparison result is that the field of view blur score is greater than or equal to the first blur threshold value and less than the second blur threshold value, it is determined that the target working state of the wiper of the target vehicle is a low-speed continuous state; or, if the blur comparison result is that the field of view blur score is greater than or equal to the second blur threshold value and less than the third blur threshold value, it is determined that the target working state of the wiper of the target vehicle is an intermittent state; or, if the blur comparison result is that the field of view blur score is greater than or equal to the third blur threshold value, it is determined that the target working state of the wiper of the target vehicle is a closed state.

[0100] In the embodiments of the present application, the wiper state prediction can be a comparison of the size relationship between the dynamic blur threshold and the field blur score. Specifically, when the field blur score is less than the first blur threshold (i.e., the aforementioned low dynamic blur threshold), the target working state of the wiper is the high-speed continuous mode; when the field blur score is greater than or equal to the first blur threshold and less than the second blur threshold (i.e., the aforementioned medium dynamic blur threshold), the target working state of the wiper is the low-speed continuous mode; when the field blur score is greater than or equal to the second blur threshold and less than the third blur threshold (i.e., the aforementioned high dynamic blur threshold), the target working state of the wiper is the intermittent state; and when the field blur score is greater than or equal to the third blur threshold, the target working state of the wiper is the off state.

[0101] Step S140, updating the current wiper working state according to the target working state.

[0102] In the embodiments of the present application, the target working state can be the same as or different from the current wiper working state. When the target working state is different from the current wiper working state, the current wiper working state can be switched to the target working state; or when the target working state is the same as the current wiper working state, the wiper can not be operated or the working speed of the wiper in this state can be fine-tuned according to the size relationship between the dynamic blur threshold and the field blur score.

[0103] For example, when the target working state determined in step S130 is the low-speed continuous mode and the current wiper working state is also the low-speed continuous mode, the working speed of the wiper in the low-speed continuous state can be adjusted according to the size difference between the current field blur score and the first blur threshold, so that the working speed of the wiper in the low-speed continuous state is closer to the upper limit of the working speed in this state when the current field blur score is closer to the first blur threshold, and the rest is the same, which is only for illustration.

[0104] Referring to FIG. 6, in some embodiments, the adaptive control method further comprises:

[0105] E1, obtaining the current system sensitivity, which is used to represent the update frequency of the current wiper working state and the threshold adjustment amplitude of the dynamic blur threshold;

[0106] E2, performing a sensitive threshold update on the dynamic blur threshold according to the current system sensitivity to obtain an updated dynamic blur threshold.

[0107] In the embodiments of the present application, the system sensitivity is used to represent the update frequency of the current wiper working state and the threshold adjustment range of the current dynamic blur threshold. Specifically, the update frequency of the current wiper working state can be the execution frequency of steps S110 to S140, and the threshold adjustment range of the current dynamic blur threshold can be the threshold range of adjusting the dynamic blur threshold based on the system sensitivity each time the process of steps S110 to S140 is executed.

[0108] It can be understood that the system sensitivity in the embodiments of the present application can be in the form of a specific numerical value or in the form of a level. For the sake of understanding, the system sensitivity in the form of a level is taken as an example in the present application, which can be specifically divided into high sensitivity and low sensitivity. If the current system sensitivity is high sensitivity, the current dynamic blur threshold can be fine-tuned based on the threshold adjustment range corresponding to the high sensitivity. The specific numerical value representing the sensitivity degree is the same, and can be simply deduced by analogy.

[0109] It should be noted that in the sensitivity threshold updating in the embodiments of the present application, the specific numerical value of the threshold adjustment range can be set according to actual conditions. For example, when the system sensitivity is high sensitivity or corresponds to a certain specific numerical value, the wiper control system is sensitive to environmental changes, and the threshold adjustment range at this time can be small, such as at least one of -2, -1, 0, +1, +2; and when the system sensitivity is low sensitivity or corresponds to another specific numerical value, the wiper control system is insensitive to environmental changes, and the threshold adjustment range at this time can be large, such as at least one of ±5, ±7, ±10. The examples in the present application are only for illustration.

[0110] In addition, in the sensitivity threshold updating in the embodiments of the present application, the current dynamic blur threshold can be the dynamic blur threshold after dynamic threshold updating. The system sensitivity feature is added to the dynamic blur threshold, so as to further improve the matching degree between the wiper working state and the actual situation and improve the driving experience of the driver.

[0111] Referring to FIG. 7, in some embodiments, the system sensitivity is updated by the following steps:

[0112] F1, obtaining current vehicle data and environmental data, and a preset sensitivity update range, environmental sensitivity conditions and vehicle sensitivity conditions;

[0113] F2, performing environmental condition determination on the current environmental data according to the environmental sensitivity conditions to obtain an environmental sensitivity determination result, and performing vehicle condition determination on the current vehicle data according to the vehicle sensitivity conditions to obtain a vehicle sensitivity determination result;

[0114] F3, if the environment sensitivity determination result is environment high risk or the vehicle sensitivity determination result is vehicle high risk, then according to the sensitivity update range, the current system sensitivity is updated sensitively; or, if the environment sensitivity determination result is environment low risk and the vehicle sensitivity determination result is vehicle low risk, then according to the sensitivity update range, the current system sensitivity is updated obtusely.

[0115] In the embodiments of the present application, the current vehicle data and environment data can be obtained in real time; the sensitivity update range can be a level range or a numerical range; the environment sensitivity condition is used to determine whether the target vehicle is in an environment scene in a high risk state, and the vehicle sensitivity condition is used to determine whether the target vehicle is in a driving condition in a high risk state.

[0116] For example, when the system sensitivity is in a level form, the sensitivity update range includes low sensitivity, medium sensitivity, high sensitivity, etc., and the current system sensitivity is taken as medium sensitivity in the examples of the present application. If the environment sensitivity determination result is environment high risk or the vehicle sensitivity determination result is vehicle high risk (i.e. at least one of the environment sensitivity determination result or the vehicle sensitivity determination result is high risk), then the current system sensitivity is updated along the sensitive direction side, i.e. the medium sensitivity is updated to high sensitivity; otherwise, if the environment sensitivity determination result is environment low risk and the vehicle sensitivity determination result is vehicle low risk, then the current system sensitivity is updated along the obtuse direction side, i.e. the medium sensitivity is updated to low sensitivity.

[0117] It is worth mentioning that the specific level range number of the sensitivity update range in the embodiments of the present application can be set according to actual conditions, for example, the specific level range number of the sensitivity update range can also be 5, at this time the sensitivity update range can include extremely low sensitivity, low sensitivity, medium sensitivity, high sensitivity and extremely high sensitivity, and the rest is similar, which can be analogized, and the examples of the present application are only for illustration. In addition, when the system sensitivity is in a specific numerical form, the sensitivity update range includes several sensitivity values of different sizes, and the specific sensitivity update and obtuse update are similar to the above-mentioned content about the level range, which can be analogized simply, and the present application will not be described here.

[0118] Further, with reference to FIG. 8, the vehicle sensitivity condition includes at least one of a vehicle speed condition, a vehicle distance condition or a neighboring vehicle behavior condition, and the step F2, according to the vehicle sensitivity condition, vehicle condition determination is performed on the current vehicle data to obtain a vehicle sensitivity determination result, including:

[0119] F21, judging the vehicle speed data according to the vehicle speed condition to obtain a vehicle speed judgment result; or judging the vehicle distance data according to the vehicle distance condition to obtain a distance judgment result; or judging the adjacent vehicle behavior data according to the adjacent vehicle behavior condition to obtain a behavior judgment result;

[0120] F22, integrating at least one of the vehicle speed judgment result, the distance judgment result or the behavior judgment result to obtain the vehicle sensitivity judgment result.

[0121] In the embodiments of the present application, the vehicle condition judgment can be specifically performed according to the vehicle speed sensitivity condition, and the corresponding vehicle data is judged to obtain the vehicle sensitivity judgment result.

[0122] Specifically, the vehicle speed condition can be used to judge whether the current vehicle speed of the target vehicle is greater than a vehicle speed threshold, which can be any one of 80 km / h, 90 km / h, 100 km / h, etc.; the vehicle distance condition is used to judge whether the distance between the target vehicle and the front vehicle is within a certain time threshold, which is reduced from a first distance threshold to a second time threshold, wherein the specific time value of the certain time threshold can be any one of 2 seconds, 3 seconds, 5 seconds, etc., the specific distance value of the first distance threshold can be any one of 40 meters, 50 meters, 60 meters, etc., and the specific distance value of the second distance threshold can be any one of 5 meters, 10 meters, 20 meters, etc.; the adjacent vehicle behavior condition is used to judge whether the number of lane changes of the adjacent vehicle is greater than or equal to a lane change threshold, and whether the change amount of the adjacent vehicle is greater than or equal to a vehicle change threshold, wherein the lane change threshold or the vehicle change threshold can be any one of 2, 3, 5, etc., which is only for illustration.

[0123] It can be understood that after obtaining at least one of the vehicle speed judgment result, the distance judgment result and the behavior judgment result, at least one of the obtained vehicle speed judgment result, the distance judgment result and the behavior judgment result can be integrated to obtain the vehicle sensitivity judgment result. Specifically, when the vehicle speed judgment result, the distance judgment result or the behavior judgment result in the vehicle sensitivity judgment result is yes, that is, the vehicle speed data meets the vehicle speed condition, the vehicle distance data meets the vehicle distance condition or the adjacent vehicle behavior data meets the adjacent vehicle behavior condition, the vehicle sensitivity judgment result obtained at this time is that the vehicle is high risk; or when the vehicle speed judgment result, the distance judgment result and the behavior judgment result in the vehicle sensitivity judgment result are all no, that is, the vehicle speed data does not meet the vehicle speed condition, the vehicle distance data does not meet the vehicle distance condition and the adjacent vehicle behavior data does not meet the adjacent vehicle behavior condition, the vehicle sensitivity judgment result obtained at this time is that the vehicle is low risk.

[0124] Further, the environmental sensitive condition comprises an environmental light intensity condition and an environmental rainfall condition, the environmental data comprises light intensity data and rainfall data, and the step F2 comprises:

[0125] F23, performing light intensity condition determination on the light intensity data according to the environmental light intensity condition to obtain a light intensity determination result, and performing rainfall condition determination on the rainfall data according to the environmental rainfall condition to obtain a rainfall determination result;

[0126] F24, integrating the light intensity determination result and the rainfall determination result to obtain the environmental sensitive determination result.

[0127] In the embodiments of the present application, the light intensity data can be collected based on a light sensor, the rainfall data can be collected based on a rainfall collection sensor, the environmental light intensity condition is used to determine whether the light intensity of the current environment of the target vehicle is less than or equal to a preset light intensity threshold, and the environmental rainfall condition is used to determine whether the rainfall of the current environment of the target vehicle is greater than or equal to a preset rainfall threshold. The specific numerical values of the specific light intensity threshold and the specific rainfall threshold can be set according to actual conditions.

[0128] It can be understood that when the light intensity determination result is that the light intensity data meets the environmental light intensity condition, or the rainfall determination result is that the rainfall data meets the environmental rainfall condition, the integrated environmental sensitive determination result is an environmental high risk; or when the light intensity determination result is that the light intensity data does not meet the environmental light intensity condition, and the rainfall determination result is that the rainfall data does not meet the environmental rainfall condition, the integrated environmental sensitive determination result is an environmental low risk.

[0129] Referring to FIG. 9, the embodiments of the present application also provide a vehicle wiper self-adaptive control method, comprising:

[0130] The acquisition unit 310 is configured to acquire a current field of view blur score of a target vehicle, a wiper working state, a dynamic blur threshold, and vehicle data, wherein the vehicle data comprises at least one of vehicle speed data, vehicle distance data, or adjacent vehicle behavior data.

[0131] The threshold updating unit 320 is configured to perform dynamic threshold updating on the dynamic blur threshold according to the vehicle data to obtain an updated dynamic blur threshold.

[0132] The state prediction unit 330 is configured to perform wiper state prediction on the current field of view blur score according to the updated dynamic blur threshold to obtain a target working state, wherein the target working state comprises any one of a high-speed continuous state, a low-speed continuous state, an intermittent state, or an off state.

[0133] The state updating unit 340 is configured to update the current wiper state according to the target wiper state.

[0134] It can be understood that the content in the above method embodiments is applicable to the present system embodiment, the present system embodiment specifically implements the same functions as the above method embodiments, and achieves the same beneficial effects as the above method embodiments.

[0135] The present application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor implements the above method when executing the computer program. The electronic device can be any smart terminal, such as a tablet computer or a vehicle-mounted computer.

[0136] It can be understood that the content in the above method embodiments is applicable to the present device embodiment, the present device embodiment specifically implements the same functions as the above method embodiments, and achieves the same beneficial effects as the above method embodiments.

[0137] Please refer to FIG. 10, which shows the hardware structure of the electronic device of another embodiment. The electronic device includes:

[0138] The processor 901 can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, and is used to execute related programs to implement the technical solutions provided by the present application;

[0139] The memory 902 can be implemented in the form of a ROM (Read Only Memory), a static storage device, a dynamic storage device, or a RAM (Random Access Memory). The memory 902 can store an operating system and other application programs. When the technical solutions provided by the present application are implemented by software or firmware, the related program codes are stored in the memory 902 and are called and executed by the processor 901 to implement the method of the present application;

[0140] The input / output interface 903 is used to realize information input and output.

[0141] The communication interface 904 is used to realize the communication interaction between the present device and other devices. The communication can be realized by a wired manner (such as a USB, a network cable, etc.) or a wireless manner (such as a mobile network, WIFI, Bluetooth, etc.).

[0142] a bus 905 for transmitting information between the various components (e.g., the processor 901, the memory 902, the input / output interface 903, and the communication interface 904) of the device;

[0143] The processor 901, the memory 902, the input / output interface 903, and the communication interface 904 are communicatively connected to each other within the device through the bus 905.

[0144] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method.

[0145] It can be understood that the contents in the above method embodiments are applicable to the present storage medium embodiment, the present storage medium embodiment specifically implements the functions of the above method embodiments, and achieves the same beneficial effects as the above method embodiments.

[0146] The memory, as a non-transitory computer readable storage medium, can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0147] The embodiment of the present application further provides a vehicle, which includes the control system or the electric drive assembly of the electronic device. Specifically, the vehicle can be a private car, such as a sedan, an SUV, an MPV, a pickup truck, or the like. The vehicle can also be an operating vehicle, such as a van, a bus, a small truck, or a large trailer, etc. The vehicle can be a gasoline car or a new energy car. When the vehicle is a new energy car, it can be a hybrid car or a pure electric car.

[0148] The embodiments described in the embodiments of the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0149] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than the figures shown, or combine certain steps, or different steps.

[0150] The apparatus embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separate, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment.

[0151] Those skilled in the art can understand that all or some of the steps in the method disclosed above, the functional modules / units in the system and the device can be implemented as software, firmware, hardware and appropriate combinations thereof.

[0152] The terms "first", "second", "third", "fourth" and the like in the description of the application and in the claims of the foregoing drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the use of the terms so construed can be interchanged, such that the embodiments of the application described herein can be carried out in other than the order discussed herein without departing from the scope of the application. Further, the terms "comprise" and "comprising" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, product or apparatus that comprises a list of steps or units does not necessarily comprise only those steps or units but can include other not expressly listed steps or units.

[0153] It should be understood that in the present application, "at least one" means one or more, and "multiple" means two or more. "And / or" is used to describe the relationship between the associated objects, which means that there can be three relationships, for example, "A and / or B" can represent three cases: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally represents that the associated objects before and after are in an "or" relationship. "At least one of the following" or the like means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0154] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented by other manners. For example, the apparatus embodiments described above are merely illustrative, for example, the division of the above units is merely a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or components shown or discussed can be indirect coupling or communication connection through some interfaces, apparatuses or units, and can be electrical, mechanical or other forms.

[0155] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they can be located in one place or distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0156] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0157] If the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method of each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0158] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, but this does not limit the scope of the embodiments of the present application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. A method of adaptive control of a vehicle wiper, characterized in that, The method comprises the following steps: obtaining a current field of view blur score of a target vehicle, a wiper working state, a dynamic blur threshold and vehicle data, wherein the vehicle data comprises at least one of vehicle speed data, vehicle distance data or adjacent vehicle behavior data; performing dynamic threshold updating on the dynamic blur threshold according to the vehicle data to obtain an updated dynamic blur threshold; performing wiper state prediction on the current field of view blur score according to the updated dynamic blur threshold to obtain a target working state, wherein the target working state comprises any one of a high-speed continuous state, a low-speed continuous state, an intermittent state or an off state; updating the current wiper working state according to the target working state.

2. The adaptive control method of claim 1, wherein, The field of view blur score is obtained by the following steps: obtaining a field of view image from a windshield of the target vehicle; performing preprocessing on the field of view image to obtain a field of view intermediate image; performing image evaluation on the field of view intermediate image based on a preset Laplacian operator to obtain the field of view blur score.

3. The adaptive control method of claim 1, wherein, The dynamic threshold updating on the dynamic blur threshold according to the vehicle data comprises the following steps: obtaining a preset steady-state blur threshold and a vehicle adaptive adjustment coefficient corresponding to the vehicle data; performing dynamic transformation on the steady-state blur threshold according to the vehicle adaptive adjustment coefficient to obtain a dynamic transformation threshold; performing threshold replacement on the dynamic blur threshold according to the dynamic transformation threshold to obtain the updated dynamic blur threshold.

4. The adaptive control method of claim 3, wherein, The vehicle adaptive adjustment coefficient is obtained by the following steps: obtaining at least one of a vehicle speed adjustment coefficient corresponding to the vehicle speed data, a distance adjustment coefficient corresponding to the vehicle distance data or a behavior adjustment coefficient corresponding to the adjacent vehicle behavior data; generating the vehicle adaptive adjustment coefficient according to at least one of the obtained vehicle speed adjustment coefficient, distance adjustment coefficient or behavior adjustment coefficient; wherein the vehicle speed adjustment coefficient is negatively correlated with the vehicle speed data, the distance adjustment coefficient is positively correlated with the vehicle distance data, and the behavior adjustment coefficient is negatively correlated with the adjacent vehicle behavior data.

5. The adaptive control method of claim 1, wherein, The dynamic blur threshold comprises a first blur threshold, a second blur threshold and a third blur threshold, and the wiper state prediction on the current field of view blur score according to the updated dynamic blur threshold comprises the following steps: comparing the dynamic blur threshold and the field of view blur score to obtain a blur comparison result; If the fuzzy comparison result is that the field of view blur score is less than the first blur threshold, it is determined that the target working state of the target vehicle wiper is a high-speed continuous state; or, if the fuzzy comparison result is that the field of view blur score is greater than or equal to the first blur threshold and less than the second blur threshold, it is determined that the target working state of the target vehicle wiper is a low-speed continuous state; or, if the fuzzy comparison result is that the field of view blur score is greater than or equal to the second blur threshold and less than the third blur threshold, it is determined that the target working state of the target vehicle wiper is an intermittent state; or, if the fuzzy comparison result is that the field of view blur score is greater than or equal to the third blur threshold, it is determined that the target working state of the target vehicle wiper is a closed state.

6. The adaptive control method of claim 1, wherein, The adaptive control method further comprises: obtaining a current system sensitivity, the system sensitivity being used to represent an update frequency of the current wiper working state and a threshold adjustment amplitude of the dynamic blur threshold; performing a sensitive threshold update on the dynamic blur threshold according to the current system sensitivity to obtain an updated dynamic blur threshold.

7. The adaptive control method of claim 6, wherein, The system sensitivity is updated by the following steps: obtaining current vehicle data and environmental data, and a preset sensitive update amplitude, environmental sensitive conditions and vehicle sensitive conditions; performing environmental condition determination on the current environmental data according to the environmental sensitive conditions to obtain an environmental sensitive determination result, and performing vehicle condition determination on the current vehicle data according to the vehicle sensitive conditions to obtain a vehicle sensitive determination result; if the environmental sensitive determination result is an environmental high risk or the vehicle sensitive determination result is a vehicle high risk, performing a sensitive update on the current system sensitivity according to the sensitive update amplitude; or, if the environmental sensitive determination result is an environmental low risk and the vehicle sensitive determination result is a vehicle low risk, performing a dull update on the current system sensitivity according to the sensitive update amplitude.

8. The adaptive control method of claim 7, wherein, The vehicle sensitive conditions include at least one of a vehicle speed condition, a vehicle distance condition or a neighboring vehicle behavior condition, and the vehicle condition determination on the current vehicle data according to the vehicle sensitive conditions to obtain the vehicle sensitive determination result comprises: performing vehicle speed condition determination on the vehicle speed data according to the vehicle speed condition to obtain a vehicle speed determination result; or performing distance condition determination on the vehicle distance data according to the vehicle distance condition to obtain a distance determination result; or performing behavior condition determination on the neighboring vehicle behavior data according to the neighboring vehicle behavior condition to obtain a behavior determination result; integrating at least one of the vehicle speed determination result, the distance determination result or the behavior determination result to obtain the vehicle sensitive determination result. The environmental sensitive conditions include an environmental luminosity condition and an environmental rainfall condition, the environmental data includes luminosity data and rainfall data, and the environmental condition determination on the current environmental data according to the environmental sensitive conditions to obtain the environmental sensitive determination result comprises:

9. The adaptive control method of claim 7, wherein, ​ According to the ambient light condition, the light condition of the light data is determined to obtain a light determination result, and according to the ambient rainfall condition, the rainfall condition of the rainfall data is determined to obtain a rainfall determination result; The light determination result and the rainfall determination result are integrated to obtain the environmental sensitivity determination result.

10. An adaptive control system for a vehicle wiper, characterized in that Comprise: An acquisition unit is configured to acquire a current field of view blur score of a target vehicle, a wiper working state, a dynamic blur threshold, and vehicle data, the vehicle data including at least one of vehicle speed data, vehicle distance data, or adjacent vehicle behavior data; A threshold updating unit is configured to dynamically update the dynamic blur threshold according to the vehicle data to obtain an updated dynamic blur threshold; A state prediction unit is configured to predict the wiper state according to the current field of view blur score and the updated dynamic blur threshold to obtain a target working state, the target working state including any one of a high-speed continuous state, a low-speed continuous state, an intermittent state, or an off state; A state updating unit is configured to update the current wiper working state according to the target working state.

11. An electronic device, comprising: Comprise: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method of any one of claims 1 to 9.

12. A computer-readable storage medium, the computer-readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to implement the method of any one of claims 1 to 9.

13. A vehicle characterized by comprising: The vehicle comprises the adaptive control system of claim 10 or the electronic device of claim 11.

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