Wiper rubber strip aging warning method, device, equipment, storage medium and vehicle

Abstract

The embodiment of the present invention relates to the technical field of windshield wipers, and discloses a method, device, equipment, storage medium and vehicle for early warning of aging of wiper rubber strips, the method comprising: obtaining the current position of a vehicle to be detected; obtaining target weather forecast information based on the current position; determining the target sensed rainfall corresponding to the target weather forecast information based on the correspondence between the weather forecast information and the sensed rainfall; predicting the wiper gear position based on the target sensed rainfall to obtain the predicted wiper gear position; determining the early warning result of aging of the wiper rubber strip based on the predicted wiper gear position and preset early warning conditions. The application of the present invention can effectively evaluate the actual aging degree of the vehicle wiper rubber strip, so that the vehicle wiper rubber strip can be replaced in time, avoiding dangerous driving due to excessive aging of the wiper rubber strip.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of windshield wipers, and specifically to a method, device, equipment, storage medium and vehicle for early warning of aging of a wiper rubber strip. Background Art

[0002] The wiper is an important part that affects driving safety. It is used to clean the rain on the front windshield. The rubber strips generally contain rubber components, which will inevitably age over time. The degree of aging has a great impact on the cleaning ability. Ordinary car owners lack experience in the degree of aging of the rubber strips and find it difficult to grasp the cycle of replacing the wiper rubber strips. Failure to replace the wiper rubber strips for a long time will cause great safety risks when driving in rainy days. Especially in heavy rain or rainstorm weather, the rainfall is greater than the cleaning ability of the wiper, which is likely to cause serious safety accidents.

[0003] In the past, the replacement of wiper strips often relied on the driver's intuitive feelings. For example, when driving in the rain, the driver would realize that the wiper strips needed to be replaced only when he clearly felt that the wiper's cleaning ability was insufficient. However, if the aging of the wiper strips to a certain extent can meet the cleaning needs during light spring rainfall, the driver failed to realize that it can no longer meet the heavy summer rainfall and did not replace the wiper strips. It is likely that in a heavy rain in the summer, the rainfall will exceed the maximum cleaning capacity of the wipers. Obviously, the above traditional method of replacing wiper strips hides great safety risks.

[0004] Although some high-end models are currently equipped with rain sensors and wiper linkage functions, the wipers can automatically set the gear according to the sensed rainfall. However, in this way, the correlation between rainfall and gear is set at the factory, which cannot adapt to the situation after the wiper strips are aged, and there are still safety risks in driving in rainy days. Therefore, how to effectively evaluate the actual aging degree of vehicle wiper strips and replace vehicle wiper strips in time is a problem that needs to be solved urgently. Summary of the invention

[0005] In view of the above problems, the embodiments of the present invention provide a wiper strip aging warning method, device, equipment, storage medium and vehicle, which can effectively evaluate the actual aging degree of the vehicle's wiper strips, so that the vehicle's wiper strips can be replaced in time, avoiding dangerous driving due to excessive aging of the wiper strips.

[0006] According to one aspect of an embodiment of the present invention, a wiper rubber strip aging early warning method is provided, the method comprising:

[0007] Get the current position of the vehicle to be detected;

[0008] Obtaining target weather forecast information based on the current location;

[0009] Determining a target sensed rainfall corresponding to the target weather forecast information based on a correspondence between the weather forecast information and the sensed rainfall;

[0010] Predicting the wiper gear position based on the target sensed rainfall to obtain a predicted wiper gear position;

[0011] Based on the predicted gear position of the wiper and the preset warning condition, an aging warning result of the wiper rubber strip is determined.

[0012] According to another aspect of an embodiment of the present invention, a wiper rubber strip aging warning device is provided, comprising:

[0013] An acquisition module is used to obtain the current position of the vehicle to be detected;

[0014] A weather forecast information determination module, used to obtain target weather forecast information based on the current location;

[0015] A sensing rainfall determination module, used to determine the target sensing rainfall corresponding to the target weather forecast information based on the corresponding relationship between the weather forecast information and the sensing rainfall;

[0016] A wiper predicted gear determination module, used for predicting the wiper gear based on the target sensed rainfall to obtain the wiper predicted gear;

[0017] The aging warning result generating module is used to determine the aging warning result of the wiper rubber strip based on the predicted gear position of the wiper and the preset warning condition.

[0018] According to another aspect of an embodiment of the present invention, a wiper strip aging warning device is provided, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; the memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute the operation of the wiper strip aging warning method as described in the above embodiment.

[0019] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, in which at least one executable instruction is stored, and the executable instruction enables the wiper strip aging warning device / apparatus to perform the operation of the wiper strip aging warning method as described in the above embodiment.

[0020] According to another aspect of an embodiment of the present invention, a vehicle is provided, comprising: a vehicle body and a wiper arranged on the vehicle body; the wiper strip aging warning device as described in the above embodiment is arranged in the vehicle body, and is used for the wiper strip aging warning method.

[0021] The embodiment of the present invention can obtain the target weather forecast information of the current position based on the current position by acquiring the current position of the vehicle to be detected; then determine the target sensed rainfall corresponding to the target weather forecast information based on the corresponding relationship between the weather forecast information and the sensed rainfall, and predict the wiper gear based on the target sensed rainfall to obtain the predicted wiper gear that matches the target sensed rainfall; then determine the aging warning result of the wiper rubber strip based on the predicted wiper gear and preset warning conditions, and effectively evaluate the actual aging degree of the vehicle's wiper rubber strip to remind the user to replace the wiper rubber strip in time, which not only avoids dangerous driving due to excessive aging of the wiper rubber strip, but also avoids the waste of wiper rubber strip due to premature replacement of the wiper rubber strip.

[0022] The above description is only an overview of the technical solution of the embodiment of the present invention. In order to more clearly understand the technical means of the embodiment of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiment of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present invention. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:

[0024] Figure 1 A schematic diagram showing the flow of a first embodiment of a method for early warning of aging of a wiper rubber strip provided by the present invention;

[0025] Figure 2 A schematic diagram showing the flow of a second embodiment of the wiper rubber strip aging early warning method provided by the present invention;

[0026] Figure 3 A schematic flow chart showing a specific example of the wiper rubber strip aging early warning method provided by the present invention;

[0027] Figure 4 A schematic flow chart of a method for determining a rainfall prediction model provided by the present invention is shown;

[0028] Figure 5 A schematic diagram of a rainfall prediction model provided by the present invention is shown;

[0029] Figure 6 A schematic structural diagram of a first embodiment of a wiper rubber strip aging warning device provided by the present invention is shown;

[0030] Figure 7 A structural schematic diagram of an embodiment of a wiper rubber strip aging warning device provided by the present invention is shown. DETAILED DESCRIPTION

[0031] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0032] Figure 1 The flowchart of the first embodiment of the wiper rubber strip aging warning method of the present invention is shown, and the method is executed by the wiper rubber strip aging warning device. Figure 1 As shown, the method comprises the following steps:

[0033] Step 110, obtaining the current position of the vehicle to be detected.

[0034] The current location may be latitude and longitude information, or a geographical location, such as X province, X city, etc., which is not specifically limited here.

[0035] In an optional manner, the current position of the vehicle to be detected can be obtained through the on-board inertial navigation system of the vehicle to be detected, or can be obtained by a map application running on the on-board terminal of the vehicle to be detected, or can be obtained by a map application running on an intelligent terminal (such as a smart phone, etc.) located on the vehicle to be detected, but is not limited to this; when the vehicle to be detected is an autonomous driving vehicle, the current position of the vehicle to be detected can also be calculated through the global navigation satellite system data, inertial measurement unit (Inertial Measurement Unit, IMU) data and laser point cloud data of the autonomous driving vehicle; or, the current position of the vehicle to be detected can also be obtained by positioning the vehicle to be detected using other positioning systems, such as the global positioning system or the Beidou satellite navigation system, etc., which are not specifically limited here.

[0036] In addition, the current position may be the position of the vehicle to be detected before it is powered on, the real-time position of the vehicle to be detected during the power-on process, or the position of the vehicle to be detected after it is powered off. It can be determined based on actual conditions and is not specifically limited here.

[0037] Step 120, obtaining target weather forecast information based on the current location.

[0038] The target weather forecast information is the maximum value of the weather forecast information within a preset time period (for example, within 48 hours or within 7 days) corresponding to the current location. There are many ways to obtain the target weather forecast information. For example, the vehicle to be detected is connected to the network via WIFI (Wireless Fidelity) or general packet radio service (GPRS), and requests the target weather forecast information corresponding to the current location from the weather forecast data source (such as the meteorological website where the vehicle is located), and receives the target weather forecast information corresponding to the current location returned by the weather forecast data source in response to the request. No specific restrictions are made here.

[0039] Step 130: determining a target sensed rainfall corresponding to the target weather forecast information based on the correspondence between the weather forecast information and the sensed rainfall.

[0040] The target sensing rainfall is used to represent the maximum rainfall sensed by the rain sensor disposed in the vehicle to be detected at the current position, that is, the maximum rainfall sensing level data.

[0041] Specifically, based on the correspondence between weather forecast information and induced rainfall, the target induced rainfall corresponding to the target weather forecast information is determined, that is, according to the target weather forecast information, the correspondence between the weather forecast information and the induced rainfall is matched to obtain the target induced rainfall corresponding to the target weather forecast information. The correspondence between the weather forecast information and the induced rainfall can be represented in the form of a list, in the form of a data structure, in the form of a model, and so on.

[0042] Step 140 , predicting the wiper gear position based on the target sensed rainfall to obtain the predicted wiper gear position.

[0043] The predicted wiper gear position matches the target sensing rainfall, and the predicted wiper gear position is used to characterize the required wiper gear position when the rainfall reaches the target sensing rainfall in order to maintain the clarity of the windshield of the vehicle to be detected while driving.

[0044] Specifically, the predicted wiper gear of the vehicle to be tested is predicted according to the target sensed rain. For example, the correspondence between the preset sensed rain and the preset wiper predicted gear is obtained, and the corresponding relationship between the preset sensed rain and the preset wiper predicted gear is matched according to the target sensed rain to obtain the wiper predicted gear corresponding to the target sensed rain. For another example, a preset wiper gear prediction model is obtained, and the target sensed rain is input into the preset wiper gear prediction model to obtain the wiper predicted gear. Among them, the wiper gear prediction model is constructed based on a neural network model, and there is no specific limitation on the structure of the neural network model. The preset wiper gear prediction model is in the reasoning process. Of course, the method for determining the wiper predicted gear is not limited to the above, and other methods can also be used, which are not specifically limited here.

[0045] Step 150, determining the aging warning result of the wiper rubber strip based on the predicted wiper gear position and the preset warning condition.

[0046] Specifically, the aging degree of the wiper strips is evaluated based on the predicted gear position of the wiper and the preset warning conditions. When the predicted gear position of the wiper reaches the preset warning conditions, it means that the aging degree of the wiper strips poses a driving risk. At this time, the aging warning result of the wiper strips can be obtained to remind the user that the wiper is aged to a large extent and will not be able to provide sufficient cleaning ability in future heavy rainfall weather, thus affecting driving safety.

[0047] Compared with the traditional method in the related art of judging the aging state of the wiper strips based on the subjective experience of the user and replacing the wiper strips at a fixed time, the wiper strip aging warning method of the embodiment of the present invention can obtain the target weather forecast information of the current position based on the current position by acquiring the current position of the vehicle to be detected; then, based on the correspondence between the weather forecast information and the sensed rainfall, the target sensed rainfall corresponding to the target weather forecast information is determined, and the wiper gear position can be predicted based on the target sensed rainfall to obtain the predicted wiper gear position that matches the target sensed rainfall; then, based on the predicted wiper gear position and preset warning conditions, the aging warning result of the wiper strips is determined, and the actual aging degree of the vehicle's wiper strips can be effectively evaluated to remind the user to replace the wiper strips in time. This not only avoids dangerous driving due to excessive aging of the wiper strips, but also avoids the waste of wiper strips due to premature replacement of the wiper strips.

[0048] Figure 2 The flowchart of the second embodiment of the wiper rubber strip aging warning method of the present invention is shown, and the method is executed by the wiper rubber strip aging warning device. Figure 2 As shown, the method comprises the following steps:

[0049] Step 210, obtaining the current position of the vehicle to be detected.

[0050] For details, please see Figure 1 Step 110 of the illustrated embodiment will not be described in detail here.

[0051] Step 220, obtaining target weather forecast information based on the current location.

[0052] For details, please see Figure 1 Step 120 of the illustrated embodiment will not be described in detail here.

[0053] Step 230: Determine the target sensed rainfall corresponding to the target weather forecast information based on the correspondence between the weather forecast information and the sensed rainfall.

[0054] Specifically, the above step 230 includes:

[0055] Step 2301, obtaining sample weather forecast information and first sample sensed rainfall of multiple first sample vehicles.

[0056] The sample weather forecast information is used to characterize the weather forecast rainfall at the geographical location of the first sample vehicle, and the first sample sensed rainfall is used to characterize the rainfall sensed by the rain sensor installed in the first sample vehicle at the geographical location (ie, rainfall sensing level data).

[0057] Step 2302: fitting is performed based on the sample weather forecast information and the first sample induced rainfall to obtain a corresponding relationship between the weather forecast information and the induced rainfall.

[0058] Among them, the number of first sample vehicles can be 2, 5 or more, and there is no specific limitation here. The sample weather forecast information and the first sample induced rainfall corresponding to each first sample vehicle are a set of data, that is, the sample weather forecast information and the first sample induced rainfall are corresponding to each other. Therefore, when fitting based on the sample weather forecast information and the first sample induced rainfall, the sample weather forecast information and the first sample induced rainfall corresponding to the sample weather forecast information are fitted, so as to ensure the accuracy of the correspondence between the obtained weather forecast information and the induced rainfall.

[0059] Exemplarily, the first sample sensed rainfall may be the rainfall level of the first sample vehicle when the wipers are turned on (taking a certain vehicle model as an example, divided into 0 to 13, where 0 represents no rain and 13 represents the highest rainfall).

[0060] Exemplarily, fitting is performed based on the sample weather forecast information and the first sample induced rainfall. Specifically, the sample weather forecast information can be used as the independent variable, the first sample induced rainfall can be used as the dependent variable, and a linear regression can be performed on the sample weather forecast information and the first sample induced rainfall to obtain a rainfall prediction model that predicts the target induced rainfall according to the target weather forecast information; or, the sample weather forecast information can be used as the independent variable, the first sample induced rainfall can be used as the dependent variable, and a non-linear regression can be performed on the sample weather forecast information and the first sample induced rainfall to obtain a non-rainfall prediction model that predicts the target induced rainfall according to the target weather forecast information, and so on. No specific limitation is made here.

[0061] In an embodiment of the present application, by acquiring sample weather forecast information and first sample induced rainfall of multiple first sample vehicles and performing fitting based on the sample weather forecast information and the first sample induced rainfall, the error in the correspondence between the weather forecast information and the induced rainfall can be reduced, and the accuracy of the correspondence between the weather forecast information and the induced rainfall can be improved, thereby improving the accuracy of the target induced rainfall obtained based on the correspondence between the weather forecast information and the induced rainfall in subsequent steps.

[0062] In an optional manner, the above step 2301 specifically includes:

[0063] Step a1, obtaining location information of a plurality of first sample vehicles.

[0064] The location information may be the location of the first sample vehicle before it is powered on, the real-time location of the first sample vehicle during the power-on process, or the location of the first sample vehicle after it is powered off. It may be determined based on actual conditions and is not specifically limited here.

[0065] Among them, the method for obtaining the position information of the first sample vehicle is similar to the method for obtaining the current position of the vehicle to be detected, that is, the position information of the first sample vehicle can be obtained through the on-board inertial navigation system of the first sample vehicle, or can also be obtained by the map application running on the on-board terminal of the first sample vehicle, or can also be obtained by the map application running on the intelligent terminal (such as a smart phone, etc.) located on the first sample vehicle, and so on; when the first sample vehicle is an autonomous driving vehicle, the position information of the first sample vehicle can also be calculated through the global navigation satellite system data, inertial measurement unit data and laser point cloud data of the autonomous driving vehicle; or, the position information of the first sample vehicle can also be obtained by positioning the vehicle to be detected using other positioning systems, such as the global positioning system or the Beidou satellite navigation system, etc., and no specific restrictions are made here.

[0066] Step a2: obtaining sample weather forecast information corresponding to the first sample vehicle based on the location information.

[0067] The sample weather forecast information corresponding to the first sample vehicle is obtained based on the location information, which is similar to the method of determining the target weather forecast information and will not be repeated here.

[0068] In an embodiment of the present application, by acquiring location information of multiple first sample vehicles and obtaining sample weather forecast information corresponding to the first sample vehicles based on the location information, subsequent steps can obtain the correspondence between weather forecast information and induced rainfall based on the sample weather forecast information and the first sample induced rainfall corresponding to the sample weather forecast information.

[0069] Step 240 , predicting the wiper gear position based on the target sensed rainfall to obtain the predicted wiper gear position.

[0070] Specifically, the above step 240 includes:

[0071] Step 2401, obtaining target minimum light information collected by the vehicle to be detected.

[0072] The target minimum light information is the light intensity with the minimum value collected by the vehicle to be detected. The target minimum light information can be discrete light data or continuous light data, which is specifically determined by the light information collection device, wherein the light information collection device can be a light intensity sensor or other devices. For example, if the target minimum light information is collected by a light intensity sensor, the target minimum light information is continuous light data.

[0073] In addition, there are multiple light quantity information collected from the vehicle to be detected, and the light quantity information with the smallest value (ie, the target minimum light quantity information) can be obtained from the multiple light quantity information.

[0074] Step 2402, predicting the wiper position based on the target minimum light information and the target sensed rainfall to obtain the predicted wiper position.

[0075] It can be understood that by obtaining the maximum predicted wiper gear (i.e., the wiper predicted gear) under the scenario of minimum light intensity and maximum rainfall, the subsequent steps can generate an aging warning result when the predicted probability of the maximum wiper gear is greater than the probability of exceeding the maximum wiper gear configured for the vehicle to be tested (i.e., the preset probability).

[0076] Specifically, based on the target minimum light information and the target sensed rain amount, the wiper gear is predicted to obtain the predicted wiper gear. The predicted wiper gear can be obtained based on the mapping relationship among the target minimum light information, the target sensed rain amount and the wiper gear. The predicted wiper gear can also be obtained by substituting the target minimum light information and the target sensed rain amount into a preset calculation formula formed by the three parameters of light information, sensed rain amount and wiper gear position to calculate the predicted wiper gear, and so on.

[0077] In an optional manner, the prediction of the wiper gear is implemented based on the gear prediction model. Since the gear prediction model processes input discrete data, when the target minimum light information is continuous light data, according to the input requirements of the gear prediction model, the target minimum light information needs to be discretized, and the continuous light data is converted into discrete continuous light data to obtain discrete target minimum light information, and the discrete target minimum light information and the target sensed rain are input into the gear prediction model, and the wiper gear is predicted by the gear prediction model to obtain the predicted wiper gear; when the target minimum light information is discrete light data, the target minimum light information and the target sensed rain can be directly input into the gear prediction model, and the wiper gear is predicted by the gear prediction model to obtain the predicted wiper gear.

[0078] The discretization process for the target minimum light amount information may be a clustering-based discretization process for the target minimum light amount information, or other discretization methods, which are not specifically limited herein.

[0079] Furthermore, the gear prediction model can be determined by obtaining original sample data of multiple second sample vehicles, where the original sample data includes the original sample wiper gear, the original sample light information and the second sample sensed rainfall at the same time; for each second sample vehicle, the original sample data is preprocessed to obtain sample data, as well as the second sample sensed rainfall, sample light information and sample wiper gear of the sample data at the same time; and then a preset gear prediction model is trained based on the sample data to obtain the gear prediction model.

[0080] The second sample sensing rainfall and sample light quantity information at the same time are inputs of the preset gear prediction model, and the sample wiper gear at the same time is the output of the preset gear prediction model.

[0081] The second sample vehicle and the first sample vehicle can be the same vehicle or different vehicles, which can be determined according to actual needs. The original sample wiper gear position, the original sample light information and the second sample sensing rainfall at the same time, that is, the original sample wiper gear position, the original sample light information and the second sample sensing rainfall are collected at the same time, and the three are in a one-to-one correspondence.

[0082] For example, the range of the original sample light quantity information may be 0 to 30630 lumens. The sample wiper gear may be any one of 0 to 4, where 0 is not turned on and 4 is the highest gear.

[0083] In an embodiment of the present application, by obtaining original sample data of multiple second sample vehicles and preprocessing the original sample data for each second sample vehicle, the quality of the original sample data can be improved, and then by training a preset gear prediction model based on the sample data to obtain a gear prediction model, the gear prediction performance of the gear prediction model can be improved, and the accuracy of the gear prediction model in gear prediction can be improved.

[0084] In an optional manner, the original sample data is preprocessed to obtain sample data, specifically, the original sample light quantity information is discretized to obtain sample light quantity information, and the sample wiper maximum gear of the second sample vehicle and the minimum original sample induced rainfall corresponding to the sample wiper maximum gear in the original sample data are obtained. Then, the original sample induced rainfall to be adjusted whose original sample induced rainfall is greater than the minimum original sample induced rainfall in the original sample data is queried. Finally, the original sample wiper gear corresponding to the original sample induced rainfall to be adjusted is increased to obtain the sample wiper gear corresponding to the original sample induced rainfall to be adjusted, so as to obtain sample data.

[0085] The original sample light quantity information is not the minimum light quantity information, but all the light quantity information collected by the sample vehicle.

[0086] The original sample light quantity information is discretized to obtain the sample light quantity information, that is, the continuous original sample light quantity information is converted into discrete sample light quantity information. In addition, the original sample light quantity information can be discretized based on clustering, or other discretization methods, which are not specifically limited here.

[0087] In addition, the original sample wiper gear corresponding to the original sample sensing rainfall to be adjusted is adjusted higher, which can be adjusted higher by 1 gear, 2 gears, or even more gears, which is determined according to the actual situation. It should be noted that the sample wiper gear after the original sample wiper gear is adjusted higher can ensure that when the actual rainfall reaches the original sample sensing rainfall to be adjusted, the field of vision through the front windshield of the sample vehicle is clear, so as to ensure the safety of driving in rainy days.

[0088] In the embodiment of the present application, by raising the original sample wiper gear corresponding to the original sample sensed rainfall to be adjusted, it is possible to ensure that the clarity of the field of vision through the front windshield of the sample vehicle is maintained when the actual rainfall of the adjusted sample wiper gear reaches the original sample sensed rainfall to be adjusted, thereby ensuring the gear prediction model obtained based on the sample wiper gear training for the prediction performance of the aging of the wiper rubber strips.

[0089] Step 250, determining the aging warning result of the wiper rubber strip based on the predicted wiper gear position and the preset warning conditions.

[0090] Specifically, when the predicted gear position of the wiper includes the probability of each predicted gear position of the wiper, and the preset warning condition includes the preset probability, the above step 250 includes:

[0091] Step 2501, obtaining the maximum gear position of the wiper of the vehicle to be detected.

[0092] Step 2502, based on the predicted probabilities of the various gears of the wiper, obtain the predicted probability of the maximum gear of the wiper.

[0093] The predicted probability of each gear of the wiper includes a corresponding relationship between the gear number and the predicted probability, wherein the predicted probability of the gear is used to characterize the probability that the gear of the wiper is greater than the preset gear.

[0094] The predicted probability of each wiper gear position can be pre-tested, and the predicted probability of the wiper maximum gear position is obtained by matching the predicted probability of each wiper gear position with the wiper maximum gear position of the vehicle to be tested. The predicted probability of the wiper maximum gear position is used to characterize the probability that the wiper maximum gear position is greater than the preset maximum gear position.

[0095] Step 2503: if the predicted probability of the maximum gear of the wiper is greater than the preset probability, the aging warning result is determined to output aging warning information.

[0096] The method of outputting the aging warning information includes at least one of telephone, email, instant message or vehicle-mounted terminal output, which is not specifically limited here.

[0097] In an embodiment of the present application, by obtaining the maximum gear of the wiper of the vehicle to be tested and the predicted probability based on each gear of the wiper, the predicted probability of the maximum gear of the wiper can be obtained. If the predicted probability of the maximum gear of the wiper is greater than the preset probability, it indicates that the aging degree of the wiper rubber strip poses a driving risk. At this time, aging warning information can be output to prompt the user to replace the wiper rubber strip in time to ensure driving safety.

[0098] In an optional manner, when the preset warning conditions include the maximum gear of the wiper of the vehicle to be tested, the aging warning result of the wiper strip is determined based on the predicted gear of the wiper and the preset warning conditions. Specifically, the maximum predicted gear of the wiper can be determined from the predicted gear of the wiper. If the maximum predicted gear of the wiper is greater than the maximum gear of the wiper, the aging warning result is determined to output aging warning information.

[0099] There are several predicted wiper gears. When there are multiple predicted wiper gears, the predicted wiper gears can be sorted in ascending order or descending order to quickly determine the maximum predicted wiper gear from the predicted wiper gears.

[0100] In an embodiment of the present application, the maximum predicted wiper gear is determined from the predicted wiper gear, and the maximum predicted wiper gear is compared with the maximum wiper gear. If the maximum predicted wiper gear is greater than the maximum wiper gear, it indicates that the aging degree of the wiper rubber strip poses a driving risk. At this time, aging warning information can be output to prompt the user to replace the wiper rubber strip in time to ensure driving safety.

[0101] The process of the wiper rubber strip aging warning method provided in the embodiment of the present application is described in detail below with a specific example.

[0102] Reference Figure 3 and Figure 4 , step 1, collect the location information and rainfall sensing level data (i.e., first sample sensing rainfall) of multiple first sample vehicles at different times, and obtain the sample weather forecast information (i.e., the corresponding rainfall data in the weather forecast) of the area where the first sample vehicles are located based on the location information.

[0103] Specifically, assuming that the first sample vehicle is a vehicle of model vin001, and the location information corresponding to the vehicle is X city Y district, then the rainfall sensing level data corresponding to the location information collected by the rain sensor is shown in Table 1 below, and the sample weather forecast information corresponding to the location information of the first sample vehicle is shown in Table 2, wherein the rainfall sensing level data is collected by the rain sensor once per second, and the sample weather forecast information is collected once per hour, so the mode of the second-level rainfall sensing level data is taken to obtain the hourly sample weather forecast information (i.e., the corresponding rainfall data in the weather forecast). In addition, the location information in this example is the latitude and longitude information.

[0104] Table 1

[0105]

[0106]

[0107] Table 2

[0108]

[0109] It should be noted that the timestamp “2023 / 6 / 1 11” in the first row of data in Tables 1 and 2 refers to hourly data, and the corresponding rainfall sensing level data is the specific value obtained after time scale normalization.

[0110] Next, by summarizing and correlating the above Table 1 and Table 2, we can obtain the data shown in the following Table 3.

[0111] Table 3

[0112]

[0113]

[0114] Step 2: Perform linear regression on the multiple groups of sample weather forecast information collected in step 1 and the first sample induced rainfall to obtain a rainfall prediction model with the sample weather forecast information (weather forecast rainfall data) as the independent variable and the first sample induced rainfall (i.e., the rainfall sensing level data sensed by the rain sensor) as the dependent variable. The rainfall prediction model is as follows: Figure 5 shown.

[0115] Step 3: Collect multiple groups of original sample data at different times when the wipers of the second sample vehicles are turned on. The original sample data include the original sample wiper gear, original sample light information and second sample sensed rainfall at the same time. Among them, the second sample vehicle is the same as the first sample vehicle, that is, both are vehicles of model vin001. The original sample data are shown in Table 4.

[0116] Table 4

[0117]

[0118] Step 4: Discretize the original sample light information collected in step 3 based on clustering, convert continuous data into discrete values, and obtain sample light information. Record the lowest sample light information, recorded as x1.

[0119] Step 5: Replace the original sample light quantity information in step 3 with the sample light quantity information in step 4 to obtain the sample data shown in Table 5.

[0120] Table 5

[0121]

[0122] Step 6: If the maximum gear of the sample wiper of the second sample vehicle is 5, the sample data of the wiper gear of the same sample vehicle is 5, and the maximum gear of the sample wiper of the second sample vehicle is obtained as shown in Table 6 below, as well as the original sample sensed rainfall corresponding to the maximum gear of the sample wiper in the original sample data.

[0123] Table 6

[0124]

[0125]

[0126] According to the above table, the minimum original sample induced rainfall Xmin is 12. The original sample induced rainfall greater than the minimum original sample induced rainfall Xmin is determined as the original sample induced rainfall to be adjusted. The original sample wiper gear corresponding to the original sample induced rainfall to be adjusted is increased by 1 gear to obtain the sample wiper gear 6. The updated sample data is shown in Table 7 below.

[0127] Table 7

[0128]

[0129] The preset gear prediction model is trained based on the sample data, that is, the second sample sensing rainfall and the sample light information are used as the input of the preset gear prediction model, and the sample wiper gear at the same time is used as the output of the preset gear prediction model. The Bayesian classification model is trained to obtain the gear prediction model.

[0130] Step 7: After the vehicle to be detected gets off the electric lock, collect its last uploaded current location, and obtain the rainfall in the weather forecast for the next 48 hours in the current area of ​​the vehicle to be detected based on the current location.

[0131] Step 8: Input the maximum rainfall value in the weather forecast in step 7 (i.e., target weather forecast information) into the rainfall prediction model obtained in step 2 to predict the maximum rainfall sensing level data x2 (i.e., target sensing rainfall) that the rain sensor may sense in the next 48 hours.

[0132] Step nine: Input the lowest sample light information x1 in step four and the maximum rain sensing level data x2 in step eight into the gear prediction model in step six to obtain the predicted probability of each wiper gear required when the weather forecast has the maximum rainfall and the worst light intensity (i.e., the target minimum light information) in the next 48 hours.

[0133] Step ten: Count the predicted probabilities of the wiper gears in step nine, and find the predicted probability of the wiper maximum gear (i.e., the wiper predicted gear) that exceeds the preset wiper maximum gear (5 in this embodiment), i.e., the probability p that the wiper gear is 6, and compare it with the preset probability p' (0.5 in this embodiment). When p>p', push the wiper strip aging warning information to the user to remind the user to replace the wiper strip in time.

[0134] In summary, compared with the traditional method of replacing wiper strips at a fixed time, the wiper strip aging warning method of this embodiment effectively evaluates the actual aging degree of the vehicle's wiper strips, avoids driving hazards caused by excessive aging of the wiper strips, and avoids the waste caused by premature replacement of wiper strips.

[0135] Figure 6 FIG. 2 is a schematic diagram showing the structure of an embodiment of the wiper rubber strip aging warning device of the present invention. Figure 6 As shown, the wiper rubber strip aging warning device 600 includes:

[0136] The acquisition module 610 is used to acquire the current position of the vehicle to be detected;

[0137] A weather forecast information determination module 620, for obtaining target weather forecast information based on the current location;

[0138] The sensed rainfall determination module 630 is used to determine the target sensed rainfall corresponding to the target weather forecast information based on the corresponding relationship between the weather forecast information and the sensed rainfall;

[0139] A wiper predicted gear determination module 640 is used to predict the wiper gear based on the target sensed rainfall to obtain the wiper predicted gear;

[0140] The aging warning result generating module 650 is used to determine the aging warning result of the wiper rubber strip based on the predicted gear position of the wiper and the preset warning conditions.

[0141] In an optional manner, the predicted gear position of the wiper includes the probability of each predicted gear position of the wiper, the preset warning condition includes the preset probability, and the aging warning result generating module 650 specifically includes:

[0142] The first acquisition submodule is used to acquire the maximum gear position of the wiper of the vehicle to be detected;

[0143] A first determination submodule, configured to obtain a prediction probability of a maximum gear position of the wiper based on the prediction probabilities of each gear position of the wiper;

[0144] The first aging warning result generating submodule is used to determine the aging warning result as outputting aging warning information if the predicted probability of the maximum gear position of the wiper is greater than a preset probability.

[0145] In an optional manner, the preset warning condition includes the maximum gear position of the wiper of the vehicle to be detected, and the aging warning result generation module 650 specifically includes:

[0146] A wiper maximum predicted gear determination submodule, used to determine the wiper maximum predicted gear from the wiper predicted gears;

[0147] The second aging warning result generating submodule determines the aging warning result as outputting aging warning information if the wiper maximum predicted gear is greater than the wiper maximum gear.

[0148] In an optional manner, the sensed rainfall determination module 630 specifically includes:

[0149] A second acquisition submodule is used to acquire sample weather forecast information and first sample sensed rainfall of a plurality of first sample vehicles;

[0150] The second determination submodule is used to perform fitting based on the sample weather forecast information and the first sample induced rainfall to obtain a corresponding relationship between the weather forecast information and the induced rainfall.

[0151] In an optional manner, the second acquisition submodule specifically includes:

[0152] A first acquisition unit, used to acquire position information of a plurality of second sample vehicles;

[0153] The sample weather forecast information determining unit is used to obtain the sample weather forecast information corresponding to the second sample vehicle based on the location information.

[0154] In an optional manner, the wiper predicted gear determination module 640 specifically includes:

[0155] The third acquisition submodule is used to obtain the target minimum light information collected by the vehicle to be detected;

[0156] The wiper gear prediction submodule is used to predict the wiper gear based on the target minimum light information and the target sensed rainfall to obtain the wiper predicted gear.

[0157] In an optional manner, the prediction of the wiper gear is implemented based on a gear prediction model, and the wiper rubber strip aging warning device further includes a gear prediction model determination module, and the gear prediction model determination module includes:

[0158] A fourth acquisition submodule is used to acquire original sample data of multiple second sample vehicles, where the original sample data includes original sample wiper gear positions, original sample light information, and second sample sensed rainfall at the same time;

[0159] A preprocessing submodule, for preprocessing the original sample data for each second sample vehicle to obtain sample data, as well as second sample sensing rainfall, sample light information and sample wiper gear position of the sample data at the same time;

[0160] The training submodule is used to train the preset gear prediction model based on the sample data to obtain the gear prediction model. The second sample sensed rainfall and sample light information at the same time are the input of the preset gear prediction model, and the sample wiper gear at the same time is the output of the preset gear prediction model.

[0161] In an optional manner, the preprocessing submodule specifically includes:

[0162] A discretization unit, used for discretizing the original sample light quantity information to obtain the sample light quantity information;

[0163] A second acquisition unit is used to acquire the maximum gear position of the sample wiper of the second sample vehicle and the minimum original sample induced rainfall corresponding to the maximum gear position of the sample wiper in the original sample data;

[0164] A query unit, used for querying the original sample induced rainfall to be adjusted in the original sample data, where the original sample induced rainfall is greater than the minimum original sample induced rainfall;

[0165] The sample data acquisition unit is used to increase the original sample wiper gear corresponding to the original sample sensed rainfall to be adjusted, obtain the sample wiper gear corresponding to the original sample sensed rainfall to be adjusted, and obtain sample data.

[0166] The wiper rubber strip aging warning device provided in the embodiment of the present invention can obtain the target weather forecast information of the current position based on the current position; then based on the corresponding relationship between the weather forecast information and the sensed rainfall, determine the target sensed rainfall corresponding to the target weather forecast information, and can predict the wiper gear based on the target sensed rainfall to obtain the wiper predicted gear that matches the target sensed rainfall; then based on the wiper predicted gear and preset warning conditions, determine the aging warning result of the wiper rubber strip, and can effectively evaluate the actual aging degree of the vehicle's wiper rubber strips to remind the user to replace the wiper rubber strips in time. This not only avoids dangerous driving due to excessive aging of the wiper rubber strips, but also avoids the waste of wiper rubber strips due to premature replacement of the wiper rubber strips.

[0167] Figure 7 A schematic structural diagram of an embodiment of the wiper rubber strip aging warning device of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the wiper rubber strip aging warning device.

[0168] like Figure 7 As shown, the wiper rubber strip aging warning device may include: a processor (processor) 702, a communication interface (Communications Interface) 704, a memory (memory) 706, and a communication bus 708.

[0169] The processor 702, the communication interface 704, and the memory 706 communicate with each other via the communication bus 708. The communication interface 704 is used to communicate with other devices such as a client or other server network elements. The processor 702 is used to execute the program 710, which can specifically execute the relevant steps in the above-mentioned embodiment of the method for early warning of aging of wiper rubber strips.

[0170] Specifically, the program 710 may include program code including computer executable instructions.

[0171] The processor 702 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiment of the present invention. The one or more processors included in the wiper rubber strip aging warning device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0172] The memory 706 is used to store the program 710. The memory 706 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0173] According to an embodiment of the present invention, a vehicle is provided, comprising: a vehicle body and a wiper arranged on the vehicle body; a wiper rubber strip aging warning device as in the above embodiment is arranged in the vehicle body, and is used for a wiper rubber strip aging warning method.

[0174] An embodiment of the present invention provides a computer-readable storage medium, which stores at least one executable instruction. When the executable instruction is executed on a wiper strip aging warning device / apparatus, the wiper strip aging warning device / apparatus executes the wiper strip aging warning method in any of the above-mentioned method embodiments.

[0175] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system or other device. In addition, the embodiments of the present invention are not directed to any particular programming language.

[0176] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. Similarly, in order to simplify the present invention and help understand one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, the various features of the embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. Wherein, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, wherein each claim itself is a separate embodiment of the present invention.

[0177] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and further may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive.

[0178] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

Claims

1. A wiper rubber strip aging early warning method, characterized in that: The method comprises: Get the current position of the vehicle to be detected; Obtaining target weather forecast information based on the current location; Determining a target sensed rainfall corresponding to the target weather forecast information based on a correspondence between the weather forecast information and the sensed rainfall; Predicting the wiper gear position based on the target sensed rainfall to obtain a predicted wiper gear position; Based on the predicted gear position of the wiper and the preset warning condition, an aging warning result of the wiper rubber strip is determined.

2. The method according to claim 1, characterized in that The predicted wiper gear includes the probability of each predicted wiper gear, the preset warning condition includes a preset probability, and the aging warning result of the wiper rubber strip is determined based on the predicted wiper gear and the preset warning condition, including: Obtaining the maximum gear position of the wiper of the vehicle to be detected; Based on the predicted probabilities of the various gears of the wiper, the predicted probability of the maximum gear of the wiper is obtained; If the predicted probability of the maximum gear of the wiper is greater than the preset probability, the aging warning result is determined to output aging warning information.

3. The method according to claim 1, characterized in that: The preset warning condition includes the maximum gear position of the wiper of the vehicle to be detected, and the aging warning result of the wiper rubber strip is determined based on the predicted gear position of the wiper and the preset warning condition, including: Determining a maximum predicted wiper gear position from the predicted wiper gear positions; If the wiper maximum predicted gear is greater than the wiper maximum gear, determining the aging warning result is outputting aging warning information.

4. The method according to claim 1, characterized in that: The corresponding relationship between the weather forecast information and the sensed rainfall is determined in the following manner: Obtaining sample weather forecast information and first sample sensed rainfall of a plurality of first sample vehicles; Fitting is performed based on the sample weather forecast information and the first sample sensed rainfall to obtain a corresponding relationship between the weather forecast information and the sensed rainfall.

5. The method according to claim 4, characterized in that The step of obtaining sample weather forecast information of a plurality of first sample vehicles includes: Obtaining location information of a plurality of the first sample vehicles; Sample weather forecast information corresponding to the first sample vehicle is obtained based on the location information.

6. The method according to claim 1, characterized in that The predicting of the wiper gear position based on the target sensed rainfall to obtain the predicted wiper gear position includes: Acquiring target minimum light quantity information collected by the vehicle to be detected; Based on the target minimum light amount information and the target sensed rainfall amount, the wiper gear position is predicted to obtain the wiper predicted gear position.

7. The method according to claim 6, characterized in that The prediction of the wiper gear position is realized based on a gear position prediction model, and the determination method of the gear position prediction model includes: Acquire original sample data of a plurality of second sample vehicles, wherein the original sample data includes original sample wiper gear positions, original sample light quantity information, and original second sample sensed rainfall at the same time; For each of the second sample vehicles, preprocessing the original sample data to obtain sample data, as well as second sample sensing rainfall, sample light information and sample wiper gear position of the sample data at the same time; A preset gear prediction model is trained based on the sample data to obtain the gear prediction model, the second sample sensed rainfall and sample light information at the same time are the input of the preset gear prediction model, and the sample wiper gear at the same time is the output of the preset gear prediction model.

8. The method according to claim 7, characterized in that The preprocessing of the original sample data to obtain sample data includes: Discretizing the original sample light quantity information to obtain the sample light quantity information; Acquire the original sample windshield wiper maximum gear position of the second sample vehicle, and the minimum original sample sensed rainfall corresponding to the original sample windshield wiper maximum gear position in the original sample data; Query the original sample induced rainfall in the original sample data, which is greater than the minimum original sample induced rainfall, for the original sample induced rainfall to be adjusted; The original sample wiper gear corresponding to the original sample sensed rainfall to be adjusted is adjusted higher to obtain the sample wiper gear corresponding to the original sample sensed rainfall to be adjusted, so as to obtain the sample data.

9. A wiper rubber strip aging warning device, characterized in that: The device comprises: An acquisition module is used to obtain the current position of the vehicle to be detected; A weather forecast information determination module, used to obtain target weather forecast information based on the current location; A sensing rainfall determination module, used to determine the target sensing rainfall corresponding to the target weather forecast information based on the corresponding relationship between the weather forecast information and the sensing rainfall; A wiper predicted gear determination module, used for predicting the wiper gear based on the target sensed rainfall to obtain the wiper predicted gear; The aging warning result generating module is used to determine the aging warning result of the wiper rubber strip based on the predicted gear position of the wiper and the preset warning condition.

10. A wiper rubber strip aging warning device, characterized in that: include: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform the operation of the wiper strip aging warning method as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that: The storage medium stores at least one executable instruction. When the executable instruction is executed on the wiper strip aging warning device / apparatus, the wiper strip aging warning device / apparatus performs the operation of the wiper strip aging warning method as described in any one of claims 1 to 8.

12. A vehicle, characterized in that: include: A vehicle body and a wiper disposed on the vehicle body; The wiper strip aging warning device as described in claim 10 is arranged in the vehicle body and is used to execute the wiper strip aging warning method.

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