Rearview mirror frost fog processing method and device, vehicle, storage medium and product

Abstract

The invention discloses a rearview mirror frost fog processing method and device, a vehicle, a storage medium and a product, and relates to the technical field of vehicle defrosting, and the method comprises the steps that environment information of the environment where a rearview mirror outside a target vehicle is located and driving information of the target vehicle are obtained; the environment information and the driving information are input into a preset risk prediction model, a frost and fog risk index of the surface of the rearview mirror is obtained, and the frost and fog risk index represents the frosting and / or fogging risk; and under the condition that the frost and fog risk index is larger than a preset threshold value, the rearview mirror is defrosted and / or defrosted. According to the application, the defrosting and demisting accuracy of the outside rear-view mirror of the vehicle can be improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle defrosting technology, and in particular to a rearview mirror frost treatment method, device, vehicle, storage medium and product. Background Art

[0002] Vehicle exterior mirrors are key components to ensure the driver's driving safety. Their normal operation is crucial to maintaining road traffic safety. In cold and wet weather, frost or condensation fog easily forms on the surface of the vehicle's exterior mirrors, obstructing the driver's field of vision and posing a threat to driving safety.

[0003] At present, the defrosting and defogging device of the vehicle's exterior rearview mirror usually uses electric heating elements such as heating films or heating wires to defrost and defog the exterior rearview mirror. Specifically, the working principle of the defrosting and defogging device is that when the surface temperature of the rearview mirror is lower than a certain threshold, the rearview mirror starts to be heated at a fixed power, and the surface of the rearview mirror is heated to increase its temperature, so that the frost and fog on the rearview mirror melt or evaporate. However, the defrosting and defogging device determines whether the rearview mirror is frosted and fogged based on the temperature, which has the problem of low accuracy and is prone to overheating or underheating.

[0004] Therefore, how to improve the accuracy of defrosting and defogging the vehicle's exterior rearview mirrors is a problem that urgently needs to be solved. Summary of the invention

[0005] The main purpose of this application is to provide a rearview mirror frost and fog processing method, device, vehicle, storage medium and product, aiming to improve the accuracy of defrosting and defogging the vehicle's exterior rearview mirrors.

[0006] To achieve the above-mentioned purpose, the present application provides a method for treating frost and fog of a rearview mirror, the method for treating frost and fog of a rearview mirror comprising:

[0007] Acquiring environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and driving information of the target vehicle;

[0008] Inputting the environmental information and the driving information into a preset risk prediction model to obtain a frost and fog risk index of the rearview mirror surface, wherein the frost and fog risk index represents the risk of frost and / or fogging;

[0009] When the frost and fog risk index is greater than a preset threshold, the rearview mirror is defrosted and / or defogged.

[0010] In one embodiment, the step of obtaining environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and the driving information of the target vehicle includes:

[0011] Acquire sensor data from a sensor installed on an exterior rearview mirror of the vehicle, and determine environmental information of an environment in which the rearview mirror is located based on the sensor data, wherein the sensor data includes at least temperature, humidity and air pressure;

[0012] The vehicle speed is determined, and the vehicle speed is used as the driving information of the vehicle.

[0013] In one embodiment, the step of determining the environmental information of the environment in which the exterior rearview mirror is located based on the sensor data comprises:

[0014] Calculating a dew point temperature of an environment in which the rearview mirror is located based on the temperature and humidity in the sensor data;

[0015] The sensor data and the dew point temperature are used as environmental information of the environment in which the rearview mirror is located.

[0016] In one embodiment, the step of obtaining environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and the driving information of the target vehicle includes:

[0017] For any data item in the sensor data and the driving information, determine whether the data item meets a data mutation condition, wherein the data mutation condition is that the difference between the current value and the historical value of the data item is greater than a preset mutation threshold, and the historical value is the value of the data item detected last time;

[0018] When the data item does not satisfy the data mutation condition, acquiring the environment information and the driving information once every first preset period;

[0019] In the case where the data item meets the data mutation condition, the environmental information and the driving information are acquired once at intervals of a second preset period, wherein the second preset period is shorter than the first preset period.

[0020] In one embodiment, after the step of acquiring the environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and the driving information of the target vehicle, the method further includes:

[0021] Determining whether the humidity in the environmental information reaches a preset high humidity threshold;

[0022] When the humidity reaches the preset high humidity threshold, the air conditioner in the vehicle is controlled to operate in a dehumidification mode.

[0023] In one embodiment, the risk prediction model is trained using sample environmental information and sample driving information as model input data, and using a sample frost and fog risk index that characterizes the actual frosting and / or fogging conditions of the sample rearview mirror as a model training label. The sample environmental information is environmental information of the environment in which the sample rearview mirror outside the sample vehicle is located, and the sample driving information is driving information of the sample vehicle.

[0024] In one embodiment, the step of defrosting and / or defogging the rearview mirror comprises:

[0025] Determining a frost and fog density gradient on the rearview mirror, wherein the frost and fog density gradient represents a degree of density variation of the frost layer and / or fog at different positions;

[0026] Determining a temperature change rate and a humidity change rate based on historical environmental information and the environmental information, wherein the historical environmental information at least includes the environmental information acquired last time;

[0027] Determine a difference between the dew point temperature in the environmental information and a preset dew point temperature, and use the difference as an environmental dew point deviation, wherein the preset dew point temperature is a dew point temperature threshold capable of preventing fogging and frosting of the rearview mirror;

[0028] Calculate a PID parameter based on one or more of the frost fog density gradient, the temperature change rate, the humidity change rate, and the ambient dew point deviation;

[0029] The power of the heating module on the rearview mirror is determined based on the PID parameters to defrost and / or defog the rearview mirror.

[0030] In one embodiment, the step of determining the frost density gradient on the rearview mirror comprises:

[0031] Acquiring image data obtained by photographing the rearview mirror;

[0032] determining the thickness and area of ​​the frost layer and / or fog on the rearview mirror based on the image data;

[0033] A frost density gradient on the rearview mirror is determined based on the thickness and the area.

[0034] In one embodiment, the heating module includes a plurality of heating submodules, and the step of determining the power of the heating module on the rearview mirror based on the PID parameter to defrost and / or defog the rearview mirror includes:

[0035] For any target submodule in each of the heating submodules, determining a heating area of ​​the target submodule on the rearview mirror, and determining a target thickness and a target area of ​​frost and / or fog on the heating area based on the thickness and the area;

[0036] Determining a power weight of the target submodule based on the target thickness and the target area;

[0037] The power of the target submodule is determined based on the PID parameter and the power weight to defrost and / or defog the heating area.

[0038] In one embodiment, the method further comprises:

[0039] monitoring the remaining charge of the vehicle;

[0040] When the remaining power is lower than a preset power threshold, the power of the heating module on the rearview mirror is reduced and / or the dehumidification gear of the air conditioner in the vehicle is lowered.

[0041] In addition, to achieve the above-mentioned purpose, the present application also provides a rearview mirror frost and fog processing device, the rearview mirror frost and fog processing device comprising:

[0042] An acquisition module, used to acquire environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and driving information of the target vehicle;

[0043] A prediction module, used for inputting the environmental information and the driving information into a preset risk prediction model to obtain a frost risk index of the rearview mirror surface;

[0044] The defrost and fog module is used to defrost and / or defog the rearview mirror when the frost and fog risk index is greater than a preset threshold.

[0045] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, which is a computer-readable storage medium, and a program for implementing the rearview mirror frost processing method is stored on the computer-readable storage medium. The program for implementing the rearview mirror frost processing method is executed by a processor to implement the steps of the rearview mirror frost processing method as described above.

[0046] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the rearview mirror frost processing method as described above.

[0047] The present application provides a method for processing frost and fog on a rearview mirror. The present application first obtains environmental information of the environment in which the exterior rearview mirror of a target vehicle is located and driving information of the target vehicle, constructs a target feature vector based on the environmental information and driving information, inputs the target feature vector into a risk prediction model, obtains a frost and fog risk index on the surface of the rearview mirror, and defrosts the rearview mirror when the frost and fog risk index is greater than a preset threshold.

[0048] In summary, the present application predicts the frost risk index of the rearview mirror surface based on the environmental information of the environment in which the rearview mirror is located and the driving information of the vehicle, and defrosts the rearview mirror when the frost risk index is greater than a preset threshold. In this way, compared with the traditional method of determining whether the rearview mirror is frosted based on a single piece of information, the present application improves the accuracy of defrosting the vehicle's exterior rearview mirror. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0051] Figure 1 This is a flow chart of the first embodiment of the rearview mirror frost treatment method of the present application;

[0052] Figure 2 A schematic diagram of a rearview mirror frost and fog processing process according to an embodiment of a rearview mirror frost and fog processing method of the present application;

[0053] Figure 3 A schematic diagram of the structure of a rearview mirror involved in an embodiment of a method for treating frost and fog on a rearview mirror of the present application;

[0054] Figure 4 A schematic diagram of the architecture of a rearview mirror frost and fog processing system according to an embodiment of the rearview mirror frost and fog processing method of the present application;

[0055] Figure 5 This is a schematic diagram of the module structure of the rearview mirror frost and fog treatment device of this application;

[0056] Figure 6 Schematic diagram of the equipment structure of the hardware operating environment involved in the rearview mirror frost processing method in the embodiment of the present application.

[0057] Description of Figure Numbers:

[0058] 10. Rearview mirror lens; 20. Sensor; 30. Rearview mirror front cover; 40. Rearview mirror control module; 50. Heating adjustment device; 60. Rearview mirror housing; 70. Wiring harness; 80. Rearview mirror base.

[0059] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0060] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0061] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0062] The main solution of the present application is: to obtain environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and the driving information of the target vehicle; to input the environmental information and the driving information into a preset risk prediction model to obtain a frost and fog risk index on the surface of the rearview mirror; and to defrost and / or defog the rearview mirror when the frost and fog risk index is greater than a preset threshold.

[0063] At present, the defrosting and defogging device of the vehicle's exterior rearview mirror usually uses electric heating elements such as heating films or heating wires to defrost and defog the exterior rearview mirror. Specifically, the working principle of the defrosting and defogging device is that when the surface temperature of the rearview mirror is lower than a certain threshold, the rearview mirror starts to be heated at a fixed power, and the surface of the rearview mirror is heated to increase its temperature, so that the frost and fog on the rearview mirror melt or evaporate. However, the defrosting and defogging device determines whether the rearview mirror is frosted and fogged based on the temperature, which has the problem of low accuracy and is prone to overheating or underheating.

[0064] Therefore, how to improve the accuracy of defrosting and defogging the vehicle's exterior rearview mirrors is a problem that urgently needs to be solved.

[0065] The present application predicts the frost risk index of the rearview mirror surface based on the environmental information of the environment in which the rearview mirror is located and the driving information of the vehicle, and defrosts the rearview mirror when the frost risk index is greater than a preset threshold. In this way, compared with the traditional method of determining whether the rearview mirror is frosted based on a single piece of information, the present application improves the accuracy of defrosting the vehicle's exterior rearview mirror.

[0066] It should be noted that the execution subject of the method in each embodiment of the rearview mirror frost treatment method of the present application can be a rearview mirror frost treatment system, or a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or a vehicle capable of realizing the above functions, etc., and this embodiment does not specifically limit this. The following takes the rearview mirror frost treatment system as an example of the execution subject to explain this embodiment and the following embodiments.

[0067] Based on this, the present application proposes a method for treating rearview mirror frost and fog in the first embodiment, please refer to Figure 1 The rearview mirror frost treatment method includes steps S10 to S30:

[0068] Step S10, obtaining environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and driving information of the target vehicle;

[0069] It should be noted that the environment in which the vehicle's exterior rearview mirror is located is referred to as the environment for distinction. Environmental information at least includes weather information and air pressure information. The vehicle that currently needs to perform rearview mirror frost treatment is referred to as the target vehicle.

[0070] In this embodiment, the step S10 may include:

[0071] Step S101, acquiring sensor data from a sensor installed on an exterior rearview mirror of a vehicle, and determining environmental information of an environment in which the rearview mirror is located based on the sensor data, wherein the sensor data includes at least temperature, humidity and air pressure;

[0072] It should be noted that a temperature sensor and a humidity sensor are installed on the vehicle rearview mirror lens, which are used to collect temperature and humidity information on the surface of the rearview mirror lens in real time, and transmit the collected temperature and humidity to the rearview mirror control module. A pressure sensor is also installed on the vehicle rearview mirror to collect the air pressure of the environment in which the rearview mirror is located in real time. And, in a feasible implementation, the temperature sensor and humidity sensor in the embodiment of the present application are both high-precision digital sensors, the temperature sensor can perform high-precision measurements within 0 degrees Celsius to 40 degrees Celsius, and the humidity sensor can perform high-precision measurements within 20% RH to 90% RH.

[0073] Sensor data are respectively obtained from the temperature sensor, humidity sensor and air pressure sensor installed in the environment of the vehicle's exterior rearview mirror, that is, the sensor data at least includes the temperature, humidity and air pressure on the rearview mirror lens, and then the environmental information of the environment in which the rearview mirror is located is determined based on the sensor data.

[0074] In this embodiment, the step S101 may include:

[0075] Step A10, calculating the dew point temperature of the environment in which the rearview mirror is located based on the temperature and humidity in the sensor data;

[0076] Step A20: Using the sensor data and the dew point temperature as environmental information of the environment in which the rearview mirror is located.

[0077] It should be noted that, under standard atmospheric pressure, the dew point temperature can be determined based on temperature and humidity.

[0078] First, the dew point temperature in the environment is calculated based on the temperature and humidity in the sensor data, and then both the sensor data and the dew point temperature are used as environmental information of the environment.

[0079] In one feasible implementation, the temperature and humidity are substituted into the Magnus empirical formula to calculate the dew point temperature in the environment. The Magnus empirical formula is expressed as:

[0080]

[0081] Among them, T d is the dew point temperature, T is the temperature in the sensor data, RH is the humidity in the sensor data, a=17.27, b=237.7 degrees Celsius,

[0082] Step S102, determining the speed of the vehicle, and using the speed as the driving information of the vehicle.

[0083] In a feasible implementation manner, the vehicle's driving information is acquired from a wheel speed sensor of the vehicle through a rearview mirror control module, and the driving information at least includes the vehicle speed.

[0084] Step S20, inputting the environmental information and the driving information into a preset risk prediction model to obtain a frost and fog risk index of the rearview mirror surface, wherein the frost and fog risk index represents the risk of frost and / or fogging;

[0085] In this embodiment, the risk prediction model is trained using sample environmental information and sample driving information as model input data, and using a sample frost and fog risk index that characterizes the actual frosting and / or fogging conditions of the sample rearview mirror as a model training label. The sample environmental information is environmental information of the environment in which the sample rearview mirror outside the sample vehicle is located, and the sample driving information is driving information of the sample vehicle.

[0086] It should be noted that the initial prediction model is trained in advance. Specifically, the environmental information (hereinafter referred to as the sample environmental information for distinction) of the environment in which the vehicle (exterior rearview mirror (hereinafter referred to as the sample rearview mirror for distinction) is located is obtained, and the driving information of the vehicle (hereinafter referred to as the sample driving information for distinction) is obtained, and a feature vector is constructed based on the sample environmental information and the sample driving information. In addition, a frost and fog risk index (hereinafter referred to as the sample frost and fog risk index for distinction) is obtained, which characterizes the actual frosting and / or fogging conditions of the sample rearview mirror in the second environment. Then, the initial prediction model is trained with the feature vector as the model input data and the sample frost and fog risk index as the model training label to obtain a risk prediction model. It can be understood that the corresponding frost and fog risk index can be mapped based on the degree of frost and fogging of the sample rearview mirror in the second environment. Exemplarily, the frost and fog risk index can be a value between 0 and 1, where 0 indicates that there is no risk of frost and fogging, and 1 indicates that the frost layer and / or fog on the rearview mirror can affect the normal driving of the driver.

[0087] In one feasible implementation, the step of inputting environmental information and driving information into the risk prediction model may include: performing data preprocessing on each item of data in the environmental information and driving information respectively to obtain the characteristic quantity corresponding to each item of data; combining each characteristic quantity to obtain a characteristic vector (hereinafter referred to as the target characteristic vector for distinction); and then inputting the target characteristic vector into the risk prediction model.

[0088] The environmental information and driving information are input into a pre-trained risk prediction model to obtain a frost and fog risk index on the rearview mirror surface, wherein the frost and fog risk index represents the risk of frost and / or fogging on the rearview mirror surface.

[0089] The model input data includes the temperature, humidity, air pressure and dew point temperature in the environment, as well as the vehicle speed. It should be understood that the effect of temperature on the frosting of the rearview mirror is that the lower the temperature, the greater the possibility of water vapor condensing into frost, and the faster the frosting speed may be; humidity reflects the content of water vapor in the air, so the effect of humidity on the frosting of the rearview mirror is that the higher the humidity, the easier it is for water vapor to condense into frost when the temperature drops below the dew point temperature; the speed affects the relative movement speed of the rearview mirror and the surrounding air. The faster the speed, the more intense the heat exchange between the air and the rearview mirror surface, the faster the heat loss on the rearview mirror surface, and the faster the temperature drops, which may cause the surface temperature of the rearview mirror to drop below the dew point temperature faster, thereby increasing the risk of frosting. The influence of each data on fogging is similar.

[0090] Step S30, when the frost and fog risk index is greater than a preset threshold, defrosting and / or defogging the rearview mirror.

[0091] It should be noted that the index threshold for turning on the defrost function, ie, the above-mentioned preset threshold, is set in advance according to an empirical value. The embodiment of the present application does not limit the specific size of the above-mentioned preset threshold.

[0092] After obtaining the frost and fog risk index output by the risk prediction model, it is determined whether the frost and fog risk index is greater than a preset threshold. If the frost and fog risk index is greater than the preset threshold, the rearview mirror defrosting and defogger function is started.

[0093] The embodiment of the present application predicts the frost and fog risk index of the rearview mirror surface based on the environmental information of the environment in which the rearview mirror is located and the driving information of the vehicle, and defrosts and defogs the rearview mirror when the frost and fog risk index is greater than a preset threshold. In this way, compared with the traditional method of determining whether the rearview mirror is frosted and fogged based on a single piece of information, the present application improves the accuracy of defrosting and defogging the vehicle's exterior rearview mirror.

[0094] In this embodiment, the step S10 may include:

[0095] Step B10, for any data item in the sensor data and the driving information, determining whether the data item meets a data mutation condition, wherein the data mutation condition is that the difference between the current value and the historical value of the data item is greater than a preset mutation threshold, and the historical value is the value of the data item detected last time;

[0096] It should be noted that the sensor data includes at least temperature, humidity and air pressure, and the driving information includes at least vehicle speed. The mutation conditions corresponding to each data item are pre-set, that is, the above-mentioned data mutation conditions. Exemplarily, the data mutation condition of temperature can be: compared with the temperature detected last time, the temperature detected this time increases or decreases by 10 degrees Celsius; the data mutation condition of humidity can be: compared with the humidity detected last time, the humidity detected this time increases or decreases by 15%RH; the data mutation condition of air pressure can be: compared with the air pressure detected last time, the air pressure detected this time increases or decreases by 5kPa; the data mutation condition of vehicle speed can be: compared with the vehicle speed detected last time, the vehicle speed detected this time increases or decreases by 20 yards.

[0097] For any data item in the sensor data and driving information, namely, temperature, humidity, air pressure and vehicle speed, determine whether each data item meets the data mutation condition. The current value of the data item is the value of the data item detected at that time, and the historical value of the data item is the value of the data item detected last time.

[0098] Step B20, when the data item does not satisfy the data mutation condition, acquiring the environmental information and the driving information once every first preset period;

[0099] It should be noted that the cycle for obtaining environmental information and driving information is pre-set, that is, the above-mentioned first preset cycle. This application does not limit the specific duration of the first preset cycle. In this embodiment, the first preset cycle can be set to 200ms.

[0100] When the data item does not satisfy the data mutation condition, the environmental information and the driving information are acquired once every first preset period.

[0101] Step B30: When the data item meets the data mutation condition, the environmental information and the driving information are acquired once at intervals of a second preset period, wherein the second preset period is smaller than the first preset period.

[0102] It should be noted that another cycle for obtaining environmental information and driving information is preset, that is, the second preset cycle mentioned above, and the second preset cycle is smaller than the first preset cycle. In this embodiment, the second preset cycle can be set to 10 ms.

[0103] When the data item meets the data mutation condition, the environmental information and the driving information are acquired once at every second preset period.

[0104] In one possible implementation, if Figure 2 The figure shows a schematic diagram of the rearview mirror frost and fog processing flow, for each data item in the sensor data and driving information, determine whether the data item meets the data mutation condition; if not, obtain the environmental information and driving information once every first preset period; if so, obtain the environmental information and driving information once every second preset period; input the environmental information and driving information into a pre-trained risk prediction model to obtain the frost and fog risk index of the rearview mirror; when the frost and fog risk index is greater than a preset threshold, control the heating module to heat, defrost and defog the rearview mirror; and when the frost and fog risk index is less than or equal to the preset threshold, return to execute the step of performing mutation judgment on the data item.

[0105] In this way, the embodiment of the present application switches to a faster channel when a data mutation is detected, so as to pay more attention to the changes in the risk of frost and fogging of the rearview mirror, and thus heat, defrost and defog the rearview mirror in time based on the frost and fog risk index.

[0106] In this embodiment, after step S10, the rearview mirror frost treatment method of the present application further includes:

[0107] Step C10, determining whether the humidity in the environmental information reaches a preset high humidity threshold;

[0108] Step C20, when the humidity reaches the preset high humidity threshold, controlling the air conditioner in the vehicle to operate in a dehumidification mode.

[0109] It should be noted that the humidity threshold for determining that the environment is high humidity is pre-set, that is, the above-mentioned preset high humidity threshold. The embodiment of the present application does not limit the specific size of the preset high humidity threshold. In this embodiment, the preset high humidity threshold can be set to 90%.

[0110] After obtaining the environmental information, the humidity of the environment in which the rearview mirror is currently detected is determined, and it is judged whether the humidity reaches the preset high humidity threshold. If it is detected that the humidity reaches the preset high humidity threshold, the rearview mirror control module sends an air conditioning command to the air conditioner to turn on the air conditioner for dehumidification.

[0111] In this way, the embodiment of the present application not only uses various monitored data to predict risks, but also automatically controls air conditioning dehumidification based on the monitored humidity to enhance the intelligence of the system.

[0112] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. On this basis, the step S30 may include:

[0113] Step S301, determining a frost and fog density gradient on the rearview mirror, wherein the frost and fog density gradient represents a degree of density change of the frost layer and / or fog at different positions;

[0114] It should be noted that the frost and fog density gradient on the rearview mirror refers to the degree of density change of the frost layer and / or fog at different positions on the rearview mirror.

[0115] In this embodiment, the step S301 may include:

[0116] Step D10, acquiring image data obtained by photographing the rearview mirror;

[0117] Step D20 determines the thickness and area of ​​the frost layer and / or fog on the rearview mirror based on the image data;

[0118] Step D30 determines a frost density gradient on the rearview mirror based on the thickness and the area.

[0119] It should be noted that an integrated micro camera is embedded in the edge of the rearview mirror to capture the image of the rearview mirror.

[0120] The rearview mirror control module obtains image data from the camera by shooting the rearview mirror, and analyzes the image data with the image processing algorithm to obtain the thickness and area of ​​the frost and fog on the rearview mirror surface, and then determines the frost and fog density gradient on the rearview mirror based on the thickness and area.

[0121] Step S302, determining a temperature change rate and a humidity change rate based on historical environmental information and the environmental information, wherein the historical environmental information at least includes the environmental information acquired last time;

[0122] It should be noted that the present application sets a fixed period (first preset period) to perform a frost determination on the rearview mirror, that is, environmental information and driving information are obtained once every first preset period, and the environmental information obtained last time is referred to as historical environmental information for distinction. Specifically, the historical environmental information at least includes the environmental information obtained last time, so it can be understood that in a feasible implementation, the historical environmental information can include the environmental information obtained three times before.

[0123] The temperature change rate and humidity change rate are determined based on the historical environmental information and the current environmental information.

[0124] Step S303, determining a difference between the dew point temperature in the environmental information and a preset dew point temperature, and using the difference as an environmental dew point deviation, wherein the preset dew point temperature is a dew point temperature threshold capable of preventing the rearview mirror from fogging and frosting;

[0125] It should be noted that the dew point temperature threshold that will not cause fogging and frost on the rearview mirror is predetermined, that is, the preset dew point temperature.

[0126] The difference between the actual dew point temperature and the preset dew point temperature in the environmental information detected at the time is calculated, and the difference is used as the environmental dew point deviation, wherein the environmental dew point deviation represents the degree of humidity deviation.

[0127] Step S304, calculating PID parameters based on one or more of the frost fog density gradient, the temperature change rate, the humidity change rate and the ambient dew point deviation;

[0128] Dynamically calculate PID (proportional, integral, differential) parameters based on one or more of frost density gradient, temperature change rate, humidity change rate and ambient dew point deviation.

[0129] In the first feasible implementation, PID parameters are calculated based on the temperature change rate, frost fog density gradient and ambient dew point deviation. Specifically, the three input variables are divided into five fuzzy sets: NB (Negative Big), NS (Negative Small), ZO (Zero), PS (Positive Small), PB (Positive Big). Among them, the membership function of the input variables adopts trigonometric functions to cover the full range of variables, for example: the temperature change rate range is [-2, 2] ℃ / s; the frost fog density gradient range is [0, 5] g / cm3 ; The ambient dew point deviation range is [-3,3]°C. For example, the membership functions of the temperature change rate are NB:[-2,-1,0], NS:[-1,0,1], ZO:[0,1,2], PS:[1,2,3] and PB:[2,3,4]. Then, the output variables (K in PID parameters) are p , K i , K d ) is divided into 5 levels: VS (Very Small), S (Smal l), M (Medium), L (Large), VL (Very Large). Among them, the membership function of the output variable adopts a single value or a narrow trigonometric function to facilitate defuzzification. The rule form in the fuzzy rule base defined based on expert experience and experimental data is: Where ΔT / Δt refers to the rate of temperature change, Refers to the frost density gradient, and ΔE refers to the ambient dew point deviation. Exemplarily, the fuzzy rule table can be defined as follows:

[0130] Fuzzy rule table

[0131] And, the fuzzy reasoning mechanism includes fuzzy matching, rule activation and output aggregation, wherein fuzzy matching includes: calculating the membership of the input variable to each fuzzy set (for example, when ΔT / Δt=1.2, the membership is PS=0.7, ZO=0.3); rule activation includes: traversing all rules and calculating the activation strength of each rule (taking the minimum membership or product), for example, in rule 2, ΔT / Δt=PS(0.7), ΔE=PS(0.6), activation strength=min(0.7,0.5,0.6)=0.5; output aggregation includes: intercepting the output fuzzy set corresponding to each rule according to the activation strength and taking the union. Then defuzzification is performed and the centroid method is used to calculate the precise output parameters:

[0132]

[0133] K i , K d The calculation is similar. In this way, the dynamic adjustment process of PID parameters is: in each control cycle, the input variables are collected, the fuzzy reasoning calculation is determined based on the input variables, and the PID parameters are obtained to update the PID controller parameters based on the PID parameters. Among them, the calculation formula of the PID control amount is as follows:

[0134]

[0135] Among them, the proportional term is K p e(t), used to directly respond to the current error e(t) (the difference between the set value and the actual value), K p The larger the K, the faster the response speed, but too large a value will cause overshoot and oscillation. p Dynamically adjust according to the rate of change of temperature and humidity. If the temperature and humidity change rapidly (such as ΔT / Δt is large), increase K p To speed up the response, if it is close to steady state (ΔT / Δt is small), reduce K p Avoid oscillation. The integral term is Used to accumulate historical errors and eliminate steady-state errors (such as long-term temperature deviations). i The larger the value, the faster the steady-state error converges, but too large a value will lead to integral saturation (continuous overshoot). i Affected by the frost fog density gradient. If the frost is severe ( Larger), increase K i To accelerate melting, if the frost is slight ( Smaller), reduce K i Avoid excessive integration. The differential term is Used to predict future error trends (through error change rate) and suppress overshoot. d The larger the value, the stronger the system damping, but it is more sensitive to noise. In adaptive fuzzy PID, K d Adjust according to the ambient dew point deviation (ΔE). If the dew point deviation is large (humidity deviates seriously from the target), increase K d Enhance stability. If the target dew point is close (ΔE is small), reduce K. d Avoid amplification of high-frequency noise.

[0136] In the second feasible implementation, the PID parameters are calculated based on the temperature change rate. First, the temperature change rate is divided into 5 fuzzy sets: NB (negative large), NS (negative small), ZO (zero), PS (positive small), PB (positive large), and the output variable (PID parameter) is divided into 5 levels: VS (very small), S (small), M (medium), L (large), VL (large). The definition rule form is: IFΔT / Δt=A THEN K p =X,K i =Y,K d = Z. Then use the centroid method to calculate K p , K i and K d , thereby updating the PID control parameters based on the PID parameters to achieve power control in each control cycle.

[0137] In the third feasible implementation, the PID parameters are calculated based on the temperature change rate and the humidity change rate. First, the two input variables are divided into five fuzzy sets: NB (negative large), NS (negative small), ZO (zero), PS (positive small), PB (positive large), and the output variables (PID parameters) are divided into five levels: VS (very small), S (small), M (medium), L (large), VL (large). The definition rule form is: IFΔT / Δt=A ANDΔH / Δt=B THEN K p =X,K i =Y,K d =Z. Where ΔH / Δt refers to the rate of change of humidity. Then the center of gravity method is used to calculate K p , K i and K d , thereby updating the PID control parameters based on the PID parameters to achieve power control in each control cycle.

[0138] Step S305: determining the power of the heating module on the rearview mirror based on the PID parameters to defrost and / or defog the rearview mirror.

[0139] It should be noted that the rearview mirror frost treatment system includes a heating module, which is installed on the surface of the rearview mirror lens and usually adopts a heating film or heating wire. The heating module can automatically adjust the heating power according to the instructions issued by the rearview mirror control module to achieve the best defrosting effect. The heating module includes a three-layer gradient heating structure, namely the surface layer, the middle layer and the bottom layer. The surface layer is a nano silver wire flexible heating film, the middle layer is a PTC (Positive Temperature Coefficient) ceramic heating plate, and the bottom layer is a graphene thermal conductive layer.

[0140] The operating power of the heating module on the rearview mirror is determined based on the PID parameters to defrost and defog the rearview mirror.

[0141] For example, Figure 3 The figure shows a schematic diagram of the structure of a rearview mirror, which includes a rearview mirror lens 10, a sensor 20, a rearview mirror front cover 30, a rearview mirror control module 40, a heating adjustment device 50, a rearview mirror housing 60, a wiring harness 70 and a rearview mirror base 80. The sensor 20 includes at least a temperature sensor, a humidity sensor and an air pressure sensor.

[0142] In this embodiment, the heating module includes a plurality of heating submodules, and the step S304 may include:

[0143] Step E10, for any target submodule in each of the heating submodules, determining a heating area of ​​the target submodule on the rearview mirror, and determining a target thickness and a target area of ​​frost and / or fog on the heating area based on the thickness and the area;

[0144] It should be noted that the heating module includes a plurality of heating submodules to heat the rearview mirror surface in different zones. For example, the mirror surface can be divided into 7*7 grids, and each grid is heated independently.

[0145] Any submodule in each heating submodule is called a target submodule, and the heating area of ​​the target submodule on the rearview mirror is determined. Then, based on the thickness and area of ​​the frost and fog on the rearview mirror obtained previously, the thickness (hereinafter referred to as the target thickness for distinction) and area (hereinafter referred to as the target area for distinction) of the frost and fog on the heating area are determined.

[0146] Step E20, determining the power weight of the target submodule based on the target thickness and the target area;

[0147] The power weight of the target submodule is calculated based on the target thickness and target area of ​​the heating area corresponding to the target submodule. That is, under the condition that the total power used to heat the entire rearview mirror surface is determined, the power proportion of the target submodule is its power weight.

[0148] Step E30: determining the power of the target submodule based on the PID parameter and the power weight, so as to defrost and / or defog the heating area.

[0149] It should be noted that the total power used to heat the entire rearview mirror surface can be determined based on the PID parameters. Therefore, the total power is determined based on the PID parameters, and then the total power is multiplied by the power weight of the target submodule to obtain the heating power of the target submodule. In this way, the heating power of each submodule is determined to defrost and defog the entire rearview mirror surface. And, after the frost and fog on the rearview mirror are cleared, the heating module is controlled to turn off.

[0150] In one possible implementation, if Figure 4 The figure shows a schematic diagram of the architecture of the rearview mirror frost and fog processing system. The rearview mirror frost and fog processing system includes a temperature sensor, a humidity sensor, an air pressure sensor, a rearview mirror control module, a heating module, an on-board air conditioner and a power module. The rearview mirror control module is respectively communicated with each sensor, heating module and on-board air conditioner, and the power module supplies power to each module.

[0151] The embodiment of the present application improves the accuracy of the defrost process by performing zoned heating on the rearview mirror surface. Specifically, the thicker the frost layer and the fog, the greater the heating power, thereby saving energy while achieving effective defrosting and defogger.

[0152] In this embodiment, the rearview mirror frost treatment method of the present application further includes:

[0153] Step F10, monitoring the remaining power of the vehicle;

[0154] Step F20, when the remaining power is lower than a preset power threshold, reducing the power of the heating module on the rearview mirror and / or lowering the dehumidification gear of the air conditioner in the vehicle.

[0155] It should be noted that the power threshold for determining that the vehicle is low on power is preset, that is, the preset power threshold. The present application embodiment does not limit the specific size of the preset power threshold, but in this embodiment, the preset power threshold can be set to 20%.

[0156] During the process of monitoring the frost and fogging of the rearview mirror, the remaining power of the vehicle is also monitored. When it is detected that the remaining power of the vehicle is lower than the preset power threshold, the operating condition of the heating module on the rearview mirror is reduced and / or the dehumidification gear of the air conditioner in the vehicle is lowered.

[0157] In one feasible implementation, an energy consumption optimization algorithm is set to dynamically adjust the power ratio of each system to give priority to ensuring the basic safety power of the rearview mirror. The basic safety power is usually set to more than 70% of the rated power. The energy consumption optimization algorithm is expressed as: Q = Σ(P i ×t i ) / Eremai n. P i represents the real-time operating power (unit: watt, W) of the ith subsystem (such as air conditioning dehumidification, rearview mirror heating), for example, air conditioning dehumidification power (P1 = 1000W), rearview mirror heating power (P2 = 200W); t i represents the expected operating time of the ith subsystem after adjustment (unit: hour, h), which can be a fixed time window (such as the next hour), or the operating time predicted based on user habits; Eremai n represents the remaining available power of the battery (unit: watt-hour, Wh). For example, the remaining battery power Eremai n = 5000Wh; Σ(P i ×t i ) represents the total energy consumption of all subsystems in the expected time (unit: Wh). If the air conditioner runs for 1 hour (t1 = 1) and the rearview mirror runs for 1 hour (t2 = 1), the total energy consumption is (1000×1+200×

[0158] 1=1200Wh); Q represents the energy consumption urgency index, which indicates the ratio of total energy consumption to remaining power. For example, if Q=0.5, it means that under the current power allocation, the remaining power can support the total energy consumption for 2 hours, and if Q=1, it can only support 1 hour. The low power trigger mechanism is: if the remaining battery power drops to Eremai n=1500Wh), the initial Q=1200 / 1500=0.8, which is close to the danger threshold. The arbitration action is:

[0159] Force rearview mirror power ≥ 140W (70% design value); reduce air conditioning power to P 1 =600W, total energy consumption 600×1+140×1=740Wh; new Q=740 / 1500≈0.49, and the battery life is extended to about 2 hours.

[0160] In this way, the embodiment of the present application saves electricity by monitoring the remaining power of the vehicle on the basis of defrosting, demisting and / or dehumidification.

[0161] The present application also provides a rearview mirror frost treatment device, please refer to Figure 5 , the rearview mirror frost treatment device comprises:

[0162] An acquisition module 100 is used to acquire environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and driving information of the target vehicle;

[0163] The prediction module 200 is used to input the environmental information and the driving information into a preset risk prediction model to obtain a frost and fog risk index of the rearview mirror surface, wherein the frost and fog risk index represents the risk of frost and / or fogging;

[0164] The defrost and fog module 300 is used to defrost and / or defog the rearview mirror when the frost and fog risk index is greater than a preset threshold.

[0165] Optionally, the acquisition module 100 is further used for:

[0166] Acquire sensor data from a sensor installed on an exterior rearview mirror of the vehicle, and determine environmental information of an environment in which the rearview mirror is located based on the sensor data, wherein the sensor data includes at least temperature, humidity and air pressure;

[0167] The vehicle speed is determined, and the vehicle speed is used as the driving information of the vehicle.

[0168] Optionally, the acquisition module 100 is further used for:

[0169] Calculating a dew point temperature of an environment in which the rearview mirror is located based on the temperature and humidity in the sensor data;

[0170] The sensor data and the dew point temperature are used as environmental information of the environment in which the rearview mirror is located.

[0171] Optionally, the acquisition module 100 is further used for:

[0172] For any data item in the sensor data and the driving information, determine whether the data item meets a data mutation condition, wherein the data mutation condition is that the difference between the current value and the historical value of the data item is greater than a preset mutation threshold, and the historical value is the value of the data item detected last time;

[0173] When the data item does not satisfy the data mutation condition, acquiring the environment information and the driving information once every first preset period;

[0174] In the case where the data item meets the data mutation condition, the environmental information and the driving information are acquired once at intervals of a second preset period, wherein the second preset period is shorter than the first preset period.

[0175] Optionally, the rearview mirror frost treatment device further includes a humidity monitoring module, and the humidity monitoring module is used to:

[0176] Determining whether the humidity in the environmental information reaches a preset high humidity threshold;

[0177] When the humidity reaches the preset high humidity threshold, the air conditioner in the vehicle is controlled to operate in a dehumidification mode.

[0178] Optionally, the risk prediction model is trained using sample environmental information and sample driving information as model input data, and using a sample frost and fog risk index that characterizes the actual frosting and / or fogging conditions of the sample rearview mirror as a model training label. The sample environmental information is environmental information of the environment in which the sample rearview mirror outside the sample vehicle is located, and the sample driving information is driving information of the sample vehicle.

[0179] Optionally, the defrost mist module 300 is further used for:

[0180] Determining a frost and fog density gradient on the rearview mirror, wherein the frost and fog density gradient represents a degree of density variation of the frost layer and / or fog at different positions;

[0181] Determining a temperature change rate and a humidity change rate based on historical environmental information and the environmental information, wherein the historical environmental information at least includes the environmental information acquired last time;

[0182] Determine a difference between the dew point temperature in the environmental information and a preset dew point temperature, and use the difference as an environmental dew point deviation, wherein the preset dew point temperature is a dew point temperature threshold capable of preventing fogging and frosting of the rearview mirror;

[0183] Calculate a PID parameter based on one or more of the frost fog density gradient, the temperature change rate, the humidity change rate and the ambient dew point deviation;

[0184] The power of the heating module on the rearview mirror is determined based on the PID parameters to defrost and / or defog the rearview mirror.

[0185] Optionally, the defrost mist module 300 is further used for:

[0186] Acquiring image data obtained by photographing the rearview mirror;

[0187] determining the thickness and area of ​​the frost layer and / or fog on the rearview mirror based on the image data;

[0188] A frost density gradient on the rearview mirror is determined based on the thickness and the area.

[0189] Optionally, the heating module includes a plurality of heating submodules, and the defrost mist module 300 is further used for:

[0190] For any target submodule in each of the heating submodules, determining a heating area of ​​the target submodule on the rearview mirror, and determining a target thickness and a target area of ​​frost and / or fog on the heating area based on the thickness and the area;

[0191] Determining a power weight of the target submodule based on the target thickness and the target area;

[0192] The power of the target submodule is determined based on the PID parameter and the power weight to defrost and / or defog the heating area.

[0193] Optionally, the rearview mirror frost treatment device further includes a power monitoring module, and the power monitoring module is used to:

[0194] monitoring the remaining charge of the vehicle;

[0195] When the remaining power is lower than a preset power threshold, the power of the heating module on the rearview mirror is reduced and / or the dehumidification gear of the air conditioner in the vehicle is lowered.

[0196] The rearview mirror frost and fog treatment device provided in the embodiment of the present application adopts the rearview mirror frost and fog treatment method in the above embodiment, which can solve the technical problem of how to improve the accuracy of defrosting and defogging the vehicle's exterior rearview mirror. Compared with the prior art, the beneficial effects of the rearview mirror frost and fog treatment device provided in the embodiment of the present application are the same as the beneficial effects of the rearview mirror frost and fog treatment method provided in the above embodiment, and other technical features in the rearview mirror frost and fog treatment device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0197] The present application provides a vehicle, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the rearview mirror frost processing method in the above-mentioned embodiment one.

[0198] Reference below Figure 6 , which shows a schematic structural diagram of a vehicle suitable for implementing an embodiment of the present application. Figure 6 The vehicle shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0199] like Figure 6 As shown, the vehicle may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which may perform various appropriate actions and processes according to a program stored in a read-only memory 1002 or a program loaded from a storage device 1003 to a random access memory 1004. Various programs and data required for vehicle operation are also stored in the random access memory 1004. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are connected to each other via a bus 1005. An input / output interface 1006 is also connected to the bus. Generally, the following systems may be connected to the input / output interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the vehicle to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a vehicle with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0200] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0201] The vehicle provided by the present application adopts the rearview mirror frost and fog treatment method in the above embodiment, which can solve the technical problem of how to improve the accuracy of defrosting and defogging the vehicle's exterior rearview mirror. Compared with the prior art, the beneficial effects of the vehicle provided by the present application are the same as the beneficial effects of the rearview mirror frost and fog treatment method provided by the above embodiment, and other technical features in the vehicle are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0202] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0203] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0204] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the rearview mirror frost processing method in the above-mentioned embodiment.

[0205] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM: Erasable Programmable Read On ly Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read On ly Memory), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination thereof.

[0206] The computer-readable storage medium may be included in the vehicle, or may exist independently without being installed in the vehicle.

[0207] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the vehicle, the vehicle: obtains environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and the driving information of the target vehicle; obtains environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and the driving information of the target vehicle; inputs the environmental information and the driving information into a preset risk prediction model to obtain a frost and fog risk index of the surface of the rearview mirror, wherein the frost and fog risk index represents the risk of frosting and / or fogging; when the frost and fog risk index is greater than a preset threshold, the rearview mirror is defrosted and / or defogged.

[0208] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0209] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0210] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0211] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned rearview mirror frost and fog processing method, and can solve the technical problem of how to improve the accuracy of defrosting and defogging the vehicle's exterior rearview mirror. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the rearview mirror frost and fog processing method provided by the above-mentioned embodiment, and will not be repeated here.

[0212] An embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the rearview mirror frost processing method as described above.

[0213] The computer program product provided in this application can improve the accuracy of defrosting and defogging the vehicle's exterior rearview mirror. Compared with the prior art, the beneficial effects of the computer program product provided in the embodiment of this application are the same as the beneficial effects of the rearview mirror frost and fog processing method provided in the above embodiment, which will not be repeated here.

[0214] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent processing scope of the present application.

Claims

1. A method for treating frost on a rearview mirror, characterized in that: The rearview mirror frost and fog processing method comprises: Acquiring environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and driving information of the target vehicle; Inputting the environmental information and the driving information into a preset risk prediction model to obtain a frost and fog risk index of the rearview mirror surface, wherein the frost and fog risk index represents the risk of frost and / or fogging; When the frost and fog risk index is greater than a preset threshold, the rearview mirror is defrosted and / or defogged.

2. The method according to claim 1, characterized in that The step of obtaining environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and driving information of the target vehicle includes: Acquire sensor data from a sensor installed on an exterior rearview mirror of the vehicle, and determine environmental information of an environment in which the rearview mirror is located based on the sensor data, wherein the sensor data includes at least temperature, humidity and air pressure; The vehicle speed is determined, and the vehicle speed is used as the driving information of the vehicle.

3. The method according to claim 2, characterized in that The step of determining the environmental information of the environment in which the exterior rearview mirror is located based on the sensor data comprises: Calculating a dew point temperature of an environment in which the rearview mirror is located based on the temperature and humidity in the sensor data; The sensor data and the dew point temperature are used as environmental information of the environment in which the rearview mirror is located.

4. The method according to claim 2, characterized in that The step of obtaining environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and driving information of the target vehicle includes: For any data item in the sensor data and the driving information, determine whether the data item meets a data mutation condition, wherein the data mutation condition is that the difference between the current value and the historical value of the data item is greater than a preset mutation threshold, and the historical value is the value of the data item detected last time; When the data item does not satisfy the data mutation condition, acquiring the environment information and the driving information once every first preset period; In the case where the data item meets the data mutation condition, the environmental information and the driving information are acquired once at intervals of a second preset period, wherein the second preset period is shorter than the first preset period.

5. The method according to claim 2, characterized in that After the step of acquiring the environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and the driving information of the target vehicle, the method further includes: Determining whether the humidity in the environmental information reaches a preset high humidity threshold; When the humidity reaches the preset high humidity threshold, the air conditioner in the vehicle is controlled to operate in a dehumidification mode.

6. The method according to claim 1, characterized in that The risk prediction model is trained using sample environmental information and sample driving information as model input data, and using a sample frost and fog risk index that characterizes the actual frosting and / or fogging conditions of the sample rearview mirror as a model training label. The sample environmental information is environmental information of the environment in which the sample rearview mirror outside the sample vehicle is located, and the sample driving information is driving information of the sample vehicle.

7. The method according to claim 4, characterized in that The step of defrosting and / or defogging the rearview mirror comprises: Determining a frost and fog density gradient on the rearview mirror, wherein the frost and fog density gradient represents a degree of density variation of the frost layer and / or fog at different positions; Determining a temperature change rate and a humidity change rate based on historical environmental information and the environmental information, wherein the historical environmental information at least includes the environmental information acquired last time; Determine a difference between the dew point temperature in the environmental information and a preset dew point temperature, and use the difference as an environmental dew point deviation, wherein the preset dew point temperature is a dew point temperature threshold capable of preventing fogging and frosting of the rearview mirror; Calculating PID parameters based on one or more of the frost fog density gradient, the temperature change rate, the humidity change rate and the ambient dew point deviation; The power of the heating module on the rearview mirror is determined based on the PID parameters to defrost and / or defog the rearview mirror.

8. The method according to claim 7, characterized in that The step of determining the frost density gradient on the rearview mirror comprises: Acquiring image data obtained by photographing the rearview mirror; determining the thickness and area of ​​the frost layer and / or fog on the rearview mirror based on the image data; A frost density gradient on the rearview mirror is determined based on the thickness and the area.

9. The method according to claim 8, characterized in that The heating module includes a plurality of heating submodules, and the step of determining the power of the heating module on the rearview mirror based on the PID parameter to defrost and / or defog the rearview mirror includes: For any target submodule in each of the heating submodules, determining a heating area of ​​the target submodule on the rearview mirror, and determining a target thickness and a target area of ​​frost and / or fog on the heating area based on the thickness and the area; Determining a power weight of the target submodule based on the target thickness and the target area; The power of the target submodule is determined based on the PID parameter and the power weight to defrost and / or defog the heating area.

10. The method according to any one of claims 1 to 9, characterized in that: The method further comprises: monitoring the remaining charge of the vehicle; When the remaining power is lower than a preset power threshold, the power of the heating module on the rearview mirror is reduced and / or the dehumidification gear of the air conditioner in the vehicle is lowered.

11. A rearview mirror frost treatment device, characterized in that: The rearview mirror frost treatment device comprises: An acquisition module, used to acquire environmental information of the environment in which the exterior rearview mirror of the target vehicle is located and driving information of the target vehicle; A prediction module, used for inputting the environmental information and the driving information into a preset risk prediction model to obtain a frost and fog risk index of the surface of the rearview mirror, wherein the frost and fog risk index represents the risk of frost and / or fogging; The defrost and fog module is used to defrost and / or defog the rearview mirror when the frost and fog risk index is greater than a preset threshold.

12. A vehicle, characterized in that: The vehicle comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the rearview mirror frost processing method according to any one of claims 1 to 10.

13. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the rearview mirror frost processing method according to any one of claims 1 to 10 are implemented.

14. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the rearview mirror frost processing method according to any one of claims 1 to 10 are implemented.

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