Electronic rearview mirror heating method, chip, and electronic rearview mirror system

Abstract

The application provides an electronic rearview mirror heating method, a chip and an electronic rearview mirror system. The method comprises the following steps: acquiring visual perception data and environmental perception data of an electronic rearview mirror; inputting the visual perception data into a pre-trained recognition model to obtain weather conditions and / or a shielding state output by the recognition model; determining a freezing risk determination result of the electronic rearview mirror according to the environmental perception data, determining a partition heating strategy for an edge protection area and / or a center imaging area; and executing the partition heating strategy. The weather condition recognition and the shielding state perception are realized through a neural network model, and a differential partition heating strategy for the edge protection area and the center imaging area is further determined, which is beneficial to improving the intelligence of the electronic rearview mirror heating, and compared with using a rain and sunlight sensor to realize weather condition recognition, the cost is reduced.

Description

Technical Field

[0001] This application belongs to the field of electronic rearview mirror heating, specifically relating to an electronic rearview mirror heating method, chip, and electronic rearview mirror system. Background Technology

[0002] Many car models have electronic rearview mirrors with heating functions. In environments with low temperatures or high humidity, the lens glass surface of the camera is prone to frost and fog. Activating the heating function can eliminate the frost and fog on the lens glass surface of the electronic rearview mirror and restore its clarity.

[0003] However, the current heating solutions for electronic rearview mirrors often use constant power heating throughout the entire range. Regardless of whether there is fog or ice, or the ambient temperature, the heating is at full power throughout the entire process. This results in high power consumption, uneven heat generation, and easy damage to lens coatings, sensors, and PCB circuit boards, thus reducing the lifespan of the camera. Summary of the Invention

[0004] This application provides an electronic rearview mirror heating method, chip, and electronic rearview mirror system. It uses a neural network model to identify weather conditions and perceive occlusion status, and further determines a differentiated heating strategy for the edge protection zone and the center imaging zone. This improves the intelligence of the electronic rearview mirror heating and reduces costs compared to using rain and sunlight sensors to identify weather conditions.

[0005] In a first aspect, embodiments of this application provide a method for heating an electronic rearview mirror, including: The system acquires visual perception data and environmental perception data from an electronic rearview mirror, which includes an edge protection zone and a central imaging zone. The central imaging zone is an effective imaging area located at the center of the electronic rearview mirror, and the edge protection zone is an outer area surrounding the central imaging zone. The visual perception data is input into a pre-trained recognition model to obtain the weather conditions and / or occlusion status output by the recognition model. Based on the environmental perception data, the freezing risk assessment result of the electronic rearview mirror is determined; Based on the occlusion status and the freezing risk assessment result, a zoned heating strategy for the edge protection area and / or the central imaging area is determined; Execute the partitioned heating strategy.

[0006] In one possible example, inputting the visual perception data into a pre-trained recognition model to obtain the weather conditions and / or occlusion status output by the recognition model includes: The visual perception data is input into a pre-trained rain and snow recognition model to obtain the weather conditions output by the rain and snow recognition model. If the weather conditions indicate rain or snow, the visual perception data is input into a pre-trained rain and snow occlusion recognition model to obtain the rain and snow occlusion judgment result and image blur status output by the rain and snow occlusion recognition model.

[0007] In one possible example, determining the freezing risk assessment result of the electronic rearview mirror based on the environmental perception data includes: Based on the environmental sensing data, determine the ambient temperature and ambient humidity; Determine the dew point temperature based on the ambient temperature and the ambient humidity; If it is determined that the ambient temperature is greater than the dew point temperature, then the condensation risk assessment result is determined to be that there is no condensation risk. If it is determined that the ambient temperature is less than or equal to the dew point temperature and greater than or equal to a preset temperature threshold, then the condensation risk assessment result is determined to be that there is a risk of condensation. If the ambient temperature is determined to be lower than the preset temperature threshold, the freezing risk assessment result is determined to be that there is a risk of freezing.

[0008] In one possible example, determining the zonal heating strategy for the edge protection zone and / or the central imaging zone based on the occlusion status and the freezing risk assessment result includes: If the rain and snow cover determination result is that there is no rain and snow cover and the freezing risk determination result is that there is a risk of condensation or freezing, then the first heating strategy for the edge protection area is determined. If the rain and snow obstruction determination result is that there is rain and snow obstruction and the freezing risk determination result is that there is no condensation risk and no freezing risk, then a second heating strategy for the central imaging area is determined. If the rain and snow obstruction determination result indicates that there is rain and snow obstruction and the freezing risk determination result indicates that there is a risk of condensation or freezing, then a third heating strategy for the edge protection area and the central imaging area is determined.

[0009] In one possible example, determining a second heating strategy for the central imaging region includes: Obtain the image blur state of the electronic rearview mirror; Based on the image blur state, the PWM duty cycle signal for controlling the heating component corresponding to the central imaging area is determined.

[0010] In one possible example, determining the PWM duty cycle signal for controlling the heating component corresponding to the central imaging area based on the image blur state includes: Based on the image blur state, determine the image blur level; The heating power for heating the central imaging area is determined based on the heating power curve corresponding to the image blur level. The heating power is normalized according to the image blur level and converted into a PWM duty cycle signal to control the heating component corresponding to the central imaging area.

[0011] In one possible example, after executing the partitioned heating strategy, the method further includes: Continuously acquire visual perception data and environmental perception data from the electronic rearview mirror; The zone heating strategy is dynamically adjusted based on the visual perception data and the environmental perception data to restore the electronic rearview mirror to a clear state.

[0012] In a second aspect, embodiments of this application provide an electronic rearview mirror chip, including: a processor and a memory; and one or more programs, the one or more programs being stored in the memory and configured to be executed by the processor, the programs including instructions for some or all of the steps as described in the first aspect.

[0013] Thirdly, this application provides an electronic rearview mirror system, which includes an electronic rearview mirror body, an electronic rearview mirror chip disposed on the electronic rearview mirror body, a heating unit and a sensing system, wherein the electronic rearview mirror chip is connected to the heating unit and the sensing system respectively, and the electronic rearview mirror body includes an edge protection area and a central imaging area. The heating unit includes a first heating component and a second heating component. The electronic rearview mirror chip is used to control the first heating component to heat the edge protection area, and the electronic rearview mirror chip is also used to control the second heating component to heat the central imaging area.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium for storing a computer program that causes a computer to execute instructions for some or all of the steps described in the first aspect of embodiments of this application.

[0015] Fifthly, embodiments of this application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in the first aspect of embodiments of this application. The computer program product may be a software installation package.

[0016] As can be seen, in this embodiment, visual perception data and environmental perception data of the electronic rearview mirror are first acquired. Then, the visual perception data is input into a pre-trained recognition model to obtain the weather conditions and / or occlusion status output by the recognition model. Next, based on the environmental perception data, the freezing risk assessment result of the electronic rearview mirror is determined. Further, based on the occlusion status and freezing risk assessment result, a zoned heating strategy for the edge protection zone and / or the central imaging zone is determined. Finally, the zoned heating strategy is executed. Using a neural network model to achieve weather condition recognition and occlusion status perception, and further determining the differentiated zoned heating strategy for the edge protection zone and the central imaging zone, improves the intelligence of the electronic rearview mirror heating and reduces costs compared to using rain and sunlight sensors for weather condition recognition. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is an architectural diagram of an electronic rearview mirror system provided in an embodiment of this application; Figure 2 This is a cross-sectional view of an electronic rearview mirror provided in an embodiment of this application; Figure 3 This is a schematic diagram of an electronic rearview mirror provided in an embodiment of this application; Figure 4 This is a schematic flowchart of an electronic rearview mirror heating method provided in an embodiment of this application; Figure 5 This is a schematic diagram of a process for determining weather conditions and obstruction status provided in an embodiment of this application; Figure 6 This is a flowchart illustrating a method for determining a zoned heating strategy, as provided in an embodiment of this application. Figure 7 This is a schematic diagram of the structure of an electronic rearview mirror chip provided in an embodiment of this application. Detailed Implementation

[0019] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0020] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0021] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] In the embodiments of this application, "and / or" describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone; A and B exist simultaneously; B exists alone. Among them, A and B can be singular or plural.

[0023] In this embodiment, the symbol " / " can indicate that the preceding and following objects are in an "or" relationship. Alternatively, the symbol " / " can also represent a division sign, i.e., performing a division operation. For example, A / B can mean A divided by B.

[0024] In the embodiments of this application, "at least one item" or its similar expression refers to any combination of these items, including any combination of a single item or a plurality of items. "One or more" means one or more, while "multiple" means two or more. For example, "at least one item" of a, b, or c can represent the following seven cases: a, b, c; a and b; a and c; b and c; a, b, and c. Each of a, b, and c can be an element or a set containing one or more elements.

[0025] In the embodiments of this application, "equal to" can be used with "greater than" and is applicable to technical solutions used when "greater than" is used; it can also be used with "less than" and is applicable to technical solutions used when "less than" is used. When "equal to" is used with "greater than", it is not used with "less than"; when "equal to" is used with "less than", it is not used with "greater than".

[0026] Please see Figure 1 , Figure 1 This is an architectural diagram of an electronic rearview mirror system provided in an embodiment of this application. The electronic rearview mirror system 1 includes an electronic rearview mirror body 10 and an electronic rearview mirror chip 20, a heating unit 30 and a sensing system 40 disposed on the electronic rearview mirror body 10.

[0027] The sensing system 40 includes a camera module, a temperature sensor, a humidity sensor, and other sensors that can be equipped with the electronic rearview mirror, which are not limited here.

[0028] The electronic rearview mirror chip 20 is connected to the sensing system 40 and can acquire sensing data from the sensing system 40, specifically including visual perception data and environmental perception data. The visual perception data includes image data collected by the camera, and the environmental perception data includes ambient temperature data collected by the temperature sensor and ambient humidity data collected by the humidity sensor.

[0029] The electronic rearview mirror body 10 can be divided into zones, specifically an edge protection zone and a center imaging zone. Please refer to [link / reference needed]. Figure 2 and Figure 3 , Figure 2 This is a cross-sectional view of an electronic rearview mirror provided in an embodiment of this application. Figure 3 This is a schematic diagram of an electronic rearview mirror provided in an embodiment of this application. Figure 2 The image shows the edge protection zone and the central imaging zone. Figure 3 The edge protection zone, the central imaging zone, the first heating component, and the second heating component are shown.

[0030] The electronic rearview mirror chip 20 is connected to the heating unit 30. The electronic rearview mirror chip 20 can control the heating unit 30 to perform differentiated heating on different areas of the electronic rearview mirror. The heating unit 30 includes a first heating component located near the edge protection area and a second heating component located near the center imaging area. The first heating component is used to heat the edge protection area, and the second heating component is used to heat the center imaging area. The first heating component can be a heating film made of opaque or semi-transparent conductive material, such as metal mesh, to heat the edge protection area and prevent fogging and icing from spreading to the center imaging area. The second heating component can be a transparent heating layer, which is a transparent conductive film with high transmittance to visible and infrared light, ensuring that it does not interfere with optical imaging, and it can cover all or part of the effective light-transmitting surface of the center imaging area.

[0031] In one possible example, the electronic rearview mirror chip 20 first acquires visual perception data and environmental perception data of the electronic rearview mirror. Then, the electronic rearview mirror chip 20 inputs the visual perception data into a pre-trained recognition model to obtain the weather conditions and / or occlusion status output by the recognition model. Next, based on the environmental perception data, the electronic rearview mirror chip 20 determines the icing risk assessment result for the electronic rearview mirror. Further, based on the occlusion status and icing risk assessment result, the electronic rearview mirror chip 20 determines a zoned heating strategy for the edge protection zone and / or the central imaging zone. Finally, the electronic rearview mirror chip 20 executes the zoned heating strategy. Using a neural network model to achieve weather condition recognition and occlusion status perception, and further determining differentiated zoned heating strategies for the edge protection zone and the central imaging zone, improves the intelligence of the electronic rearview mirror heating and reduces costs compared to using rain and sunlight sensors for weather condition recognition.

[0032] Please see Figure 4 , Figure 4 This is a flowchart illustrating an electronic rearview mirror heating method provided in an embodiment of this application. The method includes: Step S401: Obtain visual perception data and environmental perception data of the electronic rearview mirror, wherein the electronic rearview mirror includes an edge protection zone and a central imaging zone.

[0033] The visual perception data includes image data collected by the camera module of the electronic rearview mirror, and the environmental perception data includes ambient temperature data collected by the temperature sensor on the electronic rearview mirror and humidity data collected by the humidity sensor.

[0034] The central imaging area is the effective imaging area located at the center of the electronic rearview mirror, while the edge protection area is the outer area surrounding the central imaging area.

[0035] Step S402: Input the visual perception data into the pre-trained recognition model to obtain the weather conditions and / or occlusion status output by the recognition model.

[0036] The occlusion status includes whether the electronic rearview mirror is obscured by rain or snow and whether the image is blurred.

[0037] Among them, a pre-trained recognition model can be used to identify weather conditions and / or occlusion status based on visual perception data.

[0038] Step S403: Determine the freezing risk assessment result of the electronic rearview mirror based on the environmental perception data.

[0039] Among them, the freezing risk assessment result indicates whether there is a risk of condensation or freezing.

[0040] Step S404: Based on the occlusion status and the freezing risk determination result, determine the partitioned heating strategy for the edge protection area and / or the central imaging area respectively.

[0041] When the occlusion status indicator shows rain or snow obstruction, it means that the camera image is unclear due to the obstruction. The central imaging area can be heated to eliminate the rain or snow obstruction.

[0042] If the freezing risk assessment result indicates that there is a risk of condensation or freezing, then water and ice removal are required. This can be achieved by heating the edge protection area.

[0043] Step S405: Execute the partitioned heating strategy.

[0044] The controllable heating unit can independently or simultaneously activate the first heating component and the second heating component according to the zoned heating strategy to heat the edge protection area and / or the central imaging area, so as to restore the lens to sharpness.

[0045] As can be seen, in this embodiment, visual perception data and environmental perception data of the electronic rearview mirror are first acquired. Then, the visual perception data is input into a pre-trained recognition model to obtain the weather conditions and / or occlusion status output by the recognition model. Next, based on the environmental perception data, the freezing risk assessment result of the electronic rearview mirror is determined. Further, based on the occlusion status and freezing risk assessment result, a zoned heating strategy for the edge protection zone and / or the central imaging zone is determined. Finally, the zoned heating strategy is executed. Using a neural network model to achieve weather condition recognition and occlusion status perception, and further determining the differentiated zoned heating strategy for the edge protection zone and the central imaging zone, improves the intelligence of the electronic rearview mirror heating and reduces costs compared to using rain and sunlight sensors for weather condition recognition.

[0046] Please see Figure 5 Regarding the input of the visual perception data into a pre-trained recognition model to obtain the weather conditions and / or occlusion status output by the recognition model, the above method may include the following steps: Step S501: Input the visual perception data into the pre-trained rain and snow recognition model to obtain the weather conditions output by the rain and snow recognition model.

[0047] The weather conditions may include whether it is raining or snowing, and may include the intensity of the snowfall, for example: the weather condition is raining, and it is heavy rain; the weather condition is snowing, and it is light snow.

[0048] In this process, a training set of rain and snow images can be collected in advance to train the neural network model, resulting in a well-trained rain and snow recognition model.

[0049] The rain and snow recognition model takes images captured by electronic rearview mirrors as input and outputs weather conditions.

[0050] Step S502: If the weather conditions indicate rain or snow, the visual perception data is input into the pre-trained rain and snow occlusion recognition model to obtain the rain and snow occlusion judgment result and image blur status output by the rain and snow occlusion recognition model.

[0051] In this process, a training set of rain and snow occlusion images can be collected in advance to train the neural network model, resulting in a trained rain and snow occlusion recognition model.

[0052] The rain and snow recognition model takes the image captured by the electronic rearview mirror as input and outputs the rain and snow occlusion judgment result and the image blur status.

[0053] In addition to rain or snow, it further identifies whether the rain or snow obstructs the rearview mirror and the blurry state of the captured image.

[0054] As can be seen, in this embodiment of the application, by analyzing visual perception data, the occlusion status of the electronic rearview mirror lens and the weather conditions are determined, which are then used to determine the heating decision, thus improving the intelligence of the electronic rearview mirror heating.

[0055] In one possible example, regarding the determination of the freezing risk assessment result of the electronic rearview mirror based on the environmental perception data, the above method may include the following steps: determining the ambient temperature and ambient humidity based on the environmental perception data; determining the dew point temperature based on the ambient temperature and the ambient humidity; determining that there is no freezing risk when the ambient temperature is determined to be greater than the dew point temperature; determining that there is a freezing risk when the ambient temperature is determined to be less than or equal to the dew point temperature and greater than or equal to a preset temperature threshold; and determining that there is an icing risk when the ambient temperature is determined to be less than the preset temperature threshold.

[0056] Among them, the ambient temperature T and the ambient humidity (relative humidity) RH can be determined separately.

[0057] Among them, dew point temperature The formula is as follows: .

[0058] in, , The preset temperature threshold can be set manually or by system default, and there is no restriction here. For example, the preset temperature threshold is 0℃.

[0059] As can be seen, in this example, determining the dew point temperature first, and then judging whether there is a risk of condensation or freezing based on the dew point temperature and the preset temperature threshold, helps to improve the accuracy of judging the risk of condensation and freezing.

[0060] Please see Figure 6 In determining the zoned heating strategy for the edge protection zone and / or the central imaging zone based on the occlusion state and the freezing risk assessment result, the above method may further include the following steps: Step S601: If the rain and snow cover determination result is that there is no rain and snow cover and the freezing risk determination result is that there is a risk of condensation or a risk of freezing, then determine the first heating strategy for the edge protection area. Step S602: If the rain and snow obstruction determination result is that there is rain and snow obstruction and the freezing risk determination result is that there is no condensation risk and no freezing risk, then determine the second heating strategy for the central imaging area. Step S603: If the rain and snow obstruction determination result is that there is rain and snow obstruction and the freezing risk determination result is that there is condensation risk or freezing risk, then a third heating strategy for the edge protection area and the central imaging area is determined.

[0061] When the occlusion status indicates rain or snow obstruction and the condensation risk assessment result is that there is no risk of condensation or icing, it means that the camera image is unclear due to occlusion. The central imaging area can be heated to eliminate the rain or snow obstruction.

[0062] The first heating strategy for the edge protection zone includes determining the heating power based on the rain and snow conditions. Specifically, different heating powers are used for rain and snow, and different heating powers are used based on the amount of rain and snow; a higher heating power is used for snow than for rain, and the heavier the rain and snow, the higher the heating power is used. The heating power can be converted into a PWM signal to control the heating components, thereby controlling the heating.

[0063] If the freezing risk assessment result indicates that there is a risk of condensation or freezing and the shading status indicates that there is no rain or snow shading, then only water and ice removal are required. Water and ice removal can be achieved by heating the edge protection area.

[0064] When the occlusion status indicates rain or snow and the freezing risk assessment result is that there is a risk of condensation or freezing, it means that the camera image is unclear due to occlusion and needs to be de-watered and de-iced. The central imaging area and the edge protection area can be heated at the same time.

[0065] As can be seen, in this example, determining the partitioned heating strategy for the edge protection area and / or the central imaging area based on the occlusion status and freezing risk assessment results is beneficial to improving the intelligence of the electronic rearview mirror heating control.

[0066] In one possible example, the method may further include the following steps in determining the second heating strategy for the central imaging area: acquiring the image blur state of the electronic rearview mirror; and determining the PWM duty cycle signal for controlling the heating component corresponding to the central imaging area based on the image blur state.

[0067] The image blur state can be specifically classified into three levels: very blurry, moderately blurry, and clear. Alternatively, it can be further divided into other image blur levels, with higher levels indicating greater blur and lower levels indicating greater clarity. Other classifications are also possible, and no specific limitation is made here.

[0068] Among them, the image blurring state is positively correlated with the heating power; the blurrier the image, the greater the heating power, and the clearer the image, the smaller the heating power.

[0069] For example, the heating power corresponding to a very fuzzy condition is greater than the heating power corresponding to a generally fuzzy condition.

[0070] Different PWM duty cycle signals are used to control the heating component to heat the central imaging area differently.

[0071] As can be seen, in this example, considering different heating powers for the central imaging area based on the image blur state is beneficial for saving vehicle power and improving the intelligence of electronic rearview mirror heating.

[0072] In one possible example, regarding the determination of the PWM duty cycle signal for controlling the heating component corresponding to the central imaging area based on the image blur state, the above method may include the following steps: determining the image blur level based on the image blur state; determining the heating power for heating the central imaging area based on the heating power curve corresponding to the image blur level; and normalizing the heating power according to the image blur level to convert it into a PWM duty cycle signal for controlling the heating component corresponding to the central imaging area.

[0073] The heating power curve corresponding to each image blur level can be preset.

[0074] First, the heating power for heating the central imaging area can be determined, and then the heating power can be normalized and converted into a PWM duty cycle signal to control the heating component corresponding to the central imaging area.

[0075] As can be seen, in this example, the image blur level is determined according to the image blur state, and different heating powers are applied to the central imaging area based on the image blur level. Furthermore, the heating power is converted into a PWM duty cycle signal to control the heating component, which helps to save vehicle power and improve the intelligence of the electronic rearview mirror heating.

[0076] In one possible example, after the execution of the zone heating strategy, the above method may further include the following steps: continuously acquiring visual perception data and environmental perception data of the electronic rearview mirror; dynamically adjusting the zone heating strategy according to the visual perception data and the environmental perception data so that the electronic rearview mirror returns to a clear state.

[0077] After implementing the zoned heating strategy, the system can acquire real-time visual perception data and environmental perception data of the electronic rearview mirror, analyze the obstruction status and freezing risk of the electronic rearview mirror, and dynamically adjust the zoned heating strategy accordingly to restore the electronic rearview mirror to a clear state.

[0078] As can be seen in this example, the zone heating strategy can be dynamically adjusted to restore the electronic rearview mirror to a clear state, which helps to improve the intelligence of the electronic rearview mirror heating.

[0079] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of an electronic rearview mirror chip provided in an embodiment of this application, as shown below. Figure 7 As shown, the electronic rearview mirror chip 20 includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs are configured to be executed by the processor according to the following instructions: The system acquires visual perception data and environmental perception data from an electronic rearview mirror, which includes an edge protection zone and a central imaging zone. The central imaging zone is an effective imaging area located at the center of the electronic rearview mirror, and the edge protection zone is an outer area surrounding the central imaging zone. The visual perception data is input into a pre-trained recognition model to obtain the weather conditions and / or occlusion status output by the recognition model. Based on the environmental perception data, the freezing risk assessment result of the electronic rearview mirror is determined; Based on the occlusion status and the freezing risk assessment result, a zoned heating strategy for the edge protection area and / or the central imaging area is determined; Execute the partitioned heating strategy.

[0080] As can be seen from this embodiment, the electronic rearview mirror chip 20 first acquires visual perception data and environmental perception data of the electronic rearview mirror. Then, it inputs the visual perception data into a pre-trained recognition model to obtain the weather conditions and / or occlusion status output by the recognition model. Next, based on the environmental perception data, it determines the freezing risk assessment result of the electronic rearview mirror. Further, based on the occlusion status and freezing risk assessment result, it determines a zoned heating strategy for the edge protection zone and / or the central imaging zone. Finally, it executes the zoned heating strategy. Using a neural network model to achieve weather condition recognition and occlusion status perception, and further determining the differentiated zoned heating strategy for the edge protection zone and the central imaging zone, improves the intelligence of the electronic rearview mirror heating and reduces costs compared to using rain and sunlight sensors for weather condition recognition.

[0081] In one possible example, regarding the input of the visual perception data into a pre-trained recognition model to obtain the weather conditions and / or occlusion status output by the recognition model, the above procedure includes instructions for performing the following steps: The visual perception data is input into a pre-trained rain and snow recognition model to obtain the weather conditions output by the rain and snow recognition model. If the weather conditions indicate rain or snow, the visual perception data is input into a pre-trained rain and snow occlusion recognition model to obtain the rain and snow occlusion judgment result and image blur status output by the rain and snow occlusion recognition model.

[0082] In one possible example, regarding the determination of the freezing risk assessment result of the electronic rearview mirror based on the environmental perception data, the above procedure includes instructions for performing the following steps: Based on the environmental sensing data, determine the ambient temperature and ambient humidity; Determine the dew point temperature based on the ambient temperature and the ambient humidity; If it is determined that the ambient temperature is greater than the dew point temperature, then the condensation risk assessment result is determined to be that there is no condensation risk. If it is determined that the ambient temperature is less than or equal to the dew point temperature and greater than or equal to a preset temperature threshold, then the condensation risk assessment result is determined to be that there is a risk of condensation. If the ambient temperature is determined to be lower than the preset temperature threshold, the freezing risk assessment result is determined to be that there is a risk of freezing.

[0083] In one possible example, regarding the determination of a zoned heating strategy for the edge protection zone and / or the central imaging zone based on the occlusion status and the freezing risk assessment result, the above procedure includes instructions for performing the following steps: If the rain and snow cover determination result is that there is no rain and snow cover and the freezing risk determination result is that there is a risk of condensation or freezing, then the first heating strategy for the edge protection area is determined. If the rain and snow obstruction determination result is that there is rain and snow obstruction and the freezing risk determination result is that there is no condensation risk and no freezing risk, then a second heating strategy for the central imaging area is determined. If the rain and snow obstruction determination result indicates that there is rain and snow obstruction and the freezing risk determination result indicates that there is a risk of condensation or freezing, then a third heating strategy for the edge protection area and the central imaging area is determined.

[0084] In one possible example, regarding the determination of the second heating strategy for the central imaging region, the above procedure further includes instructions for performing the following steps: Obtain the image blur state of the electronic rearview mirror; Based on the image blur state, the PWM duty cycle signal for controlling the heating component corresponding to the central imaging area is determined.

[0085] In one possible example, regarding the determination of the PWM duty cycle signal for controlling the heating component corresponding to the central imaging area based on the image blur state, the above procedure further includes instructions for performing the following steps: Based on the image blur state, determine the image blur level; The heating power for heating the central imaging area is determined based on the heating power curve corresponding to the image blur level. The heating power is normalized according to the image blur level and converted into a PWM duty cycle signal to control the heating component corresponding to the central imaging area.

[0086] In one possible example, after the execution of the partitioned heating strategy, the above procedure further includes instructions for performing the following steps: Continuously acquire visual perception data and environmental perception data from the electronic rearview mirror; The zone heating strategy is dynamically adjusted based on the visual perception data and the environmental perception data to restore the electronic rearview mirror to a clear state.

[0087] The above mainly describes the solution of the embodiments of this application from the perspective of the method execution process. It is understood that, in order to achieve the above functions, the electronic rearview mirror chip includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments provided herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0088] This application embodiment can divide the electronic rearview mirror chip into functional units according to the above method example. For example, each function can be divided into a separate functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0089] It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here.

[0090] The electronic rearview mirror chip provided in this embodiment is used to perform the above-described electronic rearview mirror heating method, and thus can achieve the same effect as the above-described implementation method.

[0091] When using an integrated unit, the electronic rearview mirror chip may include a processing module, a storage module, and a communication module. The processing module can be used to control and manage the operation of the electronic rearview mirror chip; for example, it can support the electronic rearview mirror chip in executing the steps performed by the aforementioned functional units. The storage module can support the electronic rearview mirror chip in storing program code and data. The communication module can support communication between the electronic rearview mirror chip and other devices.

[0092] The processing module can be a processor or a controller. It can implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module can be a memory. The communication module can specifically be a radio frequency circuit, a Bluetooth chip, a Wi-Fi chip, or other devices that interact with other chips.

[0093] This application also provides a computer storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the methods described in the above method embodiments.

[0094] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer includes a control platform.

[0095] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0096] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0097] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0098] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0099] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0100] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0101] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: a flash drive, a read-only memory, a random access memory, a magnetic disk, or an optical disk, etc.

[0102] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for heating an electronic rearview mirror, characterized in that, include: The system acquires visual perception data and environmental perception data from an electronic rearview mirror, which includes an edge protection zone and a central imaging zone. The central imaging zone is an effective imaging area located at the center of the electronic rearview mirror, and the edge protection zone is an outer area surrounding the central imaging zone. The visual perception data is input into a pre-trained rain and snow recognition model to obtain the weather conditions output by the rain and snow recognition model. If the weather conditions indicate rain or snow, the visual perception data is input into a pre-trained rain and snow occlusion recognition model to obtain the occlusion status, which includes the rain and snow occlusion determination result and the image blur status. Based on the environmental perception data, the freezing risk assessment result of the electronic rearview mirror is determined; Based on the occlusion status and the freezing risk assessment result, a zoned heating strategy for the edge protection area and / or the central imaging area is determined, wherein the freezing risk assessment result indicates whether there is a risk of condensation or a risk of freezing. Execute the partitioned heating strategy.

2. The method according to claim 1, characterized in that, The step of determining the freezing risk assessment result of the electronic rearview mirror based on the environmental perception data includes: Based on the environmental sensing data, determine the ambient temperature and ambient humidity; Determine the dew point temperature based on the ambient temperature and the ambient humidity; If it is determined that the ambient temperature is greater than the dew point temperature, then the condensation risk assessment result is determined to be that there is no condensation risk. If it is determined that the ambient temperature is less than or equal to the dew point temperature and greater than or equal to a preset temperature threshold, then the condensation risk assessment result is determined to be that there is a risk of condensation. If the ambient temperature is determined to be lower than the preset temperature threshold, the freezing risk assessment result is determined to be that there is a risk of freezing.

3. The method according to claim 1, characterized in that, The step of determining a zoned heating strategy for the edge protection zone and / or the central imaging zone based on the occlusion status and the freezing risk assessment result includes: If the rain and snow cover determination result is that there is no rain and snow cover and the freezing risk determination result is that there is a risk of condensation or freezing, then the first heating strategy for the edge protection area is determined. If the rain and snow obstruction determination result is that there is rain and snow obstruction and the freezing risk determination result is that there is no condensation risk and no freezing risk, then a second heating strategy for the central imaging area is determined. If the rain and snow obstruction determination result indicates that there is rain and snow obstruction and the freezing risk determination result indicates that there is condensation risk or freezing risk, then a third heating strategy for the edge protection area and the central imaging area is determined.

4. The method according to claim 3, characterized in that, The determination of the second heating strategy for the central imaging region includes: Obtain the image blur state of the electronic rearview mirror; Based on the image blur state, the PWM duty cycle signal for controlling the heating component corresponding to the central imaging area is determined.

5. The method according to claim 4, characterized in that, Based on the image blur state, determine the PWM duty cycle signal for controlling the heating component corresponding to the central imaging area, including: Based on the image blur state, determine the image blur level; The heating power for heating the central imaging area is determined based on the heating power curve corresponding to the image blur level. The heating power is normalized according to the image blur level and converted into a PWM duty cycle signal to control the heating component corresponding to the central imaging area.

6. The method according to claim 1, characterized in that, After executing the partitioned heating strategy, the method further includes: Continuously acquire visual perception data and environmental perception data from the electronic rearview mirror; The zone heating strategy is dynamically adjusted based on the visual perception data and the environmental perception data to restore the electronic rearview mirror to a clear state.

7. An electronic rearview mirror chip, characterized in that, It includes a processor and a memory, the memory being used to store one or more programs and configured to be executed by the processor, the programs including instructions for performing the steps of the method as described in any one of claims 1-6.

8. An electronic rearview mirror system, characterized in that, The electronic rearview mirror system includes an electronic rearview mirror body, an electronic rearview mirror chip as described in claim 7, a heating unit, and a sensing system disposed on the electronic rearview mirror body, wherein the electronic rearview mirror chip is connected to the heating unit and the sensing system respectively, and the electronic rearview mirror body includes an edge protection area and a center imaging area. The heating unit includes a first heating component and a second heating component. The electronic rearview mirror chip is used to control the first heating component to heat the edge protection area, and the electronic rearview mirror chip is also used to control the second heating component to heat the central imaging area.

9. A computer-readable storage medium, characterized in that, A computer program for storing electronic data interchange is provided, wherein the computer program causes a computer to perform the method as described in any one of claims 1-6.

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