A vehicle window control method, device and vehicle

Abstract

The application discloses a vehicle window control method and device and a vehicle. The method comprises the following steps: acquiring environment data of a vehicle driving area, wherein the environment data comprises at least one of real-time environment data collected by the vehicle and cloud environment data obtained from a cloud server; when it is determined that the vehicle driving area has water accumulation according to the environment data, acquiring window-up judging data; and when it is determined that the window-up judging data meets a preset window-up condition, performing window-up control on the vehicle window. The application realizes automatic window control in a water accumulation environment through the detection results of road water accumulation and environment data, thereby reducing manual operation of a user and improving the user's vehicle experience.

Description

Technical Field

[0001] This invention belongs to the field of automotive technology and relates to a method, device and vehicle for controlling vehicle windows. Background Technology

[0002] In recent years, due to heavy rainfall or poor drainage in urban drainage systems, large amounts of water have frequently accumulated in low-lying areas such as urban tunnels and underpasses.

[0003] Because the window control buttons are far from the steering wheel, and when encountering water on the road, the driver may need to perform multiple operations such as slowing down, changing driving mode, and adjusting the air conditioning. This may not only prevent the driver from raising the window in time and getting splashed with water, but may also increase the risk of driving due to the complicated manual operation.

[0004] Therefore, it is necessary to provide improved technical solutions to overcome the above-mentioned technical problems existing in the prior art. Summary of the Invention

[0005] The purpose of this application is to provide a method, device and vehicle for controlling vehicle windows, which realizes automated window control in waterlogged environments by detecting road surface water and environmental data, thereby reducing manual operation by the user and improving the user's driving experience.

[0006] To achieve the above objectives:

[0007] In a first aspect, the present invention provides a method for controlling vehicle windows, comprising:

[0008] The vehicle acquires environmental data of the driving area, the environmental data including at least one of real-time environmental data collected by the vehicle and cloud environmental data acquired from a cloud server.

[0009] When the environmental data determines that there is water accumulation in the vehicle's driving area, window lifting judgment data is obtained.

[0010] When the window lifting judgment data is determined to meet the preset window lifting conditions, the vehicle window is controlled to lift.

[0011] In one embodiment, the real-time environmental data includes at least one of real-time radar data, real-time image data, and real-time acoustic data, and the cloud-based environmental data includes cloud-based weather data.

[0012] In one embodiment, determining the presence of water accumulation in the vehicle's driving area based on the environmental data includes at least one of the following:

[0013] In response to the presence of echoes with no echo or regular changes in the real-time radar data, it is determined that there is water accumulation in the area where the vehicle is traveling;

[0014] In response to the presence of a preset type of texture feature in the real-time image data, it is determined that there is water accumulation in the vehicle's driving area;

[0015] In response to the presence of a preset type of voiceprint feature in the real-time acoustic data, it is determined that there is water accumulation in the vehicle's driving area;

[0016] In response to determining, through the cloud-based weather data, that there is rain or snow in the area where the vehicle is traveling, and that there is standing water in the area where the vehicle is traveling.

[0017] In one embodiment, the window lifting determination data includes at least one of the following: the vehicle's first speed, precipitation signal data, oncoming traffic prediction data, the tilt angle of the road segment in the vehicle's driving area, the water depth, and the road segment type.

[0018] In one embodiment, determining that the window raising judgment data meets the preset window raising conditions includes at least one of the following:

[0019] In response to the precipitation amount in the precipitation signal data being greater than a preset precipitation threshold, it is determined that the preset windowing condition is met;

[0020] In response to the oncoming traffic prediction data meeting the preset oncoming traffic splash conditions, it is determined that the preset window raising conditions are met;

[0021] In response to the water depth being higher than the water depth threshold corresponding to the current tilt angle, it is determined that the preset window raising condition is met;

[0022] In response to the first vehicle speed being greater than the first vehicle speed threshold corresponding to the current road segment type, it is determined that the preset window raising condition is met.

[0023] In one embodiment, the oncoming vehicle prediction data includes the oncoming vehicle prediction area, the water accumulation area, the second speed of the oncoming vehicles, and the vehicle type;

[0024] The vehicle meeting prediction data meets the preset vehicle meeting splash conditions, including:

[0025] In response to the spatial overlap between the predicted oncoming traffic area and the water accumulation area, and the second vehicle speed being greater than the second vehicle speed threshold corresponding to the vehicle model, it is determined that the preset oncoming traffic splashing condition is met.

[0026] In one embodiment, after obtaining the window-raising judgment data when it is determined from the environmental data that there is water accumulation in the vehicle's driving area, the method further includes:

[0027] Obtain weather signals sent to the cloud server by all identifiable vehicles within a preset area;

[0028] If the proportion of vehicles sending rain / snow weather signals to the total number of identifiable vehicles is greater than a preset ratio, and the precipitation in the precipitation signal data is less than a preset precipitation threshold, then the preset window-raising condition is determined not to be met.

[0029] In one embodiment, after controlling the window of the vehicle to rise, the method further includes:

[0030] When the window raising judgment data does not meet the preset window raising conditions and the duration exceeds the preset duration, the vehicle window is lowered.

[0031] In a second aspect, the present invention provides a vehicle window control device, comprising:

[0032] An environmental data acquisition module is used to acquire environmental data of the vehicle's driving area. The environmental data includes at least one of real-time environmental data collected by the vehicle and cloud environmental data acquired from a cloud server.

[0033] The judgment data acquisition module is used to acquire window lifting judgment data when it is determined from the environmental data that there is water accumulation in the vehicle's driving area.

[0034] The window raising control module is used to control the window of the vehicle to rise when the window raising judgment data meets the preset window raising conditions.

[0035] In one embodiment, the data acquisition module specifically includes at least one of the following:

[0036] In response to the presence of echoes with no echo or regular changes in the real-time radar data, it is determined that there is water accumulation in the area where the vehicle is traveling;

[0037] In response to the presence of a preset type of texture feature in the real-time image data, it is determined that there is water accumulation in the vehicle's driving area;

[0038] In response to the presence of a preset type of voiceprint feature in the real-time acoustic data, it is determined that there is water accumulation in the vehicle's driving area;

[0039] In response to determining, through the cloud-based weather data, that there is rain or snow in the area where the vehicle is traveling, and that there is standing water in the area where the vehicle is traveling.

[0040] In one embodiment, the window raising control module specifically includes at least one of the following:

[0041] In response to the precipitation amount in the precipitation signal data being greater than a preset precipitation threshold, it is determined that the preset windowing condition is met;

[0042] In response to the oncoming traffic prediction data meeting the preset oncoming traffic splash conditions, it is determined that the preset window raising conditions are met;

[0043] In response to the water depth being higher than the water depth threshold corresponding to the current tilt angle, it is determined that the preset window raising condition is met;

[0044] In response to the first vehicle speed being greater than the first vehicle speed threshold corresponding to the current road segment type, it is determined that the preset window raising condition is met.

[0045] Thirdly, vehicles, including window control devices as described in the second aspect.

[0046] This application provides a method, device, and vehicle for controlling vehicle windows, comprising: acquiring environmental data of the vehicle's driving area, wherein the environmental data includes at least one of real-time environmental data collected by the vehicle and cloud-based environmental data acquired from a cloud server; when it is determined from the environmental data that there is standing water in the vehicle's driving area, acquiring window-raising judgment data; and when it is determined that the window-raising judgment data meets preset window-raising conditions, controlling the vehicle's windows to raise. This invention achieves automated window control in waterlogged environments by detecting road surface water and environmental data, thereby reducing manual operation by the user and improving the user's driving experience. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a flowchart illustrating the window control method provided in an embodiment of the present invention.

[0049] Figure 2 This is a schematic diagram of the structure of the window control device provided in an embodiment of the present invention;

[0050] Figure 3 This is a schematic diagram illustrating the working process of the window control device provided in an embodiment of the present invention. Detailed Implementation

[0051] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of systems and methods consistent with some aspects of this application as detailed in the appended claims.

[0052] It should be noted that step designations such as S1 and S2 are used in this document for the purpose of more clearly and concisely describing the corresponding content, and do not constitute a substantial limitation on the order. In specific implementation, those skilled in the art may execute S2 first and then S1, etc., but these should all be within the protection scope of this application.

[0053] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0054] like Figure 1 As shown in the figure, this application provides a method for controlling vehicle windows, including:

[0055] Step S101: Obtain environmental data of the vehicle's driving area. The environmental data includes at least one of real-time environmental data collected by the vehicle and cloud environmental data obtained from a cloud server.

[0056] In one embodiment, the real-time environmental data further includes at least one of real-time radar data, real-time image data, and real-time acoustic data, and the cloud-based environmental data includes cloud-based weather data.

[0057] It is understandable that when a vehicle is in motion, it will automatically detect the water accumulation on the road surface and combine the vehicle's cloud-based weather data with real-time data perceived by the vehicle's hardware sensors to make a comprehensive data assessment of whether there is water accumulation on the road surface.

[0058] Furthermore, the vehicle acquires real-time radar data through onboard LiDAR, real-time image data through onboard camera, real-time sound wave data through onboard microphone, and cloud weather data of the vehicle's driving area or the area it is about to drive in through cloud server and real-time GPS positioning.

[0059] Step S102: When it is determined from environmental data that there is water accumulation in the vehicle's driving area, obtain the window lifting judgment data.

[0060] In one embodiment, determining the presence of water accumulation in the vehicle's driving area based on environmental data includes at least one of the following:

[0061] The presence of water accumulation in the vehicle's driving area is determined by responding to the presence of echo-less or regularly changing echoes in real-time radar data; the presence of water accumulation in the vehicle's driving area is determined by responding to the presence of preset type texture features in real-time image data; the presence of water accumulation in the vehicle's driving area is determined by responding to the presence of preset type voiceprint features in real-time acoustic data; and the presence of water accumulation in the vehicle's driving area is determined by responding to the presence of rain or snow in the vehicle's driving area based on cloud-based weather data.

[0062] It's understandable that when there are no ripples in a waterlogged area, the water will reflect the incident light directly in the opposite direction of the echo, preventing the vehicle-mounted LiDAR from acquiring the laser point cloud signal at the receiving end. When there are ripples in the water, the water surface ripples have a certain degree of order, and the echoes hitting the water will exhibit certain characteristic regular changes. Furthermore, these regular changes differ from the original point cloud angular resolution. Therefore, during the vehicle-mounted LiDAR's road surface scanning process, if no echo or a regular change in the standard point cloud spacing is detected within the range of two adjacent lanes centered on the vehicle's own lane, then a waterlogged area is determined to exist on the road surface.

[0063] Furthermore, when there is standing water on the road surface, the texture features of the road surface image will be significantly different from the surrounding asphalt and road embankments. Therefore, the road surface area can be identified through image noise reduction and target recognition. When data with preset texture features is identified, it is determined that there is a standing water area on the road surface.

[0064] Furthermore, when a vehicle drives through a flooded area, the splashes it creates generate sound waves, which can be captured by the vehicle's external microphones. Additionally, microphone arrays positioned at different locations on the vehicle can identify sounds originating from different directions, and the distance between the sound source and the vehicle can be determined using the Doppler effect.

[0065] In one embodiment, the window-raising determination data includes at least one of the following: the vehicle's first speed, precipitation signal data, oncoming traffic prediction data, the tilt angle of the road segment in the vehicle's driving area, the water depth, and the road segment type.

[0066] It is understandable that the vehicle obtains its current speed through the speed sensor, precipitation signal data through the rain sensor and the onboard camera, and onboard camera data including the oncoming traffic prediction area, the water accumulation area, the second speed of the oncoming vehicles and the vehicle type, as well as the water depth and road type of the current road section.

[0067] Step S103: When the window lifting judgment data meets the preset window lifting conditions, the vehicle window is lifted.

[0068] In one embodiment, determining that the window raising judgment data meets preset window raising conditions includes at least one of the following:

[0069] The preset window-raising condition is determined to be met if the precipitation in the precipitation signal data is greater than the preset precipitation threshold; if the oncoming traffic prediction data meets the preset oncoming traffic splash condition; if the water depth is higher than the water depth threshold corresponding to the current tilt angle; and if the first vehicle speed is greater than the first vehicle speed threshold corresponding to the current road segment type.

[0070] It is understandable that the vehicle uses onboard solar and rain sensors and cameras to collect real-time data on precipitation and snowfall in the environment, which serves as the basis for judging the rain and snow conditions in the area where the vehicle is traveling. At the same time, the vehicle sets a threshold for the precipitation signal data. When the precipitation in the precipitation signal data exceeds the preset precipitation threshold, it is determined that the preset window-opening conditions are met.

[0071] Furthermore, if the rainfall represented by the precipitation signal data is within a certain range and the seat occupancy signal on the window side is valid, the window will be raised to a fixed position; if the seat occupancy signal on the window side is invalid, the window will be completely closed; if the rainfall represented by the precipitation signal data is above a certain range, the window will be completely closed; if a user is detected to have intervened in the window control a second time, the window control will be performed according to the user's control requirements.

[0072] In one embodiment, the oncoming vehicle prediction data includes the oncoming vehicle prediction area, the water accumulation area, the second speed of the oncoming vehicles, and the vehicle type; the oncoming vehicle prediction data satisfies preset oncoming vehicle splash conditions, including:

[0073] In response to the spatial overlap between the oncoming traffic prediction area and the water accumulation area, and the second vehicle speed being greater than the second vehicle speed threshold corresponding to the vehicle model, it is determined that the preset oncoming traffic splashing condition is met.

[0074] It's understandable that when a vehicle detects other vehicles traveling within a certain range, it predicts the area where the two vehicles will meet and converts this area into a distance value from the vehicle's forward direction. Simultaneously, it compares the waterlogged area with the area where the two vehicles will meet. If there is an overlap, it means that both vehicles will pass through the waterlogged area together, potentially splashing water into the vehicle's interior.

[0075] Furthermore, because large and small vehicles have different heights, the height of the water splashes they generate at the same speed differs. Therefore, during a meeting of two vehicles, the vehicle type is determined, and the decision to raise the window is comprehensively considered based on the different water splash heights generated by different vehicle types. For example, using the vehicle's onboard camera, at a specific distance from the oncoming vehicle, the vehicle type is determined by identifying the number and height of the oncoming vehicle's wheels.

[0076] Furthermore, based on the differences in the height of the water deflector lines on the windows of different vehicle models, the vehicle speeds of different models when passing through water are calibrated: for example, sedans have a lower body height, and when meeting oncoming vehicles in a waterlogged area, the risk of water splashing into the car is greater. Therefore, by establishing a correspondence between different vehicle models and vehicle speeds, when it is determined that the oncoming vehicle's speed exceeds the current vehicle model's speed threshold, a preset oncoming splash condition is met.

[0077] It is understandable that when there is standing water in the area where a vehicle is traveling, the water depth is measured using ultrasound, and the vehicle's inertial navigation system measures the road's tilt angle. The pre-set water depth threshold will vary depending on the direction and magnitude of the tilt angle. Specifically, since the road's tilt angle is a variable and continuous quantity, there should be a one-to-one correspondence with the water depth. That is, when the tilt angle is in the same direction as the driving direction, the larger the tilt angle, the lower the water depth threshold above the ground; conversely, when the tilt angle is in the opposite direction of the driving direction, the larger the tilt angle, the higher the water depth threshold above the ground.

[0078] Furthermore, the vehicle monitors road information and its current speed in real time, and sets different speed thresholds based on the different road sections it is traveling on. For example, when the vehicle is traveling on an elevated road or highway and the speed is higher than 80 kph, the preset window-opening conditions are met; when the vehicle is traveling on an urban road and the speed is higher than a certain threshold of 40 kph, the preset window-opening conditions are met.

[0079] In one embodiment, after obtaining window-raising judgment data after determining that there is water accumulation in the vehicle's driving area through environmental data, the method further includes:

[0080] Obtain weather signals sent to the cloud server by all identifiable vehicles within the preset area; if the proportion of vehicles sending rain / snow weather signals to the total number of identifiable vehicles is greater than a preset ratio, and the precipitation in the precipitation signal data is less than a preset precipitation threshold, then it is determined that the preset window opening conditions are not met.

[0081] It is understandable that when a vehicle determines that there is a rain or snow forecast in its driving area based on cloud-based weather data and GPS positioning data, it will continuously monitor the signal from the onboard rain sensor, simultaneously acquire information from other identifiable vehicles within a preset range (vehicles of the same brand as the vehicle in this application or vehicles with shared information channels), and send a message to the cloud server indicating that rain or snow is expected in the vehicle's driving area. If the proportion of vehicles sending rain or snow weather signals to the number of identifiable vehicles is greater than a preset ratio, then the preset window-raising condition is determined to be met.

[0082] Preferably, when the judgment result based on the weather signal from the cloud server is inconsistent with the judgment result based on precipitation signal data provided in the aforementioned embodiment, the preset window-raising conditions are determined according to the judgment result based on the precipitation signal data of the vehicle.

[0083] In one embodiment, after controlling the vehicle's windows to rise, the method further includes:

[0084] When the window raising judgment data does not meet the preset window raising conditions and the duration exceeds the preset time, the vehicle window will be lowered.

[0085] It is understandable that when the vehicle is in intelligent driving mode and the window raising step described in the aforementioned embodiment has been activated, the vehicle will inform the driver via voice or text that the window raising operation has been automatically completed and remind the driver to pay attention to the driving environment; if the vehicle does not meet the conditions for intelligent driving, the vehicle will remind the driver to close the window as soon as possible.

[0086] Using the above methods, based on multi-dimensional water accumulation detection methods and window lifting determination methods, the detection results of road water accumulation and environmental data can be obtained, and different controls can be applied to the windows according to the detection results to realize automated window control in water accumulation environments, thereby reducing manual operation by users and improving the user's driving experience.

[0087] Based on the same inventive concept as the foregoing embodiments, this application provides a vehicle window control device. (See also...) Figure 2 This application provides a vehicle window control device, which can be implemented using software and / or hardware. The device includes:

[0088] The environmental data acquisition module 201 is used to acquire environmental data of the vehicle's driving area. The environmental data includes at least one of real-time environmental data collected by the vehicle and cloud-based environmental data acquired from a cloud server.

[0089] The judgment data acquisition module 202 is used to acquire window lifting judgment data when it is determined from environmental data that there is water accumulation in the vehicle driving area.

[0090] The window lifting control module 203 is used to control the vehicle windows to lift when the window lifting judgment data meets the preset window lifting conditions.

[0091] In one embodiment, the data acquisition module 202 specifically includes at least one of the following:

[0092] The presence of water accumulation in the vehicle's driving area is determined by responding to the presence of echo-less or regularly changing echoes in real-time radar data; the presence of water accumulation in the vehicle's driving area is determined by responding to the presence of preset type texture features in real-time image data; the presence of water accumulation in the vehicle's driving area is determined by responding to the presence of preset type voiceprint features in real-time acoustic data; and the presence of water accumulation in the vehicle's driving area is determined by responding to the presence of rain or snow in the vehicle's driving area based on cloud-based weather data.

[0093] In one embodiment, the window raising control module 203 specifically includes at least one of the following:

[0094] The preset window-raising condition is determined to be met if the precipitation in the precipitation signal data is greater than the preset precipitation threshold; if the oncoming traffic prediction data meets the preset oncoming traffic splash condition; if the water depth is higher than the water depth threshold corresponding to the current tilt angle; and if the first vehicle speed is greater than the first vehicle speed threshold corresponding to the current road segment type.

[0095] Based on the aforementioned inventive concept, the following is a detailed description of the device's workflow. (See attached document.) Figure 3 This is a schematic diagram of the working process of the window control device provided in an embodiment of the present invention.

[0096] like Figure 3 As shown, in step S301, environmental data of the vehicle's driving area is acquired, including real-time radar data, real-time image data, real-time acoustic data, and cloud-based weather data. Then, step S302 is executed. In step S302, it is determined whether there are echoes without echoes or echoes exhibiting regular changes in the real-time radar data. If so, step S306 is executed; otherwise, step S303 is executed. In step S303, it is determined whether there are texture feature data of a preset type in the real-time image data. If so, step S306 is executed; otherwise, step S304 is executed. In step S304, the real-time acoustic data is determined... If the data contains data of a preset type of voiceprint feature, proceed to step S306; otherwise, continue to step S305. In step S305, determine whether there is rain or snow in the vehicle's driving area using cloud weather data. If so, continue to step S306; otherwise, repeat step S301. In step S306, determine that there is water accumulation in the vehicle's driving area and obtain window lifting judgment data, which includes the vehicle's first speed, precipitation signal data, oncoming traffic prediction data, the tilt angle of the road segment in the vehicle's driving area, the water depth, and the road segment type. Then, continue to step S307.

[0097] Further, in step S307, it is determined whether the precipitation in the precipitation signal data is greater than the preset precipitation threshold. If so, step S is executed; otherwise, step S308 is executed. In step S308, it is determined whether the oncoming traffic prediction data meets the preset oncoming traffic splashing conditions. If so, step S is executed; otherwise, step S309 is executed. In step S309, it is determined whether the water depth is higher than the water depth threshold corresponding to the current tilt angle. If so, step S is executed; otherwise, step S310 is executed. In step S310, it is determined whether the first vehicle speed is greater than the first vehicle speed threshold corresponding to the current road segment type. If so, step S311 is executed; otherwise, step S306 is executed again. In step S311, when the preset window raising conditions are met, the vehicle window is raised.

[0098] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For example, see reference... Figure 1 In step S102, in Figure 3 This is specifically implemented through steps S302, S303, S304, S305, and S306; see reference. Figure 1 In step S103, in Figure 3 The process is specifically implemented through steps S307, S308, S309, S310, and S311.

[0099] Based on the same inventive concept as the foregoing embodiments, this application provides a vehicle including the window control device described in the foregoing embodiments.

[0100] In this application, the same or similar terms, concepts, technical solutions and / or application scenario descriptions are generally described in detail only when they appear for the first time. When they appear again, they are generally not repeated for the sake of brevity. When understanding the technical solutions and other contents of this application, the same or similar terms, concepts, technical solutions and / or application scenario descriptions that are not described in detail later can be referred to their previous relevant detailed descriptions.

[0101] In this application, the descriptions of the various embodiments have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0102] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0103] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for controlling vehicle windows, characterized in that, The method includes: The vehicle acquires environmental data of the driving area, the environmental data including at least one of real-time environmental data collected by the vehicle and cloud environmental data acquired from a cloud server. When the environmental data determines that there is water accumulation in the vehicle's driving area, the window-raising judgment data is obtained. When the window lifting judgment data is determined to meet the preset window lifting conditions, the window of the vehicle is controlled to be lifted. The window-raising judgment data includes oncoming traffic prediction data; The step of determining that the windowing judgment data meets the preset windowing conditions includes: In response to the oncoming traffic prediction data meeting the preset oncoming traffic splash conditions, it is determined that the preset window raising conditions are met; The oncoming vehicle prediction data includes the oncoming vehicle prediction area, the waterlogged area, the second speed of the oncoming vehicles, and the vehicle type. The vehicle meeting prediction data meets the preset vehicle meeting splash conditions, including: In response to the spatial overlap between the predicted oncoming traffic area and the water accumulation area, and the second vehicle speed being greater than the second vehicle speed threshold corresponding to the vehicle model, it is determined that the preset oncoming traffic splashing condition is met.

2. The method according to claim 1, characterized in that, The real-time environmental data includes at least one of real-time radar data, real-time image data, and real-time acoustic data, and the cloud-based environmental data includes cloud-based weather data.

3. The method according to claim 2, characterized in that, The determination that there is standing water in the vehicle's driving area based on the environmental data includes at least one of the following: In response to the presence of echoes with no echo or regular changes in the real-time radar data, it is determined that there is water accumulation in the area where the vehicle is traveling; In response to the presence of a preset type of texture feature in the real-time image data, it is determined that there is water accumulation in the vehicle's driving area; In response to the presence of a preset type of voiceprint feature in the real-time acoustic data, it is determined that there is water accumulation in the vehicle's driving area; In response to determining, based on the cloud-based weather data, that there is rain or snow in the area where the vehicle is traveling, and that there is standing water in the area where the vehicle is traveling.

4. The method according to claim 1, characterized in that, The window lifting judgment data also includes at least one of the following: the vehicle's first speed, precipitation signal data, the tilt angle of the road segment in the vehicle's driving area, the water depth, and the road segment type.

5. The method according to claim 4, characterized in that, The determination that the window raising judgment data meets the preset window raising conditions also includes at least one of the following: In response to the precipitation amount in the precipitation signal data being greater than a preset precipitation threshold, it is determined that the preset windowing condition is met; In response to the water depth being higher than the water depth threshold corresponding to the current tilt angle, it is determined that the preset window raising condition is met; In response to the first vehicle speed being greater than the first vehicle speed threshold corresponding to the current road segment type, it is determined that the preset window raising condition is met.

6. The method according to claim 4, characterized in that, After obtaining the window-raising judgment data when it is determined from the environmental data that there is water accumulation in the vehicle's driving area, the method further includes: Obtain weather signals sent to the cloud server by all identifiable vehicles within a preset area; If the proportion of vehicles sending rain / snow weather signals to the total number of identifiable vehicles is greater than a preset ratio, and the precipitation in the precipitation signal data is less than a preset precipitation threshold, then the preset window-raising condition is determined not to be met.

7. The method according to claim 1, characterized in that, After controlling the windows of the vehicle to rise, the method also includes: When the window raising judgment data does not meet the preset window raising conditions and the duration exceeds the preset duration, the vehicle window is lowered.

8. A vehicle window control device, characterized in that, The device includes: An environmental data acquisition module is used to acquire environmental data of the vehicle's driving area, including real-time environmental data and cloud-based environmental data. The judgment data acquisition module is used to acquire window lifting judgment data when it is determined from the environmental data that there is water accumulation in the vehicle's driving area. The window raising control module is used to control the window of the vehicle to rise when the window raising judgment data meets the preset window raising conditions. The window-raising judgment data includes oncoming traffic prediction data; The step of determining that the windowing judgment data meets the preset windowing conditions includes: In response to the oncoming traffic prediction data meeting the preset oncoming traffic splash conditions, it is determined that the preset window raising conditions are met; The oncoming vehicle prediction data includes the oncoming vehicle prediction area, the waterlogged area, the second speed of the oncoming vehicles, and the vehicle type. The vehicle meeting prediction data meets the preset vehicle meeting splash conditions, including: In response to the spatial overlap between the predicted oncoming traffic area and the water accumulation area, and the second vehicle speed being greater than the second vehicle speed threshold corresponding to the vehicle model, it is determined that the preset oncoming traffic splashing condition is met.

9. A vehicle, characterized in that, Includes the window control device as described in claim 8.

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