Method and apparatus for determining an altitude of a vehicle

Abstract

The present disclosure provides a method for determining an altitude of a vehicle, comprising: obtaining an image of a sky from a vehicle-mounted camera unit; and determining a first altitude of the vehicle based on at least one of a sky color in the image of the sky, an image brightness, or a shape of a cloud in the image of the sky.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle control, and more specifically, to methods and apparatus for determining the altitude of a vehicle. Background Technology

[0002] The performance requirements of a vehicle vary depending on the driving scenario. For example, the road conditions encountered when driving in a high-altitude area are different from those when driving in a flat area. Therefore, in order to ensure that the vehicle is in good condition, it is necessary to adjust the vehicle settings to suit the driving scenario so that the vehicle's performance can meet the requirements of the current driving scenario.

[0003] The accuracy of current vehicles in determining the altitude of their driving environment still needs improvement. Summary of the Invention

[0004] The aim is to provide a method and apparatus for determining the altitude of a vehicle, which can maximize vehicle safety and improve user experience.

[0005] According to a first aspect of this disclosure, a method for determining the altitude of a vehicle is provided, comprising: acquiring an image of the sky from an onboard camera unit; and determining a first altitude of the vehicle based on at least one of the sky color in the image of the sky, the image brightness, or the shape of clouds in the image of the sky.

[0006] According to a second aspect of this disclosure, an apparatus for determining the altitude of a vehicle is provided, comprising: a memory; and a processor coupled to the memory and configured to perform the method according to the first aspect.

[0007] According to a third aspect of this disclosure, a computer program product for determining the altitude of a vehicle is provided, which stores a computer program including instructions that, when executed by a processor, cause the processor to perform the method according to the first aspect. Attached Figure Description

[0008] The above and other objects, features and advantages of the embodiments of this disclosure will become more apparent from the more detailed description of the embodiments in conjunction with the accompanying drawings, in which the same reference numerals generally represent the same elements.

[0009] Figure 1 This is a flowchart of a method for determining the altitude of a vehicle in accordance with this disclosure.

[0010] Figure 2This is a flowchart of another method for determining the altitude of a vehicle, based on the present disclosure.

[0011] Figure 3 This is an exemplary schematic diagram of an apparatus for determining the altitude of a vehicle in accordance with the present disclosure.

[0012] Figure 4 This is another exemplary schematic diagram of another device for determining the altitude of a vehicle in accordance with the present disclosure. Detailed Implementation

[0013] The subject matter described in this disclosure will now be discussed with reference to various embodiments. It should be understood that these embodiments are discussed merely to enable those skilled in the art to better understand and implement the subject matter described in this disclosure, and are not intended to limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the elements discussed without departing from the scope of the claims. Various processes or components may be omitted, substituted, or added as needed in the various embodiments.

[0014] When driving in high-altitude areas, drivers may encounter several unique challenges. For example, high altitudes result in lower air pressure and thinner air due to lower oxygen levels; the terrain is highly varied, with steep slopes and dips, and some roads may be narrow, with the potential for potholes, mudslides, and other geological hazards; weather conditions change rapidly, with sudden rain, snow, and strong winds. These unique conditions can affect the driver's physical condition, increase driving difficulty, and potentially reduce engine and braking performance. Therefore, accurately determining whether the vehicle is currently in a high-altitude area is crucial for more effective vehicle control.

[0015] One method for determining a vehicle's altitude is to install a barometer on the vehicle and calculate the altitude using atmospheric pressure. However, because barometers are highly sensitive, the data fluctuates significantly, resulting in relatively low accuracy when using barometers to determine a vehicle's altitude.

[0016] Another method for determining a vehicle's altitude is to install a vacuum pump on the vehicle (see CN109580244A). If the vacuum pump runs for longer than a predetermined time and there is no braking signal within that time, the vehicle is determined to be in high-altitude operation when the vacuum level is below or equal to a predetermined threshold, and a high-altitude control strategy is implemented. However, due to the rapid changes in weather conditions in high-altitude areas, instantaneous weather anomalies may occur, and these sudden situations may interfere with the accurate detection of vacuum pump operation time and braking signals. Furthermore, the response of vacuum pump operation time and braking signals varies for different vehicle models. Adaptive adjustments for different vehicle models may increase the complexity of the system. Therefore, using a vacuum pump to determine a vehicle's altitude also presents problems in terms of accuracy and versatility.

[0017] To address the issues of accuracy and versatility in determining the altitude of vehicles, this disclosure proposes several methods and apparatuses for determining the altitude of vehicles. According to this disclosure, in one example, the altitude of the vehicle's current location is estimated by analyzing features of a sky image. In another example, to avoid frequent altitude estimations by the vehicle-mounted camera unit, the vehicle can first use its onboard barometer to make a preliminary judgment on its altitude, determining whether it is currently in a plain or plateau region. When the vehicle is in a plain region, the barometer can be used directly to measure the air pressure, and the altitude can be determined based on this air pressure value. Only when the altitude determined by the barometer preliminarily indicates that the vehicle is in a plateau region is the onboard camera unit activated to obtain a sky image and analyze the sky image to determine the vehicle's altitude. Using such methods and apparatuses can improve the accuracy and versatility in determining the altitude of vehicles.

[0018] The term "vehicle" as used in this disclosure can include any type of transport vehicle and vehicle capable of being controlled, including but not limited to vehicles, ships, aircraft, or other devices with or without autonomous driving capabilities. For ease of understanding, a vehicle is used as an example in this disclosure; however, those skilled in the art will understand that "vehicle" is merely an illustrative application scenario, and other application scenarios applicable to this disclosure are within the scope of this disclosure.

[0019] The term "processor" as used in this disclosure may include any device or component thereof capable of controlling a vehicle, including, but not limited to, any available processor in a vehicle, ship, aircraft, or other device with or without autonomous driving capabilities.

[0020] The “machine learning model” mentioned in this disclosure can be any type of machine learning model in the art that can perform the methods for determining the altitude of a vehicle as described in this disclosure using artificial intelligence algorithms, including but not limited to various deep neural network models applicable to this disclosure.

[0021] Figure 1 This is a flowchart of a method for determining the altitude of a vehicle in accordance with this disclosure. Figure 1 The operations can be performed by a processor in a vehicle (e.g., a vehicle).

[0022] In step 110, the processor can acquire an image of the sky from the vehicle-mounted camera unit.

[0023] The vehicle can be equipped with an onboard camera unit for acquiring images of the sky. This onboard camera unit can be any type of image-capturing functional unit applicable to the present disclosure in this art. After receiving the sky image acquired from the onboard camera unit, the processor can preprocess the image, such as performing noise reduction and contrast adjustment, to optimize the image quality and provide better input data for subsequent depth analysis.

[0024] At step 120, the processor may determine the vehicle's altitude based on at least one of the sky color, image brightness, or cloud shape in the sky image; the altitude determined based on the sky image will also be referred to herein as the first altitude.

[0025] The following example uses a comparison between plateau and plain areas to illustrate the differences between sky images collected in plateau and plain areas.

[0026] The air in high-altitude areas is relatively thin, resulting in less scattering of sunlight as it passes through the atmosphere. This makes the sky appear deep blue, especially at high altitudes, where this deep blue is more pronounced. Consequently, images of the sky in high-altitude areas captured by vehicle-mounted cameras will show a relatively deep blue color. In contrast, in plains areas, the air is relatively dense, causing more scattering of sunlight as it passes through the atmosphere. This results in a lighter blue sky, making images of the sky in plains areas captured by vehicle-mounted cameras appear a relatively lighter blue. Therefore, there is a significant difference in color between images of the sky in high-altitude areas and images of the sky in plains areas captured by vehicle-mounted cameras.

[0027] In high-altitude areas, sunlight radiation is stronger, making the sky appear clearer and the sun's rays more dazzling. Therefore, images of the sky in high-altitude areas captured by vehicle-mounted cameras tend to be brighter. In contrast, in plains areas, sunlight radiation is more uniform, and the overall brightness of the sky is more stable and less intense than in high-altitude regions. Consequently, images of the sky in plains captured by vehicle-mounted cameras tend to be less bright. Therefore, there is a significant difference in brightness between images of the sky in high-altitude areas and images of the sky in plains captured by vehicle-mounted cameras.

[0028] In high-altitude areas, clouds tend to float at a relatively lower altitude, making their shapes and textures more clearly visible. High-altitude regions may also exhibit unique mountain clouds, such as mountain mists and cirrus clouds. In contrast, in plains areas, clouds tend to float at a relatively higher altitude, and due to the flatter field of vision, their shapes are more uniform, forming broad cloud layers. Therefore, the cloud shapes in images of the sky over high-altitude areas obtained through a vehicle-mounted camera unit differ significantly from those in images of the sky over plains areas.

[0029] Since the sky images obtained at different altitudes will have the aforementioned different characteristics, the processor can determine the vehicle's altitude based on one or more of the sky color, image brightness, or cloud shape in the sky image obtained through the vehicle-mounted camera unit.

[0030] In one example, if the blue hue of the sky in the sky image exceeds a corresponding threshold, it indicates that the vehicle is currently in a high-altitude region; or if the similarity between the blue hue of the sky in the sky image and the blue hue corresponding to the corresponding altitude exceeds a corresponding threshold, it indicates that the vehicle's altitude is the altitude corresponding to that threshold.

[0031] In one example, if the brightness of the sky image exceeds a corresponding threshold, it indicates that the vehicle is currently in a high-altitude region; or if the similarity between the brightness of the sky image and the brightness corresponding to a certain altitude exceeds a corresponding threshold, it indicates that the vehicle's altitude is the altitude corresponding to that threshold.

[0032] In one example, if the shape of the clouds in the sky image matches the shape of clouds corresponding to a plateau region, it indicates that the vehicle is currently in a plateau region; or if the similarity between the shape of the clouds in the sky image and the shape of clouds corresponding to a certain altitude exceeds a certain threshold, it indicates that the vehicle's altitude is the altitude corresponding to that threshold.

[0033] In another example, one or more of the sky color, image brightness, or cloud shape in an image of the sky can be combined to determine whether the vehicle is currently in a high-altitude region or to determine the vehicle's altitude. For example, any one of the sky color, image brightness, or cloud shape in an image of the sky can be used as an indicator to determine whether the vehicle is currently in a high-altitude region or to determine the vehicle's altitude; any two of the sky color, image brightness, or cloud shape in an image of the sky (e.g., sky color and image brightness; sky color and cloud shape; or image brightness and cloud shape) can be used as indicators to determine whether the vehicle is currently in a high-altitude region or to determine the vehicle's altitude; or all three of the sky color, image brightness, and cloud shape in an image of the sky can be used simultaneously as indicators to determine whether the vehicle is currently in a high-altitude region or to determine the vehicle's altitude.

[0034] Because of the aforementioned correlation between altitude and the sky color, image brightness, or cloud shape in an image of the sky, the processor can determine the vehicle's first altitude based on at least one of the sky color, image brightness, or cloud shape in an image of the sky.

[0035] In a further example, the processor can input an image of the sky into a pre-trained first machine learning model. This model then uses the sky image to determine the vehicle's initial altitude by processing the sky's color, brightness, or cloud shape. Since the sky image captured by the vehicle's onboard camera unit is correlated with the vehicle's altitude, using the first machine learning model based on the sky image allows for a more efficient determination of the vehicle's initial altitude.

[0037] Furthermore, the processor can input both the image features of the sky and the altitude corresponding to the average of at least one air pressure value collected over a predetermined time period (also referred to as the second altitude in this paper) into a pre-trained second machine learning model to determine the vehicle's first altitude. Inputting the second altitude, corresponding to the average of at least one air pressure value collected over a predetermined time period, into the second machine learning model can help determine the vehicle's first altitude more accurately.

[0038] The first and second machine learning models used in this disclosure can be any type of machine learning model in the art suitable for determining the altitude of a vehicle based on sky-based images, wherein the machine learning model can be trained by supervised learning during the training phase, and the first and second machine learning models can be the same or different machine learning models.

[0039] Figure 1 The advantages of the method shown are that, compared with the method of using a barometer, the method of using a vehicle-mounted camera unit to determine the altitude of a vehicle has higher data stability and accuracy; compared with the method of using a vacuum pump, the method of using a vehicle-mounted camera unit to determine the altitude of a vehicle has lower requirements on the vehicle model, which helps to improve the versatility of determining the altitude of a vehicle.

[0040] Figure 2 This is a flowchart of another method for determining the altitude of a vehicle, based on the present disclosure. Figure 2 The operations can also be performed by a processor in a vehicle (e.g., a vehicle).

[0041] At step 210, the processor may collect air pressure values ​​at the vehicle. In one example, the processor may collect one or more air pressure values ​​at the vehicle within a predetermined time period.

[0042] The vehicle can be equipped with a barometer that collects external air pressure data, reflecting the ambient air pressure. A processor on the vehicle can periodically collect air pressure values ​​at the vehicle's location, or it can collect air pressure values ​​based on triggered events. In one example, the processor can collect air pressure values ​​at the vehicle's location over a predetermined time period as a set of data. The predetermined time period can be any length preset in the processor, such as 5 minutes or other time lengths. The processor on the vehicle can periodically collect one or more air pressure values ​​at the vehicle's location within the predetermined time period, or it can collect one or more air pressure values ​​at the vehicle's location within the predetermined time period based on triggered events. The period for collecting air pressure values ​​at the vehicle's location or collecting one or more air pressure values ​​at the vehicle's location within the predetermined time period can be preset in the processor or set by the user through the vehicle-user interaction interface; the trigger event for collecting air pressure values ​​at the vehicle's location or collecting one or more air pressure values ​​at the vehicle's location within the predetermined time period can be preset in the processor or triggered by the user through the vehicle-user interaction interface.

[0043] The processor can preprocess the collected air pressure values ​​and use filtering methods to smooth them, which helps to eliminate noise and fluctuations in the data and improve the accuracy of subsequent altitude calculations.

[0044] At step 220, the processor can compare the second altitude corresponding to the air pressure value with the target threshold range.

[0045] When the collected air pressure value is a single value, the processor can determine the air pressure value collected within a predetermined time period, and then determine the altitude corresponding to the air pressure value by querying the air pressure-altitude relationship table that indicates the correspondence between air pressure value and altitude. This altitude is then used as the second altitude, and the second altitude is compared with the target threshold interval.

[0046] When multiple air pressure values ​​are collected, the processor can determine the average value of the multiple air pressure values ​​collected within a predetermined time period. Then, by querying the air pressure-altitude relationship table that indicates the correspondence between air pressure values ​​and altitude, it determines the altitude corresponding to the average value of the multiple air pressure values, uses it as the second altitude, and then compares the second altitude with the target threshold interval.

[0047] The target threshold range can be pre-set in the processor or set by the user through the interaction interface between the vehicle and the user. For example, the target threshold range can be greater than or equal to 3500 meters, or greater than or equal to any other altitude; the target threshold range can also be from 3500 meters to another altitude greater than 3500 meters, etc. The above are just examples and are not intended to be restrictive.

[0048] At step 230, the processor can determine whether the second altitude falls within the target threshold range. If the second altitude falls within the target threshold range, i.e., it is preliminarily determined that the vehicle is currently in an area with an altitude corresponding to the target threshold range (e.g., but not limited to plateau areas), the processor executes step 240.

[0049] At step 240, the processor can activate the vehicle-mounted camera unit to obtain an image of the sky based on determining that the second altitude falls within the target threshold range, as described in step 110.

[0050] The onboard camera unit is activated when the processor determines that the altitude corresponding to one or more atmospheric pressure values ​​collected over a predetermined time period falls within a target threshold range. This approach saves system resources by ensuring the onboard camera unit is activated only when the vehicle is in an area at the altitude corresponding to the target threshold range.

[0051] In step 250, the processor may determine the first altitude of the vehicle based on at least one of the sky color in the sky image, the image brightness, or the shape of the clouds in the sky image, as described in step 120.

[0052] In step 260, the processor may perform operations on the vehicle corresponding to a first altitude. In one example, the processor may perform operations on the vehicle corresponding to a first altitude, including but not limited to the following operations.

[0053] In one example, the processor can be pre-set with driving modes corresponding to different altitudes or altitude ranges, and then set the vehicle to the driving mode corresponding to its altitude after the vehicle's altitude is determined.

[0054] In one example, the processor can present the vehicle's altitude to the user in the form of text, sound, video, or other means to draw the user's attention.

[0055] The advantage of operating a vehicle according to its altitude, which corresponds to the altitude of its location, is that it helps to adjust the vehicle to a more suitable altitude for operation in a timely manner, thereby improving the vehicle's safety and user experience.

[0056] In a further example, the processor can also acquire images of the sky at predetermined time intervals, such as acquiring a first sky image and a second sky image with predetermined time intervals; then determine the image variation between the first and second sky images; if the image variation is less than or equal to a preset variation threshold, output a first altitude, i.e., the altitude determined based on the analysis of the sky images; if the image variation is greater than the preset variation threshold, output a second altitude, i.e., the altitude determined by querying a barometric altitude table. For example, since the variation between sky images taken in high-altitude areas may be small, while the variation between sky images taken in plains areas may be large, for areas such as plains where the sky image variation is large, the altitude of the vehicle's location can be determined solely by using a barometer; for areas such as high-altitude areas where the sky image variation is small, it may be more suitable to utilize... Figure 2 The method shown determines the altitude of the area where the vehicle is located. Here, image changes can be changes in brightness or color, and therefore the corresponding change threshold can be the amount or rate of change in brightness or color. In another example, image changes can also be the degree of shape matching between a cloud before and after a change in shape, and the corresponding change threshold could be, for example, a mismatch rate threshold indicating a shape change, where if the value is less than or equal to the mismatch rate threshold, the cloud shape is considered unchanged; otherwise, the cloud shape is determined to have changed. In this way, the accuracy of determining the vehicle's altitude can be further improved. Accordingly, when the processor outputs a second altitude, in step 260, the processor performs operations on the vehicle corresponding to that second altitude.

[0057] Returning to step 230, if the second altitude does not fall within the target threshold range, meaning it is preliminarily determined that the vehicle is not currently in an area with an altitude corresponding to the target threshold range, the processor executes step 270. In step 270, the processor can disable the onboard camera unit. If the processor determines that the second altitude does not fall within the target threshold range, it indicates that the vehicle is not currently in an area requiring a more accurate altitude determination; therefore, it is not necessary to activate the vehicle's onboard camera unit, and disabling it at this point saves system resources.

[0058] Figure 2The advantages of the method shown are as follows: First, the determination of the vehicle's altitude is based not only on the air pressure value collected by the barometer, but also on the sky image obtained by the vehicle-mounted camera unit. By comprehensively utilizing two data sources, the accuracy of determining the vehicle's altitude can be improved. Second, by comparing the altitude initially determined using the air pressure value with the threshold target range to determine whether to activate the vehicle-mounted camera unit to obtain the sky image, not only can the accuracy of determining the vehicle's altitude be improved, but system resources can also be saved.

[0059] Figure 3 This is an exemplary schematic diagram of an apparatus for determining the altitude of a vehicle according to the present disclosure. The apparatus 300 may include a data acquisition unit 310, a processing unit 320, a vehicle-mounted camera unit 330, and a control unit 340. The data acquisition unit 310 can perform actions such as... Figure 1 Step 110 and Figure 2 The operation described in step 210; the processing unit 320 can perform, as follows Figure 1 Step 120 and Figure 2 The operations described in steps 220, 230, 230, 250, and 270; the vehicle-mounted camera unit 330 can be enabled to capture images of the sky or disabled according to control information from the processing unit 320; the control unit 340 can perform actions such as Figure 2 The operations described in step 260 are not repeated here.

[0060] The methods and apparatus for determining the altitude of a vehicle as described in this disclosure can be applied to current and future intelligent driving systems, automotive weather sensing systems, and vehicle safety assistance systems, helping to improve the safety and comfort of driving for users even in complex terrain and weather conditions.

[0061] Figure 4 This is another exemplary schematic diagram of an apparatus for determining the altitude of a vehicle in accordance with the present disclosure.

[0062] Device 400 includes a processor 404 connected to an internal communication bus 402, the processor 404 being configured to execute instructions in memory 406 to implement instructions by combining Figures 1-3The method described is for determining the altitude of a vehicle. Examples of processor 404 may include a central processing unit (CPU), a microcontroller, etc. Memory 406 suitable for tangibly representing computer program instructions and data includes various forms of memory, such as EPROM, EEPROM, and flash memory devices, etc. Apparatus 400 may also include an input interface 408 and an output interface 410. Input interface 408 is used to receive barometric pressure values ​​from the barometer described above and images from the vehicle-mounted camera unit described above. Output interface 410 is used to send data or instructions for performing operations corresponding to the first altitude of the vehicle based on the determined first altitude to a unit capable of performing the corresponding operations on the vehicle.

[0063] Computer program instructions may include computer-executable instructions for causing the processor 404 of device 400 to perform operations by combining... Figures 1-2 The method described herein is for determining the altitude of a vehicle. The program can be recorded on any data storage medium, including memory. For example, the program can be implemented as digital electronic circuitry, or as computer hardware, firmware, software, or a combination thereof. The process / method steps described in this disclosure can be executed by a programmable processor that executes program instructions to perform methods, steps, or operations by processing input data and generating output.

[0064] For example, memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), static random access memory (SRAM), hard disk, flash memory, or any memory available in the art, etc.

[0065] In one example, a computer program product for determining the altitude of a vehicle stores instructions that, when executed by a processor, cause the processor to be configured to perform actions in conjunction with... Figures 1-3 The method described is for determining the altitude of a vehicle.

[0066] The foregoing has described specific embodiments of this disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0067] Not all steps and modules in the above process and system structure diagrams are mandatory; some steps or units can be omitted according to actual needs. The device structure described in the above embodiments can be a physical structure or a logical structure. That is, some units may be implemented by the same physical entity, some units may be implemented by multiple physical entities, or they may be jointly implemented by certain components in multiple independent devices.

[0068] For the purpose of providing an understanding of the described techniques, the detailed implementation includes specific details. However, these techniques can be implemented without these specific details. In some instances, well-known structures and apparatuses are shown in block diagram form to avoid obscuring the concepts of the described embodiments.

[0069] The optional embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present disclosure are not limited to the specific details in the above embodiments. Within the scope of the technical concept of the embodiments of the present disclosure, various variations can be made to the technical solutions of the embodiments of the present disclosure, and these variations all fall within the protection scope of the embodiments of the present disclosure.

Claims

1. A method for determining the altitude of a vehicle, comprising: Acquire images of the sky from the vehicle-mounted camera unit; as well as The first altitude of the vehicle is determined based on at least one of the sky color, image brightness, or cloud shape in the image of the sky.

2. The method according to claim 1, further comprising: The air pressure value was collected at the vehicle. The second altitude corresponding to the air pressure value is compared with the target threshold range; When it is determined that the second altitude falls within the target threshold range, the vehicle-mounted camera unit is activated to obtain an image of the sky.

3. The method according to claim 2, wherein, The air pressure values ​​collected at the vehicle include: Periodically collect at least one air pressure value at the vehicle within a predetermined time period; or At least one air pressure value at the vehicle within the predetermined time period is collected based on a triggering event.

4. The method according to claim 3, wherein, The second altitude was determined in the following way: Calculate the average value of the at least one air pressure value; The altitude corresponding to the average value, determined by consulting the barometric pressure-altitude relationship table, is taken as the second altitude.

5. The method according to claim 2, wherein the method further comprises: Acquire at least a first sky image and a second sky image at a predetermined time interval; Determine the image changes between the first sky image and the second sky image; If the image change is less than or equal to a predetermined change threshold, the first altitude is output; otherwise, if the image change is greater than the predetermined change threshold, the second altitude is output.

6. The method according to claim 2, wherein the method further comprises: The vehicle-mounted camera unit is disabled based on the fact that the second altitude does not fall within the target threshold range.

7. The method according to any one of claims 1-5, wherein the method further comprises: The first altitude is estimated by processing at least one of the sky color, the image brightness, or the cloud shape in the image of the sky using a trained first machine learning model.

8. The method according to any one of claims 1-5, wherein the method further comprises: The first altitude is estimated by processing at least one of the sky color, the image brightness, or the cloud shape in the image of the sky, and the second altitude using a trained second machine learning model.

9. The method according to claim 1, wherein the method further comprises: Based on the first altitude of the vehicle, operations corresponding to the first altitude are performed on the vehicle.

10. The method according to any one of claims 1-5, the method further comprising: If the blueness of the sky exceeds a chromaticity threshold, the brightness of the sky exceeds a brightness threshold, and the clouds in the sky are identified as being in a high-altitude cloud state, then the vehicle is determined to be in a high-altitude environment.

11. An apparatus for determining the altitude of a vehicle, comprising: Memory; A processor coupled to the memory and configured to perform the method according to any one of claims 1-10.

12. A computer program product for determining the altitude of a vehicle, comprising storing a computer program including instructions that, when executed by a processor, cause the processor to be configured to perform the method according to any one of claims 1-10.

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