Vehicle wading early warning method, device, equipment and medium

Abstract

The invention discloses a vehicle wading early warning method, device and equipment and a medium. The method comprises the steps of obtaining multiple pieces of ultrasonic data of ultrasonic radar equipment in a to-be-detected vehicle and vehicle posture data and external environment data of the to-be-detected vehicle in response to the fact that a user of the to-be-detected vehicle is in an off-vehicle state; calculating a water depth data set of the position of the to-be-detected vehicle according to the ultrasonic data and the vehicle posture data; the water depth data set comprises a plurality of pieces of water depth data calculated according to the collection time sequence of the ultrasonic data; according to the water depth data set and the external environment data, performing wading anomaly detection on the to-be-detected vehicle to obtain an anomaly detection result; and in response to the abnormal detection result, adjusting the suspension of the to-be-detected vehicle to the highest state, and sending the abnormal detection result to a mobile device bound with the user. According to the embodiment of the invention, the wading early warning requirement of the unattended vehicle can be realized.

Description

Technical Field

[0001] This invention relates to the field of vehicle control technology, and in particular to a method, device, equipment and medium for vehicle wading warning. Background Technology

[0002] With rapid urbanization and frequent extreme weather events such as torrential rains, urban roads, especially low-lying areas, often experience short-term flooding, causing parked vehicles to be submerged or even destroyed. To reduce property damage caused by flooded vehicles, it is necessary to monitor and issue early warnings about water levels at the location of parked vehicles in real time. If the rising water level can be identified in advance and the user is notified promptly when a vehicle is unattended, it will help the user take appropriate measures and avoid losses.

[0003] Currently, existing technologies mainly focus on water risk warnings during driving, that is, providing real-time reminders when a driver is on the road, aiming to assist driving decisions.

[0004] However, vehicles still face a high risk of wading through water when parked unattended, and existing technologies cannot meet the need for water wading warnings when vehicles are parked unattended. Summary of the Invention

[0005] This invention provides a method, device, equipment, and medium for vehicle wading warning. The embodiments of this invention can meet the need for wading warning of unattended vehicles.

[0006] In a first aspect, embodiments of the present invention provide a vehicle wading warning method, the method comprising:

[0007] In response to the user being away from the vehicle, the system acquires multiple ultrasonic data from the ultrasonic radar device in the vehicle, as well as the vehicle's posture data and external environment data.

[0008] Based on the ultrasonic data and vehicle posture data, a set of water depth data for the location of the vehicle under test is calculated; the water depth data set includes multiple water depth data calculated in the order of ultrasonic data acquisition time.

[0009] Based on the water depth data set and external environmental data, the vehicle to be tested is subjected to water wading anomaly detection, and the anomaly detection results are obtained.

[0010] In response to an anomaly detection result, the suspension of the vehicle under test is adjusted to its highest position, and the anomaly detection result is sent to the user's bound mobile device.

[0011] Secondly, embodiments of the present invention also provide a vehicle wading warning device, the device comprising:

[0012] The data acquisition module is used to acquire multiple ultrasonic data from the ultrasonic radar device in the vehicle under test, as well as the vehicle posture data and external environment data, in response to the user of the vehicle under test being away from the vehicle.

[0013] The water depth calculation module is used to calculate the water depth data set of the location of the vehicle under test based on various ultrasonic data and vehicle posture data; the water depth data set includes multiple water depth data calculated in the order of ultrasonic data acquisition time.

[0014] The anomaly detection module is used to perform water wading anomaly detection on the vehicle to be tested based on the water depth data set and external environmental data, and obtain the anomaly detection results;

[0015] The result response module is used to adjust the suspension of the vehicle under test to the highest position in response to an anomaly detection result, and send the anomaly detection result to the user's bound mobile device.

[0016] Thirdly, embodiments of the present invention also provide a vehicle wading warning device, the vehicle wading warning device comprising:

[0017] At least one processor; and

[0018] A memory that is communicatively connected to at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to execute the vehicle wading warning method according to any embodiment of the present invention.

[0020] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions, which are used to cause a processor to execute the vehicle wading warning method of any embodiment of the present invention.

[0021] The technical solution of this invention, by acquiring ultrasonic data, vehicle posture data, and external environment data when the user is away from the vehicle, can achieve continuous perception of the water wading situation of the parked vehicle. By calculating a water depth data set based on ultrasonic data and vehicle posture data, it can quantitatively record the change of water depth at the vehicle's location over time. By using the water depth data set and external environment data to detect water wading anomalies, it can achieve trend and environmental judgment of water accumulation risk. By adjusting the suspension to the highest state when the detection result is abnormal, it can temporarily enhance the vehicle's water wading capability. By sending the result to the user's bound mobile device when the detection result is abnormal, it can achieve the effect of remotely notifying the user of water wading risk. This solves the technical problem that the prior art cannot meet the water wading warning needs of vehicles in an unattended parked state, thus realizing the need for water wading warnings for unattended vehicles.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A flowchart of a vehicle wading warning method provided in an embodiment of the present invention;

[0025] Figure 2 A flowchart of a vehicle wading warning method provided in an embodiment of the present invention;

[0026] Figure 3 This is a schematic diagram of the structure of a vehicle wading warning device provided in an embodiment of the present invention;

[0027] Figure 4 This is a structural schematic diagram of a vehicle wading warning device provided in an embodiment of the present invention. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] The acquisition, storage, and application of ultrasonic data, vehicle posture data, and external environment data involved in the technical solutions of this invention comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0031] Figure 1 This is a flowchart illustrating a vehicle wading warning method provided in an embodiment of the present invention. This embodiment is applicable to situations where a vehicle is parked unattended and a wading warning is issued. The method can be executed by a vehicle wading warning device, which can be implemented in hardware and / or software.

[0032] See Figure 1 The vehicle wading warning methods shown include:

[0033] S101. In response to the user of the vehicle to be tested being away from the vehicle, acquire multiple ultrasonic data from the ultrasonic radar device in the vehicle to be tested, as well as the vehicle posture data and external environment data of the vehicle to be tested.

[0034] The vehicle to be tested can refer to the target vehicle for which a water wading risk assessment is required. Through onboard sensors and a vehicle control system, data on the surrounding environment and the vehicle itself are collected, serving as the basis for subsequent water depth calculations and anomaly detection. The type of vehicle to be tested is not limited to traditional gasoline-powered vehicles, but also applies to new energy vehicles; however, the vehicle to be tested must have the ability to collect ultrasonic data and execute suspension control.

[0035] The "away from vehicle" state refers to the state where the user has left the vehicle under inspection and is no longer directly controlling it. This state can be determined through information such as door lock signals, key removal detection, and driver's seat status. The "away from vehicle" state triggers the vehicle to enter parking mode, at which point the wading warning system activates, ensuring that it can still monitor for water accumulation even when unattended. The "away from vehicle" state serves as the trigger condition for the wading warning system, preventing the system from being mistakenly triggered while the vehicle is in motion or in other states.

[0036] Ultrasonic data refers to the echo data collected by ultrasonic radar equipment. Ultrasonic data is used to reflect the distance between the radar and the water or land surface. When ultrasonic data encounters the ground or water surface, it is reflected; by calculating the propagation time, the target distance can be determined.

[0037] Optionally, the ultrasonic radar device can be mounted under the rearview mirror of the vehicle to be inspected.

[0038] Vehicle attitude data refers to a set of parameters representing the state of the vehicle being tested. This data may include vehicle height, tire pressure, pitch angle, and roll angle. Onboard sensors detect the vehicle's attitude, correcting for errors in water depth calculation caused by changes in vehicle posture.

[0039] External environmental data refers to auxiliary information about the external environment in which the vehicle being tested is located. This data may include weather data (rainfall, intensity of rainfall), geographic location data, and historical flood data. By combining external environmental data with water depth change trends, the reliability of assessing water-related risks is enhanced.

[0040] S102. Calculate the water depth data set of the location of the vehicle to be detected based on the ultrasonic data and vehicle posture data; the water depth data set includes multiple water depth data calculated in the order of ultrasonic data acquisition time.

[0041] The water depth dataset can refer to a collection of multiple sets of water depth data calculated within a time window. The water depth dataset consists of multiple water depth data points arranged in chronological order, in the form of a time series. The water depth dataset is not limited to a fixed sampling interval; adaptive sampling can also be used, but the water depth dataset must reflect the pattern of water depth change over time. Specifically, the water depth data can refer to the depth of the water at the location of a vehicle at a given moment.

[0042] S103. Based on the water depth data set and external environment data, conduct water wading anomaly detection on the vehicle to be tested and obtain the anomaly detection results.

[0043] Water wading anomaly detection refers to the process of detecting whether a vehicle under inspection has a risk of water wading. The anomaly detection result refers to the judgment output by the water wading anomaly detection. Anomaly detection results can be either abnormal or normal. When the anomaly detection result is abnormal, it indicates that the vehicle under inspection has a high risk of water wading; when the anomaly detection result is normal, it indicates that the vehicle under inspection does not have a high risk of water wading.

[0044] S104. In response to the abnormality detection result being abnormal, adjust the suspension of the vehicle to be tested to the highest state and send the abnormality detection result to the user's bound mobile device.

[0045] The "highest state" refers to the maximum vehicle height that the suspension system can provide. The highest state corresponds to the maximum suspension travel; when the vehicle's suspension is in its highest state, the distance between the vehicle body under test and the ground is greatest. By controlling the suspension actuators to adjust the suspension to its highest state, the wading capability of the vehicle under test can be temporarily enhanced.

[0046] The mobile device refers to the communication terminal device that the user is linked to the vehicle being inspected. Mobile devices can include devices such as mobile phones, tablets, or laptops. Through wireless communication, the mobile device can receive anomaly detection results and video surveillance footage captured by the vehicle being inspected.

[0047] As can be seen, in this embodiment, by acquiring ultrasonic data, vehicle posture data, and external environment data when the user is away from the vehicle, continuous perception of the water wading situation of the parked vehicle can be achieved. By calculating a water depth data set based on ultrasonic data and vehicle posture data, the change of water depth at the vehicle's location over time can be quantitatively recorded. By using the water depth data set and external environment data for water wading anomaly detection, trend and environmental judgment of water accumulation risk can be achieved. By adjusting the suspension to the highest state when the detection result is abnormal, the vehicle's water wading capability can be temporarily enhanced. By sending the result to the user's bound mobile device when the detection result is abnormal, the effect of remotely notifying the user of water wading risk can be achieved. This solves the technical problem that the existing technology cannot meet the water wading warning needs when the vehicle is parked unattended, thereby realizing the need for water wading warning for unattended vehicles.

[0048] In an optional embodiment, Figure 2The flowchart of a vehicle wading warning method provided in this embodiment of the invention refines the process of "conducting wading anomaly detection on the vehicle to be tested based on a water depth data set and external environmental data, and obtaining anomaly detection results" into "determining the water depth change gradient of the water depth data set; comparing the water depth change gradient with a preset gradient anomaly threshold to determine the water depth detection result; determining the environmental detection result of the vehicle to be tested based on external environmental data; and determining the anomaly detection result based on the water depth detection result and the environmental detection result," thereby improving the operation of the vehicle wading warning.

[0049] It should be noted that for parts not described in detail in the embodiments of the present invention, please refer to the descriptions in other embodiments.

[0050] See Figure 2 The vehicle wading warning methods shown include:

[0051] S201. In response to the user of the vehicle to be tested being away from the vehicle, acquire multiple ultrasonic data from the ultrasonic radar device in the vehicle to be tested, as well as the vehicle posture data and external environment data of the vehicle to be tested.

[0052] S202. Based on the ultrasonic data and vehicle posture data, calculate the water depth data set of the location of the vehicle to be detected; the water depth data set includes multiple water depth data calculated in the order of ultrasonic data acquisition time.

[0053] S203. Based on the water depth data set, determine the water depth variation gradient of the water depth data set.

[0054] The water depth gradient refers to the gradient of the water depth at the location of the vehicle under test over a period of time. By comparing the magnitude of the water depth change between adjacent time points, it can be reflected whether the water level is rising rapidly. If the gradient is large, it indicates that the water level is increasing sharply.

[0055] S204. Compare the water depth change gradient with the preset gradient anomaly threshold to determine the water depth detection result.

[0056] The gradient anomaly threshold can be a preset critical value used to determine whether the gradient of water depth change is abnormal. The gradient anomaly threshold can be a fixed value or dynamically adjusted according to weather data or geographical location. For example, the gradient anomaly threshold in normal weather can be preset to 1 cm / min, while in heavy rain, the gradient anomaly threshold can be reduced to 0.5 cm / min.

[0057] The water depth detection result can refer to the comparison between the water depth change gradient and the gradient anomaly threshold. By determining whether the water depth change gradient exceeds the gradient anomaly threshold, the system outputs whether the water level status is within the dangerous change range.

[0058] S205. Determine the environmental test results of the vehicle to be tested based on external environmental data.

[0059] Environmental monitoring results can refer to conclusions about water-related risks derived from external environmental data (such as weather, geographical location, and historical flood records). By analyzing external environmental data, it is determined whether the vehicle under inspection is in heavy rain or located in a low-lying area, thus obtaining an environmental risk assessment result. If the weather data indicates heavy rain and the vehicle is located in a historically flood-prone area, the environmental monitoring result is high risk.

[0060] S206. Based on the water depth detection results and environmental detection results, determine the abnormal detection results.

[0061] S207. In response to the abnormality detection result being abnormal, the suspension of the vehicle to be tested is adjusted to the highest state, and the abnormality detection result is sent to the user's bound mobile device.

[0062] As can be seen, in this embodiment, by calculating the water depth change gradient from the water depth data set, the trend of water level changes around the vehicle can be reflected. By comparing the water depth change gradient with the gradient anomaly threshold, it is possible to determine whether there are abnormal water level changes. By generating environmental detection results using external environmental data, a comprehensive identification of the vehicle's environmental conditions can be achieved. By combining the water depth detection results and the environmental detection results, a comprehensive assessment of the vehicle's water wading risk can be achieved.

[0063] In some embodiments, determining abnormal detection results based on water depth detection results and environmental detection results includes:

[0064] The water depth detection results and environmental monitoring results are weighted and calculated to obtain a water-related risk score;

[0065] The water-related risk score is compared with a preset risk threshold to determine the abnormal detection results.

[0066] The water wading risk score is a numerical value that quantifies the risk of a vehicle wading through water. It reflects the degree of risk from both water depth and environmental monitoring results. Through weighted calculation or model fusion, the trend of water depth changes is superimposed with environmental conditions to obtain a single indicator.

[0067] The risk threshold can refer to the threshold value for determining water-related risk scores. When the water-related risk score exceeds the risk threshold, the system determines it as an abnormal water-related situation.

[0068] As can be seen, in this embodiment, by weighting the water depth detection results and the environmental detection results, the risk of vehicle wading can be quantitatively expressed. By comparing the wading risk score with the risk threshold, it is possible to determine whether the vehicle wading has reached an abnormal state.

[0069] In some embodiments, vehicle posture data includes at least one of the following: suspension height data, tire pressure data, and vehicle angle data.

[0070] Among them, suspension height data can refer to parameters that reflect the vehicle's ground clearance.

[0071] Tire pressure data refers to the air pressure inside a vehicle's tires. Tire pressure affects vehicle posture, and changes in tire pressure can cause changes in the distance between ultrasonic waves and the ground.

[0072] Among them, vehicle angle data can refer to parameters that reflect the vehicle's attitude, such as pitch angle and roll angle.

[0073] Specifically, based on the suspension height data, tire pressure data, and vehicle angle data in the vehicle posture data, the exact height of the ultrasonic radar equipment in the vehicle can be calculated.

[0074] As can be seen, in this embodiment, by acquiring suspension height data, the vehicle's ground clearance can be reflected; by acquiring tire pressure data, the vehicle's tire force can be reflected; and by acquiring vehicle angle data, the vehicle's attitude changes can be reflected. Thus, the ultrasonic radar equipment can be accurately corrected for height compensation.

[0075] In some embodiments, a set of water depth data for the location of the vehicle under test is calculated based on the ultrasonic data and vehicle posture data, including:

[0076] Based on the ultrasonic data, calculate the first set of vertical distances between the ultrasonic radar device and the water surface;

[0077] Based on vehicle posture data, determine the second set of vertical distances between the ultrasonic radar device and the ground;

[0078] Based on the first vertical distance set and the second vertical distance set, calculate the water depth data set at the location of the vehicle to be detected.

[0079] The first vertical distance set can refer to the set of distances between the ultrasonic radar device and the water surface. It consists of distance data from multiple time points, arranged in the order of the ultrasonic data sampling time. The first vertical distance set includes multiple first vertical distances.

[0080] The second vertical distance set can refer to the set of distances between the ultrasonic radar device and the ground. It consists of distance data from multiple time points, arranged in the order of the ultrasonic data sampling time. The second vertical distance includes multiple second vertical distances.

[0081] Specifically, the water depth data set can be calculated in the following way: the radar echo of the ultrasonic data is used to calculate the first vertical distance; the second vertical distance is obtained by correcting the installation height of the ultrasonic radar equipment calibrated by the vehicle and parameters such as real-time attitude, suspension and tire pressure; the difference between the first vertical distance and the second vertical distance is determined as the water depth data of the location of the vehicle to be detected, and thus the water depth data set is obtained.

[0082] As can be seen, in this embodiment, by calculating the first vertical distance set based on ultrasonic data, the distance between the vehicle sensor and the water surface can be quantitatively represented. By determining the second vertical distance set based on vehicle posture data, the relative position of the vehicle sensor and the ground can be reflected. By combining the first vertical distance set and the second vertical distance set, the water depth data at the vehicle's location can be estimated.

[0083] In some embodiments, external environment data includes at least one of the following: weather data, geographic location data, and historical flood data.

[0084] Weather data refers to information reflecting the meteorological conditions of the area where the vehicle is located. Weather data can include parameters such as rainfall, rainfall intensity, and weather warnings.

[0085] The geographic location data refers to the spatial coordinates of the vehicle's parking location. This data is obtained through a positioning system and combined with the geographic environment to identify risk areas, helping to determine whether the vehicle is in a flood-prone area. For example, the vehicle may be located in a low-lying area on XX Road in a certain city.

[0086] Historical flood data refers to records of past waterlogging and flooding events in a region. This data may include historical parameters such as water depth, frequency, and duration. As prior environmental information, historical flood data is used to improve the accuracy of flood risk assessment.

[0087] As can be seen, in this embodiment, by introducing weather data, in addition to water depth data detection, it is possible to identify whether there is severe weather such as rain or blizzard, thereby improving the accuracy of water wading anomaly detection results. By introducing geographical location data, water depth detection can be combined with the specific road or regional environment where the vehicle is located, thereby achieving differentiated judgment of water wading risk for different areas. By introducing historical flood data, when the current water depth detection is insufficient to reflect potential risks, supplementary judgment can be made based on historical data, thereby improving the comprehensiveness of water wading risk warning.

[0088] In some embodiments, after sending the anomaly detection result to the user-bound mobile device, the method further includes:

[0089] Obtain real-time monitoring video of the vehicle to be inspected;

[0090] Send real-time monitoring video to the user's linked mobile device.

[0091] Real-time monitoring video refers to images of the surrounding environment captured by the vehicle's cameras while it is parked. Real-time monitoring video provides users with a clear visual picture, helping them decide whether to approach the vehicle.

[0092] As can be seen, in this embodiment, by acquiring real-time monitoring video, a direct presentation of the vehicle's wading environment can be achieved, avoiding a single judgment based solely on detection data. By sending real-time monitoring video to the user's bound mobile device, the user can remotely view the wading situation around the vehicle, thereby assisting the user in making further decisions. By providing real-time monitoring video after sending abnormal detection results, dual verification of the detection results and the actual video footage can be achieved, thereby improving the credibility of the wading warning and the user's perception experience.

[0093] Figure 3 This invention provides a schematic diagram of a vehicle wading warning device. This invention is applicable to situations where a vehicle is parked unattended and requires a wading warning. The device can execute a vehicle wading warning method and can be implemented in hardware and / or software.

[0094] See Figure 3 The vehicle wading warning device shown includes: a data acquisition module 301, a water depth calculation module 302, an anomaly detection module 303, and a result response module 304, wherein...

[0095] The data acquisition module 301 is used to acquire multiple ultrasonic data from the ultrasonic radar device in the vehicle under test, as well as the vehicle posture data and external environment data of the vehicle under test, in response to the user of the vehicle under test being away from the vehicle.

[0096] The water depth calculation module 302 is used to calculate the water depth data set of the location of the vehicle to be detected based on the ultrasonic data and vehicle posture data; the water depth data set includes multiple water depth data calculated in the order of ultrasonic data acquisition time.

[0097] The anomaly detection module 303 is used to perform water wading anomaly detection on the vehicle to be tested based on the water depth data set and external environmental data, and obtain the anomaly detection results.

[0098] The result response module 304 is used to adjust the suspension of the vehicle under test to the highest state in response to the abnormal detection result being abnormal, and to send the abnormal detection result to the user's bound mobile device.

[0099] The technical solution of this invention, by acquiring ultrasonic data, vehicle posture data, and external environment data when the user is away from the vehicle, can achieve continuous perception of the water wading situation of the parked vehicle. By calculating a water depth data set based on ultrasonic data and vehicle posture data, it can quantitatively record the change of water depth at the vehicle's location over time. By using the water depth data set and external environment data to detect water wading anomalies, it can achieve trend and environmental judgment of water accumulation risk. By adjusting the suspension to the highest state when the detection result is abnormal, it can temporarily enhance the vehicle's water wading capability. By sending the result to the user's bound mobile device when the detection result is abnormal, it can achieve the effect of remotely notifying the user of water wading risk. This solves the technical problem that the prior art cannot meet the water wading warning needs of vehicles in an unattended parked state, thus realizing the need for water wading warnings for unattended vehicles.

[0100] In some embodiments, in order to perform wading anomaly detection on the vehicle to be tested based on a water depth dataset and external environmental data, and to obtain anomaly detection results, the anomaly detection module 303 is specifically used for:

[0101] Based on the water depth data set, determine the water depth variation gradient of the water depth data set;

[0102] The water depth change gradient is compared with a preset gradient anomaly threshold to determine the water depth detection result;

[0103] Based on external environmental data, determine the environmental testing results of the vehicle to be tested;

[0104] Based on the water depth and environmental monitoring results, abnormal monitoring results were identified.

[0105] In some embodiments, in determining anomaly detection results based on water depth detection results and environmental detection results, the anomaly detection module 303 is specifically used for:

[0106] The water depth detection results and environmental monitoring results are weighted and calculated to obtain a water-related risk score;

[0107] The water-related risk score is compared with a preset risk threshold to determine the abnormal detection results.

[0108] In some embodiments, vehicle posture data includes at least one of the following: suspension height data, tire pressure data, and vehicle angle data.

[0109] In some embodiments, in calculating the water depth data set of the location of the vehicle to be detected based on the ultrasonic data and vehicle posture data, the water depth calculation module 302 is specifically used for:

[0110] Based on the ultrasonic data, calculate the first set of vertical distances between the ultrasonic radar device and the water surface;

[0111] Based on vehicle posture data, determine the second set of vertical distances between the ultrasonic radar device and the ground;

[0112] Based on the first vertical distance set and the second vertical distance set, calculate the water depth data set at the location of the vehicle to be detected.

[0113] In some embodiments, external environment data includes at least one of the following: weather data, geographic location data, and historical flood data.

[0114] In some embodiments, the vehicle wading warning device further includes:

[0115] The monitoring acquisition module is used to acquire real-time monitoring videos of the vehicle to be inspected.

[0116] The monitoring sending module is used to send real-time monitoring videos to the user's bound mobile device.

[0117] The vehicle wading warning device provided in this embodiment of the invention can execute the vehicle wading warning method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the vehicle wading warning method.

[0118] Figure 4 This is a structural schematic diagram of a vehicle wading warning device provided in an embodiment of the present invention.

[0119] like Figure 4As shown, the vehicle wading warning device 400 includes at least one processor 401 and a memory, such as a read-only memory (ROM) 402 and a random access memory (RAM) 403, communicatively connected to the at least one processor 401. The memory stores computer programs executable by the at least one processor. The processor 401 can perform various appropriate actions and processes based on the computer program stored in the ROM 402 or loaded into the RAM 403 from the storage unit 408. The RAM 403 can also store various programs and data required for the operation of the vehicle wading warning device 400. The processor 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 408 is also connected to the bus 404.

[0120] Multiple components in the vehicle wading warning device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard or mouse; an output unit 407, such as various types of displays or speakers; a storage unit 408, such as a disk or optical disk; and a communication unit 409, such as a network card, modem, or wireless transceiver. The communication unit 409 allows the vehicle wading warning device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0121] Processor 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 401 performs the various methods and processes described above, such as vehicle wading warning methods.

[0122] In some embodiments, the vehicle wading warning method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the vehicle wading warning device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by processor 401, one or more steps of the vehicle wading warning method described above may be performed. Alternatively, in other embodiments, processor 401 may be configured to perform the vehicle wading warning method by any other suitable means (e.g., by means of firmware).

[0123] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0124] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0125] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0126] To provide user interaction, the systems and techniques described herein can be implemented on the operational detection device, which includes: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the vehicle wading warning device. Other types of devices can also be used to provide user interaction; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0127] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0128] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability.

[0129] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0130] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A vehicle wading pre-warning method, characterized by, The method comprises: in response to a user of a to-be-detected vehicle being in a state of leaving the vehicle, acquiring a plurality of ultrasonic wave data of an ultrasonic wave radar device in the to-be-detected vehicle, and vehicle posture data and external environment data of the to-be-detected vehicle; calculating a water depth data set of a position where the to-be-detected vehicle is located according to each of the ultrasonic wave data and the vehicle posture data; the water depth data set comprises a plurality of water depth data calculated in sequence according to acquisition times of the ultrasonic wave data; performing wading abnormality detection on the to-be-detected vehicle according to the water depth data set and the external environment data to obtain an abnormality detection result; in response to the abnormality detection result being abnormal, adjusting a suspension of the to-be-detected vehicle to a highest state, and sending the abnormality detection result to a mobile device bound to the user.

2. The method of claim 1, wherein, The performing wading abnormality detection on the to-be-detected vehicle according to the water depth data set and the external environment data to obtain an abnormality detection result comprises: determining a water depth change gradient of the water depth data set according to the water depth data set; comparing the water depth change gradient with a preset gradient abnormality threshold to determine a water depth detection result; determining an environment detection result of the to-be-detected vehicle according to the external environment data; determining an abnormality detection result according to the water depth detection result and the environment detection result.

3. The method of claim 2, wherein, The determining an abnormality detection result according to the water depth detection result and the environment detection result comprises: performing weighted calculation on the water depth detection result and the environment detection result to obtain a wading risk score; comparing the wading risk score with a preset risk threshold to determine the abnormality detection result.

4. The method of claim 1, wherein, The vehicle posture data comprises at least one of suspension height data, tire pressure data, and vehicle angle data.

5. The method of claim 4, wherein, The calculating a water depth data set of a position where the to-be-detected vehicle is located according to each of the ultrasonic wave data and the vehicle posture data comprises: calculating a first vertical distance set between the ultrasonic wave radar device and a water surface according to each of the ultrasonic wave data; determining a second vertical distance set between the ultrasonic wave radar device and the ground according to the vehicle posture data; calculating a water depth data set of a position where the to-be-detected vehicle is located according to the first vertical distance set and the second vertical distance set.

6. The method of claim 1, wherein, The external environment data comprises at least one of weather data, geographical position data, and historical flood data.

7. The method of claim 1, wherein, After the sending the abnormality detection result to the mobile device bound to the user, the method further comprises: acquiring a real-time monitoring video of the to-be-detected vehicle; sending the real-time monitoring video to the mobile device bound to the user.

8. A vehicle wading early warning device, characterized by, The method comprises: a data acquisition module, configured to, in response to a user of a to-be-detected vehicle being in a state of leaving the vehicle, acquire a plurality of ultrasonic wave data of an ultrasonic wave radar device in the to-be-detected vehicle, and vehicle posture data and external environment data of the to-be-detected vehicle; The water depth calculation module is configured to calculate a water depth data set of a position of the vehicle to be detected according to the ultrasonic data and the vehicle posture data, and the water depth data set includes a plurality of water depth data calculated in sequence according to the collection time of the ultrasonic data. The anomaly detection module is configured to perform a wading anomaly detection on the vehicle to be detected according to the water depth data set and the external environment data, and obtain an anomaly detection result. The result response module is configured to adjust a suspension of the vehicle to be detected to a highest state and send the anomaly detection result to the mobile device bound by the user in response to the anomaly detection result being abnormal.

9. A vehicle wading warning apparatus characterized by comprising: The vehicle wading early warning device includes: at least one processor; and a memory connected in communication with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the vehicle wading early warning method in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling the processor to execute the vehicle wading early warning method in any one of claims 1-7 when executed.

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