Amphibious vehicle water entry safety monitoring method, device, equipment and program product

Abstract

The application discloses an amphibious vehicle water inlet safety monitoring method, device, equipment and program product, comprising: acquiring driving state time series data, water inlet speed time series data and destination driving distance of the amphibious vehicle; predicting the predicted water inlet amount when the amphibious vehicle reaches the destination according to the driving state time series data, the water inlet speed time series data and the destination driving distance; and when the predicted water inlet amount is greater than a preset safe water inlet amount, carrying out return control on the amphibious vehicle. The application realizes accurate prediction of the water inlet amount of the amphibious vehicle, improves the safety and reliability of the amphibious vehicle driving on water, and can be applied to the technical field of amphibious vehicles.

Description

Technical Field

[0001] This invention relates to the field of amphibious vehicle technology, and in particular to a method, device, equipment and program product for monitoring the safety of amphibious vehicles when they are submerged in water. Background Technology

[0002] Amphibious vehicles combine land and water driving capabilities and are widely used in emergency rescue, field exploration, and leisure activities. When a vehicle enters water, gaps can easily appear in the vehicle's sealing structure due to wear, aging, or external impact, leading to a small amount of water entering. If this water ingress is not monitored promptly, as the amount of water increases, it can cause problems such as vehicle weight imbalance, electrical system short circuits, and power system malfunctions, seriously threatening driving safety.

[0003] Current amphibious vehicles mostly employ passive sealing designs for water ingress protection. Some models are equipped with simple water level alarm devices, but these only trigger when the water level reaches a critical threshold. They cannot comprehensively assess safe passage capability based on parameters such as water ingress speed, vehicle speed, and remaining distance, and also lack an active return-to-base control mechanism. When a vehicle experiences a small amount of water ingress in waters far from the shore, the driver may find it difficult to determine whether they can continue to their destination, easily leading to accidents due to misjudgment.

[0004] The above problems urgently need to be addressed. Summary of the Invention

[0005] The purpose of this invention is to at least partially solve one of the technical problems existing in the prior art.

[0006] Therefore, one objective of this invention is to provide a method for monitoring the water ingress safety of amphibious vehicles. This method predicts the predicted water ingress volume when the amphibious vehicle reaches its destination based on the time-series data of the amphibious vehicle's driving status, the time-series data of the water ingress speed, and the distance traveled to the destination. When the predicted water ingress volume is greater than the safe water ingress volume, the method controls the amphibious vehicle to return to its starting point. This achieves accurate prediction of the water ingress volume of the amphibious vehicle and improves the safety and reliability of the amphibious vehicle's waterborne operation.

[0007] Another objective of this invention is to provide a water ingress safety monitoring device for amphibious vehicles.

[0008] To achieve the above-mentioned technical objectives, the technical solutions adopted in the embodiments of the present invention include: On one hand, embodiments of the present invention provide a method for monitoring the safety of amphibious vehicles ingress into water, comprising the following steps: Acquire time-series data on the driving status of amphibious vehicles, time-series data on water ingress speed, and travel distance to the destination; Based on the driving status time series data, the water inflow speed time series data, and the destination driving distance, the predicted water inflow volume when the amphibious vehicle reaches its destination is predicted. When the predicted water inflow exceeds the preset safe water inflow, the amphibious vehicle will be controlled to return to its starting point.

[0009] Furthermore, in one embodiment of the present invention, the acquisition of the amphibious vehicle's driving status time-series data, water ingress speed time-series data, and destination driving distance specifically includes: The driving status timing data is obtained through the CAN bus of the amphibious vehicle; Real-time liquid level values ​​are obtained by installing liquid level sensors in the body compartment of the amphibious vehicle. Real-time water inflow is determined based on the real-time liquid level values ​​and the structure of the body compartment. The water inflow rate time series data is calculated based on the real-time water inflow. The amphibious vehicle's onboard navigation system obtains the distance the amphibious vehicle travels from its current location to the target land location.

[0010] Furthermore, in one embodiment of the present invention, the step of predicting the predicted water inflow when the amphibious vehicle reaches its destination based on the driving status time-series data, the water inflow speed time-series data, and the destination driving distance specifically includes: The predicted remaining travel time is determined based on the driving status time-series data and the destination driving distance; The driving status time series data, the water inflow speed time series data, and the predicted remaining driving time are input into a pre-trained water inflow prediction model to obtain the predicted water inflow.

[0011] Furthermore, in one embodiment of the present invention, the influent flow prediction model is trained through the following steps: Obtain time-series samples of the driving status and water ingress speed of the test vehicle in the first test period under the test scenario, and obtain the actual water ingress volume of the test vehicle in the second test period. The remaining driving time of the sample is determined based on the time interval between the first test period and the second test period; Training samples are determined based on the driving status time series samples, the water inflow speed time series samples, and the remaining driving time of the samples, and corresponding water inflow labels are determined based on the actual water inflow volume. The training samples are input into a pre-constructed two-layer LSTM neural network to obtain the predicted water inflow. The loss value is determined based on the predicted inflow volume and the inflow volume label. The parameters of the two-layer LSTM neural network are updated using the backpropagation algorithm based on the loss value to obtain the trained water inflow prediction model.

[0012] Furthermore, in one embodiment of the present invention, the dual-layer LSTM neural network includes a first LSTM branch, a second LSTM branch, a feature fusion layer, and a fully connected layer. The step of inputting the training samples into the pre-constructed dual-layer LSTM neural network to obtain the predicted water inflow specifically includes: The driving state time sequence sample and the remaining driving time of the sample are input into the first LSTM branch to calculate the hidden state and obtain the first hidden state vector. The inflow velocity time series sample and the remaining driving time of the sample are input into the second LSTM branch to calculate the hidden state and obtain the second hidden state vector. The feature fusion layer performs feature fusion on the first hidden state vector and the second hidden state vector based on a self-attention mechanism to obtain a fused feature vector. The fully connected layer maps the fused feature vector to the predicted inflow value.

[0013] Furthermore, in one embodiment of the present invention, the return-to-base control of the amphibious vehicle specifically includes: The optimal return route is obtained by planning the return route based on the starting position and current position of the amphibious vehicle. The amphibious vehicle is controlled to return to its destination according to the optimal return path, and the real-time water intake of the amphibious vehicle is monitored. When the real-time water inflow reaches the preset drainage threshold, the emergency drainage system is activated to drain the water from the amphibious vehicle.

[0014] On the other hand, embodiments of the present invention provide a water ingress safety monitoring device for amphibious vehicles, comprising: The data acquisition module is used to acquire time-series data of the amphibious vehicle's driving status, water ingress speed, and destination travel distance. The water inflow prediction module is used to predict the water inflow when the amphibious vehicle reaches its destination based on the driving status time-series data, the water inflow speed time-series data, and the destination driving distance. The return-to-base control module is used to control the amphibious vehicle to return to its home position when the predicted water inflow exceeds the preset safe water inflow.

[0015] Furthermore, in one embodiment of the present invention, the return-to-base control of the amphibious vehicle specifically includes: The optimal return route is obtained by planning the return route based on the starting position and current position of the amphibious vehicle. The amphibious vehicle is controlled to return to its destination according to the optimal return path, and the real-time water intake of the amphibious vehicle is monitored. When the real-time water inflow reaches the preset drainage threshold, the emergency drainage system is activated to drain the water from the amphibious vehicle.

[0016] On the other hand, embodiments of the present invention provide an electronic device, including: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the above-described method for monitoring the water ingress safety of an amphibious vehicle.

[0017] On the other hand, embodiments of the present invention also provide a computer-readable storage medium storing a processor-executable computer program that, when executed by a processor, implements the above-described method for monitoring the water ingress safety of an amphibious vehicle.

[0018] On the other hand, embodiments of the present invention also provide a computer program product, including a computer program that, when executed by a processor, implements the above-described method for monitoring the water ingress safety of an amphibious vehicle.

[0019] The advantages and beneficial effects of the present invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention: This invention acquires time-series data of the amphibious vehicle's driving status, water ingress speed, and destination travel distance. Based on these data, it predicts the predicted water ingress volume when the amphibious vehicle reaches its destination. If the predicted water ingress volume exceeds a preset safe water ingress volume, the amphibious vehicle is controlled to return to its starting point. This invention achieves accurate prediction of water ingress volume for amphibious vehicles, improving the safety and reliability of their waterborne operation. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the embodiments of the present invention are described below. It should be understood that the drawings described below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A flowchart illustrating the steps of a water ingress safety monitoring method for amphibious vehicles provided in this embodiment of the invention; Figure 2 This is a structural block diagram of an amphibious vehicle water ingress safety monitoring device provided in an embodiment of the present invention; Figure 3 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In the following description, when referring to the accompanying 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 the embodiments of this invention; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this invention as detailed in the appended claims.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to limit the invention.

[0024] The amphibious vehicle water ingress safety monitoring method provided in this invention can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application that implements the amphibious vehicle water ingress safety monitoring method, but is not limited to the above forms.

[0025] This invention can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0026] It should be noted that in various specific embodiments of the present invention, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user parking space location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of the present invention require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to a confirmation page. Only after obtaining the user's separate permission or consent is the necessary user-related data for the normal operation of the embodiments of the present invention acquired.

[0027] Reference Figure 1 This invention provides a method for monitoring the safety of amphibious vehicles from water ingress, specifically including the following steps: S101. Obtain the driving status time series data, water ingress speed time series data, and destination driving distance of the amphibious vehicle; S102. Based on driving status time series data, water ingress speed time series data and destination driving distance, predict the predicted water ingress volume when the amphibious vehicle reaches the destination. S103. When the predicted water inflow exceeds the preset safe water inflow, the amphibious vehicle shall be controlled to return to its starting point.

[0028] This invention, based on the time-series data of the amphibious vehicle's driving status, the time-series data of the water ingress speed, and the destination travel distance, predicts the predicted water ingress volume when the amphibious vehicle reaches its destination. When the predicted water ingress volume exceeds the safe water ingress volume, the amphibious vehicle is controlled to return to its starting point. This achieves accurate prediction of the water ingress volume of the amphibious vehicle, improving the safety and reliability of the amphibious vehicle's water travel.

[0029] As a further optional implementation, the amphibious vehicle's driving status time-series data, water ingress speed time-series data, and destination travel distance are acquired, specifically including: S1011. Obtain driving status timing data through the CAN bus of the amphibious vehicle; S1012. The real-time liquid level value is obtained by a liquid level sensor installed in the body compartment of the amphibious vehicle. The real-time water inflow is determined based on the real-time liquid level value and the structure of the body compartment. The water inflow speed time series data is calculated based on the real-time water inflow. S1013. Obtain the destination travel distance of the amphibious vehicle from its current location to the target land location through the vehicle's onboard navigation system.

[0030] Specifically, for acquiring driving status time-series data, real-time driving data is collected from the vehicle's CAN bus (Controller Area Network), including propeller speed, rudder angle, and speed in surface mode, generating time-stamped driving status time-series data. For acquiring water ingress speed time-series data, high-precision liquid level sensors and flow sensors are installed in the vehicle's body compartment to monitor the water ingress speed in each area in real time, generating time-stamped water ingress speed time-series data. In addition, environmental data, including water flow speed, wave height, and water depth, can be collected simultaneously as auxiliary reference variables for water ingress speed, used for subsequent correction of the prediction model. For acquiring the destination driving distance, the remaining straight-line distance and actual driving distance from the current location to the destination are obtained through the vehicle navigation system, which facilitates the subsequent calculation of the remaining driving time in combination with the real-time driving status.

[0031] As a further optional implementation, the predicted water inflow volume when the amphibious vehicle reaches its destination is predicted based on driving status time-series data, water inflow speed time-series data, and destination driving distance. Specifically, this includes: S1021. Determine the predicted remaining travel time based on the driving status time series data and the destination travel distance; S1022. Input the driving status time series data, water inflow speed time series data and the predicted remaining driving time into the pre-trained water inflow prediction model to obtain the predicted water inflow.

[0032] Specifically, the amphibious vehicle is simulated based on driving status time series data and destination driving distance to obtain the predicted remaining driving time; the driving status time series data, water ingress speed time series data and the predicted remaining driving time are input into a pre-trained water ingress prediction model to obtain the predicted water ingress.

[0033] As an optional implementation, the influent flow prediction model is trained through the following steps: S201. Obtain the time-series samples of the driving status and water ingress speed of the test vehicle in the first test period under the test scenario, and obtain the actual water ingress volume of the test vehicle in the second test period. S202. Determine the remaining driving time of the sample based on the time interval between the first test period and the second test period; S203. Determine training samples based on driving status time series samples, water inflow speed time series samples, and remaining driving time of the samples, and determine the corresponding water inflow label based on the actual water inflow. S204. Input the training samples into a pre-constructed two-layer LSTM neural network to obtain the predicted water inflow. S205. Determine the loss value based on the predicted inflow rate and the inflow rate label; S206. Update the parameters of the two-layer LSTM neural network according to the loss value through the backpropagation algorithm to obtain the trained water inflow prediction model.

[0034] Specifically, the process involves acquiring time-series samples of the test vehicle's driving status and water ingress speed during the first test period, and obtaining the actual water ingress volume of the test vehicle during the second test period. The remaining driving time of the samples is determined based on the time interval between the first and second test periods. Training samples are determined based on the driving status time-series samples, water ingress speed time-series samples, and the remaining driving time of the samples, and corresponding water ingress volume labels are determined based on the actual water ingress volume. The training samples are input into a pre-constructed two-layer LSTM neural network to obtain predicted water ingress volumes. A loss value is determined based on the predicted water ingress volume and the water ingress volume labels. The parameters of the two-layer LSTM neural network are updated using the backpropagation algorithm based on the loss value, completing one iteration of training. Training stops when the number of iterations reaches a preset threshold or the loss value falls below the preset threshold, thus obtaining a trained water ingress volume prediction model.

[0035] As a further optional implementation, the two-layer LSTM neural network includes a first LSTM branch, a second LSTM branch, a feature fusion layer, and a fully connected layer. By inputting training samples into the pre-constructed two-layer LSTM neural network, a predicted inflow value is obtained, specifically including: S2041. Input the driving state time sequence sample and the remaining driving time of the sample into the first LSTM branch to calculate the hidden state and obtain the first hidden state vector. S2042. Input the water inflow velocity time series sample and the remaining driving time of the sample into the second LSTM branch to calculate the hidden state and obtain the second hidden state vector. S2043. The first hidden state vector and the second hidden state vector are fused by the feature fusion layer based on the self-attention mechanism to obtain the fused feature vector. S2044. The fused feature vector is mapped to the predicted influent volume through a fully connected layer.

[0036] Specifically, the two-layer LSTM neural network includes a first LSTM branch, a second LSTM branch, a feature fusion layer, and a fully connected layer. The first LSTM branch is used to calculate the hidden state of the time-series samples of driving status based on the remaining driving time of the samples to obtain a first hidden state vector. The second LSTM branch is used to calculate the hidden state of the time-series samples of water inflow speed based on the remaining driving time of the samples to obtain a second hidden state vector. The feature fusion layer is used to fuse the first and second hidden state vectors based on a self-attention mechanism to obtain a fused feature vector. The fully connected layer is used to map the fused feature vector to the predicted value of water inflow.

[0037] As a further optional implementation, return control for the amphibious vehicle is implemented, specifically including: S1031. Based on the starting position and current position of the amphibious vehicle, plan the return route to obtain the optimal return route; S1032. Control the amphibious vehicle to return to shore according to the optimal return path, and monitor the real-time water intake of the amphibious vehicle. S1033. When the real-time water inflow reaches the preset drainage threshold, the emergency drainage system is activated to drain water from the amphibious vehicle.

[0038] Specifically, preset safe water ingress thresholds are used for different driving scenarios. For example, the safe water ingress threshold for high-speed driving on water is lower than that for low-speed driving. The corresponding threshold is called according to the current driving state. The predicted water ingress is compared with the safe water ingress threshold. If the predicted water ingress is greater than or equal to the threshold, the return-to-base control process is triggered.

[0039] The system automatically switches vehicle driving modes, prioritizing propeller speed and rudder angle adjustments to plan the shortest return route to the nearest land or docking point. Simultaneously, it sends a return command to the vehicle control system and issues an alert to the driver via the onboard display and voice system, showing predicted water ingress, safety thresholds, and return route information, allowing the driver to manually intervene in control.

[0040] During the return journey, the water ingress will be continuously monitored. If the actual water ingress exceeds the emergency threshold, the emergency drainage system will be activated, and the driving speed will be further reduced to ensure vehicle safety.

[0041] The method steps of the embodiments of the present invention have been described above. It can be understood that the embodiments of the present invention predict the predicted water ingress volume when the amphibious vehicle reaches its destination based on the driving status time-series data of the amphibious vehicle, the water ingress speed time-series data, and the destination driving distance, and control the amphibious vehicle to return when the predicted water ingress volume is greater than the safe water ingress volume, thereby achieving accurate prediction of the water ingress volume of the amphibious vehicle and improving the safety and reliability of the amphibious vehicle's water travel.

[0042] Reference Figure 2 This invention provides a water ingress safety monitoring device for amphibious vehicles, comprising: The data acquisition module is used to acquire time-series data of the amphibious vehicle's driving status, water ingress speed, and destination travel distance. The water inflow prediction module is used to predict the water inflow when the amphibious vehicle reaches its destination based on driving status time-series data, water inflow speed time-series data, and destination driving distance. The return-to-base control module is used to control the amphibious vehicle to return to its home position when the predicted water inflow exceeds the preset safe water inflow.

[0043] As a further optional implementation, return control for the amphibious vehicle is implemented, specifically including: The optimal return route is obtained by planning the return route based on the starting position and current position of the amphibious vehicle. The amphibious vehicle is controlled to return to its destination based on the optimal return path, and the real-time water intake of the amphibious vehicle is monitored. When the real-time water inflow reaches the preset drainage threshold, the emergency drainage system is activated to drain water from the amphibious vehicle.

[0044] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0045] Reference Figure 3This invention provides an electronic device, comprising: At least one processor; At least one memory for storing at least one program; When the above-mentioned at least one program is executed by the above-mentioned at least one processor, the above-mentioned at least one processor implements the above-mentioned method for monitoring the water ingress safety of amphibious vehicles.

[0046] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0047] This invention also provides a computer-readable storage medium storing a processor-executable computer program that, when executed by a processor, implements the above-described method for monitoring the water ingress safety of an amphibious vehicle.

[0048] This invention provides a computer-readable storage medium that can execute a method for monitoring the water ingress safety of an amphibious vehicle provided in the method embodiments of this invention. It can execute any combination of the implementation steps of the method embodiments and has the corresponding functions and beneficial effects of the method.

[0049] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for monitoring the water ingress safety of an amphibious vehicle.

[0050] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0051] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0052] The embodiments described in this invention are for the purpose of more clearly illustrating the technical solutions of the embodiments of this invention, and do not constitute a limitation on the technical solutions provided by the embodiments of this invention. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this invention are also applicable to similar technical problems.

[0053] The terms "first," "second," "third," "fourth," etc. (if present) in the specification 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 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.

[0054] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the aforementioned blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0055] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the aforementioned functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0056] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0057] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0058] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the aforementioned program can be printed, because the aforementioned program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0059] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0060] In the foregoing description of this specification, references to terms such as "one embodiment," "another embodiment," or "some embodiments" indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0061] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0062] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. A method for monitoring the safety of amphibious vehicles ingress into water, characterized in that, Includes the following steps: Acquire time-series data on the driving status of amphibious vehicles, time-series data on water ingress speed, and travel distance to the destination; Based on the driving status time series data, the water inflow speed time series data, and the destination driving distance, the predicted water inflow volume when the amphibious vehicle reaches its destination is predicted. When the predicted water inflow exceeds the preset safe water inflow, the amphibious vehicle will be controlled to return to its starting point.

2. The method for monitoring the safety of amphibious vehicles ingress into water according to claim 1, characterized in that, The acquisition of time-series data on the driving status of the amphibious vehicle, time-series data on the water ingress speed, and the destination driving distance specifically includes: The driving status timing data is obtained through the CAN bus of the amphibious vehicle; Real-time liquid level values ​​are obtained by a liquid level sensor installed in the body compartment of the amphibious vehicle. The real-time water inflow is determined based on the real-time liquid level values ​​and the structure of the body compartment. The water inflow rate time series data is calculated based on the real-time water inflow. The amphibious vehicle's onboard navigation system obtains the distance the amphibious vehicle travels from its current location to the target land location.

3. The method for monitoring water ingress safety of an amphibious vehicle according to claim 1, characterized in that, The step of predicting the predicted water inflow when the amphibious vehicle reaches its destination based on the driving status time-series data, the water inflow speed time-series data, and the destination driving distance specifically includes: The predicted remaining travel time is determined based on the driving status time-series data and the destination driving distance; The driving status time series data, the water inflow speed time series data, and the predicted remaining driving time are input into a pre-trained water inflow prediction model to obtain the predicted water inflow.

4. The method for monitoring water ingress safety of an amphibious vehicle according to claim 3, characterized in that, The inflow prediction model is trained through the following steps: Obtain time-series samples of the driving status and water ingress speed of the test vehicle in the first test period under the test scenario, and obtain the actual water ingress volume of the test vehicle in the second test period. The remaining driving time of the sample is determined based on the time interval between the first test period and the second test period; Training samples are determined based on the driving status time series samples, the water inflow speed time series samples, and the remaining driving time of the samples, and corresponding water inflow labels are determined based on the actual water inflow volume. The training samples are input into a pre-constructed two-layer LSTM neural network to obtain the predicted water inflow. The loss value is determined based on the predicted inflow volume and the inflow volume label. The parameters of the two-layer LSTM neural network are updated using the backpropagation algorithm based on the loss value to obtain the trained water inflow prediction model.

5. A method for monitoring the safety of amphibious vehicles ingress into water, as described in claim 4, is characterized in that... The dual-layer LSTM neural network includes a first LSTM branch, a second LSTM branch, a feature fusion layer, and a fully connected layer. The step of inputting the training samples into the pre-constructed dual-layer LSTM neural network to obtain the predicted water inflow specifically includes: The driving state time sequence sample and the remaining driving time of the sample are input into the first LSTM branch to calculate the hidden state and obtain the first hidden state vector. The inflow velocity time series sample and the remaining driving time of the sample are input into the second LSTM branch to calculate the hidden state and obtain the second hidden state vector. The feature fusion layer performs feature fusion on the first hidden state vector and the second hidden state vector based on a self-attention mechanism to obtain a fused feature vector. The fully connected layer maps the fused feature vector to the predicted inflow value.

6. The method for monitoring the safety of amphibious vehicles ingress into water according to claim 1, characterized in that, The return control of the amphibious vehicle specifically includes: The optimal return route is obtained by planning the return route based on the starting position and current position of the amphibious vehicle. The amphibious vehicle is controlled to return to its destination according to the optimal return path, and the real-time water intake of the amphibious vehicle is monitored. When the real-time water inflow reaches the preset drainage threshold, the emergency drainage system is activated to drain the water from the amphibious vehicle.

7. A water ingress safety monitoring device for amphibious vehicles, characterized in that, include: The data acquisition module is used to acquire time-series data of the amphibious vehicle's driving status, water ingress speed, and destination travel distance. The water inflow prediction module is used to predict the water inflow when the amphibious vehicle reaches its destination based on the driving status time-series data, the water inflow speed time-series data, and the destination driving distance. The return-to-base control module is used to control the amphibious vehicle to return to its home position when the predicted water inflow exceeds the preset safe water inflow.

8. The amphibious vehicle water ingress safety monitoring device according to claim 7, characterized in that, The return control of the amphibious vehicle specifically includes: The optimal return route is obtained by planning the return route based on the starting position and current position of the amphibious vehicle. The amphibious vehicle is controlled to return to its destination according to the optimal return path, and the real-time water intake of the amphibious vehicle is monitored. When the real-time water inflow reaches the preset drainage threshold, the emergency drainage system is activated to drain the water from the amphibious vehicle.

9. An electronic device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a method for monitoring the safety of amphibious vehicle water ingress as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements a method for monitoring the safety of amphibious vehicles inundation as described in any one of claims 1 to 6.

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