Security monitoring method and device based on security boundary detection, equipment, medium and program product

Abstract

The embodiment of the invention provides a safety monitoring method and device based on safety boundary detection, equipment, a medium and a program product, and relates to the technical field of vehicle safety monitoring, and the method comprises the steps: obtaining vehicle state information; according to the vehicle state information, judging whether a triggering condition of a safety boundary is reached based on a set rule; if the triggering condition is met, collecting burying point data and sending the burying point data to the cloud platform so as to instruct the cloud platform to perform analysis based on the burying point data; receiving and executing a security risk repair instruction of the cloud platform to complete security monitoring; according to the method, possible risks existing in the automatic driving process are predicted, safety boundary risks are detected and avoided, and safety accidents are avoided.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle safety monitoring, and in particular to a safety monitoring method, device, equipment, medium and program product based on safety boundary detection. Background Art

[0002] The trigger conditions for traditional autonomous driving systems to collect data are when the system processing capacity is insufficient and the driver takes over, or when a safety condition (such as emergency braking) is triggered. This traditional data collection trigger covers limited scenarios, and the collected driving data is limited to a few specific situations. It cannot predict the possible risks in the autonomous driving process, and it cannot quickly accumulate vehicle-side data to support subsequent analysis and technical improvements. It is also impossible to judge safety boundary risks in advance, leading to safety accidents. Summary of the invention

[0003] The purpose of the embodiments of the present application is to provide a safety monitoring method, device, equipment, medium and program product based on safety boundary detection, so as to solve the problem that the existing vehicle monitoring technology cannot predict the possible risks in the automatic driving process and cannot judge the safety boundary risks in advance, leading to the occurrence of safety accidents.

[0004] In a first aspect, an embodiment of the present application provides a security monitoring method based on security boundary detection, including:

[0005] Get vehicle status information;

[0006] According to the vehicle status information, determine whether the triggering conditions of the safety boundary are met based on the set rules;

[0007] If the trigger condition is met, the tracking data is collected and sent to the cloud platform to instruct the cloud platform to perform analysis based on the tracking data;

[0008] Receive and execute security risk remediation instructions from the cloud platform to complete security monitoring.

[0009] In the above implementation process, the vehicle status information is obtained; based on the vehicle status information, it is determined whether the triggering conditions of the safety boundary are met based on the set rules; if the triggering conditions are met, the buried data is collected and sent to the cloud platform to instruct the cloud platform to perform analysis based on the buried data; the cloud platform's security risk repair instructions are received and executed to complete safety monitoring; the possible risks in the autonomous driving process are predicted, and the safety boundary risks are detected and avoided to avoid the occurrence of safety accidents.

[0010] Furthermore, the triggering condition of determining whether the safety boundary is reached based on the set rules includes:

[0011] In the case of autonomous driving, if it is detected that the lateral distance and / or longitudinal distance between the vehicle and surrounding vehicles exceeds the safety boundary, or it is detected that the vehicle has unexpected lateral movement and / or longitudinal movement, it is determined that the vehicle has reached the trigger condition of the safety boundary.

[0012] In the above implementation process, it is ensured that real vehicle data under extreme conditions of autonomous driving can be collected efficiently, the possible collision risks or abnormal driving conditions during the driving of the car can be detected, and alarm information can be provided to the driver in a timely manner.

[0013] Furthermore, the triggering condition of determining whether the safety boundary is reached based on the set rules includes:

[0014] In the case of an unexpected vehicle dynamic behavior classification, it is detected whether the vehicle speed exceeds a safety boundary, wherein the vehicle speed includes lateral acceleration, longitudinal acceleration and jerk.

[0015] In the above implementation process, possible collision risks or abnormal driving conditions that may exist during the driving of the car are detected, and alarm information is provided to the driver in a timely manner.

[0016] Furthermore, the buried data includes but is not limited to: basic vehicle information, vehicle status and dynamic information, driver status and operation information, perception-related information, automatic driving system operation information, instrument and HMI display information, environmental information and new energy information.

[0017] In the above implementation process, real vehicle data is collected more efficiently and specifically, so as to achieve richer data accumulation for potential functions of autonomous driving.

[0018] Furthermore, the collecting of the buried point data and sending the buried point data to the cloud platform to instruct the cloud platform to perform analysis based on the buried point data includes:

[0019] Collect and record buried data;

[0020] The data collection request is sent to the big data collection component through the vehicle-side trigger to trigger the upload of the vehicle's tracking data, instructing the cloud platform to complete scene restoration, problem analysis and risk assessment based on the tracking data, and send instructions for security risk repair and software upgrade.

[0021] In the above implementation process, through real-time monitoring of safety boundary detection and safety monitoring, in the automatic driving state, when the vehicle's driving state exceeds the safety boundary, the vehicle driving data is recorded in time and uploaded to the cloud platform; through the data recording and uploading functions, scene data is accumulated, R&D technical analysis is supported, long-tail problem vulnerabilities are solved, and product safety is improved.

[0022] Furthermore, the vehicle status information includes but is not limited to: radar monitoring signals, automatic driving function status signals, camera signals and vehicle speed signals.

[0023] In the above implementation process, in terms of autonomous driving data collection, real vehicle data can be collected more efficiently and specifically for extreme distance scenarios, thereby achieving richer data accumulation for potential autonomous driving functions.

[0024] In a second aspect, an embodiment of the present application provides a security monitoring device based on security boundary detection, including:

[0025] An information acquisition module, used to acquire vehicle status information;

[0026] A trigger judgment module is used to judge whether the trigger condition of the safety boundary is reached based on the vehicle status information and the set rules;

[0027] The feedback analysis module is used to collect the buried point data and send the buried point data to the cloud platform if the trigger condition is met, so as to instruct the cloud platform to perform analysis based on the buried point data;

[0028] The risk repair module is used to receive and execute security risk repair instructions from the cloud platform to complete security monitoring.

[0029] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0030] A processor, a memory and a bus, wherein the processor is connected to the memory via the bus, and the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, they are used to implement the security monitoring method based on security boundary detection as described above.

[0031] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a server, the security monitoring method based on security boundary detection as described above is implemented.

[0032] In a fifth aspect, an embodiment of the present invention provides a computer program product, which includes instructions, and when the instructions are executed by a computer, the computer implements the security monitoring method based on security boundary detection as described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 A schematic diagram of a flow chart of a security monitoring method based on security boundary detection provided in an embodiment of the present application;

[0035] Figure 2 It is a structural schematic diagram of a security monitoring device based on security boundary detection provided by an embodiment of the present application;

[0036] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0038] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0039] HMI (Human-Machine Interface) is a device and system used for interaction between humans and machines. It allows users to communicate and operate machines through graphical interfaces, touch screens, buttons, sounds, etc.

[0040] NOP (Navigate on Pilot) is an advanced driver assistance system that combines high-precision maps, positioning technology, sensor data and advanced algorithms to enable autonomous navigation and driving of the vehicle.

[0041] OTA (Over-The-Air) is a wireless update technology that allows devices (such as smartphones, tablets, car systems, etc.) to receive and install software updates from a remote server via a wireless network.

[0042] Please see Figure 1 , Figure 1 A schematic diagram of a flow chart of a security monitoring method based on security boundary detection provided in an embodiment of the present application. Figure 1The security monitoring method based on security boundary detection includes:

[0043] 100. Obtain vehicle status information.

[0044] Specifically, the vehicle status information includes but is not limited to: radar monitoring signals (obtaining signals such as the distance to the oncoming vehicle and the relative speed of the oncoming vehicle), automatic driving function status signals (determining whether the automatic driving function is turned on), camera signals and vehicle speed signals (information such as the lateral and longitudinal speeds and accelerations of the vehicle), etc.

[0045] It can be understood that the vehicle status data is collected through the vehicle's sensors and interfaces.

[0046] Among them, radar monitoring signals are obtained through vehicle-mounted radar sensors to provide real-time environmental data. Vehicle-mounted radar sensors monitor the vehicle's surrounding environment by transmitting and receiving radio waves. Radio waves can be used to detect obstacles, vehicles, pedestrians, etc., and measure their distance and speed from the vehicle.

[0047] Among them, the automatic driving function status signal is obtained through on-board sensors, on-board controllers, etc.

[0048] As a result, more scenarios can be covered in terms of autonomous driving data collection, and real vehicle data can be collected more efficiently and specifically for extreme distance scenarios, thereby achieving richer data accumulation for potential autonomous driving functions.

[0049] 200. According to the vehicle status information, determine whether the triggering condition of the safety boundary is reached based on the set rules.

[0050] Specifically, in the case of automatic driving, if it is detected that the lateral distance and / or longitudinal distance between the vehicle and the surrounding vehicles exceeds the safety boundary, or it is detected that the vehicle has unexpected lateral movement and / or longitudinal movement, it is judged that the vehicle has reached the triggering conditions of the safety boundary; thereby ensuring that the real vehicle data under the limit of automatic driving can be collected efficiently, the possible collision risks or abnormal driving conditions during the driving of the car can be detected, and the driver can be provided with alarm information in a timely manner.

[0051] It can be understood that the safety boundary thresholds of the horizontal distance and the vertical distance can be set according to the needs, and the embodiments of the present application do not limit the specific values.

[0052] It should be noted that unexpected lateral and / or longitudinal movement of the vehicle may be caused by movements of the vehicle that are inconsistent with the driver's intention or normal driving state during driving; unexpected lateral movement may include sudden sideslip, vehicle skidding out of control, excessive skidding when turning, etc.; unexpected longitudinal movement may include sudden acceleration or deceleration, instability during braking, or wheel slippage during acceleration.

[0053] Among them, the lateral distance and / or longitudinal distance between the vehicle and the surrounding vehicles exceeds the safety boundary, and the vehicle undergoes unexpected lateral movement and / or longitudinal movement. There are many possible reasons, which may be sensor failure or error, control algorithm limitations, vehicle functional safety issues, system delay and response time, hardware failure, etc.

[0054] Specifically, in the case of unexpected vehicle dynamic behavior classification, it is detected whether the vehicle speed exceeds the safety boundary, where the vehicle speed includes lateral acceleration, longitudinal acceleration and jerk; thereby, the possible collision risk or abnormal driving conditions during the driving of the car are detected, and the driver is provided with warning information in a timely manner.

[0055] Among them, unexpected vehicle dynamic behaviors may include unexpected lateral movement, unexpected loss of lateral movement control, heavy steering without power assistance, unexpected longitudinal movement, unexpected deceleration, unexpected loss of deceleration ability, unexpected brake pedal sinking affecting personnel's operation of the vehicle, etc.

[0056] It is understandable that the lateral acceleration, longitudinal acceleration and jerk can be used to set safety boundary thresholds according to requirements, and the embodiments of the present application do not limit the specific values.

[0057] 300. If the trigger condition is met, the tracking point data is collected and sent to the cloud platform to instruct the cloud platform to perform analysis based on the tracking point data.

[0058] It can be understood that the vehicle establishes a connection with the cloud platform through the on-board communication system (such as 4G / 5G, Wi-Fi, etc.) to ensure the real-time transmission of data, so that the vehicle can upload its own status information, security log and other data to the cloud platform in real time for analysis and monitoring by the cloud platform.

[0059] In some embodiments, the buried data includes but is not limited to: basic vehicle information, vehicle status and dynamic information, driver status and operation information, perception-related information, automatic driving system operation information, instrument and HMI display information, environmental information and new energy information.

[0060] Furthermore, the basic vehicle information may be the vehicle VIN, location, etc.; the vehicle status and dynamic information may be ignition information, etc.; the driver status and operation information may be driver status monitoring information, etc.; the perception-related information may be camera-related video, etc.; the automatic driving system operation information may be the requested steering angle, etc.; the instrument and HMI display information may be DTC-related information, etc.

[0061] In some embodiments, collecting the buried point data and sending the buried point data to the cloud platform to instruct the cloud platform to perform analysis based on the buried point data includes:

[0062] Collect and record buried data.

[0063] The data collection request is sent to the big data collection component through the vehicle-side trigger to trigger the upload of the vehicle's tracking data, instructing the cloud platform to complete scene restoration, problem analysis and risk assessment based on the tracking data, and send instructions for security risk repair and software upgrade.

[0064] As mentioned above, through real-time monitoring of safety boundary detection and safety monitoring, in the state of autonomous driving, when the driving state of the vehicle exceeds the safety boundary, the vehicle driving data is recorded in time and uploaded to the cloud platform; through the data recording and uploading functions, scene data is accumulated, R&D technical analysis is supported, long-tail problem vulnerabilities are solved, and product safety is improved.

[0065] 400. Receive and execute security risk repair instructions from the cloud platform to complete security monitoring.

[0066] Specifically, the vehicle receives security risk repair instructions sent by the cloud platform through the on-board communication system, where the security risk repair instructions may include operations such as updating software, fixing vulnerabilities, and adjusting security policies. After receiving the instructions, the vehicle will verify the instructions to ensure the legality and validity of the instructions.

[0067] Specifically, the vehicle parses the received security risk repair instructions to clarify the specific operation content and steps; according to the parsed instructions, the vehicle performs corresponding operations, such as updating software modules, repairing security vulnerabilities, adjusting security policies, etc., so as to avoid risks. It should be noted that these operations usually need to be performed under the premise of ensuring the normal operation of the vehicle to avoid affecting the normal use of the vehicle; optionally, after executing the security risk repair instructions, the vehicle will feedback the execution results to the cloud platform. The cloud platform evaluates the execution effect of the instructions based on the feedback results and adjusts subsequent security policies accordingly.

[0068] For example, under the NOP function, the lateral deviation distance of the vehicle is greater than the safety boundary, which is used as an example of a dangerous scenario: the safety monitoring detection vehicle-side trigger realizes monitoring based on safety boundary detection by monitoring the L3 function activation status signal and the centerline lateral deviation distance signal. When the L3 function status signal is 1 (activated state) and the centerline lateral deviation distance signal is greater than 0.4m, the safety boundary detection safety monitoring vehicle-side trigger will alarm the driver. At the same time, referring to the rule trigger timestamp identifier as the origin, the vehicle buried data within (-15s, 5s) is stored in the vehicle-side domain controller. When the collected data accumulates to a certain peak value, the trigger data is uploaded and stored in the platform database. The technician pulls the buried data in the database through the cloud platform, completes the scene restoration, risk assessment and problem analysis, and upgrades the vehicle software through OTA after the safety risk is repaired.

[0069] As described above, the embodiments of the present application obtain vehicle status information; determine whether the triggering conditions of the safety boundary are met based on the set rules according to the vehicle status information; if the triggering conditions are met, collect the buried data and send the buried data to the cloud platform to instruct the cloud platform to perform analysis based on the buried data; receive the security risk repair instructions from the cloud platform and execute them to complete security monitoring; predict the possible risks in the autonomous driving process, detect and avoid the safety boundary risks, and avoid the occurrence of safety accidents.

[0070] In terms of autonomous driving data collection, the embodiments of the present application can collect real vehicle data more efficiently and specifically for extreme distance scenarios, thereby achieving richer data accumulation for potential autonomous driving functions. Through real-time monitoring of safety boundary detection and safety monitoring, in the autonomous driving state, when the vehicle's driving state exceeds the safety boundary, the vehicle driving data is recorded in a timely manner and uploaded to the cloud platform to accumulate scene data, support R&D technical analysis, solve long-tail problem vulnerabilities, and improve product safety. It can detect possible collision risks or abnormal driving conditions during the driving of the car, and provide alarm information to the driver in a timely manner. Once an accident occurs, the on-board data is convenient for restoring the accident scene and clarifying the responsibilities of all parties.

[0071] The above steps are not to be performed in a strict order as described in the numbers, but should be understood as an overall solution.

[0072] In the second aspect, based on the above embodiments, Figure 2 A schematic diagram of the structure of a security monitoring device based on security boundary detection provided by an embodiment of the present application. Figure 2 The security monitoring device based on security boundary detection provided in this embodiment specifically includes: an information acquisition module 201, a trigger judgment module 202, a feedback analysis module 204 and a risk repair module 205.

[0073] Among them, the information acquisition module 201 is used to obtain vehicle status information; the trigger judgment module 202 is used to judge whether the trigger condition of the safety boundary is met based on the vehicle status information and the set rules; the feedback analysis module 203 is used to collect the buried data and send the buried data to the cloud platform if the trigger condition is met, so as to instruct the cloud platform to perform analysis based on the buried data; the risk repair module 204 is used to receive and execute the security risk repair instructions of the cloud platform to complete security monitoring.

[0074] As described above, the embodiments of the present application obtain vehicle status information; determine whether the triggering conditions of the safety boundary are met based on the set rules according to the vehicle status information; if the triggering conditions are met, collect the buried data and send the buried data to the cloud platform to instruct the cloud platform to perform analysis based on the buried data; receive the security risk repair instructions from the cloud platform and execute them to complete security monitoring; predict the possible risks in the autonomous driving process, detect and avoid the safety boundary risks, and avoid the occurrence of safety accidents.

[0075] The security monitoring device based on security boundary detection provided in the embodiment of the present application can be used to execute the security monitoring method based on security boundary detection provided in the above embodiment, and has corresponding functions and beneficial effects.

[0076] In a third aspect, an embodiment of the present application further provides an electronic device, which can integrate the security monitoring device based on security boundary detection provided by an embodiment of the present application. Figure 3 Schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Figure 3 The electronic device includes: an input device 43, an output device 44, a memory 42 and one or more processors 41; the memory 42 is used to store one or more programs; when the one or more programs are executed by the one or more processors 41, the one or more processors 41 implement the security monitoring method based on security boundary detection as provided in the above embodiment. The input device 43, the output device 44, the memory 42 and the processor 41 can be connected by a bus or other means. Figure 3 The example of connecting through bus is taken in the following.

[0077] The processor 41 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 42, that is, implements the above-mentioned security monitoring method based on security boundary detection.

[0078] The electronic device provided above can be used to execute the security monitoring method based on security boundary detection provided in the above embodiment, and has corresponding functions and beneficial effects.

[0079] In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the security monitoring method based on security boundary detection as described above, and can achieve the same beneficial effects.

[0080] Of course, the storage medium containing computer executable instructions provided in an embodiment of the present application, whose computer executable instructions are not limited to the security monitoring method based on security boundary detection as described above, can also execute related operations in the security monitoring method based on security boundary detection provided in any embodiment of the present application.

[0081] In a fifth aspect, the embodiments of the present application also provide a computer program product, and the methods described in the various embodiments of the present application can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instruction is loaded and executed on a computer, the processes or functions described in the various embodiments of the present application are executed in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user device, a core network device, an OAM (OpenAplicationModel, open application model) or other programmable device.

[0082] The computer program or instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer program or instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired or wireless means. The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; it may also be an optical medium, such as a digital video disk; it may also be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both volatile and non-volatile types of storage media.

[0083] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0084] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0085] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for an electronic device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0086] The above description is only an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0087] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0088] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

Claims

1. A security monitoring method based on security boundary detection, characterized in that: include: Get vehicle status information; According to the vehicle status information, determine whether the triggering conditions of the safety boundary are met based on the set rules; If the trigger condition is met, the tracking data is collected and sent to the cloud platform to instruct the cloud platform to perform analysis based on the tracking data; Receive and execute security risk remediation instructions from the cloud platform to complete security monitoring.

2. The security monitoring method based on security boundary detection according to claim 1 is characterized in that: The triggering condition of determining whether the safety boundary is reached based on the set rules includes: In the case of autonomous driving, if it is detected that the lateral distance and / or longitudinal distance between the vehicle and surrounding vehicles exceeds the safety boundary, or it is detected that the vehicle has unexpected lateral movement and / or longitudinal movement, it is determined that the vehicle has reached the trigger condition of the safety boundary.

3. The security monitoring method based on security boundary detection according to claim 1 is characterized in that: The triggering condition of determining whether the safety boundary is reached based on the set rules includes: In the case of an unexpected vehicle dynamic behavior classification, it is detected whether the vehicle speed exceeds a safety boundary, wherein the vehicle speed includes lateral acceleration, longitudinal acceleration and jerk.

4. The security monitoring method based on security boundary detection according to claim 1 is characterized in that: The buried data include but are not limited to: basic vehicle information, vehicle status and dynamic information, driver status and operation information, perception-related information, automatic driving system operation information, instrument and HMI display information, environmental information and new energy information.

5. The security monitoring method based on security boundary detection according to claim 1 is characterized in that: The collecting of the buried point data and sending the buried point data to the cloud platform to instruct the cloud platform to perform analysis based on the buried point data includes: Collect and record buried data; The data collection request is sent to the big data collection component through the vehicle-side trigger to trigger the upload of the vehicle's tracking data, instructing the cloud platform to complete scene restoration, problem analysis and risk assessment based on the tracking data, and send instructions for security risk repair and software upgrade.

6. The security monitoring method based on security boundary detection according to claim 1 is characterized in that: The vehicle status information includes but is not limited to: radar monitoring signals, automatic driving function status signals, camera signals and vehicle speed signals.

7. A security monitoring device based on security boundary detection, characterized in that: include: An information acquisition module, used to acquire vehicle status information; A trigger judgment module is used to judge whether the trigger condition of the safety boundary is reached based on the vehicle status information and the set rules; The feedback analysis module is used to collect the buried point data and send the buried point data to the cloud platform if the trigger condition is met, so as to instruct the cloud platform to perform analysis based on the buried point data; The risk repair module is used to receive and execute security risk repair instructions from the cloud platform to complete security monitoring.

8. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the processor is connected to the memory via the bus, and the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, they are used to implement the security monitoring method based on security boundary detection as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the server, the security monitoring method based on security boundary detection as described in any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product comprises instructions, which, when executed by a computer, enable the computer to implement the security monitoring method based on security boundary detection according to any one of claims 1 to 6.

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