Vehicle-cloud collaboration based risk mitigation method, storage medium, and system

Abstract

The present invention relates to the technical field of vehicles. Disclosed are a vehicle-cloud collaboration based risk mitigation method, a storage medium, and a system. The method comprises: in response to a trigger event of a target rule, uploading target data to a safety monitoring platform deployed at the cloud, wherein the target rule is used for determining that a vehicle is in a target risk state; receiving a risk mitigation scheme returned by the safety monitoring platform, wherein the risk mitigation scheme is generated on the basis of risk analysis data, and the risk analysis data is calculated by the safety monitoring platform on the basis of the target data; and performing complete risk mitigation on the vehicle according to the risk mitigation scheme, so that the vehicle gets out of the target risk state. The present invention solves the technical problem of low vehicle safety caused by a single safety monitoring function and a poor risk mitigation ability of the solution of integrating a safety monitoring system inside a vehicle.

Description

Risk repair method, storage medium and system for vehicle-cloud collaboration Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a risk repair method, storage medium, and system for vehicle-cloud collaboration. Background Art

[0002] As vehicles become more intelligent, electrified, connected, and shared, the need for vehicle safety is becoming increasingly important. In practical applications, safety monitoring systems monitor the safe operating status of vehicles in real time and collect safety-related data. The accumulated safety scenario data can aid in vehicle product development and improve vehicle safety. Furthermore, safety monitoring systems can provide rapid analysis and response services when a safety incident is detected, reconstructing the accident scene to assist in determining responsibility and providing quick assistance to users.

[0003] However, the security monitoring systems provided in related technologies are typically integrated within vehicles. Due to limitations in the vehicle's computing power and storage resources, these systems often struggle to meet the aforementioned functional requirements for security monitoring systems in specific application scenarios. In other words, existing security monitoring systems integrated within vehicles struggle to meet the functional requirements for real-time vehicle safety monitoring in specific application scenarios, resulting in lower vehicle safety.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far.

[0005] Summary of the Invention

[0006] An embodiment of the present invention provides a vehicle-cloud collaborative risk repair method, storage medium, and system to at least solve the technical problem that the solution of integrating the safety monitoring system inside the vehicle has a single safety monitoring function and poor risk repair capability, resulting in low vehicle safety.

[0007] According to one aspect of an embodiment of the present invention, a risk repair method for vehicle-cloud collaboration is provided, comprising: in response to a triggering event of a target rule, uploading target data to a security monitoring platform deployed on the cloud, wherein the target rule is used to determine whether the vehicle is in a target risk state; receiving a risk repair plan returned by the security monitoring platform, wherein the risk repair plan is generated based on risk analysis data, and the risk analysis data is calculated by the security monitoring platform based on the target data; and performing risk repair on the entire vehicle according to the risk repair plan to enable the vehicle to escape the target risk state.

[0008] Optionally, the target rule includes at least: the vehicle's passive safety component sends a collision signal; the vehicle's lateral acceleration is greater than a first threshold and the lateral acceleration duration is greater than a second threshold; the vehicle's positioning data is lost for a duration greater than a third threshold.

[0009] Optionally, the target data includes vehicle safety data within a target duration corresponding to the triggering event, and the vehicle safety data includes bus data, perception data, and audio and video acquisition data.

[0010] According to another aspect of an embodiment of the present invention, a vehicle-cloud collaborative risk repair method is also provided, which runs on a security monitoring platform deployed on the cloud. The risk repair method includes: receiving target data uploaded by the vehicle, wherein the target data is uploaded by a trigger event of the vehicle to a target rule, and the target rule is used to determine whether the vehicle is in a target risk state; performing risk analysis and calculation on the target data to obtain risk analysis data; generating a risk repair plan based on the risk analysis data, wherein the risk repair plan is used to control the vehicle to leave the target risk state; and returning the risk repair plan to the vehicle to assist the vehicle in performing risk repair of the entire vehicle.

[0011] Optionally, performing risk analysis calculations on the target data to obtain risk analysis data includes at least one of the following: performing risk assessment calculations on the target data to obtain risk assessment data in the risk analysis data; performing risk scenario restoration calculations on the target data to obtain scenario restoration data in the risk analysis data; performing accident analysis on the target data to obtain accident analysis data in the risk analysis data.

[0012] Optionally, generating a risk repair plan based on the risk analysis data includes: obtaining a risk repair strategy corresponding to the target rule; and generating a risk repair plan based on the risk analysis data and the risk repair strategy.

[0013] Optionally, the risk repair method further includes: storing the target data in a safety scenario database corresponding to the vehicle.

[0014] According to another aspect of an embodiment of the present invention, a risk repair method for vehicle-cloud collaboration is also provided, in which an operation interface is provided through a cloud device, and the display content of the operation interface includes at least a functional safety real-time monitoring scenario of the vehicle, and communication is established between the vehicle and the cloud device. The risk repair method includes: responding to a first control operation of the risk monitoring component in the functional safety real-time monitoring scenario, receiving target data uploaded by the vehicle, and displaying monitoring information in the operation interface based on the target data, wherein the monitoring information includes map information and chart information, wherein the target data is uploaded by a trigger event of the vehicle to a target rule, and the target rule is used to determine whether the vehicle is in a target risk state; responding to a second control operation of the risk analysis component in the functional safety real-time monitoring scenario, performing risk analysis calculation on the target data to obtain risk analysis data, wherein the risk repair plan is used to control the vehicle to leave the target risk state; generating a risk repair plan based on the risk analysis data, and returning the risk repair plan to the vehicle to assist the vehicle in performing whole-machine risk repair.

[0015] Optionally, the risk repair method also includes: responding to a third control operation acting on a query component in a functional safety real-time monitoring scenario, obtaining a target index item, querying the vehicle's scene safety database according to the target index item to obtain target query data, and displaying a query chart in an operation interface based on the target query data; responding to a fourth control operation acting on a scene restoration component in a functional safety real-time monitoring scenario, performing risk scenario restoration calculation on the target data to obtain scene restoration data, generating a scene playback video based on the scene restoration data, and displaying the scene playback video in the operation interface.

[0016] According to another aspect of an embodiment of the present invention, a vehicle-cloud collaborative risk repair device is provided, including: an upload module for uploading target data to a security monitoring platform deployed on the cloud in response to a triggering event of a target rule, wherein the target rule is used to determine whether the vehicle is in a target risk state; a receiving module for receiving a risk repair plan returned by the security monitoring platform, wherein the risk repair plan is generated based on risk analysis data, and the risk analysis data is calculated by the security monitoring platform based on the target data; a repair module for performing risk repair on the entire vehicle according to the risk repair plan to enable the vehicle to escape from the target risk state.

[0017] Optionally, in the above-mentioned vehicle-cloud collaborative risk repair device, the target rules include at least: the vehicle's passive safety components send a collision signal; the vehicle's lateral acceleration is greater than a first threshold and the lateral acceleration duration is greater than a second threshold; the vehicle's positioning data is lost for a duration greater than a third threshold.

[0018] Optionally, in the above-mentioned vehicle-cloud collaborative risk repair device, the target data includes vehicle safety data within the target time range corresponding to the triggering event, and the vehicle safety data includes: bus data, perception data and audio and video acquisition data.

[0019] According to another aspect of an embodiment of the present invention, a vehicle-cloud collaborative risk repair device is provided, which is arranged in a security monitoring platform deployed on the cloud. The vehicle-cloud collaborative risk repair device includes: a receiving module for receiving target data uploaded by a vehicle, wherein the target data is uploaded by a trigger event of the vehicle to a target rule, and the target rule is used to determine whether the vehicle is in a target risk state; a calculation module for performing risk analysis calculation on the target data to obtain risk analysis data; a generation module for generating a risk repair plan based on the risk analysis data, wherein the risk repair plan is used to control the vehicle to leave the target risk state; and a return module for returning the risk repair plan to the vehicle to assist the vehicle in performing whole-machine risk repair.

[0020] Optionally, the above-mentioned calculation module is also used to: perform risk assessment calculation on the target data to obtain risk assessment data in the risk analysis data; perform risk scenario restoration calculation on the target data to obtain scenario restoration data in the risk analysis data; perform accident analysis on the target data to obtain accident analysis data in the risk analysis data.

[0021] Optionally, the above-mentioned generation module is further used to: obtain the risk repair strategy corresponding to the target rule; and generate a risk repair plan based on the risk analysis data and the risk repair strategy.

[0022] Optionally, the above-mentioned vehicle-cloud collaborative risk repair device also includes a storage module for storing target data in a safety scenario database corresponding to the vehicle.

[0023] According to another aspect of an embodiment of the present invention, a risk repair device for vehicle-cloud collaboration is provided, in which an operation interface is provided by a cloud device, and the display content of the operation interface includes at least a functional safety real-time monitoring scenario of the vehicle, and a communication association is established between the vehicle and the cloud device. The device includes: a first control module, which is used to respond to a first control operation of the risk monitoring component in the functional safety real-time monitoring scenario, receive target data uploaded by the vehicle, and display monitoring information in the operation interface based on the target data, wherein the monitoring information includes map information and chart information, wherein the target data is uploaded by a trigger event of the vehicle to a target rule, and the target rule is used to determine whether the vehicle is in a target risk state; a second control module, which is used to respond to a second control operation of the risk analysis component in the functional safety real-time monitoring scenario, perform risk analysis calculations on the target data, and obtain risk analysis data, wherein the risk repair plan is used to control the vehicle to leave the target risk state; a repair module, which is used to generate a risk repair plan based on the risk analysis data, and return the risk repair plan to the vehicle to assist the vehicle in performing whole-machine risk repair.

[0024] Optionally, the above-mentioned vehicle-cloud collaborative risk repair device also includes a third control module, which is used to: respond to the third control operation of the query component in the functional safety real-time monitoring scenario, obtain the target index item, obtain the target query data from the vehicle's scene safety database according to the target index item, and display the query chart in the operation interface based on the target query data; respond to the fourth control operation of the scene restoration component in the functional safety real-time monitoring scenario, perform risk scenario restoration calculation on the target data, obtain scene restoration data, generate a scene playback video based on the scene restoration data, and display the scene playback video in the operation interface.

[0025] According to another aspect of an embodiment of the present invention, a storage medium is also provided, which includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute any one of the above-mentioned vehicle-cloud collaboration risk repair methods.

[0026] According to another aspect of an embodiment of the present invention, a vehicle-cloud collaborative risk repair system is also provided, comprising: a vehicle and a safety monitoring platform, wherein the vehicle comprises an on-board memory and an on-board processor, a computer program is stored in the on-board memory, and the on-board processor is configured to run the computer program to execute any one of the methods of claims 1 to 3; the safety monitoring platform is deployed on a cloud server, and the safety monitoring platform is used to execute any one of the methods of claims 4 to 8.

[0027] In an embodiment of the present invention, in response to a triggering event of a target rule, target data is uploaded to a security monitoring platform deployed in the cloud, wherein the target rule is used to determine whether the vehicle is in a target risk state; a risk repair plan returned by the security monitoring platform is received, wherein the risk repair plan is generated based on risk analysis data, and the risk analysis data is calculated by the security monitoring platform based on the target data; and the vehicle is subjected to risk repair for the entire vehicle according to the risk repair plan, so that the vehicle is out of the target risk state. Thus, the present invention achieves the purpose of achieving real-time cloud-based monitoring and risk repair of vehicle safety characteristics through vehicle-cloud collaboration, thereby achieving the technical effect of enriching vehicle safety monitoring functions, enhancing risk repair capabilities, and improving vehicle safety, thereby solving the technical problem of low vehicle safety caused by the solution of integrating the safety monitoring system inside the vehicle, which has a single safety monitoring function and poor risk repair capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0029] FIG1 is a hardware structure block diagram of a vehicle terminal according to an optional risk repair method for vehicle-cloud collaboration according to an embodiment of the present invention;

[0030] FIG2 is a flow chart of a risk repair method for vehicle-cloud collaboration according to an embodiment of the present invention;

[0031] FIG3 is a flowchart of another risk repair method for vehicle-cloud collaboration according to an embodiment of the present invention;

[0032] FIG4 is a schematic diagram of an optional risk repair process of vehicle-cloud collaboration according to an embodiment of the present invention;

[0033] FIG5 is a flowchart of another risk repair method for vehicle-cloud collaboration according to an embodiment of the present invention;

[0034] FIG6 is a schematic diagram of an optional operation interface according to an embodiment of the present invention;

[0035] FIG7 is a schematic diagram of another optional operation interface according to an embodiment of the present invention;

[0036] FIG8 is a schematic diagram of another optional operation interface according to an embodiment of the present invention;

[0037] FIG9 is a structural block diagram of a risk repair device for vehicle-cloud collaboration according to an embodiment of the present invention;

[0038] FIG10 is a structural block diagram of another vehicle-cloud collaborative risk repair device according to an embodiment of the present invention;

[0039] FIG11 is a structural block diagram of another vehicle-cloud collaborative risk repair device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0041] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0042] According to an embodiment of the present invention, a method embodiment of a risk repair method for vehicle-cloud collaboration is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0043] FIG1 is a block diagram of the hardware structure of a vehicle terminal for an optional risk repair method for vehicle-cloud collaboration according to an embodiment of the present invention. As shown in FIG1 , the vehicle terminal (or a mobile device having a communication association with the vehicle) may include one or more processors 102 (the processor 102 may include but is not limited to a processing device such as a microcontroller unit (MCU) or a programmable logic device (Field Programmable Gate Array, FPGA)), a memory 104 configured to store data, and a transmission device 106 configured to implement a communication function. In addition, it may also include: a display device 110, an input and output device 108, a universal serial bus (USB) port (which may be included as one of the ports of a computer bus, not shown in the figure), a network interface (not shown in the figure), a power supply (not shown in the figure) and / or a camera (not shown in the figure). It will be understood by those skilled in the art that the structure shown in FIG1 is merely illustrative and does not limit the structure of the above-mentioned vehicle terminal. For example, the vehicle terminal may also include more or fewer components than those shown in FIG1 , or have a configuration different from that shown in FIG1 .

[0044] It should be noted that the one or more processors 102 and / or other data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuit may be a single independent processing module, or may be fully or partially integrated into any of the other components in the vehicle terminal (or mobile device).

[0045] The memory 104 can be configured to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the vehicle-cloud collaborative risk repair method in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, to implement the above-mentioned vehicle-cloud collaborative risk repair method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely located relative to the processor 102, and these remote memories may be connected to the vehicle terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0046] The transmission device 106 is configured to receive or transmit data via a network. A specific example of such a network may include a wireless network provided by a communications provider of the vehicle terminal. In one embodiment, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device 106 may be a radio frequency (RF) module configured to communicate with the Internet wirelessly.

[0047] In the above operating environment, an embodiment of the present invention provides a risk repair method for vehicle-cloud collaboration as shown in FIG2 . FIG2 is a flow chart of a risk repair method for vehicle-cloud collaboration according to an embodiment of the present invention. As shown in FIG2 , the method includes the following implementation steps:

[0048] Step S201, in response to a triggering event of a target rule, uploading target data to a security monitoring platform deployed in the cloud, wherein the target rule is used to determine whether the vehicle is in a target risk state;

[0049] Step S202: receiving a risk remediation plan returned by the security monitoring platform, wherein the risk remediation plan is generated based on risk analysis data, which is calculated by the security monitoring platform based on target data;

[0050] Step S203: Perform risk repair on the entire vehicle according to the risk repair plan to remove the vehicle from the target risk state.

[0051] In this application scenario, multiple safety feature data of the vehicle is monitored in real time to determine whether the vehicle has triggered the target rules. When the vehicle triggers at least one of the target rules, the vehicle is considered to be in the target risk state corresponding to the rule triggered by the vehicle.

[0052] Considering the inherent computing resource limitations of vehicles, when a vehicle triggers a target rule, the target data is uploaded to a cloud-based security monitoring platform for processing, improving data processing efficiency and enriching vehicle safety monitoring capabilities. Furthermore, the aforementioned real-time monitoring of multiple vehicle safety feature data can also be performed by the security monitoring platform.

[0053] In this application scenario, when a vehicle is in a target risk state, the safety monitoring platform will quickly respond to the vehicle, performing risk analysis and generating a remediation plan based on the vehicle's current target data. Furthermore, the safety monitoring platform can transmit the remediation plan back to the vehicle through real-time online channels for risk remediation.

[0054] Optionally, the target rule includes at least: the vehicle's passive safety component sends a collision signal; the vehicle's lateral acceleration is greater than a first threshold and the lateral acceleration duration is greater than a second threshold; the vehicle's positioning data is lost for a duration greater than a third threshold.

[0055] In application scenarios, target rules can be specified based on scenario requirements. For example, a target rule might include a collision signal from a vehicle's passive safety components (such as airbags). Based on this, the airbag data is monitored in real time. When a vehicle crashes, the airbag's collision signal is set, triggering the rule.

[0056] For example, a target rule might include: the vehicle's lateral acceleration exceeds a first threshold and the duration of lateral acceleration exceeds a second threshold. Based on this, the system monitors the vehicle's lateral acceleration data in real time. When the vehicle's lateral acceleration exceeds 0.3g (g represents the acceleration due to gravity) and the duration of lateral acceleration exceeds 200 milliseconds, the vehicle is considered to be in a risky state, triggering the vehicle dynamic behavior rule.

[0057] For example, a target rule might include the following: If a vehicle's positioning data (such as high-precision positioning data) is lost for longer than a third threshold, the vehicle's high-precision positioning is monitored in real time. If the vehicle's high-precision positioning data is lost for more than 20 seconds, the vehicle is considered at risk, triggering the vehicle loss rule.

[0058] In the application scenario, some exemplary target rules are also provided, including vehicle-side post-recording rules and vehicle-side pre-prediction rules. Vehicle-side post-recording rules include: collision detection rules, body stability system activation rules, minimum risk control rules, driver takeover wake-up protection rules (such as behavior detection when the driver does not have the ability to take over), battery thermal runaway rules, four-door and two-lid release rules during movement, safety boundary rules, override rules (such as steering wheel override, accelerator pedal override, brake pedal override, etc.), unexpected vehicle dynamic behavior rules (such as lateral and longitudinal acceleration boundaries, etc.), and safety fault rules. Vehicle-side pre-prediction rules include: traffic rules (such as speeding, etc.), hazard identification and risk perception rules (such as abnormal jumps in target detection, continuous loss of high-precision positioning signals, etc.), and safety pre-trigger event activation rules (such as warning function triggering, automatic driving warning faults, etc.).

[0059] In application scenarios, the above-mentioned target rules may also include system failure rules, automatic driving parking rules, etc., which are not limited by the present invention.

[0060] Optionally, the target data includes vehicle safety data within a target duration corresponding to the triggering event, and the vehicle safety data includes bus data, perception data, and audio and video acquisition data.

[0061] In the application scenario, when a vehicle triggers a target rule, the target data uploaded to the security monitoring platform includes the vehicle's safety characteristic data within the time range of 15 seconds before and 15 seconds after the trigger (a total of 30 seconds). For example, safety characteristic data includes bus data of some vehicle buses, raw perception data, intermediate perception data, and audio and video acquisition data.

[0062] In an embodiment of the present invention, in response to a triggering event of a target rule, target data is uploaded to a security monitoring platform deployed in the cloud, wherein the target rule is used to determine whether the vehicle is in a target risk state; a risk repair plan returned by the security monitoring platform is received, wherein the risk repair plan is generated based on risk analysis data, and the risk analysis data is calculated by the security monitoring platform based on the target data; and the vehicle is subjected to risk repair for the entire vehicle according to the risk repair plan, so that the vehicle is out of the target risk state. Thus, the present invention achieves the purpose of achieving real-time cloud-based monitoring and risk repair of vehicle safety characteristics through vehicle-cloud collaboration, thereby achieving the technical effect of enriching vehicle safety monitoring functions, enhancing risk repair capabilities, and improving vehicle safety, thereby solving the technical problem of low vehicle safety caused by the solution of integrating the safety monitoring system inside the vehicle, which has a single safety monitoring function and poor risk repair capabilities.

[0063] Compared to the above-mentioned risk repair method for vehicle-cloud collaboration implemented on a vehicle terminal, an embodiment of the present invention further provides a risk repair method for vehicle-cloud collaboration running on a security monitoring platform deployed on the cloud. FIG4 is a flow chart of another risk repair method for vehicle-cloud collaboration according to an embodiment of the present invention. As shown in FIG4 , the method includes the following implementation steps:

[0064] Step S301: receiving target data uploaded by a vehicle, wherein the target data is uploaded by a triggering event of a target rule by the vehicle, and the target rule is used to determine whether the vehicle is in a target risk state;

[0065] Step S302, performing risk analysis calculation on the target data to obtain risk analysis data;

[0066] Step S303: generating a risk restoration plan based on the risk analysis data, wherein the risk restoration plan is used to control the vehicle to escape from the target risk state;

[0067] Step S304: Return the risk repair plan to the vehicle to assist the vehicle in performing risk repair on the entire vehicle.

[0068] Based on the above implementation steps, vehicle safety is monitored and remediated in real time according to the vehicle-cloud collaborative risk remediation process shown in Figure 4. Specifically, as shown in Figure 4, the implementation architecture corresponding to the risk remediation process includes: a vehicle, a target rule component (a memory for storing target rules or a processor for detecting vehicle status according to the target stored rules), a vehicle data package, a security monitoring platform deployed in the cloud, a security scenario database, a security risk remediation component, and an over-the-air (OTA) upgrade channel.

[0069] When a vehicle is detected triggering a target rule, the security monitoring platform receives target data (i.e., vehicle data) uploaded by the vehicle. For example, the target data includes: bus data of some vehicle buses, perception raw data, perception intermediate data, and audio and video acquisition data.

[0070] Optionally, in step S302, performing risk analysis calculation on the target data to obtain risk analysis data may further include at least one of the following execution steps:

[0071] Step S321, performing risk assessment calculation on the target data to obtain risk assessment data in the risk analysis data;

[0072] Step S322: Perform risk scenario restoration calculation on the target data to obtain scenario restoration data in the risk analysis data;

[0073] Step S323: perform accident analysis on the target data to obtain accident analysis data in the risk analysis data.

[0074] Furthermore, as shown in Figure 4, the security monitoring platform performs risk analysis and calculations based on the target data. The risk analysis and calculations include at least risk assessment, scenario restoration, and problem analysis. Accordingly, the resulting risk analysis data includes at least risk assessment data, scenario restoration data, and accident analysis data.

[0075] Optionally, the above-mentioned vehicle-cloud collaboration risk repair method may further include the following method steps:

[0076] Step S305: storing the target data in a safety scenario database corresponding to the vehicle.

[0077] Still as shown in FIG4 , the safety monitoring platform can also store the target data in a safety scenario database corresponding to the vehicle. This safety scenario database can correspond to the vehicle model. Furthermore, the safety monitoring platform can also store the calculated risk analysis data (including at least risk assessment data, scenario reconstruction data, and accident analysis data) in real time in the safety scenario database.

[0078] In vehicle safety monitoring scenarios, the safety scenario database will accumulate and store historical vehicle safety data, historical risk analysis data, and historical risk remediation data for the corresponding vehicle or model. This safety scenario database can be used to assist vehicle developers in optimizing and improving vehicles or models, thereby enhancing system safety and stability.

[0079] Optionally, in step S303 above, generating a risk remediation plan based on the risk analysis data may further include the following execution steps:

[0080] Step S331, obtaining the risk repair strategy corresponding to the target rule;

[0081] Step S332: Generate a risk repair plan based on the risk analysis data and the risk repair strategy.

[0082] After the safety monitoring platform calculates and analyzes the risk analysis data as described in Figure 4, it can also obtain the risk remediation strategy corresponding to the target rule from the candidate remediation strategies in the safety scenario database. This risk remediation strategy can be for all target rules or for some of the rules currently triggered by the vehicle.

[0083] In an embodiment of the present invention, target data uploaded by a vehicle is received, wherein the target data is uploaded by a trigger event of the vehicle to a target rule, and the target rule is used to determine whether the vehicle is in a target risk state; a risk analysis calculation is performed on the target data to obtain risk analysis data; a risk repair plan is generated based on the risk analysis data, wherein the risk repair plan is used to control the vehicle from the target risk state; and the risk repair plan is returned to the vehicle to assist the vehicle in performing risk repair on the entire vehicle. Thus, the present invention achieves the purpose of achieving real-time cloud-based monitoring and risk repair of vehicle safety characteristics through vehicle-cloud collaboration, thereby achieving the technical effect of enriching vehicle safety monitoring functions, enhancing risk repair capabilities, and improving vehicle safety, thereby solving the technical problem of low vehicle safety caused by the solution of integrating the safety monitoring system inside the vehicle, which has a single safety monitoring function and poor risk repair capabilities.

[0084] In addition, as still shown in FIG4 , the security monitoring platform can also display target data and / or vehicle events, and can also support functions such as data download, data-based scene restoration, restored video playback and download, problem analysis, and statistics.

[0085] In application scenarios, vehicle developers can conduct development and analysis based on data from the security scenario database associated with the security monitoring platform. This data can be evaluated to determine whether vehicle risks are reasonable. Emergency response mechanisms can be activated, and over-the-air (OTA) upgrades can be used to suppress certain vehicle functions to improve safety and avoid significant losses (such as loss of life and property for users, and loss of reputation for automakers). Furthermore, the data accumulated in the security scenario database can be used to iteratively update vehicle safety product defects, improving product safety.

[0086] For example, the formulation of vehicle-side target rules is illustrated as follows. In a certain scenario, the target rules include the following three items.

[0087] Rule SR01 (also known as Rule ID): Category: Delayed Action; The rule describes that in Level 3 autonomous driving, based on signals from passive safety systems (such as airbags), a collision is determined. Vehicle-side signals monitored for this rule include the Level 3 function activation status signal and the airbag collision signal. The rule is triggered when the Level 3 function activation status signal is active and the airbag collision signal is crashed. The output data packet of this rule is the first data packet. The first data packet includes all vehicle data (point cloud data, video data, bus data, etc.).

[0088] Rule SR02: Category is hysteresis measure; the rule description is that in L3 level autonomous driving, the vehicle's lateral acceleration exceeds 0.3g and lasts for more than 200ms; the vehicle-side signals considered for monitoring for this rule include the L3 function activation status signal, the vehicle's lateral acceleration signal, and the timer signal; when the signal value of the L3 function activation status signal is active, the signal value of the vehicle's lateral acceleration signal is greater than 0.3g, and the timer signal value exceeds 200ms, the rule is determined to be triggered; the output data packet of this rule is the first data packet.

[0089] Rule SR03: Category: Pre-emptive measures; description: During L3 autonomous driving, the vehicle's high-precision positioning data is lost for more than 20 seconds. Vehicle-side signals monitored for this rule include the L3 function activation status signal, the high-precision positioning signal, and the timer signal. The rule is triggered when the L3 function activation status signal value is active, the high-precision positioning signal is lost, and the timer signal value exceeds 20 seconds. The output data packet of this rule is the second data packet. The second data packet contains the vehicle's positioning anomaly data.

[0090] As described above, for each target rule, set the monitoring object, rule triggering logic and data packet corresponding to the rule.

[0091] In an exemplary application scenario, a data structure as shown in Table 1 below is proposed, which includes a data packet sequence number, a data category, and data content.

[0092] Table 1

[0093] According to Table 1 above, when the vehicle triggers rules SR01 and SR02, the data packet uploaded by the vehicle is data packet No. 1 in Table 1. When the vehicle triggers rule SR03, the data packet uploaded by the vehicle is data packet No. 7 in Table 1.

[0094] In summary, considering that current vehicle-cloud collaboration systems typically employ solutions such as shadow mode and driver data analysis, these solutions primarily support vehicle development and do not involve analyzing and monitoring vehicle safety features. This invention proposes a safety monitoring solution based on vehicle-cloud collaboration that can monitor vehicle safety in real time, accumulate safety scenario data to assist in the development of vehicle safety features, conduct real-time vehicle safety assessments, and rapidly respond to and restore vehicle safety incidents, facilitating public opinion control and responsibility determination for vehicle safety incidents.

[0095] Based on the above-mentioned vehicle-cloud collaborative risk remediation method running on a security monitoring platform deployed in the cloud, an embodiment of the present invention further provides a visualization scheme for the vehicle-cloud collaborative risk remediation method. FIG5 is a flowchart of another vehicle-cloud collaborative risk remediation method according to an embodiment of the present invention. An operation interface is provided by a cloud device. The display content of the operation interface includes at least a real-time monitoring scenario of the functional safety of the vehicle. The vehicle and the cloud device communicate with each other. As shown in FIG5, the method includes the following implementation steps:

[0096] Step S501, in response to a first control operation acting on a risk monitoring component in a functional safety real-time monitoring scenario, receiving target data uploaded by a vehicle, and displaying monitoring information in an operation interface based on the target data, the monitoring information including map information and chart information, wherein the target data is uploaded by a triggering event of a target rule by the vehicle, and the target rule is used to determine whether the vehicle is in a target risk state;

[0097] Step S502 , in response to a second control operation acting on the risk analysis component in the functional safety real-time monitoring scenario, performing risk analysis calculation on the target data to obtain risk analysis data, wherein a risk remediation solution is used to control the vehicle to escape from the target risk state;

[0098] Step S503: Generate a risk repair plan based on the risk analysis data, and return the risk repair plan to the vehicle to assist the vehicle in performing risk repair on the entire vehicle.

[0099] According to the above implementation steps, an operation interface as shown in Figure 6 is provided for the cloud-based security monitoring platform. This operation interface displays the graphical user interface of the functional safety risk monitoring platform. The risk monitoring component can be a component used to trigger the acquisition of target data uploaded by the vehicle. In an application scenario, the functional safety risk monitoring platform can continuously monitor the safety of the vehicle in real time. Therefore, the target data uploaded by the vehicle can be received periodically after the real-time safety monitoring is triggered by the first control operation.

[0100] In addition, as shown in Figure 6, the operation interface also includes four sub-functions: "Risk Monitoring", "Risk Analysis", "Historical Query" and "Scenario Playback".

[0101] When implementing the risk monitoring sub-function, the risk events uploaded by the vehicle are displayed as a whole on the operation interface. The displayed information includes the chart part of the map part. The map part is centered on the vehicle position, and the monitoring points are divided into two categories according to color: green monitoring points represent preceding events, and red monitoring points represent lagging events.

[0102] Furthermore, by clicking a monitoring point on the map displayed within the operation interface, a window such as Figure 7 pops up. The window displays information including the vehicle number, time, location, event type, and function buttons (such as data details, scene playback, and data download). Clicking a function button within the window jumps to the corresponding interface.

[0103] The chart portion of the risk monitoring sub-function's display content may include multiple charts, which surround the map portion. These charts may include pie charts, line charts, bar charts, waterfall charts, heat maps, bubble charts, and other chart types. These multiple charts are used to display the real-time safety statistics of all vehicles monitored by the safety monitoring platform.

[0104] When implementing the risk analysis sub-function, the target data uploaded to the cloud is extracted. If a failure event is reported in a key vehicle system (such as the steering system, braking system, powertrain, etc.) when the target rule is triggered, the relationship between the failure and the corresponding target rule, as well as the trend of the failure occurrence, are statistically analyzed. Furthermore, the number, frequency, and trend of target rule triggers can be analyzed, and the results can be used to assist in vehicle risk management.

[0105] Optionally, the above-mentioned vehicle-cloud collaboration risk repair method may further include the following method steps:

[0106] Step S504, in response to the third control operation acting on the query component in the functional safety real-time monitoring scenario, obtaining a target index item, querying the vehicle scenario safety database according to the target index item to obtain target query data, and displaying a query chart in the operation interface based on the target query data;

[0107] Step S505, in response to the fourth control operation acting on the scene restoration component in the functional safety real-time monitoring scenario, a risk scenario restoration calculation is performed on the target data to obtain scene restoration data, a scene playback video is generated based on the scene restoration data, and the scene playback video is displayed in the operation interface.

[0108] Furthermore, when implementing the historical query sub-function, the operation interface is shown in Figure 8. Select index items as needed, which can include: project name, time, event type, etc. After clicking the query button, the query results are displayed in a list or map format. Selecting a data item in the list / map will display the specific parameters of the event.

[0109] When implementing the scene playback sub-function, based on the target data uploaded by the vehicle, the scene when the vehicle triggers the target rule is simulated (that is, the state of the entire vehicle and the state of surrounding obstacles from 15 seconds before to 15 seconds after the trigger moment), and a video or animated image of the scene is generated, and the video or animated image is displayed in the operation interface.

[0110] According to the above visualization solution, users can monitor, manage and repair risks of vehicles intuitively and conveniently through the cloud-based security monitoring platform.

[0111] In embodiments of the present invention, a vehicle-cloud collaborative risk remediation device configured to implement the aforementioned vehicle-cloud collaborative risk remediation method and preferred embodiments is also provided. In the vehicle-cloud collaborative risk remediation device, the "module" referred to may be a combination of software and / or hardware that implements the predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0112] FIG9 is a structural block diagram of a risk repair device for vehicle-cloud collaboration according to an embodiment of the present invention. As shown in FIG9 , the device includes:

[0113] An upload module 901 is configured to upload target data to a security monitoring platform deployed in the cloud in response to a trigger event of a target rule, wherein the target rule is used to determine whether the vehicle is in a target risk state;

[0114] A receiving module 902 is configured to receive a risk remediation plan returned by the security monitoring platform, wherein the risk remediation plan is generated based on risk analysis data, which is calculated by the security monitoring platform based on target data;

[0115] The repair module 903 is configured to perform risk repair on the entire vehicle according to the risk repair plan, so as to remove the vehicle from the target risk state.

[0116] Optionally, in the above-mentioned vehicle-cloud collaborative risk repair device, the target rules include at least: the vehicle's passive safety components send a collision signal; the vehicle's lateral acceleration is greater than a first threshold and the lateral acceleration duration is greater than a second threshold; the vehicle's positioning data is lost for a duration greater than a third threshold.

[0117] Optionally, in the above-mentioned vehicle-cloud collaborative risk repair device, the target data includes vehicle safety data within the target time range corresponding to the triggering event, and the vehicle safety data includes: bus data, perception data and audio and video acquisition data.

[0118] FIG10 is a structural block diagram of another vehicle-cloud collaborative risk repair device according to an embodiment of the present invention. The device is provided in a security monitoring platform deployed in the cloud. As shown in FIG10 , the device includes:

[0119] The receiving module 1001 is configured to receive target data uploaded by a vehicle, wherein the target data is uploaded by a triggering event of the vehicle for a target rule, and the target rule is used to determine whether the vehicle is in a target risk state;

[0120] The calculation module 1002 is configured to perform risk analysis calculation on the target data to obtain risk analysis data;

[0121] A generating module 1003 is configured to generate a risk restoration plan based on the risk analysis data, wherein the risk restoration plan is used to control the vehicle to escape from a target risk state;

[0122] The return module 1004 is configured to return the risk repair plan to the vehicle to assist the vehicle in performing the whole-machine risk repair.

[0123] Optionally, the above-mentioned calculation module 1002 is also configured to: perform risk assessment calculation on the target data to obtain risk assessment data in the risk analysis data; perform risk scenario restoration calculation on the target data to obtain scenario restoration data in the risk analysis data; perform accident analysis on the target data to obtain accident analysis data in the risk analysis data.

[0124] Optionally, the generating module 1003 is further configured to: obtain a risk restoration strategy corresponding to the target rule; and generate a risk restoration plan based on the risk analysis data and the risk restoration strategy.

[0125] Optionally, the above-mentioned vehicle-cloud collaborative risk repair device includes, in addition to all the above-mentioned modules, a storage module 1005 (not shown in the figure), which is configured to store the target data in the safety scenario database corresponding to the vehicle.

[0126] FIG11 is a block diagram of another vehicle-cloud collaborative risk remediation device according to an embodiment of the present invention. In the device, an operation interface is provided by a cloud device. The display content of the operation interface includes at least a real-time monitoring scene of the functional safety of the vehicle. The vehicle and the cloud device communicate with each other. As shown in FIG11 , the device includes:

[0127] A first control module 1101 is configured to respond to a first control operation of a risk monitoring component in a functional safety real-time monitoring scenario, receive target data uploaded by a vehicle, and display monitoring information based on the target data in an operation interface, the monitoring information including map information and chart information, wherein the target data is uploaded when a target rule triggers an event in which the vehicle triggers the target rule, and the target rule is used to determine whether the vehicle is in a target risk state;

[0128] The second control module 1102 is configured to respond to a second control operation of the risk analysis component in the functional safety real-time monitoring scenario, perform risk analysis calculations on the target data, and obtain risk analysis data, wherein the risk remediation plan is used to control the vehicle to leave the target risk state;

[0129] The repair module 1103 is configured to generate a risk repair plan based on the risk analysis data, and return the risk repair plan to the vehicle to assist the vehicle in performing risk repair on the entire vehicle.

[0130] Optionally, the above-mentioned vehicle-cloud collaborative risk repair device includes, in addition to all the above-mentioned modules, a third control module 1104 (not shown in the figure), which is configured to: respond to the third control operation of the query component in the functional safety real-time monitoring scenario, obtain the target index item, obtain the target query data from the vehicle's scene safety database according to the target index item, and display the query chart in the operation interface based on the target query data; respond to the fourth control operation of the scene restoration component in the functional safety real-time monitoring scenario, perform risk scenario restoration calculation on the target data, obtain scene restoration data, generate a scene playback video based on the scene restoration data, and display the scene playback video in the operation interface.

[0131] It should be noted that the above modules can be implemented through software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0132] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, the storage medium including a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute any of the aforementioned vehicle-cloud collaboration risk repair methods.

[0133] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for performing the following steps: in response to a triggering event of a target rule, uploading the target data to a security monitoring platform deployed in the cloud, wherein the target rule is used to determine whether the vehicle is in a target risk state; receiving a risk repair plan returned by the security monitoring platform, wherein the risk repair plan is generated based on risk analysis data, and the risk analysis data is calculated by the security monitoring platform based on the target data; performing whole-vehicle risk repair on the vehicle according to the risk repair plan to make the vehicle escape from the target risk state.

[0134] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for performing the following steps: the passive safety component of the vehicle sends a collision signal; the lateral acceleration of the vehicle is greater than a first threshold and the lateral acceleration duration is greater than a second threshold; the positioning data of the vehicle is lost for a duration greater than a third threshold.

[0135] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for performing the following steps: the target data includes vehicle safety data within the target time range corresponding to the triggering event, and the vehicle safety data includes: bus data, perception data and audio and video acquisition data.

[0136] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for executing the following steps: receiving target data uploaded by the vehicle, wherein the target data is uploaded by a trigger event of the vehicle to a target rule, and the target rule is used to determine whether the vehicle is in a target risk state; performing risk analysis calculations on the target data to obtain risk analysis data; generating a risk repair plan based on the risk analysis data, wherein the risk repair plan is used to control the vehicle to exit the target risk state; and returning the risk repair plan to the vehicle to assist the vehicle in performing whole-machine risk repair.

[0137] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for executing the following steps: performing risk assessment calculations on the target data to obtain risk assessment data in the risk analysis data; performing risk scenario restoration calculations on the target data to obtain scenario restoration data in the risk analysis data; performing accident analysis on the target data to obtain accident analysis data in the risk analysis data.

[0138] Optionally, in this embodiment, the storage medium may be configured to store a computer program for executing the following steps: obtaining a risk repair strategy corresponding to the target rule; and generating a risk repair plan based on the risk analysis data and the risk repair strategy.

[0139] Optionally, in this embodiment, the storage medium may be configured to store a computer program for executing the following steps: storing the target data in a safety scenario database corresponding to the vehicle.

[0140] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for performing the following steps: in response to a first control operation of a risk monitoring component in a functional safety real-time monitoring scenario, receiving target data uploaded by the vehicle, and displaying monitoring information in an operation interface based on the target data, wherein the monitoring information includes map information and chart information, wherein the target data is uploaded by a trigger event of the vehicle to a target rule, and the target rule is used to determine that the vehicle is in a target risk state; in response to a second control operation of a risk analysis component in a functional safety real-time monitoring scenario, performing a risk analysis calculation on the target data to obtain risk analysis data, wherein a risk repair plan is used to control the vehicle to exit the target risk state; based on the risk analysis data, generating a risk repair plan, and returning the risk repair plan to the vehicle to assist the vehicle in performing whole-machine risk repair.

[0141] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for performing the following steps: responding to a third control operation acting on a query component in a functional safety real-time monitoring scenario, obtaining a target index item, querying the vehicle's scene safety database according to the target index item to obtain target query data, and displaying a query chart in an operation interface based on the target query data; responding to a fourth control operation acting on a scene restoration component in a functional safety real-time monitoring scenario, performing risk scenario restoration calculation on the target data to obtain scene restoration data, generating a scene playback video based on the scene restoration data, and displaying the scene playback video in the operation interface.

[0142] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0143] According to another aspect of an embodiment of the present invention, a vehicle is also provided, including an on-board memory and an on-board processor, wherein a computer program is stored in the on-board memory, and the on-board processor is configured to run the computer program to execute any one of the aforementioned vehicle-cloud collaborative risk repair methods.

[0144] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: in response to a triggering event of a target rule, uploading the target data to a security monitoring platform deployed in the cloud, wherein the target rule is used to determine whether the vehicle is in a target risk state; receiving a risk repair plan returned by the security monitoring platform, wherein the risk repair plan is generated based on risk analysis data, and the risk analysis data is calculated by the security monitoring platform based on the target data; performing risk repair on the entire vehicle according to the risk repair plan to make the vehicle escape from the target risk state.

[0145] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: the vehicle's passive safety component sends a collision signal; the vehicle's lateral acceleration is greater than a first threshold and the lateral acceleration duration is greater than a second threshold; the vehicle's positioning data is lost for a duration greater than a third threshold.

[0146] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: the target data includes vehicle safety data within a target time range corresponding to the triggering event, and the vehicle safety data includes: bus data, perception data, and audio and video acquisition data.

[0147] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: receiving target data uploaded by the vehicle, wherein the target data is uploaded by the vehicle triggering an event of a target rule, and the target rule is used to determine whether the vehicle is in a target risk state; performing risk analysis calculations on the target data to obtain risk analysis data; generating a risk repair plan based on the risk analysis data, wherein the risk repair plan is used to control the vehicle to leave the target risk state; and returning the risk repair plan to the vehicle to assist the vehicle in performing overall risk repair.

[0148] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: perform risk assessment calculations on the target data to obtain risk assessment data in the risk analysis data; perform risk scenario restoration calculations on the target data to obtain scenario restoration data in the risk analysis data; perform accident analysis on the target data to obtain accident analysis data in the risk analysis data.

[0149] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: obtaining a risk repair strategy corresponding to the target rule; and generating a risk repair plan based on the risk analysis data and the risk repair strategy.

[0150] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: storing the target data into a safety scenario database corresponding to the vehicle.

[0151] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: responding to a first control operation of a risk monitoring component in a functional safety real-time monitoring scenario, receiving target data uploaded by the vehicle, and displaying monitoring information in an operation interface based on the target data, wherein the monitoring information includes map information and chart information, wherein the target data is uploaded by a trigger event of the vehicle to a target rule, and the target rule is used to determine that the vehicle is in a target risk state; responding to a second control operation of a risk analysis component in a functional safety real-time monitoring scenario, performing risk analysis calculations on the target data to obtain risk analysis data, wherein a risk repair plan is used to control the vehicle to exit the target risk state; generating a risk repair plan based on the risk analysis data, and returning the risk repair plan to the vehicle to assist the vehicle in performing whole-machine risk repair.

[0152] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: responding to a third control operation acting on a query component in a functional safety real-time monitoring scenario, obtaining a target index item, querying the target query data from the vehicle's scene safety database according to the target index item, and displaying a query chart in the operation interface based on the target query data; responding to a fourth control operation acting on a scene restoration component in a functional safety real-time monitoring scenario, performing risk scenario restoration calculation on the target data to obtain scene restoration data, generating a scene playback video based on the scene restoration data, and displaying the scene playback video in the operation interface.

[0153] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiment and its optional implementation manners, which will not be repeated here.

[0154] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0155] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0156] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0157] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0158] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0159] If the integrated unit is implemented in the form of a software functional unit 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 invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0160] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A vehicle-cloud collaborative risk repair method, comprising: In response to a trigger event of a target rule, uploading target data to a security monitoring platform deployed in the cloud, where the target rule is used to determine that the vehicle is in a target risk state; Receiving a risk repair plan returned by the security monitoring platform, where the risk repair plan is generated based on risk analysis data, and the risk analysis data is calculated by the security monitoring platform based on the target data; Performing overall vehicle risk repair according to the risk repair plan, so that the vehicle gets out of the target risk state.

2. The risk mitigation method according to claim 1, wherein, The target rule at least includes: The passive safety component of the vehicle emits a collision signal; The lateral acceleration of the vehicle is greater than a first threshold and the lateral acceleration duration is greater than a second threshold; The duration of the loss of the positioning data of the vehicle is greater than a third threshold.

3. The risk repair method according to claim 1, wherein, The target data includes vehicle safety data within a target duration corresponding to the trigger event, and the vehicle safety data includes: bus data, perception data, and audio-video acquisition data.

4. A risk repair method for vehicle-cloud collaboration, wherein, Running on a security monitoring platform deployed in the cloud, the risk repair method includes: Receiving target data uploaded by a vehicle, where the target data is triggered and uploaded by the vehicle for a trigger event of a target rule, and the target rule is used to determine that the vehicle is in a target risk state; Performing risk analysis calculation on the target data to obtain risk analysis data; Generating a risk repair plan based on the risk analysis data, where the risk repair plan is used to control the vehicle to get out of the target risk state; Returning the risk repair plan to the vehicle to assist the vehicle in performing overall vehicle risk repair.

5. The risk repair method according to claim 4, wherein, Performing risk analysis calculation on the target data to obtain the risk analysis data includes at least one of the following: Performing risk assessment calculation on the target data to obtain risk assessment data in the risk analysis data; Performing risk scenario restoration calculation on the target data to obtain scenario restoration data in the risk analysis data; Original data; Performing accident analysis on the target data to obtain accident analysis data in the risk analysis data.

6. The risk mitigation method according to claim 4, wherein Generating the risk repair plan based on the risk analysis data includes: Obtaining a risk repair strategy corresponding to the target rule; Generating the risk repair plan based on the risk analysis data and the risk repair strategy.

7. A risk repair method for vehicle-cloud collaboration, wherein, Providing an operation interface through a cloud device, where the display content of the operation interface at least includes a real-time functional safety monitoring scenario of the vehicle, and the vehicle and the cloud device are communicatively associated. The risk repair method includes: In response to a first control operation on a risk monitoring component in the real-time functional safety monitoring scenario, receiving the target data uploaded by the vehicle, and displaying monitoring information in the operation interface based on the target data, where the monitoring information includes map information and chart information. The target data is triggered and uploaded by the vehicle for a trigger event of a target rule, and the target rule is used to determine that the vehicle is in a target risk state; In response to a second control operation acting on the risk analysis component in the functional safety real-time monitoring scenario, performing risk analysis calculation on the target data to obtain risk analysis data, wherein the risk repair solution is used to control the vehicle to leave the target risk state; Based on the risk analysis data, a risk repair plan is generated, and the risk repair plan is returned to the vehicle to assist the vehicle in performing whole-machine risk repair.

8. The risk repair method according to claim 7, wherein, The risk repair method further includes: In response to a third control operation acting on the query component in the functional safety real-time monitoring scenario, obtaining a target index item, querying a scenario safety database of the vehicle to obtain target query data according to the target index item, and displaying a query chart in the operation interface based on the target query data; In response to the fourth control operation acting on the scene restoration component in the functional safety real-time monitoring scenario, a risk scenario restoration calculation is performed on the target data to obtain scene restoration data, a scene playback video is generated based on the scene restoration data, and the scene playback video is displayed in the operation interface.

9. A storage medium, the storage medium including a stored program, wherein, When the program is running, the device where the storage medium is located is controlled to execute the risk repair method for vehicle-cloud collaboration as described in any one of claims 1 to 8.

10. A vehicle-cloud collaborative risk repair system, comprising: Vehicle and security monitoring platform, where The vehicle comprises an on-board memory and an on-board processor, the on-board memory stores a computer program, and the on-board processor is configured to run the computer program to perform the method according to any one of claims 1 to 3; The security monitoring platform is deployed on a cloud server, and the security monitoring platform is configured to execute the method described in any one of claims 4 to 8.

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