Vehicle data presetting method and system, vehicle and storage medium

Abstract

The invention discloses a data presetting method and system of a vehicle, the vehicle and a storage medium. The method comprises the steps that data detection is conducted on a vehicle, a detection result is obtained, and the detection result is used for representing whether initial data needed by vehicle operation are successfully preset or not; in response to the detection result indicating that the initial data is preset unsuccessfully, sending a data acquisition request to the cloud, the data acquisition request being used for requesting to acquire target data, the target data being data allowed to be preset on the vehicle, and the data volume of the target data being greater than a data volume threshold; acquiring target data issued by the cloud in response to the data acquisition request; and presetting the target data on the vehicle. The technical problem that the data presetting efficiency of the vehicle is low is solved.

Description

Technical Field

[0001] The present invention relates to the fields of autonomous driving and vehicle networking, and in particular to a vehicle data presetting method, system, vehicle and storage medium. Background Art

[0002] At present, in the field of Internet of Vehicles, vehicle-side pre-set data management plays a vital role, ensuring that the vehicle can quickly obtain basic operating information when it starts. Therefore, how to manage vehicle-side pre-set data more accurately, safely and efficiently is very important.

[0003] In the related art, the cloud is relied upon to periodically send the data to be preset to the vehicle one by one through protocols such as Message Queuing Telemetry Transport (MQTT) and the like. On the one hand, the above method requires the vehicle to passively accept the frequency and period of the data to be preset sent by the cloud, resulting in the vehicle being unable to flexibly and actively obtain data according to its actual needs, causing waste and low efficiency in data transmission, and also causing the vehicle to be unable to obtain the latest data in a timely manner, affecting the real-time performance and response speed of the vehicle during driving. On the other hand, in the above method, the cloud needs to send data one by one, which may cause confusion and instability in data transmission, thereby affecting the integrity and accuracy of the data, and in the face of large-scale data to be preset, sending them one by one is obviously unrealistic, resulting in the technical problem of low efficiency of vehicle data preset.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] Embodiments of the present invention provide a method and system for presetting data of a vehicle, a vehicle and a storage medium, so as to at least solve the technical problem of low efficiency of presetting data of the vehicle.

[0006] According to one aspect of an embodiment of the present invention, a method for presetting data of a vehicle is provided, comprising: performing data detection on the vehicle to obtain a detection result, wherein the detection result is used to indicate whether initial data required for vehicle operation is successfully preset; in response to the detection result indicating that the initial data preset fails, sending a data acquisition request to the cloud, wherein the data acquisition request is used to request to obtain target data, the target data is data allowed to be preset on the vehicle, and the data volume of the target data is greater than a data volume threshold; obtaining the target data sent by the cloud in response to the data acquisition request; and presetting the target data on the vehicle.

[0007] Optionally, performing data detection on the vehicle to obtain a detection result includes: detecting an operating state of the vehicle; and performing data detection on the vehicle based on the operating state to obtain a detection result.

[0008] Optionally, based on the operating status, data detection is performed on the vehicle to obtain detection results, including: in response to the operating status being a startup state, data detection is performed on the digital certificate on the vehicle to obtain detection results, wherein the digital certificate is at least used to record initial data; in response to the operating status being a driving state, a target message sent from the cloud is received, wherein the target message is used to represent the detection result.

[0009] Optionally, in response to the running state being the startup state, performing data detection on the digital certificate on the vehicle to obtain a detection result, including: in response to the running state being the startup state, performing data detection on the attribute information of the digital certificate to obtain a detection result, wherein the attribute information is used to represent the integrity index and / or version of the digital certificate, and the detection result is used to indicate whether the integrity index of the digital certificate reaches an integrity index threshold, and / or whether the version reaches a version threshold, and the integrity index is used to indicate the degree of integrity of the digital certificate; the method also includes: in response to the integrity index being lower than the integrity index threshold, and / or the version being lower than the version threshold, determining that the detection result is a failure to preset initial data on the vehicle.

[0010] Optionally, in response to the running state being the driving state, receiving a target message sent from the cloud, including: in response to the running state being the driving state, sending a message subscription request for the target message to the cloud; receiving the target message sent from the cloud in response to the message subscription request, wherein the target message is used to indicate whether the initial data is abnormal and / or needs to be updated; the method also includes: in response to the initial data being abnormal and / or needing to be updated, determining that the detection result is a failure to preset the initial data on the vehicle.

[0011] Optionally, receiving a target message in response to a message subscription request from the cloud includes: receiving a target message in response to a message subscription request from a monitoring module, monitoring the data status of the initial data, and sending the target message, wherein the target message includes an update strategy, the update strategy is used to represent update rules for updating the initial data, and the monitoring module is deployed on the cloud.

[0012] Optionally, in response to a detection result indicating a failure in initial data preset, sending a data acquisition request to the cloud, including: in response to a detection result indicating a failure in preset initial data on the vehicle, performing a two-way verification on the data preset interface of the vehicle and the cloud to obtain a verification result; in response to a verification result indicating a successful two-way verification of the vehicle and the data preset interface, sending a data acquisition request to the cloud.

[0013] Optionally, obtaining target data sent by the cloud in response to a data acquisition request includes: obtaining target data queried from a database when the cloud recognizes that identification information in the data acquisition request has been preset on the cloud, wherein the identification information is used to identify the vehicle, and a monitoring module deployed on the cloud is used to monitor the information status of the identification information; or obtaining initialization preset data of the cloud as target data when the cloud recognizes that the identification information has not been preset on the cloud, wherein the database allows storage of the initialization preset data, and log data corresponding to the initialization preset data is monitored by the monitoring module.

[0014] According to another aspect of an embodiment of the present invention, a vehicle data presetting system is also provided, including: a vehicle, used to perform data detection on the vehicle to obtain a detection result, wherein the detection result is used to indicate whether initial data required for vehicle operation is successfully preset; in response to the detection result indicating that the initial data preset fails, sending a data acquisition request to the cloud, wherein the data acquisition request is used to request to obtain target data, the target data is data allowed to be preset on the vehicle, and the data volume of the target data is greater than a data volume threshold; the cloud, used to respond to the data acquisition request and obtain the target data; send the target data to the vehicle; wherein the vehicle is used to preset the target data on the vehicle.

[0015] According to another aspect of an embodiment of the present invention, a data presetting device for a vehicle is also provided, including: a detection unit, used to perform data detection on the vehicle to obtain a detection result, wherein the detection result is used to indicate whether initial data required for vehicle operation has been successfully preset; a sending unit, used to send a data acquisition request to the cloud in response to the detection result indicating that the initial data preset has failed, wherein the data acquisition request is used to request to obtain target data, the target data is data allowed to be preset on the vehicle, and the data volume of the target data is greater than a data volume threshold; an acquisition unit, used to obtain the target data sent by the cloud in response to the data acquisition request; and a presetting unit, used to preset the target data on the vehicle.

[0016] Optionally, the detection unit may include: a first detection module, used to detect the operating state of the vehicle; and a second detection module, used to perform data detection on the vehicle based on the operating state to obtain a detection result.

[0017] Optionally, the second detection module may include: a first detection submodule, used to perform data detection on the digital certificate on the vehicle in response to the running state being a startup state, to obtain a detection result, wherein the digital certificate is at least used to record the initial data; a first receiving submodule, used to receive a target message sent from the cloud in response to the running state being a driving state, wherein the target message is used to represent the detection result.

[0018] Optionally, the second detection module may also include: a second detection submodule, used to perform data detection on the attribute information of the digital certificate in response to the running state being the startup state, to obtain a detection result, wherein the attribute information is used to represent the integrity index and / or version of the digital certificate, and the detection result is used to indicate whether the integrity index of the digital certificate reaches the integrity index threshold, and / or whether the version reaches the version threshold, and the integrity index is used to indicate the degree of integrity of the digital certificate; the device may also include: a first determination unit, used to determine that the detection result is a failure to preset initial data on the vehicle in response to the integrity index being lower than the integrity index threshold, and / or the version being lower than the version threshold.

[0019] Optionally, the second detection module may include: a sending submodule, used to send a message subscription request for a target message to the cloud in response to the operating state being a driving state; a second receiving submodule, used to receive the target message sent by the cloud in response to the message subscription request, wherein the target message is used to indicate whether the initial data is abnormal and / or needs to be updated; the device may also include: a second determination unit, used to determine that the detection result is a failure to preset the initial data on the vehicle in response to the initial data being abnormal and / or needing to be updated.

[0020] Optionally, the second detection module may include: a third receiving sub-module, used to receive the monitoring module's response to the message subscription request, monitor the data status of the initial data, and send the target message, wherein the target message includes an update strategy, the update strategy is used to represent the update rules for updating the initial data, and the monitoring module is deployed on the cloud.

[0021] Optionally, the sending unit may include: a verification module for performing a two-way verification on the data preset interface of the vehicle and the cloud in response to a detection result that the initial data preset on the vehicle fails to be preset, to obtain a verification result; a sending module for sending a data acquisition request to the cloud in response to a verification result that the two-way verification of the vehicle and the data preset interface is successful.

[0022] Optionally, the acquisition unit may include: a first acquisition module, used to acquire target data queried from a database when the cloud recognizes that the identification information in the data acquisition request has been preset on the cloud, wherein the identification information is used to identify the vehicle, and the monitoring module deployed on the cloud is used to monitor the information status of the identification information; or, a second acquisition module, used to acquire the initialization preset data of the cloud as the target data when the cloud recognizes that the identification information has not been preset on the cloud, wherein the database allows the storage of the initialization preset data, and the log data corresponding to the initialization preset data is monitored by the monitoring module.

[0023] According to another aspect of an embodiment of the present invention, a vehicle is provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes any one of the above methods when running.

[0024] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium including a stored executable program, wherein when the executable program runs, the device where the storage medium is located is controlled to execute any one of the above methods.

[0025] According to another aspect of an embodiment of the present invention, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, any one of the above methods is implemented.

[0026] In an embodiment of the present invention, if it is necessary to confirm whether the data required by the vehicle is successfully preset, and to handle the preset failure in a timely manner, the vehicle can be tested for data to determine whether the data required in the vehicle are successfully preset, and the corresponding test results can be obtained. If the test result is that the required data (for example, initial data) is not successfully preset, a data acquisition request for re-presetting the data can be generated to re-determine the target data corresponding to the initial data from the cloud. The above data acquisition request can be actively sent to the cloud, and after receiving the data acquisition request, the cloud can determine the target data to be preset required by the vehicle. The target data can also be sent to the vehicle, and the vehicle can preset the target data.

[0027] It is worth noting that, through the above method in the embodiment of the present invention, on the one hand, when it is discovered in time that there is a failure in data presetting in the vehicle, the vehicle can actively send a data acquisition request to the cloud to obtain the data to be preset according to actual needs, without waiting for the cloud to periodically send data, thereby saving the data presetting time. On the other hand, when the amount of data to be preset is large, the cloud can upload a large amount of data to the vehicle at one time, avoiding the situation where the cloud splits the above data and sends small amounts of data one by one. The vehicle only needs to receive the required data once, without receiving it multiple times, thereby saving communication costs and transmission time. Thereby achieving the technical effect of improving the data presetting efficiency of the vehicle and solving the technical problem of low data presetting efficiency of the vehicle. 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 the present invention. 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] Figure 1is a flow chart of a vehicle data presetting method according to an embodiment of the present invention;

[0030] Figure 2 is a flow chart of an efficient and secure data presetting method for Internet of Vehicles according to an embodiment of the present invention;

[0031] Figure 3 is a schematic diagram of a vehicle data presetting system according to an embodiment of the present invention;

[0032] Figure 4 is a structural block diagram of a vehicle data presetting device according to an embodiment of the present invention;

[0033] Figure 5 is a structural block diagram of an autonomous driving vehicle according to an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments 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 creative work should fall within the scope of protection of the present invention.

[0035] It should be noted that the terms "first", "second", etc. in the specification 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 data 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 that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0036] According to an embodiment of the present invention, a method embodiment for presetting data of a vehicle 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.

[0037] Figure 1 FIG. 1 is a flow chart of a method for presetting vehicle data according to an embodiment of the present invention. Figure 1 As shown, the method may include a cloud 10, a network 11 and a vehicle 12, and the vehicle 12 and the cloud 10 may be connected through the network 11 to exchange data. The vehicle 12 may transmit a data acquisition request to the cloud 10 through the network 11. After receiving the data acquisition request, the cloud 10 may transmit the target data requested by the data acquisition request to the vehicle 12 through the network 11. The method includes the following steps:

[0038] Step S102, performing data detection on the vehicle to obtain a detection result.

[0039] In the technical solution provided in the above step S102 of the present invention, the vehicle may also be referred to as the vehicle end, and may be an intelligent vehicle, such as an unmanned vehicle. The detection result may be used to indicate whether the initial data required for the operation of the vehicle is successfully preset. The initial data may be used to indicate the basic data required by the vehicle during operation, and may also be referred to as basic operation information, which may be information or data necessary for the normal operation and execution of tasks of the vehicle. For example, the basic configuration information, software version, and map data of the vehicle. The timeliness and accuracy of the initial data play an important role and significance to the normal operation, response speed, stability, autonomy, and safety of the vehicle.

[0040] It should be noted that the above initial data is for illustration only and is not specifically limited here. It can be determined based on the information required to maintain the normal operation of different types of vehicles.

[0041] In this embodiment, data detection may be performed on the vehicle to determine whether the initial data required by the vehicle are successfully preset, and obtain corresponding detection results.

[0042] Optionally, data detection is performed in the vehicle, and the detection result is used to determine whether the initial data required for vehicle operation has been successfully preset. The data detection process may include checking the data stored in the vehicle, verifying the integrity and accuracy of the data, etc., to ensure that the basic data required by the vehicle has been correctly preset in the vehicle.

[0043] It should be noted that the specific method of data detection mentioned above is only for illustration and is not specifically limited here. As long as the process and method can analyze whether the initial data required by the vehicle is successfully preset, it is within the protection scope of the embodiment of the present invention.

[0044] Optionally, if the test result shows that the initial data preset is successful, it means that the vehicle already has the necessary basic data and can operate normally. Conversely, if the test result shows that the initial data preset fails, it means that the vehicle lacks the necessary basic data, which may cause problems such as the vehicle being unable to start, navigate and communicate, thereby affecting the normal operation of the vehicle.

[0045] In the embodiment of the present invention, by performing data detection on the vehicle and judging the preset status of the initial data according to the detection result, data missing or error can be found in time, so that corresponding measures can be taken to solve the problem. This helps to ensure that the vehicle has the necessary basic data during operation and improve the operation efficiency and stability of the vehicle. Therefore, data detection is of great significance to ensure the normal operation of the vehicle.

[0046] Step S104: in response to the detection result indicating that the initial data presetting fails, a data acquisition request is sent to the cloud.

[0047] In the technical solution provided in the above step S104 of the present invention, the failure of initial data preset can be used to indicate that the vehicle is found to lack necessary basic data after data detection and cannot operate normally. The data acquisition request is a request sent by the vehicle to the cloud, which can be used to request to obtain the target data. The request may include the identity information of the vehicle, the content of the requested data, etc. This is only an example and is not specifically limited. The target data can be data that is allowed to be preset on the vehicle, and the data volume of the target data is greater than the data volume threshold. The target data is set to solve the problem caused by the failure of initial data preset, which may include the basic data and other necessary information required by the vehicle. The target data can be the data that failed to be preset in the initial data required by the vehicle. For example, if the data required in the vehicle includes basic configuration information, software version and map data, etc., if it is determined through detection that the basic configuration information and software version are successfully preset, and the map data preset fails, then the map data is the target data.

[0048] Optionally, in this embodiment, the target data with a data volume greater than the data volume threshold may be referred to as large-capacity data. It should be noted that the data volume of the above target data is only for illustration and is not specifically limited here. It may be target data with a data volume less than the data volume threshold, or large-capacity data with a data volume greater than the data volume threshold. The target data with a data volume greater than the data volume threshold can be used to distinguish the problem that the target data to be preset needs to be sent one by one in the related technology, and in the embodiment of the present invention, through the above method, it can be directly ensured that the large-capacity data is sent and preset by the cloud at one time.

[0049] Optionally, the data acquisition request is a request sent by the vehicle to the cloud to obtain target data to supplement the basic data missing from the vehicle, thereby solving the problem of initial data presetting failure. The data acquisition request may include the identity information of the vehicle, the data content of the requested target data, the purpose of the request, the timestamp of the request, and other necessary information. The data acquisition request may contain the unique identifier or other identity information of the vehicle so that the cloud can identify which vehicle sent the request. The data acquisition request will state which data the vehicle needs to obtain, that is, the specific content and type of the target data. These data may include basic configuration information, map data, software updates, etc. that are missing from the vehicle. The data acquisition request will state the purpose of sending the data acquisition request, that is, the vehicle finds that the initial data presetting fails and needs to obtain the target data to complete the presetting to ensure the normal operation of the vehicle. In order to ensure the timeliness of the data acquisition request, the data acquisition request may contain timestamp information, indicating the time when the data acquisition request was sent. Depending on the specific situation, the data acquisition request may also contain other necessary information, such as the priority of the request, the processing method of the request, etc.

[0050] It should be noted that the content contained in the above data acquisition request is only for illustration and no specific limitation is made here.

[0051] In this embodiment, after data detection is performed on the vehicle and the detection result is obtained, when the detection result indicates that the initial data preset fails, a data acquisition request can be sent to the cloud to obtain the target data to be preset.

[0052] Optionally, by performing data detection on the vehicle, the detection result is determined, and the detection result is used to display whether the initial data preset fails. This means that it is possible to determine whether the basic data required for the operation of the vehicle is missing data or there is erroneous data. If the above situation exists, the vehicle cannot operate normally. Based on the detection results, the vehicle actively sends a data acquisition request to the cloud. The above process is the vehicle's response to the failure of initial data preset, and it obtains the required target data by sending a request to the cloud. The data acquisition request is a request sent by the vehicle to the cloud to request the acquisition of target data, which may include the vehicle's identity information and the requested data content, so that the cloud can accurately identify the vehicle's needs and provide corresponding target data.

[0053] Optionally, through the above method, the vehicle can promptly discover the problem of initial data presetting failure, and obtain the required target data by actively sending a data acquisition request to the cloud to supplement the missing basic data in the vehicle. The above vehicle actively requests to obtain target data, which can effectively improve the efficiency and accuracy of data presetting and ensure the normal operation of the vehicle. The above process of obtaining target data reflects the collaborative work between the vehicle and the cloud, and improves the efficiency and performance of data presetting.

[0054] Optionally, through a data acquisition request, the vehicle can clearly indicate the required information to the cloud and request to obtain the target data to solve the problem of initial data provisioning failure. After receiving the data acquisition request, the cloud will prepare the target data according to the content in the request and the identity information of the vehicle, and send the target data to the vehicle so that the vehicle can complete the data provisioning and ensure the normal operation of the vehicle. The whole process realizes the collaborative work between the vehicle and the cloud, and improves the efficiency and performance of data provisioning.

[0055] In the relevant data presetting method, the cloud needs to send data to the vehicle one by one, that is, the vehicle can only passively receive the data periodically sent by the cloud one by one. This means that data transmission is carried out in batches, and data needs to be transmitted and received one by one, which is inefficient, especially when the amount of data is large. It will increase communication overhead and time consumption. It also means that the vehicle cannot actively choose whether to preset data and the time to preset data, so as to actively obtain the corresponding data from the cloud.

[0056] However, in an embodiment of the present invention, the data volume of the target data is greater than the data volume threshold, which means that the cloud can upload a large amount of data to the vehicle at one time, rather than sending it down in batches one by one. The above-mentioned one-time large-capacity presetting method can greatly improve the efficiency and speed of data transmission, reduce communication overhead and time consumption, and speed up the process of data presetting. Therefore, the above-mentioned one-time large-capacity presetting is more efficient and faster than the method of sending data one by one in the related art. By uploading the target data to the vehicle at one time, data presetting can be completed more quickly to ensure the normal operation of the vehicle. Secondly, when the data detection of the vehicle finds that there is data that fails to be preset in the vehicle, the vehicle can actively initiate a data acquisition request corresponding to the above data to the cloud, thereby actively receiving the required data from the cloud. Compared with the method of the cloud periodically sending data one by one in the related art, unnecessary data transmission is avoided, which not only improves the efficiency of data presetting, but also improves the overall performance and stability of the vehicle.

[0057] Step S106, obtaining the target data sent by the cloud in response to the data acquisition request.

[0058] In the technical solution provided in the above step S106 of the present invention, after the vehicle sends a data acquisition request to the cloud, the cloud receives the data acquisition request and can send corresponding target data to the vehicle.

[0059] Optionally, the vehicle sends a data acquisition request to the cloud, requesting to acquire target data to supplement the missing initial data. The data acquisition request contains the identity information of the vehicle, the content of the requested data, etc. After receiving the data acquisition request sent by the vehicle, the cloud will process the acquired data acquisition request and prepare to send the target data to the vehicle based on the content in the data acquisition request and the identity information of the vehicle. The cloud will send the prepared target data to the vehicle at one time. The target data is data that is allowed to be pre-set on the vehicle. The data volume is large and can supplement the missing basic data of the vehicle to ensure the normal operation of the vehicle.

[0060] Through the above method, the vehicle can obtain the required target data in time to solve the problem of initial data presetting failure. After receiving the data acquisition request, the cloud responds quickly and sends the target data to the vehicle at one time, avoiding the low efficiency caused by sending data in batches one by one. The above method of sending a large amount of target data at one time improves the efficiency and speed of data presetting, ensures that the vehicle can complete data presetting in time, and ensures the normal operation of the vehicle. The whole process reflects the collaborative work between the vehicle and the cloud, which improves the efficiency and performance of data presetting.

[0061] Step S108, presetting the target data on the vehicle.

[0062] In the technical solution provided in the above step S108 of the present invention, after receiving the target data sent by the cloud, the vehicle can preset the target data.

[0063] Optionally, the vehicle receives target data sent from the cloud. These target data are prepared to supplement the missing basic data of the vehicle. The data volume is large and is sent all at once. The vehicle presets the received target data in the vehicle's storage device or memory. The presetting process may require data parsing, verification, and storage operations to ensure that the data is correctly stored in the vehicle.

[0064] Optionally, after the vehicle is pre-installed, the data may be verified and checked to ensure that the target data is correctly pre-installed on the vehicle. This step may include data integrity verification, data format check and other processes. Once the target data is successfully pre-installed on the vehicle and verified to be correct, the vehicle can start the relevant application or function. In this way, the vehicle can use the newly added data to operate and work normally.

[0065] Through the above method, the vehicle can successfully preset the target data obtained from the cloud on the vehicle, solving the problem of initial data preset failure caused by various situations during the data preset process, such as network connection problems, data loss or damage, communication failures, and data format errors when the vehicle and the cloud are transmitting data. The above data preset method can effectively improve the efficiency and speed of data preset, ensure that the vehicle has the necessary basic data, and thus ensure the normal operation and performance of the vehicle. The whole process reflects the collaborative work between the vehicle and the cloud, and improves the efficiency and accuracy of data preset.

[0066] For example, after a smart car detects that the initial data preset fails and the latest map data is missing, it can send a data acquisition request to the cloud to obtain the target data for preset. The vehicle detects that the initial data preset fails and the latest map data is missing, and can send a data acquisition request to the cloud. After the cloud receives the data acquisition request sent by the vehicle, it prepares to send the latest map data as the target data to the vehicle. The cloud sends the file containing the latest map data to the vehicle at one time. This data is large in size and includes the map information required by the vehicle. The vehicle receives and parses the data sent by the cloud and presets the map data in the vehicle's navigation system. After the vehicle completes the preset of the map data, it performs data verification to ensure the integrity and accuracy of the data. The vehicle starts the navigation system and uses the newly preset map data for navigation operations.

[0067] It should be noted that the above-mentioned target data pre-setting process and method are only for illustration and are not specifically limited here. As long as the process and method can successfully pre-set the target data on the vehicle at one time through the collaboration between the vehicle and the cloud, and ensure that the vehicle has the necessary basic data for normal operation, they are all within the protection scope of the embodiments of the present invention.

[0068] In the above steps S102 to S108 of the present application, if it is necessary to confirm whether the data required by the vehicle is successfully preset, and to handle it in time when the preset fails, the vehicle can be tested for data to determine whether the data required in the vehicle are successfully preset, and the corresponding test results are obtained. If the test result is that the required data (for example, initial data) is not successfully preset, a data acquisition request for re-presetting the data can be generated to re-determine the target data corresponding to the initial data from the cloud. The above data acquisition request can be actively sent to the cloud, and the cloud can determine the target data to be preset required by the vehicle after receiving the data acquisition request. And the target data can be sent to the vehicle, and the vehicle can preset the target data. In this embodiment, the vehicle can actively send a data acquisition request to the cloud to obtain the data to be preset according to actual needs, without waiting for the cloud to periodically send data, thereby achieving the purpose of saving data preset time. In addition, the cloud can upload a large capacity of data to the vehicle at one time, and the vehicle only needs to receive the required data once, without receiving it multiple times, thereby achieving the purpose of saving communication costs and transmission time. Thereby achieving the technical effect of improving the data presetting efficiency of the vehicle and solving the technical problem of low data presetting efficiency of the vehicle.

[0069] The following further describes how to perform data detection on a vehicle in this embodiment to obtain a detection result of whether the initial data in the vehicle fails to be preset.

[0070] As an optional implementation method, step S102, performing data detection on the vehicle to obtain a detection result, includes: detecting the operating state of the vehicle; and performing data detection on the vehicle based on the operating state to obtain a detection result.

[0071] In an embodiment, during the process of performing data detection on a vehicle, the running state of the vehicle may be detected, and data detection may be performed on the vehicle based on the running state of the vehicle to obtain a detection result, wherein the running state may include the vehicle being in a powered-on state and the vehicle being in a driving state. The powered-on state may also be referred to as a startup phase, and may be an active mode, that is, a mode in which data detection and active presetting are performed actively. The driving state may be a passive mode, that is, a mode in which data detection and passive presetting are performed by passively receiving instructions.

[0072] Optionally, when performing data detection on the vehicle and obtaining the detection results, different methods of data detection can be performed according to the operating state of the vehicle, so as to achieve different technical effects.

[0073] Optionally, when the vehicle is powered on, an active mode can be used for data detection and data presetting. In this process, the vehicle can actively initiate a data detection request to ensure that the vehicle has the necessary data to operate normally during the startup phase. The above active mode can detect data missing or errors in a timely manner, so that appropriate measures can be taken to solve the problem and ensure the normal operation of the vehicle.

[0074] Optionally, when the vehicle is in driving state, a passive mode can be used for data detection and data preset. In this process, the vehicle may not actively initiate a data detection request, but passively receive instructions to perform data detection and data preset. In the driving state, the vehicle may need to update and preset data according to instructions from the cloud or central control system. The above passive mode can more flexibly detect and preset data for the vehicle according to actual conditions, and adapt to changes in the state of the vehicle during operation.

[0075] Optionally, the vehicle-side power-on self-test (power-on check) means that when the vehicle is powered on, a series of self-test operations can be automatically performed to ensure the normal operation of the vehicle and the integrity of the data. When the vehicle is started or powered on, the on-board system will start running, and each module will start and initialize. The integrity and version information of the pre-installed certificates in the vehicle's local storage can be checked. These pre-installed certificates may contain important information such as the vehicle's digital key and identity authentication certificate. The integrity of the above certificates can be verified to ensure that the data has not been damaged or tampered with, and the version information of the certificate can be checked. If it is found that the pre-installed certificate data in the local storage is missing or the version is too old, it means that the data may have expired or is unavailable. This may cause the vehicle to be unable to perform operations such as remote unlocking and starting, thereby affecting the normal use of the vehicle. Once it is determined that there is a problem with the certificate data in the local storage, a cloud data pre-installation interface request can be automatically triggered. This means that the cloud can send a request to re-obtain the latest certificate data and pre-install it in the vehicle-side local storage. The cloud can receive requests from the vehicle, regenerate the latest certificate data based on the vehicle's identity information and needs, and send the data to the vehicle through relevant secure transmission protocols to complete the data pre-setting operation.

[0076] Through the vehicle-side power-on self-check process, the integrity and version information of the certificate data can be automatically checked when the vehicle is started. Once a problem is found, the latest data can be requested from the cloud in a timely manner to ensure the safety and stability of the vehicle. The above power-on self-check can help the vehicle find problems in time and take measures to ensure the normal operation of the vehicle.

[0077] In the embodiment of the present invention, in the active mode, data presetting problems can be discovered and solved in time during the vehicle startup phase, ensuring that the vehicle has the data required for normal operation at the earliest stage, thereby improving the stability and reliability of the vehicle. The passive mode can flexibly perform data detection and presetting according to the actual operating status of the vehicle and the needs of the driver, thereby reducing interference with the vehicle operation and ensuring the stability and safety of the vehicle operation process.

[0078] The following further describes the process of performing data detection on the vehicle when the vehicle is in a running state according to this embodiment.

[0079] As an optional implementation method, based on the operating status, data detection is performed on the vehicle to obtain a detection result, including: in response to the operating status being a startup state, data detection is performed on the digital certificate on the vehicle to obtain a detection result, wherein the digital certificate is at least used to record initial data; in response to the operating status being a driving state, a target message sent from the cloud is received, wherein the target message is used to represent the detection result.

[0080] In an embodiment, when the operating state is a startup state, data detection can be performed on the digital certificate on the vehicle to obtain a detection result. When the operating state is a driving state, the target information sent by the cloud can be received to obtain the detection result, wherein the operating state may include a startup state and a driving state. The startup state may also be referred to as a startup phase. The digital certificate may be used at least to record initial data, and may also be referred to as a preset certificate or certificate. The target message may be used to indicate the detection result, and may be a specific message or topic published by MQTT, and may be used to indicate whether the data verification fails or whether the version matches.

[0081] Optionally, according to different operating states of the vehicle (start-up state and driving state), different methods of data detection are performed on the vehicle to obtain corresponding detection results, thereby achieving different functions and effects.

[0082] Optionally, the digital certificate on the vehicle is tested to ensure its validity and integrity. Digital certificates are usually used to record or verify initial data and can serve as a guarantee of data integrity and security. Through the testing of digital certificates, the source and authenticity of the initial data can be verified to ensure the security and credibility of the data.

[0083] Optionally, when the vehicle is in driving state, it can receive target messages sent from the cloud to indicate the test results. These target messages may contain information such as whether the data verification fails and whether the version matches. By receiving and processing the target messages, the vehicle can further verify and confirm the data to ensure the correctness and validity of the data. The above method can timely obtain and process the messages sent from the cloud during the operation of the vehicle to ensure the correct use and preset of the data.

[0084] In the embodiment of the present invention, through the above method, according to different operating states and requirements, the vehicle can perform targeted data detection and processing to ensure the security, integrity and correctness of the data. Using digital certificates to record and verify initial data, receive and process target messages sent from the cloud, helps to improve the safety and stability of the vehicle and ensure the normal operation of the vehicle under various operating conditions.

[0085] The following further describes the process of how to perform data detection on the digital certificate on the vehicle when the vehicle is in the startup state in this embodiment.

[0086] As an optional implementation mode, in response to the operating state being the startup state, performing data detection on the digital certificate on the vehicle to obtain a detection result, including: in response to the operating state being the startup state, performing data detection on the attribute information of the digital certificate to obtain a detection result, wherein the attribute information is used to represent the integrity index and / or version of the digital certificate, and the detection result is used to indicate whether the integrity index of the digital certificate reaches an integrity index threshold, and / or whether the version reaches a version threshold, and the integrity index is used to indicate the degree of integrity of the digital certificate; the method also includes: in response to the integrity index being lower than the integrity index threshold, and / or the version being lower than the version threshold, determining that the detection result is a failure to preset initial data on the vehicle.

[0087] In an embodiment, when the running state is the startup state, the attribute information of the digital certificate can be subjected to data detection to obtain a detection result. When the integrity index is lower than the integrity index threshold, and / or the version is lower than the version threshold, it is determined that the detection result is a failure to preset the initial data on the vehicle. Among them, the attribute information can be used to represent the integrity index and / or version of the digital certificate. The integrity index can be used to indicate whether the data in the digital certificate is missing. If the integrity index reaches the integrity index threshold, it means that the data in the digital certificate is complete and there is no missing situation. Otherwise, it means that the data in the digital certificate is incomplete and there is a missing situation. The version threshold can be used to indicate whether it is too old, that is, if the version does not reach the version threshold, it means that the version is too old. Otherwise, it can be said that the version is not old. The detection result can be used to indicate whether the integrity index of the digital certificate reaches the integrity index threshold, and / or whether the version reaches the version threshold.

[0088] Optionally, for a vehicle whose operating state is the startup state, a detailed data check is performed on the attribute information of the digital certificate to determine the integrity and version of the digital certificate, and then determine the preset status of the initial data.

[0089] Optionally, when the vehicle is in the startup state, the system performs data detection on the attribute information of the digital certificate. The attribute information includes the integrity index and / or version information of the digital certificate. The integrity index is used to indicate whether the data in the digital certificate is complete, and the version information is used to indicate the version number of the digital certificate. During the data detection process, it can be determined whether the integrity index of the digital certificate reaches the integrity index threshold. If the integrity index is lower than the integrity index threshold, it means that the data in the digital certificate is missing or wrong and does not meet the integrity requirements. It can also be determined whether the version of the digital certificate reaches the version threshold, that is, whether the data in the digital certificate is outdated. If the version of the digital certificate is lower than the version threshold, it means that the version of the digital certificate is older and meets the update requirements. If it is found in the data detection that the integrity index is lower than the integrity index threshold, or the version is lower than the version threshold, it can be determined that the detection result is a failure to preset the initial data on the vehicle. This means that the data in the digital certificate is incomplete or the version is too old, and a data repair or update operation is required.

[0090] In the embodiment of the present invention, through the above method, data detection can be performed according to the attribute information of the digital certificate, and the integrity and update status of the digital certificate can be judged according to the integrity index and version information. The above detailed data detection process can help the system to timely discover problems with the digital certificate, ensure the integrity and validity of the digital certificate, and thus ensure the safe operation of the vehicle and the reliability of the data.

[0091] Optionally, active acquisition logic optimization during the vehicle startup phase includes health checks, data integrity, timeliness verification, and optimized network connection management strategies.

[0092] Optionally, during the vehicle startup phase, the vehicle can perform a health check on local data. This process covers multiple aspects, including the existence of pre-set data, data integrity and timeliness verification. Through health checks, the vehicle can ensure that the data is in good condition, avoid using damaged or outdated data, and improve the stability and reliability of the vehicle.

[0093] Optionally, in addition to checking whether the preset data exists, it should also be extended to verify the integrity and timeliness of the data, that is, the verification of integrity indicators and versions. Data integrity verification ensures that the data has not been tampered with or damaged, and timeliness verification ensures that the data is up-to-date and valid. Through these verifications, the vehicle can ensure that the data used is accurate, complete and timely, thereby improving the accuracy and efficiency of the system.

[0094] Optionally, during the process of optimizing the network connection management strategy, if the local data health check fails, that is, the data is incomplete or outdated, the vehicle can obtain the target data through the cloud. In order to efficiently obtain large amounts of data and reduce startup delays, this can be achieved by optimizing the network connection management strategy. For example, the multiplexing technology of Hypertext Transfer Protocol version 2 (HTTP2) can simultaneously transmit multiple requests and responses on a single connection, thereby improving the efficiency and speed of data transmission. The above method can reduce the overhead of network communication and speed up data download, thereby shortening the vehicle startup time and improving the user experience.

[0095] In summary, through the above-mentioned active acquisition logic optimization, that is, through health checks, data integrity, timeliness verification, and optimized network connection management strategies during the vehicle startup phase, the vehicle side can ensure the use of accurate, complete, and timely data during the startup process, improve the startup speed and stability of the vehicle, optimize the user experience, and provide important guarantees for the normal operation of the vehicle's intelligent driving system. These measures help reduce data transmission delays and improve the responsiveness and performance of the vehicle.

[0096] The following further describes the process of how the vehicle receives the target message sent from the cloud when the vehicle is in the driving state in this embodiment.

[0097] As an optional implementation manner, in response to the operating state being a driving state, receiving a target message sent from the cloud includes: in response to the operating state being a driving state, sending a message subscription request for the target message to the cloud; receiving the target message sent from the cloud in response to the message subscription request, wherein the target message is used to indicate whether the initial data is abnormal and / or needs to be updated; the method also includes: in response to the initial data being abnormal and / or needing to be updated, determining that the detection result is a failure to preset the initial data on the vehicle.

[0098] In an embodiment, when the operating state is a driving state, the vehicle may send a message subscription request for a target message to the cloud, and after receiving the message subscription request, the cloud may send the target information to the vehicle. When the vehicle receives the target message, the target message may be analyzed to determine whether the initial data is abnormal and / or needs to be updated. If the initial data is abnormal and / or needs to be updated, it may be determined that the detection result is a failure to preset the initial data on the vehicle, wherein the message subscription request may be a request sent by the vehicle to the cloud to subscribe to messages of a specific type or topic. Through the message subscription request, the vehicle may indicate to the cloud that it is interested in a certain message type or topic and hopes to receive the relevant target message. The target message may be used to indicate whether the initial data is abnormal and / or needs to be updated.

[0099] Optionally, when the vehicle is in driving state, the vehicle needs to receive the target message sent by the cloud to determine whether the initial data is abnormal or needs to be updated. The vehicle sends a message subscription request to the cloud, requesting to subscribe to messages of a specific type or topic to determine the status of the initial data. The message subscription request will include the subscribed message type or topic information, as well as the vehicle's identity, etc. After the cloud receives the message subscription request sent by the vehicle, it will process it and prepare the corresponding target message for sending to the vehicle based on the request content. The cloud sends target messages to the vehicle, which are used to indicate whether the initial data is abnormal or needs to be updated. The target message may include data verification results, update prompts, etc. to help the vehicle determine the status of the initial data.

[0100] In the embodiment of the present invention, through the message subscription request, the vehicle can obtain the target message sent by the cloud in time, which helps to determine whether the initial data is abnormal or needs to be updated. The above subscription mechanism enables the vehicle to dynamically adjust the data processing strategy according to the real-time message, find problems in time and take corresponding measures to ensure the normal operation of the vehicle. The message subscription request establishes a timely communication mechanism between the vehicle and the cloud, improving the efficiency and reliability of data pre-setting.

[0101] Optionally, the above-mentioned intelligent linkage mechanism for passive data acquisition and self-repair on the vehicle side may include real-time monitoring of data update instructions or abnormal signals by subscribing to specific topics published by MQTT on the cloud, and automatically triggering the data reset process when receiving the corresponding message, wherein the specific topic generally refers to the topic name used to identify and distinguish different types of messages or events in messaging. Specific topics can be used to subscribe to or publish messages so that the vehicle can receive or send specific types of messages. The setting of specific topics is usually based on the requirements and functions of the system design, and is used to distinguish different message types or events, so that the vehicle can subscribe to or publish messages according to different topics. For example, data update instruction topics, abnormal signal topics, system status topics, and control instruction topics, etc., are only used as examples here and are not specifically limited.

[0102] Optionally, the Data Update Instructions topic can be used to publish data update instructions sent by the cloud, so that the vehicle can receive the latest data update instructions and update the data in a timely manner. The Abnormal Signal topic can be used to publish abnormal signals or events, so that the vehicle can receive abnormal information and make corresponding processing or repair operations. The System Status topic can be used to publish changes in vehicle status or alarm information, so that the vehicle can monitor the system status in real time and make corresponding responses. The Control Instructions topic can be used to publish control instructions, so that the cloud system can send control instructions to the vehicle to achieve remote control or operation. The settings of specific topics can be customized according to specific needs and functional designs, and play an important role in distinguishing different message types or events in the Internet of Vehicles system. By subscribing to specific topics, vehicles can obtain the required information and realize the intelligence and adaptability of the system.

[0103] Optionally, the vehicle side can monitor the data update instructions or abnormal signals sent by the cloud in real time by subscribing to specific topics published by the cloud through MQTT. By subscribing to specific topics, the vehicle side can obtain important data instructions or abnormal information sent by the cloud in a timely manner. Once the vehicle side receives a message indicating that the data verification has failed or the version does not match, the system will automatically trigger the data reset process. The data reset process may include operations such as re-downloading data and restoring default settings to ensure the consistency and correctness of the data. By automatically triggering the data reset process, the system can quickly respond to data anomalies and avoid the impact of data errors on the system. In the basic data reset process, intelligent strategy judgment can also be introduced. For example, the data update timing is dynamically adjusted based on the vehicle driving status and network conditions. Through intelligent strategy judgment, the timing of data update can be flexibly adjusted according to the real-time vehicle driving status and network conditions, avoiding data reset during key driving operations and ensuring driving safety. The above intelligent strategies can improve the intelligence and adaptability of the system and better meet actual needs.

[0104] In summary, through the intelligent linkage mechanism of passive data acquisition and self-repair, the vehicle side can respond to the data update command or abnormal signal from the cloud in real time, automatically trigger the data reset process, and ensure the consistency and integrity of the data. Through intelligent strategy judgment, the system can flexibly adjust the data update timing according to the real-time situation, improve the intelligence and safety of the vehicle, and provide better data support and guarantee for the driving process. Among them, the data update command is a command sent from the cloud to the vehicle side to update the data or configuration information in the vehicle. The data update command usually contains information such as the data content to be updated, the update method, and the update time to guide the vehicle side system to perform the corresponding data update operation. Abnormal signals refer to signals or events generated when abnormal situations occur in the Internet of Vehicles system. These abnormal situations may include system failures, error states, abnormal events, etc., which require processing or response by the vehicle or cloud system. The generation of abnormal signals can help the system to detect problems in time and take corresponding measures to ensure the normal operation and safety of the system.

[0105] Alternatively, the passive mode generally refers to a state where the vehicle or device is in a state of waiting to receive an external command or signal, rather than actively initiating a request or operation. In the passive mode, the vehicle generally triggers a corresponding response or action by listening to an external signal or event, rather than initiating an action on its own.

[0106] The following further describes the process of how the vehicle receives the target message sent by the cloud in response to the message subscription request in this embodiment.

[0107] As an optional implementation method, receiving a cloud response message subscription request, and sending a target message includes: receiving a monitoring module response message subscription request, monitoring the data status of the initial data, and sending a target message, wherein the target message includes an update strategy, the update strategy is used to represent the update rules for updating the initial data, and the monitoring module is deployed on the cloud.

[0108] In an embodiment, the target information sent by the monitoring module in response to the message subscription request to monitor the data status of the initial data can be received, wherein the target message may include an update strategy, and the update strategy may represent the update rules for updating the initial data, and may also be called a repair strategy, such as a repair strategy for incremental updates, a repair strategy for full data reset, etc., which is only used as an example and is not specifically limited. The monitoring module can be deployed on the cloud. The monitoring module can also be called a monitoring system.

[0109] Optionally, the monitoring module plays a key role in it, responsible for real-time monitoring of the system operation status, data flow, detecting abnormal situations and taking corresponding measures. The monitoring module provides a data reporting portal, and realizes efficient, real-time transmission and storage of data through open source distributed stream processing platforms and message queue systems (such as Kafka) and message queue technologies such as MQTT. Kafka and MQTT are both popular messaging protocols that can support large-scale, high-concurrency data transmission to ensure data reliability and real-time performance. The monitoring module can perform real-time analysis on the reported data, including data content, format, frequency, etc. Through data analysis, system abnormalities, performance problems or potential risks can be discovered in a timely manner to help respond quickly. The monitoring module can classify and process the data based on the results of data analysis. For example, abnormal data is classified as abnormal repair and needs to be processed immediately; performance data is classified as report display, which is used to generate system performance reports for analysis and optimization. Once the monitoring module finds abnormal data, the corresponding exception handling process will be triggered immediately. By classifying abnormal data into abnormal repair categories, problems can be quickly identified and corresponding measures can be taken, such as automatic repair and alarm notification, to ensure the normal operation of the system. The monitoring module can be responsible for reporting data, including system performance reports, fault reports, etc. Through report display, system administrators can intuitively understand the operating status and performance of the system, identify problems in a timely manner, and make optimization improvements.

[0110] In general, the monitoring module plays an important role in monitoring, analyzing and processing data. By providing functions such as data reporting portal, real-time data analysis, data classification processing, abnormal repair and report display, the monitoring module can help the system monitor the operating status in real time, find problems and deal with them in a timely manner, and improve the stability and reliability of the system. The above settings help improve the operation and maintenance efficiency and management level of the vehicle, ensuring that the vehicle can operate continuously and efficiently.

[0111] Optionally, the monitoring system can automatically trigger the data repair process when it detects an abnormal situation. This means that the system can detect data anomalies in a timely manner and take appropriate repair measures to prevent the problem from further expanding or affecting system operation. The monitoring system has intelligent decision-making capabilities and can select the most appropriate repair strategy based on the type and severity of the anomaly. Depending on the abnormal situation, the system can adopt different repair strategies, such as incremental updates or full data resets, to minimize the impact of data inconsistency. By introducing an automated testing framework, such as an open source continuous integration and continuous delivery tool (Jenkins), the repaired data can be quickly verified. Through the automated testing framework, the effectiveness of the repair operation can be verified to ensure the correctness and effectiveness of the repair operation. The above closed-loop management can help the system quickly verify the repair effect, reduce manual intervention and improve repair efficiency.

[0112] Through the above method, the monitoring system can quickly respond and automatically trigger the data repair process when an abnormality is found. It has the intelligent decision-making ability to select the most appropriate repair strategy, and at the same time verify the repair operation through the automated testing framework to ensure the effectiveness and accuracy of the repair operation. The above intelligent upgraded automated repair mechanism can improve the stability and reliability of the system, reduce human errors and reduce the impact of abnormalities on the system.

[0113] Optionally, when the monitoring system detects an abnormal situation, it can not only automatically trigger the data repair process, but also has intelligent decision-making capabilities. This means that the most appropriate repair strategy can be selected according to the type and severity of the abnormality. For example, for mild data inconsistency problems, incremental updates can be used to repair them, and only part of the data is updated to achieve consistency; for serious version conflicts, a full data reset can be performed to ensure data integrity and consistency. In order to ensure the effectiveness of the repair operation, an automated testing framework (for example, Jenkins) is introduced to quickly verify the repaired data. The automated testing framework can automatically execute test cases to verify whether the repaired data meets the expected requirements and whether the system is running normally. Through the application of the automated testing framework, the test efficiency can be improved, human errors can be reduced, and the quality and reliability of the repair operation can be ensured.

[0114] Through the application of intelligent decision-making capabilities and automated testing frameworks, the monitoring system can quickly and accurately repair data when an abnormality is found, and ensure the effectiveness of the repair through testing and verification, thus forming a closed-loop management. The above intelligent upgraded automated repair mechanism not only improves the stability and reliability of the system, but also reduces human intervention, speeds up problem solving, and improves overall operation and maintenance efficiency.

[0115] In summary, the introduction of intelligent decision-making and automated testing makes the automated repair mechanism more intelligent and reliable, and can more effectively deal with various abnormal situations and ensure the normal operation of the system. At the same time, the implementation of closed-loop management also helps to continuously improve and optimize the repair process and improve the stability and maintainability of the system.

[0116] The following further describes the process of how the vehicle sends a data acquisition request to the cloud when the detection result of the vehicle data detection in this embodiment is that the initial data preset fails.

[0117] As an optional implementation method, step S104, in response to the detection result indicating that the initial data preset fails, sending a data acquisition request to the cloud, includes: in response to the detection result that the initial data preset on the vehicle fails, bidirectionally verifying the data preset interface of the vehicle and the cloud to obtain a verification result; in response to the verification result that the bidirectional verification of the vehicle and the data preset interface is successful, sending a data acquisition request to the cloud.

[0118] In an embodiment, if the detection result is that the initial data presetting on the vehicle fails, a two-way verification can be performed on the data presetting interface of the vehicle and the cloud to obtain a verification result. When the verification result is that the above two-way verification is successful, a data acquisition request can be sent to the cloud, wherein the data presetting interface on the cloud can be a cloud interface, which can also be called a cloud data presetting interface. The two-way verification can be a two-way Transport Layer Security (TLS) authentication.

[0119] Optionally, TLS is a secure transmission protocol used to provide security and integrity of data transmission in network communications. Bidirectional authentication means that when establishing a connection, both the server and the client are required to verify the identity of the client. Through the cloud interface based on TLS bidirectional authentication, the identity authentication of both parties in communication and the security of data transmission are ensured to prevent unauthorized access and data tampering.

[0120] Optionally, a transmission architecture that emphasizes both security and efficiency is adopted in the Internet of Vehicles environment, which mainly involves the process of implementing two-way TLS authentication by using the Hypertext Transfer Protocol Secure (HTTPS) protocol in the cloud application programming interface (API) in combination with the certificate chain mechanism of Engine X (Nginx). The cloud API interface uses the HTTPS protocol, namely the Hypertext Transfer Protocol Secure, to ensure the security of data transmission. HTTPS encrypts data transmission by adding the Secure Sockets Layer / Transport Layer Security (SSL / TLS) encryption communication protocol to the HTTP protocol, preventing data from being eavesdropped or tampered with during transmission and protecting data security.

[0121] Alternatively, Nginx is a high-performance open source web server software with load balancing, reverse proxy and other functions. Nginx's certificate chain mechanism means that Nginx can be used as an SSL terminal and is responsible for handling SSL connections. The certificate chain mechanism means that Nginx can configure and manage SSL certificates for encrypting and verifying data transmission.

[0122] Optionally, two-way TLS authentication means that in a TLS connection, both the client and the server need to verify each other's identity to ensure the security of communication. Through two-way TLS authentication, not only the data transmission process is encrypted, but also the authenticity of the data request and the reliability of the source are ensured by verifying the identities of both ends. This can effectively prevent security issues such as man-in-the-middle attacks and data forgery.

[0123] Optionally, by adopting the HTTPS protocol, Nginx's certificate chain mechanism and two-way TLS authentication, this secure transmission architecture effectively improves the security level of data interaction. Ensuring the security and privacy of data during transmission is an important cornerstone of data protection in the Internet of Vehicles environment. The above secure transmission architecture can protect user data from malicious attacks and theft, and improve the safety and reliability of the vehicle.

[0124] In the embodiment of the present invention, by adopting the HTTPS protocol and two-way TLS authentication, the data can be effectively prevented from being eavesdropped, tampered or forged during the transmission process, thereby improving the security of data transmission. Two-way TLS authentication can verify the identities of both parties in the data transmission, ensure the authenticity of the data request and the reliability of the source, reduce the risk of identity forgery and malicious attacks, and improve the reliability of data transmission. The use of two-way TLS authentication can effectively resist man-in-the-middle attacks, ensure the integrity and security of data transmission, and protect the privacy and confidentiality of data. Although encryption will increase certain computing overhead, the transmission speed and efficiency can be optimized in combination with the certificate chain mechanism of Nginx, balancing security and efficiency, and ensuring efficient data transmission. In summary, the above-mentioned transmission architecture design that emphasizes both security and efficiency effectively improves the security level of data interaction, provides an important cornerstone for data protection in the Internet of Vehicles environment, and ensures the security, reliability and efficiency of data transmission. The above design helps to ensure the security and stability of data transmission between the cloud and the vehicle, and provides reliable data protection and support for the intelligent driving system.

[0125] The following further describes the process of how the vehicle obtains the target data sent by the cloud in response to the data acquisition request in this embodiment.

[0126] As an optional implementation method, step S106, obtaining the target data sent by the cloud in response to the data acquisition request, includes: obtaining the target data queried from the database when the cloud recognizes that the identification information in the data acquisition request has been preset on the cloud, wherein the identification information is used to identify the vehicle, and the monitoring module deployed on the cloud is used to monitor the information status of the identification information; or, obtaining the initialization preset data of the cloud as the target data when the cloud recognizes that the identification information has not been preset on the cloud, wherein the database allows the storage of the initialization preset data, and the log data corresponding to the initialization preset data is monitored by the monitoring module.

[0127] In an embodiment, in the process of obtaining the target data sent by the cloud in response to the data acquisition request, the cloud can find the corresponding target data from the database when it recognizes that the identification information in the data acquisition request has been preset on the cloud. Alternatively, when the cloud recognizes that the identification information has not been preset on the cloud, the initialization preset data of the cloud can be used as the target data, wherein the identification information can be used to identify the vehicle, and can be a vehicle identification number (VIN for short). The monitoring module deployed on the cloud can be used to monitor the information status of the identification information. The database can be used to allow the storage of the initialization preset data, and can be a relational database management system (for example, MYSQL). The log data corresponding to the initialization preset data can be monitored by the monitoring module.

[0128] Optionally, to achieve the idempotence of the interface, each request is assigned a unique identifier, such as the vehicle VIN code. By tracking the unique identifier, different requests can be identified and distinguished, ensuring that each request is unique in the system. A processing status mapping table is maintained in the cloud to record the processing status and results of each request. By maintaining the mapping table, the processing process of the request can be tracked to ensure the consistency and integrity of the data and avoid unexpected changes in the data status. The use of idempotent design simplifies the error handling logic. Even if the network is unstable and causes request retransmission or multi-threaded concurrent calls, the system can correctly process the request, avoid data status changes caused by repeated operations, and ensure the consistency and integrity of the system data. The idempotent design provides a logical guarantee for the stability of the system. By tracking the unique identifier and processing the status mapping table, the system can effectively prevent data status changes caused by repeated requests, ensure data consistency and integrity, and improve the stability and reliability of the system.

[0129] In summary, the logical rigor of the idempotent design can effectively ensure the correctness and stability of the cloud data provisioning interface when processing requests. By tracking and processing the state mapping table with a unique identifier, the system can accurately identify and process each request, avoid data inconsistency problems caused by repeated operations, simplify error handling logic, and improve system stability and reliability. This design provides a solid logical guarantee for the system, ensures the consistency and integrity of data processing, and improves system stability and performance.

[0130] Optionally, idempotency means that multiple calls to the same request produce the same effect as a single call. In interface design, implementing idempotency can ensure that the same request will not produce unexpected changes to the data state, thereby improving the stability of the system and the consistency of the data. By tracking a unique identifier for each request, such as using the vehicle VIN code as a unique identifier, a processing state mapping table can be maintained in the cloud. It can ensure that the same request is not processed repeatedly, avoiding unexpected changes to the data state caused by repeated operations. Maintaining a processing state mapping table in the cloud can track the processing status of each request to ensure that the same request is not processed repeatedly. This mechanism simplifies the error handling logic and enables the system to better cope with situations such as network instability, request retransmission, or multi-threaded concurrent calls. Through idempotent design and maintenance of the processing state mapping table, data consistency and integrity can be ensured even in the case of network instability or request retransmission. This provides a solid logical guarantee for the stability of the system, avoids duplication or errors in data operations, and improves the reliability and stability of the system. Through the above method, the logical rigor of the interface can be ensured through idempotent design, the stability of the system and the consistency of data can be improved, the complexity of error handling can be reduced, and the reliable operation of the system can be guaranteed.

[0131] In the embodiment of the present invention, through the idempotent design, it is ensured that the effect of multiple calls of the same request is the same as that of a single call, and the data state change caused by repeated operations is avoided. This can ensure that the data operation in the system is stable and repeatable. The idempotent design can effectively prevent repeated operations from occurring in situations such as network instability or request retransmission, and avoid unexpected changes in data state. The system can identify repeated requests and reject repeated processing to maintain data consistency. The idempotent design simplifies the system's logic for error handling, and the system can ensure data consistency and integrity even in the event of network anomalies or request retransmission. This reduces the complexity and risk of system maintenance. By implementing the idempotence of the interface, the system can maintain the state consistency of data operations in abnormal situations, ensuring the correctness and stability of the data. This helps to reduce the risk of system failures and data corruption, and improve the stability and reliability of the system. In summary, the logical rigor of the idempotent design can effectively ensure the security and correctness of data operations, simplify the system's error handling logic, prevent repeated operations and data state changes, thereby improving the stability and reliability of the vehicle, and ensuring that the vehicle's data processing and operations in complex environments are logically rigorous.

[0132] Optionally, build a multi-level monitoring system, including log monitoring, performance monitoring, and exception monitoring, and use message queue technologies such as Kafka and ELK Stack for real-time data analysis and visualization.

[0133] Optionally, log monitoring is used to record data interaction logs between the vehicle and the cloud, performance monitoring is used to monitor the performance indicators of the system, and anomaly monitoring is used to detect system anomalies. These three types of monitoring form a comprehensive monitoring system that can help monitor the system operation status in real time and detect problems in a timely manner. Kafka, as a message queue technology, is used to collect data interaction logs between the vehicle and the cloud, realizing efficient data collection and transmission. Through Kafka, a large amount of log data can be processed and transmitted asynchronously to ensure high reliability and real-time performance of the data. Elastic search, log aggregation and basic stack (Elasticsearch, Logstash and Kibana Stack, referred to as ELK Stack) consists of Elasticsearch, Logstash and Kibana, and is used for real-time data analysis and visualization. Elasticsearch is used to store and index data, Logstash is used for data collection and processing, and Kibana is used for data visualization.

[0134] Optionally, the above combination can help analyze, query and display the collected log data, and provide an intuitive monitoring view. The monitoring system can provide real-time feedback on the progress and success rate of data provisioning, helping monitoring personnel understand the system operation. By monitoring the progress and success rate of data provisioning, problems can be discovered in a timely manner and corresponding measures can be taken to ensure the accuracy and timeliness of data provisioning. The monitoring system uses machine learning algorithms to predict potential abnormal trends and warn of possible problems in advance. Through the analysis of historical data and model training, the monitoring system can detect abnormal patterns and issue alarms before the abnormality occurs, helping to avoid potential failures and problems.

[0135] Through the construction of the above-mentioned multi-level monitoring system, it is possible to fully monitor and analyze the system operation status, discover problems in a timely manner and issue early warnings, improve the stability and reliability of the system, and ensure the smooth progress of the data provisioning process.

[0136] In an embodiment of the present invention, if it is necessary to confirm whether the data required by the vehicle is successfully preset, and to handle the preset failure in time, the vehicle can be tested for data to determine whether the data required in the vehicle are successfully preset, and obtain the corresponding test results. If the test result is that the required data (for example, initial data) is not successfully preset, a data acquisition request for re-presetting the data can be generated to re-determine the target data corresponding to the initial data from the cloud. The above data acquisition request can be actively sent to the cloud, and after receiving the data acquisition request, the cloud can determine the target data to be preset required by the vehicle. And the target data can be sent to the vehicle, and the vehicle can preset the target data. Through the above method, according to actual needs, a data acquisition request can be actively sent to the cloud to obtain the data to be preset, without waiting for the cloud to periodically send data, thereby achieving the purpose of saving data preset time. A large capacity of data can be uploaded to the vehicle at one time, avoiding the situation where the cloud splits the above data and sends small data one by one. The vehicle only needs to receive the required data once, without receiving it multiple times, thereby achieving the purpose of saving communication costs and transmission time. Thereby achieving the technical effect of improving the data presetting efficiency of the vehicle and solving the technical problem of low data presetting efficiency of the vehicle.

[0137] The technical solution of the embodiment of the present invention is illustrated below in conjunction with preferred implementation modes.

[0138] Currently, in the field of Internet of Vehicles, vehicle-side pre-set data management is a key link to ensure that the vehicle can start quickly and have basic operating information. However, there are some shortcomings in the current technical solutions, including low data transmission efficiency, insufficient security, data consistency issues, and lack of monitoring and automatic repair.

[0139] Alternatively, for the problem of low data transmission efficiency, the relevant data transmission method relies on periodically sending data one by one through protocols such as MQTT, which is inefficient and not suitable for large-scale data sets. In order to improve data transmission efficiency, you can consider using batch data transmission to package multiple data into one data packet for transmission, reduce the number of transmissions, and improve transmission efficiency.

[0140] Alternatively, for the problem of insufficient security, data security is crucial in the process of vehicle-side preset data management. The lack of an effective security authentication mechanism may cause data to be intercepted or tampered with during transmission, thereby affecting the integrity and authenticity of the data. In order to improve security, encrypted transmission can be used to encrypt the transmitted data to ensure security during data transmission.

[0141] Optionally, for data consistency issues, multiple issuance or update of data during the vehicle-side preset data management process may lead to data consistency issues. The lack of an effective idempotence control mechanism will lead to inconsistent vehicle-side data. In order to solve the data consistency problem, an idempotence mechanism can be introduced to ensure that the effects of multiple issuance or update of the same data are consistent, avoiding data inconsistency.

[0142] Alternatively, for the problem of lack of monitoring and automatic repair, the lack of an effective monitoring mechanism during the vehicle-side pre-set data management process may result in errors and abnormalities not being discovered and handled in a timely manner. In order to improve the monitoring and automatic repair capabilities, a real-time monitoring system can be introduced to monitor errors and abnormalities during data pre-set, and automatically handle pre-set failures or data abnormalities to ensure the stability and reliability of the data pre-set process.

[0143] Therefore, the above process still has the technical problem of low efficiency in presetting vehicle data.

[0144] However, the embodiment of the present invention proposes an efficient and secure data presetting method for the Internet of Vehicles. Through the data management strategy of the cloud and the vehicle-side collaboration, an efficient, secure, and self-healing data presetting system is constructed to support the intelligent driving experience. The goal of this solution is to solve the challenges faced by the current Internet of Vehicles technology in data consistency, security, and fault handling, and to provide a more reliable and efficient data presetting mechanism for intelligent driving. Through the collaboration between the cloud and the vehicle-side, real-time synchronization and interaction of data can be achieved. The cloud, as a data center, is responsible for the storage, processing, and management of data, and the vehicle-side can obtain the preset data issued by the cloud in a timely manner to achieve synchronous update of data. This collaborative approach can ensure the timeliness and consistency of data. The adoption of an efficient data management strategy can improve the transmission efficiency and processing speed of data. It is committed to improving the security of the data presetting system, ensuring the security of data during transmission through encryption algorithms and secure transmission protocols, preventing data from being maliciously tampered with or unauthorized access, thereby ensuring the integrity and authenticity of the data. By introducing a self-healing mechanism, it can automatically identify and repair when a system failure or abnormal situation occurs. This automated approach can reduce the need for manual intervention and improve the stability and reliability of the system.

[0145] In summary, in the embodiments of the present invention, through the coordination between the cloud and the vehicle, efficient data management strategies, security assurance and self-repair capabilities, a more efficient, secure and stable data pre-setting system is constructed to provide reliable data support for intelligent driving and enhance the intelligent driving experience. This achieves the technical effect of improving the data pre-setting efficiency of the vehicle and solves the technical problem of low data pre-setting efficiency of the vehicle.

[0146] In this embodiment, Figure 2 is a flow chart of an efficient and secure data presetting method for Internet of Vehicles according to an embodiment of the present invention. Figure 2 As shown, the method can be executed by the vehicle side A, the cloud side B and the monitoring module C, which may include the following steps:

[0147] Step S201, power on the vehicle for inspection.

[0148] In this embodiment, confirming whether a certificate exists during the vehicle-side power-on check means that when the vehicle system is started or powered on, it can be checked whether the vehicle has a specific certificate file to ensure normal operation and secure communication.

[0149] Optionally, after the vehicle system is powered on, it will start running the system software and hardware modules to prepare for the normal operation of the system. During the power-on check, the system will check whether there is a specific certificate file in the local storage. These certificate files are usually used for security purposes such as identity authentication, encrypted communication or access control. Certificates can include digital certificates, digital identity certificates, digital key certificates, etc. Digital certificates are used to verify the authenticity and integrity of data, digital identity certificates are used to verify the identity of users or devices, and digital key certificates are used to encrypt communications and protect data security. The role of certificates in vehicle systems is very important. Through certificates, the system can communicate and transmit data securely to ensure the security and integrity of data. Certificates can also be used for identity authentication to prevent unauthorized access and data tampering. Check the validity and expiration of certificates regularly, and update certificates in a timely manner to ensure the security and normal operation of the system. The update of certificates usually requires digital signatures and authentication to ensure the legitimacy and validity of the certificates.

[0150] In general, the purpose of confirming the existence of a certificate during the vehicle-side power-on check is to ensure the security and normal operation of the system. Certificates play an important role in vehicle systems and are used for secure communications, identity authentication, and data protection. By checking the existence and validity of certificates, the system can ensure the secure transmission of data and the security of the system, and prevent potential security threats. Therefore, the existence and validity of certificates are crucial to the security and normal operation of vehicle systems.

[0151] Step S202, determining whether a certificate exists.

[0152] In this embodiment, during the power-on check, it can be detected whether there is a certificate in the vehicle. If not, step S203 can be executed.

[0153] Step S203: Active data acquisition.

[0154] In this embodiment, if the certificate does not exist, it can be said that data pre-setting has failed. At this time, the vehicle side A can actively obtain the data to be pre-set from the cloud side B.

[0155] Optionally, the active acquisition logic optimization during the vehicle startup phase includes health checks, data integrity, timeliness verification, and optimized network connection management strategies. During the vehicle startup phase, the vehicle first performs a health check on the local data. The above process covers multiple aspects, including whether there is preset data, data integrity and timeliness verification. Through health checks, the vehicle can ensure that the system's data is in good condition and avoid using invalid data, which may include damaged data or outdated data, thereby improving the stability and reliability of the system. In addition to checking whether there is preset data, it should also be extended to verify the integrity and timeliness of the data. Data integrity verification ensures that the data has not been tampered with or damaged, and timeliness verification ensures that the data is up-to-date and valid. Through these verifications, the vehicle can ensure that the data used is accurate, complete, and timely, thereby improving the accuracy and efficiency of the system. Optimized network connection management strategies (such as HTTP2 multiplexing). If the data check fails, the vehicle will use optimized network connection management strategies, such as using HTTP2 multiplexing technology, to efficiently initiate cloud API calls to achieve fast download of large amounts of data. HTTP2's multiplexing allows multiple data streams to be transmitted simultaneously over a single connection, reducing the number of connections and improving data transmission efficiency, thereby reducing delays when starting a vehicle and speeding up system startup.

[0156] That is to say, during the vehicle startup phase, the vehicle first performs a health check on the local data. This process not only includes the existence of preset data, but also extends to the integrity and timeliness of the data. If the data passes the check, it is used directly. Otherwise, through the optimized network connection management strategy (such as HTTP2 multiplexing), cloud API calls are efficiently initiated to achieve fast download of large amounts of data and reduce startup delays.

[0157] In summary, by performing health checks, data integrity, and timeliness verification during the vehicle startup phase, as well as optimizing network connection management strategies, the vehicle side can ensure the use of accurate, complete, and timely data during the startup process, improve the startup speed and stability of the system, optimize the user experience, and provide important guarantees for the normal operation of the intelligent driving system. The above measures help reduce data transmission delays and improve system responsiveness and performance.

[0158] Step S204: data preset API.

[0159] In this embodiment, through an optimized network connection management strategy, cloud API calls are efficiently initiated to achieve fast download of large amounts of data and reduce startup delays.

[0160] Optionally, in the Internet of Vehicles environment, by adopting a transmission architecture design that emphasizes both security and efficiency, including using the HTTPS protocol and Ngi nx's certificate chain mechanism to implement two-way TLS authentication, the security and reliability of the data transmission process can be ensured. By encrypting data transmission, preventing data eavesdropping and tampering, and verifying the authenticity of data requests and the reliability of the source, the security level of data interaction is effectively improved, becoming an important cornerstone of data protection in the Internet of Vehicles environment. The above design not only ensures the security of data transmission, but also takes into account the efficiency of data interaction, providing a solid guarantee for the stable operation and data security of the Internet of Vehicles system.

[0161] Step S205, determining whether the VIN code has been preset.

[0162] In this embodiment, it can be determined whether the VIN code has been preset, and if so, step S209 can be executed, otherwise, step S206 can be executed.

[0163] Optionally, the rigor and stability of the system logic can be ensured by implementing interface idempotence. Specifically, interface idempotence means that no matter how many times the same request is called repeatedly, the state of the system should remain consistent and will not cause unexpected changes in the data state. Methods for implementing interface idempotence include tracking each request with a unique identifier, which can usually be tracked using a unique identifier such as a vehicle VIN code. A processing status mapping table is maintained in the cloud to record the processing status of each request to ensure that the same request is not processed repeatedly or cause changes in the data state. This mechanism can simplify the error handling logic and ensure data consistency and integrity even when the network is unstable and causes request retransmissions or multi-threaded concurrent calls.

[0164] By implementing interface idempotence, data anomalies or state changes caused by repeated or concurrent requests can be effectively prevented, ensuring system stability and data accuracy. This design mechanism provides a solid logical guarantee for the system, reduces the complexity of error handling, improves system reliability and stability, and also enhances the system's ability to withstand pressure in the face of network fluctuations or high concurrency. Therefore, the implementation of interface idempotence is of great significance to the logical rigor and stability of the intelligent driving system in the vehicle.

[0165] Step S206, initializing preset data.

[0166] In this embodiment, the VIN code is a unique identification number of the vehicle, which is used to identify and recognize the vehicle. In the vehicle networking environment, if the VIN code is not preset, that is, not stored in the device or system in advance, an operation of initializing the preset data can be performed.

[0167] For example, when using the Internet of Vehicles system, users can initialize it by entering the VIN code through the interface. The system provides an input box in which the user enters the VIN code, and the VIN code is stored in the device or system as preset data. Some Internet of Vehicles devices may be equipped with devices such as scanners or cameras, and users can initialize by scanning the VIN code on the vehicle. The system will obtain the VIN code information through scanning and store it in the device or system. In some cases, the VIN code of the vehicle may be obtained remotely by the vehicle manufacturer or related service providers. When the user initializes in the system, he can choose to obtain the VIN code remotely. The system will obtain the VIN code from the remote server and store it in the device or system. The above are some possible ways to initialize the preset VIN code data. Through these methods, it can be ensured that the Internet of Vehicles system can correctly identify and identify the vehicle, providing an accurate vehicle information basis for subsequent data interaction and functional operations.

[0168] Step S207, store in MYSQL.

[0169] In this embodiment, the above successfully initialized data can be stored in MYSQL.

[0170] Optionally, after initializing the preset data, storing the data in the MYSQL database may generally include the following steps: A connection to the MYSQL database may be established in the vehicle's application. The connection may be implemented using a client library or an object-relational mapping tool provided by MYSQL. Create a table in the MYSQL database to store the preset data. The structure of the table should match the properties of the preset data. The table structure may be created using SQL statements or ORM tools. Insert the initialized preset data into the created table. The INSERT statement may be used to insert data one by one or to insert multiple data in batches. In general, after initializing the preset data, the process of storing the data in the MYSQL database includes steps such as connecting to the database, creating a table structure, and inserting data. Through the above method, the preset data can be effectively stored in the MYSQL database for subsequent data query and operation.

[0171] Step S208, query MYSQL to obtain preset data.

[0172] In this embodiment, the preset data can be queried from MYSQL.

[0173] Optionally, use the client library or object-relational mapping tool provided by MYSQL to achieve the connection. According to the attributes and table structure of the preset data, write the corresponding SQL query statement to obtain the preset data. Execute the written query statement, send a request to the MYSQL database and obtain the query result. The obtained result can be the data of the entire table, or specific data can be filtered out according to the conditions. After processing the query results, the results can be displayed to the user or further processed and analyzed in the application.

[0174] Through the above method, you can effectively query the MYSQL database to obtain the preset data. Connecting to the database, writing query statements, executing queries, and processing query results are the steps to complete data query. Through the above steps, you can easily obtain the preset data and perform corresponding operations and displays in the application.

[0175] Step S209, assembling interface response data.

[0176] In this embodiment, after the initialization preset data is stored in MYSQL, the interface response data can be assembled.

[0177] Optionally, the preset data that has been stored can be queried in the MYSQL database. The queried preset data can be processed and formatted into the data structure required by the interface. According to the requirements of the interface design, the query results may need to be converted, filtered or processed to meet the format and content of the interface response. Assemble the processed preset data into the data format of the interface response. This includes operations such as building the response data structure, filling in data fields, and setting the response status code. Return the assembled interface response data to the caller. It can be encrypted with TLS, and the encrypted data is returned to the vehicle end through HTTP response.

[0178] Optionally, in the process of assembling the interface response data, it is necessary to consider the handling of various abnormal situations, such as data query failure, data processing error, etc. A unified error code and error message can be defined to convey the error information to the caller.

[0179] Through the above method, the initialization preset data can be stored in MYSQL, and after processing and assembly, the response data that meets the interface specification can be obtained and correctly returned to the caller. The above process can ensure the integrity, accuracy and standardization of the interface response data, and improve the maintainability and scalability of the system.

[0180] Step S210, decrypt and store locally.

[0181] In this embodiment, after the vehicle receives the TLS-encrypted data, it can decrypt it to obtain the original data and store it locally.

[0182] Optionally, the vehicle side can use the TLS protocol to decrypt the received encrypted data. TLS decryption usually requires the use of certificates and private keys for decryption operations. The vehicle side needs to have the corresponding certificates and private keys to perform decryption operations. Once the data is successfully decrypted using the TLS protocol, the vehicle side can obtain the original data. The decryption process should perform correct decryption operations according to the encryption algorithm and key to ensure the accuracy and integrity of the data. The decrypted original data can be stored in the local storage device of the vehicle side, such as a database, file system, etc. According to the needs and data types, select the appropriate storage method and ensure the security and reliability of data storage. After storing locally, the vehicle side can further process, analyze or apply the data. This may involve operations such as parsing, converting, and filtering data to meet specific needs.

[0183] In summary, after receiving the TLS-encrypted data on the vehicle side, the TLS decryption operation can be performed to obtain the original data and store it locally. The correct decryption and storage process can ensure the security, integrity and availability of the data, and provide the necessary data support for the functions and functions of the vehicle side system.

[0184] Step S211, periodically perform data health self-check.

[0185] In this embodiment, the vehicle side can ensure the stability of the system and the integrity of the data by implementing a periodic data health self-check function.

[0186] Optionally, the vehicle side can set a period for data health self-check, such as performing a self-check once a day, week, or month. This is only an example and is not limited to specific examples. Periodic self-checks can help to detect potential problems in a timely manner and deal with them. The vehicle side can write programs or scripts to regularly check the integrity of the data stored locally. This includes checking whether the data is missing, whether it conforms to the expected format, whether there are abnormal values, etc. When performing a data health self-check, the vehicle side can verify the accuracy of the data and compare the stored data with the expected results or standard data to ensure the accuracy of the data. During the data health self-check process, the vehicle side can also check the usage of local storage space to ensure that the storage device has enough space to store the data. When performing a data health self-check, the vehicle side can record the self-check results and generate logs for subsequent analysis and tracking of problems. At the same time, an alarm mechanism can be set to send an alarm to notify relevant personnel in a timely manner when problems or abnormal situations are found.

[0187] By periodically performing data health self-checks, the vehicle side can promptly detect data anomalies or problems, thus improving the stability and reliability of the system. At the same time, data health self-checks can also help prevent data loss or damage, and ensure data integrity and accuracy. The above health self-check mechanism is of great significance to the normal operation of the Internet of Vehicles system and data quality assurance.

[0188] Step S212: whether abnormal data is found.

[0189] In this embodiment, during the data health self-check process, it can be determined whether abnormal data is found, and if so, step S213 can be executed.

[0190] Optionally, during the data health self-check process, if abnormal data is found, the following steps are usually required: Check the integrity of the data, including checking whether there is missing data, duplicate data, or incomplete data. The data can be judged to be complete by comparing the expected data volume with the actual data volume. Verify the accuracy of the data and compare the stored data with the expected results or standard data. If the data does not match the expected results, there may be abnormal data. Check whether the data conforms to the expected format and specifications. If the data format does not meet the requirements, it may cause data processing errors or anomalies. Detect whether there are abnormal values ​​in the data, such as out-of-range values, unreasonable data, etc. Abnormal values ​​may affect the accuracy of the data and the analysis results. Check the correlation and consistency between the data to ensure that the correlation between different data is correct and coordinated. Once abnormal data is found, it can be marked and processed according to the specific situation. Possible processing methods include repairing data, deleting abnormal data, and re-collecting data. Record the abnormal data found, the type of abnormality, and the processing process, and generate corresponding logs. Set alarm rules according to the severity of the abnormality and notify relevant personnel to handle the abnormal situation in time.

[0191] Through the above methods, abnormal data can be discovered and processed in a timely manner during the data health self-check process to ensure the quality and accuracy of system data. Continuously improving the data health self-check mechanism and processing abnormal data in a timely manner can improve the stability of the system and data quality and ensure the normal operation of the system.

[0192] Step S213, collecting abnormal data.

[0193] In this embodiment, the abnormal data is collected to analyze and process the abnormal situations occurring in the system so as to improve the stability and performance of the system.

[0194] Optionally, a corresponding monitoring mechanism can be set up in the system to monitor abnormal situations that occur in the system. Monitoring can include system logs, performance indicators, error logs, etc. Once an abnormal situation is monitored, it is necessary to identify the abnormal data and determine the type of abnormality. The abnormal data can be automatically identified by setting rules or thresholds, or the monitoring data can be manually reviewed to confirm the abnormal situation. For the identified abnormal data, relevant information needs to be recorded, including the time when the abnormality occurred, the type of abnormality, the specific content of the abnormal data, etc. This information is helpful for subsequent analysis and processing. Collect abnormal data and store it in a suitable location, such as a database, log file or monitoring system. Ensure the integrity and traceability of abnormal data to facilitate subsequent analysis and processing. Analyze the collected abnormal data to find out the cause and root cause of the abnormality. In-depth analysis can be performed through data analysis tools, log analysis tools, etc. to further handle the abnormal situation. According to the analysis results of the abnormal data, take corresponding measures to handle the abnormal situation. Possible processing methods include repairing data, optimizing system configuration, updating software versions, etc. Regularly review the collected abnormal data, analyze the evolution trend and law of abnormal situations, and continuously improve the monitoring mechanism and abnormality handling process to improve the stability and performance of the system.

[0195] Through the above method, we can effectively collect abnormal data in the system, discover and handle abnormal situations in time, and ensure the normal operation of the system and data quality. The collection and processing of abnormal data is of great significance to system operation and performance optimization.

[0196] Step S214: real-time monitoring and analysis.

[0197] In this embodiment, the monitoring module C can monitor and analyze the reported data in real time.

[0198] Optionally, the monitoring module plays a key role in the system, responsible for real-time monitoring of the system operation status and data flow, detecting abnormal situations and taking corresponding measures.

[0199] Optionally, the monitoring module provides a data reporting portal, and realizes efficient, real-time transmission and storage of data through message queue technologies such as Kafka and MQTT. Kafka and MQTT are both popular messaging protocols that can support large-scale, high-concurrency data transmission and ensure data reliability and real-time performance. The monitoring module will perform real-time analysis on the reported data, including the content, format, frequency, etc. of the data. Through data analysis, system abnormalities, performance problems or potential risks can be discovered in a timely manner, helping system administrators or operation and maintenance personnel to respond quickly. The monitoring module will classify and process the data based on the results of data analysis. For example, abnormal data is classified as abnormal repair and needs to be processed immediately; performance data is classified as report display and is used to generate system performance reports for analysis and optimization. Once the monitoring module finds abnormal data, the corresponding exception handling process will be triggered immediately. By classifying abnormal data as abnormal repair, the system can quickly identify the problem and take corresponding measures, such as automatic repair, alarm notification, etc., to ensure the normal operation of the system. The monitoring module is also responsible for displaying data in reports, including system performance reports, fault reports, etc. Through report display, system administrators can intuitively understand the system's operating status and performance, identify problems in a timely manner and make optimization improvements.

[0200] In summary, the monitoring module plays an important role in monitoring, analyzing and processing data in the system. By providing functions such as data reporting portal, real-time data analysis, data classification processing, abnormal repair and report display, the monitoring module can help the system monitor the operating status in real time, find problems and deal with them in a timely manner, and improve the stability and reliability of the system. This design helps to improve the system's operation and maintenance efficiency and management level, ensuring that the system can operate continuously and efficiently.

[0201] Step S215, continuously tracking the progress, success rate, and abnormal frequency of data presetting.

[0202] In this embodiment, the progress, success rate, and abnormal frequency of data presetting can be continuously tracked.

[0203] Optionally, in this embodiment, a multi-level monitoring system is proposed, which mainly includes three components: log monitoring, performance monitoring and exception monitoring. The data interaction logs of the vehicle and the cloud are collected and recorded by the log monitoring system. The log records the operation and events of the system, which can help the monitoring system track the operation of the system, user operations, etc. The efficient collection and transmission of logs can be achieved by using message queue technologies such as Kafka. The log monitoring system can help monitoring personnel understand the operating status of the system, discover abnormal situations in time and deal with them. The performance monitoring system is used to monitor the performance indicators of the system, such as memory usage, network bandwidth, etc. By monitoring these performance indicators, the performance bottlenecks and resource bottlenecks of the system can be discovered in time, the system performance can be optimized, and the system operation efficiency can be improved. The performance monitoring system usually provides real-time monitoring and historical data query functions to help monitoring personnel understand the performance of the system. The exception monitoring system is used to monitor whether the system has abnormal situations in real time. By monitoring the logs, performance indicators and other data of the system, anomaly detection and early warning can be performed. The monitoring system can predict potential abnormal trends through machine learning algorithms, discover potential problems in advance, and take timely measures to deal with them to avoid system failures or data loss. Combined with ELK Stack for real-time data analysis and visualization, monitoring data can be centrally managed, analyzed, and displayed.

[0204] Step S216, generating report data.

[0205] In this embodiment, the report data is generated to visualize and analyze indicators such as the progress of data preset, success rate, and abnormal frequency that are continuously tracked.

[0206] Optionally, determine the data presetting indicators that need to be displayed, including progress, success rate, abnormal frequency, etc. Clarify the purpose and content of the report according to the needs. Collect relevant data by continuously tracking the process of data presetting, including progress updates, success and failure situations, abnormal situations, etc. Organize the data to ensure that the data is accurate and complete. Analyze and calculate the collected data to calculate indicators such as presetting progress, success rate, abnormal frequency, etc. Data cleaning, screening, statistics, etc. can be performed as needed. Design the style, layout, and chart type of the report according to the determined report requirements. Select appropriate data visualization tools to convert the calculated indicator data into charts, tables, etc. to generate report data. The generated report data can be displayed and shared with relevant personnel through emails, sharing links, report platforms, etc. Ensure the readability and understandability of the report to help decision makers quickly understand the situation of data presetting. Regularly analyze report data to understand the trends and changes in data presetting and identify problems and improvement points. Adjust data presetting strategies and processes in a timely manner based on report data feedback.

[0207] Through the above method, report data including data provisioning progress, success rate, abnormal frequency and other indicators can be generated to help the team and management understand the data provisioning situation, find problems in time and optimize them. The generation and analysis of report data is of great significance for the monitoring and improvement of data provisioning work.

[0208] Step S217, identifying abnormal data on the vehicle side.

[0209] In this embodiment, by continuously tracking indicators such as the progress, success rate, and abnormal frequency of data preset, it can help identify abnormal data on the vehicle side.

[0210] Optionally, continuously track indicators such as the progress, success rate, and frequency of abnormalities of data provisioning. You can use a monitoring system or data analysis tool to monitor changes in these indicators in real time. Regularly check the trends and changes of these indicators. Set corresponding thresholds and alarm rules based on historical data and requirements. When the data provisioning indicator exceeds the set threshold, an alarm is triggered to indicate that abnormal data may exist. Once an alarm is triggered, the abnormal situation needs to be analyzed. For example, check the source, occurrence time, specific content, and other information of the abnormal data to determine the cause and scope of the abnormality. Compare and verify the abnormal data and compare it with the data under normal conditions. Check whether the abnormal data meets the expected results and whether there are errors or abnormalities. Troubleshoot and handle the identified abnormal data. You can take appropriate measures according to the specific situation, such as repairing data, re-presetting data, and optimizing the data provisioning process. Based on the identified abnormal data and processing results, continuously optimize the data provisioning process and improve data quality control measures. Continuous iteration and improvement can reduce the incidence and impact of abnormal data.

[0211] In the above method, by continuously tracking the progress, success rate, and abnormal frequency of data presetting, abnormal data on the vehicle side can be identified and processed in a timely manner to ensure the stability of the system and data quality. Timely detection and processing of abnormal data is crucial to ensure the normal operation of the Internet of Vehicles system and data accuracy.

[0212] Step S218: issue a repair instruction.

[0213] In this embodiment, after identifying abnormal data on the vehicle side, the monitoring module sends a repair instruction to the vehicle side.

[0214] Optionally, the monitoring module detects abnormal data on the vehicle side by continuously monitoring and analyzing the data preset indicators. Abnormal data may include data loss, data errors, abnormal data format, etc. Once abnormal data is found, the monitoring module needs to determine the repair strategy based on the abnormal situation. The monitoring module generates a repair instruction based on the determined repair strategy. The repair instruction should include clear repair content, execution time, execution conditions and other information. The monitoring module sends the repair instruction to the vehicle side through the communication channel with the vehicle side. Ensure the security and integrity of the repair instruction. After receiving the repair instruction, the vehicle side performs the corresponding repair operation. The monitoring module should continuously monitor the execution of the repair operation and collect the repair results in a timely manner. Ensure that the repair operation is successfully executed and the abnormal data problem is solved. According to the repair results, the monitoring module should promptly feedback the repair situation to the relevant personnel and record the repair process and results. This is helpful for subsequent analysis of the causes of abnormal data and improvement of the data preset process.

[0215] Through the above method, the monitoring module can timely identify abnormal data on the vehicle side and send repair instructions to the vehicle side to ensure the accuracy and stability of system data. Timely processing of abnormal data is crucial to ensure the normal operation and data quality of the Internet of Vehicles system.

[0216] Step S219, subscribe and execute repair instructions.

[0217] In this embodiment, after receiving the repair instruction, the vehicle end can perform corresponding processing by subscribing to and executing the repair instruction.

[0218] Optionally, the vehicle side needs to establish a subscription mechanism for receiving repair instructions. You can subscribe to the receipt of repair instructions by establishing a connection with the communication channel of the cloud. Once the repair instruction is received, the vehicle side needs to parse the instruction content, including information such as the repair content, execution conditions, and execution time. Ensure that the repair instruction can be correctly understood and executed. According to the parsed repair instruction content, the vehicle side performs the corresponding repair operation. It may involve operations such as re-presetting data, updating software versions, and adjusting parameter settings. After executing the repair operation, the vehicle side should feedback the execution result to the monitoring module. Including information such as whether the repair operation is successful, execution time, and abnormal conditions. Ensure that the monitoring module can understand the repair situation in a timely manner. The vehicle side should record the process and results of executing the repair operation and generate corresponding logs. This helps to track the execution of the repair operation and provide a reference for subsequent analysis and optimization. The vehicle side can regularly check the effect and results of the repair operation to verify whether the repair instruction successfully solves the abnormal data problem. Timely discover problems and re-execute the repair operation to ensure data accuracy and system stability.

[0219] Through the above method, the vehicle side can subscribe and execute repair instructions, effectively handle abnormal data and ensure the normal operation of the system. Establishing a complete subscription and execution mechanism will help the vehicle side respond to repair instructions in a timely manner, ensuring data quality and system stability.

[0220] In the embodiment of the present invention, the HTTPS protocol is used for one-time presetting of large-capacity data, instead of transmitting data in batches like the traditional MQTT protocol. This method significantly improves the efficiency of data transmission and can complete the data transmission process faster. At the same time, the use of the HTTPS protocol also enhances the security of the data. The HTTPS protocol has the function of encrypting and transmitting data, which can effectively prevent the data from being stolen or tampered with, and improve the security of data transmission. The idempotent interface design is adopted to ensure the final consistency of data operations. The advantage of the idempotent interface design is that even if repeated requests are received, the system can ensure that only one operation is performed, avoiding duplication or inconsistency of data. The consistency and reliability of data can be improved to ensure the integrity of data. A monitoring mechanism and an automatic repair process are established, and automatic abnormal monitoring and repair are realized through intelligent decision-making capabilities. The need for manual intervention can be reduced and the stability and robustness of the system can be improved. The monitoring mechanism can monitor the system operation status in real time, find abnormal situations and take measures in time. The automatic repair process can automatically trigger the repair operation when a problem is found, thereby improving the reliability and self-repair ability of the system. Thereby achieving the technical effect of improving the data presetting efficiency of the vehicle and solving the technical problem of low data presetting efficiency of the vehicle.

[0221] According to another aspect of the embodiment of the present invention, corresponding to the embodiment of the above-mentioned vehicle data presetting method, this specification also provides a vehicle data presetting system, Figure 3 FIG. 1 is a structural block diagram of a vehicle data presetting system according to an embodiment of the present invention. Figure 3 As shown, the vehicle data pre-setting system 300 may include: a vehicle 302 and a cloud 304 .

[0222] Vehicle 302 is used to perform data detection on the vehicle and obtain a detection result, wherein the detection result is used to indicate whether the initial data required for the operation of the vehicle is successfully preset; in response to the detection result indicating that the initial data preset fails, a data acquisition request is sent to the cloud, wherein the data acquisition request is used to request to obtain target data, the target data is data allowed to be preset on the vehicle, and the data volume of the target data is greater than a data volume threshold; the vehicle is used to preset the target data on the vehicle.

[0223] The cloud 304 is used to respond to the data acquisition request, obtain the target data, and send the target data to the vehicle.

[0224] In the data presetting system of the vehicle of this embodiment, if it is necessary to confirm whether the data required by the vehicle is successfully preset, and to handle in time when the preset fails, the vehicle can be tested for data to determine whether the data required in the vehicle are successfully preset, and obtain the corresponding test results. If the test result is that the required data (for example, initial data) is not successfully preset, a data acquisition request for re-presetting the data can be generated to re-determine the target data corresponding to the initial data from the cloud. The vehicle can actively send the above data acquisition request to the cloud, and the cloud can determine the target data to be preset required by the vehicle after receiving the data acquisition request. And the target data can be sent to the vehicle, and the vehicle can preset the target data. Through the above method, according to actual needs, a data acquisition request can be actively sent to the cloud to obtain the data to be preset, without waiting for the cloud to periodically send data, thereby achieving the purpose of saving data preset time. A large capacity of data can be uploaded to the vehicle at one time, avoiding the situation where the cloud splits the above data and sends small data one by one. The vehicle only needs to receive the required data once, without receiving it multiple times, thereby achieving the purpose of saving communication costs and transmission time. Thereby achieving the technical effect of improving the data presetting efficiency of the vehicle and solving the technical problem of low data presetting efficiency of the vehicle.

[0225] According to another aspect of the embodiment of the present invention, corresponding to the embodiment of the above-mentioned vehicle data presetting method, this specification also provides a vehicle data presetting device, Figure 4 is a structural block diagram of a vehicle data presetting device according to an embodiment of the present invention. Figure 4 As shown, the vehicle data presetting device 400 may include: a detection unit 402 , a sending unit 404 , an acquisition unit 406 and a presetting unit 408 .

[0226] The detection unit 402 is used to perform data detection on the vehicle to obtain a detection result, wherein the detection result is used to indicate whether the initial data required for the operation of the vehicle is successfully preset.

[0227] The sending unit 404 is used to send a data acquisition request to the cloud in response to the detection result indicating that the initial data preset fails, wherein the data acquisition request is used to request to obtain target data, the target data is data allowed to be preset on the vehicle, and the data volume of the target data is greater than the data volume threshold.

[0228] The acquisition unit 406 is used to acquire the target data sent by the cloud in response to the data acquisition request.

[0229] The presetting unit 408 is used to preset the target data on the vehicle.

[0230] In this embodiment, the following units are provided in the data presetting device of the vehicle: a detection unit, which is used to perform data detection on the vehicle and obtain a detection result, wherein the detection result is used to indicate whether the initial data required for the operation of the vehicle is successfully preset; a sending unit, which is used to send a data acquisition request to the cloud in response to the detection result indicating that the initial data preset fails, wherein the data acquisition request is used to request to obtain target data, the target data is data that is allowed to be preset on the vehicle, and the data volume of the target data is greater than the data volume threshold; an acquisition unit, which is used to obtain the target data sent by the cloud in response to the data acquisition request; a presetting unit, which is used to preset the target data on the vehicle. Thus, the purpose of saving communication costs and transmission time is achieved. In addition, the technical effect of improving the data presetting efficiency of the vehicle is achieved, and the technical problem of low data presetting efficiency of the vehicle is solved.

[0231] According to another aspect of an embodiment of the present invention, a vehicle is provided, which may be an autonomous driving vehicle, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes any one of the above methods when running.

[0232] Figure 5 is a structural block diagram of an automatic driving vehicle according to an embodiment of the present invention. Figure 5 As shown, the components of the autonomous driving vehicle 500 include but are not limited to a memory 510 and a processor 520. The processor 520 is connected to the memory 510 via a bus 530, and the database 550 is used to store data.

[0233] The autonomous vehicle 500 may also include an access device 540 that enables the autonomous vehicle 500 to communicate via one or more networks 560. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 540 may include one or more of any type of wired or wireless network interface (e.g., a network interface card (NIC)), such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a World Wide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, a Near Field Communication (NFC) interface, and the like.

[0234] In one embodiment of the present disclosure, the above components of the autonomous driving vehicle 500 and Figure 5 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Figure 5 The structure block diagram of the autonomous driving vehicle shown is for illustrative purposes only and is not intended to limit the scope of the present disclosure. Those skilled in the art may add or replace other components as needed.

[0235] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium including a stored executable program, wherein when the executable program runs, the device where the storage medium is located is controlled to execute any one of the above methods.

[0236] According to another aspect of an embodiment of the present invention, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, any one of the above methods is implemented.

[0237] It should be noted that the serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0238] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0239] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic, for example, the division of units can be a logical function division, and there can be other division methods in actual implementation, 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, 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.

[0240] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0241] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0242] 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, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, referred to as Read-Only Memory), random access memory (RAM, referred to as Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0243] The above are only preferred embodiments 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 the scope of protection of the present invention.

Claims

1. A vehicle data presetting method, characterized in that: include: Performing data detection on the vehicle to obtain a detection result, wherein the detection result is used to indicate whether the initial data required for the operation of the vehicle is successfully preset; In response to the detection result indicating that the initial data presetting fails, sending a data acquisition request to the cloud, wherein the data acquisition request is used to request acquisition of target data, the target data is data that is allowed to be preset on the vehicle, and the data volume of the target data is greater than a data volume threshold; Acquire the target data sent by the cloud in response to the data acquisition request; The target data is preset on the vehicle.

2. The method according to claim 1, characterized in that Perform data detection on the vehicle and obtain the detection results, including: Detecting the operating state of the vehicle; Based on the running status, data detection is performed on the vehicle to obtain the detection result.

3. The method according to claim 2, characterized in that Based on the running state, data detection is performed on the vehicle to obtain detection results, including: In response to the running state being the startup state, performing data detection on the digital certificate on the vehicle to obtain the detection result, wherein the digital certificate is at least used to record the initial data; In response to the operating state being a driving state, a target message sent from the cloud is received, wherein the target message is used to represent the detection result.

4. The method according to claim 3, characterized in that In response to the running state being the startup state, performing data detection on the digital certificate on the vehicle to obtain the detection result includes: In response to the running state being the startup state, performing data detection on the attribute information of the digital certificate to obtain the detection result, wherein the attribute information is used to represent the integrity index and / or version of the digital certificate, and the detection result is used to represent whether the integrity index of the digital certificate reaches an integrity index threshold and / or whether the version reaches a version threshold, and the integrity index is used to represent the integrity of the digital certificate; The method further includes: in response to the integrity index being lower than the integrity index threshold and / or the version being lower than the version threshold, determining that the detection result is a failure to pre-install the initial data on the vehicle.

5. The method according to claim 3, characterized in that: In response to the running state being the driving state, receiving the target message sent by the cloud, including: In response to the operating state being the driving state, sending a message subscription request for the target message to the cloud; receiving the target message sent by the cloud in response to the message subscription request, wherein the target message is used to indicate whether the initial data is abnormal and / or needs to be updated; The method further includes: in response to the initial data being abnormal and / or requiring updating, determining that the detection result is a failure to preset the initial data on the vehicle.

6. The method according to claim 5, characterized in that Receiving the target message sent by the cloud in response to the message subscription request, including: The receiving monitoring module responds to the message subscription request, monitors the data status of the initial data, and sends the target message, wherein the target message includes an update strategy, and the update strategy is used to represent the update rules for updating the initial data. The monitoring module is deployed on the cloud.

7. The method according to claim 1, characterized in that In response to the detection result indicating that the initial data presetting fails, sending a data acquisition request to the cloud, including: In response to the detection result that presetting the initial data on the vehicle fails, bidirectionally verifying the data presetting interface of the vehicle and the cloud to obtain a verification result; In response to the verification result being successful bidirectional verification of the vehicle and the data presetting interface, the data acquisition request is sent to the cloud.

8. The method according to claim 1, characterized in that Acquiring the target data sent by the cloud in response to the data acquisition request, including: acquiring the target data retrieved from the database by the cloud when the cloud recognizes that the identification information in the data acquisition request has been preset on the cloud, wherein the identification information is used to identify the vehicle, and the monitoring module deployed on the cloud is used to monitor the information status of the identification information; or When the cloud recognizes that the identification information is not preset on the cloud, the initialization preset data of the cloud is used as the target data, wherein the database allows the storage of the initialization preset data, and the log data corresponding to the initialization preset data is monitored by the monitoring module.

9. A vehicle data presetting system, characterized in that: include: A vehicle, configured to perform data detection on the vehicle and obtain a detection result, wherein the detection result is used to indicate whether the initial data required for the operation of the vehicle is successfully preset; in response to the detection result indicating that the initial data preset fails, sending a data acquisition request to the cloud, wherein the data acquisition request is used to request to obtain target data, the target data is data that is allowed to be preset on the vehicle, and the data volume of the target data is greater than a data volume threshold; The cloud is used to respond to the data acquisition request, obtain the target data, and send the target data to the vehicle; Wherein, the vehicle is used to preset the target data on the vehicle.

10. A vehicle, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program executes the method according to any one of claims 1 to 8 when running.

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