Vehicle service anomaly detection method and electronic equipment

Abstract

The invention discloses a vehicle service anomaly detection method and electronic equipment, and the method comprises the steps: determining target burying point data corresponding to each of a plurality of services for executing a target vehicle control instruction, and determining an instruction execution rule corresponding to the target vehicle control instruction; and performing association arrangement processing on the services according to the instruction execution rule to obtain a service link, determining abnormal services in the service link according to the target burying point data corresponding to each service, performing marking processing on the abnormal services in the service link, and displaying the marked service link and the target burying point data corresponding to each service. And taking the result as a vehicle service anomaly detection result. According to the method, the burying point data is automatically collected for the execution process of the vehicle control instruction, abnormal services are checked, the whole service link, the abnormal services in the service link and the burying point data of all the services are displayed, automatic problem positioning is achieved, and a user can conveniently conduct problem analysis.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle abnormality detection, and in particular to a vehicle service abnormality detection method and electronic equipment. Background Art

[0002] With the continuous development of Internet of Vehicles technology, the degree of automobile intelligence is getting higher and higher, and the functions of vehicles are becoming more and more open. With the theoretical support of the new generation of software cars, the automobile architecture is also constantly adjusting, and the service-oriented architecture (SOA) is implemented in the whole vehicle. For the SOA architecture, each function of the vehicle can be reflected in a service-oriented way, so that the vehicle can respond flexibly and quickly to service functions. As the number of vehicle functions increases, the corresponding service volume is also increasing, and there are more and more intermediate service links to realize the corresponding functions. Problems in any service link related to the realization of vehicle functions will lead to the failure of vehicle function realization. Therefore, the difficulty coefficient of troubleshooting after problems with vehicle function realization is getting higher and higher.

[0003] Currently, if a vehicle function fails to be implemented, the corresponding vehicle control execution logs are collected and manually analyzed to locate the problem of the vehicle function failure. This requires a lot of manpower investment and is time-consuming and labor-intensive. Summary of the invention

[0004] The present application provides a vehicle service anomaly detection method and electronic device, which are used to solve the problem of manually analyzing logs to locate vehicle function failure problems in the prior art, which is time-consuming and labor-intensive.

[0005] Among them, by obtaining the buried data corresponding to each service that executes the target vehicle control command, and according to the command execution rules corresponding to the target vehicle control command, the services are associated and arranged, the service link of the target vehicle control command is obtained, and the services with abnormalities in the service link are marked, and the marked service link and the buried data of each service are displayed. In this way, the buried data collection and abnormal service troubleshooting are automatically performed for vehicle control, and the entire service link and abnormal services are displayed, so as to realize the automatic location of vehicle function failure problems and facilitate users to analyze problems.

[0006] To solve the above technical problems, on the first aspect, the implementation method of the present application discloses a vehicle service anomaly detection method, which includes: determining the target buried point data corresponding to each service among multiple services that execute the target vehicle control instruction, and determining the instruction execution rule corresponding to the target vehicle control instruction; according to the instruction execution rule, the services are associated and arranged to obtain a service link, and the abnormal services in the service link are determined according to the target buried point data corresponding to each service, the abnormal services in the service link are marked, and the marked service link and the target buried point data corresponding to each service are displayed as the vehicle service anomaly detection result.

[0007] The vehicle service anomaly detection method provided by the implementation of the present application determines the target buried data corresponding to each service in multiple services that execute the target vehicle control command, and performs correlation and arrangement processing on the services according to the command execution rules to obtain a service link, and determines the abnormal services according to the target buried data corresponding to each service, marks the abnormal services in the service link, and displays the marked service link and the target buried data corresponding to each service. In this way, the buried data is automatically collected for the execution process of the vehicle control command, and the abnormal services are checked, and the entire service link, the abnormal services in the service link, and the buried data of each service are displayed to realize automatic problem location and facilitate users to analyze problems.

[0008] According to another specific implementation of the present application, the implementation of the present application discloses a vehicle service anomaly detection method, in which the target buried point data includes the buried point status information of the business processing logic corresponding to the service execution target vehicle control instruction, and the abnormal services in the service link are determined according to the target buried point data corresponding to each service, including: determining the abnormal services in the service link according to the buried point status information corresponding to each service.

[0009] By adopting the above technical solution, the tracking point status information of the business processing logic corresponding to the target vehicle control instruction executed by the service can directly determine the abnormal service in the service link, without the need for manual abnormal service investigation, making vehicle service anomaly detection more efficient.

[0010] According to another specific implementation method of the present application, the vehicle service anomaly detection method disclosed in the implementation method of the present application determines the target buried point data corresponding to each service in multiple services that execute the target vehicle control instruction, including: calling the buried point component, and obtaining the buried point data of each service in multiple services that execute each vehicle control instruction based on the buried point component; determining the target instruction execution rule number corresponding to the target vehicle control instruction, and the instruction execution rule number information included in the buried point data, and determining the buried point data whose instruction execution rule number is the same as the target instruction execution rule number from the buried point data as the target buried point data corresponding to the service that executes the target vehicle control instruction.

[0011] By adopting the above technical solution, the target buried point data of each service that executes the target vehicle control instruction is filtered according to the target instruction execution rule number of the target vehicle control instruction, so as to facilitate service abnormality analysis of any target vehicle control instruction.

[0012] According to another specific implementation method of the present application, the vehicle service anomaly detection method disclosed in the implementation method of the present application, the target burial point data also includes service number information, burial point number information of the business processing logic corresponding to the service execution target vehicle control instruction, anomaly description information of the business processing logic corresponding to the service execution target vehicle control instruction and burial point time information.

[0013] By adopting the above technical solution, it is convenient to determine the cause of the service abnormality by obtaining the service number information, the tracking point number information of the business processing logic corresponding to the service execution target vehicle control instruction, the exception description information and tracking time information of the business processing logic corresponding to the service execution target vehicle control instruction, which is beneficial for users to troubleshoot and repair abnormal services.

[0014] According to another specific implementation method of the present application, the vehicle service anomaly detection method disclosed in the implementation method of the present application, the instruction execution rules include service number information of the corresponding service, service number information of the next associated service, and the tracking point number information of the business processing logic corresponding to the target vehicle control instruction of the corresponding service execution, the next tracking point number information of the business processing logic corresponding to the target vehicle control instruction of the corresponding service execution, and the execution order information of the business processing logic corresponding to the target vehicle control instruction of the corresponding service execution.

[0015] By adopting the above technical solution, the service link is arranged according to the instruction execution rules, and the service link for executing the target vehicle control instruction is intuitively displayed to the user, which is convenient for the user to perform service analysis.

[0016] According to another specific implementation method of the present application, the vehicle service anomaly detection method disclosed in the implementation method of the present application also includes: performing data structure conversion processing on the buried point data, and storing the buried point data after the data structure conversion processing in a database; determining the buried point data whose instruction execution rule number is the same as the target instruction execution rule number from the buried point data, as the target buried point data corresponding to the service that executes the target vehicle control instruction, including: determining the buried point data whose instruction execution rule number is the same as the target instruction execution rule number from the buried point data stored in the database, as the target buried point data corresponding to the service that executes the target vehicle control instruction.

[0017] By adopting the above technical solution, the buried point data is saved in the database, which is convenient for users to trace the data later.

[0018] According to another specific implementation of the present application, the implementation of the present application discloses a vehicle service anomaly detection method, wherein the target vehicle control instruction is a remote vehicle control instruction.

[0019] By adopting the above technical solution, it is possible to perform abnormal detection on vehicle services related to remote vehicle control instructions.

[0020] In the second aspect, the implementation method of the present application also discloses an electronic device, including: a processor, and a memory connected to the processor for communication; the memory stores a computer program, and the processor executes the computer program stored in the memory, so that the electronic device implements the vehicle service anomaly detection method provided by any one of the implementation methods of the first aspect mentioned above.

[0021] In a third aspect, an implementation method of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the vehicle service anomaly detection method provided by any one of the implementation methods of the first aspect above.

[0022] In a fourth aspect, an implementation of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the vehicle service anomaly detection method provided in any one of the implementations of the first aspect above.

[0023] It can be understood that the beneficial effects of the second to fourth aspects mentioned above can also be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flow chart of a vehicle service anomaly detection method provided in an embodiment of the present application;

[0025] Figure 2 It is a schematic diagram of the principle of vehicle service anomaly detection provided by an embodiment of the present application;

[0026] Figure 3 It is a schematic diagram of target burial point data provided by an embodiment of the present application;

[0027] Figure 4 is a schematic diagram of a service link display provided in an embodiment of the present application;

[0028] Figure 5 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0029] Specific implementation method

[0030] As mentioned above, with the continuous development of Internet of Vehicles technology, the degree of automobile intelligence is getting higher and higher, and the functions of vehicles are becoming more and more open. Under the theoretical support of the new generation of software cars, the automobile architecture is also constantly adjusting, and the service-oriented (SOA) architecture is implemented in the whole vehicle. For the service-oriented architecture, the various functions of the vehicle can be reflected in a service-oriented way, so that the vehicle can respond flexibly and quickly to service functions (such as upgrade functions). However, as the number of vehicle functions increases, the corresponding service volume is also increasing, and the number of intermediate service links to realize the corresponding functions is also increasing. Problems in any service link related to the realization of vehicle functions will lead to the failure of vehicle function realization. Therefore, the difficulty coefficient of troubleshooting after problems with vehicle function realization is also increasing.

[0031] Taking vehicle control as an example, remote control is when a user initiates a request through a mobile terminal or other device APP. The request is called through a series of services (including travel services and dependent branch services, etc.) to control the vehicle's various actuators to perform vehicle control operations. If any service in the middle has a problem, the remote control operation will fail.

[0032] At present, whether it is vehicle remote control or other control, each service can only be analyzed from top to bottom from the request initiator to the request execution end, and finally the problematic service or actuator is located. If the request execution fails, the corresponding vehicle control execution log is collected and manually analyzed to locate the problem. Obviously, this requires a lot of manpower and operation and maintenance costs, and it takes a lot of time and energy. At the same time, if too much time is spent on troubleshooting, the problem cannot be solved for the customer in time, which will also lead to a decrease in customer recognition of the brand. In addition, the existing log analysis can only locate general anomalies, and cannot identify business anomalies.

[0033] Based on this, the implementation of this application provides a vehicle service anomaly detection method, such as Figure 1 As shown, the specific steps include the following steps.

[0034] S100, determining target buried point data corresponding to each service among multiple services that execute a target vehicle control instruction, and determining an instruction execution rule corresponding to the target vehicle control instruction.

[0035] S200, according to the instruction execution rules, the services are associated and arranged to obtain the service link, and the abnormal services in the service link are determined according to the target buried point data corresponding to each service, and the abnormal services in the service link are marked, and the marked service link and the target buried point data corresponding to each service are displayed as the vehicle service anomaly detection result.

[0036] The vehicle service anomaly detection method provided by the implementation of the present application determines the target buried data corresponding to each service in multiple services that execute the target vehicle control command, and performs correlation and arrangement processing on the services according to the command execution rules to obtain a service link, and determines the abnormal services according to the target buried data corresponding to each service, marks the abnormal services in the service link, and displays the marked service link and the target buried data corresponding to each service. In this way, the buried data is automatically collected for the execution process of the vehicle control command, and the abnormal services are checked, and the entire service link, the abnormal services in the service link, and the buried data of each service are displayed to realize automatic problem location and facilitate users to analyze problems.

[0037] In the implementation of this application, the target vehicle control instruction is a remote vehicle control instruction, that is, a control instruction sent by a user to a vehicle through a remote control terminal. In the process of executing the remote vehicle control instruction, multiple services will be called, so it is necessary to detect service anomalies.

[0038] In the implementation method of the present application, the link execution rules (ie, instruction execution rules) are first configured, and then the business tracking component is introduced for all services involved in the remote control link to collect tracking data such as business data.

[0039] In the implementation method of the present application, the instruction execution rules include the service number information of the corresponding service, the service number information of the next associated service, the tracking point number information of the business processing logic corresponding to the target vehicle control instruction of the corresponding service execution, the next tracking point number information of the business processing logic corresponding to the target vehicle control instruction of the corresponding service execution, and the execution order information of the business processing logic corresponding to the target vehicle control instruction of the corresponding service execution.

[0040] For example, Figure 2 As shown, the user triggers the vehicle control command through the APP, and the vehicle control command is executed by the corresponding business processing logic through the APP, cloud service 1, cloud service 2, actuator 1, and actuator 2.

[0041] Therefore, the services corresponding to the target vehicle control instructions include APP service, cloud service 1, cloud service 2, actuator 1 service, and actuator 2 service.

[0042] As shown in Table 1, the services included in the command execution rule of the target vehicle control command include APP service, cloud service 1, cloud service 2, actuator 1 service, and actuator 2 service.

[0043] Table 1 Instruction execution rules

[0044] Service Name Service Tag Next Service Tag Point number Next point number order APP Services s001 s002 p001 p002 1 Cloud Service 1 s002 s003 p002 p003 2 Cloud Service 2 s003 s004, s005 p003 p004, p005 3 Executor 1 Service s004 / p004 / 4 Executor 2 Service s005 / p005 / 5

[0045] Among them, the service number (s001) of the APP service (as an example of the service number information of the corresponding service), the service number (s002) of the next service of the APP service (that is, cloud service 1) (as an example of the service number information of the next associated service of the corresponding service), the tracking point number (p001) (as an example of the tracking point number information of the business processing logic corresponding to the corresponding service execution target vehicle control instruction), the next tracking point number (p002) (as an example of the next tracking point number information of the business processing logic corresponding to the corresponding service execution target vehicle control instruction), and the sequence (1) (as the execution sequence information of the business processing logic corresponding to the corresponding service execution target vehicle control instruction). It is used to define the tracking point of the APP service (s001) executing the target vehicle control instruction as p001, the execution sequence is 1, and the next execution tracking point is p002.

[0046] The service number (s002) of cloud service 1 (as an example of the service number information of the corresponding service), the service number (s003) of the next service of cloud service 1 (i.e., cloud service 2) (as an example of the service number information of the next associated service of the corresponding service), the tracking point number (p002) (as an example of the tracking point number information of the business processing logic corresponding to the corresponding service executing the target vehicle control instruction), the next tracking point number (p003) (as an example of the next tracking point number information of the business processing logic corresponding to the corresponding service executing the target vehicle control instruction), and the sequence (2) (as the execution sequence information of the business processing logic corresponding to the corresponding service executing the target vehicle control instruction). It is used to define the tracking point of cloud service 1 (s002) executing the target vehicle control instruction as p002, the execution sequence as 2, and the next execution tracking point as p003.

[0047] The service number (s003) of cloud service 2 (as an example of the service number information of the corresponding service), the service number (s004, s005) of the next service of cloud service 2 (i.e., actuator 1 service) (as an example of the service number information of the next associated service of the corresponding service), the tracking point number (p003) (as an example of the tracking point number information of the business processing logic corresponding to the corresponding service executing the target vehicle control instruction), the next tracking point number (p004, p005) (as an example of the next tracking point number information of the business processing logic corresponding to the corresponding service executing the target vehicle control instruction), and the sequence (3) (as the execution sequence information of the business processing logic corresponding to the corresponding service executing the target vehicle control instruction). It is used to define the tracking point of cloud service 2 (s003) executing the target vehicle control instruction as p003, the execution sequence is 3, and the next execution tracking points are p004 and p005.

[0048] The service number (s004) of actuator 1 service (as an example of the service number information of the corresponding service), the next associated service of actuator 1 service is empty (as an example of the service number information of the next associated service of the corresponding service), the tracking point number (p004) (as an example of the tracking point number information of the business processing logic corresponding to the corresponding service executing the target vehicle control instruction), the next tracking point number is empty (as an example of the next tracking point number information of the business processing logic corresponding to the corresponding service executing the target vehicle control instruction), and the sequence (4) (as the execution sequence information of the business processing logic corresponding to the corresponding service executing the target vehicle control instruction). It is used to define the tracking point of actuator 1 service (s004) executing the target vehicle control instruction as p004, and the execution sequence is 4.

[0049] The service number (s005) of actuator 2 service (as an example of the service number information of the corresponding service), the next associated service of actuator 2 service is empty, the tracking point number (p001) (as an example of the tracking point number information of the business processing logic corresponding to the corresponding service execution of the target vehicle control instruction), the next tracking point number is empty (as an example of the next tracking point number information of the business processing logic corresponding to the corresponding service execution of the target vehicle control instruction), and the sequence (5) (as the execution sequence information of the business processing logic corresponding to the corresponding service execution of the target vehicle control instruction). It is used to define the tracking point of actuator 2 service (s005) executing the target vehicle control instruction as p005, and the execution sequence is 5.

[0050] In this way, the services for executing the target vehicle control instruction can be obtained according to the instruction execution rule corresponding to the target vehicle control instruction, including APP service, cloud service 1, cloud service 2, actuator 1 service and actuator 2 service.

[0051] Furthermore, in the implementation method of the present application, the target tracking data corresponding to each of the multiple services that execute the target vehicle control instruction is determined, including: calling the tracking component, and obtaining the tracking data of each of the multiple services that execute the vehicle control instruction based on the tracking component.

[0052] Exemplarily, a tracking component is introduced into all services related to executing vehicle control instructions, and then the tracking data of each service is collected based on the interface of the tracking component.

[0053] In the implementation method of the present application, the tracking data of each service includes instruction execution rule number information, service number information, tracking point number information of the business processing logic corresponding to the service execution target vehicle control instruction, tracking point status information of the business processing logic corresponding to the service execution target vehicle control instruction, exception description information and tracking time information of the business processing logic corresponding to the service execution target vehicle control instruction.

[0054] like Figure 3 As shown, the tracking data of cloud services (such as target tracking data) include link number (that is, instruction execution rule number), service number (as an example of service number information corresponding to the service), point number (that is, tracking point number information), point status (that is, tracking point status information), exception description (that is, exception description information of the service executing the target vehicle control instruction) and tracking time (that is, tracking time information).

[0055] The buried point data for vehicle-side services include link number (also known as instruction execution rule number), part number (as an example of service number information), point number (also known as buried point number information), point status (also known as buried point status information), exception description (also known as exception description information of the service executing the target vehicle control instruction) and buried point time (also known as buried point time information).

[0056] The link number serves as a unique identifier for each execution of the corresponding vehicle control instruction (i.e., vehicle control request) in the remote control execution link, and is used to connect all services and tracking points in each execution of the vehicle control instruction according to the link number corresponding to the instruction execution rule.

[0057] The service ID is the unique identifier of each service in the remote control execution link and is used to locate the corresponding service during subsequent troubleshooting.

[0058] The point number is used as the number of each specific business processing logic in the remote control execution link, and is used to locate the specific problem point during subsequent troubleshooting.

[0059] The point status corresponds to the point number and serves as a mark of the business logic processing result status (for example, error codes corresponding to successful or failed business processing), which is used to locate the specific link abnormality type during subsequent problem troubleshooting.

[0060] The exception description corresponds to the point status and is the additional descriptive information of the code corresponding to the point status. It is used to more intuitively view the cause of the link exception during subsequent troubleshooting.

[0061] The tracking time corresponds to the point number and serves as a specific time marker for business logic processing. It is used to locate the time when the problem occurred during subsequent troubleshooting.

[0062] In the implementation method of the present application, all nodes involved in vehicle remote control (including cloud service nodes and vehicle-side actuator nodes) will be mapped to corresponding services to collect corresponding business processing data for the service nodes involved in the entire execution process of the vehicle remote control instructions to obtain buried point data.

[0063] It should be noted that, because a service may not only execute one vehicle control instruction, the tracking data corresponding to a service may specifically be the business processing data of multiple vehicle control instructions, that is, the service includes multiple tracking data corresponding to multiple vehicle control instructions, and each tracking data includes the instruction execution rule number information corresponding to the corresponding vehicle control instruction, service number information, tracking point number information of the business processing logic corresponding to the vehicle control instruction executed by the service, tracking point status information of the business processing logic corresponding to the vehicle control instruction executed by the service, exception description information and tracking time information of the business processing logic corresponding to the target vehicle control instruction executed by the service.

[0064] For example, Figure 2 As shown, taking the instruction execution rules of APP service, cloud service 1, cloud service 2, executor 1 service, and executor 2 service as an example, target tracking data is collected based on the tracking components of each service.

[0065] In the process of APP service executing the corresponding business processing logic, the tracking interface of the tracking component is called to collect the tracking data of the APP service, including the link number corresponding to the current vehicle remote control instruction (that is, the instruction execution rule number), the service number of the current service, the tracking point number of the business processing logic currently executing the vehicle remote control instruction, the tracking time of the tracking point of the business processing logic currently executing the vehicle remote control instruction, the tracking point status of the business processing logic currently executing the vehicle remote control instruction, and exception description information.

[0066] In the process of cloud service 1 executing the corresponding business processing logic, the tracking interface of the tracking component is called to collect the tracking data of cloud service 1, including the link number corresponding to the current vehicle remote control instruction (that is, the instruction execution rule number), the service number of the current service, the tracking point number of the business processing logic currently executing the vehicle remote control instruction, the tracking time of the tracking point of the business processing logic currently executing the vehicle remote control instruction, the tracking point status of the business processing logic currently executing the vehicle remote control instruction, and exception description information.

[0067] In the process of cloud service 1 executing the corresponding business processing logic, the tracking interface of the tracking component is called to collect the tracking data of cloud service 1, including the link number corresponding to the current vehicle remote control instruction (that is, the instruction execution rule number), the service number of the current service, the tracking point number of the business processing logic currently executing the vehicle remote control instruction, the tracking time of the tracking point of the business processing logic currently executing the vehicle remote control instruction, the tracking point status of the business processing logic currently executing the vehicle remote control instruction, and exception description information.

[0068] In the process of cloud service 2 executing the corresponding business processing logic, the tracking interface of the tracking component is called to collect the tracking data of cloud service 2, including the link number corresponding to the current vehicle remote control instruction (that is, the instruction execution rule number), the service number of the current service, the tracking point number of the business processing logic currently executing the vehicle remote control instruction, the tracking time of the tracking point of the business processing logic currently executing the vehicle remote control instruction, the tracking point status of the business processing logic currently executing the vehicle remote control instruction, and exception description information.

[0069] During the process of executor 1 service executing the corresponding business processing logic, the tracking interface of the tracking component is called to collect the tracking data of cloud service 1, including the link number corresponding to the current vehicle remote control instruction (that is, the instruction execution rule number), the service number of the current service, the tracking point number of the business processing logic currently executing the vehicle remote control instruction, the tracking time of the tracking point of the business processing logic currently executing the vehicle remote control instruction, the tracking point status of the business processing logic currently executing the vehicle remote control instruction, and exception description information.

[0070] During the process of executor 2 service executing the corresponding business processing logic, the tracking interface of the tracking component is called to collect the tracking data of cloud service 1, including the link number corresponding to the current vehicle remote control instruction (that is, the instruction execution rule number), the service number of the current service, the tracking point number of the business processing logic currently executing the vehicle remote control instruction, the tracking time of the tracking point of the business processing logic currently executing the vehicle remote control instruction, the tracking point status of the business processing logic currently executing the vehicle remote control instruction, and exception description information.

[0071] It should be noted that when implementing this application, the point status information can be represented by 0 or 1, where 0 indicates successful execution and 1 indicates failed execution. If the execution is successful, the exception description information is empty. If the execution fails, the exception description information includes the exception code and exception details.

[0072] Furthermore, in the implementation method of the present application, the collected burial point data is also subjected to data structure conversion processing to convert it into the data structure required by the database, and the burial point data after the data structure conversion processing is stored in the database (that is, the burial point data storage method is executed to store the data in the database).

[0073] For example, because a service may not only execute one vehicle control instruction, the buried data corresponding to a service may specifically be the business processing data of multiple vehicle control instructions, and in actual problem troubleshooting, only the target vehicle control instruction may be fully checked. Therefore, in the implementation of this application, all buried data of the service executing each vehicle control instruction will be converted into a corresponding data structure format to be converted into a data structure that can be stored and recognized by the database, and then the buried data after the data structure conversion will be stored in the database.

[0074] Furthermore, when troubleshooting problems with target vehicle control execution instructions, the target instruction execution rule number corresponding to the target vehicle control instruction and the instruction execution rule number information included in the buried point data are determined, and the buried point data whose instruction execution rule number is the same as the target instruction execution rule number is determined from the buried point data as the target buried point data corresponding to the service that executes the target vehicle control instruction (that is, the execution buried point data processing method).

[0075] Exemplarily, each target vehicle control instruction corresponds to a unique target instruction execution rule number, and the buried data of each service also includes a unique instruction execution rule number. The buried data with the same instruction execution rule number as the target instruction execution rule number is determined from the buried data stored in the database as the target buried data corresponding to the service that executes the target vehicle control instruction.

[0076] In the implementation of the present application, the target vehicle control instruction may specifically be a control instruction that fails to execute. After the tracking data of each service corresponding to multiple vehicle control instructions are stored in the database, the control instruction that fails to execute is determined, and the target instruction execution rule number corresponding to the target vehicle control instruction that fails to execute is determined, so as to filter out the service corresponding to the target instruction execution rule number and the tracking data of the corresponding service from the tracking data stored in the database.

[0077] Furthermore, after filtering out the services corresponding to the target vehicle control instruction and the target buried point data of each service, it is necessary to intuitively display to the user the service execution link for executing the target vehicle control instruction and the relevant information of the business processing logic of each service executing the target vehicle control instruction. Therefore, it is necessary to perform service association arrangement processing according to the instruction execution rules corresponding to the target vehicle control instruction.

[0078] According to the service number information and execution order of each service, the associated sorting (i.e. serial sorting) is performed to obtain the following Figure 4 The service link shown is: start-APP-service 1-service 2-executor 1, executor 2. In addition, the target burying point data of each service executing the target vehicle control instruction is obtained according to the burying point position number information corresponding to each service in the instruction execution rule and the next associated burying point position number information.

[0079] Furthermore, the abnormal services in the service chain are determined based on the target tracking data corresponding to each service.

[0080] Exemplarily, based on the tracking point status information included in the target tracking point data of each service, the service corresponding to the tracking point with failed tracking point status information in the service link is determined, and the abnormal service is obtained. The service is marked to distinguish it from non-abnormal nodes.

[0081] Furthermore, the service link is displayed on the display panel (also known as the link data dashboard), and the abnormal service is highlighted, and the buried data of the abnormal service is displayed (for example, if actuator 2 is an abnormal service, the part number, point number, abnormal code, abnormal description and abnormal time (buried time) of actuator 2 are displayed) as the vehicle service abnormality detection result.

[0082] The vehicle service anomaly detection method provided by the implementation method of the present application is also a method for troubleshooting and locating remote vehicle control problems in the Internet of Vehicles. First, the instruction execution rules are configured, and then the business tracking component is introduced for all services involving vehicle control instructions to collect tracking data, and the collected tracking data is persisted in the database. According to the target vehicle control instruction, the collected tracking data is filtered to obtain the target tracking data corresponding to the target vehicle control instruction, and the target tracking data is aggregated and processed to obtain the service link for executing the target vehicle control instruction and the tracking data of the abnormal service, and finally the service link is displayed to after-sales personnel through the link data dashboard for intuitive problem location. Compared with the existing log collection method, in the implementation method of the present application, the business tracking data of the service executing vehicle control instructions can be collected based on the tracking component, and the business execution results of the service are distinguished in combination with the actual business scenarios and business definitions to define the definition rules of success and failure, and different exception descriptions are assigned according to different error codes. Finally, the link dashboard can more accurately and intuitively show the user the service nodes where the problems occur and the reasons for the problems, solving the problem of difficult and inefficient positioning of abnormal services for remote control commands, greatly improving the efficiency of after-sales personnel in locating problems, making vehicle service anomaly detection more efficient and after-sales service faster.

[0083] The vehicle service anomaly detection method provided by the implementation of the present application can be applied to a cloud server, and of course can also be applied to vehicles or other electronic devices.

[0084] See also Figure 5 , Figure 5 The figure is a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 5As shown, the electronic device may include: a transceiver 121 , a processor 122 , and a memory 123 .

[0085] The processor 122 executes the computer execution instructions stored in the memory, so that the processor 122 executes the technical solution of the vehicle service abnormality detection method in the above embodiment. The processor 122 can be a general-purpose processor, including a central processing unit CPU, a network processor (NP), etc.; it can also be a digital data processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0086] The memory 123 is connected to the processor 122 via a system bus and completes communication between them. The memory 123 is used to store computer program instructions.

[0087] By way of example and not limitation, the memory 123 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 123 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 123 may be inside or outside the integrated gateway device. In a particular embodiment, the memory 123 is a non-volatile solid-state memory. In a particular embodiment, the memory 123 includes a read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0088] The transceiver 121 may be used to obtain tasks to be executed and configuration information of the tasks to be executed.

[0089] The system bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The system bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. The transceiver is used to realize the communication between the database access device and other computers (such as clients, read-write libraries, and read-only libraries). The memory may include random access memory (RAM) and may also include non-volatile memory.

[0090] An embodiment of the present application also provides a chip for running instructions, which is used to execute the technical solution of the vehicle service anomaly detection method in the above embodiment.

[0091] An embodiment of the present application also provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed on a processor of an electronic device, the processor of the electronic device executes the technical solution of the vehicle service anomaly detection method of the above embodiment.

[0092] In some possible implementations, various aspects of the method provided in the present application can also be implemented in the form of a program product, which includes program code. When the program product is run on a processor of an electronic device, the program code is used to enable the processor of the electronic device to execute the steps of the method described above in this specification according to various exemplary implementations of the present application. For example, the electronic device can execute the vehicle service anomaly detection method recorded in the embodiments of the present application.

[0093] The program product may employ any combination of one or more readable media. The readable medium may be a readable data medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0094] The implementation method of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When at least one processor executes the computer program, it can implement the technical solution of the vehicle service anomaly detection method in the above-mentioned embodiment.

[0095] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices and computer program products according to the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable information processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable information processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0096] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable information processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0097] These computer program instructions can also be loaded onto a computer or other programmable information processing device so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0098] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary technical means in the art that are not disclosed in the present application.

[0099] It should be noted that, in addition to the implementation of the present application described in the above-mentioned specific embodiments, those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Although the description of the present application is introduced in conjunction with the preferred embodiment, this does not mean that the features of this invention are limited to the implementation. On the contrary, the purpose of introducing the invention in conjunction with the implementation is to cover other options or modifications that may extend based on the claims of the present application. In order to provide an in-depth understanding of the present application, the above description contains many specific details, and the present application may also be implemented without using these details. In addition, in order to avoid confusion or blurring the focus of the present application, some specific details will be omitted in the description. It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0100] It should be noted that in this specification, similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0101] Although the present application has been illustrated and described by referring to certain preferred implementations of the present application, it should be understood by those skilled in the art that the above contents are further detailed descriptions of the present application in combination with specific implementations, and it cannot be determined that the specific implementation of the present application is limited to these descriptions. Those skilled in the art may make various changes in form and details, including making several simple deductions or substitutions, without departing from the spirit and scope of the present application.

Claims

1. A vehicle service anomaly detection method, characterized in that: The method comprises: Determine target buried point data corresponding to each service in a plurality of services for executing a target vehicle control instruction, and determine an instruction execution rule corresponding to the target vehicle control instruction; The services are associated and arranged according to the instruction execution rules to obtain a service link, and the abnormal services in the service link are determined according to the target buried point data corresponding to each of the services. The abnormal services in the service link are marked, and the service link after the marking process and the target buried point data corresponding to each of the services are displayed as vehicle service anomaly detection results.

2. The vehicle service anomaly detection method according to claim 1, characterized in that: The target buried point data includes buried point status information of the service executing the business processing logic corresponding to the target vehicle control instruction, and determining the abnormal service in the service link according to the target buried point data corresponding to each of the services includes: Determine the abnormal services in the service link according to the tracking point status information corresponding to each of the services.

3. The vehicle service anomaly detection method according to claim 2, characterized in that: Determine the target tracking point data corresponding to each of the multiple services that execute the target vehicle control command, including: Calling a tracking component, and obtaining tracking data of each of the multiple services that execute each vehicle control instruction based on the tracking component; Determine the target instruction execution rule number corresponding to the target vehicle control instruction, and the instruction execution rule number information included in the embedded point data, and determine the embedded point data whose instruction execution rule number is the same as the target instruction execution rule number from the embedded point data as the target embedded point data corresponding to the service that executes the target vehicle control instruction.

4. The vehicle service anomaly detection method according to claim 3, characterized in that: The target tracking data also includes service number information, tracking point number information of the service executing the business processing logic corresponding to the target vehicle control instruction, exception description information and tracking time information of the service executing the business processing logic corresponding to the target vehicle control instruction.

5. The vehicle service anomaly detection method according to claim 4, characterized in that: The instruction execution rules include service number information of the corresponding service, service number information of the next associated service, and the point number information of the corresponding service executing the business processing logic corresponding to the target vehicle control instruction, the next point number information of the corresponding service executing the business processing logic corresponding to the target vehicle control instruction, and the execution order information of the corresponding service executing the business processing logic corresponding to the target vehicle control instruction.

6. The vehicle service anomaly detection method according to claim 5, characterized in that: The method further comprises: Performing data structure conversion processing on the buried point data, and storing the buried point data after the data structure conversion processing in a database; Determining from the buried point data the buried point data having the same instruction execution rule number as the target instruction execution rule number as the target buried point data corresponding to the service for executing the target vehicle control instruction includes: The buried point data having the same instruction execution rule number as the target instruction execution rule number is determined from the buried point data stored in the database as the target buried point data corresponding to the service for executing the target vehicle control instruction.

7. The vehicle service anomaly detection method according to any one of claims 1 to 6, characterized in that: The target vehicle control instruction is a remote vehicle control instruction.

8. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores a computer program, and the processor executes the computer program stored in the memory so that the electronic device implements the vehicle service anomaly detection method as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it is used to implement the vehicle service anomaly detection method as described in any one of claims 1-7.

10. A computer program product, characterized in that It includes a computer program, which, when executed by a processor, implements the vehicle service anomaly detection method as described in any one of claims 1 to 7.

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