Vehicle remote task diagnosis method and device, equipment and storage medium

Abstract

The invention discloses a vehicle remote task diagnosis method, device and equipment and a storage medium, and relates to the technical field of the Internet of Things, and the method comprises the steps: detecting whether the vehicle information and task type of a vehicle remote task exist in an existing relation library of a server; if the vehicle information and the task type of the vehicle remote task do not exist in the existing relationship library of the server, adding a preset key step of the vehicle remote task and a command interaction pair of corresponding data to the existing relationship library of the server based on a data model of the vehicle remote task obtained by pre-training; and executing the vehicle remote task based on the preset key steps of the vehicle remote task and the command interaction pair of the corresponding data. According to the method, the situation that the preset key steps of the vehicle remote task manually uploaded to the data server and the corresponding command interaction pair are not updated in time can be avoided, the data workload and the maintenance cost are effectively reduced, and the data of the vehicle executing the new task are automatically learned and perfected.

Description

Technical Field

[0001] The present application relates to the technical field of the Internet of Things, and in particular to a diagnostic method, device, equipment and storage medium for a vehicle remote task. Background Art

[0002] With the rapid development of smart cars and IoT technologies, remote diagnosis and maintenance of vehicles are becoming increasingly important. Traditional remote diagnosis methods rely on manual collection and organization of vehicle data to obtain the preset key steps and corresponding command interaction pairs for vehicle execution functions, and then upload them to the data server for analysis. This method cannot automatically learn and add unconfigured functions and the corresponding preset key steps and command interaction pairs. It has problems such as untimely updates, large data volumes, and inconvenient maintenance, and it is difficult to meet the efficiency and accuracy requirements of modern vehicle diagnosis.

[0003] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of this application is to provide a diagnostic method, device, equipment and storage medium for vehicle remote tasks, aiming to solve the technical problems that traditional remote diagnostic methods rely on manual collection and organization of vehicle data, the preset key steps of vehicle remote tasks uploaded to the data server and the corresponding command interaction pairs are not updated in a timely manner, the data volume is large, and the maintenance cost is high.

[0005] To achieve the above objectives, the present application proposes a vehicle remote task diagnosis method, the method comprising:

[0006] Detect whether the vehicle information and task type of the vehicle remote task exist in the existing relationship database of the server;

[0007] If the vehicle information and task type of the vehicle remote task do not exist in the existing relationship library of the server, based on the pre-trained data model of the vehicle remote task, add the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data to the existing relationship library of the server;

[0008] The vehicle remote task is executed based on the preset key steps of the vehicle remote task and the command interaction pairs of corresponding data.

[0009] In one embodiment, the step of detecting whether the vehicle information and task type of the vehicle remote task exist in the existing relationship library of the server includes:

[0010] Receive a query request from a client for vehicle information and task type of a vehicle remote task;

[0011] A query is performed in the existing relationship database according to the query request to obtain a query result.

[0012] In one embodiment, the learning and training steps of the data model of the vehicle remote task include:

[0013] Get diagnostic data of the vehicle;

[0014] Based on the diagnostic data of the vehicle, obtaining a command interaction pair of preset key steps and corresponding data of the vehicle remote task by analyzing the execution log and error information in the diagnostic data;

[0015] Preprocessing and constructing a data set based on the necessary steps of the vehicle remote task and the command interaction of the corresponding data;

[0016] The data set is trained by a machine learning algorithm to obtain a data model of the vehicle remote function.

[0017] In one embodiment, the step of adding the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data to the existing relationship library of the server based on the data model of the vehicle remote task obtained by pre-training includes:

[0018] Load the pre-trained data model of vehicle remote tasks;

[0019] Inputting relevant data of the vehicle remote task into the loaded data model of the vehicle remote task;

[0020] Using the loaded data model of the vehicle remote task to predict the input data, and identifying the preset key steps of the vehicle remote task;

[0021] Parsing the prediction results of the data model of the vehicle remote task, and extracting the preset key steps and corresponding data of the vehicle remote task;

[0022] Constructing command interaction pairs based on the extracted preset key steps and corresponding data;

[0023] The constructed command interaction pair is transmitted to the existing relationship library of the server, and the existing relationship library is updated.

[0024] In one embodiment, the command interaction pair based on the preset key steps and corresponding data of the vehicle remote task, before executing the step of the vehicle remote task, further includes:

[0025] Determine whether there is an operation path for the vehicle remote task;

[0026] If there is an operation path for the vehicle remote task, the client automatically executes each step according to the operation path, performs data communication with the detected vehicle, and completes the specified function;

[0027] If the operation path of the vehicle remote task does not exist, the client prompts the user that the specified function cannot be completed automatically and requires manual intervention or the server to provide corresponding evidence.

[0028] In one embodiment, the step of executing the vehicle remote task based on the preset key steps of the vehicle remote task and the command interaction pair of corresponding data includes:

[0029] Obtain the command interaction pairs of preset key steps and corresponding data of the vehicle remote task;

[0030] Check and ensure that the network connection between the vehicle and the server is normal, and initialize the software and hardware resources required for task execution;

[0031] Based on a preset sequence of key steps of the vehicle remote task, sequentially sending command interaction pairs of corresponding data to the vehicle and receiving a response from the vehicle;

[0032] The execution status and results of each preset key step are monitored in real time based on the response of the vehicle.

[0033] In addition, to achieve the above-mentioned purpose, the present application also proposes a vehicle remote task diagnostic device, the device comprising:

[0034] A data acquisition module, used to acquire vehicle information, task type and diagnostic data of a remote task of a vehicle;

[0035] A relationship database processing module, used for detecting whether the vehicle information and task type of the vehicle remote task exist in the existing relationship database of the server, and updating the existing relationship database of the server;

[0036] The data model processing module predicts the input data by loading the pre-trained data model of the vehicle remote task, identifies the preset key steps and corresponding data of the vehicle remote task, and constructs the command interaction pair;

[0037] The task execution control module is used to determine whether there is an operation path for the vehicle remote task. If so, the task is automatically executed. If not, the user is prompted to intervene manually or the server provides corresponding evidence;

[0038] The data storage module is used to store the existing relationship database, diagnostic data, data model and task execution results of the service client.

[0039] In addition, to achieve the above-mentioned purpose, the present application also proposes a diagnostic device for vehicle remote tasks, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the diagnostic method for vehicle remote tasks as described above.

[0040] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the vehicle remote task diagnosis method described above are implemented.

[0041] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the vehicle remote task diagnosis method as described above are implemented.

[0042] The vehicle remote task diagnosis method, device, equipment and storage medium proposed in this application have at least the following technical effects:

[0043] By detecting whether the vehicle information and task type of the vehicle remote task exist in the existing relationship library of the server, if the vehicle information and task type of the vehicle remote task do not exist in the existing relationship library of the server, then based on the data model of the vehicle remote task obtained by pre-training, the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data are added to the existing relationship library of the server, and based on the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data, the vehicle remote task is executed. Based on the scheme of the present application, through the existing relationship library of the server and the data model of the vehicle remote task, the automated data collection and analysis process can update the vehicle status and fault information in real time, more accurately identify the preset key steps of the vehicle to perform the task and the command interaction pairs of the corresponding data, improve the efficiency of data processing, greatly reduce the manual workload, improve the diagnostic efficiency, and reduce the maintenance cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0046] Figure 1A flow chart of a first embodiment of a diagnostic method for a remote vehicle task of the present application;

[0047] Figure 2 A flow chart of a second embodiment of the diagnostic method for a remote vehicle task of the present application;

[0048] Figure 3 A brief flow chart of the third embodiment of the diagnostic method for vehicle remote tasks of the present application;

[0049] Figure 4 A brief flow chart of the fourth embodiment of the diagnostic method for vehicle remote tasks of the present application;

[0050] Figure 5 A brief flow chart of the fifth embodiment of the diagnostic method for vehicle remote tasks of the present application is provided;

[0051] Figure 6 A brief flow chart of the sixth embodiment of the diagnostic method for vehicle remote tasks of the present application;

[0052] Figure 7 This is a schematic diagram of the module structure of the diagnostic device for vehicle remote tasks in an embodiment of the present application;

[0053] Figure 8 A schematic diagram of a module structure of a diagnostic device for a vehicle remote task in this application;

[0054] Fig. 9 Schematic diagram of the device structure of the hardware operating environment involved in the vehicle remote task diagnosis method in the embodiment of the present application.

[0055] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0056] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0057] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0058] In this embodiment, for ease of description, the following description is made with the server as the execution subject.

[0059] Since the traditional vehicle remote diagnosis method in the prior art relies on manual collection and organization of vehicle data to obtain the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data, and then upload them to the data server to analyze and diagnose the vehicle's execution of the task, this method has problems such as untimely updates, large data volume, and inconvenient maintenance, and it is difficult to meet the efficiency and accuracy requirements of modern vehicle diagnosis.

[0060] The present application provides a solution, by detecting whether the vehicle information and task type of the vehicle remote task exist in the existing relationship library of the server; if the vehicle information and task type of the vehicle remote task do not exist in the existing relationship library of the server, then based on the data model of the vehicle remote task obtained by pre-training, the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data are added to the existing relationship library of the server; based on the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data, the vehicle remote task is executed. Based on the solution of the present application, through the existing relationship library of the server and the data model of the vehicle remote function, the automated data collection and analysis process can update the vehicle status and fault information in real time, more accurately identify the preset key steps of the vehicle to perform tasks and the command interaction pairs of the corresponding data, improve the efficiency of data processing, greatly reduce the manual workload, improve the diagnostic efficiency, and reduce the maintenance cost.

[0061] Based on this, the embodiment of the present application provides a vehicle remote task diagnosis method, referring to Figure 1 , Figure 1 This is a flow chart of a first embodiment of a diagnostic method for a vehicle remote task of the present application.

[0062] In this embodiment, the vehicle remote task diagnosis method includes steps S10 to S30:

[0063] Step S10: Check whether the vehicle information and task type of the vehicle remote task exist in the existing relationship database of the server.

[0064] It should be noted that the vehicle information may include vehicle ID, model, production date, etc.; the task types may include diagnosis, repair, maintenance, etc.; the existing relationship library on the server side contains vehicle information, task types, and manually sorted command interaction pairs of preset key steps and corresponding data required for a certain function or task of the vehicle; the vehicle remote task is usually a series of tasks for remote operation or management of the vehicle through remote control or automation technology.

[0065] Specifically, when a vehicle is equipped with a system that supports remote diagnosis, the telematics system connected to the vehicle can use an account to log in for identity authentication, authorize the application to access the vehicle's diagnostic data, and obtain the diagnostic data through the application; when the vehicle initiates a remote diagnostic request through the application, the system communicates with the vehicle's OBD system to obtain real-time diagnostic data and save the diagnostic data to the local device; the diagnostic data includes at least engine status, battery status, tire pressure, fuel efficiency, etc.; the client can send query requests such as vehicle information and task type of vehicle remote tasks to the existing relationship library of the server through a network request. After receiving the request, the server searches for matching records in the relationship library according to the query conditions and feeds back the query results.

[0066] Step S20: If the vehicle information and task type of the vehicle remote task do not exist in the existing relationship library of the server, based on the pre-trained data model of the vehicle remote task, add the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data to the existing relationship library of the server.

[0067] It should be noted that the data of the command interaction pairs of the vehicle's operating steps and corresponding data when performing various functions can come from the vehicle's sensors, control units, user operation records, etc.; the collected data usually needs to be preprocessed, and the preprocessing steps include: data cleaning, data normalization and feature extraction; data cleaning includes removing noise data, missing value processing, outlier detection and processing; data normalization can convert data of different dimensions to the same dimension to facilitate model training; feature extraction can extract useful features from the original data, such as time series features, statistical features, etc.; the preset key steps should ensure the integrity and correctness of the task or function, and avoid missing key operations; the command interaction pairs define the way data is sent and received in each step of the vehicle's function execution, to ensure the accuracy and efficiency of data interaction.

[0068] Specifically, if the vehicle information and task type of the vehicle remote task do not exist in the existing relationship library of the server, the acquired diagnostic data is analyzed in detail based on the pre-trained data model of the vehicle remote task to determine the current status of the vehicle and existing problems, identify key data points that affect the vehicle's execution functions, and based on the analysis results of the diagnostic data, determine the preset key steps required to complete the vehicle's execution functions. While determining the preset key steps, generate command interaction pairs of corresponding data, and automatically upload and update the preset key steps and command interaction pairs of corresponding data to the existing relationship library of the server.

[0069] In addition, if the vehicle information and task type of the vehicle remote task exist in the existing relationship library of the server, the command interaction pairs of the preset key steps and corresponding data of the vehicle remote task can be directly retrieved for diagnosis and execution of the vehicle remote task.

[0070] Step S30: executing the vehicle remote task based on the preset key steps of the vehicle remote task and the command interaction pairs of corresponding data.

[0071] It should be noted that the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data can be loaded from a database or configuration file. Through the loaded preset key steps, each step is executed in sequence. By monitoring and providing feedback during the task execution, the user experience is improved, and an exception handling mechanism should be included in each step.

[0072] Specifically, the preset key steps and corresponding data of the vehicle remote task are obtained from the existing relationship library on the server side. By parsing the obtained command interaction pairs, the execution conditions, execution order, expected results and other information of each step are extracted. According to the parsed preset key steps and corresponding data, commands can be sent to the vehicle through the network interface and the vehicle's response can be received. At the same time, the execution status of each key step can be monitored through the real-time data stream to ensure that each key step is executed as expected. If a key step is not executed or executed incorrectly, the user can be prompted to perform corresponding processing to ensure the integrity and correctness of the task.

[0073] This embodiment provides a method for diagnosing a vehicle remote task, by detecting whether the vehicle information and task type of the vehicle remote task exist in the existing relationship library of the server, obtaining the corresponding preset key steps and command interaction pairs based on the existing relationship library of the server and the data model of the vehicle remote task, and executing the vehicle remote service. The automated data collection and analysis process can update the vehicle status and fault information in real time, more accurately identify the necessary steps for the vehicle to execute the task and the command interaction pairs of the corresponding data, greatly reducing the manual workload, improving data processing efficiency, and reducing maintenance costs.

[0074] Further, refer to Figure 2 The second embodiment of the vehicle remote task diagnosis method of the present application provides a flow chart based on the above Figure 2 The embodiment shown further refines the step S10 of "detecting whether there is vehicle information and task type of the vehicle remote task in the existing relationship library of the server side", including steps A201-A202:

[0075] Step A201: receiving a query request for querying vehicle information and task type of a vehicle remote task sent by a client.

[0076] It should be noted that the vehicle information of the vehicle remote task may include vehicle ID, model, production date, etc., and the task type may include diagnosis, maintenance, repair, etc.

[0077] Specifically, the client can receive vehicle information and task type from the user interface or API interface; the client can send a query request to the server through the network interface. For example, to query the diagnostic task with vehicle ID "V54321", the client sends a query request to the server, where the vehicle information is that the vehicle ID is "54321" and the task type is a diagnostic task. The server can obtain the query request {"vehicle_id":"V54321","task_type":"diagnosis"}.

[0078] Step A202: query the existing relationship database according to the query request to obtain query results.

[0079] Specifically, after receiving the query request, the server searches for matching records in the existing relationship library of the server according to the query request and returns the query results. If a matching record is found, the preset key steps corresponding to the vehicle information and task type and the command interaction pairs of the corresponding data are returned; if no matching record is found, the prompt message "does not exist" is returned to the client.

[0080] In this embodiment, the client can effectively detect whether the vehicle information and task type of the vehicle remote task exist in the existing relationship library of the server by sending a query request to the server, which can improve the accuracy of the query and the security and integrity of the data.

[0081] In this embodiment, through the automated data collection and analysis process, human intervention is reduced, the efficiency of data processing is improved, the vehicle status and fault information can be updated in real time, the timeliness of diagnosis is improved, and at the same time the manual workload is greatly reduced, the system reliability is enhanced, and the maintenance cost is reduced.

[0082] Further, refer to Figure 3 The third embodiment of the vehicle remote task diagnosis method of the present application provides a flow chart based on the above Figure 3 In the embodiment shown, the learning and training of the data model of the vehicle remote task is further refined, including steps A301 to A304:

[0083] Step A301: Obtain vehicle diagnostic data.

[0084] Specifically, the vehicle can obtain diagnostic information through the on-board diagnostic system (OBD), such as using an OBD scan tool connected to the vehicle's OBD port and starting the scan tool to obtain the vehicle's real-time diagnostic data, including the vehicle's status information, fault codes, sensor data, execution logs, and error information.

[0085] Step A302: Based on the diagnostic data of the vehicle, by analyzing the execution log and error information in the diagnostic data, the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data are obtained.

[0086] Specifically, data analysis software can be used to import diagnostic data, identify the various steps of the vehicle's execution function by analyzing the execution log, and determine the key issues that affect the vehicle's execution function by analyzing the error information; based on the analysis results of the diagnostic data, determine the necessary steps required to complete the vehicle's execution function. For example, based on the execution log, determine the execution steps of vehicle starting, acceleration, braking and other functions; based on the error information, determine the steps of the vehicle's execution function that need to be repaired or adjusted; while determining the key steps, generate corresponding data command interaction pairs, define the method of sending and receiving data for each execution step, and ensure the accuracy and efficiency of data interaction.

[0087] In addition, for diagnostic data, the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data can be obtained through manual sorting and packaging, and the sorted data can be packaged into a compressed file for uploading or transmission. The status and storage space of the data server can be checked to ensure that the data server is correctly configured, and then uploaded to the data server to manually update the data on the data server.

[0088] Step A303: Preprocess and construct a data set based on the necessary steps of the vehicle remote task and the command interaction of the corresponding data.

[0089] Specifically, the preprocessing steps include: data cleaning, such as removing noise values, processing missing values, detecting and processing outliers; data normalization, by converting data of different dimensions to the same dimension to facilitate model training; feature extraction of the data of the same dimension, extracting useful features from the original data, such as time series features, statistical features, etc.; through these preprocessing steps, a high-quality data set is constructed.

[0090] Step A304: Train the data set using a machine learning algorithm to obtain a data model of the vehicle remote function.

[0091] Specifically, according to the characteristics of the data and modeling requirements, select the appropriate machine learning algorithm. Common algorithms include supervised learning (such as linear regression, decision tree, random forest, support vector machine, neural network, etc.), unsupervised learning (such as clustering algorithm, principal component analysis, etc.), reinforcement learning (such as Q-learning, deep Q network, etc.); at the same time, divide the data set into training set, validation set and test set, use the training set data to train the model, and adjust the model parameters to optimize the performance; use the validation set to verify the trained model to ensure the accuracy and reliability of the model, and evaluate the performance of the model through performance evaluation (such as accuracy, recall rate, F1 score, etc.) and error analysis, and apply the trained model to the actual vehicle function execution, and provide feedback and adjustment according to the actual execution results; input the real-time collected vehicle data into the data model, and the data model automatically generates the key steps of the execution function and the command interaction pairs of the corresponding data according to the current vehicle status and user needs, and feedbacks to the data model according to the actual execution results for further adjustment and optimization, and regularly collect new vehicle operation data, update the data set, and retrain the model to maintain the accuracy and adaptability of the data model.

[0092] In this embodiment, a data model of vehicle execution functions can be established through learning and training based on the preset key steps of vehicle execution functions and the command interaction pairs of corresponding data. This model can automatically identify and predict the behavior and state of the vehicle when performing different functions, thereby improving the vehicle's automation level and user experience, improving the vehicle's intelligence level, and also providing strong support for remote diagnosis and maintenance of the vehicle.

[0093] Further, refer to Figure 4 The fourth embodiment of the vehicle remote task diagnosis method of the present application provides a flow chart based on the above Figure 4 In the embodiment shown, the step S20 of "if the vehicle information and task type of the vehicle remote task do not exist in the existing relationship library of the server, based on the data model of the vehicle remote task obtained by pre-training, adding the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data to the existing relationship library of the server" is further refined, including steps A401 to A406:

[0094] Step A401: Load the pre-trained data model of the vehicle remote task.

[0095] Specifically, the data model file is loaded from the model storage location, such as the local file system, cloud storage, etc., and the data model is initialized.

[0096] Step A402: inputting relevant data of the vehicle remote task into the loaded data model of the vehicle remote task.

[0097] Specifically, data is obtained from data sources such as vehicle sensors, execution logs, and error information, and is input into the data model of the loaded vehicle remote task.

[0098] Step A403: Use the loaded data model of the vehicle remote task to predict the input data and identify the preset key steps of the vehicle remote task.

[0099] Specifically, the prediction interface of the data model can be called to process the input data and generate prediction results of preset key steps.

[0100] Step A404: parsing the prediction results of the data model of the vehicle remote task, and extracting the preset key steps and corresponding data of the vehicle remote task.

[0101] Specifically, the prediction results are parsed to extract information such as the names of preset key steps, execution order, required data, etc.

[0102] Step A405: construct a command interaction pair based on the extracted preset key steps and corresponding data.

[0103] It should be noted that when combining the preset key steps and corresponding data into command interaction pairs, it is necessary to ensure that each command interaction pair contains complete execution information.

[0104] Step A406: Transmit the constructed command interaction pair to the existing relationship library of the server, and update the existing relationship library.

[0105] Specifically, by collecting relevant documents and requirements of the vehicle execution function, obtaining detailed documents and requirement descriptions of the vehicle execution function from the project management tool or document library, using natural language processing (NLP) technology, automatically extracting key information in the document, including functional objectives, operation steps and data interaction requirements, and storing the extracted information in a temporary database; obtaining a pre-trained data model of the vehicle execution function from the data server, using a data matching algorithm, matching the extracted operation steps with the data structure and data flow in the data model, identifying the operation steps and data interaction methods not included in the data model, and automatically generating corresponding data command interaction pairs, using a data update tool, adding the identified non-existent necessary steps and corresponding data command interaction pairs to the data model; transmitting the command interaction pairs to the existing relationship library on the server side through a network request to ensure the stability and security of data transmission.

[0106] Through the above embodiment, it is possible to effectively and automatically identify and add the preset key steps and corresponding data command interaction pairs of the vehicle execution function that do not exist, and upload them to the existing relationship library of the data server. This method not only improves the completeness and accuracy of function implementation, improves the accuracy and efficiency of operation, reduces the huge workload and errors of manual sorting, but also provides a reliable foundation for subsequent data analysis and application.

[0107] Further, refer to Figure 5 The fifth embodiment of the vehicle remote task diagnosis method of the present application provides a flow chart based on the above Figure 5 In the embodiment shown, before the step S30 of "executing the vehicle remote task based on the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data", the steps A501 to A503 are also included:

[0108] Step A501: Determine whether there is an operation path for the vehicle remote task.

[0109] Step A502: If there is an operation path for the vehicle remote task, the client automatically executes each step according to the operation path, performs data communication with the detected vehicle, and completes the specified function.

[0110] Step A503: If the operation path of the vehicle remote task does not exist, the client prompts the user that the specified function cannot be completed automatically and manual intervention or the server provides corresponding evidence is required.

[0111] It should be noted that the operation path is used to guide the client on how to interact with the detected vehicle to complete the remote task; the client can verify whether the operation path for the vehicle remote task exists by sending a request to the server; when the server returns the existence status of the operation path, the client performs the next operation according to the returned result; if the server returns that the operation path exists, the client automatically executes each step according to the operation path, wherein the client interacts with the detected vehicle to complete the remote task; if the server returns that the operation path does not exist, the client prompts the user that it cannot automatically determine whether the preset key steps are executed, and the client will prompt to complete the remote task, which requires manual intervention or provision of relevant evidence.

[0112] In this embodiment, by requesting the operation path corresponding to the vehicle remote task, the accuracy and completeness of the operation path are ensured to avoid task failure due to path errors. During the data interaction process, the security and integrity of the data are ensured to avoid data leakage or damage. During the operation process, progress prompts and operation guidance are provided to the user in a timely manner to improve the user experience. When the error handling mechanism is running, the user can be advised to contact relevant technical support or provide necessary evidence to help determine whether the preset key steps are executed, thereby replacing the user experience and avoiding users wasting time on the wrong path.

[0113] Further, refer to Figure 6 The sixth embodiment of the vehicle remote task diagnosis method of the present application provides a flow chart based on the above Figure 6 In the embodiment shown, the step S30 of "executing the vehicle remote task based on the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data" is further refined to include steps A601 to A603:

[0114] Step A601: Obtain command interaction pairs of preset key steps and corresponding data of the vehicle remote task.

[0115] Step A602: Check and ensure that the network connection between the vehicle and the server is normal, and initialize the software and hardware resources required for task execution.

[0116] It should be noted that the software resources at least include an image module, a control module, a data processing module, etc.; the hardware resources at least include sensors, actuators, and communication equipment, etc.

[0117] Specifically, when an abnormality occurs in the network connection, corresponding repair measures are taken according to the network diagnosis results, such as restarting the network equipment, checking the network configuration, replacing the network line, etc.

[0118] Step A603: Based on the preset key step sequence of the vehicle remote task, send command interaction pairs of corresponding data to the vehicle in sequence and receive the vehicle's response.

[0119] Step A604: Monitor the execution status and results of each preset key step in real time based on the response of the vehicle.

[0120] Specifically, the server receives the response data sent by the vehicle through the communication module, including execution status, results, timestamp and other information, and parses the received corresponding data, records the parsed key information in the log file or database, and then reads the execution status and results in the log or database in real time, performs corresponding processing and feedback based on the monitoring results, and if an abnormal situation occurs, the task execution strategy can be adjusted or an alarm can be sent in time.

[0121] In this embodiment, based on the existing relationship library of the data server and the pre-trained data model of the vehicle remote task, the received vehicle information and task type are diagnosed, and the task type not entered in the existing relationship library can be quickly identified, and the preset key steps of the unentered task type and the command interaction pairs of the corresponding data are quickly matched through the data model of the vehicle remote task, and the vehicle remote task is executed based on the preset key steps and the command interaction pairs of the corresponding data. This method improves the accuracy and efficiency of diagnosis, ensures real-time feedback of query results, reduces task completion time, and greatly improves user experience.

[0122] In addition, this application also provides a vehicle remote task diagnostic device, please refer to Figure 7 , the vehicle remote task diagnostic device comprises:

[0123] Step 10: A data detection module is used to detect whether the vehicle information and task type of the vehicle remote task exist in the existing relationship database of the server;

[0124] Step 20: The data model processing module predicts the input data by loading the pre-trained data model of the vehicle remote task, identifies the preset key steps and corresponding data of the vehicle remote task, and constructs a command interaction pair;

[0125] Step 30: The task execution control module is used to determine whether there is an operation path for the vehicle remote task. If so, the task is executed according to the preset key step sequence and the command interaction of the corresponding data. If not, the user is prompted to perform manual intervention or the server provides corresponding evidence.

[0126] Further, refer to Figure 8 , a schematic diagram of a module structure of a diagnostic device for a vehicle remote task of the present application, wherein:

[0127] A data acquisition module, used to acquire vehicle information, task type and diagnostic data of a remote task of a vehicle;

[0128] A relationship database processing module, used for detecting whether the vehicle information and task type of the vehicle remote task exist in the existing relationship database of the server, and updating the existing relationship database of the server;

[0129] The data model processing module predicts the input data by loading the pre-trained data model of the vehicle remote task, identifies the preset key steps and corresponding data of the vehicle remote task, and constructs the command interaction pair;

[0130] A data storage module, used to store diagnostic data, data models and function expansion results;

[0131] The task execution control module is used to determine whether there is an operation path for the vehicle remote task. If so, the task is automatically executed. If not, the user is prompted to intervene manually or the server provides corresponding evidence.

[0132] The vehicle remote task diagnostic device provided by the present application adopts the vehicle remote task diagnostic method in the above-mentioned embodiment, which can solve the technical problem of vehicle remote task diagnosis. Compared with the prior art, the beneficial effects of the vehicle remote task diagnostic device provided by the present application are the same as the beneficial effects of the vehicle remote task diagnostic method provided by the above-mentioned embodiment, and the other technical features in the vehicle remote task diagnostic device are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0133] In addition, the present application also provides a vehicle remote task diagnostic device, the vehicle remote task diagnostic device includes: at least one processor; and, a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the vehicle remote task diagnostic method in the above-mentioned embodiment one.

[0134] Reference below Fig. 9 , which shows a schematic diagram of the structure of a diagnostic device suitable for implementing a vehicle remote task in an embodiment of the present application. The diagnostic device for the vehicle remote task in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Fig. 9 The diagnostic device for the vehicle remote task shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0135] like Fig. 9As shown, the diagnostic device of the vehicle remote task may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the xxx device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the vehicle remote task diagnostic device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows the vehicle remote task diagnostic device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have instead.

[0136] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0137] The vehicle remote task diagnostic device provided by the present application adopts the vehicle remote task diagnostic method in the above embodiment, which can solve the technical problem of vehicle remote task diagnosis. Compared with the prior art, the beneficial effects of the vehicle remote task diagnostic device provided by the present application are the same as the beneficial effects of the vehicle remote task diagnostic method provided by the above embodiment, and the other technical features in the vehicle remote task diagnostic device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0138] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0139] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0140] In addition, the present application also provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the vehicle remote task diagnosis method in the above-mentioned embodiment.

[0141] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer 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. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0142] The computer-readable storage medium may be included in the diagnostic device of the vehicle remote mission; or may exist independently without being assembled into the diagnostic device of the vehicle remote mission.

[0143] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the diagnostic equipment of the vehicle remote task, the diagnostic equipment of the vehicle remote task: based on the said diagnostic data, obtains the necessary steps for the vehicle to execute the function and the command interaction pairs of the corresponding data, and establishes a data model of the vehicle execution function.

[0144] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0145] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0146] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0147] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned vehicle remote task diagnosis method, and can solve the technical problem of vehicle remote task diagnosis. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the vehicle diagnosis method provided by the above-mentioned embodiment, and will not be repeated here.

[0148] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A diagnostic method for a vehicle remote task, characterized in that: The method is applied to the server, and the method includes: Check whether the vehicle information and task type of the vehicle remote task exist in the existing relationship database of the server; If the vehicle information and task type of the vehicle remote task do not exist in the existing relationship library of the server, based on the pre-trained data model of the vehicle remote task, add the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data to the existing relationship library of the server; The vehicle remote task is executed based on the preset key steps of the vehicle remote task and the command interaction pairs of corresponding data.

2. The method according to claim 1, characterized in that The step of detecting whether the vehicle information and task type of the vehicle remote task exist in the existing relationship library of the server includes: Receive a query request from a client for vehicle information and task type of a vehicle remote task; A query is performed in the existing relationship database according to the query request to obtain a query result.

3. The method according to claim 1, characterized in that The learning and training steps of the data model of the vehicle remote task include: Get diagnostic data of the vehicle; Based on the diagnostic data of the vehicle, obtaining a command interaction pair of preset key steps and corresponding data of the vehicle remote task by analyzing the execution log and error information in the diagnostic data; Preprocessing and constructing a data set based on the necessary steps of the vehicle remote task and the command interaction of the corresponding data; The data set is trained by a machine learning algorithm to obtain a data model of the vehicle remote function.

4. The method according to claim 3, characterized in that The step of adding the preset key steps of the vehicle remote task and the command interaction pairs of the corresponding data to the existing relationship library of the server based on the data model of the vehicle remote task obtained by pre-training includes: Load the pre-trained data model of vehicle remote tasks; Inputting relevant data of the vehicle remote task into the loaded data model of the vehicle remote task; Using the loaded data model of the vehicle remote task to predict the input data, and identifying the preset key steps of the vehicle remote task; Parsing the prediction results of the data model of the vehicle remote task, and extracting the preset key steps and corresponding data of the vehicle remote task; Constructing command interaction pairs based on the extracted preset key steps and corresponding data; The constructed command interaction pair is transmitted to the existing relationship library of the server, and the existing relationship library is updated.

5. The method according to claim 4, characterized in that The command interaction pair based on the preset key steps and corresponding data of the vehicle remote task, before executing the step of the vehicle remote task, also includes: Determine whether there is an operation path for the vehicle remote task; If there is an operation path for the vehicle remote task, the client automatically executes each step according to the operation path, performs data communication with the detected vehicle, and completes the specified function; If the operation path of the vehicle remote task does not exist, the client prompts the user that the specified function cannot be completed automatically and requires manual intervention or the server to provide corresponding evidence.

6. The method according to claim 5, characterized in that The step of executing the vehicle remote task based on the preset key steps of the vehicle remote task and the command interaction pair of corresponding data includes: Obtain the command interaction pairs of preset key steps and corresponding data of the vehicle remote task; Check and ensure that the network connection between the vehicle and the server is normal, and initialize the software and hardware resources required for task execution; Based on a preset sequence of key steps of the vehicle remote task, sequentially sending command interaction pairs of corresponding data to the vehicle and receiving a response from the vehicle; The execution status and results of each preset key step are monitored in real time based on the response of the vehicle.

7. A diagnostic device for a vehicle remote task, characterized in that: The device comprises: A data detection module, used to detect whether the vehicle information and task type of the vehicle remote task exist in the existing relationship database of the server; The data model processing module predicts the input data by loading the pre-trained data model of the vehicle remote task, identifies the preset key steps and corresponding data of the vehicle remote task, and constructs the command interaction pair; The task execution control module is used to determine whether there is an operation path for the vehicle remote task. If so, the task is executed according to the preset key step sequence and the command interaction of the corresponding data. If not, the user is prompted to intervene manually or the server provides corresponding evidence.

8. A diagnostic device for vehicle remote tasks, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the vehicle remote task diagnosis method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the vehicle remote task diagnosis method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the vehicle remote task diagnosis method according to any one of claims 1 to 6 are implemented.

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