Vehicle task flow processing method and device, equipment and storage medium

Abstract

The invention provides a vehicle task flow processing method and device, equipment and a storage medium. The method comprises the steps that vehicle task information is acquired; inputting the vehicle task information into a task classification model to obtain a task type output by the task classification model; wherein the task classification model is obtained by training based on vehicle task training data and task classification labels corresponding to the vehicle task training data; creating a corresponding task according to the task type in combination with a preset task creation rule, and executing the task; wherein the preset task creation rule is used for limiting the flow nodes corresponding to the task types and the relationship between the flow nodes. According to the invention, efficient and intelligent task processing can be realized, and driving safety and driving experience are improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and particularly to a method, device, equipment and storage medium for processing vehicle task processes. Background Art

[0002] In the wave of the development of the current automotive industry, the intelligence and networking of vehicles have become an irreversible trend. The functions of vehicle equipment are becoming increasingly rich, and the system complexity is continuously increasing, which has led to an increase in the diversity and complexity of vehicle task processing. The processing efficiency and accuracy of vehicle tasks directly affect vehicle operation safety, user experience, and vehicle management efficiency.

[0003] Currently, vehicle task processing mainly relies on in-vehicle electronic control units (ECUs) and in-vehicle communication systems. By using preset programs and algorithms, the data collected by various vehicle sensors, cameras, etc. are processed. During the processing, vehicle tasks are decomposed into multiple subtasks, and then the in-vehicle electronic control unit (ECU) schedules and manages each subtask.

[0004] However, when the ECU processing method encounters complex tasks or abnormal situations, due to its limited reaction speed and decision-making quality, it is difficult to achieve efficient task processing. Moreover, due to the fixed algorithm, the system cannot adaptively adjust to different driving scenarios, resulting in poor task processing effects. In addition, the preset data transmission protocol shows low adaptability and flexibility in the face of changing data forwarding requirements. In addition, the existing systems have relatively single coping strategies when dealing with emergencies, which are prone to cause potential safety hazards. Summary of the Invention

[0005] The present invention provides a method, device, equipment and storage medium for processing vehicle task processes, which are used to solve the defect that traditional processing methods in the prior art are difficult to cope with complex tasks or abnormal situations, and to achieve efficient and intelligent task processing, and improve driving safety and driving experience.

[0006] The present invention provides a method for processing vehicle task processes, including: obtaining vehicle task information; inputting the vehicle task information into a task classification model to obtain the task type output by the task classification model; wherein, the task classification model is trained based on vehicle task training data and task classification labels corresponding to the vehicle task training data; according to the task type, combined with a preset task creation rule, creating a corresponding task and executing it; wherein, the preset task creation rule is used to define the process nodes corresponding to each task type and the relationships between the process nodes.

[0007] A vehicle task process handling method provided by the present invention for executing a corresponding created task includes: executing a start node of the corresponding created task to start executing the task and executing the next node defined in the start node; in the case where the next node defined in the start node is a first method judgment node, if the first method judgment node is a single device check, determining whether the vehicle device corresponding to the license plate identifier is unique; based on the vehicle device corresponding to the license plate identifier not being unique, executing a first condition judgment node defined in the first method judgment node to determine whether vehicle device information is stored in a preset database; wherein the preset database is previously created based on the license plate identifier and the vehicle device information corresponding to the license plate identifier; if the vehicle device information does not exist in the preset database, executing a first process output node defined in the first condition judgment node to notify the user to confirm whether the device exists and end the process; otherwise, executing a second condition judgment node defined in the first condition judgment node to determine whether the vehicle device information in the preset database corresponds to multiple vehicle devices; if the vehicle device information in the preset database corresponds to multiple vehicle devices, executing a first execution node defined in the second condition judgment node to query vehicle device information according to the vehicle identifier, and based on the queried vehicle device information, executing a first user input execution node defined in the first execution node to notify the user that there are multiple devices and receive device selection information returned by the user based on the notification of the existence of multiple devices, and based on the received device selection information from the user, executing an asynchronous task node defined in the first user input execution node to asynchronously execute the corresponding task; otherwise, executing an asynchronous task node defined in the second condition judgment node to asynchronously execute the corresponding task; based on the vehicle device corresponding to the vehicle identifier being unique, executing an asynchronous task node defined in the first method judgment node to asynchronously execute the corresponding task.

[0008] A vehicle task process handling method provided by the present invention, based on the vehicle device corresponding to the license plate identifier not being unique, executes a first condition judgment node defined in the first method judgment node to determine whether vehicle device information is stored in a preset database, including: based on the vehicle device corresponding to the license plate identifier not being unique, using a first condition execution model to execute the first condition judgment node defined in the first method judgment node to extract vehicle device information and search and match it in the preset database; wherein the first condition execution model is trained based on vehicle device information training data and the true labels of the vehicle device information training data. If the vehicle device information does not exist in the preset database, execute the first process output node defined in the first conditional judgment node to notify the user to confirm whether the device exists and end the process, including: according to the result output by the first conditional execution model that the vehicle device information does not exist in the preset database, use the first output model to execute the first process output node defined in the first conditional judgment node to extract that the vehicle device information does not exist in the preset database and combine the corresponding context information, and perform polishing output according to the corresponding preset result output template to notify the user to confirm whether the device exists and end the process; wherein, the first output model is trained based on the vehicle device information training data and the result label of the vehicle device information training data; If the vehicle device information in the preset database corresponds to multiple vehicle devices, execute the first execution node defined in the second conditional judgment node to query the vehicle device information according to the vehicle identifier, including: based on the fact that the vehicle device information in the preset database corresponds to multiple vehicle devices, use the device identification model to execute the first execution node defined in the second conditional judgment node to extract and identify the vehicle identifier features to obtain the vehicle device information; wherein, the device identification model is used to be trained based on the vehicle training identifier and the device label corresponding to the vehicle training identifier; based on the queried vehicle device information, execute the first user input execution node defined in the first execution node to notify the user that there are multiple devices and receive the device selection information returned by the user based on the notification of the existence of multiple devices, and based on the received device selection information from the user, execute the asynchronous task node defined in the first user input execution node, including: based on the queried vehicle device information, use the first user input execution model to execute the first user input execution node defined in the first execution node, output multiple devices and receive the device selection information returned by the user based on the notification of the existence of multiple devices, and extract the device information parameters of the device selection information and trigger the execution of the asynchronous task node; wherein, the first user input execution model is used to be trained based on the device training data and the device parameter label corresponding to the device training data.

[0009] According to a vehicle task process processing method provided by the present invention, the task type is a vehicle device restart task, and execute the asynchronous task node, including: execute the second execution node defined in the asynchronous task node to restart the vehicle device; execute the third conditional judgment node defined in the second execution node to check whether the vehicle device is restarted successfully. If the vehicle device is restarted successfully, execute the first task result output node defined in the third conditional judgment node to send a notification of successful restart and end the process; otherwise, execute the second task result output node defined in the third conditional judgment node to send a notification of failed restart and end the process.

[0010] A vehicle task process handling method provided according to the present invention, where the task type is a vehicle equipment offline task, and an asynchronous task node is executed, including: executing a fourth condition judgment node defined in the asynchronous task node to check whether the vehicle equipment is online; if the vehicle equipment is online, executing a third task result output node defined in the fourth condition judgment node to output a device online notification; otherwise, executing a fifth condition judgment node defined in the fourth condition judgment node to check whether the vehicle equipment is in a service state; if it is not in a service state, executing a third execution node defined in the fifth condition judgment node to output a service error reminder and end the process; otherwise, executing a sixth condition judgment node defined in the fifth condition judgment node to check whether the user identification card of the corresponding vehicle equipment is in a normal state; if the user identification card is not in a normal state, executing a fifth execution node defined in the sixth condition judgment node to output a user identification card error reminder and end the process; otherwise, executing a second process output node defined in the sixth condition judgment node to notify the user of equipment debugging, and executing a fourth execution node defined in the second process output node to perform equipment debugging, and based on the completion of the equipment debugging, executing a seventh condition judgment node defined in the fourth execution node to check whether the vehicle equipment is successfully debugged; if the vehicle equipment is successfully debugged, executing a fifth execution node defined in the seventh condition judgment node to asynchronously process the equipment debugging result, and executing a third process output node defined in the fifth execution node to output a device debugging success notification and end the process; otherwise, executing a fourth task result output node defined in the seventh condition judgment node to output a device debugging failure notification and result status and end the process.

[0011] According to a vehicle task process handling method provided by the present invention, the task type is a vehicle device forwarding task, and an asynchronous task node is executed, including: executing an eighth conditional judgment node defined in the asynchronous task node to determine whether the data recipient is bound to a vehicle device; if the data recipient is not bound to a vehicle device, then executing a fifth task result output node defined in the eighth conditional judgment node to output a vehicle not bound notification; otherwise, executing a second method judgment node defined in the eighth conditional judgment node to check whether the data recipient is correct; based on the data recipient being incorrect, executing a ninth conditional judgment node defined in the second method judgment node to determine whether there are multiple data recipients for the vehicle device information to be forwarded. If there are multiple data recipients for the vehicle device information to be forwarded, then executing a second user input execution node defined in the ninth conditional judgment node to output the corresponding multiple data recipients and notify the user to select a data recipient, and based on the recipient selection information returned by the user, executing a sixth execution node defined in the second user input execution node to perform vehicle device data forwarding; otherwise, executing a sixth task result output node defined in the ninth conditional judgment node to output a notification of incorrect data recipient and end the process; based on the data recipient being correct, executing a sixth execution node defined in the second method judgment node to perform vehicle device data forwarding; based on the data forwarding being completed, executing a tenth conditional judgment node defined in the sixth execution node to determine whether the data forwarding is successful. If successful, then executing a seventh task result output node defined in the tenth conditional judgment node to output a notification of successful device forwarding and end the process; otherwise, executing an eighth task result output node defined in the tenth conditional judgment node to output a notification of failed device forwarding and end the process.

[0012] According to a vehicle task process handling method provided by the present invention, an eighth conditional judgment node defined in the asynchronous task node is executed to determine whether the data recipient is bound to a vehicle device, including: using a second conditional execution model to execute the eighth conditional judgment node defined in the asynchronous task node to extract data recipient information and detect whether the corresponding recipient is bound to a vehicle device; wherein, the second conditional execution model is trained based on recipient information training data and true labels of recipient information training data. If the data recipient is not bound to a vehicle device, then executing a fifth task result output node defined in the eighth conditional judgment node to output a vehicle not bound notification, including: based on the vehicle device not being bound, using a second result output model to execute the fifth task result output node defined in the eighth conditional judgment node to extract information of the vehicle device not bound and combine corresponding context information, and perform polishing and output according to the corresponding preset result output template to output a vehicle not bound notification and end the process; wherein, the second result output model is trained based on vehicle device binding information training data, result labels and status labels of vehicle device binding information training data. Based on the incorrect data recipient, execute the ninth conditional judgment node defined in the second method judgment node to determine whether there are multiple data recipients for the vehicle device information to be forwarded, including: Based on the incorrect data recipient, use the third conditional execution model to execute the ninth conditional judgment node defined in the second method judgment node to extract the vehicle device information to be forwarded and detect whether there are multiple data recipients for the vehicle device information to be forwarded; wherein, the third conditional execution model is trained based on the vehicle device information training data and the recipient label of the vehicle device information training data. If there are multiple data recipients for the vehicle device information to be forwarded, then execute the second user input execution node defined in the ninth conditional judgment node to output the corresponding multiple data recipients and notify the user to select a data recipient, and based on the recipient selection information returned by the received user, execute the sixth execution node defined in the second user input execution node, including: Based on the incorrect data recipient, use the second user input execution model to execute the ninth conditional judgment node defined in the second method judgment node to output a notification of the corresponding multiple data recipients and receive the recipient selection information returned by the user based on the notification of the existence of multiple data recipients, and extract the device information parameters of the recipient selection information and trigger the execution of the sixth execution node defined in the second user input execution node; wherein, the second user input execution model is trained based on the vehicle training data and the recipient label corresponding to the vehicle training data. Execute the sixth execution node defined in the second user input execution node to forward the vehicle device data, including: Use the first action execution model to execute the sixth execution node defined in the second user input execution node to identify the device information parameters and forward them to the corresponding data recipient; wherein, the first action execution model is trained based on the device training data and the item label corresponding to the device training data. Based on the completion of data forwarding, execute the tenth conditional judgment node defined in the sixth execution node to determine whether the data forwarding is successful, including: Based on the completion of data forwarding, use the fourth conditional execution model to execute the tenth conditional judgment node defined in the sixth execution node to detect whether the data forwarding is successful; wherein, the fourth conditional execution model is trained based on the device training data and the status label corresponding to the device training data. If successful, execute the seventh task result output node defined in the tenth conditional judgment node to output a device forwarding success notification and end the process; otherwise, execute the eighth task result output node defined in the tenth conditional judgment node to output a device forwarding failure notification and end the process, including: using the third result output model, based on successful data forwarding, execute the seventh task result output node defined in the tenth conditional judgment node to extract successful data forwarding information and combine it with the corresponding context information, and polish and output it according to the corresponding preset result output template to send a device forwarding success notification and success status and end the process, or, based on failed data forwarding, execute the eighth task result output node defined in the tenth conditional judgment node to extract failed data forwarding information and combine it with the corresponding context information, and polish and output it according to the corresponding preset result output template to send a device forwarding failure notification and failure status and end the process; wherein, the third result output model is trained based on the result labels and status labels of the data forwarding status information training data and the data forwarding status information training data.

[0013] The present invention also provides a vehicle task process processing device, including: an information acquisition module, which acquires vehicle task information; a task classification module, which inputs the vehicle task information into a task classification model to obtain the task type output by the task classification model; wherein, the task classification model is used to be trained based on vehicle task training data and task classification labels corresponding to the vehicle task training data; a task processing module, which creates and executes corresponding tasks according to the task type in combination with a preset task creation rule; wherein, the preset task creation rule is used to define the process nodes corresponding to each task type and the relationships between the process nodes.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, it implements the vehicle task process processing method as described in any one of the above.

[0015] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the vehicle task process processing method as described in any one of the above.

[0016] The present invention also provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the vehicle task process processing method as described in any one of the above.

[0017] The vehicle task process handling method, device, equipment, and storage medium provided by the present invention use a task classification model trained with a large amount of vehicle task training data and corresponding classification labels to identify the task type of the acquired vehicle task information, so as to intelligently determine the task type based on the input task information, providing an accurate basis for subsequent task creation, enabling the system to handle diverse vehicle task scenarios, improving the efficiency and accuracy of task classification, reducing errors and time costs that may be brought by manual intervention, and further creating and executing corresponding tasks according to preset task creation rules. Moreover, the preset task creation rules clearly define the process nodes corresponding to each task type and the relationships between the nodes, ensuring the standardization and consistency of the task creation process, and helping to improve the quality and stability of the overall business process. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] To more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0019] Figure 1 is one of the flow diagrams of the vehicle task process handling method provided by the present invention; Figure 2 is another flow diagram of the vehicle task process handling method provided by the present invention; Figure 3 is yet another flow diagram of the vehicle task process handling method provided by the present invention; Figure 4 is still another flow diagram of the vehicle task process handling method provided by the present invention; Figure 5 is yet another flow diagram of the vehicle task process handling method provided by the present invention; Figure 6 is the structural diagram of the vehicle task process handling device provided by the present invention; Figure 7 is the structural diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0021] Figure 1 is a schematic flowchart of the vehicle task process handling method provided by the present invention. As Figure 1 shown, the method includes: S11, obtaining vehicle task information; S12, inputting the vehicle task information into a task classification model to obtain the task type output by the task classification model; wherein, the task classification model is trained based on vehicle task training data and task classification labels corresponding to the vehicle task training data; S13, creating and executing a corresponding task according to the task type in combination with a preset task creation rule; wherein, the preset task creation rule is used to define the process nodes corresponding to each task type and the relationships between the process nodes.

[0022] It should be noted that the step numbers "S1N" in this specification do not represent the sequence of the vehicle task process handling method. The vehicle task process handling method of the present invention will be specifically described below in combination with Figures 2 - 5 description.

[0023] Step S11, obtaining vehicle task information.

[0024] It should be noted that the vehicle task information can be determined according to the actual vehicle tasks to be processed. For example, if the vehicle task is vehicle equipment restart, the corresponding vehicle task information can be determined according to the restart corresponding license plate identification; for another example, if the vehicle task is vehicle equipment offline, the corresponding vehicle task information can be determined according to the corresponding license plate identification being offline; for another example, if the vehicle task is vehicle equipment forwarding, the corresponding vehicle task information can be determined according to forwarding the corresponding license plate identification to the corresponding data recipient. No further limitation is made here.

[0025] Step S12, inputting the vehicle task information into a task classification model to obtain the task type output by the task classification model; wherein, the task classification model is trained based on vehicle task training data and task classification labels corresponding to the vehicle task training data.

[0026] It should be noted that the task classification model can be selected based on design requirements, such as a large language model, etc. No further limitation is made here.

[0027] Step S13, creating and executing a corresponding task according to the task type in combination with a preset task creation rule; wherein, the preset task creation rule is used to define the process nodes corresponding to each task type and the relationships between the process nodes.

[0028] It should be added that the types of process nodes include start node start, execution node action, user input execution node user_action, method judgment node action_condition, condition judgment node condition, process output node output, task result output node result_output, asynchronous task node async_task, and end node end.

[0029] In this embodiment, before creating a corresponding task according to the task type and in combination with the preset task creation rule, configure the corresponding process nodes so that when creating a corresponding task according to the task type and in combination with the preset task creation rule, select the corresponding process nodes for combination to obtain the corresponding task.

[0030] Specifically, configuring start includes: configuring start based on the required data nodes and the next node of start. Start is used to cache the configuration of data nodes and jump to the next node for execution. The data nodes can be pre-configured according to the process nodes involved in the actual task, such as single device check (singleDeviceCheck), multi-device notification (tellMultiDevice), device restart (deviceRestart), and process output (output), etc. No further limitation is made here. Configuring action includes: configuring action according to the required execution method of action and the next node. Action is used to execute the configured method and jump to the next node, which can be specifically configured according to the actual task requirements. No further limitation is made here. Configuring user_action includes: configuring user_action according to the required execution method of user_action and the next node. User_action is used to feedback information to the user, receive the information returned by the user, and extract parameters using the large language model and jump to the next node, which can be specifically configured according to the actual task requirements. No further limitation is made here. Configuring action_condition includes: configuring action_condition according to the required execution method of action_condition and the next nodes corresponding to different situations (true / false) returned based on the execution method. Action_condition is used to execute the method and jump to the corresponding next node according to the true and false returned by the method, which can be specifically configured according to the actual task requirements. No further limitation is made here. Configuring condition includes: configuring condition according to the required execution condition of condition, the judgment result returned based on the execution condition, and the next nodes corresponding to each result. Condition can use the large language model to execute the condition judgment and jump to the corresponding next node according to the returned judgment result, which can be specifically configured according to the actual task requirements. No further limitation is made here. Configuring output includes: configuring output according to the required result output template of output and the next node. Output can use the large language model to obtain the output result according to the context and the corresponding result output template and jump to the next node, which can be specifically configured according to the actual task requirements. No further limitation is made here. Configuring result_output includes: configuring result_output according to the required output result template, result status, and the next node of result_output. Result_output can use the large language model to obtain the output result according to the context and the corresponding result output template, save the result status and result information, and jump to the next node, which can be specifically configured according to the actual task requirements. No further limitation is made here.Configure async_task, including: Configure async_task according to the required result output template, next node, and asynchronous task steps of async_task. Async_task can use the large language model for prompt output and record the weekly headquarters of the asynchronous task for task execution progress calculation, and start the execution of the asynchronous task and jump to the next node, which can be specifically configured according to actual task requirements and will not be further limited here. Configure end, including: Configure end according to the task end requirements to end the task.

[0031] In addition, refer to Figure 2, execute the corresponding created task, including: execute the start node start of the corresponding created task to start executing the task, and execute the next node defined in the start node; when the next node defined in the start node is the first method judgment node action_condition, if the first method judgment node action_condition is singleDeviceCheck, determine whether the vehicle device corresponding to the license plate identification is unique; based on the vehicle device corresponding to the license plate identification not being unique, execute the first condition judgment node isExistDevice defined in the first method judgment node to determine whether vehicle device information is stored in the preset database; wherein, the preset database is created in advance based on the license plate identification and the vehicle device information corresponding to the license plate identification; if the vehicle device information does not exist in the preset database, execute the first process output node tellConfirmDevice defined in the first condition judgment node to notify the user to confirm whether the device exists and end the process end; otherwise, execute the second condition judgment node isMultiDevice defined in the first condition judgment node to determine whether the vehicle device information in the preset database corresponds to multiple vehicle devices; if the vehicle device information in the preset database corresponds to multiple vehicle devices, execute the first execution node tellMultiDevice defined in the second condition judgment node to query the vehicle device information according to the vehicle identification, and based on the queried vehicle device information, execute the first user input execution node multiDeviceOutput defined in the first execution node to notify the user that there are multiple devices and receive the device selection information returned by the user based on the notification of the existence of multiple devices, and based on the received device selection information from the user, execute the asynchronous task node startAsyncTask defined in the first user input execution node to asynchronously execute the corresponding task; otherwise, execute the asynchronous task node startAsyncTask defined in the second condition judgment node to asynchronously execute the corresponding task; based on the vehicle device corresponding to the vehicle identification being unique, execute the asynchronous task node startAsyncTask defined in the first method judgment node to asynchronously execute the corresponding task. It should be noted that the preset database needs to be updated in real time according to the license plate identification and the vehicle device information corresponding to the license plate identification to avoid affecting the accuracy of the results. In addition, the preset database can be defined with a name according to actual design requirements, such as gpsnos, etc., and no further limitation is made here.

[0032] For example, the next node of start is singleDeviceCheck, and the data nodes of start include singleDeviceCheck, tellMultiDevice, deviceRestart, and multiDevice. Further, the type of singleDeviceCheck is action_condition, and the execution method of singleDeviceCheck can be to determine whether the vehicle device corresponding to the license plate identification is unique. When the vehicle device corresponding to the license plate identification is not unique, the next node can be isExistDevice. When the vehicle device corresponding to the license plate identification is unique, the next node can be startAsyncTask. In addition, singleDeviceCheck also includes the tools used in the execution method, which are specifically configured according to the actual design requirements and will not be further limited here. It should be added that determining whether the vehicle device corresponding to the license plate identification is unique includes: obtaining the license plate identification based on the obtained vehicle task information and determining whether the vehicle device corresponding to the license plate identification is unique.

[0033] Further, the type of isExistDevice is condition, and the execution condition of isExistDevice is to determine whether vehicle device information is stored in the preset database. When vehicle device information is stored in the preset database, the next node is isMultiDevice. When vehicle device information is not stored in the preset database, the next node is tellConfirmDevice. It should be noted that the execution condition of isExistDevice can be implemented based on a large language model. Specifically, based on the fact that the vehicle device corresponding to the license plate identification is not unique, execute the first condition judgment node defined in the first method judgment node to determine whether vehicle device information is stored in the preset database, including: based on the fact that the vehicle device corresponding to the license plate identification is not unique, use the first condition execution model to execute the first condition judgment node defined in the first method judgment node to extract vehicle device information and search and match it in the preset database; wherein, the first condition execution model is trained based on vehicle device information training data and the true labels of vehicle device information training data.

[0034] Further, the type of tellConfirmDevice is output, and the next node of tellConfirmDevice is the end node end. The output result can be determined according to the result output template designed according to the actual situation. For example, it can be "Please confirm whether the device exists: TELL_RESTART_CONFIRM_DEVICE", and no further limitation is made here. It should be added that the output result can be polished and output by using the large language model in combination with the result output template to ensure that the output result is output according to the corresponding preset template. Specifically, if there is no vehicle device information in the preset database, the first process output node defined in the first conditional judgment node is executed to notify the user to confirm whether the device exists and end the process, including: according to the result of the model output executed according to the first condition that there is no vehicle device information in the preset database, using the first output model, execute the first process output node defined in the first conditional judgment node to extract that there is no vehicle device information in the preset database and combine the corresponding context information, and polish and output according to the corresponding preset result output template to notify the user to confirm whether the device exists and end the process; where the first output model is trained based on the vehicle device information training data and the result labels of the vehicle device information training data.

[0035] Further, the type of isMultiDevice is condition, and the execution condition of isMultiDevice is to determine whether the vehicle device information in the preset database corresponds to multiple vehicle devices. When the vehicle device information in the preset database corresponds to multiple vehicle devices, the next node is tellMultiDevice; when the vehicle device information in the preset database does not correspond to multiple vehicle devices, the next node is startAsyncTask. It should be noted that the execution condition of isMultiDevice can be implemented based on the large language model. The specific condition execution method can refer to the first condition execution model mentioned above. When searching and matching in the preset database according to the extracted vehicle device information, determine whether it corresponds to multiple vehicle devices according to the number of matches, and no repeated elaboration is made here.

[0036] Further, the type of tellMultiDevice is action. The execution method of tellMultiDevice is to query vehicle device information based on the vehicle identifier, and the next node is multiDeviceOutput. Additionally, tellMultiDevice also includes the tools used in the execution method, which are specifically configured according to the actual design requirements and will not be further limited here. It should be added that the execution method of tellMultiDevice can be implemented based on a large language model. Specifically, if the vehicle device information in the preset database corresponds to multiple vehicle devices, the first execution node defined in the second conditional judgment node is executed to query the vehicle device information based on the vehicle identifier, including: based on the fact that the vehicle device information in the preset database corresponds to multiple vehicle devices, using the device recognition model, execute the first execution node defined in the second conditional judgment node to extract and identify the vehicle identifier features to obtain the vehicle device information; among them, the device recognition model is trained based on the vehicle training identifier and the device label corresponding to the vehicle training identifier.

[0037] Further, the type of multiDeviceOutput is user_action. The execution method of multiDeviceOutput is to output device information parameters corresponding to multiple devices and notify the user to select at least one and extract the device selection information returned by the user, and the next node is startAsyncTask. It should be added that multiDeviceOutput also includes a prompt message for prompting the user to select a device; multiDeviceOutput also includes the tools used in the execution method, which are specifically configured according to the actual design requirements and will not be further limited here. Additionally, based on the queried vehicle device information, execute the first user input execution node defined in the first execution node to notify the user that there are multiple devices and receive the device selection information returned by the user based on the notification of the existence of multiple devices, and based on the received device selection information returned by the user, execute the asynchronous task node defined in the first user input execution node, including: based on the queried vehicle device information, using the user input execution model, execute the first user input execution node defined in the first execution node, output multiple devices and receive the device selection information returned by the user based on the notification of the existence of multiple devices, and extract the device information parameters of the device selection information and trigger the execution of the asynchronous task node; among them, the first user input execution model is trained based on the device training data and the device parameter label corresponding to the device training data.

[0038] In an alternative embodiment, refer to Figure 3, the task type is a vehicle device restart task, and the asynchronous task node is executed, including: executing the second execution node deviceRestart defined in the asynchronous task node to restart the vehicle device; executing the third conditional judgment node isDeviceRestartSucc defined in the second execution node to check whether the vehicle device has been restarted successfully. If the vehicle device has been restarted successfully, execute the first task result output node tellDeviceRestartTrue defined in the third conditional judgment node to send a notification of successful restart and end the process end; otherwise, execute the second task result output node tellDeviceRestartFail defined in the third conditional judgment node to send a notification of failed restart and end the process end.

[0039] It should be added that in the case where the task type is a vehicle device restart task, the type of startAsyncTask is async_task, the next node of startAsyncTask is deviceRestart, and the asynchronous task step is 4. In addition, when executing startAsyncTask, it is also necessary to output a notification that the device is being restarted. The device restart notification can be expressed as DEVICE_RESTART_TASK_START_TEMPLATE, which can be specifically set according to actual design requirements and will not be further limited here. In addition, startAsyncTask also includes a task execution button button, such as auto_handle_case for automatically executing the process.

[0040] Furthermore, the type of deviceRestart is action, the execution method of deviceRestart is to restart the vehicle device, and the next node is isDeviceRestartSucc. In addition, deviceRestart also includes the tools used in the execution method, which can be specifically configured according to actual design requirements and will not be further limited here. It should be added that the execution method of deviceRestart can be implemented based on a large language model, and specific reference can be made to the node of the action type above, which will not be further limited here.

[0041] Further, the type of isDeviceRestartSucc is condition. The execution condition of isDeviceRestartSucc is to check whether the vehicle device has restarted successfully. When the device restarts successfully, the next node is tellDeviceRestartTrue; when the device restart fails, the next node is tellDeviceRestartFail. It should be added that if the vehicle device restart fails, isDeviceRestartSucc also includes an output error symbol nextFalseOutput, and the error symbol can be set according to actual design requirements, such as NEW_LINE, which is not further limited here. Additionally, to check whether the vehicle device has restarted successfully includes: determining whether the last code value is 0. If it is 0, the restart is successful; otherwise, the restart fails. It should be added that isDeviceRestartSucc can be implemented based on a large language model. Specifically, reference can be made to the nodes of the condition type above, which is not further limited here.

[0042] Further, the type of tellDeviceRestartTrue is result_output. The output of tellDeviceRestartTrue includes an output result and a result status. The output result is that the device has restarted successfully, and the result status is true or other forms indicating successful operation. The next node is end. The output result can be determined according to the corresponding previously configured result output template, such as DEVICE_RESTART_SUCC_TEMPLATE, which is not further limited here. It should be added that the execution of tellDeviceRestartTrue can be implemented based on a large language model. Specifically, if the vehicle device has restarted successfully, the first task result output node defined in the third conditional judgment node is executed to send a notification of successful restart and end the process, including: based on the successful restart of the vehicle device, using the first result output model, execute the first task result output node defined in the third conditional judgment node to extract the information of successful restart of the vehicle device and combine the corresponding context information, and polish and output according to the corresponding preset result output template to send a notification of successful restart and the restart status and end the process; where the first result output model is trained based on the vehicle device information training data and the result labels and status labels of the vehicle device information training data.

[0043] Further, the type of tellDeviceRestartFail is result_output. The output of tellDeviceRestartFail includes the output result and the result status. The output result is that the device restart fails, and the result status is false or other forms indicating operation failure. The next node is end. The output result can be determined according to the corresponding result output template configured previously, such as DEVICE_RESTART_FAIL_TEMPLATE, and no further limitation is made here. It should be added that tellDeviceRestartFail can refer to tellDeviceRestartTrue above, and no repeated elaboration is made here.

[0044] In an alternative embodiment, referring to Figure 4, the task type is a vehicle equipment offline task, and the asynchronous task node is executed, including: executing the fourth conditional judgment node isOnline defined in the asynchronous task node to check whether the vehicle equipment is online. If the vehicle equipment is online, execute the third task result output node tallOnline defined in the fourth conditional judgment node to output a device online notification; otherwise, execute the fifth conditional judgment node isServiceCorrect defined in the fourth conditional judgment node to check whether the vehicle equipment is in a service state; if it is not in a service state, execute the third execution node defined in the fifth conditional judgment node to output a service error reminder and end the process; otherwise, execute the sixth conditional judgment node isSimCorrect defined in the fifth conditional judgment node to check whether the user identification card of the corresponding vehicle equipment is in a normal state; if the user identification card is not in a normal state, execute the fifth execution node noticeSimStopError defined in the sixth conditional judgment node to output a user identification card error reminder and end the process end; otherwise, execute the second process output node deviceDebugOutPut defined in the sixth conditional judgment node to notify the user of device debugging, and execute the fourth execution node deviceDebug defined in the second process output node to perform device debugging. And based on the completion of device debugging, execute the seventh conditional judgment node isDeviceDebugSucc defined in the fourth execution node to check whether the vehicle equipment is successfully debugged; if the vehicle equipment is successfully debugged, execute the fifth execution node deviceDebugSuccess defined in the seventh conditional judgment node to asynchronously process the device debugging result, and execute the third process output node tellDebugSuccess defined in the fifth execution node to output a device debugging success notification and end the process; otherwise, execute the fourth task result output node tellDeviceDebugFail defined in the seventh conditional judgment node to output a device debugging failure notification and the result status and end the process.

[0045] It should be added that in the case where the task type is a vehicle equipment offline task, the type of startAsyncTask is async_task, the next node of startAsyncTask is isOnline, and the asynchronous task step is 9. Additionally, when executing startAsyncTask, a device debugging notification also needs to be output. The device debugging notification can be represented as DEVICE_HANDLE_TASK_START_TEMPLATE, which can be specifically set according to actual design requirements and will not be further limited here. Furthermore, startAsyncTask also includes a task execution button button, such as auto_handle_case for automatically executing the process.

[0046] Furthermore, the type of isOnline is condition, and the execution condition of isOnline is to check whether the vehicle device is online. When the vehicle device is online, the next node is tallOnline; when the vehicle device is not online, the next node is isServiceCorrect. It should be added that isOnline can be implemented based on the large language model. For details, please refer to the nodes of the condition type mentioned above, and no further limitation is made here.

[0047] Furthermore, the type of tallOnline is result_output. The output of tallOnline includes the output result and the result status. The output result is the device online notification, and the result status is true or other forms indicating successful operation. The next node is end. The output result can be determined according to the corresponding previously configured result output template, such as DEVICE_ONLINE_TEMPLATE, and no further limitation is made here. It should be added that tallOnline can be implemented based on the large language model. For details, please refer to the nodes of the result_output type mentioned above, and no further limitation is made here.

[0048] In addition, the type of isServiceCorrect is condition. The execution condition of isServiceCorrect is to check whether the vehicle device is in the service state. When it is not in the service state, the next node is noticeServiceExpires; when it is in the service state, the next node is isSimCorrect. In addition, when it is in the service state, isServiceCorrect also includes outputting a service success notification, which can be determined according to the actually designed template, such as SERVICE_SUCC_TEMPLATE, and no further limitation is made here. It should be added that isServiceCorrect can be implemented based on the large language model. For details, please refer to the nodes of the condition type mentioned above, and no further limitation is made here.

[0049] Furthermore, the type of noticeServiceExpires is action, and its execution method is service error reminder for reminder processing. The next node is tellServiceExpires. In addition, deviceRestart also includes the tools used in the execution method, which can be specifically configured according to actual design requirements and will not be further limited here. It should be added that noticeServiceExpires can be implemented based on a large language model. For details, reference can be made to the nodes of the action type above, which will not be further limited here.

[0050] Furthermore, the type of tellServiceExpires is output, and its output result is service error notification for hinting during processing. The next node is deviceServiceErrorMonitor, and the output result can be specifically determined according to the result output template of the actual design. For example, it can be SEND_TO_OPERATOR_TEMPLATE, which will not be further limited here. It should be added that tellServiceExpires can be implemented based on a large language model. For details, reference can be made to the nodes of the output type above, which will not be further limited here.

[0051] Furthermore, the type of deviceServiceErrorMonitor is action, and its execution method can be determined according to the actual task asynchronous processing method. For example, it can be the asynchronous processing of device service error monitoring async_deal_device_service_error_monitor, which will not be further limited here. The next node is end. In addition, deviceServiceErrorMonitor also includes the tools used in the execution method, which can be specifically configured according to actual design requirements and will not be further limited here. It should be added that deviceServiceErrorMonitor can be implemented based on a large language model. For details, reference can be made to the nodes of the action type above, which will not be further limited here.

[0052] Accordingly, if not in the service state, execute the third execution node defined in the fifth conditional judgment node to output a service error reminder and end the process, including: execute the third execution node defined in the fifth conditional judgment node to execute the service error reminder and jump to tellServiceExpires; based on jumping to tellServiceExpires, notify the service error and jump to deviceServiceErrorMonitor; based on jumping to deviceServiceErrorMonitor, asynchronously process the device service error monitoring and end the process.

[0053] In addition, if in the service state, execute the sixth conditional judgment node isSimCorrect defined in the fifth conditional judgment node. The type of isSimCorrect is condition, and the execution condition of isSimCorrect is to check whether the user identification card of the corresponding vehicle device is in a normal state. When the user identification card is in a normal state, the next node is deviceDebugOutPut. When the user identification card is not in a normal state, the next node is noticeSimStopError. It should be added that if the user identification card is in a normal state, isSimCorrect also includes a user identification card normal notice, and the user identification card normal notice can be determined according to the actually designed template, such as SIM_SUCC_TEMPLATE, and no further limitation is made here.

[0054] Furthermore, the type of noticeSimStopError is action, and the execution method of noticeSimStopError is to remind of the user identification card error for handling, and the next node is tellSimError. The tool used in the execution method can be configured according to the actual design requirements, and no further limitation is made here. It should be added that noticeSimStopError can be implemented based on the large language model. For details, please refer to the above nodes of the action type, and no further limitation is made here.

[0055] Furthermore, the type of tellSimError is output, and the output result of tellSimError is a user identification card error notification to prompt the processing. The next node is deviceErrorMonitor, and the output result can be specifically determined according to the actually designed result output template, such as SEND_TO_GROUP_TEMPLATE, and no further limitation is made here. It should be added that tellSimError can be implemented based on the large language model. For details, please refer to the above nodes of the output type, and no further limitation is made here.

[0056] Furthermore, the type of deviceErrorMonitor is action, and the execution method of deviceErrorMonitor can be determined according to the actual task asynchronous processing method. For example, it can be the asynchronous processing of device service error monitoring async_deal_device_service_error_monitor. No further limitation is made here, and the next node is end. In addition, deviceServiceErrorMonitor also includes the tools used in the execution method, which can be specifically configured according to the actual design requirements. No further limitation is made here. It should be added that deviceErrorMonitor can be implemented based on the large language model. For specific reference, please refer to the above nodes of the action type. No further limitation is made here.

[0057] Correspondingly, if the user identification card is not in a normal state, the fifth execution node noticeSimStopError defined in the sixth conditional judgment node is executed to output a user identification card error reminder and end the process end, including: executing the fifth execution node defined in the sixth conditional judgment node to execute the user identification card error reminder and jump to tellSimError; based on jumping to tellSimError, notifying the user identification card error and jumping to deviceErrorMonitor; based on jumping to deviceErrorMonitor, asynchronously processing the device service error monitoring and ending the process.

[0058] In addition, the type of deviceDebugOutPut is output, and the output result of deviceDebugOutPut is the user device debugging notification. The next node is deviceDebug, and the output result can be determined according to the actual design result output template. For example, it can be DEVICE_DEBUG_TEMPLATE. No further limitation is made here. It should be added that deviceDebugOutPut can be implemented based on the large language model. For specific reference, please refer to the above nodes of the output type. No further limitation is made here.

[0059] Furthermore, the type of deviceDebug is action, the execution method of deviceDebug is to debug the device, the next node is isDeviceDebugSucc, and the tools used in the execution method can be configured according to the actual design requirements. No further limitation is made here. It should be added that deviceDebug can be implemented based on the large language model. For specific reference, please refer to the above nodes of the action type. No further limitation is made here.

[0060] Further, the type of isDeviceDebugSucc is condition, and the execution condition of isDeviceDebugSucc is to check whether the vehicle device is successfully debugged. When the vehicle device is successfully debugged, the next node is deviceDebugSuccess; when the vehicle device is not successfully debugged, the next node is tellDeviceDebugFail. It should be added that checking whether the vehicle device is successfully debugged includes: determining whether the final status code code is 0. If it is 0, the vehicle device is successfully debugged; otherwise, the vehicle device is not successfully debugged. It should be added that isDeviceDebugSucc can be implemented based on the large language model. Specifically, reference can be made to the nodes of the condition type above, and no further limitation is made here.

[0061] Further, the type of deviceDebugSuccess is action, and the execution method of deviceDebugSuccess is to asynchronously process the device debugging result. The next node is tellDebugSuccess, and the tool used in the execution method can be configured in advance according to the method to be executed, and no further limitation is made here. It should be added that deviceDebugSuccess can be implemented based on the large language model. Specifically, reference can be made to the nodes of the action type above, and no further limitation is made here.

[0062] Further, the type of tellDebugSuccess is output, and the output result of tellDebugSuccess is the device debugging success notification. The next node is end, and the output result can be determined according to the actually designed result output template. For example, it can be DEVICE_DEBUG_SUCC_TEMPLATE, and no further limitation is made here. It should be added that tellDebugSuccess can be implemented based on the large language model. Specifically, reference can be made to the nodes of the output type above, and no further limitation is made here.

[0063] Further, the type of tellDeviceDebugFail is result_output. The output of tellDeviceDebugFail includes the output result and the result status. The output result is a device debug failure notification, and the result status is false or other forms indicating debug failure. The next node is end. The output result can be determined according to the corresponding result output template configured previously, such as DEVICE_DEBUG_ERROR_TEMPLATE, and no further limitation is made here. It should be added that tellDeviceDebugFail can be implemented based on the large language model. Specifically, reference can be made to the nodes of the result_output type above, and no further limitation is made here.

[0064] In addition, the next node of tellDeviceDebugFail can also be configured as dealOfflineFailCase for handling offline failure cases, which can be specifically configured according to actual design requirements, and no further limitation is made here.

[0065] In an alternative embodiment, refer to Figure 5, the task type is a vehicle equipment forwarding task, and the asynchronous task node is executed, including: executing the eighth conditional judgment node isbindTruck defined in the asynchronous task node to determine whether the data recipient is bound to the vehicle equipment; if the vehicle equipment is not bound, execute the fifth task result output node notBindTruck defined in the eighth conditional judgment node to output a notification of unbound; otherwise, execute the second method judgment node forwardProjectCheck defined in the eighth conditional judgment node to check whether the data recipient is correct; based on the incorrect data recipient, execute the ninth conditional judgment node projectMultiCheck defined in the second method judgment node to determine whether there are multiple data recipients for the vehicle equipment information to be forwarded. If there are multiple data recipients for the vehicle equipment information to be forwarded, execute the second user input execution node userCheckProject defined in the ninth conditional judgment node to output the corresponding multiple data selectors and notify the user to select a data recipient, and based on the recipient selection information returned by the received user, execute the sixth execution node add_device_forward defined in the second user input execution node to perform vehicle equipment data forwarding; otherwise, execute the sixth task result output node projectCheckFail defined in the ninth conditional judgment node to output a notification of incorrect data recipient and end the process; based on the correct data recipient, execute the sixth execution node add_device_forward defined in the second method judgment node to perform vehicle equipment data forwarding; based on the completion of data forwarding, execute the tenth conditional judgment node isAddSucc defined in the sixth execution node to determine whether the data forwarding is successful. If successful, execute the seventh task result output node deviceAddSucc defined in the tenth conditional judgment node to output a notification of successful device forwarding and end the process end; otherwise, execute the eighth task result output node deviceAddFail defined in the tenth conditional judgment node to output a notification of failed device forwarding and end the process end.

[0066] It should be added that in the case where the task type is a vehicle equipment forwarding task, the type of startAsyncTask is async_task, the next node of startAsyncTask is isbindTruck, and the asynchronous task step is 5. Additionally, when executing startAsyncTask, a device forwarding notification also needs to be output. The device forwarding notification can be expressed as FORWARD_DEVICE_TASK_START_TEMPLATE, which can be specifically set according to actual design requirements and will not be further limited here. Furthermore, startAsyncTask also includes a task execution button button, such as auto_handle_case for the automatic execution process.

[0067] Furthermore, the type of isbindTruck is condition. The execution condition of isbindTruck is to determine whether the data recipient is bound to a vehicle equipment. When the equipment is not bundled, the next node is notBindTruck; when the equipment is bundled, the next node is forwardProjectCheck. It should be added that the eighth conditional judgment node defined in the asynchronous task node is executed to determine whether the data recipient is bound to a vehicle equipment, including: using the second conditional execution model to execute the eighth conditional judgment node defined in the asynchronous task node to extract the data recipient information and detect whether the corresponding recipient is bound to a vehicle equipment; among them, the second conditional execution model is trained based on the recipient information training data and the true labels of the recipient information training data. Further, to check whether the data recipient is bound to a vehicle equipment, it includes: detecting whether the preset parameter for data reception has a value. If the preset parameter has a value, it is determined that the equipment is bundled; otherwise, it is determined that the equipment is not bundled. The preset parameter can be determined according to actual definitions, such as truck_no, and will not be further limited here.

[0068] Furthermore, the type of notBindTruck is result_output. The output of notBindTruck includes an output result and a result status. The output result is a device online notification, and the result status is false or other forms indicating operation failure. The next node is end. The output result can be determined according to the corresponding result output template configured in advance, such as FORWARD_DEVICE_NO_TRUCK, and no further limitation is made here. Further, if the vehicle device is not bound, the fifth task result output node defined in the eighth conditional judgment node is executed to output a vehicle not bound notification, including: based on the unbound vehicle device, using the second result output model, executing the fifth task result output node defined in the eighth conditional judgment node to extract the information of the unbound vehicle device and combine the corresponding context information, and performing polishing output according to the corresponding preset result output template to output the vehicle not bound notification and end the process; wherein, the second result output model is trained based on the vehicle device binding information training data and the result labels and status labels of the vehicle device binding information training data.

[0069] In addition, the type of forwardProjectCheck is action_condition. The execution method of forwardProjectCheck can be to check whether the data recipient is correct. When the data recipient is incorrect, the next node is projectMultiCheck. When the data recipient is correct, the next node is add_device_forward. It should be added that forwardProjectCheck also includes the tools used in the execution method, which are specifically configured with reference to the actual design requirements and no further limitation is made here.

[0070] Further, the type of projectMultiCheck is condition, and the execution condition of projectMultiCheck is to determine whether there are multiple data recipients for the vehicle device information to be forwarded. When there are multiple data recipients, the next node is userCheckProject; when there are no multiple data recipients, the next node is projectCheckFail. It should be added that based on incorrect data recipients, the ninth condition judgment node defined in the second method judgment node is executed to determine whether there are multiple data recipients for the vehicle device information to be forwarded, including: based on incorrect data recipients, using the third condition execution model, executing the ninth condition judgment node defined in the second method judgment node to extract the vehicle device information to be forwarded and detect whether there are multiple data recipients for the vehicle device information to be forwarded; wherein, the third condition execution model is trained based on the vehicle device information training data and the recipient labels of the vehicle device information training data. Additionally, if the data recipients are distinguished by project, determining whether there are multiple data recipients for the vehicle device information to be forwarded includes: determining whether the optional project names for forwarding are multiple. If so, there are multiple data recipients; if not, there are no multiple data recipients.

[0071] Further, the type of userCheckProject is user_action, and the execution method of userCheckProject is to output the corresponding multiple data recipients and notify the user to select at least one and extract the device information parameters of the device selection information returned by the user, and the next node is add_device_forward. It should be added that userCheckProject also includes a prompt message for prompting to select data recipients; additionally, userCheckProject also includes the tools used in the execution method, which are specifically configured according to the actual design requirements and will not be further limited here. Specifically, if there are multiple data recipients for the vehicle device information to be forwarded, the second user input execution node defined in the ninth condition judgment node is executed to output the corresponding multiple data recipients and notify the user to select data recipients, and based on the recipient selection information returned by the received user, the sixth execution node defined in the second user input execution node is executed, including: based on incorrect data recipients, using the second user input execution model, executing the ninth condition judgment node defined in the second method judgment node to output the notification of the corresponding multiple data recipients and receive the recipient selection information returned by the user based on the notification of the existence of multiple data recipients, and extract the device information parameters of the recipient selection information and trigger the execution of the sixth execution node defined in the second user input execution node; wherein, the second user input execution model is trained based on the vehicle training data and the recipient labels corresponding to the vehicle training data.

[0072] Furthermore, the type of add_device_forward is action, the execution method of add_device_forward is to forward vehicle device data, and the next node is isAddSucc. In addition, add_device_forward also includes the tools used in the execution method, which can be specifically configured according to actual design requirements and will not be further limited here. Specifically, executing the sixth execution node defined in the second user input execution node to forward vehicle device data includes: using the first action execution model to execute the sixth execution node defined in the second user input execution node to identify device information parameters and forward them to the corresponding data recipient; wherein, the first action execution model is trained based on device training data and the project labels corresponding to the device training data.

[0073] Furthermore, the type of isAddSucc is condition, the execution condition of isAddSucc is to determine whether the data forwarding is successful. When the data forwarding is successful, the next node is deviceAddSucc; when the data forwarding fails, the next node is deviceAddFail. It should be added that determining whether the data forwarding is successful includes: determining whether the character at the preset position of the device status code is 0. If it is 0, the forwarding is successful; otherwise, the forwarding fails. Specifically, based on the completion of data forwarding, execute the tenth condition judgment node defined in the sixth execution node to determine whether the data forwarding is successful, including: based on the completion of data forwarding, use the fourth condition execution model to execute the tenth condition judgment node defined in the sixth execution node to detect whether the data forwarding is successful; wherein, the fourth condition execution model is trained based on device training data and the status labels corresponding to the device training data.

[0074] Furthermore, the type of deviceAddSucc is result_output, the output of deviceAddSucc includes the output result and the result status. The output result is a device forwarding success notification, and the result status is true or other forms indicating successful operation. The next node is end, and the output result can be determined according to the corresponding previously configured result output template, such as FORWARD_DEVICE_ADD_SUCC, which will not be further limited here.

[0075] In addition, the type of deviceAddFail is result_output. The output of deviceAddFail includes the output result and the result status. The output result is a device forwarding failure notification, and the result status is false or other forms indicating forwarding failure. The next node is end. The output result can be determined according to the corresponding pre-configured result output template, such as FORWARD_DEVICE_ADD_FAIL, and no further limitation is made here.

[0076] Specifically, if successful, execute the seventh task result output node defined in the tenth conditional judgment node to output a device forwarding success notification and end the process; otherwise, execute the eighth task result output node defined in the tenth conditional judgment node to output a device forwarding failure notification and end the process, including: using the third result output model, based on successful data forwarding, execute the seventh task result output node defined in the tenth conditional judgment node to extract the successful data forwarding information and combine it with the corresponding context information, and polish and output according to the corresponding preset result output template to send a device forwarding success notification and the success status and end the process, or, based on failed data forwarding, execute the eighth task result output node defined in the tenth conditional judgment node to extract the failed data forwarding information and combine it with the corresponding context information, and polish and output according to the corresponding preset result output template to send a device forwarding failure notification and the failure status and end the process; among them, the third result output model is trained based on the result labels and status labels of the data forwarding status information training data and the data forwarding status information training data.

[0077] In addition, the type of projectCheckFail is result_output. The output of projectCheckFail includes the output result and the result status. The output result is a data receiver error notification, and the result status is false or other forms indicating receiver error. The next node is end. The output result can be determined according to the corresponding pre-configured result output template, such as PROJECT_ERROR, and no further limitation is made here.

[0078] In summary, the embodiment of the present invention uses a task classification model trained with a large amount of vehicle task training data and corresponding classification labels to identify the task type of the vehicle task information obtained, so as to intelligently judge the task type according to the input task information, providing an accurate basis for subsequent task creation, enabling the system to handle diverse vehicle task scenarios, improving the efficiency and accuracy of task classification, reducing errors and time costs that may be brought by manual intervention, and further creating and executing corresponding tasks according to the preset task creation rules. Moreover, the preset task creation rules clearly define the process nodes corresponding to each task type and the relationships between the nodes, ensuring the standardization and consistency of the task creation process, and helping to improve the quality and stability of the overall business process.

[0079] The vehicle task process processing device provided by the present invention will be described below. The vehicle task process processing device described below can be correspondingly referred to the vehicle task process processing method described above.

[0080] Figure 6 The structural schematic diagram of a vehicle task process processing device is shown. The device includes: An information acquisition module 61, which acquires vehicle task information; A task classification module 62, which inputs the vehicle task information into the task classification model to obtain the task type output by the task classification model; wherein, the task classification model is trained based on vehicle task training data and task classification labels corresponding to the vehicle task training data; A task processing module 63, which creates and executes corresponding tasks according to the task type in combination with the preset task creation rules; wherein, the preset task creation rules are used to define the process nodes corresponding to each task type and the relationships between the process nodes.

[0081] Since the principle of the device in the embodiment of the present invention is the same as that of the method in the above embodiment, the more detailed explanation content will not be elaborated here.

[0082] It should be noted that in the embodiment of the present invention, the relevant functional modules can be implemented by a hardware processor.

[0083] Figure 7 The structural schematic diagram of an electronic device is exemplified, as Figure 7As shown in the figure, the electronic device may include: a processor 710, a communications interface 720, a memory 730, and a communication bus 740. Among them, the processor 710, the communications interface 720, and the memory 730 complete their mutual communication through the communication bus 740. The processor 710 may call the logical instructions in the memory 730 to execute the vehicle task process handling method, which includes: obtaining vehicle task information; inputting the vehicle task information into a task classification model to obtain the task type output by the task classification model; wherein, the task classification model is trained based on vehicle task training data and task classification labels corresponding to the vehicle task training data; according to the task type, combining with a preset task creation rule, creating and executing a corresponding task; wherein, the preset task creation rule is used to define the process nodes corresponding to each task type and the relationships between the process nodes.

[0084] In addition, when the logical instructions in the above-mentioned memory 730 are implemented in the form of software functional units and sold or used as an independent product, they may be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, may be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs, Read-Only Memories), random access memories (RAMs, Random Access Memories), magnetic disks, or optical discs that can store program codes.

[0085] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the vehicle task process handling method provided by the above-mentioned various methods. The method includes: obtaining vehicle task information; inputting the vehicle task information into a task classification model to obtain the task type output by the task classification model; wherein, the task classification model is trained based on vehicle task training data and task classification labels corresponding to the vehicle task training data; according to the task type, combining with a preset task creation rule, creating and executing a corresponding task; wherein, the preset task creation rule is used to define the process nodes corresponding to each task type and the relationships between the process nodes.

[0086] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the vehicle task process handling method provided by the above-mentioned various methods. The method includes: obtaining vehicle task information; inputting the vehicle task information into a task classification model to obtain the task type output by the task classification model; wherein, the task classification model is trained based on vehicle task training data and task classification labels corresponding to the vehicle task training data; creating and executing corresponding tasks according to the task type in combination with a preset task creation rule; wherein, the preset task creation rule is used to define the process nodes corresponding to each task type and the relationships between the process nodes.

[0087] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative effort.

[0088] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A vehicle task process handling method, characterized in that, Including: Obtain vehicle task information; Input the vehicle task information into a task classification model to obtain the task type output by the task classification model; wherein, the task classification model is trained based on vehicle task training data and task classification labels corresponding to the vehicle task training data; According to the task type, in combination with a preset task creation rule, create and execute a corresponding task; wherein, the preset task creation rule is used to define the process nodes corresponding to each task type and the relationships between the process nodes.

2. The vehicle task process handling method according to claim 1, wherein Execute the corresponding created task, including: Execute the start node of the corresponding created task to start executing the task and execute the next node defined in the start node; In the case where the next node defined in the start node is a first method judgment node, if the first method judgment node is a single device inspection, determine whether the vehicle device corresponding to the license plate identification is unique; Based on the vehicle device corresponding to the license plate identification not being unique, execute the first condition judgment node defined in the first method judgment node to determine whether vehicle device information is stored in a preset database; wherein, the preset database is created in advance based on the license plate identification and the vehicle device information corresponding to the license plate identification; If the vehicle device information does not exist in the preset database, execute the first process output node defined in the first condition judgment node to notify the user to confirm whether the device exists and end the process; otherwise, execute the second condition judgment node defined in the first condition judgment node to determine whether the vehicle device information in the preset database corresponds to multiple vehicle devices; If the vehicle device information in the preset database corresponds to multiple vehicle devices, execute the first execution node defined in the second condition judgment node to query the vehicle device information according to the vehicle identification, and based on the queried vehicle device information, execute the first user input execution node defined in the first execution node to notify the user that there are multiple devices and receive the device selection information returned by the user based on the notification of the existence of multiple devices, and based on the received device selection information returned by the user, execute the asynchronous task node defined in the first user input execution node to asynchronously execute the corresponding task; otherwise, execute the asynchronous task node defined in the second condition judgment node to asynchronously execute the corresponding task; Based on the vehicle device corresponding to the vehicle identification being unique, execute the asynchronous task node defined in the first method judgment node to asynchronously execute the corresponding task.

3. The vehicle task process handling method according to claim 2, characterized in that, Based on the vehicle device corresponding to the license plate identification not being unique, execute the first condition judgment node defined in the first method judgment node to determine whether vehicle device information is stored in a preset database, including: Based on the vehicle device corresponding to the license plate identification not being unique, use a first condition execution model to execute the first condition judgment node defined in the first method judgment node to extract vehicle device information and search and match it in the preset database; wherein, the first condition execution model is trained based on vehicle device information training data and the true labels of the vehicle device information training data; If the vehicle device information does not exist in the preset database, execute the first process output node defined in the first conditional judgment node to notify the user to confirm whether the device exists and end the process, including: According to the result output by the first conditional execution model that the vehicle device information does not exist in the preset database, use the first output model to execute the first process output node defined in the first conditional judgment node, so as to extract that the vehicle device information does not exist in the preset database and combine the corresponding context information, and perform polishing output according to the corresponding preset result output template to notify the user to confirm whether the device exists and end the process; wherein, the first output model is trained based on the vehicle device information training data and the result label of the vehicle device information training data; If the vehicle device information in the preset database corresponds to multiple vehicle devices, execute the first execution node defined in the second conditional judgment node to query the vehicle device information according to the vehicle identifier, including: Based on the fact that the vehicle device information in the preset database corresponds to multiple vehicle devices, use the device identification model to execute the first execution node defined in the second conditional judgment node to extract and identify the vehicle identifier features to obtain the vehicle device information; wherein, the device identification model is trained based on the vehicle training identifier and the device label corresponding to the vehicle training identifier; Based on the queried vehicle device information, execute the first user input execution node defined in the first execution node to notify the user that there are multiple devices and receive the device selection information returned by the user based on the notification of the existence of multiple devices, and based on the received device selection information of the user, execute the asynchronous task node defined in the first user input execution node, including: Based on the queried vehicle device information, use the first user input execution model to execute the first user input execution node defined in the first execution node, output multiple devices and receive the device selection information returned by the user based on the notification of the existence of multiple devices, and extract the device information parameters of the device selection information and trigger the execution of the asynchronous task node; wherein, the first user input execution model is trained based on the device training data and the device parameter label corresponding to the device training data.

4. The vehicle task process handling method according to claim 2, characterized in that, The task type is the vehicle device restart task, execute the asynchronous task node, including: Execute the second execution node defined in the asynchronous task node to restart the vehicle device; Execute the third conditional judgment node defined in the second execution node to check whether the vehicle device is restarted successfully. If the vehicle device is restarted successfully, execute the first task result output node defined in the third conditional judgment node to send a notification of successful restart and end the process; otherwise, execute the second task result output node defined in the third conditional judgment node to send a notification of failed restart and end the process.

5. The vehicle task process handling method according to claim 2, wherein The task type is the vehicle device offline task, execute the asynchronous task node, including: Execute the fourth conditional judgment node defined in the asynchronous task node to check whether the vehicle device is online. If the vehicle device is online, execute the third task result output node defined in the fourth conditional judgment node to output a device online notification; otherwise, execute the fifth conditional judgment node defined in the fourth conditional judgment node to check whether the vehicle device is in a service state; If it is not in a service state, execute the third execution node defined in the fifth conditional judgment node to output a service error reminder and end the process; otherwise, execute the sixth conditional judgment node defined in the fifth conditional judgment node to check whether the user identification card of the corresponding vehicle device is in a normal state; If the user identification card is not in a normal state, execute the fifth execution node defined in the sixth conditional judgment node to output a user identification card error reminder and end the process; otherwise, execute the second process output node defined in the sixth conditional judgment node to notify the user device for debugging, and execute the fourth execution node defined in the second process output node to perform device debugging. And based on the completion of device debugging, execute the seventh conditional judgment node defined in the fourth execution node to check whether the vehicle device is successfully debugged; If the vehicle device is successfully debugged, execute the fifth execution node defined in the seventh conditional judgment node to asynchronously process the device debugging result, and execute the third process output node defined in the fifth execution node to output a device debugging success notification and end the process; Otherwise, execute the fourth task result output node defined in the seventh conditional judgment node to output a device debugging failure notification and result status and end the process.

6. The vehicle task process handling method according to claim 2, wherein, The task type is a vehicle device forwarding task. Executing the asynchronous task node includes: Execute the eighth conditional judgment node defined in the asynchronous task node to determine whether the data recipient is bound to a vehicle device; If the vehicle device is not bound, execute the fifth task result output node defined in the eighth conditional judgment node to output an unbound vehicle notification; otherwise, execute the second method judgment node defined in the eighth conditional judgment node to check whether the data recipient is correct; Based on the incorrect data recipient, execute the ninth conditional judgment node defined in the second method judgment node to determine whether there are multiple data recipients for the vehicle device information to be forwarded. If there are multiple data recipients for the vehicle device information to be forwarded, execute the second user input execution node defined in the ninth conditional judgment node to output the corresponding multiple data recipients and notify the user to select a data recipient. Based on the received recipient selection information returned by the user, execute the sixth execution node defined in the second user input execution node to perform vehicle device data forwarding; otherwise, execute the sixth task result output node defined in the ninth conditional judgment node to output a notification of incorrect data recipient and end the process; Based on the correct data recipient, execute the sixth execution node defined in the second method judgment node to perform vehicle device data forwarding; Based on the completion of data forwarding, execute the tenth conditional judgment node defined in the sixth execution node to determine whether the data forwarding is successful. If successful, execute the seventh task result output node defined in the tenth conditional judgment node to output a notification of successful device forwarding and end the process; otherwise, execute the eighth task result output node defined in the tenth conditional judgment node to output a notification of failed device forwarding and end the process.

7. The vehicle task process handling method according to claim 6, characterized in that, Execute the eighth conditional judgment node defined in the asynchronous task node to determine whether the data recipient is bound to a vehicle device, including: Use the second conditional execution model to execute the eighth conditional judgment node defined in the asynchronous task node to extract the data recipient information and detect whether the corresponding recipient is bound to a vehicle device; wherein, the second conditional execution model is trained based on the recipient information training data and the true labels of the recipient information training data. If not bound to a vehicle device, execute the fifth task result output node defined in the eighth conditional judgment node to output a notification of not bound to a vehicle, including: Based on not being bound to a vehicle device, use the second result output model to execute the fifth task result output node defined in the eighth conditional judgment node to extract the information of the unbound vehicle device and combine the corresponding context information, and polish and output according to the corresponding preset result output template to output a notification of not bound to a vehicle and end the process; wherein, the second result output model is trained based on the vehicle device binding information training data and the result labels and status labels of the vehicle device binding information training data. Based on the incorrect data recipient, execute the ninth conditional judgment node defined in the second method judgment node to determine whether there are multiple data recipients for the vehicle device information to be forwarded, including: Based on the incorrect data recipient, use the third conditional execution model to execute the ninth conditional judgment node defined in the second method judgment node to extract the vehicle device information to be forwarded and detect whether there are multiple data recipients for the vehicle device information to be forwarded; wherein, the third conditional execution model is trained based on the vehicle device information training data and the recipient labels of the vehicle device information training data. If there are multiple data recipients for the vehicle device information to be forwarded, execute the second user input execution node defined in the ninth conditional judgment node to output the corresponding multiple data recipients and notify the user to select a data recipient, and based on the recipient selection information returned by the received user, execute the sixth execution node defined in the second user input execution node, including: Based on the incorrect data recipient, execute the model using the second user input, and execute the ninth condition judgment node defined in the second method judgment node to output notifications corresponding to multiple data recipients and receive recipient selection information returned by the user based on the notification of the existence of multiple data recipients, and extract the device information parameters of the recipient selection information and trigger the execution of the sixth execution node defined in the second user input execution node; wherein, the second user input execution model is trained based on vehicle training data and recipient labels corresponding to the vehicle training data. Execute the sixth execution node defined in the second user input execution node to perform vehicle device data forwarding, including: Use the first action execution model to execute the sixth execution node defined in the second user input execution node to identify the device information parameters and forward them to the corresponding data recipient; wherein, the first action execution model is trained based on device training data and item labels corresponding to the device training data. Based on the completion of data forwarding, execute the tenth condition judgment node defined in the sixth execution node to determine whether the data forwarding is successful, including: Based on the completion of data forwarding, use the fourth condition execution model to execute the tenth condition judgment node defined in the sixth execution node to detect whether the data forwarding is successful; wherein, the fourth condition execution model is trained based on device training data and status labels corresponding to the device training data. If successful, execute the seventh task result output node defined in the tenth condition judgment node to output a notification of successful device forwarding and end the process; otherwise, execute the eighth task result output node defined in the tenth condition judgment node to output a notification of failed device forwarding and end the process, including: Use the third result output model, based on successful data forwarding, execute the seventh task result output node defined in the tenth condition judgment node to extract successful data forwarding information and combine it with the corresponding context information, and polish and output it according to the corresponding preset result output template to send a notification of successful device forwarding and the success status and end the process, or, based on failed data forwarding, execute the eighth task result output node defined in the tenth condition judgment node to extract failed data forwarding information and combine it with the corresponding context information, and polish and output it according to the corresponding preset result output template to send a notification of failed device forwarding and the failure status and end the process; wherein, the third result output model is trained based on data forwarding status information training data and result labels and status labels of data forwarding status information training data.

8. A vehicle task process handling device, characterized in that, Include: An information acquisition module that acquires vehicle task information; A task classification module that inputs the vehicle task information into a task classification model to obtain the task type output by the task classification model; wherein, the task classification model is trained based on vehicle task training data and task classification labels corresponding to the vehicle task training data. The task processing module creates and executes corresponding tasks according to the task type in combination with the preset task creation rules; wherein, the preset task creation rules are used to define the process nodes corresponding to each task type and the relationships between the process nodes.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the vehicle task process processing method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the vehicle task process processing method according to any one of claims 1 to 7.

Images