A method and apparatus for generating a vehicle inspection checklist

Abstract

The application discloses a kind of generation method and device of vehicle inspection list, it is related to vehicle service technical field.The specific embodiment of the method includes: based on the vehicle identification code and vehicle mileage data of vehicle, utilize vehicle type maintenance manual library and historical maintenance database, determine maintenance overage ratio, according to maintenance overage ratio determine should do the list of undone item;According to vehicle identification code and historical maintenance database, determine the set of unrepairable item and the set of repaired item, determine the list of historical remaining item based on the set of unrepairable item, according to the correlation rule base of pre-constructed, the set of repaired item is associated with inference, obtains the list of associated inspection item;According to should do the list of undone item, historical remaining item list and the list of associated inspection item generate vehicle inspection list.This embodiment can be structured with the depth of unstructured historical maintenance data of vehicle type maintenance manual data Fusion, automatically generate vehicle inspection list, improve the efficiency of list generation and accuracy.

Description

Technical Field

[0001] This invention relates to the field of vehicle service technology, and in particular to a method for generating a vehicle inspection checklist. Background Technology

[0002] In automotive repair and maintenance, receiving the vehicle and issuing an order is a crucial starting point in the service process. At this stage, technicians need to verify the vehicle's identification information (VIN, license plate, model, year), record the current mileage, manually review the paper or PDF version of the vehicle maintenance manual, and synthesize all the above information to generate a vehicle inspection checklist. This process requires technicians to quickly process heterogeneous information scattered across different systems or media, manually selecting inspection items in the system or handwriting the vehicle inspection checklist, which is inefficient and prone to errors. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method and apparatus for generating a vehicle inspection checklist, which can match the vehicle model maintenance manual library and historical repair database according to the vehicle identification number and vehicle mileage data, deeply integrate the structured vehicle model maintenance manual data with the unstructured historical repair data, and automatically generate a vehicle inspection checklist, thereby improving the efficiency and accuracy of checklist generation.

[0004] To achieve the above objectives, according to one aspect of the present invention, a method for generating a vehicle inspection checklist is provided, comprising: Based on the vehicle identification number and mileage data, and using a pre-built model maintenance manual library and historical repair database, the vehicle's maintenance overdue rate is determined, and a list of maintenance items that should have been done but were not is determined based on the maintenance overdue rate. The vehicle identification number and the historical maintenance database are used to determine the unrepaired items set and the repaired items set of the vehicle. The unrepaired items set is used to determine the list of historical legacy items. The repaired items set is used to perform association reasoning based on a pre-built association rule base to obtain the list of associated inspection items. A vehicle inspection checklist is generated based on the list of items that should have been done but were not, the list of historical items, and the list of related inspection items.

[0005] Optionally, before determining the vehicle's maintenance overdue rate using a pre-built model maintenance manual library and historical repair database based on the vehicle's vehicle identification number and mileage data, the following steps are also included: Perform validity verification on the vehicle identification number and confirm that the validity verification was successful; Perform mileage logic verification on the vehicle mileage data and confirm that the mileage logic verification is successful. In response to a failure in validity verification or mileage logic verification, the vehicle mileage data generates an error message and sends it back to the user so that the user can re-enter the vehicle identification number or vehicle mileage data based on the error message.

[0006] Optionally, based on the vehicle's vehicle identification number (VIN) and mileage data, a pre-built model maintenance manual library and historical repair database are used to determine the vehicle's maintenance overdue rate, including: Based on the vehicle identification number, extract the corresponding maintenance item set for the vehicle from the vehicle maintenance manual database; Iterate through each maintenance item in the maintenance item set and query the target execution record corresponding to each maintenance item from the historical maintenance database. Based on the target execution record, determine the historical execution mileage data and historical execution time data corresponding to each maintenance item. Based on vehicle mileage data, historical mileage data corresponding to each maintenance item, and preset mileage cycles corresponding to each maintenance item, determine the mileage overdue rate for each maintenance item. Based on the acquired target time data, the historical execution time data corresponding to each maintenance item, and the preset time cycle corresponding to each maintenance item, determine the time overdue ratio corresponding to each maintenance item. The mileage overdue rate and time overdue rate of each maintenance item are compared numerically, and the maintenance overdue rate of the vehicle is determined based on the numerical comparison results.

[0007] Optionally, a list of required but unfulfilled maintenance items for the vehicle can be determined based on the maintenance overdue rate, including: Determine whether the maintenance overdue rate for each maintenance item exceeds the preset maintenance overdue threshold; In response to the maintenance overdue rate of the maintenance item exceeding the preset maintenance overdue threshold, the maintenance item is broken down into basic inspection sub-items and in-depth investigation sub-items; Generate a list of items that should have been done but were not, based on the basic inspection sub-items and the in-depth investigation sub-items.

[0008] Optionally, a list of legacy items can be determined based on the set of unrepaired items, including: Determine the time-depreciation information for each unmaintained item in the unmaintained item set; Based on the time-depreciation information corresponding to each unrepaired item, a list of historical legacy items for the vehicle is determined.

[0009] Optionally, a vehicle inspection checklist is generated based on the list of items that should have been done but were not, the list of historical items, and the list of related inspection items, including: The list of uncompleted items, the list of legacy items, and the list of related inspection items are merged to obtain a merged list of inspection items. The merged list of test items is deduplicated to obtain the target list of test items. Determine the priority of each target detection item in the target detection item list; Based on the priority of each target detection item in the target detection item list, a vehicle inspection checklist is generated for the vehicle.

[0010] Optionally, the priority of each target detection item in the target detection item list is determined, including: Determine the safety score, timeliness score, and value score corresponding to each target detection item; Based on preset weighting coefficients, the safety score, timeliness score, and value score are weighted and summed to obtain the comprehensive score corresponding to each target detection item. The priority of each target detection item is determined based on the comprehensive score corresponding to each target detection item.

[0011] According to a second aspect of the present invention, a vehicle inspection checklist generation apparatus is provided, comprising: The first determination module is used to determine the vehicle's maintenance overdue rate based on the vehicle identification number and vehicle mileage data, using a pre-built vehicle model maintenance manual library and historical repair database, and to determine the vehicle's list of required but unfulfilled maintenance items based on the maintenance overdue rate. The second determination module is used to determine the unrepaired item set and the repaired item set of a vehicle based on the vehicle identification code and the historical maintenance database, determine the historical legacy item list based on the unrepaired item set, and perform association reasoning on the repaired item set according to the pre-built association rule base to obtain the associated inspection item list. The checklist generation module is used to generate a vehicle inspection checklist based on the list of items that should have been done but were not, the list of historical legacy items, and the list of related inspection items.

[0012] According to a third aspect of the present invention, an electronic device is provided, comprising: One or more processors; Memory, used to store one or more programs. When one or more programs are executed by one or more processors, the one or more processors implement the methods of any of the above embodiments.

[0013] According to a fourth aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method of any of the above embodiments.

[0014] According to a fifth aspect of the present invention, a computer program product is provided, including a computer program that, when executed by a processor, implements the method of any of the above embodiments.

[0015] One embodiment of the above invention has the following advantages or beneficial effects: By utilizing a pre-built vehicle model maintenance manual library and historical repair database based on the vehicle identification number (VIN) and vehicle mileage data, the vehicle's maintenance overdue rate is determined; based on the maintenance overdue rate, a list of required but un-done items for the vehicle is determined; based on the VIN and historical repair database, a set of un-repaired items and a set of repaired items for the vehicle are determined; based on the un-repaired item set, a list of historical legacy items is determined; based on a pre-built association rule library, association reasoning is performed on the repaired item set to obtain a list of associated inspection items; and a vehicle inspection checklist is generated based on the list of required but un-done items, the list of historical legacy items, and the list of associated inspection items. This embodiment can match the vehicle model maintenance manual library and historical repair database based on the vehicle's VIN and vehicle mileage data, deeply integrate structured vehicle model maintenance manual data with unstructured historical repair data, and automatically generate a vehicle inspection checklist, improving the efficiency and accuracy of checklist generation.

[0016] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0017] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein: Figure 1 This is a schematic diagram of the main flow of the method for generating a vehicle inspection checklist according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the main flow of a method for generating a vehicle inspection checklist according to a preferred embodiment of the present invention; Figure 3 This is a schematic diagram of the main modules of a vehicle inspection checklist generation device according to an embodiment of the present invention; Figure 4 This is an exemplary system architecture diagram in which embodiments of the present invention can be applied; Figure 5 This is a schematic diagram of the structure of a computer system suitable for implementing terminal devices or servers of the present invention. Detailed Implementation

[0018] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0019] It should be noted that the acquisition, storage, and application of personal information involved in the embodiments of the present invention comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0020] In automotive repair and maintenance, receiving the vehicle and issuing an order is a crucial starting point in the service process. At this stage, technicians need to verify the vehicle's identification information (VIN, license plate, model, year), record the current mileage, manually review the paper or PDF version of the vehicle maintenance manual, and synthesize all the above information to generate a vehicle inspection checklist. This process requires technicians to quickly process heterogeneous information scattered across different systems or media, manually selecting inspection items in the system or handwriting the vehicle inspection checklist, which is inefficient and prone to errors.

[0021] In view of this, according to one aspect of the present invention, a method for generating a vehicle inspection checklist is provided.

[0022] Figure 1 This is a schematic diagram illustrating the main flow of a method for generating a vehicle inspection checklist according to an embodiment of the present invention. Figure 1 As shown, the method for generating a vehicle inspection list according to an embodiment of the present invention includes the following steps S101 to S103.

[0023] Step S101: Based on the vehicle identification number and vehicle mileage data, using a pre-built vehicle model maintenance manual library and historical repair database, determine the vehicle's maintenance overdue rate, and determine the list of items that should have been done but were not done based on the maintenance overdue rate.

[0024] In this embodiment, the Vehicle Identification Number (VIN) is a unique identifier for the vehicle, preferably a 17-digit VIN conforming to international standards. The VIN includes vehicle brand information, model information, engine type information, production year information, and manufacturer information. The VIN can be obtained by scanning the vehicle nameplate, reading data from the on-board diagnostic interface, querying license plate information, or manual input. Vehicle mileage data is operational data representing the vehicle's current usage status, preferably accumulated mileage data. Vehicle mileage data can be automatically read from the vehicle's electronic control unit via the on-board diagnostic interface, or obtained through dashboard recognition or manual input.

[0025] The vehicle maintenance manual database is a pre-built structured database of maintenance knowledge used to store standard maintenance rules for different vehicle models. It may include data such as vehicle identification number prefix, vehicle name, vehicle year, maintenance item name, maintenance interval mileage, maintenance interval time, safety level, item category, and whether it is a mandatory maintenance item. The historical repair database is a time-series database used to store historical vehicle repair data. It may include data such as historical repair time, historical mileage, performed repairs, recommended but not performed repairs, customer-rejected repairs, fault code information, technician notes, and parts replacement records.

[0026] The maintenance overdue ratio is a quantitative indicator used to characterize the extent to which a vehicle's current maintenance status has exceeded the preset maintenance cycle. It reflects the degree to which maintenance items deviate from the prescribed maintenance period. The higher the maintenance overdue ratio, the greater the extent to which the corresponding maintenance item has exceeded the recommended maintenance cycle, and the greater the possibility of vehicle performance degradation or malfunction. By introducing the maintenance overdue ratio, the overdue status of different maintenance items can be uniformly and quantitatively evaluated. The list of items that should have been done but were not is a set of pending items that have reached or exceeded their maintenance cycle but have not yet been performed.

[0027] Specifically, this embodiment first matches the maintenance items and corresponding standard maintenance cycles for the corresponding vehicle model from the vehicle maintenance manual database based on the vehicle identification number. Then, it extracts the historical mileage data corresponding to the most recent execution record of each maintenance item from the historical repair database. Based on the difference between the current vehicle mileage data and the historical mileage data, and the standard maintenance cycle of the corresponding maintenance item, it calculates the maintenance overdue rate. Further, maintenance items whose maintenance overdue rate reaches a preset maintenance overdue threshold are identified as overdue or expired items, and the corresponding items are added to the list of items that should be done but have not been done, thereby forming maintenance recommendations that conform to the actual usage status of the vehicle.

[0028] In another implementation, in addition to combining vehicle mileage data, a comprehensive analysis is also performed using historical execution time information corresponding to maintenance items. Specifically, a time overdue ratio is determined based on the time interval between the current time and the historical execution time. This time overdue ratio is then compared with a mileage overdue ratio determined based on vehicle mileage data, and the larger of the two is selected as the maintenance overdue ratio, reflecting the maintenance principle of "whichever comes first, the time cycle or the mileage cycle." Maintenance items are categorized into different statuses based on the maintenance overdue ratio. Maintenance items with an overdue ratio exceeding a preset overdue threshold are identified as severely overdue items and added to the list of items that should have been done but were not. Maintenance items with an overdue ratio close to the preset overdue threshold are identified as items nearing their expiration date, allowing for advance maintenance reminders and improving the accuracy and completeness of vehicle maintenance management.

[0029] Step S102: Determine the unrepaired item set and the repaired item set of the vehicle based on the vehicle identification code and the historical maintenance database. Determine the list of historical legacy items based on the unrepaired item set. Perform association reasoning on the repaired item set based on the pre-built association rule base to obtain the list of associated inspection items.

[0030] The unrepaired items set refers to the collection of maintenance and repair items extracted from the historical maintenance database that have not yet been completed. This includes items refused by the customer, items recommended for future maintenance, partially completed but not fully resolved items, and items requiring continuous follow-up. The repaired items set includes the collection of completed repair items recorded in the historical maintenance database, along with a list of fault codes. It records information such as the execution time, mileage, replaced parts, and repair results for each item. The legacy items list refers to the collection of items marked as recommended for future maintenance, refused by the customer, or temporarily not processed during historical maintenance, and which are currently still unresolved.

[0031] The association rule base is a pre-built maintenance knowledge base used to describe the relationships between different maintenance items, fault phenomena, component status, and inspection items. The associated inspection item list is a set of associated risk inspection items obtained through automatic reasoning. For example, if there is a shock absorber replacement record in the historical maintenance data, a four-wheel alignment inspection item or an abnormal noise re-inspection item will be automatically generated.

[0032] Specifically, based on the vehicle identification number (VIN), all repair records for the vehicle are extracted from the historical repair database. The status fields of the repair records are parsed, and items with statuses such as recommended repair, delayed repair, customer-rejected repair, or incomplete repair are categorized into the "unrepaired items" set. Items with statuses such as completed repair, completed maintenance, or completed replacement are categorized into the "repaired items" set. A risk assessment is performed on each item in the "unrepaired items" set, determining its importance based on factors such as the system category, historical frequency, and cumulative usage since the last recommended repair. Items meeting preset criteria are included in the legacy items list. Furthermore, a rule-based matching system is used to match each repair item in the "repaired items" set, identifying inspection items with subsequent verification relationships, accompanying inspection relationships, or consequential impact relationships with the corresponding repair items, thereby generating a list of associated inspection items.

[0033] In another implementation, maintenance behavior sequences can be formed by extracting vehicle maintenance records from a historical maintenance database based on the vehicle identification number (VIN). The sets of unrepaired and repaired items are then identified by analyzing the changes in these sequences. For the unrepaired item set, not only are currently unprocessed items retained, but items that have been repeatedly suggested but remain unprocessed are further identified and designated as key items in the historical legacy item list. For the repaired item set, multi-level association reasoning is performed in the association rule base, considering the repair location, component category, and fault resolution status of each item. For example, if the repaired item set contains engine ignition system maintenance records, spark plug working status checks, ignition coil connection status checks, and engine operating condition checks can be generated; if the repaired item set contains steering system maintenance records, steering angle detection checks, chassis connection component checks, and tire wear status checks can be generated. This association reasoning process yields a list of associated inspection items, enabling proactive discovery of potential vehicle risks and associated faults, thus improving the comprehensiveness and accuracy of vehicle inspections.

[0034] Step S103: Generate a vehicle inspection checklist based on the list of items that should have been done but were not, the list of historical legacy items, and the list of related inspection items.

[0035] A vehicle inspection checklist is a collection of inspection items generated based on the vehicle's current operating status. It is used to show mechanics the maintenance, repairs, and risk checks that need to be performed on the vehicle. Each inspection item in the vehicle inspection checklist may include information such as item name, item category, priority, risk warning, inspection basis, and suggested handling method.

[0036] In this embodiment, the lists of items that should have been done but were not, legacy items, and related inspection items are first compiled and categorized according to their respective systems, forming inspection sets for engine systems, braking systems, steering systems, electrical systems, chassis systems, and so on. Then, based on the risk level, fault impact range, and inspection complexity of each item, corresponding inspection content, testing standards, and inspection sequence are generated, and dependencies between items are established. For example, when a four-wheel alignment inspection item exists in the related inspection item list, tire wear inspection and suspension system inspection items can be automatically associated, forming a complete inspection chain. Finally, the inspection items corresponding to each system are integrated to generate a vehicle inspection checklist, improving on-site inspection efficiency and coverage.

[0037] In another implementation, when generating a vehicle inspection checklist based on the list of items to be done but not yet completed, the list of historical legacy items, and the list of related inspection items, dynamic assembly can be performed based on vehicle maintenance profile information in a historical maintenance database. Specifically, a vehicle risk profile is constructed based on the vehicle's historical fault frequency, maintenance preferences, parts replacement patterns, and vehicle usage intensity. This risk profile is then used to filter and expand items in the lists of items to be done but not yet completed, the historical legacy items, and the related inspection items. When an item is found to be associated with a high-frequency historical fault characteristic of the vehicle, a corresponding verification inspection item can be automatically added. When multiple items are found to involve the same component or system, they can be automatically merged into a comprehensive inspection task. For example, if the list of items to be done but not yet completed includes brake fluid replacement and the historical legacy items include brake system anomaly items, brake line sealing inspection and brake actuator status inspection items can be further generated. The expanded inspection items are organized and arranged according to the level of concern corresponding to the vehicle risk profile to form a vehicle inspection checklist, thereby enabling proactive discovery of potential vehicle faults and improving the accuracy of inspection results and the relevance of maintenance recommendations.

[0038] Furthermore, in some implementations, the vehicle inspection checklist can also simultaneously generate corresponding inspection instructions, risk warnings, and repair suggestions, and establish a traceability relationship between inspection items and historical repair records. This allows technicians to quickly understand the source basis, causes, and suggested handling methods for each inspection item, thereby improving the efficiency of information utilization and the accuracy of decision-making during the vehicle receipt and order processing stage.

[0039] This embodiment utilizes a pre-built vehicle model maintenance manual library and historical repair database based on the vehicle identification number (VIN) and mileage data to determine the vehicle's maintenance overdue rate. Based on this rate, it identifies a list of required but uncompleted maintenance items. Then, it determines the vehicle's unrepaired and repaired item sets based on the VIN and historical repair database. A list of legacy items is derived from the unrepaired item set, and a list of associated inspection items is obtained by performing association reasoning on the repaired item set using a pre-built association rule library. Finally, a vehicle inspection checklist is generated based on the list of required but uncompleted items, the list of legacy items, and the list of associated inspection items. This embodiment can match the vehicle model maintenance manual library and historical repair database using the vehicle identification number and mileage data, deeply integrating structured vehicle maintenance manual data with unstructured historical repair data to automatically generate a vehicle inspection checklist, improving the efficiency and accuracy of checklist generation.

[0040] Optionally, before determining the vehicle's maintenance overdue rate based on the vehicle identification number (VIN) and vehicle mileage data using a pre-built vehicle maintenance manual library and historical repair database, the process further includes: performing validity verification on the VIN and confirming successful validity verification; performing mileage logic verification on the vehicle mileage data and confirming successful mileage logic verification; and generating an error message in response to a validity verification failure or mileage logic verification failure, and feeding the error message back to the user so that the user can re-enter the VIN or vehicle mileage data based on the error message.

[0041] In this embodiment, after obtaining the vehicle identification number (VIN) input by the user, the encoding length, character composition, and verification rules of the VIN are parsed, and it is determined whether the VIN conforms to the preset VIN encoding standard. For example, it can be verified whether the VIN has a preset number of digits, whether it contains illegal characters, and whether the check bits are correct. After confirming the validity of the VIN, the vehicle model information, year information, and power configuration data in the VIN are further parsed, and the parsing results are used for subsequent matching processing with the vehicle maintenance manual database. After completing the validity verification of the VIN, mileage logic verification processing is performed on the vehicle mileage data. Specifically, the vehicle mileage data is compared with the historical mileage data in the historical maintenance database, and it is determined whether the vehicle mileage data is less than the historical mileage data, has an abnormal surge, or exceeds a preset change range. For example, when the vehicle mileage data is less than the most recent historical mileage data, it is determined that there is a risk of mileage inversion; when the difference between the vehicle mileage data and the historical mileage data exceeds a preset abnormal threshold, it is determined that there is a suspected risk of odometer tampering. After confirming that the vehicle mileage data meets the preset logic rules, the vehicle mileage data is used for subsequent maintenance cycle calculation and historical legacy status analysis.

[0042] When the vehicle identification number (VIN) validity check fails or the mileage logic check fails, a corresponding error message is generated and sent to the user, prompting them to re-enter the VIN or mileage data. The error message may include information such as an incorrect VIN format, incorrect mileage, conflicting historical mileage records, or data retrieval failure, thereby improving the accuracy of the input data.

[0043] In another implementation, the vehicle identification number (VIN) and mileage data from the vehicle's electronic control unit can be automatically read via the on-board diagnostic (ODI) interface. Cross-validation is then performed between the ODI results and user input. If the automatically read results differ from the user input, an anomaly confirmation process is automatically triggered, prioritizing the use of the more reliable data source as the final vehicle data. This approach further reduces the impact of manual data entry errors and odometer tampering on the accuracy of subsequent inspection data generation.

[0044] The above embodiments enable effective verification of vehicle basic data before generating a vehicle inspection list, avoiding errors in maintenance item matching, repair cycle calculation, and risk assessment due to incorrect vehicle identification codes, abnormal vehicle mileage, or historical data conflicts, thereby improving the accuracy and reliability of the generated vehicle inspection list.

[0045] Optionally, based on the vehicle identification number (VIN) and mileage data, a pre-built vehicle maintenance manual library and historical repair database are used to determine the vehicle's maintenance overdue rate. This includes: extracting the maintenance item set corresponding to the vehicle from the vehicle maintenance manual library based on the VIN; traversing each maintenance item in the maintenance item set and querying the target execution record corresponding to each maintenance item from the historical repair database, determining the historical execution mileage data and historical execution time data corresponding to each maintenance item based on the target execution record; determining the mileage overdue rate of each maintenance item based on the vehicle mileage data, the historical execution mileage data corresponding to each maintenance item, and the preset mileage cycle corresponding to each maintenance item; determining the time overdue rate of each maintenance item based on the obtained target time data, the historical execution time data corresponding to each maintenance item, and the preset time cycle corresponding to each maintenance item; and comparing the mileage overdue rate and time overdue rate of each maintenance item numerically, determining the vehicle's maintenance overdue rate based on the numerical comparison result.

[0046] In this embodiment, the vehicle identification number (VIN) and mileage data of the vehicle are acquired, and the corresponding maintenance item set for the vehicle model is matched from the vehicle model maintenance manual library based on the VIN. The vehicle model maintenance manual library pre-stores the preset mileage cycle and preset time cycle for each maintenance item. For each maintenance item in the maintenance item set, the corresponding target execution record is queried from the historical maintenance database, and the historical execution mileage data and historical execution time data are extracted from the target execution record. The mileage overdue ratio for each maintenance item is obtained by dividing the difference between the vehicle mileage data and the historical execution mileage data by the preset mileage cycle of the corresponding maintenance item; simultaneously, the time overdue ratio for each maintenance item is calculated based on the time interval between the acquired target time data and the historical execution time data, as well as the preset time cycle of the corresponding maintenance item. Furthermore, the mileage overdue ratio and the time overdue ratio are numerically compared, and the larger value is selected as the maintenance overdue ratio for the corresponding maintenance item, thereby satisfying the business rule of "mileage condition and time condition, whichever comes first" in the vehicle maintenance process. By simultaneously incorporating two dimensions—vehicle usage intensity and usage duration—we can more accurately reflect the vehicle's true maintenance status, avoiding maintenance judgment biases caused by relying on only a single dimension, and improving the accuracy and reliability of maintenance item identification.

[0047] In another embodiment, when determining the maintenance overdue rate of a vehicle, a maintenance cycle benchmark model can be constructed based on a vehicle model maintenance manual library and a historical repair database. Specifically, the maintenance item set corresponding to the vehicle is determined according to the vehicle identification number, and historical execution mileage data and historical execution time data corresponding to multiple execution records of each maintenance item are extracted from the historical repair database to calculate the actual execution cycle of each maintenance item. Subsequently, a deviation analysis is performed between the actual execution cycle and the preset mileage cycle and preset time cycle in the vehicle model maintenance manual library to obtain the degree of cycle deviation corresponding to each maintenance item. This deviation is then combined with the current vehicle mileage data and target time data to calculate the degree of deviation between the current maintenance status and the standard maintenance status, and the degree of deviation is determined as the maintenance overdue rate. This implementation not only considers the current maintenance status but also comprehensively considers the vehicle's historical maintenance patterns, which can more realistically reflect the long-term usage characteristics and maintenance status of the vehicle, thereby further improving the rationality and adaptability of the maintenance overdue rate calculation results.

[0048] Optionally, a list of required but uncompleted maintenance items for the vehicle is determined based on the maintenance overdue rate, including: determining whether the maintenance overdue rate corresponding to each maintenance item exceeds a preset maintenance overdue threshold; in response to the maintenance overdue rate corresponding to the maintenance item exceeding the preset maintenance overdue threshold, breaking down the maintenance item into basic inspection sub-items and in-depth investigation sub-items; and generating a list of required but uncompleted maintenance items based on the basic inspection sub-items and in-depth investigation sub-items.

[0049] In this embodiment, the overdue maintenance ratio for each maintenance item is first obtained, and then compared with a preset overdue maintenance threshold. The preset overdue maintenance threshold can be set according to maintenance rules in the vehicle maintenance manual library, such as a threshold corresponding to a severely overdue state. When the overdue maintenance ratio for a certain maintenance item exceeds the preset overdue maintenance threshold, it indicates that the maintenance item has significantly exceeded the normal maintenance cycle and has a high potential risk of failure. At this point, the maintenance item is no longer treated as a single inspection item, but is further broken down according to pre-built item decomposition rules, generating basic inspection sub-items and in-depth investigation sub-items. The basic inspection sub-items are used to confirm whether the maintenance item meets the execution conditions and its current working status, while the in-depth investigation sub-items are used to detect associated faults, performance degradation, or component damage that may be caused by long-term overdue maintenance. For example, when the engine lubrication system maintenance item is severely overdue, basic inspection sub-items such as engine oil condition detection and filter condition detection can be generated, as well as in-depth investigation sub-items such as engine wear condition detection and lubrication system pressure detection. A list of required but uncompleted items is generated based on basic inspection sub-items and in-depth investigation sub-items, making vehicle inspections more comprehensive. By introducing a maintenance item breakdown mechanism, the problem of performing only routine maintenance on long-overdue vehicles while neglecting potential hidden dangers can be avoided, improving the ability to detect vehicle faults and the accuracy of repair recommendations.

[0050] In another embodiment, when determining the list of maintenance items that should be done but haven't been done based on the maintenance overdue rate, a tiered screening method can be used. Specifically, maintenance items are divided into items that are about to expire, expired items, and severely overdue items according to the numerical range of the maintenance overdue rate, and different processing strategies are assigned to each. For items that are about to expire, a pre-reminder item can be generated; for expired items, they can be directly added to the list of maintenance items that should be done but haven't been done; for severely overdue items, risk warning information and key inspection marks are added in addition to being added to the list of maintenance items that should be done but haven't been done. Furthermore, the importance of the maintenance items to the system to which they belong can be considered to prioritize the inclusion of safety-related items such as braking systems, steering systems, and airbag systems, thereby forming a list of maintenance items that should be done but haven't been done that reflects the actual risk status of the vehicle, improving the pertinence and safety of maintenance decisions.

[0051] Optionally, a list of legacy items is determined based on the set of unrepaired items, including: determining the time-depreciation information corresponding to each unrepaired item in the set of unrepaired items; and determining the list of legacy items for the vehicle based on the time-depreciation information corresponding to each unrepaired item.

[0052] In this embodiment, each unrepaired item in the unrepaired item set may include data such as item name, suggested repair time, suggested repair mileage, reason for refusal, and technician remarks. Based on the time interval between the current time and the suggested repair time for the corresponding unrepaired item, a time-depreciation coefficient for the corresponding unrepaired item is calculated. Combined with the mileage difference between the vehicle mileage data and the suggested repair mileage, the degree of long-term non-processing of the corresponding unrepaired item is determined. When a corresponding unrepaired item has exceeded a preset time range or a preset mileage range without being repaired, the risk level of the corresponding unrepaired item is increased, and the corresponding unrepaired item is marked as an overdue unprocessed item. Based on the time-depreciation information and risk level corresponding to each unrepaired item, a list of historical legacy items for the vehicle is determined.

[0053] In another implementation, dynamic risk analysis can be performed on unrepaired items by combining information such as the item category, recurrence frequency, and safety level. Specifically, based on historical fault records in the historical maintenance database, the recurrence frequency of faults associated with corresponding unrepaired items is counted. When a corresponding fault recurs multiple times, the risk level of the corresponding unrepaired item is increased, and the time-related degradation of the corresponding unrepaired item is reduced, so that high-risk unrepaired items maintain a high priority even after prolonged periods of neglect. Furthermore, the risk status of corresponding unrepaired items can be dynamically adjusted based on the vehicle mileage growth rate, thereby improving the accuracy of identifying legacy items.

[0054] Through the above implementation methods, it is possible to continuously track and dynamically identify risk items that have not been addressed in the historical maintenance process, avoiding the problem that historical suggested items are easily overlooked in traditional maintenance systems, thereby improving the ability to identify potential vehicle risks and the completeness of the vehicle inspection checklist generation results.

[0055] Preferably, determining the list of associated inspection items for a vehicle further includes: extracting the list of executed items and the list of fault codes corresponding to the vehicle from the historical maintenance database based on the vehicle identification number; and performing association reasoning processing on the list of executed items and the list of fault codes respectively according to a pre-built association rule base to obtain the list of associated inspection items for the vehicle.

[0056] In this embodiment, firstly, based on the vehicle identification number (VIN), historical maintenance records corresponding to the vehicle are extracted from the historical maintenance database, and then a list of executed items and a list of fault codes are extracted from these historical maintenance records. The list of executed items may include data such as historical parts replacement items, historical maintenance items, and historical repair items; the list of fault codes may include data such as engine fault codes, brake system fault codes, and electronic control system fault codes. After obtaining the list of executed items and the list of fault codes, association reasoning processing is performed on the list of executed items and the list of fault codes respectively according to a pre-built association rule base. Specifically, based on the historical maintenance items in the list of executed items, inspection items that are associated with the corresponding historical maintenance items are searched in the association rule base. For example, when there is a shock absorber replacement item in the historical maintenance record, a four-wheel alignment inspection item and a shock absorber abnormal noise re-inspection item are automatically generated based on the association rule base. Based on the fault code information in the list of fault codes, risk inspection items that are associated with the corresponding fault codes are searched in the association rule base. For example, when there is an engine misfire fault code in the historical maintenance record, spark plug inspection items, ignition coil inspection items, and fuel injection system inspection items can be automatically generated. Then, the various associated inspection items obtained from the association reasoning are summarized to determine the list of associated inspection items for the vehicle.

[0057] In other embodiments, dynamic confidence adjustment processing can be performed on the association inference results based on maintenance time information, fault recurrence frequency, and vehicle mileage change data in the historical maintenance database. Specifically, the number of times the corresponding fault code or historical maintenance item recurs within a preset time range is counted, and the association confidence of the corresponding associated inspection item is dynamically increased based on the number of recurrences. At the same time, the difference between vehicle mileage data and historical maintenance mileage data can be combined to determine whether the corresponding associated inspection item meets the preset review conditions, thereby filtering out associated inspection items with a higher degree of matching with the current operating status of the vehicle.

[0058] Through the above implementation methods, potential associated risks can be automatically identified based on the vehicle's historical maintenance behavior and historical fault trajectories. This avoids the problem of missing associated risks due to relying solely on human experience in the traditional maintenance process, thereby improving the completeness of the vehicle inspection checklist and the vehicle's ability to identify potential faults.

[0059] Optionally, a vehicle inspection list is generated based on the list of items to be done but not yet done, the list of historical items, and the list of related inspection items. This includes: merging the list of items to be done but not yet done, the list of historical items, and the list of related inspection items to obtain a merged inspection item list; deduplicating the merged inspection item list to obtain a target inspection item list; determining the priority of each target inspection item in the target inspection item list; and generating the vehicle inspection list based on the priority of each target inspection item in the target inspection item list.

[0060] In this embodiment, a merging process is performed on the list of projects that should have been but were not, the list of legacy projects, and the list of related inspection projects to obtain a merged inspection project list. The merging process includes, but is not limited to, uniformly converting the inspection projects in different project lists to a unified format and establishing a mapping relationship between corresponding project names, project codes, project categories, and risk sources. For example, the same inspection project may exist simultaneously in both the list of projects that should have been but were not, and the list of legacy projects. Corresponding inspection projects are uniformly associated, and multi-source risk information for each inspection project is retained, thus forming a merged inspection project list containing all projects to be inspected. After the merging process is completed, deduplication is performed on the merged inspection project list to obtain the target inspection project list. Specifically, based on project codes, project names, component identification information, and association rules, etc., inspection projects with duplicate relationships are matched and identified; when multiple inspection projects correspond to the same component or the same inspection target, the multiple inspection projects are merged into the same target inspection project, retaining the status of projects with higher risk levels and their corresponding risk source information. For example, when brake fluid replacement is both a project that should have been done but wasn't and a legacy project, the higher risk level should be retained as the final target inspection project status.

[0061] After obtaining the list of target inspection items, each item can be comprehensively evaluated from multiple dimensions, including safety risk level, urgency level, and repair value. Safety risk level characterizes the impact of the target inspection item on vehicle driving safety; urgency level characterizes the extent to which the corresponding problem is overdue or its deterioration trend; and repair value characterizes the contribution of the target inspection item to vehicle performance recovery, customer needs fulfillment, and subsequent repair value. Priorities are calculated based on the evaluation results of each target inspection item, and these items are sorted according to priority to obtain a priority sequence. After determining the priority of each target inspection item, they can be arranged in descending order of priority, with higher-priority items placed at the beginning of the vehicle inspection list and lower-priority items at the end. Furthermore, the target inspection items can be categorized into key inspection items, routine inspection items, and recommended inspection items based on priority, with corresponding inspection requirements, risk warnings, and repair suggestions configured for each. For example, high-priority inspection items involving the braking system, steering system, or airbag system can be marked as key inspection items; inspection items nearing their maintenance cycle can be marked as recommended inspection items. This ultimately generates a structured vehicle inspection checklist for technicians to use for vehicle inspection and repair decisions.

[0062] In another implementation, conflict resolution can be performed based on the relationships between target detection items. Specifically, target detection items with conflicting or duplicate detection processes are prioritized and merged according to the item category, risk level, and detection dependencies. For example, when multiple target detection items correspond to the same detection process, a unified detection task is automatically generated, and the final detection priority is determined based on the highest risk level corresponding to each target detection item, thereby reducing the number of duplicate detections.

[0063] Through the above embodiments, inspection items from different sources can be unified, integrated, and intelligently deduplicated, avoiding problems such as duplicate inspections, item conflicts, and risk omissions in the traditional vehicle inspection process, thereby improving the completeness, consistency, and inspection efficiency of the generated vehicle inspection checklist.

[0064] Optionally, the priority of each target detection item in the target detection item list is determined, including: determining the safety score, timeliness score, and value score of each target detection item; performing weighted summation on the safety score, timeliness score, and value score based on preset weighting coefficients to obtain the comprehensive score of each target detection item; and determining the priority of each target detection item based on the comprehensive score of each target detection item.

[0065] In this embodiment, the safety score, timeliness score, and value score corresponding to each target inspection item are first determined. The safety score characterizes the impact of the corresponding target inspection item on vehicle driving safety and can be determined based on the component category, fault risk level, and importance of the corresponding safety system. For example, target inspection items related to the braking system, steering system, and airbag system correspond to higher safety scores. The timeliness score characterizes the urgency of the corresponding target inspection item and can be determined based on its overdue status, overdue mileage, and overdue time; when a target inspection item is severely overdue or has been unprocessed for a long time, the corresponding timeliness score is increased. The value score characterizes the repair value and risk conversion value of the corresponding target inspection item and can be determined based on historical legacy status, correlation reasoning results, and historical customer acceptance records. After determining the safety score, timeliness score, and value score, a weighted summation is performed on each score using preset weighting coefficients to obtain the comprehensive score corresponding to the target inspection item. The comprehensive score is calculated using the formula P = w1 × S_safety + w2 × T_urgency + w3 × V_opportunity, where P represents the comprehensive score, S_safety represents the safety score, T_urgency represents the timeliness score, V_opportunity represents the value score, and w1, w2, and w3 represent the weighting coefficients for the corresponding score items. Preferably, w1 is greater than w2, and w2 is greater than w3 to highlight the importance of vehicle safety factors in priority assessment. For example, w1 can be set to 0.5, w2 to 0.3, and w3 to 0.2. Items are sorted according to their comprehensive scores, and their priorities are determined based on the comprehensive score. A higher comprehensive score indicates that the target inspection item requires priority inspection or processing. By introducing a weighted scoring mechanism, vehicle safety risks, repair urgency, and business value factors can be considered simultaneously, enabling intelligent sorting of vehicle inspection items and improving the accuracy and rationality of the generated vehicle inspection list.

[0066] Furthermore, the system can dynamically adjust the safety, timeliness, and value scores of corresponding target inspection items by combining the vehicle's lifecycle status, fault recurrence frequency, and customer's historical repair behavior. Specifically, it can dynamically improve the timeliness score of corresponding target inspection items based on fault recurrence records in the historical repair database, and dynamically adjust the value score of corresponding target inspection items based on the customer's historical refusal to repair. At the same time, it can also dynamically adjust the safety score of corresponding target inspection items based on the vehicle's current usage intensity and the aging status of key components, thereby improving the matching degree between the priority calculation results and the actual risk status of the vehicle.

[0067] Through the above implementation methods, a unified risk quantification analysis can be performed on target inspection items from different sources, and the corresponding priorities can be dynamically determined based on the actual operating status of the vehicle. This avoids the problems of inaccurate priorities and omission of high-risk items that exist in traditional manual experience judgment, thereby improving the accuracy of vehicle inspection checklist generation and maintenance decision-making efficiency.

[0068] This invention, in a preferred embodiment, relates to a method for generating an intelligent vehicle inspection checklist based on vehicle maintenance manuals and historical repair records. It aims to address the problems of reliance on manual experience for maintenance items, low utilization of historical repair data, and easy omission of inspection items in existing vehicle repair reception scenarios. By constructing an intelligent analysis system based on multi-source heterogeneous data fusion, it achieves automatic identification, dynamic reasoning, and priority ranking of vehicle inspection items, thereby improving vehicle reception efficiency, repair accuracy, and customer service quality. This embodiment includes a data layer, an agent processing layer, and an output layer. The data layer is used for unified storage and management of basic vehicle data, standard maintenance rule data, and historical repair data; the agent processing layer is used for performing temporal reasoning, correlation reasoning, and risk analysis; and the output layer is used to generate a structured intelligent vehicle inspection checklist and display it to repair technicians and customers.

[0069] In this embodiment, a vehicle maintenance manual library and a historical repair record library are pre-built. The vehicle maintenance manual library is used to pre-set standard maintenance item data for different vehicle models, which can include information such as maintenance items, standard cycles, and execution conditions. For example, maintenance items can include spark plug replacement, brake fluid replacement, and oil and oil filter replacement; standard cycles can include cycle rules such as replacing spark plugs every 40,000 kilometers and changing engine oil every 5,000 kilometers; execution conditions can include time conditions and mileage conditions, and adopt a method of determining whichever comes first. The historical repair database is used to structurally store the historical repair records of the target vehicle. The historical repair database can include data such as executed items, suggested but not executed items, fault code snapshots, parts replacement time, and parts replacement mileage. For example, it can record the engine oil change item that has been executed during a certain repair, the brake fluid change item that the customer refused to perform, and the engine fault code information read during the repair process, so as to form a complete historical repair trajectory of the vehicle.

[0070] Figure 2 This is a schematic diagram illustrating the main flow of a method for generating a vehicle inspection checklist according to a preferred embodiment of the present invention. Figure 2As shown, the data acquisition and preprocessing process is executed first. Specifically, the Vehicle Identification Number (VIN) and mileage data of the target vehicle are acquired. The VIN can be obtained through a barcode scanner, license plate recognition, or manual input. The mileage data is preferably automatically read from the vehicle's electronic control unit via the OBD-II interface. After acquiring the VIN and current mileage data, a VIN validity check and a mileage logic check are performed. The VIN validity check determines whether the VIN conforms to the 17-digit encoding rules defined in the ISO 3779 standard; the mileage logic check determines whether there are any mileage inversions or abnormal jumps in the mileage data. When the check fails, an error message is generated and fed back to the repair technician so that the technician can receive a re-entered VIN or current mileage data, thereby ensuring the accuracy of subsequent data analysis.

[0071] After data collection and preprocessing, a benchmark alignment process with the vehicle maintenance manual library is performed. Specifically, based on the vehicle identification number prefix, the maintenance item set corresponding to the target vehicle is extracted from the pre-built vehicle maintenance manual library, and each maintenance item in the set is traversed. Further, the most recent execution record of the corresponding maintenance item is queried from the historical repair database, and the mileage overdue rate is calculated based on vehicle mileage data, historical mileage data, and the standard cycle of the corresponding maintenance item. .in, This indicates the current vehicle mileage data. This indicates the historical mileage data for the most recent maintenance service. This indicates the preset standard cycle for the corresponding maintenance item. Then, based on the mileage overdue rate, the status of the corresponding maintenance item is determined, and it is marked as severely overdue, expired, about to expire, or normal, generating a list of required but unperformed maintenance items. .

[0072] After generating the list of items that should have been done but weren't, a further historical legacy retrieval process is performed. Specifically, all items marked "recommended for next maintenance" or "customer rejected" are extracted from the historical maintenance database and marked as unrepaired items. A time-depletion coefficient is calculated based on the time interval between the current date and the historical recommended date. ,in This represents the time-related decay coefficient, which decreases over time but will not fall below a minimum value. It is used to reduce the impact of old data or behaviors. This indicates the number of historical days since the current time for the corresponding project; 0.5 is a constant representing the minimum or lower limit of the time-related decay coefficient, regardless of... How large is the value of ? The final result will not be lower than 0.5; 180 is a constant, representing a half-life or time base (in days), which determines the decay rate. When it equals 180, The value is exactly 0.5. After 180 days, the value will be less than 0.5, but will be truncated by the max function. Further checks are made to determine if any of the unrepaired items have been unprocessed for more than a year or more than 20,000 kilometers. When the corresponding conditions are met, the corresponding item is marked as "overdue and unprocessed" to generate a list of historical legacy items. .

[0073] After generating the list of historical legacy items, the system further performs association reasoning processing. Specifically, it extracts the list of executed items and the list of fault codes from historical maintenance data records, and performs first-level and second-level association reasoning based on a pre-built association rule base. First-level association reasoning generates associated inspection items based on historical executed items; for example, if a shock absorber replacement item exists in the historical maintenance record, it automatically generates a four-wheel alignment inspection item and a shock absorber noise re-inspection item. Second-level association reasoning generates associated inspection items based on historical fault codes; for example, if an engine misfire fault code exists in the historical record, it automatically generates an ignition system inspection item and a fuel injection system inspection item. Additionally, the association confidence level can be dynamically adjusted based on the recurrence frequency of the corresponding fault or maintenance item, thereby improving the matching degree between the association reasoning results and the actual risk status of the target vehicle, in order to generate the associated inspection item list. .

[0074] Complete the list of items that should have been done but were not. List of historical legacy projects and a list of related inspection items After generation, a merge, deduplication, and conflict resolution process is performed. Specifically, the process will... , as well as The three project lists are merged, and duplicate testing items are deduplicated. When the same testing item originates from multiple project lists, the status and corresponding risk information of the highest priority item are retained. Simultaneously, testing items with conflicting cycles or statuses can be handled based on preset conflict resolution rules. For example, when different sources correspond to different maintenance cycles, the stricter cycle rule is preferred, thereby improving the security of the final testing results.

[0075] After merging, deduplication, and conflict resolution, priority sorting and hierarchical output processing are performed. Specifically, the safety score, timeliness score, and value score for each inspection item are calculated. The safety score indicates the impact of the corresponding inspection item on vehicle safety; the timeliness score indicates the urgency of the overdue inspection item; and the value score indicates the repair conversion value and potential risk value of the corresponding inspection item. A comprehensive priority score P is calculated based on the safety score, timeliness score, and value score, and sorting is performed in descending order of the comprehensive priority score P. Based on the sorting results, the inspection items are divided into mandatory items, key review items, and value-added pre-reminder items. Mandatory items mainly include high-safety-risk items that have already expired; key review items mainly include historically risky items; and value-added pre-reminder items mainly include items that will expire within the next one to two maintenance cycles.

[0076] After generating the intelligent vehicle inspection checklist, the system further performs interactive execution and closed-loop feedback processing. Specifically, repair technicians view the intelligent vehicle inspection checklist on the vehicle reception interface and perform corresponding inspection items according to customer needs. The actual execution results and customer feedback are recorded, and the corresponding execution results are written back to the historical repair database for time-series alignment processing when the target vehicle enters the workshop again. Simultaneously, the system can periodically analyze repair item conversion rates, customer acceptance rates, and fault recurrence rates, and dynamically optimize the weights of safety scoring, timeliness scoring, and value scoring based on the statistical results, thereby continuously improving the accuracy and adaptability of the intelligent vehicle inspection checklist generation results.

[0077] This embodiment constructs an agent-based intelligent system with temporal reasoning and correlation mining capabilities. It can deeply align and fuse structured maintenance manual data with unstructured historical repair data, and automatically generate a dynamic priority intelligent vehicle inspection checklist. Compared to traditional methods relying on human experience and manual querying of maintenance manuals, this embodiment represents a technological leap from a passive manual query mode to a proactive intelligent recommendation mode. This improves vehicle reception efficiency, the accuracy of maintenance item identification, and the ability to identify potential risks, while reducing the risk of missed repairs and lost customer value.

[0078] According to a second aspect of the present invention, an apparatus for generating a vehicle inspection checklist is provided.

[0079] Figure 3 This is a schematic diagram of the main modules of a vehicle inspection checklist generation device according to an embodiment of the present invention. Figure 3 As shown, the vehicle inspection checklist generation device 300 includes: The first determining module 301 is used to determine the vehicle's maintenance overdue rate based on the vehicle identification number and vehicle mileage data using a pre-built vehicle model maintenance manual library and historical repair database, and to determine the vehicle's list of items that should have been done but were not based on the maintenance overdue rate. The second determining module 302 is used to determine the unrepaired item set and the repaired item set of a vehicle based on the vehicle identification code and the historical maintenance database, determine the historical legacy item list based on the unrepaired item set, and perform association reasoning on the repaired item set according to the pre-built association rule base to obtain the associated inspection item list. The list generation module 303 is used to generate a vehicle inspection list based on the list of items that should have been done but were not, the list of historical legacy items, and the list of related inspection items.

[0080] Optionally, the vehicle inspection checklist generation device 300 further includes an inspection processing module, which is used for: Perform validity verification on the vehicle identification number and confirm that the validity verification was successful; Perform mileage logic verification on the vehicle mileage data and confirm that the mileage logic verification is successful. In response to a failure in validity verification or mileage logic verification, the vehicle mileage data generates an error message and sends it back to the user so that the user can re-enter the vehicle identification number or vehicle mileage data based on the error message.

[0081] Optionally, the first determining module 301 is further configured to: Based on the vehicle identification number, extract the corresponding maintenance item set for the vehicle from the vehicle maintenance manual database; Iterate through each maintenance item in the maintenance item set and query the target execution record corresponding to each maintenance item from the historical maintenance database. Based on the target execution record, determine the historical execution mileage data and historical execution time data corresponding to each maintenance item. Based on vehicle mileage data, historical mileage data corresponding to each maintenance item, and preset mileage cycles corresponding to each maintenance item, determine the mileage overdue rate for each maintenance item. Based on the acquired target time data, the historical execution time data corresponding to each maintenance item, and the preset time cycle corresponding to each maintenance item, determine the time overdue ratio corresponding to each maintenance item. The mileage overdue rate and time overdue rate of each maintenance item are compared numerically, and the mileage overdue rate of the vehicle is determined based on the comparison results.

[0082] Optionally, the first determining module 301 is further configured to: Determine whether the maintenance overdue rate for each maintenance item exceeds the preset maintenance overdue threshold; In response to the maintenance overdue rate of the maintenance item exceeding the preset maintenance overdue threshold, the maintenance item is broken down into basic inspection sub-items and in-depth investigation sub-items; Generate a list of items that should have been done but were not, based on the basic inspection sub-items and the in-depth investigation sub-items.

[0083] Optionally, the second determining module 302 is further configured to: Determine the time-depreciation information for each unmaintained item in the unmaintained item set; Based on the time-depreciation information corresponding to each unrepaired item, a list of historical legacy items for the vehicle is determined.

[0084] Optionally, the manifest generation module 303 is also used for: The list of uncompleted items, the list of legacy items, and the list of related inspection items are merged to obtain a merged list of inspection items. The merged list of test items is deduplicated to obtain the target list of test items. Determine the priority of each target detection item in the target detection item list; Based on the priority of each target detection item in the target detection item list, a vehicle inspection checklist is generated for the vehicle.

[0085] Optionally, the manifest generation module 303 is also used for: Determine the safety score, timeliness score, and value score corresponding to each target detection item; Based on preset weighting coefficients, the safety score, timeliness score, and value score are weighted and summed to obtain the comprehensive score corresponding to each target detection item. The priority of each target detection item is determined based on the comprehensive score corresponding to each target detection item.

[0086] It should be noted that the specific implementation of the vehicle inspection checklist generation device of the present invention has been described in detail in the above-described vehicle inspection checklist generation method, so the content will not be repeated here.

[0087] According to a third aspect of the present invention, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method provided in the first aspect of the present invention.

[0088] According to a fourth aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method provided in the first aspect of the present invention.

[0089] According to a fifth aspect of the present invention, a computer program product is provided, including a computer program that, when executed by a processor, implements the method provided in the first aspect of the present invention.

[0090] Figure 4 An exemplary system architecture 400 is shown, to which the vehicle inspection list generation method or vehicle inspection list generation apparatus of embodiments of the present invention can be applied.

[0091] like Figure 4 As shown, system architecture 400 may include terminal devices 401, 402, and 403, a network 404, and a server 405. Network 404 serves as the medium for providing communication links between terminal devices 401, 402, and 403 and server 405. Network 404 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0092] Users can use terminal devices 401, 402, and 403 to interact with server 405 via network 404 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 401, 402, and 403, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0093] Terminal devices 401, 402, and 403 can be various electronic devices with displays that support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0094] Server 405 can be a server providing various services, such as a backend management server supporting shopping websites browsed by users using terminal devices 401, 402, and 403 (for example only). The backend management server can analyze and process data such as received vehicle inspection checklist generation requests, and feed back the processing results (e.g., vehicle inspection checklist - for example only) to the terminal device.

[0095] It should be noted that the vehicle inspection list generation method provided in this embodiment of the invention is generally run by server 405, and correspondingly, the vehicle inspection list generation device is generally set in server 405.

[0096] It should be understood that Figure 4 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0097] The following is for reference. Figure 5 It shows a schematic diagram of the structure of a computer system 500 suitable for implementing a terminal device of the present invention. Figure 5 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0098] like Figure 5 As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 502 or programs loaded from storage section 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the system 500. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0099] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. Drive 510 is also connected to I / O interface 505 as needed. Removable media 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 510 as needed so that computer programs read from them can be installed into storage section 508 as needed.

[0100] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is run by the central processing unit (CPU) 501, it performs the functions defined above in the system of this invention.

[0101] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium, a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit programs for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0102] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more operable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually operate substantially in parallel, and they may sometimes operate in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0103] The modules described in the embodiments of the present invention can be implemented in software or hardware. The described modules can also be housed in a processor; for example, a processor may be described as including a first determining module, a second determining module, and a list generation module. The names of these modules do not necessarily limit the module itself; for example, the list generation module may also be described as a module that "generates a vehicle inspection list based on a list of items to be done but not yet done, a list of historical legacy items, and a list of associated inspection items."

[0104] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs that, when executed by the device, cause the device to include: determining the vehicle's maintenance overdue rate based on the vehicle identification number (VIN) and vehicle mileage data using a pre-built vehicle model maintenance manual library and a historical repair database; determining a list of required but un-done maintenance items for the vehicle based on the maintenance overdue rate; determining a set of un-repaired items and a set of repaired items for the vehicle based on the VIN and the historical repair database; determining a list of historical legacy items based on the un-repaired items; performing association reasoning on the repaired items set according to a pre-built association rule library to obtain a list of associated inspection items; and generating a vehicle inspection checklist based on the list of required but un-done items, the list of historical legacy items, and the list of associated inspection items.

[0105] The computer program product provided in this embodiment of the invention includes a computer program that, when executed by a processor, implements the method for generating a vehicle inspection list in this embodiment of the invention.

[0106] The technical solution of this invention has the following advantages or beneficial effects: By utilizing a pre-built vehicle model maintenance manual library and historical repair database based on the vehicle identification number (VIN) and vehicle mileage data, the vehicle's maintenance overdue rate is determined; based on the maintenance overdue rate, a list of required but un-done items for the vehicle is determined; based on the VIN and historical repair database, the vehicle's un-repaired item set and repaired item set are determined; based on the un-repaired item set, a list of historical legacy items is determined; based on a pre-built association rule library, association reasoning is performed on the repaired item set to obtain an associated inspection item list; and based on the list of required but un-done items, the historical legacy item list, and the associated inspection item list, a vehicle inspection list is generated. This embodiment can match the vehicle model maintenance manual library and historical repair database based on the vehicle's VIN and vehicle mileage data, deeply integrating structured vehicle model maintenance manual data with unstructured historical repair data to automatically generate a vehicle inspection list, improving the efficiency and accuracy of list generation.

[0107] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

[0108] It should be noted that the acquisition, storage, and application of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

Claims

1. A method for generating a vehicle inspection checklist, characterized in that, include: Based on the vehicle identification number and vehicle mileage data, using a pre-built model maintenance manual library and historical repair database, the maintenance overdue rate of the vehicle is determined, and a list of items that should have been done but were not is determined based on the maintenance overdue rate. The vehicle identification number and the historical maintenance database are used to determine the unrepaired items set and the repaired items set of the vehicle. A list of historical legacy items is determined based on the unrepaired items set. The repaired items set is then subjected to association reasoning based on a pre-built association rule base to obtain a list of associated inspection items. A vehicle inspection checklist is generated based on the list of items that should have been done but were not, the list of historical legacy items, and the list of related inspection items.

2. The method according to claim 1, characterized in that, Before determining the vehicle's maintenance overdue rate based on the vehicle identification number (VIN) and mileage data using a pre-built vehicle maintenance manual library and historical repair database, the process also includes: Perform a validity verification on the vehicle identification code and confirm that the validity verification was successful; Perform mileage logic verification on the vehicle mileage data and confirm that the mileage logic verification is successful. In response to a failure in validity verification or mileage logic verification, the vehicle mileage data generates an error message and sends the error message back to the user so that the user can re-enter the vehicle identification number or vehicle mileage data based on the error message.

3. The method according to claim 1, characterized in that, Based on the vehicle identification number (VIN) and mileage data, and utilizing a pre-built vehicle maintenance manual library and historical repair database, the vehicle's maintenance overdue rate is determined, including: Based on the vehicle identification number, extract the maintenance item set corresponding to the vehicle from the vehicle maintenance manual database; Iterate through each maintenance item in the maintenance item set and query the target execution record corresponding to each maintenance item from the historical maintenance database. Determine the historical execution mileage data and historical execution time data corresponding to each maintenance item based on the target execution record. Based on the vehicle mileage data, the historical mileage data corresponding to each maintenance item, and the preset mileage cycle corresponding to each maintenance item, the mileage overdue rate of each maintenance item is determined. Based on the acquired target time data, the historical execution time data corresponding to each maintenance item, and the preset time cycle corresponding to each maintenance item, the time overdue ratio corresponding to each maintenance item is determined. The mileage overdue rate and time overdue rate of each maintenance item are compared numerically, and the maintenance overdue rate of the vehicle is determined based on the numerical comparison results.

4. The method according to claim 3, characterized in that, Based on the aforementioned maintenance overdue rate, a list of required but uncompleted maintenance items for the vehicle is determined, including: Determine whether the maintenance overdue rate for each maintenance item exceeds the preset maintenance overdue threshold; In response to the maintenance overdue rate corresponding to the maintenance item exceeding the preset maintenance overdue threshold, the maintenance item is broken down into basic inspection sub-items and in-depth investigation sub-items; The list of items that should have been done but were not is generated based on the basic inspection sub-items and the in-depth investigation sub-items.

5. The method according to claim 1, characterized in that, Based on the set of unrepaired items, a list of legacy items is determined, including: Determine the time-depreciation information corresponding to each unmaintained item in the set of unmaintained items; Based on the time-depreciation information corresponding to each unrepaired item, a list of historical legacy items for the vehicle is determined.

6. The method according to claim 1, characterized in that, A vehicle inspection checklist is generated based on the list of items that should have been done but were not, the list of historical legacy items, and the list of related inspection items, including: The list of items that should have been done but were not, the list of historical items, and the list of related inspection items are merged to obtain a merged list of inspection items. The merged list of test items is deduplicated to obtain the target list of test items; Determine the priority of each target detection item in the target detection item list; Based on the priority of each target detection item in the target detection item list, a vehicle inspection list is generated for the vehicle.

7. The method according to claim 6, characterized in that, Determining the priority of each target detection item in the target detection item list includes: Determine the safety score, timeliness score, and value score corresponding to each target detection item; Based on preset weighting coefficients, the safety score, timeliness score and value score are weighted and summed to obtain the comprehensive score corresponding to each target detection item. Based on the comprehensive score corresponding to each target detection item, the priority of each target detection item is determined.

8. A device for generating a vehicle inspection checklist, characterized in that, include: The first determining module is used to determine the maintenance overdue rate of the vehicle based on the vehicle identification number and vehicle mileage data using a pre-built vehicle model maintenance manual library and historical repair database, and to determine the list of items that should have been done but were not done for the vehicle based on the maintenance overdue rate. The second determining module is used to determine the unrepaired item set and the repaired item set of the vehicle based on the vehicle identification code and the historical maintenance database, determine the historical legacy item list based on the unrepaired item set, and perform association reasoning on the repaired item set according to the pre-built association rule base to obtain the associated inspection item list. The list generation module is used to generate a vehicle inspection list for the vehicle based on the list of items that should have been done but were not, the list of historical legacy items, and the list of related inspection items.

9. An electronic device, characterized in that, include: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-7.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-7.

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