Method, system and terminal for vehicle preparation operations

Abstract

The application relates to a method, system and terminal for vehicle preparation operation, the method comprising: generating a vehicle preparation operation set; matching the generated vehicle preparation operation set with a vehicle; generating a vehicle preparation operation instance dedicated to the vehicle according to the generated vehicle preparation operation set; and executing the vehicle preparation operation instance for the vehicle. The method can flexibly determine the vehicle preparation operation according to actual conditions, accurately and quickly recommend the vehicle preparation operation, improve efficiency, reduce cost and realize good user experience.

Description

Technical Field

[0001] This invention relates to the field of vehicle maintenance, and more specifically, to methods, systems, and terminals for vehicle preparation operations. Background Technology

[0002] In the automotive aftermarket, that is, in the series of service transactions that occur after a car is sold and around the usage phase, services such as technical support, repair, maintenance, and servicing occupy an important position; these can be referred to as vehicle preparation operations. The existing acquisition models for goods (especially virtual goods) related to vehicle preparation operations mainly include the following: 1. Fixed Package Model: Multiple vehicle maintenance operations (such as oil change, oil filter change, interior refurbishment, mechanical performance restoration, electronic function testing, etc.) are bundled into a fixed package for sale. After purchase, the user receives all the confirmed vehicle maintenance operations included in the package.

[0003] 2. Single electronic voucher model: For example, common electronic component maintenance vouchers, car wash vouchers, paint inspection vouchers, etc. Each purchase corresponds to a specific vehicle preparation operation, and users need to make an appointment and redeem the voucher upon use.

[0004] 3. General prepaid card model: After purchasing a prepaid card of a certain value, users can make purchases at specific merchants or platforms. In essence, it is a fund account, rather than an aggregation for vehicle preparation operations.

[0005] The aforementioned existing technologies have the following main drawbacks: 1. Limited flexibility, potentially leading to wasted operational resources: Fixed package models rigidly bind vehicle preparation operations to the vehicle (a process that can be called matching), preventing users from selecting and adjusting based on the vehicle's actual condition (such as mileage and age) and their own needs. For example, some vehicles may not require the deep cleaning service included in the package (also known as the vehicle preparation operation set), and this service cannot be refunded separately, resulting in wasted vehicle preparation operations and a poor user experience.

[0006] 2. High user decision-making costs and fragmented purchase frequency: The single electronic voucher model requires users to make multiple purchase decisions and payment operations for different vehicle maintenance services. For example, users may need to purchase services such as basic maintenance, air conditioning cleaning, and tire inspection separately. The operation process is cumbersome and cannot meet the comprehensive maintenance needs of the vehicle within a cycle through a single purchase, which is not conducive to increasing the platform's total transaction volume (GMV).

[0007] 3. Lack of intelligent linkage with vehicle status: None of the above modes are deeply integrated with vehicle data (e.g., VIN code, mileage, maintenance history, etc.). The system cannot proactively and accurately recommend the most suitable vehicle preparation operation to the user based on the actual condition of the vehicle, resulting in a low match between service and demand.

[0008] 4. Low efficiency in scheduling operational resources: The existing appointment system is usually independent of the management of vehicle preparation operations. It is difficult to make forward-looking optimization of the allocation of operational resources (work bays, technicians, parts) of offline service stores based on the overall sales of services for vehicle preparation operations and user appointment intentions, which can easily lead to idle resources or congestion.

[0009] The above-mentioned shortcomings arise because existing technologies treat "product sales" and "service triggering" as two separate processes, and the content of vehicle preparation operations is static and predetermined, lacking an intelligent management method that can activate, recommend, and schedule vehicle preparation operations based on dynamic conditions (such as user selection, vehicle status, seasonal changes, etc.). Summary of the Invention

[0010] Therefore, the present invention aims to overcome the shortcomings of the prior art and solve the following technical problems: 1. How to provide a flexible and accurate vehicle preparation operation acquisition mode, so that users can obtain the right to choose from multiple vehicle preparation operations with a single purchase, and can dynamically make reservations and redeem them according to actual needs, thereby reducing user decision-making costs and reducing resource waste.

[0011] 2. How to intelligently link vehicle preparation operation recommendations and redemptions with the real-time status of vehicles to improve the accuracy of service matching and user experience.

[0012] 3. How to optimize the utilization rate of offline operational resources and achieve an efficient balance between user demand and service supply through an effective appointment and verification mechanism.

[0013] In view of this, embodiments of the present invention provide a method for vehicle preparation operations. This method can flexibly determine vehicle preparation operations according to actual conditions and can accurately and quickly recommend vehicle preparation operations, thereby improving efficiency, reducing costs, and achieving a good user experience.

[0014] To achieve the above objectives, according to one aspect of the present invention, a method for vehicle preparation operation is provided, the method comprising: Generate a set of vehicle preparation operations; Match the generated set of vehicle preparation operations with the vehicle. Based on the generated set of vehicle preparation operations and the vehicle information, generate a vehicle preparation operation instance specifically for the vehicle; and An example of performing the vehicle preparation operation on the vehicle.

[0015] In one embodiment, generating a vehicle preparation operation instance specific to the vehicle based on the generated set of vehicle preparation operations and information about the vehicle includes: Multiple weights are generated based on the vehicle's information; The priority of multiple vehicle preparation operations in the generated vehicle preparation operation set is determined based on the generated weights. Based on the priority of the multiple vehicle preparation operations, a recommended vehicle preparation operation is generated using preset service rules; and Generate a vehicle preparation operation instance specifically for the vehicle based on the recommended vehicle preparation operations.

[0016] Furthermore, in another embodiment, generating a vehicle preparation operation instance specifically for the vehicle based on the generated set of vehicle preparation operations and the vehicle's information includes: Multiple weights are generated based on the vehicle's information; Recommended vehicle maintenance operations are extracted from the generated set of vehicle maintenance operations using multiple weights; and Generate a vehicle preparation operation instance specifically for the vehicle based on the recommended vehicle preparation operations.

[0017] Specifically, in one embodiment, the plurality of weights includes: Vehicle safety dimension weighting; Weighting of vehicle performance dimensions; The weighting of vehicle comfort dimensions; and Weighting of vehicle cost dimension.

[0018] In one embodiment, generating a set of vehicle preparation operations includes: Create a template for vehicle preparation operations; Select the vehicle preparation operation from the vehicle preparation operation database; Add the selected vehicle preparation operations to the vehicle preparation operation set template to form a vehicle preparation operation set; and Set the usage rules for the resulting set of vehicle preparation operations.

[0019] In one embodiment, the usage rules of the vehicle preparation operation set include: The price of the vehicle preparation operation set; The validity period of the vehicle preparation operation set; and The usage restrictions of the vehicle preparation operation set.

[0020] In one embodiment, matching the generated set of vehicle preparation operations with the vehicle includes: Identifiers for the vehicle; Verify the validity of the identifier; Obtain information about the vehicle; and Based on the identifier and the vehicle information, the generated set of vehicle preparation operations is activated.

[0021] In one embodiment, if the identifier is invalid, the generated set of vehicle preparation operations is re-matched with the vehicle.

[0022] In one embodiment, performing the vehicle preparation operation on the vehicle includes: The vehicle preparation operation to be performed is determined from the vehicle preparation operation examples described above. Determine the operational resources corresponding to the vehicle preparation operation to be performed; and Match the operating resources with the vehicle.

[0023] In one embodiment, the method according to an embodiment of the present invention further includes: Select a vehicle preparation operation from different vehicle preparation operation instances to form a new vehicle preparation operation instance.

[0024] In addition, another aspect of the present invention provides a system for vehicle preparation operations, comprising: An operating device configured to provide an operating interface; A vehicle preparation operation management device, the vehicle preparation operation management device being configured to perform the method according to the above embodiments; and A data management device configured to store data output by the vehicle preparation operation set management device.

[0025] Furthermore, another aspect of the present invention provides a terminal for vehicle preparation operations, characterized in that it comprises: One or more processors; A storage device for storing one or more programs, and When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to the above embodiments.

[0026] In addition, another aspect of the present invention provides a computer-readable medium having a computer program stored thereon, characterized in that the program, when executed by a processor, implements the method according to the above embodiments.

[0027] Furthermore, another aspect of the present invention provides a computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the method according to the above embodiments.

[0028] In summary, the method, system, and terminal for vehicle preparation operations according to the present invention can generate a set of vehicle preparation operations, flexibly determine each vehicle preparation operation in the set according to actual conditions, and accurately and quickly recommend vehicle preparation operations, thereby improving efficiency, reducing costs, and achieving a good user experience.

[0029] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0030] The accompanying drawings are provided to better understand the invention and do not constitute an undue limitation thereof. In these drawings: Figure 1 This is a schematic diagram of the steps of a method for vehicle preparation operations according to the present invention; Figure 2 This is a schematic diagram of a first embodiment of a method for vehicle preparation operations according to the present invention; Figure 3 This is a schematic diagram of a second embodiment of the method for vehicle preparation operation according to the present invention; Figure 4 This is a schematic diagram of a third embodiment of the method for vehicle preparation operation according to the present invention; Figure 5 This is another schematic diagram of a third embodiment of the method for vehicle preparation operation according to the present invention; Figure 6 This is a schematic diagram of a fourth embodiment of the method for vehicle preparation operation according to the present invention; Figure 7 This is a schematic diagram of a fifth embodiment of the method for vehicle preparation operation according to the present invention; Figure 8 This is a schematic diagram illustrating the operation process of a set of vehicle preparation operations used in the method for vehicle preparation operations according to the present invention; and Figure 9 This is a schematic diagram of the system for vehicle preparation operations according to the present invention. Detailed Implementation

[0031] 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.

[0032] The steps of the method for vehicle preparation operation according to the present invention are as follows: Figure 1 As shown.

[0033] First, different vehicle preparation operation sets are pre-set. In this invention, such vehicle preparation operation sets can be called card sets.

[0034] Furthermore, a specific vehicle maintenance operation set is selected from different vehicle maintenance operation sets, the generated vehicle maintenance operation set is matched with the vehicle, and based on the vehicle's operating status, the vehicle maintenance operation is selected from the generated vehicle maintenance operation set to generate a vehicle maintenance operation instance specifically for the vehicle.

[0035] Finally, a vehicle preparation operation instance is performed on the vehicle, that is, the vehicle preparation operation in the vehicle preparation operation instance is performed.

[0036] In practice, the specific process of the method according to the present invention can be divided into different stages, as detailed below.

[0037] In this invention, multiple different vehicle maintenance operation sets can be pre-set. However, these sets are not fixed. Depending on factors such as vehicle type, user needs, city location, and natural environment, multiple sets of vehicle maintenance operations are obviously required, and each set may include different vehicle maintenance operations. Furthermore, the operator can adjust the number of vehicle maintenance operation sets and the vehicle maintenance operations included in each set according to actual circumstances.

[0038] like Figure 2 As shown, firstly, vehicle maintenance operation set templates can be created; there can be one or more templates. Then, some vehicle maintenance operations are selected from the vehicle maintenance operation database, and different combinations of these operations are added to the vehicle maintenance operation set templates, thus forming different vehicle maintenance operation sets. Furthermore, the operator can set usage rules for these vehicle maintenance operation sets.

[0039] In this invention, different prices, validity periods, and usage restrictions can be set for each vehicle preparation operation set. For example, some stores performing vehicle preparation operations are unable to install vehicle lifts due to limitations, and therefore cannot inspect the vehicle chassis.

[0040] For example, in this invention, this process can be referred to as configuration and purchase: specifically, the operator provides different vehicle preparation operation sets in the background, among which the most commonly used vehicle preparation operation sets are, for example, "Annual Vehicle Maintenance and Preparation Operation Set," "Quarterly Vehicle Maintenance and Preparation Operation Set," "Monthly Vehicle Maintenance and Preparation Operation Set," etc., which can also be referred to as a vehicle preparation operation pool. For example, this vehicle preparation operation set may include five vehicle preparation operations such as basic maintenance, air conditioning cleaning, safety inspection, scratch inspection, and operating system inspection, but is not limited to these.

[0041] Furthermore, such as Figure 3 As shown, after generating multiple different vehicle maintenance operation sets, users can browse the list of vehicle maintenance operation sets and select and purchase the appropriate one. After successfully purchasing a vehicle maintenance operation set, users can match (or associate, bind) the vehicle maintenance operation set with their vehicle. For example, users can enter the vehicle's identifier (e.g., usually the VIN code), and the operator can verify the validity of the VIN code. If the VIN code is valid, it means that the user has successfully activated the generated vehicle maintenance operation set. If an error message is displayed indicating a VIN code error, the user needs to re-enter the VIN code.

[0042] In addition to the VIN code, vehicle identifiers can also include the vehicle's engine number, vehicle nameplate, license plate, owner's identity information, etc., but this invention is not limited to these.

[0043] Furthermore, after a user selects a set of vehicle maintenance operations, since the set includes multiple vehicle maintenance operations, the user does not necessarily need to select all of them each time. In this invention, an intelligent vehicle maintenance operation set management device (or, in this embodiment, an intelligent recommendation engine) can be used to recommend specific vehicle maintenance operations to the user and display them in, for example, a list format.

[0044] For example, after matching the vehicle maintenance operation set with the vehicle, the aforementioned intelligent recommendation engine detects that the matched vehicle has driven 20,000 kilometers. Based on general vehicle maintenance habits, it believes that the engine may need maintenance. Therefore, it can prioritize recommending the "oil and filter change" operation, highlighting it on the interface and displaying the message, "Based on your vehicle's mileage, this vehicle maintenance operation is recommended." Other vehicle maintenance operations can also be displayed simultaneously, but in a lower order.

[0045] Furthermore, in addition to obtaining vehicle mileage, it is also possible to query the vehicle's maintenance operation history, fault records, repair records, etc., and calculate the priority of each maintenance operation in the vehicle maintenance operation set based on a rule model. This priority corresponds to the vehicle's current condition. Then, a recommended list of vehicle maintenance operations in the vehicle maintenance operation set can be generated using a pre-established machine learning model. Alternatively, a recommended list of vehicle maintenance operations can be generated based on preset rules.

[0046] Alternatively, users can manually match vehicle preparation operations from the set with their vehicles. During the matching process, users can input vehicle information, such as the vehicle model, approximate mileage range (e.g., "under 10,000 km", "10,000-30,000 km", "30,000-50,000 km"), and whether the vehicle has any obvious abnormalities. Users can also manually select any one or more vehicle preparation operations from the set based on their actual needs and vehicle preparation operation history. This reduces the complexity of the operation and thus improves efficiency.

[0047] Alternatively, in addition to obtaining the aforementioned vehicle information, user profile data (such as user driving habits, historical service preferences, etc.) can be introduced for collaborative filtering recommendations, thereby forming a multi-dimensional recommendation model, which can improve the accuracy of recommendations.

[0048] Specifically, during the vehicle preparation operation set and vehicle matching process, several pieces of information about the vehicle are obtained. Based on this information, weight calculations can be performed, such as safety dimension weight calculations, including brakes, tires, etc.; performance dimension weight calculations, including engine, transmission, etc.; comfort dimension weight calculations, including air conditioning, interior, etc.; and cost dimension weight calculations, including fuel efficiency, energy consumption per unit mileage (electric vehicles), maintenance costs, etc.

[0049] Based on these weights, the intelligent recommendation engine can determine the most needed vehicle maintenance operations. In other words, it can prioritize vehicle maintenance operations within a set and rank them accordingly. Then, using the rule model in the intelligent recommendation engine, a list of vehicle maintenance operations can be generated based on preset rules. There are several preset rules corresponding to the aforementioned dimensions. For example, in the safety dimension, preset rules can be used to assess the vehicle's actual condition, such as tire pressure, tire wear, suspension condition, brake pad condition, headlight brightness, and response time, among other things. Similarly, in the performance dimension, preset rules can be used to assess the vehicle's actual condition, such as engine or motor torque, intake and exhaust systems, turbocharger condition, cooling system condition, steering ratio, and power steering condition, among other things. For example, in the comfort dimension, preset rules can be used to judge based on the actual conditions of the vehicle, such as the softness and support of the vehicle seats, and the status of adjustment functions (such as lumbar support, leg rests, seat ventilation, seat heating, etc.). Common examples also include the air conditioning status and air circulation status, and so on. Similarly, in the economy dimension, preset rules can also be used to judge based on the actual conditions of the vehicle, such as the engine's thermal efficiency, the transmission efficiency, the operation of the kinetic energy recovery system, and energy consumption per unit mileage, and so on.

[0050] After using the above-mentioned preset rules to make judgments, it is possible to determine in what aspects the vehicle needs to be prepared, thereby determining the specific vehicle preparation operations from the set of vehicle preparation operations.

[0051] Alternatively, instead of using a rule-based model, a recommendation model can be used, which in this invention can be implemented as a machine learning model to generate a list of vehicle maintenance operations. In fact, based on the various vehicle information mentioned above, such as vehicle brand, model, engine displacement, battery capacity, vehicle age, mileage, maintenance operation history, repair records, and selected service center, combined with the various data used in calculating multiple weights, a machine learning model can be pre-generated to predict the necessary vehicle maintenance operations. This prediction can be understood as listing the possible vehicle maintenance operations in order, reflecting the priority or urgency of each user's needs. Furthermore, this machine learning model can be updated using new data generated each time a vehicle maintenance operation is performed. Further, this machine learning model can also combine the specific service center performing the vehicle maintenance operation, natural factors, and the owner's preferences to generate another list of vehicle maintenance operations, which can include the reasons and priorities for recommending vehicle maintenance operations. The above process... Figure 4 and Figure 5 It is shown schematically in the middle.

[0052] Furthermore, such as Figure 6 As shown, after a vehicle maintenance operation is determined (forming a vehicle maintenance operation instance), these operations need to be actually performed, which requires the store and staff to execute the operation. For example, a user determines the "oil and filter change" vehicle maintenance operation and selects a desired arrival time. The appointment scheduling engine in this invention (which can be a component of the intelligent vehicle maintenance operation collection management device of this invention) queries the store resource database, confirms that there are available resources for that time slot, locks these resources, and generates a unique appointment QR code to send to the user. This method effectively avoids the situation where no resources are available when the user arrives at the store, thus improving the user experience.

[0053] Furthermore, since vehicle maintenance operations are performed based on vehicle maintenance operation instances, and these instances are actually further refined from a set of vehicle maintenance operations, there may be other vehicle maintenance operations remaining within the instance after the initial operation. The user may use up the remaining operations this time or save them for later. Therefore, the state of the vehicle maintenance operation instance needs to be updated. Additionally, the history of vehicle maintenance operations can be recorded to further train the aforementioned machine learning model or update preset rules.

[0054] Alternatively, the allocation of operational resources corresponding to vehicle preparation operations can be achieved using methods such as "probabilistic allocation" or "buffer pooling." For example, instead of locking specific operational resources for each set of vehicle preparation operations in real time, the system reserves a certain quota of operational resources for each appointment. Users confirm their eligibility when making an appointment, and the system then performs precise allocation and notification of operational resources at a specific time before the service (e.g., the day before arrival). This is suitable for scenarios where operational resources are not so scarce and can reduce the complexity of real-time system interactions.

[0055] Furthermore, upon arrival at the store, staff can verify the user's identity by scanning the aforementioned QR code. The verification management engine will then confirm that the vehicle preparation operation is valid and unused, and proceed with the verification. The system will record this service and update the status of the vehicle preparation operation set (e.g., "1 / 5 vehicle preparation operations used"). The user can then perform the operation again to schedule other vehicle preparation operations from the set.

[0056] Furthermore, such as Figure 7As shown, after a user performs multiple vehicle maintenance operations—that is, after one or more instances of vehicle maintenance operations—the user's behavior can be analyzed, and the list of recommended vehicle maintenance operations for the next time can be optimized. For example, the machine learning model or preset rules can be updated based on the actual vehicle maintenance operations used and their execution.

[0057] Alternatively, after repeatedly using vehicle maintenance operations from various sets of operations, users can also select vehicle maintenance operations from different sets to create a new set. This new set may include operations that best meet the user's actual needs. This approach further enhances the user experience.

[0058] Based on the above, the operation process of the vehicle preparation operation set in this invention can be clearly understood. This operation process is as follows: Figure 8 As shown, the vehicle preparation operation set has multiple different states, meaning that the state of the vehicle preparation operation set can dynamically change as the vehicle preparation operation process proceeds.

[0059] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the various figures can be implemented as a computer program product. For example, the embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, and the computer program containing program code for performing the methods shown in the flowchart.

[0060] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or 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 a program 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.

[0061] Furthermore, the process described above can be executed by a system used for vehicle preparation operations. Figure 9 The architecture of the system is shown in the figure.

[0062] In this invention, the system can adopt a layered architecture, which mainly includes: 1. User interaction layer (which may correspond to the operating device of the system for vehicle preparation operations of the present invention): It is used to provide users with an interactive interface, for example, for purchasing, enabling (activating), scheduling, and viewing a set of vehicle preparation operations. The user terminal may be an APP on a mobile communication device or an application installed in the vehicle's operating system.

[0063] Alternatively, the terminal can also be implemented in the form of a physical machine, which may include a processor and a storage device storing programs that, when executed by the processor, cause the processor to implement the method according to the above embodiments. For example, in some cases, users can go directly to a store and perform self-service operations such as vehicle maintenance, inspection, and repair on the machines inside the store.

[0064] 2. An application service layer (which may correspond to the intelligent vehicle preparation operation collection management device of the system for vehicle preparation operation of the present invention), comprising: Vehicle preparation operation set management engine: responsible for creating vehicle preparation operation set templates, instantiating vehicle preparation operation sets (generating a unique card after user purchase), and managing status (e.g., not enabled, enabled, partially used, completed, etc.).

[0065] The intelligent recommendation engine (which may include the preset rules and preset recommendation model according to the present invention): When a user binds (matches) a vehicle, the engine will obtain data such as VIN code, mileage, and items of the last maintenance operation from the vehicle database, and calculate the most suitable vehicle maintenance operation for the user at present through the built-in rule model (also known as the rule engine) (for example, if the vehicle mileage is >10,000km, it recommends oil and filter replacement; or if it has been more than half a year since the last air conditioning cleaning, it recommends air conditioning cleaning, etc.) or machine learning model, and display it in a sorted list.

[0066] Appointment scheduling engine: After receiving the user's appointment request, it interacts with the store's resource database to query the available workstations, technicians and parts inventory within the specified time period, complete the resource locking, and prevent over-ordering.

[0067] 3. A data storage layer (which may correspond to the data management device of the system for vehicle preparation operations of the present invention), comprising: Vehicle preparation operation library: Stores all available standardized service items (vehicle preparation operations), such as "minor fully synthetic oil change" and "air conditioning system cleaning".

[0068] Vehicle database: By connecting to manufacturers or third-party data sources, such as VIN codes, it obtains data such as vehicle information and mileage uploaded by users.

[0069] Store Resource Database: Stores real-time data on the service capabilities, working hours, and parts inventory of each store.

[0070] In addition, the system may include a data access layer, in which gateways and data access objects can be set up to act as a connection between the user interaction layer and the application service layer.

[0071] Furthermore, the system may also include external service interfaces to receive data generated during the implementation of the above methods.

[0072] Alternatively, the system can also adopt a distributed architecture. The embodiments in this invention do not limit the system distribution method.

[0073] In addition, the terminology used in this invention can be explained as follows: Vehicle preparation operation set: refers to a virtual product, which does not mean a fixed set of vehicle preparation operations, but a right certificate that allows the holder to make multiple, time-sharing, and selective reservations for specific services in a preset "vehicle preparation operation pool".

[0074] Vehicle preparation operation pool: A collection of all available vehicle services that are preset for a set of vehicle preparation operations.

[0075] Vehicle preparation operation: refers to a specific vehicle preparation operation that can be redeemed by the user and is included in the set of vehicle preparation operations. For example, an oil change, a vehicle inspection, an air conditioning filter replacement, a car wash, a brake pad check, a chassis check, a vehicle engine check, a vehicle battery check, etc., and is not limited to the items listed above.

[0076] VIN code: Vehicle Identification Number, is a unique identifier for a vehicle and contains a wealth of information such as the vehicle's manufacturer, engine number, and model.

[0077] Verification: This refers to the process by which the operator confirms the completion of vehicle preparation operations after the user visits the store, and invalidates the corresponding preparation operation through system operation.

[0078] GMV: Gross Merchandise Volume, which is a core indicator for e-commerce platforms to measure transaction volume.

[0079] 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.

Claims

1. A method for vehicle preparation operations, characterized in that, include: Generate a set of vehicle preparation operations; Match the generated set of vehicle preparation operations with the vehicle. Based on the generated set of vehicle preparation operations and the information of the vehicle, generate a vehicle preparation operation instance specifically for the vehicle. as well as An example of performing the vehicle preparation operation on the vehicle.

2. The method according to claim 1, wherein, Based on the generated set of vehicle preparation operations and the vehicle's information, generate a vehicle preparation operation instance specifically for the vehicle, including: Multiple weights are generated based on the vehicle's information; The priority of multiple vehicle preparation operations in the generated vehicle preparation operation set is determined based on the generated weights. Based on the priority of the multiple vehicle preparation operations, a recommended vehicle preparation operation is generated using preset service rules; and Generate a vehicle preparation operation instance specifically for the vehicle based on the recommended vehicle preparation operations.

3. The method according to claim 1, wherein, Based on the generated set of vehicle preparation operations and the vehicle's information, generate a vehicle preparation operation instance specifically for the vehicle, including: Multiple weights are generated based on the vehicle's information; Recommended vehicle maintenance operations are extracted from the generated set of vehicle maintenance operations using multiple weights; and Generate a vehicle preparation operation instance specifically for the vehicle based on the recommended vehicle preparation operations.

4. The method according to claim 2 or 3, wherein, The multiple weights include: Vehicle safety dimension weighting; Weighting of vehicle performance dimensions; The weighting of vehicle comfort dimensions; and Weighting of vehicle cost dimension.

5. The method according to claim 1, wherein, The generated vehicle preparation operation set includes: Create a template for vehicle preparation operations; Select the vehicle preparation operation from the vehicle preparation operation database; Add the selected vehicle preparation operations to the vehicle preparation operation set template to form a vehicle preparation operation set; and Set the usage rules for the resulting set of vehicle preparation operations.

6. The method according to claim 5, wherein, The usage rules of the vehicle preparation operation set include: The price of the vehicle preparation operation set; The validity period of the vehicle preparation operation set; and The usage restrictions of the vehicle preparation operation set.

7. The method according to claim 1, wherein, Matching the generated set of vehicle preparation operations with the vehicle includes: Identifiers for the vehicle; Verify the validity of the identifier; Obtain information about the vehicle; and Based on the identifier and the vehicle information, the generated set of vehicle preparation operations is activated.

8. The method according to claim 7, wherein, If the identifier is invalid, the generated set of vehicle preparation operations will be re-matched with the vehicle.

9. The method according to claim 1, wherein, The vehicle preparation operation instance performed on the vehicle includes: The vehicle preparation operation to be performed is determined from the vehicle preparation operation examples described above. Determine the operational resources corresponding to the vehicle preparation operation to be performed; and Match the operating resources with the vehicle.

10. The method according to claim 1, further comprising: Select a vehicle preparation operation from different vehicle preparation operation instances to form a new vehicle preparation operation instance.

11. A system for vehicle preparation operations, comprising: An operating device configured to provide an operating interface; A vehicle preparation operation management device, the vehicle preparation operation management device being configured to perform the method according to any one of claims 1-10; as well as A data management device configured to store data output by the vehicle preparation operation management device.

12. A terminal for vehicle preparation operations, characterized in that, include: One or more processors; A storage device for storing one or more programs, and When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1-10.

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

14. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method according to any one of claims 1-10.

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