Vehicle upgrading strategy determination method and related equipment

Abstract

The invention provides a vehicle upgrading strategy determination method and related equipment, and the method comprises the steps: obtaining vehicle problem data, and classifying the vehicle problem data; and performing statistical analysis on each type of classified vehicle problem data, and determining the occurrence frequency of each type of vehicle problem data. The vehicle problem data with the occurrence frequency larger than the preset frequency serve as target data, if the occurrence frequency is larger than the preset frequency, it is indicated that the target data belong to vehicle problem data which frequently occurs, and the target data reflect common problems among different vehicles which cross vehicle types and cross brands. And determining the corresponding upgrading strategy according to the attribute information of the target data, so that the upgrading processing modes of the common problem corresponding to the target data can be unified, the upgrading modes for the same common problem on different vehicles are the same, the upgrading difference between the vehicles is reduced, and the satisfaction degree of users is improved.

Description

Technical Field

[0001] This application relates to the technical field of vehicle upgrades, and particularly to a method for determining a vehicle upgrade strategy and related devices. Background Art

[0002] With the rapid development of intelligent connected vehicle technology, over-the-air (FOTA) software upgrades have become an important means for promoting the application of new functions and solving market problems in intelligent connected vehicles. However, for the same vehicle problems, the FOTA upgrade processes and cycles corresponding to vehicles of different brands and models vary. This leads to dissatisfaction and complaints from users when common problems occur in the market because the handling solutions of different brands and models are inconsistent. Summary of the Invention

[0003] In view of this, the purpose of this application is to propose a method for determining a vehicle upgrade strategy and related devices to solve the problem of inconsistent handling solutions for common problems among different brands and models.

[0004] Based on the above purpose, the first aspect of this application provides a method for determining a vehicle upgrade strategy, including:

[0005] Obtain vehicle problem data;

[0006] Classify the vehicle problem data, perform statistical analysis on each classified vehicle problem data, and determine the occurrence frequency of each classified vehicle problem data;

[0007] Use the vehicle problem data of a category with an occurrence frequency greater than a preset frequency as target data, determine the corresponding upgrade strategy according to the attribute information of the target data, and determine the upgrade cycle corresponding to the upgrade strategy.

[0008] Through this embodiment, the upgrade processing methods for common problems corresponding to the target data can be unified, so that the upgrade methods for the same common problem on different vehicles are the same, reducing the upgrade differences between vehicles and improving user satisfaction.

[0009] Optionally, the classifying of the vehicle problem data includes:

[0010] Perform a first classification operation on the vehicle problem data according to a preset vehicle function category;

[0011] Perform a second classification operation on the vehicle problem data after the first classification operation according to a preset problem nature category.

[0012] Through the method of this embodiment, a method for classifying vehicle problem data is given. The vehicle problem data is finely divided according to different dimensions, and the root cause of the vehicle problem data can be accurately determined. Furthermore, a more reasonable and targeted upgrade strategy can be formulated to solve the vehicle problem data through the upgrade strategy and improve user satisfaction.

[0013] Optionally, the upgrade strategy includes an upgrade priority; the attribute information includes severity, impact range, and occurrence frequency;

[0014] Determining the corresponding upgrade strategy according to the attribute information of the target data includes:

[0015] Determining the upgrade priority of the target data according to the severity, the impact range, and the occurrence frequency; wherein, the severity is positively correlated with the upgrade priority, the impact range is positively correlated with the upgrade priority, and the occurrence frequency is positively correlated with the upgrade priority.

[0016] Through the method of this embodiment, a method for determining the upgrade priority of target data is given. According to the attribute information of the target data, the upgrade priority of the target data can be accurately determined to ensure that during the vehicle upgrade process, the upgrade strategy with a higher priority can be upgraded first to ensure vehicle driving safety.

[0017] Optionally, the method further includes:

[0018] Determining the upgrade cycle corresponding to the upgrade strategy according to the attribute information of the target data.

[0019] Through the method of this embodiment, the upgrade cycle can be accurately determined. The accurate determination of the upgrade cycle can not only ensure that important fault problems are processed first, but also reduce the occurrence rate of fault problems, reduce user complaints, and improve user satisfaction.

[0020] Optionally, the attribute information includes severity and occurrence frequency; determining the upgrade cycle corresponding to the upgrade strategy according to the attribute information of the target data includes:

[0021] Determining the upgrade cycle according to the severity and the occurrence frequency; wherein, the severity is negatively correlated with the upgrade cycle, and the occurrence frequency is negatively correlated with the upgrade cycle.

[0022] Through the method of this embodiment, the relationship between severity, occurrence frequency, and upgrade cycle is determined, enabling adaptive adjustment of the upgrade cycle. This avoids user complaints caused by all upgrade strategies using the same upgrade cycle, enhancing user satisfaction. Determining the upgrade cycle based on severity and occurrence frequency can prevent vehicle problems that are severe or occur frequently from not being repaired in a timely manner, posing potential vehicle safety hazards, and can also prevent less severe or less frequent vehicle problems from being repaired too frequently, causing unnecessary upgrade processes for users.

[0023] Optionally, the method further includes:

[0024] Obtaining the running state data of the vehicle in real time;

[0025] Determining the aging degree of the vehicle based on the running state data;

[0026] Adjusting the upgrade cycle according to the aging degree; wherein, the aging degree is negatively correlated with the upgrade cycle.

[0027] Through the method of this embodiment, a corresponding upgrade cycle can be formulated for each vehicle, realizing the customization of vehicle upgrade strategies, providing a more suitable upgrade cycle for each vehicle according to its actual situation, and meeting the driving needs of different vehicles.

[0028] Optionally, the attribute information further includes the trigger condition of the target data; the method further includes:

[0029] Determining the frequent occurrence time period of the target data according to the trigger condition;

[0030] Adjusting the upgrade cycle according to the frequent occurrence time period.

[0031] Through the method of this embodiment, the upgrade cycle can be dynamically adjusted according to the trigger condition, realizing the rational setting of the upgrade cycle, providing a more intelligent upgrade plan for users, and thus enhancing user satisfaction.

[0032] Optionally, the method further includes:

[0033] Real-time monitoring of the vehicle performance data after the vehicle is upgraded according to the upgrade cycle and the upgrade strategy, and evaluating the vehicle upgrade effect based on the vehicle performance data;

[0034] Adjusting the upgrade cycle and the upgrade strategy according to the evaluation result.

[0035] Through this embodiment, the upgrade strategy and the upgrade cycle can be flexibly adjusted in real time according to the upgrade effect, paying real-time attention to the vehicle operation situation, usage situation, and user satisfaction, ensuring effective upgrades and enhancing user satisfaction.

[0036] Based on the same inventive concept, a second aspect of the present application further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable by the processor. When the processor executes the computer program, the method described in the first aspect is implemented.

[0037] Based on the same inventive concept, a third aspect of the present application further provides a non-transitory computer-readable storage medium. The non-transitory computer-readable storage medium stores computer instructions for causing a computer to execute the method described in the first aspect.

[0038] As can be seen from the above, the vehicle upgrade strategy determination method and related devices provided by the present application. The method includes obtaining vehicle problem data, which can reflect problems existing during vehicle use or problems feedback by users, etc. The collection of vehicle problem data is beneficial for formulating more upgrade strategies that meet the actual vehicle use needs and user needs in the future. Classifying the vehicle problem data can refine which vehicle components or component attributes the vehicle problem data is related to. Conducting statistical analysis on each classified category of vehicle problem data to determine the occurrence frequency of each category of vehicle problem data. Through the occurrence frequency, it can be determined whether the vehicle problem data is universal. By classifying the vehicle problem data and determining the occurrence frequency, it can help screen out common problems among different vehicles, so as to formulate vehicle upgrade strategies targeted at the common problems in the future and effectively improve vehicle performance. Taking a category of vehicle problem data with an occurrence frequency greater than a preset frequency as target data. An occurrence frequency greater than the preset frequency indicates that the target data belongs to frequently occurring vehicle problem data, and the target data reflects common problems among different vehicles across vehicle models and brands. Determining the corresponding upgrade strategy according to the attribute information of the target data can unify the upgrade processing methods for the common problems corresponding to the target data, so that the upgrade methods for the same common problem on different vehicles are the same, reducing the upgrade differences between vehicles and improving user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the present application or related technologies, the following will briefly introduce the drawings required for use in the embodiments or related technology descriptions. Obviously, the drawings described below are only the embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0040] Figure 1 It is a flowchart of the vehicle upgrade strategy determination method according to the embodiment of the present application;

[0041] Figure 2Structural schematic diagram of the vehicle upgrade strategy determination device according to the embodiment of the present application;

[0042] Figure 3 Hardware structure schematic diagram of the electronic device according to the embodiment of the present application. Detailed implementation manners

[0043] To make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to specific embodiments and the accompanying drawings.

[0044] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should have the ordinary meanings understood by those of ordinary skill in the art to which the present application belongs. The terms "first", "second" and similar terms used in the embodiments of the present application do not denote any order, quantity or importance, but are only used to distinguish different components. The terms such as "including" or "comprising" mean that the elements or objects appearing before this term cover the elements or objects listed after this term and their equivalents, without excluding other elements or objects. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0045] FOTA technology can remotely update the firmware system of a vehicle through a network, including the driver programs of the vehicle computer, the software of the central control system, etc. These updates can improve the performance and stability of the vehicle, repair the vulnerabilities in the software, and ensure the normal operation of the vehicle. FOTA technology can not only improve the safety of the vehicle, but also bring more convenience to the vehicle owner. For example, the vehicle owner can remotely control the vehicle through a mobile terminal, such as starting the vehicle in advance for preheating, turning on the air conditioner, etc. By performing remote upgrades through FOTA, the frequency of the vehicle owner going to the 4S store can be reduced, and the maintenance cost can be lowered. At the same time, this technology also helps to reduce vehicle failures caused by software problems and reduce the repair cost.

[0046] Currently, due to reasons such as different vehicle brands and models on the market, the FOTA upgrade solutions for different vehicles are different. Especially for the upgrade solutions and upgrade cycles for the same problem, the upgrade processing methods for different vehicles vary greatly, resulting in customer dissatisfaction.

[0047] In view of this, the present application proposes an upgrade strategy determination method, which screens out the common problems among different vehicles by collecting vehicle problem data, and then determines a unified upgrade plan and upgrade cycle according to the common problems, so that when facing the same common problem, the upgrade methods for different vehicles are the same, thereby improving user satisfaction.

[0048] The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0049] The present application proposes a method for determining a vehicle upgrade strategy, referring to Figure 1 , including the following steps:

[0050] Step 102: Obtain vehicle problem data.

[0051] Specifically, vehicle problem data refers to the problem data that occurs during the use of the vehicle. The data sources of vehicle problem data are not limited to user feedback, after-sales service records, vehicle diagnostic logs, social media, and forum discussions, etc. The richness of the data sources can ensure the comprehensiveness of vehicle problem data.

[0052] After obtaining the vehicle problem data, the vehicle problem data can be cleaned. Data cleaning can remove duplicate data, fuzzy data, or invalid data in the vehicle problem data to ensure that each piece of data is independent, clear, and verifiable. Among them, for important or complex data, its authenticity and universality can be further verified.

[0053] The judgment of important or complex data can be comprehensively evaluated according to dimensions such as the severity, influence range, and solution difficulty of the vehicle problem data. Exemplarily, if the vehicle problem data causes the vehicle to be unable to drive or there are safety hazards, or affects the normal use of the vehicle by the user or occurs frequently, etc., it is determined that the severity of the vehicle problem data is relatively high and belongs to important data. If the vehicle problem data involves multiple components in the vehicle, or involves multiple vehicle models or brands, etc., it is determined that the influence range of the vehicle problem data is relatively large and belongs to serious data. If the vehicle failure caused by the vehicle problem data is difficult to solve or repair, etc., it is determined that the solution difficulty is relatively high and belongs to complex data. To ensure the authenticity of the data, further verification of important or complex data is required. Further verification can be carried out by methods such as reproducing the problem, analyzing the log, or simulating the test. If it is determined through further verification that there is no problem reflected in the vehicle problem data, it means that the vehicle problem data feedback is incorrect and can be excluded to avoid affecting the formulation of subsequent upgrade strategies.

[0054] Step 104: Classify the vehicle problem data, perform statistical analysis on each classified type of vehicle problem data, and determine the occurrence frequency of each type of vehicle problem data.

[0055] Specifically, when classifying vehicle problem data, it can be classified according to the vehicle components or problem natures corresponding to the vehicle problem data. This is equivalent to making a fine-grained division of the vehicle problem data from different dimensions, which is beneficial to formulating the accuracy of the upgrade strategy. After classification, the occurrence frequency of each type of vehicle problem data can be determined respectively. A high occurrence frequency indicates that this type of vehicle problem data belongs to frequently occurring problem data, and a low occurrence frequency indicates that this type of vehicle problem data belongs to problem data with a small occurrence probability. Through classification and determination of the occurrence frequency, frequent common problems among different vehicles can be screened out, which is beneficial to formulating an upgrade strategy for the frequent common problems subsequently, so as to uniformly solve the common problems of the vehicles, reduce the failure rate of the vehicles, and improve user satisfaction.

[0056] After classifying the vehicle problem data, a database can be constructed to store the classified data. At the same time, detailed descriptions can be made for each type of vehicle problem data, and the corresponding attribute information of each type of vehicle problem data can be determined. For example, the attribute information can include the unique identifier of the vehicle problem data, problem description, scope of influence, triggering conditions, discovery time, solution, and solution status, etc. Use a database management system to store and manage the classified vehicle problem data. Exemplarily, the database management system can be MySQL or Oracle, etc. With the generation of new vehicle problem data and the solution of old vehicle problem data, the database can be updated accordingly to maintain the timeliness and accuracy of the database. At the same time, the database can also be cleaned and optimized regularly to improve the query efficiency of the database.

[0057] Step 106: Take a type of vehicle problem data with an occurrence frequency greater than the preset frequency as the target data, and determine the corresponding upgrade strategy according to the attribute information of the target data.

[0058] Specifically, the target data is a type of vehicle problem data with an occurrence frequency greater than the preset frequency. An occurrence frequency greater than the preset frequency indicates that the target data is frequently occurring problem data, which needs to be taken seriously enough and corresponding upgrade strategies should be formulated to prevent the vehicle problems corresponding to the target data from further causing failures in more vehicles, so as to achieve the purpose of repairing the problems existing in the vehicles in a timely manner. Determine the upgrade strategy according to the attribute information of the target data. Specifically, the upgrade content, steps, time window, and upgrade method in the upgrade strategy can be determined according to the problem description, scope of influence, triggering conditions, discovery time, etc. in the attribute information. The cause of the problem can be determined through the problem description, scope of influence, and triggering conditions, etc., and then the corresponding upgrade content and steps can be formulated. The upgrade content includes repairing specific problems or optimizing relevant performances. In order to avoid affecting users' use of the vehicle, the upgrade time window is preferably selected during vehicle idle time or low-traffic periods for upgrading.

[0059] The upgrade methods include full upgrade or segmented upgrade. Among them, full upgrade is applicable to widespread problems and is required when all vehicles or most vehicles need to be upgraded. For example, if a system vulnerability or security defect affects all vehicles or most vehicles, then a full upgrade is needed. Segmented upgrade is applicable to situations where the problems are relatively limited or the upgrade plan needs to be gradually verified. For example, if a new function or optimization is only tested on some vehicle models, then a segmented upgrade method can be adopted, where some vehicles are upgraded first, and after observing the upgrade effect, it is gradually promoted.

[0060] It should be noted that when formulating the upgrade strategy, compatibility issues also need to be considered. Due to different vehicle models, there are certain differences in the technical architecture, hardware configuration, and software version of vehicles. In order to meet the upgrade requirements of different vehicle models simultaneously, by understanding the technical architecture, software and hardware configuration information of different vehicle models and brands, a general upgrade plan is formulated, and sufficient testing and verification are carried out on the target vehicle models. In addition, a compatibility check mechanism is added during the upgrade process to determine the matching of the upgrade strategy with the vehicle.

[0061] Based on the above steps 102 to 106, this embodiment provides a method for determining a vehicle upgrade strategy, including obtaining vehicle problem data. The vehicle problem data can reflect the problems existing during the use of the vehicle or the problems feedback by users, etc. The collection of vehicle problem data is conducive to formulating a more upgrade strategy that meets the actual use needs of the vehicle and the user needs in the future. Classifying the vehicle problem data can refine which vehicle components or component attributes the vehicle problem data is related to. Statistically analyzing each classified category of vehicle problem data to determine the occurrence frequency of each category of vehicle problem data. Through the occurrence frequency, it can be determined whether the vehicle problem data is universal. By classifying the vehicle problem data and determining the occurrence frequency, it can help screen out the common problems among different vehicles, so as to formulate a vehicle upgrade strategy targeted at the common problems in the future and effectively improve the vehicle performance. Taking a category of vehicle problem data with an occurrence frequency greater than the preset frequency as the target data. An occurrence frequency greater than the preset frequency indicates that the target data belongs to frequently occurring vehicle problem data, and the target data reflects the common problems among different vehicles across vehicle models and brands. Determining the corresponding upgrade strategy according to the attribute information of the target data can unify the upgrade processing methods for the common problems corresponding to the target data, so that the upgrade methods for the same common problem on different vehicles are the same, reducing the upgrade differences among vehicles and improving user satisfaction.

[0062] In order to further refine which vehicle components or component attributes the vehicle problem data is related to, it is necessary to classify the vehicle problem data. The following specifically introduces the method for classifying the vehicle problem data.

[0063] In some embodiments, classifying the vehicle problem data includes:

[0064] Performing a first classification operation on the vehicle problem data according to a preset vehicle function category;

[0065] Performing a second classification operation on the vehicle problem data after the first classification operation according to a preset problem nature category.

[0066] In this embodiment, the vehicle problem data is mainly classified according to the vehicle function category and the problem nature category. Among them, the classification operation according to the vehicle function category is denoted as the first classification operation, and the classification operation according to the problem nature category is denoted as the second classification operation. Through the vehicle function category, it can be determined which components or modules in the vehicle the vehicle problem data is related to, and through the problem nature category, it can be determined what aspects of the components or modules have problems. Exemplarily, the preset vehicle function categories may include a power system, an intelligent driving system, a vehicle networking system, etc., and the preset problem nature categories may include performance degradation, frequent failures, or safety hazards, etc. Through the classification process, the categories corresponding to the vehicle problem data can be accurately divided, which is beneficial to accurately determining the upgrade strategy. At the same time as the classification, the vehicle problem data is also sorted out, and the attribute information such as the influence range and trigger conditions of the vehicle problem data is determined. The influence range refers to the number of vehicles, vehicle models, system modules, or functions that may be affected after the vehicle problem data appears. For example, if a certain vehicle problem may cause all vehicles installed with a specific version of software to fail to start normally, then the influence range is all vehicles installed with this version of software. The trigger condition refers to the specific condition or environment that causes the vehicle problem data to occur. For example, if a certain vehicle problem only appears when the vehicle speed exceeds 120 km / h, then the trigger condition is that the vehicle speed exceeds 120 km / h.

[0067] In addition to the above classification method, the vehicle problem data can also be divided into more fine-grained categories according to the actual situation. For example, the power system can be further decomposed into components such as an engine, a generator, and a transmission. In this way, the root cause of the vehicle problem data can be further located, which is convenient for optimizing the subsequent upgrade strategy.

[0068] Through the method of this embodiment, a method for classifying vehicle problem data is given. The vehicle problem data is divided into fine-grained categories according to different dimensions, and the root cause of the vehicle problem data can be accurately determined. Furthermore, a more reasonable and targeted upgrade strategy can be formulated to solve the vehicle problem data through the upgrade strategy and improve user satisfaction.

[0069] When there are multiple upgrade strategies, upgrades need to be carried out in order of urgency to ensure the safety of vehicle driving. Therefore, when formulating upgrade strategies, the priority corresponding to each upgrade strategy can be set, which will be illustrated by specific embodiments below.

[0070] In some embodiments, the upgrade strategy includes an upgrade priority; the attribute information includes severity, scope of influence, and frequency of occurrence;

[0071] Determining the corresponding upgrade strategy according to the attribute information of the target data includes:

[0072] Determining the upgrade priority of the target data according to the severity, the scope of influence, and the frequency of occurrence; wherein, the severity is positively correlated with the upgrade priority, the scope of influence is positively correlated with the upgrade priority, and the frequency of occurrence is positively correlated with the upgrade priority.

[0073] Specifically, when determining the upgrade priority, it can be jointly determined by comprehensively considering the severity, scope of influence, and frequency of occurrence of the target data. The higher the severity, the higher the upgrade priority; the larger the scope of influence, the higher the upgrade priority; the higher the frequency of occurrence, the higher the upgrade priority.

[0074] When determining the upgrade priority, it is first necessary to ensure the safety of the vehicle. Therefore, the severity has the highest priority. If the severities are the same, the upgrade priority can be determined according to the scope of influence or the frequency of occurrence. Exemplarily, when determining the upgrade priorities of vehicle problem data A and vehicle problem data B, if the severities of A and B are the same, the scopes of influence of A and B are respectively determined. If the scope of influence of A exceeds that of B, the upgrade priority of A is higher than that of B; or, if the severities of A and B are the same, the frequencies of occurrence of A and B are respectively determined. If the frequency of occurrence of A exceeds that of B, the upgrade priority of A is higher than that of B; or, if the severities of A and B are the same and the frequencies of occurrence are also the same, the scopes of influence of A and B are respectively determined. If the scope of influence of A exceeds that of B, the upgrade priority of A is higher than that of B.

[0075] The method of this embodiment gives a method for determining the upgrade priority of the target data. According to the attribute information of the target data, the upgrade priority of the target data can be accurately determined to ensure that during the vehicle upgrade process, the upgrade strategy with a higher priority can be upgraded first, guaranteeing the driving safety of the vehicle.

[0076] It should be noted that the method for determining the upgrade priority in this embodiment is only for illustrative purposes and does not have a restrictive effect. When determining the upgrade priority corresponding to the target data, influencing factors other than the severity, scope of influence, and occurrence frequency can also be considered, such as user habits, weather factors, and seasonal factors, etc., to determine a more reasonable upgrade priority.

[0077] After determining the upgrade strategy, it is also necessary to determine the upgrade cycle corresponding to the upgrade strategy to achieve unified formulation and management of the upgrade cycle, and further improve user satisfaction.

[0078] In some embodiments, the method further includes: determining the upgrade cycle corresponding to the upgrade strategy according to the attribute information of the target data.

[0079] Specifically, in addition to formulating the upgrade strategy, the reasonable determination of the upgrade cycle is also crucial. For important upgrades, the upgrade cycle should be appropriately shortened to optimize the software and hardware versions on the vehicle end before a fault problem occurs and reduce the failure rate. For fault problems that have been solved or unimportant upgrades, the upgrade cycle can be appropriately extended to avoid disturbing users due to frequent upgrades. The upgrade cycle can be reasonably determined according to the attribute information of the target data. The attribute information includes problem description, scope of influence, trigger condition, discovery time, solution, and solution status, etc. The importance of the upgrade strategy can be determined according to the problem description, scope of influence, etc. For relatively important problems, the upgrade cycle can be shortened. The reasonable upgrade time and upgrade cycle of the upgrade strategy can be determined through the trigger condition and discovery time, etc., which can effectively avoid triggering fault problems or optimizing the vehicle end configuration before the period of frequent fault problems to reduce the occurrence rate of fault problems. Through the solution and solution status, it is possible to continuously monitor whether the upgrade strategy and upgrade cycle are reasonable. If they are not reasonable, the upgrade strategy and upgrade cycle can be further optimized.

[0080] Through the method of this embodiment, the upgrade cycle can be accurately determined. The accurate determination of the upgrade cycle can not only ensure that important fault problems are given priority treatment, but also reduce the occurrence rate of fault problems, reduce user complaints, and improve user satisfaction.

[0081] The following uses specific embodiments to illustrate how to determine the upgrade cycle according to the attribute information.

[0082] In some embodiments, the attribute information includes severity and occurrence frequency; the determining the upgrade cycle corresponding to the upgrade strategy according to the attribute information of the target data includes:

[0083] Determining the upgrade cycle according to the severity and the occurrence frequency; wherein, the severity is negatively correlated with the upgrade cycle, and the occurrence frequency is negatively correlated with the upgrade cycle.

[0084] Specifically, when determining the upgrade cycle, the severity and occurrence frequency in the attribute information need to be considered. Among them, the higher the severity, the more likely the vehicle problem data will seriously affect vehicle safety. For such vehicle problem data, it is necessary to shorten the upgrade cycle and increase the update frequency of the vehicle-end software and hardware versions to avoid the failure problems caused by such vehicle problem data or reduce the severity of the failure problems. The higher the occurrence frequency, the more frequently the vehicle problem data appears, and it has a greater impact on a certain model or some models. It is necessary to shorten the upgrade cycle and increase the update frequency of the vehicle-end software and hardware versions to slow down the occurrence frequency of the failure problems caused by such vehicle problem data. Therefore, both the severity and the occurrence frequency are negatively correlated with the upgrade cycle.

[0085] In addition, if the upgrade cycles determined by the severity and the occurrence frequency are different for the same vehicle problem data, the shorter upgrade cycle is preferentially selected as the final upgrade cycle to ensure that vehicle safety hazards can be eliminated in a timely manner.

[0086] Through the method of this embodiment, the relationship between the severity, the occurrence frequency and the upgrade cycle is determined, and the adaptive adjustment of the upgrade cycle can be realized. Avoiding that all upgrade strategies adopt the same upgrade cycle causes user complaints and improving user satisfaction. Determining the upgrade cycle according to the severity and the occurrence frequency can not only avoid the failure to repair serious or frequently occurring vehicle problems in a timely manner, bringing vehicle safety hazards, but also avoid the relatively frequent repair of non-serious or less-occurring vehicle problems, bringing unnecessary upgrade processes to users.

[0087] The upgrade cycle is not only related to the upgrade strategy, but also the difference in the vehicle aging degree needs to be considered to formulate an upgrade cycle that meets different vehicle aging conditions. This will be illustrated by specific embodiments below.

[0088] In some embodiments, the method further includes:

[0089] Obtaining the running state data of the vehicle in real time;

[0090] Determining the aging degree of the vehicle according to the running state data;

[0091] Adjusting the upgrade cycle according to the aging degree; wherein, the aging degree is negatively correlated with the upgrade cycle.

[0092] Specifically, the aging degrees of vehicles are different. To timely learn about the aging degrees of different vehicles, it is necessary to collect the operation status data of the vehicles in real time. The operation status data may include the driving mileage, usage duration, failure rate, etc. of the vehicle. Through the operation status data, the operation status and aging degree of the vehicle can be understood. If a vehicle has a longer driving mileage, a longer usage duration, or a higher failure rate, it can be determined that the aging degree of the vehicle is higher. Compared with vehicles with a lower aging degree, vehicles with a higher aging degree usually have a greater probability of failure. Therefore, for vehicles with a higher aging degree, the frequency of the upgrade cycle can be appropriately increased, the upgrade cycle can be appropriately shortened, and the software and hardware versions of the vehicle terminal can be upgraded in time to reduce the vehicle failure rate.

[0093] Furthermore, the vehicles can be classified according to the aging degree based on evaluation dimensions such as the driving mileage, usage duration, and failure rate of the vehicle. The higher the aging degree level, the more serious the aging degree. Exemplarily, if the driving mileage is within 30,000 kilometers, the score corresponding to the driving mileage is determined to be 10 points. If the driving mileage is between 30,000 kilometers and 50,000 kilometers, the score corresponding to the driving mileage is determined to be 7 points. If the driving mileage is between 50,000 kilometers and 100,000 kilometers, the score corresponding to the driving mileage is determined to be 5 points, and so on. The scoring methods for the usage duration and failure rate are the same as that for the driving mileage and will not be elaborated one by one. Then, the weighted sum is calculated based on the scores of the driving mileage, usage duration, and failure rate respectively to determine the final aging score. Then, the corresponding aging degree level can be determined according to the aging score. For example, if the aging score is above 10 points, the aging degree level is level one. If the aging score is between 5 points and 10 points, the aging degree level is level two. If the aging score is below 5 points, the aging degree level is level three. The aging degree level of level one indicates a relatively mild aging degree, and the aging degree level of level three indicates a relatively serious aging degree.

[0094] Through the method of this embodiment, a corresponding upgrade cycle can be formulated for each vehicle, realizing the customization of the vehicle upgrade strategy, providing a more suitable upgrade cycle for each vehicle according to the actual situation of the vehicle, and meeting the driving needs of different vehicles.

[0095] In addition to the aging degree of the vehicle, some failures occur at specific times or seasons. Therefore, when dynamically adjusting the upgrade cycle, it is also necessary to consider the frequent occurrence period of the failure to avoid the occurrence of the failure in advance. The following is illustrated by specific embodiments.

[0096] In some embodiments, the attribute information further includes the trigger condition of the target data; the method further includes:

[0097] Determine the frequent occurrence period of the target data according to the trigger condition;

[0098] Adjust the upgrade cycle according to the frequent occurrence period.

[0099] Specifically, some fault problems at the vehicle end may occur concentrated in a certain time period. For example, with the change of seasons, some faults are likely to occur in seasons with lower temperatures, such as winter. To avoid the occurrence of such fault problems, before entering winter, the software and hardware corresponding to the possible fault problems at the vehicle end can be optimized. The attribute information of the target data includes a trigger condition, and the trigger condition describes the conditions under which the vehicle problem data occurs, such as environmental temperature and humidity, vehicle speed, or driving mode, etc. Through the trigger condition, it can be analyzed and determined whether the target data occurs randomly. Exemplarily, if the environmental temperature corresponding to the target data is all below zero degrees, it is determined that the target data does not occur randomly. If the environmental temperature range corresponding to the target data is large, it is determined that the target data occurs randomly. Another example is that if the vehicle speed corresponding to the target data is all above 100 km / h, it is determined that the target data does not occur randomly. If the vehicle speed range corresponding to the target data is large, including vehicle speeds in each speed segment, it is determined that the target data occurs randomly. Another example is that if the driving mode corresponding to the target data is concentrated within one mode, it is determined that the target data does not occur randomly. If the driving mode corresponding to the target data is distributed within several modes, it is determined that the target data occurs randomly. If it does not occur randomly, the trigger characteristics of the trigger condition, such as the frequently occurring time period, can be statistically analyzed. Then, the upgrade cycle can be adjusted according to the frequently occurring time period. The specific adjustment method can be to optimize the software and hardware at the vehicle end in advance before entering the frequently occurring time period, so that after the vehicle enters the frequently occurring time period, the fault occurrence rate can be avoided or significantly reduced. Through the method of this embodiment, the upgrade cycle can be dynamically adjusted according to the trigger condition, realizing the rational setting of the upgrade cycle, providing a more intelligent upgrade plan for users, and thus improving user satisfaction.

[0100] After determining the upgrade strategy and upgrade cycle, the vehicle end executes the upgrade strategy according to the upgrade cycle. However, after the upgrade, the vehicle end problems may not be solved or other vehicle end problems may be caused. It is also necessary to monitor the upgrade result of the vehicle in real time to further provide an effective upgrade plan for users.

[0101] In some embodiments, the method further includes:

[0102] Real-time monitoring of the vehicle performance data after the vehicle is upgraded according to the upgrade cycle and the upgrade strategy, and evaluating the vehicle upgrade effect according to the vehicle performance data;

[0103] Adjusting the upgrade cycle and the upgrade strategy according to the evaluation result.

[0104] Specifically, after the vehicle is upgraded according to the upgrade cycle and upgrade strategy, vehicle performance data will be generated, and the upgrade effect of the vehicle can be evaluated by collecting the vehicle performance data. During the upgrade process, closely monitor the upgrade progress and user feedback to ensure the smooth progress of the upgrade. After the upgrade is completed, if the fault problem still exists or new problems occur, it is necessary to determine the next upgrade strategy and upgrade cycle according to the newly collected vehicle problem data to achieve flexible adjustment of the upgrade strategy and upgrade cycle. After the upgrade is completed, if the fault problem has been solved or the frequency of the fault problem has decreased significantly, the upgrade cycle can be appropriately extended to avoid continuous frequent upgrades causing user complaints. Through this embodiment, the upgrade strategy and upgrade cycle can be flexibly adjusted in real time according to the upgrade effect, and the vehicle operation situation, usage situation and user satisfaction can be monitored in real time to ensure effective upgrade and improve user satisfaction.

[0105] In addition, some users may have higher requirements for vehicle performance, or some vehicle models may require special upgrade solutions due to technical architecture differences. Through channels such as user feedback or after-sales service records, the special needs or problems of specific users or vehicle models can be identified. Based on specific needs, customize personalized upgrade strategies. The upgrade strategy includes solutions to specific problems, upgrade steps and precautions, etc., to ensure that the upgrade strategy matches the user needs and technical architecture. After determining the personalized upgrade strategy, select a small range to implement the personalized upgrade strategy and conduct sufficient testing. Ensure that the upgrade strategy effectively solves specific problems and does not have a negative impact on vehicle performance. The selection of small-scale test vehicles usually includes two types: test vehicles and user vehicles. Test vehicles are used to initially verify the effectiveness and safety of the personalized upgrade strategy. User vehicles are used to verify the upgrade effect in the actual use environment and collect user feedback. At the same time, when selecting small-scale test vehicles, it is necessary to fully consider the differences of the vehicles to ensure the compatibility of the upgrade strategy. According to the test results of the small-scale test vehicles, optimize and improve the personalized upgrade strategy. After that, it can be promoted and implemented on a large scale to meet the needs of more users or vehicle models. At the same time, continuously collect user feedback and vehicle usage data to further optimize the upgrade strategy.

[0106] After formulating the upgrade strategy and upgrade cycle, the server can timely push upgrade information to the vehicle terminal to prompt that the vehicle terminal can be upgraded.

[0107] In some embodiments, the method further includes:

[0108] Real-time collect the current software and hardware version information of the vehicle;

[0109] Determine whether there is an upgrade strategy corresponding to the current software and hardware version information;

[0110] In response to the presence, obtain the operating status data of the vehicle, and determine the aging degree of the vehicle according to the operating status data;

[0111] Adjust the upgrade cycle corresponding to the upgrade strategy according to the aging degree, and send the adjusted upgrade cycle and upgrade strategy to the vehicle terminal, so that the vehicle terminal executes the upgrade strategy according to the adjusted upgrade cycle.

[0112] Specifically, after formulating various upgrade strategies, the server can actively push the upgrade strategies to the vehicle terminal to achieve timely upgrade and optimization of the vehicle terminal. In order to determine whether each vehicle terminal needs to be upgraded, it is necessary to collect the current software and hardware version information of each vehicle in real time. In the database where each upgrade strategy is pre-stored, determine whether there is an upgrade strategy corresponding to the current software and hardware version information through matching query. If it exists, it means that the vehicle terminal can currently perform the upgrade of relevant functions. In the database, each upgrade strategy corresponds to an initial upgrade cycle. The initial upgrade cycle is comprehensively determined according to the severity, occurrence frequency, and trigger conditions of the vehicle problem data when formulating the upgrade strategy. The determination method is the same as that in the foregoing embodiment and will not be elaborated here.

[0113] Since it is considered that the aging degrees of each vehicle are different, when pushing the upgrade strategy, it is also necessary to further determine the aging degree of each vehicle, and the aging degree is determined according to the collected operating status data of the vehicle. The method for determining the aging degree according to the operating status data is the same as that in the foregoing embodiment and will not be elaborated here too much. After determining the aging degree, adjust the initial upgrade cycle of the upgrade strategy according to the aging degree. If the aging degree is relatively low, the upgrade cycle can be appropriately extended. If the aging degree is relatively high, the upgrade cycle can be appropriately shortened. In order to further quickly adjust the upgrade cycle, a corresponding relationship between the aging degree and the upgrade cycle can also be pre-constructed in the database, and the upgrade cycle corresponding to different aging degrees can be quickly queried through the corresponding relationship. After determining the adjusted upgrade cycle, send the upgrade strategy and the adjusted upgrade cycle to the vehicle terminal, so that the vehicle terminal executes the upgrade strategy according to the adjusted upgrade cycle, realizing flexible adjustment of the upgrade cycle for different vehicles. It is equivalent to generating a customized upgrade plan for each vehicle, providing an upgrade cycle that more conforms to the actual situation of the vehicle, meeting the differentiated needs of the vehicle on the basis of optimizing the vehicle performance, and improving user satisfaction.

[0114] It should be noted that the method of the embodiment of the present application can be executed by a single device, such as a computer or a server, etc. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In this case of a distributed scenario, one of the multiple devices can only execute one or more steps in the method of the embodiment of the present application, and these multiple devices will interact with each other to complete the described method.

[0115] It should be noted that some embodiments of the present application have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the above embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0116] Based on the same inventive concept, corresponding to any of the above-described method embodiments, the present application further provides a vehicle upgrade strategy determination device.

[0117] Referring to Figure 2 , the vehicle upgrade strategy determination device includes:

[0118] An acquisition module 202, configured to acquire vehicle problem data;

[0119] A first determination module 204, configured to classify the vehicle problem data, perform statistical analysis on each classified type of vehicle problem data, and determine the occurrence frequency of each type of vehicle problem data;

[0120] A second determination module 204, configured to use a type of vehicle problem data with an occurrence frequency greater than a preset frequency as target data, and determine a corresponding upgrade strategy according to the attribute information of the target data.

[0121] In some embodiments, the first determination module 204 is configured to perform a first classification operation on the vehicle problem data according to a preset vehicle function category; and perform a second classification operation on the vehicle problem data after the first classification operation according to a preset problem nature category

[0122] In some embodiments, the upgrade strategy includes an upgrade priority; the attribute information includes severity, impact range, and occurrence frequency; the second determination module 204 is configured to determine the upgrade priority of the target data according to the severity, the impact range, and the occurrence frequency; wherein, the severity is positively correlated with the upgrade priority, the impact range is positively correlated with the upgrade priority, and the occurrence frequency is positively correlated with the upgrade priority.

[0123] In some embodiments, the second determination module 204 is configured to determine an upgrade cycle corresponding to the upgrade strategy according to the attribute information of the target data.

[0124] In some embodiments, the attribute information includes severity and occurrence frequency; a second determination module 204, configured to determine the upgrade cycle according to the severity and the occurrence frequency; wherein, the severity is negatively correlated with the upgrade cycle, and the occurrence frequency is negatively correlated with the upgrade cycle.

[0125] In some embodiments, the second determination module 204 is configured to obtain the operation state data of the vehicle in real time; determine the aging degree of the vehicle according to the operation state data; adjust the upgrade cycle according to the aging degree; wherein, the aging degree is negatively correlated with the upgrade cycle.

[0126] In some embodiments, the attribute information further includes a trigger condition for target data; the second determination module 204 is configured to determine a frequent occurrence time period of the target data according to the trigger condition; adjust the upgrade cycle according to the frequent occurrence time period.

[0127] In some embodiments, the second determination module 204 is configured to monitor in real time the vehicle performance data after the vehicle is upgraded according to the upgrade cycle and the upgrade strategy, evaluate the vehicle upgrade effect according to the vehicle performance data; adjust the upgrade cycle and the upgrade strategy according to the evaluation result.

[0128] For convenience of description, when describing the above device, various modules are described separately according to their functions. Of course, when implementing the present application, the functions of each module can be implemented in one or more software and / or hardware.

[0129] The device in the above embodiment is used to implement the corresponding vehicle upgrade strategy determination method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0130] Based on the same inventive concept, corresponding to the method in any of the above embodiments, the present application further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the vehicle upgrade strategy determination method described in any of the above embodiments when executing the program.

[0131] Figure 3 FIG. shows a more specific schematic diagram of the hardware structure of the electronic device provided in this embodiment. The device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. Among them, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are communicatively connected to each other inside the device through the bus 1050.

[0132] The processor 1010 can be implemented in the form of a general - purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0133] The memory 1020 can be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 1020 can store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0134] The input / output interface 1030 is used to connect to the input / output module to achieve information input and output. The input / output module can be configured as a component in the device (not shown in the figure) or can be externally connected to the device to provide corresponding functions. Among them, the input device can include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device can include a display, a speaker, a vibrator, an indicator light, etc.

[0135] The communication interface 1040 is used to connect to a communication module (not shown in the figure) to achieve communication interaction between this device and other devices. Among them, the communication module can achieve communication through a wired method (such as USB, network cable, etc.) or can achieve communication through a wireless method (such as a mobile network, WIFI, Bluetooth, etc.).

[0136] The bus 1050 includes a path for transmitting information between various components of the device (such as the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0137] It should be noted that although the above - mentioned device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in the specific implementation process, this device may also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above - mentioned device may also only include the components necessary to implement the solutions of the embodiments of this specification, and does not necessarily include all the components shown in the figure.

[0138] The electronic device of the above embodiment is used to implement the corresponding vehicle upgrade strategy determination method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated herein.

[0139] Based on the same inventive concept, corresponding to the method of any of the above embodiments, the present application also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the vehicle upgrade strategy determination method as described in any of the foregoing embodiments.

[0140] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0141] The computer instructions stored in the storage medium of the above embodiment are used to cause the computer to execute the vehicle upgrade strategy determination method as described in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be elaborated herein.

[0142] Based on the same concept, corresponding to the method of any of the above embodiments, the present application also provides a computer program product including computer program instructions, which when run on a computer, cause the computer to execute the method as described in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be elaborated herein.

[0143] It can be understood that before using the technical solutions of the various embodiments of the present disclosure, the types, usage scopes, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner and the user's authorization will be obtained.

[0144] For example, when responding to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested by the user will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, an application program, a server, or a storage medium that performs the operations of the present disclosure's technical solution based on the prompt message.

[0145] As an optional but non-limiting implementation manner, the way of sending a prompt message to the user in response to receiving the user's active request can be, for example, in the form of a pop-up window, and the prompt message can be presented in text in the pop-up window. In addition, the pop-up window can also carry selection controls for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0146] It can be understood that the above process of notifying and obtaining user authorization is only illustrative and does not limit the implementation manner of the present disclosure. Other ways that meet relevant laws and regulations can also be applied to the implementation manner of the present disclosure.

[0147] Those of ordinary skill in the art should understand that the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the present application is limited to these examples; under the idea of the present application, the technical features between the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations in different aspects of the embodiments of the present application as described above, and they are not provided in detail for the sake of brevity.

[0148] In addition, for the sake of simplicity of description and discussion, and in order not to make the embodiments of the present application difficult to understand, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation manner of these block diagram devices are highly dependent on the platform on which the embodiments of the present application will be implemented (that is, these details should be completely within the understanding of those skilled in the art). In the case where specific details (such as circuits) are set forth to describe the exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or with variations of these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0149] Although the present application has been described in connection with specific embodiments of the present application, many substitutions, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. For example, other memory architectures (such as dynamic RAM (DRAM)) can be used with the embodiments discussed.

[0150] The embodiments of the present application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the present application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application shall be included within the protection scope of the present application.

Claims

1. A method for determining a vehicle upgrade strategy, characterized in that: include: Get vehicle problem data; Classifying the vehicle problem data, performing statistical analysis on each type of classified vehicle problem data, and determining the occurrence frequency of each type of vehicle problem data; The vehicle problem data of a type with an occurrence frequency greater than a preset frequency is taken as target data, and a corresponding upgrade strategy is determined according to attribute information of the target data.

2. The method according to claim 1, characterized in that The classifying the vehicle problem data comprises: Performing a first classification operation on the vehicle problem data according to a preset vehicle function category; A second classification operation is performed on the vehicle problem data after the first classification operation according to a preset problem nature category.

3. The method according to claim 1, characterized in that The upgrade strategy includes upgrade priority; the attribute information includes severity, impact scope and occurrence frequency; The determining a corresponding upgrade strategy according to the attribute information of the target data includes: The upgrade priority of the target data is determined according to the severity, the scope of impact and the frequency of occurrence; wherein the severity is positively correlated with the upgrade priority, the scope of impact is positively correlated with the upgrade priority, and the frequency of occurrence is positively correlated with the upgrade priority.

4. The method according to claim 1, characterized in that The method further comprises: An upgrade cycle corresponding to the upgrade strategy is determined according to the attribute information of the target data.

5. The method according to claim 4, characterized in that The attribute information includes severity and frequency of occurrence; and determining the upgrade cycle corresponding to the upgrade strategy according to the attribute information of the target data includes: The upgrade cycle is determined according to the severity and the occurrence frequency; wherein the severity is negatively correlated with the upgrade cycle, and the occurrence frequency is negatively correlated with the upgrade cycle.

6. The method according to claim 5, characterized in that The method further comprises: Obtain vehicle operation status data in real time; determining the aging degree of the vehicle according to the operating status data; The upgrade cycle is adjusted according to the aging degree; wherein the aging degree is negatively correlated with the upgrade cycle.

7. The method according to claim 5, characterized in that The attribute information also includes a trigger condition of the target data; the method also includes: Determine a time period in which target data frequently occurs according to the trigger condition; The upgrade cycle is adjusted according to the frequently occurring time period.

8. The method according to claim 1, characterized in that The method further comprises: Real-time monitoring of vehicle performance data after the vehicle is upgraded according to the upgrade cycle and the upgrade strategy, and evaluating the vehicle upgrade effect according to the vehicle performance data; The upgrade cycle and the upgrade strategy are adjusted according to the evaluation result.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 8 is implemented.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 8.

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