Vehicle function optimization method and device, equipment, storage medium and program product

Abstract

The invention relates to a vehicle function optimization method and device, equipment, a storage medium and a program product. The method comprises the steps of determining a to-be-optimized vehicle function from candidate vehicle functions according to historical behavior data associated with a target user, determining a user behavior mode of the target user according to the historical behavior data and function influence factors corresponding to the to-be-optimized function, and determining a to-be-optimized vehicle function according to the user behavior mode and function configuration information of the to-be-optimized vehicle function. And optimizing the to-be-optimized vehicle function to obtain an optimized target vehicle function. By adopting the method, the efficiency and reliability of vehicle function optimization can be improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a vehicle function optimization method, device, equipment, storage medium and program product. Background Art

[0002] With the continuous development of intelligent vehicles, in order to ensure the driver's driving experience during the driving process, it is necessary to adaptively optimize and adjust the vehicle functions of the driver's vehicle.

[0003] The existing vehicle function optimization method generally optimizes the vehicle function adaptively by manually modifying the setting parameters. However, the existing vehicle function optimization method reduces the efficiency of vehicle function optimization by manually configuring vehicle parameters. Summary of the invention

[0004] Based on this, it is necessary to provide a vehicle function optimization method, device, equipment, storage medium and program product that can improve the efficiency of vehicle function optimization in response to the above technical problems.

[0005] In a first aspect, the present application provides a vehicle function optimization method, comprising:

[0006] Determine the vehicle function to be optimized from among the candidate vehicle functions based on the historical behavior data associated with the target user;

[0007] Determine the user behavior patterns of target users based on historical behavior data and the functional influencing factors corresponding to the function to be optimized;

[0008] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0009] In one embodiment, based on the historical behavior data associated with the target user, determining the vehicle function to be optimized from the candidate vehicle functions includes:

[0010] Based on the historical behavior data associated with the target user, determine the functional keywords corresponding to the historical behavior data; based on the functional keywords corresponding to the historical behavior data, determine the usage frequency of each candidate vehicle function; based on the usage frequency of each candidate vehicle function, determine the vehicle function to be optimized.

[0011] In one embodiment, determining the user behavior pattern of the target user according to the historical behavior data and the function influencing factors corresponding to the function to be optimized includes:

[0012] According to the functional influencing factors corresponding to the functions to be optimized, feature extraction and processing are performed on the historical behavior data to obtain user behavior features corresponding to each functional influencing factor; according to the user behavior features corresponding to each functional influencing factor, the user behavior pattern of the target user is determined.

[0013] In one embodiment, the vehicle function to be optimized is optimized according to the user behavior pattern and the function configuration information of the vehicle function to be optimized to obtain the optimized target vehicle function, including:

[0014] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, a functional optimization plan for the vehicle function to be optimized is determined; based on the functional optimization plan and the vehicle function to be optimized, a virtual vehicle function model corresponding to the vehicle function to be optimized is constructed; according to the user behavior pattern and the virtual vehicle function model, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0015] In one embodiment, the vehicle function to be optimized is optimized according to the user behavior pattern and the virtual vehicle function model to obtain the optimized target vehicle function, including:

[0016] According to the user behavior pattern, the associated behavior data related to the target user is obtained from the standard behavior data; the associated behavior data is input into the virtual vehicle function model to obtain the function operation result; according to the function operation result and the function optimization plan, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0017] In one embodiment, the vehicle function to be optimized is optimized according to the function operation result and the function optimization plan to obtain the optimized target vehicle function, including:

[0018] When the function operation result is normal, the function optimization plan is adopted to optimize the vehicle function to be optimized, and the optimized target vehicle function is obtained; when the function operation result is abnormal operation, the function optimization plan is adjusted according to the abnormal operation parameters in the function operation result, and the adjusted function optimization plan is adopted to optimize the vehicle function to be optimized, and the optimized target vehicle function is obtained.

[0019] In a second aspect, the present application also provides a vehicle function optimization device, comprising:

[0020] A function determination module, used to determine the vehicle function to be optimized from various candidate vehicle functions based on the historical behavior data associated with the target user;

[0021] A pattern determination module is used to determine the user behavior pattern of the target user based on the historical behavior data and the function influencing factors corresponding to the function to be optimized;

[0022] The function optimization module is used to optimize the vehicle function to be optimized according to the user behavior pattern and the function configuration information of the vehicle function to be optimized, so as to obtain the optimized target vehicle function.

[0023] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0024] Determine the vehicle function to be optimized from among the candidate vehicle functions based on the historical behavior data associated with the target user;

[0025] Determine the user behavior patterns of target users based on historical behavior data and the functional influencing factors corresponding to the function to be optimized;

[0026] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0027] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0028] Determine the vehicle function to be optimized from among the candidate vehicle functions based on the historical behavior data associated with the target user;

[0029] Determine the user behavior patterns of target users based on historical behavior data and the functional influencing factors corresponding to the function to be optimized;

[0030] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0031] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0032] Determine the vehicle function to be optimized from among the candidate vehicle functions based on the historical behavior data associated with the target user;

[0033] Determine the user behavior patterns of target users based on historical behavior data and the functional influencing factors corresponding to the function to be optimized;

[0034] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0035] The above-mentioned vehicle function optimization method, device, equipment, storage medium and program product determine the vehicle function to be optimized from each candidate vehicle function according to the historical behavior data associated with the target user, and determine the user behavior pattern of the target user according to the historical behavior data and the functional influencing factors corresponding to the function to be optimized; then, according to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function. Compared with the related art, in which the vehicle function is adaptively optimized and adjusted by manually configuring the vehicle parameters, the above-mentioned method analyzes the user behavior pattern according to the historical behavior data and the functional influencing factors corresponding to the function to be optimized, and then optimizes the vehicle function to be optimized based on the user behavior pattern, which can improve the efficiency and reliability of vehicle function optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments of the present application or the related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 A schematic diagram of a process flow of a vehicle function optimization method in one embodiment;

[0038] Figure 2 A schematic diagram of a process for determining a vehicle function to be optimized in one embodiment;

[0039] Figure 3 A schematic diagram of a process for determining a user behavior pattern in one embodiment;

[0040] Figure 4 A schematic diagram of a process for determining a target vehicle function in one embodiment;

[0041] Figure 5 A schematic diagram of a process for determining a target vehicle function in another embodiment;

[0042] Figure 6 A schematic flow chart of a vehicle function optimization method in another embodiment;

[0043] Figure 7 A structural block diagram of a vehicle function optimization device in one embodiment;

[0044] Figure 8 It is a structural block diagram of a vehicle function optimization device in another embodiment;

[0045] Fig. 9 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] With the continuous development of intelligent vehicles, in order to ensure the driver's driving experience during the driving process, it is necessary to adaptively optimize and adjust the vehicle functions of the driver's vehicle.

[0048] The existing vehicle function optimization method generally optimizes the vehicle function adaptively by manually modifying the setting parameters. However, the existing vehicle function optimization method reduces the efficiency of vehicle function optimization by manually configuring vehicle parameters.

[0049] Based on this, in an exemplary embodiment, Figure 1 As shown, a vehicle function optimization method is provided, which is described by taking the method applied to a function optimization device as an example, and specifically includes the following steps:

[0050] S101, determining a vehicle function to be optimized from candidate vehicle functions according to historical behavior data associated with a target user.

[0051] Among them, the target user is any vehicle driving user; the historical behavior data is the behavior data generated by the target user when driving the vehicle, which can be the behavior data corresponding to the user's trigger operation on the corresponding screen of the vehicle terminal; the candidate vehicle functions are the various functions that the vehicle terminal can provide, such as seat adjustment function, navigation function and intelligent recommendation function, etc.; the vehicle function to be optimized is the vehicle function that needs to be optimized, for example, the function that can be used frequently by the target user.

[0052] Optionally, historical behavior data corresponding to the triggering operation of the target user on the corresponding screen of the vehicle terminal during the historical period can be obtained from the target vehicle driven by the target user according to the user identification information of the target user; then, the historical behavior data associated with the target user can be input into the trained function determination model, and the function determination model outputs the vehicle function to be optimized according to the historical behavior data and model parameters. The function determination model is trained using the sample behavior data corresponding to each candidate vehicle function.

[0053] It is understandable that in order to ensure the reliability of data acquisition, before collecting historical behavior data, data embedding processing can be performed in advance in each candidate vehicle function to obtain the historical behavior data of the target user in each candidate vehicle function within the historical period.

[0054] S102, determining the user behavior pattern of the target user according to the historical behavior data and the function influencing factors corresponding to the function to be optimized.

[0055] Among them, the function influencing factors are relevant factors that affect the operation of each candidate function. For example, the function influencing factors for the navigation function may include but are not limited to information such as the network conditions and vehicle model at the current location; the user behavior pattern is the behavior pattern of the target user when using the vehicle function.

[0056] Optionally, based on the functional influencing factors corresponding to the functions to be optimized, the behavioral data corresponding to the functional influencing factors in the historical behavioral data may be summarized; then, the summarized results may be subjected to feature extraction processing to determine the user behavior pattern of the target user.

[0057] S103, optimizing the vehicle function to be optimized according to the user behavior pattern and the function configuration information of the vehicle function to be optimized, and obtaining an optimized target vehicle function.

[0058] Among them, the functional configuration information is information related to the basic functional configuration; the target vehicle function is the vehicle function after the vehicle function to be optimized is optimized.

[0059] Optionally, based on the user behavior pattern of the user, a parameter adjustment method is determined within a parameter adjustment range corresponding to the functional configuration information of the vehicle function to be optimized; then, the vehicle function to be optimized is optimized using the parameter adjustment method to obtain an optimized target vehicle function.

[0060] In addition, in order to provide target users with a better driving experience, the associated functions corresponding to the optimized functions may be optimized based on user behavior patterns.

[0061] For example, for the vehicle battery usage function, the historical electricity usage behavior data of user A can be summarized and processed based on the remaining power of the target vehicle and the road environment, and it can be determined that the electricity usage behavior characteristics of user A are that when the road environment is stable and the remaining power is greater than 40%, electricity is used preferentially.

[0062] Furthermore, based on the battery configuration information corresponding to the vehicle battery usage function, the vehicle battery usage function can be set to automatically use electric energy for driving when the road environment is stable and the remaining power is greater than 40%; correspondingly, in order to ensure the normal operation of the vehicle, when the remaining power is about to be less than 40%, a nearby charging station can be automatically recommended to user A.

[0063] In the above vehicle function optimization method, the vehicle function to be optimized is determined from each candidate vehicle function according to the historical behavior data associated with the target user, and the user behavior pattern of the target user is determined according to the historical behavior data and the functional influencing factors corresponding to the function to be optimized; then, the vehicle function to be optimized is optimized according to the user behavior pattern and the functional configuration information of the vehicle function to be optimized to obtain the optimized target vehicle function. Compared with the related art, in which the vehicle function is adaptively optimized and adjusted by manually configuring the vehicle parameters, the above method analyzes the user behavior pattern according to the historical behavior data and the functional influencing factors corresponding to the function to be optimized, and then optimizes the vehicle function to be optimized based on the user behavior pattern, which can improve the efficiency and reliability of vehicle function optimization.

[0064] In order to ensure the accuracy of the determined vehicle function to be optimized, based on the above embodiment, in this embodiment, an optional method for determining the vehicle function to be optimized is provided, such as Figure 2 As shown, the specific steps include:

[0065] S201, determining functional keywords corresponding to the historical behavior data according to the historical behavior data associated with the target user.

[0066] Among them, the function keywords are keywords corresponding to the functions of each candidate vehicle.

[0067] Optionally, for any piece of historical behavior data associated with the target user, the historical behavior data may be input into a trained keyword determination model, and the keyword determination model outputs a functional keyword corresponding to the historical behavior data based on the historical behavior data and model parameters.

[0068] S202, determining the usage frequency of each candidate vehicle function according to the function keywords corresponding to the historical behavior data.

[0069] Optionally, the function keywords corresponding to each piece of historical behavior data may be aggregated to obtain a keyword aggregation result; then, based on the association between each function keyword and each candidate vehicle function, the usage frequency of each candidate vehicle function may be determined according to the keyword aggregation result.

[0070] S203: Determine the vehicle function to be optimized according to the usage frequency of each candidate vehicle function.

[0071] Optionally, the candidate vehicle functions may be sorted according to the frequency of use to obtain a function ranking order; then, the function at the front of the function ranking order may be used as the vehicle function to be optimized. For example, if two vehicle functions need to be optimized, the function at the second position in the function ranking order may be used as the vehicle function to be optimized.

[0072] In an embodiment of the present application, the usage frequency of each candidate vehicle function is determined based on the function keywords corresponding to the historical behavior data, and then the vehicle function to be optimized is determined, thereby ensuring the accuracy of the determination of the vehicle function to be optimized.

[0073] In order to ensure the accuracy of the user behavior pattern, based on the above embodiment, in this embodiment, an optional method for determining the user behavior pattern is provided, such as Figure 3 As shown, the specific steps include:

[0074] S301, performing feature extraction processing on historical behavior data according to the function influencing factors corresponding to the function to be optimized, and obtaining user behavior features corresponding to each function influencing factor.

[0075] Among them, user behavior characteristics are the behavior characteristics of target users under the influence of functional factors.

[0076] Optionally, for any function influencing factor corresponding to the function to be optimized, the behavior data corresponding to the function influencing factor can be extracted from the historical behavior data; then, the behavior data corresponding to the function influencing factor is input into a trained feature extraction model, and the feature extraction model outputs the user behavior features corresponding to the function influencing factor based on the behavior data corresponding to the function influencing factor and the model parameters.

[0077] For example, one of the influencing factors of the navigation function is lane congestion. Based on the lane congestion, the route selection behavior of user B under each lane congestion condition can be extracted from the historical behavior data of user B; then, based on the road selection behavior under each congestion condition in the route selection behavior of user B, it can be determined that the behavioral characteristics of user B are that, in the case of road congestion, the user prefers to travel on roads that take less time.

[0078] S302: Determine the user behavior pattern of the target user according to the user behavior characteristics corresponding to each functional influencing factor.

[0079] Optionally, the user behavior features corresponding to each functional influencing factor may be combined to obtain the user behavior pattern of the target user. Exemplarily, the user behavior features corresponding to each functional influencing factor may be combined according to the priority of each functional influencing factor to obtain the user behavior pattern of the target user.

[0080] In the embodiment of the present application, by determining the user behavior pattern of the target user according to the user behavior characteristics corresponding to each function influencing factor, the accuracy of the determination of the user behavior pattern can be ensured.

[0081] In order to ensure the rationality of the target vehicle function, based on the above embodiment, in this embodiment, an optional method for determining the target vehicle function is provided, such as Figure 4 As shown, the specific steps include:

[0082] S401, determining a function optimization scheme for the vehicle function to be optimized according to a user behavior pattern and function configuration information of the vehicle function to be optimized.

[0083] Among them, the function optimization plan is a plan for optimizing the function to be optimized.

[0084] Optionally, the initial adjustment method corresponding to each functional parameter in the vehicle function to be optimized can be determined based on the user behavior pattern; then, for the initial adjustment method corresponding to any functional parameter, it can be determined whether the initial adjustment method corresponding to the functional parameter is feasible based on the functional configuration information of the vehicle function to be optimized. If so, the initial adjustment method corresponding to the functional parameter is directly used as the parameter adjustment method in the functional optimization plan.

[0085] If not, the initial adjustment method corresponding to the function parameter is adjusted based on the function configuration information of the vehicle function to be optimized to obtain the parameter adjustment method in the function optimization solution.

[0086] S402: constructing a virtual vehicle function model corresponding to the vehicle function to be optimized based on the function optimization solution and the vehicle function to be optimized.

[0087] Among them, the virtual vehicle function model is a virtual model that can simulate the operation of the vehicle function to be optimized.

[0088] Optionally, based on the function optimization solution, you can perform simple modeling processing on the vehicle function to be optimized to obtain a virtual vehicle function model that can simulate the operation of the vehicle function to be optimized.

[0089] S403, optimizing the vehicle function to be optimized according to the user behavior pattern and the virtual vehicle function model to obtain an optimized target vehicle function.

[0090] Optionally, a virtual vehicle function model may be run based on user behavior patterns to obtain function operation feedback data; then, the actual vehicle function to be optimized may be optimized based on the function operation feedback data to obtain the optimized target vehicle function.

[0091] In the embodiment of the present application, the vehicle function to be optimized is optimized according to the user behavior pattern and the virtual vehicle function model to obtain the optimized target vehicle function, thereby ensuring the rationality of the target vehicle function.

[0092] In order to further ensure the rationality of the target vehicle function, based on the above embodiment, in this embodiment, another optional method for determining the target vehicle function is provided, such as Figure 5 As shown, the specific steps include:

[0093] S501, acquiring associated behavior data related to a target user from standard behavior data according to the user behavior pattern.

[0094] Among them, standard behavior data is the regular behavior data of users collected from other vehicles; and associated behavior data is behavior data that is highly relevant to the target user.

[0095] Optionally, the user behavior pattern may be used as an index to obtain associated behavior data related to the target user from the association relationship between the standard behavior data and the behavior pattern.

[0096] S502, inputting the associated behavior data into the virtual vehicle function model to obtain the function operation result.

[0097] Among them, the functional operation result is the functional operation result obtained by simulating the virtual vehicle functional model.

[0098] Optionally, the associated behavior data may be input into a virtual vehicle function model, and the virtual vehicle function model may be used to simulate the operation of the vehicle function under the associated behavior data, thereby obtaining the function operation result.

[0099] S503, optimizing the vehicle function to be optimized according to the function operation result and the function optimization plan to obtain the optimized target vehicle function.

[0100] Optionally, the feasibility of the function optimization scheme can be verified based on the function operation results, and the vehicle function to be optimized can be optimized according to the verification results to obtain the optimized target vehicle function.

[0101] Exemplarily, when the function operation result is normal operation, a function optimization plan is adopted to optimize the vehicle function to be optimized to obtain the optimized target vehicle function; when the function operation result is abnormal operation, the function optimization plan is adjusted according to the abnormal operation parameters in the function operation result, and the adjusted function optimization plan is adopted to optimize the vehicle function to be optimized to obtain the optimized target vehicle function.

[0102] Among them, the abnormal operating parameters are abnormal functional parameters that exist when the virtual vehicle function model is running.

[0103] Optionally, when the function operation result is normal, it is proved that the function optimization plan meets the operation requirements. Therefore, the function optimization plan can be directly adopted to optimize the vehicle function to be optimized and obtain the optimized target vehicle function.

[0104] When the function operation result is an abnormal operation, it proves that the function optimization plan does not meet the operation requirements. Therefore, it is necessary to extract the abnormal operation parameters from the function operation result; then, according to the parameter values ​​corresponding to the abnormal operation parameters, the function optimization plan is adjusted, and the adjusted function optimization plan is used to optimize the vehicle function to obtain the optimized target vehicle function.

[0105] In the embodiment of the present application, by using a virtual vehicle function model to simulate the vehicle function and determining the optimized target vehicle function according to the function operation result, the rationality of the target vehicle function can be ensured.

[0106] Figure 6 FIG. 2 is a flow chart of a vehicle function optimization method in another embodiment. Based on the above embodiment, this embodiment provides an optional example of a vehicle function optimization method. Figure 6 The specific implementation process is as follows:

[0107] S601, determining function keywords corresponding to the historical behavior data according to the historical behavior data associated with the target user.

[0108] S602, determining the usage frequency of each candidate vehicle function according to the function keywords corresponding to the historical behavior data.

[0109] S603: Determine the vehicle function to be optimized according to the usage frequency of each candidate vehicle function.

[0110] S604: Perform feature extraction processing on the historical behavior data according to the function influencing factors corresponding to the function to be optimized, and obtain user behavior features corresponding to each function influencing factor.

[0111] S605: Determine the user behavior pattern of the target user according to the user behavior characteristics corresponding to each functional influencing factor.

[0112] S606: Determine a function optimization solution for the vehicle function to be optimized based on the user behavior pattern and the function configuration information of the vehicle function to be optimized.

[0113] S607: Based on the function optimization scheme and the vehicle function to be optimized, a virtual vehicle function model corresponding to the vehicle function to be optimized is constructed.

[0114] S608, acquiring associated behavior data related to the target user from the standard behavior data according to the user behavior pattern.

[0115] S609, inputting the associated behavior data into the virtual vehicle function model to obtain the function operation result.

[0116] S610, optimizing the vehicle function to be optimized according to the function operation result and the function optimization plan to obtain the optimized target vehicle function.

[0117] Optionally, when the function operation result is normal operation, a function optimization plan is adopted to optimize the vehicle function to be optimized to obtain the optimized target vehicle function; when the function operation result is abnormal operation, the function optimization plan is adjusted according to the abnormal operation parameters in the function operation result, and the adjusted function optimization plan is adopted to optimize the vehicle function to be optimized to obtain the optimized target vehicle function.

[0118] The specific process of S601-S610 can refer to the description of the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0119] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0120] Based on the same inventive concept, the embodiment of the present application also provides a vehicle function optimization device for implementing the vehicle function optimization method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more vehicle function optimization device embodiments provided below can refer to the limitations of the vehicle function optimization method above, and will not be repeated here.

[0121] In an exemplary embodiment, Figure 7 As shown, a vehicle function optimization device 1 is provided, comprising: a function determination module 10, a mode determination module 20 and a function optimization module 30, wherein:

[0122] A function determination module 10, for determining a vehicle function to be optimized from among various candidate vehicle functions according to historical behavior data associated with a target user;

[0123] A pattern determination module 20, for determining a user behavior pattern of a target user based on historical behavior data and function influencing factors corresponding to the function to be optimized;

[0124] The function optimization module 30 is used to optimize the vehicle function to be optimized according to the user behavior pattern and the function configuration information of the vehicle function to be optimized, so as to obtain the optimized target vehicle function.

[0125] In an exemplary embodiment, the function determination module 10 is specifically configured to:

[0126] Based on the historical behavior data associated with the target user, determine the functional keywords corresponding to the historical behavior data; based on the functional keywords corresponding to the historical behavior data, determine the usage frequency of each candidate vehicle function; based on the usage frequency of each candidate vehicle function, determine the vehicle function to be optimized.

[0127] In an exemplary embodiment, the mode determination module 20 is specifically configured to:

[0128] According to the functional influencing factors corresponding to the functions to be optimized, feature extraction and processing are performed on the historical behavior data to obtain user behavior features corresponding to each functional influencing factor; according to the user behavior features corresponding to each functional influencing factor, the user behavior pattern of the target user is determined.

[0129] In an exemplary embodiment, Figure 8 As shown, the function optimization module 30 includes:

[0130] A solution determination unit 31, used to determine a function optimization solution for the vehicle function to be optimized according to the user behavior pattern and the function configuration information of the vehicle function to be optimized;

[0131] A model building unit 32, configured to build a virtual vehicle function model corresponding to the vehicle function to be optimized based on the function optimization scheme and the vehicle function to be optimized;

[0132] The function optimization unit 33 is used to optimize the vehicle function to be optimized according to the user behavior pattern and the virtual vehicle function model to obtain the optimized target vehicle function.

[0133] In an exemplary embodiment, the function optimization unit 33 is specifically used to:

[0134] According to the user behavior pattern, the associated behavior data related to the target user is obtained from the standard behavior data; the associated behavior data is input into the virtual vehicle function model to obtain the function operation result; according to the function operation result and the function optimization plan, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0135] In an exemplary embodiment, the function optimization unit 33 is further configured to:

[0136] When the function operation result is normal, the function optimization plan is adopted to optimize the vehicle function to be optimized, and the optimized target vehicle function is obtained; when the function operation result is abnormal operation, the function optimization plan is adjusted according to the abnormal operation parameters in the function operation result, and the adjusted function optimization plan is adopted to optimize the vehicle function to be optimized, and the optimized target vehicle function is obtained.

[0137] Each module in the above-mentioned vehicle function optimization device can be implemented in whole or in part by software, hardware or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0138] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Fig. 9 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, near field communication (Near Field Communication, NFC) or other technologies. When the computer program is executed by the processor, a vehicle function optimization method is realized. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0139] Those skilled in the art will understand that Fig. 9The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0140] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0141] Determine the vehicle function to be optimized from among the candidate vehicle functions based on the historical behavior data associated with the target user;

[0142] Determine the user behavior patterns of target users based on historical behavior data and the functional influencing factors corresponding to the function to be optimized;

[0143] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0144] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0145] Based on the historical behavior data associated with the target user, determine the functional keywords corresponding to the historical behavior data; based on the functional keywords corresponding to the historical behavior data, determine the usage frequency of each candidate vehicle function; based on the usage frequency of each candidate vehicle function, determine the vehicle function to be optimized.

[0146] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0147] According to the functional influencing factors corresponding to the functions to be optimized, feature extraction and processing are performed on the historical behavior data to obtain user behavior features corresponding to each functional influencing factor; according to the user behavior features corresponding to each functional influencing factor, the user behavior pattern of the target user is determined.

[0148] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0149] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, a functional optimization plan for the vehicle function to be optimized is determined; based on the functional optimization plan and the vehicle function to be optimized, a virtual vehicle function model corresponding to the vehicle function to be optimized is constructed; according to the user behavior pattern and the virtual vehicle function model, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0150] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0151] According to the user behavior pattern, the associated behavior data related to the target user is obtained from the standard behavior data; the associated behavior data is input into the virtual vehicle function model to obtain the function operation result; according to the function operation result and the function optimization plan, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0152] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0153] When the function operation result is normal, the function optimization plan is adopted to optimize the vehicle function to be optimized, and the optimized target vehicle function is obtained; when the function operation result is abnormal operation, the function optimization plan is adjusted according to the abnormal operation parameters in the function operation result, and the adjusted function optimization plan is adopted to optimize the vehicle function to be optimized, and the optimized target vehicle function is obtained.

[0154] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0155] Determine the vehicle function to be optimized from among the candidate vehicle functions based on the historical behavior data associated with the target user;

[0156] Determine the user behavior patterns of target users based on historical behavior data and the functional influencing factors corresponding to the function to be optimized;

[0157] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0158] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0159] Based on the historical behavior data associated with the target user, determine the functional keywords corresponding to the historical behavior data; based on the functional keywords corresponding to the historical behavior data, determine the usage frequency of each candidate vehicle function; based on the usage frequency of each candidate vehicle function, determine the vehicle function to be optimized.

[0160] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0161] According to the functional influencing factors corresponding to the functions to be optimized, feature extraction and processing are performed on the historical behavior data to obtain user behavior features corresponding to each functional influencing factor; according to the user behavior features corresponding to each functional influencing factor, the user behavior pattern of the target user is determined.

[0162] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0163] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, a functional optimization plan for the vehicle function to be optimized is determined; based on the functional optimization plan and the vehicle function to be optimized, a virtual vehicle function model corresponding to the vehicle function to be optimized is constructed; according to the user behavior pattern and the virtual vehicle function model, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0164] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0165] According to the user behavior pattern, the associated behavior data related to the target user is obtained from the standard behavior data; the associated behavior data is input into the virtual vehicle function model to obtain the function operation result; according to the function operation result and the function optimization plan, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0166] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0167] When the function operation result is normal, the function optimization plan is adopted to optimize the vehicle function to be optimized, and the optimized target vehicle function is obtained; when the function operation result is abnormal operation, the function optimization plan is adjusted according to the abnormal operation parameters in the function operation result, and the adjusted function optimization plan is adopted to optimize the vehicle function to be optimized, and the optimized target vehicle function is obtained.

[0168] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0169] Determine the vehicle function to be optimized from among the candidate vehicle functions based on the historical behavior data associated with the target user;

[0170] Determine the user behavior patterns of target users based on historical behavior data and the functional influencing factors corresponding to the function to be optimized;

[0171] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0172] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0173] Based on the historical behavior data associated with the target user, determine the functional keywords corresponding to the historical behavior data; based on the functional keywords corresponding to the historical behavior data, determine the usage frequency of each candidate vehicle function; based on the usage frequency of each candidate vehicle function, determine the vehicle function to be optimized.

[0174] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0175] According to the functional influencing factors corresponding to the functions to be optimized, feature extraction and processing are performed on the historical behavior data to obtain user behavior features corresponding to each functional influencing factor; according to the user behavior features corresponding to each functional influencing factor, the user behavior pattern of the target user is determined.

[0176] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0177] According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, a functional optimization plan for the vehicle function to be optimized is determined; based on the functional optimization plan and the vehicle function to be optimized, a virtual vehicle function model corresponding to the vehicle function to be optimized is constructed; according to the user behavior pattern and the virtual vehicle function model, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0178] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0179] According to the user behavior pattern, the associated behavior data related to the target user is obtained from the standard behavior data; the associated behavior data is input into the virtual vehicle function model to obtain the function operation result; according to the function operation result and the function optimization plan, the vehicle function to be optimized is optimized to obtain the optimized target vehicle function.

[0180] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0181] When the function operation result is normal, the function optimization plan is adopted to optimize the vehicle function to be optimized, and the optimized target vehicle function is obtained; when the function operation result is abnormal operation, the function optimization plan is adjusted according to the abnormal operation parameters in the function operation result, and the adjusted function optimization plan is adopted to optimize the vehicle function to be optimized, and the optimized target vehicle function is obtained.

[0182] It should be noted that the data involved in this application (including but not limited to historical behavior data, etc.) are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0183] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0184] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0185] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A vehicle function optimization method, characterized in that: The method comprises: Determine the vehicle function to be optimized from among the candidate vehicle functions based on the historical behavior data associated with the target user; Determining a user behavior pattern of the target user according to the historical behavior data and the function influencing factors corresponding to the function to be optimized; According to the user behavior pattern and the functional configuration information of the vehicle function to be optimized, the vehicle function to be optimized is optimized to obtain an optimized target vehicle function.

2. The method according to claim 1, characterized in that The step of determining the vehicle function to be optimized from each candidate vehicle function according to the historical behavior data associated with the target user includes: Determine, based on the historical behavior data associated with the target user, the function keywords corresponding to the historical behavior data; Determining the usage frequency of each candidate vehicle function according to the function keywords corresponding to the historical behavior data; The vehicle function to be optimized is determined based on the usage frequency of each candidate vehicle function.

3. The method according to claim 1, characterized in that The determining the user behavior pattern of the target user according to the historical behavior data and the function influencing factors corresponding to the function to be optimized includes: According to the function influencing factors corresponding to the function to be optimized, feature extraction processing is performed on the historical behavior data to obtain user behavior features corresponding to each function influencing factor; According to the user behavior characteristics corresponding to each functional influencing factor, the user behavior pattern of the target user is determined.

4. The method according to claim 1, characterized in that: The optimizing the vehicle function to be optimized according to the user behavior pattern and the function configuration information of the vehicle function to be optimized to obtain the optimized target vehicle function includes: Determining a function optimization scheme for the vehicle function to be optimized according to the user behavior pattern and the function configuration information of the vehicle function to be optimized; Based on the function optimization scheme and the vehicle function to be optimized, constructing a virtual vehicle function model corresponding to the vehicle function to be optimized; According to the user behavior pattern and the virtual vehicle function model, the vehicle function to be optimized is optimized to obtain an optimized target vehicle function.

5. The method according to claim 4, characterized in that The optimizing the vehicle function to be optimized according to the user behavior pattern and the virtual vehicle function model to obtain the optimized target vehicle function includes: According to the user behavior pattern, acquiring associated behavior data related to the target user from the standard behavior data; Inputting the associated behavior data into the virtual vehicle function model to obtain a function operation result; According to the function operation result and the function optimization plan, the vehicle function to be optimized is optimized to obtain an optimized target vehicle function.

6. The method according to claim 5, characterized in that The optimizing the vehicle function to be optimized according to the function operation result and the function optimization scheme to obtain the optimized target vehicle function includes: When the function operation result is normal, the function optimization scheme is adopted to optimize the vehicle function to be optimized to obtain an optimized target vehicle function; In the case where the function operation result is an abnormal operation, the function optimization scheme is adjusted according to the abnormal operation parameters in the function operation result, and the adjusted function optimization scheme is used to optimize the vehicle function to be optimized to obtain the optimized target vehicle function.

7. A vehicle function optimization device, characterized in that: The device comprises: A function determination module, used to determine the vehicle function to be optimized from various candidate vehicle functions based on the historical behavior data associated with the target user; A pattern determination module, used to determine the user behavior pattern of the target user according to the historical behavior data and the function influencing factors corresponding to the function to be optimized; The function optimization module is used to optimize the vehicle function to be optimized according to the user behavior pattern and the function configuration information of the vehicle function to be optimized to obtain the optimized target vehicle function.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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