User vehicle preference parameter configuration method and device, medium and vehicle

Abstract

The invention discloses a vehicle preference parameter configuration method and device of a user, a medium and a vehicle, and relates to the technical field of vehicle intelligent interaction.The scheme includes the steps that when it is monitored that a target user logs in a target vehicle through a target account, a face identifier of the target user is determined through face recognition; obtaining historical vehicle preference parameters associated with a first combination from historical vehicle preference parameters stored in the cloud platform based on the first combination formed by the target account, the face identifier and the vehicle type of the target vehicle; if the historical vehicle preference parameters are vehicle preference parameters corresponding to vehicles of different accounts and / or different vehicle models associated with the face identification, converting the historical vehicle preference parameters into vehicle preference parameters adapted to the target account and / or the vehicle model of the target vehicle; and configuring a current vehicle preference parameter of the target user in the target vehicle based on the converted vehicle preference parameter. Therefore, adaptive vehicle preference parameter configuration of different user dimensions is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle intelligent interaction, and in particular to a user vehicle preference parameter configuration method, device medium and vehicle. BACKGROUND

[0002] Generally, a user can log in an application (APP) account of a vehicle manufacturer corresponding to a target vehicle when using the target vehicle, and configure the user's vehicle preferences for the target vehicle, such as seat position, rearview mirror angle, air conditioning temperature, etc., by inputting vehicle preference parameters under the account. The traditional vehicle memory system will associate the vehicle preference parameters configured by the target user to the logged account.

[0003] Different users can log in different accounts on the target vehicle and correspondingly configure their own vehicle preference parameters for the target vehicle. Next time the user logs in the same account when using the target vehicle, the user can obtain the historical vehicle preference parameters associated under the account from the vehicle memory system of the target vehicle and reconfigure them to the vehicle.

[0004] However, when the user logs in the account on other vehicles, the user needs to reconfigure the vehicle preference parameters for the other vehicles on the other vehicles. Or, when the user logs in a new account on the target vehicle, the user also needs to reconfigure the vehicle preference parameters for the target vehicle on the target vehicle.

[0005] Therefore, the user needs to manually repeat the configuration operation of the vehicle preference parameters, and the frequent manual configuration operation reduces the operation efficiency of the user configuring the vehicle preference parameters, and easily causes security risks due to configuration forgetting or error configuration, which seriously affects the efficiency of the vehicle preference configuration and the user experience.

[0006] The existing vehicle memory system cannot meet the user's vehicle preference configuration demand in a complex scenario, and how to improve the efficiency of the user configuring the vehicle preference is a technical problem to be solved at present. SUMMARY

[0007] The purpose of the embodiments of the present application is to provide a user vehicle preference parameter configuration method, device medium and vehicle, so as to solve the problem of low efficiency of user vehicle preference configuration existing in the existing vehicle memory system.

[0008] In order to solve the above technical problems, the present specification is implemented as follows: In a first aspect, a user vehicle preference parameter configuration method is provided, comprising: When it is monitored that a target user logs in a target vehicle using a target account, determining a face identifier of the target user through face recognition; obtain, from historical vehicle preference parameters stored in the cloud platform, a historical vehicle preference parameter associated with a first combination of the target account, the face identifier, and a vehicle model of the target vehicle; If the historical vehicle preference parameter is a vehicle preference parameter corresponding to a different account associated with the face identifier and / or a vehicle of a different vehicle model, convert the historical vehicle preference parameter into a vehicle preference parameter adapted to the target account and / or the vehicle model of the target vehicle; configure the current vehicle preference parameter of the target user in the target vehicle based on the converted vehicle preference parameter.

[0009] In a second aspect, a vehicle preference parameter configuration apparatus for a user is provided, comprising: a determination module configured to determine a face identifier of a target user through face recognition when it is monitored that the target user logs in a target vehicle using a target account; an obtaining module configured to obtain, from historical vehicle preference parameters stored in the cloud platform, a historical vehicle preference parameter associated with a first combination of the target account, the face identifier, and a vehicle model of the target vehicle; a conversion module configured to convert the historical vehicle preference parameter into a vehicle preference parameter adapted to the target account and / or the vehicle model of the target vehicle if the historical vehicle preference parameter is a vehicle preference parameter corresponding to a different account associated with the face identifier and / or a vehicle of a different vehicle model; a configuration module configured to configure the current vehicle preference parameter of the target user in the target vehicle based on the converted vehicle preference parameter.

[0010] In a third aspect, a vehicle is provided, comprising a processor and a memory, wherein the memory stores programs or instructions executable on the processor, and the programs or instructions are executed by the processor to implement the steps of the method according to the first aspect.

[0011] In a fourth aspect, a readable storage medium is provided, wherein the readable storage medium stores programs or instructions, and the programs or instructions are executed by a processor to implement the steps of the method according to the first aspect.

[0012] The user vehicle preference parameter configuration scheme provided by the embodiment of the application is configured for different users recognized by the face recognition, a user dimension combination based on the face identification-target account-target vehicle model is constructed, and the combination is used to query the historical vehicle preference parameters that can be associated with the combination from a cloud platform that stores historical vehicle preference parameters of different user dimensions, including the vehicle preference parameters corresponding to any account and / or any vehicle model of the vehicle associated with the face identification. Even if the queried historical vehicle preference parameters are the vehicle preference parameters corresponding to different accounts and / or different vehicle models of the vehicle associated with the face identification, the accurate and adaptive automatic configuration of the user's preference parameters on different accounts and different vehicle models of the vehicle can be realized by converting the vehicle preference parameters into the vehicle preference parameters suitable for the target account and / or the target vehicle model, the accuracy and scene adaptability of the personalized vehicle function configuration recommendation of the user are improved, and the efficiency of the user's vehicle preference configuration is improved. BRIEF DESCRIPTION OF DRAWINGS

[0013] The accompanying drawings illustrated herein are used to provide a further understanding of the application, form a part of the application, and are used to explain the application and its specific embodiments, and do not constitute an improper limitation on the application. In the drawings: Figure 1 FIG. 1 is a flow diagram of a user vehicle preference parameter configuration method according to an embodiment of the application.

[0014] Figure 2 FIG. 3 is a structural block diagram of a user vehicle preference parameter configuration device according to an embodiment of the application.

[0015] Figure 3 FIG. 4 is a structural block diagram of a user vehicle according to another embodiment of the application. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, but not all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the application. The figure numbers in the application are only used to distinguish the steps in the solutions, and are not used to limit the execution order of the steps. The specific execution order is described in the description.

[0017] The user vehicle preference parameter configuration scheme embodiments of the application include a user vehicle preference parameter configuration method, a device medium and a vehicle. The embodiments will be described in detail below.

[0018] An embodiment of the application provides a user vehicle preference parameter configuration method, Figure 1FIG. 1 is a flowchart of a vehicle preference parameter configuration method of a user of an embodiment of the present application.

[0019] As shown in FIG. 1, the vehicle preference parameter configuration method of the embodiment includes the following steps S102 to S106. Figure 1

[0020] Step S102, when it is monitored that a target user logs in a target vehicle using a target account, the face identification of the target user is determined through face recognition.

[0021] The target user is the user currently using the target vehicle, and in the single-person mode, it usually refers to the driver, and in the multi-person mode, it can be the driver or a passenger other than the driver. The target account is a unique account bound to the user, for example, an application (APP) account of the vehicle manufacturer corresponding to the target vehicle, which can be associated and bound through the user's phone number or the account of other third-party platforms. The target account can be an account associated and bound by the target user's phone number or the account of other third-party platforms, and logged in and used by the target user on the target vehicle. It can also be that the target user logs in and uses the target vehicle using the application account of other users of the vehicle manufacturer, which is an account associated and bound by the phone number or the account of other third-party platforms corresponding to other users.

[0022] Regardless of the application scenario, in this step, when it is monitored that the target user logs in the target vehicle using the target account, the face identification of the target user needs to be determined through face recognition. The face identification refers to the identification corresponding to the face features of the target user, which is used to uniquely associate the face features. The face identification of different faces or different users is different, and the face identification is used to bind the identity of the target user. When it is monitored that there is an event of logging in the target vehicle using the target account, the face image of the user in the vehicle can be collected through the vehicle-mounted camera of the target vehicle, and the corresponding target user is identified based on image recognition technology.

[0023] Step S104, based on a first combination of the target account, the face identification, and the vehicle model of the target vehicle, a historical vehicle preference parameter associated with the first combination is obtained from the historical vehicle preference parameters stored in the cloud platform.

[0024] ​In the embodiment of the application, based on the face identification of the target user and other indicators, such as the target account used by the target user and / or the target vehicle logged in by the target account, a plurality of dimensions are superimposed to obtain a plurality of dimensions as search keywords. The cloud platform can obtain the historical vehicle preference parameters corresponding to the dimensions. The cloud platform is a unified management platform for different users, different application accounts and different vehicle models. It is used to store the face identification of different users, the vehicle opening function of different accounts and the structure of different vehicle models, and the historical vehicle preference parameters corresponding to the dimension or dimension combination. Here, the face identification, the vehicle opening function of the account and the structure of the vehicle model are collected by the cloud platform when the user registers in the cloud platform; the historical vehicle preference parameters are collected by the corresponding vehicle memory system, including indicators of multiple dimensions, and are synchronously uploaded to the cloud platform for storage.

[0025] The first combination of associated historical vehicle preference parameters can include vehicle preference data historically configured by the user using the target account on the target vehicle with the same face identification. The first combination of associated historical vehicle preference parameters can also include vehicle preference parameters corresponding to different accounts and / or different vehicle models associated with the same face identification, such as: vehicle preference data historically configured by the user using other accounts different from the target account on the target vehicle with the same face identification; or vehicle preference data historically configured by the user using other accounts different from the target account on other vehicles with different vehicle models from the target vehicle with the same face identification; or vehicle preference data historically configured by the user using the target account on other vehicles with different vehicle models from the target vehicle with the same face identification.

[0026] In one specific embodiment, the historical vehicle preference parameters include at least one of: account-related first vehicle preference parameters determined based on long-term preference behavior of the user using the corresponding account on the vehicle; face identification-related second vehicle preference parameters determined based on adjustment of the corresponding face identification of the user to the corresponding parameters of the vehicle; and vehicle model-related third vehicle preference parameters determined based on adjustment of the user to the inherent characteristic parameters of the vehicle corresponding to the vehicle model.

[0027] The first vehicle preference parameter related to the account is an application account bound to a user, such as the application account of the vehicle manufacturer as described above. The first vehicle preference parameter records the long-term personalized preferences of the corresponding user, which are determined based on the long-term preference behavior of the user on the corresponding vehicle. For example, the user's most preferred preferences are determined by collecting and statistically determining the vehicle parameters configured by the user under the account multiple times. Different scenarios can correspond to different vehicle preference parameters, including commonly used seat positions (such as a backrest angle of 105° and a seat height of 40 cm), air conditioner temperatures (such as 24℃ in summer and 22℃ in winter), steering wheel positions (adjustment of height and angle), media playlists, navigation frequently used destinations, driving assistance function opening preferences (such as lane keeping sensitivity, entering the driving assistance menu through the center control screen or the steering wheel button, and selecting the sensitivity level as high / medium / low), and the like.

[0028] The second vehicle preference parameter related to the face identification is based on the face bound user identity, and is obtained by collecting the biological characteristics and real-time state data of the corresponding identity user, including face recognition, body posture detection (such as height estimation to automatically adjust the height of the corresponding seat, steering wheel, and / or screen; whether to wear a seat belt to automatically remind and warn), hand operation habit (such as commonly used center control key area to automatically configure the functions frequently operated by the user in the center control area), voice tone preference (such as wake-up word response sensitivity to automatically configure the wake-up word sensitivity level adapted to the corresponding voice tone), and the like. The second vehicle preference parameter can be obtained by statistically collecting data collected by the vehicle-mounted camera, seat pressure sensor, microphone, and the like, and the user can adjust it manually or by voice.

[0029] The third vehicle preference parameter related to the vehicle model is based on the vehicle bound to the vehicle model, and records the inherent characteristic parameters or static parameters of the corresponding vehicle, including the vehicle model, seat adjustment stroke range, steering wheel angle range, air conditioner air duct layout, suspension adaptation mode (such as sport / comfort mode parameters), vehicle-mounted device interface type (such as USB-C power), and the like. The second vehicle preference parameter can be preconfigured when the vehicle is shipped, can be updated by over-the-air (OTA) technology, and can be adjusted by the user manually or by voice.

[0030] In the initial state, the third vehicle preference parameter related to the vehicle model of the target vehicle can be automatically written when the vehicle is shipped. In the initial state, the first vehicle preference parameter related to the account is written by configuring the vehicle personalized preferences of the user for the first time after logging in to the account. In the initial state, after the user enters the vehicle, the face recognition is completed by the camera, and the posture and operation habit data are collected to complete the real-time data storage of the second vehicle preference parameter related to the face identification of the user.

[0031] When the vehicle is started, the first vehicle preference parameter, the second vehicle preference parameter and the third vehicle preference parameter can be synchronized to the cloud platform as the historical vehicle preference parameter corresponding to the combination association of the face identification-account-vehicle model, and can be subsequently updated based on the adjustment of the corresponding user. The historical vehicle preference parameter stored in the cloud platform can be used for automatic and accurate recommendation for each registered user.

[0032] The various types of vehicle preference parameters described above can be recorded by the corresponding vehicle memory system and stored locally, and synchronized to the cloud platform for storage, thereby forming the corresponding associated historical vehicle preference parameter.

[0033] Step S106, if the historical vehicle preference parameter is the vehicle preference parameter corresponding to the different account and / or vehicle of different vehicle model associated with the face identification, the historical vehicle preference parameter is converted into the vehicle preference parameter adapted to the target account and / or the vehicle model of the target vehicle.

[0034] If the historical vehicle preference parameter corresponding to the first combination of the target account, the face identification and the vehicle model of the target vehicle can be obtained from the cloud platform, the historical vehicle preference parameter obtained by the user using the target account in the target vehicle can be directly and automatically configured to the target vehicle based on the historical vehicle preference parameter, and the current vehicle preference parameter of the target vehicle is obtained.

[0035] If the historical vehicle preference parameter obtained from the cloud platform based on the first combination is the vehicle preference parameter of different accounts and / or vehicles of different vehicle models associated with the face identification, it indicates that the user of the face identification does not store the vehicle preference parameter of the target account and / or the vehicle preference parameter of the vehicle model of the target vehicle in the cloud platform. At this time, the obtained historical vehicle preference data cannot be directly and automatically configured to the target vehicle, and needs to be converted into the vehicle preference parameter adapted to the target account and / or the vehicle model of the target vehicle.

[0036] Next, the conversion step of the associated historical vehicle preference parameter obtained by the first combination is described in combination with different embodiments.

[0037] In the first embodiment, the historical vehicle preference parameter is the historical vehicle preference parameter corresponding to the target account associated with the face identification in the first vehicle, and the vehicle model of the first vehicle is the same as the vehicle model of the target vehicle; the historical vehicle preference parameter is converted into the vehicle preference parameter adapted to the target account and / or the vehicle model of the target vehicle, which includes: using the historical vehicle preference parameter of the first vehicle as the vehicle preference parameter of the vehicle model of the target vehicle.

[0038] In this embodiment, the first combination includes the target account, the face identification of the target user, and the three-dimensional index of the model of the target vehicle, so that the corresponding historical vehicle preference parameters of the cloud platform can be queried based on the first combination, and the target account, the face identification of the target user, and the model of the target vehicle corresponding to the keyword are queried. Here, the target account, the face identification of the target user, and the model of the target vehicle all have corresponding historical vehicle preference data. Therefore, based on the unique face identification of the target user, the face identification of the target user under the target account in the historical preference data of the vehicle configuration of the same model of the vehicle can be located.

[0039] If the corresponding associated historical vehicle preference data is queried, it means that the target user has historically used the target account to log in to a first vehicle of the same model and has configured corresponding vehicle preference parameters on the first vehicle, including account-related first vehicle preference parameters, face identification-related second vehicle preference parameters, and / or model-related third vehicle preference parameters. The vehicle of the same model can be the target vehicle, or other vehicles with the same model as the target vehicle.

[0040] The first vehicle and the target vehicle have the same model, and usually the parts are also universal. Therefore, the historical vehicle preference parameters of the first vehicle obtained accurately match the three-dimensional indicators of the first combination, and correspondingly, based on the corresponding historical vehicle preference parameters of the first vehicle obtained, the current vehicle preference parameters of the target user in the target vehicle can be directly configured as the vehicle preference parameters of the target vehicle.

[0041] The multiple dimensions corresponding to the historical vehicle preference parameters obtained are completely consistent with the dimensions of the current first combination of the user, and therefore, based on the direct automatic configuration of the historical vehicle preference parameters, accurate recommendation and self-adaptive automatic configuration of the vehicle preference parameters of the user can be realized, the accuracy and scene adaptability of personalized vehicle function configuration recommendation of the user are improved, and the efficiency of vehicle preference configuration of the user is improved.

[0042] In this way, cross-vehicle use of the same model can be supported, such as the target user changing from the first vehicle to the target vehicle, automatically adapting the characteristics of the target vehicle based on the historical vehicle preference parameters of the first vehicle associated with the target account, and having strong scene adaptability, so as to accurately, automatically, and efficiently configure the vehicle preference parameters of the target user on the target vehicle.

[0043] In the second embodiment, the historical vehicle preference parameter is a historical vehicle preference parameter of the target account using the face identification of the target user in a second vehicle associated with the target account, and the second vehicle has a different vehicle model from the target vehicle; and converting the historical vehicle preference parameter into a vehicle preference parameter adapted to the target account and / or the vehicle model of the target vehicle includes: converting the historical vehicle preference parameter into a vehicle preference parameter adapted to the vehicle model of the target vehicle based on a component mapping relationship between the target vehicle and the second vehicle.

[0044] In this embodiment, the first combination includes the target account, the face identification of the target user, and the three-dimensional index of the vehicle model of the target vehicle, so that the corresponding historical vehicle preference parameter of the cloud platform can be queried based on the first combination, and the target account, the face identification of the target user, and the vehicle model of the target vehicle corresponding to the keyword are queried. The face identification of the target user is used under the target account to associate a plurality of vehicles of different vehicle models, and the vehicles of different vehicle models include the vehicle used by the target user based on the target account. Here, the vehicle model of the target vehicle is regarded as a new vehicle model used by the target user for the first time, and there is no corresponding historical vehicle preference data. Therefore, based on the unique face identification of the target user and the target account, the historical preference data configured by the face identification of the target user under the target account in the vehicles corresponding to different vehicle models can be located.

[0045] If the historical vehicle preference data corresponding to the second vehicle associated with the target account is queried, and the vehicle model of the second vehicle is different from the vehicle model of the target vehicle, it indicates that the target user has historically used the target account to log in to the second vehicle of a different vehicle model, and has configured corresponding vehicle preference parameters on the second vehicle, including the first vehicle preference parameter related to the account, the second vehicle preference parameter related to the face identification, and / or the third vehicle preference parameter related to the vehicle model.

[0046] The vehicle model of the second vehicle is different from the vehicle model of the target vehicle, and the component structure of the vehicle is different, so the historical vehicle preference parameter of the second vehicle obtained cannot accurately match the two-dimensional index of the first combination, i.e., the current vehicle preference parameter of the target user in the target vehicle cannot be directly configured based on the historical vehicle preference parameter of the second vehicle obtained.

[0047] In this embodiment, when the historical vehicle preference parameters associated with the first combination are obtained from the cloud platform, the cloud platform performs a component mapping between the different vehicle model and the vehicle model of the target vehicle based on the search results associated with the first combination. The historical preference parameters of the vehicle of the different vehicle model associated with the face identification are returned, and the component mapping relationship between the different vehicle model and the vehicle model of the target vehicle is carried in the historical vehicle preference parameters.

[0048] After the target vehicle receives the historical vehicle parameter data returned by the cloud platform, the historical vehicle preference parameters are first converted into vehicle preference parameters suitable for the structure of the target vehicle based on the component mapping relationship between the target vehicle and the second vehicle, i.e., converted into vehicle preference parameters suitable for the vehicle model of the target vehicle, and then the current vehicle preference parameters of the target user in the target vehicle are configured based on the converted vehicle preference parameters.

[0049] The vehicle components of different vehicle models, such as the interior space, the overall vehicle size, the seat backrest, the steering wheel, the rearview mirror, etc., are different in the application scenarios of vehicle preference parameter adjustment, and the corresponding component mapping relationship between different vehicle models needs to be performed on the user preference configuration, such as the seat backrest, the steering wheel, and the rearview mirror. The most common vehicle component mapping relationship is linear proportional mapping, which is suitable for simple scaling of size and position parameters.

[0050] Taking the seat backrest as an example, the seat front-to-back adjustment distance range of the compact car is located in 200-280 mm, and the seat front-to-back adjustment distance range of the medium-sized sport utility vehicle (SUV) is located in 230-310 mm. Therefore, according to the linear interpolation of the minimum value and the maximum value, the component mapping relationship between the two different vehicle models can be obtained, for example, y = 1.15x + 5, where x represents the seat front-to-back adjustment distance of the compact car, and y represents the seat front-to-back adjustment distance of the medium-sized SUV.

[0051] In the use of the user of the medium-sized SUV (target vehicle) based on the first combination to obtain the historical vehicle preference parameters associated with the cloud platform, the cloud platform performs a component mapping between the compact car (second vehicle) and the vehicle model of the medium-sized SUV based on the search results associated with the first combination for the face identification history using the same account in the historical vehicle preference parameters of the compact car, and obtains the component mapping relationship including the vehicle seat front-to-back adjustment. The historical vehicle preference parameters of the compact car associated with the face identification are returned, and the component mapping relationship between the compact car and the vehicle model of the medium-sized SUV is carried in the historical vehicle preference parameters.

[0052] After the target vehicle receives the historical vehicle parameter data returned by the cloud platform, first, based on the mapping relationship between the parts of the medium-sized SUV and the compact car, such as the seat adjustment distance, the seat adjustment distance of the compact car in the historical vehicle preference parameters is converted to the seat adjustment distance suitable for the structure of the medium-sized SUV, and then the seat adjustment distance of the target user in the medium-sized SUV is configured as the converted seat adjustment distance.

[0053] In this way, cross-model vehicle use is supported, such as when the target user changes from a second vehicle to a target vehicle. The characteristics of the target vehicle are automatically adapted based on the historical vehicle preference parameters of the second vehicle associated with the target account and the mapping relationship between the vehicle parts of different vehicle models, which has strong scene adaptability and can accurately, automatically and efficiently configure the vehicle preference parameters of the target user on the target vehicle.

[0054] In a third embodiment, the historical vehicle preference parameters are historical vehicle preference parameters corresponding to the first account associated with the face identification on the first vehicle, the first account is different from the target account, and the vehicle model of the first vehicle is the same as the vehicle model of the target vehicle; converting the historical vehicle preference parameters into vehicle preference parameters suitable for the vehicle model of the target account and / or the target vehicle includes: based on the similar vehicle opening functions in the vehicle opening functions associated with the first account and the target account, mapping the historical vehicle preference parameters to vehicle preference parameters suitable for the similar vehicle opening functions.

[0055] In this embodiment, the first combination includes the target account, the face identification of the target user, and the vehicle model of the target vehicle. Based on the first combination, the corresponding historical vehicle preference parameters of the cloud platform can be queried, and the keywords correspond to the target account, the face identification of the target user, and the vehicle model of the target vehicle. The face identification of the target user is associated with multiple different accounts, and each different account is bound to the face identification of the target user.

[0056] If the historical vehicle preference parameters obtained from the cloud platform based on the first combination are the vehicle preference parameters corresponding to the vehicles of different accounts associated with the face identification, it indicates that the user of the face identification does not store the vehicle preference parameters of the target account in the cloud platform. Here, the target account is considered as a new account used by the target user for the first time, and there is no corresponding historical vehicle preference data. Therefore, based on the unique face identification of the target user and the vehicle model of the target vehicle, different accounts can be located, such as the historical preference data configured by the target user's face identification in the same vehicle model, such as the first vehicle. The first vehicle of the same vehicle model includes the target vehicle or other vehicles.

[0057] If the corresponding associated historical vehicle preference data of the first vehicle under the different account is queried, it indicates that the target user has historically logged in the first vehicle of the same vehicle model using a different account and configured corresponding vehicle preference parameters on the first vehicle, including account-related first vehicle preference parameters, face identification-related second vehicle preference parameters and / or vehicle model-related third vehicle preference parameters.

[0058] The face identification of the target user is associated with multiple accounts different from the target account, and the accounts different from each other may need to be bound to different functions opened. Therefore, the historical vehicle preference parameters of the first vehicle obtained cannot accurately match the two-dimensional indicators of the first combination, i.e., the current vehicle preference parameters of the target user on the target vehicle cannot be directly configured based on the corresponding obtained historical vehicle preference parameters of the first vehicle.

[0059] In this embodiment, when the associated historical vehicle preference parameters are obtained from the cloud platform based on the first combination, the cloud platform performs a similarity comparison of vehicle opening functions between the different account and the target account when the face identification historical vehicle preference parameters of the same vehicle model are used by the different account. Using a content similarity algorithm, some vehicle opening functions of the first account are found to be similar to the logical functions of the target account, i.e., the vehicle opening functions similar to the first account in the target account are determined. The historical preference parameters of the vehicle of the different account associated with the face identification are returned, and the similar vehicle opening functions between the different account and the vehicle model of the target vehicle are carried in the historical vehicle preference parameters.

[0060] After the target vehicle receives the historical vehicle parameter data returned by the cloud platform, the current vehicle preference parameters of the target user on the target vehicle are configured based on the historical vehicle preference parameters of the first vehicle corresponding to the similar vehicle opening functions.

[0061] For example, the target account opens the "smart seat memory" function, e.g., including seat height, backrest angle, waist support strength, etc., and the first account opens the "driver personalized profile" function, e.g., including seat height, backrest angle, waist support strength, steering wheel tilt, air conditioning temperature, etc.

[0062] In the fourth embodiment, the historical vehicle preference parameter is the historical vehicle preference parameter of the first account associated with the face identification, the first account is different from the target account, and the model of the second vehicle is different from the model of the target vehicle; converting the historical vehicle preference parameter into a vehicle preference parameter adapted to the model of the target account and / or the target vehicle comprises: mapping the historical vehicle preference parameter into a first vehicle preference parameter adapted to a similar vehicle opening function based on the similar vehicle opening function in the vehicle opening function associated with the first account and the vehicle opening function associated with the target account; converting the historical vehicle preference parameter into a second vehicle preference parameter adapted to the target vehicle based on the mapping relationship between the parts of the target vehicle and the second vehicle; and converting the first vehicle preference parameter and the second vehicle preference parameter into a current vehicle preference parameter adapted to the target vehicle.

[0063] After receiving the historical vehicle parameter data returned by the cloud platform, the target vehicle configures the current vehicle preference parameter of the target user using the target account in the target vehicle based on the historical vehicle preference parameter corresponding to the similar vehicle opening function: seat height, backrest angle, and waist support strength.

[0064] In this way, cross-account use of the same user can be supported, such as the target user switching from the first account to log in to the first vehicle to log in to the target vehicle of the same model in the target account. According to the historical vehicle preference parameter of the first vehicle associated with the first account and the similar vehicle opening function of different accounts, the characteristics of the target vehicle are automatically adapted, the scene adaptation is strong, and the vehicle preference parameter of the target user can be precisely, automatically, and efficiently configured on the target vehicle.

[0065] In the fourth embodiment, the historical vehicle preference parameter is the historical vehicle preference parameter of the first account associated with the face identification, the first account is different from the target account, and the model of the second vehicle is different from the model of the target vehicle; converting the historical vehicle preference parameter into a vehicle preference parameter adapted to the model of the target account and / or the target vehicle comprises: mapping the historical vehicle preference parameter into a first vehicle preference parameter adapted to a similar vehicle opening function based on the similar vehicle opening function in the vehicle opening function associated with the first account and the vehicle opening function associated with the target account; converting the historical vehicle preference parameter into a second vehicle preference parameter adapted to the target vehicle based on the mapping relationship between the parts of the target vehicle and the second vehicle; and converting the first vehicle preference parameter and the second vehicle preference parameter into a current vehicle preference parameter adapted to the target vehicle.

[0066] In this embodiment, the first combination includes the target account, the face identification of the target user, and the three-dimensional index of the model of the target vehicle. Thus, based on the first combination, the corresponding historical vehicle preference parameters of the cloud platform can be queried, and the keywords corresponding to the face identification of the target user, the target account, and the model of the target vehicle can be queried. The face identification of the target user is associated with multiple different accounts, and the face identification of the target user is bound to different accounts. In addition, the face identification of the target user is associated with multiple vehicles of different models, and the face identification of the target user is bound to vehicles of different models.

[0067] If the historical vehicle preference parameters obtained from the cloud platform based on the first combination are the vehicle preference parameters associated with different accounts and different vehicle models for the face identification, it indicates that the user of the face identification does not store the vehicle preference parameters of the target account and the vehicle preference parameters of the target vehicle model in the cloud platform.

[0068] Here, the target account is considered as a new account first used by the target user, and there is no corresponding historical vehicle preference data. The target vehicle model is considered as a new vehicle model first used by the target user, and there is no corresponding historical vehicle preference data.

[0069] Therefore, based on the unique face identification of the target user, the historical preference data of the target user's face identification in the vehicle of a different model (for example, a second vehicle) configured under a different account (for example, a first account) from the target account can be located.

[0070] If the historical vehicle preference data of the second vehicle under the corresponding associated different account is queried, it indicates that the target user has historically used different accounts to log in to the second vehicle of a different model and has configured corresponding vehicle preference parameters on the second vehicle, including account-related first vehicle preference parameters, face identification-related second vehicle preference parameters, and / or vehicle model-related third vehicle preference parameters.

[0071] At this time, the obtained historical vehicle preference parameters cannot be directly and automatically configured to the target vehicle, and the obtained historical vehicle preference data needs to be converted into vehicle preference parameters suitable for the target account and the vehicle model of the target vehicle.

[0072] The multiple accounts associated with the face identification of the target user are different from the target account, and the accounts may be different in many functions that need to be opened and bound to the account. Therefore, the obtained historical vehicle preference parameters of the first vehicle cannot accurately match the first combination, that is, the current vehicle preference parameters of the target user on the target vehicle cannot be directly configured based on the corresponding obtained historical vehicle preference parameters of the first vehicle.

[0073] Correspondingly, the vehicle model of the vehicle associated with the face identification of the target user is different from the vehicle model of the target vehicle, and the structures of the vehicles are different, so that the obtained historical vehicle preference parameters of the second vehicle cannot accurately match the first combination, that is, the current vehicle preference parameters of the target user in the target vehicle cannot be directly configured based on the corresponding obtained historical vehicle preference parameters of the second vehicle.

[0074] In this embodiment, when the historical vehicle preference parameters associated with the first combination are obtained from the cloud platform based on the first combination, the cloud platform maps the components between the different vehicle models and the vehicle model of the target vehicle, and the similar vehicle opening functions between the different accounts and the target account when the historical vehicle preference parameters of the different vehicle models and the different accounts are used by the face identification history using different accounts.

[0075] The historical preference parameters of the vehicles of different vehicle models and the historical vehicle preference parameters of different accounts associated with the face identification are returned at the same time, and the component mapping relationship and the similar vehicle opening function are carried in the historical vehicle preference parameters.

[0076] After the target vehicle receives the historical vehicle parameter data returned by the cloud platform, the historical vehicle preference parameters corresponding to the different vehicle models can be first converted into vehicle preference parameters suitable for the structure of the target vehicle, that is, converted into the first vehicle preference parameters suitable for the vehicle model of the target vehicle, based on the component mapping relationship between the target vehicle and the second vehicle. Then, based on the similar vehicle opening functions in the target account and the first account, the historical vehicle preference parameters corresponding to the different accounts are converted into vehicle preference parameters suitable for the target account, that is, converted into the second vehicle preference parameters suitable for the vehicle opening function of the target account.

[0077] Finally, based on the second vehicle preference parameters corresponding to the similar vehicle opening functions and the first vehicle preference parameters corresponding to the component mapping relationship, the current vehicle preference parameters of the target user in the target vehicle are configured. For example, the intersection between the first vehicle preference parameters and the second vehicle preference parameters is used to configure the current vehicle preference parameters of the target user when logging in to the target vehicle using the target account.

[0078] In this way, the vehicle use of the same user across accounts and across vehicle models can be supported, the scene adaptability is strong, and the vehicle preference parameters of the target user can be accurately, automatically and efficiently configured on the target vehicle.

[0079] In one specific embodiment, after the current vehicle preference parameters of the target user in the target vehicle are configured based on the converted vehicle preference parameters, the current vehicle preference parameters are synchronized to the cloud platform for storage as the historical vehicle preference parameters associated with the first combination.

[0080] For the application scenario that the target user uses a new vehicle model for the first time and / or a new account (i.e., an application account of a vehicle manufacturer) with a face identifier, the current vehicle preference parameter can be configured based on the obtained historical vehicle preference parameter, and the face identifier is associated with the combination of the new vehicle model and / or the new account, and the current vehicle preference parameter is stored in the cloud platform as the historical vehicle preference parameter for subsequent vehicle preference parameter configuration of the target user, the target account and / or the target vehicle.

[0081] The cloud synchronization function realizes the synchronization and update of the vehicle preference parameter across accounts, vehicles and vehicle models, enriches the historical vehicle preference data stored in the cloud platform, and facilitates efficient management of user data and platform sharing.

[0082] Next, the vehicle preference parameter configuration method of the user of the present application will be described in conjunction with specific embodiments.

[0083] Currently, user A uses account A to log in to vehicle A corresponding to the vehicle model, and then needs to query user A from the cloud platform based on the face identifier, and then query vehicle A and account A associated with user A.

[0084] If the vehicle model of vehicle A and account A are both used by user A historically, the historical vehicle preference parameter of user A using account A on vehicle A, such as seat height, backrest angle, waist support strength, steering wheel inclination, air conditioning temperature, rearview mirror, etc., can be queried from the cloud platform. The historical vehicle preference parameter can be directly configured to vehicle A to achieve automatic and accurate recommendation for user A. Corresponding to the first embodiment described above.

[0085] If the vehicle model of vehicle A is used by user A for the first time, and the vehicle models of account A and vehicle B are both used by user A historically, the historical vehicle preference parameter of user A using account A on vehicle B can be queried from the cloud platform. Vehicle B and vehicle A have different vehicle models, and the historical vehicle preference parameter on vehicle B needs to be converted into the historical vehicle preference parameter suitable for vehicle A through the mapping relationship of the parts, such as seat height, backrest angle, waist support strength, steering wheel, rearview mirror, etc., and then configured to vehicle A to achieve automatic and accurate recommendation for user A. Corresponding to the second embodiment described above.

[0086] If account A is the first use of user A, the vehicle model of vehicle A and account B are used by user A, the historical vehicle preference parameters of user A using account B on vehicle A can be queried from the cloud platform. Account B is different from account A, the vehicle opening function corresponding to different accounts is different, then the vehicle opening function corresponding to account B needs to be mapped with the vehicle opening function corresponding to account A, find some vehicle opening functions on account B similar to the logical functions on account A, such as seat height, backrest angle, waist support strength, etc. Then the historical vehicle preference parameters corresponding to the similar vehicle opening functions are configured on vehicle A to realize the automatic and accurate recommendation of user A. Corresponding to the third embodiment.

[0087] If account A and the vehicle model of vehicle A are both used by user A for the first time, and account B and the vehicle model of vehicle B are both used by user A, the historical vehicle preference parameters of user A using account B on vehicle B can be queried from the cloud platform. User A uses a new account A and vehicle A, then find the historical vehicle preference parameters of user A on account B and vehicle B, and then get the historical vehicle preference parameters corresponding to the adaptive vehicle A through the mapping relationship of the same parts and the mapping relationship of the vehicle opening function, including the seat height, backrest angle, waist support strength, steering wheel inclination, air conditioning temperature, rearview mirror and the like described in the above embodiments, and configure them to vehicle A. Or, further push the historical vehicle preference parameters of each user of similar vehicles on vehicle A to ensure automatic and accurate recommendation of users while exploring new vehicle preferences of users. Corresponding to the fourth embodiment.

[0088] In one specific embodiment, the use scenarios of the target vehicle include a basic scenario corresponding to single driving of the target user, and an overlapping scenario corresponding to at least one of multi-person travel, cross-city driving and off-road driving. Different use scenarios correspond to different vehicle preference parameters. Configuring the current vehicle preference parameters of the target user in the target vehicle based on the converted vehicle preference parameters includes: assigning corresponding weights based on different use scenarios; if the use scenarios of the target vehicle include both the basic scenario and the overlapping scenario, configuring part of the current vehicle preference parameters of the target user in the target vehicle and part of the current vehicle preference parameters of the target user in the target vehicle corresponding to the overlapping scenario based on the historical vehicle preference parameters determined based on the weights corresponding to the basic scenario and the overlapping scenario.

[0089] The basic scenario is a scenario that will occur in different use scenarios of the vehicle. The target user is a single driver in the single driving scenario. The superimposed scenario is a scenario that is additionally combined with the use of the vehicle based on the single driving scenario of the target user as the driver. For example, the superimposed scenario corresponding to multi-person travel is understood as introducing other passengers into the vehicle based on the single driving scenario of the target user as the driver. The superimposed scenario corresponding to cross-city driving is understood as the vehicle traveling between different cities based on the single driving scenario of the target user as the driver. The superimposed scenario corresponding to off-road driving is understood as the vehicle driving off-road based on the single driving scenario of the target user as the driver. Of course, based on different use scenarios, other superimposed scenarios such as self-driving tours can also be included.

[0090] Different use scenarios correspond to different configured vehicle preference parameters.

[0091] For example, for the basic scenario, only a single user, i.e., the driver, exists. Therefore, based on the target user as the driver using the target account to log in to the target vehicle, the historical vehicle preference parameters are obtained from the cloud platform and the current vehicle preference parameters of the target user in the target vehicle are configured.

[0092] For use scenarios that simultaneously exist in the basic scenario and the superimposed scenario, in order to coordinate the driver and the special case of the other superimposed scenario, the corresponding weights of the basic scenario and the superimposed scenario can be allocated. The weights are used to coordinate the vehicle preference parameters applicable to the driver in the basic scenario and the vehicle preference parameters applicable to the special case in the superimposed scenario.

[0093] If multiple superimposed scenarios are additionally combined in the basic scenario, the weights of the basic scenario and the multiple superimposed scenarios are allocated respectively. The weights of the corresponding vehicle preference parameters are dynamically allocated according to the number and type of the superimposed scenarios.

[0094] For example, if only one type of basic scenario exists, the weight of the corresponding vehicle preference parameter is allocated as 100%, and the data in two dimensions is completely configured according to the historical vehicle preference parameters obtained by the driver.

[0095] If the basic scenario and one superimposed scenario exist simultaneously, the weight of the corresponding vehicle preference parameter is allocated as: the weight of the basic scenario is 60%+the weight of the superimposed scenario is 40%. If the basic scenario and two superimposed scenarios exist simultaneously, the weight of the corresponding vehicle preference parameter is allocated as: the weight of the basic scenario is 50%+the weight of the superimposed scenario 1 is 30%+the weight of the superimposed scenario 2 is 20%.

[0096] By combining the weights allocated for different use scenarios of the vehicle, the current vehicle preference parameter configuration of the corresponding vehicle can be performed, which can coordinate the special cases of the driver and other superimposed scenarios, and realize the automatic and accurate recommendation of the vehicle preference parameters of the user in the vehicle under the corresponding use scenario.

[0097] By setting the weight allocation strategy corresponding to different use scenarios, the influence of the vehicle preference parameters under each use scenario can be flexibly adjusted according to the specific scenario, and the reasonable participation of the vehicle preference parameters under each use scenario in decision-making can be ensured through dynamic proportional adjustment, which can avoid the excessive influence of single-dimensional data and ensure that the configuration result is close to the actual application demand, thereby improving the scientificity of the recommended configuration.

[0098] In addition to configuring the current vehicle preference parameters of the vehicle according to the historical vehicle preference parameters or the converted vehicle preference parameters obtained from the cloud platform, the real-time state of the vehicle can also be combined to automatically recommend and adjust the vehicle preference parameters, so as to achieve the vehicle preference state corresponding to the use scenario.

[0099] The following will be illustrated by combining the various use scenarios in Table 1.

[0100]

[0101] For example, in the embodiment of the above table, for the basic scenario, i.e., the driver uses the vehicle alone, the weight of the corresponding vehicle preference parameter is allocated as 100%. When the driver logs in to the vehicle using the account, the current vehicle preference parameter configuration is completely performed according to the historical vehicle preference data or the converted vehicle preference data of the driver obtained from the cloud platform.

[0102] For the basic scene superimposed with the multi-person travel scene, in addition to the driver, there are other passengers passing through, and the corresponding historical vehicle preference parameters can be obtained from the cloud platform by identifying the face identification of the driver, and the corresponding historical vehicle preference parameters can be obtained from the cloud platform by identifying the face identification of the target passenger. In the case of obtaining the historical vehicle preference parameters of two different users at the same time, the weights corresponding to the basic scene and the superimposed scene can be allocated according to the preset, for example, the weight of the basic scene is 60%, and the weight of the superimposed scene is 40%. The historical vehicle preference data (or converted vehicle preference parameters) corresponding to the driver is determined and configured in proportion to the weight 60%, and the historical vehicle preference data (or converted vehicle preference parameters) corresponding to the target passenger is determined and configured in proportion to the weight 40%. Specifically, the vehicle preference parameters of the driver are mainly configured with the vehicle functions related to the main driver, and the vehicle preference parameters of the target passenger are mainly configured with the vehicle functions related to the other non-main driver.

[0103] The vehicle functions related to the main driver directly affect the vehicle control and safety, for example, including steering wheel configuration, rearview mirror configuration, main driver seat backrest configuration, air conditioner temperature, etc. Taking the target passenger as the copilot as an example, the vehicle functions related to the non-main driver focus on the riding experience and entertainment, for example, including copilot seat configuration, copilot entertainment system, etc.

[0104] After obtaining the historical vehicle preference parameters of the driver and the copilot, the steering wheel, the rearview mirror, and the main driver seat backrest are configured according to the proportion of the corresponding weight of the historical vehicle preference data corresponding to the driver, and the seat backrest and the entertainment system are configured according to the proportion of the corresponding weight of the historical vehicle preference data corresponding to the copilot.

[0105] By configuring the main driver and non-main driver functions according to the vehicle preference data weight, the optimal personalized experience can be provided for passengers in different positions, while ensuring driving safety and system stability.

[0106] For the basic scene superimposed with off-road driving scene, the corresponding historical vehicle preference parameters can be obtained from the cloud platform by identifying the driver's face identification, and the historical preference parameters of the vehicle off-road scene used by the driver can be obtained from the cloud platform by identifying the off-road scene. In the case of obtaining two types of historical vehicle preference parameters, the corresponding weights of the basic scene and the superimposed scene are preset, for example, the weight of the basic scene is 70%, and the weight of the superimposed scene is 70%. The proportion of the weight 70% is determined from the historical vehicle preference data (or converted vehicle preference parameters) corresponding to the driver, and the proportion of the weight 30% is determined from the historical preference parameters (or converted vehicle preference parameters) of the vehicle off-road scene. Part of the vehicle preference data is configured. Specifically, the vehicle preference parameters of the driver are mainly configured with the vehicle functions related to the main driver, and the vehicle preference parameters of the off-road scene are mainly configured with the vehicle functions related to the off-road.

[0107] The vehicle functions related to the main driver directly affect the vehicle control and safety, for example, including steering wheel configuration, rearview mirror configuration, main driver seat backrest configuration, etc. The off-road related vehicle functions include air conditioning temperature, media audio, atmosphere lamp, volume setting of audio channel, sunshade curtain state, fragrance state, in-vehicle greeting, etc. in off-road scene.

[0108] After obtaining the historical vehicle preference parameters of the driver and the copilot, the steering wheel, rearview mirror, main driver seat backrest are configured according to the proportion of the corresponding weight of the historical vehicle preference data corresponding to the driver, and the air conditioning temperature, media audio, atmosphere lamp, volume setting of audio channel, sunshade curtain state, fragrance state and / or in-vehicle greeting are configured according to the proportion of the corresponding weight of the historical vehicle preference data corresponding to the off-road scene.

[0109] This weight allocation strategy ensures that in the off-road scene, the vehicle can provide sufficient safety control performance and provide the comfort of the driver in the off-road scene, achieving the best balance between safety and comfort.

[0110] Combining the corresponding allocation of weights in multiple use scenarios for vehicle preference parameter configuration when different scenes appear at the same time, the degree of personalization can be specifically higher, covering the user preferences of different functions in the "driving-comfort-entertainment" whole scene, and realizing the whole link personalization.

[0111] In addition, when the user manually adjusts the automatically configured vehicle preference parameters, the adjustment behavior can be automatically identified, the corresponding vehicle preference data is updated, and the adjustment scene is recorded for optimizing the subsequent recommendation logic. When the user manually adjusted parameters do not match, the optimal solution that can be implemented by the current vehicle can be automatically adjusted to ensure the executability of the recommendation result.

[0112] Output the corresponding configuration control instruction based on the finally determined current vehicle preference parameter. The instruction is sent to the corresponding components (seat motor, air conditioner controller, car machine navigation, and other modules corresponding to the vehicle preference parameter) of the current vehicle through the Controller Area Network (CAN) bus, and the corresponding adjustment is automatically performed.

[0113] Optionally, as shown in Figure 2 The embodiment of the application also provides a user's vehicle preference parameter configuration 1000, which comprises: The determining module 1200 is configured to determine a face identifier of the target user through face recognition when it is monitored that the target user logs in the target vehicle using the target account; The obtaining module 1400 is configured to obtain, from historical vehicle preference parameters stored in a cloud platform, a historical vehicle preference parameter associated with a first combination of the target account, the face identifier, and a vehicle model of the target vehicle; The conversion module 1600 is configured to convert the historical vehicle preference parameter into a vehicle preference parameter adapted to the target account and / or the vehicle model of the target vehicle if the historical vehicle preference parameter corresponds to a vehicle preference parameter of a vehicle of a different account associated with the face identifier and / or a different vehicle model; The configuration module 1800 is configured to configure the current vehicle preference parameter of the target user in the target vehicle based on the converted vehicle preference parameter.

[0114] Optionally, the historical vehicle preference parameter is a historical vehicle preference parameter corresponding to a first account associated with the face identifier in a first vehicle, the first account is different from the target account, and the vehicle model of the first vehicle is the same as the vehicle model of the target vehicle; The conversion module 1600 converts the historical vehicle preference parameter into a vehicle preference parameter adapted to the target account and / or the vehicle model of the target vehicle, comprising: Based on the similar vehicle opening function in the vehicle opening function associated with the first account and the vehicle opening function associated with the target account, the historical vehicle preference parameter is mapped into a vehicle preference parameter adapted to the similar vehicle opening function.

[0115] Optionally, the historical vehicle preference parameter is a historical vehicle preference parameter of a second vehicle associated with the face identifier using the target account, and the vehicle model of the second vehicle is different from the vehicle model of the target vehicle; The conversion module 1600 converts the historical vehicle preference parameter into a vehicle preference parameter adapted to the target account and / or the vehicle model of the target vehicle, comprising: The historical vehicle preference parameter is converted into a vehicle preference parameter adapted to the vehicle model of the target vehicle based on a part mapping relationship between the target vehicle and the second vehicle.

[0116] Optionally, the historical vehicle preference parameter is a historical vehicle preference parameter of a second vehicle associated with the face identification, the first account is different from the target account, and the vehicle model of the second vehicle is different from the vehicle model of the target vehicle. The conversion module 1600 converts the historical vehicle preference parameter into a vehicle preference parameter adapted to the target account and / or the vehicle model of the target vehicle, including: The historical vehicle preference parameter is mapped into a first vehicle preference parameter adapted to a similar vehicle opening function based on a similar vehicle opening function between the vehicle opening functions associated with the first account and the target account. The historical vehicle preference parameter is converted into a second vehicle preference parameter adapted to the target vehicle based on a part mapping relationship between the target vehicle and the second vehicle. The first vehicle preference parameter and the second vehicle preference parameter are converted into a current vehicle preference parameter adapted to the target vehicle.

[0117] Optionally, the historical vehicle preference parameter includes at least one of the following: An account-related first vehicle preference parameter determined based on long-term preference behavior of a user using a corresponding account on a vehicle; A face identification-related second vehicle preference parameter determined based on adjustment of a biological feature of a user corresponding to a face identification to a corresponding parameter of a vehicle; A vehicle model-related third vehicle preference parameter determined based on adjustment of a user of a vehicle corresponding to a vehicle model to an inherent characteristic parameter of the vehicle.

[0118] Optionally, further comprising a synchronization module (not shown in the figure) configured to synchronize the current vehicle preference parameter as a historical vehicle preference parameter of the first combination to the cloud platform for storage after configuring the current vehicle preference parameter of the target user on the target vehicle based on the converted vehicle preference parameter.

[0119] Optionally, the use scenarios of the target vehicle include a basic scenario corresponding to single driving of the target user and an overlapping scenario corresponding to at least one of multi-person travel, cross-city driving, and off-road driving, and different use scenarios correspond to different vehicle preference parameters. The configuration module 1800 configures the target user's current vehicle preference parameters in the target vehicle based on the converted vehicle preference parameters, including: corresponding weights are assigned based on different use scenarios; If the use scenario of the target vehicle includes a basic scenario and an overlay scenario at the same time, the converted vehicle preference parameters determined based on the weights corresponding to the basic scenario and the overlay scenario are used to configure part of the target user's current vehicle preference parameters in the target vehicle and part of the target user's current vehicle preference parameters in the target vehicle corresponding to the overlay scenario.

[0120] The user's vehicle preference parameter configuration device provided by the embodiments of the present specification can achieve Figure 1 The method embodiments achieve various processes, and to avoid repetition, details are not repeated here.

[0121] Optionally, as Figure 3 indicated, the present application also provides a vehicle 2000, including a processor 2400 and a memory 2200, the memory 2200 stores programs or instructions executable on the processor 2400, the programs or instructions are executed by the processor 2400 to implement various steps of the above-mentioned user's vehicle preference parameter configuration method embodiments, and achieve the same technical effects, to avoid repetition, details are not repeated here.

[0122] The present application also provides a readable storage medium, the readable storage medium stores programs or instructions, the programs or instructions are executed by the processor to implement various processes of any one of the above-mentioned user's vehicle preference parameter configuration method embodiments, and achieve the same technical effects, to avoid repetition, details are not repeated here. The readable storage medium includes a computer readable storage medium, such as a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk, etc.

[0123] The present application also provides a computer program product, which includes a non-transitory computer readable storage medium storing a computer program, the computer program is operable to cause a computer to execute to implement various processes of any one of the above-mentioned user's vehicle preference parameter configuration method embodiments, and achieve the same technical effects, to avoid repetition, details are not repeated here.

[0124] It should be noted that, in the present document, the terms "comprising", "comprising" or any other variant thereof are intended to cover non-exclusive inclusions, so that a process, method, article, or apparatus that includes a list of elements not only includes those elements, but also includes other elements not explicitly listed, or inherent to such a process, method, article, or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0125] From the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be realized by means of software and the necessary general hardware platform, of course, they can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a plurality of instructions for making a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) execute the methods described in various embodiments of the present application.

Claims

1. A method for configuring user vehicle preference parameters, characterized in that, include: When it is detected that a target user logs into a target vehicle using a target account, the facial identifier of the target user is determined through facial recognition; Based on the first combination consisting of the target account, the face identifier, and the vehicle model of the target vehicle, the historical vehicle preference parameters associated with the first combination are obtained from the historical vehicle preference parameters stored on the cloud platform. If the historical vehicle preference parameters are vehicle preference parameters corresponding to different accounts and / or different vehicle models associated with the face identifier, then the historical vehicle preference parameters are converted into vehicle preference parameters adapted to the target account and / or the target vehicle model. Configure the target user's current vehicle preference parameters for the target vehicle based on the converted vehicle preference parameters.

2. The method according to claim 1, characterized in that, The historical vehicle preference parameters are the historical vehicle preference parameters corresponding to the first account associated with the face identifier on the first vehicle. The first account is different from the target account, and the model of the first vehicle is the same as the model of the target vehicle. Converting the historical vehicle preference parameters into vehicle preference parameters adapted to the vehicle model of the target account and / or the target vehicle includes: Based on the vehicle activation functions associated with the first account that are similar to the vehicle activation functions associated with the target account, the historical vehicle preference parameters are mapped to vehicle preference parameters that are adapted to the similar vehicle activation functions.

3. The method according to claim 1, characterized in that, The historical vehicle preference parameter is the historical vehicle preference parameter of the second vehicle associated with the target account using the facial recognition, where the model of the second vehicle is different from that of the target vehicle; Converting the historical vehicle preference parameters into vehicle preference parameters adapted to the vehicle model of the target account and / or the target vehicle includes: Based on the component mapping relationship between the target vehicle and the second vehicle, the historical vehicle preference parameters are converted into vehicle preference parameters that are adapted to the model of the target vehicle.

4. The method according to claim 1, characterized in that, The historical vehicle preference parameters are the historical vehicle preference parameters of the first account associated with the face identifier in the second vehicle. The first account is different from the target account, and the vehicle model of the second vehicle is different from the vehicle model of the target vehicle. Converting the historical vehicle preference parameters into vehicle preference parameters adapted to the vehicle model of the target account and / or the target vehicle includes: Based on the vehicle activation functions associated with the first account that are similar to the vehicle activation functions associated with the target account, the historical vehicle preference parameters are mapped to first vehicle preference parameters that are adapted to the similar vehicle activation functions. Based on the component mapping relationship between the target vehicle and the second vehicle, the historical vehicle preference parameters are converted into second vehicle preference parameters adapted to the target vehicle; The first vehicle preference parameter and the second vehicle preference parameter are converted into current vehicle preference parameters adapted to the target vehicle.

5. The method according to claim 1, characterized in that, The historical vehicle preference parameters include at least one of the following: The first vehicle preference parameter related to the account is determined based on the long-term preference behavior of the user using the corresponding account on the vehicle. A second vehicle preference parameter related to a face identifier, wherein the second vehicle preference parameter is determined by adjusting the corresponding parameters of the vehicle based on the biometrics of the user with the corresponding face identifier; A third vehicle preference parameter related to the vehicle model, which is determined based on the adjustment of the inherent characteristic parameters of the vehicle by the user of the corresponding vehicle model.

6. The method according to claim 1, characterized in that, After configuring the target user's current vehicle preference parameters for the target vehicle based on the converted vehicle preference parameters, the method further includes: The current vehicle preference parameters are used as the historical vehicle preference parameters associated with the first combination and synchronized to the cloud platform for storage.

7. The method according to claim 1, characterized in that, The target vehicle's usage scenarios include basic scenarios corresponding to the target user driving alone, and superimposed scenarios corresponding to at least one of the following: multi-person travel, intercity driving, and off-road driving. Different usage scenarios correspond to different vehicle preference parameters. Configure the target user's current vehicle preference parameters for the target vehicle based on the converted vehicle preference parameters, including: Assign corresponding weights based on different usage scenarios; If the usage scenario of the target vehicle includes both a basic scenario and an overlay scenario, then based on the converted vehicle preference parameters determined by the weights assigned to the basic scenario and the overlay scenario, configure the target user's partial current vehicle preference parameters in the target vehicle and the partial current vehicle preference parameters of the overlay scenario in the target vehicle.

8. A user vehicle preference parameter configuration device, characterized in that, include: The determination module is used to determine the facial identifier of the target user through facial recognition when it is detected that the target user logs into the target vehicle using the target account; The acquisition module is used to acquire historical vehicle preference parameters associated with the first combination based on the target account, the face identifier, and the vehicle model of the target vehicle from historical vehicle preference parameters stored on the cloud platform. The conversion module is used to convert the historical vehicle preference parameters into vehicle preference parameters that are adapted to the target account and / or the target vehicle model if the historical vehicle preference parameters are vehicle preference parameters corresponding to different accounts and / or different vehicle models associated with the face identifier. The configuration module is used to configure the target user's current vehicle preference parameters in the target vehicle based on the converted vehicle preference parameters.

9. A vehicle, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the method as described in any one of claims 1-7.

10. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1-7.

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