Vehicle driving position adjusting method and system, electronic equipment, storage medium and vehicle

Abstract

The invention discloses a vehicle driving position adjusting method and system, electronic equipment, a storage medium and a vehicle. The method comprises the steps of obtaining face image data of a driver; performing face recognition according to the face image data to obtain a face recognition result; determining an expected adjustment mode according to the face recognition result; wherein the expected adjustment mode comprises local adjustment and cloud adjustment; when it is determined that the expected adjustment mode is local adjustment, a driving position expected parameter is determined according to the face recognition result and a local database, or when it is determined that the expected adjustment mode is cloud adjustment, a preset height parameter of a driver is obtained, and the driving position expected parameter is determined through the cloud database according to the preset height parameter; and performing parameter adjustment on the vehicle driving position according to the driving position expected parameter. According to the embodiment of the invention, the adjustment of the driving positions of different drivers can be customized, and the efficiency of adjusting the driving positions of the vehicle and the driving safety coefficient are improved. The method can be widely applied to the technical field of vehicle adjustment.

Description

Technical Field

[0001] The present application relates to the field of vehicle adjustment technology, and in particular to a vehicle driving position adjustment method, system, electronic device, storage medium and vehicle. Background Art

[0002] With the rapid development of the automobile industry, by adjusting the driving position of the vehicle, different drivers can have a comfortable and correct driving posture while improving the comfort and flexibility of operating the steering wheel and pedals. At present, the adjustment of the driving position of the vehicle is mainly divided into two categories: mechanical adjustment and electric adjustment. In the related technology, the driving position of the vehicle is mainly adjusted by electric adjustment. However, during the electric adjustment process, it is difficult to adjust the driving position accordingly for different drivers, and the driving position adjustment process is relatively cumbersome.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to propose a vehicle driving position adjustment method, system, electronic device, storage medium and vehicle, which can realize customized driving position adjustment for different drivers, effectively improving the efficiency of vehicle driving position adjustment and driving safety factor.

[0005] To achieve the above object, one aspect of an embodiment of the present application provides a method for adjusting a vehicle driving position, the method comprising the following steps:

[0006] Acquire facial image data of the driver;

[0007] Performing face recognition according to the face image data to obtain a face recognition result;

[0008] Determining a desired adjustment method according to the face recognition result; wherein the desired adjustment method includes local adjustment and cloud adjustment;

[0009] When it is determined that the desired adjustment mode is the local adjustment, the desired parameters of the driving position are determined according to the face recognition result and the local database, or, when it is determined that the desired adjustment mode is the cloud adjustment, the preset height parameters of the driver are obtained to determine the desired parameters of the driving position through the cloud database according to the preset height parameters;

[0010] The parameters of the vehicle driving position are adjusted according to the desired parameters of the driving position.

[0011] In some embodiments, determining the desired adjustment method according to the face recognition result includes:

[0012] When the face recognition result is recognition passed, determining that the desired adjustment mode is the local adjustment;

[0013] Alternatively, when the face recognition result is recognition failure, it is determined that the expected adjustment method is the cloud-based adjustment.

[0014] In some embodiments, determining the expected parameters of the driving position according to the face recognition result and the local database includes:

[0015] Determining the identity information of the driver according to the face recognition result;

[0016] The driving position memory data is extracted from the local database through the identity information to obtain the driving position expected parameters; wherein the driving position memory data corresponds to the identity information.

[0017] In some embodiments, before determining the expected parameters of the driving position according to the face recognition result and the local database, the method further includes:

[0018] Acquiring the driver's account information to log into the driving account according to the account information;

[0019] When it is determined that the driving account has logged in successfully, the local database is updated through preset cloud record data; wherein the preset cloud record data includes the driving position memory data stored in the cloud database corresponding to the driving account.

[0020] In some embodiments, the obtaining of the preset height parameter of the driver to determine the expected parameters of the driving position through a cloud database according to the preset height parameter includes:

[0021] Collecting preset position data through a preset infrared monitoring module; wherein the preset position data includes foot position data, knee position data, shoulder position data, hip position data and head position data;

[0022] Collecting the driver's weight data through a seat gravity module;

[0023] Analyze and calculate the preset position data, the face image data and the weight data to obtain preset body index data;

[0024] According to the preset body index data, target body index data are matched from the cloud database to determine the corresponding expected driving position parameters through the target body index data; wherein the expected driving position parameters include expected steering wheel parameters and expected seat parameters.

[0025] In some embodiments, the analyzing and calculating based on the preset position data, the face image data and the weight data to obtain the preset body index data includes:

[0026] Calculating preset arm data according to the shoulder position data;

[0027] Calculating preset height data according to the foot position data, the knee position data, the hip position data, and the head position data;

[0028] Analyze the facial image data to determine preset gender information;

[0029] The preset body index data is determined according to the preset arm data, the preset height data, the weight data and the preset gender information.

[0030] In some embodiments, the matching of the preset body index data from the cloud database to obtain target body index data, so as to determine the corresponding expected parameters of the driving position through the target body index data, includes:

[0031] Calculate indicator weight data according to the preset height data and the weight data;

[0032] The target body index data is obtained by matching from the cloud database according to the index weight data; wherein the target body index data includes the weight index of the driver in the cloud database whose distance from the index weight data is less than a preset distance threshold;

[0033] Obtain the desired parameters of the driving position corresponding to the target body index data.

[0034] In some embodiments, the step of adjusting the parameters of the vehicle driving position according to the expected parameters of the driving position includes:

[0035] Controlling an electric steering column controller to adjust a vehicle steering wheel according to the desired steering wheel parameters;

[0036] A seat adjustment controller is controlled to adjust the vehicle seat according to the seat desired parameters.

[0037] In some embodiments, after performing the analysis and calculation based on the preset position data, the face image data and the weight data to obtain the preset body index data, the method further includes:

[0038] Calculate the desired steering wheel adjustment data according to the preset arm data and the steering wheel position data;

[0039] The steering column adjustment parameters are calculated according to the desired steering wheel adjustment data; wherein the steering column adjustment parameters include a steering column adjustment angle and a steering column adjustment height.

[0040] In some embodiments, after performing the step of adjusting the parameters of the vehicle driving position according to the desired parameters of the driving position, the method further includes:

[0041] Acquiring driving position fine-tuning data of the driver;

[0042] The parameters of the vehicle driving position are adjusted according to the driving position fine-tuning data.

[0043] In some embodiments, after performing the step of adjusting the parameters of the vehicle driving position according to the driving position fine-tuning data, the method further includes:

[0044] updating the local database according to the driving position fine-tuning data;

[0045] The driving position fine-tuning data is sent to the cloud database to update the data of the cloud database.

[0046] To achieve the above-mentioned purpose, another aspect of the embodiment of the present application provides a vehicle driving position adjustment system, the system comprising:

[0047] The first module is used to obtain the facial image data of the driver;

[0048] The second module is used to perform face recognition based on the face image data to obtain a face recognition result;

[0049] A third module is used to determine a desired adjustment method according to the face recognition result; wherein the desired adjustment method includes local adjustment and cloud adjustment;

[0050] A fourth module is used for, when it is determined that the desired adjustment mode is the local adjustment, determining the desired parameters of the driving position according to the face recognition result and the local database, or, when it is determined that the desired adjustment mode is the cloud adjustment, obtaining the preset height parameter of the driver, so as to determine the desired parameters of the driving position through the cloud database according to the preset height parameter;

[0051] The fifth module is used to adjust the parameters of the vehicle driving position according to the expected parameters of the driving position.

[0052] To achieve the above objective, another aspect of an embodiment of the present application provides an electronic device, the electronic device comprising:

[0053] at least one processor;

[0054] at least one memory for storing at least one program;

[0055] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0056] To achieve the above objective, another aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0057] To achieve the above objectives, an embodiment of the present application further proposes a vehicle, which includes the above vehicle driving position adjustment system or electronic device.

[0058] The embodiments of the present application include at least the following beneficial effects: The present application provides a method, system, electronic device, storage medium and vehicle for adjusting the driving position of a vehicle. The scheme obtains the facial image data of the driver, performs facial recognition according to the facial image data, obtains the facial recognition result, and then determines the desired adjustment method according to the facial recognition result, including local adjustment and cloud adjustment. Accordingly, when it is determined that the desired adjustment method is local adjustment, the embodiment of the present invention determines the driving position expected parameters according to the facial recognition result and the local database. Alternatively, when it is determined that the desired adjustment method is cloud adjustment, the embodiment of the present invention obtains the preset height parameter of the driver, and determines the driving position expected parameters through the cloud database according to the preset height parameter. Finally, the example of the present invention adjusts the parameters of the vehicle driving position according to the determined driving position expected parameters to achieve vehicle driving position adjustment. It is easy to understand that the embodiment of the present invention can effectively call the corresponding driving position expected parameters from the local through facial recognition, and can also determine the corresponding driving position expected parameters through the cloud according to the obtained preset height parameters, thereby achieving customization of driving position adjustment for different drivers. In addition, the embodiment of the present invention determines the corresponding expected adjustment method through the face recognition result, and then determines the expected parameters of the driving seat through local adjustment or cloud adjustment. The method of adjusting the parameters of the vehicle driving position can effectively improve the efficiency of the vehicle driving position adjustment, so that the vehicle driving position adjustment result can be more suitable for the driver, thereby improving the driving safety factor. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 is a flow chart of a vehicle driving position adjustment method provided by an embodiment of the present invention;

[0060] Figure 2 is a flow chart of determining a desired adjustment method according to a face recognition result provided by an embodiment of the present invention;

[0061] Figure 3 is a flow chart of determining the expected parameters of the driving position according to the face recognition result and the local database provided by an embodiment of the present invention;

[0062] Figure 4 It is a flow chart of updating a local database by presetting cloud recorded data provided by an embodiment of the present invention;

[0063] Figure 5 It is a flow chart of obtaining a preset height parameter of a driver provided by an embodiment of the present invention, so as to determine the expected parameters of a driving position through a cloud database according to the preset height parameter;

[0064] Figure 6 It is a flow chart of obtaining preset body index data by analyzing and calculating preset position data, face image data and weight data provided by an embodiment of the present invention;

[0065] Figure 7 It is a flow chart of obtaining target body index data from a cloud database according to preset body index data, so as to determine corresponding driving position expected parameters through the target body index data, provided by an embodiment of the present invention;

[0066] Figure 8 is a flow chart of adjusting parameters of a vehicle driving position according to expected parameters of the driving position provided by an embodiment of the present invention;

[0067] Fig. 9 is a flow chart of calculating steering column adjustment parameters provided by an embodiment of the present invention;

[0068] Fig.10 is a flow chart of adjusting parameters of a vehicle driving position according to driving position fine-tuning data provided by an embodiment of the present invention;

[0069] Fig.11 It is a flow chart of updating data in a local database and a cloud database according to driving position fine-tuning data provided by an embodiment of the present invention;

[0070] Fig.12 is an overall flow chart of a vehicle driving position adjustment method provided by an embodiment of the present invention;

[0071] Fig.13 It is a schematic diagram of an architecture for determining the expected parameters of the driving position by analyzing and calling a module according to an embodiment of the present invention;

[0072] Fig.14 is a structural schematic diagram of a vehicle driving position adjustment system provided by an embodiment of the present invention;

[0073] Fig.15 It is a schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

[0075] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0076] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0077] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0078] Before describing the embodiments of the present application in detail, some nouns and terms involved in the embodiments of the present application are first described. The nouns and terms involved in the embodiments of the present application are subject to the following explanations.

[0079] Face recognition: It is a biometric identification technology that uses facial feature information to identify a person. It extracts key feature points or feature vectors from facial images and compares the extracted features with pre-stored facial features to obtain recognition results.

[0080] With the rapid development of the automobile industry, the steering wheel position is adjusted in height and angle through the steering column, which facilitates different drivers to have a comfortable and correct driving posture while keeping the driver's arms and legs at an appropriate distance from the steering wheel. Correct driving posture can reduce the driver's fatigue and improve the comfort and flexibility of manipulating the steering wheel and pedals. At present, the position adjustment of the steering wheel is divided into two categories: mechanical and electric. Mechanical adjustment is achieved by the mechanical steering column. The driver manually opens the handle, adjusts the steering wheel position, and then manually closes the handle to lock the steering mechanism to achieve steering wheel position adjustment. However, the mechanical adjustment of the steering wheel cannot achieve the steering wheel position function memory and welcome function. In the related art, the vehicle driving position is mainly adjusted by electric adjustment, but during the electric adjustment process, it is difficult to adjust the driving position for different drivers, and the driving position adjustment process is relatively cumbersome. For example, the electric adjustment method of the steering wheel includes adjustment buttons, adjustment rods, or steering wheel buttons and central control screen joint adjustment. The steering wheel position memory function is recorded by the steering column controller after the steering column position, and the steering wheel memory position is selected through the main driver's side door option button or the option button under the main driver's seat, and the adjustment process is relatively cumbersome.

[0081] In view of this, a method, system, electronic device, storage medium and vehicle for adjusting the driving position of a vehicle are provided in an embodiment of the present application. The scheme obtains facial image data of the driver to perform facial recognition based on the facial image data to obtain facial recognition results, and then determines the desired adjustment method based on the facial recognition results, including local adjustment and cloud adjustment. Accordingly, when it is determined that the desired adjustment method is local adjustment, the embodiment of the present invention determines the desired parameters of the driving position based on the facial recognition results and the local database. Alternatively, when it is determined that the desired adjustment method is cloud adjustment, the embodiment of the present invention obtains the preset height parameters of the driver to determine the desired parameters of the driving position through the cloud database based on the preset height parameters. Finally, the example of the present invention adjusts the parameters of the vehicle driving position according to the determined desired parameters of the driving position, so as to realize customized adjustment of the driving position for different drivers, effectively improving the efficiency of the vehicle driving position adjustment and the driving safety factor.

[0082] The vehicle driving position adjustment method provided in the embodiment of the present application relates to the field of vehicle adjustment technology. The vehicle driving position adjustment method provided in the embodiment of the present application can be applied to a terminal, can also be applied to a server, and can also be software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a vehicle-mounted terminal, etc., but is not limited to this; the server side can be configured as an independent physical server, or it can be configured as a server cluster or a distributed system composed of multiple physical servers, and can also be configured to provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms and other basic cloud computing services. The server can also be a node server in a blockchain network; the software can be an application that implements the vehicle driving position adjustment method, etc., but is not limited to the above forms.

[0083] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0084] It should be noted that in each specific implementation of the present application, when it comes to the need to perform relevant processing based on data related to user identity or characteristics such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of these data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0085] Figure 1 is an optional flow chart of the vehicle driving position adjustment method provided in an embodiment of the present application, Figure 1 The method may include but is not limited to steps S110 to S150.

[0086] Step S110: Acquire the driver's facial image data.

[0087] Step S120: performing face recognition according to the face image data to obtain a face recognition result.

[0088] Step S130: Determine the desired adjustment method according to the face recognition result, wherein the desired adjustment method includes local adjustment and cloud adjustment.

[0089] Step S140: When it is determined that the desired adjustment method is local adjustment, the desired parameters of the driving seat are determined according to the face recognition result and the local database; or, when it is determined that the desired adjustment method is cloud adjustment, the preset height parameters of the driver are obtained to determine the desired parameters of the driving seat through the cloud database according to the preset height parameters.

[0090] Step S150: adjusting the parameters of the vehicle driving position according to the expected parameters of the driving position.

[0091] During the working process of this specific embodiment, the embodiment of the present invention first obtains the facial image data of the driver to perform facial recognition based on the facial image data to obtain the facial recognition result. Specifically, after the driver gets on the car, the embodiment of the present invention obtains the facial image of the driver, that is, the facial image data, through a pre-set camera module, such as a facial recognition module on the steering wheel. Correspondingly, the embodiment of the present invention performs facial recognition on the facial image data to determine whether the identity information of the current driver is recognized and obtains the corresponding facial recognition result, such as successful recognition or failed recognition. Then, the embodiment of the present invention determines the desired adjustment method based on the facial recognition result. Specifically, the desired adjustment method in the embodiment of the present invention refers to the method of adjusting the driving position of the vehicle, including local adjustment and cloud adjustment. Among them, local adjustment refers to adjusting the driving position of the vehicle through a local database, and cloud adjustment refers to adjusting the driving position of the vehicle through a cloud database. Further, when it is determined that the expected adjustment mode is local adjustment, the embodiment of the present invention determines the expected parameters of the expected driving position according to the face recognition result and the local database, or, when it is determined that the expected adjustment mode is cloud adjustment, the embodiment of the present invention obtains the preset height parameter of the driver to determine the expected parameters of the driving position through the cloud database according to the preset height parameter. Specifically, when it is determined that the expected adjustment mode of the vehicle driving position is the local adjustment mode, the embodiment of the present invention determines the corresponding expected parameters of the driving position from the local database in combination with the face recognition result. Wherein, the expected parameters of the driving position refer to the target adjustment data of the vehicle driving position adjustment. Correspondingly, the local database in the embodiment of the present invention stores the vehicle driving position data of several different drivers. In addition, when it is determined that the expected adjustment mode is cloud adjustment, the embodiment of the present invention obtains the preset height parameter of the driver to determine the expected parameters of the driving position through the cloud database according to the preset height parameter. Wherein, the preset height parameter in the embodiment of the present invention refers to the height and weight data of the driver, and by obtaining the preset height parameter of the driver, the vehicle driving position data corresponding to the height and weight data that is closer to the driver is determined through the cloud database, and then the corresponding expected parameters of the driving position are obtained. Wherein, the cloud database in the embodiment of the present invention is obtained by big data construction. Finally, the embodiment of the present invention adjusts the parameters of the vehicle driving position according to the expected parameters of the driving position. Specifically, after determining the expected parameters of the driving position, the embodiment of the present invention adjusts the vehicle driving position, such as the seat and steering wheel position, according to the corresponding expected parameters of the driving position, so that the driving position adjustment of different drivers can be customized, so that the vehicle driving position can meet the needs of the corresponding drivers, effectively improving the efficiency of the vehicle driving position adjustment and the driving safety factor.

[0092] Combination Figure 1 , refer to Figure 2In some embodiments of the present invention, determining the desired adjustment method according to the face recognition result includes but is not limited to the following steps:

[0093] Step S210: When the face recognition result is recognition passed, it is determined that the desired adjustment method is local adjustment.

[0094] Step S220: When the face recognition result is recognition failure, determine that the desired adjustment method is cloud adjustment.

[0095] In this specific embodiment, the face recognition result includes recognition pass and recognition failure. Among them, when the face recognition result is recognition pass, the embodiment of the present invention determines that the expected adjustment mode is local adjustment, or when the face recognition result is recognition failure, the embodiment of the present invention determines that the expected adjustment mode is cloud adjustment. Specifically, recognition pass in the embodiment of the present invention refers to face recognition of the collected face image data, identifying the identity information of the driver, or matching the index identifier of the corresponding local database. Correspondingly, when the face recognition result is recognition pass, it means that the local database stores the driver's driving position historical data, and the vehicle driving position can be adjusted by calling the data of the local database, so the expected adjustment mode is determined to be local adjustment. Or, when the face recognition result is recognition failure, it means that the driver's identity information cannot be identified, or the index identifier of the local database cannot be matched, that is, the local database does not store the relevant driving position historical data of the driver. Therefore, the embodiment of the present invention determines that the expected adjustment mode is cloud adjustment, that is, the expected parameters of the driver's driving position are determined by the cloud database constructed by big data.

[0096] Reference Figure 3 In some embodiments of the present invention, determining the expected parameters of the driving position according to the face recognition result and the local database includes but is not limited to the following steps:

[0097] Step S310: Determine the driver's identity information based on the face recognition result.

[0098] Step S320: extracting the driver's seat memory data from the local database according to the identity information to obtain the driver's seat expected parameters, wherein the driver's seat memory data corresponds to the identity information.

[0099] In this specific embodiment, the embodiment of the present invention first determines the identity information of the driver according to the face recognition result, and then extracts the driving position incentive data from the local database through the identity information to obtain the driving position expected parameters. Specifically, the driving position memory data in the embodiment of the present invention refers to the driving position historical data of the relevant driver, such as the seat position, steering wheel position and other data set last time. Correspondingly, the driving position memory data stored in the local database in the embodiment of the present invention corresponds to the identity information, that is, each driver stores its corresponding driving position memory data. Among them, the embodiment of the present invention determines the identity information of the driver in the current vehicle driving position by face recognition. When the face recognition result is recognition through, that is, the identity information of the driver is recognized, it means that the driving position memory data of the driver is stored in the local database. At this time, the embodiment of the present invention extracts the corresponding driving position memory data from the local database as the driving position expected parameters of the current driver according to the recognized identity information. Among them, the driving position expected parameters in the embodiment of the present invention include seat expected parameters and steering wheel expected parameters.

[0100] Reference Figure 4 In some embodiments of the present invention, before determining the desired parameters of the driving position according to the face recognition result and the local database, the vehicle driving position adjustment method provided by the embodiment of the present invention further includes but is not limited to the following steps:

[0101] Step S410: Obtain the driver's account information to log in to the driving account according to the account information.

[0102] Step S420: When it is determined that the driver account has logged in successfully, the local database is updated through the preset cloud record data, wherein the preset cloud record data includes the driver position memory data stored in the cloud database corresponding to the driver account.

[0103] In this specific embodiment, the embodiment of the present invention obtains the driver's account information to log in the driving account according to the account information, and then when it is determined that the driving account login is successful, the local database is updated by the preset cloud record data. Specifically, before the embodiment of the present invention determines the expected parameters of the driving position according to the face recognition result mixed with the local database, the corresponding driving account is first logged in. It is easy to understand that when the driver changes the vehicle, the local database may not store the driving position data of the corresponding driver. Therefore, the embodiment of the present invention logs in the driving account of the corresponding driver to extract the corresponding preset cloud record data from the corresponding cloud database and update it to the local database, so that the corresponding driving position memory data can be called in the local database to adjust the vehicle driving position. Among them, the preset cloud record data in the embodiment of the present invention includes the driving position memory data stored in the cloud database corresponding to the driving account. For example, when the driver changes the vehicle, logs in his own account, and the steering wheel position memorized in the account will be logged in together with the account. The embodiment of the present invention uses facial recognition to call the steering wheel position of other vehicles of the same brand with one key, without the need to readjust it on the new car. At the same time, the embodiment of the present invention cancels the steering wheel position memory button, and can store multiple steering wheel position information, which is more flexible and changeable.

[0104] Reference Figure 5 In some embodiments of the present invention, obtaining the preset height parameters of the driver to determine the expected parameters of the driving position through the cloud database according to the preset height parameters includes but is not limited to the following steps:

[0105] Step S510: Collecting preset position data through a preset infrared monitoring module, wherein the preset position data includes foot position data, knee position data, shoulder position data, hip position data and head position data.

[0106] Step S520: Collecting the driver's weight data through the seat gravity module.

[0107] Step S530: Analyze and calculate the preset position data, face image data and weight data to obtain preset body index data.

[0108] Step S540: According to the preset body index data, target body index data is matched from the cloud database to determine the corresponding driving position expected parameters through the target body index data, wherein the driving position expected parameters include steering wheel expected parameters and seat expected parameters.

[0109] In this specific embodiment, the embodiment of the present invention first collects preset position data through a preset infrared monitoring module. Specifically, the preset position data in the embodiment of the present invention includes foot position data, knee position data, shoulder position data, hip position data and head position data. Correspondingly, after the face recognition of the driver fails, the embodiment of the present invention collects data on the foot position, knee position, shoulder position, hip position and head position of the driver in the driving position of the vehicle through the preset infrared monitoring module to obtain the corresponding preset position data. At the same time, the embodiment of the present invention collects the weight data of the driver through the seat gravity module. Specifically, the embodiment of the present invention is provided with a seat gravity module on the seat of the driving position of the vehicle, and when collecting the preset position data of the driver, the weight data of the driver is measured by the seat gravity module. Further, the embodiment of the present invention analyzes and calculates according to the preset position data, face image data and weight data to obtain preset body index data. Specifically, in the embodiment of the present invention, the relevant body indexes of the driver are estimated in combination with the preset position data, weight data and face image data obtained by measurement to obtain preset body index data. Among them, the preset body index data in the embodiment of the present invention refers to the body index data of the driver, such as height, weight estimation data, etc. Further, the embodiment of the present invention matches the target body index data from the cloud database according to the preset body index data, so as to determine the corresponding driving position expected parameters through the target body index data. Specifically, the cloud database of the embodiment of the present invention stores various body index data and driving position historical data corresponding to the corresponding body index data, that is, driving position memory data. Accordingly, the embodiment of the present invention first compares the preset body index data obtained by evaluation with the data in the cloud database to filter out the closest body index data and obtain the target body index data. Then, the embodiment of the present invention obtains the driving position expected parameters by calling the driving position memory data corresponding to the target body index data. Accordingly, the driving position expected parameters in the embodiment of the present invention include steering wheel expected parameters and seat expected parameters. Among them, the seat expected parameters refer to the position parameters of the driver's seat, such as front and rear position data, and the steering wheel expected parameters refer to the position parameters of the steering wheel, such as steering wheel angle, steering wheel height, etc.

[0110] Reference Figure 6 In some embodiments of the present invention, the preset body index data is obtained by analyzing and calculating the preset position data, face image data and weight data, including but not limited to the following steps:

[0111] Step S610: Calculate preset arm data according to the shoulder position data.

[0112] Step S620: Calculate the preset height data according to the foot position data, the knee position data, the hip position data and the head position data.

[0113] Step S630: Analyze the facial image data to determine preset gender information.

[0114] Step S640: Determine preset body index data according to preset arm data, preset height data, weight data and preset gender information.

[0115] In this specific embodiment, the embodiment of the present invention first calculates the preset arm data according to the shoulder position data. Specifically, the preset arm data in the embodiment of the present invention refers to the arm length and arm angle data of the driver. For example, the driver of the embodiment of the present invention grasps the steering wheel at 3 and 9 o'clock positions with both hands at the current steering wheel position. Then, the embodiment of the present invention determines the corresponding shoulder position data according to the infrared reflection through the shoulder infrared monitoring module, and then calculates the driver's upper arm length L1, the forearm length L2 and the current angle A of the upper arm and forearm, that is, the preset arm data is obtained. Further, the embodiment of the present invention calculates the preset height data according to the foot position data, the knee position data, the hip position data and the head position data. Specifically, the preset height data in the embodiment of the present invention refers to the height estimation data of the driver. Accordingly, the embodiment of the present invention estimates the height of the driver by combining the detected foot, knee, hip and head position data of the driver. For example, the embodiment of the present invention uses the head infrared monitoring module as the measurement reference, obtains the distance L3 from the plane of the main driving seat and the distance L4 from the top of the driver's head, and obtains the driver's upper torso height L5=L3-L4. At the same time, the embodiment of the present invention measures the coordinate points of the driver's hips, knees and feet through the foot and knee infrared detection modules, which are (y1, z1), (y2, z2), and (y2, z2), respectively, and uses the foot infrared monitoring module as the reference plane. Correspondingly, in the embodiment of the present invention, the driver's thigh length L6=((z1-z2)^2+(y1-y2)^2)^(1 / 2). At the same time, in the embodiment of the present invention, the driver's calf length L7=((z2-z3)^2+(y2-y3)^2)^(1 / 2). In summary, the embodiment of the present invention can calculate the driver's height as: L0=L5+L6+L7. Further, the embodiment of the present invention performs analysis based on the face image data to determine the preset gender information. Specifically, the preset gender information in the embodiment of the present invention refers to the gender of the driver, such as a male driver or a female driver. Accordingly, the embodiment of the present invention determines the gender of the driver in the vehicle cab by performing image analysis on the collected face image, so as to determine the expected parameters of the driving position in combination with the gender information of the driver. Finally, the embodiment of the present invention determines the preset body index data according to the preset arm data, preset height data, weight data and preset gender information. Specifically, the embodiment of the present invention uses the preset arm data, preset height data, weight data and preset gender information of the detected driver to profile the driver's body index, combines the multi-dimensional data for analysis, and determines the corresponding preset body index data, so as to match the target body index data similar to the driver from the cloud database, thereby improving the fit between the expected parameters of the driving position and the driver, and realizing customized adjustment of the driving position for different drivers.

[0116] Reference Figure 7In some embodiments of the present invention, the target body index data is obtained by matching the preset body index data from the cloud database, so as to determine the corresponding driving position expected parameters through the target body index data, including but not limited to the following steps:

[0117] Step S710: Calculate index weight data according to preset height data and weight data.

[0118] Step S720: Obtain target body index data from the cloud database according to the index weight data, wherein the target body index data includes the driver weight index in the cloud database whose distance from the index weight data is less than a preset distance threshold.

[0119] Step S730: Obtain the expected parameters of the driving position corresponding to the target body index data.

[0120] In this specific embodiment, the embodiment of the present invention first calculates the index weight data according to the preset height data and weight data, and matches the target body index data from the cloud database according to the index weight data, and then obtains the driving position expected parameters corresponding to the target body index data. Specifically, the index weight data in the embodiment of the present invention refers to the comprehensive index evaluation parameters of the driver, which are calculated by the preset height data and weight data of the driver. For example, in the embodiment of the present invention, the cloud database organizes data according to the height, weight, steering wheel height and angle of the driver, and the index weight data. Among them, the index weight data in the embodiment of the present invention = (preset height data (mm) * 3 + weight data (kg) * 4) / 7. Correspondingly, the target body index data in the embodiment of the present invention includes the driver weight index in the cloud database whose distance from the index weight data is less than the preset distance threshold. For example, after the embodiment of the present invention calculates the index weight data of the current driver, the closest driver weight index in the cloud database is selected as the target body index data, and the steering wheel position data and seat position data of the driver corresponding to the driver weight index are obtained to obtain the driving position expected parameters.

[0121] Reference Figure 8 In some embodiments of the present invention, the parameters of the vehicle driving position are adjusted according to the expected parameters of the driving position, including but not limited to the following steps:

[0122] Step S810: Controlling the electric steering column controller to adjust the vehicle steering wheel according to the desired parameters of the steering wheel.

[0123] Step S820: Control the seat adjustment controller to adjust the vehicle seat according to the desired seat parameters.

[0124] In this specific embodiment, the embodiment of the present invention first controls the electric steering column controller to adjust the vehicle steering wheel according to the desired parameters of the steering wheel, and controls the seat adjustment controller to adjust the vehicle seat according to the desired parameters of the seat. Specifically, the embodiment of the present invention controls the electric steering column controller and the seat adjustment controller respectively according to the determined desired parameters of the driving position, that is, the desired parameters of the steering wheel and the desired parameters of the seat, so as to adjust the height, angle and front and rear position of the seat, so that the steering wheel position and seat position of the vehicle driving position are adjusted to a position suitable for the driver, without relying on mechanical buttons to achieve steering wheel position memory, thereby improving the efficiency and accuracy of the vehicle driving position adjustment.

[0125] Reference Fig. 9 In some embodiments of the present invention, after performing analysis and calculation based on the preset position data, face image data and weight data to obtain the preset body index data, the vehicle driving position adjustment method provided by the embodiment of the present invention also includes but is not limited to:

[0126] Step S910: Calculate the desired steering wheel adjustment data based on the preset arm data and steering wheel position data.

[0127] Step S920: Calculate the steering column adjustment parameters according to the desired steering wheel adjustment data, wherein the steering column adjustment parameters include the steering column adjustment angle and the steering column adjustment height.

[0128] In this specific embodiment, the embodiment of the present invention first calculates the desired adjustment data of the steering wheel according to the preset arm data and the steering wheel position data, and then calculates the steering column adjustment parameters according to the desired adjustment data of the steering wheel. Specifically, the steering wheel position data in the embodiment of the present invention refers to the current vehicle steering wheel center position data. Correspondingly, the steering column adjustment parameters in the embodiment of the present invention refer to the data for adjusting the vehicle steering column, including the steering column adjustment angle and the steering column adjustment height. Exemplarily, after the embodiment of the present invention detects the driver's arm length L1, arm length L2 and the current angle A of the arm and arm according to the shoulder infrared monitoring module, the distance that the steering wheel needs to be adjusted in the y direction (i.e., in the front and rear direction of the vehicle) is Ly=|350-(L1^2+L2^2-2L1L2 / cosA)^(1 / 2)|. At the same time, the embodiment of the present invention subtracts the measured distance of the head from the infrared monitoring module from the height of the head infrared monitoring module to obtain the distance L8 of the driver's head from the reference plane. Similarly, the distance L9 between the driver's shoulder and the reference plane and the distance L10 between the current position of the steering wheel center and the foot infrared monitoring module can be calculated. The distance Lz=L10-L9 that the steering wheel needs to be adjusted in the z direction (i.e., the up and down direction). Next, the embodiment of the present invention calculates that the angle that the steering column needs to be adjusted is θ=arctan(Lz / Ly), and calculates that the corresponding height of the steering column needs to be adjusted is ρ=(Ly^2+Lz^2)^(1 / 2).

[0129] Reference Fig.10 In some embodiments of the present invention, after adjusting the parameters of the vehicle driving position according to the expected parameters of the driving position, the vehicle driving position adjustment method provided by the embodiment of the present invention further includes but is not limited to the following steps:

[0130] Step S1010: Acquire the driver's driving position fine-tuning data.

[0131] Step S1020: adjusting the parameters of the vehicle driving position according to the driving position fine-tuning data.

[0132] In this specific embodiment, after adjusting the parameters of the vehicle driving position according to the driving position expected parameters, the embodiment of the present invention further obtains the driving position fine-tuning data of the vehicle driver, so as to adjust the parameters of the vehicle driving position according to the driving position fine-tuning data. Specifically, the driving position fine-tuning data in the embodiment of the present invention refers to the manual adjustment parameters of the vehicle driving position by the driver. It is easy to understand that after the embodiment of the present invention adjusts the parameters of the vehicle driving position according to the driving position expected parameters, the current position of the vehicle driving position may not reach the optimal position. At this time, the driver can fine-tune the vehicle driving position to make the vehicle driving position more in line with the driver's needs. Accordingly, after obtaining the corresponding driving position fine-tuning data, the embodiment of the present invention performs a secondary adjustment on the vehicle driving position through the driving position fine-tuning data, thereby effectively improving the accuracy and comfort of the vehicle driving position adjustment.

[0133] Reference Fig.11 In some embodiments of the present invention, after the parameters of the vehicle driving position are adjusted according to the driving position fine-tuning data, the vehicle driving position adjustment method provided by the embodiment of the present invention further includes but is not limited to the following steps:

[0134] Step S1110: Update the local database according to the driving position fine-tuning data.

[0135] Step S1120: Send the driving position fine-tuning data to the cloud database to update the data in the cloud database.

[0136] In this specific embodiment, after the driver fine-tunes the parameters of the vehicle's driving position, the embodiment of the present invention also updates the local database and the cloud database according to the driving position fine-tuning data. Specifically, the embodiment of the present invention first updates the local data through the driving position fine-tuning data, that is, updates the driving position memory data of the corresponding driver recorded in the local database. In addition, when the driving position memory data of the corresponding driver does not exist in the local database, new driving position memory data is added and recorded. At the same time, the embodiment of the present invention sends the driving position fine-tuning data to the cloud database, and updates the corresponding driving position memory data in the cloud database through the driving position fine-tuning data, so that when the subsequent driver changes the vehicle, the latest driving position memory data can be obtained in time, thereby improving the reliability and accuracy of the vehicle driving position adjustment.

[0137] Next, in conjunction with a specific vehicle driving position adjustment scenario, the solution of the embodiment of the present invention is described in detail and explained:

[0138] For example, refer to Fig.12 and Fig.13 ,in, Fig.12 is an overall flow chart of the vehicle driving position adjustment method provided by an embodiment of the present invention, Fig.13 : is a schematic diagram of the architecture for determining the expected parameters of the driving position through the analysis and calling module provided by an embodiment of the present invention. Specifically, after the driver gets on the vehicle, the embodiment of the present invention first logs in the driver's account. Then, the embodiment of the present invention obtains the driver's facial image data to perform facial recognition through the facial recognition module. Correspondingly, when it is determined that the facial recognition is successful, that is, after the driver's identity information is identified, the corresponding steering wheel memory position data and seat memory position data are called to adjust the parameters of the vehicle's driving position. Conversely, when it is determined that the facial recognition fails, the embodiment of the present invention collects the driver's preset position data through the preset infrared monitoring module, and collects the driver's weight data through the seat gravity module, and sends it to the analysis and calling module to estimate the driver's height and weight, such as Fig.13 As shown. Accordingly, the embodiment of the present invention compares the estimated height and weight of the driver with the data in the cloud database to filter out the closest data, and calls the steering wheel position and seat position data corresponding to the closest height and weight to control the electric adjustment steering column controller and the seat adjustment controller to adjust the steering wheel and the seat. Then, the embodiment of the present invention obtains the driver's driving position fine-tuning data to fine-tune the current vehicle driving position. Finally, after completing the fine-tuning of the vehicle driving position, the embodiment of the present invention asks the driver whether to save the corresponding position memory data. When the driver confirms to save the corresponding position memory data, the embodiment of the present invention updates the local database and the cloud database according to the driving position fine-tuning data.

[0139] It is easy to understand that the embodiment of the present invention obtains the driver's facial features through the facial recognition module, and adjusts the correct and appropriate vehicle driving position parameters, such as the steering wheel position and the seat position, for different drivers recorded in the account in a fast comparison manner. There is no need to rely on mechanical buttons to achieve steering wheel position memory, and the operation is more convenient, and the number of steering wheel position memories is greater. At the same time, when replacing a new car, the embodiment of the present invention realizes the memory synchronization of the vehicle driving position parameters by logging into the account, and there is no need to adjust the relevant parameters of the vehicle driving position again and then enter them. After logging into the account, the memory position of the steering wheel and the seat can be directly obtained by facial recognition, which effectively improves the efficiency of adjusting the vehicle driving position. In addition, the embodiment of the present invention obtains the corresponding driver's physical data through measurement modules such as the facial recognition module, the foot infrared monitoring module, the knee infrared monitoring module, the head position sensor and the seat gravity module, calculates and infers the driver's height and weight, and compares the driver's height and weight with the driver's height and weight in the cloud data to call out the steering wheel position used by drivers of the same height and weight. The electric steering column controller and the seat controller jointly call out this position, and the driver makes fine adjustments, thereby achieving customized adjustment of the driving position for different drivers, effectively improving the efficiency of the vehicle's driving position adjustment and the driving safety factor. Accordingly, when the vehicle is used for the first time, the embodiment of the present invention can directly call the steering wheel and seat positions of drivers of the same gender, similar height and weight in the database after calculation by the detection module, and the driver only needs to make minor adjustments later, which is more comfortable, convenient and quick.

[0140] See also Fig.14 The embodiment of the present application further provides a vehicle driving position adjustment system, which can implement the above-mentioned vehicle driving position adjustment method, and the system includes:

[0141] The first module 1210 is used to obtain facial image data of the driver.

[0142] The second module 1220 is used to perform face recognition according to the face image data to obtain a face recognition result.

[0143] The third module 1230 is used to determine the desired adjustment method according to the face recognition result, wherein the desired adjustment method includes local adjustment and cloud adjustment.

[0144] The fourth module 1240 is used to determine the expected parameters of the driving seat according to the face recognition result and the local database when the expected adjustment method is determined to be local adjustment, or to obtain the preset height parameters of the driver when the expected adjustment method is determined to be cloud adjustment, so as to determine the expected parameters of the driving seat through the cloud database according to the preset height parameters.

[0145] The fifth module 1250 is used to adjust the parameters of the vehicle driving position according to the expected parameters of the driving position.

[0146] It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0147] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned vehicle driving position adjustment method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0148] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0149] See also Fig.15 , Fig.15 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0150] The processor 1310 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0151] The memory 1320 may be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1320 may store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 1320, and the processor 1310 is used to call and execute the vehicle driving position adjustment method of the embodiment of this application;

[0152] Input / output interface 1330, used to implement information input and output;

[0153] The communication interface 1340 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.);

[0154] bus 1350 , which transmits information between the various components of the device (e.g., processor 1310 , memory 1320 , input / output interface 1330 , and communication interface 1340 );

[0155] The processor 1310 , the memory 1320 , the input / output interface 1330 , and the communication interface 1340 are connected to each other in communication within the device via a bus 1350 .

[0156] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned vehicle driving position adjustment method is implemented.

[0157] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0158] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0159] To achieve the above objectives, an embodiment of the present application further proposes a vehicle, which includes the above vehicle driving position adjustment system or electronic device.

[0160] The embodiment of the present application also provides a vehicle, which includes the above-mentioned vehicle driving position adjustment system or the electric drive assembly of the electronic device. Specifically, the vehicle can be a private car, such as a sedan, SUV, MPV or pickup truck. The vehicle can also be an operating vehicle, such as a van, bus, small truck or large trailer. The vehicle can be a gasoline vehicle or a new energy vehicle. When the vehicle is a new energy vehicle, it can be a hybrid vehicle or a pure electric vehicle.

[0161] It can be understood that the contents of the above method embodiments are all applicable to the present vehicle embodiment, the functions specifically implemented by the present vehicle embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0162] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0163] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0164] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0165] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0166] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0167] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0168] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0169] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0170] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0171] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0172] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A method for adjusting a vehicle driving position, characterized in that: The method comprises the following steps: Acquire facial image data of the driver; Performing face recognition according to the face image data to obtain a face recognition result; Determining a desired adjustment method according to the face recognition result; wherein the desired adjustment method includes local adjustment and cloud adjustment; When it is determined that the desired adjustment mode is the local adjustment, the desired parameters of the driving position are determined according to the face recognition result and the local database, or, when it is determined that the desired adjustment mode is the cloud adjustment, the preset height parameters of the driver are obtained to determine the desired parameters of the driving position through the cloud database according to the preset height parameters; The parameters of the vehicle driving position are adjusted according to the desired parameters of the driving position.

2. The method according to claim 1, characterized in that: The determining of the desired adjustment method according to the face recognition result includes: When the face recognition result is recognition passed, determining that the desired adjustment mode is the local adjustment; Alternatively, when the face recognition result is recognition failure, it is determined that the expected adjustment method is the cloud-based adjustment.

3. The method according to claim 1, characterized in that The determining the expected parameters of the driving position according to the face recognition result and the local database includes: Determining the identity information of the driver according to the face recognition result; The driving position memory data is extracted from the local database through the identity information to obtain the driving position expected parameters; wherein the driving position memory data corresponds to the identity information.

4. The method according to claim 3, characterized in that: Before performing the step of determining the expected parameters of the driving position according to the face recognition result and the local database, the method further includes: Acquire the driver's account information to log in to the driving account according to the account information; When it is determined that the driving account has logged in successfully, the local database is updated through preset cloud record data; wherein the preset cloud record data includes the driving position memory data stored in the cloud database corresponding to the driving account.

5. The method according to claim 1, characterized in that The obtaining of the preset height parameter of the driver to determine the expected parameters of the driving position through a cloud database according to the preset height parameter includes: Collecting preset position data through a preset infrared monitoring module; wherein the preset position data includes foot position data, knee position data, shoulder position data, hip position data and head position data; Collecting the driver's weight data through a seat gravity module; Analyze and calculate the preset position data, the face image data and the weight data to obtain preset body index data; According to the preset body index data, target body index data are matched from the cloud database to determine the corresponding expected driving position parameters through the target body index data; wherein the expected driving position parameters include expected steering wheel parameters and expected seat parameters.

6. The method according to claim 5, characterized in that The step of analyzing and calculating the preset position data, the face image data and the weight data to obtain the preset body index data includes: Calculating preset arm data according to the shoulder position data; Calculating preset height data according to the foot position data, the knee position data, the hip position data, and the head position data; Analyze the facial image data to determine preset gender information; The preset body index data is determined according to the preset arm data, the preset height data, the weight data and the preset gender information.

7. The method according to claim 6, characterized in that The step of obtaining target body index data from the cloud database according to the preset body index data, so as to determine the corresponding expected parameters of the driving position through the target body index data, includes: Calculate indicator weight data according to the preset height data and the weight data; The target body index data is obtained by matching from the cloud database according to the index weight data; wherein the target body index data includes the weight index of the driver in the cloud database whose distance from the index weight data is less than a preset distance threshold; Obtain the desired parameters of the driving position corresponding to the target body index data.

8. The method according to claim 5, characterized in that The step of adjusting the parameters of the vehicle driving position according to the expected parameters of the driving position includes: Controlling an electric steering column controller to adjust a vehicle steering wheel according to the desired steering wheel parameters; A seat adjustment controller is controlled to adjust the vehicle seat according to the seat desired parameters.

9. The method according to claim 6, characterized in that After performing the analysis and calculation based on the preset position data, the face image data and the weight data to obtain the preset body index data, the method further includes: Calculate the desired steering wheel adjustment data according to the preset arm data and the steering wheel position data; The steering column adjustment parameters are calculated according to the desired steering wheel adjustment data; wherein the steering column adjustment parameters include a steering column adjustment angle and a steering column adjustment height.

10. The method according to claim 1, characterized in that After performing the step of adjusting the parameters of the vehicle driving position according to the expected parameters of the driving position, the method further includes: Acquiring driving position fine-tuning data of the driver; The parameters of the vehicle driving position are adjusted according to the driving position fine-tuning data.

11. The method according to claim 10, characterized in that After performing the step of adjusting the parameters of the vehicle driving position according to the driving position fine-tuning data, the method further includes: updating the local database according to the driving position fine-tuning data; The driving position fine-tuning data is sent to the cloud database to update the data of the cloud database.

12. A vehicle driving position adjustment system, characterized in that: The system comprises: The first module is used to obtain the facial image data of the driver; The second module is used to perform face recognition based on the face image data to obtain a face recognition result; A third module is used to determine a desired adjustment method according to the face recognition result; wherein the desired adjustment method includes local adjustment and cloud adjustment; A fourth module is used for, when it is determined that the desired adjustment mode is the local adjustment, determining the desired parameters of the driving position according to the face recognition result and the local database, or, when it is determined that the desired adjustment mode is the cloud adjustment, obtaining the preset height parameter of the driver, so as to determine the desired parameters of the driving position through the cloud database according to the preset height parameter; The fifth module is used to adjust the parameters of the vehicle driving position according to the expected parameters of the driving position.

13. An electronic device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 11.

14. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 11 is implemented.

15. A vehicle, characterized in that: The vehicle comprises the vehicle driving position adjustment system according to claim 12 or the electronic device according to claim 13.

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