Automobile seat adjusting method and device, electronic equipment, system, medium and program product

Abstract

The invention relates to an automobile seat adjusting method, device and system and electronic equipment, and relates to the technical field of automobile control, and the method in one embodiment comprises the steps that user body type data of a driver and a passenger are obtained; acquiring a first seat parameter matched with the user body type data, and adjusting an automobile seat based on the first seat parameter; when it is detected that the user sits on the automobile seat, pressure distribution data of the automobile seat are collected, pressure distribution characteristics of the pressure distribution data are extracted, and the comfort level corresponding to the pressure distribution characteristics is determined through a comfort level determination model determined through training; and the seat parameters are updated, and the automobile seat is adjusted until the comfort degree reaches the target comfort degree. By adopting the scheme of the embodiment, not only can the requirement based on the body type of the user be met, but also the comfort requirement of personalized pressure can be met.

Description

Technical Field

[0001] The present application relates to the field of automobile control technology, and in particular to a vehicle seat adjustment method, a vehicle seat adjustment device, an electronic device, a vehicle seat adjustment system, a computer-readable storage medium, and a computer program product. Background Art

[0002] With the booming development of the automotive industry, cars have become an important means of transportation for people's daily travel. Adjusting the car seat to a suitable position allows for a comfortable sitting posture, which greatly enhances the driving experience. In related art, when adjusting a car seat, after entering the cabin, the user usually needs to repeatedly adjust the seat height and angle to find a comfortable sitting position.

[0003] In order to avoid the tedious operation of frequent manual adjustments, related technologies have emerged that automatically adjust car seats when a user enters a vehicle based on pre-entered body information such as the user's height. However, this method is difficult to meet the user's personalized comfort needs. Summary of the Invention

[0004] Based on this, it is necessary to provide a car seat adjustment method, car seat adjustment device, car seat adjustment system, electronic device, computer-readable storage medium and computer program product that can improve comfort in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for adjusting a car seat, the method comprising:

[0006] Obtain the user's body shape data of the driver;

[0007] Obtaining seat parameters that match the user's body shape data and adjusting the car seat based on the seat parameters;

[0008] When it is detected that a user is sitting on the car seat, pressure distribution data of the car seat is collected, and pressure distribution features of the pressure distribution data are extracted, and a comfort level corresponding to the pressure distribution features is determined by a comfort level determination model determined by training;

[0009] The seat parameters are updated to obtain updated seat parameters, and the car seat is adjusted based on the updated seat parameters until the comfort corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat reaches the target comfort after the car seat is adjusted based on the updated seat parameters.

[0010] In some embodiments, obtaining seat parameters that match the user's body shape data includes:

[0011] Classify the user's body shape data using the trained body shape classification model to determine the user's body shape category corresponding to the user's body shape data;

[0012] From a database containing correspondences between body type categories and adjustment parameters, seat parameters matching the user's body type category are queried and obtained.

[0013] In some embodiments, obtaining seat parameters that match the user's body shape data includes:

[0014] Querying and obtaining target body shape data having the highest similarity to the user's body shape data from a database containing corresponding relationships between body shape data and adjustment parameters;

[0015] The seat parameters corresponding to the target body shape data are used as the first seat parameters that match the user body shape data.

[0016] In some embodiments, updating seat parameters to obtain updated seat parameters and adjusting the vehicle seat based on the updated seat parameters until a current comfort level corresponding to a pressure distribution characteristic of pressure distribution data of the vehicle seat reaches a target comfort level after the vehicle seat is adjusted based on the updated seat parameters includes:

[0017] Carry out a number of vehicle seat adjustment procedures, wherein during each adjustment procedure:

[0018] Updating the seat parameters of the last adjustment of the car seat with a preset step length to obtain updated seat parameters;

[0019] Adjusting the car seat based on the updated seat parameters, collecting pressure distribution data of the adjusted car seat, extracting pressure distribution characteristics of the pressure distribution data, and determining a comfort level corresponding to the pressure distribution characteristics using a comfort level determination model;

[0020] During multiple adjustments to the car seat, when the comfort level changes from an increasing trend to a decreasing trend, the maximum comfort level during the adjustment process is determined as the target comfort level, and the car seat is adjusted based on the seat parameters corresponding to the maximum comfort level.

[0021] In some embodiments, updating the seat parameters of the last adjustment of the car seat with a preset step size to obtain the updated seat parameters includes:

[0022] Obtaining a seat parameter range corresponding to the user's body shape data, where the seat parameter range includes seat parameters that match the user's body shape data;

[0023] Taking the seat parameter range as a constraint condition, the seat parameters of the last adjustment of the car seat are updated with a preset step size to obtain updated seat parameters.

[0024] In some embodiments, the method further comprises:

[0025] When a user has been sitting on the car seat for a continuous period greater than or equal to a first preset period, controlling a massager of the car seat to perform a massage operation;

[0026] After the first preset time is reached, the massager of the car seat is controlled to perform a massage operation at intervals of a second preset time, where the second preset time is shorter than the first preset time.

[0027] In some embodiments, controlling a massager of a car seat to perform a massage operation includes:

[0028] Collecting pressure distribution data of the car seat, and extracting the maximum pressure area and the maximum pressure gradient area based on the collected pressure distribution data;

[0029] A start instruction is sent to a massager of a car seat, where the start instruction is used to instruct to perform a massage operation on the seat area corresponding to the maximum pressure area and the maximum pressure gradient area.

[0030] In some embodiments, the method further comprises:

[0031] The correspondence between the user body shape data and the seat parameters corresponding to the target comfort level is stored in a database, or the correspondence between the user body shape category corresponding to the user body shape data and the seat parameters corresponding to the target comfort level is stored in a database.

[0032] In some embodiments, the method further comprises:

[0033] Acquire driving scene information, which includes road information and environmental information;

[0034] determining a driving scene mode based on the driving scene information;

[0035] The seat parameters are updated to obtain updated seat parameters, and the car seat is adjusted based on the updated seat parameters until the adjusted comfort is within the comfort range matching the driving scenario mode, wherein the adjusted comfort is the comfort corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat after the car seat is adjusted based on the updated seat parameters.

[0036] In some embodiments, the pressure distribution characteristics include: maximum pressure, average pressure, maximum pressure gradient, average pressure gradient, and asymmetry coefficient.

[0037] In some embodiments, the user's body shape data includes user torso parameters and limb parameters.

[0038] In some embodiments, the seat parameters include seat back parameters, seat cushion parameters, and leg rest parameters.

[0039] In some embodiments, updating the seat parameters to obtain updated seat parameters includes:

[0040] Obtain the comfort range corresponding to the driving scenario mode;

[0041] The car seat is adjusted with the comfort level corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat being within the comfort level range corresponding to the driving scene mode as an adjustment target.

[0042] In a second aspect, the present application also provides a vehicle seat adjustment device. The device comprises:

[0043] A body shape data acquisition module is used to acquire body shape data of the driver and passenger;

[0044] a first adjustment module, configured to obtain seat parameters matching the user's body shape data and adjust the car seat based on the seat parameters;

[0045] The second adjustment module is used to collect pressure distribution data of the car seat when it is detected that a user is sitting on the car seat, and extract the pressure distribution characteristics of the pressure distribution data, and determine the comfort corresponding to the pressure distribution characteristics through a comfort determination model determined by training; update the seat parameters to obtain updated seat parameters, and adjust the car seat based on the updated seat parameters until the comfort corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat reaches the target comfort after the car seat is adjusted based on the updated seat parameters.

[0046] In a third aspect, the present application further provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the vehicle seat adjustment method in any of the above embodiments when executing the computer program.

[0047] In a fourth aspect, the present application further provides a vehicle seat adjustment system, comprising a camera device, a pressure sensor disposed on the vehicle seat, and a controller communicatively connected to the camera device and the pressure sensor;

[0048] A camera device configured to capture images of a driver or passenger;

[0049] a pressure sensor configured to collect pressure distribution data of a car seat;

[0050] The controller is configured to obtain user body shape data based on the image and execute the steps of the car seat adjustment method in any of the above embodiments.

[0051] In a fifth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the vehicle seat adjustment method in any of the above-described embodiments.

[0052] In a sixth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, implements the steps of the vehicle seat adjustment method in any of the above embodiments.

[0053] The above-mentioned car seat adjustment method, car seat adjustment device, electronic device, car seat adjustment system, computer-readable storage medium and computer program product, after obtaining the user body shape data of the driving user, first obtains seat parameters matching the user body shape data to adjust the car seat, so as to make preliminary adjustments to the car seat. When it is further detected that there is a user sitting on the car seat, that is, after the user sits on the car seat, the pressure distribution data of the car seat is collected and the pressure distribution characteristics of the pressure distribution data are extracted. The corresponding comfort is determined by the comfort determination model, and then the seat parameters are further updated and the car seat is adjusted based on the target comfort. After the car seat is preliminarily adjusted based on the user body shape data to meet the riding requirements of the user body shape data, the pressure generated on the car seat after the user sits on the car seat is further adjusted based on the target comfort. This can not only meet the needs based on the user body shape, but also meet the personalized pressure comfort requirements of different users after sitting on the seat. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is a schematic diagram of an application environment of the car seat adjustment method in some embodiments;

[0055] Figure 2 is a schematic diagram of a configuration of a pressure sensor for a car seat in some embodiments;

[0056] Figure 3 is a flowchart of a method for adjusting a car seat according to some embodiments;

[0057] Figure 4 A schematic diagram of a process for obtaining first seat parameters in some embodiments;

[0058] Figure 5 A schematic diagram of a process for obtaining first seat parameters in some other embodiments;

[0059] Figure 6 Schematic diagram of the flow of car seat adjustment methods according to other embodiments;

[0060] Figure 7A schematic diagram of a process for adjusting a car seat in some embodiments;

[0061] Figure 8 Schematic diagram of the flow of car seat adjustment methods according to other embodiments;

[0062] Figure 9 A schematic diagram of a flow chart of controlling a car seat massager to perform a massage operation in some embodiments;

[0063] Figure 10 Schematic diagram of the flow of car seat adjustment methods according to other embodiments;

[0064] Figure 11 Schematic diagram of the flow of car seat adjustment methods according to other embodiments;

[0065] Figure 12 is a flowchart of a method for adjusting a car seat in a specific example;

[0066] Figure 13 FIG. 4 is a structural block diagram of a car seat adjustment device in one embodiment. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0068] The following embodiments of the technical solution of the present application will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application and are therefore only examples and are not intended to limit the scope of protection of the present application.

[0069] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0070] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0071] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0072] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0073] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0074] It should be noted that the information and data involved in this application (including but not limited to data for analysis, stored data, displayed data, etc.) are all information and data authorized by the user or fully authorized by all parties, and the acquisition, transmission, storage, use and processing of relevant data are in compliance with the relevant provisions of national laws and regulations. For content pushed to users (such as driving modes, etc.), users can refuse or easily refuse content push, etc. In the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0075] Currently, automated car seat adjustments typically require pre-entering the user's height and other body information, which is then automatically adjusted based on this information. However, research has found that even after adjusting the seat using pre-set seat parameters, users of similar body types often require further adjustments. This is because even users of similar or even identical body types can have different sitting postures and, consequently, different pressures applied to the car seat. This, combined with the relationship between action and reaction forces, can lead to varying levels of comfort. Therefore, after adjusting the car seat based on the user's body data, the user's comfort level can be assessed based on the pressure applied by the seat after sitting. Based on this comfort level, the car seat can be further adjusted to meet and enhance the user's individual comfort needs.

[0076] The solution provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, a car 1000 is provided with a car seat 10, a camera device 20 and a controller 30, a pressure sensor 101 is provided on the car seat 10, and the camera device 20, the pressure sensor 101 and the controller 30 are in communication connection.

[0077] Among them, the camera device 20 can be built into the car 1000, or it can be a device independent of the car 1000, as long as it can communicate with the controller 30 of the car 1000 to provide the captured image to the controller 30, or provide the user body shape data obtained by image analysis based on the captured image to the controller 1000.

[0078] The pressure sensor 101 is arranged at a position corresponding to the side of the car seat that can be contacted by the user. Figure 2 As shown, in some examples, the pressure sensor 101 may include at least one of a first pressure sensor 1011 and a second pressure sensor 1012. The first pressure sensor 1011 may be disposed on the seat back of the car seat, and the second pressure sensor 1012 may be disposed on the seat cushion of the car seat. In relevant embodiments of the present application, the pressure sensor 101 may include both the first pressure sensor 1011 and the second pressure sensor 1012 to more comprehensively and accurately obtain pressure data after the user sits on the car seat, thereby helping to improve the accuracy of car seat adjustment.

[0079] It is understood that the first pressure sensor 1011 can include multiple sensors and be distributed along the seat back of the automobile seat to simultaneously collect pressure from multiple locations on the seat back and obtain pressure distribution data on the seat back, thereby improving the comprehensiveness and accuracy of the pressure data obtained on the seat back. Similarly, the second pressure sensor 1012 also includes multiple sensors and is distributed along the seat cushion of the automobile seat to simultaneously collect pressure from multiple locations on the seat cushion and obtain pressure distribution data on the seat cushion, thereby improving the comprehensiveness and accuracy of the pressure data obtained on the seat cushion. The more sensors included in the first pressure sensor 1011 and the second pressure sensor 1012, the more pressure data collected, the more refined the distribution of the pressure data, and the more helpful it is to improve the accuracy of automobile seat adjustment.

[0080] The controller 30 can obtain user body shape data based on the images captured by the camera 20, determine seat parameters based on the user body shape data, and use the seat parameters to adjust the car seat. After the user sits in the car seat, the controller 30 can further update and adjust the seat parameters based on the pressure distribution data collected by the pressure sensor 101, and use the updated and adjusted seat parameters to adjust the car seat to further improve comfort.

[0081] Continue to refer Figure 1 As shown, a massager 102 may be further provided on the car seat 10 . The massager 102 is connected to the controller 30 . The controller 30 may control the massager 102 to perform a massage operation to further improve the comfort of the car seat.

[0082] It is understandable that the car seat can also be provided with adjustment components and corresponding driving components for adjusting the seat parameters of the car seat, as well as driving components for controlling the massager to perform massage operations. The specific implementation methods of these components are not specifically limited in the embodiments of the present application.

[0083] Based on this, if Figure 3 As shown, some embodiments of the present application provide a method for adjusting a car seat, which is applied to Figure 1 The controller 30 in FIG. 1 is used as an example to illustrate that the controller 30 includes at least the following steps S301 to S304.

[0084] Step S301: Obtaining the body shape data of the driver.

[0085] User body shape data refers to data related to the user's body shape, including but not limited to height, user torso parameters (such as torso length), limb parameters (such as forearm length), etc.

[0086] There is no limitation on the method of obtaining the user's body shape data. In some examples, the user's body shape data can be obtained by capturing an image with a camera and performing image analysis on the image.

[0087] The camera device 20 can be installed at a location such as a door interior panel, and when the door is detected to be open, the camera device captures the image to obtain an image. In some examples, when the door is opened, a door opening signal is triggered to be sent to the controller 30. After receiving the door opening signal, the controller 30 sends a capture instruction to the camera device 20 corresponding to the door receiving the door opening signal. The camera device 20 captures the image based on the capture instruction. In other examples, when the door is opened, a capture instruction is triggered to be sent to the camera device 20 at the corresponding location of the door. The camera device 20 captures the image based on the capture instruction.

[0088] After the camera device 20 captures and obtains an image, the camera device 20 may perform image analysis on the image to obtain the user's body shape data, and then send the obtained user's body shape data to the controller 30. In other examples, after the camera device 20 captures and obtains an image, the camera device 20 may send the image to the controller 30, and the controller 30 may perform image analysis on the image to obtain the user's body shape data. In other examples, after the camera device 20 captures and obtains an image, the camera device 20 may send the image to an image processing module, and the image processing module may perform image analysis on the image to obtain the user's body shape data, and then provide the obtained user's body shape data to the controller 30. The image processing module may be a processing module integrated in the controller 30, or may be an independent processing module or processing chip, and the embodiments of the present application do not specifically limit this.

[0089] Step S302: Acquire seat parameters that match the user's body shape data, and adjust the car seat based on the seat parameters.

[0090] The seat parameters that match the user's body shape data are the seat parameters for adjusting the car seat determined based on the user's body shape data. The specific parameter types of the seat parameters are not limited, and include but are not limited to seat back parameters, seat cushion parameters, and leg support parameters, such as backrest angle, seat cushion angle, and leg support angle.

[0091] There are various ways to obtain seat parameters that match the user's body shape data. The following only uses two of these ways as examples.

[0092] refer to Figure 4 In some examples, obtaining seat parameters that match the user's body shape data in step S302 includes:

[0093] Step S401: classifying the user's body shape data using the body shape classification model obtained through training, and determining the user's body shape category corresponding to the user's body shape data.

[0094] The body shape classification model is a model used to classify user body shape data, wherein the body shape classification model can be pre-trained and deployed in the memory of the car for call by the controller of the car.

[0095] There is no limitation on the method for training and obtaining the body shape classification model. In some embodiments, the method for training and obtaining the body shape classification model may be as follows.

[0096] First, a sample data set is obtained. Each piece of sample data in the sample data set includes user body shape data and a label corresponding to the user body shape data. The label is the body shape category to which the user body shape data belongs. The user body shape data in the sample data set can be a large amount of user body shape data obtained from a preset database. The specific categories of body shape categories in the sample data set can be predetermined. The greater the number of body shape categories, the finer the division of body shape categories, and thus the more accurate the seat parameters determined for different body shape categories. After obtaining the sample data set, the sample data set is divided into a training set, a validation set, and a test set. For example, 70% of the sample data constitutes the training set, 15% of the sample data constitutes the validation set, and the remaining 15% of the sample data constitutes the test set to evaluate the generalization ability of the model.

[0097] After the sample data set is divided, the model training process can be carried out. During the model training process, the body shape classification model is trained using the training set, and during or after the training, the performance of the body shape classification model is evaluated using the validation set, and the trained body shape classification model is finally tested using the test set to ensure the performance of the model in practical applications. It can be understood that in the process of training the body shape classification model, the body shape classification model divides the sample data into body shape categories, obtains the test category, and compares the test category with the body shape category labeled with the sample data to calculate the training loss, and adjusts the body shape classification model based on the calculated training loss to achieve the update of the body shape classification model. After the model training is completed, the body shape classification model with the last update is used as the trained body shape classification model.

[0098] After obtaining the user's body shape data, the trained body shape classification model may be called to classify the user's body shape data, thereby obtaining the body shape category corresponding to the user's body shape data, which is referred to as the user's body shape category in the embodiment of the present application.

[0099] Step S402: querying and obtaining seat parameters that match the user's body type from a database containing correspondences between body type categories and adjustment parameters.

[0100] The correspondence between body type categories and adjustment parameters refers to a correspondence between one body type category and a set of adjustment parameters, where the adjustment parameters are parameters for adjusting the vehicle seat. The correspondence between body type categories and adjustment parameters can be stored in a database. The database storing the correspondence between body type categories and adjustment parameters can be a database stored in the vehicle's memory or a cloud database that is communicable with the vehicle.

[0101] After obtaining the user's body type category, the user's body type category is obtained from the correspondence between the body type category and the adjustment parameters, that is, the body type category consistent with the user's body type category in the correspondence between the body type category and the adjustment parameters is obtained, and the adjustment parameters corresponding to the body type category are used as the seat parameters that match the user's body type category.

[0102] Accordingly, by storing the correspondence between body type categories and adjustment parameters, after obtaining the user's body type data, the matching seat parameters are queried from the correspondence based on the user's body type category corresponding to the user's body type data. This allows for quick and convenient acquisition of seat parameters that match the user's body type data, thereby improving the efficiency of obtaining seat parameters and efficiently meeting the user's body type data's riding needs.

[0103] refer to Figure 5 As shown, in other examples, obtaining seat parameters that match the user's body shape data in step S302 includes:

[0104] Step S501: querying and obtaining target body shape data having the highest similarity to the user body shape data from a database containing correspondences between body shape data and adjustment parameters.

[0105] The correspondence between body shape data and adjustment parameters refers to a correspondence between a set of body shape data and a set of adjustment parameters, where the adjustment parameters are parameters for adjusting the vehicle seat. The correspondence between the body shape data and the adjustment parameters can be stored in a database. The database storing the correspondence between the body shape data and the adjustment parameters can be a database stored in the vehicle's memory or a cloud database that is communicable with the vehicle.

[0106] After obtaining the user's body shape data, the body shape data that is most similar to the user's body shape data is queried from the corresponding relationship between the body shape data and the adjustment parameters. The body shape data is referred to as target body shape data in the embodiment of the present application.

[0107] The method for calculating the similarity between the body data in the corresponding relationship between the body data and the adjustment parameters and the user's body data is not limited, including but not limited to calculating the cosine similarity between the body data in the corresponding relationship between the body data and the adjustment parameters and the user's body data. In the process of calculating the similarity, the corresponding weight coefficients can be set differently for different body data. For example, the weight coefficients corresponding to height data and user torso length can be set relatively large, but the present invention is not limited to this. In related embodiments, after calibrating the similarity between any two sets of body data, a fitting relationship corresponding to the similarities of the multiple sets of body data can be fitted to obtain a fitting relationship for the similarity between the two sets of body data. Among them, when calibrating the similarity between any two sets of body shape data, for multiple sets of body shape data, the similarity between the set of body shape data and the set of body shape data itself can also be determined separately. For example, the similarity between one set of body shape data A and the set of body shape data A is 1 or 100%. Therefore, when fitting the fitting relationship, the fitting can be performed based on the same relationship of the two completely identical sets of body shape data, so that the similarity fitting can be performed based on the two completely identical sets of body shape data, which can help improve the accuracy of the obtained similarity fitting relationship.

[0108] When querying to obtain target body shape data with the highest similarity to the user's body shape data, in some examples, the similarity between the body shape data in the database and the user's body shape data can be directly calculated, and the body shape data with the highest similarity can be used as the target body shape data. In other examples, the database can be first searched to see if there is body shape data that is completely consistent with the user's body shape data. If so, the completely consistent body shape data can be used as the target body shape data with the highest similarity. If not, the similarity between the body shape data in the database and the user's body shape data can be calculated, and the body shape data with the highest similarity can be used as the target body shape data. This allows the user to obtain completely consistent body shape data without the need for similarity calculation, thus reducing computing resources and improving the accuracy of the obtained target body shape data.

[0109] Step S502: using the seat parameters corresponding to the target body shape data as the seat parameters matching the user body shape data.

[0110] After the target body shape data is obtained, the adjustment parameters corresponding to the target body shape data are queried from the corresponding relationship between the body shape data and the adjustment parameters, and are used as the seat parameters matching the user's body shape data.

[0111] Accordingly, by storing the correspondence between body shape data and adjustment parameters, after obtaining the user's body shape data, the target body shape data that is most similar to the user's body shape data is matched, and the seat parameters corresponding to the target body shape data are used as the seat parameters that match the user's body shape data. If there is no body shape data that is identical to the user's body shape data in the correspondence, the seat parameters of the target body shape data that is most similar to the user's body shape data are used as the seat parameters that match the user's body shape data. Therefore, the seat parameters that match the user's body shape data are the seat parameters in the database that are closest to the user's body shape data. This ensures that the obtained seat parameters have a high degree of accuracy, and the adjusted car seat can more accurately meet the user's body shape data's riding requirements. If there is body shape data that is identical to the user's body shape data in the correspondence, the corresponding seat parameters that match the user's body shape data can be directly obtained, and the seat parameters that completely match the user's body shape data can improve the accuracy of the obtained seat parameters that match the user's body shape data, and the adjusted car seat can more accurately meet the user's body shape data's riding requirements.

[0112] Step S303: When it is detected that a user is sitting on the car seat, the pressure distribution data of the car seat is collected, and the pressure distribution characteristics of the pressure distribution data are extracted. The comfort level corresponding to the pressure distribution characteristics is determined by the comfort level determination model determined by training.

[0113] Detecting that a user is seated in a car seat refers to the car seat switching from an unoccupied state to an occupied state. There are various methods for detecting whether a user is seated in a car seat. In some examples, the detection can be based on pressure data collected by a pressure sensor in the car seat. For example, if a pressure value in the collected pressure data is greater than or equal to a preset pressure threshold, it is determined that a user is seated in the car seat.

[0114] In other examples, it may also be possible to determine that there is a user sitting on the car seat when, among the pressure data collected by the pressure sensor of the car seat, there are a preset number of pressure data with pressure values greater than or equal to a preset pressure threshold, so as to reduce the possibility of pressure being applied to the car seat due to non-users sitting, such as hand-supported seats, etc., and adjust the seat parameters based solely on the pressure value due to the mistaken assumption that there is a user sitting, so as to improve the accuracy of determining that there is a user sitting.

[0115] In other examples, it may be possible to determine that there is a user sitting on the car seat when, among the pressure data collected by the pressure sensor of the car seat, there are pressure values greater than or equal to a preset number of pressure data, greater than or equal to a preset pressure threshold, and the pressure distribution of greater than or equal to the preset number of pressure data conforms to the ergonomic distribution, so as to improve the accuracy of determining that there is a user sitting on the car seat.

[0116] In other examples, when the pressure value in the pressure data collected by the pressure sensor of the car seat is greater than or equal to a preset pressure threshold, it is analyzed at the same time whether the object sitting on the car seat is a human body, such as by photographing the position of the car seat to obtain an image, and analyzing the photographed image to see whether there is a human body. If the object sitting on the car seat is a human body, it is determined that there is a user sitting on the car seat, thereby further improving the accuracy of the analysis and judgment of whether the user is sitting on the car seat.

[0117] The pressure distribution data of a car seat is the data of pressure values collected by the pressure sensor of the car seat. Taking the pressure sensor including the first pressure sensor 101 and the second pressure sensor 101 as described above as an example, the collected pressure distribution data includes: the pressure distribution data collected by the distributed pressure sensors arranged on the seat back (referred to as the first pressure distribution data in the relevant embodiments below in this application), and the pressure distribution data collected by the distributed pressure sensors arranged on the seat cushion (referred to as the second pressure distribution data in the relevant embodiments below in this application).

[0118] The pressure distribution feature is information used to characterize the characteristics of pressure distribution data. In relevant embodiments of the present application, the pressure distribution feature may include: maximum pressure, average pressure, maximum pressure gradient, average pressure gradient and asymmetry coefficient.

[0119] Among them, the maximum pressure refers to the maximum value of the pressure values in the pressure distribution data, which can be the maximum value of the first pressure distribution data and the second pressure distribution data, or it can include the maximum value in the first pressure distribution data and the maximum value in the second pressure distribution data. In other examples, it can also include: the maximum value in the first pressure distribution data and the second pressure distribution data, the maximum value in the first pressure distribution data, and the maximum value in the second pressure distribution data.

[0120] The average pressure refers to the average value of the pressure values in the pressure distribution data, which can be the average value of the first pressure distribution data and the second pressure distribution data, or can include the average value of the first pressure distribution data and the average value of the second pressure distribution data. In other examples, it can also include: the average value of the first pressure distribution data and the second pressure distribution data, the average value of the first pressure distribution data, and the average value of the second pressure distribution data. In other examples, the seat back can be divided into multiple sub-areas, and the average value of the first pressure distribution data can include the average value of the pressure values of the multiple sub-areas. The seat cushion can also be divided into multiple sub-areas, and the average value of the second pressure distribution data can include the average value of the pressure values of the multiple sub-areas, but is not limited to this.

[0121] The maximum pressure gradient is used to reflect the degree of sudden change in the pressure distribution. The pressure gradient can be determined by the ratio of the pressure values of two or more adjacent pressure sensors to the distance between the sensors, and one or more maximum pressure gradients can be determined therefrom. The maximum pressure gradient can be a maximum pressure gradient determined based on both the first pressure distribution data and the second pressure distribution data, or can include a maximum pressure gradient determined based on the first pressure distribution data and a maximum pressure gradient determined based on the second pressure distribution data. In other examples, the maximum pressure gradient can also include: a maximum pressure gradient determined based on the first pressure distribution data and the second pressure distribution data, a maximum pressure gradient determined based on the first pressure distribution data, and a maximum pressure gradient determined based on the second pressure distribution data, but is not limited thereto.

[0122] The average pressure gradient is used to represent the average value of the pressure gradient, which can be the average value of multiple pressure gradients determined based on the first pressure distribution data and the second pressure distribution data, or it can include the average value of multiple pressure gradients determined based on the first pressure distribution data and the average value of multiple pressure gradients determined based on the second pressure distribution data. In other examples, it can also include: the average value of multiple pressure gradients determined based on the first pressure distribution data and the second pressure distribution data, the average value of multiple pressure gradients determined based on the first pressure distribution data, and the average value of multiple pressure gradients determined based on the second pressure distribution data, but is not limited to this.

[0123] The asymmetry coefficient is a coefficient used to describe the uneven pressure distribution of a car seat. The corresponding asymmetry coefficients can be calculated for the seat back and seat cushion of the car seat respectively.

[0124] Based on this, the comfort level can be comprehensively evaluated from multiple dimensions including maximum pressure, average pressure, maximum pressure gradient, average pressure gradient and asymmetry coefficient, which helps to improve the accuracy of the comfort level obtained.

[0125] The comfort determination model is a model used to determine the comfort corresponding to the pressure distribution characteristics, wherein the comfort determination model can be pre-trained and deployed in the memory of the car for call by the car controller.

[0126] The method for obtaining the comfort level determination model through training is not limited. In some embodiments, the method for obtaining the comfort level determination model through training can be as follows.

[0127] First, a sample data set is obtained. Each sample data in the sample data set includes a pressure distribution feature and a label corresponding to the pressure distribution feature. The label is the comfort level to which the pressure distribution feature belongs. The comfort level can be a specific comfort level value or a specific comfort level level. The pressure distribution feature in the sample data set can be a large number of pressure distribution features obtained from a preset database, such as a pressure distribution feature extracted based on a large amount of pressure distribution data. The comfort level in the sample data set can be predetermined. Taking comfort level as an example, the more comfort levels there are, the finer the division of comfort levels, and thus the more accurate the seat parameters determined based on comfort level. After obtaining the sample data set, the sample data set is divided into a training set, a validation set, and a test set. For example, 70% of the sample data constitutes the training set, 15% of the sample data constitutes the validation set, and the remaining 15% of the sample data constitutes the test set to evaluate the generalization ability of the model.

[0128] After the sample data set is divided, the model training process can be carried out. During the model training process, the comfort determination model is trained using the training set, and during or after the training process, the performance of the comfort determination model is evaluated using the validation set, and the trained comfort determination model is finally tested using the test set to ensure the performance of the model in practical applications. It can be understood that in the process of training the comfort determination model, the comfort determination model determines the corresponding comfort level for the sample data, and compares the comfort level with the comfort level annotated for the sample data to calculate the training loss, and adjusts the comfort determination model based on the calculated training loss to achieve an update of the comfort determination model. After the model training is completed, the comfort determination model with the last update is used as the trained comfort determination model.

[0129] Step S304: Update the seat parameters, obtain updated seat parameters, and adjust the car seat based on the updated seat parameters until the comfort corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat reaches the target comfort after the car seat is adjusted based on the updated seat parameters.

[0130] Based on the obtained pressure distribution characteristics, the corresponding comfort level can be determined. However, the comfort level obtained after adjusting the seat parameters based on the user's body shape data may not be optimal. Therefore, the seat parameters can be updated. After obtaining the updated seat parameters, the car seat can be conditioned based on the updated seat parameters until the adjusted comfort level reaches the target comfort level. This allows the target comfort level to be met by further updating and adjusting the seat parameters.

[0131] Based on the car seat adjustment method of this embodiment, after obtaining the user body shape data of the driving user, it first obtains the seat parameters matching the user body shape data to adjust the car seat, so as to make a preliminary adjustment to the car seat. When it is further detected that there is a user sitting on the car seat, that is, after the user sits on the car seat, the pressure distribution data of the car seat is collected, and the pressure distribution characteristics of the pressure distribution data are extracted. The corresponding comfort is determined by the comfort determination model, and then the seat parameters are further updated and the car seat is adjusted with the target comfort as the adjustment target. Therefore, after the car seat is preliminarily adjusted based on the user body shape data to meet the riding needs of the user body shape data, the pressure generated on the car seat after the user sits on the car seat is further adjusted with the target comfort as the target. This can not only meet the needs based on the user's body shape, but also meet the personalized pressure comfort needs of different users after sitting on the seat.

[0132] refer to Figure 6 As shown, in some embodiments, updating the seat parameters in step S304 to obtain updated seat parameters, and adjusting the car seat based on the updated seat parameters until the current comfort level corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat reaches the target comfort level after the car seat is adjusted based on the updated seat parameters, may include:

[0133] Step S601: Execute the process of adjusting the car seat multiple times, wherein in each adjustment process: update the seat parameters of the last adjustment of the car seat with a preset step size to obtain updated seat parameters; adjust the car seat based on the updated seat parameters, and collect pressure distribution data of the adjusted car seat, extract the pressure distribution characteristics of the pressure distribution data, and determine the comfort corresponding to the pressure distribution characteristics through the comfort determination model.

[0134] The preset step size refers to the adjustment range for each seat parameter adjustment. Different seat parameters can have the same or different preset step sizes. For example, if seat parameters include backrest angle, seat cushion angle, and leg rest angle, different preset step sizes can be set for each.

[0135] Each time the seat parameters are adjusted based on a preset step length and the car seat is adjusted accordingly, the pressure applied by the user on the car seat will change, so that the pressure distribution data of the adjusted car seat can be collected, and the comfort of the car seat after adjustment based on the adjusted seat parameters can be determined accordingly.

[0136] Accordingly, each time the seat parameters are adjusted and the car seat is adjusted accordingly, the pressure applied by the user on the car seat will change, thereby having corresponding different comfort levels, and the target comfort level can be determined based on these multiple comfort levels.

[0137] Step S602: During the process of adjusting the car seat multiple times, when the trend of comfort changes from an increasing trend to a decreasing trend, the maximum comfort in the adjustment process is determined as the target comfort, and the car seat is adjusted based on the seat parameters corresponding to the maximum comfort.

[0138] Among them, in the above process of adjusting the seat parameters with preset step lengths, since the same step length is adjusted each time, the adjustment direction is the same, and the corresponding comfort will also tend to gradually increase or decrease.

[0139] During the adjustment process of the car seat many times, when the trend of the comfort change changes from the maximum trend to the decreasing trend, it means that the comfort has gradually increased to the maximum value and the comfort has decreased, that is, the adjustment parameter with the maximum comfort has been passed during the adjustment process. Therefore, the maximum comfort in the process that has changed from the maximum trend to the decreasing trend can be used as the target comfort, and the car seat can be adjusted based on the seat parameters corresponding to the maximum comfort, that is, the car seat can be adjusted based on the seat parameters adjusted to obtain the maximum comfort, so that the comfort after adjustment can be the maximum comfort, thereby meeting the maximum comfort requirement.

[0140] In some embodiments, reference Figure 6 As shown, step S304 may further include:

[0141] Step S603: During the process of adjusting the car seat for multiple times, if the trend of the comfort level change is a decreasing trend, the seat parameters are adjusted in the opposite direction.

[0142] Adjusting the seat parameters in the opposite direction means that if the seat parameters were originally adjusted to increase, the next adjustment will be to decrease the seat parameters. If the seat parameters were originally adjusted to decrease, the next adjustment will be to increase the seat parameters. This allows the comfort level to be adjusted from a decreasing trend to an increasing trend, so that the target comfort level can be found more quickly.

[0143] In some embodiments, reference Figure 7 As shown, in step S601, the seat parameters of the last adjustment of the car seat are updated with a preset step length to obtain the updated seat parameters, including:

[0144] Step S701: Acquire a seat parameter range corresponding to the user's body shape data, where the seat parameter range includes seat parameters that match the user's body shape data.

[0145] The seat parameter range is determined based on the user's body shape data and can be adjusted for the seat.

[0146] There is no limit to the method of obtaining the seat parameter range corresponding to the user's body shape data. Taking the above-mentioned method of obtaining seat parameters matching the user's body shape data through the user's body shape category as an example, the database can also store the correspondence between the body shape category and the seat parameter range. Accordingly, after obtaining the user's body shape category based on the user's body shape data, the seat parameter range corresponding to the user's body shape category in the correspondence between the body shape category and the seat parameter range can be used as the seat parameter range corresponding to the user's body shape data.

[0147] In other examples, after obtaining seat parameters that match the user's body shape data, a seat parameter range corresponding to the user's body shape data may be obtained based on the seat parameters that match the user's body shape data and the deviation ranges of the seat parameters. Different seat parameters may have different deviation ranges based on the type of seat parameters in the seat parameters. For example, if a seat parameter is m and the deviation range corresponding to the seat parameter is ±a, the parameter range of the seat parameter is [ma, m+a]. Other seat parameters may be processed accordingly, so that the seat parameter range corresponding to the user's body shape data can be obtained based on the first seat parameter.

[0148] Step S702: Using the seat parameter range as a constraint condition, the seat parameters of the last adjustment of the car seat are updated with a preset step size to obtain updated seat parameters.

[0149] After obtaining the seat parameter range, the seat parameters can be updated with the seat parameter range as a constraint condition, that is, the seat parameters are adjusted within the seat parameter range, and the adjusted seat parameters cannot exceed the seat parameter range.

[0150] Based on this, a corresponding seat adjustment range can be set according to the user's body shape data, and the seat parameters can be adjusted with the seat adjustment range as a constraint condition, so that the adjustment goal of the target comfort can be achieved more efficiently, and the adjustment efficiency of the car seat can be improved.

[0151] When a user is driving a car, for example, when the car is traveling long distances, there may be a situation where the user needs to sit on the car seat for a long time. Figure 8 As shown, in some embodiments, the method of some embodiments further includes:

[0152] Step S801: When a user has been sitting on the car seat for a duration greater than or equal to a first preset duration, control the massager of the car seat to perform a massage operation.

[0153] The duration of time that a user is seated on the car seat refers to the duration of time that a user is continuously detected to be seated on the car seat. The specific value of the first preset duration is not limited, for example, 2 hours, etc., but is not limited thereto.

[0154] A car seat massager refers to a massage device installed on a car seat. The massager can stimulate the muscles and acupoints of the human body through mechanical vibration or electromagnetic induction to achieve the effect of relieving fatigue.

[0155] Step S802: After the first preset time is reached, the massager of the car seat is controlled to perform a massage operation at intervals of a second preset time, where the second preset time is shorter than the first preset time.

[0156] After reaching the first preset duration, the massager of the car seat can be controlled to perform a massage operation at intervals of a second preset duration to further improve comfort. The second preset duration interval can be a second preset duration interval directly after reaching the first preset duration. For example, the moment when the first preset duration is reached is T1, and the second preset duration is recorded as T2. Then, at moments T1+T2, T1+2T2, T1+3T2, etc., the massager of the car seat is controlled to perform a massage operation. In other examples, the second preset duration interval can be a second preset duration interval after the massage operation. For example, the moment when the first preset duration is reached is T1, and the second preset duration is recorded as T2. Assuming the massage duration is t0, the massager of the car seat can be controlled to perform a massage operation at moments T1+t0+T2, T1+2t0+2T2, T1+3t0+3T2, etc. In the relevant embodiments of the present application, an example is taken to illustrate how to control the massager of a car seat to perform a massage operation at the moments of T1+T2, T1+2T2, T1+3T2, etc.

[0157] It is understood that during the execution of the method, the car seat massager may also perform a massage operation based on a massage command manually triggered by the user. The massage command manually triggered by the user may be triggered by, but is not limited to, a button on the car seat or a command issued by the user's voice. After the massage operation is performed based on the manually triggered massage command, the second preset duration may be initialized, i.e., the second preset duration is restarted upon receipt of the manually triggered massage command.

[0158] Accordingly, when a user's seat time in a car seat is greater than or equal to a first preset duration, the car seat's massager is controlled to perform a massage operation, thereby alleviating driver fatigue and further improving driver comfort. Subsequently, at shorter intervals of a second preset duration, the car seat's massager is controlled to perform a massage operation, further alleviating driver fatigue during extended rides and further improving driver comfort.

[0159] When performing a massage operation through a massager, it is possible to control all components of the massager to be in a working state, that is, to massage all areas that the massager can touch. In the relevant examples of this application, it is possible to specifically turn on the massage components of some areas and massage only some areas to perform a massage operation in a targeted manner. Accordingly, in some embodiments, reference is made to Figure 9 As shown, the above step S802 of controlling the massager of the car seat to perform the massage operation includes:

[0160] Step S8021: Collect pressure distribution data of the car seat, and determine the maximum pressure area and the maximum pressure gradient area based on the collected pressure distribution data.

[0161] Step S8022: Send a start instruction to the massager of the car seat, where the start instruction is used to instruct to perform a massage operation on the seat area corresponding to the maximum pressure area and the maximum pressure gradient area.

[0162] Accordingly, when controlling the massager to perform a massage operation, the pressure distribution data of the car seat is collected, and a massage operation is performed on the seat area corresponding to the maximum pressure area and the maximum pressure gradient area extracted based on the pressure distribution data. The massage operation of the massager is performed on the area where the user exerts the greatest force and the area with the largest pressure difference, so that driving fatigue can be relieved in a targeted manner, which can help to further improve driving comfort.

[0163] refer to Figure 10 As shown, in some embodiments, the method further includes:

[0164] Step S305: storing the correspondence between the user body shape data and the seat parameters corresponding to the target comfort level in a database, or storing the correspondence between the user body shape category corresponding to the user body shape data and the seat parameters corresponding to the target comfort level in a database.

[0165] Accordingly, after determining the target comfort and the corresponding seat parameters, the correspondence between the user body shape data and the seat parameters corresponding to the target comfort can be stored in a database, or the correspondence between the user body shape category corresponding to the user body shape data and the seat parameters corresponding to the target comfort can be stored in a database, so that it can be stored as sample data, so that in the subsequent process of adjusting the car seat, if there is the same or similar user body shape data, it can be matched to closer seat parameters, thereby improving the efficiency of subsequent seat adjustment.

[0166] In some embodiments, reference Figure 11 As shown, the method further includes:

[0167] Step S111: Acquire driving scene information, which includes road information and environment information.

[0168] Driving scenario information refers to information related to the vehicle's driving scenario, and may include road information related to the road scene and environmental information related to the driving environment. In some examples, road information includes, but is not limited to, road type, number and width of lane lines, curves, road slope, and traffic signs. In some examples, environmental information includes, but is not limited to, weather information, lighting conditions, and visibility.

[0169] In other examples, driving scene information may also include driving parameters. The driving parameters in some examples include but are not limited to driving speed, whether the intelligent driving mode is turned on, etc.

[0170] Step S112: Determine a driving scene mode based on the driving scene information.

[0171] A car can be provided with multiple different driving scene modes to suit different driving scenarios. Some possible driving scene modes include but are not limited to high-speed intelligent driving mode, urban intelligent driving mode, human driving mode, etc. In other examples, driving scene modes include but are not limited to comfort mode, relatively comfortable mode, sports mode, etc., wherein the comfort mode can be applicable to high-speed driving scenarios, relatively comfortable mode can be applicable to urban intelligent driving scenarios, and sports mode can be applicable to scenarios such as user manual driving (i.e., without using intelligent assisted driving). It is understandable that based on different technical requirements, other driving scene modes or other numbers of driving scene modes can be set.

[0172] There is no limit to the method of determining the driving scene mode based on the driving scene information. For example, based on the road type and traffic signs in the road information, it can be determined that it is a high-speed scene, and further combined with the lane line curve, road slope, and environmental information in the road information, a normal driving scene or a low-speed driving scene in the high-speed scene can be determined, but it is not limited to this. In the case where the driving scene information includes driving parameters, the driving scene mode can also be determined in combination with the driving parameters. For example, when the vehicle speed is greater than a preset speed (for example, 80 km / hour (kilometers per hour)) and the intelligent driving mode is turned on, the driving scene mode is determined to be a high-speed intelligent driving mode. When the vehicle speed is less than or equal to the preset speed and the intelligent driving mode is turned on, the driving scene mode is determined to be an urban intelligent driving mode. When the intelligent driving mode is not turned on, the driving scene mode is determined to be a human driving mode, etc.

[0173] Step S113: Update the seat parameters, obtain updated seat parameters, and adjust the car seat based on the updated seat parameters until the adjusted comfort is within the comfort range matching the driving scene pattern. The adjusted comfort is the comfort corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat after the car seat is adjusted based on the updated seat parameters.

[0174] Among them, the adjustment of seat parameters can have different focuses for different driving scenario modes. For example, in human driving mode, both the convenience of the user's driving operation and the comfort needs must be considered. In high-speed intelligent driving mode, the road conditions are relatively simple, and assisted driving can be performed through the intelligent driving mode, so higher comfort requirements can be met.

[0175] In some examples, seat parameters are updated to obtain updated seat parameters, and the vehicle seat is adjusted based on the updated seat parameters until the adjusted comfort level is within a comfort level range that matches the driving scenario mode, including:

[0176] Obtain the comfort range corresponding to the driving scenario mode;

[0177] Carry out a number of vehicle seat adjustment procedures, wherein during each adjustment procedure:

[0178] Updating the seat parameters of the last adjustment of the car seat with a preset step length to obtain updated seat parameters;

[0179] Adjusting the car seat based on the updated seat parameters, collecting pressure distribution data of the adjusted car seat, extracting pressure distribution characteristics of the pressure distribution data, and determining a comfort level corresponding to the pressure distribution characteristics using a comfort level determination model;

[0180] When the determined comfort level is within the comfort level range corresponding to the driving scenario mode, the adjustment process is terminated.

[0181] Different comfort ranges can be set for different driving scenarios. For example, the comfort range for high-speed intelligent driving mode is wider, while the comfort range for human driving mode is narrower. In this case, the car seat can be adjusted until the comfort level corresponding to the pressure distribution characteristics of the car seat's pressure distribution data falls within the comfort range corresponding to the driving scenario mode, thereby meeting the seat adjustment comfort requirements for different driving scenarios.

[0182] Based on this, during the driving process of the car, the car seat can also be adjusted according to the driving scene mode determined based on the driving scene information, so that the adjusted seat parameters can not only meet the riding needs of the user's body data, but also meet the driving needs of the driving scene mode, which can help to further improve comfort.

[0183] Based on the above examples, the following is an illustration with reference to specific examples.

[0184] refer to Figure 12 As shown, in step S1201, it is checked whether the user has opened the car door. If the user has opened the car door, it means that the user has opened the car door to prepare to get on the car, and the process goes to step S1202.

[0185] In step S1202, an image is obtained by photographing a camera, for example, an image can be obtained by photographing a camera on a door interior panel. The image can be transmitted to a controller or other image processing module via the vehicle data transmission bus CAN (Controller Area Network) bus.

[0186] In step S1203, the obtained image is analyzed to obtain the user body shape data of the driver; for example, the controller or the module performing image processing analyzes the image to obtain user body shape data such as the user's height and torso length, and provides the obtained user body shape data to the controller for decision-making.

[0187] In step S1204, seat parameters matching the user's body shape data are acquired, and the car seat is adjusted based on the seat parameters matching the user's body shape data.

[0188] In step S1205 , it is checked whether there is a user sitting on the car seat. If it is detected that there is a user sitting on the car seat, the process proceeds to step S1206 .

[0189] In step S1206, the pressure distribution data of the car seat is collected, and the pressure distribution characteristics of the pressure distribution data are extracted. The pressure distribution characteristics include but are not limited to maximum pressure, average pressure, maximum pressure gradient, average pressure gradient and asymmetry coefficient, and then enter step S1207.

[0190] In step S1207, the comfort level corresponding to the pressure distribution feature is determined by the comfort level determination model determined through training, and the process proceeds to steps S1208 and S1209.

[0191] In step S1208, the seat parameters are updated with a preset step length to obtain updated seat parameters, and the car seat is adjusted based on the updated seat parameters, and then the process returns to step S1206.

[0192] In step S1209, the changing trend of the comfort after multiple adjustments is determined. When the changing trend of the comfort changes from an increasing trend to a decreasing trend, the maximum comfort during the adjustment process is determined as the target comfort, and the car seat is adjusted based on the seat parameters corresponding to the maximum comfort to complete the adjustment process and enter step S1210.

[0193] In step S1210, the correspondence between the user body shape data and the seat parameters corresponding to the target comfort level is stored in the database, or the correspondence between the user body shape category corresponding to the user body shape data and the seat parameters corresponding to the target comfort level is stored in the database.

[0194] Based on the above processing, the process of adaptively adjusting the car seat can be completed from the time the user opens the car door to the time the user sits on the car seat. After the user sits on the car seat, the car seat can be further adaptively adjusted while the car is driving.

[0195] Continue to refer Figure 12 As shown, during the driving process of the car, in step S1211, driving scene information is obtained, the driving scene information includes road information and environmental information, and then step S1212 is entered.

[0196] In step S1212 , the driving scene mode is determined based on the driving scene information, and the process proceeds to step S1213 .

[0197] In step S1213, the seat parameters are updated to obtain updated seat parameters, and the car seat is adjusted based on the updated seat parameters until the adjusted comfort level is within the comfort level range that matches the driving scenario pattern.

[0198] After the user sits on the car seat, the massager of the car seat can be further controlled to perform massage operations during the driving of the car. Figure 12As shown, during the driving of the car, in step S1214, it is determined whether the duration of the user sitting on the car seat is greater than or equal to the first preset duration T1. If so, the process proceeds to step S1215.

[0199] In step S1215 , the pressure distribution data of the car seat is collected, the maximum pressure area and the maximum pressure gradient area are extracted based on the pressure distribution data, and the process proceeds to step S1216 .

[0200] In step S1216, a start instruction is sent to the massager of the car seat, where the start instruction is used to instruct to perform a massage operation on the seat area corresponding to the maximum pressure and maximum pressure gradient area, and then enter step S1217.

[0201] In step S1217, it is determined whether the second preset time T2 has elapsed. If so, the process returns to step S1215. The massage process can be started continuously from step S1215 to step S1217 until the user leaves the car seat.

[0202] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0203] Based on the same inventive concept, embodiments of the present application also provide an automobile seat adjustment device for implementing the aforementioned automobile seat adjustment method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more of the following embodiments of the automobile seat adjustment device can be found in the above-described limitations of the automobile seat adjustment method and will not be further elaborated here.

[0204] In one embodiment, Figure 13 As shown, a car seat adjustment device is provided, comprising: a body shape data acquisition module 131, a first adjustment module 132 and a second adjustment module 133, wherein:

[0205] The body shape data acquisition module 131 is used to acquire the body shape data of the driver;

[0206] A first adjustment module 132 is configured to obtain first seat parameters that match the user's body shape data and adjust the car seat based on the first seat parameters;

[0207] The second adjustment module 133 is used to collect pressure distribution data of the car seat and extract pressure distribution characteristics of the pressure distribution data when it detects that a user is sitting on the car seat, and determine the comfort corresponding to the pressure distribution characteristics through a comfort determination model determined by training; update the seat parameters to obtain updated seat parameters, and adjust the car seat based on the updated seat parameters until the comfort corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat reaches the target comfort after the car seat is adjusted based on the updated seat parameters.

[0208] In some embodiments, the first adjustment module 132 is used to classify the user's body shape data through the trained body shape classification model to determine the user's body shape category corresponding to the user's body shape data; and query and obtain seat parameters that match the user's body shape category from a database containing the correspondence between body shape categories and adjustment parameters.

[0209] In some embodiments, the first adjustment module 132 is used to query and obtain target body shape data with the highest similarity to the user body shape data from a database containing the correspondence between body shape data and adjustment parameters; and use the seat parameters corresponding to the target body shape data as the seat parameters matching the user body shape data.

[0210] In some embodiments, the pressure distribution characteristics include: maximum pressure, average pressure, maximum pressure gradient, average pressure gradient, and asymmetry coefficient.

[0211] In some embodiments, the second adjustment module 133 is used to execute the process of adjusting the car seat multiple times, wherein in each adjustment process: the seat parameters of the last adjustment of the car seat are updated with a preset step size to obtain updated seat parameters; the car seat is adjusted based on the updated seat parameters, and the pressure distribution data of the adjusted car seat is collected, the pressure distribution characteristics of the pressure distribution data are extracted, and the comfort corresponding to the pressure distribution characteristics is determined by a comfort determination model; in the adjustment process of adjusting the car seat multiple times, when the trend of the change in comfort changes from an increasing trend to a decreasing trend, the maximum comfort in the adjustment process is determined as the target comfort, and the car seat is adjusted based on the seat parameters corresponding to the maximum comfort.

[0212] In some embodiments, the second adjustment module 133 is used to obtain the seat parameter range corresponding to the user's body shape data, and the seat parameter range includes seat parameters that match the user's body shape data; with the seat parameter range as a constraint condition, the seat parameters of the last adjustment of the car seat are updated with a preset step size to obtain updated seat parameters.

[0213] In some embodiments, the apparatus further comprises:

[0214] The massage control module is used to control the massager of the car seat to perform a massage operation when a user sits on the car seat for a duration greater than or equal to a first preset duration; after reaching the first preset duration, the massager of the car seat is controlled to perform a massage operation at intervals of a second preset duration, where the second preset duration is less than the first preset duration.

[0215] In some embodiments, a massage control module is used to collect pressure distribution data of a car seat, determine the maximum pressure area and the maximum pressure gradient area based on the collected pressure distribution data, and send a start instruction to the massager of the car seat, where the start instruction is used to instruct a massage operation to be performed on the seat area corresponding to the maximum pressure area and the maximum pressure gradient area.

[0216] In some embodiments, the apparatus further comprises:

[0217] The data updating module is used to store the correspondence between the user's body shape data and the seat parameters corresponding to the target comfort level in the database, or to store the correspondence between the user's body shape category corresponding to the user's body shape data and the seat parameters corresponding to the target comfort level in the database.

[0218] In some embodiments, the apparatus further comprises:

[0219] A mode adaptation module is used to obtain driving scene information, including road information and environmental information; and determine a driving scene mode based on the driving scene information;

[0220] The third adjustment module updates the seat parameters, obtains updated seat parameters, and adjusts the car seat based on the updated seat parameters until the adjusted comfort is within the comfort range matching the driving scene mode. The adjusted comfort is the comfort corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat after the car seat is adjusted based on the updated seat parameters.

[0221] In some embodiments, the user's body shape data includes user torso parameters and limb parameters.

[0222] In some embodiments, the seat parameters include seat back parameters, seat cushion parameters, and leg rest parameters.

[0223] Each module in the aforementioned vehicle seat adjustment device may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor within a computer device in hardware form, or may be stored in a computer device memory in software form, allowing the processor to call and execute the corresponding operations of each module.

[0224] In one embodiment, an electronic device is provided, which may be a terminal and includes a processor, memory, and a communication interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal via wired or wireless communication, where the wireless communication may be achieved via Wi-Fi, a mobile cellular network, NFC (near field communication), or other technologies. When the computer program is executed by the processor, a method for adjusting a car seat is implemented. The electronic device may also include a display screen and an input device. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device may be a touch layer covering the display screen, or may be buttons, a trackball, or a touchpad provided on the computer device housing, or may be an external keyboard, touchpad, or mouse.

[0225] Those skilled in the art will understand that the structure of the electronic device described above is merely an illustration of a portion of the structure related to the present application scheme, and does not constitute a limitation on the electronic device to which the present application scheme is applied. The specific electronic device may include more or fewer components, or combine certain components, or have a different component arrangement.

[0226] In some embodiments, an electronic device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of the car seat adjustment method of any of the above embodiments are implemented.

[0227] In some embodiments, a car seat adjustment system is provided, referring to Figure 1 As shown, it includes a camera 20, a pressure sensor 101 provided on a car seat, and a controller 30 that is communicatively connected to the camera 20 and the pressure sensor 101;

[0228] The camera device 20 is configured to capture images of the driver and passenger;

[0229] The pressure sensor 101 is configured to collect pressure distribution data of the car seat;

[0230] The controller 30 is configured to obtain the user's body shape data based on the image and execute the steps of the car seat adjustment method according to any of the above embodiments.

[0231] In some embodiments, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the vehicle seat adjustment method of any of the above embodiments are implemented.

[0232] In some embodiments, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of the vehicle seat adjustment method according to any of the above embodiments.

[0233] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0234] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0235] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for adjusting a car seat, characterized in that: The method comprises: Obtain the user's body shape data of the driver; Acquiring seat parameters that match the user's body shape data, and adjusting the car seat based on the seat parameters; When a user is detected sitting on the car seat, pressure distribution data of the car seat is collected, pressure distribution features of the pressure distribution data are extracted, and a comfort level corresponding to the pressure distribution features is determined by a comfort level determination model determined through training; The seat parameters are updated to obtain updated seat parameters, and the car seat is adjusted based on the updated seat parameters until the comfort corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat reaches the target comfort after the car seat is adjusted based on the updated seat parameters.

2. The method according to claim 1, characterized in that The obtaining of seat parameters matching the user's body shape data includes: Classify the user body shape data using a body shape classification model obtained through training, and determine the user body shape category corresponding to the user body shape data; The seat parameters matching the user's body type are obtained by querying a database containing correspondences between body type categories and adjustment parameters.

3. The method according to claim 1, characterized in that The obtaining of seat parameters matching the user's body shape data includes: Querying and obtaining target body shape data having the highest similarity to the user body shape data from a database containing correspondences between body shape data and adjustment parameters; The seat parameters corresponding to the target body shape data are used as the seat parameters matching the user body shape data.

4. The method according to claim 1, wherein Updating the seat parameters to obtain updated seat parameters, and adjusting the automobile seat based on the updated seat parameters until a comfort level corresponding to a pressure distribution characteristic of pressure distribution data of the automobile seat reaches a target comfort level after the automobile seat is adjusted based on the updated seat parameters, comprising: Carry out a number of vehicle seat adjustment procedures, wherein during each adjustment procedure: Updating the seat parameters of the last adjustment of the car seat with a preset step length to obtain updated seat parameters; adjusting the car seat based on the updated seat parameters, collecting pressure distribution data of the adjusted car seat, extracting pressure distribution characteristics of the pressure distribution data, and determining a comfort level corresponding to the pressure distribution characteristics using the comfort level determination model; During the process of adjusting the car seat multiple times, when the trend of comfort changes from an increasing trend to a decreasing trend, the maximum comfort in the adjustment process is determined as the target comfort, and the car seat is adjusted based on the seat parameters corresponding to the maximum comfort.

5. The method according to claim 4, characterized in that The seat parameters of the last adjustment of the car seat are updated with a preset step length to obtain updated seat parameters, including: Acquire a seat parameter range corresponding to the user body shape data, where the seat parameter range includes seat parameters that match the user body shape data; Taking the seat parameter range as a constraint condition, the seat parameters of the last adjustment of the car seat are updated with a preset step size to obtain updated seat parameters.

6. The method according to any one of claims 1 to 5, characterized in that The method further comprises: When a user has been sitting on the car seat for a period of time that is greater than or equal to a first preset period of time, controlling a massager of the car seat to perform a massage operation; After the first preset time is reached, the massager of the car seat is controlled to perform a massage operation at intervals of a second preset time, where the second preset time is shorter than the first preset time.

7. The method according to claim 6, characterized in that The step of controlling the massager of the car seat to perform a massage operation includes: collecting pressure distribution data of the car seat, and determining a maximum pressure area and a maximum pressure gradient area based on the collected pressure distribution data; A start instruction is sent to the massager of the car seat, wherein the start instruction is used to instruct to perform a massage operation on the seat area corresponding to the maximum pressure area and the maximum pressure gradient area.

8. The method according to any one of claims 1 to 5, characterized in that The method also includes: The correspondence between the user body shape data and the seat parameters corresponding to the target comfort level is stored in a database, or the correspondence between the user body shape category corresponding to the user body shape data and the seat parameters corresponding to the target comfort level is stored in a database.

9. The method according to any one of claims 1 to 5, characterized in that The method also includes: Acquiring driving scene information, wherein the driving scene information includes road information and environment information; determining a driving scene mode based on the driving scene information; The seat parameters are updated to obtain updated seat parameters, and the car seat is adjusted based on the updated seat parameters until the adjusted comfort level is within the comfort range matching the driving scenario pattern, wherein the adjusted comfort level is the comfort level corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat after the car seat is adjusted based on the updated seat parameters.

10. A car seat adjustment device, characterized in that: The device comprises: A body shape data acquisition module is used to acquire body shape data of the driver and passenger; a first adjustment module, configured to obtain seat parameters matching the user's body shape data and adjust the car seat based on the seat parameters; The second adjustment module is used to collect pressure distribution data of the car seat when it is detected that a user is sitting on the car seat, and extract pressure distribution characteristics of the pressure distribution data, and determine the comfort corresponding to the pressure distribution characteristics through a comfort determination model determined by training; update the seat parameters to obtain updated seat parameters, and adjust the car seat based on the updated seat parameters until the comfort corresponding to the pressure distribution characteristics of the pressure distribution data of the car seat reaches the target comfort after the car seat is adjusted based on the updated seat parameters.

11. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

12. A car seat adjustment system, characterized in that: It includes a camera, a pressure sensor provided on a car seat, and a controller in communication with the camera and the pressure sensor; The camera device is configured to capture images of the driver or passenger; The pressure sensor is configured to collect pressure distribution data of the car seat; The controller is configured to obtain user body shape data based on the image and execute the steps of any one of the methods of claims 1 to 9.

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

14. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

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