Intelligent driving mode adjusting method and related equipment

Abstract

The invention discloses an intelligent driving mode adjusting method and related equipment, relates to the field of intelligent driving of vehicles, and mainly aims to solve the problem that a more intelligent and humanized control method still lacks for adjustable elements on vehicles at present. The method comprises the steps that basic information of a driver is obtained, and the basic information comprises height information, eye spot position information and head space distance information; determining an optimal adjustment interval of a motor component used by the driver through a position function model based on the driver basic information; and controlling the motor component based on the optimal adjustment interval. The method is used for the intelligent driving mode adjusting process.

Description

Technical Field

[0001] The present invention relates to the field of vehicle intelligent driving, and in particular to an intelligent driving mode adjustment method and related equipment. Background Art

[0002] At present, the motor components related to drivers in cars include electric seats, electric exterior mirrors, electric interior mirrors, electric steering wheels, and electric central control screens. On the other hand, with the development of automobile electrification, there will be more and more motor components, such as electric sun visors and electric central armrests. At present, except for the electric seats and electric exterior mirrors that have the position memory function of 1-2 people, other motor components are not related to the specific needs of drivers. Therefore, there is still a lack of a more intelligent and humanized control method for the adjustable components on the vehicle. Summary of the invention

[0003] In view of the above problems, the present invention provides an intelligent driving mode adjustment method and related equipment, the main purpose of which is to solve the problem that there is still a lack of a more intelligent and humane control method for adjustable components on vehicles.

[0004] In order to solve at least one of the above technical problems, in a first aspect, the present invention provides an intelligent driving mode adjustment method, the method comprising:

[0005] Obtaining basic information of the driver, wherein the basic information includes height information, eye point position information and head space distance information;

[0006] Determining the optimal adjustment range of the motor component used by the driver through a position function model based on the driver basic information;

[0007] The motor component is controlled based on the optimal regulation interval.

[0008] Optionally, obtaining basic information of the driver includes:

[0009] The basic information of the driver is obtained based on touch information, wherein the touch information is triggered by the driver,

[0010] Or, the basic information of the driver is obtained based on sensors.

[0011] Optionally, the above method further includes:

[0012] Determine a driver data set, wherein the driver data set is divided into a height dimension, an eye point dimension, and a head space dimension;

[0013] An electric machine adjustment data set is determined based on the driver data set, wherein the electric machine adjustment data set is related to a height dimension, an eye point dimension, and a head space dimension.

[0014] Optionally, the above method further includes:

[0015] constructing the position function model based on the driver data set and the electric mechanism adjustment data set;

[0016] The position function model is trained based on a neural network, wherein the position function model includes an input layer, a hidden layer and an output layer.

[0017] Optional,

[0018] The relationship between the hidden layer and the input layer is:

[0019] H=W1*X+b1

[0020] Wherein, H is a hidden layer, W1 is a weight coefficient in the first neural network training process between the hidden layer and the input layer, X is an input layer, and b1 is a bias correction amount of the weight coefficient in the first neural network training process;

[0021] The relationship between the hidden layer and the output layer is:

[0022] Y=W2*H+b2

[0023] Among them, Y is the output layer, W2 is the weight coefficient in the second neural network training process between the hidden layer and the output layer, H is the hidden layer, and b2 is the bias correction amount of the weight coefficient in the second neural network training process.

[0024] Optionally, the motor components include seats, a steering wheel, an exterior rearview mirror, an interior rearview mirror, a central control screen, a sun visor and a central armrest.

[0025] Optionally, the position function model is stored in an ECU, and the method further includes:

[0026] Transmitting the basic driver information to the ECU;

[0027] Calling the position function model based on the ECU to determine the optimal adjustment range of the motor component corresponding to the driver basic information;

[0028] The electric motor member is controlled by the ECU based on the optimal adjustment interval.

[0029] In a second aspect, an embodiment of the present invention further provides an intelligent driving mode adjustment device, comprising:

[0030] An acquisition unit, used to acquire basic information of the driver, wherein the basic information includes height information, eye point position information and head space distance information;

[0031] A determination unit, configured to determine an optimal adjustment interval of the motor component used by the driver through a position function model based on the basic information of the driver;

[0032] A control unit is used to control the motor component based on the optimal adjustment interval.

[0033] In order to achieve the above-mentioned purpose, according to the third aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the above-mentioned program is executed by a processor, the steps of the above-mentioned intelligent driving mode adjustment method are implemented.

[0034] In order to achieve the above-mentioned purpose, according to the fourth aspect of the present invention, an electronic device is provided, comprising at least one processor and at least one memory connected to the processor; wherein the above-mentioned processor is used to call the program instructions in the above-mentioned memory to execute the steps of the above-mentioned intelligent driving mode adjustment method.

[0035] Through the above technical scheme, the intelligent driving mode adjustment method and related equipment provided by the present invention solve the problem that there is still a lack of a more intelligent and humanized control method for the adjustable elements on the vehicle. The present invention obtains the basic information of the driver, wherein the basic information includes height information, eye point position information and head space distance information; determines the optimal adjustment range of the motor component used by the driver through the position function model based on the basic information of the driver; and controls the motor component based on the optimal adjustment range. In the above scheme, the proposed automatic adjustment method of the relevant motor components based on the driver's driving posture identifies and triggers human body information based on different recognition methods, and calls the model to drive the position adjustment of each motor component, which can meet the personalized and intelligent driver-related automatic adjustment of the riding, accessibility, and visual related components, and can solve the problem of cumbersome manual adjustment of traditional vehicles, while improving the intelligence of the vehicle.

[0036] Correspondingly, the intelligent driving mode adjustment device, equipment and computer-readable storage medium provided in the embodiments of the present invention also have the above-mentioned technical effects.

[0037] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0039] Figure 1 A schematic diagram of a flow chart of an intelligent driving mode adjustment method provided by an embodiment of the present invention is shown;

[0040] Figure 2 A schematic diagram of related motor components in an intelligent driving mode adjustment mode provided by an embodiment of the present invention is shown;

[0041] Figure 3 A schematic diagram showing a control relationship of a related motor component provided by an embodiment of the present invention is shown;

[0042] Figure 4 A schematic diagram of constructing a position function model provided by an embodiment of the present invention is shown;

[0043] Figure 5 A schematic block diagram showing the composition of an intelligent driving mode adjustment device provided by an embodiment of the present invention is shown;

[0044] Figure 6 A schematic block diagram of the composition of an intelligent driving mode adjustment electronic device provided by an embodiment of the present invention is shown;

[0045] Among them, seat 1, steering wheel 2, exterior rearview mirror 3, interior rearview mirror 4, central control screen 5, sun visor 6, central armrest 7, instrument cluster 8. DETAILED DESCRIPTION

[0046] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to enable the scope of the present invention to be fully communicated to those skilled in the art.

[0047] In order to solve the problem that there is still a lack of a more intelligent and humanized control method for adjustable components on a vehicle, an embodiment of the present invention provides an intelligent driving mode adjustment method, such as Figure 1 As shown, the method includes:

[0048] S101, obtaining basic information of the driver, wherein the basic information includes height information, eye point position information and head space distance information;

[0049] Specifically, each driver will adjust the position that he or she thinks is most comfortable due to differences in height and personal preferences. Height is the most important factor in determining the sitting position, which determines the position and angle of the operating parts, including the steering wheel, central armrest, etc. Furthermore, based on the height, the body proportions further determine the eye point position, which in turn determines the position and angle of the visible parts, including the inside and outside rearview mirrors, the central control screen, the sun visor, etc. However, from a statistical point of view, each height state corresponds to a position or position range with the highest probability, so the above-mentioned parts positions are associated with the height and the eye point.

[0050] The above-mentioned step S101 also includes: S1011: acquiring the basic information of the driver based on touch information, wherein the touch information is triggered by the driver, or acquiring the basic information of the driver based on a sensor.

[0051] Specifically, the above-mentioned driver's touch information is triggered based on the on-board touch display screen. It can be understood that based on HMI (Human Machine Interface, human-machine interface), including but not limited to obtaining the above-mentioned driver's basic information through on-board touch screens and buttons, pushing rotary controllers, sliding and gesture functions, and even voice recognition technology.

[0052] Furthermore, the basic information of the driver may be obtained by installing radar sensors inside and outside the vehicle.

[0053] S102, determining the optimal adjustment range of the motor component used by the driver through a position function model based on the basic information of the driver;

[0054] Specifically, the above method also includes: constructing a position function model.

[0055] The above steps of constructing the position function model also include: S1021, S1022, S1023 and S1024:

[0056] S1021, determining a driver data set, wherein the driver data set is divided into a height dimension, an eye point dimension, and a head space dimension;

[0057] An electric machine adjustment data set is determined based on the driver data set, wherein the electric machine adjustment data set is related to a height dimension, an eye point dimension, and a head space dimension.

[0058] Exemplarily, a target driver population is selected, which generally covers at least 5% to 95% of the height and meets certain male-female ratio requirements. The target group can be selected by referring to GB1000-2023 and the height information in the human-machine simulation software; the second step is to organize each driver to adjust the driver posture of the actual vehicle, adjust the angles and positions of all the aforementioned related motor components to their most comfortable driving state, and record the positions of the motor components, and also record the corresponding human body information, including height, eye position or head space distance, etc. The height can be obtained by measurement, and the eye position and head space can be obtained by scanning or measurement.

[0059] S1022, constructing the position function model based on the driver data set and the electric mechanism adjustment data set;

[0060] The position function model is trained based on a neural network, wherein the position function model includes an input layer, a hidden layer and an output layer.

[0061] S1023. The relationship between the hidden layer and the input layer is:

[0062] H=W1*X+b1

[0063] Wherein, H is a hidden layer, W1 is a weight coefficient in the first neural network training process between the hidden layer and the input layer, X is an input layer, and b1 is a bias correction amount of the weight coefficient in the first neural network training process;

[0064] The relationship between the hidden layer and the output layer is:

[0065] Y=W2*H+b2

[0066] Among them, Y is the output layer, W2 is the weight coefficient in the second neural network training process between the hidden layer and the output layer, H is the hidden layer, and b2 is the bias correction amount of the weight coefficient in the second neural network training process.

[0067] like Figure 4As shown, exemplarily, a position function model is established, and data training and learning can be performed based on a neural network. The input end includes the height, eye point position, head space distance, etc. obtained in the above steps, and the output end includes the angle and position information of each motor component. After learning and training, a function model of the position of each mechanism component with respect to human body information is obtained. The model is as follows. In the current embodiment, the input layer is at least one of the above-mentioned height, eye point position, and head space distance, or two or three of them. Human body information can also be further added. For example, X1 is the driver's height information, X2 is the collected driver's eye point position information, X3 is the collected driver's head space distance information, and X4 is other driver body size information (such as seat height and joint size measured based on GB10000-2023).

[0068] The above hidden layer can set the number of calculation dimensions. The more the number, the greater the training volume and the more accurate it is. Its simplified relationship with the input layer is H = W1*X+b1; the output layer corresponds to the position or angle information of each mechanism component with the best or highest probability, and its simplified relationship with the hidden layer is Y = W2*H+b2, so as to perform data training, model generation and verification. When applied, the model can call the position and angle information of each mechanism component that corresponds to the most likely position by inputting at least one condition, such as height or eye point position or head space distance, such as Y1 corresponding to seat position and angle, Y2 corresponding to steering wheel front and back and up and down position, Y3 corresponding to exterior rearview mirror front and back and up and down angle, Y4 corresponding to interior rearview mirror front and back and up and down angle, Y5 corresponding to the position and angle of the central control screen, Y6 corresponding to the rotation angle of the sun visor, Y7 corresponding to the position of the central armrest, etc.

[0069] Among them, W1 is the weight coefficient in the first layer of neural network training process, b1 is its bias correction; W2 is the weight coefficient in the second layer of neural network training process, b2 is its bias correction.

[0070] S1024. In one embodiment, the position function model is stored in an ECU, and the method further includes:

[0071] Transmitting the basic driver information to the ECU;

[0072] Calling the position function model based on the ECU to determine the optimal adjustment range of the motor component corresponding to the driver basic information;

[0073] The electric motor member is controlled by the ECU based on the optimal adjustment interval.

[0074] Figure 3It is a control relationship diagram of related motor components. Each motor component corresponds to its controller. The above controller can be separate or shared. For example, the seat and rearview mirror controllers are generally shared. The controller stores individual information such as the height and eye point of each driver and the optimal mechanism position function. The position of the mechanism is realized by its motor control, which is generally based on Hall motors, stepper motors, etc. to realize motor closed-loop control. At the same time, the controller accepts input information from the recognition module. The recognition module includes but is not limited to the human body information that is initially calibrated, such as height, eye point, etc.

[0075] Furthermore, the position function model of each motor component is stored in the ECU, and the recognition module obtains the human body information and transmits the information to the ECU.

[0076] Three embodiments provided by this application are shown below:

[0077] In case one, a selection menu from 150 to 190 cm (with height in steps of 1 cm) may be provided on the display interface for the driver to actively select his or her height information for passive identification and triggering.

[0078] In the second case, the DMS or other cameras actively identify and trigger the eye point position. The identification prerequisite can be set to wait for a few seconds after the driver inserts the seat belt.

[0079] In case three, a sensor can be placed on the ceiling to measure the head space, or the DMS or other cameras can calculate the height of the head space, both of which can be actively identified and triggered. The identification prerequisites are the same as above.

[0080] Finally, the ECU receives the information provided by the identification module and calls the position model data of each mechanism component to complete the adjustment.

[0081] S103: Control the motor component based on the optimal adjustment interval.

[0082] In summary, the above scheme specifically includes the selection of target population, recording of driving posture human body information and mechanism component position information, training and verification of the above information based on neural network to obtain a model of mechanism component position regarding human body information, identifying and triggering human body information based on different recognition methods, and calling the model to drive the position adjustment of each motor component, which can meet the personalized and intelligent driver-related automatic adjustment of riding, accessibility, and visual related mechanism components, solve the problem of cumbersome manual adjustment of traditional vehicles, and at the same time improve the intelligence level of the vehicle.

[0083] In one embodiment, the motor components include seats, a steering wheel, an exterior rearview mirror, an interior rearview mirror, a central control screen, a sun visor, and a central armrest.

[0084] like Figure 2As shown, it is understandable that, because it involves intelligent driving mode adjustment, the mechanism is generally required to have electric adjustment function. Among them, the electric seat generally has 3 or 4 motors, corresponding to the electric adjustment of the whole seat forward and backward, the whole seat height, the backrest angle, and the seat cushion angle; the electric steering wheel generally has 2 motors, corresponding to the electric adjustment of the steering wheel axis extension and rotation; the exterior rearview mirror generally has 2 motors, corresponding to the electric adjustment of the lens left and right rotation and up and down rotation; the interior rearview mirror generally has 2 motors, corresponding to the electric adjustment of the lens left and right rotation and up and down rotation; the central control screen generally has 2 motors, corresponding to the electric adjustment of the screen left and right rotation and up and down rotation; the sun visor generally has 1 motor, corresponding to the electric adjustment of its front and back rotation; the central armrest generally has 1 motor, corresponding to the electric adjustment of its front and back translation.

[0085] This application takes into account the current adjustment of the driver's driving posture, which can be divided into two contents: adjustment before driving and adjustment during driving. Adjustment before driving mainly includes seats, seat belts, internal and external rearview mirrors, etc.; adjustment during driving mainly includes central control screen, sun visor, etc. In the current technology, seats, rearview mirrors, steering wheels, etc. need to be manually adjusted to the required position, which cannot meet the development trend of intelligence and personalization. A method for automatic adjustment of related motor components based on the driver's driving posture is proposed, which can realize intelligent, personalized and adaptive adjustment, and can be completed without manual intervention of the driver, thereby improving the driving experience and meeting the user's demand for vehicle intelligence.

[0086] Through the above technical scheme, the intelligent driving mode adjustment method provided by the present invention solves the problem that there is still a lack of a more intelligent and humanized control method for the adjustable elements on the vehicle. The present invention obtains the basic information of the driver, wherein the basic information includes height information, eye point position information and head space distance information; determines the optimal adjustment range of the motor component used by the driver through the position function model based on the basic information of the driver; and controls the motor component based on the optimal adjustment range. In the above scheme, the proposed automatic adjustment method of the relevant motor components based on the driver's driving posture identifies and triggers human body information based on different identification methods, and calls the model to drive the position adjustment of each motor component, which can meet the personalized and intelligent driver-related automatic adjustment of the riding, accessibility, and visual related components, and can solve the problem of cumbersome manual adjustment of traditional vehicles, while improving the intelligence of the vehicle.

[0087] Furthermore, as a response to the above Figure 1 In order to realize the method shown in the figure, the embodiment of the present invention also provides an intelligent driving mode adjustment device for adjusting the above Figure 1The device embodiment corresponds to the aforementioned method embodiment. For ease of reading, this device embodiment will not repeat the details of the aforementioned method embodiment one by one, but it should be clear that the device in this embodiment can correspond to all the contents of the aforementioned method embodiment. Figure 5 As shown, the device includes: an acquisition unit 21, a determination unit 22 and a control unit 23, wherein

[0088] An acquisition unit 21 is used to acquire basic information of the driver, wherein the basic information includes height information, eye point position information and head space distance information;

[0089] A determination unit 22, configured to determine an optimal adjustment interval of the motor component used by the driver through a position function model based on the basic information of the driver;

[0090] The control unit 23 is used to control the motor component based on the optimal adjustment interval.

[0091] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and an intelligent driving mode adjustment method is implemented by adjusting kernel parameters, which can solve the problem that there is still a lack of a more intelligent and humanized control method for the adjustable components on the vehicle.

[0092] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, and when the program is executed by a processor, the intelligent driving mode adjustment method is implemented.

[0093] An embodiment of the present invention provides a processor, which is used to run a program, wherein the intelligent driving mode adjustment method is executed when the program is running.

[0094] An embodiment of the present invention provides an electronic device, the electronic device comprising at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the intelligent driving mode adjustment method as described above

[0095] An embodiment of the present invention provides an electronic device 30, such as Figure 6 As shown, the electronic device includes at least one processor 301, and at least one memory 302 and a bus 303 connected to the processor; wherein the processor 301 and the memory 302 communicate with each other through the bus 303; the processor 301 is used to call the program instructions in the memory to execute the above-mentioned intelligent driving mode adjustment method.

[0096] The intelligent electronic devices in this article can be PCs, PADs, mobile phones, etc.

[0097] The present application also provides a computer program product, which, when executed on a process management electronic device, is suitable for executing a program initialized with the above-mentioned intelligent driving mode adjustment method steps.

[0098] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0099] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0100] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0101] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0102] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0103] The present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device is caused to execute the following Figure 1 This corresponds to the flow of control of the memory in the embodiment.

[0104] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)), etc.

[0105] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0106] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0107] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0108] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0109] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0110] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An intelligent driving mode adjustment method, characterized in that: include: Obtaining basic information of the driver, wherein the basic information includes height information, eye point position information and head space distance information; Determining the optimal adjustment range of the motor component used by the driver through a position function model based on the driver basic information; The motor component is controlled based on the optimal regulation interval.

2. The method according to claim 1, characterized in that The obtaining of basic driver information includes: The basic information of the driver is obtained based on touch information, wherein the touch information is triggered by the driver, Or, the basic information of the driver is obtained based on sensors.

3. The method according to claim 1, characterized in that Also includes: Determine a driver data set, wherein the driver data set is divided into a height dimension, an eye point dimension, and a head space dimension; An electric machine adjustment data set is determined based on the driver data set, wherein the electric machine adjustment data set is related to a height dimension, an eye point dimension, and a head space dimension.

4. The method according to claim 3, characterized in that Also includes: constructing the position function model based on the driver data set and the electric mechanism adjustment data set; The position function model is trained based on a neural network, wherein the position function model includes an input layer, a hidden layer and an output layer.

5. The method according to claim 4, characterized in that The relationship between the hidden layer and the input layer is: H=W1*X+b1 Wherein, H is a hidden layer, W1 is a weight coefficient in the first neural network training process between the hidden layer and the input layer, X is an input layer, and b1 is a bias correction amount of the weight coefficient in the first neural network training process; The relationship between the hidden layer and the output layer is: Y=W2*H+b2 Among them, Y is the output layer, W2 is the weight coefficient in the second neural network training process between the hidden layer and the output layer, H is the hidden layer, and b2 is the bias correction amount of the weight coefficient in the second neural network training process.

6. The method according to claim 1, characterized in that The motor components include seats, steering wheels, exterior rearview mirrors, interior rearview mirrors, a central control screen, a sun visor and a central armrest.

7. The method according to claim 1, characterized in that The position function model is stored in the ECU, and the method further includes: Transmitting the basic driver information to the ECU; Calling the position function model based on the ECU to determine the optimal adjustment range of the motor component corresponding to the driver basic information; The electric motor member is controlled by the ECU based on the optimal adjustment interval.

8. An intelligent driving mode adjustment device, characterized in that: Also includes: An acquisition unit, used to acquire basic information of the driver, wherein the basic information includes height information, eye point position information and head space distance information; A determination unit, configured to determine an optimal adjustment interval of the motor component used by the driver through a position function model based on the basic information of the driver; A control unit is used to control the motor component based on the optimal adjustment interval.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the steps of the intelligent driving mode adjustment method according to any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: The electronic device includes at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the steps of the intelligent driving mode adjustment method as described in any one of claims 1 to claim 7.

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