Vehicle seat adjusting method and system and electronic equipment

Abstract

The invention relates to the technical field of automobile seats, and discloses a vehicle seat adjusting method and system and electronic equipment. The method comprises the following steps: acquiring current posture information corresponding to a target vehicle in a current area to obtain a current motion posture of the target vehicle and a current human body posture of a target passenger; predicting a predicted motion posture of the target vehicle and a predicted human body posture of the target passenger according to the turning parameter and the current posture information, thereby performing calculation based on a first posture difference between the current motion posture and the predicted motion posture and a second posture difference between the current human body posture and the predicted human body posture, the seat is adjusted according to the calculated seat adjusting parameters, compared with seat adjustment only through turning parameters or vehicle movement postures, the reference range of seat adjustment is widened, and then the riding safety of passengers is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile seats, and in particular to a vehicle seat adjustment method, system and electronic equipment. Background Art

[0002] With the rapid development of the automobile industry, automobile manufacturing technology is constantly improving, and consumers' demands for automobiles are becoming increasingly diversified. While pursuing excellent automobile performance such as acceleration, braking, and handling stability, car seats, as an important part of car interiors, their design not only affects the convenience of operation for drivers and passengers, but also directly affects the comfort and safety of riding.

[0003] During the driving process, especially when turning, due to inertia, the passenger's body tends to maintain the original straight-line motion state, which may cause the passenger's body to tilt or even fall. By adjusting the turning radius to control the vehicle's driving trajectory and using the vehicle posture control system to dynamically adjust the tilt angle of the body, better support and balance can be provided to the passengers, offsetting the impact of inertia on the passengers to a certain extent.

[0004] However, differences in passengers' sitting postures when turning, such as leaning forward, backward or lateral deviation, will have different effects on the body posture under the action of inertia. It is still difficult to completely avoid the risk of passengers tipping over when turning by simply adjusting the turning radius or automatically controlling the vehicle's posture. Especially in extreme situations such as high-speed driving or sharp turns, the reference range of seat adjustment is small and the safety of passengers may still be threatened. Summary of the invention

[0005] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical components or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0006] In view of the above-mentioned shortcomings of the prior art, the present application provides a vehicle seat adjustment method, system and electronic device to improve the reference range of seat adjustment, thereby improving passenger safety.

[0007] The present application provides a vehicle seat adjustment method, comprising: obtaining current posture information corresponding to a target vehicle in a current area, wherein the current posture information includes the current motion posture of the target vehicle and the current human body posture of a target passenger in the target vehicle; if there is a turning area in the driving direction of the target vehicle, obtaining target turning parameters of the turning area, and predicting according to the target turning parameters and the current posture information to obtain predicted posture information, wherein the predicted posture information includes the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger; calculating according to a first posture difference between the current motion posture and the predicted motion posture and a second posture difference between the current human body posture and the predicted human body posture to obtain seat adjustment parameters; and adjusting the vehicle seat corresponding to the target passenger according to the seat adjustment parameters.

[0008] In one embodiment of the present application, the current motion posture is obtained in the following manner: an inertial measurement unit is set in the target vehicle; the current motion posture of the target vehicle is collected by the inertial measurement unit, wherein the current motion posture includes at least one of current acceleration, current angular velocity, current yaw angle, current pitch angle and current roll angle.

[0009] In one embodiment of the present application, the predicted motion posture is obtained in the following manner: the target vehicle is modeled according to the vehicle dynamics principle to obtain a vehicle motion model; the current motion posture and the target turning parameters are passed into the vehicle motion model, and the motion posture of the target vehicle is predicted through the vehicle motion model using the Kalman filter theory to obtain a predicted motion posture.

[0010] In one embodiment of the present application, the current human body posture is obtained in the following manner: an image sensor and / or a pressure sensor is pre-arranged on the target vehicle; an image of the target passenger is captured by the image sensor to obtain a current passenger image, and / or a weight parameter of the target passenger is captured by a pressure sensor; key point identification is performed on the target passenger based on the current passenger image to obtain human body key points and key point coordinates corresponding to the human body key points, and calculations are performed based on the key point coordinates to obtain key point angles and / or key point distances; the current human body posture is generated based on at least one of the human body key points, the key point coordinates, the key point angles, the key point distances, and the weight parameters.

[0011] In one embodiment of the present application, the predicted human body posture is obtained in the following manner: a human body posture sequence is obtained, wherein the historical human body posture sequence includes a plurality of time nodes arranged in chronological order, and the time nodes include historical human body postures and historical turning parameters; model training samples with posture labels are extracted from the human body posture sequence to form a model training library, wherein the model training sample is any time node, and the posture label corresponding to the model training sample is a historical human body posture that is one sequence after the model training sample; machine learning is performed using the model training library to obtain a human body posture recognition model; the human body posture of the target passenger is predicted by the human body posture recognition model according to the current human body posture and the target turning parameters to obtain a predicted human body posture.

[0012] In one embodiment of the present application, the target turning parameters of the turning area are obtained, including: obtaining the area distance between the current area and the turning area, and obtaining the turning radius corresponding to the turning area; calculating according to the area distance and the turning radius to obtain the turning angle of the target vehicle when traveling from the current area to the turning area, and using the turning angle as the target turning parameter.

[0013] In one embodiment of the present application, seat adjustment parameters are obtained by calculation based on a first posture difference between the current motion posture and the predicted motion posture, and a second posture difference between the current human body posture and the predicted human body posture, including: establishing a Cartesian coordinate system according to the vehicle seat corresponding to the target passenger to obtain a seat coordinate system; obtaining a first mapping difference by mapping the first posture difference according to the coordinate direction corresponding to the seat coordinate system, and obtaining a second mapping difference by mapping the second posture difference according to the coordinate direction corresponding to the seat coordinate system; and obtaining seat adjustment parameters by calculation based on the first mapping difference and the second mapping difference.

[0014] In one embodiment of the present application, a seat adjustment parameter is obtained by calculation based on the first mapping difference and the second mapping difference, including: obtaining user set parameters, wherein the user set parameters include a first adjustment coefficient corresponding to the first mapping difference and a second adjustment coefficient corresponding to the second mapping difference; adjusting the first mapping difference and the second mapping difference by the first adjustment coefficient and the second adjustment coefficient respectively, and obtaining the seat adjustment parameter by calculation based on the adjusted first mapping difference and second mapping difference.

[0015] The present application provides a vehicle seat adjustment system, comprising: an acquisition module, used to acquire current posture information corresponding to a target vehicle in a current area, wherein the current posture information includes the current motion posture of the target vehicle and the current human body posture of a target passenger in the target vehicle; a prediction module, used to acquire target turning parameters of a turning area if there is a turning area in the driving direction of the target vehicle, and to perform prediction based on the target turning parameters and the current posture information to obtain predicted posture information, wherein the predicted posture information includes the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger; a calculation module, used to perform calculation based on a first posture difference between the current motion posture and the predicted motion posture and a second posture difference between the current human body posture and the predicted human body posture to obtain seat adjustment parameters; an adjustment module, used to perform seat adjustment on the vehicle seat corresponding to the target passenger according to the seat adjustment parameters.

[0016] The present application provides an electronic device, comprising: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the above method.

[0017] Beneficial effects of this application:

[0018] By acquiring the current posture information corresponding to the target vehicle in the current area, the current motion posture of the target vehicle and the current human body posture of the target passenger are obtained, and before the target vehicle enters the turning area, the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger are predicted based on the turning parameters and the current posture information, so as to calculate based on the first posture difference between the current motion posture and the predicted motion posture, and the second posture difference between the current human body posture and the predicted human body posture, and perform seat adjustment according to the calculated seat adjustment parameters. In this way, compared with seat adjustment only through turning parameters or vehicle motion posture, the motion posture of the target vehicle and the current human body posture of the target passenger are obtained, and the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger are predicted in combination with the turning parameters, so that the turning parameters, vehicle motion posture, and passenger human body posture are combined to perform seat adjustment, thereby improving the reference range of seat adjustment and thus improving the riding safety of passengers. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flow chart of a vehicle seat adjustment method in an embodiment of the present application;

[0020] Figure 2 is a flow chart of a method for acquiring a current human body posture in an embodiment of the present application;

[0021] Figure 3It is a flowchart of a method for predicting human body posture acquisition in an embodiment of the present application;

[0022] Figure 4 is a flow chart of another vehicle seat adjustment method in an embodiment of the present application;

[0023] Figure 5 is a structural schematic diagram of a vehicle seat adjustment system in an embodiment of the present application;

[0024] Figure 6 It is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and sub-samples in the embodiments can be combined with each other without conflict.

[0026] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0027] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0028] The terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so that the embodiments of the embodiments of the present disclosure described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.

[0029] Unless otherwise stated, the term "plurality" means two or more.

[0030] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B indicates: A or B.

[0031] The term "and / or" is a description of the association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.

[0032] Combination Figure 1 As shown, the embodiment of the present disclosure provides a vehicle seat adjustment method, comprising:

[0033] Step S101, obtaining current posture information corresponding to the target vehicle in the current area;

[0034] The current posture information includes the current motion posture of the target vehicle and the current human posture of the target passenger in the target vehicle;

[0035] Step S102, if there is a turning area in the driving direction of the target vehicle, then obtaining a target turning parameter of the turning area, and performing prediction based on the target turning parameter and the current posture information to obtain predicted posture information;

[0036] The predicted posture information includes the predicted motion posture of the target vehicle and the predicted human posture of the target passenger;

[0037] Step S103, calculating according to a first posture difference between the current motion posture and the predicted motion posture, and a second posture difference between the current human body posture and the predicted human body posture, to obtain a seat adjustment parameter;

[0038] Step S104: adjusting the vehicle seat corresponding to the target passenger according to the seat adjustment parameters.

[0039] The vehicle seat adjustment method provided by the embodiment of the present disclosure is adopted, by obtaining the current posture information corresponding to the target vehicle in the current area, the current motion posture of the target vehicle and the current human body posture of the target passenger are obtained, and before the target vehicle enters the turning area, the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger are predicted according to the turning parameters and the current posture information, so as to calculate based on the first posture difference between the current motion posture and the predicted motion posture, and the second posture difference between the current human body posture and the predicted human body posture, and perform seat adjustment according to the calculated seat adjustment parameters. In this way, compared with seat adjustment performed only by turning parameters or vehicle motion posture, the motion posture of the target vehicle and the current human body posture of the target passenger are obtained, and the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger are predicted in combination with the turning parameters, so that the turning parameters, the vehicle motion posture, and the passenger human body posture are combined to perform seat adjustment, thereby improving the reference range of seat adjustment, and thus improving the riding safety of passengers.

[0040] Optionally, obtaining the target turning parameters of the turning area includes: obtaining the area distance between the current area and the turning area, and obtaining the turning radius corresponding to the turning area; calculating according to the area distance and the turning radius to obtain the turning angle of the target vehicle from the current area to the turning area, and using the turning angle as the target turning parameter.

[0041] In some embodiments, a high-precision map or a GPS (Global Positioning System) positioning system is used to obtain precise location information of the target vehicle's current area and the turning area it is about to enter; the regional distance between the current area and the turning area is calculated using the Euclidean distance, and the road features of the turning area are identified through map data or sensors to determine the turning radius, wherein the turning radius is a direct reflection of the road curvature, which can usually be pre-acquired in the map data, or obtained through real-time perception when the vehicle approaches the turning area; the turning angle of the target vehicle from the current area to the turning area is calculated based on the regional distance and the turning radius, and in actual applications, due to the influence of factors such as road conditions, vehicle performance, and traffic conditions, the calculation of the turning angle may need to be further adjusted. Considering the steering system characteristics of the vehicle and the lateral stiffness of the tires, an adjustment coefficient may need to be introduced to correct the calculated turning angle.

[0042] In some embodiments, the area distance between the current area and the turning area is obtained by formula (1):

[0043]

[0044] In formula (1), d is the distance between the current area and the turning area, x destination is the map horizontal coordinate corresponding to the turning area, x current is the horizontal coordinate of the map corresponding to the current area, y destination is the map ordinate corresponding to the turning area, y current The vertical coordinate of the map corresponding to the current area.

[0045] In some embodiments, the turning angle of the target vehicle from the current area to the turning area is obtained by formula (2):

[0046]

[0047] In formula (2), θ 角 is the turning angle in degrees, θ 弧 is the turning angle in radians, and R is the turning radius corresponding to the turning area.

[0048] Optionally, the current motion posture is obtained in the following manner: an inertial measurement unit is set in the target vehicle; the current motion posture of the target vehicle is collected through the inertial measurement unit, wherein the current motion posture includes at least one of current acceleration, current angular velocity, current yaw angle, current pitch angle and current roll angle.

[0049] In some embodiments, the inertial measurement unit (IMU) uses a six-axis inertial measurement unit or a nine-axis inertial measurement unit. The inertial measurement unit measures the acceleration, angular velocity and direction of the vehicle through a combination of a gyroscope and an accelerometer. The inertial measurement unit is installed under the vehicle chassis through a fixed bracket, close to the center of gravity of the vehicle, to reduce the impact of vehicle vibration on measurement accuracy. At the same time, ensure that the inertial measurement unit is connected to the CAN (Controller Area Network) bus, Bluetooth or Wi-Fi (Wireless LAN). Fidelity, wireless local area network technology) is connected to the data acquisition system of the vehicle; the zero bias, scale factor and cross-axis sensitivity of the inertial measurement unit are adjusted to ensure the accuracy of the measurement data; the current motion posture data of the vehicle is collected in real time through the inertial measurement unit, including the current acceleration, the current angular velocity, the current yaw angle, the current pitch angle and the current roll angle, wherein the current acceleration includes the acceleration of the vehicle along the X-axis, the Y-axis and the Z-axis respectively, the current angular velocity includes the rotation rate of the vehicle along the X-axis, the Y-axis and the Z-axis respectively, the current yaw angle includes the rotation angle of the vehicle around the vertical axis, the current pitch angle includes the rotation angle of the vehicle around the front and rear axes, and the current roll angle includes the rotation angle of the vehicle around the left and right axes; the collected data is further processed and analyzed, including steps such as data filtering, noise removal, attitude estimation and error correction, so as to improve the accuracy and reliability of the data.

[0050] Optionally, the predicted motion posture is obtained in the following manner: the target vehicle is modeled according to the vehicle dynamics principle to obtain a vehicle motion model; the current motion posture and target turning parameters are passed into the vehicle motion model, and the motion posture of the target vehicle is predicted through the vehicle motion model using Kalman filtering theory to obtain a predicted motion posture.

[0051] In some embodiments, a kinematic model of the vehicle is established based on Newton's second law and the principle of rigid body dynamics. The kinematic model takes into account the longitudinal acceleration, lateral acceleration, yaw acceleration, pitch acceleration and roll acceleration of the vehicle, as well as the relationship between these accelerations and parameters such as vehicle driving force, braking force, steering angle, tire grip, etc. At the same time, the model parameters of the kinematic model also include vehicle mass, moment of inertia, tire radius, suspension system parameters, air resistance coefficient, etc.; according to the vehicle dynamics principle, a state equation of the vehicle is established to describe the relationship between the vehicle's motion states such as speed, position, and posture at different time points, and an observation equation is established to characterize the relationship between the current motion posture measured by the inertial measurement unit and the actual posture of the vehicle through the observation equation; the initial states such as the initial speed, position, and posture of the Kalman filter are set, and an initial covariance matrix for describing the uncertainty of the state estimation is set; the current motion posture and target turning parameters are used as input, and the state is predicted through the vehicle motion model to obtain the predicted state at the next time point, and the state prediction and observation update process is repeated to obtain the predicted motion posture of the vehicle at different time points through iterative calculation.

[0052] Combination Figure 2 As shown, the current human body posture is obtained by:

[0053] Step S201, pre-installing an image sensor and / or a pressure sensor on a target vehicle;

[0054] Step S202, collecting an image of the target passenger using an image sensor to obtain a current passenger image, and / or collecting a weight parameter of the target passenger using a pressure sensor;

[0055] Step S203, performing key point recognition on the target passenger according to the current passenger image, obtaining key points of the human body and key point coordinates corresponding to the key points of the human body, and performing calculations according to the key point coordinates to obtain key point angles and / or key point distances;

[0056] Step S204, generating a current human body posture according to at least one of human body key points, key point coordinates, key point angles, key point distances, and weight parameters.

[0057] In some embodiments, the key points of the human body include at least a part of the head, neck, back, waist, buttocks, thighs, calves and movable joints; by calculating the key point coordinates of the key points of the human body, the key point distances such as the target passenger's height, shoulder width, hip width, etc. are obtained, and the key point angles such as the elbow bending angle and the angle between the head and back are obtained.

[0058] In some embodiments, a high-definition camera is installed above the seat area of ​​the target vehicle as an image sensor to ensure that the camera's field of view can fully cover the passenger's upper body to the thigh, and each key point will have a corresponding key point coordinate, indicating its position in the image; a pressure distribution sensor is embedded inside the seat to accurately measure the pressure distribution of the passenger when sitting, thereby estimating the weight; a deep learning model trained based on the OpenPose model or the DeepLabCut model is used to identify the key points of the human body in the current passenger image, and identify key points such as the head, neck, back, waist, buttocks, thighs, calves, and major movable joints; based on the identified key point coordinates, the target passenger's height, shoulder width, hip width and other key point distances are calculated, where the height is estimated from the distance from the head to the sole of the foot, which needs to be corrected in combination with the seat height; the elbow bending angle is calculated by calculating the key point coordinates of the elbow joint, shoulder joint, and wrist, and the angle between the head and the back is calculated by calculating the key point coordinates of the head, neck, and back, and so on; a three-dimensional human posture model of the current passenger is constructed by combining the human key points, key point coordinates, key point angles, key point distances, and weight parameters to obtain the current human posture.

[0059] Combination Figure 3 As shown, the predicted human posture is obtained by:

[0060] Step S301, obtaining a human body posture sequence;

[0061] The historical human posture sequence includes a plurality of time nodes arranged in chronological order, and the time nodes include historical human postures and historical turning parameters;

[0062] Step S302, extracting model training samples with posture labels from the human posture sequence to form a model training library;

[0063] The model training sample is any time node, and the posture label corresponding to the model training sample is a historical human posture that is one sequence after the model training sample;

[0064] Step S303, using the model training library to perform machine learning to obtain a human posture recognition model;

[0065] Step S304: predicting the target passenger's body posture according to the current body posture and the target turning parameter by using a body posture recognition model to obtain a predicted body posture.

[0066] In some embodiments, when the car turns, the passenger's body posture will deflect, and the current human body posture collected over a period of time is input into the human body posture recognition model to predict the change in the target passenger's body posture at the turn.

[0067] Optionally, seat adjustment parameters are obtained by calculation based on a first posture difference between the current motion posture and the predicted motion posture, and a second posture difference between the current human body posture and the predicted human body posture, including: establishing a Cartesian coordinate system according to the vehicle seat corresponding to the target passenger to obtain a seat coordinate system; obtaining a first mapping difference by mapping the first posture difference according to the coordinate direction corresponding to the seat coordinate system, and obtaining a second mapping difference by mapping the second posture difference according to the coordinate direction corresponding to the seat coordinate system; and obtaining seat adjustment parameters by calculation based on the first mapping difference and the second mapping difference.

[0068] In some embodiments, a fixed point such as the center of the bottom of the vehicle seat is selected as the origin to establish a Cartesian coordinate system, i.e., a seat coordinate system, which includes an X-axis representing the left-right direction, a Y-axis representing the front-back direction, and a Z-axis representing the up-down direction; considering the impact of the vehicle posture on the passenger's sitting posture, the first posture difference is calculated using the vehicle's yaw angle, pitch angle, and roll angle, and the second posture difference is calculated by comparing the key point coordinates and key point angles in the current human body posture and the predicted human body posture; the first posture difference and the second posture difference are decomposed into components in the three directions of X, Y, and Z to obtain a first mapping difference and a second mapping difference; based on the first mapping difference and the second mapping difference, the vehicle posture changes and the passenger's own sitting posture changes are comprehensively considered to calculate seat adjustment parameters, such as the seat forward and backward movement, the seat up and down lifting amount, the seat tilt angle adjustment amount, etc.

[0069] In some embodiments, the vehicle yaw angle, vehicle pitch angle, and vehicle roll angle are extracted from the current motion posture and the predicted motion posture, and a first posture difference is calculated based on the extracted vehicle yaw angle, vehicle pitch angle, and vehicle roll angle. The calculation formula of the first posture difference is shown in formula (3):

[0070]

[0071] In formula (3), Δφ is the yaw angle difference in the first posture difference, φ 预测 To predict the vehicle yaw angle in motion posture, φ 当前 is the vehicle yaw angle in the current motion posture, Δθ is the pitch angle difference in the first posture difference, θ 预测 To predict the vehicle pitch angle in motion posture, θ 当前 is the vehicle pitch angle in the current motion posture, Δψ is the tilt angle difference in the first posture difference, ψ 预测 To predict the vehicle tilt angle in motion posture, ψ 当前 is the vehicle's tilt angle in the current motion posture.

[0072] In some embodiments, key point coordinates and key point angles are extracted from the current human body posture and the predicted human body posture, and the second posture difference is calculated based on the extracted key point coordinates and key point angles; if the number of human body key points is n and the number of key point angles is m, the calculation formula of the second posture difference is as shown in formula (4):

[0073]

[0074] In formula (4), Δx i is the horizontal coordinate difference of the i-th human key point, x′ i is the horizontal coordinate of the key point of the i-th human body key point in the predicted human body posture, x i is the horizontal coordinate of the key point of the i-th human body key point in the current human body posture, Δy i is the vertical coordinate difference of the i-th human key point, y′ i is the vertical coordinate of the key point of the i-th human body key point in the predicted human body posture, y i is the key point ordinate of the i-th human key point in the current human posture, i is a positive integer and i∈[1, n]; is the angle difference of the jth key point angle, To predict the jth key point angle of human posture, is the jth key point angle of the current human body posture, j is a positive integer and j∈[1,m].

[0075] Optionally, seat adjustment parameters are obtained by calculation based on the first mapping difference and the second mapping difference, including: obtaining user set parameters, wherein the user set parameters include a first adjustment coefficient corresponding to the first mapping difference and a second adjustment coefficient corresponding to the second mapping difference; adjusting the first mapping difference and the second mapping difference by the first adjustment coefficient and the second adjustment coefficient respectively, and obtaining the seat adjustment parameters by calculation based on the adjusted first mapping difference and the second mapping difference.

[0076] In some embodiments, due to different passenger feelings, the user can adjust the adjustment granularity through the vehicle system, thereby providing each passenger with a personalized seat adjustment experience and improving the flexibility of seat adjustment.

[0077] In some embodiments, the seat is adaptively adjusted during a preset time period before the vehicle enters a turning area. During this preset time period, the user can also determine whether to trigger the seat adjustment.

[0078] In some embodiments, the seat adjustment parameters are calculated by formula (5):

[0079] Δ 调节 =ω1·Δ 车辆 +ω2·Δ乘客 Formula (5)

[0080] In formula (5), Δ 调节 is the seat adjustment parameter, ω1 is the first adjustment coefficient, Δ 车辆 is the first mapping difference, ω2 is the second adjustment coefficient, Δ 乘客 is the second mapping difference.

[0081] Combination Figure 4 As shown, the embodiment of the present disclosure provides a vehicle seat adjustment method, comprising:

[0082] Step S401, identifying that there is a turning area in the driving direction of the target vehicle, and jumping to step S402 and step S403;

[0083] Step S402, collecting the current motion posture of the target vehicle in the current area by an inertial measurement unit arranged on the target vehicle, and then jumping to step S404;

[0084] Step S403, collecting the current human posture of the target passenger in the current area by using an image sensor and / or a pressure sensor provided in the target vehicle, and then jumping to step S404;

[0085] Step S404, calculating according to the area distance between the current area and the turning area and the turning radius corresponding to the turning area, obtaining the target turning parameter, and jumping to step S405 and step S407;

[0086] Step S405, the current motion posture and the target turning parameter are input into the vehicle motion model, and the motion posture of the target vehicle is predicted by the vehicle motion model using Kalman filter theory to obtain a predicted motion posture;

[0087] Step S406, determining a first posture difference according to the current motion posture and the predicted motion posture, and jumping to step S409;

[0088] Step S407, predicting the human body posture of the target passenger according to the current human body posture and the target turning parameter by using a human body posture recognition model to obtain a predicted human body posture;

[0089] Step S408, determining a second posture difference according to the current human body posture and the predicted human body posture, and jumping to step S409;

[0090] Step S409, calculating according to the first posture difference and the second posture difference to obtain a seat adjustment parameter;

[0091] Step S410: adjusting the vehicle seat corresponding to the target passenger according to the seat adjustment parameters.

[0092] The vehicle seat adjustment method provided by the embodiment of the present disclosure is adopted, by obtaining the current posture information corresponding to the target vehicle in the current area, the current motion posture of the target vehicle and the current human body posture of the target passenger are obtained, and before the target vehicle enters the turning area, the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger are predicted according to the turning parameters and the current posture information, so as to calculate based on the first posture difference between the current motion posture and the predicted motion posture, and the second posture difference between the current human body posture and the predicted human body posture, and perform seat adjustment according to the calculated seat adjustment parameters. In this way, compared with seat adjustment performed only by turning parameters or vehicle motion posture, the motion posture of the target vehicle and the current human body posture of the target passenger are obtained, and the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger are predicted in combination with the turning parameters, so that the turning parameters, the vehicle motion posture, and the passenger human body posture are combined to perform seat adjustment, thereby improving the reference range of seat adjustment, and thus improving the riding safety of passengers.

[0093] Combination Figure 5 As shown, an embodiment of the present disclosure provides a vehicle seat adjustment system, including an acquisition module 501 , a prediction module 502 , a calculation module 503 and an adjustment module 504 .

[0094] The acquisition module 501 is used to acquire the current posture information corresponding to the target vehicle in the current area, wherein the current posture information includes the current motion posture of the target vehicle and the current body posture of the target passenger in the target vehicle.

[0095] The prediction module 502 is used to obtain the target turning parameters of the turning area if there is a turning area in the driving direction of the target vehicle, and to make predictions based on the target turning parameters and current posture information to obtain predicted posture information, wherein the predicted posture information includes the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger.

[0096] The calculation module 503 is used to calculate according to a first posture difference between the current motion posture and the predicted motion posture, and a second posture difference between the current human body posture and the predicted human body posture, to obtain a seat adjustment parameter.

[0097] The adjustment module 504 is used to adjust the vehicle seat corresponding to the target passenger according to the seat adjustment parameters.

[0098] The vehicle seat adjustment system provided by the embodiment of the present disclosure obtains the current posture information corresponding to the target vehicle in the current area, obtains the current motion posture of the target vehicle and the current human body posture of the target passenger, and predicts the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger according to the turning parameters and the current posture information before the target vehicle enters the turning area, thereby performing calculations based on the first posture difference between the current motion posture and the predicted motion posture and the second posture difference between the current human body posture and the predicted human body posture, and performing seat adjustment according to the calculated seat adjustment parameters. In this way, compared with seat adjustment performed only by turning parameters or vehicle motion posture, the motion posture of the target vehicle and the current human body posture of the target passenger are obtained, and the predicted motion posture of the target vehicle and the predicted human body posture of the target passenger are predicted in combination with the turning parameters, thereby combining the turning parameters, the vehicle motion posture, and the passenger's human body posture to perform seat adjustment, thereby improving the reference range of seat adjustment, and thereby improving the riding safety of passengers.

[0099] An embodiment of the present disclosure further provides an electronic device, including: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the above method.

[0100] Figure 6 The structure diagram of the computer system suitable for implementing the electronic device of the embodiment of the present application is shown. It should be noted that: Figure 6 The computer system 600 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0101] like Figure 6 As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage part 608 to the random access memory (RAM) 603, such as executing the method in the above embodiment. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, ROM 602 and RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0102] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed so that a computer program read therefrom is installed into the storage section 608 as needed.

[0103] The electronic device disclosed in this embodiment includes a processor, a memory, a transceiver and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication with each other. The memory is used to store computer programs, the communication interface is used to communicate, and the processor and the transceiver are used to run the computer program so that the electronic device executes each step of the above method.

[0104] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent possible changes only. Unless explicitly required, separate components and functions are optional, and the order of operation can be changed. Parts and sub-samples of some embodiments may be included in or replace parts and sub-samples of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and the claims, unless the context clearly indicates, the singular forms of "a", "an" and "the" are intended to include plural forms as well. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of listings containing one or more associated ones. In addition, when used in the present application, the term "comprise" and its variants "comprises" and / or comprising refer to the presence of a stated sub-sample, whole, step, operation, element, and / or component, but do not exclude the presence or addition of one or more other sub-samples, wholes, steps, operations, elements, components and / or groups of these. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the presence of other identical elements in the process, method or device comprising the elements. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments may refer to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can refer to the description of the method part.

[0105] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. Technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present disclosure. Technicians can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0106] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units can be only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some sub-samples can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to implement this embodiment. In addition, each functional unit in the embodiment of the present disclosure may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit.

[0107] The flowchart and block diagram in the accompanying drawings show the possible architecture, functions and operations of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and a part of the module, program segment or code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A vehicle seat adjustment method, characterized in that: include: Acquire current posture information corresponding to the target vehicle in the current area, wherein the current posture information includes the current motion posture of the target vehicle and the current human posture of the target passenger in the target vehicle; If there is a turning area in the driving direction of the target vehicle, a target turning parameter of the turning area is obtained, and prediction is performed according to the target turning parameter and the current posture information to obtain predicted posture information, wherein the predicted posture information includes a predicted motion posture of the target vehicle and a predicted human body posture of the target passenger; Calculating according to a first posture difference between the current motion posture and the predicted motion posture, and a second posture difference between the current human body posture and the predicted human body posture, to obtain a seat adjustment parameter; The vehicle seat corresponding to the target passenger is adjusted according to the seat adjustment parameters.

2. The method according to claim 1, characterized in that Get the current motion posture by: providing an inertial measurement unit on the target vehicle; The current motion posture of the target vehicle is collected by the inertial measurement unit, wherein the current motion posture includes at least one of a current acceleration, a current angular velocity, a current yaw angle, a current pitch angle, and a current roll angle.

3. The method according to claim 1 or 2, characterized in that: Get the predicted motion pose by: Modeling the target vehicle according to the vehicle dynamics principle to obtain a vehicle motion model; The current motion posture and the target turning parameter are transmitted to the vehicle motion model, and the motion posture of the target vehicle is predicted by the vehicle motion model using Kalman filter theory to obtain a predicted motion posture.

4. The method according to claim 1, characterized in that: Get the current human body posture by: Pre-arrange an image sensor and / or a pressure sensor on the target vehicle; Capturing an image of the target passenger using an image sensor to obtain a current passenger image, and / or capturing a weight parameter of the target passenger using a pressure sensor; Performing key point recognition on the target passenger according to the current passenger image to obtain key points of the human body and key point coordinates corresponding to the key points of the human body, and performing calculations according to the key point coordinates to obtain key point angles and / or key point distances; The current human body posture is generated according to at least one of the human body key points, the key point coordinates, the key point angles, the key point distances, and the weight parameters.

5. The method according to claim 1 or 4, characterized in that: Get the predicted human pose by: Acquire a human body posture sequence, wherein the historical human body posture sequence includes a plurality of time nodes arranged in chronological order, and the time nodes include historical human body postures and historical turning parameters; Extracting model training samples with posture labels from the human posture sequence to form a model training library, wherein the model training sample is any time node, and the posture label corresponding to the model training sample is a historical human posture located at a sequence after the model training sample; Using the model training library to perform machine learning to obtain a human posture recognition model; The human body posture recognition model is used to predict the human body posture of the target passenger according to the current human body posture and the target turning parameter to obtain a predicted human body posture.

6. The method according to claim 1, characterized in that Obtaining target turning parameters of the turning area includes: Obtaining the area distance between the current area and the turning area, and obtaining the turning radius corresponding to the turning area; A calculation is performed based on the area distance and the turning radius to obtain a turning angle of the target vehicle when it travels from the current area to the turning area, and the turning angle is used as a target turning parameter.

7. The method according to claim 1, characterized in that Calculating according to a first posture difference between the current motion posture and the predicted motion posture, and a second posture difference between the current human body posture and the predicted human body posture, to obtain a seat adjustment parameter, including: Establishing a Cartesian coordinate system according to the vehicle seat corresponding to the target passenger to obtain a seat coordinate system; A first mapping difference is obtained by mapping the first posture difference according to a coordinate direction corresponding to a seat coordinate system, and a second mapping difference is obtained by mapping the second posture difference according to a coordinate direction corresponding to the seat coordinate system; A seat adjustment parameter is obtained by performing calculation according to the first mapping difference and the second mapping difference.

8. The method according to claim 7, characterized in that Calculating according to the first mapping difference and the second mapping difference to obtain a seat adjustment parameter includes: Acquire user-set parameters, wherein the user-set parameters include a first adjustment coefficient corresponding to the first mapping difference and a second adjustment coefficient corresponding to the second mapping difference; The first mapping difference and the second mapping difference are adjusted respectively by using the first adjustment coefficient and the second adjustment coefficient, and a seat adjustment parameter is obtained by performing calculation according to the adjusted first mapping difference and second mapping difference.

9. A vehicle seat adjustment system, characterized in that: include: An acquisition module, used to acquire current posture information corresponding to the target vehicle in the current area, wherein the current posture information includes the current motion posture of the target vehicle and the current human posture of the target passenger in the target vehicle; A prediction module, configured to obtain target turning parameters of the turning area if there is a turning area in the driving direction of the target vehicle, and to perform prediction based on the target turning parameters and the current posture information to obtain predicted posture information, wherein the predicted posture information includes the predicted motion posture of the target vehicle and the predicted human posture of the target passenger; a calculation module, configured to calculate according to a first posture difference between the current motion posture and the predicted motion posture, and a second posture difference between the current human body posture and the predicted human body posture, to obtain a seat adjustment parameter; An adjustment module is used to adjust the vehicle seat corresponding to the target passenger according to the seat adjustment parameters.

10. An electronic device, characterized in that: include: Processor and memory; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the method according to any one of claims 1 to 8.

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