Method and system for adjusting self-adaptive touch sensitivity of touch screen

Abstract

The invention relates to the technical field of virtual magnetic field touch sensitivity adjustment, in particular to a self-adaptive touch sensitivity adjustment method and system for a touch screen. The method is used for performing adaptive touch sensitivity adjustment by creating the virtual magnetic field model to improve the touch precision of the vehicle-mounted touch screen; parameters of the touch points are obtained, and the vibration frequency and the vibration strength in the vehicle driving process are obtained; according to the UI element characteristics, creating a dynamic button magnetic field model for adsorbing a touch behavior of a user; a vibration frequency characteristic adaptive adjustment method is designed by analyzing the vibration frequency characteristic of the vehicle; self-adaptive magnetic control is set according to different UI element button functions; predicting a touch track by using a first track prediction algorithm, and enhancing the magnetic field of the target area in advance according to the predicted track; the future touch position is predicted by analyzing the nearest touch track and speed of the user, the operation intention of the user is recognized, and adaptive adjustment of the predictive magnetic field is carried out.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual magnetic field touch sensitivity adjustment, and in particular to a touch screen adaptive touch sensitivity adjustment method and system. Background Art

[0002] With the rise of intelligent technology, touchscreens have become the primary means of user-device interaction. However, touchscreen sensitivity requirements vary across different usage environments and user behaviors. With the rapid development of smart cars, the demand for touchscreen sensitivity adjustment during driving has further intensified. Under specific driving conditions, touchscreen sensitivity is affected by factors such as vibration, vehicle speed, and driver status. Therefore, it is necessary to develop adaptive touch sensitivity adjustment methods that can adapt to vehicle vibration and enhance user touch response. This approach can effectively reduce false touches, improve operational efficiency, and ultimately enhance user satisfaction. Summary of the Invention

[0003] (1) Technical problems to be solved

[0004] The purpose of the present invention is to provide a method and system for adaptive touch sensitivity adjustment of a touch screen, which creates a dynamic button magnetic field model to adjust the differentiated distribution of the magnetic field and sets adaptive magnetic control according to the button functions of different UI elements; uses a first trajectory prediction algorithm to predict the touch trajectory, identify the user's operation intention, and perform predictive magnetic field adaptive adjustment.

[0005] (2) Technical solution

[0006] To achieve the above objectives, the present invention provides a method for adaptively adjusting the touch sensitivity of a touch screen. For an in-vehicle touch screen, the method improves the touch accuracy of the in-vehicle touch screen by adaptively adjusting the touch sensitivity by creating a virtual magnetic field model. The method comprises the following steps:

[0007] Step S1, obtaining parameters of the touch point, including coordinate position, velocity, acceleration, touch point pressure value and touch point contact area; obtaining vibration frequency and vibration intensity during vehicle driving.

[0008] Step S2: creating a dynamic button magnetic field model based on the UI element characteristics to absorb the user's touch behavior. The dynamic button magnetic field model is gradient distributed with the UI element button as the core.

[0009] Step S3, based on the vibration frequency obtained during vehicle driving, by analyzing the frequency characteristics of vehicle vibration, a vibration frequency characteristic adaptive adjustment method is designed, wherein the vibration frequency characteristic adaptive adjustment method is to perform differentiated distribution adjustment of the magnetic field for different vibration frequencies; and set adaptive magnetic control according to the functions of different UI element buttons.

[0010] Step S4: Based on the acquired parameters of the touch point, the touch trajectory is predicted using a first trajectory prediction algorithm, and the magnetic field of the target area is enhanced in advance according to the predicted trajectory; the future touch position is predicted by analyzing the user's recent touch trajectory and speed, the user's operation intention is identified, and predictive magnetic field adaptive adjustment is performed.

[0011] Furthermore, the dynamic button magnetic field model is gradient distributed, including a core area, a close area, a middle area and a far area. The core area is within the button boundary and is set to a preset magnetic value of 1; the close area is 0-20px outside the button and is set to a preset magnetic value of 2; the middle area is 20-40px outside the button and is set to a preset magnetic value of 3; the far area is 40-60px outside the button and is set to a preset magnetic value of 4; the preset magnetic value 1>preset magnetic value 2>preset magnetic value 3>preset magnetic value 4.

[0012] The dynamic button magnetic field model will introduce a formula to calculate the attraction, and the formula is:

[0013] F(d)=k*(1 / (d^2+ε))*v(t);

[0014] Where d is the distance from the touch point to the center of the button; F(d) is the attractive force vector acting on the touch point; k is the base magnetic coefficient; ε is a small constant to prevent division by zero; and v(t) is the current vibration intensity value.

[0015] Furthermore, the vibration frequency characteristic adaptive adjustment method includes:

[0016] By analyzing the frequency characteristics of vehicle vibration, the magnetic distribution is differentiated. Low-frequency vibration with a threshold range of 1-5Hz increases the horizontal magnetic intensity, medium-frequency vibration with a threshold range of 5-15Hz increases the magnetic intensity in all directions, and high-frequency vibration with a threshold range greater than 15Hz increases the vertical magnetic intensity.

[0017] Adaptive magnetic control is set according to the functions of different UI element buttons. The key function buttons are set with a preset magnetic radius A and a preset magnetic strength A, the commonly used function buttons are set with a preset magnetic radius B and a preset magnetic strength B, and the secondary function buttons are set with a preset magnetic radius C and a preset magnetic strength C. The preset magnetic radius A>preset magnetic radius B>preset magnetic radius C, and the preset magnetic strength A>preset magnetic strength B>preset magnetic strength C.

[0018] Furthermore, the method for setting adaptive magnetic control includes:

[0019] Correct the touch points within the magnetic radius from the button center. The correction formula is:

[0020]

[0021] Among them, (x t ,y t ) is the coordinate of the user's touch point; (x b ,y b ) is the coordinate of the center point of the button; d is the distance from the user touch point to the center of the button, R is the physical radius of the button; i∈{A,B,C}; R A is the magnetic radius of the key function button, R B is the magnetic radius of the commonly used function buttons, R C is the magnetic radius of the secondary function button, R A >R B >R C ;d <R i ;M A is the magnetic strength of the key function button, M B is the magnetic strength of the commonly used function buttons, M C is the magnetic strength of the secondary function button, M A >M B >M C ;(x' t ,y′ t ) is the corrected touch coordinate; f(d,R i ) is the magnetic attenuation function based on distance.

[0022] The magnetic force attenuation function is defined as:

[0023]

[0024] Determine whether the button responds based on the corrected user touch coordinates. If The button response is triggered.

[0025] Furthermore, the method of predicting the touch trajectory using the first trajectory prediction algorithm includes:

[0026] The parameters of the touch point are recorded as the state vector X, which includes coordinate position, velocity and acceleration. The state vector is: X = [x, y, Vx, Vy, Ax, Ay] T .

[0027] Where (x, y) is the coordinate position of the touch point on the touch screen; Vx and Vy are the velocity components in the x-axis and y-axis directions; Ax and Ay are the acceleration components in the x-axis and y-axis directions.

[0028] The first trajectory prediction algorithm is used to predict the touch point position at the next moment. The calculation formula is:

[0029] X(k+1)=F·X(k)+B·u(k)+w(k);

[0030] Where X(k) is the state vector of the touch point at the current moment; X(k+1) is the predicted state vector of the touch point at the next moment; F is the state transfer matrix; B is the control input matrix; u(k) is the control input; w(k) is the process noise, which obeys the normal distribution.

[0031] The state transfer matrix F is:

[0032]

[0033] Where Δt is the sampling time interval.

[0034] The control input matrix is ​​the received external control signal parameters, which are converted into changes in the parameter state vector through the matrix B; the control input u(k) is a vector representing the external control signal parameters applied at time k.

[0035] Furthermore, the method for identifying the user's operation intention includes:

[0036] The touch point parameters collected in real time are recorded as a sequence P. The sampling frequency is divided into a preset sampling frequency and a preset dynamic sampling frequency according to the state.

[0037] The sequence P is: P = {(x1, y1, t1, p1, a1), (x2, y2, t2, p2, a2), ..., (x n ,y n ,t n ,p n ,a n )}; x, y are coordinate positions; t is the timestamp; p is the pressure value; and a is the contact area.

[0038] Data preprocessing is used to filter out outliers and obtain data with equal sampling time intervals; velocity vectors, acceleration vectors, and touch point direction changes and curvature are obtained through feature vector extraction; and the user's operation intention is identified by analyzing features such as duration, speed, and trajectory shape; the operation intention includes clicking, dragging, and sliding.

[0039] Furthermore, the method for performing predictive magnetic field adaptive adjustment includes:

[0040] According to the operation intention recognition analysis, when the user's touch point approaches the UI element, the magnetic field strength of the UI element will be automatically enhanced; when the user's touch speed is faster, the attraction range of the magnetic field will be expanded; when in a vibrating environment, the magnetic field strength will be increased according to the vibration intensity.

[0041] Based on the same inventive concept, on the other hand, the present invention also provides a touch screen adaptive touch sensitivity adjustment system, which includes: a first data acquisition module, a dynamic button magnetic field module, an adaptive magnetic field module, and a trajectory prediction and magnetic field adjustment module, and the modules are connected in sequence.

[0042] The first data acquisition module is used to acquire parameters of the touch point, including coordinate position, speed, acceleration, touch point pressure value and contact area; and to acquire vibration frequency and vibration intensity during vehicle driving.

[0043] The dynamic button magnetic field module is used to create a dynamic button magnetic field model according to the characteristics of the UI element. The dynamic button magnetic field model is gradient distributed with the UI element button as the core.

[0044] The adaptive magnetic field module is used to analyze the frequency characteristics of vehicle vibration and design a vibration frequency characteristic adaptive adjustment method. The vibration frequency characteristic adaptive adjustment method is to perform differentiated magnetic field distribution adjustments for vibrations in different frequency bands; and set adaptive magnetic control according to the functions of different UI element buttons.

[0045] The trajectory prediction and magnetic field adjustment module is used to predict the touch trajectory by using a first trajectory prediction algorithm, and enhance the magnetic field of the target area in advance according to the predicted trajectory; predict the future touch position by analyzing the user's recent touch trajectory and speed, identify the user's operation intention, and perform predictive magnetic field adaptive adjustment.

[0046] (3) Beneficial effects

[0047] Compared with the prior art, the beneficial effects of the present invention are: the use of a virtual magnetic field model realizes adaptive touch sensitivity adjustment of the vehicle-mounted touch screen, thereby improving user experience and operation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a flowchart of a method for adaptively adjusting touch sensitivity of a touch screen according to embodiment 1 of the present invention;

[0049] Figure 2 This is a schematic diagram of the module composition of a touch screen adaptive touch sensitivity adjustment system according to embodiment 2 of the present invention. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] Example 1: Figure 1 As shown, this embodiment provides a touch screen adaptive touch sensitivity adjustment method. For an in-vehicle touch screen, the touch sensitivity is adaptively adjusted by creating a virtual magnetic field model to improve the touch accuracy of the in-vehicle touch screen. The method includes the following steps:

[0052] Step S1, obtaining parameters of the touch point, including coordinate position, velocity, acceleration, touch point pressure value and touch point contact area; obtaining vibration frequency and vibration intensity during vehicle driving.

[0053] For example, in the test workshop of an automotive R&D center, engineers conducted touch sensitivity tests on the central control touchscreen of a new generation SUV model under vibration conditions. The test used a 10.4-inch high-definition capacitive touchscreen with a resolution of 1920×1080 pixels and adaptive touch sensitivity adjustment. Testers first collected touch point parameter data. On a road bump simulation device, a slight drift of the touch point coordinate position from (430,525) to (432,528) was detected, with a touch point sliding speed of approximately 75 pixels / second and an acceleration of 25 pixels / second². The vibration frequency simulated by the vibration table was 8.5Hz and the vibration intensity was 0.42g. The touch point pressure value was measured to be 0.82N, and the contact area was approximately 78 square millimeters.

[0054] Step S2: creating a dynamic button magnetic field model based on the UI element characteristics to absorb the user's touch behavior. The dynamic button magnetic field model is gradient distributed with the UI element button as the core.

[0055] It should be noted that UI elements refer to interactive components in the touch screen user interface, including but not limited to buttons, sliders, input boxes, switches, menu items, etc.; in the vehicle environment, the design of UI elements must take driving safety into consideration. Common UI elements include navigation control buttons, media playback controls, temperature adjustment buttons, emergency call buttons, etc.

[0056] The dynamic button magnetic field model is gradient distributed, including a core area, a close area, a middle area and a far area. The core area is within the button boundary and is set to a preset magnetic value of 1; the close area is 0-20px outside the button and is set to a preset magnetic value of 2; the middle area is 20-40px outside the button and is set to a preset magnetic value of 3; the far area is 40-60px outside the button and is set to a preset magnetic value of 4; the preset magnetic value 1>preset magnetic value 2>preset magnetic value 3>preset magnetic value 4.

[0057] The dynamic button magnetic field model will introduce a formula to calculate the attraction, and the formula is:

[0058] F(d)=k*(1 / (d^2+ε))*v(t);

[0059] Where d is the distance from the touch point to the center of the button; F(d) is the attractive force vector acting on the touch point; k is the base magnetic coefficient; ε is a small constant to prevent division by zero; and v(t) is the current vibration intensity value.

[0060] It should be noted that in the attraction calculation formula, k is the basic magnetic coefficient, and the value range is usually 0.5-2.0. The coefficient value will be adjusted according to the importance of the button. Key function buttons are usually set to 1.5-2.0, commonly used function buttons are set to 1.0-1.5, and secondary function buttons are set to 0.5-1.0. v(t) is the current vibration intensity value, in g, and the value range is usually 0.1-1.0. It acts as a multiplicative factor to dynamically adjust the magnetic field strength to adapt to different vibration environments; the closer the touch point distance, the greater the calculated attraction. At the same time, the real-time impact of the vibration environment is taken into account to ensure stronger attraction compensation under strong vibration.

[0061] Step S3, based on the vibration frequency obtained during vehicle driving, by analyzing the frequency characteristics of vehicle vibration, a vibration frequency characteristic adaptive adjustment method is designed, wherein the vibration frequency characteristic adaptive adjustment method is to perform differentiated distribution adjustment of the magnetic field for different vibration frequencies; and set adaptive magnetic control according to the functions of different UI element buttons.

[0062] The vibration frequency characteristic adaptive adjustment method includes: differentiating the magnetic force distribution by analyzing the frequency characteristics of vehicle vibration, low-frequency vibration with a threshold range of 1-5Hz increases the horizontal magnetic force intensity, medium-frequency vibration with a threshold range of 5-15Hz increases the magnetic force intensity in all directions, and high-frequency vibration with a threshold range greater than 15Hz increases the vertical magnetic force intensity.

[0063] It should be noted that during actual vehicle driving, the vibration environment is complex and changeable. For example, when driving smoothly on a highway, the vehicle vibration frequency is usually in the range of 4-5Hz, and the vibration intensity is relatively low, about 0.1-0.2g; when driving on rough roads, the vibration frequency may exceed 15Hz, and the vibration intensity can reach above 0.8g. The vibration frequency characteristic adaptation adjustment method will be designed based on these actual driving scenarios to ensure that a good touch experience can be maintained under different vibration conditions. Through differentiated magnetic force distribution adjustment strategies, the horizontal magnetic force is enhanced for low-frequency vibrations, and the vertical magnetic force is enhanced for high-frequency vibrations, which can effectively compensate for the interference of vibrations of different frequencies on user touch behavior.

[0064] Adaptive magnetic control is set according to the functions of different UI element buttons. The key function buttons are set with a preset magnetic radius A and a preset magnetic strength A, the commonly used function buttons are set with a preset magnetic radius B and a preset magnetic strength B, and the secondary function buttons are set with a preset magnetic radius C and a preset magnetic strength C. The preset magnetic radius A>preset magnetic radius B>preset magnetic radius C, and the preset magnetic strength A>preset magnetic strength B>preset magnetic strength C.

[0065] For example: Under the 3Hz low-frequency vibration simulation, the system increases the horizontal magnetic strength of the navigation button from the default value of 0.65g to 0.85g, so that the touch point can still stably trigger the button when vibrating left and right. When switching to the 12Hz medium-frequency vibration, the all-round magnetic strength is automatically increased from 0.70g to 0.92g, allowing testers to accurately touch the return button even in severe bumps. In the 18Hz high-frequency vibration test, the vertical magnetic strength is increased from 0.68g to 0.95g, so that the volume slider can still be adjusted up and down accurately.

[0066] Correct the touch points within the magnetic radius from the button center. The correction formula is:

[0067]

[0068] Among them, (x t ,y t ) is the coordinate of the user's touch point; (x b ,y b ) is the coordinate of the center point of the button; d is the distance from the user touch point to the center of the button, R is the physical radius of the button; i∈{A,B,C}; R A is the magnetic radius of the key function button, R B is the magnetic radius of the commonly used function buttons, R C is the magnetic radius of the secondary function button, R A >R B >R C ;d <R i ;M A is the magnetic strength of the key function button, M B is the magnetic strength of the commonly used function buttons, M C is the magnetic strength of the secondary function button, M A >M B >M C ;(x' t ,y' t ) is the corrected touch coordinate; f(d,R i ) is the magnetic attenuation function based on distance.

[0069] It should be noted that M A, M B , M C Represents the magnetic strength of buttons of different functional categories, satisfying M A >M B >M C to ensure that important functions have stronger adsorption capacity; f(d,R i ) is a distance-based magnetic attenuation function that ensures that the magnetic effect decays smoothly with distance.

[0070] The magnetic force attenuation function is defined as:

[0071]

[0072] Determine whether the button responds based on the corrected user touch coordinates. If The button response is triggered.

[0073] It should be noted that when the distance d between the touch point and the button center is greater than or equal to the magnetic radius R i When d is less than the magnetic radius R, the function value is 0, indicating that it is not affected by the magnetic field; when d is less than the magnetic radius R i , the function value decreases linearly with increasing distance, achieving a smooth transition from the center of the button outward. Compared to exponential decay or step functions, this linear attenuation model can provide a more natural touch experience and avoid users perceiving abrupt touch point "jumps."

[0074] For example, the emergency call button, a key function, had a magnetic radius of 60 pixels and a magnetic strength of 0.95g; the volume control, a common function, had a magnetic radius of 45 pixels and a magnetic strength of 0.85g; and the theme switch, a secondary function, had a magnetic radius of 30 pixels and a magnetic strength of 0.75g. When simulating a bumpy road, the touch point was 42 pixels from the center of the emergency call button. The magnetic field attracted the actual touch point, correcting it to 18 pixels from the center, successfully triggering the button function.

[0075] Step S4: Based on the acquired parameters of the touch point, the touch trajectory is predicted using a first trajectory prediction algorithm, and the magnetic field of the target area is enhanced in advance according to the predicted trajectory; the future touch position is predicted by analyzing the user's recent touch trajectory and speed, the user's operation intention is identified, and predictive magnetic field adaptive adjustment is performed.

[0076] The method for predicting a touch trajectory using a first trajectory prediction algorithm includes: obtaining parameters of a touch point and recording them as a state vector X, wherein the parameters include coordinate position, velocity, and acceleration, and the state vector is: X = [x, y, Vx, Vy, Ax, Ay] T .

[0077] Where (x, y) is the coordinate position of the touch point on the touch screen; Vx and Vy are the velocity components in the x-axis and y-axis directions; Ax and Ay are the acceleration components in the x-axis and y-axis directions.

[0078] The first trajectory prediction algorithm is used to predict the touch point position at the next moment. The calculation formula is:

[0079] X(k+1)=F·X(k)+B·u(k)+w(k);

[0080] Where X(k) is the state vector of the touch point at the current moment; X(k+1) is the predicted state vector of the touch point at the next moment; F is the state transfer matrix; B is the control input matrix; u(k) is the control input; w(k) is the process noise, which obeys the normal distribution.

[0081] The state transfer matrix F is:

[0082]

[0083] Where Δt is the sampling time interval.

[0084] It should be noted that the state transfer matrix F is established based on Newton's kinematic equations, corresponding to the state updates of position, velocity, and acceleration respectively. The first and second rows represent the updates of the x and y coordinate positions, taking into account the effects of velocity and acceleration; the third and fourth rows represent the updates of the x and y direction velocities, taking into account the effects of acceleration; the fifth and sixth rows represent the assumption that the acceleration remains unchanged in a short period of time. Δt is the sampling time interval, usually 8-16ms. This matrix can accurately simulate the movement of the touch point in a short period of time. The 0.5Δt in the matrix 2 The term comes from the displacement formula Ensure that the prediction model conforms to the laws of physical motion.

[0085] The control input matrix is ​​the received external control signal parameters, which are converted into changes in the parameter state vector through matrix B. The control input u(k) is a vector representing the external control signal parameters applied at time k, mainly considering the impact of vehicle vibration on touch control, and its value is derived from the real-time acquisition of vibration sensor data.

[0086] For example, during testing, it was found that when a user touched the volume slider in a bumpy environment, the touch trajectory exhibited a typical fluctuating pattern. The trajectory prediction algorithm collected the current touch point state vector, including coordinates (650, 320), velocity (85, 10) pixels / second, and acceleration (12, 3) pixels / second², with a sampling interval of 12 milliseconds. The algorithm predicted the next touch point position to be (651, 320), with a deviation of only 1.4 pixels from the actual touch position (652, 321). This enhanced the magnetic field in the volume slider area 0.2 seconds in advance.

[0087] The method for identifying the user's operation intention includes: recording the touch point parameters collected in real time as a sequence P, and the sampling frequency is divided into a preset sampling frequency and a preset dynamic sampling frequency according to the state.

[0088] The sequence P is: P = {(x1, y1, t1, p1, a1), (x2, y2, t2, p2, a2), ..., (x n ,y n ,t n ,p n ,a n )}; x, y are coordinate positions; t is the timestamp; p is the pressure value; and a is the contact area.

[0089] Data preprocessing is used to filter out outliers and obtain data with equal sampling time intervals; velocity vectors, acceleration vectors, and touch point direction changes and curvature are obtained through feature vector extraction; and the user's operation intention is identified by analyzing features such as duration, speed, and trajectory shape; the operation intention includes clicking, dragging, and sliding.

[0090] For example, action intention recognition utilizes a multi-feature analysis method, specifically using the following feature combinations for identification: For click actions, the characteristics are contact duration <300ms, touch point movement distance <15 pixels, and minimal velocity fluctuation; for drag actions, the characteristics are contact duration >300ms, touch point movement distance >15 pixels, relatively constant velocity, and relatively stable pressure; for swipe actions, the characteristics are contact duration typically between 100-500ms, distinct directional movement of the touch point, and high initial acceleration. In the test, a touch point sequence P was sampled at a frequency of 120 times per second, recording a user dragging from point A to point B on a navigation map. Analysis revealed a velocity vector of (42, -15) pixels / second, an acceleration vector of (5, -2) pixels / second², and a touch trajectory curvature of 0.08. This was identified as an intention to drag the map, rather than a click, with a duration exceeding 0.8 seconds, a steady velocity, and a regularly changing trajectory.

[0091] The method for predictive magnetic field adaptive adjustment includes: automatically enhancing the magnetic field strength of the UI element when the user touch point approaches the UI element based on operation intention recognition and analysis; expanding the attraction range of the magnetic field when the user touches at a faster speed; and increasing the magnetic field strength according to the vibration intensity when in a vibration environment to reduce external interference with touch.

[0092] For example, if the system detects a user zooming in or out on a map and detects the touch point approaching a zoom control UI element at a rate of 95 pixels per second, it automatically increases the element's magnetic field strength from 0.75 to 0.92, expanding the magnetic field range from 40 pixels to 55 pixels. If the vehicle experiences a sudden 0.68g vibration, the system immediately increases the magnetic field strength to 0.98, allowing the user to continue zooming accurately without interruption.

[0093] Example 2: Based on the same inventive concept, Figure 2 As shown, this embodiment also provides a touch screen adaptive touch sensitivity adjustment system, which includes: a first data acquisition module, a dynamic button magnetic field module, an adaptive magnetic field module, and a trajectory prediction and magnetic field adjustment module, and the modules are connected in sequence.

[0094] The first data acquisition module is used to acquire parameters of the touch point, including coordinate position, speed, acceleration, touch point pressure value and contact area; and to acquire vibration frequency and vibration intensity during vehicle driving.

[0095] The dynamic button magnetic field module is used to create a dynamic button magnetic field model according to the characteristics of the UI element. The dynamic button magnetic field model is gradient distributed with the UI element button as the core.

[0096] The adaptive magnetic field module is used to analyze the frequency characteristics of vehicle vibration and design a vibration frequency characteristic adaptive adjustment method. The vibration frequency characteristic adaptive adjustment method is to perform differentiated magnetic field distribution adjustments for vibrations in different frequency bands; and set adaptive magnetic control according to the functions of different UI element buttons.

[0097] The trajectory prediction and magnetic field adjustment module is used to predict the touch trajectory by using a first trajectory prediction algorithm, and enhance the magnetic field of the target area in advance according to the predicted trajectory; predict the future touch position by analyzing the user's recent touch trajectory and speed, identify the user's operation intention, and perform predictive magnetic field adaptive adjustment.

[0098] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated on here.

[0099] Finally, it should be noted that although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A touch screen adaptive touch sensitivity adjustment method, characterized in that: For an in-vehicle touch screen, a virtual magnetic field model is created to perform adaptive touch sensitivity adjustment to improve the touch accuracy of the in-vehicle touch screen. The method includes the following steps: Step S1, obtaining parameters of the touch point, including coordinate position, velocity, acceleration, touch point pressure value and touch point contact area; obtaining vibration frequency and vibration intensity during vehicle driving; Step S2: creating a dynamic button magnetic field model based on the UI element characteristics to absorb the user's touch behavior. The dynamic button magnetic field model is gradient distributed with the UI element button as the core; Step S3: Based on the vibration frequency acquired during vehicle driving, by analyzing the frequency characteristics of vehicle vibration, a vibration frequency characteristic adaptive adjustment method is designed. The vibration frequency characteristic adaptive adjustment method comprises differentially adjusting the magnetic field distribution for different vibration frequencies; and setting adaptive magnetic force control according to the functions of different UI element buttons. Step S4: Based on the acquired parameters of the touch point, the touch trajectory is predicted using a first trajectory prediction algorithm, and the magnetic field of the target area is enhanced in advance according to the predicted trajectory; the future touch position is predicted by analyzing the user's recent touch trajectory and speed, the user's operation intention is identified, and predictive magnetic field adaptive adjustment is performed.

2. The method for adaptively adjusting touch sensitivity of a touch screen according to claim 1, wherein: The dynamic button magnetic field model is gradient distributed, including a core area, a near area, a middle area, and a far area. The core area is within the button boundary and is set to a preset magnetic value of 1; the near area is 0-20px outside the button and is set to a preset magnetic value of 2; the middle area is 20-40px outside the button and is set to a preset magnetic value of 3; the far area is 40-60px outside the button and is set to a preset magnetic value of 4; The preset magnetic value 1>preset magnetic value 2>preset magnetic value 3>preset magnetic value 4; The dynamic button magnetic field model will introduce a formula to calculate the attraction, and the formula is: F(d)=k*(1 / (d^2+ε))*v(t); Where d is the distance from the touch point to the center of the button; F(d) is the attractive force vector acting on the touch point; k is the base magnetic coefficient; ε is a small constant to prevent division by zero; and v(t) is the current vibration intensity value.

3. The method for adaptively adjusting touch sensitivity of a touch screen according to claim 1, wherein: The vibration frequency characteristic adaptive adjustment method includes: By analyzing the frequency characteristics of vehicle vibration, the magnetic force distribution is differentiated. Low-frequency vibration with a threshold range of 1-5Hz increases the horizontal magnetic force intensity, medium-frequency vibration with a threshold range of 5-15Hz increases the magnetic force intensity in all directions, and high-frequency vibration with a threshold range greater than 15Hz increases the vertical magnetic force intensity. Adaptive magnetic control is set according to the functions of different UI element buttons. The key function buttons are set with a preset magnetic radius A and a preset magnetic strength A, the commonly used function buttons are set with a preset magnetic radius B and a preset magnetic strength B, and the secondary function buttons are set with a preset magnetic radius C and a preset magnetic strength C. The preset magnetic radius A>preset magnetic radius B>preset magnetic radius C, and the preset magnetic strength A>preset magnetic strength B>preset magnetic strength C.

4. The method for adjusting the touch screen's adaptive touch sensitivity according to claim 3, wherein: The method for setting adaptive magnetic force control includes: Correct the touch points within the magnetic radius from the button center. The correction formula is: Among them, (x t ,y t ) is the coordinate of the user's touch point; (x b ,y b ) is the coordinate of the center point of the button; d is the distance from the user touch point to the center of the button, R is the physical radius of the button; i∈{A,B,C}; R A is the magnetic radius of the key function button, R B is the magnetic radius of the commonly used function buttons, R C is the magnetic radius of the secondary function button, R A >R B >R C ;d <R i ;M A is the magnetic strength of the key function button, M B is the magnetic strength of the commonly used function buttons, M C is the magnetic strength of the secondary function button, M A >M B >M C ;(x' t ,y' t ) is the corrected touch coordinate; f(d,R i ) is the magnetic attenuation function based on distance; The magnetic force attenuation function is defined as: Determine whether the button responds based on the corrected user touch coordinates. If The button response is triggered.

5. The touch screen adaptive touch sensitivity adjustment method according to claim 1, wherein: The method for predicting a touch trajectory using a first trajectory prediction algorithm includes: The parameters of the touch point are recorded as the state vector X, which includes coordinate position, velocity and acceleration. The state vector is: X = [x, y, Vx, Vy, Ax, Ay] T ; Where (x, y) is the coordinate position of the touch point on the touch screen; Vx, Vy are the velocity components in the x-axis and y-axis directions; Ax, Ay are the acceleration components in the x-axis and y-axis directions; The first trajectory prediction algorithm is used to predict the touch point position at the next moment. The calculation formula is: X(k+1)=F·X(k)+B·u(k)+w(k); Where X(k) is the state vector of the touch point at the current moment; X(k+1) is the predicted state vector of the touch point at the next moment; F is the state transfer matrix; B is the control input matrix; u(k) is the control input; w(k) is the process noise, which obeys the normal distribution. The state transfer matrix F is: Wherein, Δt is the sampling time interval; The control input matrix is ​​the received external control signal parameters, which are converted into changes in the parameter state vector through the matrix B; the control input u(k) is a vector representing the external control signal parameters applied at time k.

6. The method for adaptively adjusting touch sensitivity of a touch screen according to claim 5, wherein: The method for identifying the user's operation intention includes: The touch point parameters collected in real time are recorded as sequence P. The sampling frequency is divided into preset sampling frequency and preset dynamic sampling frequency according to the state; The sequence P is: P = {(x1, y1, t1, p1, a1), (x2, y2, t2, p2, a2), ..., (x n ,y n ,t n ,p n ,a n )}; where x, y are coordinate positions; t is the timestamp; p is the pressure value; a is the contact area; Data preprocessing is used to filter out outliers and obtain data with equal sampling time intervals; velocity vectors, acceleration vectors, and touch point direction changes and curvature are obtained through feature vector extraction; and the user's operation intention is identified by analyzing features such as duration, speed, and trajectory shape; the operation intention includes clicking, dragging, and sliding.

7. The method for adaptively adjusting touch sensitivity of a touch screen according to claim 6, wherein: The method for performing predictive magnetic field adaptive adjustment includes: According to the operation intention recognition analysis, when the user's touch point approaches the UI element, the magnetic field strength of the UI element will be automatically enhanced; when the user's touch speed is faster, the attraction range of the magnetic field will be expanded; when in a vibrating environment, the magnetic field strength will be increased according to the vibration intensity.

8. A touch screen adaptive touch sensitivity adjustment system, used to execute the method according to any one of claims 1 to 7, characterized in that: The system includes: a first data acquisition module, a dynamic button magnetic field module, an adaptive magnetic field module, and a trajectory prediction and magnetic field adjustment module, wherein the modules are connected in sequence; The first data acquisition module is used to acquire parameters of the touch point, including coordinate position, velocity, acceleration, touch point pressure value and contact area; and to acquire vibration frequency and vibration intensity during vehicle driving; The dynamic button magnetic field module is used to create a dynamic button magnetic field model according to the characteristics of the UI element. The dynamic button magnetic field model is distributed in a gradient with the UI element button as the core; The adaptive magnetic field module is used to analyze the frequency characteristics of vehicle vibration and design a vibration frequency characteristic adaptive adjustment method. The vibration frequency characteristic adaptive adjustment method is to adjust the magnetic field distribution differentially for vibrations in different frequency bands; and set adaptive magnetic force control according to the functions of different UI element buttons; The trajectory prediction and magnetic field adjustment module is used to predict the touch trajectory by using a first trajectory prediction algorithm, and enhance the magnetic field of the target area in advance according to the predicted trajectory; predict the future touch position by analyzing the user's recent touch trajectory and speed, identify the user's operation intention, and perform predictive magnetic field adaptive adjustment.

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