Method and system for enhancing tactile feedback of in-vehicle smart surfaces

Abstract

The present invention relates to the field of vehicle-mounted intelligent interaction technology, and in particular to a method and system for enhancing tactile feedback of a vehicle-mounted intelligent surface, comprising the following steps: S1: collecting multi-touch input data on the vehicle-mounted intelligent surface and driving status data of the vehicle; S2: correcting the touch point positions in the multi-touch input data using a dynamic weighting algorithm; S3: identifying and eliminating false touch data that does not meet preset conditions; S4: calculating the true position of each touch point and generating a touch point position mapping table; S5: configuring parameters of a tactile feedback system; S6: optimizing the intensity and frequency of tactile feedback in real time to meet the needs under different driving conditions; the present invention optimizes the accuracy and adaptability of tactile feedback of the vehicle-mounted intelligent surface through dynamic weighting and adaptive regression algorithms, effectively reduces data deviations caused by dynamic changes of the vehicle, ensures the real-time and accuracy of tactile feedback, and thus improves the intuitiveness and safety of driving experience.

Description

Technical Field

[0001] The present invention relates to the field of in-vehicle intelligent interaction technology, and in particular to a method and system for enhancing tactile feedback of an in-vehicle intelligent surface. Background Art

[0002] With the continuous development of automobile intelligence, the interaction mode of in-vehicle intelligent systems has gradually become a key technology to enhance the driving experience, especially in the field of tactile feedback of in-vehicle intelligent surfaces. Accurate touch feedback can not only enhance the driver's operating intuition, but also play an important role in improving safety. In current in-vehicle systems, touch feedback technology mainly relies on traditional touch recognition systems. These systems can detect the position of the touch point and certain touch pressure information. However, these systems are often disturbed by the vehicle's own motion state (such as vibration and tilt), which affects the touch accuracy and real-time feedback.

[0003] Existing technologies have obvious deficiencies in dealing with the impact of vehicle dynamic changes on the touch system. For example, when a vehicle is traveling on an uneven road or turning at high speed, due to the influence of vibration and acceleration, existing touch recognition systems often find it difficult to accurately capture and correct the true position of the touch point, resulting in misoperation or delayed response in touch feedback. In addition, existing systems generally do not fully consider changes in touch point pressure and contact area, which limits the adaptability and personalization of tactile feedback.

[0004] Therefore, it is particularly urgent to develop an in-vehicle intelligent surface tactile feedback system that can adapt to vehicle dynamic changes and provide precise touch feedback to ensure the application effect and safety of touch technology in vehicle intelligent systems. Summary of the invention

[0005] Based on the above objectives, the present invention provides a method and system for enhancing tactile feedback of an in-vehicle smart surface.

[0006] The method for enhancing tactile feedback of an in-vehicle smart surface comprises the following steps:

[0007] S1: Collecting multi-touch input data on the vehicle-mounted intelligent surface, the input data including the position, pressure, contact area and dynamic change information of each touch point, and collecting the vehicle's driving status data, the driving status data including speed, direction, acceleration and road condition information;

[0008] S2: Correcting the touch point positions in the multi-touch input data using a dynamic weighting algorithm based on the vehicle's driving state data, so as to reduce the touch data deviation caused by vehicle vibration or tilt;

[0009] S3: performing cluster analysis based on the corrected touch point position data to identify and eliminate false touch data that does not meet preset conditions and screen out valid touch point data;

[0010] S4: performing multi-dimensional modeling on the screened touch point data to calculate the real position of each touch point and generate a touch point position mapping table;

[0011] S5: Based on the touch point position mapping table, configure the parameters of the tactile feedback system so that the tactile feedback response of each touch point can match its actual position, and dynamically adjust the feedback parameters according to the changes in pressure and contact area;

[0012] S6: During vehicle operation, the input data and feedback parameters of the touch points are continuously monitored, and the intensity and frequency of tactile feedback are optimized in real time through the feedback adjustment algorithm to meet the needs under different driving conditions.

[0013] Optionally, the S1 specifically includes:

[0014] S11: Arranging a multi-touch sensor array on the vehicle-mounted smart surface, wherein the sensor array includes a pressure sensor and a capacitive position sensor, for simultaneously detecting the position, pressure, contact area and dynamic change information of each touch point, and transmitting the data to a data processing module through a vehicle-mounted bus interface;

[0015] S12: in the data processing module, preprocessing the collected touch input data, including performing time series analysis on the pressure, position and contact area of ​​each touch point, calculating the dynamic change information of the touch point, and generating a complete data set related to each touch point;

[0016] S13: using a vehicle-mounted sensor network to collect driving status data of the vehicle, the sensor network includes a vehicle speed sensor, a direction sensor, an accelerometer and a road condition monitoring sensor, and respectively obtains the vehicle's speed, direction, acceleration and road condition information;

[0017] S14: The collected vehicle driving status data is transmitted to the data processing module, and synchronized with the touch input data to ensure that the touch data matches the vehicle driving status data at the same timestamp to form a comprehensive data set with time correlation.

[0018] Optionally, the S12 specifically includes:

[0019] S121: Collect time series data on the position, pressure and contact area of ​​each touch point and record them at each time point The touch point position below ,pressure and contact area , and form a time series dataset ,in Indicates a point in time, and Respectively indicate the touch point The horizontal and vertical coordinates of the moment, Indicates that the touch point is The pressure of the moment, Indicates that the touch point is The contact area at the moment;

[0020] S122: Using the moving average method to calculate the position sequence of the touch points Perform smoothing and calculate the smoothed position ;

[0021] S123: Pressure and contact area Normalization is performed to eliminate the dimension differences between different touch points. After normalization, they are expressed as pressure and contact area ;

[0022] S124: Calculate the dynamic change information of the touch point, including the position change rate and acceleration , the formula is;

[0023] S125: smooth the touch point position , normalized pressure and contact area , Position change rate and acceleration Composing a complete data set , expressed as: .

[0024] Optionally, the S2 specifically includes:

[0025] S21: Collect vehicle driving status data, including vehicle speed , acceleration and tilt angle ,in, represents the speed of the vehicle, represents the vehicle's acceleration, Indicates the vehicle's tilt angle;

[0026] S22: Time-align the vehicle's driving status data with the touch input data to ensure that they are at the same time point On the top, vehicle status data and touch point location data synchronous;

[0027] S23: Correct the touch point position using a dynamic weighting algorithm. The correction formula is:

[0028] ;

[0029] ;in, and Respectively represent the horizontal and vertical coordinates of the touch point after correction, and is the touch point position after preprocessing, and is the correction coefficient, which is dynamically adjusted according to the vehicle's driving status data. is the state function, and the specific calculation is: ,in, and is a weight coefficient used to dynamically correct the touch point position deviation according to the vehicle's speed, acceleration and tilt angle;

[0030] S24: After performing the above correction on all touch point positions, regenerate the touch point position data set , as the corrected touch input data.

[0031] Optionally, the S3 specifically includes:

[0032] S31: Obtaining a calibrated touch point position data set ;

[0033] S32: Perform a preliminary cluster analysis on the corrected touch point position data, using a density clustering algorithm to set a minimum number of sample points. and neighborhood radius , cluster the touch point data and generate several preliminary clusters ,in Indicates A cluster contains several touch points;

[0034] S33: For each preliminary cluster Perform feature analysis and calculate the center point of each cluster and standard deviation ;

[0035] S34: Eliminate clusters that do not meet the conditions according to preset conditions. The preset conditions include:

[0036] Condition 1, clustering Standard Deviation Whether it exceeds the preset threshold ,like , it is considered to contain false touch data and will be removed;

[0037] Condition 2, clustering Number of touch points within Is it less than the minimum number of sample points MinPts? , it is considered as a noise cluster and is removed;

[0038] S35: The data set after removing the clusters that do not meet the conditions is used as the valid touch point data set .

[0039] Optionally, the S4 specifically includes:

[0040] S41: Filtering the effective touch point data set Perform multi-dimensional feature extraction, including the location coordinates of the touch point ,pressure , contact area , Position change rate and acceleration , and establish a multidimensional data vector containing the above features ;

[0041] S42: Using multi-dimensional feature vectors As input, a multidimensional regression model is established. The goal of the model is to predict the true position of each touch point, and the model parameters are gradually adjusted to make predictions by minimizing the error between the predicted position and the actual position;

[0042] S43: Optimize the parameters of the regression model through the gradient descent method, so that the model gradually reduces the prediction error during the training process ;

[0043] S44: The trained and optimized regression model is used to calculate the true position of each touch point , and generate a touch point position mapping table, the mapping table including the real position coordinates of all touch points.

[0044] Optionally, the S5 specifically includes:

[0045] S51: Read the actual position of each touch point from the touch point position mapping table and matching it with the corresponding physical tactile feedback unit on the vehicle smart surface to determine the position correspondence of each physical unit;

[0046] S52: According to the pressure of the touch point and contact area Set the initial parameters of tactile feedback, including feedback strength and feedback frequency , the specific calculation formula is:

[0047] ;

[0048] ,in, Indicates the strength of tactile feedback; Indicates the frequency of tactile feedback; and are the feedback strength coefficients of pressure and contact area, respectively; and are the feedback frequency coefficients of pressure and contact area, respectively;

[0049] S53: configuring the initial parameters to the corresponding physical tactile feedback unit;

[0050] S54: During the touch process, real-time monitoring of the pressure of the touch point and contact area and uses a dynamic adjustment algorithm to adjust the feedback intensity and frequency.

[0051] Optionally, the S51 specifically includes:

[0052] S511: Reading the actual position of each touch point in the touch point position mapping table ;

[0053] S512: Obtaining the position coordinates of the physical tactile feedback unit on the vehicle-mounted smart surface ,in and Respectively represent the position of the physical unit in the horizontal and vertical coordinate systems;

[0054] S513: Calculate each touch point All physical tactile feedback units on the vehicle's smart surface The Euclidean distance between , the formula is: ,in, Indicates touch point With physical feedback unit The distance between

[0055] S514: For each touch point Calculated distance Perform minimum value screening to determine the nearest physical tactile feedback unit ;

[0056] S515: Establishing a position correspondence relationship mapping table between touch points and physical tactile feedback units, for recording each touch point The corresponding physical unit of matching information.

[0057] Optionally, the S6 specifically includes:

[0058] S61: During vehicle operation, real-time collection of touch point input data, including the location of the touch point ,pressure and contact area ;

[0059] S62: Dynamically analyze the touch point input data collected in real time and calculate the position change rate of the touch point and pressure change rate ;

[0060] S63: Monitor the current feedback parameters of the tactile feedback system, including feedback strength and feedback frequency and compare it with the real-time input data of the touch point to determine whether adjustment is needed;

[0061] S64: Optimize and adjust the feedback intensity and frequency of the touch point using a feedback adjustment algorithm. The specific optimization formula is: ; ,in, and They are respectively the feedback intensity and feedback frequency after optimization adjustment; is the feedback intensity adjustment amount based on the position change rate and pressure change rate; is the feedback frequency adjustment amount based on the position change rate and pressure change rate;

[0062] S65: Depending on driving conditions, including vehicle speed and acceleration , dynamically adjust the optimization strategy of feedback parameters to ensure that tactile feedback can adapt to various driving environments.

[0063] A system for enhancing tactile feedback of an in-vehicle smart surface, used to implement the above-mentioned method for enhancing tactile feedback of an in-vehicle smart surface, comprises the following modules:

[0064] Touch input acquisition module: used to collect multi-touch input data on the vehicle-mounted smart surface in real time, including the position, pressure, contact area and dynamic change information of each touch point, and transmit the collected data to the data processing module;

[0065] Vehicle driving status monitoring module: used to monitor the vehicle's driving status data in real time, including the vehicle's speed, acceleration, tilt angle and road condition information, and transmit the monitored data to the data processing module;

[0066] Data processing module: receives data from the touch input acquisition module and the vehicle driving status monitoring module, uses a dynamic weighting algorithm to correct the touch point position in the multi-touch input data, reduces the touch data deviation caused by vehicle vibration or tilt, and generates corrected touch point position data;

[0067] Cluster analysis module: Based on the corrected touch point position data, cluster analysis is performed to identify and eliminate false touch data that does not meet the preset conditions, and to filter out valid touch point data;

[0068] Multi-dimensional modeling module: multi-dimensional modeling is performed on the filtered effective touch point data to calculate the real position of each touch point and generate a touch point position mapping table;

[0069] Haptic feedback control module: Based on the touch point position mapping table, the haptic feedback system is configured with parameters to ensure that the haptic feedback response of each touch point matches its actual position, and the feedback parameters are dynamically adjusted according to the changes in pressure and contact area to adapt to different touch input characteristics;

[0070] Feedback Optimization Module: During vehicle operation, the module continuously monitors the input data and feedback parameters of the touch points, and optimizes the intensity and frequency of tactile feedback in real time through the feedback adjustment algorithm to ensure that the tactile feedback can adapt to different driving conditions.

[0071] Beneficial effects of the present invention:

[0072] The present invention corrects the touch point position through a dynamic weighted algorithm, effectively reducing the data deviation caused by the vehicle's motion state. This correction ensures that the position data of the touch point is more accurate, so that the tactile feedback is highly consistent with the driver's actual operating intention, enhancing the driver's operating intuition and the vehicle's operating safety.

[0073] The present invention optimizes the calculation of the real position of the touch point and dynamically adjusts the tactile feedback parameters in combination with the pressure and contact area of ​​the touch point, so that the tactile feedback can be adjusted in real time according to different driving conditions. This not only improves the personalization and adaptability of the tactile feedback, but also ensures that in complex or rapidly changing driving environments, the tactile feedback can accurately convey the necessary operating information and warnings, greatly improving the driving comfort and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0075] Figure 1 A schematic flow chart of a method for enhancing tactile feedback of an in-vehicle smart surface according to an embodiment of the present invention;

[0076] Figure 2 Schematic diagram of a system for enhancing tactile feedback of an in-vehicle smart surface according to an embodiment of the present invention. DETAILED DESCRIPTION

[0077] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0078] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0079] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0080] like Figure 1 As shown, the method for enhancing the tactile feedback of the vehicle-mounted smart surface comprises the following steps:

[0081] S1: Collect multi-touch input data on the vehicle-mounted smart surface, including the position, pressure, contact area and dynamic change information of each touch point, and collect the vehicle's driving status data, including speed, direction, acceleration and road condition information;

[0082] S2: Correcting the touch point positions in the multi-touch input data using a dynamic weighting algorithm based on the vehicle's driving state data, so as to reduce the touch data deviation caused by vehicle vibration or tilt;

[0083] S3: performing cluster analysis based on the corrected touch point position data to identify and eliminate false touch data that does not meet preset conditions and screen out valid touch point data;

[0084] S4: performing multi-dimensional modeling on the filtered touch point data to calculate the real position of each touch point and generate a touch point position mapping table to reflect the multi-touch distribution on the in-vehicle smart surface;

[0085] S5: Based on the touch point position mapping table, configure the parameters of the tactile feedback system so that the tactile feedback response of each touch point can match its actual position, and dynamically adjust the feedback parameters according to the changes in pressure and contact area;

[0086] S6: During vehicle operation, the input data and feedback parameters of the touch points are continuously monitored, and the intensity and frequency of tactile feedback are optimized in real time through the feedback adjustment algorithm to adapt to the needs under different driving conditions and ensure the accuracy and response speed of tactile feedback.

[0087] S1 specifically includes:

[0088] S11: Arranging a multi-touch sensor array on the vehicle-mounted smart surface, the sensor array including a pressure sensor and a capacitive position sensor, for simultaneously detecting the position, pressure, contact area and dynamic change information of each touch point, and transmitting the data to a data processing module through a vehicle-mounted bus interface;

[0089] S12: In the data processing module, the collected touch input data is preprocessed, including time series analysis of the pressure, position and contact area of ​​each touch point, calculation of dynamic change information of the touch point, and generation of a complete data set related to each touch point;

[0090] S13: using the vehicle-mounted sensor network to collect the driving status data of the vehicle, the sensor network includes a vehicle speed sensor, a direction sensor, an accelerometer and a road condition monitoring sensor, and respectively obtains the speed, direction, acceleration and road condition information of the vehicle;

[0091] S14: The collected vehicle driving status data is transmitted to the data processing module, and synchronized with the touch input data to ensure that the touch data matches the vehicle driving status data at the same timestamp to form a comprehensive data set with time correlation; through the above steps, the multi-touch input data and vehicle driving status data of the vehicle-mounted smart surface can be accurately collected and processed to ensure the integrity and synchronization of the data, providing reliable basic data for subsequent correction steps.

[0092] S12 specifically includes:

[0093] S121: Collect time series data on the position, pressure and contact area of ​​each touch point and record them at each time point The touch point position below ,pressure and contact area , and form a time series dataset ,in Indicates a point in time, and Respectively indicate the touch point The horizontal and vertical coordinates of the moment, Indicates that the touch point is The pressure of the moment, Indicates that the touch point is The contact area at the moment;

[0094] S122: Using the moving average method to calculate the position sequence of the touch points Perform smoothing and calculate the smoothed position , the formula is: and ,in, represents the size of the moving window, and Respectively represent the touch points after smoothing The horizontal and vertical coordinates of the moment are used to reduce the impact of instantaneous position fluctuations caused by vehicle vibration on the data;

[0095] S123: Pressure and contact area Normalization is performed to eliminate the dimension differences between different touch points. After normalization, they are expressed as pressure and contact area , the normalization formula is as follows: ; ,in, and denote the normalized pressure and contact area, respectively. and Respectively represent the minimum and maximum pressure values ​​in the current touch point sequence. and Respectively represent the minimum contact area and maximum contact area values ​​in the current touch point sequence;

[0096] S124: Calculate the dynamic change information of the touch point, including the position change rate and acceleration , the formula is: ; ,in, Indicates that the touch point is The speed of time, and Respectively indicate the touch point The horizontal and vertical displacements at the moment, Represents the time interval between adjacent time points. Indicates that the touch point is The acceleration of time, Indicates that the touch point is The speed of the moment changes;

[0097] S125: The smoothed touch point position , normalized pressure and contact area , Position change rate and acceleration Composing a complete data set , expressed as: , for subsequent processing; through the above steps, the collected touch input data can be effectively preprocessed to generate a complete data set containing touch point position, pressure, contact area and dynamic change information, laying a solid foundation for improving multi-touch accuracy.

[0098] S21: Collect vehicle driving status data, including vehicle speed , acceleration and tilt angle ,in, represents the speed of the vehicle, represents the vehicle's acceleration, Indicates the vehicle's tilt angle;

[0099] S22: Time-align the vehicle's driving status data with the touch input data to ensure that they are at the same time point On the top, vehicle status data and touch point location data synchronous;

[0100] S23: Correct the touch point position using a dynamic weighting algorithm. The correction formula is:

[0101] ;

[0102] ;in, and Respectively represent the horizontal and vertical coordinates of the touch point after correction, and is the touch point position after preprocessing, and is the correction coefficient, which is dynamically adjusted according to the vehicle's driving status data. is the state function, and the specific calculation is: ,in, and is a weight coefficient used to dynamically correct the touch point position deviation according to the vehicle's speed, acceleration and tilt angle to ensure the accuracy of the touch point position;

[0103] S24: After performing the above correction on all touch point positions, regenerate the touch point position data set , as the corrected touch input data, providing corrected high-precision input for subsequent processing steps; through the above steps, the touch point positions in the multi-touch input data can be dynamically corrected according to the vehicle's driving status data, reducing the touch data deviation caused by vehicle vibration or tilt, thereby improving the accuracy and reliability of the touch input.

[0104] S3 specifically includes:

[0105] S31: Obtaining a calibrated touch point position data set ,in and Respectively represent the coordinates of the touch point in the horizontal and vertical directions after correction, in pixels;

[0106] S32: Perform a preliminary cluster analysis on the calibrated touch point position data, using a density clustering algorithm (DBSCAN) to set a minimum number of sample points. and neighborhood radius , cluster the touch point data and generate several preliminary clusters ,in Indicates A cluster contains several touch points;

[0107] S33: For each preliminary cluster Perform feature analysis and calculate the center point of each cluster and standard deviation ,in, and Represents clusters The horizontal and vertical center coordinates are calculated as follows: ; ; Cluster The standard deviation of the inner touch point position is calculated as: ,in, Represents clusters The number of touch points within;

[0108] S34: Eliminate clusters that do not meet the conditions according to preset conditions. The preset conditions include:

[0109] Condition 1, clustering Standard Deviation Whether it exceeds the preset threshold ,like , it is considered to contain false touch data and will be removed;

[0110] Condition 2, clustering Number of touch points within Is it less than the minimum number of sample points MinPts? , it is considered as a noise cluster and is removed;

[0111] S35: The data set after removing the clusters that do not meet the conditions is used as the valid touch point data set , for subsequent processing.

[0112] S4 specifically includes:

[0113] S41: Filtering the effective touch point data set Perform multi-dimensional feature extraction, including the location coordinates of the touch point ,pressure , contact area , Position change rate and acceleration , and establish a multidimensional data vector containing the above features ;

[0114] S42: Using multi-dimensional feature vectors As input, a multidimensional regression model is established. The goal of the model is to predict the true position of each touch point. By minimizing the error between the predicted position and the actual position, the model parameters are gradually adjusted for prediction. The regression equation formula is:

[0115] ;

[0116] ;in, and Respectively represent the horizontal and vertical coordinates of the predicted real position of the touch point; are the regression weight coefficients of each input feature, which are adaptively adjusted through training data; and They are the bias values ​​of the regression model, which are used to correct the prediction error;

[0117] S43: Optimize the parameters of the regression model through the gradient descent method, so that the model gradually reduces the prediction error during the training process , the formula is defined as: , Indicates the number of training samples; and They are the horizontal and vertical coordinates of the actual position of the touch point respectively;

[0118] S44: The trained and optimized regression model is used to calculate the true position of each touch point , and generate a touch point position mapping table, which includes the real position coordinates of all touch points for subsequent response adjustment of the tactile feedback system; through the above steps, multi-dimensional modeling can be performed based on the screened touch point data, and an adaptive regression algorithm can be used to accurately calculate the real position of each touch point, and generate a touch point position mapping table, thereby providing reliable data support for the precise control of tactile feedback.

[0119] S5 specifically includes:

[0120] S51: Read the actual position of each touch point from the touch point position mapping table and match it with the corresponding physical tactile feedback unit on the vehicle smart surface to determine the position correspondence of each physical unit, ensuring that the tactile feedback signal can be accurately transmitted to the actual touch position;

[0121] S52: According to the pressure of the touch point and contact area Set the initial parameters of tactile feedback, including feedback strength and feedback frequency , the specific calculation formula is:

[0122] ;

[0123] ,in, Indicates the strength of tactile feedback in Newtons; Indicates the frequency of tactile feedback in Hertz; and are the feedback strength coefficients of pressure and contact area, respectively; and are the feedback frequency coefficients of pressure and contact area, respectively;

[0124] S53: configuring the initial parameters to the corresponding physical tactile feedback unit to ensure that the tactile feedback response of each touch point can match its actual position and input characteristics;

[0125] S54: During the touch process, real-time monitoring of the pressure of the touch point and contact area The feedback intensity and frequency are adjusted by using a dynamic adjustment algorithm. The formula is: ;

[0126] ,in, and are the feedback intensity and frequency after dynamic adjustment respectively; and The adjustment amount is calculated based on the real-time monitored pressure and contact area changes. The calculation formula for the adjustment amount is: ; ,in, represents the rate of change of pressure over time, It represents the rate of change of contact area with time; and are the influence coefficients of pressure change on feedback intensity adjustment; and are the influence coefficients of pressure change on feedback frequency adjustment respectively; through the above steps, the parameters of the tactile feedback system can be configured based on the touch point position mapping table to ensure that the tactile feedback response of the touch point matches its actual position, and through real-time monitoring and dynamic adjustment, it can be ensured that the tactile feedback can adapt to the changes in pressure and contact area of ​​the touch point to provide accurate tactile feedback experience.

[0127] S51 specifically includes:

[0128] S511: Reading the actual position of each touch point in the touch point position mapping table ;

[0129] S512: Obtaining the position coordinates of the physical tactile feedback unit on the vehicle-mounted smart surface ,in and Respectively represent the position of the physical unit in the horizontal and vertical coordinate systems, in pixels;

[0130] S513: Calculate each touch point All physical tactile feedback units on the vehicle's smart surface The Euclidean distance between , the formula is: ,in, Indicates touch point With physical feedback unit The distance between them, in pixels;

[0131] S514: For each touch point Calculated distance Perform minimum value screening to determine the nearest physical tactile feedback unit , the expression is: , which is used to determine the physical tactile feedback unit With touch point The optimal matching relationship ensures that the tactile feedback signal can be accurately transmitted to the actual touch position;

[0132] S515: Establishing a position correspondence relationship mapping table between touch points and physical tactile feedback units, for recording each touch point The corresponding physical unit The matching information is used for the subsequent tactile feedback response configuration; through the above steps, the actual position of each touch point can be read from the touch point position mapping table, and it can be accurately matched with the corresponding physical tactile feedback unit on the vehicle-mounted smart surface to ensure that the position correspondence of each physical unit is accurate, providing a basis for the accurate transmission of tactile feedback signals.

[0133] S6 specifically includes:

[0134] S61: During vehicle operation, real-time collection of touch point input data, including the location of the touch point ,pressure and contact area and transmits these data to the on-board processing module for real-time processing;

[0135] S62: Dynamically analyze the touch point input data collected in real time and calculate the position change rate of the touch point and pressure change rate , the formula is: ; ,in, and They are the changes in the horizontal and vertical coordinates of the touch point, in pixels; and Represents two consecutive time points. and are the pressure values ​​at these two time points, in Newton;

[0136] S63: Monitor the current feedback parameters of the tactile feedback system, including feedback strength and feedback frequency and compare it with the real-time input data of the touch point to determine whether adjustment is needed;

[0137] S64: Optimize and adjust the feedback intensity and frequency of the touch point using a feedback adjustment algorithm. The specific optimization formula is: ; ,in, and They are respectively the feedback intensity and feedback frequency after optimization adjustment; is the feedback intensity adjustment amount based on the position change rate and pressure change rate; is the feedback frequency adjustment amount based on the position change rate and pressure change rate;

[0138] S65: Depending on driving conditions, including vehicle speed and acceleration , dynamically adjust the optimization strategy of feedback parameters to ensure that tactile feedback can adapt to various driving environments. The specific adjustment formula is:

[0139] ;

[0140] ;in, and are the influence coefficients of position change rate on feedback strength and frequency respectively; and are the influence coefficients of pressure change rate on feedback intensity and frequency respectively; and are the influence coefficients of driving conditions on feedback intensity and frequency, and the function It represents the combined impact of vehicle speed and acceleration on feedback adjustment. Through the above steps, the input data and feedback parameters of the touch points can be continuously monitored during vehicle operation, and the intensity and frequency of the tactile feedback can be optimized in real time through the feedback adjustment algorithm to ensure that the tactile feedback can adapt to the needs under different driving conditions and improve driving safety and user experience.

[0141] like Figure 2 As shown, the system for enhancing the tactile feedback of an in-vehicle smart surface, used to implement the above-mentioned method for enhancing the tactile feedback of an in-vehicle smart surface, includes the following modules:

[0142] Touch input acquisition module: used to collect multi-touch input data on the vehicle-mounted smart surface in real time, including the position, pressure, contact area and dynamic change information of each touch point, and transmit the collected data to the data processing module;

[0143] Vehicle driving status monitoring module: used to monitor the vehicle's driving status data in real time, including the vehicle's speed, acceleration, tilt angle and road condition information, and transmit the monitored data to the data processing module for synchronous processing with the touch input data;

[0144] Data processing module: receives data from the touch input acquisition module and the vehicle driving status monitoring module, uses a dynamic weighting algorithm to correct the touch point position in the multi-touch input data, reduces the touch data deviation caused by vehicle vibration or tilt, and generates corrected touch point position data;

[0145] Cluster analysis module: Based on the corrected touch point position data, cluster analysis is performed to identify and eliminate false touch data that does not meet the preset conditions, and to filter out valid touch point data for subsequent tactile feedback control;

[0146] Multi-dimensional modeling module: multi-dimensional modeling is performed on the filtered effective touch point data to calculate the real position of each touch point and generate a touch point position mapping table to control the response of the tactile feedback system;

[0147] Haptic feedback control module: Based on the touch point position mapping table, the haptic feedback system is configured with parameters to ensure that the haptic feedback response of each touch point matches its actual position, and the feedback parameters are dynamically adjusted according to the changes in pressure and contact area to adapt to different touch input characteristics;

[0148] Feedback Optimization Module: During vehicle operation, the module continuously monitors the input data and feedback parameters of the touch points, and optimizes the intensity and frequency of tactile feedback in real time through the feedback adjustment algorithm, ensuring that the tactile feedback can adapt to different driving conditions and improve the system's response accuracy and user experience.

[0149] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0150] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for enhancing tactile feedback of an in-vehicle smart surface, characterized in that: The following steps are involved: S1: Collecting multi-touch input data on the vehicle-mounted intelligent surface, the input data including the position, pressure, contact area and dynamic change information of each touch point, and collecting the vehicle's driving status data, the driving status data including speed, direction, acceleration and road condition information; S2: Correcting the touch point positions in the multi-touch input data using a dynamic weighting algorithm based on the vehicle's driving state data, so as to reduce the touch data deviation caused by vehicle vibration or tilt; The S2 specifically includes: S21: Collect vehicle driving status data, including vehicle speed , acceleration and tilt angle ,in, represents the speed of the vehicle, represents the vehicle's acceleration, Indicates the vehicle's tilt angle; S22: Time-align the vehicle's driving status data with the touch input data to ensure that they are at the same time point On the top, vehicle status data and touch point location data synchronous; S23: Correct the touch point position using a dynamic weighting algorithm. The correction formula is: ； ;in, and Respectively represent the horizontal and vertical coordinates of the touch point after correction, and is the touch point position after preprocessing, and is the correction coefficient, which is dynamically adjusted according to the vehicle's driving status data. is the state function, and the specific calculation is: ,in, , and is a weight coefficient used to dynamically correct the touch point position deviation according to the vehicle's speed, acceleration and tilt angle; S24: After performing the above correction on all touch point positions, regenerate the touch point position data set , as the corrected touch input data; S3: performing cluster analysis based on the corrected touch point position data to identify and eliminate false touch data that does not meet preset conditions and screen out valid touch point data; S4: performing multi-dimensional modeling on the screened touch point data to calculate the real position of each touch point and generate a touch point position mapping table; S5: Based on the touch point position mapping table, configure the parameters of the tactile feedback system so that the tactile feedback response of each touch point can match its actual position, and dynamically adjust the feedback parameters according to the changes in pressure and contact area; S6: During vehicle operation, the input data and feedback parameters of the touch points are continuously monitored, and the intensity and frequency of tactile feedback are optimized in real time through the feedback adjustment algorithm to meet the needs of different driving conditions; The S6 specifically includes: S61: During vehicle operation, real-time collection of touch point input data, including the location of the touch point ,pressure and contact area ; S62: Dynamically analyze the touch point input data collected in real time and calculate the position change rate of the touch point and pressure change rate ; S63: Monitor the current feedback parameters of the tactile feedback system, including feedback strength and feedback frequency and compare it with the real-time input data of the touch point to determine whether adjustment is needed; S64: Optimize and adjust the feedback intensity and frequency of the touch point using a feedback adjustment algorithm. The specific optimization formula is: ; ,in, and They are respectively the feedback intensity and feedback frequency after optimization adjustment; is the feedback intensity adjustment amount based on the position change rate and pressure change rate; is the feedback frequency adjustment amount based on the position change rate and pressure change rate; S65: Depending on driving conditions, including vehicle speed and acceleration , dynamically adjust the optimization strategy of feedback parameters to ensure that tactile feedback can adapt to various driving environments.

2. The method for enhancing tactile feedback of an in-vehicle smart surface according to claim 1, characterized in that: The S1 specifically includes: S11: Arranging a multi-touch sensor array on the vehicle-mounted smart surface, wherein the sensor array includes a pressure sensor and a capacitive position sensor, for simultaneously detecting the position, pressure, contact area and dynamic change information of each touch point, and transmitting the data to a data processing module through a vehicle-mounted bus interface; S12: in the data processing module, preprocessing the collected touch input data, including performing time series analysis on the pressure, position and contact area of ​​each touch point, calculating the dynamic change information of the touch point, and generating a complete data set related to each touch point; S13: using a vehicle-mounted sensor network to collect driving status data of the vehicle, the sensor network includes a vehicle speed sensor, a direction sensor, an accelerometer and a road condition monitoring sensor, and respectively obtains the vehicle's speed, direction, acceleration and road condition information; S14: The collected vehicle driving status data is transmitted to the data processing module, and synchronized with the touch input data to ensure that the touch data matches the vehicle driving status data at the same timestamp to form a comprehensive data set with time correlation.

3. The method for enhancing tactile feedback of an in-vehicle smart surface according to claim 2, characterized in that: The S12 specifically includes: S121: Collect time series data on the position, pressure and contact area of ​​each touch point and record them at each time point The touch point position below ,pressure and contact area , and form a time series dataset ,in Indicates a point in time, and Respectively indicate the touch point The horizontal and vertical coordinates of the moment, Indicates that the touch point is The pressure of the moment, Indicates that the touch point is The contact area at the moment; S122: Using the moving average method to calculate the position sequence of the touch points Perform smoothing and calculate the smoothed position ; S123: Pressure and contact area Normalization is performed to eliminate the dimension differences between different touch points. After normalization, they are expressed as pressure and contact area ; S124: Calculate the dynamic change information of the touch point, including the position change rate and acceleration , the formula is; S125: smooth the touch point position , normalized pressure and contact area , Position change rate and acceleration Composing a complete data set , expressed as: .

4. The method for enhancing tactile feedback of an in-vehicle smart surface according to claim 1, characterized in that: The S3 specifically includes: S31: Obtaining a calibrated touch point position data set ; S32: Perform a preliminary cluster analysis on the corrected touch point position data, using a density clustering algorithm to set a minimum number of sample points. and neighborhood radius , cluster the touch point data and generate several preliminary clusters ,in Indicates A cluster contains several touch points; S33: For each preliminary cluster Perform feature analysis and calculate the center point of each cluster and standard deviation ; S34: Eliminate clusters that do not meet the conditions according to preset conditions. The preset conditions include: Condition 1, clustering Standard Deviation Whether it exceeds the preset threshold ,like , it is considered to contain false touch data and will be removed; Condition 2, clustering Number of touch points within Is it less than the minimum number of sample points MinPts? , it is considered as a noise cluster and is removed; S35: The data set after removing the clusters that do not meet the conditions is used as the valid touch point data set .

5. The method for enhancing tactile feedback of an in-vehicle smart surface according to claim 4, characterized in that: The S4 specifically includes: S41: Filtering the effective touch point data set Perform multi-dimensional feature extraction, including the location coordinates of the touch point ,pressure , contact area , Position change rate and acceleration , and establish a multidimensional data vector containing the above multidimensional features ; S42: Using multi-dimensional feature vectors As input, a multidimensional regression model is established. The goal of the model is to predict the true position of each touch point, and the model parameters are gradually adjusted to make predictions by minimizing the error between the predicted position and the actual position; S43: Optimize the parameters of the regression model through the gradient descent method, so that the model gradually reduces the prediction error during the training process ; S44: The trained and optimized regression model is used to calculate the true position of each touch point , and generate a touch point position mapping table, the mapping table including the real position coordinates of all touch points.

6. The method for enhancing tactile feedback of an in-vehicle smart surface according to claim 1, characterized in that: The S5 specifically includes: S51: Read the actual position of each touch point from the touch point position mapping table and matching it with the corresponding physical tactile feedback unit on the vehicle smart surface to determine the position correspondence of each physical unit; S52: According to the pressure of the touch point and contact area Set the initial parameters of tactile feedback, including feedback strength and feedback frequency , the specific calculation formula is: ； ,in, Indicates the strength of tactile feedback; Indicates the frequency of tactile feedback; and are the feedback strength coefficients of pressure and contact area, respectively; and are the feedback frequency coefficients of pressure and contact area, respectively; S53: configuring the initial parameters to the corresponding physical tactile feedback unit; S54: During the touch process, real-time monitoring of the pressure of the touch point and contact area and uses a dynamic adjustment algorithm to adjust the feedback intensity and frequency.

7. The method for enhancing tactile feedback of an in-vehicle smart surface according to claim 6, characterized in that: The S51 specifically includes: S511: Reading the actual position of each touch point in the touch point position mapping table ; S512: Obtaining the position coordinates of the physical tactile feedback unit on the vehicle-mounted smart surface ,in and Respectively represent the position of the physical unit in the horizontal and vertical coordinate systems; S513: Calculate each touch point All physical tactile feedback units on the vehicle's smart surfaces The Euclidean distance between , the formula is: ,in, Indicates touch point With physical feedback unit The distance between S514: For each touch point Calculated distance Perform minimum value screening to determine the nearest physical tactile feedback unit ; S515: Establishing a position correspondence relationship mapping table between touch points and physical tactile feedback units, for recording each touch point The corresponding physical unit of matching information.

8. A system for enhancing tactile feedback of an in-vehicle smart surface, for implementing the method for enhancing tactile feedback of an in-vehicle smart surface as claimed in any one of claims 1 to 7, characterized in that: Includes the following modules: Touch input acquisition module: used to collect multi-touch input data on the vehicle-mounted smart surface in real time, including the position, pressure, contact area and dynamic change information of each touch point, and transmit the collected data to the data processing module; Vehicle driving status monitoring module: used to monitor the vehicle's driving status data in real time, including the vehicle's speed, acceleration, tilt angle and road condition information, and transmit the monitored data to the data processing module; Data processing module: receives data from the touch input acquisition module and the vehicle driving status monitoring module, uses a dynamic weighting algorithm to correct the touch point position in the multi-touch input data, reduces the touch data deviation caused by vehicle vibration or tilt, and generates corrected touch point position data; Cluster analysis module: Based on the corrected touch point position data, cluster analysis is performed to identify and eliminate false touch data that does not meet the preset conditions, and to filter out valid touch point data; Multi-dimensional modeling module: multi-dimensional modeling is performed on the filtered effective touch point data to calculate the real position of each touch point and generate a touch point position mapping table; Haptic feedback control module: Based on the touch point position mapping table, the haptic feedback system is configured with parameters to ensure that the haptic feedback response of each touch point matches its actual position, and the feedback parameters are dynamically adjusted according to the changes in pressure and contact area to adapt to different touch input characteristics; Feedback Optimization Module: During vehicle operation, the module continuously monitors the input data and feedback parameters of the touch points, and optimizes the intensity and frequency of tactile feedback in real time through the feedback adjustment algorithm to ensure that the tactile feedback can adapt to different driving conditions.

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