Adaptive method and device for touch page, vehicle, storage medium and product

Abstract

The application relates to the technical field of vehicles, in particular to a self-adaptive method and device for a touch page, a vehicle, a storage medium and a product, wherein the method comprises the following steps: collecting dynamic data of a suspension system of the vehicle; extracting characteristic values of the dynamic data of the suspension system, inputting the characteristic values into a pre-trained prediction model, and outputting point touch offsets corresponding to the characteristic values by the prediction model; and adjusting a response area of a touch interface of the vehicle according to the point touch offsets. Thus, the problem that in the related art, indirect data of a screen point touch event are collected for analysis and then deviation is corrected, which leads to inaccurate correction of the deviation, point touch errors may still occur, and driving experience and safety are affected, is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, in particular to a self-adaptive method and device for a touch page, a vehicle, a storage medium and a product. BACKGROUND

[0002] The touch technology of the central control screen of a vehicle is very mature, but during the driving of the vehicle, the touch operation of a user may be inaccurate due to the bumping of the road surface, which affects the driving experience and safety.

[0003] In the related art, the response speed and accuracy of the touch screen are improved, and the deviation is corrected after indirect data analysis of the touch event, but when the vehicle is driven on a bumpy road, the shaking of the vehicle body and the shaking of the driver's body will cause the touch operation to be unstable, and when the deviation is corrected by using an algorithm, the indirect data of the user's finger operation caused by the shaking is used, and the way of the user's operation is different for different people, which will cause the judgment result to be unreliable, and further affect the user experience. SUMMARY

[0004] The present application provides a self-adaptive method and device for a touch page, a vehicle, a storage medium and a product to solve the problem that the deviation is not corrected accurately in the related art by analyzing the indirect data of the screen touch event, which may still cause touch errors and affect the driving experience and safety.

[0005] The first aspect of the present application provides a self-adaptive method for a touch page, comprising the following steps: collecting suspension system data of a vehicle; extracting a characteristic value of the suspension system data, inputting the characteristic value into a pre-trained prediction model, and outputting a touch offset corresponding to the characteristic value by the prediction model; and adjusting a response area of a touch interface of the vehicle according to the touch offset.

[0006] Optionally, adjusting the response area of the touch interface of the vehicle according to the touch offset comprises: identifying an offset position of the touch offset; and adjusting an actual position of the response area according to the offset position, wherein the offset position and the actual position are opposite.

[0007] Optionally, after adjusting the response area of the touch interface of the vehicle according to the touch offset, the method further comprises: detecting an actual road condition of the vehicle; and dynamically adjusting a layout of the touch page and / or adjusting a display effect of a virtual keyboard or button according to the actual road condition.

[0008] Optionally, before the characteristic value is input into the pre-trained prediction model, the method further comprises: obtaining a data set, wherein the data set comprises suspension system data and actual point touch positions under different road conditions; splitting the data set into a training set and a verification set; training the prediction model using the training set, and verifying the trained prediction model using the verification set until a preset condition is met to stop training.

[0009] Optionally, before the characteristic value of the suspension system data is extracted, the method further comprises: pre-processing the suspension system data, wherein the pre-processing comprises denoising processing, filtering processing, and isolation processing.

[0010] Optionally, the characteristic value comprises one or more of a vibration amplitude, a vibration frequency, a vibration duration, and a change rate of acceleration.

[0011] The second aspect embodiment of the application provides a self-adaptive device for a touch page, comprising: a collection module configured to collect suspension system data of a vehicle; an input and output module configured to extract a characteristic value of the suspension system data, input the characteristic value into a pre-trained prediction model, and output a point touch offset corresponding to the characteristic value by the prediction model; and a first adjustment module configured to adjust a response area of a touch interface of the vehicle according to the point touch offset.

[0012] Optionally, the adjustment module is further configured to identify an offset position of the point touch offset, and adjust an actual position of the response area according to the offset position, wherein the offset position and the actual position are opposite.

[0013] Optionally, the self-adaptive device for the touch page further comprises: a detection module configured to detect an actual road condition of the vehicle; and a second adjustment module configured to dynamically adjust a layout of the touch page and / or adjust a display effect of a virtual keyboard or button according to the actual road condition.

[0014] Optionally, the self-adaptive device for the touch page further comprises: a training module configured to, before the characteristic value is input into the pre-trained prediction model, obtain a data set, wherein the data set comprises suspension system data and actual point touch positions under different road conditions; split the data set into a training set and a verification set; train the prediction model using the training set, and verify the trained prediction model using the verification set until a preset condition is met to stop training.

[0015] Optionally, the self-adaptive device for the touch page further comprises: a pre-processing module configured to, before the characteristic value of the suspension system data is extracted, pre-process the suspension system data, wherein the pre-processing comprises denoising processing, filtering processing, and isolation processing.

[0016] Optionally, the characteristic value comprises one or more of a vibration amplitude, a vibration frequency, a vibration duration, and a change rate of acceleration.

[0017] The third aspect of the present application provides a vehicle, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the program to implement the adaptive method of the touch page according to the above-mentioned embodiments.

[0018] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program or instructions, and the computer program or instructions are executed to implement the adaptive method of the touch page according to the above-mentioned embodiments.

[0019] The fifth aspect of the present application provides a computer program product, comprising a computer program or instructions, and the computer program or instructions are executed to implement the adaptive method of the touch page according to the above-mentioned embodiments.

[0020] Therefore, the present application has at least the following beneficial effects:

[0021] The embodiments of the present application predict and quantify the point touch offset caused by bumping by collecting and analyzing the dynamic data of the vehicle suspension system, and dynamically adjust the response area of the touch interface to compensate for the point touch error caused by bumping, which can improve the user's operation experience in the bumping road conditions while ensuring driving safety, and reduce the inconvenience caused by operation errors. Therefore, the problem that the correction error is inaccurate and point touch error still occurs, affecting the driving experience and safety, etc. in the related art is solved by analyzing the indirect data collected by the screen touch event and then correcting the deviation.

[0022] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0023] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, taken in conjunction with the accompanying drawings, in which:

[0024] Figure 1 A flowchart of the adaptive method of the touch page according to the embodiments of the present application is provided;

[0025] Figure 2 An example diagram of the adaptive touch correction system according to the embodiments of the present application is provided;

[0026] Figure 3 A block diagram of the adaptive device of the touch page according to the embodiments of the present application is provided;

[0027] Figure 4 A structural schematic diagram of the vehicle according to the embodiments of the present application is provided. DETAILED DESCRIPTION

[0028] Embodiments of the present application are described below in detail, examples of which are shown in the accompanying drawings, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by reference to the drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

[0029] The adaptive method, device, vehicle, and storage medium computer program product of a touch page of the embodiments of the present application are described below with reference to the accompanying drawings. In view of the problems mentioned in the background art, the present application provides an adaptive method of a touch page, in which the method, by collecting and analyzing dynamic data of the suspension system of the vehicle, predicts and quantifies the point touch deviation caused by jolting, and dynamically adjusts the response area of the touch interface to compensate for the point touch error caused by jolting. The user's operation experience in jolting road conditions can be improved while ensuring driving safety, and the inconvenience and potential risks caused by operation errors can be reduced. Thus, the problem that the correction deviation is inaccurate and point touch errors still occur, affecting driving experience and safety, etc. in the related art is solved by analyzing indirect data collected from screen point touch events.

[0030] Secondly, the adaptive device of a touch page according to the embodiments of the present application is described with reference to the accompanying drawings.

[0031] Specifically, Figure 1 A flowchart of an adaptive method of a touch page provided by the embodiments of the present application is shown in FIG. 1.

[0032] As Figure 1 shown, the adaptive method of a touch page includes the following steps:

[0033] In step S101, the suspension system data of the vehicle is collected.

[0034] It can be understood that when the vehicle is driven on a jolting road, the point touch error of the driver or passenger when using the touch interface of the center control screen is caused by the dynamic response of the vehicle suspension system. The embodiments of the present application collect and detect the suspension system data of the vehicle, such as vibration and motion state, through the suspension system sensors (accelerometer, gyroscope, etc.). The sensor operating temperature range is usually between -40°C and +85°C. In actual execution, the embodiments of the present application can install the accelerometer and gyroscope sensors in appropriate positions of the vehicle suspension system. These positions can be suspension arms, shock absorbers, sub-frames, or other parts of the vehicle body that can accurately reflect the dynamic response of the suspension.

[0035] In step S102, the characteristic values of the suspension system data are extracted, the characteristic values are input into a pre-trained prediction model, and the prediction model outputs a point touch deviation corresponding to the characteristic values.

[0036] In the embodiments of the present application, the characteristic values can include: vibration amplitude, vibration frequency, vibration duration, acceleration rate of change, etc., which should have a direct relationship with the point touch offset. Among them, the vibration frequency detection range can be from 0.5 Hz to 50 Hz or higher, depending on the characteristics of the vehicle suspension system. The vibration amplitude detection range is usually between ±5g and ±50g, depending on the vehicle type and road conditions. The vibration duration detection can vary from a few milliseconds to a few seconds.

[0037] Specifically, the embodiments of the present application can use machine learning algorithms or physical models to train a prediction model. This model will learn the relationship between sensor data features and actual point touch offset. Once the model is trained, it can be used to predict the point touch offset corresponding to new sensor data. Input new sensor data, the model will output a predicted point touch offset. During vehicle driving, the suspension system sensor will collect data in real time, which is sent to the trained prediction model, and the model will predict the point touch offset in real time, and then this offset is used to dynamically adjust the response area of the touch interface to compensate for the point touch error caused by bumps.

[0038] In an embodiment of the present application, before inputting the characteristic values into the pre-trained prediction model, it further includes: obtaining a data set, wherein the data set includes suspension system data and actual point touch positions under different road conditions; splitting the data set into a training set and a validation set; training the prediction model using the training set, and validating the trained prediction model using the validation set until the training stops when the preset condition is met.

[0039] Among them, the data set can be obtained by experiment, and these data should include various conditions, such as different users, different point touch forces, different vehicle states (acceleration, deceleration, turning, etc.) and different road conditions (flat, bumpy, slippery, etc.). Each group of data should contain the output signal of the sensor and the actual point touch position. These data will be used to train your prediction model to understand the complex relationship between sensor signals and point touch offsets.

[0040] During model training, the embodiments of the present application can divide the data set into a training set and a validation set, the training set is used to train the model to make the model learn the inherent law of the data, and the validation set is used to adjust the model parameters and hyperparameters, and evaluate the performance of the model on unseen data. When the performance of the model on the validation set no longer improves significantly, or reaches the predetermined performance indicator, the training can be stopped to avoid overfitting, so as to avoid overfitting of the model to the training data and poor generalization ability to new data.

[0041] In one embodiment of this application, before extracting the feature values ​​of the suspension system data, the method further includes: preprocessing the suspension system data, which includes noise reduction, filtering, and isolation.

[0042] To ensure that the signal quality meets the requirements of data acquisition, the embodiments of this application can perform noise reduction, filtering, amplification and isolation on the acquired suspension system data to remove noise and interference and ensure the accuracy of the signal.

[0043] Furthermore, the processed data will be converted into digital signals via an analog-to-digital converter for processing by the central processing unit or microcontroller. The acquired digital signals must be transmitted to the vehicle's central processing unit or central control screen system via some communication protocol (such as CAN bus, LIN bus, Ethernet, or other in-vehicle networks).

[0044] In step S103, the response area of ​​the vehicle's touch interface is adjusted according to the touch offset.

[0045] In one embodiment of this application, adjusting the response area of ​​a vehicle's touch interface based on a touch offset includes: identifying the offset position of the touch offset; and adjusting the actual position of the response area based on the offset position, wherein the offset position and the actual position are opposite.

[0046] This application embodiment can dynamically adjust the response area of ​​buttons or other interactive elements on the touch interface based on the predicted touch offset to compensate for touch errors caused by bumps, resulting in higher accuracy and adaptability, and significantly improving the driving experience and safety. For example, if it is predicted that the touch point will shift to the lower right, this application embodiment will shift the response area of ​​the actual touch point to the upper left to ensure that when the user attempts to click a button, the user's true intention can be recognized.

[0047] It should be noted that the adjustment speed of the interface response area should be able to match the dynamic changes of the vehicle's suspension system. The adjustment range of the interface response area is usually between a few millimeters and a few centimeters, depending on the predicted touch offset.

[0048] Furthermore, after adjusting the response area of ​​the vehicle's touch interface based on the touch offset, the system also includes: detecting the actual road conditions of the vehicle; dynamically adjusting the layout of the touch page according to the actual road conditions; and / or adjusting the display effect of the virtual keyboard or buttons.

[0049] Under normal conditions, this embodiment of the application can temporarily enlarge the size of the virtual keyboard or buttons and hide unimportant or infrequently used function buttons while driving to increase the accuracy of user touches. Visual or auditory cues can also guide the user's operation; for example, by highlighting the target button or guessing the user's intention, or by using voice prompts to assist the user, helping them operate accurately without taking their eyes off the road.

[0050] The following is combined Figure 2 A specific structural example illustrates the adaptive method for a touch page according to an embodiment of this application, including the following steps:

[0051] Step 1: Data Acquisition: Suspension system sensors, including accelerometers and gyroscopes, are used to measure the vehicle's vibration and motion. The sensor data acquisition unit is the hardware used to receive and process sensor signals. The data transmission system includes the necessary circuitry and interfaces for transmitting sensor data to the vehicle's central processing unit (CPU) or central control screen.

[0052] Step 2: Data Storage and Analysis: The central processing unit (CPU) is the hardware used to execute data analysis algorithms. Data analysis software includes algorithms and programs used to process and interpret sensor data.

[0053] Step 3: Adaptive Calibration of the Touchscreen: The central control screen, a touchscreen display, is typically part of the vehicle's infotainment system. The adaptive calibration module is a software module integrated into the central control screen's operating system or application. It receives and analyzes suspension system data and calculates touch offset in real time.

[0054] Step 4: Touch Interface Correction: A dynamic adjustment algorithm is used to adjust the response area of ​​the touch interface based on the predicted touch offset. As the user interface software for the central control screen, the touch interface software needs to be able to update the interface response area in real time.

[0055] The adaptive touchscreen method proposed in this application collects and analyzes dynamic data from the vehicle suspension system to predict and quantify touch offset caused by bumps, and dynamically adjusts the response area of ​​the touchscreen interface to compensate for touch errors caused by bumps. This method can improve the user's operating experience on bumpy roads while ensuring driving safety and reducing inconvenience caused by operational errors. Therefore, it solves the problems in related technologies where indirect data collection of screen touch events is used for analysis and correction, resulting in inaccurate correction and potential touch errors that affect driving experience and safety.

[0056] Next, with reference to the accompanying drawings, an adaptive device for a touch page according to an embodiment of this application is described.

[0057] Figure 3 This is a block diagram of an adaptive device for a touch page according to an embodiment of this application.

[0058] like Figure 3 As shown, the adaptive device 10 of the touch page includes: a data acquisition module 100, an input / output module 200, and a first adjustment module 300.

[0059] The acquisition module 100 is used to acquire suspension system data of the vehicle; the input-output module 200 is used to extract feature values ​​from the suspension system data, input the feature values ​​into a pre-trained prediction model, and output the touch offset corresponding to the feature values; the first adjustment module 300 is used to adjust the response area of ​​the vehicle's touch interface according to the touch offset.

[0060] Optionally, the adjustment module 300 is further used to identify the offset position of the touch offset; and adjust the actual position of the response area according to the offset position, wherein the offset position and the actual position are opposite.

[0061] In one embodiment of this application, the adaptive device 10 for the touch page further includes a detection module and a second adjustment module.

[0062] The detection module is used to detect the actual road conditions of the vehicle; the second adjustment module is used to dynamically adjust the layout of the touch page according to the actual road conditions, and / or adjust the display effect of the virtual keyboard or buttons.

[0063] In one embodiment of this application, the adaptive device 10 for the touch page further includes: a training module, configured to acquire a dataset before inputting feature values ​​into a pre-trained prediction model, wherein the dataset includes suspension system data and actual touch positions under different road conditions; split the dataset into a training set and a validation set; train the prediction model using the training set and validate the trained prediction model using the validation set, until training stops when a preset condition is met.

[0064] In one embodiment of this application, the adaptive device 10 for the touch page further includes a preprocessing module for preprocessing the suspension system data before extracting the feature values ​​of the suspension system data. The preprocessing includes noise reduction, filtering, and isolation.

[0065] In one embodiment of this application, the feature values ​​include one or more of the following: vibration amplitude, vibration frequency, vibration duration, and rate of change of acceleration.

[0066] It should be noted that the foregoing explanation of the adaptive method embodiment for touch page also applies to the adaptive device for touch page in this embodiment, and will not be repeated here.

[0067] The adaptive touchscreen device proposed in this application collects and analyzes dynamic data from the vehicle's suspension system to predict and quantify touch offset caused by bumps, and dynamically adjusts the response area of ​​the touchscreen interface to compensate for touch errors caused by bumps. This improves the user experience on bumpy roads while ensuring driving safety, reducing inconvenience and potential risks caused by operational errors. Therefore, it solves the problems in related technologies where indirect data collection of screen touch events is used for analysis and correction, leading to inaccurate correction and potential touch errors that affect driving experience and safety.

[0068] Next, with reference to the accompanying drawings, an adaptive device for a touch page according to an embodiment of this application is described.

[0069] Figure 4 A schematic diagram of the structure of a vehicle provided in an embodiment of this application. The vehicle may include:

[0070] The memory 401, the processor 402, and the computer program stored on the memory 401 and capable of running on the processor 402.

[0071] When the processor 402 executes the program, it implements the adaptive method for the touch page provided in the above embodiments.

[0072] Furthermore, the vehicle also includes:

[0073] Communication interface 403 is used for communication between memory 401 and processor 402.

[0074] The memory 401 is used to store computer programs that can run on the processor 402.

[0075] The memory 401 may include high-speed RAM (Random Access Memory) memory, and may also include non-volatile memory, such as at least one disk storage.

[0076] If the memory 401, processor 402, and communication interface 403 are implemented independently, then the communication interface 403, memory 401, and processor 402 can be interconnected via a bus to complete communication between them. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0077] Optionally, in a specific implementation, if the memory 401, processor 402, and communication interface 403 are integrated on a single chip, then the memory 401, processor 402, and communication interface 403 can communicate with each other through an internal interface.

[0078] Processor 402 may be a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of this application.

[0079] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described adaptive method for touch pages.

[0080] This application also provides a computer program product, including: a computer program or instructions, which, when executed, implement the above-described adaptive method for touch pages.

[0081] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0082] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0083] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0084] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (FPGAs), field-programmable gate arrays (FPGAs), etc.

[0085] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0086] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. An adaptive method for touch pages, characterized in that, Includes the following steps: Collect data on the vehicle's suspension system; The feature values ​​of the suspension system data are extracted, and the feature values ​​are input into a pre-trained prediction model. The prediction model outputs the touch offset corresponding to the feature values. The response area of ​​the vehicle's touch interface is adjusted according to the touch offset.

2. The adaptive method for touch pages according to claim 1, characterized in that, Adjusting the response area of ​​the vehicle's touch interface based on the touch offset includes: Identify the offset position of the touch offset; The actual position of the response region is adjusted according to the offset position, wherein the offset position and the actual position are opposite.

3. The adaptive method for touch pages according to claim 1, characterized in that, After adjusting the response area of ​​the vehicle's touch interface according to the touch offset, the method further includes: Detect the actual road conditions under which the vehicle is traveling; The layout of the touch page is dynamically adjusted according to the actual road conditions, and / or the display effect of the virtual keyboard or buttons is adjusted.

4. The adaptive method for touch pages according to claim 1, characterized in that, Before inputting the feature values ​​into the pre-trained prediction model, the method further includes: Obtain a dataset, wherein the dataset includes suspension system data and actual contact positions under different road surface conditions; The dataset is split into a training set and a validation set; The prediction model is trained using the training set and validated using the validation set until a preset condition is met, at which point training stops.

5. The adaptive method for touch pages according to claim 1, characterized in that, Before extracting the feature values ​​of the suspension system data, the process also includes: The suspension system data is preprocessed, including noise reduction, filtering, and isolation.

6. The adaptive method for a touch page according to any one of claims 1-5, characterized in that, The characteristic values ​​include one or more of the following: vibration amplitude, vibration frequency, vibration duration, and rate of change of acceleration.

7. An adaptive device for a touch page, characterized in that, include: The data acquisition module is used to collect data from the vehicle's suspension system. The input / output module is used to extract feature values ​​from the suspension system data, input the feature values ​​into a pre-trained prediction model, and output the touch offset corresponding to the feature values. The first adjustment module is used to adjust the response area of ​​the vehicle's touch interface according to the touch offset.

8. A vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the adaptive method for a touch page as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed, they implement the adaptive method for the touch page as described in any one of claims 1-6.

10. A computer program product comprising: A computer program or instruction, characterized in that, when executed, the computer program or instruction implements the adaptive method for a touch page as described in any one of claims 1-6.

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