Car window anti-pinch method and device and storage medium

Abstract

The invention discloses a car window anti-pinch method and device and a storage medium. The method comprises the steps that first data generated when a car window runs at the time is obtained; the first data comprises first current data of the vehicle window driving part during current operation; based on the difference between the first current data and the current threshold data, whether an obstacle exists in the vehicle window or not is determined; the current threshold data is obtained by performing clustering analysis on second data generated during multiple times of operation of the vehicle window at the historical moment, and each piece of second data comprises second current data when the vehicle window driving piece drives the vehicle window to operate each time. By means of the mode, the accuracy of anti-pinch judgment can be improved, and accurate anti-pinch can be achieved.

Description

Technical Field

[0001] The present application relates to the field of automobile safety technology, and in particular to a vehicle window anti-pinch method, device and storage medium. Background Art

[0002] As users' demand for safety protection increases, the anti-pinch function of car windows has become a research hotspot. In traditional methods, the setting of the anti-pinch threshold often relies on engineers' experience and experimental data. This method is not only time-consuming and labor-intensive, but also easily affected by human factors, resulting in inaccurate anti-pinch thresholds, which in turn leads to misjudgment during the operation of the car windows. Therefore, how to improve the accuracy of anti-pinch judgment is crucial to user safety. Summary of the invention

[0003] The main technical problem solved by the present application is to provide a vehicle window anti-pinch method, device and storage medium, which can improve the accuracy of anti-pinch judgment and thus accurately prevent pinching.

[0004] In order to solve the above technical problems, a technical solution adopted in the present application is: to provide a method for preventing vehicle windows from being pinched, the method comprising: obtaining first data generated by the vehicle window during the current operation; the first data comprises first current data of the vehicle window driving component during the current operation; based on the difference between the first current data and the current threshold data, determining whether there is an obstacle on the vehicle window; the current threshold data is obtained by clustering analysis of second data generated respectively when the vehicle window is operated at several times at historical moments, and each second data comprises second current data of the vehicle window driving component when driving the vehicle window at each operation.

[0005] The first data and the second data also include a plurality of window data when the window is operated in corresponding times, and each second current data includes the first current corresponding to the window driving component when driving the window to operate in the plurality of window data.

[0006] The vehicle window data includes at least one of a vehicle window position and a vehicle window operation time corresponding to when the vehicle window moves to the vehicle window position.

[0007] Among them, before determining whether there is an obstacle on the vehicle window based on the difference between the first current data and the current threshold data, it also includes: determining the number of categories to be clustered; performing cluster analysis on the second data generated by the vehicle window during several operations to obtain the number of first current sets of categories; and obtaining current threshold data based on each first current set.

[0008] The number of categories is the same as the number of window data when the window is operated at each time, and the current threshold data includes the target current threshold corresponding to the window when the window is operated at each window data; cluster analysis is performed on the second data generated by the window when the window is operated several times to obtain the number of first current sets of categories, including: selecting the number of first currents of categories from each second current data as the reference current thresholds corresponding to the number of window data of categories; obtaining the second current set corresponding to each window data based on the distance from each first current to the reference current threshold corresponding to each window data; for each window data, selecting from the second current set of the window data A first current is used as a new reference current threshold for the vehicle window data, and the distance from each first current to the reference current threshold corresponding to each vehicle window data is re-executed to obtain a second current set corresponding to each vehicle window data and subsequent steps, until the number of times the second current set corresponding to each vehicle window data is obtained reaches a preset number, or when the difference between the reference current threshold obtained this time and the previous time is less than the first preset threshold, the second current set obtained last time is used as the first current set; based on each first current set, current threshold data is obtained, including: the centroid of each first current set is used as the target current threshold corresponding to the vehicle window when the window operates at each vehicle window data.

[0009] The step of acquiring the first data generated by the vehicle window during the current operation is performed when the vehicle window enters a preset anti-pinch area.

[0010] Among them, the first current data includes the second current corresponding to the window operating at each window position or at each operating time, and the current threshold data includes the target current threshold corresponding to the window operating at each window position or at each operating time; based on the difference between the first current data and the current threshold data, determining whether there is an obstacle on the window includes: in response to the difference between the second current operating at any window position or at any operating time and the corresponding target current threshold being greater than a second preset threshold, determining that there is an obstacle on the window.

[0011] The current threshold data is obtained by clustering the second data generated by the vehicle window during several operations using a trained target clustering algorithm; and / or each second data is data determined when there is no obstacle in the vehicle window.

[0012] To solve the above technical problems, another technical solution adopted in the present application is: to provide an electronic device, comprising a memory and a processor coupled to each other, the memory storing program instructions; the processor is used to execute the program instructions stored in the memory to implement the above method.

[0013] In order to solve the above technical problem, another technical solution adopted by the present application is: providing a computer-readable storage medium for storing program instructions, which can be executed to implement the above method.

[0014] In the above scheme, after obtaining the first data generated by the window during the current operation, the difference between the first current data of the window driver during the current operation and the current threshold data in the first data is used to determine whether there is an obstacle on the window. The current threshold data is an anti-pinch judgment parameter, which is obtained by clustering the second data generated by the window during several operations at historical moments, and each second data includes the second current data of the window driver when driving the window during each operation. Since the current threshold data of the present application is obtained by clustering the historical current data of the window during multiple operations, the multiple historical current data include the operation of the window under different conditions. Compared with the method of determining the current threshold using multiple cycle experimental data, the current threshold data of the present application is determined by considering the current characteristics of the window under different operating conditions. Therefore, the current threshold determined by the present application can reflect the current characteristics of the window under different operating conditions, thereby improving the accuracy of the anti-pinch judgment, and thus accurately preventing pinching. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of an embodiment of a vehicle window anti-pinch method provided by the present application;

[0016] Figure 2 yes Figure 1 The flowchart of an embodiment before step S12 is shown;

[0017] Figure 3 It is a schematic diagram of the framework of an embodiment of a vehicle window anti-pinch device provided by the present application;

[0018] Figure 4 It is a schematic diagram of a framework of an embodiment of an electronic device provided by the present application;

[0019] Figure 5 It is a schematic diagram of the framework of the computer-readable storage medium provided by this application. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and effect of the present application clearer and more specific, the present application is further described in detail below with reference to the accompanying drawings and examples.

[0021] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0022] See also Figure 1 , Figure 1 1 is a flow chart of an embodiment of the vehicle window anti-pinch method provided by the present application. It should be noted that if there are substantially the same results, this embodiment is not limited to Figure 1 The process sequence shown is limited. Figure 1 As shown, this embodiment includes:

[0023] S11: Acquire first data generated when the vehicle window is currently operating; the first data includes first current data of the vehicle window driving component when the vehicle window is currently operating.

[0024] In one embodiment, the first data also includes a number of window data when the window is running, wherein the window data includes at least one of the window position and the window running time corresponding to when the window runs to the window position. The window position is the position point that the window passes during the operation process, and the window running time is the running time corresponding to when the window starts to run to the corresponding position point. In this embodiment, the first current data includes the second current corresponding to the window drive component when the window runs at each window position or each running time.

[0025] The window drive component may be a drive motor or other structure capable of driving the window to operate. The current of the window drive component during the operation of the window may be acquired by using a set hardware circuit.

[0026] S12: Determine whether there is an obstacle on the vehicle window based on the difference between the first current data and the current threshold data; the current threshold data is obtained by clustering analysis of second data generated respectively when the vehicle window is operated at several historical moments, and each second data includes the second current data of the vehicle window driving component when driving the vehicle window at each operation.

[0027] In summary, the current threshold data in this embodiment is obtained by clustering analysis of the second current data of the window driving component when the window is operated at each historical moment.

[0028] In one embodiment, the second current data during each operation includes the first current corresponding to the window driver when driving the window to operate in several window data. The current threshold data in this embodiment includes multiple current thresholds obtained by clustering analysis of the first current corresponding to the window operating in each window data for multiple times.

[0029] Specifically, the current threshold data includes the target current threshold corresponding to the window when it is operating at each window position or at each operating time. That is, in this embodiment, when the window is at each operating position point (window position) or each operating time point, there is a corresponding target current threshold, and the target current threshold is the current threshold for anti-pinch judgment at the corresponding window position or the corresponding operating time.

[0030] If the difference between the second current and the corresponding target current threshold when the window is running at any window position or at any running time is greater than a second preset threshold, it is determined that there is an obstacle in the window. At this time, the window anti-pinch function can be activated, such as controlling the window drive member to reverse or stop rotating to prevent the obstacle located at the window from being pinched. The obstacle can be, but is not limited to, various parts of the user's body, and can also be other objects.

[0031] In one implementation scenario, the second data are data determined when there is no obstacle in the vehicle window. Therefore, the current threshold data obtained by cluster analysis reflects the normal current representative value of the vehicle window driving component when there is no obstacle.

[0032] In one embodiment, the second preset threshold value may be 0, that is, when the second current is greater than the corresponding target current threshold value, it is determined that there is an obstacle on the vehicle window. In another embodiment, the second preset threshold value may also be set to a value slightly greater than 0, so that when the second current is greater than the corresponding target current threshold value and the corresponding difference is greater than the second preset threshold value, it is determined that there is an obstacle on the vehicle window.

[0033] It should be noted that, since the cluster analysis is performed based on historical current data, as new data is continuously added, the current threshold data can be dynamically updated and adjusted to better adapt to the operating conditions of the vehicle windows at different times and in different environments.

[0034] In addition, cluster analysis is an unsupervised learning technique that can automatically identify patterns and structures in data without prior knowledge. Therefore, in the window anti-pinch application, the cluster analysis algorithm can discover the common features of current data under different operating conditions, and thus build a more accurate current threshold based on these features.

[0035] In addition, cluster analysis can process a large amount of historical current data, which includes the operation of the windows under different conditions (such as temperature, humidity, load, speed, etc.). This diversity ensures the comprehensiveness and representativeness of the analysis results, so that the current threshold can cover a wider range of possible operating conditions, thereby making the obtained current threshold data more accurate.

[0036] In the above scheme, after obtaining the first data generated by the window during the current operation, the difference between the first current data of the window driver during the current operation and the current threshold data in the first data is used to determine whether there is an obstacle on the window. The current threshold data is an anti-pinch judgment parameter, which is obtained by clustering the second data generated by the window during several operations at historical moments, and each second data includes the second current data of the window driver when driving the window during each operation. Since the current threshold data of the present application is obtained by clustering the historical current data of the window during multiple operations, the multiple historical current data include the operation of the window under different conditions. Compared with the method of determining the current threshold using multiple cycle experimental data, the current threshold data of the present application is determined by considering the current characteristics of the window under different operating conditions. Therefore, the current threshold determined by the present application can reflect the current characteristics of the window under different operating conditions, thereby improving the accuracy of the anti-pinch judgment, and thus accurately preventing pinching.

[0037] In some embodiments, step S11 is performed when the vehicle window enters a preset anti-pinch area. Exemplarily, when the vehicle window enters the preset anti-pinch area, the second current of the vehicle window driving component is collected at a preset time or preset position interval to obtain the first data generated by the vehicle window during the current operation.

[0038] In some embodiments, before step S12 , current threshold data needs to be determined.

[0039] Specifically, see Figure 2 , Figure 2 yes Figure 1 The flowchart of an embodiment before step S12 is shown. This embodiment includes:

[0040] S21: Determine the number of categories to be clustered.

[0041] In one embodiment, considering that the user's body may be at any position in the anti-pinch area during the operation of the window, in order to achieve window anti-pinch at various positions, the number of clustered data to be clustered can be set to be the same as the number of window data (each window position or each operation time) at each operation of the window, and the current threshold data includes the target current threshold corresponding to the window under each window data.

[0042] S22: performing cluster analysis on the second data generated when the vehicle window is operated for a plurality of times, and obtaining first current sets of the number of categories.

[0043] As can be seen from the above, each second current data of the window during each operation includes the first currents corresponding to the window driver when driving the window to operate in a plurality of window data. In this embodiment, cluster analysis is performed on the first currents of the window when operating in each window data for multiple times to obtain the first current sets of the number of categories. For example, cluster analysis is performed on the first currents at each window position for multiple times or at each operation time for multiple times to obtain the first current sets at each window position or each operation time.

[0044] Among them, in the clustering process, firstly, a first current of a category number is selected from each second current data as the reference current threshold corresponding to the category number of window data respectively; then, based on the distance from each first current to the reference current threshold corresponding to each window data, the second current set corresponding to each window data is obtained; for each window data, a first current is selected from the second current set of the window data as the new reference current threshold of the window data, and the distance from each first current to the reference current threshold corresponding to each window data is re-executed to obtain the second current set corresponding to each window data and subsequent steps, until the number of times the second current set corresponding to each window data is obtained reaches a preset number, or when the difference between the reference current threshold obtained this time and the previous time is less than the first preset threshold, the second current set obtained last time is used as the first current set.

[0045] Exemplarily, taking the number of categories as K and the window data as the window position as an example, the above clustering analysis process is explained: first, K first currents are randomly selected from multiple second current data generated when the window is operated multiple times as reference current thresholds at each window position, and then the distance from each first current to each reference current threshold is determined, and each first current and the current corresponding to its nearest reference current threshold are combined according to the distance to obtain a second current set corresponding to each window position, and then a new reference current threshold is determined from the second current set of each window data (which can be the centroid of the second current set, or the first current closest to the centroid), and the current corresponding to each first current and the reference current threshold are combined according to the distance to obtain the second current set corresponding to each window data and subsequent steps, until the number of times the second current set corresponding to each window position is obtained reaches a preset number, or when the difference between the reference current thresholds obtained by the current clustering and the previous clustering is less than the first preset threshold, the second current set obtained for the last time is used as the first current set.

[0046] S23: Obtaining current threshold data based on each first current set.

[0047] In one embodiment, the centroid of each first current set may be used as the target current threshold corresponding to the vehicle window when operating at each vehicle window data.

[0048] In another embodiment, the first current in each first current set that is closest to the centroid of the corresponding first current set may be used as the target current threshold corresponding to the vehicle window when operating at each vehicle window data.

[0049] In some embodiments, considering that the above-mentioned current may be collected at preset time intervals or preset position intervals, after obtaining the target current threshold corresponding to each window data in step S23, the target current threshold corresponding to each window data can be fitted to obtain a fitting curve, and the fitting curve is used as a current threshold curve, so as to obtain the current threshold when the window passes through each position or runs at each time point, and use the difference between the second current collected at each position or each time point and the corresponding current threshold to determine whether there is an obstacle on the window.

[0050] In some embodiments, the current threshold data is obtained by performing cluster analysis on second data generated by the vehicle window during several operations using a trained target clustering algorithm.

[0051] In one embodiment, before using the trained target clustering algorithm to cluster the second data generated by the window during several operations to obtain the current threshold data, the target clustering algorithm needs to be trained. Exemplarily, the training process includes: first, the current data generated by the window driver during operation is collected through a hardware circuit, with 5ms as a sampling point, and the recording starts after the window enters the anti-pinch area, and the relevant state information of the window is recorded at the same time, such as position, speed, whether there is an object, etc. Then, the collected data is cleaned and preprocessed to remove noise and outliers, and the data is standardized or normalized to facilitate the processing of the target clustering algorithm; meaningful features are extracted from the original collected current data, including frequency, amplitude, phase and other features, and then the current data is converted into corresponding feature representations through Fourier transform; the preprocessed data and the extracted features are used to train the target clustering algorithm, and the algorithm parameters are adjusted to obtain the best target clustering algorithm.

[0052] Finally, the trained target clustering algorithm is deployed to the car's window control system to realize the anti-pinch function of the window.

[0053] Please see Figure 3 , Figure 3It is a schematic diagram of the framework of an embodiment of the vehicle window anti-pinch device provided by the present application. In this embodiment, the vehicle window anti-pinch device 30 includes an acquisition module 31 and a determination module 32. The acquisition module 31 is used to acquire the first data generated by the vehicle window during the current operation; the first data includes the first current data of the vehicle window driver during the current operation; the determination module 32 is used to determine whether there is an obstacle on the vehicle window based on the difference between the first current data and the current threshold data; the current threshold data is obtained by clustering analysis of the second data generated by the vehicle window during several operations at historical moments, and each second data includes the second current data of the vehicle window driver when driving the vehicle window during each operation.

[0054] In some embodiments, the first data and the second data further include a plurality of vehicle window data when the vehicle window operates in corresponding times, and each second current data includes the first current corresponding to the vehicle window driving component when driving the vehicle window to operate in the plurality of vehicle window data.

[0055] In some embodiments, the vehicle window data includes at least one of a vehicle window position and a corresponding vehicle window operation time when the vehicle window moves to the vehicle window position.

[0056] In some embodiments, before the determination module 32 determines whether there is an obstacle on the vehicle window based on the difference between the first current data and the current threshold data, it also includes: determining the number of categories to be clustered; performing cluster analysis on the second data generated by the vehicle window during several operations to obtain the number of first current sets of categories; and obtaining current threshold data based on each first current set.

[0057] In some embodiments, the number of categories is the same as the number of window data when the window is operated at each time, and the current threshold data includes a target current threshold corresponding to the window when the window is operated at each window data; cluster analysis is performed on the second data generated by the window when the window is operated for several times to obtain the first current sets of the number of categories, including: selecting the first currents of the number of categories from each second current data as the reference current thresholds corresponding to the number of categories of window data; obtaining the second current set corresponding to each window data based on the distance from each first current to the reference current threshold corresponding to each window data; for each window data, determining a new reference current threshold from the second current set of the window data, and re-performing the distance from each first current to the reference current threshold corresponding to each window data to obtain the second current set corresponding to each window data and subsequent steps, until the number of times the second current set corresponding to each window data is obtained reaches a preset number of times, or when the difference between the reference current threshold obtained this time and the previous time is less than the first preset threshold, the second current set obtained last time is used as the first current set; obtaining the current threshold data based on each first current set includes: using the centroid of each first current set as the target current threshold corresponding to the window when the window is operated at each window data.

[0058] In some embodiments, the step of the acquisition module 31 acquiring the first data generated by the vehicle window during the current operation is performed when the vehicle window enters a preset anti-pinch area.

[0059] In some embodiments, the first current data includes a second current corresponding to the window operating at each window position or at each operating time, and the current threshold data includes a target current threshold corresponding to the window operating at each window position or at each operating time; the determination module 32 determines whether there is an obstacle on the window based on the difference between the first current data and the current threshold data, including: in response to the difference between the second current operating at any window position or at any operating time and the corresponding target current threshold being greater than a second preset threshold, determining that there is an obstacle on the window.

[0060] In some embodiments, the current threshold data is obtained by clustering the second data generated by the vehicle window during several operations using a trained target clustering algorithm; and / or each second data is data determined when there is no obstacle in the vehicle window.

[0061] See also Figure 4 , Figure 4 4 is a schematic diagram of a framework of an electronic device according to an embodiment of the present application. In this embodiment, the electronic device 40 includes a memory 41 and a processor 42 coupled to each other.

[0062] The memory 41 stores program instructions, and the processor 42 is used to execute the program instructions stored in the memory 41 to implement the steps of any of the above-mentioned method implementation methods. In a specific implementation scenario, the electronic device 40 may include but is not limited to: a microcomputer, a server, and in addition, the electronic device 40 may also include a mobile device such as a laptop computer and a tablet computer, which is not limited here.

[0063] Specifically, the processor 42 is used to control itself and the memory 41 to implement the steps of any of the above-mentioned embodiments. The processor 42 can also be called a CPU (Central Processing Unit). The processor 42 may be an integrated circuit chip with signal processing capabilities. The processor 42 can also be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field-programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. In addition, the processor 42 can be implemented by an integrated circuit chip.

[0064] See also Figure 5 , Figure 5 It is a schematic diagram of the framework of the computer-readable storage medium provided by the present application. The computer-readable storage medium 50 of the embodiment of the present application stores a program instruction 51, and when the program instruction 51 is executed, the method provided by any embodiment of the above method and any non-conflicting combination is implemented. Among them, the program instruction 51 can form a program file and be stored in the above-mentioned computer-readable storage medium 50 in the form of a software product, so that a computer device (which can be a personal computer, a server, or a network device, etc.) executes all or part of the steps of each implementation method of the present application. The aforementioned computer-readable storage medium 50 includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, or a terminal device such as a computer, a server, a mobile phone, and a tablet.

[0065] In the above scheme, after obtaining the first data generated by the window during the current operation, the difference between the first current data of the window driver during the current operation and the current threshold data in the first data is used to determine whether there is an obstacle on the window. The current threshold data is an anti-pinch judgment parameter, which is obtained by clustering the second data generated by the window during several operations at historical moments, and each second data includes the second current data of the window driver when driving the window during each operation. Since the current threshold data of the present application is obtained by clustering the historical current data of the window during multiple operations, the multiple historical current data include the operation of the window under different conditions. Compared with the method of determining the current threshold using multiple cycle experimental data, the current threshold data of the present application is determined by considering the current characteristics of the window under different operating conditions. Therefore, the current threshold determined by the present application can reflect the current characteristics of the window under different operating conditions, thereby improving the accuracy of the anti-pinch judgment, and thus accurately preventing pinching.

[0066] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0067] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

[0068] In the several embodiments provided in the present application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device implementation described above is only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0069] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0070] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0071] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) or a processor (processor) to perform all or part of the steps of each implementation method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

[0072] The above description is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A vehicle window anti-pinch method, characterized in that: The method comprises: Acquire first data generated when the vehicle window is operated at the time; the first data includes first current data of the vehicle window driving component when the vehicle window is operated at the time; Based on the difference between the first current data and the current threshold data, it is determined whether there is an obstacle on the vehicle window; the current threshold data is obtained by clustering analysis of second data generated respectively when the vehicle window is operated several times at historical moments, and each second data includes second current data of the window driving component when driving the vehicle window at each operation.

2. The method according to claim 1, characterized in that The first data and the second data also include a plurality of vehicle window data when the vehicle window operates in corresponding times, and each of the second current data includes the first currents corresponding to the vehicle window driving component when driving the vehicle window to operate in the plurality of the vehicle window data.

3. The method according to claim 2, characterized in that The vehicle window data includes at least one of a vehicle window position and a corresponding vehicle window operation time when the vehicle window operates to the vehicle window position.

4. The method according to claim 2 or 3, characterized in that: Before determining whether there is an obstacle on the vehicle window based on the difference between the first current data and the current threshold data, the method further includes: Determine the number of categories to be clustered; Performing cluster analysis on the second data generated by the vehicle window during a plurality of operations to obtain the first current sets of the number of categories; The current threshold data is obtained based on each first current set.

5. The method according to claim 4, characterized in that The number of categories is the same as the number of window data of the window at each operation, and the current threshold data includes a target current threshold corresponding to each window data when the window operates; The cluster analysis is performed on the second data generated by the vehicle window during a plurality of operations to obtain the first current sets of the number of categories, including: Selecting the first currents of the number of categories from each of the second current data as reference current thresholds corresponding to the number of window data of the number of categories; Based on the distance between each first current and the reference current threshold corresponding to each window data, obtaining a second current set corresponding to each window data; For each of the vehicle window data, a new reference current threshold is determined from the second current set of the vehicle window data, and the distance from each of the first currents to the reference current threshold corresponding to each of the vehicle window data is re-executed to obtain the second current set corresponding to each of the vehicle window data and subsequent steps, until the number of times the second current set corresponding to each of the vehicle window data is obtained reaches a preset number of times, or when the difference between the reference current threshold obtained this time and the previous time is less than the first preset threshold, the second current set obtained last time is used as the first current set; The obtaining the current threshold data based on each first current set includes: The centroid of each of the first current sets is used as the target current threshold corresponding to the vehicle window when the vehicle window operates at each of the vehicle window data.

6. The method according to claim 1, characterized in that The step of acquiring the first data generated by the vehicle window during the current operation is performed when the vehicle window enters a preset anti-pinch area.

7. The method according to claim 1, characterized in that The first current data includes a second current corresponding to the window operating at each window position or at each operating time, and the current threshold data includes a target current threshold corresponding to the window operating at each window position or at each operating time; The determining whether there is an obstacle on the vehicle window based on the difference between the first current data and the current threshold data comprises: In response to a difference between the second current under any window position or at any operating time and the corresponding target current threshold being greater than a second preset threshold, it is determined that an obstacle exists on the window.

8. The method according to claim 1, characterized in that The current threshold data is obtained by clustering the second data generated by the vehicle window during several operations using a trained target clustering algorithm; And / or, each of the second data is data determined when there is no obstacle in the vehicle window.

9. An electronic device, characterized in that: comprising a memory and a processor coupled to each other, The memory stores program instructions; The processor is used to execute the program instructions stored in the memory to implement the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program instructions that can be run by a processor, and the program instructions can be executed by the processor to implement the method according to any one of claims 1 to 8.

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