A vehicle window control method and device, vehicle and storage medium

Abstract

This invention discloses a method, device, vehicle, and storage medium for controlling vehicle windows. The method includes: collecting brainwave data of a target occupant currently inside the vehicle; determining the target occupant's emotional information based on emotional brainwaves in the brainwave data, and determining the target occupant's window control needs based on window control brainwaves and / or weather-sensing brainwaves in the brainwave data, wherein the weather-sensing brainwaves are brainwaves generated by the target occupant upon seeing the current weather conditions; and controlling the vehicle windows based on the emotional information and the window control needs. The technical solution of this invention, by utilizing the brainwave data of occupants inside the vehicle, not only achieves control of windows in different locations but also ensures the accuracy of window control by combining the emotional information of the occupants.

Description

Technical Field

[0001] This invention relates to the field of vehicle control technology, and in particular to a method, device, vehicle, and storage medium for controlling vehicle windows. Background Technology

[0002] With the continuous development of information technology, intelligent vehicles have become a research hotspot in the field of vehicle engineering and a new driving force for the growth of the automotive industry in recent years. Many countries have incorporated them into their key intelligent transportation systems.

[0003] Intelligent vehicles are comprehensive systems integrating environmental perception, planning and decision-making, and multi-level assisted driving functions. They utilize technologies such as computers, modern sensing, information fusion, communication, artificial intelligence, and automatic control, making them typical high-tech complexes. Research on intelligent vehicles primarily focuses on improving vehicle safety and comfort, as well as providing superior human-vehicle interaction interfaces.

[0004] However, traditional vehicle window control methods are usually manual or voice control. When the vehicle is traveling at high speed, traditional vehicle window control methods may affect driving safety and may also lead to accidental opening and closing of windows, affecting the user experience. Summary of the Invention

[0005] This invention provides a method, device, vehicle, and storage medium for controlling vehicle windows, in order to solve the problem of poor user experience in traditional vehicle window control methods.

[0006] In a first aspect, the present invention provides a method for controlling vehicle windows, comprising:

[0007] Collect brainwave data of the target occupants currently inside the vehicle;

[0008] The emotional information of the target person is determined based on the emotional brainwaves in the brainwave data, and the window control needs of the target person are determined based on the window control brainwaves and / or weather perception brainwaves in the brainwave data, wherein the weather perception brainwaves are the brainwaves generated by the target person after seeing the current weather conditions.

[0009] Based on the emotional information and the window control request, control the windows of the current vehicle.

[0010] Secondly, the present invention provides a vehicle window control device, comprising:

[0011] The data acquisition module is used to collect the electroencephalogram (EEG) data of the target occupants inside the vehicle.

[0012] The control demand determination module is used to determine the emotional information of the target person based on the emotional brainwaves in the brainwave data, and to determine the window control demand of the target person based on the window control brainwaves and / or weather perception brainwaves in the brainwave data, wherein the weather perception brainwaves are the brainwaves generated by the target person after seeing the current weather conditions.

[0013] The window control module is used to control the windows of the current vehicle based on the emotional information and the window control requirements.

[0014] Thirdly, the present invention provides a vehicle comprising:

[0015] At least one processor;

[0016] and memory that is communicatively connected to at least one processor;

[0017] The memory stores a computer program that can be executed by at least one processor, which enables the at least one processor to perform the window control method of the first aspect described above.

[0018] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the window control method of the first aspect described above.

[0019] The vehicle window control scheme provided by this invention collects brainwave data of a target occupant inside the vehicle. Based on the emotional brainwaves within the brainwave data, the scheme determines the target occupant's emotional information. Furthermore, based on the window control brainwaves and / or weather-sensing brainwaves within the brainwave data, the scheme determines the target occupant's window control needs. The weather-sensing brainwaves are those generated when the target occupant observes the current weather conditions. Based on the emotional information and the window control needs, the scheme controls the vehicle's windows. By employing this technical solution and utilizing the brainwave data of the occupant, the scheme achieves control of windows in different locations. Compared to traditional vehicle window control methods, this improves driving safety. Since emotional fluctuations may occur during window control, inaccurate control can lead to negative emotions. Therefore, the scheme also accurately determines the occupant's emotions based on the brainwave data, further ensuring the accuracy of window control.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of a vehicle window control method provided in Embodiment 1 of the present invention;

[0023] Figure 2 This is a flowchart of a window control method according to Embodiment 2 of the present invention;

[0024] Figure 3 This is a schematic diagram of the structure of a window control device according to Embodiment 3 of the present invention;

[0025] Figure 4 This is a structural schematic diagram of a vehicle provided according to Embodiment 4 of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. In the description of this invention, unless otherwise stated, "a plurality of" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist; for example, A and / or B can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0028] Example 1

[0029] Figure 1 The flowchart of a vehicle window control method is provided in Embodiment 1 of the present invention. This embodiment is applicable to the control of vehicle windows. The method can be executed by a vehicle window control device, which can be implemented in hardware and / or software. The vehicle window control device can be configured in a vehicle, that is, the method can be executed by a vehicle. Specifically, it can be implemented in hardware and / or software. The vehicle is equipped with an electroencephalogram (EEG) data acquisition device, a processor, and a memory that is communicatively connected to the processor.

[0030] like Figure 1 As shown, the vehicle window control method provided in Embodiment 1 of the present invention specifically includes the following steps:

[0031] S101. Collect the brainwave data of the target person inside the current vehicle.

[0032] In this embodiment, the brain-computer interface can first be connected to the onboard computer signal of the current vehicle (hereinafter referred to as the vehicle). After the signal connection is completed, an electroencephalogram (EEG) data acquisition device, such as a headgear with EEG electrodes, is placed on the head of the target person (e.g., the driver). Using this EEG data acquisition device, the target person's EEG data can be acquired and input into the onboard computer via the brain-computer interface, thereby enabling control of the vehicle's windows. The target person can be any person in the vehicle who needs to control the windows. The brain-computer interface can be a non-implantable brain-computer interface, and it can include an acquisition module, a signal conversion module, a controller module, a data transmission module, and a power management module, etc.

[0033] S102. Determine the emotional information of the target person based on the emotional brainwaves in the brainwave data, and determine the target person's window control needs based on the window control brainwaves and / or weather perception brainwaves in the brainwave data, wherein the weather perception brainwaves are the brainwaves generated by the target person after seeing the current weather conditions.

[0034] In this embodiment, since emotional fluctuations also affect a person's brainwaves, the brainwaves of a first preset brain region, such as the frontal lobe, can be identified as emotional brainwaves. Based on these emotional brainwaves, the target person's emotional information can be determined. For example, the brainwave data can be input into a preset emotion recognition model, and the target person's emotional information can be determined based on the model's output. This emotional information can include the type of emotion, the degree of emotional positivity, and the time when the emotion occurs. Emotion types include excitement, pleasure, frustration, and anger, etc. The more positive the emotion type, the higher the degree of positivity. By recognizing the brainwaves related to car window control, the car window control needs can be determined. For example, the brainwaves of a second preset brain region, such as the occipital lobe, can be identified as car window control brainwaves. These brainwaves can then be input into a preset car window control need model, and the car window control needs can be determined based on the model's output. The car window control needs can include opening and closing the car window at different locations and the window's range. The weather conditions outside the car are closely related to the opening and closing of car windows. Therefore, by recognizing weather-sensing brainwaves, the window control needs can be determined. For example, the brainwaves of a third preset brain region, such as the parietal lobe, can be identified as weather-sensing brainwaves. These brainwaves are then input into a preset weather recognition model. The model's output determines the type of weather, and the window control needs are determined based on the weather type. For instance, if the weather type is heavy rain, the window control need is to close the window. If the first need determined by the window control brainwaves differs from the second need determined by the weather-sensing brainwaves, the window control need can be determined based on the order of events. For example, if the second need precedes the first need and they are different, the second need can be identified as the window control need first, and then the first need can be identified as the window control need. The second need will not be identified as the window control need again within a preset time period. Conversely, if the first need precedes the second need and they are different, the first need can be identified as the window control need first, and the second need will not be identified as the window control need again within a preset time period.

[0035] For example, the process of determining window control needs based on brainwaves related to window control can be as follows:

[0036] First, signal data from 17 brain electrodes related to vision, such as those in the occipital and parietal lobes, were selected as the target person's brainwaves for window control. These 17 electrodes are: P1, P2, P3, P4, P5, P6, P7, P8, Pz, POz, Oz, PO3, PO4, PO7, PO8, O1, and O2. Then, a Multilayer Perceptron (MLP) was used to identify the window control brainwaves. This MLP consists of an input layer, a hidden layer, and an output layer. The sigmoid function was used as the activation function. The number of neurons in the input layer is positively correlated with the amount of input window control brainwave data, and the number of neurons in the output layer is positively correlated with the number of categories of output window control requests. For example, if there are eight output window control requests, representing the raising and lowering of four windows, the number of neurons in the hidden layer can be between that in the input and output layers, ensuring that the hidden layer network does not overfit.

[0037] In the process of training an MLP, the sigmoid activation function can be used to map linear data (i.e., sample EEG data with category labels indicating window control needs) to non-linear data. This non-linear data is then processed in batches via forward propagation, calculating the error between the current output and the sample label, i.e., the loss, and continuously adjusting the weights in the neurons to update them. By correcting the node weights to minimize the loss, when the loss reaches its minimum and no longer changes, it indicates that the network has converged, and the trained MLP is complete.

[0038] S103. Control the windows of the current vehicle according to the emotional information and the window control requirements.

[0039] In this embodiment, since emotional fluctuations may occur during the window control process, the accuracy of the window control request can be determined based on emotional information. For example, when the window control request is inaccurately determined, the emotional information may be irritability. When the positiveness of the emotional information gradually decreases, it can be inferred that the window control request may be inaccurate. At this time, the EEG data and associated window control requests during this period can be recorded for subsequent analysis by developers to ensure continuous optimization of the accuracy of window control request recognition.

[0040] It is worth noting that the collection of EEG data from the target individuals, the determination of emotional information, and the determination of their window control needs all require prior authorization from the target individuals.

[0041] The vehicle window control method provided in this invention collects brainwave data of a target occupant inside the vehicle. Based on the emotional brainwaves within the brainwave data, the method determines the target occupant's emotional information. Furthermore, based on the window control brainwaves and / or weather-sensing brainwaves within the brainwave data, the method determines the target occupant's window control needs. The weather-sensing brainwaves are those generated when the target occupant observes the current weather conditions. Based on the emotional information and the window control needs, the method controls the vehicle's windows. This invention, by utilizing the brainwave data of occupants, achieves control of windows in different locations, improving driving safety compared to traditional vehicle window control methods. Since emotional fluctuations may occur during window control, inaccurate control can lead to negative emotions. Therefore, the method also accurately determines the occupant's emotions based on the brainwave data, further ensuring the accuracy of window control.

[0042] Example 2

[0043] Figure 2 This is a flowchart of a vehicle window control method provided in Embodiment 2 of the present invention. The technical solution of the present invention is further optimized based on the above optional technical solutions, and provides a specific way to control the vehicle windows.

[0044] Optionally, determining the target person's window control needs based on weather-sensing brainwaves in the brainwave data includes: determining a weather recognition result based on the weather-sensing brainwaves and a first preset brainwave recognition model; determining a target weather recognition result matching the weather recognition result from sample weather recognition results in a preset weather-window relationship database, wherein the preset weather-window relationship database contains a first association between the sample weather recognition results and preset window control needs; determining the target window control need corresponding to the target weather recognition result from the preset window control needs based on the first association, and identifying the target window control need as the target person's window control need. The advantage of this setup is that by utilizing the corresponding brainwave responses under different weather conditions, window control can be achieved based on the identified weather conditions before the person generates window control brainwaves.

[0045] Optionally, controlling the windows of the current vehicle based on the emotional information and the window control requirements includes: controlling the windows of the current vehicle based on the window control requirements, and during the process of controlling the windows of the current vehicle, determining the emotional change information of the emotional information and the demand change information of the window control requirements; determining whether the brainwave data is consistent with the actual needs of the target person based on at least one of the emotional change information, the demand change information, and a preset brainwave error library, wherein the preset brainwave error library contains abnormal brainwaves inconsistent with the actual needs; if consistent, then continuing to control the windows of the current vehicle based on the window control requirements. The advantage of this setting is that, since the target person's emotions and window control requirements usually change when their brainwave data is inconsistent with their actual needs, it is possible to accurately determine whether the target person's brainwave data is consistent with their actual needs based on the emotional change information, the demand change information, and at least one of the predetermined brainwave error library.

[0046] Optionally, after determining whether the EEG data matches the actual needs of the target person, the method further includes: if they do not match, determining target EEG data from the EEG data based on the change time of window control needs in the demand change information and / or the change time of emotional positivity in the emotion change information; determining target abnormal EEGs that match the target EEG data from the abnormal EEGs; determining the target control needs associated with the target abnormal EEGs based on the preset EEG error library, and controlling the windows of the current vehicle based on the target control needs, wherein the preset EEG error library also contains the association relationship between the abnormal EEGs and window control needs associated with window control operations. The advantage of this setup is that when the target person's EEG data does not match their actual needs, by comparing the target abnormal EEGs during the abnormal time period with the abnormal EEGs in the preset EEG error library, the correct window control needs—that is, the window control needs corresponding to the target person's actual window control operations—can be used to control the windows.

[0047] like Figure 2 As shown, the second embodiment of the present invention provides a vehicle window control method, which specifically includes the following steps:

[0048] S201. Collect the brainwave data of the target person inside the current vehicle.

[0049] S202. Determine the emotional information of the target person based on the emotional brainwaves in the brainwave data.

[0050] S203. Determine the weather recognition result based on the weather-sensing brainwaves and the first preset brainwave recognition model.

[0051] Specifically, weather-sensing brainwaves can be input into a first preset brainwave recognition model to obtain the model's output, i.e., the weather recognition result. The weather recognition result can be the type of weather, such as light rain, moderate rain, heavy rain, torrential rain, light snow, moderate snow, or heavy to blizzard conditions, etc., without limitation.

[0052] Optionally, weather-sensing brainwaves can be compared with sample brainwaves in a pre-defined weather brainwave sample database. The sample brainwave in the database that best matches the collected weather-sensing brainwaves is identified as the target sample, and the weather type corresponding to the target sample is identified as the weather recognition result. The sample brainwaves in the weather brainwave sample database can be pre-stored brainwaves of the target person. For example, the sample brainwave for "light snow" could be the brainwave of the target person when they saw light snow weather; this brainwave would be pre-stored in the weather brainwave sample database.

[0053] S204. Determine the target weather recognition result that matches the weather recognition result from the sample weather recognition results in the preset weather window relationship database.

[0054] The preset weather window relationship database contains the first association between the sample weather recognition results and the preset window control requirements.

[0055] For example, if the preset weather window relationship database contains relationships such as "light snow" and "close the window to the first preset position" (relationship 1) and "moderate snow" and "close the window to the second preset position" (relationship 2), then as described above, the target weather identification result is "light snow".

[0056] S205. Based on the first association relationship, determine the target window control requirement corresponding to the target weather recognition result from the preset window control requirements, and determine the target window control requirement as the window control requirement of the target person.

[0057] For example, as mentioned above, the target window control requirement corresponding to the target weather recognition result should be "close the window to the first preset position", which is the window control requirement of the target person.

[0058] Optionally, the preset window control requirements include window opening range requirements. Different preset window control requirements are associated with different weather recognition results, and the window opening range requirements are negatively correlated with the severity of the weather corresponding to the sample weather recognition results. The advantage of this setting is that it fully considers the impact of severe weather on window closing requirements, improving the accuracy of weather-aware EEG-based window control.

[0059] For example, the preset weather window relationship database may include the following: relationship 1 between "light snow" and "close the window to the first preset position", relationship 2 between "moderate snow" and "close the window to the second preset position", and relationship 3 between "heavy snow" and "close the window to the third preset position". The window opening range corresponding to the first preset position is greater than that corresponding to the second preset position, and the window opening range corresponding to the second preset position is greater than that corresponding to the third preset position. In other words, the required window opening range is negatively correlated with the severity of the weather corresponding to the sample weather recognition result.

[0060] S206. Control the windows of the current vehicle according to the window control requirements, and in the process of controlling the windows of the current vehicle, determine the emotional change information of the emotional information and the change information of the window control requirements.

[0061] Specifically, during the process of controlling the car windows according to the window control needs, the changes in the target person's emotions and the changes in the window control needs should also be recorded. If the changes in emotions and / or the changes in window control needs are abnormal in a short period of time, such as frequent changes or large changes, it indicates that the window control may also be abnormal.

[0062] S207. Based on at least one of the information on emotional changes, information on changes in needs, and a preset EEG error database, determine whether the EEG data is consistent with the actual needs of the target person. If they are consistent, proceed to step 208; if they are inconsistent, proceed to step 209.

[0063] The preset EEG error database contains abnormal EEG waves that are inconsistent with the actual requirements.

[0064] For example, if, within a short period of time, it is determined whether at least one of the following situations has occurred:

[0065] 1) Emotional change information shows that the target person's emotions change significantly, such as from pleasure to irritability; 2) Needs change information shows that the target person's needs change significantly and frequently, such as from opening the window to closing the window more than three times; 3) The target person's EEG data matches the EEG data in the preset EEG error database.

[0066] If this occurs, it can be determined that the target person's EEG data is inconsistent with the target person's actual needs.

[0067] Optionally, determining whether the brainwave data matches the actual needs of the target person based on at least one of the emotion change information, the demand change information, and a preset brainwave error database includes: if, within a first preset duration, the emotional positivity in the emotion change information shows a downward trend, and / or the frequency of changes in the window control demand in the demand change information is greater than a preset number, then it is determined that the brainwave data does not match the actual needs of the target person. The advantage of this setting is that it accurately determines whether the brainwave data matches the actual needs of the target person by utilizing the target person's emotion changes and the frequency of changes in window control demand.

[0068] For example, if the first preset duration is 1 minute and the preset number of times is 3, then if within 1 minute, the positive emotional level in the emotional change information is on a downward trend or a preset negative emotion appears, such as changing from pleasure to irritability or irritability, and / or the frequency of changes in the window control demand in the demand change information is greater than 3 times, then it can be determined that the target person's EEG data is inconsistent with the target person's actual needs.

[0069] Furthermore, after determining that the EEG data is inconsistent with the actual needs of the target person, the method further includes: determining target EEG data from the EEG data based on the change time of the window control needs and / or the change time of the emotional positivity; and determining whether to update the preset EEG error database based on the matching result of the target EEG data and a preset EEG error database. The advantage of this setup is that updating the preset EEG error database ensures the accuracy of determining whether the EEG data is consistent with the actual needs.

[0070] Specifically, if it is determined that the EEG data is inconsistent with the actual needs of the target person, target EEG data can be determined based on the timing of changes in window control needs and / or changes in emotional positivity. For example, EEG data during frequent changes in window control needs can be identified as target EEG data, and / or, EEG data during periods of decreased emotional positivity can be identified as target EEG data. This target EEG data is then matched against a pre-set EEG error database. If no matching EEG data exists in the database, the target EEG data can be added to the database to update the pre-set EEG error database.

[0071] Furthermore, determining whether to update the preset EEG error database based on the matching result between the target EEG data and the preset EEG error database includes: if the matching result is unsuccessful, receiving a window control operation, establishing a second association between the window control operation's associated window control request and the target EEG data, and storing the second association in the preset EEG error database. The advantage of this setup is that by receiving a window control operation, the correct window control request can be obtained. Furthermore, by establishing and storing the second association, when the same target EEG data is collected again, the preset EEG error database can be directly used to determine the window control request, increasing the likelihood that the window control requests in the database match the actual requests.

[0072] Specifically, once it is determined that there is no brainwave in the preset brainwave error database that is identical to the target brainwave data, the window control operation input by the target person can be received, and a second association relationship can be established between the window control operation and the window control request (which is the actual request of the target person) and the target brainwave data. This second association relationship is stored in the preset brainwave error database to update the preset brainwave error database.

[0073] Optionally, the system can also record the number of times the same EEG data in a preset error database is updated, i.e., the number of times the association relationship of the same EEG data changes. If the number exceeds a preset limit, such as three times, the EEG data can be stored in a preset blacklist database, indicating that the window control request based on the EEG data has been incorrectly identified multiple times. Within a preset time period, the system will no longer be able to determine the window control request based on that EEG. This EEG will also be a key research focus for developers to upgrade and optimize the method.

[0074] S208. Continue to control the windows of the current vehicle according to the window control requirements.

[0075] S209. Based on the change time of window control demand in the demand change information and / or the change time of emotional positivity in the emotion change information, determine the target EEG data from the EEG data.

[0076] S210. Determine the target abnormal brainwave that matches the target brainwave data from the abnormal brainwaves.

[0077] Specifically, from the abnormal brainwaves in the preset brainwave error database, brainwaves that match the target brainwave data are selected, and these brainwaves are the target abnormal brainwaves.

[0078] S211. Based on the preset EEG error database, determine the target control requirements associated with the target abnormal EEG, and control the windows of the current vehicle according to the target control requirements.

[0079] The preset EEG error database also includes the correlation between the abnormal EEG and the window control requirements associated with the window control operation.

[0080] Specifically, as mentioned above, the correlation corresponding to the target abnormal brainwave can be selected from multiple correlations stored in the preset brainwave error database. The window control operation associated with the window control operation in this correlation is the target control requirement control. Based on the target control requirement control, the window of the current vehicle can be accurately controlled.

[0081] The car window control method provided in this invention utilizes the corresponding brainwave responses under different weather conditions. Before a person generates brainwaves for window control, the method can control the car window based on the identified weather conditions. Since the target person's emotions and window control needs usually change when their brainwave data is inconsistent with their actual needs, the method can accurately determine whether the target person's brainwave data is consistent with their actual needs based on at least one of the following: emotion change information, need change information, and a pre-determined brainwave error database. When the target person's brainwave data is inconsistent with their actual needs, the method compares the abnormal brainwaves during the abnormal period with the abnormal brainwaves in the pre-determined brainwave error database. Based on the comparison result, the correct window control needs—that is, the window control needs corresponding to the target person's actual window control operation—can be used to control the car window.

[0082] Example 3

[0083] Figure 3 This is a schematic diagram of a window control device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes: a data acquisition module 301, a control requirement determination module 302, and a window control module 303, wherein:

[0084] The data acquisition module is used to collect the electroencephalogram (EEG) data of the target occupants inside the vehicle.

[0085] The control demand determination module is used to determine the emotional information of the target person based on the emotional brainwaves in the brainwave data, and to determine the window control demand of the target person based on the window control brainwaves and / or weather perception brainwaves in the brainwave data, wherein the weather perception brainwaves are the brainwaves generated by the target person after seeing the current weather conditions.

[0086] The window control module is used to control the windows of the current vehicle based on the emotional information and the window control requirements.

[0087] The window control device provided in this invention utilizes the brainwave data of occupants to control windows in different locations. Compared with traditional vehicle window control methods, this improves driving safety. Since emotional fluctuations may occur during window control, inaccurate control can lead to negative emotions. Therefore, the device also accurately determines the emotions of occupants based on brainwave data, further ensuring the accuracy of window control.

[0088] Optionally, the control requirements determination module includes:

[0089] The weather determination unit is used to determine the weather recognition result based on the weather-sensing brainwaves and the first preset brainwave recognition model.

[0090] The target weather determination unit is used to determine a target weather identification result that matches the weather identification result from the sample weather identification results in the preset weather window relationship database, wherein the preset weather window relationship database contains a first association relationship between the sample weather identification result and the preset window control requirements;

[0091] The control requirement determination unit is used to determine the target window control requirement corresponding to the target weather recognition result from the preset window control requirements according to the first association relationship, and to determine the target window control requirement as the window control requirement of the target person.

[0092] Optionally, the preset window control requirements include window opening range requirements. The preset window control requirements associated with different sample weather recognition results are different, and the window opening range requirements are negatively correlated with the severity of the weather corresponding to the sample weather recognition results.

[0093] Optionally, the window control module includes:

[0094] The demand change information determination unit is used to control the windows of the current vehicle according to the window control demand, and in the process of controlling the windows of the current vehicle, determine the emotion change information of the emotion information and the demand change information of the window control demand.

[0095] The demand judgment unit is used to determine whether the brainwave data is consistent with the actual needs of the target person based on at least one of the emotion change information, the demand change information, and a preset brainwave error library, wherein the preset brainwave error library contains abnormal brainwaves that are inconsistent with the actual needs.

[0096] The first control unit is configured to continue controlling the windows of the current vehicle according to the window control requirements if the information returned by the demand judgment unit is consistent.

[0097] Optionally, determining whether the brainwave data is consistent with the actual needs of the target person based on at least one of the emotion change information, the demand change information, and a preset brainwave error database includes: if the emotional positivity in the emotion change information is declining within a first preset time period, and / or the frequency of changes in the window control demand in the demand change information is greater than a preset number, then it is determined that the brainwave data is inconsistent with the actual needs of the target person.

[0098] Furthermore, after determining that the EEG data is inconsistent with the actual needs of the target person, the method further includes: determining target EEG data from the EEG data based on the change time of the window control needs and / or the change time of the emotional positivity, and determining whether to update the preset EEG error database based on the matching result of the target EEG data and the preset EEG error database.

[0099] Furthermore, determining whether to update the preset EEG error database based on the matching result of the target EEG data and the preset EEG error database includes: if the matching result is unsuccessful, receiving a window control operation, establishing a second association between the window control operation and the target EEG data, and storing the second association in the preset EEG error database.

[0100] Optionally, the window control module also includes:

[0101] The target data determination unit is used to determine the target brainwave data from the brainwave data after determining whether the brainwave data is consistent with the actual needs of the target person. If the information returned by the demand judgment unit is inconsistent, the target brainwave data is determined based on the change time of the window control demand in the demand change information and / or the change time of the positive emotion in the emotion change information.

[0102] An abnormal brainwave determination unit is used to determine, from the abnormal brainwaves, a target abnormal brainwave that matches the target brainwave data;

[0103] The second control unit is used to determine the target control requirements associated with the target abnormal brainwave based on the preset brainwave error database, and to control the windows of the current vehicle based on the target control requirements. The preset brainwave error database also includes the association relationship between the abnormal brainwave and the window control requirements associated with the window control operation.

[0104] The window control device provided in the embodiments of the present invention can execute the window control method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0105] Example 4

[0106] Figure 4 A schematic diagram of a vehicle 40 that can be used to implement embodiments of the present invention is shown. The vehicle may include at least one electroencephalogram (EEG) data acquisition device, at least one processor, and a memory communicatively connected to the at least one processor. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0107] like Figure 4 As shown, the vehicle 40 includes at least one processor 41, a memory 42 communicatively connected to the at least one processor 41, and an electroencephalogram (EEG) data acquisition device 43. The memory 42 can be a read-only memory (ROM), random access memory (RAM), etc., wherein the memory stores computer programs executable by at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer programs stored in the read-only memory (ROM) or loaded from memory units into the random access memory (RAM). The RAM can also store various programs and data required for operation. The processor 41, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0108] Multiple components in vehicle 40 are connected to I / O interfaces, including: input units such as keyboards and mice; output units such as various types of displays and speakers; storage units such as disks and optical discs; and communication units such as network interface cards, modems, and wireless transceivers. The communication units allow vehicle 40 to exchange information / data with other devices via computer networks such as the Internet and / or various telecommunications networks.

[0109] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as the window control method.

[0110] In some embodiments, the window control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on the vehicle 40 via ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the processor 41, one or more steps of the window control method described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to perform the window control method by any other suitable means (e.g., by means of firmware).

[0111] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0112] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0113] The computer equipment provided above can be used to execute the window control method provided in any of the above embodiments, and has the corresponding functions and beneficial effects.

[0114] Example 5

[0115] In the context of this invention, the computer-readable storage medium may be a tangible medium, and the computer-executable instructions, when executed by a computer processor, are used to perform a window control method, the method comprising:

[0116] Collect brainwave data of the target occupants currently inside the vehicle;

[0117] The emotional information of the target person is determined based on the emotional brainwaves in the brainwave data, and the window control needs of the target person are determined based on the window control brainwaves and / or weather perception brainwaves in the brainwave data, wherein the weather perception brainwaves are the brainwaves generated by the target person after seeing the current weather conditions.

[0118] Based on the emotional information and the window control requirements, control the windows of the current vehicle.

[0119] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by, or in conjunction with, an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0120] The computer equipment provided above can be used to execute the window control method provided in any of the above embodiments, and has the corresponding functions and beneficial effects.

[0121] It is worth noting that in the above embodiments of the window control device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0122] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for controlling vehicle windows, characterized in that, include: Collect brainwave data of the target occupants currently inside the vehicle; The emotional information of the target person is determined based on the emotional brainwaves in the brainwave data, and the window control needs of the target person are determined based on the window control brainwaves and / or weather perception brainwaves in the brainwave data, wherein the weather perception brainwaves are the brainwaves generated by the target person after seeing the current weather conditions. Based on the emotional information and the window control requirements, control the windows of the current vehicle; The step of controlling the windows of the current vehicle based on the emotion information and the window control requirements includes: Control the windows of the current vehicle according to the window control requirements, and determine the emotional change information of the emotional information and the change information of the window control requirements during the process of controlling the windows of the current vehicle. Based on at least one of the emotional change information, the demand change information, and a preset EEG error database, determine whether the EEG data is consistent with the actual demand of the target person, wherein the preset EEG error database contains abnormal EEGs that are inconsistent with the actual demand; If they match, then continue to control the windows of the current vehicle according to the window control requirements.

2. The method according to claim 1, characterized in that, The step of determining the target person's window control needs based on weather-sensing brainwaves in the brainwave data includes: The weather recognition result is determined based on the weather-sensing brainwaves and the first preset brainwave recognition model; From the sample weather recognition results in the preset weather window relationship database, a target weather recognition result that matches the weather recognition result is determined, wherein the preset weather window relationship database contains a first association between the sample weather recognition result and the preset window control requirements; Based on the first association relationship, the target window control requirement corresponding to the target weather recognition result is determined from the preset window control requirements, and the target window control requirement is determined as the window control requirement of the target person.

3. The method according to claim 2, characterized in that, The preset window control requirements include window opening range requirements. Different preset window control requirements are associated with different sample weather recognition results. The window opening range requirements are negatively correlated with the severity of the weather corresponding to the sample weather recognition results.

4. The method according to claim 1, characterized in that, The step of determining whether the brainwave data matches the actual needs of the target person based on at least one of the emotional change information, the demand change information, and a preset brainwave error database includes: If, within a first preset time period, the positive emotional level in the emotional change information is on a downward trend, and / or the frequency of changes in the window control demand in the demand change information is greater than a preset number, then it is determined that the EEG data is inconsistent with the actual needs of the target person. The process, after determining that the EEG data does not match the actual needs of the target individual, further includes: Based on the change time of the window control demand and / or the change time of the emotional positivity, target EEG data is determined from the EEG data, and based on the matching result of the target EEG data with the preset EEG error database, it is determined whether to update the preset EEG error database.

5. The method according to claim 4, characterized in that, The step of determining whether to update the preset brainwave error database based on the matching result between the target brainwave data and the preset brainwave error database includes: If the matching result is unsuccessful, the window control operation is received, and a second association relationship is established between the window control operation and the target EEG data, and the second association relationship is stored in the preset EEG error database.

6. The method according to claim 1, characterized in that, After determining whether the EEG data matches the actual needs of the target person, the process further includes: If they are inconsistent, the target EEG data is determined from the EEG data based on the change time of the window control demand in the change demand information and / or the change time of the positive emotion in the change emotion information. Identify the target abnormal brainwave from the abnormal brainwaves that matches the target brainwave data; Based on the preset EEG error database, the target control requirements associated with the target abnormal EEG are determined, and the windows of the current vehicle are controlled according to the target control requirements. The preset EEG error database also contains the association between the abnormal EEG and the window control requirements associated with the window control operation.

7. A vehicle window control device, characterized in that, include: The data acquisition module is used to collect the electroencephalogram (EEG) data of the target occupants inside the vehicle. The control demand determination module is used to determine the emotional information of the target person based on the emotional brainwaves in the brainwave data, and to determine the window control demand of the target person based on the window control brainwaves and / or weather perception brainwaves in the brainwave data, wherein the weather perception brainwaves are the brainwaves generated by the target person after seeing the current weather conditions. A window control module is used to control the windows of the current vehicle based on the emotional information and the window control requirements. The window control module includes: The demand change information determination unit is used to control the windows of the current vehicle according to the window control demand, and in the process of controlling the windows of the current vehicle, determine the emotion change information of the emotion information and the demand change information of the window control demand. The demand judgment unit is used to determine whether the brainwave data is consistent with the actual needs of the target person based on at least one of the emotion change information, the demand change information, and a preset brainwave error library, wherein the preset brainwave error library contains abnormal brainwaves that are inconsistent with the actual needs. The first control unit is configured to continue controlling the windows of the current vehicle according to the window control requirements if the information returned by the demand judgment unit is consistent.

8. A vehicle, characterized in that, The vehicles include: At least one brainwave data acquisition device, at least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the window control method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the window control method according to any one of claims 1-6.

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