Seat posture adjustment methods, devices, vehicles, and computer-readable storage media

Abstract

This application provides a seat posture adjustment method, device, vehicle, and storage medium, relating to the field of vehicle technology. The method includes: acquiring an image of a driver seat; recommending a first driver seat posture adapted to the driver's body shape based on the image; acquiring the driver seat posture resulting from manual adjustment to obtain at least one second driver seat posture; fusing the first driver seat posture and the at least one second driver seat posture to obtain a target driver seat posture; and adjusting the current driver seat posture to the target driver seat posture. This application, based on the real-time state of the driver sitting in the driver seat, uses the driver's body shape and the driver's habit of manually adjusting the driver seat as the basis for adjusting the driver seat posture, achieving automatic adjustment of the driver seat posture. This makes the adjusted driver seat posture more suitable for the driver's seat adjustment needs, improving the driver's driving experience.

Description

Technical Field

[0001] This application relates to the field of vehicles, and more specifically, to a seat posture adjustment method, apparatus, vehicle, and computer-readable storage medium in the field of vehicles. Background Technology

[0002] With social progress and the development of science and technology, the automotive industry has risen rapidly, and the penetration rate of vehicles is increasing. Vehicle seats are the parts that people have the most contact with in a car, and they play a crucial role in the driving and riding experience.

[0003] Traditionally, vehicle seats are adjusted manually by the user. However, manually adjusting the driver's seat is a cumbersome process, resulting in a poor driving experience. Summary of the Invention

[0004] This application provides a seat posture adjustment method, device, vehicle, and computer-readable storage medium, which can adjust the driver's seat posture based on the driver's real-time state while sitting in the driver's seat, taking the driver's body shape and the driver's habit of manually adjusting the driver's seat as the basis for adjusting the driver's seat posture. On the basis of realizing automatic adjustment of the driver's seat posture, the adjusted driver's seat posture is more in line with the driver's seat adjustment needs, which is conducive to improving the driver's driving experience.

[0005] The driver's seat posture is automatically adjusted based on the driver's body size and the driver's seat posture data after manual adjustment, improving the driver's comfort and enhancing the driving experience.

[0006] In a first aspect, a seat posture adjustment method is provided, the method comprising: acquiring an image of a driver in a driver's seat; recommending a first driver's seat posture adapted to the driver's body shape based on the image; acquiring a driver's seat posture generated after the driver's seat is manually adjusted to obtain at least one second driver's seat posture; fusing the first driver's seat posture and the at least one second driver's seat posture to obtain a target driver's seat posture; and adjusting the current driver's seat posture to the target driver's seat posture.

[0007] In the embodiments of this application, a technical solution is implemented that automatically adjusts the driver's seat posture based on the real-time state of the driver sitting in the driver's seat, without requiring manual adjustment. This solution involves acquiring an image of the driver in the driver's seat, recommending a first driver's seat posture adapted to the driver's body type based on the image, acquiring the driver's seat posture after manual adjustment, obtaining at least one second driver's seat posture, fusing the first and at least one second driver's seat posture to obtain a target driver's seat posture, and adjusting the current driver's seat posture to the target posture. Since the first driver's seat posture is recommended based on the driver's body type and is associated with it, and the acquired second driver's seat postures are all generated by previous users manually adjusting the driver's seat according to their habits, the second driver's seat posture reflects the driver's seat adjustment habits. Adjusting the current driver's seat posture to the target driver's seat posture, while taking the driver's body type as the adjustment basis, also considers the user's habit of manually adjusting the driver's seat, making the adjusted driver's seat posture more in line with the driver's seat adjustment needs and improving the driver's driving experience.

[0008] In conjunction with the first aspect, in some possible implementations, recommending a first driver's seat posture adapted to the driver's body shape based on the image includes: obtaining the driver's facial information based on the image; determining whether there is preset facial information in a preset information database that matches the facial information; if so, recommending a first driver's seat posture adapted to the driver's body shape based on the image.

[0009] In combination with the first aspect and the above implementation methods, in some possible implementation methods, determining whether there is preset facial information in the preset information database that matches the facial information includes: determining the similarity between the facial information and each preset facial information in the preset information database to obtain multiple similarities; determining whether there is a similarity greater than a similarity threshold among the multiple similarities, so as to determine whether there is preset facial information in the preset information database that matches the facial information.

[0010] In combination with the first aspect and the above implementation methods, in some possible implementation methods, recommending a first driver's seat posture adapted to the driver's body shape based on the image includes: inputting the image into a pre-trained seat posture recommendation model, extracting the driver's body shape features from the image by the seat posture recommendation model, and outputting multiple candidate seat postures corresponding to the body shape features and probability values ​​corresponding to the multiple candidate seat postures; determining the maximum probability value among the probability values ​​corresponding to the multiple candidate seat postures; and determining the candidate seat posture corresponding to the maximum probability value among the multiple candidate seat postures as the first driver's seat posture.

[0011] In the embodiments of this application, the recommendation of the first driver's seat posture is achieved through models and images, which helps to improve the efficiency and accuracy of driver's seat posture recommendation. Furthermore, this first driver's seat posture is recommended based on the user's body characteristics, conforming to the user's body shape. Using the first driver's seat posture as the basis for adjusting the driver's seat makes the user more comfortable in the driver's seat, thereby improving the user experience.

[0012] In combination with the first aspect and the above implementation methods, in some possible implementation methods, obtaining the driver seat posture generated after the driver seat is manually adjusted to obtain at least one second driver seat posture includes: if there is preset facial information matching the facial information in the preset information database, obtaining the driver seat posture after the driver has previously adjusted the driver seat to obtain the at least one second driver seat posture; wherein, the seat posture includes the distance between the driver seat cushion and the vehicle floor, the distance between the driver seat cushion and the brake pedal, and the angle between the driver seat cushion and the backrest.

[0013] In the embodiments of this application, when there is preset facial information matching the facial information in the preset information database, the driver's previous driver seat posture after adjusting the driver's seat is obtained to obtain at least one second driver seat posture. The obtained second driver seat posture can accurately reflect the driver's adjustment habits of the driver's seat.

[0014] In combination with the first aspect and the above implementation methods, in some possible implementation methods, the step of fusing the first driver's seat posture and the at least one second driver's seat posture to obtain the target driver's seat posture includes: setting weight values ​​for the first driver's seat posture and the at least one second driver's seat posture respectively, and performing a weighted calculation on the first driver's seat posture and the at least one second driver's seat posture according to the weight values ​​to obtain the target driver's seat posture.

[0015] In the embodiments of this application, the target driver's seat posture is obtained by setting weights for the first driver's seat posture and at least one second driver's seat posture and then fusing them, so that the result of obtaining the target driver's seat posture better combines the first driver's seat posture and the second driver's seat posture.

[0016] In conjunction with the first aspect and the above implementation methods, in some possible implementation methods, setting weight values ​​for the first driver's seat posture and the at least one second driver's seat posture respectively includes: determining the weight value of the first driver's seat posture based on the number of first driver's seat postures, the number of times n the driver's seat is adjusted corresponding to the at least one second driver's seat posture, and the natural constant e; determining the weight value of the driver's seat posture MCI generated by the i-th manual adjustment of the driver's seat based on the weight value of the first driver's seat posture and the number of adjustments n; where n is a positive integer, i = 1, 2, 3, ..., n, and MCI belongs to the at least one second driver's seat posture.

[0017] In the embodiments of this application, weights are set for the first driver's seat posture and at least one second driver's seat posture using an exponential function model. The first driver's seat posture is recommended based on the user's body type, and the second driver's seat posture is obtained based on data after manual adjustment by the user, representing the driver's personal habits. Therefore, by setting weights for the first and second driver's seat postures using an exponential function model, the user's body type and the driver's personal habits are taken into account, thereby improving the driver's comfort while sitting in the seat and enhancing the user experience.

[0018] Secondly, a vehicle control device is provided, the device comprising:

[0019] The first acquisition module is used to acquire an image of the driver in the driver's seat;

[0020] The recommendation module is used to recommend a first driver's seat posture that is adapted to the driver's body type based on the image;

[0021] The second acquisition module is used to acquire the driver seat posture after the driver seat is manually adjusted, and to obtain at least one second driver seat posture.

[0022] The third acquisition module is used to fuse the first driver's seat posture and the at least one second driver's seat posture to obtain the target driver's seat posture;

[0023] An adjustment module is used to adjust the current driver's seat posture to the target driver's seat posture.

[0024] In conjunction with the second aspect, in some implementations of the second aspect, the recommendation module includes:

[0025] An information acquisition unit is used to acquire the driver's facial information based on the image;

[0026] An information matching unit is used to determine whether there is preset facial information in a preset information database that matches the facial information;

[0027] A posture recommendation unit is used to recommend a first driver's seat posture that is adapted to the driver's body type based on the image if the condition is met.

[0028] In combination with the second aspect and the above implementation methods, in some implementation methods of the second aspect, the information matching unit is used to determine the similarity between the facial information and each preset facial information in the preset information database to obtain multiple similarities; and to determine whether there is a similarity greater than a similarity threshold among the multiple similarities, so as to determine whether there is preset facial information in the preset information database that matches the facial information.

[0029] In conjunction with the second aspect and the above implementation methods, in some implementation methods of the second aspect, the posture recommendation unit is used to input the image into a pre-trained seat posture recommendation model, the seat posture recommendation model extracts the driver's body shape features from the image, and outputs multiple candidate seat postures corresponding to the body shape features and probability values ​​corresponding to the multiple candidate seat postures; determines the maximum probability value among the probability values ​​corresponding to the multiple candidate seat postures; and determines the candidate seat posture corresponding to the maximum probability value among the multiple candidate seat postures as the first driver's seat posture.

[0030] In conjunction with the second aspect and the above implementation methods, in some implementation methods of the second aspect, the second acquisition module is specifically used to: when there is preset facial information matching the facial information in the preset information database, acquire the driver's previous driver seat posture after adjusting the driver's seat, and obtain the at least one second driver seat posture; wherein, the seat posture includes the distance between the driver's seat cushion and the vehicle floor, the distance between the driver's seat cushion and the brake pedal, and the angle between the driver's seat cushion and the backrest.

[0031] In conjunction with the second aspect and the above implementation methods, in some implementation methods of the second aspect, the third acquisition module is specifically used to: set weight values ​​for the first driver's seat posture and the at least one second driver's seat posture respectively, and perform a weighted calculation on the first driver's seat posture and the at least one second driver's seat posture according to the weight values ​​to obtain the target driver's seat posture.

[0032] In conjunction with the second aspect and the above implementation methods, in some implementation methods of the second aspect, the third acquisition module is specifically used to: determine the weight value of the first driver's seat posture based on the number of first driver's seat postures, the number of times n the driver's seat is adjusted corresponding to the at least one second driver's seat posture, and the natural constant e; determine the weight value of the driver's seat posture MCI generated by the i-th manual adjustment of the driver's seat based on the weight value of the first driver's seat posture and the number of adjustments n; where n is a positive integer, i = 1, 2, 3, ..., n, and MCI belongs to the at least one second driver's seat posture.

[0033] Thirdly, a vehicle is provided, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, causing the vehicle to perform the methods of the first aspect or any possible implementation thereof.

[0034] Fourthly, a computer program product is provided, comprising: computer program code, which, when run on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof.

[0035] Fifthly, a computer-readable storage medium is provided that stores computer program code, which, when executed on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof. Attached Figure Description

[0036] Figure 1 A schematic diagram of a scenario illustrating a seat posture adjustment method provided in an embodiment of this application is shown;

[0037] Figure 2 A schematic flowchart of a seat posture adjustment method provided in an embodiment of this application is shown;

[0038] Figure 3 A schematic diagram of a driver facial recognition process provided in an embodiment of this application is shown;

[0039] Figure 4 A schematic diagram of the structure of the seat posture recommendation model provided in an embodiment of this application is shown;

[0040] Figure 5 This paper shows a schematic diagram of the structure of a seat posture adjustment device provided in an embodiment of this application;

[0041] Figure 6A schematic diagram of the structure of a vehicle provided in an embodiment of this application is shown. Detailed Implementation

[0042] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0043] In the following text, the terms "first" and "theoretical" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined with "first" or "theoretical" may explicitly or implicitly include one or more of that feature.

[0044] like Figure 1 As shown, Figure 1 This illustration shows a scenario diagram of a seat posture adjustment method provided in an embodiment of this application. The scenario includes a vehicle 100. When a user drives the vehicle 100, on the one hand, the traditional method of adjusting the seat posture mainly involves manual adjustment by the user. However, the process of manually adjusting the driver's seat is cumbersome, resulting in a poor driving experience. On the other hand, to compensate for the shortcomings of manual driver's seat adjustment, automatic seat posture adjustment technology has emerged. Currently, automatic seat posture adjustment technology mainly associates different heights and weights with corresponding seat postures in advance. Users need to set the seat posture in advance through a one-click setting method. For example, after the user inputs their height and weight, the vehicle calculates the corresponding seat posture based on the input height and weight. After the user sets the desired seat posture, the vehicle stores the user's set seat posture. When the user uses the pre-set seat posture later, they need to manually trigger the intelligent seat adjustment button on the vehicle's in-vehicle terminal, and the vehicle will adjust the seat to the user's set seat posture. Although this solution achieves automatic seat adjustment, once the seat posture is adjusted, it remains fixed and is permanently used. It cannot adjust the seat in real time according to the user's real-time status, thus reducing the user's driving experience.

[0045] To address the aforementioned issues, this application proposes a seat posture adjustment method, device, vehicle, and computer-readable storage medium that can automatically adjust the driver's seat posture based on the driver's body type and the posture data of the driver's seat after manual adjustment, thereby improving the driver's comfort and enhancing the driving experience.

[0046] The following is an exemplary embodiment of a seat posture adjustment method provided in this application.

[0047] like Figure 2 As shown, Figure 2 The diagram illustrates a flowchart of a seat posture adjustment method provided in an embodiment of this application. The method includes the following steps:

[0048] S210, acquire an image of the driver in the driver's seat.

[0049] In an exemplary embodiment, the image of the driver in the driver's seat refers to an image captured in real time by a camera showing the driver sitting in the driver's seat, or an image of the driver after entering the vehicle but not yet seated in the driver's seat, wherein the image includes full-body image information of the driver. After acquiring the image of the driver in the driver's seat and determining that the driver is seated in the driver's seat, S210 is executed. The driver depicted in the image is referred to as the current driver, i.e., the user currently driving the vehicle.

[0050] S220, based on the image, recommend a first driver's seat posture that is adapted to the driver's body type.

[0051] The image can identify the current driver's body shape, including height and weight, and recommend a driving seat posture that is suitable for the current driver's body shape, resulting in the first driving seat posture. That is, the first driving seat posture is associated with the current driver's body shape, and using the first driving seat posture as data for driving seat adjustment is more accurate and convincing.

[0052] S230, obtain the driver's seat posture after the driver's seat is manually adjusted, so as to obtain at least one second driver's seat posture.

[0053] The driver's seat being manually adjusted can be understood as the vehicle's driver's seat being manually adjusted by the same driver or by multiple different drivers in the past. Regardless of which driver manually adjusted the driver's seat, a driver's seat posture will be generated, and the data of the resulting driver's seat posture after manual adjustment will be stored in a posture database for future use. For ease of distinction, drivers who have previously adjusted the driver's seat are referred to as historical drivers, which may include the current driver.

[0054] The driver's seat posture is obtained from the posture database after the driver's seat is manually adjusted, so as to obtain at least one second driver's seat posture. Since the obtained second driver's seat postures are all generated by the previous drivers who manually adjusted the driver's seat according to their own habits, the obtained second driver's seat postures can reflect the seat adjustment habits of the previous drivers. If the obtained second driver's seat postures include the driver's seat postures generated by the current driver's previous adjustments of the driver's seat, then the current driver's seat adjustment habits can be accurately reflected.

[0055] S240, the first driver's seat posture and the at least one second driver's seat posture are fused to obtain the target driver's seat posture.

[0056] After obtaining the first driver's seat posture and at least one second driver's seat posture, the first driver's seat posture and at least one second driver's seat posture are fused to obtain the target driver's seat posture. The target driver's seat posture represents the optimal seating position for the current driver's seat adjustment needs. When the driver's seat is in the target driver's seat posture, it is considered that the current driver is sitting in the most comfortable position. Since the first driver's seat posture is recommended based on the driver's body shape, and the second driver's seat posture is obtained by manually adjusting the driver's seat, the obtained target driver's seat posture combines the current driver's body shape and personal seat adjustment habits. Using the target driver's seat posture as the adjustment target for the driver's seat is more in line with the current driver's seat adjustment needs.

[0057] S250, adjust the current driver's seat posture to the target driver's seat posture.

[0058] After obtaining the target driver's seat posture, the current driver's seat posture is adjusted to the target driver's seat posture. The aforementioned current driver's seat posture, first driver's seat posture, second driver's seat posture, and target driver's seat posture all include the distance D1 between the driver's seat cushion and the vehicle floor, the distance D2 between the driver's seat cushion and the brake pedal, and the angle B between the driver's seat cushion and the backrest. For example, in the current driver's seat posture, D1 = X1, D2 = Y1, and B = Z1; in the target driver's seat posture, D1 = X2, D2 = Y2, and B = Z2. Adjusting the current driver's seat posture to the target driver's seat posture means adjusting X1 to X2, Y1 to Y2, and Z1 to Z2. This automatic adjustment of the driver's seat posture takes into account both the current driver's body type and their habit of manually adjusting the driver's seat, making the adjusted driver's seat posture more suitable for the current driver's seat adjustment needs and improving the current driver's driving experience. Since the above images are captured in real time, the current state of the driver can be obtained from the images. Based on the real-time captured images and the driver's seat being manually adjusted, the driver's seat posture can be adjusted in real time.

[0059] The technical solution provided in this application involves acquiring an image of the driver in the driver's seat, recommending a first driver's seat posture adapted to the driver's body shape based on the image, acquiring the driver's seat posture after manual adjustment to obtain at least one second driver's seat posture, fusing the first and at least one second driver's seat posture to obtain a target driver's seat posture, and adjusting the current driver's seat posture to the target driver's seat posture. This technical solution achieves automatic adjustment of the driver's seat posture based on the real-time state of the driver sitting in the driver's seat, without the need for manual adjustment. Since the first driver's seat posture is obtained through recommendations based on the driver's body shape and is associated with the driver's body shape, and the acquired second driver's seat postures are all generated by the current driver manually adjusting the driver's seat according to their own habits, the second driver's seat posture can reflect the current driver's seat adjustment habits. Adjusting the current driver's seat posture to the target driver's seat posture, while taking the current driver's body shape as the adjustment basis, also considers the current driver's habit of manually adjusting the driver's seat, making the adjusted driver's seat posture more in line with the current driver's seat adjustment needs, which is beneficial to improving the current driver's driving experience.

[0060] In one possible implementation, the step of recommending a first driver's seat posture adapted to the driver's body type based on the image includes the following:

[0061] The driver's facial information is obtained from the image;

[0062] Determine whether there is any preset facial information in the preset information database that matches the facial information;

[0063] If so, a first driver's seat posture adapted to the driver's body type is recommended based on the image.

[0064] The driver's facial information is obtained by extracting features from the acquired image, thereby obtaining the driver's facial features, which represent the driver's facial information. Feature extraction from the acquired image is mainly performed using histogram of oriented gradients (HOG). Other feature extraction methods can also be used, and this application does not limit the specific methods used.

[0065] The preset information database includes facial information of all historical drivers who have previously driven the vehicle. After obtaining the driver's facial information, it is determined whether a preset facial information matching the facial information exists in the preset information database. The purpose of determining whether a preset facial information matching the facial information exists in the preset information database is to determine whether the current driver has driven the vehicle before. If a preset facial information matching the facial information exists in the preset information database, it means that the current driver has driven the vehicle before. Since the current driver has driven the vehicle before, they will adjust the driver's seat. The posture database stores data on the driver's seat posture resulting from the current driver manually adjusting the driver's seat. Therefore, a driver's seat posture representing the current driver's seat adjustment habits can be obtained, and then the step of recommending a first driver's seat posture adapted to the driver's body shape based on the image can be executed. If a preset facial information matching the facial information does not exist in the preset information database, it means that the current driver has not driven the vehicle before. That is, the posture database does not store data on the driver's seat posture resulting from the current driver manually adjusting the driver's seat. Therefore, a driver's seat posture representing the current driver's seat adjustment habits cannot be obtained, and the seat posture adjustment method ends.

[0066] like Figure 3 As shown, Figure 3 This illustration shows a flowchart of a driver facial recognition process provided in an embodiment of this application. In one possible implementation, determining whether there is preset facial information in the preset information database that matches the facial information includes the following scheme:

[0067] S310: Determine the similarity between the facial information and each preset facial information in the preset information database to obtain multiple similarities;

[0068] S320: Determine whether any of the multiple similarities has a similarity greater than a similarity threshold, in order to determine whether there is any preset facial information in the preset information database that matches the facial information; if any of the multiple similarities has a similarity greater than the similarity threshold, it means that there is preset facial information in the preset information database that matches the facial information, i.e., the facial information matching is successful; if none of the multiple similarities has a similarity greater than the similarity threshold, it means that there is no preset facial information in the preset information database that matches the facial information, i.e., the facial information matching fails.

[0069] After obtaining facial information, the similarity between this facial information and various preset facial information in a preset information database is calculated, resulting in multiple similarity scores. The database is then checked to determine if any of these similarity scores exceeds a similarity threshold. Specifically, if any of the multiple similarity scores exceeds the threshold, it indicates that a matching preset facial information exists in the database, meaning the current driver has previously driven and frequently drives this vehicle. Conversely, if none of the multiple similarity scores exceed the threshold, it indicates that no matching preset facial information exists in the database, meaning the current driver has not previously driven this vehicle. For example, if multiple similarity scores are obtained as 80%, 10%, 5%, 4%, and 1%, and the set similarity threshold is 75%, then 80% is considered greater than 75%, meaning the preset facial information with a similarity score of 80% matches the obtained facial information. By using similarity matching, it can determine whether there are preset facial information in the preset information database that match the facial information, making the judgment results more accurate.

[0070] In one possible implementation, the step of recommending a first driver's seat posture adapted to the driver's body type based on the image includes the following:

[0071] The image is input into a pre-trained seat posture recommendation model, which extracts the driver's body shape features from the image and outputs multiple candidate seat postures corresponding to the body shape features and the probability values ​​corresponding to the multiple candidate seat postures.

[0072] Determine the maximum probability value among the probability values ​​corresponding to the multiple candidate seat postures;

[0073] The candidate seat posture corresponding to the highest probability value among the multiple candidate seat postures is determined as the first driver seat posture.

[0074] The seat posture recommendation model employs a deep neural network algorithm, but other neural network algorithms can also be used for training; this application does not limit the specific algorithms used. The seat posture recommendation model is pre-trained and includes multiple network layers, namely L1, L2, ... Ln. The training process of the seat posture recommendation model is as follows: A large number of sample images, including the user's entire body, are prepared. Each sample image provides the current driver's body shape features, namely height and weight. Then, the corresponding seat posture is labeled for each sample image. All sample images are then divided into training and validation sets. The seat posture recommendation model is iteratively trained using the training and validation sets until the model converges, at which point training stops. The input to the seat posture recommendation model is an image, and the output consists of multiple driver seat postures carrying probability values. The final output is the driver seat posture with the highest probability value, which is used as the final model output result.

[0075] like Figure 4 As shown, Figure 4 This illustration shows a schematic diagram of the seat posture recommendation model provided in this application embodiment. The input 410 of the seat posture recommendation model 430 is the image of the driver in the driver's seat, i.e., the current driver's position in the driver's seat, and the output 420 is the first driver's seat posture. Specifically, the image of the current driver in the driver's seat is input into the seat posture recommendation model. The model extracts the driver's body shape features from the image, calculates multiple seat postures matching these features, referred to as multiple candidate seat postures, and outputs the multiple candidate seat postures and their corresponding probability values. The candidate seat posture with the highest probability value is then determined as the first driver's seat posture and used as the final output. For example, if the multiple candidate seat postures are posture 1, posture 2, and posture 3, and the probability value corresponding to posture 3 is the maximum among the probability values ​​of posture 1, posture 2, and posture 3, then posture 3 is the first driver's seat posture.

[0076] The recommendation of the first driver's seat posture was achieved through models and images, which improves the efficiency and accuracy of driver's seat posture recommendations. Furthermore, this first driver's seat posture is recommended based on the current driver's body shape characteristics, conforming to the user's body features. Using this first driver's seat posture as the basis for adjusting the driver's seat makes the current driver more comfortable, thereby improving the driving experience.

[0077] In one possible implementation, obtaining the driver's seat posture after the driver's seat has been manually adjusted, in order to obtain at least one second driver's seat posture, includes the following scheme:

[0078] If there is preset facial information in the preset information database that matches the facial information, the driver's previous driver seat posture after adjusting the driver seat is obtained to obtain the at least one second driver seat posture.

[0079] After confirming that the current driver has driven the vehicle, the posture database stores data on the driver's seat postures after previous adjustments. Therefore, this data can be retrieved from the posture database. Furthermore, if a preset facial information matching the facial information exists in the preset information database, the driver's seat postures after previous adjustments are obtained, resulting in at least one second driver's seat posture. This second driver's seat posture accurately reflects the current driver's seat adjustment habits. The driver's seat postures stored in the posture database include: the distance between the driver's seat cushion and the vehicle floor, the distance between the driver's seat cushion and the brake pedal, and the angle between the driver's seat cushion and the backrest.

[0080] In one possible implementation, fusing the first driver's seat posture and the at least one second driver's seat posture to obtain the target driver's seat posture includes the following scheme:

[0081] Weight values ​​are set for the first driver's seat posture and the at least one second driver's seat posture, and a weighted calculation is performed on the first driver's seat posture and the at least one second driver's seat posture according to the weight values ​​to obtain the target driver's seat posture.

[0082] When acquiring at least one second driver's seat posture, it is necessary not only to record the second driver's seat posture but also the time when each second driver's seat posture was adjusted. The closer to the current time, the lower the weight assigned to the corresponding second driver's seat posture. For example, if the current time is October 7th, and the driver's seat posture was manually adjusted 3 times, at 9:00 AM on October 1st, 5:00 PM on October 1st, and 12:00 PM on October 3rd, the weight assigned to the second driver's seat posture at 9:00 AM on October 1st is 0.47, the weight assigned to the second driver's seat posture at 5:00 PM on October 1st is 0.29, and the weight assigned to the second driver's seat posture at 12:00 PM on October 3rd is 0.24.

[0083] By assigning weight values ​​to the first driver's seat posture and at least one second driver's seat posture, the weight values ​​for the first driver's seat posture and at least one second driver's seat posture are different. When there are multiple second driver's seat postures, each second driver's seat posture corresponds to a time point, and the weight value of the second driver's seat posture is smaller the closer the time point is to the current time point. For example, if the multiple second driver's seat postures are posture A, posture B, and posture C, and the time points of posture A, posture B, and posture C are ordered in chronological order as posture A, posture B, and posture C, then the weight value of posture A > the weight value of posture B > the weight value of posture C. After setting weight values ​​for the first driver's seat posture and at least one second driver's seat posture, a weighted calculation is performed on the first driver's seat posture and at least one second driver's seat posture according to the weight values ​​to obtain the target driver's seat posture. This achieves the fusion of the first driver's seat posture and at least one second driver's seat posture, that is, the driver's seat posture related to the current driver's body shape and the driver's seat adjustment habit are merged. When the target driver's seat posture is used as the target adjustment basis for the driver's seat, the adjusted driver's seat posture can better meet the current driver's seat adjustment needs, which is conducive to improving the current driver's driving experience.

[0084] In one possible implementation, setting weight values ​​for the first driver's seat posture and the at least one second driver's seat posture includes the following scheme:

[0085] The weight value of the first driver seat posture is determined based on the number of first driver seat postures, the number of times n the driver seat is adjusted corresponding to the at least one second driver seat posture, and the natural constant e.

[0086] Based on the weight value of the first driver's seat posture and the number of adjustments n, determine the driver's seat posture MC resulting from the i-th manual adjustment of the driver's seat. i The weight values; where n is a positive integer, i = 1, 2, 3, ..., n, MC i It belongs to the posture of at least one second driver's seat.

[0087] Specifically, the first driver's seat posture and the at least one second driver's seat posture are input into a preset exponential function model. The preset exponential function model assigns weight values ​​to the first driver's seat posture and the at least one second driver's seat posture, respectively. A weighted calculation is performed on the first driver's seat posture and the at least one second driver's seat posture based on these weight values ​​to obtain the target driver's seat posture. The preset exponential function model is as follows:

[0088]

[0089]

[0090] Where n represents the number of times the driver's seat is adjusted, RC represents the first driver's seat posture, and MC... i MC represents the driver's seat posture resulting from the i-th manual adjustment of the driver's seat. i This refers to the second driver's seat posture, which includes the MC (Mean Driver's Seat) position. i C represents the target driver's seat posture, i represents the total number of times the driver's seat posture is manually adjusted, i = 1, 2, 3, ..., n, and b is a parameter less than a preset value, such as b < -2. The weight values ​​of the first and second driver's seat postures can be adjusted by adjusting b.

[0091] By using a preset exponential function model, the fusion of the first driver's seat posture and at least one second driver's seat posture is achieved, which improves the efficiency of generating the target driver's seat posture. Furthermore, by calculating the target driver's seat posture using the preset exponential function model, the seat posture is made to continuously approach the ideal seat posture of the driver of the current vehicle, making the adjustment of the vehicle driver's seat posture more intelligent and conducive to improving the driving experience.

[0092] like Figure 5 As shown, Figure 5 This illustration shows a structural schematic diagram of a seat posture adjustment device 500 provided in an embodiment of this application. The seat posture adjustment device 500 includes:

[0093] The first acquisition module 510 is used to acquire an image of the driver in the driver's seat;

[0094] Recommendation module 520 is used to recommend a first driver's seat posture that is adapted to the driver's body shape based on the image;

[0095] The second acquisition module 530 is used to acquire the driver seat posture after the driver seat is manually adjusted, and to obtain at least one second driver seat posture.

[0096] The third acquisition module 540 is used to fuse the first driver's seat posture and at least one second driver's seat posture to obtain the target driver's seat posture.

[0097] The adjustment module 550 is used to adjust the current driver's seat posture to the target driver's seat posture.

[0098] In one possible implementation, the recommendation module 520 includes:

[0099] The information acquisition unit is used to acquire the driver's facial information based on the image;

[0100] The information matching unit is used to determine whether there is preset facial information in the preset information database that matches the facial information;

[0101] The posture recommendation unit is used to recommend a first driver's seat posture that is adapted to the driver's body type based on the image if the condition is met.

[0102] In one possible implementation, the information matching unit is specifically used to determine the similarity between facial information and various preset facial information in a preset information database to obtain multiple similarities; and to determine whether there is a similarity greater than a similarity threshold among the multiple similarities, so as to determine whether there is preset facial information in the preset information database that matches the facial information.

[0103] In one possible implementation, the posture recommendation unit is specifically used to input the image into a pre-trained seat posture recommendation model, which extracts the driver's body shape features from the image and outputs multiple candidate seat postures corresponding to the body shape features and probability values ​​corresponding to the multiple candidate seat postures; determines the maximum probability value among the multiple candidate seat postures; and determines the candidate seat posture corresponding to the maximum probability value among the multiple candidate seat postures as the first driver's seat posture.

[0104] In one possible implementation, the second acquisition module 530 is specifically used to: when there is preset facial information matching the facial information in the preset information database, acquire the driver's seat posture after the driver has previously adjusted the driver's seat, and obtain at least one second driver's seat posture; wherein, the seat posture includes the distance between the driver's seat cushion and the vehicle floor, the distance between the driver's seat cushion and the brake pedal, and the angle between the driver's seat cushion and the backrest.

[0105] In one possible implementation, the third acquisition module 540 is specifically used to: set weight values ​​for the first driver's seat posture and at least one second driver's seat posture respectively, and perform a weighted calculation on the first driver's seat posture and at least one second driver's seat posture according to the weight values ​​to obtain the target driver's seat posture.

[0106] In one possible implementation, the third acquisition module 540, in setting weight values ​​for the first driver's seat posture and at least one second driver's seat posture, is specifically configured to: determine the weight value of the first driver's seat posture based on the number of first driver's seat postures, the number of times n the driver's seat is adjusted corresponding to the at least one second driver's seat posture, and the natural constant e; and determine the driver's seat posture MC generated by the i-th manual adjustment of the driver's seat based on the weight value of the first driver's seat posture and the number of adjustments n. i The weight values; where n is a positive integer, i = 1, 2, 3, ..., n, MC iIt belongs to the posture of at least one second driver's seat.

[0107] Figure 6 A schematic diagram of the structure of a vehicle provided in an embodiment of this application is shown. Figure 6 As shown, the vehicle 600 includes a memory 601 and a processor 602. The memory 601 stores executable program code 6011, and the processor 602 is used to call and execute the executable program code 6011 to perform a method for adjusting seat posture.

[0108] Furthermore, embodiments of this application also protect an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform a seat posture adjustment method provided in embodiments of this application.

[0109] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0110] When the functional modules are divided according to their respective functions, the device may further include a first acquisition module, a recommendation module, a second acquisition module, a third acquisition module, and an adjustment module, etc. It should be noted that all relevant content of each step involved in the above method embodiments can be referenced to the functional description of the corresponding functional module, and will not be repeated here.

[0111] It should be understood that the device provided in this embodiment is used to perform the above-described method for adjusting seat posture, and therefore can achieve the same effect as the above-described implementation method.

[0112] When using an integrated unit, the device may include a processing module and a storage module. When the device is applied to a vehicle, the processing module can be used to control and manage the vehicle's movements. The storage module can be used to support the vehicle in executing program code, etc.

[0113] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits as disclosed in this application. The processor may also be a combination of computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and microprocessors, etc., and the storage module may be a memory.

[0114] In addition, the device provided in the embodiments of this application may specifically be a chip, component or module. The chip may include a connected processor and a memory. The memory is used to store instructions. When the processor calls and executes the instructions, the chip can execute a seat posture adjustment method provided in the above embodiments.

[0115] This embodiment also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the above-described method steps to implement a seat posture adjustment method provided in the above embodiment.

[0116] This embodiment also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to implement a method for adjusting seat posture provided in the above embodiment.

[0117] In this embodiment, the device, computer-readable storage medium, computer program product, or chip are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0118] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0119] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0120] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for adjusting seat posture, characterized in that, The method includes: Acquire an image of the driver in the driver's seat; Based on the image, a first driver's seat posture adapted to the driver's body type is recommended; The driver's seat posture is obtained after the driver's seat is manually adjusted, so as to obtain at least one second driver's seat posture; The weight value of the first driver seat posture is determined based on the number of first driver seat postures, the number of times n the driver seat is adjusted corresponding to the at least one second driver seat posture, and the natural constant e. Based on the weight value of the first driver's seat posture and the number of adjustments n, determine the driver's seat posture MC resulting from the i-th manual adjustment of the driver's seat. i The weight values; where n is a positive integer, i = 1, 2, 3, ..., n, MC i Belonging to at least one of the second driver's seat postures; The first driver's seat posture and the at least one second driver's seat posture are weighted according to the weight values ​​to obtain the target driver's seat posture. Adjust the current driver's seat posture to the target driver's seat posture.

2. The method according to claim 1, characterized in that, The first driver's seat posture recommended based on the image and adapted to the driver's body type includes: The driver's facial information is obtained from the image; Determine whether there is any preset facial information in the preset information database that matches the facial information; If so, a first driver's seat posture adapted to the driver's body type is recommended based on the image.

3. The method according to claim 2, characterized in that, The determination of whether there is preset facial information in the preset information database that matches the facial information includes: Determine the similarity between the facial information and each preset facial information in the preset information database to obtain multiple similarity scores; Determine whether there is a similarity greater than a similarity threshold among the multiple similarities, so as to determine whether there is preset facial information in the preset information database that matches the facial information.

4. The method according to claim 2, characterized in that, The first driver's seat posture recommended based on the image and adapted to the driver's body type includes: The image is input into a pre-trained seat posture recommendation model, which extracts the driver's body shape features from the image and outputs multiple candidate seat postures corresponding to the body shape features and the probability values ​​corresponding to the multiple candidate seat postures. Determine the maximum probability value among the probability values ​​corresponding to the multiple candidate seat postures; The candidate seat posture corresponding to the highest probability value among the multiple candidate seat postures is determined as the first driver seat posture.

5. The method according to claim 2, characterized in that, The step of obtaining the driver seat posture after the driver seat is manually adjusted, in order to obtain at least one second driver seat posture, includes: If a preset facial information matching the facial information exists in the preset information database, the driver's previous driver seat posture after adjusting the driver seat is obtained to obtain the at least one second driver seat posture; wherein, the driver seat posture includes the distance between the driver seat cushion and the vehicle floor, the distance between the driver seat cushion and the brake pedal, and the angle between the driver seat cushion and the backrest.

6. A seat posture adjustment device, characterized in that, The device includes: The first acquisition module is used to acquire an image of the driver in the driver's seat; The recommendation module is used to recommend a first driver's seat posture that is adapted to the driver's body type based on the image; The second acquisition module is used to acquire the driver seat posture after the driver seat is manually adjusted, and to obtain at least one second driver seat posture. The third acquisition module is used to determine the weight value of the first driver's seat posture based on the number of first driver's seat postures, the number of times n the driver's seat is adjusted corresponding to the at least one second driver's seat posture, and the natural constant e; and to determine the driver's seat posture MC generated by the i-th manual adjustment of the driver's seat based on the weight value of the first driver's seat posture and the number of adjustments n. i The weight values; where n is a positive integer, i = 1, 2, 3, ..., n, MC i The first driver's seat posture and the at least one second driver's seat posture belong to the at least one second driver's seat posture; the target driver's seat posture is obtained by weighting the first driver's seat posture and the at least one second driver's seat posture according to the weight value. An adjustment module is used to adjust the current driver's seat posture to the target driver's seat posture.

7. A vehicle, characterized in that, The vehicles include: Memory, used to store executable program code; A processor for calling and running the executable program code from the memory, causing the vehicle to perform the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed, implements the method as described in any one of claims 1 to 5.

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