Seat adjusting method, device, equipment, medium and product

Abstract

The invention discloses a seat adjusting method, device and equipment, a medium and a product. The method comprises the steps of determining road environment information of a road where a vehicle is located based on at least two terrain recognition modes in a vehicle driving process, and obtaining meteorological information of an environment where the vehicle belongs; determining an environment type based on the meteorological information, processing the road environment information determined by the at least two terrain recognition modes according to the environment type, and determining road attribute information; acquiring traffic operation state information of the vehicle, and determining seat adjustment parameters based on the traffic operation state information and the road attribute information; a seat in the vehicle is adjusted based on the seat adjustment parameter. The technical effects that the seat adjusting accuracy and convenience are improved, and the comfort level and safety of a passenger are improved are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer processing, and in particular to a seat adjustment method, device, equipment, medium and product. BACKGROUND

[0002] With the rapid development of the automobile industry, users' requirements for driving comfort and safety are increasing. In different terrain conditions, such as flat roads, rugged mountain roads, slopes, etc., the support and comfort of the seat are different for drivers and passengers.

[0003] Traditional seat adjustment methods mostly rely on manual operation. In different terrain conditions, users need to frequently adjust the seat, which may still not meet the comfort and safety requirements of drivers and passengers. SUMMARY

[0004] The present application provides a seat adjustment method, device, equipment, medium and product to improve the accuracy and convenience of seat adjustment and improve the comfort and safety of the passengers.

[0005] According to an aspect of the present application, a seat adjustment method is provided, applied to a vehicle, the method comprising:

[0006] During the driving of the vehicle, the road environment information of the road where the vehicle is located is determined based on at least two terrain recognition methods, and the meteorological information of the environment to which the vehicle belongs is obtained;

[0007] The environment type is determined based on the meteorological information, and the road attribute information is determined by processing the road environment information determined by the at least two terrain recognition methods according to the environment type; wherein the road attribute information at least includes terrain type, road slope and road adhesion coefficient;

[0008] The traffic running state information of the vehicle is obtained, and the seat adjustment parameter is determined based on the traffic running state information and the road attribute information;

[0009] The seat in the vehicle is adjusted based on the seat adjustment parameter.

[0010] According to another aspect of the present application, a seat adjustment device is provided, configured in a vehicle, the device comprising:

[0011] The information acquisition module is configured to determine the road environment information of the road where the vehicle is located based on at least two terrain recognition methods during the driving of the vehicle, and obtain the meteorological information of the environment to which the vehicle belongs;

[0012] The road attribute information determination module is configured to determine an environment type based on the weather information, and process road environment information determined by at least two of the terrain recognition modes according to the environment type to determine road attribute information, wherein the road attribute information at least includes a terrain type, a road slope, and a road adhesion coefficient.

[0013] The seat adjustment parameter determination module is configured to acquire traffic running state information of the vehicle, and determine a seat adjustment parameter based on the traffic running state information and the road attribute information.

[0014] The seat adjustment module is configured to adjust a seat in the vehicle based on the seat adjustment parameter.

[0015] According to another aspect of the present application, an electronic device is provided, which comprises:

[0016] at least one processor; and a memory connected with the at least one processor in communication; wherein

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the seat adjustment method according to any one of the embodiments of the present application.

[0018] According to another aspect of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to execute the seat adjustment method according to any one of the embodiments of the present application.

[0019] According to another aspect of the present application, a computer program product is provided, which comprises a computer program for enabling a processor to execute the seat adjustment method according to any one of the embodiments of the present application when executed by the processor.

[0020] The technical scheme of the embodiment of the present application determines the road environment information of the road where the vehicle is located based on at least two terrain identification modes during the driving of the vehicle, and obtains the meteorological information of the environment to which the vehicle belongs; determines the environment type based on the meteorological information, and processes the road environment information determined by the at least two terrain identification modes according to the environment type to determine the road attribute information; obtains the traffic running state information of the vehicle, determines the seat adjustment parameter based on the traffic running state information and the road attribute information; and adjusts the seat in the vehicle based on the seat adjustment parameter, thereby solving the problem that in the prior art, the seat is manually operated and needs to be frequently adjusted by the user, and the comfort and safety requirements of the driver and the passenger cannot be met, realizing that the road environment information of the road where the vehicle is located is determined by combining at least two terrain identification modes, the meteorological information of the environment to which the vehicle belongs is obtained, then the environment type is determined based on the meteorological information, the road environment information determined by the terrain identification mode is processed considering the environment type, the road attribute information is determined, the accuracy of the determination of the road attribute information is improved, then the traffic running state information and the road attribute information are combined to determine the seat adjustment parameter, the seat in the vehicle is adjusted based on the seat adjustment parameter, the comfort of the occupant is improved, the passenger is ensured to be in the most comfortable state all the time, and the safety of driving is ensured.

[0021] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0023] Figure 1 is a flowchart of a seat adjustment method according to an embodiment of the present application;

[0024] Figure 2 is a flowchart of a seat adjustment method according to an embodiment of the present application;

[0025] Figure 3 is a structural schematic diagram of a seat adjustment device according to an embodiment of the present application;

[0026] Figure 4 is a structural schematic diagram of an electronic device for implementing the seat adjustment method of the embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the person skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" 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 does not have to be limited to those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] Embodiment one

[0030] Figure 1 It is a flow chart of a seat adjustment method according to the embodiment one of the present application. The embodiment can be applied to the case of adjusting the seat in the vehicle. The method can be executed by a seat adjustment device, which can be realized in the form of hardware and / or software, and can be configured in a computing device. As shown in the figure, the method comprises: Figure 1

[0031] S110, during the driving of the vehicle, determining the road environment information of the road where the vehicle is located based on at least two terrain identification methods, and obtaining the meteorological information of the environment to which the vehicle belongs.

[0032] ​The terrain recognition method can be a method of identifying and analyzing the terrain characteristics (such as road flatness, slope, terrain, road surface friction coefficient, etc.) of the road where the vehicle is located. For example, the terrain recognition method can be visual information-based recognition, such as using a camera to collect image data including the road, and identifying the road terrain through image processing and analysis techniques (such as binocular stereo vision, semantic segmentation, etc.); or the terrain recognition method can also be LiDAR-based recognition, such as using a LiDAR to emit a laser beam and receive a reflected signal, generating point cloud data including the road, and identifying the road terrain through point cloud processing techniques; or the terrain recognition method can also be a millimeter wave radar-based recognition method, such as using a millimeter wave radar to emit and receive millimeter wave signals, detecting the distance, speed and angle of objects on the road, and identifying the road terrain changes. The road environment information can be information reflecting the terrain characteristics of the road where the vehicle is located, including but not limited to road flatness, slope, lane line position, traffic signs, etc. The meteorological information can be information reflecting the meteorological conditions of the environment to which the vehicle belongs, such as temperature, humidity, wind speed, rainfall, visibility, etc.

[0033] In this embodiment, in order to improve the accuracy and reliability of the road environment information, at least two terrain recognition methods can be combined to determine the road environment information of the road where the vehicle is located. For example, multiple cameras (such as front, side cameras, etc.) can be installed on the vehicle, and during the driving of the vehicle, the cameras can be used to capture the road where the vehicle is located to obtain road images. Then, the road images can be denoised, corrected, etc., and key feature points (such as regions with significant gradient changes in the image, such as road signs, lane lines, road surfaces, etc.) in the processed road images can be extracted, and machine learning techniques can be used to determine the road environment information based on the feature points. Alternatively, a LiDAR can be used to emit a laser beam and receive a reflected signal to generate point cloud data corresponding to the road, and road environment information such as road slope and terrain can be identified through point cloud clustering, segmentation, etc. Alternatively, the road image and the point cloud data can be fused, for example, the road features of the two types of data are extracted and fused to determine the road environment information, thereby improving the recognition accuracy and reliability. At the same time, meteorological information of the environment to which the vehicle belongs can be obtained, such as installing a temperature sensor on the outside of the vehicle to measure the ambient temperature in real time, installing a humidity sensor on the outside of the vehicle to measure the ambient humidity in real time, installing a wind speed sensor on the top or side of the vehicle to measure the wind speed in real time, installing a rainfall sensor on the top of the vehicle to measure the rainfall in real time, or using optical or laser technology to measure the visibility of the road environment. Alternatively, meteorological information sent by a meteorological station to the vehicle can be received.

[0034] In this embodiment, the terrain recognition method for determining the road environment information of the road where the vehicle is located can include but is not limited to the following two terrain recognition methods.

[0035] As an optional mode, the terrain recognition mode can be a visual information based recognition mode. The manner of determining the road environment information of the road where the vehicle is located based on the visual information can be: acquiring at least two image processing images including the road where the vehicle is located based on at least two cameras on the vehicle; determining a disparity map based on the at least two image processing images; and determining the road environment information based on the disparity map. The disparity map is used to represent the horizontal displacement (i.e., the disparity value) of the same target point in the road space in the two image processing images.

[0036] In the embodiment, at least two cameras can be installed on the vehicle, for example, the number of cameras is two, the two cameras are arranged horizontally to simulate binocular vision of human eyes, and the baseline distance (B, the distance between the two cameras) and the focal length (f) of the two cameras are known parameters. During the driving of the vehicle, the at least two cameras synchronously acquire image processing images including the road where the vehicle is located. Further, the acquired images can be preprocessed, such as denoising, graying, and normalization, to improve the efficiency and accuracy of terrain recognition processing. The deviation relationship between the same pixel points in the two image processing images is established by a sliding window matching (SGBM algorithm) or an energy optimization method (such as a graph cut, belief propagation, or other disparity map generation algorithm) to obtain a disparity map. Each pixel value in the disparity map represents the disparity value of the pixel point. The greater the disparity value, the closer the point is to the camera. Further, the disparity value of each pixel point in the disparity map can be converted into a depth value based on the triangulation formula of binocular vision. Based on the depth value of each pixel point, a depth map is generated. The depth map is analyzed by using a deep learning technology (such as a convolutional neural network, CNN) to recognize the road environment information. Alternatively, SIFT (scale-invariant feature transform), SURF (speeded-up robust features), or ORB (oriented FAST and rotated BRIEF) algorithms are used to detect key point features in the depth map to determine the road environment information. Alternatively, the depth map is combined with a semantic segmentation map to recognize the road environment information.

[0037] For example, the road environment information can be determined by simulating the binocular parallax mechanism of the human eye, and by synchronously capturing scene images (i.e., the to-be-processed images) by two cameras with a baseline distance of B. When the same feature points of an object appear in the left and right to-be-processed images with a horizontal displacement (parallax value d), the depth value is calculated by using a triangulation formula to obtain a depth map, Z = f * B / d, where Z represents the depth value, f is the focal length, B is the baseline distance, and d is the parallax. Alternatively, the corresponding point relationship between the left and right images can be established by using a sliding window matching (Block Matching), SGBM (semi-global matching) algorithm, or an energy optimization method, a disparity map is generated after the disparity map is converted into terrain depth information to obtain a depth map. Further, robust feature points such as SIFT / SURF in the depth map are extracted, and the terrain structure is identified in combination with semantic segmentation to obtain the road environment information.

[0038] The terrain recognition method based on visual information can provide high-precision depth information, thereby realizing real-time perception and analysis of the road environment, improving the accuracy of road environment information recognition, and facilitating improvement of the accuracy and comfort of seat adjustment.

[0039] As another optional mode, the terrain recognition mode can be a kinematic information-based recognition mode. The kinematic information-based recognition mode can determine the road environment information of the road on which the vehicle is located in the following manner: obtaining current driving information of the vehicle; and determining the road environment information based on the current driving information.

[0040] The current driving information can be information related to the state of the vehicle and obtained in real time during driving of the vehicle, and can include, but is not limited to, speed, acceleration, steering angle, braking state, and the like.

[0041] In this embodiment, the current driving information of the vehicle can be detected based on the sensors deployed on the vehicle, for example, the current speed of the vehicle is measured based on a speed sensor; the acceleration of the vehicle is measured based on an acceleration sensor; the steering angle of the vehicle is measured based on a steering angle sensor; the braking state of the vehicle is detected based on a brake sensor. Alternatively, the current driving state of the vehicle can also be estimated by combining the data of multiple sensors through algorithms such as Kalman filtering, as the current driving information. The current driving information can be processed, such as calibration processing, to ensure the accuracy and reliability of the data. Further, the type of the road where the vehicle is located (such as highway, urban road, rural road, etc.) can be determined as the road environment information based on the current driving information. The slope of the road can be determined as the road environment information based on the inclination angle of the vehicle in the current driving information; the road environment information can be obtained by using target detection algorithms (such as YOLO, SSD) to identify and track obstacles based on the distance and speed information of the objects around the vehicle in the current driving information. It should be noted that the current driving information can be obtained in real time during the driving of the vehicle, and the road environment information can be dynamically updated. Machine learning algorithms can also be used to extract key features from the current driving information, and combined with historical data and prior knowledge, to infer the road environment information, such as road type, curvature, slope, traffic signs, traffic signals, positions and motion states of other vehicles and pedestrians, etc.

[0042] The advantage of this way is that the road environment information can be determined by obtaining the current driving information of the vehicle, which can improve the reliability and accuracy of determining the road environment information.

[0043] In S120, the environment type is determined based on the weather information, and the road attribute information is determined by processing the road environment information determined by the at least two terrain recognition methods according to the environment type.

[0044] The environment type can refer to an environment category classified according to the weather information, such as sunny, rainy, foggy, snowy, etc. The road attribute information can be information used to describe the physical characteristics and state of the road, including but not limited to road flatness, slipperiness, water accumulation, icing condition, terrain type (such as flat road, rugged mountain road, slope, etc.), road surface type, etc.

[0045] In this embodiment, the current environment type can be determined by comparing the weather information with the threshold of the preset weather index (such as judging as rainy if the humidity is greater than a certain threshold, judging as foggy if the visibility is lower than a certain threshold). For example, the environment type is determined as sunny if the temperature is moderate and the humidity is low and the visibility is high in the weather information. The environment type is determined as rainy if the humidity is high and the rainfall data is included in the weather information. The environment type is determined as foggy if the visibility is low and the humidity is high in the weather information. The environment type is determined as snowy if the temperature is low and the humidity is high and the snow depth data is included in the weather information.

[0046] Further, the road attribute information can be determined by fusing the road environment information determined by at least two of the terrain recognition manners according to the environment type. For example, when the environment type is sunny, the light condition is good and the visual recognition performance is high, the road environment information determined by the recognition manner based on the visual information can be selected and analyzed to determine the road attribute information. Alternatively, when the environment type is rainy, the road environment information determined by the two terrain recognition manners can be combined to determine the road attribute information due to the influence of rain and reflection.

[0047] For example, the road environment information determined by the recognition manner based on the kinematic information and the road environment information determined by the recognition manner based on the visual information can be fused to identify the specific type of the current driving terrain as the road attribute information, so as to provide input for the ideal parameters of the seat adjustment.

[0048] In the embodiment, it is considered that the surrounding environment of the vehicle can affect the accuracy of terrain recognition when the terrain recognition is based on the visual information. In order to improve the accuracy of terrain recognition, in the process of processing the road environment information determined by at least two terrain recognition manners according to the environment type to determine the road attribute information, if the environment type is a complex weather type, the weight of the road environment information determined by the recognition manner based on the visual information is reduced, and the weight of the road environment information determined by the recognition manner based on the kinematic information is increased; and the road attribute information is determined based on the road environment information determined by at least two terrain recognition manners and the processed weights.

[0049] The complex weather type can be a pre-set weather affecting the road condition recognition, for example, the complex weather type is rain, heavy fog, blizzard, strong wind and other extreme weather conditions, and the visibility is low and the road condition is complex.

[0050] Specifically, in the case of the environment type being a complex weather type, visual sensors (such as a camera) may be interfered by rain, fog, snow, etc., resulting in a decrease in recognition accuracy. Sensors based on kinematic information (such as an inertial measurement unit, a wheel speed sensor) are relatively stable. At this time, the weight of the road environment information determined by the recognition mode based on visual information can be adjusted based on the specific environment type, for example, the weight of the visual information is adjusted from 0.8 to 0.5 to reduce the fusion proportion of the road environment information, and the weight of the road environment information determined by the recognition mode based on kinematic information is adjusted, for example, the weight of the kinematic information is adjusted from 0.8 to 1.0 to increase the fusion proportion of the road environment information. Further, the road environment information determined by at least two terrain recognition modes and the corresponding processed weights can be fused, and the road attribute information is determined based on the fused road environment information. Alternatively, the road attribute information is determined based on the road environment information with the largest weight. Alternatively, the road environment information determined based on visual information and kinematic information is weighted and fused according to the adjusted weight. For example: the fused road environment information = (road environment information determined by visual information x visual weight) + (road environment information determined by kinematic information x kinematic weight), and then the road attribute information is analyzed in combination with the fused road environment information.

[0051] For example, when the environment type affecting terrain recognition, such as heavy rain, fog, snow, etc., the recognition effect is not accurate, the weight of the road environment information determined by the recognition mode based on kinematic information can be increased, thereby improving the robustness of the terrain recognition result.

[0052] In this embodiment, in the process of processing the road environment information determined by at least two terrain recognition modes according to the environment type to determine the road attribute information: if the environment type is not a complex weather type, the weight of the road environment information determined by the recognition mode based on visual information is adjusted, and the weight of the road environment information determined by the recognition mode based on kinematic information is adjusted. The road attribute information is determined based on the road environment information determined by at least two terrain recognition modes and the corresponding processed weights.

[0053] Specifically, when the environment type does not belong to the complex weather condition, it indicates that the weather condition is good, such as sunny, light fog, light rain, etc. The reliability of the visual information is usually high, so the weight of the identification mode based on the visual information can be increased, and the weight of the identification mode based on the kinematic information can be appropriately reduced. At this time, the weight of the road environment information determined by the identification mode based on the visual information can be adjusted to increase the fusion proportion of the road environment information, and the weight of the road environment information determined by the identification mode based on the kinematic information can be adjusted to reduce the fusion proportion of the road environment information. Further, the road environment information determined by at least two terrain identification modes and the corresponding processed weights can be fused, and the road attribute information can be determined based on the fused road environment information. Alternatively, the road attribute information can be determined based on the road environment information with the largest weight. Alternatively, the road environment information determined based on the visual information and the kinematic information can be weighted and fused according to the adjusted weight. Further, the road attribute information can be analyzed in combination with the fused road environment information.

[0054] For example, under normal circumstances, i.e., the environment type does not belong to the complex weather condition, the road environment information determined by the identification mode based on the visual information can be used as the main information, i.e., the weight of the road environment information is large, and the road environment information includes asphalt road, gravel road, or sand ground, etc. The road environment information determined by the identification mode based on the kinematic information can be used as the auxiliary information, i.e., the weight of the road environment information is small, and the road environment information includes slope and ground adhesion coefficient information, etc., so as to analyze the road attribute information.

[0055] Through the data fusion method based on the weight adjustment, the road attribute information can be more accurately sensed under the complex weather condition, so as to improve the accuracy of the determination of the road attribute information, improve the accuracy of the seat adjustment, and achieve the technical effects of improving the comfort and safety of the passenger.

[0056] S130, acquiring traffic running state information of the vehicle, and determining a seat adjustment parameter based on the traffic running state information and the road attribute information.

[0057] The traffic running state information can be various information related to traffic during the driving of the vehicle, including the speed, acceleration, driving direction, distance from the front vehicle, driving mode (such as automatic driving mode, sports mode, comfort mode, energy saving mode, etc.), road surface type (such as asphalt road surface, cement road surface, gravel road surface, flat highway, rugged mountain road, slope, etc.), and road type (such as ordinary highway, expressway, urban road, rural road, mountain road, etc.). The seat adjustment parameter is a parameter for controlling various adjustment functions of the seat, such as the front and rear position of the seat, the backrest angle, the height, the headrest position, the inflation amount of the seat airbag, the stiffness of the air spring, the seat adjustment speed, the inclination angle, the waist and back support, the cushion damping, etc.

[0058] In the embodiment, various sensors installed on the vehicle, such as a speed sensor, a camera, a radar, etc., can be used to obtain the speed, acceleration, road conditions ahead, driving mode, road type, and other traffic running state information of the vehicle in real time. Alternatively, through the Internet of Vehicles system, the vehicle can receive traffic running state information such as road type, road type, road conditions ahead, etc. sent from the traffic management system. Alternatively, the road type, road type, road conditions ahead, and other traffic running state information can be obtained in combination with a preset map database. Further, based on the preset correspondence between the traffic running state information and the road attribute information and the seat adjustment parameter, the seat adjustment parameter required by the vehicle can be determined. For example, the road type in the traffic running state information is a bumpy section, at this time when the vehicle is driving on the bumpy section, the inflation amount of the seat air bag can be adjusted according to the bumpy degree to increase the cushioning performance of the seat; for example, the road type in the traffic running state information is a highway, at this time the vehicle is driving at a high speed, the seat backrest angle can be adjusted to make the driver in a more comfortable and aerodynamic posture. For example, the driving mode in the traffic running state information is a dynamic mode, then in the dynamic mode, the seat adjustment speed can be appropriately accelerated. Alternatively, the traffic running state information and the road attribute information can be analyzed and processed based on a pre-trained machine learning model to calculate the seat adjustment parameter suitable for the current driving state and road conditions. For example, based on the lateral acceleration and the radius of the curve when the vehicle is driving on the curve, the lateral support force of the seat is adjusted to improve the stability and comfort of the ride.

[0059] Optionally, the road attribute information at least includes the terrain type, the road slope and the road adhesion coefficient, and correspondingly, based on the traffic running state information and the road attribute information, the seat adjustment parameter is determined, including: determining a time adjustment parameter based on the traffic running state information; determining a first adjustment parameter corresponding to the road attribute information based on the terrain type, the road slope and the road adhesion coefficient in the road attribute information, and a preset seat adjustment mapping table; determining the seat adjustment parameter based on the time adjustment parameter and the first adjustment parameter.

[0060] The terrain type can be classified according to the shape, height, slope, terrain features, etc. of the road surface. For example, the terrain type includes but is not limited to flat, asphalt road, gravel road, sandy land, rugged, mountain road, etc. The road slope can be the inclination angle of the road. The traffic running state information includes the road type and / or the driving mode. The road type refers to the surface type of the road on which the vehicle is driving, such as asphalt pavement, cement pavement, gravel pavement, etc. The preset seat adjustment mapping table can be pre-set and includes the seat adjustment position, seat adjustment angle and seat adjustment speed corresponding to different road attribute information. The road adhesion coefficient can be the friction coefficient between the road surface and the tire.

[0061] Specifically, when the road surface type is a highway, the time adjustment parameter can be determined as the parameter for pre-adjusting the seat. Simultaneously, based on the terrain type, road slope, and road surface adhesion coefficient in the road attribute information, a first adjustment parameter matching the road attribute information can be found from a preset seat adjustment mapping table. Optionally, the first adjustment parameter includes at least the seat adjustment position, seat adjustment angle, and seat adjustment speed. Furthermore, the time adjustment parameter and the first adjustment parameter can be used as the seat adjustment parameters.

[0062] For example, based on the identified road attribute information, the system can query the preset seat adjustment parameters corresponding to the three dimensions of terrain, slope, and road surface adhesion coefficient from a preset seat adjustment mapping table. These parameters include the seat's fore-and-aft position, tilt angle, lumbar and back support, and seat cushion damping. For instance, if the road slope is uphill, the seat back angle can be increased to improve passenger comfort. If the road slope is downhill, the seat back angle can be decreased. A high road surface adhesion coefficient (e.g., dry road surface) increases seat stability and support; a low road surface adhesion coefficient (e.g., wet or icy road surface) increases shock absorption, improving passenger comfort. Another example: the terrain type is a highway, the road slope is 0°, and the road surface adhesion coefficient is high. In this case, the seat adjustment position is medium height; the seat adjustment angle is 70° backrest angle and 5° seat cushion angle; and the seat adjustment speed is medium speed.

[0063] This method allows for the accurate and efficient determination of seat adjustment parameters, thereby improving passenger comfort and safety.

[0064] S140. Adjust the seats in the vehicle based on seat adjustment parameters.

[0065] In this embodiment, the vehicle seat may be equipped with an electric adjustment device, such as an electric adjustment motor or an air pump. Based on determined seat adjustment parameters, the electric adjustment device is controlled to perform corresponding actions, achieving automatic seat adjustment. For example, adjusting the seat's fore-and-aft position, backrest angle, and height.

[0066] For example, seat adjustment parameters can be sent to seat adjustment actuators (such as motors, transmission mechanisms, and other electric adjustment devices), and PID control can be used to control the seat adjustment parameters, adjust the seat position, adjust the seat back angle, adjust the lumbar support, and adjust the seat cushion damping, so as to achieve real-time adjustment of the seat posture and ensure user comfort.

[0067] It should be noted that during the seat adjustment process, the changes in traffic operation state information and road attribute information can be monitored in real time to determine the seat adjustment parameters based on the changed traffic operation state and road attribute information, so as to dynamically adjust the seat adjustment parameters to ensure that the seat is always in the best state.

[0068] It should also be noted that, in order to further ensure that the seat adjustment state meets the user's needs, the user's seat feedback information for the vehicle can also be received when the seat in the vehicle is adjusted based on the seat adjustment parameters, and the seat state information of the seat is detected; the seat adjustment parameters are adjusted based on the seat feedback information and the seat state information, so as to adjust the seat in the vehicle based on the adjusted seat adjustment parameters.

[0069] The seat feedback information can be the user's feedback content for the current seat comfort, support, and other aspects, for example, the feedback content can be "seat height is too high", "backrest angle is not suitable", "leg support is insufficient", etc. The seat state information can refer to the actual state of the seat, such as the position of the seat, the angle of the backrest and the headrest, the pressure distribution of each part of the seat, etc.

[0070] Specifically, a control for inputting seat feedback information can be developed in advance on the main control interface of the vehicle. During the process of adjusting the seat in the vehicle based on the seat adjustment parameters, the user can input the seat feedback information (for example, the seat feedback information can be voice, text or selection item type input information) in the control. When the seat feedback information is received, the current seat state information of the vehicle seat can be obtained, and then a machine learning algorithm or a pre-set rule engine can be used to adjust the seat adjustment parameters or recalculate the seat adjustment parameters in combination with the seat feedback information and the seat state information. The machine learning algorithm can be trained according to a large amount of user data and seat state data and optimal seat adjustment parameters. Further, the seat in the vehicle is adjusted based on the adjusted seat adjustment parameters, so that the adjusted seat state meets the user's current riding needs.

[0071] For example, during the adjustment of the seat, the system continuously monitors the seat state information and the user feedback seat feedback information. When the seat feedback information meets the pre-set condition, the seat is fine-tuned to optimize the adjustment effect. At the same time, the user's use habit of the seat and the seat feedback information can also be used to continuously optimize the pre-set seat adjustment mapping table, so that the adjusted seat state meets the user's needs and improves the user's comfort and driving experience.

[0072] The advantage of such an arrangement is that by receiving the seat feedback information of the user, the seat can be adjusted according to the personalized preferences of the passenger to provide a more comfortable riding experience, while ensuring that the passenger is always in the most comfortable state during driving.

[0073] The technical scheme of the embodiment determines the road environment information of the road where the vehicle is located based on at least two terrain recognition methods during driving of the vehicle, and obtains meteorological information of the environment to which the vehicle belongs; determines the environment type based on the meteorological information, and processes the road environment information determined by the at least two terrain recognition methods according to the environment type to determine road attribute information; obtains traffic running state information of the vehicle, determines seat adjustment parameters based on the traffic running state information and the road attribute information; and adjusts the seat in the vehicle based on the seat adjustment parameters, thereby solving the problem in the prior art that manual operation of the seat is relied on and the user needs to frequently adjust the seat, and still cannot meet the comfort and safety requirements of the driver and the passenger, and realizing that the road environment information of the road where the vehicle is located is determined by combining at least two terrain recognition methods, the meteorological information of the environment to which the vehicle belongs is obtained, the environment type is determined in combination with the meteorological information, the road environment information determined by the terrain recognition method is processed considering the environment type to determine the road attribute information, the accuracy of determination of the road attribute information is improved, the seat adjustment parameters are determined in combination with the traffic running state information and the road attribute information, the seat in the vehicle is adjusted based on the seat adjustment parameters, the comfort of the occupant is improved, the passenger is ensured to be always in the most comfortable state, and the safety of driving is ensured.

[0074] Embodiment Two

[0075] As an optional embodiment of the above-mentioned embodiments, in order to make the skilled in the art further clear the technical scheme of the embodiments of the present application, specific application scenario examples are given. Specifically, refer to the following specific content.

[0076] Reference is made to Figure 2The vehicle dynamics information (i.e., current driving information) can be collected in real time by various sensors (such as GPS positioning device, accelerometer, gyroscope, etc.) installed on the vehicle, and the terrain information (i.e., road environment information, including slope, road flatness, road type, etc.) can be identified according to the vehicle dynamics information. The road environment information can also be obtained by using a forward binocular camera (i.e., a camera device) through stereo vision perception. The road environment information such as the slope of the ground and the type of the road on the driving route of the vehicle can also be identified by using navigation information. Further, the road environment information obtained by the three identification methods can be fused to identify the terrain type, road slope, and road adhesion coefficient of the current driving, and other road attribute information. According to the identified road attribute information, the seat adjustment parameters corresponding to the road attribute information are obtained by querying the preset seat adjustment mapping table, including the front and rear position of the seat, the inclination angle, the waist and back support strength, etc. Further, the seat adjustment parameters obtained by the query are sent to the seat adjustment execution mechanism (such as a motor, a transmission mechanism, etc.) to drive the seat to automatically adjust according to the predetermined parameters.

[0077] During the seat adjustment process, the system can continuously monitor the seat state information and the seat feedback information fed back by the user, and make fine adjustments as necessary to optimize the adjustment effect. At the same time, the preset seat adjustment mapping table can be continuously optimized according to the user's usage habits and the seat feedback information, to improve the intelligent level of the system and the user experience.

[0078] For example, the seat adjustment control system provided by the embodiments of the present application can be deployed on a sports vehicle, which includes an acceleration sensor, a gyroscope, a height sensor, and a seat adjustment execution mechanism. When the vehicle drives on a rugged road in the mountainous area, the seat adjustment control system can adjust the seat of the vehicle based on the seat adjustment method provided by the embodiments of the present application. The specific way can be that the terrain perception sensor collects the terrain data of the road where the vehicle is located in real time and transmits it to the seat adjustment control system. After analyzing the terrain data, the seat adjustment control system determines that the current terrain slope is large and bumpy, and automatically adjusts the seat angle to keep the body of the occupant horizontal and increase the support strength of the seat to reduce the body sway. After the occupant feels the automatic adjustment of the seat, the comfort level is obviously improved, and the safety of the vehicle driving is also improved.

[0079] For example, the seat adjustment control system provided by the embodiment of the present application can be deployed on a car, and can be linked with the navigation system and the automatic driving system of the vehicle. When the vehicle travels on roads with different terrains according to the indication of the navigation system, the seat adjustment control system can adjust the seat state in advance according to the road surface type. For example, when the vehicle is about to enter an expressway, the system can automatically adjust the seat angle to make the occupant in a more comfortable driving or riding posture. When the vehicle is in an automatic driving mode, the seat adjustment control system can make more fine adjustment according to the driving state of the vehicle and the physical condition of the occupant, to improve the comfort and safety of the occupant.

[0080] The technical solution of the embodiment determines the road environment information of the road where the vehicle is located by combining multiple terrain identification methods, obtains meteorological information of the environment to which the vehicle belongs, and then determines the environment type in combination with the meteorological information. The road attribute information determined by the terrain identification method is processed in consideration of the environment type, the road attribute information is determined, the accuracy of the determination of the road attribute information is improved, and then the seat adjustment parameters are determined in combination with the traffic running state information and the road attribute information. The seat in the vehicle is adjusted based on the seat adjustment parameters, the comfort of the occupant is improved, the passenger is ensured to be in the most comfortable state at all times, and the safety of driving is ensured.

[0081] Embodiment Three

[0082] Figure 3 is a structural schematic diagram of a seat adjustment device provided by Embodiment Three of the present application. As shown in Figure 3 , the device includes an information acquisition module 210, a road attribute information determination module 220, a seat adjustment parameter determination module 230, and a seat adjustment module 240.

[0083] The information acquisition module 210 is configured to determine the road environment information of the road where the vehicle is located based on at least two terrain identification methods during the driving of the vehicle, and obtain meteorological information of the environment to which the vehicle belongs. The road attribute information determination module 220 is configured to determine the environment type based on the meteorological information, and process the road environment information determined by the at least two terrain identification methods according to the environment type to determine road attribute information. The road attribute information at least includes terrain type, road slope, and road surface adhesion coefficient. The seat adjustment parameter determination module 230 is configured to obtain traffic running state information of the vehicle, and determine seat adjustment parameters based on the traffic running state information and the road attribute information. The seat adjustment module 240 is configured to adjust the seat in the vehicle based on the seat adjustment parameters.

[0084] The technical scheme of the embodiment determines road environment information of a road where the vehicle is located based on at least two terrain recognition modes during vehicle driving, and acquires meteorological information of an environment to which the vehicle belongs; determines an environment type based on the meteorological information, and processes the road environment information determined by the at least two terrain recognition modes according to the environment type to determine road attribute information; acquires traffic running state information of the vehicle, determines a seat adjustment parameter based on the traffic running state information and the road attribute information; and adjusts the seat in the vehicle based on the seat adjustment parameter, thereby solving the problem in the prior art that manual operation of the seat is relied on, the seat needs to be frequently adjusted by the user, and the comfort and safety requirements of the driver and the passenger cannot be met, achieving the following effects: the road environment information of the road where the vehicle is located is determined by combining the at least two terrain recognition modes, the meteorological information of the environment to which the vehicle belongs is acquired, the environment type is determined based on the meteorological information, the road environment information determined by the terrain recognition mode is processed in consideration of the environment type, the accuracy of determination of the road attribute information is improved, the seat adjustment parameter is determined based on the traffic running state information and the road attribute information, the seat in the vehicle is adjusted based on the seat adjustment parameter, the comfort of the occupant is improved, the passenger is ensured to be in the most comfortable state all the time, and the safety of driving is ensured.

[0085] On the basis of the above device, optionally, the information acquisition module 210 comprises:

[0086] A to-be-processed image determination unit is configured to, in a case where the terrain recognition mode is a visual information-based recognition mode, acquire, based on at least two camera devices on the vehicle, to-be-processed images comprising a road where the vehicle is located.

[0087] A parallax map determination unit is configured to determine a parallax map based on the to-be-processed images acquired by the at least two camera devices.

[0088] A road environment information determination first unit is configured to determine road environment information based on the parallax map.

[0089] On the basis of the above device, optionally, the information acquisition module 210 comprises:

[0090] A current driving information determination unit is configured to, in a case where the terrain recognition mode is a kinematics information-based recognition mode, acquire current driving information of the vehicle.

[0091] A road environment information determination second unit is configured to determine road environment information based on the current driving information.

[0092] On the basis of the above device, optionally, the road attribute information determination module 220 comprises:

[0093] The first weight processing unit is configured to perform a weight reduction processing on the road environment information determined based on the visual information and a weight increase processing on the road environment information determined based on the kinematic information if the environment type is the complex weather type.

[0094] The road attribute information determination first unit is configured to determine the road attribute information based on the road environment information determined by the at least two terrain recognition manners and the corresponding processed weights.

[0095] On the basis of the above device, the road attribute information determination module 220 can include:

[0096] The second weight processing unit is configured to perform a weight adjustment processing on the road environment information determined based on the visual information and a weight reduction processing on the road environment information determined based on the kinematic information if the environment type is not the complex weather type.

[0097] The road attribute information determination second unit is configured to determine the road attribute information based on the road environment information determined by the at least two terrain recognition manners and the corresponding processed weights.

[0098] On the basis of the above device, the seat adjustment parameter determination module 230 can include:

[0099] The time adjustment parameter determination unit is configured to determine a time adjustment parameter based on the traffic running state information, wherein the traffic running state information includes a road surface type and / or a driving mode.

[0100] The first adjustment parameter determination unit is configured to determine a first adjustment parameter corresponding to the road attribute information based on a terrain type, a road slope and a road surface adhesion coefficient in the road attribute information, and a preset seat adjustment mapping table, wherein the first adjustment parameter at least includes a seat adjustment position, a seat adjustment angle and a seat adjustment speed.

[0101] The seat adjustment parameter determination unit is configured to determine a seat adjustment parameter based on the time adjustment parameter and the first adjustment parameter.

[0102] On the basis of the above device, the device can further include:

[0103] The seat state information determination unit is configured to receive seat feedback information of the vehicle from a user and detect seat state information of the seat.

[0104] The parameter adjusting unit is configured to adjust the seat adjusting parameter based on the seat feedback information and the seat state information, so as to adjust the seat in the vehicle based on the adjusted seat adjusting parameter.

[0105] The seat adjusting device provided by the embodiments of the present application can execute the seat adjusting method provided by any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0106] Embodiment four

[0107] Figure 4 is a structural schematic diagram of an electronic device for implementing the seat adjusting method of the embodiments of the present application. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0108] As shown in Figure 4 , the electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory 12, a random access memory 13, etc., which is communicatively connected to the at least one processor 11, wherein the memory stores a computer program that can be executed by the at least one processor. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory 12 or loaded from the storage unit 18 into the random access memory 13. In the random access memory 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the read-only memory 12, and the random access memory 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0109] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0110] The processor 11 can be various general and / or special purpose processing components having processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the seat adjustment method.

[0111] In some embodiments, the seat adjustment method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the read-only memory 12 and / or the communication unit 19. When the computer program is loaded onto the random access memory 13 and executed by the processor 11, one or more steps of the seat adjustment method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the seat adjustment method by any other suitable means, such as by means of firmware.

[0112] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0113] Computer programs used to implement the methods of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed by the processor, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0114] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0115] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0116] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0117] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. Servers can be cloud servers, also known as cloud computing servers or cloud hosts, which are a host product in the cloud computing service system to solve the defects of large management difficulty and weak business scalability in traditional physical hosts and VPS services.

[0118] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program in accordance with embodiments of the present application. For example, embodiments of the present application include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program comprising program code for executing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication unit 19, or installed from the storage unit 18, or installed from the read only memory 12. When the computer program is executed by the processor 11, the above-mentioned functions defined in the methods of the embodiments of the present application are performed.

[0119] Embodiments of the present application also provide a computer program product comprising a computer program which, when executed by a processor, implements the seat adjustment method as provided by any of the embodiments of the present application.

[0120] The computer program code implementing the present application can be written in one or more programming languages or combinations of languages including object oriented languages such as Java, Smalltalk, C++ or conventional procedural programming languages such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0121] It should be understood that various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the spirit of the present application. For example, the steps recited in the present application can be performed in parallel, in series, or in a different order, and the present application is not limited in this regard.

[0122] The above detailed description does not limit the scope of the application. Various modifications, combinations, sub-combinations and alternatives can be made to the detailed description. Any modification, equivalent replacement and improvement etc. made within the spirit and principle of the application shall be included in the scope of the application.

Claims

1. A method for adjusting a seat, characterized in that, Applied to vehicles, the method includes: During vehicle operation, road environment information of the road where the vehicle is located is determined based on at least two terrain recognition methods, and meteorological information of the environment to which the vehicle is located is obtained. Based on the meteorological information, the environment type is determined, and based on the environment type, the road environment information determined by at least two of the terrain recognition methods is processed to determine road attribute information; wherein, the road attribute information includes at least terrain type, road slope, and road surface adhesion coefficient; Obtain the traffic operation status information of the vehicle, and determine the seat adjustment parameters based on the traffic operation status information and the road attribute information; The seats in the vehicle are adjusted based on the aforementioned seat adjustment parameters.

2. The method according to claim 1, characterized in that, The determination of road environment information of the road where the vehicle is located based on at least two terrain recognition methods includes: When the terrain recognition method is a visual information-based recognition method, the images to be processed, including the road where the vehicle is located, are acquired by at least two camera devices on the vehicle. A disparity map is determined based on the images to be processed acquired by at least two of the camera devices; Based on the disparity map, road environment information is determined.

3. The method according to claim 1, characterized in that, The determination of road environment information of the road where the vehicle is located based on at least two terrain recognition methods includes: When the terrain recognition method is a kinematic information-based recognition method, the current driving information of the vehicle is obtained; Based on the current driving information, road environment information is determined.

4. The method according to claim 1, characterized in that, The process of processing road environment information determined by at least two terrain recognition methods based on the environment type to determine road attribute information includes: If the environment type is a complex weather type, the weight of the road environment information determined by the visual information-based recognition method is reduced, and the weight of the road environment information determined by the kinematic information-based recognition method is increased. Based on the road environment information determined by at least two of the terrain recognition methods and their corresponding processed weights, road attribute information is determined.

5. The method according to claim 1, characterized in that, The process of processing road environment information determined by at least two terrain recognition methods based on the environment type to determine road attribute information includes: If the environment type is not a complex weather type, the weight of the road environment information determined by the visual information recognition method is adjusted, and the weight of the road environment information determined by the kinematic information recognition method is reduced. Based on the road environment information determined by at least two of the terrain recognition methods and their corresponding processed weights, road attribute information is determined.

6. The method according to claim 1, characterized in that, The step of determining seat adjustment parameters based on the traffic operation status information and the road attribute information includes: Based on the traffic operation status information, time adjustment parameters are determined; wherein, the traffic operation status information includes road surface type and / or driving mode; Based on the terrain type, road slope, and road surface adhesion coefficient in the road attribute information, and a preset seat adjustment mapping table, a first adjustment parameter corresponding to the road attribute information is determined; wherein, the first adjustment parameter includes at least the seat adjustment position, seat adjustment angle, and seat adjustment speed; Based on the time adjustment parameter and the first adjustment parameter, the seat adjustment parameter is determined.

7. The method according to claim 1, characterized in that, When adjusting the seat in the vehicle based on the seat adjustment parameters, the method further includes: Receive user feedback on the vehicle's seats and detect the seat status information; Based on the seat feedback information and the seat status information, the seat adjustment parameters are adjusted to adjust the seat in the vehicle based on the adjusted seat adjustment parameters.

8. A seat adjustment device, characterized in that, Configured in a vehicle, the device includes: The information acquisition module is used to determine the road environment information of the road where the vehicle is located based on at least two terrain recognition methods during the vehicle's operation, and to acquire the meteorological information of the environment in which the vehicle is located. The road attribute information determination module is used to determine the environment type based on the meteorological information, and to process the road environment information determined by at least two of the terrain recognition methods according to the environment type to determine the road attribute information; wherein, the road attribute information includes at least terrain type, road slope and road surface adhesion coefficient; The seat adjustment parameter determination module is used to acquire the vehicle's traffic operation status information and determine the seat adjustment parameters based on the traffic operation status information and the road attribute information. A seat adjustment module is used to adjust the seat in the vehicle based on the seat adjustment parameters.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to said 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 seat adjustment method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the seat adjustment method according to any one of claims 1-7.

Images