Steering wheel automatic adjustment method and device, electronic equipment, computer readable storage medium and computer program product

Abstract

The embodiment of the invention provides a steering wheel automatic adjustment method and device, electronic equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a target body parameter, a target seat parameter and a target steering wheel parameter of a target object during automobile driving; the target body parameters comprise the arm length and the sitting height of the target object, the target seat parameters comprise the seat position, and the target steering wheel parameters comprise the steering wheel position and the steering wheel diameter; inputting the target body parameter, the target seat parameter and the target steering wheel parameter into an arm stress analysis model to obtain a target arm joint angle and target arm stress distribution; and determining an updated steering wheel position according to the target arm joint angle and the target arm stress distribution, and automatically adjusting the steering wheel according to the updated steering wheel position. By adopting the method, the position of the steering wheel can be accurately adjusted, and the driving comfort is improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, apparatus, electronic device, computer-readable storage medium, and computer program product for automatic steering wheel adjustment. Background Technology

[0002] With technological advancements, modern cars can automatically adjust the steering wheel when the driver's arms are on it. For example, this can be achieved by monitoring the driver's arm position to adjust the steering wheel.

[0003] However, this adjustment process takes into account only one factor and cannot accurately adjust the steering wheel. Summary of the Invention

[0004] This application provides a method, apparatus, electronic device, computer-readable storage medium, and computer program product for automatically adjusting the position of a steering wheel.

[0005] In a first aspect, embodiments of this application provide a method for automatically adjusting a steering wheel, including:

[0006] Acquire the target body parameters, target seat parameters, and target steering wheel parameters of the target object when driving a car; the target body parameters include the target object's arm length and sitting height, the target seat parameters include the seat position, and the target steering wheel parameters include the steering wheel position and steering wheel diameter.

[0007] Input the target body parameters, target seat parameters, and target steering wheel parameters into the arm force analysis model to obtain the target arm joint angles and the target arm force distribution;

[0008] Based on the target arm joint angle and the force distribution of the target arm, the updated steering wheel position is determined, and the steering wheel is automatically adjusted according to the updated steering wheel position.

[0009] In one possible implementation, the force analysis model for the arm is constructed in the following manner:

[0010] Acquire body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution of multiple test subjects when driving a car at different steering wheel positions;

[0011] By taking body parameters, seat parameters, and steering wheel parameters as inputs, and taking arm joint angles and arm force distribution as outputs, an arm force analysis model is trained.

[0012] In one possible implementation, the automatic steering wheel adjustment method further includes:

[0013] When a new test subject is driving a car, the body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution are obtained at different steering wheel positions;

[0014] Based on the new test subject's body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution, optimize the arm force analysis model.

[0015] In one possible implementation, determining the updated steering wheel position based on the target arm joint angle and the force distribution on the target arm includes:

[0016] Obtain preset sequences of arm joint angles and arm force distribution;

[0017] Based on the preset sequence of arm joint angles, the preset sequence of arm force distribution, the target arm joint angles, and the target arm force distribution, a target optimization function is constructed.

[0018] The updated steering wheel position is obtained by solving the objective optimization function.

[0019] In one possible implementation, automatically adjusting the steering wheel according to the updated steering wheel position includes:

[0020] Generate and update adjustment commands corresponding to the steering wheel position, and send the adjustment commands to the electric adjustment mechanism connected to the steering wheel;

[0021] Control the electric adjustment mechanism to drive the steering wheel to the updated steering wheel position.

[0022] In one possible implementation, after automatically adjusting the steering wheel according to the updated steering wheel position, the automatic steering wheel adjustment method further includes:

[0023] If any of the target body parameters or target seat parameters of the target object change, collect the latest target body parameters, target seat parameters, and target steering wheel parameters of the target object;

[0024] Input the latest target body parameters, target seat parameters, and target steering wheel parameters of the target object into the arm force analysis model to obtain the latest target arm joint angles and target arm force distribution;

[0025] Adjust the steering wheel based on the latest target arm joint angle and force distribution.

[0026] Secondly, embodiments of this application provide an automatic steering wheel adjustment device, comprising:

[0027] The parameter acquisition module is used to acquire the target body parameters, target seat parameters, and target steering wheel parameters of the target object when driving a car; the target body parameters include the target object's arm length and sitting height, the target seat parameters include the seat position, and the target steering wheel parameters include the steering wheel position and steering wheel diameter.

[0028] The model analysis module is used to input the target body parameters, target seat parameters, and target steering wheel parameters into the arm force analysis model to obtain the target arm joint angles and the target arm force distribution;

[0029] The steering wheel adjustment module is used to determine the updated steering wheel position based on the target arm joint angle and the force distribution of the target arm, and automatically adjust the steering wheel according to the updated steering wheel position.

[0030] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0031] The memory stores the instructions that the computer executes;

[0032] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0033] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0034] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0035] The automatic steering wheel adjustment method, device, electronic device, computer-readable storage medium, and computer program product provided in this application first acquire the target body parameters, target seat parameters, and target steering wheel parameters of the target object while driving a car. The target body parameters include the target object's arm length and sitting height; the target seat parameters include the seat position; and the target steering wheel parameters include the steering wheel position and steering wheel diameter. Further, by inputting the target body parameters, target seat parameters, and target steering wheel parameters into an arm force analysis model, the target arm joint angles and the target arm force distribution are obtained. Based on the target arm joint angles and the target arm force distribution, the updated steering wheel position is determined, and the steering wheel is automatically adjusted according to the updated steering wheel position. Using the above process, the steering wheel position can be accurately adjusted by combining multiple factors, such as the target body parameters, target seat parameters, and target steering wheel parameters of the target object while driving a car. Attached Figure Description

[0036] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0037] Figure 1 A schematic diagram illustrating a scenario for the automatic steering wheel adjustment method provided in this application;

[0038] Figure 2 A flowchart illustrating the automatic steering wheel adjustment method provided in this application;

[0039] Figure 3 A schematic diagram of the process for solving and updating the steering wheel position based on the objective function provided in this application;

[0040] Figure 4 A schematic diagram of the automatic steering wheel adjustment device provided in this application;

[0041] Figure 5 A schematic diagram of the structure of the electronic device provided in this application.

[0042] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0043] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0044] The automatic steering wheel adjustment method provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, server 100 can be connected to control unit 201, camera 202, and sensor 203 in vehicle 200 via network communication. Based on this, server 100 can obtain target body parameters, target seat parameters, and target steering wheel parameters of the target object while driving the vehicle, using data collected by camera 202 and sensor 203. Specifically, the target body parameters include the target object's arm length and sitting height, the target seat parameters include seat position, and the target steering wheel parameters include steering wheel position and steering wheel diameter. Further, server 100 can input the target body parameters, target seat parameters, and target steering wheel parameters into an arm force analysis model deployed on server 100 to obtain the target arm joint angles and target arm force distribution. Then, based on the target arm joint angles and target arm force distribution, the updated steering wheel position is determined, and an adjustment command corresponding to the updated steering wheel position is generated. This adjustment command is sent to control unit 201, causing control unit 201 to automatically adjust the steering wheel according to the updated steering wheel position indicated by the adjustment command.

[0045] The server 100 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The control unit 201 can receive, integrate, and process instructions, and ultimately issue control commands to the vehicle's actuators to drive and adjust the steering wheel position. The sensor 203 may include a seat rail position sensor, a seat height motor encoder, and a seat back angle sensor. The seat rail position sensor can be a linear Hall sensor or a magnetic encoder, used to directly measure the longitudinal displacement of the seat relative to a fixed track on the vehicle body. The seat height motor encoder can be used to measure the vertical displacement of the seat. The seat back angle sensor can specifically be a rotary potentiometer, used to measure the angle between the backrest and the seat cushion.

[0046] In one embodiment, an automatic steering wheel adjustment method is provided. This embodiment uses the application of this automatic steering wheel adjustment method to server 100 as an example for illustration. Figure 2 As shown, the automatic steering wheel adjustment methods include:

[0047] Step 202: Obtain the target body parameters, target seat parameters, and target steering wheel parameters of the target object when driving a car.

[0048] Among them, the target body parameters include the target object's arm length and sitting height, the target seat parameters include the seat position, and the target steering wheel parameters include the steering wheel position and steering wheel diameter.

[0049] Optionally, the server can acquire high-definition images of the target object from multiple angles while driving using multiple cameras deployed at different angles inside the vehicle. The server can then process these high-definition images, for example, performing deep learning-based keypoint detection and 3D reconstruction, calculating the target object's body parameters while driving, and locating the steering wheel to determine the target steering wheel parameters. Simultaneously, the server can determine the target seat parameters based on data collected from seat rail position sensors, seat height motor encoders, and seat back angle sensors within the vehicle.

[0050] Specifically, the target's arm length can be defined as the straight-line distance from the center of shoulder joint rotation to the center of the metacarpal bone when the target is holding the steering wheel, in a standard driving posture. The target's seat height can be defined as the vertical distance from the seat reference point (usually the intersection of the seat cushion and backrest) to the highest point of the head when the target is seated in a standard posture with their back against the backrest and eyes looking forward.

[0051] For example, the number of cameras is at least two, which can be two wide-angle high-definition cameras, such as infrared cameras, RGB-D cameras, or depth cameras. In addition, at least one camera is installed on the side of the driver, with a field of view covering the upper half of the driver's side, and at least one camera is installed at the rearview mirror position, with a field of view covering the driver's front and the entire steering wheel area, and the image acquisition of different cameras is strictly synchronized at the same time.

[0052] Step 204: Input the target body parameters, target seat parameters, and target steering wheel parameters into the arm force analysis model to obtain the target arm joint angles and the target arm force distribution.

[0053] The arm force analysis model can be a data-driven machine learning regression model, which is a high-dimensional nonlinear mapping function trained using massive amounts of experimental data. Based on this, the arm force analysis model can output the appropriate arm joint angle and arm force distribution for a given driver, according to the input body parameters, seat parameters, and steering wheel parameters, so that the driver can achieve theoretical comfort while driving.

[0054] Optionally, the server can input the target body parameters, target seat parameters, and target steering wheel parameters of the target object into a pre-trained arm force analysis model to obtain the target arm joint angle and target arm force distribution output by the arm force analysis model.

[0055] For example, the arm force analysis model can be trained based on deep neural networks (DNN), gradient boosting decision trees (GBDT), or support vector regression (SVR).

[0056] Step 206: Determine the updated steering wheel position based on the target arm joint angle and the force distribution of the target arm, and automatically adjust the steering wheel according to the updated steering wheel position.

[0057] Optionally, based on the target arm joint angle and the force distribution of the target arm, the updated steering wheel position is determined, and an adjustment command corresponding to the updated steering wheel position is generated. The adjustment command is sent to the vehicle's control unit, so that the control unit controls the automatic adjustment of the steering wheel position according to the updated steering wheel position indicated by the adjustment command.

[0058] For example, the height and tilt angle of the steering wheel can be adjusted according to the updated steering wheel position to improve the driving comfort of the target.

[0059] The aforementioned automatic steering wheel adjustment method first acquires the target body parameters, target seat parameters, and target steering wheel parameters of the target object while driving a car. The target body parameters include the target object's arm length and sitting height; the target seat parameters include seat position; and the target steering wheel parameters include steering wheel position and steering wheel diameter. Further, by inputting the target body parameters, target seat parameters, and target steering wheel parameters into an arm force analysis model, the target arm joint angles and the target arm force distribution are obtained. Based on these target arm joint angles and the target arm force distribution, the updated steering wheel position is determined, and the steering wheel is automatically adjusted accordingly. Using this process, multiple factors, such as the target object's target body parameters, target seat parameters, and target steering wheel parameters while driving a car, can be combined to accurately adjust the steering wheel.

[0060] In one possible implementation, the force analysis model for the arm is constructed in the following manner:

[0061] Acquire body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution of multiple test subjects when driving a car at different steering wheel positions;

[0062] By taking body parameters, seat parameters, and steering wheel parameters as inputs, and taking arm joint angles and arm force distribution as outputs, an arm force analysis model is trained.

[0063] The height and arm length of the test subjects varied to ensure that the arm force analysis model could cover the diversity of real drivers. Furthermore, when acquiring data from multiple test subjects, different driving scenarios could be selected for collection, and the data collection was synchronized to ensure that data such as body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution could be strictly correlated through timestamps.

[0064] Optionally, to obtain sufficient input-output sample pairs for model training, the server can use cameras and sensors in the car to collect and acquire body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution of multiple test subjects while driving the car at different steering wheel positions. Furthermore, the server can use body parameters, seat parameters, and steering wheel parameters as inputs, and arm joint angles and arm force distribution as outputs to construct input-output sample pairs. This allows the model to learn from a large number of known input-output sample pairs during the training phase, establishing a complex relationship from geometric space to biomechanical space, thereby training an arm force analysis model.

[0065] Specifically, during the sample collection phase, the arm joint angles of the test subject are acquired using the following method: After the test subject maintains a natural grip on the steering wheel as instructed, an optical motion capture system (such as Vicon or OptiTrack) can be deployed inside the car, and reflective markers are affixed to key bony landmarks such as the acromion, lateral epicondyle of the elbow, and radial styloid process of the wrist. The three-dimensional coordinates of these markers are captured at a high frequency (e.g., 100Hz), and precise joint angle data, such as shoulder flexion / extension angle, abduction / adduction angle, internal / external rotation angle, and elbow flexion angle, are directly calculated using biomechanical modeling software (such as Visual3D).

[0066] Specifically, during the sample collection phase, the force distribution of the test subject's arms is collected in the following way: using a customized high-resolution pressure-sensing steering wheel cover, or a steering wheel with integrated sensors, the grip strength of the test subject's hands in key areas of the steering wheel and the palm contact pressure distribution map are measured.

[0067] For example, the parameter table of the test object is shown in Table 1. Table 1 shows the body parameters (seat height and arm length), seat parameters (seat position), steering wheel parameters (steering wheel diameter and steering wheel position), arm joint angles, and arm force distribution of the test object (driver 1) at different steering wheel positions.

[0068] Table 1 Parameter table of the object to be tested

[0069]

[0070] In the above embodiments, an arm force analysis model can be trained using a large number of sample pairs to output arm joint angles and arm force distribution based on the driver's body parameters, seat parameters, and steering wheel parameters.

[0071] In one possible implementation, the automatic steering wheel adjustment method further includes:

[0072] When a new test subject is driving a car, the body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution are obtained at different steering wheel positions;

[0073] Based on the new test subject's body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution, optimize the arm force analysis model.

[0074] Optionally, when a new test subject is obtained driving a car, the server can construct new sample pairs based on the body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution at different steering wheel positions. If the amount of data in the new sample pairs reaches the preset amount of data, the server can optimize the arm force analysis model based on the new sample pairs.

[0075] Specifically, the server can incrementally train or fine-tune the original arm force analysis model based on new "input-output" samples consisting of the new body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution of the new test subject, in order to optimize the arm force analysis model, and then use the optimized arm force analysis model to cover the original arm force analysis model.

[0076] For example, a new sample pair can specifically be: [arm joint angle, arm force distribution] = f (steering wheel diameter, steering wheel position, seat height, arm length, seat position).

[0077] For example, the server can use transfer learning technology to keep the backbone network of the original arm force analysis model unchanged and only retrain some layers, so that it can learn the mapping relationship reflected in the new data that is not fully covered by the old samples while retaining the original knowledge, thus obtaining an optimized arm force analysis model.

[0078] It should be noted that the optimized arm force analysis model not only overwrites the original arm force analysis model on the server, but can also be pushed to the control units of all vehicles connected to the server for storage and local deployment. In the event of network communication failure, the vehicle's control unit can automatically adjust the steering wheel position (height and tilt angle) based on the locally deployed arm force analysis model, improving driver comfort when using the steering wheel.

[0079] In the above embodiments, personalized human-machine engineering adaptation can be achieved by optimizing the model and keeping pace with the times, thereby continuously improving driving comfort and safety in long-term use.

[0080] In one possible implementation, determining the updated steering wheel position based on the target arm joint angle and the force distribution on the target arm includes:

[0081] Obtain preset sequences of arm joint angles and arm force distribution;

[0082] Based on the preset sequence of arm joint angles, the preset sequence of arm force distribution, the target arm joint angles, and the target arm force distribution, a target optimization function is constructed.

[0083] The updated steering wheel position is obtained by solving the objective optimization function.

[0084] The preset sequences for arm joint angles and arm force distributions are stored on the server. The preset sequences for arm joint angles include several commonly used arm joint angles, and the preset sequences for arm force distributions include several commonly used arm force distributions. The arm joint angles in the preset sequences and the arm force distributions in the preset sequences can form combinations of (arm joint angles, arm force distributions). Each combination corresponds to a steering wheel position, and the correspondence between these (arm joint angles, arm force distributions) combinations and steering wheel positions can be constructed based on the comfort feedback from the test subject and ergonomic principles, with the aim of improving driver comfort.

[0085] Optionally, the server can obtain the preset sequence of arm joint angles and the preset sequence of arm force distribution from the stored data, and then construct the target optimization function based on the preset sequence of arm joint angles, the preset sequence of arm force distribution, the target arm joint angles, and the target arm force distribution:

[0086] J = min[k1 * (target arm joint angle - a certain arm joint angle in the preset sequence of arm joint angles) + k2 * (target arm force distribution - a certain arm force distribution in the preset sequence of arm force distributions)].

[0087] Where k1 and k2 are preset weighting coefficients, which can be flexibly configured according to the needs of actual application scenarios. When J is less than the preset difference value X, the optimal combination of the arm joint angle in the preset sequence of arm joint angles and the arm force distribution in the preset sequence of arm force distribution can be determined, and the steering wheel position indicated by this optimal combination is used as the solved updated steering wheel position.

[0088] For example, such as Figure 3 The diagram illustrates a process for solving the updated steering wheel position based on an objective function. When J is less than a preset difference value X, the updated steering wheel position can be determined. When J is greater than or equal to the preset difference value X, an optimization algorithm is used to select new arm joint angles from a preset sequence of arm joint angles and a new arm force distribution from a preset sequence of arm force distributions, and the solution continues. The optimization algorithms that can be used include, but are not limited to, swarm optimization algorithms and quadratic programming algorithms.

[0089] In the above embodiments, an objective function can be constructed, and the objective function and optimization algorithm can be used to solve for an updated steering wheel position that meets comfort requirements.

[0090] In one possible implementation, automatically adjusting the steering wheel according to the updated steering wheel position includes:

[0091] Generate and update adjustment commands corresponding to the steering wheel position, and send the adjustment commands to the electric adjustment mechanism connected to the steering wheel;

[0092] The electric adjustment mechanism drives the steering wheel to move vertically and / or horizontally to a new steering wheel position.

[0093] The electric adjustment mechanism can be equipped with a high-precision rotary encoder or Hall sensor, and can provide real-time feedback on the actual adjustment status of the electric adjustment mechanism to the vehicle's control unit.

[0094] Optionally, the server can generate an adjustment command corresponding to the updated steering wheel position and send the command to the vehicle's control unit. The control unit then transmits the command to the electric adjustment mechanism connected to the steering wheel. Based on this, under the control of the adjustment command, the electric adjustment mechanism can be controlled to move the steering wheel vertically and / or horizontally to the updated steering wheel position.

[0095] Specifically, the adjustment command can be in the following form: move the steering wheel backward (Y-axis) 20mm and upward (Z-axis) 10mm. Furthermore, before the electric adjustment mechanism reaches the position indicated by the adjustment command, it can switch to a low-speed fine-tuning mode to reduce steering wheel position adjustment errors.

[0096] For example, at the moment the server sends the adjustment command, a steering wheel icon and its animation can be displayed on the car's dashboard, and / or accompanied by a prompt sound, to inform the target object that "the steering wheel position adjustment is about to begin," and the target object can choose at any time whether to stop the automatic adjustment of the steering wheel position, and whether to manually adjust the steering wheel position.

[0097] In the above embodiments, the steering wheel position can be automatically adjusted, thereby improving driver comfort.

[0098] In one possible implementation, after automatically adjusting the steering wheel according to the updated steering wheel position, the automatic steering wheel adjustment method further includes:

[0099] If any of the target body parameters or target seat parameters of the target object change, collect the latest target body parameters, target seat parameters, and target steering wheel parameters of the target object;

[0100] Input the latest target body parameters, target seat parameters, and target steering wheel parameters of the target object into the arm force analysis model to obtain the latest target arm joint angles and target arm force distribution;

[0101] Adjust the steering wheel based on the latest target arm joint angle and force distribution.

[0102] Optionally, after the target vehicle starts, the server can periodically, or automatically, trigger a parameter collection and evaluation process for the target vehicle after a specific event occurs (such as detecting that the vehicle has started from a parked state). For example, it can detect whether there are any changes in any of the target vehicle's body parameters or seat parameters using cameras and sensors deployed in the vehicle. It should be noted that the target vehicle can choose to cancel automatic triggering at any time.

[0103] If any of the target body parameters or target seat parameters of the target object change, the server can obtain the latest target body parameters, target seat parameters, and target steering wheel parameters. Furthermore, the server can input these latest target body parameters, target seat parameters, and target steering wheel parameters into the arm force analysis model to obtain the latest target arm joint angles and target arm force distribution output by the arm force analysis model. Based on the latest target arm joint angles and target arm force distribution, the server can redetermine and update the steering wheel position, and then automatically adjust the steering wheel position accordingly.

[0104] In the above embodiments, the steering wheel position can be automatically adjusted by comprehensively considering the driver's seat height, arm length, seat position, steering wheel diameter, and steering wheel position, thereby improving the driving experience.

[0105] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0106] Based on the same inventive concept, this application also provides an automatic steering wheel adjustment device for implementing the above-described automatic steering wheel adjustment method. The solution provided by this automatic steering wheel adjustment device is similar to the solution described in the above-described automatic steering wheel adjustment method. Therefore, the specific limitations in one or more device embodiments provided below can be found in the limitations of the automatic steering wheel adjustment method described above, and will not be repeated here.

[0107] In one embodiment, such as Figure 4 As shown, an automatic steering wheel adjustment device 400 is provided, comprising:

[0108] The parameter acquisition module 402 is used to acquire the target body parameters, target seat parameters, and target steering wheel parameters of the target object when driving a car; the target body parameters include the target object's arm length and sitting height, the target seat parameters include the seat position, and the target steering wheel parameters include the steering wheel position and steering wheel diameter.

[0109] The model analysis module 404 is used to input the target body parameters, target seat parameters, and target steering wheel parameters into the arm force analysis model to obtain the target arm joint angles and the target arm force distribution.

[0110] The steering wheel adjustment module 406 is used to determine the updated steering wheel position based on the target arm joint angle and the force distribution of the target arm, and to automatically adjust the steering wheel according to the updated steering wheel position.

[0111] The aforementioned automatic steering wheel adjustment device acquires the target body parameters, target seat parameters, and target steering wheel parameters of the target object while driving a car. The target body parameters include the target object's arm length and sitting height; the target seat parameters include seat position; and the target steering wheel parameters include steering wheel position and steering wheel diameter. Furthermore, by inputting the target body parameters, target seat parameters, and target steering wheel parameters into an arm force analysis model, the target arm joint angles and the target arm force distribution are obtained. Based on these target arm joint angles and the target arm force distribution, the updated steering wheel position is determined, and the steering wheel is automatically adjusted accordingly. Using this process, multiple factors, such as the target object's body parameters, target seat parameters, and target steering wheel parameters while driving a car, can be combined to accurately adjust the steering wheel.

[0112] In one possible implementation, the automatic steering wheel adjustment device further includes a model building module, which is configured to:

[0113] Acquire body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution of multiple test subjects when driving a car at different steering wheel positions;

[0114] By taking body parameters, seat parameters, and steering wheel parameters as inputs, and taking arm joint angles and arm force distribution as outputs, an arm force analysis model is trained.

[0115] In one possible implementation, the automatic steering wheel adjustment device further includes:

[0116] The test object parameter update module is used to update the body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution of the test object when it is driving a car at different steering wheel positions.

[0117] The model optimization module is used to optimize the arm force analysis model based on the new body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution of the test subject.

[0118] In one possible implementation, the steering wheel adjustment module is configured as follows:

[0119] Obtain preset sequences of arm joint angles and arm force distribution;

[0120] Based on the preset sequence of arm joint angles, the preset sequence of arm force distribution, the target arm joint angles, and the target arm force distribution, a target optimization function is constructed.

[0121] The updated steering wheel position is obtained by solving the objective optimization function.

[0122] In one possible implementation, the steering wheel adjustment module is configured as follows:

[0123] Generate and update adjustment commands corresponding to the steering wheel position, and send the adjustment commands to the electric adjustment mechanism connected to the steering wheel;

[0124] The electric adjustment mechanism drives the steering wheel to move vertically and / or horizontally to a new steering wheel position.

[0125] In one possible implementation, the parameter acquisition module is further configured to: collect the latest target body parameters, target seat parameters, and target steering wheel parameters of the target object if any one of the target body parameters and target seat parameters of the target object changes;

[0126] The model analysis module is also configured to input the latest target body parameters, target seat parameters, and target steering wheel parameters of the target object into the arm force analysis model to obtain the latest target arm joint angles and target arm force distribution;

[0127] The steering wheel adjustment module is also configured to adjust the steering wheel based on the latest target arm joint angle and the force distribution of the target arm.

[0128] Each module in the above-mentioned device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0129] Figure 5 A schematic diagram of the structure of the electronic device provided in this application. Figure 5 As shown, the electronic device 500 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the electronic device 500 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus 504.

[0130] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0131] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0132] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0133] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0134] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0135] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0136] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0137] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0138] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0139] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0140] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0141] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0142] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0143] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0144] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for automatically adjusting a steering wheel, characterized in that, include: The system acquires the target body parameters, target seat parameters, and target steering wheel parameters of the target object while driving a car; the target body parameters include the target object's arm length and sitting height, the target seat parameters include the seat position, and the target steering wheel parameters include the steering wheel position and steering wheel diameter. Input the target body parameters, the target seat parameters, and the target steering wheel parameters into the arm force analysis model to obtain the target arm joint angles and the target arm force distribution; Based on the target arm joint angle and the force distribution of the target arm, the updated steering wheel position is determined, and the steering wheel is automatically adjusted according to the updated steering wheel position.

2. The method according to claim 1, characterized in that, The force analysis model for the arm is constructed in the following way: Acquire body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution of multiple test subjects when driving a car at different steering wheel positions; Using the body parameters, seat parameters, and steering wheel parameters as inputs, and the arm joint angles and arm force distribution as outputs, an arm force analysis model is trained.

3. The method according to claim 2, characterized in that, The method further includes: When a new test subject is driving a car, the body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution are obtained at different steering wheel positions; The arm force analysis model is optimized based on the new body parameters, seat parameters, steering wheel parameters, arm joint angles, and arm force distribution of the test subject.

4. The method according to claim 1, characterized in that, The step of determining and updating the steering wheel position based on the target arm joint angle and the force distribution of the target arm includes: Obtain preset sequences of arm joint angles and arm force distribution; Based on the preset sequence of arm joint angles, the preset sequence of arm force distribution, the target arm joint angles, and the target arm force distribution, a target optimization function is constructed; Based on the objective optimization function, the updated steering wheel position is solved.

5. The method according to claim 1, characterized in that, The step of automatically adjusting the steering wheel according to the updated steering wheel position includes: Generate an adjustment command corresponding to the updated steering wheel position, and send the adjustment command to the electric adjustment mechanism connected to the steering wheel; The electric adjustment mechanism is controlled to drive the steering wheel to the updated steering wheel position.

6. The method according to claim 1, characterized in that, After automatically adjusting the steering wheel according to the described updated steering wheel position, the method further includes: If any of the target body parameters or target seat parameters of the target object changes, the latest target body parameters, target seat parameters, and target steering wheel parameters of the target object shall be collected; The latest target body parameters, target seat parameters, and target steering wheel parameters of the target object are input into the arm force analysis model to obtain the latest target arm joint angles and target arm force distribution. The steering wheel is adjusted based on the latest target arm joint angle and the force distribution of the target arm.

7. An automatic steering wheel adjustment device, characterized in that, include: The parameter acquisition module is used to acquire the target body parameters, target seat parameters, and target steering wheel parameters of the target object when driving a car; the target body parameters include the target object's arm length and sitting height, the target seat parameters include the seat position, and the target steering wheel parameters include the steering wheel position and steering wheel diameter; The model analysis module is used to input the target body parameters, the target seat parameters, and the target steering wheel parameters into the arm force analysis model to obtain the target arm joint angles and the target arm force distribution; The steering wheel adjustment module is used to determine the updated steering wheel position based on the target arm joint angle and the force distribution of the target arm, and to automatically adjust the steering wheel according to the updated steering wheel position.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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