Steering assistance methods, devices, equipment and media for in-vehicle intelligent steering wheels

Abstract

This application discloses a steering assist method, device, equipment, and medium for an in-vehicle intelligent steering wheel. It involves acquiring first image data of the driver using an in-vehicle camera; determining the driver's identity information based on the first image data and obtaining a corresponding target steering assist value based on the identity information; recognizing the driver's actions based on the first image data; and providing steering assist based on the target steering assist value when the driver initiates a steering action. In this application's embodiments, users can set their own target steering assist value to meet personalized steering assist needs, significantly improving the user's actual driving experience. This application has wide applicability in the field of control technology.

Description

Technical Field

[0001] This application relates to the field of control technology, and in particular to steering assistance methods, devices, equipment and media for in-vehicle intelligent steering wheels. Background Technology

[0002] With societal progress and changing lifestyles, people's demands for automobiles are also increasing. For example, some current cars are equipped with power steering systems, which are systems designed to assist drivers in turning the steering wheel. By providing additional torque, it makes it easier for drivers to turn the steering wheel, thereby improving driving comfort and safety. A power steering system typically consists of an electric motor, steering gears, a steering column, and a power steering actuator. The electric motor drives the steering gears, causing the steering column to rotate, thus providing assistance. Power steering systems help drivers achieve effortless steering control.

[0003] In related technologies, the steering assist system of vehicles currently on the market is set to a fixed level. However, in reality, everyone's need for steering assistance is different. For example, male users, who are stronger, generally prefer less steering assistance, while female users, who are weaker, generally prefer more steering assistance. Current technical solutions cannot meet the personalized needs of users, resulting in a poor actual driving experience.

[0004] In summary, the problems existing in the relevant technologies urgently need to be solved. Summary of the Invention

[0005] The purpose of this application is to at least partially solve one of the technical problems existing in the related art.

[0006] Therefore, one objective of this application is to provide a steering assist method for an in-vehicle smart steering wheel that can meet the personalized needs of users and improve their driving experience.

[0007] Another objective of this application is to provide a steering assist device for an in-vehicle smart steering wheel.

[0008] To achieve the above-mentioned technical objectives, the technical solutions adopted in the embodiments of this application include:

[0009] On one hand, embodiments of this application provide a steering assist method for an in-vehicle intelligent steering wheel, the method comprising:

[0010] The driver's initial image data is captured via an in-vehicle camera;

[0011] Based on the first image data, the driver's identity information is determined, and the corresponding target steering assist value is obtained based on the identity information;

[0012] Based on the first image data, the driver's actions are identified;

[0013] When it is determined that the driver initiates a steering action, steering assistance is provided according to the target steering assistance value;

[0014] The target steering assist value is set in the following manner:

[0015] When the car is idling, it responds to the user's power assist selection simulation command and obtains the first power assist value input by the user.

[0016] Based on the first assist value, a second assist value is determined by measuring a first ratio; wherein, the first ratio is the ratio of the steering wheel rotation coefficient when the vehicle is idling to the steering wheel rotation coefficient when the vehicle is driving, and the rotation coefficient is the ratio of the force applied to the steering wheel to the rotation angle of the steering wheel.

[0017] Steering assistance is applied based on the second assistance value, and the process returns to the step of responding to the user's assistance selection simulation command and obtaining the first assistance value input by the user, until the user's assistance value determination command is received, and the current first assistance value is determined as the target steering assistance value corresponding to the user.

[0018] In addition, the steering assist method of the in-vehicle intelligent steering wheel according to the above embodiments of this application may also have the following additional technical features:

[0019] Furthermore, in one embodiment of this application, the target steering assist value is set in the following manner:

[0020] The system collects a second image data of the user using an in-vehicle camera, and recommends a third assist value to the user based on the second image data.

[0021] In response to the user's instruction to determine the assist value, the third assist value is determined as the target steering assist value corresponding to the user.

[0022] Furthermore, in one embodiment of this application, the step of collecting second image data of the user through an in-vehicle camera and recommending a third assist value to the user based on the second image data includes:

[0023] Based on the second image data, the user's gender information is identified;

[0024] Based on the gender information, a third assist value is recommended to the user.

[0025] Furthermore, in one embodiment of this application, the step of collecting second image data of the user through an in-vehicle camera and recommending a third assist value to the user based on the second image data includes:

[0026] Based on the second image data, the user's historical operation records are identified;

[0027] Based on the steering operation records in the historical operation log, a third assist value is recommended to the user.

[0028] Furthermore, in one embodiment of this application, the response to the user's assisted selection simulation command includes:

[0029] The user's power assistance selection simulation command is received through a terminal device, or through the vehicle's central control screen.

[0030] Respond to the simulated instruction for assist selection.

[0031] Furthermore, in one embodiment of this application, the method further includes:

[0032] Detect whether the first assist value is within a preset range;

[0033] If the first assist value is not within the preset range, a reminder message is output; the reminder message is used to inform the user to reset the first assist value.

[0034] On the other hand, embodiments of this application provide a steering assist device for an in-vehicle smart steering wheel, comprising:

[0035] The acquisition unit is used to acquire the driver's first image data through the vehicle-mounted camera;

[0036] The acquisition unit is used to determine the driver's identity information based on the first image data, and to obtain the corresponding target steering assist value based on the identity information;

[0037] The recognition unit is used to recognize the driver's actions based on the first image data;

[0038] The power steering unit is used to provide steering assistance according to the target steering assistance value when it is determined that the driver has initiated a steering action.

[0039] A first setting unit, the first setting unit being used for:

[0040] When the car is idling, it responds to the user's power assist selection simulation command and obtains the first power assist value input by the user.

[0041] Based on the first assist value, a second assist value is determined by measuring a first ratio; wherein, the first ratio is the ratio of the steering wheel rotation coefficient when the vehicle is idling to the steering wheel rotation coefficient when the vehicle is driving, and the rotation coefficient is the ratio of the force applied to the steering wheel to the rotation angle of the steering wheel.

[0042] Steering assistance is applied based on the second assistance value, and the process returns to the step of responding to the user's assistance selection simulation command and obtaining the first assistance value input by the user, until the user's assistance value determination command is received, and the current first assistance value is determined as the target steering assistance value corresponding to the user.

[0043] Furthermore, in one embodiment of this application, the device further includes a second setting unit, the second setting unit being used for:

[0044] The system collects a second image data of the user using an in-vehicle camera, and recommends a third assist value to the user based on the second image data.

[0045] In response to the user's instruction to determine the assist value, the third assist value is determined as the target steering assist value corresponding to the user.

[0046] On the other hand, embodiments of this application provide an electronic device, including:

[0047] At least one processor;

[0048] At least one memory for storing at least one program;

[0049] When the at least one program is executed by the at least one processor, the at least one processor implements the steering assist method of the in-vehicle intelligent steering wheel as described in the first aspect.

[0050] On the other hand, embodiments of this application also provide a computer-readable storage medium storing a processor-executable program, which, when executed by a processor, is used to implement the steering assistance method of the in-vehicle intelligent steering wheel described in the first aspect.

[0051] The advantages and beneficial effects of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application:

[0052] This application provides a steering assist method, device, equipment, and medium for an in-vehicle smart steering wheel. It acquires first image data of the driver using an in-vehicle camera; determines the driver's identity information based on the first image data, and obtains a corresponding target steering assist value based on the identity information; identifies the driver's actions based on the first image data; and provides steering assist based on the target steering assist value when the driver initiates a steering action. This application allows users to set their own target steering assist value, thereby meeting personalized steering assist needs and significantly improving the user's actual driving experience. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following description is provided with accompanying drawings of the relevant technical solutions in the embodiments of this application or the prior art. It should be understood that the accompanying drawings described below are only for the purpose of clearly illustrating some embodiments of the technical solutions in this application. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0054] Figure 1 This is a schematic diagram illustrating the implementation environment of a steering assist method for an in-vehicle intelligent steering wheel provided in this application embodiment;

[0055] Figure 2 This is a flowchart illustrating a steering assist method for an in-vehicle smart steering wheel provided in an embodiment of this application.

[0056] Figure 3 This is a schematic diagram of the steering assist device of an in-vehicle smart steering wheel provided in the embodiments of this application;

[0057] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0058] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application. The step numbers in the following embodiments are set only for ease of explanation, and there is no limitation on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0060] 1) Artificial Intelligence (AI) is the theory, methods, technology, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to achieve optimal results. In other words, AI is a comprehensive technology within computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can react in a way similar to human intelligence. AI studies the design principles and implementation methods of various intelligent machines, enabling them to have perception, reasoning, and decision-making capabilities. AI technology is a comprehensive discipline involving a wide range of fields, encompassing both hardware and software technologies. Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operating / interactive systems, and mechatronics. AI software technologies mainly include computer vision, speech processing, natural language processing, and machine learning / deep learning.

[0061] 2) Machine Learning (ML) is a multidisciplinary field involving probability theory, statistics, approximation theory, convex analysis, and algorithm complexity theory. It specifically studies how computers can simulate or implement human learning behavior to acquire new knowledge or skills and reorganize existing knowledge structures to continuously improve their performance. Machine learning is the core of artificial intelligence and the fundamental way to endow computers with intelligence. Its applications span all areas of artificial intelligence. Machine learning (deep learning) typically includes techniques such as artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and instructional learning.

[0062] 3) Image recognition, a computer vision technology, uses algorithms and models to identify and understand the content in images. Image recognition typically includes tasks such as image classification, object detection, image segmentation, and image recognition. The goal of image recognition is to enable computers to understand and interpret the content in images like humans, thereby achieving automated image processing and analysis. Image recognition technology has wide applications in many fields, including autonomous driving, medical diagnosis, security monitoring, and image search.

[0063] With the progress of society and the change of lifestyle, people's requirements for cars are also getting higher and higher. For example, some current cars are equipped with an automotive power steering system, which is a system used to assist the driver in turning the steering wheel. By providing additional torque, it enables the driver to turn the steering wheel more easily, thereby improving driving comfort and safety. The automotive power steering system usually consists of an electric motor, a steering gear, a steering column, a power steering booster, etc. The electric motor drives the steering gear, causing the steering column to rotate, thereby generating assistance. The automotive power steering system can help the driver achieve easy steering wheel control.

[0064] In the related art, for currently available vehicles on the market, the steering assistance set by the automotive power steering system is fixed. In fact, everyone's assistance needs when turning the steering wheel are different. For example, male users have greater strength and generally prefer less assistance when turning; while female users have less strength and generally prefer more assistance when turning. The current technical solutions are difficult to meet the personalized needs of users, resulting in a poor actual driving experience for users.

[0065] In view of this, in the embodiments of the present application, there are provided a method, device, equipment and medium for the steering assistance of an in-vehicle intelligent steering wheel. In the method of the embodiments of the present application, the platform public key of the intensive authentication platform is written into the factory firmware of the intelligent door lock, and the platform private key is only stored inside the intensive authentication platform and not外传. This can ensure that only legitimate terminal devices can obtain the one-time symmetric key used to communicate with the intelligent door lock through the intensive authentication platform, which can greatly improve the security of the intelligent door lock and improve the user experience.

[0066] Refer to Figure 1 [[ID=END]] Figure 1 shows a schematic diagram of the implementation environment of a method for the steering assistance of an in-vehicle intelligent steering wheel provided in the embodiments of the present application. In this implementation environment, the main software and hardware entities involved include a terminal device 110, a cloud platform 120, and a vehicle 130.

[0067] In the embodiments of the present application, relevant application programs can be installed in the terminal device 110. The application program can be software supporting the vehicle 130. Based on this application program, the terminal device 110 can communicate with the cloud platform 120 or the vehicle 130, transmit relevant instructions, and thus achieve the control of the vehicle 130. Of course, during communication, the legitimacy of the terminal device 110 needs to be verified. When the legitimacy authentication of the terminal device 110 passes, it can communicate with the cloud platform 120 or the vehicle 130 normally. The cloud platform 120 is a background server, which can be used to implement relevant data transmission and store information related to users or vehicles.

[0068] It should be noted that in the original text, "平台私钥仅在集约认证平台的内部保存不外传" has an incorrect character "外传". I have translated it as "外传" for now, but it might need to be corrected to a proper word in the actual context.The steering assist method for the in-vehicle smart steering wheel provided in this application embodiment can be implemented based on the interaction between the terminal device 110, the cloud platform 120, and the vehicle 130.

[0069] Specifically, in this embodiment, the user can use the terminal device 110 to set a target steering assist value. The cloud platform 120 can send the target steering assist value set by the user to the vehicle 130, which will store the target steering assist value and provide steering assistance based on the target steering assist value while driving.

[0070] The terminal device 110 in the above embodiments may include smartphones, tablets, laptops, desktop computers, smartwatches, and vehicle terminals, but is not limited to these.

[0071] The cloud platform 120 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0072] The vehicle 130 can use any product available on the market, and this application does not impose any restrictions on it.

[0073] Communication connections can be established between terminal device 110 and cloud platform 120, and between terminal device 110 and vehicle 130, via wireless or wired networks. These wireless or wired networks use standard communication technologies and / or protocols. The network can be the Internet or any other network, including but not limited to Local Area Networks (LANs), Metropolitan Area Networks (MANs), Wide Area Networks (WANs), mobile, wired or wireless networks, private networks, or any combination of virtual private networks. Furthermore, these hardware and software entities can use the same or different communication connection methods; this application does not impose specific limitations in this regard.

[0074] Of course, this is understandable. Figure 1 The implementation environment described in this application is only one of the optional application scenarios for the vehicle-mounted intelligent steering wheel steering assist method provided in this embodiment. The actual application is not fixed. Figure 1 The software and hardware environment shown.

[0075] Below, in conjunction with the aforementioned description of the implementation environment, a steering assist method for an in-vehicle intelligent steering wheel provided in this application embodiment will be introduced and explained.

[0076] Please refer to Figure 2 , Figure 2 This is a schematic diagram of a steering assist method for an in-vehicle smart steering wheel provided in an embodiment of this application. The steering assist method for the in-vehicle smart steering wheel specifically includes, but is not limited to:

[0077] Step 210: Acquire the first image data of the driver using the vehicle-mounted camera;

[0078] In this embodiment of the application, an in-vehicle camera can be installed inside the vehicle. The number of in-vehicle cameras can be one or more, and this application does not limit this. Specifically, the in-vehicle camera can be installed at the front, rear, or side of the vehicle to capture information such as the driver's facial expressions, eye contact, and gestures.

[0079] In this embodiment, the vehicle-mounted camera can automatically activate after the vehicle starts to capture initial image data of the driver. This initial image data can be used for functions such as identity recognition and motion recognition. For example, facial recognition technology can identify the driver, enabling driver authentication and behavior recording. Motion recognition technology can analyze the driver's behavior, enabling driver behavior analysis.

[0080] Step 220: Determine the driver's identity information based on the first image data, and obtain the corresponding target steering assist value based on the identity information;

[0081] In this step, the driver's identity information can be determined based on the first image data. Specifically, in this embodiment, image recognition technology can be used to detect the identity information. For example, the system can preprocess the first image data, including operations such as grayscale conversion, binarization, and denoising, to facilitate subsequent feature extraction. Then, feature extraction algorithms, such as Haar features, HOG features, and deep learning features, can be used to extract features related to the driver's identity from the first image data. These features may include the driver's facial features, body features, and clothing features. Finally, machine learning algorithms, such as support vector machines, decision trees, and neural networks, can be used to classify the extracted features, thereby determining the driver's identity information. In this embodiment, the specific algorithms and model structures used in this process are not limited and can be flexibly adjusted as needed.

[0082] In this step, after determining the driver's identity information, the corresponding target steering assist value can be obtained based on that information. Here, the target steering assist value can be used to set the level of steering assistance; it can be uniquely assigned to each user, thus providing personalized assistance to each driver and improving the driving experience. Specifically, in this embodiment, the target steering assist value can be obtained through database queries or API calls. For example, the correspondence between driver identity information and target steering assist values ​​can be pre-stored in a cloud platform database, allowing for direct database queries to retrieve the corresponding target steering assist value later.

[0083] Step 230: Based on the first image data, identify the driver's actions;

[0084] In this step, the driver's actions can be identified based on the first image data. This can be achieved through a relevant machine learning model. In image recognition, a machine learning model is an algorithm used to identify and understand image content. Machine learning models typically include supervised learning models, unsupervised learning models, and reinforcement learning models. A supervised learning model is a machine learning model that learns model parameters using a training dataset. In image recognition, supervised learning models are commonly used for image classification and object detection tasks. For example, support vector machines, decision trees, random forests, and neural networks are all commonly used supervised learning models. In this embodiment, a supervised learning model can be used as an action recognition model. The first image data is input into this model to obtain the driver's action recognition result.

[0085] Step 240: When it is determined that the driver initiates a steering action, steering assistance is provided according to the target steering assistance value.

[0086] In this step, when it is determined from the first image data that the driver initiates a steering action, steering assistance can be provided according to the target steering assistance value. Specifically, in this embodiment, the target steering assistance value can be configured into the vehicle's EPS (Electronic Power Steering) module. When the driver initiates a steering action, the EPS module can automatically provide additional torque according to the target steering assistance value, allowing the driver to turn the steering wheel more easily, thereby improving driving comfort and safety. In this embodiment, the specific structure of the EPS module is not limited.

[0087] In this embodiment of the application, the target steering assist value is set in the following manner:

[0088] When the car is idling, it responds to the user's power assist selection simulation command and obtains the first power assist value input by the user.

[0089] Based on the first assist value, a second assist value is determined by measuring a first ratio; wherein, the first ratio is the ratio of the steering wheel rotation coefficient when the vehicle is idling to the steering wheel rotation coefficient when the vehicle is driving, and the rotation coefficient is the ratio of the force applied to the steering wheel to the rotation angle of the steering wheel.

[0090] Steering assistance is applied based on the second assistance value, and the process returns to the step of responding to the user's assistance selection simulation command and obtaining the first assistance value input by the user, until the user's assistance value determination command is received, and the current first assistance value is determined as the target steering assistance value corresponding to the user.

[0091] In this embodiment, the target steering assist value can be set and adjusted by the user. Specifically, in this embodiment, when setting the target steering assist value, the user can start the car and then keep the car at idle. In this way, the car is stationary, and the user can also operate the steering wheel to feel whether the assistance is appropriate. The target steering assist value can be selected and set in a relatively safe manner.

[0092] In this embodiment, the user can trigger a power steering selection simulation command to enter the corresponding setting process. For example, in some embodiments, the user can set the target steering assist value through a terminal device; in other embodiments, the user can also set the target steering assist value through the car's central control screen. Here, both the terminal device and the car's central control screen can receive and respond to the power steering selection simulation command. The user can input an assist value in the terminal device or the car's central control screen. This assist value can be set by the user according to their actual needs and is denoted as the first assist value. Then, the second assist value can be determined based on a measured first ratio. Here, the first ratio is the ratio of the steering wheel rotation coefficient when the car is idling to the steering wheel rotation coefficient when the car is moving, and the rotation coefficient is the ratio of the force applied to the steering wheel to the steering wheel rotation angle.

[0093] It should be noted that in this embodiment of the application, when the user makes settings using a terminal device, the corresponding data can be transmitted to the cloud platform, and then the cloud platform can transmit the data to the car, thereby transmitting the set assist value to the car to perform steering assist.

[0094] It is understandable that, under normal circumstances, the force applied to the steering wheel and the steering wheel rotation angle are different when the car is idling and driving. That is, the difficulty of steering wheel operation differs between the two states. Therefore, in this embodiment, a first ratio is used to adaptively correct the simulated steering assist value to obtain a second steering assist value. This second assist value is the steering assist output converted to the idling state. Then, the steering assist output is made according to the second assist value. The user can operate the steering wheel to turn left or right to feel whether the currently set value is appropriate. If it is found to be too high or too low, causing discomfort, the user can return and re-trigger the steering assist selection simulation command to set a new first assist value. If the user finds the set first assist value appropriate, a steering assist value confirmation command can be triggered. At this time, the currently set first assist value will be determined as the target steering assist value corresponding to the user.

[0095] It is understood that, in this embodiment of the application, users can set their own target steering assist value to meet personalized steering assist needs, which can greatly improve the user's actual driving experience.

[0096] In some embodiments, the target steering assist value is further set in the following manner:

[0097] The system collects a second image data of the user using an in-vehicle camera, and recommends a third assist value to the user based on the second image data.

[0098] In response to the user's instruction to determine the assist value, the third assist value is determined as the target steering assist value corresponding to the user.

[0099] In this embodiment, the target steering assist value can also be set through system recommendation. For example, for each user, a second image data of the user can be collected through an in-vehicle camera, and then the user can be identified based on the second image data to recommend a third assist value. If the user confirms that the third assist value is appropriate, then the third assist value can be determined as the target steering assist value corresponding to the user. Exemplarily, in some embodiments, the user's gender information can be identified based on the second image data, and then a third assist value can be recommended to the user based on the gender information: if the user is male, a smaller third assist value can be determined; if the user is female, a larger third assist value can be determined. In some embodiments, the user's historical operation records can be identified based on the second image data. These historical operation records can be stored on a cloud platform and associated with the user's identity information. In this way, the system can combine the user's driving habits, such as the steering operation records in the historical operation records, to recommend a third assist value to the user. Specifically, for example, information such as the steering wheel rotation speed and time taken during the user's steering operation can be detected and compared with the average level. If it is lower than the average level, a larger third assist value can be recommended; if it is higher than the average level, a smaller third assist value can be recommended. In this embodiment of the application, the specific size of the third assist value is not limited.

[0100] In some embodiments, the method further includes:

[0101] Detect whether the first assist value is within a preset range;

[0102] If the first assist value is not within the preset range, a reminder message is output; the reminder message is used to inform the user to reset the first assist value.

[0103] In this embodiment, the user-set assist value can be constrained to a range to prevent excessively high assist values ​​from causing safety accidents. After the user sets the first assist value, the system checks whether the first assist value is within the preset range. If the first assist value is within the preset range, the subsequent process can continue. If the first assist value is not within the preset range, a reminder message is output to inform the user to reset the first assist value.

[0104] Reference Figure 3 This application also provides a steering assist device for an in-vehicle smart steering wheel, the device comprising:

[0105] Acquisition unit 201 is used to acquire first image data of the driver through an in-vehicle camera;

[0106] The acquisition unit 202 is used to determine the driver's identity information based on the first image data, and to obtain the corresponding target steering assist value based on the identity information;

[0107] The recognition unit 203 is used to recognize the driver's actions based on the first image data;

[0108] The power steering unit 204 is used to provide steering assistance according to the target steering assistance value when it is determined that the driver has initiated a steering action;

[0109] The first setting unit 205 is used for:

[0110] When the car is idling, it responds to the user's power assist selection simulation command and obtains the first power assist value input by the user.

[0111] Based on the first assist value, a second assist value is determined by measuring a first ratio; wherein, the first ratio is the ratio of the steering wheel rotation coefficient when the vehicle is idling to the steering wheel rotation coefficient when the vehicle is driving, and the rotation coefficient is the ratio of the force applied to the steering wheel to the rotation angle of the steering wheel.

[0112] Steering assistance is applied based on the second assistance value, and the process returns to the step of responding to the user's assistance selection simulation command and obtaining the first assistance value input by the user, until the user's assistance value determination command is received, and the current first assistance value is determined as the target steering assistance value corresponding to the user.

[0113] Reference Figure 4 This application provides a computer device, including:

[0114] At least one processor 301;

[0115] At least one memory 302 is used to store at least one program;

[0116] When at least one program is executed by at least one processor 301, the at least one processor 301 implements a steering assist method for an in-vehicle smart steering wheel.

[0117] Similarly, the content of the above method embodiments is applicable to the computer device embodiments. The specific functions implemented by the computer device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0118] This application embodiment also provides a computer-readable storage medium storing a program executable by a processor 301, which, when executed by the processor 301, is used to perform the above-described vehicle-mounted intelligent steering wheel steering assistance method.

[0119] Similarly, the content of the above method embodiments is applicable to the present computer-readable storage medium embodiments. The specific functions implemented by the present computer-readable storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0120] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this application are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0121] Furthermore, although this application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding this application. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional technology for an engineer. Therefore, those skilled in the art can implement the application set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of this application, which is determined by the full scope of the appended claims and their equivalents.

[0122] 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 application, in essence, 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 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 application. 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.

[0123] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0124] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0125] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0126] In the foregoing description of this specification, the references to terms such as "one embodiment," "another embodiment," or "some embodiments," etc., indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0127] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

[0128] The above is a detailed description of the preferred embodiments of this application, but this application is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A steering assist method for an in-vehicle intelligent steering wheel, characterized in that, The method includes: The driver's first image data is captured by the vehicle's onboard camera; Based on the first image data, the driver's identity information is determined, and the corresponding target steering assist value is obtained based on the identity information; Based on the first image data, the driver's actions are identified; When it is determined that the driver initiates a steering action, steering assistance is provided according to the target steering assistance value; The target steering assist value is set in the following manner: When the car is idling, it responds to the user's power assist selection simulation command and obtains the first power assist value input by the user. Based on the first assist value, a second assist value is determined by measuring a first ratio; wherein, the first ratio is the ratio of the steering wheel rotation coefficient when the vehicle is idling to the steering wheel rotation coefficient when the vehicle is driving, and the rotation coefficient is the ratio of the force applied to the steering wheel to the rotation angle of the steering wheel. Steering assistance is applied based on the second assistance value, and the process returns to the step of responding to the user's assistance selection simulation command and obtaining the first assistance value input by the user, until the user's assistance value determination command is received, and the current first assistance value is determined as the target steering assistance value corresponding to the user.

2. The steering assist method for an in-vehicle intelligent steering wheel according to claim 1, characterized in that, The target steering assist value is also set in the following way: The system collects a second image data of the user using an in-vehicle camera, and recommends a third assist value to the user based on the second image data. In response to the user's instruction to determine the assist value, the third assist value is determined as the target steering assist value corresponding to the user.

3. The steering assist method for an in-vehicle intelligent steering wheel according to claim 2, characterized in that, The step of collecting second image data of the user through an in-vehicle camera and recommending a third assist value to the user based on the second image data includes: Based on the second image data, the user's gender information is identified; Based on the gender information, a third assist value is recommended to the user.

4. The steering assist method for an in-vehicle intelligent steering wheel according to claim 2, characterized in that, The step of collecting second image data of the user through an in-vehicle camera and recommending a third assist value to the user based on the second image data includes: Based on the second image data, the user's historical operation records are identified; Based on the steering operation records in the historical operation log, a third assist value is recommended to the user.

5. The steering assist method for an in-vehicle intelligent steering wheel according to claim 2, characterized in that, The response to the user's assisted selection simulation command includes: The user's power assistance selection simulation command is received through a terminal device, or through the vehicle's central control screen. Respond to the simulated instruction for assist selection.

6. The steering assist method for an in-vehicle intelligent steering wheel according to any one of claims 1-5, characterized in that, The method further includes: Detect whether the first assist value is within a preset range; If the first assist value is not within the preset range, a reminder message is output; the reminder message is used to inform the user to reset the first assist value.

7. A steering assist device for an in-vehicle intelligent steering wheel, characterized in that, include: The acquisition unit is used to acquire the driver's first image data through the vehicle-mounted camera; The acquisition unit is used to determine the driver's identity information based on the first image data, and to obtain the corresponding target steering assist value based on the identity information; The recognition unit is used to recognize the driver's actions based on the first image data; The power steering unit is used to provide steering assistance according to the target steering assistance value when it is determined that the driver has initiated a steering action. A first setting unit, the first setting unit being used for: When the car is idling, it responds to the user's power assist selection simulation command and obtains the first power assist value input by the user. Based on the first assist value, a second assist value is determined by measuring a first ratio; wherein, the first ratio is the ratio of the steering wheel rotation coefficient when the vehicle is idling to the steering wheel rotation coefficient when the vehicle is driving, and the rotation coefficient is the ratio of the force applied to the steering wheel to the rotation angle of the steering wheel. Steering assistance is applied based on the second assistance value, and the process returns to the step of responding to the user's assistance selection simulation command and obtaining the first assistance value input by the user, until the user's assistance value determination command is received, and the current first assistance value is determined as the target steering assistance value corresponding to the user.

8. The steering assist device for an in-vehicle intelligent steering wheel according to claim 7, characterized in that, The device further includes a second setting unit, the second setting unit being used for: The system collects a second image data of the user using an in-vehicle camera, and recommends a third assist value to the user based on the second image data. In response to the user's instruction to determine the assist value, the third assist value is determined as the target steering assist value corresponding to the user.

9. An electronic device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the steering assist method for an in-vehicle smart steering wheel as described in any one of claims 1-6.

10. A computer-readable storage medium storing a processor-executable program, characterized in that: The processor-executable program, when executed by the processor, is used to implement the steering assistance method of the in-vehicle smart steering wheel as described in any one of claims 1-6.

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