Vehicle armrest intelligent interaction system and method and vehicle armrest manufacturing method

Abstract

The invention provides a vehicle armrest intelligent interaction system and method and a vehicle armrest manufacturing method. The vehicle armrest intelligent interaction system comprises an armrest body; the sensor array is embedded below the surface layer material of the armrest body and used for detecting hand actions of a user to generate gesture signals, and the gesture signals at least comprise action position information, dynamic track information and contact pressure information; the vehicle-mounted bus interface is used for establishing data connection with a vehicle-mounted bus of a vehicle and acquiring real-time running parameters of the vehicle; the control device is electrically connected with the sensor array and the vehicle-mounted bus interface, and the control device is configured to receive gesture signals output by the sensor array and vehicle real-time operation parameters transmitted by the vehicle-mounted bus interface, call an embedded machine learning model to carry out fusion analysis on the gesture signals and the vehicle real-time operation parameters, and send the gesture signals and the vehicle real-time operation parameters to the vehicle-mounted bus interface; and generating a prediction instruction matched with the user intention according to the analysis result, and executing the prediction instruction.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle cockpit human-machine interaction technology, and in particular to a vehicle handrail intelligent interaction system, method and vehicle handrail manufacturing method. Background Technology

[0002] With the continuous improvement of automotive intelligence, the comfort and technological experience of rear passengers have become one of the core indicators for measuring the luxury of a vehicle. Currently, rear passengers have increasingly frequent demands for controlling functions such as in-vehicle air conditioning and entertainment systems, but existing control methods still have many problems that urgently need to be solved.

[0003] In existing technologies, related solutions mainly fall into two categories. One relies on a separate touchpad to control the screen cursor or implement fixed gesture commands. This is only applicable to screen-related operations, and blind operation of high-frequency functions (such as volume and temperature adjustment) is cumbersome, lacks tactile feedback, and users cannot confirm the validity of the operation. The separate hardware module also disrupts the integrated interior design. The other requires a physical button to wake up the device and then receives gestures through a scanner. This involves multiple steps and poor intuitiveness. The simultaneous installation of a visible interface and scanner creates a fragmented hardware structure, affecting the aesthetics of the interior and lacking multi-mode switching capabilities and intelligent context judgment, resulting in rigid interaction logic.

[0004] In summary, existing technologies suffer from problems such as fragmented interaction logic, lack of blind operation experience, design and function conflicts, and insufficient intelligence, failing to meet the modern automotive demand for efficient, user-friendly, and hidden interaction. Summary of the Invention

[0005] This disclosure aims to solve at least one of the technical problems existing in the prior art, and proposes a vehicle handrail intelligent interactive system, method and vehicle handrail manufacturing method.

[0006] In a first aspect, embodiments of this disclosure provide a vehicle armrest intelligent interaction system, including:

[0007] The armrest itself;

[0008] A sensor array, embedded beneath the surface material of the handrail body, is used to detect the user's hand movements to generate gesture signals, the gesture signals including at least movement position information, dynamic trajectory information, and contact pressure information;

[0009] The vehicle bus interface is used to establish a data connection with the vehicle's onboard bus to obtain real-time operating parameters of the vehicle.

[0010] The control device is electrically connected to the sensor array and the vehicle bus interface, respectively. The control device is configured to: receive gesture signals output by the sensor array and real-time vehicle operating parameters transmitted by the vehicle bus interface; call an embedded machine learning model to perform fusion analysis on the gesture signals and the real-time vehicle operating parameters; generate a predictive command matching the user's intent based on the analysis results; and execute the predictive command.

[0011] In some embodiments, the control device has a built-in state management module, which is configured as follows:

[0012] In response to a first preset gesture input by the user, the system switches between at least two interaction modes, including a quick control mode for blind operation of high-frequency in-vehicle functions and a screen linkage mode for precise control of the in-vehicle screen.

[0013] The first preset gesture is a double-tap, long press, or swipe gesture along a specific trajectory.

[0014] In some embodiments, a feedback module is also included, the feedback module comprising at least one linear vibration motor;

[0015] The linear vibration motor is embedded below the sensor array and is electrically connected to the control device;

[0016] After executing the prediction command, the control device drives the linear vibration motor to generate vibration feedback at the hand movement position corresponding to the gesture signal. The intensity or frequency of the vibration feedback is related to the type of prediction command.

[0017] In some embodiments, the real-time vehicle operating parameters include at least two of the following: the on / off status of the rear display screen, the current display interface type of the rear display screen, the playback status of the in-vehicle media, the current vehicle speed, the current vehicle gear information, and the operating parameters of the in-vehicle air conditioning.

[0018] In some embodiments, the control device is further configured to:

[0019] The validity of the gesture signal is determined before the machine learning model is invoked;

[0020] The validity determination is based on at least two of the parameters in the gesture signal: contact duration, contact area, and pressure change rate. When the contact duration is within a preset duration range, the contact area is within a preset area range, and the pressure change rate meets a preset threshold condition, the gesture signal is determined to be a valid control signal; otherwise, it is determined to be an unconscious leaning signal and ignored.

[0021] Secondly, embodiments of this disclosure provide a smart interaction method for vehicle handrails, the method comprising:

[0022] By using a sensor array embedded under the upper material of the vehicle's armrest watch, the user's hand movements are detected in real time, generating gesture signals that include the position of the movement, dynamic trajectory, and contact pressure.

[0023] Data interaction is established with the vehicle bus via the vehicle bus interface to obtain real-time vehicle operating parameters;

[0024] The validity of the gesture signals is determined, and valid gesture signals are filtered out.

[0025] The valid gesture signal and the real-time operating parameters of the vehicle are input into a preset machine learning model. The machine learning model performs fusion calculations on the input information and outputs a predicted instruction that matches the user's intention.

[0026] The predicted instructions are executed to control the corresponding vehicle functions.

[0027] In some embodiments, after executing the prediction instruction, the method further includes:

[0028] A linear vibration motor embedded below the sensor array is driven to generate vibration feedback at the hand movement position corresponding to the gesture signal;

[0029] When the prediction command is an interactive mode switching command, the vibration feedback is two consecutive short vibrations.

[0030] When the predicted command is an in-vehicle function adjustment command, the vibration feedback is a single, short vibration.

[0031] In some embodiments, the method further includes:

[0032] When a user's first preset gesture is detected, the current interaction mode is switched; the interaction mode includes at least a quick control mode and a screen linkage mode.

[0033] In quick control mode, the predicted commands output by the machine learning model are directly associated with volume adjustment, temperature adjustment, or media playback start / stop control.

[0034] In screen linkage mode, the prediction instructions output by the machine learning model are associated with screen cursor movement, interface element clicks, or page switching controls.

[0035] In some embodiments, the step of determining the validity of the gesture signal and filtering valid gesture signals includes:

[0036] Extract the contact duration, contact area, and pressure change rate parameters from the gesture signal; if the contact duration is ≤3s, the contact area is ≤1 / 5 of the preset wristwatch area, and the pressure change rate is ≥0.5N / s, then the gesture signal is determined to be a valid gesture signal; otherwise, it is determined to be an unconscious leaning signal and ignored.

[0037] Thirdly, this disclosure provides a method for manufacturing a vehicle handrail, the method comprising:

[0038] The frame of the vehicle handrail is foamed and molded to obtain a handrail frame of a preset shape.

[0039] On the surface of the preset installation area of ​​the handrail frame, a flexible sensor film and a linear vibration motor are fixed respectively by an adhesive layer, ensuring that the linear vibration motor is located directly below the flexible sensor film and that the positions correspond one-to-one.

[0040] The lead wire of the flexible sensor film is led out through the preset wire harness channel inside the handrail frame and electrically connected to the signal input terminal of the preset control device.

[0041] The handrail frame, flexible sensor film, and linear vibration motor are completely covered with a surface material made of leather or fabric, making the flexible sensor film and linear vibration motor completely invisible from the outside of the handrail, and the surface of the covered material has no obvious protrusions or gaps.

[0042] Fourthly, embodiments of this disclosure provide an electronic device, including:

[0043] One or more processors;

[0044] Memory, used to store one or more programs;

[0045] When one or more programs are executed by one or more processors, the one or more processors implement the intelligent interaction method for vehicle handrails provided in the second aspect and / or the manufacturing method for vehicle handrails provided in the third aspect.

[0046] Fourthly, embodiments of this disclosure provide a computer-readable medium storing a computer program, which, when executed by a processor, implements the intelligent interaction method for vehicle handrails provided in the second aspect and / or the vehicle handrail manufacturing method provided in the third aspect.

[0047] The intelligent interactive system for vehicle armrests provided in this disclosure achieves the core function of transforming a physical armrest into an intelligent interactive surface through the collaborative work of the armrest body, sensor array, vehicle bus interface, and control device. The sensor array collects multi-dimensional gesture signals, the vehicle bus interface provides contextual data, and the control device integrates and analyzes the data to generate predictive commands. This architecture solves the problem of single interaction dimensions in existing technologies, achieving seamless integration of interactive functions with the vehicle interior. Through the collaborative work of multiple modules, it overcomes the limitations of hardware form and interaction logic defects in existing technologies, providing a complete system solution that balances design aesthetics, interaction efficiency, and user experience, and realizing integrated interaction with intelligent prediction, multi-mode switching, and accurate feedback. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the structure of a vehicle handrail intelligent interactive system provided in an embodiment of the present disclosure;

[0049] Figure 2 A schematic diagram of another intelligent interactive system for vehicle handrails provided in this embodiment of the present disclosure.

[0050] Figure 3 This is a flowchart illustrating an intelligent interactive system for vehicle handrails provided in an embodiment of the present disclosure.

[0051] Figure 4 A flowchart illustrating another intelligent interactive system for vehicle handrails provided in this embodiment of the present disclosure;

[0052] Figure 5 A schematic flowchart illustrating a method for manufacturing a vehicle handrail according to an embodiment of this disclosure;

[0053] Figure 6 This is a structural block diagram of an electronic device provided in an embodiment of the present disclosure. Detailed Implementation

[0054] To enable those skilled in the art to better understand the technical solutions of this disclosure, exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments of this disclosure to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0055] Where there is no conflict, the various embodiments of this disclosure and the features thereof in the embodiments may be combined with each other.

[0056] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0057] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Words such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0058] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and this disclosure, and will not be interpreted as having an idealized or overly formal meaning, unless expressly so defined herein.

[0059] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information in this technical solution comply with relevant laws and regulations and do not violate public order and good morals. The use of user data in this technical solution follows relevant national laws and regulations (e.g., the "Information Security Technology - Personal Information Security Specification"). For example, appropriate measures are taken for personal information access control; restrictions are imposed on the display of personal information; the purpose of using personal information does not exceed the scope of direct or reasonable association; and explicit identity targeting is eliminated when using personal information to avoid precisely identifying specific individuals.

[0060] With the rapid development of automotive intelligence and electrification, the comfort and technological experience of rear passengers have become important indicators for measuring a vehicle's luxury. Currently, rear passengers' control over functions such as air conditioning, entertainment systems, and seat adjustments mainly relies on the following two technological approaches:

[0061] Firstly, some vehicle models integrate independent touch control devices on the rear armrests, such as the technical solution disclosed in CN218839198U. This solution installs a touchpad module with clearly defined physical boundaries on the armrest, connecting to the in-vehicle entertainment system via USB or Bluetooth. Passengers can control the movement of the screen cursor or execute preset fixed gesture commands by operating this device. However, this technology has fundamental flaws: Firstly, the interaction dimension is limited, essentially serving as a remote pointer device capable only of screen-related operations. It cannot handle the rapid blind operation of high-frequency in-vehicle functions such as volume adjustment and temperature control, lacking a unified architecture for both "shortcut key" and "touchpad" modes. Secondly, it completely lacks a tactile feedback mechanism, leaving users without physical confirmation during blind operation, severely impacting the reliability of the interaction due to operational uncertainty. Thirdly, the hardware form contradicts the design philosophy, with the visible independent module disrupting the integrated aesthetics of the interior.

[0062] Secondly, another technical approach, as disclosed in CN115793857A, involves installing a user interface with physical buttons and a gesture scanner on the rear armrest. Users must first activate the device using the physical buttons, and then the scanner receives their gestures. This technology also has significant drawbacks: cumbersome operation, violating the principle of intuitive interaction; fragmented hardware form, with visible buttons and scanners coexisting, disrupting the overall aesthetic of the interior; lack of haptic feedback; and rigid interaction logic, unable to dynamically adjust command mappings based on vehicle status and lacking mode switching capabilities.

[0063] The aforementioned existing technologies generally face deep-seated problems such as contradictory interaction logic, lack of user experience, limited design concepts, and a lack of interactive intelligence. Specifically, existing solutions cannot seamlessly unify rapid blind operation with precise screen control, lack a reliable feedback loop, still rely on visible hardware modules for function implementation, and have rigid and fixed instruction mappings, failing to perceive context and predict user intentions.

[0064] In order to solve at least one or more of the above-mentioned technical problems, this disclosure provides a vehicle armrest intelligent interaction system, which aims to solve the systemic problems of the interaction experience of rear passengers.

[0065] Figure 1 This is a schematic diagram of the structure of a vehicle handrail intelligent interaction system provided in an embodiment of the present disclosure. Figure 2 This is a schematic diagram of another intelligent interactive system for vehicle handrails provided in an embodiment of this disclosure, as shown below. Figure 1 , Figure 2 As shown, the system includes:

[0066] The handrail body 100; a sensor array 110, embedded under the surface material of the handrail body, is used to detect the user's hand movements to generate gesture signals, the gesture signals including at least movement position information, dynamic trajectory information, and contact pressure information; a vehicle bus interface, used to establish a data connection with the vehicle's vehicle bus to obtain real-time vehicle operating parameters; and a control device 120, electrically connected to both the sensor array and the vehicle bus interface, the control device being configured to: receive the gesture signals output by the sensor array and the real-time vehicle operating parameters transmitted by the vehicle bus interface, call the embedded machine learning model to perform fusion analysis on the gesture signals and the real-time vehicle operating parameters, generate a predicted command matching the user's intention based on the analysis results, and execute the predicted command.

[0067] The intelligent interactive system for vehicle armrests provided in this disclosure achieves the core function of transforming a physical armrest into an intelligent interactive surface through the collaborative work of the armrest body, sensor array, vehicle bus interface, and control device. The sensor array collects multi-dimensional gesture signals, the vehicle bus interface provides contextual data, and the control device integrates and analyzes the data to generate predictive commands. This architecture solves the problem of single interaction dimensions in existing technologies, achieving seamless integration of interactive functions with the vehicle interior. Through the collaborative work of multiple modules, it overcomes the limitations of hardware form and interaction logic defects in existing technologies, providing a complete system solution that balances design aesthetics, interaction efficiency, and user experience, and realizing integrated interaction with intelligent prediction, multi-mode switching, and accurate feedback.

[0068] Preferably, the sensor array is embedded beneath the surface material of the armrest body, using a flexible pressure sensor array or a capacitive sensor array, seamlessly integrated under interior materials such as leather, and completely invisible from the outside. This sensor array can detect the user's hand movements in real time, generating gesture signals containing movement position information, dynamic trajectory information, and contact pressure information. Compared to traditional touchpads, it has no physical boundary limitations, enabling wider-range and higher-precision gesture acquisition. The sensor array overcomes the limitations of visible hardware modules in existing technologies, achieving comprehensive gesture signal acquisition without compromising the aesthetics of the interior. This provides fundamental data support for subsequent interaction judgments, thereby achieving seamless integration of interactive functions and interior design. Simultaneously, the multi-dimensional gesture signals collected provide data assurance for accurately recognizing user intentions.

[0069] Sensor arrays are not limited to pressure sensors and capacitive sensor arrays. They determine touch location and gestures by detecting changes in capacitance caused by human touch, offering high sensitivity and cost advantages. Furthermore, infrared or ultrasonic sensor arrays can be used to achieve non-contact gesture recognition, expanding the dimensions of interaction. In addition to linear vibration motors, piezoelectric ceramic actuators can also be used in the feedback module to provide higher frequency and more nuanced tactile feedback.

[0070] It should be understood that the vehicle bus interface establishes a data connection with the vehicle's CAN bus or Ethernet bus to acquire vehicle operating parameters in real time. In some embodiments, the real-time vehicle operating parameters include at least two of the following: the on / off status of the rear-seat display, the current display interface type of the rear-seat display, the playback status of the in-vehicle media, the vehicle's current speed, the vehicle's current gear information, and the operating parameters of the in-vehicle air conditioning.

[0071] Acquiring real-time vehicle status via the in-vehicle bus is key to achieving context awareness. This breaks away from the rigid pattern of fixed command mapping in existing technologies, allowing the system to adjust its interaction logic based on the actual vehicle status. It also provides rich contextual data input for subsequent machine learning models, making interaction decisions more aligned with actual user scenarios.

[0072] like Figure 1 , Figure 2 As shown, in some embodiments, the vehicle handrail intelligent interaction system provided in this disclosure also includes a feedback module 130, which includes at least one linear vibration motor 131. The linear vibration motor is embedded below the sensor array and is electrically connected to the control device. After executing the prediction command, the control device drives the linear vibration motor to generate vibration feedback at the hand movement position corresponding to the gesture signal. The intensity or frequency of the vibration feedback is related to the type of prediction command.

[0073] Preferably, the feedback module includes at least one linear vibration motor, which is embedded below the sensor array and electrically connected to the control device. When the control device executes a predicted command, it drives the linear vibration motor to generate vibration feedback at the hand movement position corresponding to the gesture signal. The vibration intensity or frequency is associated with the type of predicted command. This precise feedback design allows the user to directly perceive and confirm the operation position, eliminating the uncertainty of blind operation. When the predicted command is an interaction mode switching command, the vibration feedback is configured as two consecutive short vibrations; when the predicted command is an in-vehicle function adjustment command, it is configured as a single short vibration. This differentiated feedback encoding helps the user understand the operation result without visual input. In addition to the core tactile feedback, such as Figure 2 As shown, the multimodal feedback module may also optionally include a hidden indicator light 132 integrated in the armrest gap and a speaker 133 that emits sound through the vehicle audio system, providing optical and auditory auxiliary feedback to build a complete multi-channel confirmation mechanism.

[0074] In some embodiments, the control device has a built-in state management module, which is configured as follows:

[0075] In response to a first preset gesture input by the user, the system switches between at least two interaction modes, including a quick control mode for blind operation of high-frequency in-vehicle functions and a screen linkage mode for precise control of the in-vehicle screen; wherein the first preset gesture is a double-tap, long press, or swipe gesture along a specific trajectory.

[0076] Preferably, the state management module is implemented as an interactive state machine, switching between at least two interaction modes in response to a first preset gesture input by the user. The first preset gesture can be configured as a double-tap, long press, or a swipe gesture along a specific trajectory. This design allows users to complete mode switching through simple and intuitive actions without visually searching for physical buttons. The interaction modes include at least a quick control mode for blind operation of high-frequency in-vehicle functions and a screen linkage mode for precise control of the in-vehicle screen. In quick control mode, the predicted commands output by the machine learning model are directly associated with volume adjustment, temperature adjustment, or media playback start / stop control, allowing users to complete common operations without looking at the screen. In screen linkage mode, the predicted commands are associated with screen cursor movement, interface element clicks, or page switching control, achieving deep interaction. This mode switching mechanism solves the contradiction of a single interaction dimension in existing technologies, giving the same interactive surface a dual identity, balancing efficiency and functional depth.

[0077] In some embodiments, the control device is further configured to:

[0078] Before calling the machine learning model, the validity of the gesture signal is judged. The validity judgment is based on at least two of the parameters in the gesture signal, namely the contact duration, contact area and pressure change rate. When the contact duration is within the preset duration range, the contact area is within the preset area range and the pressure change rate meets the preset threshold condition, the gesture signal is judged as a valid control signal; otherwise, it is judged as an unconscious leaning signal and ignored.

[0079] As a preferred embodiment, a gesture signal is considered valid if the contact duration does not exceed 3 seconds, the contact area does not exceed 1 / 5 of the preset wristwatch area, and the pressure change rate is not less than 0.5 N / s. This multi-dimensional comprehensive analysis mechanism distinguishes between unconscious leaning and conscious control from three levels: temporal characteristics, spatial characteristics, and pressure profile, significantly reducing the false touch rate and improving the reliability of interaction.

[0080] Furthermore, in some embodiments, the context awareness and dynamic command mapping mechanism is implemented through a machine learning prediction model. The control device acquires key vehicle status information in real time via the vehicle bus, combines it with the recognized gesture type to form contextual and behavioral feature vectors, and inputs them into a preset machine learning model. This model is trained during the development phase by collecting a large amount of real user interaction data and adopts a decision tree, gradient boosting machine, or lightweight neural network architecture. In actual operation, the model performs real-time calculations on the input vector and outputs the probability distribution of each candidate command. The control device selects the command with the highest probability for execution. For example, when the input vector is a gesture of "double-tap" and the screen status is "play video," the model predicts that the probability of the "pause / play" command is 0.98, and the system executes the corresponding operation accordingly; when the screen status is "off," the same gesture may be mapped to the "turn on screen" command. This dynamic mapping mechanism enables the system to learn and predict the most likely needs of users in specific contexts, achieving truly human-like intelligent interaction and supporting continuous optimization of model performance through OTA upgrades.

[0081] Based on the same inventive concept described above, this disclosure also provides a vehicle handrail intelligent interaction method to realize the intelligent interaction process of the above system. Figure 3 This is a flowchart illustrating a smart interaction method for vehicle handrails provided in an embodiment of this disclosure, as shown below. Figure 3 As shown, the method includes steps S11-S15:

[0082] Step S11: The sensor array embedded under the upper material of the vehicle armrest watch detects the user's hand movements in real time and generates a gesture signal that includes the position of the movement, the dynamic trajectory and the contact pressure.

[0083] Step S12: Establish data interaction with the vehicle bus via the vehicle bus interface to obtain real-time vehicle operating parameters.

[0084] Step S13: Determine the validity of the gesture signals and filter out valid gesture signals.

[0085] Step S14: The valid gesture signal and the vehicle's real-time operating parameters are input into a preset machine learning model. The machine learning model performs fusion calculations on the input information and outputs a predicted command that matches the user's intent.

[0086] Step S15: Execute the prediction command to control the corresponding vehicle function.

[0087] The intelligent interaction method for vehicle handrails provided in this disclosure addresses the industry pain point of accidental touches through a validity judgment step, achieves intelligent intent understanding based on context fusion and machine learning prediction steps, and constructs a deterministic experience through differentiated feedback steps. This method eliminates reliance on fixed mapping rules for interaction, allowing it to dynamically adapt to real-time contexts, significantly reducing the user's memory burden. Simultaneously, the mode switching mechanism enables the same gesture to have different functions in different contexts, greatly expanding the capacity of the interaction gesture library and improving operational efficiency and flexibility.

[0088] Figure 4 This is a flowchart illustrating another intelligent interaction method for vehicle handrails provided in an embodiment of the present disclosure. In some embodiments, such as... Figure 4 As shown, the method may further include step S16:

[0089] Step S16: Drive the linear vibration motor embedded below the sensor array to generate vibration feedback at the hand movement position corresponding to the gesture signal; wherein, when the predicted command is an interaction mode switching command, the vibration feedback is two consecutive short vibrations; when the predicted command is an in-vehicle function adjustment command, the vibration feedback is a single short vibration.

[0090] In some embodiments, such as Figure 4 As shown, step S13 may specifically include step S130:

[0091] Step S130: Extract the contact duration, contact area, and pressure change rate parameters from the gesture signal; if the contact duration is ≤3s, the contact area is ≤1 / 5 of the preset wristwatch area, and the pressure change rate is ≥0.5N / s, then the gesture signal is determined to be a valid gesture signal; otherwise, it is determined to be an unconscious leaning signal and ignored.

[0092] In some embodiments, such as Figure 4 As shown, the method may further include step S17:

[0093] When the user's first preset gesture is detected, the current interaction mode is switched; the interaction mode includes at least a quick control mode and a screen linkage mode; in the quick control mode, the predicted instructions output by the machine learning model are directly associated with volume adjustment, temperature adjustment, or media playback start / stop control; in the screen linkage mode, the predicted instructions output by the machine learning model are associated with screen cursor movement, interface element clicks, or page switching control.

[0094] As a preferred embodiment, the intelligent interaction method for vehicle armrests provided in this disclosure firstly detects the user's hand movements in real time through a sensor array embedded under the upper material of the vehicle armrest, generating gesture signals that include the position of the movement, dynamic trajectory, and contact pressure. Compared to traditional single-dimensional gesture detection, multi-dimensional signal acquisition can more comprehensively reflect the user's operational intentions, providing rich and accurate raw data for subsequent validity judgment and intention prediction.

[0095] Next, data interaction is established with the vehicle bus via the vehicle bus interface to obtain real-time vehicle operating parameters. The purpose of this step is to enable the system to perceive the current vehicle status, break down the disconnect between interaction and vehicle context, make command mapping more targeted, provide contextual support for intent prediction, and avoid the problem of fixed commands being unsuitable in different scenarios.

[0096] Then, the generated gesture signals are evaluated for validity, and valid gesture signals are selected. Specifically, the contact duration, contact area, and pressure change rate parameters are extracted from the gesture signal. If the contact duration is ≤3s, the contact area is ≤1 / 5 of the preset wristwatch area, and the pressure change rate is ≥0.5N / s, it is considered a valid control signal; otherwise, it is considered an unintentional leaning signal and ignored. This validity evaluation process eliminates erroneous operations caused by unintentional user contact, ensuring that the system only responds to conscious control behaviors, thereby improving the reliability of system interaction and reducing the impact of invalid operations on user experience.

[0097] Next, the valid gesture signal and the vehicle's real-time operating parameters are input into a pre-set machine learning model. The model then performs fusion calculations on the input information and outputs a predicted command that matches the user's intent. The purpose of using a machine learning model for fusion calculation is to achieve dynamic and intelligent command mapping, replacing the fixed IF-ELSE logic in existing technologies. This allows the system to intelligently predict user needs based on different scenarios, enabling the same gesture to perform different functions in different situations, thus improving interaction efficiency and user-friendliness.

[0098] Subsequently, the predicted command is executed to control the corresponding in-vehicle function. If the command is a functional operation (such as pausing video or adjusting temperature), a control message is sent to the corresponding in-vehicle function module; if the command is a mode switch, the state record of the internal interactive state machine is updated, thereby translating the predicted user intent into actual function control, realizing an interactive closed loop, accurately responding to user needs, and completing the entire process from gesture input to function implementation.

[0099] After executing the predicted command, a linear vibration motor embedded below the sensor array is driven to generate vibration feedback at the hand movement position corresponding to the gesture signal. Different types of commands correspond to different vibration modes: mode switching commands correspond to two consecutive short vibrations, and function adjustment commands correspond to a single short vibration. In this way, operation confirmation is provided to the user, solving the information asymmetry problem during blind operation, constructing a complete interactive experience loop, enhancing user confidence, and improving the intuitiveness and reliability of the interaction.

[0100] Figure 5 This is a schematic flowchart illustrating a method for manufacturing a vehicle handrail according to an embodiment of the present disclosure, as shown below. Figure 5 As shown, the method includes steps S21-S24:

[0101] Step S21: The frame of the vehicle handrail is foamed and molded to obtain a handrail frame of a preset shape.

[0102] Step S22: On the surface of the preset installation area of ​​the handrail frame, fix the flexible sensor film and the linear vibration motor respectively with an adhesive layer to ensure that the linear vibration motor is located directly below the flexible sensor film and that the positions correspond one-to-one.

[0103] This fixing method achieves precise alignment between the sensor and the vibration motor, ensuring consistency in gesture detection and feedback position, while avoiding damage to the handrail structure during hardware installation. Ultimately, it ensures point-to-point feedback, improves the accuracy of feedback, simplifies the installation process, and guarantees the reliability of module fixing.

[0104] Step S23: The lead wire of the flexible sensor film is led out through the preset wire harness channel inside the handrail frame and electrically connected to the signal input terminal of the preset control device.

[0105] Pre-set wiring harness channels can prevent exposed wires, thus preventing wire wear or affecting the aesthetics of the interior, while ensuring the stability of signal transmission, thereby guaranteeing the reliability and safety of electrical connections without compromising the appearance of the armrest.

[0106] Step S24: Use leather or fabric as the surface material to completely cover the handrail frame, flexible sensor film and linear vibration motor, so that the flexible sensor film and linear vibration motor are completely invisible from the outside of the handrail, and the surface of the covered material has no obvious protrusions or gaps.

[0107] The vehicle armrest manufacturing method disclosed in this embodiment forms the basic structure of the armrest frame through a foam molding process. An adhesive layer ensures reliable fixation and precise alignment of sensors and vibration motors. A pre-set wiring harness channel solves the complexity of in-vehicle wiring. Finally, an overall encapsulation process conceals the functions. This method integrates electronic components into the traditional interior manufacturing process, avoiding secondary assembly, reducing production costs, and ensuring product consistency and reliability, meeting the stringent quality standards and supply chain requirements of the automotive industry.

[0108] Based on the same inventive concept, this disclosure also provides an electronic device. Figure 6 This is a structural block diagram of an electronic device provided in an embodiment of this disclosure. Figure 6 As shown, this disclosure provides an electronic device including: one or more processors 101, a memory 102, and one or more I / O interfaces 103. The memory 102 stores one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement any of the vehicle handrail intelligent interaction methods and / or vehicle handrail manufacturing methods described in the above embodiments; the one or more I / O interfaces 103 are connected between the processor and the memory, configured to enable information interaction between the processor and the memory.

[0109] The processor 101 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 102 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read / write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, including but not limited to a data bus (Bus).

[0110] In some embodiments, the processor 101, memory 102, and I / O interface 103 are interconnected via bus 104, and thus connected to other components of the computing device.

[0111] In some embodiments, the one or more processors 101 include a field-programmable gate array.

[0112] This disclosure also provides a computer-readable medium. The computer-readable medium stores a computer program, which, when executed by a processor, implements the steps of any of the vehicle handrail intelligent interaction methods and / or vehicle handrail manufacturing methods described in the above embodiments. The computer-readable storage medium may be a volatile or non-volatile computer-readable storage medium.

[0113] This disclosure also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code. When the computer-readable code is run in the processor of an electronic device, the processor in the electronic device executes the above-described intelligent interaction method for vehicle handrails and / or the vehicle handrail manufacturing method.

[0114] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable storage medium, which may include computer storage media (or non-transitory media) and communication media (or transient media).

[0115] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0116] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0117] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0118] The computer program product described herein can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0119] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0120] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0121] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0122] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0123] Example embodiments have been disclosed herein, and while specific terminology has been used, it is for illustrative purposes only and should be construed as such, and is not intended to be limiting. In some instances, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in connection with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in connection with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of this disclosure as set forth by the appended claims.

Claims

1. A vehicle handrail intelligent interactive system, characterized in that, include: The armrest itself; A sensor array, embedded beneath the surface material of the handrail body, is used to detect the user's hand movements to generate gesture signals, the gesture signals including at least movement position information, dynamic trajectory information, and contact pressure information; The vehicle bus interface is used to establish a data connection with the vehicle's onboard bus to obtain real-time operating parameters of the vehicle. The control device is electrically connected to the sensor array and the vehicle bus interface, respectively. The control device is configured to: receive gesture signals output by the sensor array and real-time vehicle operating parameters transmitted by the vehicle bus interface; call an embedded machine learning model to perform fusion analysis on the gesture signals and the real-time vehicle operating parameters; generate a predictive command matching the user's intent based on the analysis results; and execute the predictive command.

2. The intelligent interactive system for vehicle handrails according to claim 1, characterized in that, The control device has a built-in status management module, which is configured as follows: In response to a first preset gesture input by the user, the system switches between at least two interaction modes, including a quick control mode for blind operation of high-frequency in-vehicle functions and a screen linkage mode for precise control of the in-vehicle screen. The first preset gesture is a double-tap, long press, or swipe gesture along a specific trajectory.

3. The intelligent interactive system for vehicle handrails according to claim 1, characterized in that, It also includes a feedback module, which contains at least one linear vibration motor; The linear vibration motor is embedded below the sensor array and is electrically connected to the control device; After executing the prediction command, the control device drives the linear vibration motor to generate vibration feedback at the hand movement position corresponding to the gesture signal. The intensity or frequency of the vibration feedback is related to the type of prediction command.

4. The intelligent interactive system for vehicle handrails according to claim 1, characterized in that, The real-time vehicle operating parameters include at least two of the following: the on / off status of the rear display screen, the current display interface type of the rear display screen, the playback status of the in-vehicle media, the current vehicle speed, the current vehicle gear information, and the operating parameters of the in-vehicle air conditioning.

5. The intelligent interactive system for vehicle handrails according to claim 1, characterized in that, The control device is also configured to: The validity of the gesture signal is determined before the machine learning model is invoked; The validity determination is based on at least two of the parameters in the gesture signal: contact duration, contact area, and pressure change rate. When the contact duration is within a preset duration range, the contact area is within a preset area range, and the pressure change rate meets a preset threshold condition, the gesture signal is determined to be a valid control signal; otherwise, it is determined to be an unconscious leaning signal and ignored.

6. A smart interaction method for vehicle handrails, characterized in that, The method includes: By using a sensor array embedded under the upper material of the vehicle's armrest watch, the user's hand movements are detected in real time, generating gesture signals that include the position of the movement, dynamic trajectory, and contact pressure. Data interaction is established with the vehicle bus via the vehicle bus interface to obtain real-time vehicle operating parameters; The validity of the gesture signals is determined, and valid gesture signals are filtered out. The valid gesture signal and the real-time operating parameters of the vehicle are input into a preset machine learning model. The machine learning model performs fusion calculations on the input information and outputs a predicted instruction that matches the user's intention. The predicted instructions are executed to control the corresponding vehicle functions.

7. The interaction method according to claim 6, characterized in that, After executing the prediction instruction, the method further includes: A linear vibration motor embedded below the sensor array is driven to generate vibration feedback at the hand movement position corresponding to the gesture signal; When the prediction command is an interactive mode switching command, the vibration feedback is two consecutive short vibrations. When the predicted command is an in-vehicle function adjustment command, the vibration feedback is a single, short vibration.

8. The interaction method according to claim 6, characterized in that, The method further includes: When a user's first preset gesture is detected, the current interaction mode is switched; the interaction mode includes at least a quick control mode and a screen linkage mode. In quick control mode, the predicted commands output by the machine learning model are directly associated with volume adjustment, temperature adjustment, or media playback start / stop control. In screen linkage mode, the prediction instructions output by the machine learning model are associated with screen cursor movement, interface element clicks, or page switching controls.

9. The interaction method according to claim 6, characterized in that, The step of determining the validity of the gesture signal and filtering valid gesture signals includes: Extract the contact duration, contact area, and pressure change rate parameters from the gesture signal; if the contact duration is ≤3s, the contact area is ≤1 / 5 of the preset wristwatch area, and the pressure change rate is ≥0.5N / s, then the gesture signal is determined to be a valid gesture signal; otherwise, it is determined to be an unconscious leaning signal and ignored.

10. A method for manufacturing a vehicle handrail, characterized in that, The method includes: The frame of the vehicle handrail is foamed and molded to obtain a handrail frame of a preset shape. On the surface of the preset installation area of ​​the handrail frame, a flexible sensor film and a linear vibration motor are fixed respectively by an adhesive layer, ensuring that the linear vibration motor is located directly below the flexible sensor film and that the positions correspond one-to-one. The lead wire of the flexible sensor film is led out through the preset wire harness channel inside the handrail frame and electrically connected to the signal input terminal of the preset control device. The handrail frame, flexible sensor film, and linear vibration motor are completely covered with a surface material made of leather or fabric, making the flexible sensor film and linear vibration motor completely invisible from the outside of the handrail, and the surface of the covered material has no obvious protrusions or gaps.

Images