A visual adjustment method, electronic device, system and vehicle of an intelligent cockpit

Abstract

The application provides a method, an electronic device, a system and a vehicle for adjusting an intelligent cockpit. The method comprises the following steps: outputting a signal of a calibration light spot; acquiring eye data of a driver responding to the calibration light spot; and adjusting a focal length of a display device according to the eye data. According to the method, the focal length of the display device can be adaptively adjusted according to the eye data of the driver responding to the calibration light spot, so that the driver can see the display information of the display device more clearly, the visual fatigue and cognitive load of the driver are reduced, the reaction speed of the driver for seeing display information such as navigation, prompt and warning is improved, and the comfort and safety of driving are improved.

Description

Technical Field

[0001] This application relates to the field of smart cockpit technology, and in particular to a smart cockpit adjustment method, electronic equipment, system, and vehicle. Background Technology

[0002] With the continuous development of the intelligent vehicle industry, the automation and intelligence of intelligent cockpits are becoming increasingly sophisticated, aiming to provide users with a safe, intelligent, and comfortable travel experience. Some intelligent cockpits integrate interactive devices such as LCD instrument panels, central control screens, head-up displays (HUDs), rear entertainment screens, zero-gravity seats, and folding steering wheels, and are equipped with intelligent operating systems, enabling modern automotive cockpit environments with functions such as human-machine interaction, vehicle networking, and active safety.

[0003] Among them, HUD, as an important visual device in smart cockpits, allows drivers to see driving information without looking down, thus avoiding distraction from the road ahead and greatly enhancing driving safety and improving the driving experience.

[0004] In related technologies, cameras are used to detect the driver's eye position and automatically adjust the position, angle and size of the HUD display information according to the eye position, which improves the imaging effect and automation of the HUD. However, problems such as blurry or ghosting of the displayed information still exist, which can easily cause visual fatigue in the driver, increase cognitive load, and affect driving comfort and safety. Summary of the Invention

[0005] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a visual adjustment method for an intelligent cockpit to improve driving comfort and safety. Furthermore, it proposes an electronic device, an intelligent cockpit system, and a vehicle.

[0006] Firstly, in the first aspect, a visual adjustment method for an intelligent cockpit is proposed, including:

[0007] Output the signal for the calibration spot;

[0008] Acquire eye data of the driver's eye response to the calibrated light point;

[0009] The focal length of the display device is adjusted based on the eye data.

[0010] The above technical solution can adaptively adjust the focal length of the display device based on the driver's eye data in response to the calibrated light point, thereby making the displayed information on the display device clearer for the driver, reducing the driver's visual fatigue and cognitive load, improving the driver's reaction speed when seeing navigation, prompts and warnings, and thus improving driving comfort and safety.

[0011] Optionally, the signal for outputting calibration light points includes: randomly projecting multiple calibration light points, wherein the multiple calibration light points are located in different partitions of the display area; and / or, the brightness of the calibration light points is less than or equal to 50 lux.

[0012] Optionally, adjusting the focal length of the display device based on the eye data includes: fitting the driver's refractive error based on the eye data; and adjusting the focal length of the display device based on the refractive error.

[0013] Optionally, the eye data includes the pupil position, pupil size, corneal reflective spot position, measured line-of-sight vector, and eye image features when the driver's eyes respond to each light point.

[0014] Optionally, fitting the driver's refractive error based on the eye data includes:

[0015] Based on the mapping relationship between the pupil position, the corneal reflected light spot position, and the measured line of sight vector, calculate the coordinates of the predicted line of sight landing point;

[0016] Based on the predicted gaze point coordinates and the pupil position, the predicted gaze vector is obtained;

[0017] Calculate the gaze residual based on the measured gaze vector and the predicted gaze vector; calculate the focus blur based on the eye image features;

[0018] The driver's refractive error is fitted based on the visual residual, the pupil size, and the focus blur.

[0019] Optionally, fitting the driver's refractive error based on the visual residual, the pupil size, and the focus blur includes:

[0020] Determine whether the visual field residual is less than or equal to a preset threshold. If yes, fit the driver's refractive error based on the visual field residual, the pupil size, and the focus blur. If no, re-output the signal of the calibration point and calculate the visual field residual.

[0021] Optionally, before outputting the signal for calibrating the light spot, the method further includes: when the trigger condition is met, outputting interactive information on whether to activate the automatic visual adjustment function, and proceeding to subsequent steps after receiving a positive response.

[0022] Optionally, adjusting the focal length of the display device based on the eye data further includes: adjusting the focal length of the display device based on the eye data, body characteristics, and a preset mapping relationship, and adjusting the state of at least one of the following components: seat, steering wheel, interior rearview mirror, exterior rearview mirror, instrument panel display screen, and central control display screen.

[0023] Secondly, an electronic device is proposed, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the first aspect. This electronic device has the same beneficial effects as the aforementioned visual adjustment method.

[0024] Thirdly, a smart cockpit system is proposed, including the electronic devices described in the second aspect above. This smart cockpit system has the same beneficial effects as the aforementioned electronic devices.

[0025] Fourthly, a vehicle is proposed, comprising: electronic equipment as described in the second aspect above or an intelligent cockpit system as described in the third aspect above. The vehicle has the same beneficial effects as the aforementioned electronic equipment or intelligent cockpit system.

[0026] Additional aspects and advantages 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. Attached Figure Description

[0027] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0028] Figure 1 This is a schematic diagram of the hardware layout of an intelligent cockpit system according to an embodiment of this application;

[0029] Figure 2 This is a block diagram of the intelligent cockpit system architecture according to an embodiment of this application;

[0030] Figure 3 This is a flowchart of a perspective adjustment method according to a first embodiment of this application;

[0031] Figure 4 This is a flowchart of a perspective adjustment method according to a second embodiment of this application;

[0032] Figure 5 This is a flowchart of a perspective adjustment method according to a third embodiment of this application;

[0033] Figure 6 This is a schematic diagram illustrating the effect of a perspective adjustment method according to an embodiment of this application;

[0034] Figure 7 This is a schematic diagram illustrating another effect of the perspective adjustment method according to an embodiment of this application.

[0035] Figure label:

[0036] 1. Steering wheel; 2. Electric interior rearview mirror; 3. In-vehicle camera; 4. Electric exterior rearview mirror; 5. Instrument panel display and central control display; 6. Electric seat; 7. HUD display device. Detailed Implementation

[0037] 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.

[0038] In the description of this application, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, features defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0039] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0040] To better understand the embodiments of this application, the hardware layout and architecture of the intelligent cockpit system proposed in this application will first be described. This intelligent cockpit system includes multiple adjustable components that affect the driver's visual perception, as well as multi-source information acquisition devices. These components work together in terms of spatial layout and information presentation to form a comprehensive visual channel through which the driver obtains information about the external environment and the vehicle system during driving.

[0041] Please see Figure 1Adjustable components affecting the driver's visual perception include the electric seat 6, steering wheel 1, electric exterior mirrors 4, electric interior mirror 2, HUD display 7, instrument panel display, and central control display 5. These components influence the driver's visual perception from different perspectives. For example, the electric seat 6 and steering wheel 1 primarily affect the driver's visibility of the road ahead, the instrument panel area, and the surrounding environment by changing the driver's seating position, eye level, and body posture. The electric interior mirror 2 and electric exterior mirrors 4 affect the driver's coverage of the vehicle's rear side environment and the distribution of blind spots by adjusting the mirror angle or display viewing angle. The HUD display 7 projects key driving information into the driver's forward field of vision; its virtual image distance, brightness, and layout directly affect the driver's information acquisition efficiency. The instrument panel and central control display 5 affect the readability and recognition efficiency of information through parameters such as font size, interface layout, brightness, and color mode. These physical position adjustments and information display adjustments are coupled and jointly determine the driver's visual perception range, clarity, and cognitive load level.

[0042] The multi-source information acquisition device, namely the sensing device used to collect driver's visual and physical state information, includes an in-vehicle camera 3 and various physiological signal sensors. The in-vehicle camera 3 can be a driver monitoring system (DMS) or other visual acquisition devices. It can be positioned on the A-pillar, above the steering wheel, or behind the rearview mirror to collect real-time images of the driver's face and eye area. It can also be equipped with an infrared supplementary lighting module to adapt to eye-tracking in low-light environments (such as at night or in tunnels). Physiological signal sensors can be integrated into components such as the steering wheel and seats. For example, capacitive or pressure sensors in the steering wheel detect hand grip and heart rate signals, while pressure distribution sensors in the seat back and cushion detect the driver's body distribution, posture characteristics, and height. Additionally, non-contact in-cabin millimeter-wave radar, infrared body temperature sensors, or depth sensors can be included to acquire driver physical state information, such as detecting the driver's breathing, heart rate, and even subtle body movements, thereby providing a more comprehensive assessment of their physiological state. The aforementioned multi-source sensor data can serve as the basic data input for driver visual behavior modeling and visual perception state assessment.

[0043] Please see Figure 2The intelligent cockpit system can adopt the following system architecture, including a signal acquisition module 10, a feature recognition and processing module 20, and a visual display adjustment module 30. These modules interact and coordinate control through a vehicle communication bus. The signal acquisition module 10 is used to collect the driver's multimodal biometric data, i.e., the aforementioned multi-source acquisition devices, including an in-vehicle camera 3 and a physiological signal sensor 12. The feature recognition and processing module 20 can be one or more electronic control units (ECUs) of the vehicle electrically connected to the signal acquisition module 10. For example, the intelligent cockpit system domain controller can serve as the feature recognition and processing module 20. The feature recognition and processing module 20 includes a processor capable of executing programs and a memory capable of storing data, such as a driver identification module 21 for feature recognition, an eye-tracking feature analysis module 22, a body feature analysis module 23, an adjustment parameter control module 24 for processing and analyzing the structure, and a file storage module 25 for establishing and storing temporary files of driver information and adjustment parameters.

[0044] The driver identification module 21 compares facial images or iris information captured by the in-vehicle camera 3 with a driver profile database pre-stored locally in the vehicle or in the cloud to confirm the current driver's identity. Additionally, it can incorporate multimodal biometric technology. For example, when the face is obscured by a mask, gait recognition (via the camera when the driver exits the vehicle) or voiceprint recognition (via the in-vehicle microphone) can be combined to comprehensively determine the driver's identity, improving the robustness of the identification.

[0045] The eye movement feature analysis module 22 processes the eye images captured by the in-vehicle camera 3 in real time, extracts and calculates multiple eye movement data, including but not limited to: pupil diameter, fixation point coordinates, saccade path, blink frequency, and interpupillary distance. Combined with specific visual stimuli, it calculates visual physiological parameters including but not limited to: visual acuity / refractive error, astigmatism axis, center position of the eye ellipsoid, effective visual field, and color vision abnormalities (color blindness / color weakness).

[0046] The identity feature analysis module 23 processes the data collected by the physiological signal sensor 12, analyzes and infers the driver's body feature parameters, including but not limited to: height, weight, and shoulder width inferred from seat pressure distribution; resting heart rate detected by the steering wheel sensor; and sitting posture habits determined by body posture analysis.

[0047] The above analysis results are used by the adjustment parameter control module 24 to construct a driver visual perception model, which quantifies the driver's effective field of vision, visual attention area, and information acquisition ability in the current posture. Visual cognitive load is used as one of the constraints or optimization objectives to calculate the corresponding optimal visual state parameters. These parameters include both physical space-related parameters (such as eye position and gaze direction) and information presentation-related parameters (such as optimal display distance and information density range). The file storage module 25 is used to store user files and the calculated adjustment parameters.

[0048] The visual display adjustment module 30 is connected to the feature recognition and processing module 20 and the vehicle bus (such as CAN / LIN bus) to receive control commands and drive all adjustable components in the cockpit related to the driver's visual perception.

[0049] The hardware composition and layout of the embodiments of this application have been described above. The following description, in conjunction with specific embodiments, illustrates a visual adjustment method for an intelligent cockpit provided by this application. Please refer to... Figure 3 The method includes:

[0050] Step S131: Output the signal for the calibration spot;

[0051] Step S132: Acquire eye data of the driver's eye response to the calibrated light point;

[0052] Step S133: Adjust the focal length of the display device according to the eye data.

[0053] The above technical solution can adaptively adjust the focal length of the display device based on the driver's eye response data to the calibrated light point, thereby making the displayed information clearer for the driver, reducing visual fatigue and cognitive load, and improving the driver's reaction speed to key displayed information such as navigation, prompts, and warnings, thus improving driving comfort and safety. The display device can be a HUD, instrument panel, or central control screen, etc. This method can effectively alleviate the eye burden of nearsighted, farsighted, and astigmatic users, providing a clear and comfortable visual experience without requiring manual adjustment of the display device's focal length.

[0054] In some embodiments, outputting calibration light points includes randomly projecting multiple calibration light points, each located in a different partition of the display area. This avoids the user having to deliberately cooperate, which could affect the accuracy of the calibration.

[0055] For example, the system dynamically projects calibration light points in five typical zones of the HUD display area—upper left, upper right, center, lower left, and lower right—in a non-fixed order and at non-fixed intervals, covering the driver's natural gaze range and improving the comprehensiveness of data collection and the accuracy of subsequent calibration.

[0056] In some embodiments, the brightness of the calibration spot is less than or equal to 50 lux. This value is lower than the brightness of the normal HUD display content to avoid affecting the user's vision, causing severe pupil constriction or delayed visual adaptation, and ensuring the comfort and data accuracy of the calibration process.

[0057] In some embodiments, adjusting the focal length of the display device based on eye data includes: fitting the driver's refractive error based on the eye data; and adjusting the focal length of the display device based on the refractive error. This solution effectively addresses the problem of blurred HUD images caused by myopia, significantly improving information readability.

[0058] In some embodiments, eye data includes the driver's pupil position, pupil size, corneal reflective spot position, measured gaze vector, and eye image features in response to each light point. This allows for the collection of multi-category eye data, improving the accuracy of focus adjustment and providing multimodal input for subsequent refractive fitting. Furthermore, eye image features can include iris texture morphology, eyelid opening and closing, blink frequency, and conjunctival vascular distribution, which can also be used to assist in assessing fatigue status and physiological stability, allowing for targeted adjustment of display device parameters such as brightness and contrast. The eye data can be collected synchronously via a DMS or eye tracker. For example, three frames of data can be collected for each calibration light point at a frame rate of 30fps, with a single calibration light point acquisition time of 0.1 seconds, ensuring data accuracy while achieving efficient and non-intrusive calibration. In other embodiments, eye data can also be collected using more advanced radar waves or structured light sensors to achieve higher precision and less susceptibility to illumination in 3D reconstruction and tracking of the eyeball and face.

[0059] In some embodiments, please refer to Figure 4 Based on eye data, the driver's refractive error is fitted, including:

[0060] Step 201: Calculate the coordinates of the predicted line of sight landing point based on the mapping relationship between the pupil position, the corneal reflected light spot position, and the measured line of sight vector;

[0061] Step 202: Obtain the predicted gaze vector based on the predicted gaze point coordinates and the pupil position;

[0062] Step 203: Calculate the line-of-sight residual based on the measured line-of-sight vector and the predicted line-of-sight vector;

[0063] Step 204: Calculate the focus blur based on the eye image features;

[0064] Step 205: Fit the driver's refractive error based on the visual residual, the pupil size, and the focus blur.

[0065] This fitting model is highly accurate and easy to compute. For example, a personalized linear mapping equation is constructed by fitting the pupil-corneal reflex mapping relationship using the least squares method:

[0066] in, To predict the coordinates of the point where the line of sight falls, The two-dimensional coordinates of the pupil center Here are the coordinates of the corneal reflective spot. a and b are mapping weight coefficients; c is an individual bias compensation constant. Three frames of stable data are collected for each calibration point. The optimal coefficients are iteratively solved using the least squares method to fit a unique pupil-corneal reflective mapping relationship adapted to the current driver. Compared to a general model, this scheme eliminates errors caused by individual differences in eye structure, resulting in more accurate predicted gaze point coordinates. Furthermore, the gaze residual can be calculated based on these predicted gaze point coordinates. The formula is as follows:

[0067]

[0068] in, This is the measured line-of-sight vector. To predict the gaze vector.

[0069] In some embodiments, the refractive error of the driver, based on the visual residual, the pupil size, and the focus blur, can be fitted according to the following formula:

[0070]

[0071] Among them, k1, k2, and k3 are calibration coefficients, which are obtained through training with a large number of user samples. For example, the default initial values ​​can be set to k1=0.8, k2=0.3, and k3=0.5, which can be adjusted according to the vehicle model; d0 is the standard pupil diameter, with a default of 3.5mm, which is the pupil size under normal vision, and d is the actual measured pupil diameter; the focus blur σ is a characterization of the degree of image diffusion of the HUD far-field light point in the human eye pupil reflection area, which is calculated from the DMS near-field general eye image features; finally, the fitted refractive power parameters are obtained.

[0072] In some embodiments, before fitting the driver's refractive error based on the visual residual, the pupil size, and the focus blur, the following steps are included:

[0073] Determine whether the visual field residual is less than or equal to a preset threshold. If yes, fit the driver's refractive error based on the visual field residual, the pupil size, and the focus blur. If no, re-output the signal of the calibration point and calculate the visual field residual.

[0074] This scheme can improve the accuracy of refractive error calculation and eliminate misjudgments caused by driver distraction, blinking interference, or transient eye movement abnormalities.

[0075] In some embodiments, adjusting the focal length of the display device according to diopter includes adjusting the HUD focus amount according to the following mapping relationship: Where k is calibrated according to the HUD optical module specifications, for example, k = 0.8. After adjustment, the focus blur σ of the HUD image can be collected again. If σ > threshold (e.g., 0.2), the focus adjustment amount is finely adjusted until σ ≤ threshold to ensure image clarity.

[0076] In some embodiments, when the number of times the calibration point is re-output exceeds a preset number, a manual adjustment prompt is displayed. This avoids impacting the user experience.

[0077] For example, such as Figure 5 After step S203, the following is included:

[0078] Step S2031: Determine if there is visual residual. ≤0.5°? If yes, proceed to step S205; if no, proceed to step S2032.

[0079] Step S2032: Determine if the number of times the calibration light point is re-output (re-calibration) is greater than 3. If yes, proceed to step S206: Output a manual adjustment prompt; if no, proceed to step S2033: Re-output the calibration light point, for example, prompting the user to "keep the head stable". The system automatically re-projects 1-2 light points for re-calibration, triggers calibration again, and obtains eye data to calculate the visual residual.

[0080] In some embodiments, before outputting the signal for calibrating the light spot, the method further includes: when a trigger condition is met, outputting interactive information regarding whether to activate the automatic vision adjustment function; and proceeding to subsequent steps upon receiving a positive response. This method can avoid accidental triggering or interference with the driver.

[0081] For example, when the vehicle detects that a driver has entered the vehicle (which can be determined by signals such as door opening, seat pressure sensor triggering, or vehicle power-on), the system wakes up the signal acquisition module 10. When the system detects that the driver has sat down or the cabin state has changed, it triggers the adjustment process. The triggering conditions include, but are not limited to: new driver identification, changes in seat state (e.g., after the zero-gravity seat returns to its original position), or changes in steering wheel position (e.g., after the folding steering wheel returns to its original position). The system starts the signal acquisition module, first identifying the driver's identity. The in-vehicle camera 3 begins to collect the driver's facial image, the physiological signal sensor 12 collects physiological data, and the feature recognition and processing module 20 analyzes the collected data and attempts to match the driver's identity. If it is a new driver, the triggering conditions are directly met, a new temporary personal data profile is constructed, and the next initial calibration process begins. If it matches the profile in the database, it further determines whether the cabin state has changed. If there is no change, the driver's personalized preference profile (including historical adjustment parameters) is directly retrieved. If there is a change, the triggering conditions are also met, a new model is constructed, and the model is overridden on the basis of the original model. After successful triggering, the system prompts the driver whether to activate the automatic vision adjustment function through voice interaction or page pop-up window, and proceeds to the next step after receiving a positive response.

[0082] In some embodiments, adjusting the focal length of the display device based on the eye data further includes: adjusting the focal length of the display device based on the eye data, body characteristics, and a preset mapping relationship, and adjusting the state of at least one of the following components: seat, steering wheel, interior rearview mirror, exterior rearview mirror, instrument panel display, and central control display. This solution enables multi-hardware collaborative visual optimization, improving the system's automation and intelligence level.

[0083] For example, a smart cockpit can analyze body characteristics to infer the driver's approximate height and posture habits, thereby calculating the most ergonomic seat height, backrest angle, and recommended values ​​for the steering wheel's fore-aft / height position. For instance, it ensures the driver's legs remain naturally bent when pressing the pedals, and the elbows are at approximately 90-120 degrees when the arms are gripping the steering wheel at the 3 / 9 o'clock position. Furthermore, by tracking the driver's gaze point and head posture, and analyzing the acquired eye data (such as fitting refractive errors), combined with known fixed parameters like the vehicle's A / B pillars and windshield boundaries, the system can calculate and map the theoretical optimal field of vision and refractive compensation range for the driver's current posture. For example, based on the driver's eye position, the system calculates the theoretically optimal angles for the left and right side mirrors, minimizing blind spots from mirror reflections and covering the driver's most natural lateral visual field. Alternatively, it can calculate the refractive compensation parameters for the optimal virtual image distance of the HUD display interface based on the driver's refractive error, improving information readability and driving safety.

[0084] In some embodiments, the visual adjustment method further includes updating the adjustment instructions based on the user's operation after automatic adjustment. For example, after the intelligent cockpit system completes adaptive adjustment, if the driver has personalized fine-tuning needs for the final position / display effect of one or more components, they can manually correct the components within a limited range using physical buttons or a touchscreen within the vehicle. The feature recognition and processing module 20 records this fine-tuning operation and the final parameters, and binds them to the current driver's identity ID (whether newly recognized or existing), updating their personalized profile. This enables the system to continuously learn, so that the next time the driver gets in the car, the adjustment will more accurately match their personal preferences.

[0085] This application also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of the above-described method. This electronic device has the same beneficial effects as the above-described visual adjustment method. The electronic device can be a smart cockpit domain controller or a separate controller, or it can be the aforementioned feature recognition and processing module 20.

[0086] This application also provides an intelligent cockpit system, including the electronic device described above. The intelligent cockpit system has the same beneficial effects as the described electronic device.

[0087] For example, please refer to Figure 1 and Figure 2 The intelligent cockpit system includes the aforementioned components and modules, wherein the visual display adjustment module 30 specifically includes multiple sub-adjustment units:

[0088] 1) Electric seat adjustment unit 31: controls the motor of the seat to realize multi-degree-of-freedom adjustment of the seat forward and backward, up and down, backrest angle, seat cushion tilt angle, lumbar support, etc.

[0089] 2) Electric steering wheel adjustment unit 32: a motor that controls the steering wheel to adjust the height and fore-and-aft position of the steering wheel, including but not limited to folding steering wheels.

[0090] 3) Electric rearview mirror adjustment unit 33: controls the motor / display program of the left and right exterior rearview mirrors and interior rearview mirror (including streaming media rearview mirror) to achieve precise adjustment of the lens angle / viewing angle.

[0091] 4) HUD display adjustment unit 34: Communicates with the HUD controller to adjust the virtual image distance (refractive compensation), display brightness, contrast, and display content layout of the HUD to ensure that information is clearly presented near the driver's most natural line of sight.

[0092] 5) Instrument panel / central control screen display adjustment unit 35: Communicates with the instrument panel and central control screen controller to adjust the display theme (such as sport, comfort, economy mode), font size, interface brightness, color saturation, etc.

[0093] After data acquisition and analysis, the intelligent cockpit system packages all the optimal parameters (physical position parameters and display attribute parameters) into control commands and sends them to the various sub-adjustment units under the vision display adjustment module 30 via the vehicle bus. These units work collaboratively to automatically adjust all components to the optimal initial state that matches the driver's physiological characteristics in a single operation. For example... Figure 6 As shown, the electric seat adjustment unit 31 drives the motor to adjust the seat to the calculated optimal height and fore-aft position. The electric steering wheel adjustment unit 32 drives the motor to adjust the steering wheel to a position that does not obstruct the instrument display and is comfortable to hold. The electric rearview mirror adjustment unit 33 precisely rotates the rearview mirror to the theoretically optimal angle based on the calculated angle. For example... Figure 7 As shown, the HUD display adjustment unit 34 adjusts the virtual image distance (VID) to a position matching the driver's eye level distance and sets the initial brightness to the median value. The instrument panel / central control screen display adjustment unit 35 adjusts the image focal length according to the calibrated and fitted diopter parameters and adjusts the font size to "standard" or "large" mode.

[0094] This intelligent cockpit system enables adaptive visual display adjustment upon seating. Through a multi-factor fusion algorithm, it fits and calculates the equivalent refractive power of the driver's eyes, achieving seamless and accurate detection of refractive parameters, replacing traditional manual adjustments. It achieves silent and automated professional-grade eye-tracking calibration in in-vehicle scenarios, offering higher calibration accuracy and stronger anti-interference capabilities. No active user intervention is required; the process is completed within 3 seconds of entering the vehicle, making adaptation more convenient and accurate, filling the industry gap in seamless in-vehicle refractive power detection. Furthermore, it achieves dual-layer collaborative adaptation of "physical posture adjustment + optical visual compensation." Specifically, the first layer, physical posture adjustment, uniformly adjusts the position, angle, and support posture of the seat, steering wheel, interior rearview mirror, and left and right exterior rearview mirrors. The core objective is to ensure the driver's eyes fall into the optimal visual eye box, matching the standard viewing distance, laying the foundation for subsequent optical compensation. The second layer, optical visual compensation, based on the driver's refractive parameters, performs imaging focal length adjustment, refractive power compensation, and astigmatic geometric distortion correction on the HUD, while simultaneously performing visual sharpening and adaptive contrast optimization on the vehicle interface and instrument panel. Breaking through the industry limitation of "adjusting position but not clarity," this system achieves integrated "viewing distance adaptation + vision adaptation," completely resolving the pain points of visual adaptation for people with different vision levels. It allows users with myopia, hyperopia, or astigmatism to view all visual devices in the cabin clearly and comfortably without manual adjustment, significantly reducing visual load. Furthermore, it collaboratively optimizes all visual hardware, incorporating all vision-related hardware such as the HUD, vehicle interface, interior and exterior rearview mirrors, steering wheel, and seats into the same optimization chain, establishing a unified collaborative control model. After completing eye-tracking calibration and refractive calculation, the system synchronously optimizes the adjustment parameters of all hardware based on the driver's posture characteristics and vision parameters: seat and steering wheel adjustments adapt to ergonomics and standard viewing distances, rearview mirror adjustments adapt to the optimal field of vision, and HUD and vehicle interface adjustments adapt to visual characteristics, achieving "one-time calibration, full-domain adaptation." Compared with the prior art, the advantage of the embodiments of this application is that it solves the problem of independent adjustment of traditional equipment and realizes the coordinated linkage of all vision hardware. It optimizes the entire link from human eye distance, optical path and field of vision, reduces manual intervention by the driver, improves adaptation efficiency, and makes the cockpit visual experience more unified and comfortable, further improving driving safety.

[0095] This application also provides a vehicle, including the electronic equipment or intelligent cockpit system described above. This vehicle has the same beneficial effects as the aforementioned electronic equipment or intelligent cockpit system. The vehicle can be an electric vehicle, a hybrid vehicle, or a gasoline-powered vehicle, especially models equipped with features such as a folding steering wheel and a zero-gravity driver's seat, where the cockpit and driver's seat states frequently switch.

[0096] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that 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.

[0097] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations 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.

Claims

1. A visual adjustment method for an intelligent cockpit, characterized in that, include: Output the signal for the calibration spot; Acquire eye data of the driver's eye response to the calibrated light point; The focal length of the display device is adjusted based on the eye data.

2. The visual accommodation method according to claim 1, characterized in that, The signal for outputting calibration light points includes: randomly projecting multiple calibration light points, wherein the multiple calibration light points are located in different partitions of the display area; and / or, the brightness of the calibration light points is less than or equal to 50 lux.

3. The visual accommodation method according to claim 1, characterized in that, The step of adjusting the focal length of the display device based on the eye data includes: fitting the driver's refractive error based on the eye data; and adjusting the focal length of the display device based on the refractive error.

4. The visual accommodation method according to claim 3, characterized in that, The eye data includes the driver's pupil position, pupil size, corneal reflective spot position, measured line-of-sight vector, and eye image features when the driver's eyes respond to each light point; And / or, The step of fitting the driver's refractive error based on the eye data includes: Based on the mapping relationship between the pupil position, the corneal reflected light spot position, and the measured line of sight vector, calculate the coordinates of the predicted line of sight landing point; Based on the predicted gaze point coordinates and the pupil position, the predicted gaze vector is obtained; Calculate the gaze residual based on the measured gaze vector and the predicted gaze vector; calculate the focus blur based on the eye image features; The driver's refractive error is fitted based on the visual residual, the pupil size, and the focus blur.

5. The visual accommodation method according to claim 4, characterized in that, The step of fitting the driver's refractive error based on the visual residual, the pupil size, and the focus blur includes: Determine whether the visual field residual is less than or equal to a preset threshold. If yes, fit the driver's refractive error based on the visual field residual, the pupil size, and the focus blur. If no, re-output the signal of the calibration point and calculate the visual field residual.

6. The visual accommodation method according to claim 1, characterized in that, Before the signal for outputting the calibration light point, the method further includes: when the trigger condition is met, outputting interactive information on whether to start the automatic visual adjustment function, and proceeding to subsequent steps after receiving a positive response.

7. The visual accommodation method according to any one of claims 1-6, characterized in that, Adjusting the focal length of the display device based on the eye data also includes: adjusting the focal length of the display device based on the eye data, body characteristics, and a preset mapping relationship, and adjusting the state of at least one of the following components: seat, steering wheel, interior rearview mirror, exterior rearview mirror, instrument panel display screen, and central control display screen.

8. An electronic device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory, characterized in that the processor executes the computer program to implement the steps of the method according to any one of claims 1-7.

9. An intelligent cockpit system, characterized in that, Including the electronic device as described in claim 8.

10. A vehicle, characterized in that, include: This includes the electronic device as described in claim 8 or the smart cockpit system as described in claim 9.

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