Visual anti-dizzy method based on vehicle acceleration

Abstract

The invention discloses a visual anti-dizziness method based on vehicle acceleration, which relates to the technical field of vehicle-mounted augmented reality, and comprises the following steps: constructing a three-axis acceleration vector based on three-axis acceleration data, carrying out normalization processing, and compensating the three-axis acceleration vector after normalization processing based on vehicle motion correction parameters; performing screen pixel displacement calculation to obtain a pixel displacement amount, and fusing the pixel displacement amount, the sight line offset amount and the display screen center coordinate to obtain a visual anchor point coordinate; and calculating the rotation angle of the virtual layer according to the Yaw angular velocity of the gyroscope, performing angle transformation on the virtual layer in the display screen, and drawing a wave point or a prompt mark in the virtual layer after angle transformation according to the coordinate position of the visual anchor point. The method can improve the spatial accuracy of the prompt mark, achieves the visual stability in the steering process, remarkably reduces the dizziness occurrence rate of passengers, and is suitable for various driving scenes.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle-mounted augmented reality, and in particular to a method for preventing visual dizziness based on vehicle acceleration. Background Art

[0002] With the rapid development of intelligent connected vehicles and in-vehicle augmented reality (AR) technology, research on motion sickness prevention based on visual assistance has gradually become a hot topic in the field of in-vehicle human-computer interaction. Early studies mainly relied on single visual cues or optical flow perception, and attempted to alleviate the motion sickness discomfort caused by the mismatch between vehicle acceleration and visual information to a certain extent by superimposing stable reference markers on the head-up display (HUD) or the central control screen. However, since these methods often lack accurate acquisition of the vehicle's actual motion state and are based only on empirical parameter settings, the prompt markers cannot respond in time during actual acceleration, steering, or bumps. At the same time, most technologies do not consider the interference of the occupant's head posture and line of sight deviation on the perception effect, lack the fusion and dynamic correction of multi-source heterogeneous sensor data, and cannot meet the needs of efficient motion sickness prevention under complex driving conditions.

[0003] Existing acceleration-based motion sickness prevention methods typically utilize only one- or two-dimensional vehicle acceleration information for simple pixel shifting or filtering. They fail to fully incorporate the gyroscope's yaw rate to compensate for visual misalignment caused by vehicle steering. They also fail to dynamically adjust the anchor point position based on the occupant's gaze offset, resulting in insufficient spatial stability of the cue markers. Furthermore, static pixel scaling factors are prone to cumulative errors over extended periods of driving or at varying vehicle speeds, making it difficult for the visual anchor point to remain within the occupant's gaze area, reducing motion sickness prevention effectiveness. Summary of the Invention

[0004] In view of the problems existing in the existing anti-sickness method based on vehicle acceleration, the present invention is proposed. Therefore, the problem to be solved by the present invention is how to provide an anti-sickness method based on vehicle acceleration.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] In a first aspect, the present invention provides a method for preventing visual sickness based on vehicle acceleration, which includes collecting three-axis acceleration data of the vehicle, the sight offset between the occupant's head and the display screen, the gyroscope Yaw angular velocity, the pixel scaling factor, and the vehicle motion correction parameter;

[0007] Constructing a three-axis acceleration vector based on the three-axis acceleration data, performing normalization processing, and compensating the normalized three-axis acceleration vector based on the vehicle motion correction parameter;

[0008] The screen pixel displacement is calculated based on the normalized three-axis acceleration vector after compensation based on the pixel scaling factor to obtain the pixel displacement. The pixel displacement, the sight offset and the center coordinates of the display screen are integrated to obtain the visual anchor point coordinates.

[0009] The rotation angle of the virtual layer is calculated according to the yaw angular velocity of the gyroscope, the angle of the virtual layer on the display screen is transformed, and a wave dot or prompt mark is drawn in the virtual layer after the angle transformation according to the coordinate position of the visual anchor point.

[0010] As a preferred solution of the visual anti-sickness method based on vehicle acceleration described in the present invention, the vehicle motion correction parameters include the current steering wheel angle, the angle between the seat back and the vertical direction, and the current vehicle speed.

[0011] As a preferred solution of the visual anti-sickness method based on vehicle acceleration of the present invention, the normalization process includes:

[0012] Remove the gravity component from the three-axis acceleration vector and express it as:

[0013]

[0014] Among them: a lin is the three-axis acceleration vector after removing the gravity component, a x is the vehicle's x-axis acceleration, a y is the vehicle's y-axis acceleration, a z is the vehicle's z-axis acceleration, g is the gravity component;

[0015] The normalized acceleration vector is calculated and expressed as:

[0016]

[0017] in: is the normalized acceleration vector.

[0018] As a preferred solution of the visual anti-sickness method based on vehicle acceleration of the present invention, the compensating the normalized three-axis acceleration vector based on the vehicle motion correction parameter includes:

[0019] The steering wheel lateral pre-offset, seat longitudinal scaling compensation and vehicle speed sensitivity factor are calculated respectively through the vehicle motion correction parameters;

[0020] When the steering wheel turns left, negative lateral compensation is generated, and when the steering wheel turns right, positive lateral compensation is generated. The calculation formula for the steering wheel lateral pre-offset is:

[0021] st F =k s δ

[0022] Among them: st F is the lateral pre-offset of the steering wheel, k s is the lateral offset proportional coefficient, δ is the current steering wheel angle;

[0023] If the angle between the seat back and the vertical direction is below the angle threshold between the seat back and the vertical direction, the seat longitudinal scaling compensation is not triggered;

[0024] If the angle between the seat back and the vertical direction is greater than the angle threshold between the seat back and the vertical direction, the seat longitudinal scaling compensation is triggered and the seat longitudinal scaling compensation calculation is performed, which is expressed as:

[0025] re F =1+k r (θ-θ0)

[0026] Among them: F is the seat longitudinal scaling compensation, k r is the seat longitudinal scaling compensation coefficient, θ is the angle between the seat back and the vertical direction, and θ0 is the angle threshold between the seat back and the vertical direction;

[0027] The calculation formula of vehicle speed sensitivity factor is:

[0028] sp F =1+k v v

[0029] Among them: sp F is the vehicle speed sensitivity factor, k v is the vehicle speed sensitivity coefficient, v is the current speed of the vehicle;

[0030] The steering wheel lateral pre-offset, seat longitudinal scaling compensation and vehicle speed sensitivity factor are integrated to compensate the normalized acceleration vector. The compensated normalized acceleration vector is obtained, which is expressed as:

[0031]

[0032] Among them: a com is the normalized three-axis acceleration vector after compensation, is the normalized vehicle x-axis acceleration, is the normalized vehicle y-axis acceleration, is the normalized vehicle z-axis acceleration.

[0033] As a preferred solution of the visual anti-sickness method based on vehicle acceleration of the present invention, the step of calculating the screen pixel displacement of the compensated normalized three-axis acceleration vector based on the pixel scaling factor includes:

[0034] Obtain the compensated normalized acceleration vector and pixel scaling factor to calculate the screen pixel displacement, which is expressed as:

[0035]

[0036] Where: Δ in is the pixel displacement, k px is the pixel scaling factor, a x ' is the normalized vehicle x-axis acceleration after compensation, a y ' is the normalized vehicle y-axis acceleration after compensation.

[0037] As a preferred solution of the visual anti-sickness method based on vehicle acceleration of the present invention, the fusing of pixel displacement, sight offset and display screen center coordinates includes:

[0038] Based on the center coordinates of the display screen, the visual anchor point coordinates are obtained, which are expressed as:

[0039] P an =C+Δ in +Δ ga

[0040] Where: P an is the visual anchor point coordinate, C is the display screen center coordinate, Δ ga is the sight line offset.

[0041] As a preferred solution of the visual anti-sickness method based on vehicle acceleration of the present invention, the calculation of the virtual layer rotation angle according to the gyroscope Yaw angular velocity includes:

[0042] The gyroscope Yaw angular velocity is converted to the virtual layer rotation angle through the rotation mapping coefficient, which is expressed as:

[0043] θ off =k rot ω yaw

[0044] Where: θ off The rotation angle of the virtual layer; k rot is the rotation mapping coefficient, ω yaw is the gyroscope Yaw angular velocity.

[0045] In a second aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, the steps of a visual anti-sickness method based on vehicle acceleration are implemented.

[0046] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, the steps of a visual anti-sickness method based on vehicle acceleration are implemented.

[0047] The beneficial effects of the present invention are as follows: this method ensures that the visual anchor point is always located in the occupant's area of ​​focus through pixel mapping and line of sight fusion, thereby improving the spatial accuracy of the prompt mark; achieving visual stability during steering, significantly reducing the incidence of occupant dizziness, and providing a highly reliable and comfortable augmented reality anti-dizziness solution in various driving scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 The flowchart of the visual anti-sickness method based on vehicle acceleration. DETAILED DESCRIPTION

[0050] To make the above-mentioned purposes, features, and advantages of the present invention more easily understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0051] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0052] Secondly, an embodiment or embodiments herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The appearance of "an embodiment" in different places in this specification does not necessarily refer to the same embodiment, nor is it an embodiment that is exclusive or selectively mutually exclusive of other embodiments.

[0053] Reference Figure 1 , which is the first embodiment of the present invention, provides a method for preventing visual dizziness based on vehicle acceleration, comprising:

[0054] S1: Collects the vehicle's three-axis acceleration data, the line of sight offset between the occupant's head and the display screen, the gyroscope's Yaw angular velocity, the pixel scaling factor, and the vehicle's motion correction parameters;

[0055] Specifically, vehicle motion correction parameters include the current steering wheel angle, the angle between the seat backrest and the vertical, and the current vehicle speed. After starting the vehicle, the onboard IMU and OMS modules undergo a self-test to ensure proper sensor operation. A quick calibration is then performed to correct the IMU's zero bias and the OMS's initial line of sight reference, ensuring accurate and reliable data during subsequent acquisition.

[0056] A unified sampling clock is set in the main control unit (ECU), and the IMU and OMS are triggered to start sampling simultaneously through bus broadcast. A timestamp mechanism is used to mark each frame of IMU readings and OMS readings with a system-unified time stamp to ensure that the two sets of data can accurately correspond.

[0057] The onboard IMU continuously reads the vehicle's acceleration values ​​in three directions at a predetermined frequency and caches the raw data in a local buffer. The OMS captures the offset angle between the occupant's head position and the center of the display in real time, and obtains the line of sight offset through a camera or infrared ranging device, which is also cached synchronously.

[0058] A simple check is performed in the local buffer to remove obvious jitter noise or frame loss fragments, and the IMU data and OMS data with timestamps are sent to the main control module through the in-vehicle high-speed bus (CAN) for feature decoupling and compensation calculation.

[0059] The main control module continuously monitors the data flow status. Once packet loss or abnormal fluctuations are detected, it promptly issues resampling or recalibration instructions to ensure continuous and reliable data input.

[0060] After power-up, the three-axis gyroscope built into the vehicle's IMU first performs a self-test to confirm that the output of each axis is normal and that noise and offset are within acceptable ranges. While stationary, it records the raw angular velocity output for a short period of time to correct the zero bias. This clock is shared with the main control unit (ECU), and bus commands trigger the gyroscope to begin continuous sampling. The gyroscope outputs three-axis angular velocity at a fixed frequency, extracts the vertical axis (Yaw) component, appends a system timestamp, and feeds it into the calculation module. The Yaw data is then filtered (e.g., low-pass filtered) in a local buffer to remove high-frequency jitter before being transmitted via the vehicle bus for subsequent processing.

[0061] On a fixed test bench, align the screen or display device with the adjustable motion platform. The platform performs uniform acceleration motion in one or two axes according to the preset amplitude and frequency, and records the actual acceleration change curve at the same time.

[0062] Using a visual tracking system or the screen's internal coordinate system, the pixel displacement of the corresponding dot or marker on the screen is measured. A series of known acceleration values ​​are paired with the corresponding pixel offsets, and a linear fit, such as a least-squares method, is used to derive the acceleration-to-pixel ratio mapping—the pixel scaling factor.

[0063] S2: Construct a three-axis acceleration vector based on the three-axis acceleration data, perform normalization processing on it, and compensate the normalized three-axis acceleration vector based on the vehicle motion correction parameter;

[0064] Specifically, the constructed three-axis acceleration vector retains the linear acceleration of vehicle acceleration or braking and removes the gravity component, which is expressed as:

[0065]

[0066] Among them: a lin is the three-axis acceleration vector after removing the gravity component, a x is the vehicle's x-axis acceleration, a y is the vehicle's y-axis acceleration, a z is the vehicle's z-axis acceleration, g is the gravity component;

[0067] Normalize the acceleration vector and calculate the normalized acceleration vector, which is expressed as:

[0068]

[0069] in: is the normalized acceleration vector;

[0070] Based on the normalized acceleration vector, three compensation factors are calculated using the vehicle motion correction parameters: steering wheel lateral pre-offset, seat longitudinal scaling compensation, and vehicle speed sensitivity factor.

[0071] When the steering wheel turns left, negative lateral compensation is generated, and when the steering wheel turns right, positive lateral compensation is generated. The calculation formula for the steering wheel lateral pre-offset is:

[0072] st F =k s δ

[0073] Among them: st F is the lateral pre-offset of the steering wheel, k s is the lateral offset proportional coefficient, δ is the current steering wheel angle;

[0074] If the angle between the seat back and the vertical direction is below the angle threshold between the seat back and the vertical direction, the seat longitudinal scaling compensation is not triggered;

[0075] If the angle between the seat back and the vertical direction is greater than the angle threshold between the seat back and the vertical direction, the seat longitudinal scaling compensation is triggered and the seat longitudinal scaling compensation calculation is performed, which is expressed as:

[0076] re F =1+k r (θ-θ0)

[0077] Among them: F is the seat longitudinal scaling compensation, k r is the seat longitudinal scaling compensation coefficient, θ is the angle between the seat back and the vertical direction, and θ0 is the angle threshold between the seat back and the vertical direction;

[0078] The calculation formula of vehicle speed sensitivity factor is:

[0079] sp F =1+k v v

[0080] Among them: sp F is the vehicle speed sensitivity factor, k v is the vehicle speed sensitivity coefficient, v is the current speed of the vehicle;

[0081] The steering wheel lateral pre-offset, seat longitudinal scaling compensation and vehicle speed sensitivity factor are integrated to compensate the normalized acceleration vector. The compensated normalized acceleration vector is obtained, which is expressed as:

[0082]

[0083] Among them: a com is the normalized three-axis acceleration vector after compensation, is the normalized vehicle x-axis acceleration, is the normalized vehicle y-axis acceleration, is the normalized vehicle z-axis acceleration;

[0084] Through the above process, while maintaining the original motion feature information, dynamic compensation in three dimensions of steering wheel, seat and vehicle speed is introduced to generate an acceleration perception vector that can reflect the actual driving state, providing input for subsequent visual anchor point calculation and rendering.

[0085] S3: Calculate the screen pixel displacement of the compensated normalized three-axis acceleration vector based on the pixel scaling factor to obtain the pixel displacement. The pixel displacement, the sight offset, and the display screen center coordinates are integrated to obtain the visual anchor point coordinates.

[0086] Specifically, obtain the compensated normalized acceleration vector, sight offset, gyroscope Yaw angular velocity, and pixel scaling factor;

[0087] Calculate the screen pixel displacement and reversely map the vehicle's acceleration perception to the pixel displacement of the dots on the screen based on the inertial visual dynamic inverse mapping principle, expressed as:

[0088]

[0089] Where: Δ in is the pixel displacement, k px is the pixel scaling factor used to convert the physical acceleration level into screen pixel offset; a x ' is the normalized vehicle x-axis acceleration after compensation, a y ' is the normalized vehicle y-axis acceleration after compensation;

[0090] Perform sight offset fusion to generate visual anchor point coordinates. Based on the center coordinates of the display screen, the pixel displacement and sight offset are superimposed to obtain the visual anchor point coordinates, which are expressed as:

[0091] P an =C+Δ in +Δ ga

[0092] Where: P an is the visual anchor point coordinate, C is the display screen center coordinate, Δ ga is the sight line offset;

[0093] S4: Calculate the rotation angle of the virtual layer according to the Yaw angular velocity of the gyroscope, perform angle transformation on the virtual layer on the display screen, and draw a wave dot or prompt mark in the virtual layer after the angle transformation according to the coordinate position of the visual anchor point.

[0094] Specifically, in order to offset the visual dislocation caused by vehicle steering, the gyroscope Yaw angular velocity is introduced and converted into the virtual layer rotation angle through the rotation mapping coefficient, which is expressed as:

[0095] θ off =k rot ω yaw

[0096] Where: θ off The rotation angle of the virtual layer is opposite to the actual steering direction of the vehicle; k rot is the rotation mapping coefficient, used to adjust the rotation sensitivity, ω yaw is the gyroscope Yaw angular velocity;

[0097] In the virtual layer of the display screen, the center of the screen is used as the rotation anchor point, and the entire virtual layer is transformed according to the rotation angle of the virtual layer. In the transformed coordinate system, a wave dot or prompt mark is drawn according to the coordinate position of the visual anchor point;

[0098] The system directly converts the visual anchor points and rotation compensation calculated in real time into AR display effects perceptible to the occupants. Combined with continuous active-passive feedback and health monitoring, it realizes intelligent anti-motion sickness visual assistance for the vehicle's HUD or large screen in the cockpit, thereby significantly reducing the visual instability caused by vehicle movement and steering.

[0099] This embodiment also provides a computer device, which is suitable for the case of a visual anti-dizziness method based on vehicle acceleration, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement all or part of the steps of the method described in the embodiment of the present invention as proposed in the above embodiment.

[0100] This embodiment further provides a storage medium having a computer program stored thereon, which, when executed by a processor, performs the method of any optional implementation of the above embodiment. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0101] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. Technical details not fully described in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0102] In summary, this method achieves accurate perception of vehicle motion and occupant gaze through synchronous acquisition of multi-source sensors; unifies the raw acceleration into comparable and stable inputs through normalization and dynamic compensation; ensures that the visual anchor point is always located in the occupant's area of ​​attention through pixel mapping and line of sight fusion, improving the spatial accuracy of the prompt marker; achieves visual stabilization during steering through virtual layer rotation compensation driven by yaw angular velocity, thereby significantly reducing the incidence of occupant dizziness and providing a highly reliable and comfortable augmented reality anti-sickness solution in various driving scenarios.

[0103] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for preventing visual dizziness based on vehicle acceleration, characterized in that: include, Collect the vehicle's three-axis acceleration data, the line of sight offset between the occupant's head and the display screen, the gyroscope's Yaw angular velocity, the pixel scaling factor, and the vehicle's motion correction parameters; Constructing a three-axis acceleration vector based on the three-axis acceleration data, performing normalization processing, and compensating the normalized three-axis acceleration vector based on the vehicle motion correction parameter; The screen pixel displacement is calculated based on the normalized three-axis acceleration vector after compensation based on the pixel scaling factor to obtain the pixel displacement. The pixel displacement, the sight offset and the center coordinates of the display screen are integrated to obtain the visual anchor point coordinates. The rotation angle of the virtual layer is calculated according to the yaw angular velocity of the gyroscope, the angle of the virtual layer on the display screen is transformed, and a wave dot or prompt mark is drawn in the virtual layer after the angle transformation according to the coordinate position of the visual anchor point.

2. The method for preventing visual dizziness based on vehicle acceleration according to claim 1, wherein: The vehicle motion correction parameters include the current steering wheel angle, the angle between the seat back and the vertical direction, and the current vehicle speed.

3. The method for preventing visual dizziness based on vehicle acceleration according to claim 2, wherein: The normalization process includes: Remove the gravity component from the three-axis acceleration vector and express it as: Among them: a lin is the three-axis acceleration vector after removing the gravity component, a x is the vehicle's x-axis acceleration, a y is the vehicle's y-axis acceleration, a z is the vehicle's z-axis acceleration, g is the gravity component; The normalized acceleration vector is calculated and expressed as: in: is the normalized acceleration vector.

4. The method for preventing visual dizziness based on vehicle acceleration according to claim 3, wherein: The compensating the normalized three-axis acceleration vector based on the vehicle motion correction parameter includes: The steering wheel lateral pre-offset, seat longitudinal scaling compensation and vehicle speed sensitivity factor are calculated respectively through the vehicle motion correction parameters; When the steering wheel turns left, negative lateral compensation is generated, and when the steering wheel turns right, positive lateral compensation is generated. The calculation formula for the steering wheel lateral pre-offset is: st F =k s δ Among them: st F is the lateral pre-offset of the steering wheel, k s is the lateral offset proportional coefficient, δ is the current steering wheel angle; If the angle between the seat back and the vertical direction is below the angle threshold between the seat back and the vertical direction, the seat longitudinal scaling compensation is not triggered; If the angle between the seat back and the vertical direction is greater than the angle threshold between the seat back and the vertical direction, the seat longitudinal scaling compensation is triggered and the seat longitudinal scaling compensation calculation is performed, which is expressed as: re F =1+k r (θ-θ0) Among them: F is the seat longitudinal scaling compensation, k r is the seat longitudinal scaling compensation coefficient, θ is the angle between the seat back and the vertical direction, and θ0 is the angle threshold between the seat back and the vertical direction; The calculation formula of vehicle speed sensitivity factor is: sp F =1+k v v Among them: sp F is the vehicle speed sensitivity factor, k v is the vehicle speed sensitivity coefficient, v is the current speed of the vehicle; The steering wheel lateral pre-offset, seat longitudinal scaling compensation and vehicle speed sensitivity factor are integrated to compensate the normalized acceleration vector. The compensated normalized acceleration vector is obtained, which is expressed as: Among them: a com is the normalized three-axis acceleration vector after compensation, is the normalized vehicle x-axis acceleration, is the normalized vehicle y-axis acceleration, is the normalized vehicle z-axis acceleration.

5. The method for preventing visual dizziness based on vehicle acceleration according to claim 4, wherein: The calculating of screen pixel displacement of the compensated normalized three-axis acceleration vector based on the pixel scaling factor includes: Obtain the compensated normalized acceleration vector and pixel scaling factor to calculate the screen pixel displacement, which is expressed as: Where: Δ in is the pixel displacement, k px is the pixel scaling factor, a x ' is the normalized vehicle x-axis acceleration after compensation, a y ' is the normalized vehicle y-axis acceleration after compensation.

6. The method for preventing visual dizziness based on vehicle acceleration according to claim 5, wherein: The fusing of the pixel displacement, the sight line offset and the center coordinates of the display screen includes: Based on the center coordinates of the display screen, the visual anchor point coordinates are obtained, which are expressed as: P an =C+D in +D ga Where: P an is the visual anchor point coordinate, C is the display screen center coordinate, Δ ga is the sight line offset.

7. The method for preventing visual dizziness based on vehicle acceleration according to claim 6, wherein: Calculating the virtual layer rotation angle according to the gyroscope Yaw angular velocity includes: The gyroscope Yaw angular velocity is converted to the virtual layer rotation angle through the rotation mapping coefficient, which is expressed as: i off =k rot oh yaw Where: θ off The rotation angle of the virtual layer; k rot is the rotation mapping coefficient, ω yaw is the gyroscope Yaw angular velocity.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the vehicle acceleration-based visual anti-sickness method according to any one of claims 1 to 7 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the vehicle acceleration-based visual anti-sickness method according to any one of claims 1 to 7 are implemented.

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