CN114779677A - Method for alleviating carsickness of user based on synchronization of vehicle motion and VR vision - Google Patents

Abstract

The invention belongs to the technical field of VR equipment application, and discloses a method for alleviating carsickness of a user based on vehicle motion and VR vision synchronization, which comprises the following steps: step S001, performing data connection between VR equipment and a vehicle, wherein the VR equipment reads data such as vehicle high-precision GPS positioning data, inertial navigation IMU, vehicle running speed and steering angle of a steering wheel from CAN data controlled in the vehicle and performs data fusion processing; and S002, performing data fusion processing, namely when data such as high-precision GPS positioning data of the vehicle, inertial navigation IMU (inertial navigation unit), vehicle running speed, steering angle of a steering wheel and the like are acquired, checking the stability and randomness of the data by adopting autocorrelation coefficients and partial correlation coefficients, pre-judging the position, the speed and the angle through an LSTM (least squares metric) model when the data are stable, performing interpolation smooth processing, and acquiring more detailed position data l and acceleration data a after model calculation.

Description

A method for alleviating user motion sickness based on synchronization of vehicle motion and VR vision

technical field

The invention belongs to the technical field of VR equipment application, and in particular relates to a method for alleviating motion sickness of a user based on the synchronization of vehicle motion and VR vision.

Background technique

The vestibular organs in the vestibular system of the human body, the three semicircular canals, the utricle and the sac, the perceived balance and speed contradict the visual feedback of the image, and the brain considers poisoning or abnormal when processing the two contradictory signals, and takes Self-protection measures, resulting in motion sickness, also known as motion sickness.

At present, under the application of VR and car combination, passengers will suffer from motion sickness when riding in the car. At the same time, when using VR equipment, because many VR equipment content and games are immersive sports content, the body will be It is a static state, and the vision follows the content of the VR device in a state of motion, which will also cause an imbalance of vision and balance senses, resulting in motion sickness when wearing the current VR device;

In order to solve the dizziness of using VR equipment, the dynamic vision modification method is used, combined with the body movement synchronization method of spinning bike, the visual vestibular system recoupling method realized by artificial wind, and the performance optimization algorithm to solve the dizziness of VR equipment.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a method for alleviating the motion sickness of the user based on the synchronization of vehicle motion and VR vision, so as to solve the dizziness caused by the VR device when the car is driving.

In order to achieve the above object, the present invention provides the following technical solutions: a method for slowing down the user's motion sickness based on the synchronization of vehicle motion and VR vision, comprising the following steps:

Step S001, the VR device and the vehicle are connected to the data, wherein the VR device reads the CAN data controlled by the vehicle, the high-precision GPS positioning data of the vehicle, the inertial navigation IMU, the speed of the vehicle and the steering angle of the steering wheel and other data, and data fusion is performed. deal with;

Step S002, data fusion processing, when acquiring data such as vehicle high-precision GPS positioning data, inertial navigation IMU, vehicle driving speed, steering wheel steering angle, etc., the stability and randomness of the data are carried out by using autocorrelation coefficient and partial correlation coefficient. When the data is stable, the position, speed and angle are pre-judged through the LSTM model, and the interpolation is smoothed at the same time, and the more detailed position data l and acceleration data a are obtained after calculation by the model;

Step S003, using the vehicle speed, the processed smooth vehicle speed*40% is used as the running speed of the VR device content, the acceleration a data is the motion acceleration data in the VR device content, the steering wheel steering data is the VR device content steering data, and the position data l is the positioning data of the operator on the road in the VR device content, and the IMU data is the operator's pose and motion prediction data in the VR device content, and then transmitted through the communication protocol, and the processed data is sent to the SDK software package of the glasses;

Step S004, the VR device puts the data into the bottom layer of the SDK and writes it as a control field for content synchronization. When designing the virtual scene of the VR game or App, the SDK generates and adjusts the scene according to the map data of the real world, and constructs the movement speed, Accelerate and turn the same virtual scene, and obtain a visual picture that is consistent with the daily vestibular senses, speed and steering.

Preferably, in the step S002, the stationarity and randomness of the data are tested by using the autocorrelation coefficient and the partial correlation coefficient, and it also includes judging whether it is a stationary sequence or a non-stationary sequence;

When it is judged that the data is not stationary, the difference operation and the first-order difference and K-order difference operations are used to output the stationary data, and the ARIMA model is used to analyze its stationarity. It means that the data is stable.

Preferably, in the step S004, it also includes, at the same time, using the IMU data fusion processing method in the SDK of the VR device to calibrate the presentation position, the actual position and the lane of the content, so as to ensure that the motion picture of the VR content object presented is delayed from the outside motion picture. When <100ms, the content is synchronized with the actual vehicle operation.

Preferably, in the step S001, the data connection between the VR device and the vehicle includes connecting with the MCU of the vehicle cockpit domain controller through a USB cable, an OBD connector, or through WIFI, Bluetooth.

Compared with the prior art, the beneficial effects of the present invention are:

The present invention is used in a moving vehicle through an immersive VR device, and reads data such as vehicle high-precision GPS positioning data, inertial navigation IMU, vehicle speed and steering wheel steering angle through the VR device, and after data fusion processing, enables The acceleration a data is the motion acceleration data in the VR device content, the steering wheel steering data is the VR device content steering data, the position data l is the operator's positioning data on the road in the VR device content, and the IMU data is the operator's position data in the VR device content. The pose and motion prediction data are then transmitted through the communication protocol, and the processed data is sent to the SDK software package of the glasses;

And put the data into the bottom layer of the SDK through the VR device and write it as the control field of content synchronization. When designing the virtual scene of the VR game or App, the SDK generates and adjusts the scene according to the map data of the real world, and constructs the movement speed and acceleration of the real world. , turn to a consistent virtual scene, and obtain a visual image that is consistent with the daily vestibular senses in speed and steering;

At the same time, the IMU data fusion processing method is used in the SDK of the VR device to calibrate the presentation position of the content, the actual position and the lane, to ensure that the delay between the moving picture of the VR device content object and the external moving picture is less than 100ms, and the synchronization of the content and the real vehicle can be realized. ;

In this way, the contradiction between the balance perception and vision of the vestibular system is reduced by synchronizing the visual information of the car motion with the content of the VR device, mainly to ensure that in the virtual world, the passenger's attention is focused on the content, and the peripheral vision can see the outside environment and the vehicle. Movement; when the environment picture is bound to the speed and turning height, to ensure that the picture seen by the passengers matches the speed of the vehicle, and the vestibular system and vision can be balanced to solve the ride caused by imbalance and motion sickness when viewing VR content; Therefore, the method can effectively improve the user's comfort while riding, reduce the motion sickness of the passengers, and at the same time improve the entertainment of the passengers through the VR device.

Description of drawings

FIG. 1 is a schematic flow chart of the method of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

Referring to FIG. 1, the present invention provides a technical solution: a method for alleviating motion sickness of a user based on the synchronization of vehicle motion and VR vision,

Include the following steps:

Step S001, the VR device and the vehicle are connected to the data, wherein the VR device reads from the CAN data controlled by the vehicle, the high-precision GPS positioning data of the vehicle, the inertial navigation IMU, the speed of the vehicle and the steering angle of the steering wheel and other data, and data fusion is performed. deal with;

Step S002, data fusion processing, when acquiring data such as vehicle high-precision GPS positioning data, inertial navigation IMU, vehicle driving speed, steering wheel steering angle, etc., the stability and randomness of the data are carried out by using autocorrelation coefficient and partial correlation coefficient. When the data is stable, the position, speed and angle are pre-judged through the LSTM model, and the interpolation is smoothed at the same time, and the more detailed position data l and acceleration data a are obtained after calculation by the model;

Step S003, using the vehicle speed, the processed smooth vehicle speed*40% is used as the running speed of the VR device content, the acceleration a data is the motion acceleration data in the VR device content, the steering wheel steering data is the VR device content steering data, and the position data l is the positioning data of the operator on the road in the VR content, the IMU data is the operator's pose and motion prediction data in the VR device content, and then transmitted through the communication protocol, and the processed data is sent to the SDK software package of the glasses;

Step S004, the VR device puts the data into the bottom layer of the SDK and writes it as a control field for content synchronization. When designing the virtual scene of the VR game or App, the SDK generates and adjusts the scene according to the map data of the real world, and constructs the movement speed, Accelerate and turn the same virtual scene, and obtain a visual picture that is consistent with the daily vestibular senses, speed and steering.

Further, in the step S002, the stationarity and randomness of the data are tested by using the autocorrelation coefficient and the partial correlation coefficient, and it also includes judging whether it is a stationary sequence or a non-stationary sequence;

When it is judged that the data is not stationary, the difference operation and the first-order difference and K-order difference operations are used to output the stationary data, and the ARIMA model is used to analyze its stationarity. It means that the data is stable.

Further, the autocorrelation coefficient: the correlation coefficient measurement refers to the degree of mutual influence between two different events; and the autocorrelation coefficient measures the degree of correlation between the same event in two different periods, which is a measure of the image. The impact of your past actions on your present.

Further, partial correlation coefficient: in a system composed of multiple elements, when studying the influence or correlation degree of a certain element on another element, the influence of other elements is regarded as a constant (keep unchanged), that is, it is temporarily ignored. For the influence of other factors, the closeness of the relationship between the two factors is studied separately, and the numerical result obtained is the partial correlation coefficient.

Further, using SPSS to obtain the autocorrelation coefficient map and the partial correlation coefficient map, the autocorrelation coefficient map and the partial correlation coefficient map of the stationary series are either tailed or truncated;

Among them, truncation means that after a certain order, the coefficients are all 0. When the order is 1, the coefficient value is still very large; in the second order, the latter values are very small, and it is considered that it tends to 0. This situation is truncation. tail. The tail has a slow decay trend, but not all 0;

The autocorrelation coefficient plot is neither tailed nor truncated, indicating that the series is not stationary.

Further, in the analysis of the time series by the autocorrelation coefficient in the step S002, the time series {Xt, x∈T}, arbitrarily take t, s∈T, and define γ(t,s) as the autocorrelation of the sequence {Xt}. Covariance function:

γ(t,s)=E(Xt-μt)(Xs-μs)

ρ(t,s)=γ(t,s)/sqrt(DXt×DXs)

Among them, ρ(t,s) is defined as the autocorrelation coefficient of the time series {Xt}, abbreviated as ACF: E represents mathematical expectation, and D represents variance.

Further, in the step S004, it also includes, at the same time, the IMU data fusion processing method is used in the SDK of the VR device to calibrate the presentation position, the actual position and the lane of the content, so as to ensure that the presented VR content object moving picture and the external moving picture are delayed. When <100ms, the content is synchronized with the actual vehicle operation.

Further, in the step S001, the data connection between the VR device and the vehicle includes connecting with the MCU of the vehicle cockpit domain controller through a USB cable, an OBD connector, or through WIFI, Bluetooth.

Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, and substitutions can be made in these embodiments without departing from the principle and spirit of the invention and modifications, the scope of the invention is defined by the appended claims and their equivalents.

Claims (4)

1. A method for relieving user carsickness based on synchronization of vehicle motion and VR vision is characterized by comprising the following steps:

step S001, performing data connection between VR equipment and a vehicle, wherein the VR equipment reads data such as vehicle high-precision GPS positioning data, inertial navigation IMU, vehicle running speed and steering angle of a steering wheel from CAN data controlled in the vehicle and performs data fusion processing;

s002, performing data fusion processing, namely when data such as vehicle high-precision GPS positioning data, inertial navigation IMU, vehicle running speed, steering angle of a steering wheel and the like are obtained, checking the stability and randomness of the data by adopting autocorrelation coefficients and partial correlation coefficients, when the data are stable, pre-judging the position, the speed and the angle through an LSTM model, simultaneously performing interpolation smooth processing, and obtaining more detailed position data l and acceleration data a after model calculation;

step S003, using the vehicle running speed, wherein the processed stable vehicle speed is 40% as the running speed of VR equipment content, the acceleration data a is the motion acceleration data in the VR equipment content, the steering data of the steering wheel is the steering data of the VR equipment content, the position data l is the positioning data of an operator in the VR equipment content in the road, the IMU data is the pose and motion prediction data of the operator in the VR equipment content, and then transmitting the data to the SDK software package of the glasses through a communication protocol;

and step S004, the VR device puts data into an SDK bottom layer to serve as a control field for content synchronization to be written in, when a virtual scene of a VR game or an App is designed, the SDK generates and adjusts the scene according to map data of the real world, constructs the virtual scene consistent with the real movement speed, acceleration and steering, and acquires a visual picture consistent with the sense of the daily vestibule in speed and steering.

2. The method of claim 1, for mitigating user carsickness based on synchronization of vehicle motion with VR vision, comprising: in the step S002, the stationarity and randomness of the data are checked by using an autocorrelation coefficient and a partial correlation coefficient, and whether the data are a stationary sequence or an unstable sequence is determined;

when the unstable data is judged, outputting the stable data by adopting difference and operation containing first-order difference and K-order difference, analyzing the stability by using an ARIMA model, and continuing adopting difference operation until the stable data is output if the unstable data is judged; the stationary sequence then represents the data stationary.

3. The method of claim 1, for mitigating user carsickness based on synchronization of vehicle motion and VR vision, wherein: step S004 further includes, at the same time, performing calibration of the presentation position, the actual position, and the lane of the content by using an IMU data fusion processing manner in the SDK of the VR device, so as to ensure that the delay between the presented VR content object motion picture and the external motion picture is less than 100ms, thereby realizing synchronization of the content and the actual vehicle operation.

4. The method of claim 1, for mitigating user carsickness based on synchronization of vehicle motion and VR vision, wherein: in step S001, the data connection between the VR device and the vehicle includes connecting through a USB cable, an OBD connector, or through WIFI, bluetooth and an MCU of the vehicle cabin domain controller.

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