A method and system for preventing motion sickness based on visual model

Abstract

The present application relates to a method and system for preventing motion sickness based on a visual model, which is applied to automotive electronic products. The method includes: obtaining a vehicle data packet and a road condition data packet in real time; constructing a vehicle behavior model based on the vehicle data packet, and constructing a road condition model based on the road condition data packet; visually fusing the vehicle behavior model and the road condition model, and displaying them on a vehicle-mounted display device. The beneficial effect of the present application is that the present application allows passengers to predict the road condition information and vehicle behavior ahead in advance through a visual model, balance vestibular perception, increase the sense of trust in the vehicle and the sense of control over their own body, so as to achieve the effect of preventing motion sickness.

Description

Technical Field

[0001] The present application relates to the field of automotive electronics technology, and more specifically, to a method and system for preventing motion sickness based on a visual model. Background Art

[0002] With the continuous improvement of science and technology in modern society, the development of automobiles has also improved. Along with the increasing functions of intelligent devices for assisting driving in automobiles, the design and needs are getting closer and closer to humanization. According to relevant statistics, the proportion of people who suffer from motion sickness in the sample population is about 4%-10%. Motion sickness is a pain point for these people when riding in a car, which can cause vomiting, dizziness, nausea and other discomfort reactions. Summary of the invention

[0003] In order to overcome the problem of motion sickness in the above-mentioned prior art, the present application provides an anti-motion sickness method and system based on a visual model.

[0004] A motion sickness prevention method based on a visual model is applied to automotive electronic products, and the method comprises:

[0005] Acquire vehicle data packets and road condition data packets in real time;

[0006] constructing a vehicle behavior model according to the vehicle data packet, and constructing a road condition model according to the road condition data packet;

[0007] The vehicle behavior model and the road condition model are visualized and fused, and displayed on a vehicle-mounted display device.

[0008] Optionally, the vehicle data packet is obtained from a vehicle CAN bus, and the vehicle data packet includes at least one or more of vehicle speed information, turn signal, and braking force information.

[0009] Optionally, the road condition data packet is obtained through at least one or more of a camera, a radar, and a vehicle navigation system.

[0010] Optionally, constructing a vehicle behavior model according to the vehicle data packet includes:

[0011] The current vehicle state is determined according to the vehicle data packet, and a line graph of the light projected along the vehicle travel in the display area is fitted according to the current vehicle state.

[0012] Optionally, the current vehicle state includes at least one or more of a starting state, an acceleration state, a deceleration state, a speed direction change state, a sharp turn state, an uneven road state, and a speed bump state.

[0013] Optionally, the start-up state, acceleration state, and deceleration state line graphs are defined as straight line graphs, wherein the start-up state is a yellow straight line, the acceleration state is a green straight line, and the deceleration state is a purple straight line;

[0014] The line graph of the velocity direction change state is defined as a schematic diagram of upward refraction from a straight line, and the line graph of the velocity direction change state is a blue line;

[0015] The line graph of the sharp turn state is a curve graph;

[0016] The line graph of the road unevenness state is defined as a curve graph with irregular fluctuations, and the color of the line graph of the road unevenness state is orange;

[0017] The line graph of the speed bump state is defined as a curve graph with regular fluctuations, and the color of the line graph of the speed bump state is red.

[0018] Optionally, constructing a traffic condition model according to the traffic condition data packet includes:

[0019] According to the traffic data packet, determine whether the road ahead is bumpy;

[0020] If so, a turbulent and tortuous dark current line graph will be fitted;

[0021] Otherwise, a clear and regular dark flow line graph is meshed.

[0022] Optionally, visually fusing the vehicle behavior model and the road condition model includes:

[0023] The image of the road condition model is used as the background image of the display area, and the vehicle behavior model is used as the foreground image of the display area for fusion.

[0024] Optionally, the image of the vehicle behavior model and the image of the road condition model are both particle compiled and rendered by using an Xparticle particle computing plug-in in C4D.

[0025] In addition, the present application also discloses a system, including a main control module, an information acquisition module, and a display module connected to each other.

[0026] The information acquisition module is connected to one or more of the vehicle CAN bus, vehicle radar sensor, camera, vehicle navigation system, and automatic driving system to acquire vehicle data packets and road condition data packets;

[0027] The main control module runs a program including the above-mentioned anti-motion sickness method based on a visual model, and is used to process vehicle data packets and road condition data packets to identify the vehicle action and road condition of the current vehicle, and to construct a vehicle behavior model and a road condition model;

[0028] The display module is used to display the fused image of the vehicle behavior model and the road condition model.

[0029] Compared with the existing technology, the beneficial effect of the present application is that the present application can allow passengers to predict the road conditions and vehicle behavior ahead in advance through the visual model, balance the vestibular sensation, increase the sense of trust in the vehicle and the sense of control over their own body, so as to achieve the effect of preventing motion sickness. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of an embodiment of the present application.

[0031] Figure 2 This is a line diagram of the road unevenness status in an embodiment of the present application.

[0032] Figure 3 It is a line diagram of the starting state, acceleration state, and deceleration state of the embodiment of the present application.

[0033] Figure 4 This is a line diagram of the sharp turn state of an embodiment of the present application.

[0034] Figure 5 This is a line diagram of the speed direction change state of the embodiment of the present application.

[0035] Figure 6 This is a line diagram of the speed bump status of an embodiment of the present application.

[0036] Figure 7 In the embodiment of the present application, the road ahead is in a bumpy undercurrent line diagram.

[0037] Figure 8 In the embodiment of the present application, the road section ahead is a flat undercurrent line diagram. DETAILED DESCRIPTION

[0038] The present application is further described below in conjunction with specific implementation methods.

[0039] The same or similar numbers in the drawings of the embodiments of the present application correspond to the same or similar parts; in the description of the present application, it should be understood that if the terms "upper", "lower", "left", "right", "top", "bottom", "inside", "outside", etc. indicate the orientation or position relationship, it is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only used for illustrative purposes and cannot be understood as a limitation on this patent.

[0040] In addition, if there are terms such as "first" and "second", they are only used for descriptive purposes, mainly to distinguish different devices, elements or components (the specific types and structures may be the same or different), and are not used to indicate or imply the relative importance and quantity of the indicated devices, elements or components, and cannot be understood as indicating or implying relative importance.

[0041] In such Figure 1-8 In the illustrated embodiment, the present application provides a method for preventing motion sickness based on a visual model, which is applied to automotive electronic products. The method includes:

[0042] 100, real-time acquisition of vehicle data packets and road condition data packets; in this step 100, the vehicle data packets are obtained from the vehicle CAN bus, and the vehicle data packets at least include one or more of vehicle speed information, turn signal, and brake force information. The road condition data is obtained through at least one or more of a camera, a radar, and a vehicle navigation system.

[0043] 200, constructing a vehicle behavior model based on the vehicle data packet, and constructing a road condition model based on the road condition data packet; in step 200, constructing a vehicle behavior model based on the vehicle data packet, including: judging the current vehicle state based on the vehicle data packet, and fitting a line graph of the light projected along the vehicle travel in the display area based on the current vehicle state.

[0044] 300, visually fuse the vehicle behavior model and the road condition model, and display them on the vehicle display device. In step 300, the image of the road condition model is used as the background image of the display area, and the vehicle behavior model is used as the foreground image of the display area for fusion. And displayed on the vehicle display device.

[0045] In some embodiments, the vehicle data packet is obtained from the vehicle CAN bus, and the vehicle data packet includes at least one or more of vehicle speed information, turn signal, and brake force information. In this embodiment, the vehicle-mounted system can access the vehicle CAN bus through the information acquisition module to obtain the vehicle speed information, turn signal, and brake force information light data of the vehicle. Among them, if the current vehicle is in an automatic driving state, the automatic driving system plans the vehicle's speed, turning range, braking force and other driving information in advance according to the road condition information ahead, and outputs the driving information to the information acquisition module. The road condition data packet is obtained by at least one or more of a camera, a radar, and an on-board navigation system. Among them, the road condition data packet 1. Scans and identifies the environmental road conditions ahead and around through the radar, camera and high-precision on-board navigation system on the vehicle, and transmits the information to the main control module for processing.

[0046] In some embodiments, constructing a vehicle behavior model based on a vehicle data packet includes: judging the current vehicle state based on the vehicle data packet, and fitting a line graph of the light projected along the vehicle in the display area based on the current vehicle state. In this embodiment, the present application simulates the vehicle behavior state through a line graph, see Figure 2 The lines of the vehicle driving line graph are projected from the lower end of the display area to the middle of the display area, and a projection origin is set on the free end of the projection to simulate the projection line along the vehicle driving; it more intuitively reflects the vehicle behavior status.

[0047] In one implementation of the above embodiment, the current vehicle state includes at least one or more of a start state, an acceleration state, a deceleration state, a speed direction change state, a sharp turn state, an uneven road state, and a speed bump state. This application selects the above states for illustration, but this application is not limited to the above states. Other vehicle states for visual simulation of vehicle behavior fall within the protection scope of this application.

[0048] Specifically, the start-up state, acceleration state, and deceleration state line graphs of the present application are defined as straight lines: Figure 3 , where the starting state is a yellow straight line, the acceleration state is a green straight line, and the deceleration state is a purple straight line;

[0049] The linear diagram of the velocity direction change state of this application is defined as a schematic diagram of the upward refraction of a straight line Figure 5 , and the line graph of the velocity direction change state is the blue line;

[0050] The line graph of the sharp turn state of this application is a curve graph, see Figure 4 , where the turning direction can be the curve deflection direction;

[0051] The line graph of the road unevenness state in this application is defined as a curve graph with irregular fluctuations, and the color of the line graph of the road unevenness state is orange, see Figure 2 ;

[0052] The line graph of the speed bump state of the present application is defined as a curve graph with regular fluctuations, and the color of the line graph of the speed bump state is red, see Figure 6 .

[0053] In this embodiment, the application defines the line states corresponding to multiple states such as starting state, acceleration state, deceleration state, speed direction change state, sharp turn state, uneven road state, speed bump state, etc. When the vehicle state is recognized as the above state by the main control module, the corresponding line graph is queried to construct the vehicle state model.

[0054] In some embodiments, a road condition model is constructed based on a road condition data packet, including: judging whether the road ahead is bumpy based on the road condition data packet; if so, fitting a turbulent and tortuous dark flow line graph; otherwise meshing a clear and regular dark flow line graph. In this embodiment, the road condition state can be a bumpy state or a non-bumpy state, or can be defined as other states, wherein the dark flow in the dark flow line graph is formed by multiple star points. When the road surface is smooth, the dark flow flows into a planar pattern, and the dark flow pattern is clear and regular, see Figure 8 When the road is bumpy, the undercurrent tends to jump exaggeratedly, and the pattern of the undercurrent becomes agitated and tortuous. Figure 7 .

[0055] In some embodiments, the vehicle behavior model and the road condition model are visualized and fused, including: using the image of the road condition model as the background image of the display area and the vehicle behavior model as the foreground image of the display area. In this embodiment, referring to the figure, the display area felt by the user, the background image is the road condition ahead, and the moving lines are like the current vehicle, which truly and intuitively restores the way the car moves. Through the visual model, passengers can predict the road condition information ahead and the vehicle behavior in advance, balance the vestibular feeling, increase the trust in the vehicle and the sense of control over their own body, so as to achieve the effect of preventing motion sickness.

[0056] In some embodiments, the image of the vehicle behavior model and the image of the road condition model are all compiled and rendered by the Xparticle particle computing plug-in in C4D. In the present embodiment, the information is divided into two categories: vehicle behavior information and road condition information, the thick lines of the image of the vehicle behavior model represent the car information, and the thin lines of the image of the road condition model represent the road condition information, and the visualization effect diagram is simulated in C4D. The line segment of the image of the road condition model is like a nebula, and the image of the vehicle behavior model is like a comet, and the comet shuttles above the nebula, giving new metaphorical connotations to anti-motion sickness visualization. The present application is based on identifying the vehicle behavior state and the road condition state ahead, and then according to the identification content, the Xparticle particle computing plug-in in C4D performs particle compilation and rendering, and constructs the image of the vehicle behavior model and the image of the road condition model. In addition, the present application can also use the system with the same function as C4D to build the model.

[0057] In some embodiments, the present application also discloses a system, including a main control module, an information acquisition module, and a display module that are interconnected. The information acquisition module is connected to one or more of the vehicle CAN bus, vehicle radar sensor, camera, vehicle navigation system, and automatic driving system, and is used to obtain vehicle data packets and road condition data packets; the main control module runs a program including the above-mentioned anti-motion sickness method based on a visual model, which is used to process the vehicle data packet and road condition data packet to identify the vehicle action and road condition of the current vehicle, and to construct a vehicle behavior model and a road condition model; the display module is used to display a fusion image of the vehicle behavior model and the road condition model. In the present application, the vehicle obtains the road condition information ahead through sensors and map information, and identifies and judges it through the MCU. For example, if there is a curve ahead, the curve information will be identified by the MCU, and then the curve elements in the matching conditions will be matched to complete the curve road condition modeling.

[0058] In specific use, according to the analysis of the user's journey, it can be concluded that there are mainly three states in the L3 autonomous driving car interaction: continue interaction, close eyes to rest and open eyes to relieve. This application designs the visualization of anti-motion sickness based on these three states. Specifically, visualizing road conditions and car speed information can help rear-seat passengers balance the different information received by vision and vestibule, increase passengers' sense of control and security over the autonomous driving car, and thus achieve the effect of anti-motion sickness. Among them, the anti-motion sickness method of this application can be a wake-up process of foreground and background jumping, and users can decide whether they need visual interaction for motion sickness according to their needs.

[0059] Obviously, the above embodiments of the present application are merely examples for clearly illustrating the present application, and are not intended to limit the implementation methods of the present application. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all implementation methods here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present application should be included in the protection scope of the claims of the present application.

Claims

1. A motion sickness prevention method based on a visual model, characterized in that: Applied to automotive electronic products, the method comprises: Acquire vehicle data packets and road condition data packets in real time; constructing a vehicle behavior model according to the vehicle data packet, and constructing a road condition model according to the road condition data packet; Visually integrating the vehicle behavior model and the road condition model, and displaying them on a vehicle-mounted display device; Wherein, constructing a vehicle behavior model according to the vehicle data packet includes: According to the vehicle data packet, the current vehicle state is determined, and a line graph of the light projected along the vehicle travel in the display area is fitted according to the current vehicle state; the line graph is projected from the lower end of the display area to the middle of the display area, and a projection origin is set on the free end of the projection, simulating the projection line along the vehicle travel; The visually fusing the vehicle behavior model and the road condition model includes: The image of the road condition model is used as the background image of the display area, and the vehicle behavior model is used as the foreground image of the display area for fusion.

2. The anti-motion sickness method based on a visual model according to claim 1, characterized in that: The vehicle data packet is obtained from a vehicle CAN bus, and the vehicle data packet includes at least one or more of vehicle speed information, turn signal, and brake force information.

3. The anti-motion sickness method based on a visual model according to claim 2, characterized in that: The road condition data packet is obtained through at least one or more of a camera, a radar, and a vehicle navigation system.

4. The anti-motion sickness method based on a visual model according to claim 3, characterized in that: The current vehicle state includes at least one or more of a starting state, an acceleration state, a deceleration state, a speed direction change state, a sharp turn state, an uneven road state, and a speed bump state.

5. The anti-motion sickness method based on a visual model according to claim 4, characterized in that: The start-up state, acceleration state, and deceleration state line graphs are defined as straight line graphs, wherein the start-up state is a yellow straight line, the acceleration state is a green straight line, and the deceleration state is a purple straight line; The line graph of the velocity direction change state is defined as a schematic diagram of upward refraction from a straight line, and the line graph of the velocity direction change state is a blue line; The line graph of the sharp turn state is a curve graph; The line graph of the road unevenness state is defined as a curve graph with irregular fluctuations, and the color of the line graph of the road unevenness state is orange; The line graph of the speed bump state is defined as a curve graph with regular fluctuations, and the color of the line graph of the speed bump state is red.

6. The anti-motion sickness method based on a visual model according to claim 1, characterized in that: The step of constructing a traffic condition model according to the traffic condition data packet comprises: Determine whether the road ahead is bumpy based on the traffic data packet; If so, a turbulent and tortuous dark current line graph will be fitted; Otherwise, a clear and regular dark flow line graph is meshed.

7. The anti-motion sickness method based on a visual model according to claim 1, characterized in that: The image of the vehicle behavior model and the image of the road condition model are both particle compiled and rendered through the Xparticle particle computing plug-in in C4D.

8. A system, characterized in that: It includes a main control module, an information acquisition module, and a display module which are interconnected; The information acquisition module is connected to one or more of the vehicle CAN bus, vehicle radar sensor, camera, vehicle navigation system, and automatic driving system to acquire vehicle data packets and road condition data packets; The main control module is used to execute the anti-motion sickness method based on a visual model as described in any one of claims 1 to 7, so as to process the vehicle data packet and the road condition data packet to identify the vehicle action and road condition of the current vehicle, and to construct a vehicle behavior model and a road condition model; The display module is used to display the fused image of the vehicle behavior model and the road condition model.

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