Device and method for processing and dynamically displaying vehicle graphic data

Abstract

The present application relates to the field of intelligent transportation systems and vehicle-mounted information processing technology, and discloses a device and method for processing and dynamically displaying vehicle graphic data, the device comprising an input module, an information receiving module, an information processing module, a graphic information module and a display control module; the method comprising the following steps: receiving data in real time, and applying a hybrid model preprocessing to the received data, using a composite neural network model to generate semantic tags of graphic content in real time based on the received data, using an adaptive machine learning model to dynamically identify specific scenarios and potential risks in the current driving environment based on the processed data; according to the identified scenarios and risks, selecting the most appropriate information from a preset graphic information library through an advanced decision algorithm for display, and by applying the device and method provided by the present invention, the operability and accuracy of the graphic information display are ensured, thereby improving driving safety and the effectiveness of information transmission.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation systems and vehicle-mounted information processing technology, and in particular to a device and method for processing and dynamically displaying vehicle graphic data. Background Art

[0002] In modern transportation systems, communication and information transfer between vehicles have become particularly important, especially in improving road safety and driving comfort. With the development of intelligent transportation systems, using on-board systems to display important information in real time has become a key technology to improve driver reaction speed and decision-making quality. These systems help drivers better understand the surrounding environment and vehicle conditions by displaying information such as traffic warnings, navigation tips, and vehicle status information.

[0003] Most of the existing automotive display technologies rely on traditional on-board display systems, which usually include some basic graphic display functions, such as speed, fuel level and other information displayed on LED or LCD screens. With the development of technology, some high-end models have begun to adopt more advanced graphical user interfaces and interactive display systems to provide richer graphic content and interactive functions. These systems can provide environmental warnings and driving assistance information to a certain extent, but the presentation of this information is usually not intelligent enough and cannot be dynamically adjusted according to the specific driving environment and real-time data.

[0004] However, existing technologies still have some limitations, especially in terms of the accuracy and efficiency of data processing and dynamic display of graphic information. Traditional systems are usually unable to effectively integrate and process multimodal sensor data from inside and outside the vehicle, resulting in the inability to provide timely and accurate graphic information in complex or emergency driving situations. For example, in bad weather or lighting conditions, existing display systems often cannot automatically adjust display parameters such as brightness and contrast, affecting the visibility and readability of graphic information. This limits the effectiveness of information transmission and increases the risk of driving, especially in emergency situations that require a quick response.

[0005] In addition, during driving, the communication between vehicles mainly relies on light signals (such as brake lights, turn signals) and gestures. However, the information content expressed by these signals is limited and cannot meet the communication needs between vehicles in more complex road traffic.

[0006] In summary, it is necessary to propose a device and method that can effectively integrate and process multimodal sensor data from inside and outside the vehicle, display multi-color text information on the rear of the vehicle (such as the rear window), and output graphic information in a timely and accurate manner in complex or emergency driving situations, so as to more promptly and effectively convey richer and more accurate information to the drivers of the following vehicles, thereby improving driving safety and comfort. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention provides a device and method for processing and dynamically displaying automotive graphic data, which solves the problem that traditional systems are usually unable to effectively integrate and process multimodal sensor data from inside and outside the vehicle, resulting in the inability to provide timely and accurate graphic information in complex or emergency driving situations.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a device for processing and dynamically displaying graphic data for vehicles, the device comprising an input module, an information receiving module, an information processing module, a graphic information module and a display control module;

[0009] The input module is arranged near the vehicle driving platform or on the steering wheel, and is used for the driver to select the corresponding graphic information content, as well as the font and color of the graphic information content according to the display needs from the graphic information library by means of buttons, touch or voice;

[0010] The information receiving module is configured with a variety of sensors, including cameras, radars, microwave sensors and ambient light sensors, for collecting environmental data outside the vehicle, as well as driving data inside the vehicle and data input by the input module;

[0011] The graphic information module is managed by a multi-layer neural network and is used to deploy a graphic information library, preset and update the graphic information content and display parameters associated with the graphic information in the graphic information library, and store the graphic information content and the display parameters;

[0012] The information processing module is equipped with a high-performance GPU and an adaptive machine learning processor, and is used to match the data received by the information receiving module based on a hybrid model, a composite neural network model and an adaptive machine learning model, and determine the displayed graphic information content, as well as the corresponding resolution, font, color, brightness and style from the graphic information library according to the matching processing result;

[0013] The display control module is used to display the graphic information content determined according to the matching processing result in the font and color, and to perform adaptive refresh frequency adjustment and dynamic brightness adjustment on the display effect according to the display environment. The display module is arranged at the rear of the vehicle, and the rear includes the inside of the rear window of the vehicle and the outside of the trunk;

[0014] Among them, the device integrates various modules through an on-board edge computing unit and physical connections to achieve high-speed processing and low-latency response.

[0015] Preferably, the information receiving module further includes night vision and foggy weather vision enhancement functions to improve data collection capabilities under low light and bad weather conditions; the information receiving module transmits the enhanced visual data to the information processing module;

[0016] The display control module also includes a graphic rendering engine, a display unit and a control unit, wherein the graphic rendering engine is used to render the visual representation of the graphics displayed by the graphic information content according to the control instructions sent by the control unit, and transmit the rendered text display data to the display unit; the display unit is used to display the corresponding graphic information content according to the rendered text display data, or dynamically adjust and update the displayed content, resolution, font, color, brightness and style according to the control instructions sent by the control unit; the control unit is used to control the font and color of the graphic information content, and send the control instructions to the display module.

[0017] Preferably, the information processing module applies integrated learning technology, combining decision trees, random forests and deep neural networks to optimize the scene recognition and image and text information selection process, and transmits the scene recognition results to the image and text information library to guide the selection of image and text information content.

[0018] Preferably, the display control module uses real-time ray tracing technology to enhance the depth and layering of the graphic display and adapt to different lighting conditions; the device also includes a power module for providing energy for the operation of the device, and the power module is a vehicle-mounted power supply device or an independent power storage device.

[0019] Accordingly, the present invention also provides a method for processing and dynamically displaying vehicle graphic data, the method comprising the following steps:

[0020] Step 1: Based on the information receiving module, the environmental data collected by the camera, radar, microwave sensor or ambient light sensor, as well as the in-vehicle driving data and the data input by the input module are received in real time, and the hybrid model preprocessing is applied to the received data, including using noise filtering, signal enhancement and data fusion technology to improve data quality and processing efficiency;

[0021] Step 2: The information processing module uses a composite neural network model to generate semantic labels for graphic content in real time based on the received data, and uses an adaptive machine learning model to dynamically identify specific scenarios and potential risks in the current driving environment based on the processed data;

[0022] Step 3: Based on the identified scenarios and risks, the most appropriate information is selected from the preset graphic information library for display through an advanced decision-making algorithm, the semantic tags are matched with the graphic information in the graphic information library, and the graphic information content suitable for the current environment and the status of the vehicle is selected;

[0023] Step 4: Based on the display control module, the selected graphic information is visually optimized, including color saturation adjustment, contrast adjustment, and dynamic resolution adjustment to adapt to the current external visual conditions;

[0024] Step 5: Dynamically display visually optimized graphic information through the display control module, and control the content, font, color and style of the displayed content through the display control module.

[0025] Preferably, in step 2, the composite neural network model includes at least one convolutional neural network layer and at least one recurrent neural network layer, which are used to extract the features of the data received in real time by the information receiving module and generate corresponding semantic labels, and the hybrid model preprocessing step further includes using machine learning technology to automatically correct the environmental sensor data deviation to ensure the accuracy and consistency of the data.

[0026] Preferably, the step one further comprises:

[0027] receiving an input signal, the input signal including an operation instruction of a button, a touch screen or a voice control device, parsing and processing the input signal, generating corresponding text display data, as well as a font, color and style of display, and dynamically displaying graphic information content according to the generated text display data and the font, color and style of display;

[0028] The graphic information includes "thank you", "sorry", "no", "baby in the car" and "danger ahead".

[0029] Each of the graphic information contents can be displayed in different colors. When the graphic information content is "thank you", the corresponding display color is green, when the graphic information content is "sorry", the corresponding display color is blue, when the graphic information content is "no", the corresponding display color is red, when the graphic information content is "there is a baby in the car", the corresponding display color is yellow, and when the graphic information content is "danger ahead", the corresponding display color is purple.

[0030] Preferably, in step 2, the adaptive machine learning model adopts ensemble learning technology, combining decision trees, random forests and deep neural networks to improve the accuracy and response speed of scene recognition.

[0031] Preferably, in step three, the advanced decision algorithm includes an optimized logical reasoning mechanism for quickly selecting the best graphic information response in complex traffic conditions, and dynamically adjusting the displayed visual effects according to different weather and lighting conditions based on a graphic rendering engine.

[0032] Preferably, the method utilizes quantum dot technology to enhance color saturation and contrast, while reducing the impact of direct sunlight through an optical anti-glare layer; the process of automatically adjusting display parameters includes using input from an ambient light sensor and a vehicle speed sensor to dynamically adjust the display brightness and refresh rate of graphic information.

[0033] The present invention provides a device and method for processing and dynamically displaying vehicle graphic data. It has the following beneficial effects:

[0034] 1. The present invention significantly improves the quality and processing efficiency of data collected from the vehicle's internal and external environmental sensor systems by applying hybrid model preprocessing, including noise filtering, signal enhancement and data fusion technology. This ensures that high-quality and high-accuracy graphic content is generated based on the received data, thereby improving driving safety and the effectiveness of information transmission.

[0035] 2. The present invention combines a composite neural network model with an adaptive machine learning model to enable the device provided by the present invention to accurately identify the current driving environment and potential risks based on real-time data. This advanced data processing capability allows the system to respond quickly in complex traffic environments and provide drivers with timely graphic information, thereby enhancing the ability to respond to emergencies.

[0036] 3. The present invention adopts physically based rendering technology through the graphic rendering engine, combined with color saturation adjustment, contrast adjustment and dynamic resolution adjustment, so that the graphic information can maintain the best visual effect under various weather and lighting conditions, which not only improves the readability of the graphic information, but also ensures the visual appeal and effect of information transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a structural diagram of a device for processing and dynamically displaying vehicle graphic data according to the present invention;

[0038] Figure 2 A schematic diagram of power supply for a vehicle graphic data processing and dynamic display device of the present invention;

[0039] Figure 3 The present invention is a flow chart of a method for processing and dynamically displaying vehicle graphic data. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] The present invention provides a device for processing and dynamically displaying graphic data for vehicles, such as Figure 1 As shown, the device includes an input module, an information receiving module, an information processing module, a graphic information module and a display control module;

[0042] The input module is arranged near the vehicle driving platform or on the steering wheel, and is used for the driver to select the corresponding graphic information content, as well as the font and color of the graphic information content according to the display needs from the graphic information library by means of buttons, touch or voice;

[0043] The information receiving module is configured with a variety of sensors, including cameras, radars, microwave sensors and ambient light sensors, for collecting environmental data outside the vehicle, as well as driving data inside the vehicle and data input by the input module;

[0044] The graphic information module is managed by a multi-layer neural network and is used to deploy a graphic information library, preset and update the graphic information content and display parameters associated with the graphic information in the graphic information library, and store the graphic information content and the display parameters;

[0045] The information processing module is equipped with a high-performance GPU and an adaptive machine learning processor, and is used to match the data received by the information receiving module based on a hybrid model, a composite neural network model and an adaptive machine learning model, and determine the displayed graphic information content, as well as the corresponding resolution, font, color, brightness and style from the graphic information library according to the matching processing result;

[0046] The display control module is used to display the graphic information content determined according to the matching processing result in the font and color, and to perform adaptive refresh frequency adjustment and dynamic brightness adjustment on the display effect according to the display environment. The display module is arranged at the rear of the vehicle, and the rear includes the inside of the rear window of the vehicle and the outside of the trunk;

[0047] Among them, the device integrates various modules through an on-board edge computing unit and physical connections to achieve high-speed processing and low-latency response.

[0048] In actual application scenarios, the display control module can also add a rear window multi-level optoelectronic display unit using quantum dot technology and an optical anti-glare layer to display optimized graphic information content, making the visual effect of the graphic information content display clearer and adapting to environmental changes.

[0049] The input module is arranged near the vehicle driving platform or on the steering wheel, for the driver to select the text information to be displayed, and can adopt buttons, touch screens or voice control components, and can be packaged integrally with the control unit or deployed independently. The input module provides an interface for the user to interact with the system, allowing the driver to select specific graphic information according to current needs.

[0050] The input processing formula is: S = decode (I)

[0051] Among them, represents the original signal received from the input device, and the decode(I) function is used to decode the input signal and convert it into an internally recognizable instruction S.

[0052] In this embodiment, the information receiving module further includes night vision and foggy weather vision enhancement functions to improve data collection capabilities under low light and bad weather conditions; the information receiving module transmits the enhanced visual data to the information processing module;

[0053] The display control module also includes a graphic rendering engine, a display unit and a control unit, wherein the graphic rendering engine is used to render the visual representation of the graphics displayed by the graphic information content according to the control instructions sent by the control unit, and transmit the rendered text display data to the display unit; the display unit is used to display the corresponding graphic information content according to the rendered text display data, or dynamically adjust and update the displayed content, resolution, font, color, brightness and style according to the control instructions sent by the control unit; the control unit is used to control the font and color of the graphic information content, and send the control instructions to the display module.

[0054] In the actual deployment and application of the device, the display module can use an LED display screen, an OLED display screen or other low-cost and reliable optoelectronic display devices (such as light strips) to display graphic information, so that the device can take into account both performance and effect in application while making the cost more flexible and controllable.

[0055] The display unit can not only display preset graphic information content, such as "Thank you", "Sorry", "No", "Baby in the car", "Danger ahead", etc., but also display graphic information content customized by the user according to his own needs. However, no matter which method and the displayed graphic information content are used, they all belong to the protection scope of the present invention.

[0056] The control unit is arranged in the vehicle, and can be connected to the display unit by wired connection or wireless connection; the control unit can be packaged integrally with the display unit, or can be deployed independently.

[0057] The display control module is arranged at the rear of the vehicle, usually installed inside the rear window of the vehicle, and can be installed outside the vehicle (including the outside of the trunk, mainly without violating local traffic regulations) when necessary.

[0058] The display unit adopts a bright but not dazzling, low-cost and reliable optoelectronic display device, a display device that does not interfere with the vision of the driver of the following vehicle (mainly an LED or OLED screen, or other display devices: including but not limited to light strips and other devices with high brightness and multi-color display capabilities).

[0059] In this embodiment, the information processing module applies integrated learning technology, combining decision trees, random forests and deep neural networks to optimize the scene recognition and image and text information selection process, and transmits the scene recognition results to the image and text information library to guide the selection of image and text information content.

[0060] In this embodiment, the display control module uses real-time ray tracing technology to enhance the depth and layering of graphic display and adapt to different lighting conditions;

[0061] The device also includes a power module, which is used to provide energy for the operation of the device. The power module is a vehicle-mounted power supply device or an independent power storage device.

[0062] In order to enable the device provided by the present invention to obtain stable power support, as Figure 2 As shown, the power module may include one power supply unit or two power supply units. When two power supply units are selected, each power supply unit can be deployed independently and supply power to different modules; each power supply unit can be connected to the vehicle power supply or use an independent battery.

[0063] In order to make the power supply working state more stable, the power input will be detected and managed during use to ensure stable operation of the system and provide feedback information on "whether the power on and off and power supply are normal or not".

[0064] In order to ensure the reliable operation of the device, the device also includes a system status monitoring module for detecting and reporting faults to ensure the reliability of the operation of the device; and providing feedback information on "whether the system is operating normally or not".

[0065] Corresponding to a device for processing and dynamically displaying graphic data for vehicles, the present invention also provides a method for processing and dynamically displaying graphic data for vehicles, such as Figure 3 As shown, the method comprises the following steps:

[0066] Step 1: Based on the information receiving module, the environmental data collected by the camera, radar, microwave sensor or ambient light sensor, as well as the in-vehicle driving data and the data input by the input module are received in real time, and the hybrid model preprocessing is applied to the received data, including the use of noise filtering, signal enhancement and data fusion technology to improve data quality and processing efficiency.

[0067] In this embodiment, the step one further includes:

[0068] receiving an input signal, the input signal including an operation instruction of a button, a touch screen or a voice control device, parsing and processing the input signal, generating corresponding text display data, as well as a font, color and style of display, and dynamically displaying graphic information content according to the generated text display data and the font, color and style of display;

[0069] The graphic information includes "thank you", "sorry", "no", "baby in the car" and "danger ahead".

[0070] Each of the graphic information contents can be displayed in different colors. When the graphic information content is "thank you", the corresponding display color is green, when the graphic information content is "sorry", the corresponding display color is blue, when the graphic information content is "no", the corresponding display color is red, when the graphic information content is "there is a baby in the car", the corresponding display color is yellow, and when the graphic information content is "danger ahead", the corresponding display color is purple.

[0071] It should be noted that the graphic information content displayed by the device provided by the present invention can not only display preset graphic information content, such as "thank you", "sorry", "no", "baby in car", "danger ahead", etc., but also display graphic information content customized by the user according to his own needs. However, no matter which method and graphic information content displayed, they all belong to the protection scope of the present invention.

[0072] The colors and meanings of the displayed content are as follows:

[0073] a) Thank you: Green text, expressing gratitude to the following vehicle.

[0074] b) Sorry: Blue text, indicating an apology to the car behind.

[0075] c) No: Red text, indicating denial or rejection of a certain operation.

[0076] d) Baby in the car: Yellow text, reminding the driver of the following car that there is a baby in the car and needs to drive carefully.

[0077] e) Danger ahead: Purple text warns drivers of following vehicles that the road ahead is dangerous and they should drive carefully.

[0078] The displayed font can be a colored font or a filled color block with a highlighted font. The relevant display mode and color matching can be personalized and dynamically adjusted according to actual needs.

[0079] Step 2: The information processing module uses a composite neural network model to generate semantic labels for graphic content in real time based on the received data, and uses an adaptive machine learning model to dynamically identify specific scenarios and potential risks in the current driving environment based on the processed data.

[0080] In this embodiment, in step 2, the composite neural network model includes at least one convolutional neural network layer and at least one recurrent neural network layer, which are used to extract the features of the data received in real time by the information receiving module and generate corresponding semantic labels. The hybrid model preprocessing step further includes using machine learning technology to automatically correct the environmental sensor data deviation to ensure the accuracy and consistency of the data.

[0081] In one embodiment, the detailed algorithm formula of the composite neural network model is:

[0082] Feature extraction: F(x) = σ(W*x+b)

[0083] Where x is the input layer data, W and b are network parameters, and σ is the activation function, such as ReLU or Sigmoid;

[0084] Time Series Processing: H t =tanh(W h ·[H t-1 , x t ]+b h )

[0085] Among them, H t is the hidden state at time t, W h and b h are the weights and biases of the RNN layer.

[0086] Semantic tag generation: Y t =softmax(W y ·H t +b y )

[0087] where Y t is the generated semantic label, W y and b y are the weights and biases of the output layer.

[0088] In this embodiment, in step 2, the adaptive machine learning model uses integrated learning technology, combining decision trees, random forests and deep neural networks to improve the accuracy and response speed of scene recognition.

[0089] In one embodiment, the adaptive machine learning model combines the advantages of decision trees, random forests, and deep neural networks through ensemble learning techniques to enhance the generalization ability and response speed of the model. Decision trees provide a fast decision path, random forests enhance the stability and accuracy of the model, and deep neural networks are responsible for extracting complex features and patterns.

[0090] Ensemble learning algorithm formula:

[0091] M(x)=α*DT(x)+β*RF(x)+γ*DNN(x)

[0092] Where M(x) represents the model output, x is the input feature, DT(x), RF(x) represent the outputs of decision tree, random forest and deep neural network respectively, and α, β, γ are the weights of each model output.

[0093] Advanced decision-making algorithm and graphic rendering engine

[0094] Advanced decision algorithm formula:

[0095] R=argmaxi(ωi·Si)

[0096] Where R is the final selected image and text information, Si is the adaptability score of the i-th image and text information, and ωi is the weight of the corresponding information.

[0097] The multi-level optoelectronic display system uses quantum dot technology to enhance color saturation and contrast, while reducing the impact of direct sunlight through an optical anti-glare layer; the process of automatically adjusting display parameters includes using input from ambient light sensors and vehicle speed sensors to dynamically adjust the display brightness and refresh rate of graphic information.

[0098] In one embodiment, quantum dot technology is used to enhance the color saturation and contrast of the display screen. Quantum dots are tiny semiconductor particles that can emit light of a specific color when excited by light. This property makes the quantum dot screen superior in displaying a wider range of colors and deeper blacks. The optical anti-glare layer is used to reduce glare under strong lighting conditions, such as direct sunlight, which helps to maintain the visibility and clarity of the screen content. The display system includes an ambient light sensor and a vehicle speed sensor. The inputs of these sensors are used to dynamically adjust the display brightness and refresh rate of graphic information to adapt to different environmental conditions and vehicle speeds, ensuring the effective transmission of information and driving safety.

[0099] Step 3: Based on the identified scenarios and risks, the most appropriate information is selected from the preset graphic information library for display through advanced decision-making algorithms, the semantic tags are matched with the graphic information in the graphic information library, and the graphic information content suitable for the current environment and the status of the vehicle is selected.

[0100] In this embodiment, in step three, the advanced decision algorithm includes an optimized logical reasoning mechanism for quickly selecting the best graphic information response in complex traffic conditions, and dynamically adjusting the displayed visual effects according to different weather and lighting conditions based on the graphic rendering engine.

[0101] Step 4: Based on the display control module, the selected graphic information is visually optimized, including color saturation adjustment, contrast adjustment, and dynamic resolution adjustment to adapt to current external visual conditions.

[0102] Step 5: Dynamically display visually optimized graphic information through the display control module, and control the content, font, color and style of the displayed content through the display control module.

[0103] In this embodiment, the method uses quantum dot technology to enhance color saturation and contrast, while reducing the impact of direct sunlight through an optical anti-glare layer; the process of automatically adjusting display parameters includes using the input of ambient light sensors and vehicle speed sensors to dynamically adjust the display brightness and refresh rate of graphic information.

[0104] In one embodiment, a high-performance GPU and an adaptive machine learning processor receive raw and enhanced data from a data receiving module; a hybrid model preprocessing and scene recognition process: using ensemble learning techniques (decision trees, random forests, and deep neural networks) to analyze and process data; a specific scene recognition algorithm includes:

[0105] Decision tree algorithm: Classify and make decisions on various types of data by building a tree model.

[0106] Random forest algorithm: an integration of multiple decision trees to improve recognition accuracy and robustness.

[0107] Deep Neural Network (DNN): Perform in-depth analysis and feature extraction of image data through multi-layer perceptron (MLP) or convolutional neural network (CNN).

[0108] Real-time ray tracing formula:

[0109] L(o,ω o )=L e (o,ω o )+∫ Ω f r (o,ω i ,ω o )Li (o,ω i )(ω i ·n)dω i

[0110] Among them, L(o,ω o ) is from point o in direction ω o The radiance on the e is self-luminous, f r is the bidirectional reflectance distribution function (BRDF), L i is the incident radiance, ω i n is the dot product of the incident direction and the normal vector.

[0111] Comparative Example 1:

[0112] Graphic and text display system based on preset templates

[0113] System Description:

[0114] Data receiving module: includes a camera and a GPS sensor, used to collect environmental data and location information inside and outside the vehicle.

[0115] Data processing module: uses fixed algorithms to process the collected data, such as image recognition and geographic information matching.

[0116] Graphic information library: preset a variety of graphic templates, select the appropriate template according to the current location of the vehicle and the detected environment.

[0117] Display control module: adjusts the display content according to the template and refreshes the screen at a fixed frequency.

[0118] Display device: Traditional LCD display, installed in the front of the car.

[0119] Comparative Example 2:

[0120] Dynamic display system based on simple data processing

[0121] System Description:

[0122] Data receiving module: equipped with a camera and basic environmental sensors (such as temperature and humidity sensors).

[0123] Data processing module: Use simple image processing algorithms and data filtering technology to perform basic processing on the received data.

[0124] Graphic information library: contains pre-designed simple graphic information associated with different environmental conditions.

[0125] Display control module: has basic refresh rate adjustment function.

[0126] Display device: On-board display screen, using LED technology.

[0127] Comparative Example 3:

[0128] Graphic and text display system based on fixed rules

[0129] System Description:

[0130] Data receiving module: equipped with fixed sensors (such as vehicle speed sensor, temperature sensor).

[0131] Data processing module: performs data processing based on fixed rules, such as simple conditional judgment.

[0132] Graphics and text information library: stores a variety of graphic and text information, selected according to fixed rules.

[0133] Display control module: controls the display according to predetermined rules.

[0134] Display device: ordinary vehicle-mounted display.

[0135]

[0136] Table 1

[0137] Since Example 1 uses a high-performance GPU and an adaptive machine learning processor, the data preprocessing time and scene recognition time are significantly lower than those of other comparison examples. Example 1 uses a composite neural network model and an adaptive machine learning model to achieve a 95% accuracy rate in scene recognition and a 5% error recognition rate, which is much better than other comparison examples.

[0138] By implementing the above technical solution, the present invention significantly improves the quality and processing efficiency of data collected from the vehicle's internal and external environmental sensor system by applying hybrid model preprocessing, including noise filtering, signal enhancement and data fusion technology. This ensures that high-quality and high-accuracy graphic content is generated based on the received data, thereby improving driving safety and the effectiveness of information transmission.

[0139] The combination of a composite neural network model and an adaptive machine learning model enables the system to accurately identify the current driving environment and potential risks based on real-time data. This advanced data processing capability allows the system to respond quickly in complex traffic environments and provide drivers with timely graphic information, thereby enhancing the ability to respond to emergencies.

[0140] The graphic rendering engine uses physically based rendering technology, combined with color saturation adjustment, contrast adjustment and dynamic resolution adjustment, so that graphic information can maintain the best visual effect under various weather and lighting conditions. This not only improves the readability of graphic information, but also ensures the visual appeal and effect of information transmission.

[0141] In addition, by implementing the above technical solution provided by the present invention, the driver can communicate with the following vehicle through clear and intuitive text messages through simple operations without distracting attention, thereby reducing the possibility of misunderstanding and accidents. At the same time, the color, content, font and color information of the displayed graphic information content can be customized, which further meets different driving environments and personalized needs.

[0142] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A device for processing and dynamically displaying graphic data for vehicles, characterized in that: The device includes an input module, an information receiving module, an information processing module, a graphic information module and a display control module; The input module is arranged near the vehicle driving platform or on the steering wheel, and is used for the driver to select the corresponding graphic information content, as well as the font and color of the graphic information content according to the display needs from the graphic information library by means of buttons, touch or voice; The information receiving module is configured with a variety of sensors, including cameras, radars, microwave sensors and ambient light sensors, for collecting environmental data outside the vehicle, as well as driving data inside the vehicle and data input by the input module; The graphic information module is managed by a multi-layer neural network and is used to deploy a graphic information library, preset and update the graphic information content and display parameters associated with the graphic information in the graphic information library, and store the graphic information content and the display parameters; The information processing module is equipped with a high-performance GPU and an adaptive machine learning processor, and is used to match the data received by the information receiving module based on a hybrid model, a composite neural network model and an adaptive machine learning model, and determine the displayed graphic information content, as well as the corresponding resolution, font, color, brightness and style from the graphic information library according to the matching processing result; The display control module is used to display the graphic information content determined according to the matching processing result in the font and color, and to perform adaptive refresh frequency adjustment and dynamic brightness adjustment on the display effect according to the display environment. The display module is arranged at the rear of the vehicle, and the rear includes the inside of the rear window of the vehicle and the outside of the trunk; Among them, the device integrates various modules through an on-board edge computing unit and physical connections to achieve high-speed processing and low-latency response.

2. The device for processing and dynamically displaying graphic data for vehicles according to claim 1, characterized in that: The information receiving module further includes night vision and foggy weather vision enhancement functions to improve data collection capabilities in low light and bad weather conditions; the information receiving module transmits the enhanced visual data to the information processing module; The display control module also includes a graphic rendering engine, a display unit and a control unit, wherein the graphic rendering engine is used to render the visual representation of the graphics displayed by the graphic information content according to the control instructions sent by the control unit, and transmit the rendered text display data to the display unit; the display unit is used to display the corresponding graphic information content according to the rendered text display data, or dynamically adjust and update the displayed content, resolution, font, color, brightness and style according to the control instructions sent by the control unit; the control unit is used to control the font and color of the graphic information content, and send the control instructions to the display module.

3. The device for processing and dynamically displaying graphic data for vehicles according to claim 1, characterized in that: The information processing module applies integrated learning technology, combining decision trees, random forests and deep neural networks to optimize the scene recognition and image and text information selection process, and transmits the scene recognition results to the image and text information library to guide the selection of image and text information content.

4. The device for processing and dynamically displaying graphic data for vehicles according to claim 1, characterized in that: The display control module uses real-time ray tracing technology to enhance the depth and layering of graphic display and adapt to different lighting conditions; The device also includes a power module, which is used to provide energy for the operation of the device. The power module is a vehicle-mounted power supply device or an independent power storage device.

5. A method for processing and dynamically displaying vehicle graphic data according to the device of claim 1, characterized in that: The method comprises the following steps: Step 1: Based on the information receiving module, the environmental data collected by the camera, radar, microwave sensor or ambient light sensor, as well as the in-vehicle driving data and the data input by the input module are received in real time, and the hybrid model preprocessing is applied to the received data, including using noise filtering, signal enhancement and data fusion technology to improve data quality and processing efficiency; Step 2: The information processing module uses a composite neural network model to generate semantic labels for graphic content in real time based on the received data, and uses an adaptive machine learning model to dynamically identify specific scenarios and potential risks in the current driving environment based on the processed data; Step 3: Based on the identified scenarios and risks, the most appropriate information is selected from the preset graphic information library for display through an advanced decision-making algorithm, the semantic tags are matched with the graphic information in the graphic information library, and the graphic information content suitable for the current environment and the status of the vehicle is selected; Step 4: Based on the display control module, the selected graphic information is visually optimized, including color saturation adjustment, contrast adjustment, and dynamic resolution adjustment to adapt to the current external visual conditions; Step 5: Dynamically display visually optimized graphic information through the display control module, and control the content, font, color and style of the displayed content through the display control module.

6. The method for processing and dynamically displaying vehicle graphic data according to claim 5, characterized in that: In step 2, the composite neural network model includes at least one convolutional neural network layer and at least one recurrent neural network layer, which are used to extract the features of the data received in real time by the information receiving module and generate corresponding semantic labels. The hybrid model preprocessing step further includes using machine learning technology to automatically correct the environmental sensor data deviation to ensure the accuracy and consistency of the data.

7. The method for processing and dynamically displaying vehicle graphic data according to claim 5, characterized in that: The step one also includes: receiving an input signal, the input signal including an operation instruction of a button, a touch screen or a voice control device, parsing and processing the input signal, generating corresponding text display data, as well as a font, color and style of display, and dynamically displaying graphic information content according to the generated text display data and the font, color and style of display; The graphic information includes "thank you", "sorry", "no", "baby in the car" and "danger ahead". Each of the graphic information contents can be displayed in different colors. When the graphic information content is "thank you", the corresponding display color is green, when the graphic information content is "sorry", the corresponding display color is blue, when the graphic information content is "no", the corresponding display color is red, when the graphic information content is "there is a baby in the car", the corresponding display color is yellow, and when the graphic information content is "danger ahead", the corresponding display color is purple.

8. The method for processing and dynamically displaying vehicle graphic data according to claim 5, characterized in that: In step 2, the adaptive machine learning model uses ensemble learning technology, combining decision trees, random forests and deep neural networks to improve the accuracy and response speed of scene recognition.

9. The method for processing and dynamically displaying vehicle graphic data according to claim 5, characterized in that: In step three, the advanced decision algorithm includes an optimized logical reasoning mechanism for quickly selecting the best graphic information response in complex traffic conditions, and dynamically adjusting the displayed visual effects according to different weather and lighting conditions based on the graphic rendering engine.

10. The method for processing and dynamically displaying vehicle graphic data according to claim 5, characterized in that: The method utilizes quantum dot technology to enhance color saturation and contrast, while reducing the impact of direct sunlight through an optical anti-glare layer; the process of automatically adjusting display parameters includes using input from an ambient light sensor and a vehicle speed sensor to dynamically adjust the display brightness and refresh rate of graphic information.

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