Intelligent windshield system and method

Abstract

The present invention discloses an intelligent windshield system and method, relating to the fields of automobile manufacturing and intelligent display technology. The windshield system includes a high-definition projection module, an environmental perception sensor data acquisition module, a data processing module, an intelligent interaction module, and a vehicle status monitoring module. The present invention proposes that by real-time monitoring of the vehicle's surrounding environment and vehicle status, the system can promptly identify and alert the driver to potential dangers, reducing the probability of accidents and improving driving safety. The high-definition projection module projects key information directly onto the windshield in the form of graphic symbols and text, allowing the driver to quickly and intuitively obtain important information such as navigation, vehicle speed, and fuel level, reducing distraction caused by looking down at the instrument panel. Integrated voice, gesture, and eye-tracking control methods allow the driver to interact with the system more naturally, reducing operational complexity.

Description

Technical Field

[0001] The present invention relates to the fields of automobile manufacturing and intelligent display technology, and in particular to an intelligent windshield system and method. Background Art

[0002] With the advancement of technology and the rapid development of intelligent vehicles, traditional windshields have gradually failed to meet the needs of modern car users. The main function of traditional windshields is to provide a clear driving field of view and prevent interference from natural factors such as wind, rain, and sunlight. However, with the popularization of smart cars, users' demands for windshield functions are also increasing, such as information display, interactive feedback, and automatic adjustment of transparency.

[0003] Therefore, the present invention proposes a novel intelligent windshield, which aims to improve driving convenience and safety by integrating multiple intelligent functions. Summary of the Invention

[0004] In order to solve the above technical problems, an intelligent windshield system and method are provided, and this technical solution solves the above problems.

[0005] In order to achieve the above objects, the technical solution adopted by the present invention is:

[0006] An intelligent windshield system, the windshield system comprising:

[0007] High-definition projection module: The high-definition projection module is used to display information on the windshield based on optical projection technology;

[0008] Environmental perception sensor data acquisition module: The environmental perception sensor data acquisition module is electrically connected to the high-definition projection module and is used to integrate sensor data and capture vehicle surrounding environment information in real time;

[0009] Data processing module: The data processing module is electrically connected to the environmental perception sensor data acquisition module. The data processing module is used to analyze and process sensor data in real time based on deep learning and computer vision technology, identify key information, and convert it into graphic symbols and text, which are projected onto the windshield;

[0010] Intelligent interaction module: The intelligent interaction module is electrically connected to the data processing module and is used to capture the driver's voice, gestures, and eye contact information to control the content and form of information displayed;

[0011] Vehicle status monitoring module: The vehicle status monitoring module is electrically connected to the intelligent interaction module. The vehicle status monitoring module is used to monitor the operating parameters of the vehicle in real time. Once an abnormality occurs, an alarm is issued on the windshield to remind the driver to take corresponding measures.

[0012] Preferably, the high-definition projection module specifically includes:

[0013] Requirements acquisition unit: determines the functional requirements of the projection module, including navigation, vehicle speed, and warnings;

[0014] Optical System Design Unit: Design projection optical systems, including lenses and reflectors, to ensure that the optical system can project information onto the windshield at the appropriate angle and size, and use simulation software to optimize the optical path;

[0015] Image processing and generation unit: Based on the functional requirements of the projection module, it uses image processing technology to generate projection images and uses image enhancement technology to process images;

[0016] Anti-glare Design Unit: Design anti-glare coatings or use special optical materials, evaluate the impact of different coatings on glare, and ensure that projections are clearly visible in strong light environments;

[0017] Projection Correction Unit: Performs geometric correction and color correction to ensure accurate projection content and adjusts the image using correction algorithms.

[0018] Preferably, the environment perception sensor data acquisition module specifically includes:

[0019] Data acquisition unit: Develop a data acquisition module to acquire data in real time from various sensors, including cameras, radars, and laser scanners;

[0020] Data fusion unit: Based on the data fusion algorithm, it integrates the data from different sensors, uses Kalman filtering to remove noise, and converts radar and LIDAR data into a unified coordinate system;

[0021] The data fusion algorithm formula is:

[0022]

[0023] Where, is the estimated value after fusion, For the The measured values ​​of the sensors, For the The weight of each sensor, is the number of sensors.

[0024] Preferably, the data processing module specifically includes:

[0025] Environmental feature recognition unit: uses computer vision to analyze fused data, extract features, and identify the status of traffic signs, pedestrians, and obstacles;

[0026] Edge detection unit: calculates the color histogram of each pixel, uses the Canny edge detection algorithm to extract edge features in the image, uses the local binary pattern method to extract the texture information of the image, uses the directional gradient histogram to extract the shape features of the object, and uses the contour detection function of OpenCV to extract the contour information of the object in the image;

[0027] Feature extraction unit: performs image classification and feature extraction based on the convolutional neural network extraction formula;

[0028] State recognition unit: Outputs the model results, sets a confidence threshold, and only retains detection results above the threshold. Based on non-maximum suppression, it eliminates duplicate bounding boxes and only retains the bounding boxes with the highest confidence. It determines the category of traffic signs, detects the position and movement status of pedestrians, and identifies and classifies the type of obstacles. After identification, the system displays the detection results accordingly.

[0029] When dangerous traffic signs, pedestrians and obstacles are identified, alarms are triggered and real-time feedback is provided.

[0030] Preferably, the feature extraction unit specifically includes:

[0031] Image classification and feature extraction are performed based on the convolutional neural network extraction formula to perform real-time target detection. The convolutional neural network extraction formula is:

[0032]

[0033] Where, is an element in the output feature map, is the input feature map, is the convolution kernel, is the bias term are the coordinates of the output feature map, and is the size of the convolution kernel.

[0034] Preferably, the intelligent interaction module specifically includes:

[0035] Speech recognition unit: This unit recognizes the driver's commands and requests through voice input, collects the driver's voice, filters background noise, converts audio signals into text, and interprets voice commands;

[0036] Gesture control unit: recognizes the driver's gestures for control, captures the driver's gestures, provides real-time image input, analyzes image data, recognizes specific gestures and performs corresponding operations;

[0037] Eye tracking unit: Provides control by tracking the driver's gaze direction. Using an infrared camera, it captures eye movements and gaze points, analyzes eye position and movement, and determines the target of gaze.

[0038] User interface unit: displays information and interacts with the driver;

[0039] Data processing unit: processes data from various modules and makes decisions, feeding back the status of executed commands to the driver.

[0040] Preferably, the vehicle status monitoring module specifically includes:

[0041] Data acquisition unit: sensors continuously monitor the vehicle's operating parameters and send the data to the data processing unit in real time;

[0042] Data processing unit: Receives data from each sensor and uses an anomaly detection algorithm to analyze it in real time to determine whether any parameters are out of the normal range. If an anomaly is detected, the data processing unit immediately sends the information to the warning display unit and feedback response unit;

[0043] Warning Display Unit: The warning display unit displays warning information on the windshield through the head-up display, including "engine overheating" and "brake system failure", ensuring that the driver can quickly see the warning while driving;

[0044] Real-time monitoring unit: In the warning state, the monitoring module continues to monitor relevant parameters in real time to observe whether there is any improvement. The driver takes corresponding measures based on the information provided by the system.

[0045] A smart windshield method, comprising:

[0046] The system uses environmental perception sensors to capture real-time traffic information around it, including the distance to the vehicle ahead, road markings, and traffic light status.

[0047] Image processing and fusion algorithms transform the collected information into intuitive symbols and arrows, which are then projected onto the windshield via a projection module;

[0048] The system dynamically adjusts the level of detail of navigation instructions based on the vehicle's real-time location and speed, providing detailed turn instructions at complex intersections and reducing information display on straight sections of road.

[0049] The system displays vehicle speed and fuel level information in real time, and alerts the driver through icons and sound alarms when any abnormality is detected.

[0050] Preferably, the image processing and fusion algorithm converts the collected information into intuitive symbols and arrows, and projects them onto the windshield through the projection module, specifically including:

[0051] Use computer vision to analyze the fused data, extract features, and identify the status of traffic signs, pedestrians, and obstacles;

[0052] Calculate the color histogram of each pixel, extract the edge features and texture information of the image, extract the shape features of the object, and extract the contour information of the object in the image;

[0053] Image classification and feature extraction based on convolutional neural network extraction formula;

[0054] The model results are output to determine the category of traffic signs, detect the position and movement status of pedestrians, and identify and classify the types of obstacles. After identification, the system will display the corresponding results based on the detection results.

[0055] Preferably, the system displays vehicle speed and fuel level information in real time, and when an abnormality is detected, alerts the driver through icons and sound alarms. Specifically, the system includes:

[0056] Sensors continuously monitor the vehicle's operating parameters and send data to the data processing unit in real time;

[0057] Receive data from each sensor and analyze it in real time using an anomaly detection algorithm to determine if any parameters are outside the normal range. If an anomaly is detected, the data processing unit immediately sends the information to the warning display unit and the feedback response unit;

[0058] Warning messages, including "engine overheating" and "brake system failure", are displayed on the windshield. In the warning state, the monitoring module continues to monitor relevant parameters in real time to observe whether there is any improvement. The driver takes corresponding measures based on the information provided by the system.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] The present invention proposes that by real-time monitoring of the vehicle's surrounding environment and vehicle status, the system can promptly identify and alert the driver to potential dangers, such as pedestrians, traffic signs and obstacles. This real-time feedback greatly reduces the probability of accidents and improves driving safety. The high-definition projection module projects key information directly onto the windshield in the form of graphic symbols and text, allowing the driver to quickly and intuitively obtain important information such as navigation, vehicle speed, and fuel level, reducing distraction caused by looking down at the dashboard. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a step flow chart of the present invention;

[0062] Figure 2 This is a system framework diagram of the present invention. DETAILED DESCRIPTION

[0063] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are merely examples, and those skilled in the art may conceive of other obvious variations.

[0064] Reference Figure 1 As shown, an intelligent windshield system, the windshield system includes:

[0065] High-definition projection module: The high-definition projection module is used to display information on the windshield based on optical projection technology;

[0066] Environmental perception sensor data acquisition module: The environmental perception sensor data acquisition module is electrically connected to the high-definition projection module and is used to integrate sensor data and capture vehicle surrounding environment information in real time;

[0067] Data processing module: The data processing module is electrically connected to the environmental perception sensor data acquisition module. The data processing module is used to analyze and process sensor data in real time based on deep learning and computer vision technology, identify key information, and convert it into graphic symbols and text, which are projected onto the windshield;

[0068] Intelligent interaction module: The intelligent interaction module is electrically connected to the data processing module and is used to capture the driver's voice, gestures, and eye contact information to control the content and form of information displayed;

[0069] Vehicle status monitoring module: The vehicle status monitoring module is electrically connected to the intelligent interaction module. The vehicle status monitoring module is used to monitor the operating parameters of the vehicle in real time. Once an abnormality occurs, an alarm is issued on the windshield to remind the driver to take corresponding measures.

[0070] The high-definition projection module specifically includes:

[0071] Requirements acquisition unit: determines the functional requirements of the projection module, including navigation, vehicle speed, and warnings;

[0072] Optical System Design Unit: Design projection optical systems, including lenses and reflectors, to ensure that the optical system can project information onto the windshield at the appropriate angle and size, and use simulation software to optimize the optical path;

[0073] Image processing and generation unit: Based on the functional requirements of the projection module, it uses image processing technology to generate projection images and uses image enhancement technology to process images;

[0074] Anti-glare Design Unit: Design anti-glare coatings or use special optical materials, evaluate the impact of different coatings on glare, and ensure that projections are clearly visible in strong light environments;

[0075] Projection Correction Unit: Performs geometric correction and color correction to ensure accurate projection content and adjusts the image using correction algorithms.

[0076] The environment perception sensor data acquisition module specifically includes:

[0077] Data acquisition unit: Develop a data acquisition module to acquire data in real time from various sensors, including cameras, radars, and laser scanners;

[0078] Data fusion unit: Based on the data fusion algorithm, it integrates the data from different sensors, uses Kalman filtering to remove noise, and converts radar and LIDAR data into a unified coordinate system;

[0079] The data fusion algorithm formula is:

[0080]

[0081] Where, is the estimated value after fusion, For the The measured values ​​of the sensors, For the The weight of each sensor, is the number of sensors.

[0082] The data processing module specifically includes:

[0083] Environmental feature recognition unit: uses computer vision to analyze fused data, extract features, and identify the status of traffic signs, pedestrians, and obstacles;

[0084] Edge detection unit: calculates the color histogram of each pixel, uses the Canny edge detection algorithm to extract edge features in the image, uses the local binary pattern method to extract the texture information of the image, uses the directional gradient histogram to extract the shape features of the object, and uses the contour detection function of OpenCV to extract the contour information of the object in the image;

[0085] Feature extraction unit: performs image classification and feature extraction based on the convolutional neural network extraction formula;

[0086] State recognition unit: Outputs the model results, sets a confidence threshold, and only retains detection results above the threshold. Based on non-maximum suppression, it eliminates duplicate bounding boxes and only retains the bounding boxes with the highest confidence. It determines the category of traffic signs, detects the position and movement status of pedestrians, and identifies and classifies the type of obstacles. After identification, the system displays the detection results accordingly.

[0087] When dangerous traffic signs, pedestrians and obstacles are identified, alarms are triggered and real-time feedback is provided.

[0088] The feature extraction unit specifically includes:

[0089] Image classification and feature extraction are performed based on the convolutional neural network extraction formula to perform real-time target detection. The convolutional neural network extraction formula is:

[0090]

[0091] Where, is an element in the output feature map, is the input feature map, is the convolution kernel, is the bias term are the coordinates of the output feature map, and is the size of the convolution kernel.

[0092] The intelligent interaction module specifically includes:

[0093] Speech recognition unit: This unit recognizes the driver's commands and requests through voice input, collects the driver's voice, filters background noise, converts audio signals into text, and interprets voice commands;

[0094] Gesture control unit: recognizes the driver's gestures for control, captures the driver's gestures, provides real-time image input, analyzes image data, recognizes specific gestures and performs corresponding operations;

[0095] Eye tracking unit: Provides control by tracking the driver's gaze direction. Using an infrared camera, it captures eye movements and gaze points, analyzes eye position and movement, and determines the target of gaze.

[0096] User interface unit: displays information and interacts with the driver;

[0097] Data processing unit: processes data from various modules and makes decisions, feeding back the status of executed commands to the driver.

[0098] The vehicle status monitoring module specifically includes:

[0099] Data acquisition unit: sensors continuously monitor the vehicle's operating parameters and send the data to the data processing unit in real time;

[0100] Data processing unit: Receives data from each sensor and uses an anomaly detection algorithm to analyze it in real time to determine whether any parameters are out of the normal range. If an anomaly is detected, the data processing unit immediately sends the information to the warning display unit and feedback response unit;

[0101] Warning Display Unit: The warning display unit displays warning information on the windshield through the head-up display, including "engine overheating" and "brake system failure", ensuring that the driver can quickly see the warning while driving;

[0102] Real-time monitoring unit: In the warning state, the monitoring module continues to monitor relevant parameters in real time to observe whether there is any improvement. The driver takes corresponding measures based on the information provided by the system.

[0103] Reference Figure 2 As shown, a smart windshield method includes:

[0104] The system uses environmental perception sensors to capture real-time traffic information around it, including the distance to the vehicle ahead, road markings, and traffic light status.

[0105] Image processing and fusion algorithms transform the collected information into intuitive symbols and arrows, which are then projected onto the windshield via a projection module;

[0106] The system dynamically adjusts the level of detail of navigation instructions based on the vehicle's real-time location and speed, providing detailed turn instructions at complex intersections and reducing information display on straight sections of road.

[0107] The system displays vehicle speed and fuel level information in real time, and alerts the driver through icons and sound alarms when any abnormality is detected.

[0108] The image processing and fusion algorithm converts the collected information into intuitive symbols and arrows, which are projected onto the windshield via the projection module. Specifically, the algorithm includes:

[0109] Use computer vision to analyze the fused data, extract features, and identify the status of traffic signs, pedestrians, and obstacles;

[0110] Calculate the color histogram of each pixel, extract the edge features and texture information of the image, extract the shape features of the object, and extract the contour information of the object in the image;

[0111] Image classification and feature extraction based on convolutional neural network extraction formula;

[0112] The model results are output to determine the category of traffic signs, detect the position and movement status of pedestrians, and identify and classify the types of obstacles. After identification, the system will display the corresponding results based on the detection results.

[0113] The system displays vehicle speed and fuel level information in real time and alerts the driver through icons and sound alarms when an anomaly is detected.

[0114] Sensors continuously monitor the vehicle's operating parameters and send data to the data processing unit in real time;

[0115] Receive data from each sensor and analyze it in real time using an anomaly detection algorithm to determine if any parameters are outside the normal range. If an anomaly is detected, the data processing unit immediately sends the information to the warning display unit and the feedback response unit;

[0116] Warning messages, including "engine overheating" and "brake system failure", are displayed on the windshield. In the warning state, the monitoring module continues to monitor relevant parameters in real time to observe whether there is any improvement. The driver takes corresponding measures based on the information provided by the system.

[0117] In summary, the advantages of the present invention are:

[0118] By monitoring the vehicle's surroundings and status in real time, the system can promptly identify and alert the driver to potential hazards, such as pedestrians, traffic signs, and obstacles. This real-time feedback significantly reduces the probability of accidents and improves driving safety.

[0119] The high-definition projection module projects key information directly onto the windshield in the form of graphic symbols and text, allowing the driver to quickly and intuitively obtain important information such as navigation, vehicle speed, and fuel level, reducing distraction caused by looking down at the instrument panel;

[0120] Integrated voice, gesture, and eye-tracking control enable drivers to interact with the system more naturally, reducing operational complexity while improving access to information. Drivers can control navigation and vehicle settings with simple voice commands or gestures, enhancing driving pleasure and comfort.

[0121] The vehicle status monitoring module continuously analyzes real-time data and can quickly alert drivers through visual and audible alarms when vehicle abnormalities occur, ensuring that drivers can take timely measures to reduce the risk of accidents caused by faults;

[0122] The system dynamically adjusts the level of detail of navigation instructions based on the vehicle's real-time location and speed. It provides detailed turn instructions at complex intersections while reducing information display on straight sections, avoiding information overload and improving navigation efficiency and practicality.

[0123] Advanced deep learning and computer vision technologies are used for data processing to ensure accurate and real-time environmental perception. This efficient data processing can quickly identify the status of traffic signs, pedestrians, and obstacles, and provide corresponding displays and feedback, thus enhancing the intelligence level of the system.

[0124] Through the optimization of the user interface unit, the driver can view all important information intuitively, and the system's interactive design is more humane, which improves the driver's acceptance and convenience of operation.

[0125] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent windshield system, characterized in that: The windshield system includes: High-definition projection module: The high-definition projection module is used to display information on the windshield based on optical projection technology; Environmental perception sensor data acquisition module: The environmental perception sensor data acquisition module is electrically connected to the high-definition projection module and is used to integrate sensor data and capture vehicle surrounding environment information in real time; Data processing module: The data processing module is electrically connected to the environmental perception sensor data acquisition module. The data processing module is used to analyze and process sensor data in real time based on deep learning and computer vision technology, identify key information, and convert it into graphic symbols and text, which are projected onto the windshield; Intelligent interaction module: The intelligent interaction module is electrically connected to the data processing module and is used to capture the driver's voice, gestures, and eye contact information to control the content and form of information displayed; Vehicle status monitoring module: The vehicle status monitoring module is electrically connected to the intelligent interaction module. The vehicle status monitoring module is used to monitor the operating parameters of the vehicle in real time. Once an abnormality occurs, an alarm is issued on the windshield to remind the driver to take appropriate measures; The high-definition projection module specifically includes: Requirements acquisition unit: determines the functional requirements of the projection module, including navigation, vehicle speed, and warnings; Optical System Design Unit: Design projection optical systems, including lenses and reflectors, to ensure that the optical system can project information onto the windshield at the appropriate angle and size, and use simulation software to optimize the optical path; Image processing and generation unit: Based on the functional requirements of the projection module, it uses image processing technology to generate projection images and uses image enhancement technology to process images; Anti-glare Design Unit: Design anti-glare coatings or use special optical materials, evaluate the impact of different coatings on glare, and ensure that projections are clearly visible in strong light environments; Projection correction unit: performs geometric correction and color correction to ensure the accuracy of the projected content and adjusts the image using correction algorithms; The data processing module specifically includes: Environmental feature recognition unit: uses computer vision to analyze fused data, extract features, and identify the status of traffic signs, pedestrians, and obstacles; Edge detection unit: calculates the color histogram of each pixel, uses the Canny edge detection algorithm to extract edge features in the image, uses the local binary pattern method to extract the texture information of the image, uses the directional gradient histogram to extract the shape features of the object, and uses the contour detection function of OpenCV to extract the contour information of the object in the image; Feature extraction unit: performs image classification and feature extraction based on the convolutional neural network extraction formula; State recognition unit: Outputs the model results, sets a confidence threshold, and only retains detection results above the threshold. Based on non-maximum suppression, it eliminates duplicate bounding boxes and only retains the bounding boxes with the highest confidence. It determines the category of traffic signs, detects the position and movement status of pedestrians, and identifies and classifies the type of obstacles. After identification, the system displays the detection results accordingly. When dangerous traffic signs, pedestrians and obstacles are identified, alarms are triggered and real-time feedback is provided.

2. The intelligent windshield system according to claim 1, characterized in that: The environment perception sensor data acquisition module specifically includes: Data acquisition unit: Develop a data acquisition module to acquire data in real time from various sensors, including cameras, radars, and laser scanners; Data fusion unit: Based on the data fusion algorithm, it integrates the data from different sensors, uses Kalman filtering to remove noise, and converts radar and LIDAR data into a unified coordinate system; The data fusion algorithm formula is: Where, is the estimated value after fusion, x i is the measurement value of the i-th sensor, w i is the weight of the i-th sensor, and n is the number of sensors.

3. The intelligent windshield system according to claim 1, characterized in that: The feature extraction unit specifically includes: Image classification and feature extraction are performed based on the convolutional neural network extraction formula to perform real-time target detection. The convolutional neural network extraction formula is: Where Z is an element in the output feature map, X is the input feature map, K is the convolution kernel, b is the bias term, ij is the coordinate of the output feature map, and m and l are the sizes of the convolution kernel.

4. The intelligent windshield system according to claim 1, characterized in that: The intelligent interaction module specifically includes: Speech recognition unit: This unit recognizes the driver's commands and requests through voice input, collects the driver's voice, filters background noise, converts audio signals into text, and interprets voice commands; Gesture control unit: recognizes the driver's gestures for control, captures the driver's gestures, provides real-time image input, analyzes image data, recognizes specific gestures and performs corresponding operations; Eye tracking unit: Provides control by tracking the driver's gaze direction. Using an infrared camera, it captures eye movements and gaze points, analyzes eye position and movement, and determines the target of gaze. User interface unit: displays information and interacts with the driver; Data processing unit: processes data from various modules and makes decisions, feeding back the status of executed commands to the driver.

5. The intelligent windshield system according to claim 4, characterized in that: The vehicle status monitoring module specifically includes: Data acquisition unit: sensors continuously monitor the vehicle's operating parameters and send the data to the data processing unit in real time; Data processing unit: Receives data from each sensor and uses an anomaly detection algorithm to analyze it in real time to determine whether any parameters are out of the normal range. If an anomaly is detected, the data processing unit immediately sends the information to the warning display unit and feedback response unit; Warning Display Unit: The warning display unit displays warning information on the windshield through the head-up display, including "engine overheating" and "brake system failure", ensuring that the driver can quickly see warnings while driving; Real-time monitoring unit: In the warning state, the monitoring module continues to monitor relevant parameters in real time to observe whether there is any improvement. The driver takes corresponding measures based on the information provided by the system.

6. An intelligent windshield method for the intelligent windshield system according to claim 1, characterized in that: include: The system uses environmental perception sensors to capture real-time traffic information around it, including the distance to the vehicle ahead, road markings, and traffic light status. Image processing and fusion algorithms transform the collected information into intuitive symbols and arrows, which are then projected onto the windshield via a projection module; The system dynamically adjusts the level of detail of navigation instructions based on the vehicle's real-time location and speed, providing detailed turn instructions at complex intersections and reducing information display on straight sections of road. The system displays vehicle speed and fuel level information in real time, and alerts the driver through icons and sound alarms when any abnormality is detected.

7. The intelligent windshield method according to claim 6, characterized in that: The image processing and fusion algorithm converts the collected information into intuitive symbols and arrows, which are projected onto the windshield via the projection module. Specifically, the algorithm includes: Use computer vision to analyze the fused data, extract features, and identify the status of traffic signs, pedestrians, and obstacles; Calculate the color histogram of each pixel, extract the edge features and texture information of the image, extract the shape features of the object, and extract the contour information of the object in the image; Image classification and feature extraction based on convolutional neural network extraction formula; The model results are output to determine the category of traffic signs, detect the position and movement status of pedestrians, and identify and classify the types of obstacles. After identification, the system will display the corresponding results based on the detection results.

8. The intelligent windshield method according to claim 7, characterized in that: The system displays vehicle speed and fuel level information in real time and alerts the driver through icons and sound alarms when an anomaly is detected. Sensors continuously monitor the vehicle's operating parameters and send data to the data processing unit in real time; Receive data from each sensor and analyze it in real time using an anomaly detection algorithm to determine if any parameters are outside the normal range. If an anomaly is detected, the data processing unit immediately sends the information to the warning display unit and the feedback response unit; Warning messages, including "engine overheating" and "brake system failure", are displayed on the windshield. In the warning state, the monitoring module continues to monitor relevant parameters in real time to observe whether there is any improvement. The driver takes corresponding measures based on the information provided by the system.

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