AR-HUD parameter configuration method and system, storage medium and automobile

Abstract

The invention provides an AR-HUD parameter configuration method and system, a storage medium and an automobile, and the method comprises the steps: obtaining a lane line equation and image data in a preset range in front of the automobile in a current environment, obtaining a rendering coordinate of a lane line based on the image data, obtaining a target rendering parameter based on the lane line equation and the rendering coordinate, and writing the target rendering parameter into software configuration so as to display a target picture based on the target rendering parameter. According to the method, the target rendering parameter is acquired through the detected lane line equation and the image data, so that the rendering engine in the AR-HUD can directly draw the image data on the HUD virtual image, and the HUD display content is more fit with the display content through parameter configuration of the display picture; and meanwhile, the target rendering parameters are written into software configuration, so that the display performance of the HUD is improved, the method can be used for other rendering platforms, and the expansibility and flexibility of the system are improved.

Description

Technical Field

[0001] The present application belongs to the field of intelligent assisted driving technology, and specifically relates to an AR-HUD parameter configuration method, system, storage medium and automobile. Background Art

[0002] AR-HUD is an innovative solution that combines augmented reality technology with a vehicle head-up display. By projecting information onto the windshield in the driver's field of view, AR-HUD provides real-time information during driving and enhances the driving experience. It can display AR content on common targets such as lane lines, road signs, and the car in front, helping the driver to focus and reduce distractions when operating the dashboard or viewing navigation. AR-HUD can also enhance the driver's perception of road conditions and surroundings through real-time AR images, and warn of potential dangers in advance.

[0003] Since AR-HUD itself does not have a camera and cannot directly capture information in front of the car, it can only share data from the ADAS (Advanced Driver Assistance System) front-view camera. This means that it is impossible to calculate the correspondence between the two-dimensional projection space coordinates and the three-dimensional space pixel coordinates in the world coordinate system through the pixel relationship between different image spaces. Due to the differences in the size of different car models and the installation position of the ADAS front-view camera, there is currently no mature and effective algorithm to calculate the calibration parameters of the ADAS information and the rendering engine (OpenGL) in the AR-HUD system. Summary of the invention

[0004] In response to the above problems, the present technology innovatively proposes an AR-HUD parameter configuration method, system, storage medium and automobile, aiming to provide accurate target rendering parameter configuration for the HUD so that the HUD display screen can be aligned with the display screen under different rendering platforms.

[0005] Specifically, this application proposes an AR-HUD parameter configuration method, including:

[0006] The lane line equation and image data within a preset range in front of the vehicle in the current environment are obtained, the rendering coordinates of the lane line are obtained based on the image data, the target rendering parameters are obtained based on the lane line equation and the rendering coordinates, and the target rendering parameters are written into the software configuration to display the target picture based on the target rendering parameters.

[0007] In the above technical solution, the target rendering parameters are calculated to ensure that the HUD display screen is accurately aligned with the real screen, thereby improving the accuracy of the displayed information. The target rendering parameters are written into the software configuration so that the system can flexibly adjust the display effect, thereby improving the adaptability and flexibility of the system. Through precise lane line recognition, real-time rendering coordinate calculation and flexible software configuration, not only the display effect and user experience of AR-HUD are improved, but also the safety and convenience of driving are enhanced.

[0008] Further, the image data includes at least first image data and second image data, and acquiring the image data includes:

[0009] The positioning endpoint of the lane line is obtained according to the lane line equation, and the first image data is obtained based on the positioning endpoint.

[0010] The second image data is acquired according to the HUD projection chart range.

[0011] By acquiring the positioning endpoint of the lane line, the lane line position is accurately identified. Acquiring the first image data based on the positioning endpoint makes the lane line displayed on the HUD more accurate, reduces errors, and improves the accuracy of the HUD display effect. Acquiring the second image data through the HUD projection map range can ensure that the displayed information is within the driver's line of sight, thereby improving the availability and practicality of the HUD display information.

[0012] Furthermore, before obtaining the rendering coordinates of the lane line based on the image data, the method further includes:

[0013] It is determined whether there are currently confirmed rendering parameters. If so, the confirmed rendering parameters are written into the software configuration as target rendering parameters; otherwise, the rendering coordinates of the current lane line are obtained based on the image data.

[0014] If there are currently confirmed rendering parameters, the target rendering parameters can be quickly applied to the software configuration, thereby quickly adjusting and optimizing the rendering effect, avoiding the computing power consumed by recalculating the target rendering parameters, and improving rendering efficiency. In the absence of confirmed rendering parameters, the rendering coordinates of the current lane line are obtained based on the image data, and the target rendering parameters are obtained by calculation, which ensures the practicality and effectiveness of the target rendering parameters, enables the rendering parameters to be flexibly adjusted in different situations, and ensures the accuracy and consistency of the rendering effect.

[0015] Further, obtaining the rendering coordinates of the lane line based on the image data includes:

[0016] All pixel endpoints of the lane line are detected according to the first image data, and the pixel coordinates of the lane line are acquired according to the pixel endpoints and the lane line equation.

[0017] Detecting the pixel endpoints of the lane lines through the first image data ensures accurate recognition of the lane lines, ensures effective recognition of the lane lines even in complex situations, and improves the robustness of acquiring the pixel coordinates of the lane lines.

[0018] Furthermore, the acquiring the rendering coordinates of the lane line based on the image data further includes:

[0019] Based on the second image data, the pixel coordinates are converted into the rendering coordinates by using a coordinate conversion algorithm.

[0020] The coordinate conversion algorithm may be a TPS algorithm, which converts the pixel coordinates into rendering coordinates so that the data can adapt to different rendering environments, thereby improving the versatility and adaptability of the data.

[0021] Furthermore, before writing the target rendering parameters into the software configuration, the method further includes:

[0022] A 3D virtual object is detected according to the image data, and the 3D virtual object is converted into a 2D picture.

[0023] By detecting 3D virtual objects and converting them into 2D images, complex scenes can be simplified and processed, making rendering more efficient, ensuring that virtual objects can be displayed correctly on the screen and avoiding visual distortion.

[0024] Furthermore, before writing the target rendering parameters into the software configuration, the method further includes:

[0025] Verify whether the target rendering parameters can make the lane lines in the HUD display screen and the 2D screen fit with the real screen. If so, write the target rendering parameters into the software configuration; otherwise, calculate the target rendering parameters by re-collecting the lane line equation and image data until the target rendering parameters pass the verification.

[0026] By verifying the target rendering parameters, it is ensured that the target rendering parameters can be applied to the HUD, thereby optimizing the rendering process and avoiding display errors or poor effects caused by improper parameter settings. Based on the verified target rendering parameters, the lane lines in the HUD and the 2D picture are seamlessly fitted with the real picture. The user's perception of the surrounding environment while driving is enhanced to ensure the consistency of the displayed information with the real scene. The verified target rendering parameters can support real-time adjustment to adapt to display requirements under different lighting and weather conditions, thereby improving the applicability and reliability of the HUD. By verifying before writing the software configuration, the risk of system errors or crashes due to improper parameters is reduced, and the stability of the system is enhanced.

[0027] Based on the same inventive concept, the present application also proposes a system for an AR-HUD parameter configuration method, the system comprising: a data acquisition module, a coordinate detection module, a parameter calculation module and a configuration module.

[0028] The data acquisition module is used to obtain lane line equations and image data within a preset range in front of the vehicle in the current environment.

[0029] A coordinate detection module is used to obtain the rendering coordinates of the lane line based on the image data.

[0030] A parameter calculation module is used to obtain target rendering parameters based on the lane line equation and the rendering coordinates.

[0031] And, a configuration module is used to write the target rendering parameters into the software configuration to display the target picture based on the target rendering parameters.

[0032] Based on the same inventive concept, the present application also proposes a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are read by a control processor to execute the AR-HUD parameter configuration method.

[0033] Based on the same inventive concept, the present application also proposes a car, which includes an AR-HUD fusion system, and the AR-HUD fusion system is used to implement the AR-HUD parameter configuration method.

[0034] Compared with the prior art, this application has at least the following beneficial effects:

[0035] The AR-HUD parameter configuration method described in this application provides an effective parameter configuration scheme for AR-HUD in practical applications. In this application, the rendering coordinates of the lane lines are obtained through real-time collected image data, which ensures that the rendered lane lines match the lane lines on the actual road, thereby improving the accuracy of the rendered lane lines. By writing the target rendering parameters into the software configuration and displaying the target screen through the target rendering parameters, the flexibility and accuracy of the HUD display are improved. Based on the displayed target screen, the driver's understanding and reaction ability to the environment are improved, and the driving safety is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flowchart of the AR-HUD parameter configuration method shown in an embodiment of the present application.

[0037] Figure 2 It is a schematic diagram of the AR-HUD parameter configuration system shown in an embodiment of the present application. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0039] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0040] The following describes an AR-HUD parameter configuration method provided in an embodiment of the present application. Figure 1Flowchart of the AR-HUD parameter configuration method shown in the embodiment of the present application. It should be noted that this specification provides method operation steps as described in the embodiment or flowchart, but more or fewer operation steps may be included based on conventional or non-creative labor. The order of steps listed in the embodiment is only one way of executing the order of many steps and does not represent the only execution order. When the system or product is executed in practice, it can be executed in the order of the method shown in the embodiment or the accompanying drawings or in parallel.

[0041] Embodiment 1:

[0042] Please refer to Figure 1 , the AR-HUD parameter configuration method mainly includes:

[0043] Obtain the lane line equation and image data within the preset range in front of the vehicle in the current environment. The lane line equation can be obtained through the ADAS front-view camera, and the lane line equation can mainly be:

[0044]

[0045] Among them, P x , P y , P z is the coordinate position of the lane line in the ADAS coordinate system, and C is the lane line equation function.

[0046] The preset range in front of the vehicle can be mainly 10 meters or 20 meters. Those skilled in the art can adjust the preset range according to actual conditions, and are not limited thereto. The image data can be captured by an eye position camera to simulate human eyes to capture the image data in front of the vehicle.

[0047] The rendering coordinates of the lane line are obtained based on the image data. Among them, the TPS (Thin Plate Spline) algorithm can be mainly used to convert the pixel coordinates of the lane line in the image data into rendering coordinates. The TPS algorithm is mainly an interpolation and deformation method commonly used in the fields of computer graphics and image processing. The TPS algorithm constructs a set of control points and uses these points to perform smooth interpolation in two-dimensional or three-dimensional space. The algorithm can perform nonlinear deformation on the shape so that the deformed shape remains smooth and continuous. The core of the TPS algorithm lies in its energy minimization principle. By solving the shape transformation with minimum energy, the smooth deformation of the original shape is achieved.

[0048] The target rendering parameters are obtained based on the lane line equation and the rendering coordinates. Among them, the target rendering parameters can be mainly calculated by the PNL (Piecewise Nonlinear) algorithm. The PNL algorithm is mainly a piecewise nonlinear modeling method, which is mainly used to process nonlinear relationships in complex data sets. The PNL algorithm can be used to describe and predict changes in lane lines in order to better control and navigate the vehicle. By analyzing the image data obtained by the camera, the features of the lane lines are extracted, and the obtained target rendering parameters can be adapted to different lane line shapes according to the features of the lane lines. For example, straight lines, curves, etc., and complex road conditions can be modeled.

[0049] The target rendering parameters are written into the software configuration to display the target screen based on the target rendering parameters. Among them, the target rendering parameters can mainly be the MVP (Model-View-Projection) relationship between the lane equation and the rendering coordinates. The MVP relationship is an important concept in computer graphics for converting three-dimensional coordinates into two-dimensional screen coordinates. The MVP relationship involves three matrices: Model Matrix, View Matrix and Projection Matrix.

[0050] The model matrix is ​​mainly used to convert the local coordinates of an object into world coordinates to describe the position, rotation and scaling of the object in three-dimensional space, and to define the transformation of the object relative to the world coordinate system through translation, rotation and scaling operations.

[0051] The view matrix is ​​mainly used to convert the world coordinates of the scene into observation coordinates to describe the position and direction of the camera and define the way to observe the scene from the camera's perspective.

[0052] The projection matrix is ​​mainly used to transform the viewing coordinates into the clipping coordinates to define how to project the three-dimensional scene onto the two-dimensional plane.

[0053] In some embodiments, the image data includes at least first image data and second image data, and acquiring the image data includes:

[0054] The positioning endpoint of the lane line is obtained according to the lane line equation, the first image data is obtained based on the positioning endpoint, and the second image data is obtained according to the HUD projection map range. The first image data is mainly obtained by shooting with an eye position camera at the positioning endpoint of the lane line, and the second image data is obtained by shooting with an eye position camera within the HUD projection map range.

[0055] The acquisition of the positioning endpoint can mainly be achieved through the real-time image data captured by the vehicle's front-view camera, and the image processing technology is used to extract the characteristics of the lane line, such as gray processing technology, edge detection processing technology and morphological transformation technology. According to the processed image data, the lane line equation is applied to the image coordinate system. By taking into account the camera's viewing angle and camera parameters, the corresponding points of the lane line in the image are determined. The camera parameters can mainly be focal length and distortion parameters. According to the lane line equation, the endpoints of the lane line within a specific coordinate range are calculated. For example, if the lane line is a linear equation, the left and right boundaries of the image can be selected, that is, x is equal to 0 or x is equal to the image width to calculate the corresponding y value to obtain the two endpoints of the lane line.

[0056] Optionally, before acquiring the rendering coordinates of the lane line based on the image data, the method further includes:

[0057] It is determined whether there are currently confirmed rendering parameters. If so, the confirmed rendering parameters are written into the software configuration as target rendering parameters; otherwise, the rendering coordinates of the current lane line are obtained based on the image data.

[0058] By determining whether there are currently confirmed rendering parameters, the system can ensure that it can respond quickly and reduce unnecessary calculations. If confirmed rendering parameters are detected, they will be used as target rendering parameters. These parameters will be directly written into the software configuration for use in subsequent rendering processes. This method not only improves efficiency, but also maintains consistency and stability of rendering, especially in multiple driving scenarios.

[0059] Optionally, acquiring rendering coordinates of lane lines based on the image data includes:

[0060] All pixel endpoints of the lane line are detected according to the first image data, and the pixel coordinates of the lane line are acquired according to the pixel endpoints and the lane line equation.

[0061] The calculation formula of pixel coordinates can be:

[0062]

[0063] Where G is the pixel coordinate of the lane line, L is the pixel endpoint of the lane line, and C is the lane line equation function.

[0064] Optionally, the acquiring rendering coordinates of the lane line based on the image data further includes:

[0065] Based on the second image data, the pixel coordinates are converted into the rendering coordinates by using a coordinate conversion algorithm.

[0066] The coordinate conversion algorithm may be mainly a TPS algorithm, and the main calculation formula may be:

[0067]

[0068] Among them, etc represents the expansion vector of TPS, Q represents the rendering coordinates, and G represents the pixel coordinates of the lane line.

[0069] After obtaining the rendering coordinates of the lane line, the PNL algorithm may be used to calculate the target rendering parameters based on the lane line equation and the rendering coordinates. The main calculation formula may be: The MVP relationship between the lane line equation and the rendering coordinates is calculated using the PNL algorithm:

[0070]

[0071] Among them, P is the lane line coordinate in the ADAS coordinate system, and Q is the rendering coordinate.

[0072] Optionally, before writing the target rendering parameters into the software configuration, the method further includes:

[0073] A 3D virtual object is detected according to the image data, and the 3D virtual object is converted into a 2D picture.

[0074] The 3D virtual object may be detected from the image data using a computer vision algorithm, for example, a deep learning model or a convolutional neural network may be used to detect the 3D virtual object in the image data. The 3D virtual object may be mapped to a 2D plane through a projection transformation.

[0075] Optionally, before writing the target rendering parameters into the software configuration, the method further includes:

[0076] Verify whether the target rendering parameters can make the lane lines in the display screen of the HUD and the 2D screen fit the real screen. If so, write the target rendering parameters into the software configuration; otherwise, calculate the target rendering parameters by re-collecting the lane line equation and image data until the target rendering parameters pass the verification. Wherein, by verifying the target rendering parameters, the matching degree between the lane lines displayed by the HUD and the real lane lines is evaluated. A high-precision positioning system can be used to record the position information of the real lane and compare it with the lane lines displayed by the HUD. When the target rendering parameter verification fails, calculate the target rendering parameters by re-collecting the lane line equation and image data until the target rendering parameters are verified and then write the target rendering parameters into the software configuration.

[0077] The target rendering parameters mainly act on the rendering engine (OpenGL, Open Graphics Library). According to the target rendering parameters, the rendering engine directly draws the target picture in the HUD display screen. And it can make the target picture fit the real world picture. The rendering engine OpenGL is a cross-platform graphics API for rendering 2D and 3D graphics. It provides a series of functions that allow developers to interact directly with graphics hardware to create high-performance graphics applications, such as games, simulations, and scientific visualizations, and supports the rendering of various graphics effects, such as lighting, texture mapping, shadows, etc.

[0078] Embodiment 2:

[0079] Please refer to Figure 2 The present application also proposes a system adopting the AR-HUD parameter configuration method described in Example 1, which mainly includes: a data acquisition module, a coordinate detection module, a parameter calculation module and a configuration module.

[0080] The data acquisition module is used to obtain lane line equations and image data within a preset range in front of the vehicle in the current environment.

[0081] Among them, the acquisition of the lane line equation can be mainly carried out by using an ADAS front-view camera, and the acquisition of the image data can be mainly carried out by using an eye position camera installed at the position of the driver's eyes. Before acquiring the lane line equation and image data, it is also necessary to park the current vehicle in a specific environment according to the actual situation, such as parking the vehicle body on a road with clear and straight lane lines, ensuring that the current ADAS front-view camera can detect at least two lane lines on the left and right, ensuring that the HUD display range can cover at least two lane lines on the left and right, and installing the eye position camera horizontally at the position of the driver's eyes. When acquiring the lane line, the ADAS front-view camera will record the currently acquired lane line equation in the form of an ADAS coordinate equation function, detect the positioning endpoint on the lane line according to the acquired lane line equation, and use the eye position camera to shoot the image data according to the positioning endpoint.

[0082] The coordinate detection module is used to obtain the rendering coordinates of the lane line based on the image data.

[0083] Among them, all pixel endpoints of the lane line can be detected mainly through the image data, and the pixel coordinates of the lane line can be obtained according to the pixel endpoints and the lane line equation. The second image data is obtained by shooting with an eye position camera within the range of the HUD display card, and according to the second image data, the pixel coordinates of the lane line can be converted into the rendering coordinates through the TPS algorithm.

[0084] The parameter calculation module is used to obtain target rendering parameters based on the lane line equation and the rendering coordinates.

[0085] When obtaining the target rendering parameters, the PNL algorithm can be mainly used to calculate based on the lane line equation and the rendering coordinates to obtain the target rendering parameters. The target rendering parameters can mainly be MVP parameters required by the rendering engine, and the MVP parameters mainly include model matrix, view matrix and projection matrix parameters.

[0086] And, the configuration module is used to write the target rendering parameters into the software configuration to display the target picture based on the target rendering parameters.

[0087] Before writing the target rendering parameters into the software configuration, the 3D object in the captured image data may be projected into the HUD display screen and converted into a 2D screen through the rendering engine, and then the target rendering parameters may be verified to ensure that the lane lines displayed by the HUD can be integrated with the real lane lines. After writing the target rendering parameters into the software configuration, the target rendering parameters may be directly used or adjusted to render the display screen the next time the software system is run, so as to display the target screen within the HUD display range.

[0088] According to the target rendering parameters written into the software configuration, the rendering engine in the AR-HUD can mainly draw the target screen directly in the HUD display screen. In actual situations, only the lane line data needs to be calibrated, and it can also be applied to other captured target object information, so that the captured picture can be displayed within the display range of the HUD and fit the real world, significantly improving the display performance of the HUD. Those skilled in the art can apply the target rendering parameters to other rendering platforms according to actual conditions, but are not limited to this.

[0089] Embodiment three:

[0090] The present application also proposes a computer-readable storage medium, the computer-readable storage medium comprising:

[0091] The computer-readable storage medium stores computer-executable instructions.

[0092] When the computer executable instructions are executed by the control processor, the AR-HUD parameter configuration method described in Example 1 is implemented.

[0093] In the computer-readable storage medium, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk SolidState Disk (SSD)), etc.

[0094] In the fourth embodiment, the present application further proposes a car, comprising an AR-HUD parameter configuration system, wherein the AR-HUD parameter configuration system is used to implement the AR-HUD parameter configuration method described in the first embodiment.

[0095] In the car, the AR-HUD parameter configuration system is designed to enhance the driving experience, and through real-time information display, the driver can more conveniently obtain vehicle status, navigation information and safety tips. The AR-HUD parameter configuration system can collect data from multiple sensors, such as vehicle speed, fuel consumption, navigation information and surrounding environment perception data, and superimpose this information in the driver's field of view in a visual manner, ensuring driving safety while reducing dependence on the dashboard. The AR-HUD display screen supports navigation functions, and can display routes, traffic conditions and turning prompts on the front windshield in real time to help drivers better plan driving routes and avoid congestion. Technicians in this field can link the AR-HUD display screen with the vehicle safety system, and AR-HUD can provide collision warnings, blind spot monitoring and other safety reminders in real time to improve driving safety.

[0096] In summary, the present application obtains the rendering coordinates of the lane lines through real-time collected image data, thereby ensuring that the lane lines displayed by the HUD match the lane lines on the actual road. By calculating the target rendering parameters, the accurate fit between the HUD display screen and the real screen is ensured, thereby improving the accuracy of the displayed information. By writing the target rendering parameters into the software configuration, the system can flexibly adjust the display effect, thereby improving the adaptability and flexibility of the system. Through precise lane line recognition, real-time rendering coordinate calculation and flexible software configuration, the display effect of AR-HUD is improved, the driver's understanding and reaction ability to the environment is improved, and the driving safety and user experience are enhanced.

[0097] In several embodiments provided in the present application, it is understood that each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved.

[0098] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling an electronic device to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0099] The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the scope of protection of the present application. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of protection of the present application.

Claims

1. An AR-HUD parameter configuration method, characterized in that: include: Obtain the lane line equation and image data within a preset range in front of the vehicle in the current environment; Acquire rendering coordinates of lane lines based on the image data; Acquire target rendering parameters based on the lane line equation and the rendering coordinates; The target rendering parameters are written into a software configuration to display a target picture based on the target rendering parameters.

2. The AR-HUD parameter configuration method according to claim 1, characterized in that: The image data at least includes first image data and second image data, and acquiring the image data includes: Acquire a positioning endpoint of a lane line according to the lane line equation, and acquire first image data based on the positioning endpoint; The second image data is acquired according to the HUD projection chart range.

3. The AR-HUD parameter configuration method according to claim 1, characterized in that: Before obtaining the rendering coordinates of the lane line based on the image data, the method further includes: It is determined whether there are currently confirmed rendering parameters. If so, the confirmed rendering parameters are written into the software configuration as target rendering parameters; otherwise, the rendering coordinates of the current lane line are obtained based on the image data.

4. The AR-HUD parameter configuration method according to claim 2, characterized in that: The obtaining the rendering coordinates of the lane line based on the image data includes: All pixel endpoints of the lane line are detected according to the first image data, and the pixel coordinates of the lane line are acquired according to the pixel endpoints and the lane line equation.

5. The AR-HUD parameter configuration method according to claim 4, characterized in that: The obtaining the rendering coordinates of the lane line based on the image data further includes: Based on the second image data, the pixel coordinates are converted into the rendering coordinates by using a coordinate conversion algorithm.

6. The AR-HUD parameter configuration method according to claim 1, characterized in that: Before writing the target rendering parameters into the software configuration, the method further includes: A 3D virtual object is detected according to the image data, and the 3D virtual object is converted into a 2D picture.

7. The AR-HUD parameter configuration method according to claim 1, characterized in that: Before writing the target rendering parameters into the software configuration, the method further includes: Verify whether the target rendering parameters can make the lane lines in the HUD display screen and the 2D screen fit with the real screen. If so, write the target rendering parameters into the software configuration; otherwise, calculate the target rendering parameters by re-collecting the lane line equation and image data until the target rendering parameters pass the verification.

8. A system based on the AR-HUD parameter configuration method according to any one of claims 1 to 7, characterized in that: The system includes: a data acquisition module, a coordinate detection module, a parameter calculation module and a configuration module; The data acquisition module is used to acquire lane line equations and image data within a preset range in front of the vehicle in the current environment; A coordinate detection module, used for obtaining the rendering coordinates of the lane line based on the image data; A parameter calculation module, used for obtaining target rendering parameters based on the lane line equation and the rendering coordinates; And, a configuration module is used to write the target rendering parameters into the software configuration to display the target picture based on the target rendering parameters.

9. A computer-readable storage medium storing computer-executable instructions, characterized in that: When the computer executable instructions are executed by the control processor, the AR-HUD parameter configuration method according to any one of claims 1 to 7 is implemented.

10. An automobile, characterized in that: The automobile includes an AR-HUD parameter configuration system, and the AR-HUD parameter configuration system is used to implement the AR-HUD parameter configuration method according to any one of claims 1 to 7.

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