Method, device, equipment and storage medium for generating simulation scene based on point cloud

Abstract

The present invention discloses a method, device, equipment and storage medium for generating simulation scenes based on point clouds, wherein the method comprises the steps of: segmenting the point cloud data of a real road to obtain a road surface point cloud and a non-road surface point cloud; extracting the road surface point cloud and the non-road surface point cloud to generate a road surface three-dimensional model and a non-road surface three-dimensional model; converting the road surface three-dimensional model to obtain an OpenDRIVE file and an OpenCRG file; generating a simulation test scene based on the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file. The present application can automatically generate scenes for autonomous driving simulation from point cloud data, and make the generated road surface have physical characteristics, reproduce the real road surface, and have low cost and high efficiency.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device, equipment and storage medium for generating a simulation scene based on point cloud. Background Art

[0002] The development of intelligent connected vehicles cannot be separated from simulation testing, which is low-cost and highly efficient. In simulation testing, most of the industry currently uses laser radar to collect real scenes for reproducing simulation scenes. The reproduction process requires a lot of manpower and material resources, and the simulated road surface still has no physical characteristics and does not match the real road surface.

[0003] Therefore, how to use point clouds to generate scenarios for autonomous driving simulation tests while making the simulated road surface have physical properties is a technical problem that needs to be solved urgently. Summary of the invention

[0004] The main purpose of the present invention is to provide a method, device, equipment and storage medium for generating simulation scenes based on point clouds, which can automatically generate point cloud data for scenes for autonomous driving simulation, and make the generated road surface have physical properties and reproduce the real road surface with low cost and high efficiency.

[0005] In a first aspect, the present application provides a method for generating a simulation scene based on a point cloud, wherein the method comprises the steps of:

[0006] Segment the point cloud data of the real road to obtain the road surface point cloud and the non-road surface point cloud;

[0007] Extract the road surface point cloud and the non-road surface point cloud to generate a road surface three-dimensional model and a non-road surface three-dimensional model;

[0008] Convert the three-dimensional road surface model into an OpenDRIVE file and an OpenCRG file.

[0009] A simulation test scenario is generated based on the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file.

[0010] In combination with the first aspect above, as an optional implementation method, CFS filtering, gradient filtering or slope filtering is used to segment the point cloud data of the real road to obtain a road surface point cloud and a non-road surface point cloud.

[0011] In combination with the first aspect above, as an optional implementation method, point cloud data of the real road is collected by laser radar, and the collected point cloud data is filtered to eliminate invalid point clouds.

[0012] In combination with the first aspect above, as an optional implementation method, extracting the road border coordinates in the road surface three-dimensional model;

[0013] The road frame coordinates in the extracted road 3D model are converted into an OpenDRIVE file.

[0014] In combination with the first aspect above, as an optional implementation method, the road surface three-dimensional model is converted into an OpenCRG file using a simulation device.

[0015] In combination with the first aspect above, as an optional implementation method,

[0016] Align the variable coordinates of each road in the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file with the variable coordinates of each road in the actual road, and map the road surface three-dimensional model on the OpenDRIVE simulation road, and after hiding the OpenDRIVE simulation road, generate a new OpenDRIVE file and a rendering file OSGB, wherein the OpenDRIVE simulation road is generated by the frame coordinates in the road surface three-dimensional model;

[0017] A simulation test scene is generated according to the new OpenDRIVEOpenDRIVE file and the rendering file OSGB.

[0018] In a second aspect, the present application provides a device for generating a simulation scene based on a point cloud, the device comprising:

[0019] A segmentation module is used to segment the point cloud data of the real road to obtain a road surface point cloud and a non-road surface point cloud;

[0020] A first generating module, which is used to extract the road surface point cloud and the non-road surface point cloud to generate a road surface three-dimensional model and a non-road surface three-dimensional model;

[0021] A conversion module, which is used to convert the format of the road surface three-dimensional model to obtain an OpenDRIVE file and an OpenCRG file;

[0022] The second generation module is used to generate a simulation test scene based on the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file.

[0023] In combination with the above second aspect, as an optional implementation method, the segmentation module is also used to segment the point cloud data of the real road using CFS filtering, gradient filtering or slope filtering to obtain road surface point cloud and non-road surface point cloud.

[0024] In a third aspect, the present application further provides an electronic device, comprising: a processor; a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method described in any one of the first aspects is implemented.

[0025] In a fourth aspect, the present application further provides a computer-readable storage medium storing computer program instructions, which, when executed by a computer, enables the computer to execute any of the methods described in the first aspect.

[0026] The present application provides a method, device, equipment and storage medium for generating simulation scenes based on point clouds, wherein the method includes the following steps: segmenting the point cloud data of a real road to obtain a road surface point cloud and a non-road surface point cloud; extracting the road surface point cloud and the non-road surface point cloud to generate a road surface three-dimensional model and a non-road surface three-dimensional model; converting the road surface three-dimensional model to obtain an OpenDRIVE file and an OpenCRG file; generating a simulation test scene based on the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file. The present application can automatically generate scenes for autonomous driving simulation from point cloud data, and make the generated road surface have physical properties, reproduce the real road surface, and have low cost and high efficiency.

[0027] It is to be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0029] Figure 1 A flow chart of a method for generating a simulation scene based on a point cloud provided in an embodiment of the present application;

[0030] Figure 2 A schematic diagram of a device for generating a simulation scene based on a point cloud provided in an embodiment of the present application;

[0031] Figure 3 A schematic diagram of an electronic device provided in an embodiment of the present application;

[0032] Figure 4 A schematic diagram of a computer-readable program medium provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0034] Furthermore, the drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. Some of the blocks shown in the drawings are functional entities and do not necessarily correspond to physically or logically separate entities.

[0035] The embodiments of the present application provide a method, apparatus, device and storage medium for generating simulation scenes based on point clouds, which can automatically generate scenes for autonomous driving simulation from point cloud data, and make the generated road surface have physical properties and reproduce the real road surface with low cost and high efficiency.

[0036] In order to achieve the above technical effects, the general idea of ​​this application is as follows:

[0037] A method for generating a simulation scene based on a point cloud, the method comprising the steps of:

[0038] S101: Segment the point cloud data of the real road to obtain a road surface point cloud and a non-road surface point cloud.

[0039] S102: Extract the road surface point cloud and the non-road surface point cloud to generate a road surface three-dimensional model and a non-road surface three-dimensional model.

[0040] S103: Convert the format of the road surface three-dimensional model to obtain an OpenDRIVE file and an OpenCRG file.

[0041] S104: Generate a simulation test scenario based on the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file.

[0042] The embodiments of the present application are further described in detail below in conjunction with the accompanying drawings.

[0043] Reference Figure 1 , Figure 1 FIG. 1 is a flow chart of a method for generating a simulation scene based on point cloud provided by the present invention. Figure 1 As shown, the method comprises the steps of:

[0044] Step S101: Segment the point cloud data of the real road to obtain road surface point cloud and non-road surface point cloud.

[0045] Specifically, CFS filtering, gradient filtering or slope filtering is used to segment the point cloud data of the real road to obtain road surface point cloud and non-road surface point cloud.

[0046] It should be noted that CFS (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) filtering is a signal processing method based on empirical mode decomposition (EMD), which can filter out non-periodic noise and high-frequency interference signals and retain the low-frequency part of the signal. The basic idea of ​​CFS filtering is to decompose the signal into multiple intrinsic mode functions (IMFs), and then remove noise and interference signals by adaptively adjusting the energy of IMFs.

[0047] Gradient filter is one of the commonly used filtering methods in image processing. It can extract edge information from images. The basic idea of ​​gradient filtering is to measure the gradient size and direction of the current pixel by calculating the difference in pixel values ​​around the pixel. Common gradient filter operators include Sobel, Prewitt, Roberts, etc.

[0048] Slope Filter is a digital terrain model (DTM) processing method, which is mainly used to remove noise and outliers in terrain data. It determines which data points are outliers or noise based on the slope change of the terrain and filters them out. The basic idea of ​​slope filtering is to first calculate the slope of each pixel, and then compare the slope with the slopes of the surrounding pixels. If the slope of a pixel is significantly different from the slopes of the surrounding pixels, the pixel is considered to be an outlier or noise. Therefore, the pixel will be marked as a point that needs to be filtered and will be removed in subsequent processing.

[0049] In one embodiment, before segmenting the point cloud data of the real road, the point cloud data of the real road is collected by laser radar, and the collected point cloud data is filtered to remove invalid point clouds. The filtering method can be CFS filtering, gradient filtering, slope filtering or z coordinate.

[0050] It can be understood that the collected point cloud data is classified to segment the road surface point cloud and the non-road surface point cloud, wherein the non-road surface point cloud includes trees, street lights, signboards and other buildings.

[0051] Step S102: extract the road surface point cloud and the non-road surface point cloud to generate a road surface three-dimensional model and a non-road surface three-dimensional model.

[0052] Specifically, it is understood that, based on the collected real road point cloud data or the real road point cloud data collected in advance in the database, after segmenting it into road point cloud and non-road point cloud, the road point cloud and non-road point cloud are extracted to generate a three-dimensional model. It should be noted that the three-dimensional model generated at this time includes the physical features of the unevenness of the real road surface, but this three-dimensional model cannot be recognized, in other words, it cannot be recognized by the simulation software, so the generated road three-dimensional model needs to be converted into a format.

[0053] Step S103: convert the format of the road surface three-dimensional model to obtain an OpenDRIVE file and an OpenCRG file.

[0054] Specifically, after the road 3D model is generated, the autonomous driving simulation software cannot recognize and apply the road 3D model. The general road standard format in the industry is OpenDRIVE, so the road 3D model needs to be converted. The conversion method is as follows: first, use a special commercial software to extract the road border in the road 3D model; the road border is a closed curve, the format can be dxf format, and the road border can be opened with CAD. According to the needs, the road border is taken at intervals of 1 cm, and the coordinate points are imported into the simulation scene software. The road border can be obtained in the simulation scene software, and then the road structure is built in the simulation scene software, that is, according to the road border coordinates in the extracted road 3D model, it is converted into an OpenDRIVE file. It can be understood as framing the generated road 3D model, and then using the framed frame coordinates (when framing, the coordinates of any point in the frame can be obtained), the extracted coordinates are used to rebuild the road in the simulation scene software and converted into an OpenDRIVE file. If there is an OpenDRIVE converter, the road border coordinates can be input and the OpenDRIVE file can be directly output.

[0055] Since the generated 3D model has physical properties, but the simulation software cannot recognize the physical properties of the 3D model, the road microstructure (road undulations) described in the autonomous driving simulation is an OpenCRG file. Therefore, the generated road 3D model also needs to be converted into an OpenCRG file.

[0056] It can be understood that the road surface three-dimensional model is converted into two formats here, one is converted into an OpenDRIVE file, and the other is converted into an OpenCRG file.

[0057] It should be noted that OpenDRIVE is an open road description format used to describe road information in digital maps. It can provide information such as road geometry, lane width, boundaries, traffic signs, traffic lights, intersections, obstacles, etc., and is suitable for autonomous driving, traffic simulation, vehicle navigation and other fields.

[0058] OpenCRG is an open road curve format that describes the "microscopic topography of the road surface", such as the undulations and roughness of the road surface.

[0059] Step S104: Generate a simulation test scenario based on the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file.

[0060] Specifically, the OpenDRIVE file and OpenCRG file have been obtained from the 3D road model just now. On the simulated road in OpenDRIVE, the non-road model is placed according to the actual situation to keep consistent with the real situation; then the OpenCRG file is placed, and the OpenCRG file is aligned with the simulated road in OpenDRIVE. Then the road 3D model is placed on the OpenDRIVE simulated road, and the OpenDRIVE simulated road is hidden, and the road 3D model road is highlighted. In other words, the OpenDRIVE simulated road is a logical road, and its surface material, texture, or color is inconsistent with the real road. Therefore, the generated road 3D model is added to the simulated road, and the OpenCRG file is added to the simulated road again.

[0061] In simple terms, three identical roads are currently superimposed on each other. The simulated road is a logical road, which is hidden; the road surface 3D model is used for rendering; the OpenCRG file is used to characterize the microscopic characteristics of the road surface, that is, it has uneven physical properties. Then, according to the actual situation, the non-road surface 3D model is added to the simulated road. Finally, a new OpenDRIVE file and rendering file OSGB are regenerated to generate a simulation test scene.

[0062] It should be noted that the OpenDRIVE simulated road can be understood as a logical road. The road surface has no physical features, and the OpenDRIVE simulated road is generated through the road border coordinates in the three-dimensional road surface model.

[0063] It is understandable that if there is a sign on the left side of the road in the real road surface, the road surface 3D model should be the same as the real road surface (with a sign on the left side). The method is to place the non-road surface 3D model (such as the sign) on the left side of the road in the OpenDRIVE file. The same is true for the OpenCRG file. The features of the real road surface are aligned and placed in the simulation to generate a simulation scene.

[0064] In one embodiment, the road surface 3D model, the non-road surface 3D model, the OpenDRIVE file and the OpenCRG file are placed on the OpenDRIVE simulation road according to their relative positions, and the road surface 3D model is placed on the OpenDRIVE simulation road, and the OpenDRIVE simulation road is hidden. Finally, a new OpenDRIVE road file and a rendering file OSGB are generated. The OpenDRIVE road and the rendering file OSGB are used in the simulation scene software to place the required vehicles and pedestrians and run the scene.

[0065] Reference Figure 2 , Figure 2 FIG. 1 is a schematic diagram of a device for generating a simulation scene based on point cloud provided by the present invention, such as Figure 2 As shown, the device comprises:

[0066] Segmentation module 201: It is used to segment the point cloud data of the real road to obtain the road surface point cloud and the non-road surface point cloud.

[0067] The first generating module 202 is used to extract the road surface point cloud and the non-road surface point cloud, and generate a road surface three-dimensional model and a non-road surface three-dimensional model.

[0068] The conversion module 203 is used to convert the format of the road surface three-dimensional model to obtain an OpenDRIVE file and an OpenCRG file.

[0069] The second generating module 204 is used to generate a simulation test scenario based on the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file.

[0070] Furthermore, in a possible implementation manner, the segmentation module is also used to segment the point cloud data of the real road using CFS filtering, gradient filtering or slope filtering to obtain a road surface point cloud and a non-road surface point cloud.

[0071] Furthermore, in a possible implementation, a filtering module is also included, which is used to collect point cloud data of the real road through a laser radar and filter the collected point cloud data to eliminate invalid point clouds.

[0072] Furthermore, in a possible implementation manner, the conversion module is further used to extract the road frame coordinates in the road surface three-dimensional model;

[0073] The road frame coordinates in the extracted road 3D model are converted into an OpenDRIVE file.

[0074] Furthermore, in a possible implementation manner, the conversion module is further configured to convert the road surface three-dimensional model into an OpenCRG file using a simulation device.

[0075] Furthermore, in a possible implementation manner, the second generation module is also used to

[0076] Align the variable coordinates of each road in the road surface 3D model, non-road surface 3D model, OpenDRIVEOpenDRIVE file and OpenCRG file with the variable coordinates of each road in the actual road, and map the road surface 3D model on the OpenDRIVEOpenDRIVE simulation road, and after hiding the OpenDRIVE simulation road, generate a new OpenDRIVEOpenDRIVE file and rendering file OSGB, wherein the OpenDRIVE simulation road is generated by the frame coordinates in the road surface 3D model;

[0077] A simulation test scene is generated according to the new OpenDRIVEOpenDRIVE file and the rendering file OSGB.

[0078] Refer to the following Figure 3 The electronic device 300 according to this embodiment of the present invention will be described. Figure 3 The electronic device 300 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0079] like Figure 3 As shown, the electronic device 300 is in the form of a general computing device. The components of the electronic device 300 may include but are not limited to: at least one processing unit 310, at least one storage unit 320, and a bus 330 connecting different system components (including the storage unit 320 and the processing unit 310).

[0080] The storage unit stores program codes, which can be executed by the processing unit 310, so that the processing unit 310 executes the steps according to various exemplary embodiments of the present invention described in the above “Embodiment Method” section of this specification.

[0081] The storage unit 320 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 321 and / or a cache memory unit 322 , and may further include a read-only memory unit (ROM) 323 .

[0082] The storage unit 320 may also include a program / utility 324 having a set (at least one) of program modules 325, such program modules 325 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0083] Bus 330 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0084] The electronic device 300 may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 300, and / or communicate with any device that enables the electronic device 300 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 350. Furthermore, the electronic device 300 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 360. As shown, the network adapter 360 communicates with other modules of the electronic device 300 via a bus 330. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0085] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0086] According to the solution of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary implementations of the present invention described in the above "Exemplary Method" section of the present specification.

[0087] refer to Figure 4As shown, a program product 400 for implementing the above method according to an embodiment of the present invention is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0088] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0089] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0090] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0091] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0092] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0093] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

[0094] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the flowchart. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

Claims

1. A method for generating a simulation scene based on point cloud, characterized in that: include: Segment the point cloud data of the real road to obtain the road surface point cloud and the non-road surface point cloud; Extract the road surface point cloud and the non-road surface point cloud to generate a road surface three-dimensional model and a non-road surface three-dimensional model; Convert the three-dimensional road surface model into an OpenDRIVE file and an OpenCRG file. Generate a simulation test scenario based on the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file; wherein the variable coordinates of each road in the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file are aligned with the variable coordinates of each actual road, and the road surface three-dimensional model is mapped on the OpenDRIVE simulation road, and after the OpenDRIVE simulation road is hidden, a new OpenDRIVE file and a rendering file OSGB are generated, wherein the OpenDRIVE simulation road is generated by the frame coordinates in the road surface three-dimensional model; A simulation test scene is generated according to the new OpenDRIVE file and the rendering file OSGB.

2. The method according to claim 1, characterized in that The step of segmenting the point cloud data of the real road to obtain the road surface point cloud and the non-road surface point cloud includes: The point cloud data of the real road is segmented using CFS filtering, gradient filtering or slope filtering to obtain road surface point cloud and non-road surface point cloud.

3. The method according to claim 1, characterized in that Before segmenting the point cloud data of the real road, the method includes: The point cloud data of the real road is collected by LiDAR, and the collected point cloud data is filtered to eliminate invalid point clouds.

4. The method according to claim 1, characterized in that: include: Extracting the road frame coordinates in the road surface three-dimensional model; The road frame coordinates in the extracted road 3D model are converted into an OpenDRIVE file.

5. The method according to claim 1, characterized in that include: The pavement three-dimensional model is converted into an OpenCRG file using a simulation device.

6. A device for generating a simulation scene based on a point cloud, characterized in that: include: A segmentation module is used to segment the point cloud data of the real road to obtain the road surface point cloud and the non-road surface point cloud; A first generating module, which is used to extract the road surface point cloud and the non-road surface point cloud to generate a road surface three-dimensional model and a non-road surface three-dimensional model; A conversion module, which is used to convert the format of the road surface three-dimensional model to obtain an OpenDRIVE file and an OpenCRG file; A second generation module, which is used to generate a simulation test scene based on the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file; Align the variable coordinates of each road in the road surface three-dimensional model, the non-road surface three-dimensional model, the OpenDRIVE file and the OpenCRG file with the variable coordinates of each road in the actual road, and map the road surface three-dimensional model on the OpenDRIVE simulation road, and after hiding the OpenDRIVE simulation road, generate a new OpenDRIVE file and a rendering file OSGB, wherein the OpenDRIVE simulation road is generated by the frame coordinates in the road surface three-dimensional model; A simulation test scene is generated according to the new OpenDRIVE file and the rendering file OSGB.

7. The device according to claim 6, characterized in that include: The segmentation module is also used to segment the point cloud data of the real road by using CFS filtering, gradient filtering or slope filtering to obtain road surface point cloud and non-road surface point cloud.

8. An electronic device, characterized in that: The electronic device comprises: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 5 is implemented.

9. A computer-readable storage medium, characterized in that: The computer program instructions are stored therein, and when the computer program instructions are executed by a computer, the computer is caused to execute the method according to any one of claims 1 to 5.

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