High-precision map data processing method and device

Abstract

The present application relates to a method and device for processing high-precision map data. The method includes: prefabricating an image of a set pixel size; drawing different types of high-precision data in the high-precision map tile data to be processed onto the image to generate high-precision map image data; cutting the high-precision map image data into a set number of raster data according to a set data format, and setting a corresponding unique identification code for each raster data, and storing the set number of raster data and its corresponding unique identification code together. The solution provided by the present application can improve the storage and reading efficiency of high-precision map data and meet the needs of autonomous driving of vehicles.

Description

Technical Field

[0001] The present application relates to the field of high-precision map technology, and in particular to a method and device for processing high-precision map data. Background Art

[0002] In the field of autonomous driving, high-precision maps, as providers of prior environmental information, play a crucial role in high-precision positioning, assisting environmental perception, and supporting planning and decision-making. High-precision maps, also known as high-precision maps, can be used by autonomous vehicles. These maps, with precise vehicle location information and rich road element data, can help autonomous vehicles predict complex road conditions, such as slope, curvature, and heading, to better mitigate potential risks. Consequently, the high-precision map data volume used in related technologies is large, resulting in inefficient reading and storage of high-precision maps by autonomous vehicles, making them inefficient and unable to meet the needs of autonomous driving. Summary of the Invention

[0003] In order to solve or partially solve the problems existing in the related technologies, the present application provides a high-precision map data processing method and device, which can improve the storage and reading efficiency of high-precision map data and meet the needs of vehicle autonomous driving.

[0004] In a first aspect, the present application provides a method for processing high-precision map data, the method comprising:

[0005] Prefabricate images with set pixel size;

[0006] Drawing different types of high-precision data in the high-precision map tile data to be processed on the image to generate high-precision map image data;

[0007] The high-precision map image data is cut into a set number of raster data according to a set data format, and a corresponding unique identification code is set for each raster data, and the set number of raster data and its corresponding unique identification code are stored together.

[0008] Preferably, the method further comprises:

[0009] Search for the raster data of the high-precision map image data according to the unique identification code.

[0010] Preferably, the step of drawing different types of high-precision data in the high-precision map tile data to be processed onto the image to generate high-precision map image data includes:

[0011] Calculate the unit longitude and latitude corresponding to a grid of the image;

[0012] Obtaining data ranges of different types of high-precision data in the high-precision map tile data to be processed;

[0013] Obtaining image color values ​​of different types of high-precision data in the high-precision map tile data to be processed;

[0014] According to the data range, image color value, and unit longitude and latitude corresponding to a grid of the image of different types of high-precision data in the high-precision map tile data to be processed, the different types of high-precision data in the high-precision map tile data to be processed are drawn on the image to generate high-precision map image data.

[0015] Preferably, the numerical range of the image color value is 0-255, and different types of high-precision data in the high-precision map tile data are preset to correspond to different image color values.

[0016] Preferably, searching for the raster data of the high-precision map image data according to the unique identification code includes:

[0017] Calculate a unique identification code based on latitude and longitude;

[0018] Search for the raster data of the high-precision map image data according to the unique identification code.

[0019] A second aspect of the present application provides a high-precision map data processing device, the device comprising:

[0020] Prefabrication module, used to prefabricate images of set pixel size;

[0021] A processing module, configured to draw different types of high-precision data in the high-precision map tile data to be processed onto the image prefabricated by the prefabrication module to generate high-precision map image data;

[0022] The storage module is used to cut the high-precision map image data generated by the processing module into a set number of raster data according to a set data format, and set a corresponding unique identification code for each raster data, and store the set number of raster data and its corresponding unique identification code together.

[0023] Preferably, the device further comprises:

[0024] A search module is used to search for the raster data of the high-precision map image data stored in the storage module according to a unique identification code.

[0025] Preferably, the processing module is further used for:

[0026] Calculating the unit longitude and latitude corresponding to a grid of the image prefabricated by the prefabricated module;

[0027] Obtaining data ranges of different types of high-precision data in the high-precision map tile data to be processed;

[0028] Obtaining image color values ​​of different types of high-precision data in the high-precision map tile data to be processed;

[0029] According to the data range, image color value, and unit longitude and latitude corresponding to a grid of the image of different types of high-precision data in the high-precision map tile data to be processed, the different types of high-precision data in the high-precision map tile data to be processed are drawn on the image prefabricated by the prefabricated module to generate high-precision map image data.

[0030] A third aspect of the present application provides an electronic device, including:

[0031] processor; and

[0032] The memory stores executable codes thereon, and when the executable codes are executed by the processor, the processor is caused to execute the method described above.

[0033] A fourth aspect of the present application provides a computer-readable storage medium having executable code stored thereon. When the executable code is executed by a processor of an electronic device, the processor is caused to execute the method described above.

[0034] The technical solution provided by this application may have the following beneficial effects:

[0035] The technical solution of the present application draws different types of high-precision data in the high-precision map tile data to be processed on a picture of a set pixel size to generate high-precision map picture data; cuts the high-precision map picture data into a set number of raster data according to a set data format, and sets a corresponding unique identification code for each raster data, and stores the set number of raster data and its corresponding unique identification code together; it can improve the storage and reading efficiency of high-precision map data to meet the needs of vehicle autonomous driving.

[0036] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The above and other objects, features and advantages of the present application will become more apparent by describing in more detail exemplary embodiments of the present application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the present application.

[0038] Figure 1 This is a flow chart of a method for processing high-precision map data according to an embodiment of the present application;

[0039] Figure 2 This is another flowchart of the high-precision map data processing method shown in an embodiment of the present application;

[0040] Figure 3 This is a schematic diagram of the structure of a high-precision map data processing device shown in an embodiment of the present application;

[0041] Figure 4 is another structural diagram of a high-precision map data processing device shown in an embodiment of the present application;

[0042] Figure 5 It is a structural diagram of an electronic device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The following describes embodiments of the present application in more detail with reference to the accompanying drawings. Although the accompanying drawings illustrate embodiments of the present application, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. Rather, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0044] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. As used in this application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0045] It should be understood that although the terms "first", "second", "third", etc. may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0046] The embodiment of the present application provides a high-precision map data processing method, which can improve the storage and reading efficiency of high-precision map data and meet the needs of vehicle autonomous driving.

[0047] The technical solutions of the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0048] Figure 1 It is a flow chart of the high-precision map data processing method shown in an embodiment of the present application.

[0049] See also Figure 1 , a high-precision map data processing method, comprising:

[0050] In step S101, a picture of a set pixel size is prefabricated.

[0051] In one embodiment, a blank picture of a set pixel size may be prepared in advance, and the picture may be divided into a plurality of grids of equal size.

[0052] In step S102, different types of high-precision data in the high-precision map tile data to be processed are drawn on a picture to generate high-precision map picture data.

[0053] In one embodiment, different types of high-precision data in the high-precision map tile data to be processed can be represented by different numerical values ​​but are not limited to them. The different types of high-precision data in the high-precision map tile data to be processed are drawn correspondingly on the grid of the image to generate high-precision map image data.

[0054] In step S103, the high-precision map image data is cut into a set number of raster data according to the set data format, and a corresponding unique identification code is set for each raster data, and the set number of raster data and its corresponding unique identification code are stored together.

[0055] In one embodiment, high-precision map image data is cut into multiple raster data according to a set data format, such as but not limited to NDS (Navigation Data Standard); a corresponding unique identification code is set for each raster data based on the attribute data of each raster data, such as but not limited to the geographic location; and the multiple raster data and the unique identification code corresponding to each raster data are stored together.

[0056] The high-precision map data processing method shown in the embodiment of the present application draws different types of high-precision data in the high-precision map tile data to be processed on a picture of a set pixel size to generate high-precision map picture data; cuts the high-precision map picture data into a set number of raster data according to a set data format, and sets a corresponding unique identification code for each raster data, and stores the set number of raster data and its corresponding unique identification code together; it can improve the storage and reading efficiency of high-precision map data and meet the needs of vehicle autonomous driving.

[0057] Figure 2 This is another flow chart of the high-precision map data processing method shown in an embodiment of the present application. Figure 2 Relative to Figure 1 The technical solution of this application is described in more detail.

[0058] See also Figure 2 , a high-precision map data processing method, comprising:

[0059] In step S201, a picture of a set pixel size is prefabricated.

[0060] In one embodiment, a blank picture with a set pixel size, for example but not limited to 10000*10000 pixels, may be pre-made, each pixel of the picture corresponds to a grid, and an initial value is set for each grid.

[0061] In step S202 , the unit longitude and latitude corresponding to a grid of the image is calculated.

[0062] In one embodiment, the longitude and latitude range corresponding to the tile can be calculated based on the tile ID of the high-precision map tile data to be processed at the currently required level, and the maximum and minimum longitude and latitude corresponding to the tile can be obtained; the unit longitude and latitude corresponding to a grid of the image = (maximum value - minimum value) / size of the image, and the size of the image is expressed in pixels of the image. The unit longitude corresponding to a grid of the image = (maximum value of the longitude corresponding to the tile - minimum value of the longitude corresponding to the tile) / length of the image; the unit latitude corresponding to a grid of the image = (maximum value of the latitude corresponding to the tile - minimum value of the latitude corresponding to the tile) / width of the image. For example, for an image of 10000*10000 pixels, each pixel of the image corresponds to a grid, and the unit longitude and latitude corresponding to a grid of the image = (maximum value - minimum value) / 10000. The unit longitude corresponding to a grid of the image = (the maximum longitude corresponding to the tile - the minimum longitude corresponding to the tile) / 10000; the unit latitude corresponding to a grid of the image = (the maximum latitude corresponding to the tile - the minimum latitude corresponding to the tile) / 10000.

[0063] In one embodiment, the unit longitude and latitude corresponding to a grid of the image may be a longitude and latitude range.

[0064] In step S203, the data ranges of different types of high-precision data in the high-precision map tile data to be processed are obtained.

[0065] In one embodiment, the high-precision data range R of different types of high-precision data is the surface data of different types of high-precision data. The data range R of different types of high-precision data in the high-precision map tile data to be processed at the current required level can be obtained based on the high-precision map tile data to be processed at the current required level. For example, the surface data of a road surface, the surface data of a green belt, etc.

[0066] In step S204, the image color values ​​of different types of high-precision data in the high-precision map tile data to be processed are obtained.

[0067] In one embodiment, image color values ​​C corresponding to different types of high-definition data can be predefined. The value range of image color value C is 0-255. Different types of high-definition data in the high-definition map tile data are preset to correspond to different image color values. For example, the image color value C of high-definition ground data is 0, the image color value C of high-definition road data is 1, the image color value C of high-definition green belt data is 2, and so on.

[0068] In one embodiment, different types of high-precision data within the high-precision map tile data to be processed at the currently required level can be obtained based on the high-precision map tile data to be processed at the currently required level. Different image color values ​​C are assigned to the different types of high-precision data within the high-precision map tile data to be processed at the currently required level based on predefined image color values ​​C corresponding to the different types of high-precision data, thereby obtaining the image color values ​​C for the different types of high-precision data within the high-precision map tile data to be processed. Representing different types of high-precision data with different image color values ​​can reduce the amount of high-precision map tile data.

[0069] In step S205, different types of high-precision data in the high-precision map tile data to be processed are drawn on the picture according to the data range, image color value, and unit longitude and latitude corresponding to a grid of the picture to generate high-precision map picture data.

[0070] In one embodiment, the longitude and latitude range corresponding to each grid in the image of the set pixel size can be set based on the unit longitude and latitude corresponding to a grid of the image of the set pixel size and the longitude and latitude range of the high-precision map tile data to be processed at the current required level.

[0071] In one embodiment, the longitude and latitude corresponding to each grid in the image of the pixel size can be set according to the data range R and image color value C of different types of high-precision data in the high-precision map tile data to be processed at the current required level, and the different types of high-precision data in the high-precision map tile data to be processed can be rendered on the image of the set pixel size to generate high-precision map image data.

[0072] For example, the longitude and latitude of each grid in a 10,000*10,000 pixel image are set based on the unit longitude and latitude of a grid in the image and the longitude and latitude of the HD map tile data to be processed at a distance of 2,000*2,000 meters. Based on the high-precision data range R of different types of HD data in the HD map tile data to be processed at a distance of 2,000*2,000 meters, the image color value C, and the longitude and latitude of each grid in the image, the different types of HD data in the HD map tile data to be processed are rendered into a 10,000*10,000 pixel image to generate HD map image data.

[0073] In a specific embodiment, the high-precision data range R of different types of high-precision data in the high-precision map tile data to be processed corresponding to a distance of 2000 meters * 2000 meters, the image color value C, the unit longitude and latitude corresponding to a grid in the image, and the longitude and latitude of the high-precision map tile data to be processed corresponding to a distance of 2000 meters * 2000 meters can be imported into openCV, and drawn through the range assignment method of openCV. The different types of high-precision data in the high-precision map tile data to be processed are drawn on a picture of 10000 * 10000 pixels to generate high-precision map picture data.

[0074] In step S206, the high-precision map image data is cut into a set number of raster data according to the set data format, and a corresponding unique identification code is set for each raster data, and the set number of raster data and its corresponding unique identification code are stored together.

[0075] In a specific embodiment, the high-precision map image data can be cut into 64 pieces of raster data according to the NDS data specifications, and a corresponding 16-layer tile ID can be set for each piece of raster data according to the NDS data specifications and the longitude and latitude of each piece of raster data. The 64 pieces of raster data are saved together with the unique identification code corresponding to each piece of raster data and the tile ID of the high-precision map tile data.

[0076] In a specific embodiment, an autonomous driving vehicle obtains high-precision map tile data corresponding to the 13th layer (Level) in the high-precision map tile data, draws data corresponding to each distance of 2000 meters * 2000 meters in the high-precision map tile data on a picture of 10000 * 10000 pixels to generate high-precision map picture data, cuts the picture data into 16 layers of 64 raster data according to NDS data specifications, sets a corresponding unique identification code for each of the 64 raster data, and stores each of the 64 raster data as a picture. The name of the picture includes the tile ID of the high-precision map tile data and the unique identification code corresponding to each raster data. This can reduce the data volume of the high-precision map data, facilitate the search for raster data, and improve the efficiency of obtaining high-precision maps.

[0077] In step S207, the raster data of the high-precision map image data is searched according to the unique identification code.

[0078] In one embodiment, a unique identification code can be calculated based on the longitude and latitude; and raster data of the high-precision map image data can be searched based on the unique identification code.

[0079] In one specific embodiment, when an autonomous vehicle requires a high-precision map for autonomous driving, the autonomous vehicle can calculate the tile ID of the high-precision map image data of the current required level based on the current latitude and longitude of the autonomous vehicle. The vehicle then searches the stored raster data based on the tile ID to find the raster data that matches the tile ID. Furthermore, the vehicle calculates a unique identification code corresponding to the latitude and longitude of the autonomous vehicle, matches the raster data corresponding to the unique identification code within the raster data that matches the tile ID. Furthermore, the vehicle obtains high-precision map data corresponding to each image color value C in the raster data based on the image color value C of the raster data. By calculating the tile ID based on the current latitude and longitude, the autonomous vehicle can quickly locate the tile data at the current latitude and longitude based on the tile ID. By calculating the unique identification code based on the current latitude and longitude, the vehicle can quickly match the raster data to the current latitude and longitude based on the unique identification code. By obtaining high-precision map data based on the image color value C of the raster data, the autonomous vehicle can reduce the amount of data search required during the high-precision map data reading process, thereby improving the efficiency of high-precision map data search and matching.

[0080] In a specific embodiment, the unique identification code can be the relative coordinate P r The autonomous vehicle can calculate the tile ID of the high-precision map image data based on the current latitude and longitude P of the autonomous vehicle; and calculate the minimum latitude and longitude coordinates P of the tile based on the tile ID. min , maximum longitude and latitude coordinates P max ; According to the longitude and latitude P at the minimum longitude and latitude coordinates P min , maximum latitude and longitude coordinates P max The relative minimum longitude and latitude coordinates P of the rectangular image min The relative coordinate P r ; According to the relative coordinate P r Search in the stored raster data to obtain the relative coordinate P r Corresponding grid; according to the image color value C of the grid, high-precision map data corresponding to the color value C of each image in the grid is obtained, and high-precision map data corresponding to the longitude and latitude can be quickly obtained.

[0081] The high-precision map data processing method shown in the embodiment of the present application draws different types of high-precision data in the high-precision map tile data to be processed on a picture to generate high-precision map picture data of a set pixel size; cuts the high-precision map picture data into a set number of raster data according to a set data format, and sets a corresponding unique identification code for each raster data, and stores the set number of raster data and its corresponding unique identification code together; it can improve the storage and reading efficiency of high-precision map data and meet the needs of vehicle autonomous driving.

[0082] Furthermore, the high-precision map data processing method illustrated in the embodiment of the present application plots the different types of high-precision data in the high-precision map tile data to be processed onto an image based on the data range, image color value, and unit longitude and latitude corresponding to a grid cell in the image, thereby generating high-precision map image data. This reduces the amount of high-precision map data; searches for grid data of high-precision map image data based on a unique identification code; and reduces the amount of data lookup required during the high-precision map data reading process. The high-precision map data processing method of the present application can improve the storage and reading efficiency of high-precision map data, meeting the needs of autonomous vehicle driving.

[0083] Corresponding to the aforementioned application function implementation method embodiment, the present application also provides a high-precision map data processing device, electronic device and corresponding embodiments.

[0084] Figure 3 It is a structural diagram of a high-precision map data processing device shown in an embodiment of the present application.

[0085] See also Figure 3 , a high-precision map data processing device, including a prefabrication module 301, a processing module 302, and a storage module 303.

[0086] The prefabrication module 301 is used to prefabricate a picture of a set pixel size.

[0087] In one embodiment, the prefabrication module 301 may prefabricate a blank image of a set pixel size and divide the image into a plurality of grids of equal size.

[0088] The processing module 302 is used to draw different types of high-precision data in the high-precision map tile data to be processed on the image prefabricated by the prefabrication module 301 to generate high-precision map image data.

[0089] In one embodiment, the processing module 302 can, but is not limited to, use different numerical values ​​to represent different types of high-precision data in the high-precision map tile data to be processed, and draw the different types of high-precision data in the high-precision map tile data to be processed correspondingly on the grid of the image to generate high-precision map image data.

[0090] The storage module 303 is used to cut the high-precision map image data generated by the processing module 302 into a set number of raster data according to the set data format, and set a corresponding unique identification code for each raster data, and store the set number of raster data and its corresponding unique identification code together.

[0091] In one embodiment, the storage module 303 cuts the high-precision map image data into multiple raster data according to a set data format, such as but not limited to NDS; sets a corresponding unique identification code for each raster data according to the attribute data of each raster data, such as but not limited to the geographic location; and stores the multiple raster data and the unique identification code corresponding to each raster data in the autonomous driving vehicle.

[0092] The technical solution shown in the embodiment of the present application draws different types of high-precision data in the high-precision map tile data to be processed on a picture of a set pixel size to generate high-precision map picture data; cuts the high-precision map picture data into a set number of raster data according to a set data format, and sets a corresponding unique identification code for each raster data, and stores the set number of raster data and its corresponding unique identification code together; it can improve the storage and reading efficiency of high-precision map data and meet the needs of vehicle autonomous driving.

[0093] Figure 4 This is another structural diagram of the high-precision map data processing device shown in an embodiment of the present application.

[0094] See also Figure 4 A high-precision map data processing device includes a prefabrication module 301, a processing module 302, a storage module 303, and a search module 304.

[0095] The prefabrication module 301 is used to prefabricate a picture of a set pixel size.

[0096] The processing module 302 is used to calculate the unit longitude and latitude corresponding to a grid of the image prefabricated by the prefabrication module 301; obtain the data range of different types of high-precision data in the high-precision map tile data to be processed; obtain the image color value of different types of high-precision data in the high-precision map tile data to be processed; according to the data range, image color value, and unit longitude and latitude corresponding to a grid of the image of different types of high-precision data in the high-precision map tile data to be processed, the different types of high-precision data in the high-precision map tile data to be processed are drawn on the image prefabricated by the prefabrication module 301 to generate high-precision map image data.

[0097] The storage module 303 is used to cut the high-precision map image data generated by the processing module 302 into a set number of raster data according to the set data format, and set a corresponding unique identification code for each raster data, and store the set number of raster data and its corresponding unique identification code together.

[0098] The search module 304 is used to search for the raster data of the high-precision map image data stored in the storage module 303 according to the unique identification code.

[0099] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated again here.

[0100] Figure 5 It is a structural diagram of an electronic device shown in an embodiment of the present application.

[0101] See also Figure 5 , the electronic device 500 includes a memory 510 and a processor 520.

[0102] The processor 520 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0103] The memory 510 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage. ROM may store static data or instructions required by the processor 520 or other modules of the computer. The permanent storage may be a readable and writable storage device. The permanent storage may be a non-volatile storage device that retains stored instructions and data even when the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (e.g., a magnetic or optical disk, flash memory) as the permanent storage device. In other embodiments, the permanent storage device may be a removable storage device (e.g., a floppy disk, optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as dynamic random access memory. The system memory may store some or all instructions and data required by the processor during operation. In addition, the memory 510 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (e.g., DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and magnetic disks and / or optical disks may also be used. In some embodiments, the memory 510 may include a readable and / or writable removable storage device, such as a compact disc (CD), a read-only digital versatile disc (e.g., DVD-ROM, dual-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (e.g., SD card, mini SD card, Micro-SD card, etc.), a magnetic floppy disk, etc. Computer-readable storage media do not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0104] The memory 510 stores executable codes. When the executable codes are processed by the processor 520 , the processor 520 may execute part or all of the above-mentioned methods.

[0105] In addition, the method according to the present application may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing some or all of the steps in the above method of the present application.

[0106] Alternatively, the present application can also be implemented as a computer-readable storage medium (or non-transitory machine-readable storage medium or machine-readable storage medium) on which executable code (or computer program or computer instruction code) is stored. When the executable code (or computer program or computer instruction code) is executed by a processor of an electronic device (or server, etc.), the processor executes part or all of the steps of the above-mentioned method according to the present application.

[0107] The embodiments of the present application have been described above. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or improvements to the technology in the market, or to enable other persons skilled in the art to understand the embodiments disclosed herein.

Claims

1. A high-precision map data processing method, characterized in that: include: Prefabricate a picture of a set pixel size, and divide the picture into a plurality of grids of equal size; Calculate the unit longitude and latitude corresponding to a grid of the image; Obtain the data range of different types of high-precision data in the high-precision map tile data to be processed; Obtaining image color values ​​of different types of high-precision data in the high-precision map tile data to be processed; According to the data ranges and image color values ​​of different types of high-precision data in the high-precision map tile data to be processed, and the unit longitude and latitude corresponding to a grid of the image, the different types of high-precision data in the high-precision map tile data to be processed are plotted on the image to generate high-precision map image data; The high-precision map image data is cut into a set number of raster data according to a set data format, and a corresponding unique identification code is set for each raster data, and the set number of raster data and its corresponding unique identification code are stored together.

2. The method according to claim 1, characterized in that The method further comprises: Search for the raster data of the high-precision map image data according to the unique identification code.

3. The method according to claim 1, wherein: The numerical range of the image color value is 0-255, and different types of high-precision data in the high-precision map tile data are preset to correspond to different image color values.

4. The method according to claim 2, characterized in that The step of searching for the raster data of the high-precision map image data according to the unique identification code includes: Calculate a unique identification code based on latitude and longitude; Search for the raster data of the high-precision map image data according to the unique identification code.

5. A high-precision map data processing device, characterized in that: include: A prefabrication module, used to prefabricate a picture of a set pixel size and divide the picture into a plurality of grids of equal size; a processing module, configured to calculate the unit longitude and latitude corresponding to a grid of the image prefabricated by the prefabrication module; Obtaining data ranges of different types of high-precision data in the high-precision map tile data to be processed; obtaining image color values ​​of different types of high-precision data in the high-precision map tile data to be processed; According to the data range and image color value of different types of high-precision data in the high-precision map tile data to be processed, and the unit longitude and latitude corresponding to a grid of the image, the different types of high-precision data in the high-precision map tile data to be processed are plotted on the image prefabricated by the prefabrication module to generate high-precision map image data; The storage module is used to cut the high-precision map image data generated by the processing module into a set number of raster data according to a set data format, and set a corresponding unique identification code for each raster data, and store the set number of raster data and its corresponding unique identification code together.

6. The device according to claim 5, characterized in that The device further comprises: A search module is used to search for the raster data of the high-precision map image data stored in the storage module according to a unique identification code.

7. An electronic device, characterized in that: include: processor; as well as A memory having executable codes stored thereon, which, when executed by the processor, causes the processor to execute the method according to any one of claims 1 to 4.

8. A computer-readable storage medium, characterized in that An executable code is stored thereon, and when the executable code is executed by a processor of an electronic device, the processor is caused to execute the method according to any one of claims 1 to 4.

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