Map multi-scale hybrid indexing method and device based on block-layer-target

Abstract

The present invention provides a block-layer-target-based multi-scale hybrid map indexing method and device. The method comprises: Step 1: establishing a multi-scale spatial reference grid for map data of different scales; Step 2: establishing a block index structure for the spatial reference grid blocks, with grids at the same scale organized using a grid encoding method; Step 3: establishing an index structure for the layers in the map within the grid blocks; Step 4: establishing a static target index for the physical object targets based on the data content contained in each layer, pointing to the specific physical object targets. The present invention supports data information queries for block regions, layered data, and object targets, enabling the query and call of multi-scale, full-layer high-precision map data.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of high-precision map technology, and in particular to a block-layer-target based multi-scale hybrid map indexing method and device. Background Art

[0002] High-precision maps (HD maps) are a type of map product designed for autonomous driving that supports lane-level navigation. Compared to traditional electronic navigation maps, HD maps provide higher-precision data and richer map information. They can compensate for the shortcomings and limitations of a vehicle's real-time sensors and provide sufficient prior knowledge for autonomous driving systems. In recent years, with the advancement of autonomous driving technologies, demand for HD maps capable of supporting Level 3 and above has increased. However, the index structure of HD maps currently used by map vendors and autonomous driving companies is insufficient to meet the cross-layer data access and query requirements of autonomous driving systems. Therefore, the development of a multi-scale hybrid map indexing method and device based on blocks, layers, and objects, which can effectively overcome the shortcomings of these technologies, has become a pressing technical challenge for the industry. Summary of the Invention

[0003] In view of the above problems existing in the prior art, an embodiment of the present invention provides a block-layer-object-based multi-scale hybrid map indexing method and device.

[0004] In the first aspect, an embodiment of the present invention provides a block-layer-target based multi-scale hybrid map indexing method, including: step 1, establishing a multi-scale spatial reference grid for map data of different scales; step 2, establishing a block index structure for the spatial reference grid block, and organizing the grids at the same scale using a grid coding method; step 3, establishing an index structure for the layers in the map within the grid block; step 4, establishing a static target index for the physical object target for the data content contained in each layer, pointing to the specific physical object target.

[0005] Based on the content of the above method embodiment, the block-layer-target based map multi-scale hybrid indexing method provided in the embodiment of the present invention, step 1 specifically includes: establishing a grid for the map that has undergone map projection transformation, dividing the most detailed and non-map integrated high-precision map data into a 1 km × 1 km grid; map data of other scales are gridded according to the proportional relationship, and the grid size of map data with a scale of 1:100000 is 100 km × 100 km.

[0006] Based on the content of the above method embodiment, the block-layer-target-based multi-scale hybrid map indexing method provided in the embodiment of the present invention specifically includes: establishing indexes for grid blocks of data at different scales, and organizing and managing the data in each block storage area. The root node of the index points to the grid block of the upper layer of small-scale map data, while the leaf nodes point to the grid block of the lower layer of large-scale map data. In data of the same scale, the adjacency relationship between blocks is expressed and indexed using a grid coding method.

[0007] Based on the content of the above method embodiment, the block-layer-target based map multi-scale hybrid indexing method provided in the embodiment of the present invention, step 3 specifically includes: the root node of the index structure points to the storage address of the entire block data, and the leaf nodes point to the storage addresses of each layer of the map respectively.

[0008] Based on the contents of the above method embodiments, the block-layer-target-based map multi-scale hybrid indexing method provided in the embodiments of the present invention, the data content contained in each layer in step 4 includes: the road network corresponds to traditional road network data; the lane network corresponds to lane-level network data; the road traffic markings correspond to traffic markings drawn on the road surface; the traffic facility layer corresponds to road traffic signs, roadside facilities and other road safety facilities; the service point POI layer corresponds to airports, stadiums, toll booths and tourist attractions POI points.

[0009] In the second aspect, an embodiment of the present invention provides a block-layer-target based map multi-scale hybrid indexing device, including: a first main module, used to implement step 1, establishing a multi-scale spatial reference grid for map data of different scales; a second main module, used to implement step 2, establishing a block index structure for the spatial reference grid block, and the grids under the same scale are organized using a grid coding method; a third main module, used to implement step 3, establishing an index structure for the layers in the map within the grid block; a fourth main module, used to implement step 4, establishing a static target index of the physical object target for the data content contained in each layer, pointing to the specific physical object target.

[0010] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0011] at least one processor; and

[0012] at least one memory communicatively coupled to the processor, wherein:

[0013] The memory stores program instructions that can be executed by the processor. The processor calls the program instructions to execute the block-layer-object-based multi-scale hybrid map indexing method provided by any one of the various implementations of the first aspect.

[0014] In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions enable a computer to execute the block-layer-target based map multi-scale hybrid indexing method provided by any one of the various implementation methods of the first aspect.

[0015] The block-layer-target-based multi-scale hybrid map indexing method and device provided in the embodiments of the present invention support data information query of block areas, layered data and ground object targets, and realize query and call of multi-scale full-layer high-precision map data. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 A flowchart of a block-layer-object-based multi-scale hybrid map indexing method provided by an embodiment of the present invention;

[0018] Figure 2 A schematic diagram of the structure of a block-layer-object-based multi-scale hybrid map indexing device provided by an embodiment of the present invention;

[0019] Figure 3 A schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention;

[0020] Figure 4 A schematic diagram of a multi-scale spatial reference grid provided by an embodiment of the present invention;

[0021] Figure 5a A schematic diagram of data block indexes of different scales provided by an embodiment of the present invention;

[0022] Figure 5b A schematic diagram of another data block index of different scales provided by an embodiment of the present invention;

[0023] Figure 6 A schematic diagram of grid coding of data blocks of the same scale provided by an embodiment of the present invention;

[0024] Figure 7 A schematic diagram of constructing an inner index of a data block according to an embodiment of the present invention;

[0025] Figure 8 A schematic diagram of constructing a target index within layer data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In addition, the technical features in the various embodiments or single embodiments provided by the present invention can be arbitrarily combined with each other to form a feasible technical solution. This combination is not restricted by the sequence of steps and / or structural composition mode, but must be based on the ability of ordinary technicians in this field to implement it. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0027] The embodiment of the present invention provides a multi-scale hybrid indexing method for maps based on block-layer-object. Figure 1 The method includes: step 1, establishing a multi-scale spatial reference grid for map data of different scales; step 2, establishing a block index structure for the spatial reference grid block, and organizing the grids under the same scale using a grid coding method; step 3, establishing an index structure for the layers in the map within the grid block; step 4, establishing a static target index for the physical object target for the data content contained in each layer, pointing to the specific physical object target.

[0028] Based on the content of the above method embodiment, as an optional embodiment, the block-layer-target based map multi-scale hybrid indexing method provided in the embodiment of the present invention, step 1 specifically includes: establishing a grid for the map that has undergone map projection transformation, dividing the most detailed and non-map integrated high-precision map data into a 1 km × 1 km grid; map data of other scales are gridded according to the proportional relationship, and the grid size of map data with a scale of 1:100000 is 100 km × 100 km.

[0029] Based on the content of the above method embodiment, as an optional embodiment, the block-layer-target based multi-scale hybrid map indexing method provided in the embodiment of the present invention specifically includes: establishing indexes for grid blocks under different scale data, and organizing and managing the data of each block storage area. The root node of the index points to the grid block of the upper layer small-scale map data, while the leaf node points to the grid block of the lower layer large-scale map data. In data of the same scale, the adjacency relationship between blocks is expressed and indexed using a grid coding method.

[0030] Based on the content of the above method embodiment, as an optional embodiment, the block-layer-target based map multi-scale hybrid indexing method provided in the embodiment of the present invention, step 3 specifically includes: the root node of the index structure points to the storage address of the entire block data, and the leaf nodes point to the storage addresses of each layer of the map respectively.

[0031] Based on the content of the above method embodiment, as an optional embodiment, the block-layer-target-based map multi-scale hybrid indexing method provided in the embodiment of the present invention, the data content contained in each layer in step 4 includes: the road network corresponds to the traditional road network data; the lane network corresponds to the lane-level network data; the road traffic markings correspond to the traffic markings drawn on the road surface; the traffic facility layer corresponds to road traffic signs, roadside facilities and other road safety facilities; the service point POI layer corresponds to airports, stadiums, toll booths and tourist attractions POI points.

[0032] The block-layer-target based multi-scale hybrid map indexing method provided by the embodiment of the present invention supports data information query of block areas, layered data and ground object targets, and realizes the query and call of multi-scale full-layer high-precision map data.

[0033] Another embodiment provides a block-layer-target based multi-scale hybrid map indexing method, in which the spatial index establishment method includes: constructing a multi-scale spatial reference grid; establishing an index structure between map data blocks of different scales and a grid code between map data blocks at the same scale; establishing a hierarchical data spatial index for the map layer within the data block; and constructing an intra-layer target index for the ground object target.

[0034] Specifically, it includes: Step 1: Establish a multi-scale spatial reference grid for high-precision map data of different scales, establish a square grid for high-precision maps that have undergone map projection transformation, and divide the most detailed high-precision map data that has not been integrated into a 1 km × 1 km grid; after integration, high-precision map data of other scales are gridded according to the proportional relationship. For example, the grid size of high-precision map data with a scale of 1:100,000 is 100 km × 100 km. The constructed multi-scale spatial reference grid is shown in the figure. Figure 4 .

[0035] Step 2: Based on the spatial reference grid established in the previous step, create indexes for grid blocks under different scale data, and organize and manage the data in each block storage area. The root node of the index points to the grid block of the upper layer small scale map data, while the leaf node points to the grid block of the lower layer large scale map data. Figure 5a and Figure 5b , Figure 5a and Figure 5bAn example is given to describe how the block index described in the present invention retrieves one of the blocks. The quadtree index established for the three-layer map data with a scale ratio of 1:2:4 is as follows: Figure 5a As shown, Figure 5b Then Figure 5a The relative position of the region where the index is constructed in the entire experimental area. The data between data of different scales adopts different index structures according to the situation. The quadtree structure used in this embodiment is only used as an example, and the structure used for the index is not limited.

[0036] In data of the same scale, the adjacency relationship between blocks is expressed and indexed using the grid coding method. For grid coding examples, see Figure 6 , Figure 6 The row-column encoding method is used to encode the spatial grid blocks, control the spatial coordinates, and facilitate the retrieval of spatial data. The row-column encoding method used in this embodiment is only used as an example and does not limit the encoding method.

[0037] Step 3: Based on the index for the grid block established in the previous step, establish the index structure for the map layer within each block. Figure 7 , where the index's root node points to the entire data storage address (A), while the leaf nodes point to the data storage addresses of each HD map layer (B: road network, C: lane network, D: road traffic markings, E: traffic facilities layer, F: service point POI layer). The left figure shows the multi-tree index structure, and the right shows the multi-tree storage structure and logical relationships. The multi-tree structure used in this embodiment is only for example, and the index structure used is not limited.

[0038] Step 4: Based on the layer index, a static target index of the physical object target is established for the data content contained in the map layer, pointing to the specific physical object target. Each map layer and the data content contained therein are shown in Table 1. Figure 8 , Figure 8 An R-tree index is established for a three-way intersection, where E is the traffic facility layer, and the area contains two traffic signs (a: speed limit sign, b: speed measurement sign), and D is the road traffic marking layer, and the area contains five road traffic markings (c, d, e: pedestrian crossings, f, g: guide arrows). The spatial relationship is shown in the left figure. The right figure is the index structure of the established R-tree index. This embodiment does not include all the physical objects in the intersection that should be included in the high-precision map layer into the index structure, but only serves as an example of a method for establishing a target index. Similarly, the R-tree structure used in this embodiment is only used as an example, and the structure used for the index is not limited.

[0039] Table 1 Map layer data content table

[0040] High-precision map layers Data content road network Traditional road network data Lane Network Lane-level road network data Road traffic markings Traffic markings painted on the road surface Transportation facilities layer Road traffic signs, roadside facilities, and other road safety facilities Service point POI layer Airports, stadiums, toll booths, tourist attractions POI points

[0041] The implementation basis of each embodiment of the present invention is to implement it through programmed processing by a device with processor functions. Therefore, in engineering practice, the technical solutions and functions of each embodiment of the present invention can be encapsulated into various modules. Based on this reality, on the basis of the above embodiments, the embodiment of the present invention provides a block-layer-target based multi-scale hybrid map indexing device, which is used to execute the block-layer-target based multi-scale hybrid map indexing method in the above method embodiment. Figure 2 The device includes: a first main module, used to implement step 1, establishing a multi-scale spatial reference grid for map data of different scales; a second main module, used to implement step 2, establishing a block index structure for the spatial reference grid block, and organizing the grids under the same scale using a grid coding method; a third main module, used to implement step 3, establishing an index structure for the layers in the map within the grid block; and a fourth main module, used to implement step 4, establishing a static target index for the physical object target based on the data content contained in each layer, pointing to the specific physical object target.

[0042] The block-layer-target-based map multi-scale hybrid indexing device provided by the embodiment of the present invention adopts Figure 2 Several modules in it support data information query of block areas, layered data and ground objects, and realize the query and call of multi-scale full-layer high-precision map data.

[0043] It should be noted that the device in the device embodiment provided by the present invention can be used to implement the method in the above-mentioned method embodiment as well as the method in other method embodiments provided by the present invention. The only difference is that the corresponding functional modules are set. The principle is basically the same as the principle of the above-mentioned device embodiment provided by the present invention. As long as those skilled in the art refer to the specific technical solutions in other method embodiments on the basis of the above-mentioned device embodiment, obtain the corresponding technical means and the technical solutions composed of these technical means by combining technical features, and ensure the practicality of the technical solutions, they can improve the device in the above-mentioned device embodiment to obtain the corresponding device class embodiment, thereby obtaining the corresponding device class embodiment for implementing the methods in other method class embodiments. For example:

[0044] Based on the content of the above-mentioned device embodiment, as an optional embodiment, the block-layer-target-based map multi-scale hybrid indexing device provided in the embodiment of the present invention also includes: a first sub-module, which is used to implement step 1, specifically including: establishing a grid for the map that has undergone map projection transformation, and dividing the most detailed and non-map-integrated high-precision map data into a grid of 1 km × 1 km; map data of other scales are gridded according to the proportional relationship, and the grid size of map data with a scale of 1:100,000 is 100 km × 100 km.

[0045] Based on the content of the above-mentioned device embodiment, as an optional embodiment, the block-layer-target-based multi-scale hybrid map indexing device provided in the embodiment of the present invention further includes: a second submodule for implementing step 2, specifically including: establishing indexes for grid blocks under different scale data, and organizing and managing the data of each block storage area. The root node of the index points to the grid block of the upper-level small-scale map data, while the leaf node points to the grid block of the lower-level large-scale map data. In data of the same scale, the adjacency relationship between blocks is expressed and indexed using a grid coding method.

[0046] Based on the content of the above-mentioned device embodiment, as an optional embodiment, the block-layer-target-based map multi-scale hybrid indexing device provided in the embodiment of the present invention further includes: a third submodule, which is used to implement step 3, specifically including: the root node of the index structure points to the storage address of the entire block of data, and the leaf nodes point to the storage addresses of each layer of the map respectively.

[0047] Based on the content of the above-mentioned device embodiment, as an optional embodiment, the block-layer-target-based map multi-scale hybrid indexing device provided in the embodiment of the present invention further includes: a fourth sub-module, which is used to implement the data content contained in each layer in step 4, including: the road network corresponds to the traditional road network data; the lane network corresponds to the lane-level network data; the road traffic markings correspond to the traffic markings drawn on the road surface; the traffic facility layer corresponds to road traffic signs, roadside facilities and other road safety facilities; the service point POI layer corresponds to airports, stadiums, toll booths and tourist attractions POI points.

[0048] The method of the embodiment of the present invention is implemented by electronic devices, so it is necessary to introduce the relevant electronic devices. Based on this purpose, the embodiment of the present invention provides an electronic device, such as Figure 3As shown, the electronic device includes: at least one processor, a communications interface, at least one memory, and a communications bus, wherein the at least one processor, the communications interface, and the at least one memory communicate with each other via the communications bus. The at least one processor can call logic instructions in the at least one memory to execute all or part of the steps of the methods provided in the aforementioned method embodiments.

[0049] In addition, the logic instructions in the at least one memory mentioned above can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each method embodiment of the present invention. 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.

[0050] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0051] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiment.

[0052] The flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. Based on this understanding, each box in the flowchart or block diagram can represent a module, program segment or part of the code, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, or sometimes in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0053] It should be noted that the terms "comprise," "include," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, the elements defined by the phrase "comprise..." do not preclude the presence of additional identical elements in the process, method, article, or apparatus comprising the elements.

[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A multi-scale hybrid map indexing method based on block-layer-object, characterized in that: include: Step 1: Establish a multi-scale spatial reference grid for map data of different scales; Step 2: Establish a block index structure for the spatial reference grid blocks. Grids at the same scale are organized using a grid coding method. This includes: establishing indexes for grid blocks at different scales, organizing and managing the data in each block storage area; the root node of the index points to the grid block of the upper-level small-scale map data, while the leaf nodes point to the grid block of the lower-level large-scale map data; in data at the same scale, the adjacency relationship between blocks is expressed and indexed using a grid coding method; Step 3: Establish an index structure for the layers in the map within the grid block; including: the root node of the index structure points to the storage address of the entire block data, and the leaf nodes point to the storage address of each layer of the map; Step 4: Create a static target index of the physical ground object target for the data content contained in each layer, pointing to the specific physical ground object target.

2. The block-layer-target based multi-scale hybrid map indexing method according to claim 1, characterized in that: Step 1 specifically includes: establishing a square grid for the map after map projection transformation, dividing the most detailed and unmapped high-precision map data into 1 km 1 km grid; map data of other scales are gridded according to the proportional relationship. For map data with a scale of 1:100000, the grid size is 100 km. 100 kilometers.

3. The block-layer-object-based multi-scale hybrid map indexing method according to claim 1, characterized in that: The data content contained in each layer in step 4 includes: the road network corresponds to the traditional road network data; the lane network corresponds to the lane-level network data; the road traffic markings correspond to the traffic markings drawn on the road surface; the traffic facilities layer corresponds to road traffic signs, roadside facilities and other road safety facilities; the service point POI layer corresponds to the airport, stadium, toll booth and tourist attraction POI points.

4. A map multi-scale hybrid indexing device based on block-layer-object, characterized in that: include: The first main module is used to implement step 1, establishing a multi-scale spatial reference grid for map data of different scales; The second main module is used to implement step 2, establishing a block index structure for the spatial reference grid block, and organizing grids at the same scale using a grid coding method. This includes: establishing indexes for grid blocks at different scales, and organizing and managing the data in each block storage area; the root node of the index points to the grid block of the upper-level small-scale map data, and the leaf nodes point to the grid block of the lower-level large-scale map data; in data at the same scale, the adjacency relationship between blocks is expressed and indexed using a grid coding method; The third main module is used to implement step 3, establishing an index structure for the layers in the map within the grid block; including: the root node of the index structure points to the storage address of the entire block data, and the leaf nodes point to the storage address of each layer of the map; The fourth main module is used to implement step 4, establishing a static target index of the physical ground object target for the data content contained in each layer, pointing to the specific ground object physical target.

5. An electronic device, characterized in that: include: At least one processor, at least one memory and a communication interface; wherein, The processor, memory and communication interface communicate with each other; The memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the method according to any one of claims 1 to 3.

6. A non-transitory computer-readable storage medium, characterized in that The non-transitory computer-readable storage medium stores computer instructions, which cause the computer to execute the method of any one of claims 1 to 3.

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