A map information processing method, device and computer readable storage medium

Abstract

This application discloses a map information processing method, apparatus, and computer-readable storage medium. This invention can be applied to the field of mapping. It involves: acquiring initial map information; analyzing map element data in the initial map information to determine the map tile identifier to which the map element identifier under each city data belongs; identifying overlapping map tile identifiers between different city data as target map tile identifiers; merging map element identifiers corresponding to the target map tile identifiers in different city data to obtain a target map element identifier set; recording a first relationship between the target map tile identifiers and the target map element identifier set, and assigning the first relationship to any overlapping city data; and obtaining the map element identifiers in the assigned map tile identifiers under each city data and performing parallel compilation, thereby improving the efficiency of map information processing.

Description

Technical Field

[0001] This application relates to the field of map compilation technology, specifically to a map information processing method, apparatus, and computer-readable storage medium. Background Technology

[0002] Traditional navigation maps, limited by navigation positioning and data accuracy, depict map elements in a relatively simple way and have a low degree of simulation and reproduction of the real world. Although they have made navigation more convenient for users to some extent, there are still significant differences between them and real-world scenarios.

[0003] In the existing technology, high-precision maps have emerged. High-precision maps can include information on the location, shape, and type of various elements on the road. Therefore, they can comprehensively and accurately depict various road elements. In the process of researching and practicing the existing technology, the inventors of this invention found that the data volume of high-precision maps in the existing technology is very large, which makes the compilation process of high-precision maps very time-consuming and unable to meet the requirements of rapid updates. Summary of the Invention

[0004] This application provides a map information processing method, apparatus, and computer-readable storage medium, which can realize parallel compilation of map information and improve the efficiency of map information processing.

[0005] To address the aforementioned technical problems, this application provides the following technical solutions:

[0006] A map information processing method, comprising:

[0007] Obtain initial map information, which includes at least map element identifiers, corresponding map element data, and city data;

[0008] Analyze the map element data in the initial map information to determine the map tile identifier to which the map element identifier under each city data belongs;

[0009] The map tile identifiers that overlap between different city data are identified as the target map tile identifiers;

[0010] Merge the map element identifiers corresponding to different city data in the target map block identifiers to obtain the target map element identifier set;

[0011] Record the first relationship between the target map block identifier and the target map element identifier set, and assign the first relationship to any city data that overlaps;

[0012] Map element identifiers from the map tile identifiers under each city's data after allocation are obtained and compiled in parallel.

[0013] A map information processing device, comprising:

[0014] An acquisition unit is used to acquire initial map information, which includes at least map element identifiers, corresponding map element data, and city data.

[0015] The analysis unit is used to analyze the map element data in the initial map information and determine the map tile identifier to which the map element identifier under each city data belongs.

[0016] The determination unit is used to identify the map tile identifiers that overlap between different city data as the target map tile identifiers;

[0017] The merging unit is used to merge the map element identifiers corresponding to different city data in the target map block identifiers to obtain the target map element identifier set.

[0018] The allocation unit is used to record the first relationship between the target map block identifier and the target map element identifier set, and to allocate the first relationship to any city data that overlaps;

[0019] The compilation unit is used to obtain the map element identifiers from the map tile identifiers under each city's data after the division and to compile them in parallel.

[0020] In some embodiments, the acquisition unit is configured to:

[0021] Obtain initial map information, which includes at least map element identifiers, corresponding map element data, and city data;

[0022] The initial map information is stored in the first preset external storage space.

[0023] In some embodiments, the determining unit is configured to:

[0024] Generate sub-units to generate the association between map element identifiers and their respective map tile identifiers for each city's data;

[0025] The sub-unit is determined based on the aforementioned association to identify target map tiles that overlap between different city data.

[0026] In some embodiments, the generating subunit is configured to:

[0027] Obtain the map tile identifiers contained in the data for each city;

[0028] Establish the association between map tile identifiers and corresponding map element identifiers for each city's data;

[0029] The association is stored in the second preset external memory space.

[0030] In some embodiments, the classification unit includes:

[0031] Establish a sub-unit to establish a first relationship between the target map tile identifier and the target map element identifier set;

[0032] A sub-unit is defined to identify city data, including the target map block identifier, as target city data.

[0033] The acquisition subunit is used to acquire the second relationship between the target map block identifier and the corresponding map element identifier under the target city data in the association relationship;

[0034] An update subunit is used to delete the second relationship and update the first relationship to the association relationship of any target city data to obtain the updated target association relationship;

[0035] Wherein, there are no overlapping map block identifiers between different city data in the target association relationship;

[0036] The compilation unit is used for:

[0037] Based on the target association relationship, map element data corresponding to the map element identifier of the map tile identifier under each city data is obtained and compiled in parallel.

[0038] In some embodiments, the updating subunit is configured to:

[0039] Delete the second relationship, update the first relationship to the association relationship of any target city data in the second preset external storage space, and obtain the updated target association relationship stored in the second preset external storage space.

[0040] In some embodiments, the compilation unit includes:

[0041] The reading subunit is used to obtain the target association relationship in the second preset external memory space, and read the map block identifier and the corresponding map element identifier under each city data according to the target association relationship;

[0042] The compilation subunit is used to find the initial map information in the first preset external storage space according to the map element identifier, and read the map element data corresponding to the map block identifier of each city data for parallel compilation.

[0043] In some embodiments, the compilation subunit is configured to:

[0044] Based on the map element identifier, search for the initial map information in the first preset external storage space, and obtain the map element data corresponding to the map block identifier of each city data;

[0045] Using the map block identifier of each city's data as the center, select map block identifiers within a preset range;

[0046] Taking each city's data as a unit, the map element data of each city's data is combined with the map element data of the map element data of the map block within a preset range and compiled in parallel.

[0047] The compilation results of each city's data are merged to obtain the map compilation result.

[0048] In some embodiments, the analysis unit is configured to:

[0049] Read the map element identifiers and corresponding map element data for each city.

[0050] Determine the coordinate range of map element data for each city;

[0051] The map tile identifier to which the map element under each city data belongs is determined based on the coordinate range.

[0052] A computer-readable storage medium storing a plurality of instructions adapted for loading by a processor to perform the steps in the map information processing method described above.

[0053] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps in the map information processing method described above.

[0054] A computer program product or computer program includes computer instructions stored in a storage medium. A processor of a computer device reads the computer instructions from the storage medium and executes the computer instructions, causing the computer to perform the steps in the above-described map information processing method.

[0055] This application embodiment obtains initial map information; analyzes map element data in the initial map information to determine the map tile identifier to which the map element identifier under each city data belongs; identifies overlapping map tile identifiers between different city data as target map tile identifiers; merges the map element identifiers corresponding to the target map tile identifiers in different city data to obtain a target map element identifier set; records the first relationship between the target map tile identifiers and the target map element identifier set, and assigns the first relationship to any overlapping city data; and obtains the map element identifiers in the map tile identifiers under each city data after assignment and performs parallel compilation. In this way, by determining the map tile identifiers covered by each city data through map element data, merging the map element identifiers in the overlapping target map tile identifiers, and assigning them to any overlapping city data, the decoupling of map elements in the overlapping target map tile identifiers between different city data is achieved. This allows the map element data of the map tile identifiers under each city data to be compiled in parallel, greatly improving the efficiency of map information processing compared to the scheme that requires serial compilation of different city data. Attached Figure Description

[0056] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 This is a schematic diagram of a map information processing system provided in an embodiment of this application;

[0058] Figure 2a This is a flowchart illustrating the map information processing method provided in an embodiment of this application;

[0059] Figure 2b This is a schematic diagram of a scenario for the map information processing method provided in the embodiments of this application;

[0060] Figure 3a This is another schematic flowchart of the map information processing method provided in the embodiments of this application;

[0061] Figure 3b This is another schematic flowchart of the map information processing method provided in the embodiments of this application;

[0062] Figure 4 This is a schematic diagram of the structure of the map information processing device provided in the embodiments of this application;

[0063] Figure 5 This is a schematic diagram of the server structure provided in an embodiment of this application. Detailed Implementation

[0064] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0065] This application provides a map information processing method, apparatus, and computer-readable storage medium.

[0066] Please see Figure 1 , Figure 1 This is a schematic diagram of an information processing system provided in an embodiment of this application, including: a terminal 11 and a server 20. The terminal 11 and the server 20 can be connected via a communication network, which includes wireless networks and wired networks. The wireless network includes one or more combinations of wireless wide area networks, wireless local area networks, wireless metropolitan area networks, and wireless personal networks. The network includes network entities such as routers and gateways, which are not shown in the figure. The terminal 11 can interact with the server 20 through the communication network; for example, the server 20 can send map data to the terminal 11.

[0067] The information processing system may include an information processing device, which may be integrated into a terminal, such as a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, in-vehicle terminal, or smart TV. Figure 1 In the middle, this terminal is Figure 1 Terminal 11 can be equipped with various client applications required by users, such as instant messaging clients or map clients. Terminal 11 can receive and load map data sent by the server.

[0068] The information processing system may also include a server 20, which can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. It can be used to obtain initial map information, which includes at least map element identifiers, corresponding map element data, and city data; analyze the map element data in the initial map information to determine the map tile identifier to which the map element identifier under each city data belongs; identify the map tile identifiers that overlap between different city data as target map tile identifiers; merge the map element identifiers corresponding to the target map tile identifiers in different city data to obtain a target map element identifier set; record the first relationship between the target map tile identifiers and the target map element identifier set, and assign this first relationship to any overlapping city data; and obtain the map element identifiers in the map tile identifiers under each assigned city data and perform parallel compilation.

[0069] It should be noted that, Figure 1 The schematic diagram of the information processing system shown is merely an example. The information processing system and scenario described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of information processing systems and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0070] The following sections will provide detailed explanations.

[0071] This application provides a map information processing method, which is illustrated by an example of the map information processing method being executed by a server.

[0072] Please see Figure 2a , Figure 2a This is a schematic flowchart of the map information processing method provided in an embodiment of this application. The map information processing method includes:

[0073] In step 101, the initial map information is obtained.

[0074] It should be noted that the embodiments of this application adopt the NDS data standard format, which is a standardized physical storage format for navigation data advocated by automobile manufacturers, system suppliers, and map providers. The embodiments of this application use the NDS format as the storage format for high-precision maps.

[0075] The NDS uses tiles as the unit to store map information. This means dividing the entire Earth's surface into grids called tiles. Each tile is approximately a square area. A tile contains all map elements within its geographical boundaries; these map elements can be understood as traffic features such as bridges, crosswalks, and road markings.

[0076] Understandably, generating high-precision maps often requires high-precision map information, which includes the location, shape, and type of various road elements. This high-precision map information can accurately and comprehensively represent road features and generate high-precision maps. However, due to the large amount of data in high-precision map information, the time consumed in the map data compilation stage is very large. Map data compilation refers to the process of processing map data to generate more compact and easier-to-use binary files, providing them for quick use by upper-layer applications (such as navigation, positioning, guidance, rendering, etc.).

[0077] In actual testing, it was found that compiling high-precision map information for just 20 cities, including Beijing, Shanghai, Guangzhou, and Shenzhen, would take about 10 hours. Such a compilation speed is obviously unacceptable for compiling more than 300 cities across the country. Since the information on the map changes in real time, it cannot meet the daily update requirements of high-precision maps.

[0078] One major reason for the slow compilation speed is that high-precision map information is compiled sequentially by city. This sequential compilation is necessary because there are significant coupling relationships between cities, for example:

[0079] Please see Figure 2b As shown, the same tile appears in the compilation outputs of two adjacent cities. For example, the compilation outputs of city 1 and city 2 both contain tile 557040193. Within tile 557040193, some roads are assigned to city 1, and some are assigned to city 2. Therefore, after compiling city 1 and city 2 separately, the data in tile 557040193 in city 1 and city 2 needs to be merged, because in the compilation outputs of high-precision maps, data is organized by tile.

[0080] However, the merging process is extremely complex. It requires deserializing the tile data from the separately compiled outputs of each city, reconstructing the relationships between elements, and then reserializing to generate new compiled outputs. In other words, merging must be performed after each city has been compiled separately, making parallel compilation impossible. The reason for this difficulty is that the compiled outputs of each city are not decoupled, and considerable extra effort is required to handle the coupling.

[0081] To address the aforementioned issues, this application embodiment can first obtain initial map information. This initial map information includes at least map element identifiers, corresponding map element data, and city data. The map element identifier is the ID of the map element, and this ID is globally unique. The city data refers to the city name, such as Beijing, Shanghai, and Suzhou. The map element data is the specific data corresponding to the map element ID, used to describe the shape, location, and type of the map element.

[0082] In one implementation, the initial map information can be as shown in the table below:

[0083] Map Element ID City Name Specific data items (map element data) 01 Shanghai X1.txt 02 Beijing X2.txt 03 Beijing X3.txt

[0084] In step 102, the map element data in the initial map information is analyzed to determine the map tile identifier to which the map element identifier under each city data belongs.

[0085] Since each map tile contains a certain geographical location range, i.e., a set of coordinates of the area, the map element data in the initial map information can be analyzed. The tile (i.e., map tile identifier) ​​of the map element described by the map element data can be determined by the coordinates of the map element indicated in the map element data. Similarly, the map tile identifier of the map element data can be determined. Since each map tile is unique, the map tile also has a unique map tile identifier, such as "557040193".

[0086] For example, it can generate map element identifiers for Shanghai, and the map element data coverage to which the map tile identifiers belong have "557040191", "557040193" and "557040195", etc.

[0087] In step 103, the map tile identifiers that overlap between different city data are determined as the target map tile identifiers.

[0088] Since a map tile identifier contains all map elements within the geographical area of ​​that map tile boundary, in order to decouple data from different cities, the map tile identifiers covered by different city data can be compared one by one, and the target map tile identifier that overlaps can be determined as the target tile identifier.

[0089] In some implementations, determining the identifiers of target map tiles that overlap between different city data includes:

[0090] (1) Generate the association between map element identifiers and map tile identifiers under each city data;

[0091] (2) Based on this relationship, identify the target map block identifiers that cause overlap between different city data.

[0092] Based on this, a relationship can be generated between map element identifiers and corresponding map tile identifiers under each city's data. This relationship enables the map element data indicated by the map element identifier to be quickly found and the map compiled based on the map tile identifier.

[0093] Since the association relationship indicates all map tile identifiers covered by all map elements under each city's data, the map tile identifiers covered by different city data can be compared one by one based on the association relationship. The target map tile identifier with intersection and overlap can be determined as the target map tile identifier. For example, if city 1 and city 2 have an overlapping map tile identifier "557040193", then the map tile identifier "557040193" can be determined as the target map tile identifier.

[0094] In step 104, the map element identifiers corresponding to different city data of the target map block identifiers are merged to obtain the target map element identifier set.

[0095] The target map block identifier indicates that the target map block contains map elements under different city data. All map element identifiers corresponding to different city data under the target map block identifier can be merged together to obtain the target map element identifier set.

[0096] For example, the target map tile identifier "557040193" contains map element 1 of city 1 (which can be understood as the road in city 1 as shown in the figure) and map element 2 of city 2 (which can be understood as the road in city 2 as shown in the figure). The map tile identifier 1 corresponding to map element 1 and the map tile identifier 2 corresponding to map element 2 can be merged to generate a target map element identifier set, which includes map element 1 and map element 2.

[0097] In step 105, the first relationship between the target map block identifier and the target map element identifier set is recorded, and the first relationship is assigned to any city data that overlaps.

[0098] In order to decouple different cities, a new first relationship can be recorded between the target map block identifier and the target map element identifier set. In this first relationship, the target map block identifier contains all the map element identifiers of different cities under the target map block identifier.

[0099] Furthermore, the original records of the target map tile identifiers in each city's data that overlap can be deleted, and the first relationship can be assigned to any of the overlapping city's data. For example, the relationship that the target map tile identifier "557040193" contains map element 1 of city 1 (which can be understood as a road in city 1 as shown in the figure) and map element 2 of city 2 (which can be understood as a road in city 2 as shown in the figure) can be deleted. The target map tile identifier "557040193" and the corresponding set of target element identifiers can be recorded as the first relationship. That is, map element 1 and map element 2 can be assigned to either city 1 or city 2 at the same time, so that there are no overlapping target map tile identifiers between city 1 and city 2. In this way, the map tiles between city data can be decoupled.

[0100] In some implementations, the first relationship between the target element identifier set and the target map tile identifier is assigned to any of the overlapping city data, including:

[0101] (1) Establish the first relationship between the target map block identifier and the target map element identifier set;

[0102] (2) Identify the city data that includes the target map block identifier as the target city data;

[0103] (3) Obtain the second relationship between the target map block identifier and the corresponding map element identifier under the target city data in the association relationship;

[0104] (4) Delete the second relationship and update the first relationship to the association relationship of any target city data to obtain the updated target association relationship;

[0105] In this target association, there are no overlapping map tile identifiers between different city data. A new first relationship can be established between the target map tile identifier and the target map element identifier set. In this first relationship, the target map tile identifier includes all map element identifiers of different cities under that target map tile identifier.

[0106] Based on this, city data including the target map tile identifier can be identified as target city data. For example, city 1 and city 2 can be identified as target city data. Then, a second relationship is obtained between the target map tile identifier and the corresponding map element identifier under the target city data in the original association relationship. For example, the second relationship is obtained between city 1 and the target map tile identifier "557040193" and the corresponding map element identifier "Map Element 1", and between city 2 and the target map tile identifier "557040193" and the corresponding map element identifier "Map Element 2".

[0107] To achieve decoupling, the second relationship can be deleted, and the first relationship can be updated to the association relationship of any target city data, resulting in an updated target association relationship. For example, the first relationship between the target map tile identifier "557040193" and map element 1 and map element 2 can be updated to the association relationship of city 1 or city 2, resulting in an updated target association relationship. After the update, city 1 and city 2 do not have overlapping map elements for the target map tile identifier "557040193". And so on, that is, the target map tile identifier and target map element identifier set can be assigned to any overlapping city data. After determining any overlapping city, there are no overlapping target map tile identifiers, thus achieving decoupling between map tiles of city data.

[0108] For example, the first relationship between the target map tile identifier "557040193" and map tile identifier 1 and map element 2 is updated in the association relationship of city 1. The original relationship between the target map tile identifier "557040193" and map tile identifier 1 is deleted in the association relationship of city 2. The updated target association relationship is obtained, so that the target tile identifier "557040193" is associated with map tile identifier 1 and map tile identifier 2 in the target association relationship of city 1, while the corresponding target association relationship of city 2 no longer has the overlay relationship of map tile identifier "557040193", that is, the decoupling between different cities is achieved.

[0109] In step 106, the map element identifiers in the map tile identifiers under each city data after allocation are obtained and compiled in parallel.

[0110] Since the data of each city after being reassigned does not share a common map tile identifier, it can be ensured that the compilation products generated by the final compilation of each city's data are decoupled. The map element identifiers corresponding to the map tile identifiers under each city's data after reassignment can be obtained sequentially. Then, the map element data indicated by the map element identifiers can be used to achieve parallel compilation between the data of each city. Finally, the compilation products of each city are merged to generate a new map file, thus achieving fast compilation.

[0111] As described above, this embodiment of the application obtains initial map information; analyzes the map element data in the initial map information to determine the map tile identifier to which the map element identifier under each city data belongs; identifies the map tile identifiers that overlap between different city data as target map tile identifiers; merges the map element identifiers of different city data corresponding to the target map tile identifiers to obtain a target map element identifier set; records the first relationship between the target map tile identifiers and the target map element identifier set, and assigns the first relationship to any city data that overlaps; and obtains the map element identifiers in the map tile identifiers under each city data after assignment and performs parallel compilation. In this way, by determining the map tile identifiers covered by each city data through map element data, merging the map element identifiers in the overlapping target map tile identifiers, and assigning them to any city data that overlaps, the map elements in the overlapping target map tile identifiers between different city data are decoupled, and the map element data of the map tile identifiers under each city data can be compiled in parallel. Compared with the scheme that requires serial compilation of different city data, this greatly improves the efficiency of map information processing.

[0112] In this embodiment, the map information processing device will be specifically integrated into the server as an example for explanation. Please refer to the following description for details.

[0113] Please see Figure 3a , Figure 3a This is another schematic diagram of the map information processing method provided in an embodiment of this application. The method flow may include:

[0114] In step 201, the server obtains the initial map information and stores it in the first preset external storage space.

[0115] The process involves obtaining initial map information, which includes at least map element identifiers, corresponding map element data, and city data. The map element identifier is the map element's ID, and this ID is globally unique. The city data (i.e., the city name) refers to the city's name, such as Beijing, Shanghai, and Suzhou. The map element data is the specific data corresponding to the map element ID, used to describe the shape, location, and type of the map element.

[0116] In one implementation, the initial map information can be as shown in the table below:

[0117] Map Element ID City Name Specific data items (map element data) 04 Suzhou X4.txt 05 Shanghai X5.txt 06 Shanghai X6.txt

[0118] It should be noted that high-precision map information involves a very large amount of data, which not only takes a lot of time in the map data compilation stage, but also consumes a lot of memory. In addition, to improve processing efficiency, some additional data structures such as mappings or lists need to be created during the data compilation process, and this data needs to reside in memory for a long time.

[0119] Memory refers to the computer's main memory and the cache memory located between the central processing unit (CPU) and main memory. External storage refers to the computer's auxiliary storage, including hard disks, floppy disks, optical disks, etc.

[0120] Due to limited memory and the fact that memory usage can cause server sluggishness, this embodiment of the application can store the initial map information in a first preset external storage space. This first preset external storage space can be a storage space allocated in external storage, or it can be the original database. This allows for the direct retrieval of corresponding map element data by city name for compilation. The execution of obtaining the initial map information and storing the initial map information in the first preset external storage space can be processed in parallel, thereby reducing memory usage and improving server operating efficiency.

[0121] Please refer to the following: Figure 3b As shown, step 1: storing the original data into the database is the same as step 201 above.

[0122] In step 202, the server reads the map element identifiers and corresponding map element data under each city data and determines the coordinate range of the map element data under each city data.

[0123] Please continue reading for more details. Figure 2b As shown, each map tile contains a certain geographical location range, that is, the coordinate set of the area. The server can read the data of each city that needs to be compiled from the first preset external storage space, and obtain the corresponding map element identifier and the corresponding map element data from the first preset external storage space according to the data of each city, and start pre-compilation.

[0124] Furthermore, the analysis can determine the coordinate range of the map elements in each city that they represent in the real world.

[0125] In step 203, the server determines the map tile identifier to which the map element identifier under each city data belongs based on the coordinate range, obtains the map tile identifier contained in each city data, establishes the association relationship between the map tile identifier under each city data and the corresponding map element identifier, and stores the association relationship in the second preset external storage space.

[0126] The server can use this coordinate range to determine the map tile where the map element described by the map element identifier under each city's data belongs. Similarly, based on this coordinate range, it can determine the map tile identifier to which the map element identifier under each city's data belongs. Since each map tile is unique, it also has a map tile identifier, such as "557040191", "557040193", and "557040195". This achieves the pre-compilation stage of dividing all map elements in the city data into tiles. Figure 3b Step 2: Pre-compilation. The formal compilation stage also involves dividing map elements into tiles. The tile division criteria are consistent between these two stages; that is, there should be no discrepancies between the tiles assigned to a map element in the pre-compilation stage and those assigned in the formal compilation stage. Tile division is generally based on the tile where the element's coordinates are located.

[0127] Furthermore, since a map tile identifier contains all map elements within the geographical area of ​​that map tile boundary, a relationship can be established between map element identifiers under each city's data and their corresponding map tile identifiers. This relationship enables the map element data indicated by the map element identifier to be quickly found and used for map compilation based on the map tile identifier.

[0128] For example, please continue reading Figure 2b It can generate map element identifiers for city 1, and the map element data covered by these map element identifiers include "557040191", "557040193", and "557040195". The map element identifier "557040193" contains map element 1. The map element identifier "557040193" can be associated with map element identifier 1. And so on, forming an association between map element identifiers and corresponding map element identifiers under each city's data. This association can be the association between the map element identifier (ID) of all map elements under each city's data and the map element identifier (ID) of all map elements in the map block indicated by the map element identifier ID.

[0129] Finally, in order to enable fast retrieval later, the association can be stored in a second preset external storage space. This second preset external storage space can be a storage space allocated in the external storage, or it can be called an intermediate database.

[0130] In step 204, the server reads the association relationship to obtain the map tile identifier set corresponding to each city data, compares the map tile identifier sets of different city data, and determines the target map tile identifiers where the map tile identifiers overlap.

[0131] Since the association relationship indicates all map tile identifiers covered by all map elements under each city's data, the map tile identifier set corresponding to each city's data can be obtained based on the association relationship. Different city data have different map tile identifier sets; the larger the covered area, the larger the data volume of the map tile identifier set, and vice versa. By comparing the map tile identifier sets of different city data one by one, the target map tile identifier with intersection and overlap is determined as the target map tile identifier. For example, if city 1 and city 2 have an overlapping map tile identifier "557040193", then map tile identifier "557040193" can be determined as the target map tile identifier.

[0132] In step 205, the server merges the map element identifiers corresponding to different city data under the target map block identifier to obtain the target map element identifier set.

[0133] The target map block identifier indicates that the target map block contains map elements under different city data. All map element identifiers corresponding to different city data under the target map block identifier can be merged together to obtain the target map element identifier set.

[0134] For example, please continue reading Figure 2b As shown, the target map tile identifier "557040193" contains map element 1 of city 1 (which can be understood as the road of city 1 as shown in the figure) and map element 2 of city 2 (which can be understood as the road of city 2 as shown in the figure). The map tile identifier 1 corresponding to map element 1 and the map tile identifier 2 corresponding to map element 2 can be merged to generate a target map element identifier set, which includes map tile identifier 1 and map element 2.

[0135] In step 206, the server establishes a first relationship between the target map tile identifier and the target map element identifier set.

[0136] In order to decouple different cities, a new first relationship can be established between the target map block identifier and the target map element identifier set. In this first relationship, the target map block identifier contains all the map element identifiers of different cities under the target map block identifier.

[0137] For example, please continue reading Figure 2b As shown, a first relationship is established between the target map block identifier "557040193", map block identifier 1, and map element 2.

[0138] In step 207, the server determines the city data including the target map tile identifier as the target city data, and obtains the second relationship between the target map tile identifier and the corresponding map element identifier under the target city data in the association relationship.

[0139] Please continue reading for more details. Figure 2b As shown, the server can identify both City 1 and City 2, which contain the target map tile identifier, as target city data, and obtain the second relationship between the target map tile identifier "557040193" under City 1 and the corresponding map element identifier 1, and the target map tile identifier "557040193" under City 2 and the corresponding map element identifier 2.

[0140] In step 208, the server deletes the second relationship and updates the first relationship to the association relationship of any target city data in the second preset external storage space, thereby obtaining the updated target association relationship stored in the second preset external storage space.

[0141] Please continue reading for more details. Figure 2b As shown, the server can delete the second relationship between the target map tile identifier "557040193" under city 1 and the corresponding map element identifier 1 and the target map tile identifier "557040193" under city 2 and the corresponding map element identifier 2, that is, remove the coupling relationship in the duplicate target map tile identifiers.

[0142] Furthermore, the first relationship can be updated to the association relationship of city 1 or city 2 in the intermediate database (i.e., the second preset external storage space). That is, the first relationship between the target map block identifier "557040193" and map block identifier 1 and map element 2 can be assigned to the association of any city in city 1 or city 2, for example, assigned to the association relationship of city 1, so as to obtain the updated target association relationship stored in the second preset external storage space.

[0143] This makes the target block identifier "557040193" associated with map block identifier 1 and map block identifier 2 in the target association relationship of city 1, while the target association relationship of city 2 no longer has the map block identifier "557040193" covering the relationship. That is, there are no overlapping map blocks between the two cities, and the roads do not need to be merged after compilation and decompilation, thus achieving decoupling.

[0144] In step 209, the server obtains the target association relationship in the second preset external storage space and reads the map block identifier and the corresponding map element identifier under each city data.

[0145] Since each city's data does not share a common map tile identifier, the final compiled outputs for each city's data are decoupled. The server can access the target associations in the second preset external storage space (i.e., the intermediate database), and sequentially read the map tile identifiers and corresponding map element identifiers for each city to enter the formal compilation process. This initiates the implementation. Figure 3b Step 3 shown: Formal compilation.

[0146] In step 210, the server searches for the initial map information in the first preset external storage space based on the map element identifier, obtains the map element data corresponding to the map block identifier of each city data, takes the map block identifier of each city data as the center, selects map block identifiers within a preset range and compiles the map element data of the map block identifier of each city data in parallel with the map element data of the map block identifier within the preset range, and merges the compilation results of each city data to obtain the map compilation result.

[0147] The server can search for the initial map information in the first preset external storage space (i.e., the original database) based on the obtained map element identifiers, and then sequentially obtain the map element identifiers corresponding to the map block identifiers under each city data.

[0148] It should be noted that some processing steps in the data compilation process still have inherent coupling relationships that cannot be decoupled. For example, generating the relative height of roads and the relationship between the piers of elevated roads requires processing roads within a certain range in a unified manner. Roads within a certain range may span multiple map tiles or even multiple cities, so roads from multiple cities need to be processed together.

[0149] This means that during compilation, map tile identifiers for each city's data can be used as the center, selecting map tile identifiers within a preset range. For example, if the preset range is 1, then 9 map tile identifiers surrounding the currently compiled data can be selected. During compilation, each map tile identifier also needs to be used as the center, pulling out a certain range of map tile identifiers as a reference. Using each city's data as a unit, the map element data of each city's map tile identifiers is combined with the map element data of the map tile identifiers within the preset range as a reference for parallel compilation. This can better solve the data coupling problem at the junctions of multiple cities and at points like bridge piers. Finally, compilation is performed on a city-by-city basis. Each city's data only saves the compiled data under its own map tile identifiers; the compiled data under map tile identifiers within the preset range is lost. This allows each city's data to be compiled independently and in parallel. Due to the pre-compilation stage, the compiled outputs of each city are decoupled during the formal compilation stage. It is only necessary to simply merge the compiled outputs of each city into a new file without any additional processing, thus achieving [the desired result]. Figure 3b Step 4, as shown, merges the compilation outputs to generate a new map file.

[0150] This invention significantly improves the compilation speed of high-precision map information by performing parallel compilation, meeting the requirement of daily updates of high-precision maps for more than 300 cities across the country.

[0151] Experimental testing showed that this invention, tested on a cloud server with 84 CPU cores and 256GB of memory, could compile data for 77 cities, including Beijing, Shanghai, Guangzhou, and Shenzhen, within 35 minutes. Previous serial methods required at least two days to compile, significantly improving map compilation efficiency. Specific applications can utilize single-machine multi-threading or multi-machine cluster processing using big data frameworks such as Spark and Hadoop, making it widely applicable.

[0152] As described above, this embodiment of the application obtains initial map information; analyzes the map element data in the initial map information to determine the map tile identifier to which the map element identifier under each city data belongs; identifies the map tile identifiers that overlap between different city data as target map tile identifiers; merges the map element identifiers of different city data corresponding to the target map tile identifiers to obtain a target map element identifier set; records the first relationship between the target map tile identifiers and the target map element identifier set, and assigns the first relationship to any city data that overlaps; and obtains the map element identifiers in the map tile identifiers under each city data after assignment and performs parallel compilation. In this way, by determining the map tile identifiers covered by each city data through map element data, merging the map element identifiers in the overlapping target map tile identifiers, and assigning them to any city data that overlaps, the map elements in the overlapping target map tile identifiers between different city data are decoupled, and the map element data of the map tile identifiers under each city data can be compiled in parallel. Compared with the scheme that requires serial compilation of different city data, this greatly improves the efficiency of map information processing.

[0153] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a map information processing device provided in an embodiment of this application. The map information processing device may include an acquisition unit 301, an analysis unit 302, a determination unit 303, a merging unit 304, a classification unit 305, and a compilation unit 306. The map information processing device is applied to a server.

[0154] The acquisition unit 301 is used to acquire initial map information, which includes at least map element identifiers, corresponding map element data, and city data.

[0155] In some embodiments, the acquisition unit 301 is configured to:

[0156] Obtain initial map information, which includes at least map element identifiers, corresponding map element data, and city data;

[0157] The initial map information is stored in the first preset external storage space.

[0158] Analysis unit 302 is used to analyze the map element data in the initial map information and determine the map tile identifier to which the map element identifier under each city data belongs.

[0159] In some embodiments, the analysis unit 302 is configured to:

[0160] Read the map element identifiers and corresponding map element data for each city.

[0161] Determine the coordinate range of map element data for each city;

[0162] The map tile identifier to which the map element under each city data belongs is determined based on the coordinate range.

[0163] The determination unit 303 is used to determine the map tile identifiers that overlap between different city data as the target map tile identifiers.

[0164] In some embodiments, the determining unit 303 includes:

[0165] Generate sub-units to generate the association between map element identifiers and their respective map tile identifiers for each city's data;

[0166] The sub-unit is determined based on the association relationship to identify the target map tile identifiers that cause overlap between different city data.

[0167] In some embodiments, the generating subunit is used for:

[0168] Obtain the map tile identifiers contained in the data for each city;

[0169] Establish the association between map tile identifiers and corresponding map element identifiers for each city's data;

[0170] Store the association in the second preset external storage space.

[0171] Merging unit 304 is used to merge map element identifiers corresponding to different city data of the target map block identifier to obtain a target map element identifier set.

[0172] The allocation unit 305 is used to record the first relationship between the target map block identifier and the target map element identifier set, and to allocate the first relationship to any city data that overlaps.

[0173] In some embodiments, the update unit 305 includes:

[0174] Establish a sub-unit to establish the first relationship between the target map tile identifier and the target map element identifier set;

[0175] Determine the sub-unit, which is used to identify city data including the target map tile identifier as target city data;

[0176] The sub-unit is used to obtain the second relationship between the target map block identifier and the corresponding map element identifier under the target city data in the association relationship;

[0177] The update sub-unit is used to delete the second relationship and update the first relationship to the association relationship of any target city data, so as to obtain the updated target association relationship;

[0178] In this target association, there are no overlapping map tile identifiers between different city data;

[0179] This compilation unit is used for:

[0180] Based on this target association, map element data corresponding to the map element identifier of the map tile identifier under each city data is obtained and compiled in parallel.

[0181] In some embodiments, the updating subunit is used for:

[0182] Delete the second relationship, update the first relationship to the association relationship of any target city data in the second preset external storage space, and obtain the updated target association relationship stored in the second preset external storage space.

[0183] Compilation unit 306 is used to obtain the map element identifiers in the map tile identifiers under the data of each city after the division and to compile them in parallel.

[0184] In some embodiments, the compilation unit 306 includes:

[0185] The reading subunit is used to obtain the target association relationship in the second preset external memory space, and read the map block identifier and the corresponding map element identifier under each city data according to the target association relationship;

[0186] The compilation subunit is used to find the initial map information in the first preset external storage space based on the map element identifier, and read the map element data corresponding to the map block identifier of each city data for parallel compilation.

[0187] In some embodiments, the compilation subunit is used for:

[0188] Based on the map element identifier, locate the initial map information in the first preset external storage space, and obtain the map element data corresponding to the map block identifier of each city data;

[0189] Using the map block identifier of each city's data as the center, select map block identifiers within a preset range;

[0190] Taking each city's data as a unit, the map element data of each city's data is combined with the map element data of the map element data of the map block within a preset range and compiled in parallel.

[0191] The compilation results of each city's data are merged to obtain the map compilation result.

[0192] The specific implementation of each of the above units can be found in the previous embodiments, and will not be repeated here.

[0193] This application also provides a computer device, which can be a server, such as... Figure 5 As shown, it illustrates a schematic diagram of the server structure involved in an embodiment of this application. Specifically:

[0194] The computer device may include components such as a processor 401 with one or more processing cores, a memory 402 with one or more computer-readable storage media, a power supply 403, and an input unit 404. Those skilled in the art will understand that... Figure 5 The computer device structure shown does not constitute a limitation on the computer device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

[0195] Processor 401 is the control center of the computer device. It connects various parts of the computer device via various interfaces and lines. By running or executing software programs and / or modules stored in memory 402, and by calling data stored in memory 402, it performs various functions of the computer device and processes data, thereby providing overall monitoring of the computer device. Optionally, processor 401 may include one or more processing cores; optionally, processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the aforementioned modem processor may also not be integrated into processor 401.

[0196] The memory 402 can be used to store software programs and modules. The processor 401 executes various functional applications and data processing by running the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the server, etc. In addition, the memory 402 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 with access to the memory 402.

[0197] The computer equipment also includes a power supply 403 that supplies power to the various components. Optionally, the power supply 403 can be logically connected to the processor 401 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 403 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0198] The computer device may also include an input unit 404, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0199] Although not shown, the computer device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 401 in the computer device loads the executable files corresponding to the processes of one or more applications into the memory 402 according to the following instructions, and the processor 401 runs the applications stored in the memory 402, thereby implementing the various method steps provided in the foregoing embodiments, as follows:

[0200] Obtain initial map information, which includes at least map element identifiers, corresponding map element data, and city data. Analyze the map element data in the initial map information to determine the map tile identifier to which the map element identifier under each city data belongs. Identify the map tile identifiers that overlap between different city data as target map tile identifiers. Merge the map element identifiers of different city data corresponding to the target map tile identifiers to obtain a target map element identifier set. Record the first relationship between the target map tile identifiers and the target map element identifier set, and assign this first relationship to any overlapping city data. Obtain the map element identifiers in the map tile identifiers under each assigned city data and compile them in parallel.

[0201] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the detailed description of the map information processing method above, which will not be repeated here.

[0202] As described above, the computer device in this embodiment can obtain initial map information; analyze map element data in the initial map information to determine the map tile identifier to which the map element identifier under each city data belongs; determine the map tile identifiers that overlap between different city data as target map tile identifiers; merge the map element identifiers of different city data corresponding to the target map tile identifiers to obtain a target map element identifier set; record the first relationship between the target map tile identifiers and the target map element identifier set, and assign the first relationship to any city data that overlaps; and obtain the map element identifiers in the map tile identifiers under each city data after assignment and compile them in parallel. In this way, by determining the map tile identifiers covered by each city data through map element data, merging the map element identifiers in the overlapping target map tile identifiers, and assigning them to any city data that overlaps, the decoupling of map elements in the overlapping target map tile identifiers between different city data is achieved. This allows the map element data of the map tile identifiers under each city data to be compiled in parallel, greatly improving the efficiency of map information processing compared to the scheme that requires serial compilation of different city data.

[0203] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0204] Therefore, embodiments of this application provide a computer-readable storage medium storing a plurality of instructions that can be loaded by a processor to execute steps in any of the map information processing methods provided in embodiments of this application. For example, the instructions can execute the following steps:

[0205] Obtain initial map information, which includes at least map element identifiers, corresponding map element data, and city data. Analyze the map element data in the initial map information to determine the map tile identifier to which the map element identifier under each city data belongs. Identify the map tile identifiers that overlap between different city data as target map tile identifiers. Merge the map element identifiers of different city data corresponding to the target map tile identifiers to obtain a target map element identifier set. Record the first relationship between the target map tile identifiers and the target map element identifier set, and assign this first relationship to any overlapping city data. Obtain the map element identifiers in the map tile identifiers under each assigned city data and compile them in parallel.

[0206] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various optional implementations of the above embodiments.

[0207] The computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0208] Since the instructions stored in the computer-readable storage medium can execute the steps in any of the map information processing methods provided in the embodiments of this application, the beneficial effects that any of the map information processing methods provided in the embodiments of this application can achieve can be realized. For details, please refer to the previous embodiments, which will not be repeated here.

[0209] The foregoing has provided a detailed description of a map information processing method, apparatus, and computer-readable storage medium provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A map information processing method characterized by comprising: The method comprises the following steps: acquiring initial map information, wherein the initial map information at least comprises map element identifiers, corresponding map element data and belonging city data; analyzing the map element data in the initial map information to determine the map block identifiers to which the map element identifiers in each city data belong; determining the target map block identifiers which overlap between different city data, comprising: generating the association relationship between the map element identifiers and the map block identifiers in each city data; and determining the target map block identifiers which overlap between different city data based on the association relationship; merging the map element identifiers corresponding to the target map block identifiers in different city data to obtain a target map element identifier set; recording the first relationship between the target map block identifiers and the target map element identifier set, and classifying the first relationship into any city data which overlaps, comprising: establishing the first relationship between the target map block identifiers and the target map element identifier set; determining the city data comprising the target map block identifiers as target city data; acquiring the second relationship between the target map block identifiers and the corresponding map element identifiers in the target city data in the association relationship; deleting the second relationship, and updating the first relationship to the association relationship in any target city data to obtain an updated target association relationship; and the target association relationship does not have overlapping map block identifiers between different city data; acquiring the map element identifiers in the map block identifiers in each classified city data for parallel compilation.

2. The map information processing method according to claim 1, characterized by, The method comprises the following steps: acquiring initial map information, wherein the initial map information at least comprises map element identifiers, corresponding map element data and belonging city data; storing the initial map information to a first preset external memory space.

3. The map information processing method according to claim 1, characterized by, The method comprises the following steps: acquiring the map block identifiers contained in each city data; establishing the association relationship between the map block identifiers in each city data and the corresponding map element identifiers; storing the association relationship to a second preset external memory space.

4. The map information processing method according to claim 1 or 3, characterized by, The method comprises the following steps: acquiring the map element data corresponding to the map element identifiers of the map block identifiers in each city data based on the target association relationship for parallel compilation.

5. The map information processing method according to claim 1, characterized by, The method comprises the following steps: updating the first relationship to the association relationship in any target city data to obtain an updated target association relationship, comprising:

6. The map information processing method according to claim 5, characterized by, updating the first relationship to the association relationship in any target city data in the second preset external memory space to obtain the updated target association relationship stored in the second preset external memory space. The method comprises the following steps: acquiring the map element identifiers in the map block identifiers in each classified city data for parallel compilation. Obtaining a target association relationship in the second preset external memory space, and reading a map block identifier and a corresponding map element identifier under each city data according to the target association relationship; According to the map element identifier, the initial map information in the first preset external memory space is searched, and the corresponding map element data under the map block identifier of each city data is read and compiled in parallel.

7. The map information processing method according to claim 6, characterized by, The reading and parallel compiling of the map element data under the map block identifier of each city data comprises: Obtaining the map element data corresponding to the map block identifier of each city data; Selecting the map block identifier within a preset range as the center of each city data; Taking each city data as a unit, the map element data of each city data is combined with the map element data of the map block identifier within the preset range for parallel compilation; The compilation results of each city data are merged to obtain a map compilation result.

8. The map information processing method according to claim 1, characterized by, The analysis of the map element data in the initial map information to determine the map block identifier to which the map element identifier under each city data belongs comprises: Reading the map element identifier and the corresponding map element data under each city data; Determining the coordinate range of the map element data under each city data; According to the coordinate range, the map block identifier to which the map element identifier under each city data belongs is determined.

9. A map information processing apparatus characterized by comprising: Comprise: The acquisition unit is used to acquire initial map information, and the initial map information at least includes a map element identifier, corresponding map element data and belonging city data; The analysis unit is used to analyze the map element data in the initial map information, and determine the map block identifier to which the map element identifier under each city data belongs; The determination unit is used to determine the target map block identifier which overlaps between different city data; The determination unit comprises: a generation subunit for generating an association relationship between the map element identifier under each city data and the belonging map block identifier; a determination subunit for determining the target map block identifier which overlaps between different city data based on the association relationship; The merging unit is used to merge the map element identifier corresponding to the target map block identifier of different city data to obtain a target map element identifier set; The classification unit is used to record a first relationship between the target map block identifier and the target map element identifier set, and classify the first relationship into any city data which overlaps; The compiling unit is used to obtain the map element identifier in the map block identifier under each city data after classification for parallel compilation; The classification unit comprises: The establishment subunit is used to establish the first relationship between the target map block identifier and the target map element identifier set; The determination subunit is used to determine the city data including the target map block identifier as a target city data; The acquisition subunit is used to acquire a second relationship between the target map block identifier and the corresponding map element identifier under the target city data in the association relationship; The updating subunit is configured to delete the second relationship and update the first relationship to an association relationship of any target city data to obtain an updated target association relationship, and the target association relationship does not have overlapping map block identifiers between different city data.

10. The apparatus of claim 9, wherein, The obtaining unit is configured to obtain initial map information, and the initial map information at least includes a map element identifier, corresponding map element data, and city data to which the map element data belongs. The initial map information is stored in a first preset external memory space.

11. The apparatus of claim 9, wherein, The generating subunit is configured to: obtain map block identifiers included in each city data; establish an association relationship between the map block identifiers under each city data and corresponding map element identifiers; store the association relationship in a second preset external memory space.

12. The apparatus of claim 9 or 11, wherein, The compiling unit is configured to: according to the target association relationship, obtain map element data corresponding to map element identifiers of map block identifiers under each city data, and perform parallel compilation.

13. The apparatus of claim 9, wherein, The updating subunit is configured to: update the first relationship to an association relationship of any target city data in the second preset external memory space to obtain an updated target association relationship stored in the second preset external memory space.

14. The apparatus of claim 13, wherein, The compiling unit includes: a reading subunit configured to obtain a target association relationship in the second preset external memory space, and read map block identifiers under each city data and corresponding map element identifiers according to the target association relationship; a compiling subunit configured to search for initial map information in the first preset external memory space according to the map element identifiers, read corresponding map element data under the map block identifiers of each city data, and perform parallel compilation.

15. The apparatus of claim 14, wherein, The compiling subunit is configured to: obtain corresponding map element data under the map block identifiers of each city data; select map block identifiers within a preset range as a center of the map block identifiers of each city data; perform parallel compilation on the map element data of each city data and the map element data of the map block identifiers within the preset range in units of each city data; merge the compilation results of each city data to obtain a map compilation result.

16. The apparatus of claim 9, wherein, The analysis unit is configured to: read map element identifiers under each city data and corresponding map element data; determine a coordinate range of the map element data under each city data; determine map block identifiers to which the map element identifiers under each city data belong according to the coordinate range.

17. A computer readable storage medium characterized in that, The computer readable storage medium stores a plurality of instructions, and the instructions are adapted to be loaded by the processor to perform the steps in the map information processing method of any one of claims 1 to 8.

18. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor performs the computer program to realize the steps in the map information processing method of any one of claims 1 to 8.

19. A computer program product comprising computer programs or instructions, characterized in that, The computer program or instructions are executed by the processor to realize the steps in the map information processing method of any one of claims 1 to 8.

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