CN114185613A - Semantic map partitioning method and device, vehicle and storage medium - Google Patents
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Abstract
The invention discloses a semantic map partitioning method, a semantic map partitioning device, a vehicle and a storage medium, wherein the method comprises the following steps: dividing the semantic map into a plurality of block maps according to a designated area; generating a corresponding block file according to each block map; when the semantic map elements in the semantic map are positioned in a plurality of block maps, the semantic map elements are respectively stored in each block file corresponding to the plurality of block maps; creating a directory file, the directory file comprising: basic information of the semantic map and a file list of block files; and acquiring a corresponding directory file according to the basic information of the semantic map, acquiring the address information of the block file from a file list of the directory file, and downloading the block file according to the address information. According to the invention, only map blocks with changed elements need to be processed in the process of converting the original map into the semantic map, so that the map can be used more flexibly, local loading and dynamic loading are realized, the memory space is saved, and the map loading speed is accelerated.
Description
Technical Field
The invention relates to the technical field of vehicles, in particular to a semantic map partitioning method and device, a vehicle and a storage medium.
Background
With the development of artificial intelligence technology, the automatic driving technology is rapidly developed. Automated driving technology is increasingly being applied to commercial operations, such as unmanned vehicles for the taxi industry. In automatic driving, with the expansion of an operation area, a map coverage area is gradually enlarged, so that a single semantic map file is too large to be efficiently loaded into a memory of a general machine.
Disclosure of Invention
The invention mainly aims to provide a semantic map partitioning method, a semantic map partitioning device, a vehicle and a storage medium, and aims to solve the problem that a single semantic map file in the prior art is too large to be loaded into a memory of a general machine efficiently.
In order to achieve the purpose, the invention provides a semantic map partitioning method, which comprises the following steps:
dividing the semantic map into a plurality of block maps according to a designated area;
generating a corresponding block file according to each block map;
when a first semantic map element in the semantic map is located in a plurality of block maps, the first semantic map element is respectively stored in each block file corresponding to the plurality of block maps; and the second semantic map elements contained in the first semantic map elements are only stored in the block files corresponding to the attributive block maps.
Optionally, the method further comprises the steps of:
creating a directory file, the directory file comprising: basic information of the semantic map and a file list of the block files; the basic information of the semantic map comprises: semantic map names and/or semantic map versions and/or high-precision map versions; the file list includes: file identification and/or address information and/or hash values;
and acquiring the corresponding directory file according to the basic information of the semantic map, acquiring the address information of the block file from a file list of the directory file, and downloading the block file according to the address information.
Optionally, the method further comprises the steps of:
allocating a semantic map element identifier for each semantic map element of the semantic map;
when the semantic map elements contain other semantic map elements, the semantic map elements store semantic map element identifications corresponding to the other semantic map elements;
after the block file is downloaded, acquiring the corresponding semantic map element identifier according to the semantic map element contained in the block file;
judging whether the semantic map element identifier has allocated a memory space, and if the semantic map element identifier has not allocated a memory space, allocating a memory space for the semantic map element identifier;
and filling the semantic map elements contained in the downloaded block files into the memory space of the corresponding semantic map element identifiers.
Optionally, the method further comprises the steps of:
according to a first range of the semantic map needing to be downloaded, acquiring the file identification contained in the first range;
judging whether the block file corresponding to the file identifier exists or not;
and if the address information does not exist, the address information corresponding to the block file is obtained from the file directory, and the corresponding block file is downloaded according to the address information.
Optionally, the method further comprises the steps of:
after the downloading of the blocky file is finished, verifying the downloaded blocky file according to the hash value;
if the verification is passed, the downloaded block file is saved; and if the verification fails, deleting the downloaded blocky file.
Optionally, the obtaining the file identifier included in the first range according to the first range of the semantic map that needs to be downloaded includes the following steps:
indexing each block file by a line number and a column number, wherein the coordinates of the line number and the column number are UTM coordinates;
acquiring the first range of the semantic map needing to be downloaded according to the position of the unmanned vehicle and the second range;
and acquiring the file identifier corresponding to the corresponding block file according to the line number and the column number included in the first range.
Optionally, the method further comprises the steps of:
uploading the block files to a cloud server;
the address information of the block file is the cloud address of the block file in the cloud server.
In addition, in order to achieve the above object, the present invention further provides a semantic map partitioning device, including:
the map partitioning unit is used for dividing the semantic map into a plurality of block maps according to the designated area and generating corresponding block files according to each block map; when a first semantic map element in the semantic map is located in a plurality of block maps, the first semantic map element is respectively stored in each block file corresponding to the plurality of block maps; the second semantic map elements contained in the first semantic map elements are only stored in the block files corresponding to the affiliated block maps;
a directory creating unit configured to create a directory file, the directory file including: basic information of the semantic map and a file list of the block files; the basic information of the semantic map comprises: semantic map names and/or semantic map versions and/or high-precision map versions; the file list includes: file identification and/or address information and/or hash values;
and the map downloading unit is used for acquiring the corresponding directory file according to the basic information of the semantic map, acquiring the address information of the block file from a file list of the directory file, and then downloading the block file according to the address information.
Further, to achieve the above object, the present invention also proposes a vehicle comprising: a memory, a processor and a semantic map partitioning program stored on the memory and executable on the processor, the semantic map partitioning program configured to implement the steps of the semantic map partitioning method as described above.
Furthermore, to achieve the above object, the present invention also proposes a computer readable storage medium having stored thereon a computer program which, when being executed by a processor, implements the steps of the semantic map segmentation method as described above.
In the process of converting the original map into the semantic map, the invention only needs to process the map blocks affected by element change. Under the mode of the partitioned map, the map is more flexible in use mode, local loading and dynamic loading can be realized, the memory space is saved, and the speed of loading the map when the automatic driving vehicle is started is increased. By adding the verification mode to each map, the map block which has an error can be positioned more quickly, the situation that the whole map is updated due to one error is avoided, and the map verification efficiency is improved.
Drawings
Fig. 1 is a schematic flow chart of a semantic map partitioning method provided by the present invention.
Fig. 2 is another schematic flow chart of the semantic map partitioning method provided in the present invention.
Fig. 3 is another schematic flow chart of the semantic map partitioning method provided in the present invention.
Fig. 4 is another schematic flow chart of the semantic map partitioning method provided in the present invention.
Fig. 5 is a schematic flow chart of indexing block files by row numbers and column numbers according to the present invention.
Fig. 6 is a block diagram of a semantic map partitioning apparatus according to an embodiment of the present invention.
Fig. 7 is a vehicle structure diagram of a hardware operating environment according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in itself. Thus, "module", "component" or "unit" may be used mixedly.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
In one embodiment, as shown in fig. 1, the present invention provides a semantic map partitioning method, the method comprising:
and S101, dividing the semantic map into a plurality of block maps according to the designated area.
Step S102, generating corresponding block files according to each block map; when a first semantic map element in the semantic map is located in a plurality of block maps, the first semantic map element is respectively stored in each block file corresponding to the plurality of block maps; and the second semantic map elements contained in the first semantic map elements are only stored in the block files corresponding to the attributive block maps.
The semantic map is divided into blocks of e.g. 1024m by 1024m, and each block-divided block map is stored as a separate file, which we call a block file. The stored chunk files are shown in the following table:
| block map numbering | Block map filename |
| 1 | auto_1_map.proto |
| 2 | auto_2_map.proto |
| 3 | auto_3_map.proto |
Since the semantic map is partitioned into a specified area (e.g., 1024m by 1024m), it is inevitable to encounter a situation where some elements span several partitioned map files when generating the partitioned map or loading the partitioned map. For example, a road (e.g., a big-box road) may not fall into exactly one block map, and a method of redundant storage is needed to store information of the road (e.g., the big-box road) in block files of all block maps that it passes through. When the block map is loaded, no matter which block map is loaded first, the road (such as the big Bomb road) can be completely loaded into the memory. If the big huang road passes through 3 block maps with block map numbers of 1-3 respectively, block map files (auto _1_ map.proto, auto _2_ map.proto, auto _3_ map.proto) corresponding to the three block maps respectively store the information of the big huang road.
Each piece of road information also comprises road point information, and the road information stored when the block map is stored comprises an identifier of each piece of road point information; each block map storing road information does not store the road point information included in the road information, and the road point information is stored only in the belonging block map. The method comprises the steps that the big roads in the Funga tree respectively pass through 3 block maps with block map numbers of 1-3, the big roads in the Funga tree contain road points 1-6, the road points 1-2 are in the block map 1, the road points 3-4 are in the block map 2, and the road points 5-6 are in the block map 3. When the block map 1 is stored, the road information of the big road of the Cambodia is stored, including the marks of the road points 1-6, and the information of the road points 1-2 is stored.
Step S103, creating a directory file, wherein the directory file comprises: basic information of the semantic map and a file list of the block files; the basic information of the semantic map comprises: semantic map names and/or semantic map versions and/or high-precision map versions; the file list includes: file identification and/or address information and/or hash values.
A directory file is created for a semantic map, such as a business operating area (e.g., Guangzhou city) corresponding to a semantic map (e.g., Guangzhou operating area semantic map). A corresponding directory file, such as the guangzhou operating area directory file, is created for the semantic map. The directory file stores basic information of the semantic map, such as semantic map names and semantic map versions, based on which high-precision map version, a file list is stored, and the directory file records block files containing cloud addresses and hash values of the block files. As set forth in the following table:
and in the process of partitioning the semantic map, carrying out hash calculation on the partitioned file such as auto _1_ map. And then storing the hash value into a directory file, and after downloading the file from the cloud server subsequently, checking the downloaded file. And judging whether the downloaded file is correct or not by comparing the hash values. The hash algorithm may adopt a conventional algorithm, such as sha256, sha128, and the like, and may also adopt other hash algorithms, which is not limited in this technical solution.
The directory file may be stored in a database to facilitate subsequent queries. Such as in a sqlite database.
And step S104, acquiring the corresponding directory file according to the basic information of the semantic map, acquiring the address information of the block file from a file list of the directory file, and downloading the block file according to the address information.
When the unmanned vehicle uses the semantic map, the corresponding directory file is obtained according to the basic information of the semantic map. If the operating area of the unmanned vehicle A is Guangzhou, acquiring a directory file of the Guangzhou operating area: guangzhou operating area directory file. Then, obtaining the names of the blocky files needing to be downloaded from the file list in the directory file, wherein the names of the blocky files needing to be downloaded are as follows: and (3) obtaining a cloud end address corresponding to the auto _2_ map.
http:// www.autocar11.cn/map/download/auto _2_ map. auto _2_ map.
In the process of converting the original map into the semantic map, the invention only needs to process the map blocks affected by element change. Under the mode of the partitioned map, the map is more flexible in use mode, local loading and dynamic loading can be realized, the memory space is saved, and the speed of loading the map when the automatic driving vehicle is started is increased. By adding the verification mode to each map, the map block which has an error can be positioned more quickly, the situation that the whole map is updated due to one error is avoided, and the map verification efficiency is improved.
In one embodiment, FIG. 2 provides a flow of processing semantic map elements after the semantic map is segmented according to the embodiment of FIG. 1.
Step S105, distributing a semantic map element identifier for each semantic map element of the semantic map; and when the semantic map elements contain other semantic map elements, the semantic map elements store semantic map element identifications corresponding to the other semantic map elements.
The semantic map comprises a plurality of semantic map elements, and a semantic map element identifier needs to be allocated to each semantic map element. If a semantic map comprises a plurality of roads, a semantic map element identifier needs to be allocated to each road. As shown in the following table:
| road 1 | map_id_1 |
| Road 2 | map_id_2 |
| Road 3 | map_id_3 |
A semantic map element may contain a plurality of other semantic map elements, for example, a piece of road information contains which road points are on the road (a road point is generated every 0.5m, which is a basic unit for planning and controlling the use of the semantic map). The semantic map element corresponding to the road (such as the big huangbu road) stores the semantic map element identifier corresponding to other semantic map elements contained in the semantic map element. As shown in the following table:
the indexes between semantic map elements, such as a piece of road information, include which road points are on the road (we will generate a road point every 0.5m, which is the basic unit for the planning control team to use the semantic map). However, if a road crosses the boundary of two blocks, the road points on the road will have their own blocks although the road will have two blocks. For this purpose, the concept of semantic map element identification map _ id is introduced to index various semantic map elements in each map. For example, when a road is loaded, because the road stores which road points are on the road, we can create some memory spaces in advance according to the semantic map element identification map _ id of the road point stored in the road, and the map _ id of one road point corresponds to the memory space of one road point. Then, in the process of loading another block, when loading the road points, the memory space created before is filled according to the map _ id, the information (such as speed limit, etc.) of the road points is filled, and the filling is completed. Namely, the map _ id is assigned during production, and separated elements are bonded and connected through the map _ id during loading, so that the effect of piecing up one block map into the whole map is realized.
And S106, after the block file is downloaded, acquiring the corresponding semantic map element identifier according to the semantic map element contained in the block file.
After downloading the block file auto _3_ map.proto, obtaining semantic map elements included in the block file, where the semantic map elements are: dai, Bo Zhu. Semantic map elements contained in the big road of cambodia, such as road points: road point A, road point B and road point C. The road point may hold information such as speed limit. Obtaining semantic map element identifications contained in the big road of the Cambodia, wherein the semantic map element identifications are shown in the following table:
| map_id_A | road point A |
| map_id_B | Road point B |
| map_id_C | Road point C |
Step S107, judging whether the semantic map element identifier has allocated a memory space, and if the semantic map element identifier has not allocated a memory space, allocating a memory space for the semantic map element identifier.
And judging whether the semantic map element identifier is allocated with a memory space or not according to the semantic map element identifier, and if so, judging whether the map _ id _1 is allocated with the memory space or not. The judgment can be carried out by inquiring a database or a queue, and the semantic map element identification allocated with the memory and the corresponding memory address are stored in the database or the queue. If the map _ id _1 is found to have the corresponding memory space address information in the queue or the database, the semantic map element identifier is indicated to have allocated the memory space; if there is no corresponding memory space address information, a memory space needs to be allocated for the semantic map element, the size of the allocated memory space can be determined according to the type of the semantic map element, and memory spaces with different sizes are allocated for different types.
Step S108, the semantic map elements contained in the downloaded block files are filled into the memory space of the corresponding semantic map element identifiers.
And after downloading the block file auto _3_ map. Then, semantic map elements of the semantic map elements, such as road points included in the big road of the Cambodia, are obtained, and information of each road point is assigned to a memory space corresponding to a corresponding semantic map element identifier. As shown in the following table:
after downloading another block file auto _2_ map.proto, if the semantic map element identifier contained in the file already exists, the memory does not need to be redistributed, and the semantic map element can be directly assigned to the corresponding memory; and when the semantic map element identifier is consistent with the semantic map element stored in the corresponding memory and the block file auto _2_ map.
In the conversion process from the original map to the semantic map, the invention allocates an identifier for each semantic map element and then allocates a memory space for each semantic map element identifier. However, when the downloaded block files all contain the same semantic map element, a memory space is occupied later. Therefore, the memory space is saved, and the speed of loading the map when the automatic driving vehicle is started is increased.
In one embodiment, fig. 3 provides a process flow of downloading block files within a specified range after semantic map segmentation in the embodiment of fig. 1.
Step S109, acquiring the file identifier contained in the first range according to the first range of the semantic map required to be downloaded.
When the unmanned vehicle runs, the semantic map around the current vehicle can be downloaded according to the current position and operation requirements of the vehicle. The specific semantic map of how much access needs to be downloaded can be determined according to the operation condition. If the semantic map with the current vehicle position as the center and the radius of 5 kilometers is required to be downloaded. And acquiring the semantic file identifier required to be downloaded in the range according to the specified range. The specific acquisition process is shown in fig. 5.
Step S201, indexing each block file by a line number and a column number, where coordinates of the line number and the column number are UTM coordinates.
And dividing each block file according to the UTM coordinates, such as taking the operation point as the origin of the UTM coordinates. The UTM (Universal transform Mercator Grid System) coordinate is a planar rectangular coordinate, and this coordinate Grid System and its projection based on it have been widely used in topographic maps, as reference grids for satellite images and natural resource databases, and other applications requiring precise positioning.
The block files are then indexed using the row and column numbers of the UTM coordinates to form a UTM coordinate grid. Each chunk file has an attributed row number and column number, as shown in the following table:
step S202, acquiring the first range of the semantic map needing to be downloaded according to the position of the unmanned vehicle and the second range.
If the current vehicle position is taken as the center, the radius of 5 kilometers is taken as the designated range. And acquiring the row number and the column number of the UTM coordinate included in the range according to the specified range. The obtained row and column numbers are shown in the following table:
| line | Column number | |
| 10 | 20 | |
| 15 | 22 |
Step S203, obtaining the file identifier corresponding to the corresponding block file according to the row number and the column number included in the first range.
And obtaining the row number and the column number according to the specified range to query (such as querying a database), and obtaining the block file name corresponding to the row number and the column number. As shown in the following table:
| name of block file | Line number | Column number |
| auto_1_map.proto | 10 | 20 |
| auto_2_map.proto | 15 | 22 |
Step S110, determining whether the block file corresponding to the file identifier exists.
And step S111, if the address information does not exist, the address information corresponding to the block file is obtained from the file directory, and the corresponding block file is downloaded according to the address information.
And after the corresponding block file name is obtained according to the line number and the column number, judging whether the file exists locally. If so, not continuing the subsequent processing steps; if the file name does not exist, acquiring a cloud end address corresponding to the name of the block file from a directory file corresponding to the current operation area, wherein if the cloud end address is as follows:
http:// www.autocar11.cn/map/download/auto _2_ map.proto, and using the cloud address to download the corresponding block file, such as auto _2_ map.proto, to the corresponding cloud server.
The invention converts each block map coordinate into a UTM coordinate, then assigns a corresponding row number and column number to each block map, and uses the row number and column number as an index for the block map. The method comprises the steps of acquiring a range in which a semantic map needs to be downloaded according to a current position in the unmanned driving process, indexing a corresponding block map name according to a row number and a column number contained in the range, and finally downloading the corresponding block map through the block map name. So that the unmanned can download the block map dynamically according to the position.
In one embodiment, fig. 4 provides a process flow of verifying a downloaded blocky file after semantically partitioning the map of fig. 1.
And S112, after the downloading of the blocky file is finished, verifying the downloaded blocky file according to the hash value.
Step S113, if the verification is passed, the downloaded block file is saved; and if the verification fails, deleting the downloaded blocky file.
After the unmanned vehicle downloads the block file, the downloaded file needs to be checked to ensure that the semantic map file of the downloaded file is correct. The corresponding hash value is obtained from the directory file according to the block file name, as shown in the following table:
| name of block file | Hash value |
| auto_2_map.proto | e147dc3949ba59fbbe96e357f20f8e38 |
And (3) performing hash algorithm with the same hash value established when the blocky file is produced, such as sha256, on the downloaded blocky file auto _2_ map. Then judging whether the hash value A is the same as the hash value corresponding to the blocky file name in the directory file, if so, indicating that the downloaded blocky file is correct, and storing the downloaded blocky file auto _2_ map. And if the files are not the same, the downloaded block file auto _2_ map.
In the process of converting the original map into the semantic map, the invention only needs to process the map blocks affected by element change. Under the mode of the map blocks, a verification mode is added for each map block, so that the map block which has an error can be positioned more quickly, the situation that the whole map is updated due to one error is avoided, and the map verification efficiency is improved.
In addition, an embodiment of the present invention further provides a semantic map partitioning device, and referring to fig. 6, the semantic map partitioning device includes:
the map partitioning unit 10 is used for dividing the semantic map into a plurality of block maps according to the designated area, and generating corresponding block files according to each block map; when a first semantic map element in the semantic map is located in a plurality of block maps, the first semantic map element is respectively stored in each block file corresponding to the plurality of block maps; the second semantic map elements contained in the first semantic map elements are only stored in the block files corresponding to the affiliated block maps;
a directory creating unit 20, configured to create a directory file, where the directory file includes: basic information of the semantic map and a file list of the block files; the basic information of the semantic map comprises: semantic map names and/or semantic map versions and/or high-precision map versions; the file list includes: file identification and/or address information and/or hash values;
and the map downloading unit 30 is configured to obtain the corresponding directory file according to the basic information of the semantic map, obtain the address information of the block file from the file list of the directory file, and then download the block file according to the address information.
In the process of converting the original map into the semantic map, the invention only needs to process the map blocks affected by element change. Under the mode of the partitioned map, the map is more flexible in use mode, local loading and dynamic loading can be realized, the memory space is saved, and the speed of loading the map when the automatic driving vehicle is started is increased. By adding the verification mode to each map, the map block which has an error can be positioned more quickly, the situation that the whole map is updated due to one error is avoided, and the map verification efficiency is improved.
It should be noted that each unit in the apparatus may be configured to implement each step in the method, and achieve the corresponding technical effect, which is not described herein again.
Referring to fig. 7, fig. 7 is a schematic structural diagram of a vehicle in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 7, the vehicle may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include standard wired interfaces, wireless interfaces (e.g., WI-FI, 4G, 5G interfaces). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 7 does not constitute a limitation of the vehicle and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 7, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a semantic map blocking program.
In the vehicle shown in fig. 7, the network interface 1004 is mainly used for data communication with an external network; the user interface 1003 is mainly used for receiving input instructions of a user; the vehicle invokes the semantic map chunking program stored in the memory 1005 by the processor 1001 and performs the following operations:
dividing the semantic map into a plurality of block maps according to a designated area;
generating a corresponding block file according to each block map;
when a first semantic map element in the semantic map is located in a plurality of block maps, the first semantic map element is respectively stored in each block file corresponding to the plurality of block maps; and the second semantic map elements contained in the first semantic map elements are only stored in the block files corresponding to the attributive block maps.
Optionally, the method further comprises the steps of:
creating a directory file, the directory file comprising: basic information of the semantic map and a file list of the block files; the basic information of the semantic map comprises: semantic map names and/or semantic map versions and/or high-precision map versions; the file list includes: file identification and/or address information and/or hash values;
and acquiring the corresponding directory file according to the basic information of the semantic map, acquiring the address information of the block file from a file list of the directory file, and downloading the block file according to the address information.
Optionally, the method further comprises the steps of:
allocating a semantic map element identifier for each semantic map element of the semantic map;
when the semantic map elements contain other semantic map elements, the semantic map elements store semantic map element identifications corresponding to the other semantic map elements;
after the block file is downloaded, acquiring the corresponding semantic map element identifier according to the semantic map element contained in the block file;
judging whether the semantic map element identifier has allocated a memory space, and if the semantic map element identifier has not allocated a memory space, allocating a memory space for the semantic map element identifier;
and filling the semantic map elements contained in the downloaded block files into the memory space of the corresponding semantic map element identifiers.
Optionally, the method further comprises the steps of:
according to a first range of the semantic map needing to be downloaded, acquiring the file identification contained in the first range;
judging whether the block file corresponding to the file identifier exists or not;
and if the address information does not exist, the address information corresponding to the block file is obtained from the file directory, and the corresponding block file is downloaded according to the address information.
Optionally, the method further comprises the steps of:
after the downloading of the blocky file is finished, verifying the downloaded blocky file according to the hash value;
if the verification is passed, the downloaded block file is saved; and if the verification fails, deleting the downloaded blocky file.
Optionally, the obtaining the file identifier included in the first range according to the first range of the semantic map that needs to be downloaded includes the following steps:
indexing each block file by a line number and a column number, wherein the coordinates of the line number and the column number are UTM coordinates;
acquiring the first range of the semantic map needing to be downloaded according to the position of the unmanned vehicle and the second range;
and acquiring the file identifier corresponding to the corresponding block file according to the line number and the column number included in the first range.
Optionally, the method further comprises the steps of:
uploading the block files to a cloud server;
the address information of the block file is the cloud address of the block file in the cloud server.
In the process of converting the original map into the semantic map, the invention only needs to process the map blocks affected by element change. Under the mode of the partitioned map, the map is more flexible in use mode, local loading and dynamic loading can be realized, the memory space is saved, and the speed of loading the map when the automatic driving vehicle is started is increased. By adding the verification mode to each map, the map block which has an error can be positioned more quickly, the situation that the whole map is updated due to one error is avoided, and the map verification efficiency is improved.
Furthermore, an embodiment of the present invention further provides a computer-readable storage medium, where a semantic map partitioning program is stored on the computer-readable storage medium, and when executed by a processor, the semantic map partitioning program implements the following operations:
dividing the semantic map into a plurality of block maps according to a designated area;
generating a corresponding block file according to each block map;
when a first semantic map element in the semantic map is located in a plurality of block maps, the first semantic map element is respectively stored in each block file corresponding to the plurality of block maps; and the second semantic map elements contained in the first semantic map elements are only stored in the block files corresponding to the attributive block maps.
Optionally, the method further comprises the steps of:
creating a directory file, the directory file comprising: basic information of the semantic map and a file list of the block files; the basic information of the semantic map comprises: semantic map names and/or semantic map versions and/or high-precision map versions; the file list includes: file identification and/or address information and/or hash values;
and acquiring the corresponding directory file according to the basic information of the semantic map, acquiring the address information of the block file from a file list of the directory file, and downloading the block file according to the address information.
Optionally, the method further comprises the steps of:
allocating a semantic map element identifier for each semantic map element of the semantic map;
when the semantic map elements contain other semantic map elements, the semantic map elements store semantic map element identifications corresponding to the other semantic map elements;
after the block file is downloaded, acquiring the corresponding semantic map element identifier according to the semantic map element contained in the block file;
judging whether the semantic map element identifier has allocated a memory space, and if the semantic map element identifier has not allocated a memory space, allocating a memory space for the semantic map element identifier;
and filling the semantic map elements contained in the downloaded block files into the memory space of the corresponding semantic map element identifiers.
Optionally, the method further comprises the steps of:
according to a first range of the semantic map needing to be downloaded, acquiring the file identification contained in the first range;
judging whether the block file corresponding to the file identifier exists or not;
and if the address information does not exist, the address information corresponding to the block file is obtained from the file directory, and the corresponding block file is downloaded according to the address information.
Optionally, the method further comprises the steps of:
after the downloading of the blocky file is finished, verifying the downloaded blocky file according to the hash value;
if the verification is passed, the downloaded block file is saved; and if the verification fails, deleting the downloaded blocky file.
Optionally, the obtaining the file identifier included in the first range according to the first range of the semantic map that needs to be downloaded includes the following steps:
indexing each block file by a line number and a column number, wherein the coordinates of the line number and the column number are UTM coordinates;
acquiring the first range of the semantic map needing to be downloaded according to the position of the unmanned vehicle and the second range;
and acquiring the file identifier corresponding to the corresponding block file according to the line number and the column number included in the first range.
Optionally, the method further comprises the steps of:
uploading the block files to a cloud server;
the address information of the block file is the cloud address of the block file in the cloud server.
In the process of converting the original map into the semantic map, the invention only needs to process the map blocks affected by element change. Under the mode of the partitioned map, the map is more flexible in use mode, local loading and dynamic loading can be realized, the memory space is saved, and the speed of loading the map when the automatic driving vehicle is started is increased. By adding the verification mode to each map, the map block which has an error can be positioned more quickly, the situation that the whole map is updated due to one error is avoided, and the map verification efficiency is improved.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, a controller, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A semantic map partitioning method, characterized in that the method comprises the steps of:
dividing the semantic map into a plurality of block maps according to a designated area;
generating a corresponding block file according to each block map;
when a first semantic map element in the semantic map is located in a plurality of block maps, the first semantic map element is respectively stored in each block file corresponding to the plurality of block maps; and the second semantic map elements contained in the first semantic map elements are only stored in the block files corresponding to the attributive block maps.
2. The method of claim 1, further comprising the steps of:
creating a directory file, the directory file comprising: basic information of the semantic map and a file list of the block files; the basic information of the semantic map comprises: semantic map names and/or semantic map versions and/or high-precision map versions; the file list includes: file identification and/or address information and/or hash values;
and acquiring the corresponding directory file according to the basic information of the semantic map, acquiring the address information of the block file from a file list of the directory file, and downloading the block file according to the address information.
3. The method of claim 2, further comprising the steps of:
allocating a semantic map element identifier for each semantic map element of the semantic map;
when the semantic map elements contain other semantic map elements, the semantic map elements store semantic map element identifications corresponding to the other semantic map elements;
after the block file is downloaded, acquiring the corresponding semantic map element identifier according to the semantic map element contained in the block file;
judging whether the semantic map element identifier has allocated a memory space, and if the semantic map element identifier has not allocated a memory space, allocating a memory space for the semantic map element identifier;
and filling the semantic map elements contained in the downloaded block files into the memory space of the corresponding semantic map element identifiers.
4. The method of claim 2, further comprising the steps of:
according to a first range of the semantic map needing to be downloaded, acquiring the file identification contained in the first range;
judging whether the block file corresponding to the file identifier exists or not;
and if the address information does not exist, the address information corresponding to the block file is obtained from the file directory, and the corresponding block file is downloaded according to the address information.
5. The method of claim 2, further comprising the steps of:
after the downloading of the blocky file is finished, verifying the downloaded blocky file according to the hash value;
if the verification is passed, the downloaded block file is saved; and if the verification fails, deleting the downloaded blocky file.
6. The method according to claim 2, wherein the obtaining the file identifier included in the first range according to the first range of the semantic map needing to be downloaded comprises the following steps:
indexing each block file by a line number and a column number, wherein the coordinates of the line number and the column number are UTM coordinates;
acquiring the first range of the semantic map needing to be downloaded according to the position of the unmanned vehicle and the second range;
and acquiring the file identifier corresponding to the corresponding block file according to the line number and the column number included in the first range.
7. The method of claim 2, further comprising the steps of:
uploading the block files to a cloud server;
the address information of the block file is the cloud address of the block file in the cloud server.
8. A semantic map partitioning apparatus, comprising:
the map partitioning unit is used for dividing the semantic map into a plurality of block maps according to the designated area and generating corresponding block files according to each block map; when a first semantic map element in the semantic map is located in a plurality of block maps, the first semantic map element is respectively stored in each block file corresponding to the plurality of block maps; the second semantic map elements contained in the first semantic map elements are only stored in the block files corresponding to the affiliated block maps;
a directory creating unit configured to create a directory file, the directory file including: basic information of the semantic map and a file list of the block files; the basic information of the semantic map comprises: semantic map names and/or semantic map versions and/or high-precision map versions; the file list includes: file identification and/or address information and/or hash values;
and the map downloading unit is used for acquiring the corresponding directory file according to the basic information of the semantic map, acquiring the address information of the block file from a file list of the directory file, and then downloading the block file according to the address information.
9. A vehicle, characterized in that it comprises: memory, a processor and a semantic map partitioning program stored on the memory and executable on the processor, the semantic map partitioning program configured to implement the steps of the semantic map partitioning method according to any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the semantic map segmentation method according to any one of claims 1 to 7.
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Citations (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103839479A (en) * | 2012-11-20 | 2014-06-04 | 江苏省测绘研究所 | High-efficiency electronic-map lettering interaction method |
| CN104933057A (en) * | 2014-03-18 | 2015-09-23 | 北京图盟科技有限公司 | Map service providing method and apparatus |
| CN105426372A (en) * | 2014-09-17 | 2016-03-23 | 高德软件有限公司 | Electronic map data manufacturing and updating method and apparatus |
| CN105447064A (en) * | 2014-09-30 | 2016-03-30 | 高德软件有限公司 | Electronic map data making method and using method and apparatus therefor |
| CN105589891A (en) * | 2014-11-05 | 2016-05-18 | 高德软件有限公司 | Link data production and updating method and device in electronic map |
| CN105758407A (en) * | 2014-12-17 | 2016-07-13 | 高德软件有限公司 | Data generation method and data generation device |
| CN106156124A (en) * | 2015-04-08 | 2016-11-23 | 高德软件有限公司 | The storage method of map element attribute, device, and search method, device |
| CN106250781A (en) * | 2016-07-31 | 2016-12-21 | 山东大学 | A kind of user profile guard method based on virtual machine increment mirror image |
| CN106296647A (en) * | 2016-06-30 | 2017-01-04 | 广州极飞科技有限公司 | A kind of map image section update method and device |
| CN106844537A (en) * | 2016-12-30 | 2017-06-13 | 重庆知行地理信息咨询服务有限公司 | A kind of organization and management method of space-time map tile data |
| CN107180033A (en) * | 2016-03-09 | 2017-09-19 | 高德软件有限公司 | A kind of electronic map data storage method and device |
| CN109492060A (en) * | 2018-09-28 | 2019-03-19 | 湖南国科图创信息科技有限公司 | A kind of map tile storage method based on MBTiles |
| CN109639807A (en) * | 2018-12-19 | 2019-04-16 | 中国四维测绘技术有限公司 | A kind of massive remote sensing image file network transmission method based on slice slice |
| CN110084877A (en) * | 2011-09-26 | 2019-08-02 | 谷歌有限责任公司 | Map element is managed using aggregation features identifier |
| CN110880157A (en) * | 2019-11-15 | 2020-03-13 | 腾讯科技（深圳）有限公司 | Map data processing method and device, electronic equipment and storage medium |
| CN111121794A (en) * | 2019-12-31 | 2020-05-08 | 广州文远知行科技有限公司 | Map rendering method and device, terminal equipment and storage medium |
| CN111190894A (en) * | 2018-11-15 | 2020-05-22 | 阿里巴巴集团控股有限公司 | Map display method and device, related storage medium and client |
| CN111488416A (en) * | 2019-01-29 | 2020-08-04 | 阿里巴巴集团控股有限公司 | Map road data storage method and device and positioning point matching method and device |
| CN111858805A (en) * | 2020-07-08 | 2020-10-30 | 中国第一汽车股份有限公司 | High-precision map updating method, vehicle, server and storage medium |
| CN112069285A (en) * | 2020-11-11 | 2020-12-11 | 湖北亿咖通科技有限公司 | Map generation method and device based on three-dimensional high-precision map slice and electronic equipment |
| CN112070870A (en) * | 2020-07-31 | 2020-12-11 | 广州景骐科技有限公司 | Point cloud map evaluation method and device, computer equipment and storage medium |
| CN112069856A (en) * | 2019-06-10 | 2020-12-11 | 商汤集团有限公司 | Map generation method, driving control method, device, electronic equipment and system |
| CN112131333A (en) * | 2020-09-29 | 2020-12-25 | 中国船舶重工集团公司第七二四研究所 | Tile map storage method based on oracle data file |
| CN113568995A (en) * | 2021-05-11 | 2021-10-29 | 数简科技(苏州)有限公司 | Dynamic tile map making method based on retrieval conditions and tile map system |
| CN113656525A (en) * | 2021-08-19 | 2021-11-16 | 广州小鹏自动驾驶科技有限公司 | Map processing method and device |
-
2021
- 2021-11-30 CN CN202111465363.9A patent/CN114185613A/en active Pending
Patent Citations (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110084877A (en) * | 2011-09-26 | 2019-08-02 | 谷歌有限责任公司 | Map element is managed using aggregation features identifier |
| CN103839479A (en) * | 2012-11-20 | 2014-06-04 | 江苏省测绘研究所 | High-efficiency electronic-map lettering interaction method |
| CN104933057A (en) * | 2014-03-18 | 2015-09-23 | 北京图盟科技有限公司 | Map service providing method and apparatus |
| CN105426372A (en) * | 2014-09-17 | 2016-03-23 | 高德软件有限公司 | Electronic map data manufacturing and updating method and apparatus |
| CN105447064A (en) * | 2014-09-30 | 2016-03-30 | 高德软件有限公司 | Electronic map data making method and using method and apparatus therefor |
| CN105589891A (en) * | 2014-11-05 | 2016-05-18 | 高德软件有限公司 | Link data production and updating method and device in electronic map |
| CN105758407A (en) * | 2014-12-17 | 2016-07-13 | 高德软件有限公司 | Data generation method and data generation device |
| CN106156124A (en) * | 2015-04-08 | 2016-11-23 | 高德软件有限公司 | The storage method of map element attribute, device, and search method, device |
| CN107180033A (en) * | 2016-03-09 | 2017-09-19 | 高德软件有限公司 | A kind of electronic map data storage method and device |
| CN106296647A (en) * | 2016-06-30 | 2017-01-04 | 广州极飞科技有限公司 | A kind of map image section update method and device |
| CN106250781A (en) * | 2016-07-31 | 2016-12-21 | 山东大学 | A kind of user profile guard method based on virtual machine increment mirror image |
| CN106844537A (en) * | 2016-12-30 | 2017-06-13 | 重庆知行地理信息咨询服务有限公司 | A kind of organization and management method of space-time map tile data |
| CN109492060A (en) * | 2018-09-28 | 2019-03-19 | 湖南国科图创信息科技有限公司 | A kind of map tile storage method based on MBTiles |
| CN111190894A (en) * | 2018-11-15 | 2020-05-22 | 阿里巴巴集团控股有限公司 | Map display method and device, related storage medium and client |
| CN109639807A (en) * | 2018-12-19 | 2019-04-16 | 中国四维测绘技术有限公司 | A kind of massive remote sensing image file network transmission method based on slice slice |
| CN111488416A (en) * | 2019-01-29 | 2020-08-04 | 阿里巴巴集团控股有限公司 | Map road data storage method and device and positioning point matching method and device |
| CN112069856A (en) * | 2019-06-10 | 2020-12-11 | 商汤集团有限公司 | Map generation method, driving control method, device, electronic equipment and system |
| CN110880157A (en) * | 2019-11-15 | 2020-03-13 | 腾讯科技（深圳）有限公司 | Map data processing method and device, electronic equipment and storage medium |
| CN111121794A (en) * | 2019-12-31 | 2020-05-08 | 广州文远知行科技有限公司 | Map rendering method and device, terminal equipment and storage medium |
| CN111858805A (en) * | 2020-07-08 | 2020-10-30 | 中国第一汽车股份有限公司 | High-precision map updating method, vehicle, server and storage medium |
| CN112070870A (en) * | 2020-07-31 | 2020-12-11 | 广州景骐科技有限公司 | Point cloud map evaluation method and device, computer equipment and storage medium |
| CN112131333A (en) * | 2020-09-29 | 2020-12-25 | 中国船舶重工集团公司第七二四研究所 | Tile map storage method based on oracle data file |
| CN112069285A (en) * | 2020-11-11 | 2020-12-11 | 湖北亿咖通科技有限公司 | Map generation method and device based on three-dimensional high-precision map slice and electronic equipment |
| CN113568995A (en) * | 2021-05-11 | 2021-10-29 | 数简科技(苏州)有限公司 | Dynamic tile map making method based on retrieval conditions and tile map system |
| CN113656525A (en) * | 2021-08-19 | 2021-11-16 | 广州小鹏自动驾驶科技有限公司 | Map processing method and device |
Non-Patent Citations (3)
| Title |
|---|
| 余文辉等: "矢量切片地图技术在省级电网GIS平台的工程应用", 《机电信息》 * |
| 周桂英: "基于图库一体化的矢量电子地图制作――以"天地图？广东"为例", 《测绘与空间地理信息》 * |
| 常燕 等: ""应用于村镇信息自助平台的电子地图构件关键技术研究"", 《技术交流》 * |
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