Map data processing method, device, electronic device and storage medium

Abstract

The present disclosure provides a map data processing method, apparatus, electronic device, and storage medium, relating to the computer field, particularly to the field of intelligent transportation. A specific implementation scheme comprises: obtaining original map data to be processed, wherein the original map data is in units of a first level of refinement used to represent a target area; converting the original map data into target map data, wherein the target map data is in units of a second level of refinement used to represent the target area, and the second level of refinement is higher than the first level of refinement; and performing allocation processing on the target map data to obtain an allocation result.

Description

Technical Field

[0001] The present disclosure relates to the field of computers, and in particular to a method, device, electronic device, and storage medium for processing map data in the field of intelligent transportation. Background Art

[0002] Currently, in the process of map updating, map data is usually distributed in units of map sheets. That is, the smallest unit of data is the map sheet. The data has a large granularity, is prone to mutual interference, and is difficult to perform large-scale concurrent operations. Summary of the Invention

[0003] The present disclosure provides a method, device, electronic device, and storage medium for processing map data.

[0004] According to one aspect of the present disclosure, a method for processing map data is provided. The method comprises: obtaining original map data to be processed, wherein the original map data has a unit of a map sheet representing a first level of refinement for representing a target area; converting the original map data into target map data, wherein the target map data has a unit of a second level of refinement for representing the target area, and the second level of refinement is higher than the first level of refinement; and performing allocation processing on the target map data to obtain an allocation result.

[0005] According to another aspect of the present disclosure, a map data processing device is provided. The device includes: an acquisition unit for acquiring original map data to be processed, wherein the original map data is in units of a map sheet having a first level of refinement for representing a target area; a conversion unit for converting the original map data into target map data, wherein the target map data is in units of a second level of refinement for representing the target area, the second level of refinement being higher than the first level of refinement; and an allocation unit for performing allocation processing on the target map data to obtain an allocation result.

[0006] According to another aspect of the present disclosure, an electronic device is provided. The electronic device may include: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the map data processing method of an embodiment of the present disclosure.

[0007] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is further provided, wherein the computer instructions are used to enable a computer to execute the map data processing method of an embodiment of the present disclosure.

[0008] According to another aspect of the present disclosure, a computer program product is further provided, which may include a computer program. When the computer program is executed by a processor, it implements the map data processing method of the embodiment of the present disclosure.

[0009] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0011] Figure 1 is a flowchart of a method for processing map data according to an embodiment of the present disclosure;

[0012] Figure 2 is a schematic diagram of data processing according to the relevant technology of the present disclosure;

[0013] Figure 3 is a schematic diagram of data processing according to an embodiment of the present disclosure;

[0014] Figure 4 is a flow chart of a data processing method according to an embodiment of the present disclosure;

[0015] Figure 5 is a schematic diagram of a map data processing device according to an embodiment of the present disclosure;

[0016] Figure 6 The present invention is a block diagram of an electronic device that implements a method for processing map data according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0017] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0018] Figure 1 FIG. 1 is a flow chart of a method for processing map data according to an embodiment of the present disclosure. Figure 1 As shown, the method may include the following steps:

[0019] Step S102 : obtaining original map data to be processed, wherein the unit of the original map data is a map sheet of a first refinement level for representing a target area.

[0020] In the technical solution provided in the above step S102 of the present disclosure, the original map data to be processed can be obtained from the database, wherein the unit of the original map data is a map sheet of a first degree of refinement for representing the target area, which can be a data package with map sheets as units, and the first degree of refinement can refer to the granularity of the map.

[0021] Step S104 : converting the original map data into target map data, wherein the unit of the target map data is used to represent a second refinement level of the target area, and the second refinement level is higher than the first refinement level.

[0022] In the technical solution provided in the above step S104 of the present disclosure, the geometric information (e.g., points, lines, surfaces, and volumes) and related attributes (e.g., traffic lights, speed limit signs, whether the vehicle is on a highway or a regular road) corresponding to the original map data can be analyzed and processed to convert the original map data in units of map sheets into more refined target map data. The target map data can be mark-level data, and the unit of the target map data (e.g., map sheet) is used to represent a second degree of refinement of the target area. The second degree of refinement can refer to the granularity of the map, which can be reduced to the granularity of points, lines, surfaces, and volumes.

[0023] Optionally, the original map data is obtained, and by analyzing the geometric information of the marked points, lines, surfaces, bodies, and related attributes such as traffic lights, speed limit signs, whether the road is on a highway or a regular road, information such as the difficulty, priority, map sheet, and overlapping relationship of the marking is calculated and saved in a database to convert the original map data of the first level of refinement into target map data of the second level of refinement, wherein the second level of refinement is higher than the first level of refinement.

[0024] Optionally, the marking information can be calculated based on the corresponding geometric information and / or attribute information of the original map data to reduce the first refinement level (granularity) of the points, lines, surfaces, volumes, etc. of the original map data to obtain target map data of a second refinement level.

[0025] Step S106: performing allocation processing on the target map data to obtain an allocation result.

[0026] In the technical solution provided in step S106 of the present disclosure, the original map data of the first refinement level is converted into target map data of the second refinement level, and allocation processing can be performed according to conditions such as priority and difficulty of the target map data to obtain an allocation result.

[0027] Through steps S102 to S106, the original map data to be processed is obtained, wherein the units of the original map data are map sheets of a first level of refinement used to represent the target area; the original map data is converted into target map data, wherein the units of the target map data are used to represent the target area of ​​a second level of refinement, and the second level of refinement is higher than the first level of refinement; and the target map data is allocated and processed to obtain an allocation result. In other words, the present disclosure processes the original map data to reduce the original map data of the first level of refinement to the target map data of the second level of refinement. By reducing the granularity of the map data, the concurrent production capacity of data operations is improved, the efficient processing of map data is achieved, and the technical effect of improving operation processing efficiency is achieved, thereby solving the technical problem of low operation processing efficiency.

[0028] The above method of this embodiment is further described in detail below.

[0029] As an optional implementation manner, the map sheet includes multiple units of the target map data.

[0030] In this embodiment, the map sheet includes a plurality of units of the target map data, wherein a unit may be a mark in the map sheet.

[0031] Optionally, a map sheet includes multiple tags, and the map sheet is further refined into tags to achieve a technical effect of reducing the size of map data.

[0032] As an optional implementation, step S104, converting the original map data into target map data, includes: converting the original map data into target information of a unit of the target map data, wherein the target information is used to describe the unit of the target map data.

[0033] In this embodiment, original map data is acquired and analyzed to convert the original map data into target information of target map data units, wherein the target information is used to describe the units of the target map data and can be a granularity of point, line, surface, volume, etc.

[0034] This embodiment achieves the technical effect of converting original map data into target map data by converting original map data into target information of a unit of target map data.

[0035] As an optional implementation, converting the original map data into target information of the unit of the target map data includes: based on the type information of the original map data, converting geometric data of the target dimension in the original map data to obtain the target information of the unit of the target map data.

[0036] In this embodiment, the acquired original map information has corresponding type information. Different types of original map information are processed in different ways. Based on the type information of the original map data, the geometric data of the target dimension of the type information of the original map data is converted to obtain the target information of the unit of the target map data. The type information can be information obtained after the map is merged and classified according to certain characteristics and indicators of the map. According to the scale, it can be divided into large-scale maps, medium-scale maps and small-scale maps. According to the content of the map, it can be divided into ordinary maps and thematic maps (for example, natural terrain maps, cultural maps, etc.). According to the purpose, it can be divided into general maps and special maps (for example, aviation maps, traffic maps, tourist maps, etc.); according to the form of the map, it can be divided into single maps, series maps, atlases, etc.; the geometric data can include a point, a line, a surface or a body; the unit of the target map data can be a marked point in the target map data.

[0037] Optionally, based on the type information of the original map data, the geometric data of the target dimension in the original map data is converted to obtain target information of the units of the target map data, wherein the target information may be association information and attribute information between units in the target map data (for example, traffic lights, speed limit signs, whether on a highway or on an ordinary road, etc.).

[0038] This embodiment converts the geometric data of the target dimension in the original map data based on the type information of the original map data to obtain the target information of the unit of the target map data, thereby achieving the technical effect of converting the original map data into the target information of the unit of the target map data.

[0039] As an optional implementation, based on the type information of the original map data, the geometric data of the target dimension in the original map data is converted to obtain the target information of the unit of the target map data, including: expanding the geometric data of the target dimension according to the expansion size corresponding to the type information; and determining the association information between multiple units of the target map data based on the expanded geometric data, wherein the target information includes the association information.

[0040] In this embodiment, since the size of the expansion circle is related to the type information, the type information of the original map data is determined, and the geometric data of the target dimension is expanded according to the expansion circle size corresponding to the type information. The data that needs to be expanded for different types of map data can be set according to actual conditions. For example, it can be expanded from 10 meters to 50 meters.

[0041] Optionally, based on the expanded geometric data, association information between multiple units of the target map data is determined, wherein the association information may be an overlapping relationship between the multiple units.

[0042] For example, according to the type information of the original map data, the geometric data in the original map data is converted (the corresponding geometric data is expanded). For example, the points, lines, surfaces or bodies in the original map data can be expanded by 10 meters to 50 meters. A point will be expanded into a circle, a line will be expanded into a strip, and a surface will have its area expanded by one circle. When two traffic lights are at the same intersection, the expansion process can determine that the two traffic lights are overlapping.

[0043] This embodiment achieves the technical effect of determining the overlapping relationship between multiple units of the target map data by performing circle expansion processing on the geometric data of the target dimension.

[0044] As an optional implementation manner, converting the original map data into target information of units of target map data includes: determining attribute information of units of target map data in the original map data, wherein the target information includes attribute information.

[0045] In this embodiment, original map data is obtained, and attribute information of a unit of target map data is determined in the original map data, wherein the attribute information may be a classification of the unit of the target map data, for example, a traffic light, a speed limit sign, a highway, an ordinary road, etc.

[0046] Optionally, the relevant attributes of the marker are obtained for the classification of units in the map data. The attribute information of the units of the target map data can be determined in the original map data, and the difficulty, priority, map sheet, and overlapping relationship of the units of the target map data can be calculated based on the geometric information and / or attribute information. For example, the difficulty of the units of the target map data can be calculated based on the geometric complexity of the units in the original map data; the difficulty of the units of the target map data can also be calculated based on the attribute information. For example, ordinary roads can be of medium difficulty, and some speed limit signs on highways can be of easy difficulty.

[0047] Optionally, the original map data is obtained, and by analyzing the geometric information of the units in the original map data, such as points, lines, surfaces, and bodies, and the attribute information such as traffic lights, speed limit signs, whether the unit is on a highway or on an ordinary road in the original map data, the difficulty, priority, map sheet location, and overlapping relationship of the unit are calculated, thereby achieving the technical effect of converting the original map data into the target information of the unit of the target map data.

[0048] As an optional implementation manner, target information of each unit of the target map data is saved in the first database.

[0049] In this embodiment, the original map data is obtained, and the geometric information of the units in the original map data and the attribute information of the units in the original map data are analyzed to calculate the target information such as the difficulty, priority, map sheet and overlapping relationship of the units. The target information of the units in the target map data is saved in a first database, where the first database can be a cloud database (tableStorage) or other database management system (NoSQL) that is different from a traditional relational database, and can also be called a database (table).

[0050] Optionally, this embodiment can use an inverted index search engine (Elastic Search, abbreviated as ES) to save the target information of the unit of the target map data, and can quickly update, query and count the target information through various attributes (such as operation status, difficulty, associated plan, whether it can be automatically operated, return information, etc.).

[0051] Optionally, the target information of units of different target map data is not unified. For example, a point unit has a guide point to indicate the direction of the point, but a line unit or a surface unit does not have such a guide point.

[0052] This embodiment achieves the technical effect of independently storing the units in the target map data by storing the target information of the units in the target map data in the first database respectively.

[0053] As an optional implementation, the first database is a non-relational database.

[0054] In this embodiment, since the units in the target map data have many attributes, the relational database is not suitable for storing the units in the target map and will take up more space. Therefore, a non-relational database can be used, for example, a database of a database management system that is different from a traditional relational database (NoSQL database).

[0055] This embodiment achieves the technical effect of saving storage space by using a non-relational database to store map data.

[0056] As an optional implementation manner, the target information of the unit of the allocated target map data is stored from the first database to the second database.

[0057] In this embodiment, target information of units of target map data can be retrieved from the database, the target information of the units of target map data can be allocated and processed, the target information of the units of target map data after allocation and processing can be restored, and the units of target map data can be archived from the first database to the second database, wherein the second database can be a backup database, a cloud database, or other database of a database management system different from a traditional relational database.

[0058] This embodiment restores the target information of the units of the processed target map data and stores the target information of the units of the target map data from the first database to the second database, thereby achieving the technical effect of reducing the storage pressure of the first database.

[0059] As an optional implementation, the target map data is allocated and processed to obtain an allocation result including: determining first sub-target information that matches the skill level of the target object in the target information of the unit of the target map data; and allocating the first sub-target information to the target object.

[0060] In this embodiment, the target map data is allocated and processed based on the target information of the unit of the target map data, and the first sub-target information that matches the skill level of the target object is determined, and the first sub-target information is allocated to the target object to obtain an allocation result of the target object, wherein the target object can be an operator, a collector, etc.; the first sub-target information can be queried from the first database, and the target information of the unit in the target map data selected according to the skill level of the target object can be a job package.

[0061] Optionally, based on the skill level of the target object, target information with matching difficulty is queried from the first database. Based on timeliness, high-priority units can be prioritized, and then based on the overlapping relationship, units that are overlapped by the data in operation are filtered out to determine the first sub-target information (job package), and the job package can be sent to the target object.

[0062] Optionally, based on the skill level of the target object, target information with matching difficulty is retrieved from the first database, and then based on timeliness, high-priority target information is prioritized, and then based on the overlapping relationship, target information that is overlapped by the data in progress is filtered out to obtain the second sub-target information, and the second sub-target information is assigned to the target object.

[0063] Optionally, when target information is rejected due to difficulty, photo overlap, incomplete data, edge connection, etc., the rejected target information can be subsequently processed according to the actual situation. For example, if it is rejected due to difficulty, the difficulty value will be automatically increased and the next time it will be assigned to a higher-level operator; if it is rejected due to photo overlap, the collection personnel will be notified to re-collect; when the target information needs to be revoked for various reasons, the status of the target information and the bound plan and other information can be modified according to the plan.

[0064] This embodiment matches the skill level of the target object with the difficulty of the target information, thereby achieving the technical effect of improving the utilization efficiency of production capacity.

[0065] As an optional implementation, the target map data is allocated and processed to obtain an allocation result, including: filtering the target information based on at least one of the following information in the target information of the unit of the target map data to obtain second sub-target information: timeliness information of the unit of the target map data, priority of the unit of the target map data, and association information between multiple units of the target map data; and allocating the second sub-target information to the target object.

[0066] In this embodiment, the target information is filtered based on the timeliness information of the unit of the target map data, the priority of the unit of the target map data, and the association information between multiple units of the target map data to obtain the second sub-target information, and the second sub-target information is assigned to the target object to determine the assignment result.

[0067] This embodiment schedules and allocates according to the timeliness of target information. High-priority target information can be sent first, thereby ensuring the timeliness of map data. By implementing the associated sending of associated target information and paired target information, target information overlap is reduced, thereby achieving the technical effect of improving data timeliness and service quality.

[0068] In this embodiment, raw map data to be processed is obtained, wherein the raw map data is in units of a first level of refinement representing a target area; the raw map data is converted into target map data, wherein the target map data is in units of a second level of refinement representing the target area, the second level of refinement being higher than the first level of refinement; and the target map data is allocated to obtain an allocation result. In other words, the present disclosure processes the raw map data, reducing the raw map data of the first level of refinement to target map data of the second level of refinement. By reducing the granularity of the map data, the concurrent production capacity of data operations is improved, the efficient processing of map data is achieved, and the technical effect of improving operation processing efficiency is achieved, thereby resolving the technical problem of low operation processing efficiency.

[0069] The above technical solutions of the embodiments of the present disclosure are further introduced below with reference to preferred embodiments.

[0070] Figure 2 is a schematic diagram of data processing according to the relevant technology of this disclosure, such as Figure 2 As shown, the early map update job receives a request, splits the data, and only saves it in the cloud database and relational database. The data is distributed by reading the data in the relational database. In related technologies, data is stored, split, distributed and operated in units of map sheets. However, the above technology has the following problems: the smallest unit of data is the map sheet, and one data contains multiple marks. The data storage and distribution are not flexible, and there is a problem of large data granularity; the data granularity is too large, and the overlap caused by a small part of the mark will lead to the overlap of the entire data package, which will lead to the inability to operate concurrently on a large scale, affecting the timeliness of the update; the actual operation difficulty of some marks will be less than the difficulty of the data package, but because the minimum allocation The granularity is the data package, which will cause these marks to be assigned to highly skilled operators, resulting in the problem that the data difficulty cannot effectively match the operator's skills, affecting the operator configuration; the marks saved in the data package are difficult to query information and track status, and cannot achieve fine scheduling control, and there is a problem of not being able to effectively track and update information; when the data cannot be operated and is returned, the returned data needs to be unpacked and repacked according to the return status and map size, resulting in the problem of data re-entering the database, complex processes and low efficiency; because the marks are saved in the data package, duplicate deduplication cannot be performed when entering the database, and the marks will be repeatedly entered into the database, resulting in the problem of repeated operations on the same data.

[0071] Therefore, in view of the problem that data granularity is large, easy to interfere with each other, and difficult to perform large-scale concurrent operations, some highly time-sensitive data cannot be distributed in time, which seriously affects the operation efficiency and timeliness of data. The embodiment of the present disclosure unpacks, groups and counts the pre-processed collected data according to information such as the map where the data is located, saves it to the database, and then allocates operations according to the priority and difficulty of the data. Data allocation is a data package based on the map, which contains multiple units. By reducing the granularity of the operation data, the information of point data or survey line data is independently saved, wherein point data and survey line data can be represented by marks. Using point data and survey line data for allocation and operation can improve the parallelism of operations, give priority to the distribution of highly time-sensitive data, and track the status of point data and survey line data in real time.

[0072] Due to the large granularity of data, a series of problems arise when using data packages for storage, circulation and operation. To solve these problems, it is necessary to reduce the granularity of the data. According to the type of operation data, the data can be reduced to the granularity of points, lines, surfaces and solids, that is, the mark level, which can solve these problems. To achieve this goal, it is necessary to transform the warehousing, analysis, storage and circulation.

[0073] Figure 3 is a schematic diagram of data processing according to an embodiment of the present disclosure, such as Figure 3 As shown, in this embodiment, a request is received, the received data is analyzed through the geometry and related attributes of the mark, and information such as the difficulty, priority, map sheet and overlapping relationship of the mark is calculated and saved in the database.

[0074] In this embodiment, since the mark has many attributes, there is a problem of space occupation when using a relational database to store it. The attributes of different marks are not unified. For example, a point mark has a guide point to indicate which direction the point is facing, like a traffic light, but a line mark does not have one. There are some attributes that cannot be expressed in a unified data structure. Moreover, with the development of the business, the attributes are constantly developing and changing. Due to the above problems, a relational database is not suitable for saving marks. Therefore, a cloud database (tableStorage) or other database management system that is different from a traditional relational database can be used for saving, that is, a database, referred to as a table. At the same time, a search engine that supports inverted indexing (Elastic Search, referred to as ES) is used to save the basic key information and overlapping relationship information of the mark. It can quickly update, query and count data through attributes such as job status, difficulty, associated plan, whether it can be automatically operated, and return information, thereby obtaining changes in the data entry process.

[0075] Optionally, the received data contains corresponding geometric information, which is written to the database. This information is typically a point, line, surface, or volume. When analyzing the data's geometric information, the corresponding geometry is expanded to better calculate the overlap relationship of marks. For example, if two traffic lights are at the same intersection, expansion can be used to determine whether they overlap. The size of the expansion depends on the data type, typically 10 to 50 meters. A point is expanded into a circle, a line into a strip, and a surface is expanded. Volumes are calculated using projection, and the expansion is similar to that of surfaces because it is used to calculate the overlap relationship of marks.

[0076] Optionally, the relevant attributes generally refer to the classification of the mark, such as a traffic light, a speed limit sign, whether it is on a highway or on a regular road, etc.

[0077] Optionally, the difficulty of a mark is generally calculated by the geometric complexity of the mark, and can be calculated by classification. For example, an intersection on an ordinary road is of medium difficulty, while some speed limit signs on a highway are easy. No specific limitation is made here.

[0078] In this embodiment, marks with matching difficulty can be queried from the database based on the operator's skill level, and high-priority marks can be selected first based on timeliness. Then, based on the overlapping relationship, marks that are overlapped by the data in progress are filtered out, and the selected marks are combined into a job package and sent to the operator.

[0079] Optionally, the data completed by the operator is returned to the database, and the relevant status in the search engine database is directly modified according to the mark. At the same time, the mark details are archived from the database to the backup database to reduce the pressure on the main database. The backup database can be a database of a database management system such as a cloud database that is different from a traditional relational database.

[0080] Optionally, due to incomplete data, data errors and other issues, the data assigned to the operator may not be able to be operated. The operator can return the data according to the specific situation. The data return includes difficulty return, photo overprint return, incomplete data return, unconditional return, edge return, etc. The returned data can be processed later according to the actual situation. For example, if it is a difficulty return, the difficulty value will be automatically increased and the operator will be assigned to a higher level operator next time; if it is a photo overprint return, the collection personnel will be notified to re-collect.

[0081] Optionally, when an assigned job needs to be canceled for various reasons, the status of the mark and the bound plan information can be modified according to the plan.

[0082] The following is a further introduction to the process of the embodiment of the present disclosure. Figure 4 is a flow chart of a data processing method according to an embodiment of the present disclosure, such as Figure 4 As shown, the following steps may be included.

[0083] Step S402: Create a plan and bind the data to the plan number.

[0084] In this embodiment, a map update plan is created, and the data is bound to the plan number through the data allocation interface.

[0085] Optionally, data can be allocated during the plan binding process. The database system queries the allocable data through relevant conditions and binds it to the plan, that is, setting the mark plan field in ES to the plan number and changing the mark status to allocating.

[0086] In step S404, the database obtains the bound data through the plan number, processes the data to obtain a data package, and provides the data package to the plan number.

[0087] In this embodiment, the database obtains the bound data through the plan number, and performs operations, quality inspections, and other tasks on the obtained data within the plan.

[0088] Optionally, after the data is allocated, in the data preparation phase, the database uses the plan number to find the bound mark, and then queries the mark details from the table to form a job file (package), which is provided to the plan. The package file is used within the plan for flow operations.

[0089] Step S406: Submit or cancel the processed plan.

[0090] In this embodiment, the plan is submitted through the data handover interface; the plan is revoked through the data revocation interface.

[0091] Step S408: Obtain unoperated map sheets and process the unoperated map sheets.

[0092] Due to incomplete or erroneous data, some of the data assigned to operators cannot be operated, such as difficulty rejection, photo overlap rejection, incomplete data rejection, unconditional rejection, edge connection rejection, etc. The operators obtain the maps that need to be operated due to the above reasons, and perform subsequent processing on the unoperated maps through other query interfaces according to the actual situation.

[0093] This embodiment reduces the data to the granularity of points, lines, surfaces and solids according to the type of operation data, that is, the mark level, for storage, circulation and operation. With a smaller scheduling effort, the concurrent production capacity of data operations is greatly improved, and the production efficiency of map data is effectively improved; through accurate scheduling of data, the skill level of the operator can be matched with the difficulty of the data, so that the production capacity is maximized; by utilizing the timeliness of mark data for scheduling and allocation, high-priority data can be sent down first, ensuring the timeliness of map data; related data and paired data are sent down in association to reduce data overlap, thereby improving data timeliness and business quality; at the same time, data returned due to quality issues are collected, and the upstream is notified to re-collect, thereby preserving the map quality, and by using a search engine that supports inverted indexing, easy query and statistical data information can be achieved, and current inventory information and real-time status of data can be mastered at any time, thereby achieving refined control.

[0094] The disclosed embodiment reduces the data to the granularity of points, lines, surfaces and solids, that is, the mark level, according to the type of operation data, and performs storage, circulation and operation. The data is analyzed based on the geometry and related attributes of the mark to determine the difficulty, priority, map location and overlapping relationship of the mark, and the mark is allocated according to the skill level of the operator, thereby achieving the technical effect of improving the operation processing efficiency and solving the technical problem of low operation processing efficiency.

[0095] The present disclosure also provides a method for executing Figure 1The map data processing method and map data processing device of the embodiment are shown.

[0096] Figure 5 is a schematic diagram of a map data processing device according to an embodiment of the present disclosure, such as Figure 5 As shown, the data processing device 30 may include: an acquisition unit 51 , a conversion unit 52 and an allocation unit 53 .

[0097] The acquisition unit 51 is configured to acquire original map data to be processed, wherein the unit of the original map data is a map sheet of a first refinement level for representing a target area.

[0098] The conversion unit 52 is configured to convert the original map data into target map data, wherein the unit of the target map data is used to represent a second refinement level of the target area, and the second refinement level is higher than the first refinement level.

[0099] The allocation unit 53 is used to perform allocation processing on the target map data to obtain an allocation result.

[0100] Optionally, the device further comprises: a map sheet including multiple units of target map data

[0101] Optionally, the conversion unit 52 includes a conversion module for converting the original map data into target information of a unit of the target map data, wherein the target information is used to describe the unit of the target map data.

[0102] Optionally, the conversion module includes a conversion submodule for converting the geometric data of the target dimension in the original map data based on the type information of the original map data to obtain the target information of the unit of the target map data.

[0103] Optionally, the conversion submodule converts the geometric data of the target dimension in the original map data based on the type information of the original map data to obtain target information of the units of the target map data through the following steps, including: expanding the geometric data of the target dimension according to the expansion size corresponding to the type information; and determining association information between multiple units of the target map data based on the expanded geometric data, wherein the target information includes the association information.

[0104] Optionally, the conversion submodule converts the original map data into target information of a unit of target map data by the following steps, including: determining attribute information of a unit of target map data in the original map data, wherein the target information includes attribute information.

[0105] Optionally, the device further includes: saving target information of units of the target map data into the first database respectively.

[0106] Optionally, the device further includes: the first database is a non-relational database.

[0107] Optionally, the conversion submodule further includes: storing the target information of the unit of the allocated target map data from the first database to the second database.

[0108] Optionally, the allocating unit 53 includes: a determining module for determining first sub-target information matching the skill level of the target object in the target information of the unit of the target map data; and allocating the first sub-target information to the target object.

[0109] Optionally, the determination module includes: a filtering submodule, used to filter the target information based on at least one of the following information in the target information of the unit of the target map data to obtain second sub-target information: timeliness information of the unit of the target map data, priority of the unit of the target map data, and association information between multiple units of the target map data; and assign the second sub-target information to the target object.

[0110] In the device of the disclosed embodiment, an acquisition unit acquires original map data to be processed, wherein the units of the original map data are map sheets of a first degree of refinement used to represent a target area; a conversion unit converts the original map data into target map data, wherein the units of the target map data are used to represent a second degree of refinement of the target area, and the second degree of refinement is higher than the first degree of refinement; and an allocation unit performs allocation processing on the target map data to obtain an allocation result, thereby achieving the technical effect of improving job processing efficiency and solving the technical problem of low job processing efficiency.

[0111] In the technical solutions disclosed herein, the acquisition, storage, and application of user personal information involved comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0112] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0113] An embodiment of the present disclosure provides an electronic device, which may include: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the map data processing method of the embodiment of the present disclosure.

[0114] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0115] According to an embodiment of the present disclosure, the present disclosure further provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the map data processing method of the embodiment of the present disclosure.

[0116] Optionally, in this embodiment, the non-volatile storage medium may be configured to store a computer program for executing the following steps:

[0117] S1, obtaining original map data to be processed, wherein the unit of the original map data is a map sheet of a first refinement level for representing a target area;

[0118] S2, converting the original map data into target map data, wherein a unit of the target map data is used to represent a second refinement level of the target area, and the second refinement level is higher than the first refinement level;

[0119] S3, performing allocation processing on the target map data to obtain an allocation result.

[0120] Alternatively, in this embodiment, the non-transitory computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any suitable combination of the above. More specific examples of readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0121] According to an embodiment of the present disclosure, the present disclosure further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0122] S1, obtaining original map data to be processed, wherein the unit of the original map data is a map sheet of a first refinement level for representing a target area;

[0123] S2, converting the original map data into target map data, wherein a unit of the target map data is used to represent a second refinement level of the target area, and the second refinement level is higher than the first refinement level;

[0124] S3, performing allocation processing on the target map data to obtain an allocation result.

[0125] Figure 6This is a block diagram of an electronic device that implements a method for processing map data according to an embodiment of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as laptops, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are provided for example only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0126] like Figure 6 As shown, the device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the device 600 can also be stored in the RAM 603. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0127] Various components in device 600 are connected to I / O interface 605, including an input unit 606, such as a keyboard, mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a magnetic disk, optical disk, etc.; and a communication unit 609, such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows device 600 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0128] The computing unit 601 can be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 601 performs the various methods and processes described above, such as the method data processing method. For example, in some embodiments, the method data processing method can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as a storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the data processing method described above can be performed. Alternatively, in other embodiments, the computing unit 601 can be configured to perform the data processing method in any other appropriate manner (e.g., by means of firmware).

[0129] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0130] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0131] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0132] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0133] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0134] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0135] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not a limitation herein.

[0136] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A method for processing map data, comprising: Acquire original map data to be processed, wherein the unit of the original map data is a map sheet of a first refinement level for representing a target area; converting the original map data into target map data, wherein a unit of the target map data is used to represent a second level of refinement of the target area, and the second level of refinement is higher than the first level of refinement; performing allocation processing on the target map data to obtain an allocation result; The converting of the original map data into target map data includes converting the original map data into target information of units of the target map data, wherein the target information is used to describe the units of the target map data and includes association information between multiple units of the target map data and attribute information of the units of the target map data, wherein the association information is used to indicate overlapping relationships between the multiple units, and the attribute information is used to indicate classification of the units of the target map data.

2. The method according to claim 1, wherein The map sheet includes a plurality of units of the target map data.

3. The method according to claim 1, wherein The target information of the unit for converting the original map data into the target map data includes: Based on the type information of the original map data, the geometric data of the target dimension in the original map data is converted to obtain the target information of the unit of the target map data.

4. The method according to claim 3, wherein: Converting the geometric data of the target dimension in the original map data based on the type information of the original map data to obtain the target information of the unit of the target map data includes: Performing circle expansion processing on the geometric data of the target dimension according to the circle expansion size corresponding to the type information; Based on the expanded geometric data, association information between multiple units of the target map data is determined, wherein the target information includes the association information.

5. The method according to claim 1, wherein The target information of the unit for converting the original map data into the target map data includes: In the original map data, attribute information of a unit of the target map data is determined, wherein the target information includes the attribute information.

6. The method according to claim 1, wherein The method further comprises: The target information of each unit of the target map data is stored in the first database.

7. The method according to claim 6, wherein: The first database is a non-relational database.

8. The method according to claim 6, further comprising: The target information of the units of the target map data to which the allocation has been completed is stored from the first database to the second database.

9. The method according to claim 1, wherein The target map data is allocated and processed to obtain allocation results including: Determining, in the target information of the unit of the target map data, first sub-target information that matches the skill level of the target object; The first sub-target information is assigned to the target object.

10. The method according to claim 1, wherein The target map data is allocated and processed to obtain allocation results including: Filtering the target information based on at least one of the following information in the target information of the unit of the target map data to obtain second sub-target information: timeliness information of the unit of the target map data, priority of the unit of the target map data, and association information between multiple units of the target map data; The second sub-target information is assigned to the target object.

11. A map data processing device, comprising: an acquisition unit, configured to acquire original map data to be processed, wherein the unit of the original map data is a map sheet of a first refinement level for representing a target area; a conversion unit, configured to convert the original map data into target map data, wherein a unit of the target map data is used to represent a second refinement level of the target area, and the second refinement level is higher than the first refinement level; an allocation unit, configured to perform allocation processing on the target map data to obtain an allocation result; The conversion unit is configured to convert the original map data into target map data by performing the following steps: converting the original map data into target information of units of the target map data, wherein the target information is used to describe the units of the target map data and includes association information between multiple units of the target map data and attribute information of the units of the target map data, the association information is used to indicate overlapping relationships between the multiple units, and the attribute information is used to indicate classification of the units of the target map data.

12. An electronic device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 10.

13. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-10.

14. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 10.

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