CN112257207B - Road network boundary determining method and device, electronic equipment and storage medium - Google Patents
Road network boundary determining method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention provides a road network boundary determining method, a road network boundary determining device, electronic equipment and a storage medium, and relates to the field of geographic information management of traffic technology. The method comprises the following steps: preprocessing OSM data of a target area according to telecommunication signaling data of a user to acquire travel road network information; according to the travel road network information, acquiring a plurality of road network nodes of a target point within a distance threshold; the road network node is the actual intersection point of any two adjacent roads in the target area; performing exhaustive search on a plurality of road network nodes in a threshold region to obtain a region boundary meeting a preset condition; the threshold region is a region within a distance threshold from the target point, the target point being within a region bounded by a region boundary. The method can determine the regional boundary of the target point according to the OSM data, does not need manual measurement, and corrects and perfects geographic information.
Description
Technical Field
The invention relates to the field of geographic information management of traffic technology, in particular to a road network boundary determining method, a road network boundary determining device, electronic equipment and a storage medium.
Background
In order to manage geographic information, map companies acquire Area of Interest (AOI) data of buildings by performing drive tests manually or remotely sensing data through satellites.
However, the acquisition of AOI data is difficult, and the AOI boundary data is missing from the partial region boundary. Therefore, how to cut Open Street Map (OSM) road network data to obtain an AOI range of any building and obtain boundary data of the AOI data is a problem to be solved.
Disclosure of Invention
The object of the present invention includes, for example, providing a road network boundary determining method, apparatus, electronic device and storage medium, which can determine the regional boundary of a target point according to OSM data, and do not need manual measurement, and correct and perfect geographic information.
Embodiments of the invention may be implemented as follows:
in a first aspect, an embodiment of the present invention provides a road network boundary determining method, where the method includes:
preprocessing OSM data of a target area according to telecommunication signaling data of a user to acquire travel road network information;
the telecommunication signaling data represents travel track information of the user in the target area, and the travel network information represents actual road information passed by the user in the target area and actual intersection point information of each road;
acquiring a plurality of road network nodes of a target point within a distance threshold according to the travel road network information; the road network node is an actual intersection point of any two adjacent roads in the target area;
performing exhaustive search on the road network nodes in a threshold region to obtain a region boundary meeting a preset condition; the threshold area is an area within the distance threshold from the target point, and the target point is within an area enclosed by the area boundary.
In an optional embodiment, the obtaining the information of the travel network by preprocessing OSM data of the target area according to telecommunication signaling data of the user includes:
preprocessing the OSM data to obtain route data and point data; the route data represents the sampled road information in the target area, and the point location data represents the sampled intersection point information of each road in the target area;
matching the telecommunication signaling data with the route data to obtain travel route information; the travel route information represents actual road information in the target area;
matching the telecommunication signaling data with the point location data to obtain trip point location information; the trip point location information represents actual intersection point information of each road in the target area;
and combining the travel route information and the travel point location information to obtain the travel road network information.
In an optional embodiment, performing an exhaustive search on the plurality of road network nodes in a threshold region to obtain a region boundary meeting a preset condition includes:
determining a road network node closest to the target point in the plurality of road network nodes as a closed loop starting point;
gradually diverging in the threshold region by taking the closed loop starting point as a search starting point to obtain a plurality of region points; the last area point in the plurality of area points is the starting point of the closed loop;
judging whether the target point is in a closed loop formed by the closed loop starting point and the plurality of area points;
and if so, determining that a closed loop formed by the closed loop starting point and the plurality of area points is the area boundary of the target point.
In an optional embodiment, taking the closed-loop starting point as a search starting point, performing gradual divergence in the threshold region to obtain a plurality of region points, includes:
taking the closed loop starting point as a search starting point to perform divergence in the threshold value area to obtain a first area point closest to the closed loop starting point;
taking the first region point as a search starting point to perform divergence in the threshold region to obtain a second region point which is closest to the first region point except the closed loop starting point;
taking the second region point as a search starting point to perform divergence in the threshold region to obtain a third region point closest to the second region point;
and if the third area point is the closed loop starting point, stopping area point search.
In an optional embodiment, determining that a closed loop formed by the closed loop starting point and the plurality of area points is an area boundary of the target point includes:
if the closed loop starting point and the plurality of area points enclose a plurality of closed loops, estimating the map area of the building area where the target point is located according to OSM data;
determining the area of the area corresponding to each closed loop according to the travel network information;
comparing each area of the region with the area of the map to obtain a plurality of confidence coefficients;
determining a target confidence coefficient which is the smallest difference from an alignment threshold value in the confidence coefficients;
and taking the closed loop corresponding to the target confidence as the region boundary.
In a second aspect, an embodiment of the present invention provides a road network boundary determining apparatus, where the apparatus includes:
the acquisition module is used for preprocessing OSM data of a target area according to telecommunication signaling data of a user and acquiring the information of the travel road network;
the telecommunication signaling data represents travel track information of the user in the target area, and the travel network information represents actual road information passed by the user in the target area and actual intersection point information of each road;
the processing module is used for acquiring a plurality of road network nodes of a target point within a distance threshold according to the travel road network information; the road network node is an actual intersection point of any two adjacent roads in the target area;
the processing module is further used for carrying out exhaustive search on the road network nodes in a threshold region to obtain a region boundary meeting a preset condition; the threshold area is an area within the distance threshold from the target point, and the target point is within an area enclosed by the area boundary.
In an optional embodiment, the obtaining module is further configured to preprocess the OSM data to obtain route data and point data; the route data represents the sampled road information in the target area, and the point location data represents the sampled intersection point information of each road in the target area;
the acquisition module is further used for matching the telecommunication signaling data with the route data to obtain travel route information; the travel route information represents actual road information in the target area;
the acquisition module is further configured to match the telecommunication signaling data with the point location data to obtain trip point location information; the trip point location information represents actual intersection point information of each road in the target area;
the obtaining module is further configured to combine the travel route information and the travel point location information to obtain the travel network information.
In an optional embodiment, the processing module is further configured to determine a road network node closest to the target point among the plurality of road network nodes as a closed-loop starting point;
the processing module is further configured to perform gradual divergence in the threshold region with the closed-loop starting point as a search starting point to obtain a plurality of region points; the last area point in the plurality of area points is the starting point of the closed loop;
the processing module is further configured to determine whether the target point is located in a closed loop defined by the closed loop starting point and the plurality of area points;
the processing module is further configured to determine that a closed loop defined by the closed-loop starting point and the plurality of area points is an area boundary of the target point if the target point is located in the closed loop defined by the closed-loop starting point and the plurality of area points.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a processor and a memory, where the memory stores a computer program that can be executed by the processor, and the processor can execute the computer program to implement the method described in any one of the foregoing embodiments.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the method described in any one of the foregoing embodiments.
Compared with the prior art, the invention provides a road network boundary determining method, a road network boundary determining device, electronic equipment and a storage medium, and relates to the field of geographic information management of traffic technology. The method comprises the following steps: preprocessing OSM data of a target area according to telecommunication signaling data of a user to acquire travel road network information; the telecommunication signaling data represents travel track information of the user in the target area, and the travel network information represents actual road information passed by the user in the target area and actual intersection point information of each road; acquiring a plurality of road network nodes of a target point within a distance threshold according to the travel road network information; the road network node is an actual intersection point of any two adjacent roads in the target area; performing exhaustive search on the road network nodes in a threshold region to obtain a region boundary meeting a preset condition; the threshold area is an area within the distance threshold from the target point, and the target point is within an area enclosed by the area boundary. The method can determine the regional boundary of the target point according to the OSM data, does not need manual measurement, and corrects and perfects geographic information.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic block diagram of an electronic device according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a road network boundary determining method according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of another road network determining method according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a road network according to an embodiment of the present invention;
fig. 5 is a schematic flow chart of another road network determining method according to an embodiment of the present invention;
fig. 6 is a schematic flow chart of another road network determining method according to an embodiment of the present invention;
fig. 7 is a schematic diagram of a road network determining method according to an embodiment of the present application;
fig. 8 is a schematic diagram of another road network determining method according to an embodiment of the present application;
fig. 9 is a schematic flow chart of another road network determining method according to an embodiment of the present invention;
fig. 10 is a schematic diagram of another road network determining method according to an embodiment of the present application;
fig. 11 is a schematic block diagram of a road network boundary determining apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it should be noted that if the terms "upper", "lower", "inside", "outside", etc. indicate an orientation or a positional relationship based on that shown in the drawings or that the product of the present invention is used as it is, this is only for convenience of description and simplification of the description, and it does not indicate or imply that the device or the element referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention. Furthermore, the appearances of the terms "first," "second," and the like, if any, are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance. It should be noted that the features of the embodiments of the present invention may be combined with each other without conflict.
In order to manage the geographic information, map companies acquire AOI data of buildings by using manual drive tests or remotely sensing data through satellites. However, the acquisition of AOI data is difficult, and the AOI boundary data is missing from the partial region boundary. Therefore, how to cut the public OSM network data, obtain the AOI range of any building, and obtain the boundary data of the AOI data becomes a problem to be solved urgently at present.
In order to solve at least the above problems, an embodiment of the present invention provides a road network boundary determining method applied to an electronic device, please refer to fig. 1, where fig. 1 is a block diagram of an electronic device according to an embodiment of the present invention. The electronic device 60 comprises a memory 61, a processor 62 and a communication interface 63. The memory 61, processor 62 and communication interface 63 are electrically connected to each other, directly or indirectly, to enable transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 61 may be used to store software programs and modules, such as program instructions/modules corresponding to the road network boundary determining method provided in the embodiment of the present invention, and the processor 62 executes the software programs and modules stored in the memory 61, so as to execute various functional applications and data processing. The communication interface 63 may be used for communicating signaling or data with other node devices. The electronic device 60 may have a plurality of communication interfaces 63 in the present invention.
The Memory 61 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
The processor 62 may be an integrated circuit chip having signal processing capabilities. The Processor may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), etc.; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc.
Referring to fig. 2, fig. 2 is a schematic flow chart of a road network boundary determining method provided in an embodiment of the present invention based on an electronic device 60 shown in fig. 1, where the road network boundary determining method provided in the embodiment of the present invention includes the following steps:
s31, according to the telecommunication signaling data of the user, the OSM data of the target area is preprocessed, and the travel network information is obtained.
The telecommunication signaling data represent travel track information of a user in a target area, and the travel road network information represents actual road information of the user passing through the target area and actual intersection point information of each road. For example, the telecommunication signaling data may be GPS track information obtained by a user through a carrier network using a Global Positioning System (GPS) installed on a user terminal (e.g., a mobile phone, a smart band, etc.).
And S32, acquiring a plurality of road network nodes with the target points within the distance threshold value according to the travel road network information.
The road network node is the actual intersection point of any two adjacent roads in the target area.
And S33, performing exhaustive search on the road network nodes in the threshold region to obtain the region boundary meeting the preset conditions.
The threshold region is a region within a distance threshold from the target point, the target point being within a region bounded by a region boundary. The preset condition may be that the ratio of the area of the building region where the target point is located to the area of the region enclosed by the region boundary is 1, or is close to 1, or the like.
It should be understood that by using the road network boundary determining method provided by the embodiment of the invention, the area boundary of the target point can be determined according to the OSM data, manual measurement is not needed, and the geographic information is corrected and perfected.
In an optional embodiment, in order to obtain travel network information, a possible implementation is provided on the basis of fig. 2, please refer to fig. 3, and fig. 3 is a flowchart illustrating another road network determining method according to an embodiment of the present invention, which is directed to the above-mentioned S31: the method for acquiring the travel network information according to the OSM data of the target area preprocessed by the telecommunication signaling data of the user may include:
s311, the OSM data is preprocessed to obtain the route data and the dot data.
The route data represents sampled road information in the target area, and the point location data represents sampled intersection point information of each road in the target area.
And S312, matching the telecommunication signaling data with the route data to obtain the travel route information.
The travel route information represents actual road information within the target area.
And S313, matching the telecommunication signaling data with the point location data to obtain trip point location information.
The trip point location information represents actual intersection point information of each road in the target area.
And S314, combining the travel route information and the travel point location information to obtain travel road network information.
For example, the travel network information may be referred to as user travel network Node information (JRN), which may include a user number, JRN number, a Node of a departure road network, a Node of an arrival road network, longitude and latitude information of each road network Node, and the like, that is, JRN information may record which road network nodes the user passes through in traveling, and an order of passing through the road network nodes, and the like; according to JRN, it can analyze the road network that the user walks, which road network data are normally used, the switching relation between road network nodes, etc.
Obtaining the latest OSM data every year through OpenStreetMap, and after the OSM data is processed and preprocessed, obtaining the needed data, wherein the needed data is divided into two parts of data, and the first part of data is route data: df _ edge, containing the fields: from _ node, to _ node, etc., the second data is point location data: df _ node, containing the fields: a node _ id, latitube, longtube, etc. Referring to fig. 4 for the OSM data, fig. 4 is a schematic diagram of a road network according to an embodiment of the present invention, as shown in fig. 4, each line segment represents a different road or road, and each point represents an intersection between different roads or roads.
The telecommunication signaling data is matched with the route data and the point location data to obtain an active road network of the actual life of the user, namely the travel route information and the travel point location information, and the travel route information and the travel point location information are combined to obtain the active road network of the actual life of the user, namely the travel road network information, such as JRN data. For example, when drawing travel network information of a user (taking JRN data as an example), JRN data can be adjusted to obtain a user activity network of real life, which includes two pieces of data: the first is route or road data of the user activity: availability _ edge, such as from _ node, to _ node, etc. fields; the second is actual route node data: realty _ node, such as: node _ id, latitube, longtube, etc.
In an alternative embodiment, in order to obtain a region boundary of a region where a target point is located, a possible implementation is provided on the basis of fig. 2, please refer to fig. 5, where fig. 5 is a flowchart of another road network determining method provided in the embodiment of the present invention, and is directed to the above-mentioned S33: performing exhaustive search on a plurality of road network nodes in a threshold region to obtain a region boundary meeting a preset condition, which may include:
and S331, determining a road network node closest to the target point in the plurality of road network nodes as a closed loop starting point.
In a possible case, if the target point happens to be also a road network node, the target point may be used as a closed-loop starting point. Note that the closed loop starting point is also within the threshold region.
S332, taking the closed loop starting point as a search starting point, and performing gradual divergence in the threshold area to obtain a plurality of area points.
The last region point in the plurality of region points is a closed loop starting point. That is, the area enclosed by the closed loop starting point and the plurality of area points is a closed loop, and the closed loop starting point is both the starting point and the end point of the closed loop.
S333, judging whether the target point is in a closed loop formed by the closed loop starting point and the plurality of area points.
If the target point is in a closed loop formed by the closed loop starting point and the plurality of area points, executing S334; if the target point is not located in the closed loop formed by the closed loop starting point and the plurality of area points, S335 is executed.
And S334, determining a closed loop formed by the closed loop starting point and the plurality of area points as an area boundary of the target point.
And S335, determining that the search is wrong.
For example, a point of information (POI), that is, a target point is not in a closed loop, it is not valid to continue searching for df _ edge at this time, and a distance threshold (e.g., 5km) is defined at this time, that is: searching in the range by taking POI as a center and 5KM (distance threshold, namely divergence threshold) as a radius, and stopping searching when the distance threshold is exceeded; generally, this situation is rare, and a general POI spot is contained in one area, and the situation shows that the provision of POI is problematic.
In an optional embodiment, in order to achieve the acquisition of a plurality of region points, a possible implementation is given on the basis of fig. 5, please refer to fig. 6, where fig. 6 is a schematic flow diagram of another road network determining method provided in an embodiment of the present invention, and is directed to the above S332: taking the starting point of the closed loop as a search starting point to perform gradual divergence in the threshold region to obtain a plurality of region points, which may include:
s332a, taking the closed loop starting point as the search starting point, diverging in the threshold value area, and obtaining the first area point nearest to the closed loop starting point.
For example, if the target point is a and the closed loop starting point is B, then after the search relationship of "From _ Node _ A, To _ Node _ B" is obtained, the "Node _ B" is diverged to obtain "From _ Node _ B, To _ Node _ C", and the first regional point is "Node _ C".
S332b, taking the first region point as the search starting point, diverging in the threshold region to obtain a second region point closest to the first region point except the closed loop starting point.
S332c, diverging in the threshold region with the second region point as the search starting point, and obtaining a third region point closest to the second region point.
S332d, if the third area point is the closed loop starting point, the area point search is stopped.
That is to say, different region points are adopted to perform gradual divergence to obtain a plurality of region points, and when the last region point is consistent with the closed loop starting point, divergence is stopped, so that a closed loop formed by the closed loop starting point and the plurality of region points is obtained.
As shown in fig. 7, fig. 7 is a schematic diagram of a road network determining method provided in the embodiment of the present application, where a pair of data [ From _ Node _ A, To _ Node _ B ] is obtained as a pair of connection relationships, and then is diverged again by the to _ Node _ B, and if [ From _ Node _ B, To _ Node _ E ], the df _ edge is searched exhaustively, and is continuously diverged until a closed loop appears in the whole searching process, and then the searching is stopped; if the list searched finally results in: [ (a, C), (a, B), (a, D), (a, F), (B, E), (B, F), (C, E), (a, H) ], which comprises two closed rings, respectively: [ A, C, E, B, A ] and [ A, B, F, A ]. Since the target point is located in [ A, C, E, B, A ], the closed loop [ A, C, E, B, A ] is the area boundary of the target point.
In the process of continuously diverging step by step, there may be a special case, as shown in fig. 8, fig. 8 is a schematic diagram of another road network determining method provided in the embodiment of the present application, where [ a, B, F, a ] has formed a closed loop, but a POI point (target point) is not in the closed loop, and it is invalid to continue searching for df _ edge at this time, and a distance threshold of 5km is defined at this time, that is: the search is performed in the range with POI as the center and 5KM (divergence threshold) as the radius, and the search is stopped when the POI exceeds the threshold. This is generally rare, and the general POI location is contained in one area, which indicates that the provision of POI (target point) is problematic.
In an alternative embodiment, in order to determine the area boundary, a possible implementation is given on the basis of fig. 5, please refer to fig. 9, and fig. 9 is a flowchart of another road network determining method provided in the embodiment of the present invention, which is directed to the above S334: determining a closed loop formed by the closed loop starting point and the plurality of area points as an area boundary of the target point, which may include:
s334a, if the closed loop starting point and the plurality of area points form a plurality of closed loops, estimating a map area of the building area where the target point is located according to the OSM data.
That is, nesting of multiple closed loops may occur.
And S334b, determining the area of the area corresponding to each closed loop according to the travel network information.
S334c, comparing the area of each region with the area of the map to obtain a plurality of confidence levels.
For example, let the map area be SαArea of region SαConfidence coefficient is SPAnd then: sP＝Sα/Sα。
S334d, determining the target confidence level that is the least different from the alignment threshold value in the confidence levels.
For example, if the comparison threshold is 1, SPThe closer the distance 1, the closer the closed loop is to the actual area.
And taking the closed loop corresponding to the target confidence as the region boundary.
FIG. 10 is a view showing an embodiment of the present applicationAnother schematic diagram of a road network determining method is provided, which includes four closed loops: [ A, B, F, A ]]、[C，E，I，C]、[A，C，E，B，A]、[A，C，J，E，B，A]Due to a closed ring [ A, B, F, A ]]The target points are removed firstly, and the remaining three closed loops are judged by observing the types of POI points, wherein the building ranges of the types such as golf courses, schools, hospitals and the like are different; the cutting is ensured to be effective by observing the AOI analysis of the known type, and the AOI road network cutting range is judged by adjusting the divergence threshold upper limit and the convergence threshold. For example: saArea, S, delineated by road networktFor POI building area estimation, SpFor reliability of the area enclosed, SpThe closer the distance 1 is, the closer to the actual area is. Thereby producing a best-matched boundary range: sp＝Sa/StIn order to determine the area boundaries of the target point.
In order to implement the road network boundary determining method provided in any one of the above embodiments, an embodiment of the present invention provides a road network boundary determining device, please refer to fig. 11, where fig. 11 is a block schematic diagram of a road network boundary determining device provided in an embodiment of the present invention, and the road network boundary determining device includes: an acquisition module 41 and a processing module 42.
The obtaining module 41 is configured to pre-process OSM data of the target area according to the telecommunication signaling data of the user, and obtain travel network information. The telecommunication signaling data represent travel track information of a user in a target area, and the travel road network information represents actual road information of the user passing through the target area and actual intersection point information of each road.
The processing module 42 is configured to obtain a plurality of road network nodes with a target point within a distance threshold according to the travel road network information. The road network node is the actual intersection point of any two adjacent roads in the target area.
The processing module 42 is further configured to perform an exhaustive search on the plurality of road network nodes in the threshold region to obtain a region boundary meeting a preset condition. The threshold region is a region within a distance threshold from the target point, the target point being within a region bounded by a region boundary.
In an alternative embodiment, the obtaining module 41 is further configured to preprocess the OSM data to obtain the route data and the dot data. The route data represents the sampled road information in the target area, and the point location data represents the sampled intersection point information of each road in the target area. The obtaining module 41 is further configured to match the telecommunication signaling data with the route data to obtain the travel route information. The travel route information represents actual road information in the target area. The obtaining module 41 is further configured to match the telecommunication signaling data with the point location data to obtain trip point location information. The trip point location information represents actual intersection point information of each road in the target area. The obtaining module 41 is further configured to combine the travel route information and the travel point location information to obtain travel network information.
In an optional embodiment, the processing module 42 is further configured to determine a road network node closest to the target point among the plurality of road network nodes as a closed-loop starting point. The processing module 42 is further configured to perform gradual divergence in the threshold region by using the closed-loop starting point as a search starting point, so as to obtain a plurality of region points. The last region point in the plurality of region points is a closed loop starting point. The processing module 42 is further configured to determine whether the target point is located in a closed loop defined by the starting point of the closed loop and the plurality of area points. The processing module 42 is further configured to determine, if the target point is located in a closed loop formed by the closed-loop starting point and the plurality of area points, that the closed loop formed by the closed-loop starting point and the plurality of area points is an area boundary of the target point.
It should be understood that the obtaining module 41 and the processing module 42 may cooperatively implement the road network boundary determining method and possible sub-steps thereof provided in any one of the above embodiments.
The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the road network boundary determining method according to any one of the foregoing embodiments. The computer readable storage medium may be, but is not limited to, various media that can store program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a PROM, an EPROM, an EEPROM, a magnetic or optical disk, etc.
In summary, the present invention provides a road network boundary determining method, apparatus, electronic device and storage medium, and relates to the field of geographic information management in traffic technology. The road network boundary determining method comprises the following steps: preprocessing OSM data of a target area according to telecommunication signaling data of a user to acquire travel road network information; the telecommunication signaling data represents travel track information of a user in a target area, and the travel road network information represents actual road information of the user passing through the target area and actual intersection point information of each road; according to the travel road network information, acquiring a plurality of road network nodes of a target point within a distance threshold; the road network node is the actual intersection point of any two adjacent roads in the target area; performing exhaustive search on a plurality of road network nodes in a threshold region to obtain a region boundary meeting a preset condition; the threshold region is a region within a distance threshold from the target point, the target point being within a region bounded by a region boundary. The method can determine the regional boundary of the target point according to the OSM data, does not need manual measurement, and corrects and perfects geographic information.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (7)
1. A method for road network boundary determination, said method comprising:
preprocessing Open Source Map (OSM) data of a target area according to telecommunication signaling data of a user to acquire travel road network information;
the telecommunication signaling data represents travel track information of the user in the target area, and the travel network information represents actual road information passed by the user in the target area and actual intersection point information of each road;
acquiring a plurality of road network nodes of a target point within a distance threshold according to the travel road network information; the road network node is an actual intersection point of any two adjacent roads in the target area;
performing exhaustive search on the road network nodes in a threshold region to obtain a region boundary meeting a preset condition; the threshold area is an area within the distance threshold from the target point, and the target point is in an area enclosed by the area boundary;
performing exhaustive search on the road network nodes in a threshold region to obtain a region boundary meeting a preset condition, wherein the method comprises the following steps:
determining a road network node closest to the target point in the plurality of road network nodes as a closed loop starting point;
gradually diverging in the threshold region by taking the closed loop starting point as a search starting point to obtain a plurality of region points; the last area point in the plurality of area points is the starting point of the closed loop;
judging whether the target point is in a closed loop formed by the closed loop starting point and the plurality of area points;
if so, determining a closed loop formed by the closed loop starting point and the plurality of area points as an area boundary of the target point;
determining a closed loop formed by the closed loop starting point and the plurality of area points as an area boundary of the target point, including:
if the closed loop starting point and the plurality of area points enclose a plurality of closed loops, estimating the map area of the building area where the target point is located according to OSM data;
determining the area of the area corresponding to each closed loop according to the travel network information;
comparing each area of the region with the area of the map to obtain a plurality of confidence coefficients;
determining a target confidence coefficient which is the smallest difference from an alignment threshold value in the confidence coefficients;
and taking the closed loop corresponding to the target confidence as the region boundary.
2. The method of claim 1, wherein preprocessing the open source map OSM data of the target area according to the telecommunication signaling data of the user to obtain the information of the travel network comprises:
preprocessing the OSM data to obtain route data and point data; the route data represents the sampled road information in the target area, and the point location data represents the sampled intersection point information of each road in the target area;
matching the telecommunication signaling data with the route data to obtain travel route information; the travel route information represents actual road information in the target area;
matching the telecommunication signaling data with the point location data to obtain trip point location information; the trip point location information represents actual intersection point information of each road in the target area;
and combining the travel route information and the travel point location information to obtain the travel road network information.
3. The method of claim 1, wherein the step-by-step divergence in the threshold region with the closed-loop starting point as a search starting point is obtained by a plurality of region points, including:
taking the closed loop starting point as a search starting point to perform divergence in the threshold value area to obtain a first area point closest to the closed loop starting point;
taking the first region point as a search starting point to perform divergence in the threshold region to obtain a second region point which is closest to the first region point except the closed loop starting point;
taking the second region point as a search starting point to perform divergence in the threshold region to obtain a third region point closest to the second region point;
and if the third area point is the closed loop starting point, stopping area point search.
4. A road network boundary determining apparatus, comprising:
the acquisition module is used for preprocessing OSM data of a target area according to telecommunication signaling data of a user and acquiring the information of the travel road network;
the telecommunication signaling data represents travel track information of the user in the target area, and the travel network information represents actual road information passed by the user in the target area and actual intersection point information of each road;
the processing module is used for acquiring a plurality of road network nodes of a target point within a distance threshold according to the travel road network information; the road network node is an actual intersection point of any two adjacent roads in the target area;
the processing module is further used for carrying out exhaustive search on the road network nodes in a threshold region to obtain a region boundary meeting a preset condition; the threshold area is an area within the distance threshold from the target point, and the target point is in an area enclosed by the area boundary;
the processing module is further configured to determine a road network node closest to the target point among the plurality of road network nodes as a closed-loop starting point;
the processing module is further configured to perform gradual divergence in the threshold region with the closed-loop starting point as a search starting point to obtain a plurality of region points; the last area point in the plurality of area points is the starting point of the closed loop;
the processing module is further configured to determine whether the target point is located in a closed loop defined by the closed loop starting point and the plurality of area points;
the processing module is further configured to determine, if the target point is located in a closed loop formed by the closed-loop starting point and the plurality of area points, that the closed loop formed by the closed-loop starting point and the plurality of area points is an area boundary of the target point;
the processing module is further used for estimating the map area of the building area where the target point is located according to OSM data if the closed loop starting point and the plurality of area points enclose a plurality of closed loops; determining the area of the area corresponding to each closed loop according to the travel network information; comparing each area of the region with the area of the map to obtain a plurality of confidence coefficients; determining a target confidence coefficient which is the smallest difference from an alignment threshold value in the confidence coefficients; and taking the closed loop corresponding to the target confidence as the region boundary.
5. The apparatus of claim 4, wherein the obtaining module is further configured to preprocess the OSM data to obtain route data and point data; the route data represents the sampled road information in the target area, and the point location data represents the sampled intersection point information of each road in the target area;
the acquisition module is further used for matching the telecommunication signaling data with the route data to obtain travel route information; the travel route information represents actual road information in the target area;
the acquisition module is further configured to match the telecommunication signaling data with the point location data to obtain trip point location information; the trip point location information represents actual intersection point information of each road in the target area;
the obtaining module is further configured to combine the travel route information and the travel point location information to obtain the travel network information.
6. An electronic device comprising a processor and a memory, the memory storing a computer program executable by the processor, the processor being configured to execute the computer program to implement the method of any one of claims 1-3.
7. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of any one of claims 1-3.
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