CN114217333A - Road network topological abnormal position positioning method and device and related equipment - Google Patents
Road network topological abnormal position positioning method and device and related equipment Download PDFInfo
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Abstract
The application provides a road network topology abnormal position positioning method, a road network topology abnormal position positioning device and related equipment, wherein the method comprises the steps of obtaining road network topology and global positioning system GPS data of a vehicle in a target area, the target area comprises a plurality of sub-areas, the GPS data comprises N GPS points, the N GPS points are located in the same or different sub-areas of the plurality of sub-areas, and N is a positive integer; matching the N GPS points with the road network topology to obtain a matching result; determining an abnormal result of each sub-area in the plurality of sub-areas according to the matching result; and determining the abnormal position of the road network topology in the target area according to the abnormal result. The road network topological abnormal position positioning method can determine the position of the road network topological abnormal more efficiently.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method, an apparatus, and a related device for positioning a location of a topological anomaly in a road network.
Background
The road network topology comprises the connection relation among roads and is basic data in the traffic industry. Map-based analysis, such as route navigation and Global Positioning System (GPS) analysis, requires the use of road network topology. With the development of cities, the positions of roads and the connection relations among the roads are changed, so that abnormal positions which are not consistent with the actual road conditions in the road network topology need to be located, and the road network topology is timely and effectively updated.
In the related art, although a method of updating an abnormal road network topology based on GPS data is given, a method of efficiently determining the position of an abnormal road network topology is not given.
Disclosure of Invention
The embodiment of the application provides a method, a device and related equipment for positioning a road network topological abnormal position, and solves the problem of how to determine the position of the road network topological abnormal position more efficiently.
In order to achieve the above object, in a first aspect, an embodiment of the present application provides a method for positioning a location of a road network topology anomaly, including:
the method comprises the steps that road network topology and Global Positioning System (GPS) data of a vehicle in a target area are obtained, the target area comprises a plurality of sub-areas, the GPS data comprise N GPS points, the N GPS points are located in the same or different sub-areas of the sub-areas, and N is a positive integer;
matching the N GPS points with the road network topology to obtain a matching result;
determining an abnormal result of each sub-area in the plurality of sub-areas according to the matching result;
and determining the abnormal position of the road network topology in the target area according to the abnormal result.
In a second aspect, an embodiment of the present application provides a road network topological anomaly position locating device, including:
the system comprises an acquisition module, a data acquisition module and a data acquisition module, wherein the acquisition module is used for acquiring road network topology and global positioning system GPS data of a vehicle in a target area, the target area comprises a plurality of sub-areas, the GPS data comprises N GPS points, the N GPS points are positioned in the same or different sub-areas of the plurality of sub-areas, and N is a positive integer;
the first determining module is used for matching the N GPS points with the road network topology to obtain a matching result;
the second determining module is used for determining the abnormal result of each sub-area in the plurality of sub-areas according to the matching result;
and a third determining module, configured to determine, according to the abnormal result, an abnormal position of the road network topology in the target area.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a computer program stored on the memory and executable on the processor, where the computer program, when executed by the processor, implements the steps in the road network topology anomaly location method according to the first aspect.
In a fourth aspect, an embodiment of the present application provides a readable storage medium, where the readable storage medium stores a program, and the program, when executed by a processor, implements the steps in the road network topology position locating method according to the first aspect.
In the embodiment of the application, the road network topology and N GPS points of a vehicle in a target area are obtained, the target area comprises a plurality of sub-areas, and the N GPS points are located in the same or different sub-areas of the plurality of sub-areas. And then matching the N GPS points with the road network topology to obtain a matching result, and determining the abnormal result of each subregion in the plurality of subregions according to the matching result. And finally, determining the abnormal position of the road network topology in the target area according to the abnormal result. In this way, the abnormal position of the road network topology in the target area can be obtained by sequentially determining the abnormal results of the sub-areas included in the target area, and the problem of how to efficiently determine the abnormal position of the road network topology is solved.
Drawings
For a clear explanation of the technical solutions in the embodiments of the present application, the drawings of the specification are described below, it is obvious that the following drawings are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the listed drawings without any inventive effort.
Fig. 1 is a flowchart of a road network topology anomaly location positioning method according to an embodiment of the present application;
fig. 2 is a second flowchart of a road network topology anomaly location positioning method according to the present application;
FIG. 3 is a schematic diagram of a scenario in which a real path does not match a road network line segment in a road network topology;
fig. 4 is a schematic structural diagram of a road network topological anomaly position locating device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. On the basis of the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without any creative effort belong to the protection scope of the present application.
Referring to fig. 1, an embodiment of the present application provides a road network topological anomaly position locating method, and as shown in fig. 1, the road network topological anomaly position locating method provided in the embodiment of the present application may include:
in a specific implementation, the road network topology includes information of a plurality of road network segments and position information of the plurality of road network segments. The vehicle may be a bus, or a taxi, or a private car, etc. The taxi GPS data source is stable, the data volume is large, and the urban road coverage condition is good, so that the taxi GPS data can be selected to be taken out as the basis for positioning the topological abnormal position of the road network. All the GPS data of all taxis appearing in the target area in a preset time period can be acquired, and the preset time period can be a certain day or a certain week and the like.
The GPS data includes GPS points indicating the location points where the vehicle is present, it being understood that all GPS data of the vehicle within the preset time period includes N GPS points, i.e. the vehicle may be present at N locations during driving within the preset time period, the number of GPS points being related to the sampling frequency of the vehicle location within the preset time period.
The target area is an area where the location of the road network topology abnormality needs to be located, and the size and the location of the target area may be determined according to actual needs, which is not limited herein. For example, the target area may be an area a, city B, or an area with a longitude 116 to a longitude 116.5 and a latitude 39.8 to a latitude 39.9. In particular implementations, the target area may be partitioned into multiple sub-areas, a map index may be constructed, and the target area may be partitioned into multiple sub-areas in a hierarchical structure, where each sub-area may be referred to as a "grid". When constructing the map index, the map index may use a custom box, S2, or H3 as the lattice index.
The sizes of the sub-regions can be the same or different, for example, in a region with less abnormal road network topology in historical time, the area of the sub-region can be larger, so that the efficiency of positioning the abnormal position of the road network topology is improved; for example, the area of the sub-region where the position with sparsely distributed GPS points is located may be larger, so that more GPS points may be used as the basis for analysis in the sub-region, thereby improving the accuracy of positioning the topological anomaly position of the road network.
102, matching the N GPS points with the road network topology to obtain a matching result;
in specific implementation, the N GPS points may be sequentially matched with the road network topology. It can be determined from multiple angles whether a GPS point can match the road network topology.
Example one: the step 102 comprises:
matching M GPS points in a first sub-area with the road network topology to obtain u GPS points matched with the road network topology in the M GPS points, wherein the sub-areas comprise the first sub-area, and M, u are positive integers.
In specific implementation, if the GPS point is located on a road network line segment of the road network topology, the GPS point may be considered to be matched with the road network topology; if no road network line segment exists near the GPS point, the GPS point can be considered as not matched with the road network topology; if a road network line segment exists near the GPS point, but the road network line segment is obviously unreasonable, if the road network line segment is located in a building, the GPS point is also considered to be not matched with the road network topology. And matching the M GPS points in the first sub-area with the road network topology in sequence to obtain u GPS points matched with the road network topology in the M GPS points.
And determining a value obtained by dividing u by M as a first matching success rate, wherein the matching result comprises the first matching success rate.
The other sub-areas in the target area can be sequentially matched with the road network topology according to the matching mode of the first sub-area, so that a matching success rate set of each sub-area in the target area is obtained, wherein the matching success rate set comprises the first matching success rate.
Example two, the step 102 includes:
determining a target path according to the road network topology, wherein the target path is a path which is determined according to the road network topology and is positioned in the target area;
acquiring P distances from P GPS points in a second sub-area to the target path, wherein the plurality of sub-areas comprise the second sub-area, and P is a positive integer;
and sequentially comparing the P distances with a first preset value, wherein the matching result comprises information used for indicating that a third GPS point is not matched with the road network topology under the condition that the first distance is greater than the first preset value, the P distances comprise the first distance, and the first distance corresponds to the third GPS point.
In a specific implementation, the target path may select a plurality of candidate road network line segments from the road network topology, and fit the plurality of candidate road network line segments into the target path. The first preset value may be twice the average distance from all GPS points, i.e., P GPS points, in the second sub-area to the target path. If a certain distance in the P distances is larger than a first preset value, the fact that the GPS point corresponding to the distance is not matched with the road network topology can be determined.
It should be noted that the specific value of the first preset value is changed according to the change of the vehicle. Because the device conditions of different vehicles are different, a vehicle with a smaller average projection distance (i.e., the average projection distance from all GPS points in a certain area to a target path) can be considered to have a more accurate GPS track, and for a vehicle with a smaller average projection distance, the first preset value should be smaller, otherwise, the first preset value should be larger, and the first preset value may be set to be a multiple of the average distance, for example, 2 times.
And sequentially matching other sub-areas in the target area with the road network topology according to the matching mode of the second sub-area to obtain the matching condition of the GPS points of each sub-area in the target area and the road network topology.
Example three, the step 102 includes:
determining a target path according to the road network topology, wherein the target path is a path which is determined according to the road network topology and is positioned in the target area;
comparing the positions of the Q GPS points in the third sub-area with a target range to obtain k GPS points in the Q GPS points, wherein the target path is located in the target range, the sub-areas comprise the third sub-area, and Q, k are positive integers;
and determining a value obtained by dividing k by Q as a first matching coverage, wherein the matching result comprises the first matching coverage.
In a specific implementation, the target range may be 5m to the right and 5m to the left of the target path.
And sequentially matching other sub-areas in the target area with the road network topology according to the matching mode of the third sub-area to obtain a matching coverage set of each sub-area in the target area, wherein the matching coverage set comprises the first matching coverage.
In some scenarios, the GPS points may happen to all fall near a road network segment, but the real path does not match the road network segment. As shown in fig. 3, the straight dotted line in fig. 3 represents the GPS track of the vehicle, i.e., the real path, and the solid line represents the road network line segment in the road network topology. In this scenario, if the matching result is obtained only in the second example, and the P distances are all smaller than the first preset value, the GPS point that does not match the road network topology is determined to match the road network topology. Therefore, the matching results can be obtained by using the two examples and the three examples simultaneously, so that the accuracy of the road network topological anomaly position positioning method is improved.
It should be noted that the matching result may be obtained by only using any one of the above three examples, may also be obtained by using any two of the above three examples, and may also be obtained by using the above three examples at the same time. When the matching results are obtained by adopting any two of the three examples or the three examples, whether the GPS points can be matched with the road network topology or not can be determined from a plurality of angles, and the abnormal position of the road network topology in the target area can be determined according to the matching results, so that the efficiency and the accuracy of the road network topology abnormal position positioning method can be improved.
And 103, determining an abnormal result of each sub-area in the plurality of sub-areas according to the matching result.
In specific implementation, when the matching result includes information indicating that the GPS point is not matched with the road network topology, it may be directly determined that the sub-area where the GPS point is located is abnormal, and the abnormal result includes information indicating that the sub-area is abnormal. In order to avoid the influence of errors on the result of the positioning method for the road network topological abnormality, the times of mismatching of the GPS point and the road network topology in each sub-region can be counted, when the times exceed the empirically determined threshold, the sub-region abnormality that the times of mismatching of the GPS point and the road network topology in the sub-region exceed the threshold is determined, and the abnormality result includes information indicating the sub-region abnormality.
And 104, determining the abnormal position of the road network topology in the target area according to the abnormal result.
It should be noted that there may be more than one anomaly location within the target area. In the concrete implementation, if the size of the sub-region is small, according to the information indicating the sub-region abnormality in the abnormality result, one or more indicated sub-region positions are directly determined to be the abnormal positions in the target region. If the size of the sub-area is large, the abnormal sub-area can be used as a target area, the steps 101 to 104 are repeated, if a plurality of abnormal sub-areas exist, the abnormal sub-areas are sequentially used as the target area, the steps 101 to 104 are repeated until the abnormal position is obtained, and therefore the road network topological abnormal position can be located firstly, and then the specific abnormal position is determined from the abnormal sub-area in a targeted mode according to the primary locating result, and therefore the road network topological abnormal position is located more efficiently and accurately.
In the embodiment of the application, the road network topology and N GPS points of a vehicle in a target area are obtained, the target area comprises a plurality of sub-areas, and the N GPS points are located in the same or different sub-areas of the plurality of sub-areas. And then matching the N GPS points with the road network topology to obtain a matching result, and determining the abnormal result of each subregion in the plurality of subregions according to the matching result. And finally, determining the abnormal position of the road network topology in the target area according to the abnormal result. In this way, the abnormal position of the road network topology in the target area can be obtained by sequentially determining the abnormal results of the sub-areas included in the target area, and the problem of how to efficiently determine the abnormal position of the road network topology is solved.
In order to more fully consider the road network topology to obtain a more accurate matching result, optionally, the step 102 includes:
according to the road network topology, a first road network line segment set in a first range where a first GPS point is located and a second road network line segment set in a second range where a second GPS point is located are obtained, the N GPS points comprise the first GPS point and the second GPS point, and the road network topology comprises the first road network line segment set and the second road network line segment set.
In a specific implementation, the first range may be a rectangular range with the first GPS point as a center point, and the second range may be a rectangular range with the second GPS point as a center point. In order to more fully consider the road network line segment around the first GPS point and the second GPS point, optionally, the first range is a circular area range with the first GPS point as a circular point and a first preset radius value as a radius, and the second range is a circular area range with the second GPS point as a circular point and a second preset radius value as a radius. The first preset radius value and the second preset radius value can be set according to actual needs, and are not limited herein. For example, the first and second predetermined radius values may be 50 meters.
And determining a plurality of possible paths according to the first road network line segment set and the second road network line segment set.
In a specific implementation, the road network line segments in the first road network line segment set and the second road network line segment set may be combined to determine a plurality of possible paths. For example, if there are 10 road segments in the first set of road segments and 5 road segments in the second set of road segments, then combining any one of the 10 road segments with any one of the 5 road segments can determine one possible path, and a total of 50 possible paths can be determined.
Judging whether the first network segment set and the second network segment set are empty sets and whether the possible paths are reasonable or not, and obtaining a judgment result;
if the first route segment set is an empty set, it indicates that there is no route segment around the first GPS point, and if the determination result includes that the first route segment set is an empty set, the matching result includes information indicating that the first GPS point is not matched with the route topology.
If the second road network line segment set is an empty set, it indicates that there are no road network line segments around the second GPS point, and if the determination result includes that the second road network line segment set is an empty set, the matching result includes information indicating that the second GPS point is not matched with the road network topology.
There are many situations where the possible path is not reasonable, and the actual situation may be specifically determined, for example, if the traveling speed of the vehicle is determined to be faster than the flight speed of the aircraft according to the possible path, that is, if the traveling speed of the vehicle is determined to be greater than the limit value of the traveling speed of the vehicle according to the possible path, the possible path may not be reasonable. If all the possible paths are not reasonable, the situation that no reasonable path exists around the first GPS point or the second GPS point is shown. If the determination result includes that the plurality of possible paths are not reasonable, the matching result includes information indicating that the first GPS point does not match the road network topology or that the second GPS point does not match the road network topology.
Generally, if there is a mismatch between a GPS point and a road network topology, it is often the case that a plurality of GPS points within a certain range all do not match (i.e. are abnormal) with the road network topology rather than a single GPS point is abnormal. A single anomalous GPS point may be noise due to GPS data drift or inaccurate recordings, etc. Such as: the beginning and end parts of a vehicle GPS track are often abnormal because the GPS points drift more seriously when the vehicle stops at the beginning and end, and the vehicle is more likely to be located in a cell or the like, which does not contribute much to updating the road network topology (i.e., map) (because the road network topology in the cell is not the key point for updating), but may bring about a large deviation. Therefore, in order to reduce the influence of noise on the method provided in the embodiment of the present application, for the matching result determined according to the above-mentioned manner of example one, optionally, the step 103 includes:
and if the first matching success rate is smaller than a second preset value, determining that the first sub-area is an abnormal area, wherein the abnormal result comprises information used for the first sub-area to be the abnormal area.
In a specific implementation, the second preset value may be 50%, 60%, 65%, and the like, and the second preset value may be set according to actual needs, which is not limited herein.
Similarly, if the matching success rate of other sub-regions in the target region is smaller than the second preset value, the sub-region can also be determined to be an abnormal region. And determining the first sub-area as an abnormal area by setting a second preset value when the first matching success rate is smaller than the second preset value, so that the influence of noise on the positioning accuracy of the topological abnormal position of the road network can be avoided.
For the matching result determined according to the above second example, optionally, the step 103 includes:
if the matching result includes information indicating that the third GPS point is not matched with the road network topology, determining that the second sub-area is an abnormal area, and the abnormal result includes information indicating that the second sub-area is an abnormal area.
The mismatching of the third GPS point and the road network topology shows that the actual road is inconsistent with the road network topology, and the second sub-area where the third GPS point is located is an abnormal area.
Similarly, if the matching result includes that the GPS points of other sub-areas in the target area are inconsistent with the road network topology, the sub-area can also be determined to be an abnormal area. The second sub-region and the first sub-region may be the same sub-region.
In order to reduce the influence of noise on the method provided in the embodiment of the present application, for the matching result determined according to the above-mentioned manner in example three, optionally, the step 103 includes:
and under the condition that the first matching coverage is smaller than a third preset value, determining that the third sub-area is an abnormal area, wherein the abnormal result comprises information used for indicating that the third sub-area is the abnormal area.
In a specific implementation, the third preset value may be 80%, or 78%, or 81%, and the like, and the third preset value may be set according to actual needs, and is not limited herein.
Similarly, if the matching coverage of other sub-regions in the target region is smaller than the second preset value, the sub-region can also be determined to be an abnormal region. The third sub-region and the first sub-region may be the same sub-region, and the third sub-region and the second sub-region may also be the same sub-region.
The method aims to improve the accuracy of the road network topological abnormal position positioning method. The embodiment of the application can also determine the matching result according to the methods provided by the first example, the second example and the third example in sequence. The specific implementation is as follows. Referring to fig. 2, fig. 2 is a second flowchart of a road network topology anomaly location positioning method provided in the embodiment of the present application.
As shown in fig. 2, the road network topological anomaly position positioning method provided in the embodiment of the present application includes the following steps:
1. the map index is constructed, the target area is divided into sub-areas (namely grids) with a hierarchical structure, and a global variable GlobelMap for storing the abnormal times of the sub-areas is constructed. By constructing an index, each GPS point (latitude and longitude) can be mapped to each sub-area so as to count the number of abnormal times of each sub-area, and the target area can be divided into a plurality of sub-areas (i.e. grids), and generally can be divided into a square grid, or an S2 grid, or an H3 grid, etc.
2. And traversing the GPS data of all the vehicles, sequencing the GPS data including GPS points of a taxi all day in each turn, matching the GPS data with the road network topology, and constructing a variable CarMap to store whether each sub-region is marked as an abnormal region by the taxi. The variable CarMap is set, so that the situation that the weight of some sub-regions is abnormally increased due to the fact that continuous GPS points of the same vehicle are wrongly matched can be prevented, and through the variable CarMap, if the sub-region where the current GPS point is located is marked as an abnormal region by other GPS points of the current vehicle, the variable GlobelMap used for representing the abnormal times of the sub-region where the current GPS point is located does not need to be added with 1, and therefore, each vehicle can be guaranteed to provide at most one weight in the same sub-region.
3. And setting a preset number interval T, wherein the specific value of T is determined according to the sampling frequency of the GPS points, and the number of the GPS points uploaded in one minute can be generally used as the value of T.
4. And finding a first GPS point S matched with the road network topology and a last GPS point E matched with the road network topology.
5. All GPS points between points S and E are traversed in sequence.
6. The matching condition of the GPS points between the check points i and i + T is the matching condition of the GPS points between the check point S and the check point E in sequence.
7. Firstly, whether the matching success rate is smaller than a second preset value is judged. The matching success rate is a factor to be considered first, and if the GPS point is not matched with the road network topology, the GPS point is often due to the lack of road network segments (i.e., roads) or topological connection relations in the road network topology, or incorrect road direction marks, etc.
8. And then judging whether the distance (also called projection distance) from the GPS point to the target path is greater than a first preset value.
9. And finally, judging whether the matching coverage is smaller than a third preset value. In addition to the matching coverage determined as described above, the matching coverage may also be the coverage of the GPS point to the matched road network segment: and drawing a circle by taking each GPS point in the plurality of GPS points as a circle center and presetting a radius value, and inspecting the coverage condition of the plurality of circular areas on the matched road network line segments. The matching coverage can be the ratio of the sum of the lengths of the road network line segments covered by the plurality of circular areas to the total length of the road network line segments. If the real path is matched with the road network line segment, the circular area taking the GPS point as the circle center can basically cover the road network line segment, and the matching coverage degree is larger; if the real path does not match the road network segment, as shown in fig. 3, the circular area with the GPS point as the center of the circle cannot better cover the road network segment, and the matching coverage is small.
In the scenario shown in fig. 3, since the GPS points happen to all fall near the road network line segment, the projection distance from the GPS point to the target path is small, and if the matching result is obtained only by the above-mentioned method of example two, the GPS point that does not match the road network topology is determined to match the road network topology. Therefore, the accuracy of the road network topological abnormal position positioning method can be improved by further judging whether the matching coverage is smaller than the preset value.
10. And judging whether the current GPS point is the last GPS point of the current vehicle.
11. And judging whether the current vehicle is the last vehicle.
12. And counting the value of the GlobelMap of each sub-region, and if the value is greater than a certain threshold value, outputting the number of the sub-region corresponding to the value, so that the road network topology abnormity of the position where the sub-region is located can be determined, and the problem of how to efficiently determine the position of the road network topology abnormity is solved. By counting the value of the GlobelMap of each sub-region, and determining the position of the sub-region corresponding to the value as the road network topological abnormal position when the value is larger than a certain threshold value, the interference of the error generated by the GPS data abnormality of some vehicles on the final result can be avoided, and the accuracy of the road network topological abnormal position determination method provided by the embodiment of the application is improved.
The road network topology abnormal position determining method provided by the embodiment of the application can rapidly identify the area of the road network line segment needing topology updating in the road network topology to assist rapid high-frequency map iterative updating. The method provided by the embodiment of the application can also be used for checking the topological accuracy of the road network map of the same version and giving quantitative evaluation.
Referring to fig. 4, an embodiment of the present application provides a road network topology anomaly position determining apparatus 200, including:
an obtaining module 201, configured to obtain road network topology and global positioning system GPS data of a vehicle in a target area, where the target area includes multiple sub-areas, the GPS data includes N GPS points, the N GPS points are located in the same or different sub-areas of the multiple sub-areas, and N is a positive integer;
a first determining module 202, configured to match the N GPS points with the road network topology to obtain a matching result;
a second determining module 203, configured to determine, according to the matching result, an abnormal result of each sub-region in the multiple sub-regions;
a third determining module 204, configured to determine, according to the abnormal result, an abnormal position of the road network topology in the target area.
Optionally, the first determining module 202 includes:
according to the road network topology, acquiring a first road network line segment set in a first range where a first GPS point is located and a second road network line segment set in a second range where a second GPS point is located, wherein the N GPS points comprise the first GPS point and the second GPS point, and the road network topology comprises the first road network line segment set and the second road network line segment set;
determining a plurality of possible paths according to the first road network line segment set and the second road network line segment set;
judging whether the first network segment set and the second network segment set are empty sets and whether the possible paths are reasonable or not, and obtaining a judgment result;
wherein, in a case that the determination result includes that the first set of road network segments is an empty set, the matching result includes information indicating that the first GPS point is not matched with the road network topology;
under the condition that the judgment result includes that the second road network line segment set is an empty set, the matching result includes information used for indicating that the second GPS point is not matched with the road network topology;
and in the case that the judgment result includes that the plurality of possible paths are not reasonable, the matching result includes information indicating that the first GPS point is not matched with the road network topology or the second GPS point is not matched with the road network topology.
Optionally, the first range is a circular area range with the first GPS point as a circular point and a first preset radius value as a radius, and the second range is a circular area range with the second GPS point as a circular point and a second preset radius value as a radius.
Optionally, the first determining module 202 includes:
matching M GPS points in a first sub-area with the road network topology to obtain u GPS points matched with the road network topology in the M GPS points, wherein the sub-areas comprise the first sub-area, and M, u are positive integers;
and determining a value obtained by dividing u by M as a first matching success rate, wherein the matching result comprises the first matching success rate.
Optionally, the first determining module 202 includes:
determining a target path according to the road network topology, wherein the target path is a path which is determined according to the road network topology and is positioned in the target area;
acquiring P distances from P GPS points in a second sub-area to the target path, wherein the plurality of sub-areas comprise the second sub-area, and P is a positive integer;
and sequentially comparing the P distances with a first preset value, wherein the matching result comprises information used for indicating that a third GPS point is not matched with the road network topology under the condition that the first distance is greater than the first preset value, the P distances comprise the first distance, and the first distance corresponds to the third GPS point.
Optionally, the first determining module 202 includes:
determining a target path according to the road network topology, wherein the target path is a path which is determined according to the road network topology and is positioned in the target area;
comparing the positions of the Q GPS points in the third sub-area with a target range to obtain k GPS points in the Q GPS points, wherein the target path is located in the target range, the sub-areas comprise the third sub-area, and Q, k are positive integers;
and determining a value obtained by dividing k by Q as a first matching coverage, wherein the matching result comprises the first matching coverage.
Optionally, the second determining module 203 includes:
if the first matching success rate is smaller than a second preset value, determining that the first sub-area is an abnormal area, wherein the abnormal result comprises information used for indicating that the first sub-area is the abnormal area.
Optionally, the second determining module 203 includes:
if the matching result includes information indicating that the third GPS point is not matched with the road network topology, determining that the second sub-area is an abnormal area, and the abnormal result includes information indicating that the second sub-area is an abnormal area.
Optionally, the second determining module 203 includes:
and under the condition that the first matching coverage is smaller than a third preset value, determining that the third sub-area is an abnormal area, wherein the abnormal result comprises information used for indicating that the third sub-area is the abnormal area.
The road network topology abnormity position positioning device 200 provided by the embodiment of the application can realize each process which can be realized in the road network topology abnormity position positioning method of the application, and achieve the same beneficial effect, and for avoiding repetition, the detailed description is omitted here.
The embodiment of the application provides electronic equipment. As shown in fig. 5, the electronic device 300 includes: a processor 301, a memory 302 and a computer program stored on and executable on said memory 302, the various components in the electronic device 300 being coupled together by a bus system 303. It will be appreciated that the bus system 303 is used to enable communications among the components.
The processor 301 is configured to acquire a road network topology and global positioning system GPS data of a vehicle in a target area, where the target area includes a plurality of sub-areas, the GPS data includes N GPS points, the N GPS points are located in the same or different sub-areas of the plurality of sub-areas, and N is a positive integer;
matching the N GPS points with the road network topology to obtain a matching result;
determining an abnormal result of each sub-area in the plurality of sub-areas according to the matching result;
and determining the abnormal position of the road network topology in the target area according to the abnormal result.
Optionally, the processor 301 is further configured to obtain, according to the road network topology, a first road network segment set in a first range where a first GPS point is located and a second road network segment set in a second range where a second GPS point is located, where the N GPS points include the first GPS point and the second GPS point, and the road network topology includes the first road network segment set and the second road network segment set;
determining a plurality of possible paths according to the first road network line segment set and the second road network line segment set;
judging whether the first network segment set and the second network segment set are empty sets and whether the possible paths are reasonable or not, and obtaining a judgment result;
wherein, in a case that the determination result includes that the first set of road network segments is an empty set, the matching result includes information indicating that the first GPS point is not matched with the road network topology;
under the condition that the judgment result includes that the second road network line segment set is an empty set, the matching result includes information used for indicating that the second GPS point is not matched with the road network topology;
and in the case that the judgment result includes that the plurality of possible paths are not reasonable, the matching result includes information indicating that the first GPS point is not matched with the road network topology or the second GPS point is not matched with the road network topology.
Optionally, the first range is a circular area range with the first GPS point as a circular point and a first preset radius value as a radius, and the second range is a circular area range with the second GPS point as a circular point and a second preset radius value as a radius.
Optionally, the processor 301 is further configured to match M GPS points in a first sub-area with the road network topology, to obtain u GPS points matching with the road network topology in the M GPS points, where the plurality of sub-areas include the first sub-area, and M, u are all positive integers;
and determining a value obtained by dividing u by M as a first matching success rate, wherein the matching result comprises the first matching success rate.
Optionally, the processor 301 is further configured to determine a target path according to the road network topology, where the target path is a path located in the target area determined according to the road network topology;
acquiring P distances from P GPS points in a second sub-area to the target path, wherein the plurality of sub-areas comprise the second sub-area, and P is a positive integer;
and sequentially comparing the P distances with a first preset value, wherein the matching result comprises information used for indicating that a third GPS point is not matched with the road network topology under the condition that the first distance is greater than the first preset value, the P distances comprise the first distance, and the first distance corresponds to the third GPS point.
Optionally, the processor 301 is further configured to determine a target path according to the road network topology, where the target path is a path located in the target area determined according to the road network topology;
comparing the positions of the Q GPS points in the third sub-area with a target range to obtain k GPS points in the Q GPS points, wherein the target path is located in the target range, the sub-areas comprise the third sub-area, and Q, k are positive integers;
and determining a value obtained by dividing k by Q as a first matching coverage, wherein the matching result comprises the first matching coverage.
Optionally, the processor 301 is further configured to determine that the first sub-region is an abnormal region if the first matching success rate is smaller than a second preset value, where the abnormal result includes information indicating that the first sub-region is an abnormal region.
Optionally, the processor 301 is further configured to determine that the second sub-area is an abnormal area if the matching result includes information indicating that the third GPS point is not matched with the road network topology, and the abnormal result includes information indicating that the second sub-area is an abnormal area.
Optionally, the processor 301 is further configured to determine that the third sub-area is an abnormal area if the first matching coverage is smaller than a third preset value, and the abnormal result includes information indicating that the third sub-area is an abnormal area.
The electronic device 300 provided in the embodiment of the present application can implement each process that can be implemented in the road network topology abnormal position location method of the present application, and achieve the same beneficial effects, and for avoiding repetition, the details are not repeated here.
The embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the road network topology abnormal position location method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
While the present embodiments have been described with reference to the accompanying drawings, it is to be understood that the invention is not limited to the precise embodiments described above, which are meant to be illustrative and not restrictive, and that various changes may be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (12)
1. A road network topological abnormity position positioning method is characterized by comprising the following steps:
the method comprises the steps that road network topology and Global Positioning System (GPS) data of a vehicle in a target area are obtained, the target area comprises a plurality of sub-areas, the GPS data comprise N GPS points, the N GPS points are located in the same or different sub-areas of the sub-areas, and N is a positive integer;
matching the N GPS points with the road network topology to obtain a matching result;
determining an abnormal result of each sub-area in the plurality of sub-areas according to the matching result;
and determining the abnormal position of the road network topology in the target area according to the abnormal result.
2. The method according to claim 1, wherein said matching said N GPS points with said road network topology to obtain a matching result comprises:
according to the road network topology, acquiring a first road network line segment set in a first range where a first GPS point is located and a second road network line segment set in a second range where a second GPS point is located, wherein the N GPS points comprise the first GPS point and the second GPS point, and the road network topology comprises the first road network line segment set and the second road network line segment set;
determining a plurality of possible paths according to the first road network line segment set and the second road network line segment set;
judging whether the first network segment set and the second network segment set are empty sets and whether the possible paths are reasonable or not, and obtaining a judgment result;
wherein, in a case that the determination result includes that the first set of road network segments is an empty set, the matching result includes information indicating that the first GPS point is not matched with the road network topology;
under the condition that the judgment result includes that the second road network line segment set is an empty set, the matching result includes information used for indicating that the second GPS point is not matched with the road network topology;
and in the case that the judgment result includes that the plurality of possible paths are not reasonable, the matching result includes information indicating that the first GPS point is not matched with the road network topology or the second GPS point is not matched with the road network topology.
3. The method of claim 2, wherein the first range is a circular area range with a radius of a first predetermined radius value and the first GPS point is a circular dot, and the second range is a circular area range with a radius of a second predetermined radius value and the second GPS point is a circular dot.
4. The method according to claim 1, wherein said matching said N GPS points with said road network topology to obtain a matching result comprises:
matching M GPS points in a first sub-area with the road network topology to obtain u GPS points matched with the road network topology in the M GPS points, wherein the sub-areas comprise the first sub-area, and M, u are positive integers;
and determining a value obtained by dividing u by M as a first matching success rate, wherein the matching result comprises the first matching success rate.
5. The method according to claim 1, wherein said matching said N GPS points with said road network topology to obtain a matching result comprises:
determining a target path according to the road network topology, wherein the target path is a path which is determined according to the road network topology and is positioned in the target area;
acquiring P distances from P GPS points in a second sub-area to the target path, wherein the plurality of sub-areas comprise the second sub-area, and P is a positive integer;
and sequentially comparing the P distances with a first preset value, wherein the matching result comprises information used for indicating that a third GPS point is not matched with the road network topology under the condition that the first distance is greater than the first preset value, the P distances comprise the first distance, and the first distance corresponds to the third GPS point.
6. The method according to claim 1, wherein said matching said N GPS points with said road network topology to obtain a matching result comprises:
determining a target path according to the road network topology, wherein the target path is a path which is determined according to the road network topology and is positioned in the target area;
comparing the positions of the Q GPS points in the third sub-area with a target range to obtain k GPS points in the Q GPS points, wherein the target path is located in the target range, the sub-areas comprise the third sub-area, and Q, k are positive integers;
and determining a value obtained by dividing k by Q as a first matching coverage, wherein the matching result comprises the first matching coverage.
7. The method of claim 4, wherein said determining abnormal results for each of said plurality of sub-regions based on said matching results comprises:
if the first matching success rate is smaller than a second preset value, determining that the first sub-area is an abnormal area, wherein the abnormal result comprises information used for indicating that the first sub-area is the abnormal area.
8. The method of claim 5, wherein said determining abnormal results for each of said plurality of sub-regions based on said matching results comprises:
if the matching result includes information indicating that the third GPS point is not matched with the road network topology, determining that the second sub-area is an abnormal area, and the abnormal result includes information indicating that the second sub-area is an abnormal area.
9. The method of claim 6, wherein said determining abnormal results for each of said plurality of sub-regions based on said matching results comprises:
and under the condition that the first matching coverage is smaller than a third preset value, determining that the third sub-area is an abnormal area, wherein the abnormal result comprises information used for indicating that the third sub-area is the abnormal area.
10. A road network topological abnormity position positioning device is characterized by comprising:
the system comprises an acquisition module, a data acquisition module and a data acquisition module, wherein the acquisition module is used for acquiring road network topology and global positioning system GPS data of a vehicle in a target area, the target area comprises a plurality of sub-areas, the GPS data comprises N GPS points, the N GPS points are positioned in the same or different sub-areas of the plurality of sub-areas, and N is a positive integer;
the first determining module is used for matching the N GPS points with the road network topology to obtain a matching result;
the second determining module is used for determining the abnormal result of each sub-area in the plurality of sub-areas according to the matching result;
and a third determining module, configured to determine, according to the abnormal result, an abnormal position of the road network topology in the target area.
11. An electronic device, comprising a processor, a memory and a computer program stored on the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the road network topology anomaly location method according to any one of claims 1 to 9.
12. A readable storage medium, characterized in that said readable storage medium has stored thereon a program, which when executed by a processor implements the steps in the road network topology position location method according to any of claims 1 to 9.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115824231A (en) * | 2023-02-22 | 2023-03-21 | 安徽阿瑞特汽车电子科技有限公司 | Intelligent positioning management system for automobile running |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101270997A (en) * | 2007-03-21 | 2008-09-24 | 北京交通发展研究中心 | Floating car dynamic real-time traffic information processing method based on GPS data |
| CN103235848A (en) * | 2013-04-15 | 2013-08-07 | 中国科学院软件研究所 | Light-weight map matching method based on simplified map model |
| US20140278055A1 (en) * | 2013-03-15 | 2014-09-18 | Hewlett-Packard Development Company, L.P. | Updating road maps |
| WO2018122585A1 (en) * | 2016-12-30 | 2018-07-05 | 同济大学 | Method for urban road traffic incident detecting based on floating-car data |
| CN109916413A (en) * | 2019-03-18 | 2019-06-21 | 华南师范大学 | Road matching method, system, device and storage medium based on grid dividing |
-
2022
- 2022-02-21 CN CN202210154219.1A patent/CN114217333A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101270997A (en) * | 2007-03-21 | 2008-09-24 | 北京交通发展研究中心 | Floating car dynamic real-time traffic information processing method based on GPS data |
| US20140278055A1 (en) * | 2013-03-15 | 2014-09-18 | Hewlett-Packard Development Company, L.P. | Updating road maps |
| CN103235848A (en) * | 2013-04-15 | 2013-08-07 | 中国科学院软件研究所 | Light-weight map matching method based on simplified map model |
| WO2018122585A1 (en) * | 2016-12-30 | 2018-07-05 | 同济大学 | Method for urban road traffic incident detecting based on floating-car data |
| CN109916413A (en) * | 2019-03-18 | 2019-06-21 | 华南师范大学 | Road matching method, system, device and storage medium based on grid dividing |
Non-Patent Citations (4)
| Title |
|---|
| 李秋萍 等: ""基于浮动车的道路网变化探测方法"", 《2008第四届中国智能交通年会论文集》 * |
| 王晓蒙 等: ""一种面向海量浮动车数据的地图匹配方法"", 《地球信息科学》 * |
| 袁辉: ""面向时间地理分析的轨迹大数据建模与时空邻近性分析研究"", 《中国博士学位论文全文数据库电子期刊 信息科技辑》 * |
| 郭森 等: ""基于新道路发现的GIS地图更新算法"", 《计算机应用》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115824231A (en) * | 2023-02-22 | 2023-03-21 | 安徽阿瑞特汽车电子科技有限公司 | Intelligent positioning management system for automobile running |
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