CN111125293A - Automatic generation method and device of public transport network model and electronic equipment - Google Patents
Automatic generation method and device of public transport network model and electronic equipment Download PDFInfo
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- CN111125293A CN111125293A CN201911415366.4A CN201911415366A CN111125293A CN 111125293 A CN111125293 A CN 111125293A CN 201911415366 A CN201911415366 A CN 201911415366A CN 111125293 A CN111125293 A CN 111125293A
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Abstract
The application provides a method and a device for automatically generating a public transport network model and electronic equipment, and relates to the technical field of public transport informatization. After the bus GPS data of the road network of the target city and each bus in the target city are obtained, a first stop set of each bus line is obtained according to the bus GPS data of each bus corresponding to each bus line, and the first stop set comprises first geographic information of the bus stops included in the bus lines. And then matching the bus GPS data of each bus corresponding to each bus line and the first stop set of the bus line with a target city road network to obtain the geographic information of the target road section and the second geographic information of the bus stop included in each bus line so as to serve as a bus network model of the target city. Therefore, the bus network model can be quickly obtained, and the method has the characteristics of strong universality, high accuracy and the like.
Description
Technical Field
The application relates to the technical field of public transportation informatization, in particular to a method and a device for automatically generating a public transportation network model and electronic equipment.
Background
With the development of big data and informatization, urban public transportation planning requires quantification, synthesis and integration. The bus big data analysis is an important means for supporting the rationalization and the scientization of bus decisions. The urban public transport network model is constructed by utilizing the ArcGIS information platform and the multi-source data such as the public transport GPS and the public transport IC card data, the urban public transport basic database is perfected, the urban public transport trip and operation current situation is truly and comprehensively reflected by utilizing the big data analysis technology, the urban public transport network model is the basis for constructing the urban public transport model and planning the urban public transport, and real basis and important support can be provided for government decision making.
The construction and maintenance of the public transportation database are the fundamental and necessary work for building an urban traffic model (including a public transportation model). At present, each bus route is generally drawn manually by manpower, and geographic information of a target road section included in each bus route and geographic information of a bus stop included in each bus route are confirmed, so that the mode has large workload and low efficiency.
Disclosure of Invention
In view of this, an object of the present application is to provide a method and an apparatus for automatically generating a bus network model, and an electronic device.
In order to achieve the above purpose, the embodiments of the present application employ the following technical solutions:
in a first aspect, an embodiment of the present application provides an automatic generation method for a bus network model, where the method includes:
obtaining a target city road network;
the method comprises the steps of obtaining bus GPS data of each bus in a target city, and obtaining a first stop set of each bus line according to the bus GPS data of each bus corresponding to each bus line, wherein the bus GPS data comprises geographic information, and the first stop set comprises first geographic information of bus stops included by the bus lines;
the method comprises the steps of matching bus GPS data of each bus corresponding to each bus line and a first stop set of the bus line with a target city road network to obtain bus line stop information of each bus line, wherein the bus line stop information is used as a bus network model of the target city, the bus line stop information comprises a target road section set and a second stop set corresponding to the bus line, the target road section set comprises geographic information of a target road section included by the bus line, the geographic information of the target road section is distributed according to the extending direction of the bus line, and the second stop set comprises second geographic information of bus stops distributed according to the extending direction of the bus line.
In a second aspect, an embodiment of the present application provides an automatic generation apparatus for a public transportation network model, the apparatus includes:
the acquisition module is used for acquiring a target city road network;
the first processing module is used for obtaining bus GPS data of each bus in a target city and obtaining a first stop set of each bus line according to the bus GPS data of each bus corresponding to each bus line, wherein the bus GPS data comprises geographic information, and the first stop set comprises first geographic information of bus stops included by the bus lines;
the second processing module is used for matching the bus GPS data of each bus corresponding to each bus line and the first stop set of the bus line with the road network of the target city to obtain the bus line stop information of each bus line, and the bus line stop information is used as a bus network model of the target city, wherein the bus line stop information comprises a target road section set and a second stop set corresponding to the bus line, the target road section set comprises the geographic information of the target road section included by the bus line, the geographic information of the target road section is distributed according to the extending direction of the bus line, and the second stop set comprises the second geographic information of the bus stops distributed according to the extending direction of the bus line.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor and a memory, where the memory stores machine executable instructions that can be executed by the processor, and the processor can execute the machine executable instructions to implement the automatic generation method of a bus network model in any one of the foregoing embodiments.
In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the automatic generation method of a bus network model according to any one of the foregoing embodiments.
According to the method, the device and the electronic equipment for automatically generating the bus network model, bus GPS data of a road network of a target city and each bus in the target city are obtained at first, and the bus GPS data comprise geographic information. And then, obtaining a first station set of each bus route according to the bus GPS data of each bus corresponding to each bus route. The first stop set comprises first geographic information of bus stops included in the bus lines. And finally, matching the bus GPS data of each bus corresponding to each bus line and the first station set of the bus line with the road network of the target city to obtain the geographic information of the target road section and the second geographic information of the bus station included in each bus line so as to serve as the bus network model of the target city. Therefore, the public transportation network model of the target city can be automatically obtained without a large amount of manual work, batch operation can be realized, and the method has the characteristics of high efficiency, high precision, clear logic, strong universality, wide application range and the like.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required 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 application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a block schematic diagram of an electronic device provided in an embodiment of the present application;
fig. 2 is a schematic flow chart of an automatic generation method of a public transportation network model according to an embodiment of the present application;
FIG. 3 is one of the flow diagrams of the sub-steps included in step S110 of FIG. 2;
FIG. 4 is a second schematic flowchart of the sub-steps included in step S110 in FIG. 2;
FIG. 5 is a schematic flow chart of the sub-steps included in step S120 of FIG. 2;
FIG. 6 is a schematic flow chart of the sub-steps included in step S130 of FIG. 2;
fig. 7 is a schematic block diagram of an automatic bus network model generation device according to an embodiment of the present application.
Icon: 100-an electronic device; 110-a memory; 120-a processor; 130-a communication unit; 200-automatic generating device of public transport network model; 210-an obtaining module; 220-a first processing module; 230-second processing module.
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. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
It is noted that relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Referring to fig. 1, fig. 1 is a block diagram of an electronic device 100 according to an embodiment of the present disclosure. The electronic device 100 may be, but is not limited to, a computer, a server, etc. The electronic device 100 includes a memory 110, a processor 120, and a communication unit 130. The elements of the memory 110, the processor 120 and the communication unit 130 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines.
The memory 110 is used to store programs or data. The Memory 110 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 120 is used to read/write data or programs stored in the memory 110 and perform corresponding functions. For example, the memory 110 stores therein an automatic bus network model generation device 200, and the automatic bus network model generation device 200 includes at least one software functional module which can be stored in the memory 110 in the form of software or firmware (firmware). The processor 120 executes various functional applications and data processing by running software programs and modules stored in the memory 110, such as the automatic generation device 200 of the bus network model in the embodiment of the present application, so as to implement the automatic generation method of the bus network model in the embodiment of the present application.
The communication unit 130 is used for establishing a communication connection between the electronic apparatus 100 and another communication terminal via a network, and for transceiving data via the network.
It should be understood that the structure shown in fig. 1 is only a schematic structural diagram of the electronic device 100, and the electronic device 100 may also include more or fewer components than shown in fig. 1, or have a different configuration than shown in fig. 1. The components shown in fig. 1 may be implemented in hardware, software, or a combination thereof.
Referring to fig. 2, fig. 2 is a schematic flow chart of a method for automatically generating a bus network model according to an embodiment of the present application. The method is applied to the electronic device 100. The following explains the specific flow of the automatic generation method of the public transportation network model in detail.
And step S110, obtaining a target city road network.
Step S120, bus GPS data of each bus in the target city is obtained, and a first stop set of each bus route is obtained according to the bus GPS data of each bus corresponding to each bus route.
Step S130, matching the bus GPS data of each bus corresponding to each bus line and the first stop set of the bus line with the target city road network to obtain the bus line stop information of each bus line to be used as the bus network model of the target city.
In this embodiment, a target city road network is first obtained, and the target city road network includes geographic information of each road segment, which may be represented as GPS location information, i.e., longitude and latitude information. The bus of the target city can be provided with a position information acquisition unit, and the position information acquisition unit can send bus GPS data of the bus to the processing equipment according to a certain frequency. The electronic device 100 may obtain the bus GPS data of each bus in the target city from the processing device, or may obtain the bus GPS data of each bus in the target city by directly communicating with the position information acquisition unit. The bus GPS data comprises geographic information, and the geographic information can be GPS position information, namely longitude and latitude information. Each bus GPS data corresponds to one track point. Further, the bus GPS data may further include an identifier of a corresponding bus, so as to confirm the bus corresponding to the bus GPS data.
After the bus GPS data of each bus in the target city is obtained, the first station set of each bus line can be obtained according to the bus GPS data of each bus corresponding to each bus line. The first stop set of one bus line comprises first geographic information of bus stops included by the bus line. Optionally, the first geographic information in the first set of stops may be stored in order of positions of the bus stops on the bus route. For example, bus stops 1, 2, and 3 are distributed on a bus route according to the driving direction of the bus, and the first stop set of the bus route sequentially includes the geographic information of the bus stop 1, the geographic information of the bus stop 2, and the geographic information of the bus stop 3.
After the first stop set of each bus route is obtained, the bus GPS data of each bus corresponding to each bus route, the first stop set of the bus route and the target city road network can be subjected to map matching, and therefore the bus route stop information of each bus route is obtained. That is to say, map matching is carried out on the bus GPS data of each bus corresponding to one bus route, the first stop set of the bus route and the target city road network to obtain the bus route stop information of the bus route; and repeating the map matching to obtain the bus route stop information of each bus route of the target city.
The bus route station information of one bus route comprises a target road section set and a second station set corresponding to the bus route, the target road section set comprises geographic information of a target road section included by the bus route, and the second station set comprises second geographic information of a bus station included by the bus route. Optionally, the geographic information of the target road segment in the target road segment set may be distributed according to a bus route extending direction, and the second geographic information in the second station set may also be distributed according to the bus route extending direction. The bus route extending direction can be the driving direction of the bus when the bus drives on the bus route.
Through map matching, a public transportation network model which is consistent with the actual situation can be obtained. Therefore, the public transportation network model can be automatically obtained without consuming a large amount of manpower, batch operation can be performed, the public transportation network models of multiple cities are generated simultaneously, and the method has the characteristics of high efficiency, high precision, clear logic, strong universality, wide application range and the like.
In this embodiment, if the directly obtained original city road network is different from the required target city road network, the original city road network may be processed so as to perform map matching subsequently. Referring to fig. 3, fig. 3 is a flowchart illustrating one of sub-steps included in step S110 in fig. 2. Step S110 may include sub-step S111, step S112, and sub-step S113.
And a substep S111, obtaining the original city road network topology.
And a substep S112, converting a coordinate system of the original city road network topology according to a target coordinate system used by the bus GPS data to obtain a first road network topology based on the target coordinate system.
And a substep S113, checking and adjusting the first network topology according to a preset topology rule to obtain a second network topology.
In this embodiment, first, one of the existing multiple original city road network topologies may be selected, and then, whether the coordinate system of the selected original city road network topology is the same as the target coordinate system used by the bus GPS data is determined. If the two original city road network topologies are the same, the coordinate system conversion of the selected original city road network topology is not needed, and the original city road network topology is directly used as the first road network topology. And if not, performing topology conversion on the original city road network topology according to the coordinate system of the original city road network topology and the target coordinate, thereby obtaining a first road network topology based on the target coordinate system.
After the first network topology is obtained, according to a self-defined preset topology rule, checking whether roads are overlapped, whether roads are self-intersected, whether roads are connected, whether roads are broken, traffic management measure checking and the like can be carried out on the first network topology, and the first network topology is adjusted according to a checking result, so that a second network topology is obtained. The traffic management action check includes checking whether there is a single line, no left, etc. For example, if the road is not interrupted, the interruption is needed; if a certain road is a one-way road, the information can be marked; if a certain road is prohibited from traveling to the left at a certain position, the information may also be marked.
Optionally, if the traffic management measures are distinguished from time periods, for example, a certain position is prohibited between the time periods a to b, but is not prohibited outside the time periods a to b, the specific traffic management measures corresponding to different time periods and the time periods may be annotated on the first network topology.
Referring to fig. 4, fig. 4 is a second schematic flowchart of the sub-steps included in step S110 in fig. 2. After substep S113, step S110 may further include substep S114.
And a substep S114 of performing road section combination processing on the second road network topology according to a road section combination rule to obtain a third road network topology.
After the second network topology is obtained, the road sections in the second network topology which accord with the preset road section merging rule can be merged, so that the calculation amount of subsequent map matching can be reduced, and the obtained bus route network model cannot be influenced. The road segment merging rule may be set according to actual requirements, for example, a starting point of one road segment is an ending point of another road segment, and the length of each road segment is less than a preset length. For example, if there are the links 1 and 2, the end point of the link 1 is the start point of the link 2, and the links 1 and 2 are both links with a length less than 50 meters, the links 1 and 2 may be merged. At the time of merging, the end point of the link 1 and the start point of the link 2 may be deleted, so that the links 1, 2 are merged into one link, whereby the processing of the small links may be completed.
Referring to fig. 5, fig. 5 is a flowchart illustrating sub-steps included in step S120 in fig. 2. Step S120 may include substep S121, substep S122, and substep S123.
And a substep S121, preprocessing the bus GPS data of each bus in a preset time period to obtain the processed bus GPS data.
In this embodiment, the bus GPS data of each bus within a preset time period can be obtained, and then the obtained bus GPS data is preprocessed, so as to obtain the processed bus GPS data that can be directly used subsequently. The preset time period may be set according to actual requirements, for example, set to 24 hours. The bus GPS data of a bus in a preset time period can correspond to at least one effective bus route track.
Further, in order to improve the accuracy of the first geographical information of the subsequently obtained bus stops, the bus GPS data of each bus in the preset time period corresponds to a plurality of effective bus route tracks. The similarity between the corresponding effective bus route tracks of one bus in a preset time period is greater than a preset value, and the preset value is set according to actual requirements. That is, a bus corresponds to a plurality of similar effective bus route tracks within a preset time period. For example, if a bus route is from a starting point a to an ending point B, the bus GPS data of the bus in the preset time period corresponds to the bus route track from the starting point a to the ending point B for a plurality of times. When the bus GPS data of each bus in the preset time period corresponds to a plurality of effective bus route tracks, one bus correspondingly returns to and returns two bus routes, for example, if the bus 1 returns to and returns among bus stops A, 1, 2, 3 and B, the bus A corresponds to the bus route A → B and the bus route B → A. And subsequently, when map matching is carried out, matching the bus route A → B, and matching the bus route B → A.
The bus GPS data of the bus corresponding to each bus line can be determined according to the corresponding relationship of the pre-stored identification of the bus line and the identification of the bus. And calculating the similarity among all the bus route tracks, and taking the bus route tracks with the similarity larger than the preset similarity as the bus route tracks corresponding to the same bus route, thereby determining the bus GPS data of the bus corresponding to each bus route. Optionally, the two modes can be combined, so that the bus GPS data of the bus corresponding to each bus route is determined.
Alternatively, the pre-treatment may be accomplished by:
carrying out data cleaning on bus GPS data of each bus within a preset time period;
and performing difference completion on the bus GPS data after data cleaning, and extracting bus GPS data of an effective bus route track from the bus GPS data after difference completion to obtain the processed bus GPS data.
After the bus GPS data is obtained, data cleaning processing such as invalid redundancy elimination, filtering denoising and the like can be carried out on the bus GPS data of each bus. The GPS data can also comprise time information and station entering and exiting information. For example, two track points respectively correspond to the bus GPS data 1 and the bus GPS data 2, and the bus GPS data 1 and the bus GPS data 2 correspond to the bus a, and if the first geographic information and the time information in the bus GPS data 1 are the same as those in the bus GPS data 2, the bus GPS data 1 or the bus GPS data 2 can be deleted to reduce the calculation amount of subsequent map matching. The influence of individual abnormal data in the bus GPS data can be reduced through filtering and denoising.
Furthermore, if the bus GPS data of each bus also comprises invalid bus GPS data corresponding to a return yard and the like, the invalid bus GPS data can be deleted when the data are cleaned, so that the bus GPS data corresponding to the valid bus route track can be obtained.
After the data cleaning is completed, difference completion can be performed, so that the situation that the bus GPS data after the data cleaning does not comprise all required data is avoided, and the correctness of a subsequently generated bus network model is further ensured.
And a substep S122 of extracting target GPS data from the processed bus GPS data according to the station entering and exiting information.
Optionally, in an implementation manner of this embodiment, when the bus GPS data corresponds to a bus stop, the bus GPS data includes information of coming in and going out of the bus stop. For example, when a bus enters a bus stop 1, the bus GPS data corresponding to the bus stop 1 includes an arrival; when leaving the bus stop 1, the corresponding bus GPS data can include the departure. In another implementation manner of this embodiment, the station entering and exiting information may be classified into station entering, station exiting, and non-station entering and exiting, and whether the current position is a bus stop may be determined according to the station entering and exiting information. Therefore, the target GPS data of each bus can be obtained based on the preprocessed bus GPS data of each bus. The target GPS data comprises bus GPS data corresponding to the station entering and bus GPS data corresponding to the station exiting.
And a substep S123 of generating a first stop set of each bus line by a spatial clustering method based on the target GPS data corresponding to each bus line.
The geographic information of the bus stop can be determined according to the target GPS data, and the position of the bus stop on the corresponding bus line can be determined according to the time information in the target GPS data. For example, if the time information in the target GPS data of the bus stop 1 is earlier than the time information in the target GPS data of the bus stop 2, it can be determined that the bus stop 1 is before the bus stop 2 in the traveling direction of the bus.
Further, the bus GPS data also comprises angle information. Alternatively, the angle information may be an angle between a straight line of the current position and the set position and a north direction of the set position.
Optionally, the first station set may further include a station direction of each bus station. If one bus route only corresponds to one bus and the bus GPS data of each bus in the preset time period only corresponds to one effective bus route track, the geographic information and the angle information in the target GPS data can be used as the first geographic information and the stop direction of the bus stop.
If the bus GPS data in the preset time period corresponding to one bus route corresponds to a plurality of effective bus route tracks, the first geographic information of each bus stop included in each bus route can be obtained through a spatial clustering method and a plurality of target GPS data corresponding to the same bus stop on the same bus route. Optionally, an average value of geographic information in a plurality of target GPS data corresponding to the same bus stop on the same bus line may be used as the first geographic information of the bus stop. The station direction of each bus station can be obtained by obtaining angle information from a plurality of target GPS data corresponding to the same bus station on the same bus line by using a linear direction average value method. The first geographic information of the bus stops in the first stop set can be sorted according to the extending direction of the bus route.
Referring to fig. 6, fig. 6 is a flowchart illustrating sub-steps included in step S130 in fig. 2. The sub-step S130 may include a sub-step S131 and a sub-step S132.
And a substep S131, determining adjacent bus stops according to the first stop set, and matching first geographic information of the adjacent bus stops and bus GPS data of track points between the adjacent bus stops with geographic information of road sections in the target city road network to obtain a road section matching result of the track between the adjacent bus stops.
In this embodiment, after the first station set is obtained, since the first geographic information in the first station set is sorted according to the extending direction of the bus route, the adjacent station can be determined based on the first station set. And then matching the first geographic information of the adjacent stops and the geographic information in the bus GPS data of the track points between the adjacent stops with the geographic information of each road section in the target city road network, thereby obtaining a road section matching result of the track between the adjacent bus stops. And the road section matching result comprises geographic information of a target road section corresponding to the track between the adjacent bus stops. And the geographic information in the road section matching result is the geographic information of the target road section in the target city road network. By repeating the above process, the geographic information of the target road section corresponding to the track between all adjacent bus stops in each bus route can be obtained, so that the geographic information of the target road section included in each bus route is obtained.
And a substep S132 of adjusting the first geographic information of the bus stop through neighbor analysis according to the road section matching result of the track between each adjacent bus stop of each bus line and the stop direction of each bus stop to obtain the second geographic information of the bus stop.
In this embodiment, the first geographic information of the bus stop can be directly used as the second geographic information, and the first geographic information can also be adjusted, so that the second geographic information of the bus stop is obtained. Optionally, second geographic information of the bus stop can be obtained through neighbor analysis based on a road section matching result of a track between adjacent bus stops of each bus line, the stop direction of the bus stop and the first geographic information of the bus stop. Therefore, the situation that the obtained geographic information of the bus stop is inconsistent with the actual situation can be avoided.
Meanwhile, according to the time information in the bus GPS data for obtaining the bus network model, the time corresponding to the bus network model can be determined, so that the bus network model corresponding to the proper time can be selected conveniently in the follow-up process according to the requirement. For example, if the latest bus network model needs to be used, the latest bus network model can be determined by comparing the respective corresponding times of the existing bus network models.
In order to execute the corresponding steps in the foregoing embodiment and various possible manners, an implementation manner of the automatic bus network model generation apparatus 200 is given below, and optionally, the automatic bus network model generation apparatus 200 may adopt the device structure of the electronic device 100 shown in fig. 1. Further, referring to fig. 7, fig. 7 is a block schematic diagram of an automatic generating apparatus 200 for a bus network model according to an embodiment of the present application. It should be noted that the basic principle and the generated technical effect of the automatic generation device 200 for a bus network model provided in the present embodiment are the same as those of the above embodiments, and for the sake of brief description, no part of the present embodiment is mentioned, and reference may be made to the corresponding contents in the above embodiments. The automatic generation device 200 for the public transportation network model may include: an obtaining module 210, a first processing module 220, and a second processing module 230.
The obtaining module 210 is configured to obtain a target city road network.
The first processing module 220 is configured to obtain bus GPS data of each bus in the target city, and obtain a first stop set of each bus route according to the bus GPS data of each bus corresponding to each bus route. The bus GPS data comprises geographic information, and the first stop set comprises first geographic information of bus stops included in a bus line.
The second processing module 230 is configured to match the bus GPS data of each bus corresponding to each bus route and the first station set of the bus route with the road network of the target city, to obtain the bus route station information of each bus route, so as to serve as a bus network model of the target city. The bus route station information comprises a target road section set and a second station set corresponding to the bus route, the target road section set comprises geographic information of target road sections included by the bus route, the geographic information of the target road sections is distributed according to the extending direction of the bus route, and the second station set comprises second geographic information of the bus stations distributed according to the extending direction of the bus route.
Optionally, in this embodiment, each bus GPS data corresponds to one track point, the bus GPS data further includes angle information, and the first station set further includes a station direction of a bus station.
The first processing module 220 is specifically configured to: and obtaining the station direction of each bus station by using a linear direction average value method according to the angle information of each bus station.
The second processing module 230 is specifically configured to: determining adjacent bus stops according to the first stop set, and matching first geographic information of the adjacent bus stops and bus GPS data of track points between the adjacent bus stops with geographic information of road sections in the target urban road network to obtain road section matching results of tracks between the adjacent bus stops, wherein the road section matching results comprise geographic information of target road sections corresponding to the tracks between the adjacent bus stops; and adjusting the first geographic information of the bus stop through neighbor analysis according to the road section matching result of the track between the adjacent bus stops of each bus line and the stop direction of each bus stop to obtain the second geographic information of the bus stop.
Alternatively, the modules may be stored in the memory 110 shown in fig. 1 in the form of software or Firmware (Firmware) or be fixed in an Operating System (OS) of the electronic device 100, and may be executed by the processor 120 in fig. 1. Meanwhile, data, codes of programs, and the like required to execute the above-described modules may be stored in the memory 110.
The embodiment of the application also provides a readable storage medium, wherein a computer program is stored on the readable storage medium, and when the computer program is executed by a processor, the automatic generation method of the public transportation network model is realized.
In summary, the embodiment of the application provides a method and a device for automatically generating a bus network model and electronic equipment. Firstly, acquiring the public traffic GPS data of a road network of a target city and each bus in the target city, wherein the public traffic GPS data comprises geographic information. And then, obtaining a first station set of each bus route according to the bus GPS data of each bus corresponding to each bus route. The first stop set comprises first geographic information of bus stops included in the bus lines. And finally, matching the bus GPS data of each bus corresponding to each bus line and the first station set of the bus line with the road network of the target city to obtain the geographic information of the target road section and the second geographic information of the bus station included in each bus line so as to serve as the bus network model of the target city. Therefore, the public transportation network model of the target city can be automatically obtained without a large amount of manual work, batch operation can be realized, and the method has the characteristics of high efficiency, high precision, clear logic, strong universality, wide application range and the like.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A method for automatically generating a public transportation network model is characterized by comprising the following steps:
obtaining a target city road network;
the method comprises the steps of obtaining bus GPS data of each bus in a target city, and obtaining a first stop set of each bus line according to the bus GPS data of each bus corresponding to each bus line, wherein the bus GPS data comprises geographic information, and the first stop set comprises first geographic information of bus stops included by the bus lines;
the method comprises the steps of matching bus GPS data of each bus corresponding to each bus line and a first stop set of the bus line with a target city road network to obtain bus line stop information of each bus line, wherein the bus line stop information is used as a bus network model of the target city, the bus line stop information comprises a target road section set and a second stop set corresponding to the bus line, the target road section set comprises geographic information of a target road section included by the bus line, the geographic information of the target road section is distributed according to the extending direction of the bus line, and the second stop set comprises second geographic information of bus stops distributed according to the extending direction of the bus line.
2. The method as claimed in claim 1, wherein obtaining the first station set of each bus route according to the bus GPS data of each bus corresponding to each bus route comprises:
preprocessing bus GPS data of each bus within a preset time period to obtain processed bus GPS data, wherein the bus GPS data also comprises time information and station entering and exiting information, and the bus GPS data of each bus within the preset time period corresponds to a plurality of effective bus route tracks;
extracting target GPS data from the processed bus GPS data according to the station entering and exiting information, wherein the target GPS data comprises bus GPS data corresponding to station entering and bus GPS data corresponding to station exiting;
and generating a first stop set of each bus line through a spatial clustering method based on the target GPS data corresponding to each bus line, wherein the first geographic information of the bus stops in the first stop set is sorted according to the extending direction of the bus lines.
3. The method according to claim 2, wherein the pre-processing the bus GPS data of each bus within a preset time period to obtain the processed bus GPS data comprises:
carrying out data cleaning on bus GPS data of each bus within a preset time period;
and performing difference completion on the bus GPS data after data cleaning, and extracting bus GPS data of an effective bus route track from the bus GPS data after difference completion to obtain the processed bus GPS data.
4. The method according to claim 2, wherein each bus GPS data corresponds to a track point, the bus GPS data further comprises angle information, the first station set further comprises station directions of bus stations,
the method comprises the following steps of obtaining a first station set of each bus route according to bus GPS data of each bus corresponding to each bus route, and further comprising:
obtaining the station direction of each bus station by using a linear direction average value method according to the angle information of each bus station;
the method for matching the bus GPS data of each bus corresponding to each bus line and the first stop set of the bus line with the target city road network to obtain the bus line stop information of each bus line comprises the following steps:
determining adjacent bus stops according to the first stop set, and matching first geographic information of the adjacent bus stops and bus GPS data of track points between the adjacent bus stops with geographic information of road sections in the target urban road network to obtain road section matching results of tracks between the adjacent bus stops, wherein the road section matching results comprise geographic information of target road sections corresponding to the tracks between the adjacent bus stops;
and adjusting the first geographic information of the bus stop through neighbor analysis according to the road section matching result of the track between the adjacent bus stops of each bus line and the stop direction of each bus stop to obtain the second geographic information of the bus stop.
5. The method according to any one of claims 1-4, wherein said obtaining a target urban road network comprises:
obtaining an original city road network topology;
according to a target coordinate system used by the bus GPS data, carrying out coordinate system conversion on the original city road network topology to obtain a first road network topology based on the target coordinate system;
and checking and adjusting the first road network topology according to a preset topology rule to obtain a second road network topology, wherein the checking comprises checking whether roads are overlapped, whether the roads are intersected automatically, whether the roads are connected, whether the roads are interrupted and checking traffic management measures, and the checking of the traffic management measures comprises checking whether a single road exists, forbidding to pass and forbidding to left.
6. The method of claim 5, wherein obtaining a target urban road network further comprises:
and carrying out road section merging processing on the second road network topology according to the road section merging rule to obtain a third road network topology.
7. An automatic generation device of a public transportation network model is characterized in that the device comprises:
the acquisition module is used for acquiring a target city road network;
the first processing module is used for obtaining bus GPS data of each bus in a target city and obtaining a first stop set of each bus line according to the bus GPS data of each bus corresponding to each bus line, wherein the bus GPS data comprises geographic information, and the first stop set comprises first geographic information of bus stops included by the bus lines;
the second processing module is used for matching the bus GPS data of each bus corresponding to each bus line and the first stop set of the bus line with the road network of the target city to obtain the bus line stop information of each bus line, and the bus line stop information is used as a bus network model of the target city, wherein the bus line stop information comprises a target road section set and a second stop set corresponding to the bus line, the target road section set comprises the geographic information of the target road section included by the bus line, the geographic information of the target road section is distributed according to the extending direction of the bus line, and the second stop set comprises the second geographic information of the bus stops distributed according to the extending direction of the bus line.
8. The device of claim 7, wherein each bus GPS data corresponds to a track point, the bus GPS data further comprises angle information, the first station set further comprises station directions of bus stations,
the first processing module is specifically configured to:
obtaining the station direction of each bus station by using a linear direction average value method according to the angle information of each bus station;
the second processing module is specifically configured to:
determining adjacent bus stops according to the first stop set, and matching first geographic information of the adjacent bus stops and bus GPS data of track points between the adjacent bus stops with geographic information of road sections in the target urban road network to obtain road section matching results of tracks between the adjacent bus stops, wherein the road section matching results comprise geographic information of target road sections corresponding to the tracks between the adjacent bus stops;
and adjusting the first geographic information of the bus stop through neighbor analysis according to the road section matching result of the track between the adjacent bus stops of each bus line and the stop direction of each bus stop to obtain the second geographic information of the bus stop.
9. An electronic device comprising a processor and a memory, the memory storing machine executable instructions executable by the processor to implement the method of automatically generating a bus network model of any of claims 1-6.
10. A readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method for automatic generation of a bus network model according to any one of claims 1 to 6.
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