CN111143955A - Method and system for acquiring urban road network topological connection edge weight - Google Patents
Method and system for acquiring urban road network topological connection edge weight Download PDFInfo
- Publication number
- CN111143955A CN111143955A CN201911307303.7A CN201911307303A CN111143955A CN 111143955 A CN111143955 A CN 111143955A CN 201911307303 A CN201911307303 A CN 201911307303A CN 111143955 A CN111143955 A CN 111143955A
- Authority
- CN
- China
- Prior art keywords
- road network
- weight
- urban road
- obtaining
- representing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000005070 sampling Methods 0.000 claims description 12
- 238000012545 processing Methods 0.000 abstract description 2
- 238000007405 data analysis Methods 0.000 description 3
- 238000010276 construction Methods 0.000 description 2
- 238000005034 decoration Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Traffic Control Systems (AREA)
Abstract
The application provides a method and a system for acquiring urban road network topological connection edge weight, and relates to the field of data processing. The acquisition method comprises the following steps: acquiring a connecting edge for constructing a topological graph of an urban road network of a region to be discovered; extracting the track data of the moving object in the connecting edge, and obtaining the track data and a preset weight formula
Obtaining the weight of each time section, wherein CtiRepresenting the number of moving objects in the current time period, CmaxRepresenting the maximum number of moving objects, C, throughout the dayminRepresenting the minimum number of moving objects throughout the day. Topological graph capable of conveniently and quickly acquiring urban trajectory dataAnd weights of different time periods of the middle connecting side are connected, so that a topological graph of the urban trajectory data is drawn quickly.
Description
Technical Field
The application belongs to the field of data processing, and particularly relates to a method and a system for acquiring urban road network topological connection edge weights.
Background
At present, along with the development of cities, the number of people and motor vehicles also increases rapidly, the increased people and vehicles increase the pressure on traffic traveling, and the prior art has no technical scheme for effectively solving the traffic traveling pressure. The trace data analysis is a new research direction, and the travel habits of people and the pedestrian volume of each street can be known through the trace data analysis. However, the trajectory data analysis is not yet effectively applied to the problem solution of the travel.
Disclosure of Invention
The embodiment of the invention mainly aims to provide a method for acquiring the directions of topological connecting edges of an urban road network.
In a first aspect, a method for obtaining urban road network topology connection edge weight is provided, including:
acquiring a connecting edge for constructing a topological graph of an urban road network of a region to be discovered;
extracting the connecting edge shiftThe track data of the moving object is obtained according to the track data and a preset weight formula
Obtaining the weight of each time section, wherein CtiRepresenting the number of moving objects in the current time period, CmaxRepresenting the maximum number of moving objects, C, throughout the dayminRepresenting the minimum number of moving objects throughout the day.
In one possible implementation, the trajectory data includes: sampling point position, sampling time and sampling speed.
In another possible implementation, the mobile object includes: human, automotive, non-automotive.
In yet another possible implementation, the Cmax、CminAnd obtaining by comparing the track data in the urban road network data.
In a second aspect, a system for obtaining a weight of a topological connecting edge of an urban road network is provided, which includes:
the acquisition module is used for acquiring a connecting edge for constructing a topological graph of the urban road network of the area to be discovered;
a weight obtaining module for extracting the track data of the moving object in the connecting edge and obtaining the weight of the moving object according to the track data and a preset weight formula
Obtaining the weight of each time section, wherein CtiRepresenting the number of moving objects in the current time period, CmaxRepresenting the maximum number of moving objects, C, throughout the dayminRepresenting the minimum number of moving objects throughout the day.
In one possible implementation, the trajectory data includes: sampling point position, sampling time and sampling speed.
In yet another possible implementation, the mobile object includes: human, automotive, non-automotive.
In yet another possible implementationSaid C ismax、CminAnd obtaining by comparing the track data in the urban road network data.
The beneficial effect that technical scheme that this application provided brought is: the weights of different time periods of the connecting edges in the topological graph of the urban trajectory data can be conveniently and quickly obtained, and then the topological graph of the urban trajectory data can be quickly drawn.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below.
Fig. 1 is a flowchart of a method for obtaining a topological connection edge weight of an urban road network according to an embodiment of the present invention;
fig. 2 is a structural diagram of a system for acquiring a topological connection edge weight of an urban road network according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar modules or modules having the same or similar functionality throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, modules, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, modules, components, and/or groups thereof. It will be understood that when a module is referred to as being "connected" or "coupled" to another module, it can be directly connected or coupled to the other module or intervening modules may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
The technical solutions of the present application and the technical solutions of the present application, for example, to solve the above technical problems, will be described in detail with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Example one
Fig. 1 is a flowchart of a method for obtaining a topological connection edge weight of an urban road network according to an embodiment of the present invention, including:
step S101, obtaining a connecting edge for constructing a topological graph of the urban road network of the region to be discovered.
In the embodiment of the invention, in the construction process of the urban road network topological graph, the key nodes represent intersections of roads, the connecting edges are road segments used for representing the connection of the two key nodes, and the connecting edges represent that a moving object moves from one end point of the connecting edges to the other end point.
Step S102, extracting the track data of the moving object in the connecting edge, and according to the track data and a preset weight formula
Obtaining the weight of each time section, wherein CtiRepresenting the number of moving objects in the current time period, CmaxRepresenting the maximum number of moving objects, C, throughout the dayminRepresenting the minimum number of moving objects throughout the day.
In the embodiment of the invention, a formula is set
To obtain a weight for each time segment, wherein CtiNumber of moving objects for current time period, CmaxFor the maximum number of moving objects throughout the day, CminC in the data is the minimum number of moving objects in the whole time of the daytiCan be retrieved directly from the raw data, Cmax、CminThe method comprises the steps of comparing track data in vehicle road network data to obtain the track data. The weight of one connecting side can be calculated through the formula, and all the connecting sides are sequentially calculated until the weights of all the connecting sides are calculated.
It should be noted that the mobile object includes, but is not limited to: human, automotive, non-automotive.
According to the embodiment of the invention, the connecting edges for constructing the urban road network topological graph of the to-be-discovered region are obtained, the track data of the moving object in the connecting edges are extracted, and the weight of each time period is obtained according to the track data and the preset weight formula. The system can conveniently and quickly acquire the weights of different time periods of the connecting edges in the topological graph of the urban trajectory data, and then the topological graph of the urban trajectory data can be quickly drawn.
Example two
Fig. 2 is a structural diagram of a system for acquiring a topological connection edge weight of an urban road network according to an embodiment of the present invention, where the system includes:
an obtaining module 201, configured to obtain a connecting edge for constructing a topological graph of an urban road network of a to-be-discovered region.
In the embodiment of the invention, in the construction process of the urban road network topological graph, the key nodes represent intersections of roads, the connecting edges are road segments used for representing the connection of the two key nodes, and the connecting edges represent that a moving object moves from one end point of the connecting edges to the other end point.
A weight obtaining module 202, configured to extract trajectory data of the moving object in the connected edges, according to the trajectory data and a preset weight formula
Obtaining the weight of each time section, wherein CtiRepresenting the number of moving objects in the current time period, CmaxRepresenting the maximum number of moving objects, C, throughout the dayminRepresenting the minimum number of moving objects throughout the day.
In the embodiment of the invention, a formula is set
To obtain a weight for each time segment, wherein CtiNumber of moving objects for current time period, CmaxFor the maximum number of moving objects throughout the day, CminC in the data is the minimum number of moving objects in the whole time of the daytiCan be retrieved directly from the raw data, Cmax、CminThe method comprises the steps of comparing track data in vehicle road network data to obtain the track data. The weight of one connecting side can be calculated through the formula, and all the connecting sides are sequentially calculated until the weights of all the connecting sides are calculated.
It should be noted that the mobile object includes, but is not limited to: human, automotive, non-automotive.
According to the embodiment of the invention, the connecting edges for constructing the urban road network topological graph of the to-be-discovered region are obtained, the track data of the moving object in the connecting edges are extracted, and the weight of each time period is obtained according to the track data and the preset weight formula. The system can conveniently and quickly acquire the weights of different time periods of the connecting edges in the topological graph of the urban trajectory data, and then the topological graph of the urban trajectory data can be quickly drawn.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The foregoing is only a partial embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (8)
1. A method for acquiring the weight of a topological connecting edge of an urban road network is characterized by comprising the following steps:
acquiring a connecting edge for constructing a topological graph of an urban road network of a region to be discovered;
extracting the track data of the moving object in the connecting edge, and obtaining the track data and a preset weight formula
Obtaining the weight of each time section, wherein CtiRepresenting the number of moving objects in the current time period, CmaxRepresenting the maximum number of moving objects, C, throughout the dayminRepresenting the minimum number of moving objects throughout the day.
2. The acquisition method as set forth in claim 1, wherein the trajectory data includes: sampling point position, sampling time and sampling speed.
3. The acquisition method as set forth in claim 1, wherein the moving object includes: human, automotive, non-automotive.
4. The method for obtaining as claimed in any of claims 1 to 3, wherein C ismax、CminAnd obtaining by comparing the track data in the urban road network data.
5. A system for acquiring urban road network topology connection edge weight is characterized by comprising:
the acquisition module is used for acquiring a connecting edge for constructing a topological graph of the urban road network of the area to be discovered;
a weight obtaining module for extracting the track data of the moving object in the connecting edge and obtaining the weight of the moving object according to the track data and a preset weight formula
Obtaining the weight of each time section, wherein CtiRepresenting the number of moving objects in the current time period, CmaxRepresenting the maximum number of moving objects, C, throughout the dayminRepresenting the minimum number of moving objects throughout the day.
6. The acquisition system as set forth in claim 5, wherein the trajectory data comprises: sampling point position, sampling time and sampling speed.
7. The acquisition system as set forth in claim 5, wherein the moving object comprises: human, automotive, non-automotive.
8. The acquisition system as set forth in any one of claims 5 to 7, wherein C ismax、CminAnd obtaining by comparing the track data in the urban road network data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911307303.7A CN111143955A (en) | 2019-12-18 | 2019-12-18 | Method and system for acquiring urban road network topological connection edge weight |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911307303.7A CN111143955A (en) | 2019-12-18 | 2019-12-18 | Method and system for acquiring urban road network topological connection edge weight |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111143955A true CN111143955A (en) | 2020-05-12 |
Family
ID=70518720
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911307303.7A Pending CN111143955A (en) | 2019-12-18 | 2019-12-18 | Method and system for acquiring urban road network topological connection edge weight |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111143955A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101373559A (en) * | 2007-08-24 | 2009-02-25 | 同济大学 | Method for evaluating city road net traffic state based on floating vehicle data |
| CN104392094A (en) * | 2014-10-17 | 2015-03-04 | 北京航空航天大学 | Reliability evaluation method of urban road network based on data of floating vehicles |
| CN105427581A (en) * | 2015-11-16 | 2016-03-23 | 北京科技大学 | Traffic simulation method and traffic simulation system based on floating car data |
| CN109190056A (en) * | 2018-08-22 | 2019-01-11 | 深圳先进技术研究院 | A kind of track of vehicle method for reconstructing, system and electronic equipment |
| CN110111575A (en) * | 2019-05-16 | 2019-08-09 | 北京航空航天大学 | A kind of Forecast of Urban Traffic Flow network analysis method based on Complex Networks Theory |
-
2019
- 2019-12-18 CN CN201911307303.7A patent/CN111143955A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101373559A (en) * | 2007-08-24 | 2009-02-25 | 同济大学 | Method for evaluating city road net traffic state based on floating vehicle data |
| CN104392094A (en) * | 2014-10-17 | 2015-03-04 | 北京航空航天大学 | Reliability evaluation method of urban road network based on data of floating vehicles |
| CN105427581A (en) * | 2015-11-16 | 2016-03-23 | 北京科技大学 | Traffic simulation method and traffic simulation system based on floating car data |
| CN109190056A (en) * | 2018-08-22 | 2019-01-11 | 深圳先进技术研究院 | A kind of track of vehicle method for reconstructing, system and electronic equipment |
| CN110111575A (en) * | 2019-05-16 | 2019-08-09 | 北京航空航天大学 | A kind of Forecast of Urban Traffic Flow network analysis method based on Complex Networks Theory |
Non-Patent Citations (3)
| Title |
|---|
| 唐炉亮等: "基于GPS时空轨迹的路网拓扑自动变化检测", 《武汉大学学报(信息科学版)》 * |
| 蒋新华 等: "基于浮动车数据的道路单向限行状态动态识别", 《计算机应用》 * |
| 闫文彩等: "基于复杂网络的城市路网可靠性分析", 《山东科学》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108955693B (en) | Road network matching method and system | |
| CN103413437B (en) | Method and system for identifying road intersection steering based on vehicle data collection | |
| CN106197458B (en) | A kind of mobile phone user's trip mode recognition methods based on mobile phone signaling data and navigation route data | |
| CN103226892B (en) | A kind of road congestion state discovery method of Optimization-type | |
| WO2017084221A1 (en) | Method and apparatus for acquiring traffic state | |
| CN102024325B (en) | Traffic jam point identification method based on floating car technology | |
| CN103942969B (en) | Right-hand lane turning crossing dynamic traffic signal control method borrowed by left-hand rotation motor vehicles | |
| CN105809962A (en) | Traffic trip mode splitting method based on mobile phone data | |
| CN103079270B (en) | A kind of mobile node based on wireless location assembles cognitive method | |
| CN104156524A (en) | Aggregate query method and system for traffic data flows | |
| CN103714708A (en) | Optimal path planning method based on split-time experience path of taxi | |
| CN102708698A (en) | Vehicle optimal-path navigation method based on vehicle internet | |
| CN1707544A (en) | Method for estimating city road network traffic flow state | |
| CN105551082A (en) | Method and device of pavement identification on the basis of laser-point cloud | |
| CN103632540A (en) | An urban main road traffic operation information processing method based on floating vehicle data | |
| CN104978858A (en) | Highway real-time traffic monitoring method based on mobile phone signaling | |
| CN103680130B (en) | A kind ofly obtain lead the way expert's method of region based on floating car technology | |
| CN107393301B (en) | A kind of track of vehicle recognition methods based on RFID data | |
| CN101989381A (en) | Method for road one-way restriction and traffic state identification based on floating car technology | |
| CN105608895A (en) | Local abnormity factor-based urban heavy-traffic road detection method | |
| CN109520499B (en) | Method for realizing regional real-time isochrones based on vehicle GPS track data | |
| CN114529081A (en) | Space-time combined traffic flow prediction method and device | |
| CN106447138A (en) | Electronic map travelling time calculation method based on velocity matrix | |
| CN111145540B (en) | Method and system for discovering topological connecting edges of urban road network | |
| CN104504245A (en) | Method of utilizing GPS trip survey data to identify trips and activities |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200512 |
|
| RJ01 | Rejection of invention patent application after publication |