CN108495254A - A kind of traffic zone population characteristic's method of estimation based on signaling data - Google Patents
A kind of traffic zone population characteristic's method of estimation based on signaling data Download PDFInfo
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- 238000004364 calculation method Methods 0.000 claims description 4
- 238000013480 data collection Methods 0.000 claims description 3
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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- 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
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- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
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- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/535—Tracking the activity of the user
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/35—Services specially adapted for particular environments, situations or purposes for the management of goods or merchandise
Abstract
Traffic zone population characteristic's method of estimation based on signaling data that the invention discloses a kind of, includes the following steps：(1) residential subscribers in each cellular base station service range are obtained based on mobile phone signaling data；(2) the residential subscribers' information got is matched with the user information of operator, obtains the personal information of residential subscribers in each cellular base station coverage area；(3) residential subscribers' personal information corresponding to cellular base station that step (2) is obtained is converted to traffic zone residential subscribers' characteristic information by the correspondence based on cellular base station and traffic zone.The present invention can utilize Mobile Network Operator data, without extras, obtain traffic zone population characteristic's information necessary to traffic programme.
Description
Technical field
The present invention relates to traffic big data technical field, especially a kind of traffic zone population characteristic based on signaling data
Method of estimation.
Background technology
Traffic programme Four-stage Method is drawn based on resident trip survey by Trip generation forecast, traffic distribution, mode of transportation
Divide, Traffic growth rate four-stage composition.Resident trip survey is the basic data of traffic programme, between traditional investigation method is
Every the trip survey that several years carry out questionnaire type, sampling rate is relatively low and needs to expend a large amount of manpower and materials and time cost, and
And due to the limitation of sample size and memory accuracy, obtained result cannot meet analysis demand.With data acquisition technology
Continue to develop, traffic study data source gradually from traditional questionnaire, coil to radar, microwave detector, bayonet, GPS Floating Cars,
The development such as electronic tag.These detectors needs install equipment on road, need to buy special equipment, and need in road
Road is constructed, and is spent human and material resources.In addition, traditional method is for statistical analysis from macroscopic perspective to resident, result
It is affected by the method for sampling, survey mode etc., effect is poor, it is difficult to obtain accurate information.
Since 21 century, mobile network's coverage rate is more and more wider, and mobile phone terminal becomes basically universal.By 2016, China moved
Mobile phone user reaches 13.2 hundred million, and the time span of huge user base number and data in mobile phone provides good for information collection
Basis.Data in mobile phone includes large-scale time and spatial information, rationally utilizes these data, for characterizing traffic circulation shape
State, assessment means of transportation and Policy Effect and traffic administration aid decision important role.In addition, the real name of mobile phone user
Registration policy processed so that the information such as age-sex of user are accurately recorded.However, due to mobile phone signaling data and user
Information includes the individual privacy informations such as phone, the position of user, cannot be directly applied.
The important references feature that traffic zone resident diagnostics is distributed as traffic in traffic programme Four-stage Method, has important
Meaning.Field of traffic is in addition to traditional questionnaire survey is there are no the extraction that other methods are applied to traveler personal characteristics at present,
Cell phone carrier quotient data to extract traveler feature, analysis travel behaviour.The present invention excavates data in mobile phone value,
Its advantage in sample size and accuracy is given full play to, trip survey labor intensive, material resources, time and dependence is compensated for and is adopted
Visit person remembers the defect of accuracy；Focus on, to the secrecy of individual information, personal information collection being calculated as traffic zone group simultaneously
Information avoids leakage privacy of user, to provide a kind of new data capture method for traffic programme.
Invention content
Technical problem to be solved by the present invention lies in provide a kind of traffic zone population characteristic based on signaling data and estimate
Meter method can utilize Mobile Network Operator data, without extras, obtain necessary to traffic programme
Traffic zone population characteristic's information.
In order to solve the above technical problems, the present invention provides a kind of traffic zone population characteristic estimation side based on signaling data
Method includes the following steps：
(1) residential subscribers in each cellular base station service range are obtained based on mobile phone signaling data；
(2) the residential subscribers' information got is matched with the user information of operator, obtains each cellular base station and covers
The personal information of residential subscribers within the scope of lid；
(3) correspondence based on cellular base station and traffic zone, corresponding to the cellular base station that step (2) is obtained
Residential subscribers' personal information is converted to traffic zone residential subscribers' characteristic information.
Preferably, in step (1), the tool of the residential subscribers in each cellular base station service range is obtained based on mobile phone signaling data
Body includes the following steps：
(11) survey region is chosen from Study dates continuous several days signaling datas forward, is inquired each base station and is rested daily
Period recorded data collection one；
(12) if in above-mentioned data set one, it is most of in one day record of user that certain user has the data of enough number of days to meet
Data recorded by same base station, then it is assumed that the user inhabits in the base station service range.
Preferably, in step (2), residential subscribers' personal information acquisition methods are in cellular base station coverage area：According to base
It stands the number of residential subscribers, counting user APP is obtained using the underlying table of the information such as preference and correlation inquiry gender containing age of user
Preference information is used to user's gender, age, occupational group and APP.
Preferably, in step (3), the correspondence based on cellular base station and traffic zone, the hand that step (2) is obtained
Residential subscribers' personal information corresponding to machine base station is converted to traffic zone residential subscribers' characteristic information, specifically includes following step
Suddenly：
(31) it is polygon to export its Tyson using base station as input point using establishment Thiessen polygon tool in ArcGIS
Shape region, these regions indicate any of which position to the distance of its relating dot all than the distance to any other point input element
Close whole region, the service range of each base station are its Thiessen polygon region, and any position is to its association base in the region
The distance stood is all closer than the distance to any other base station；
(32) base station C is setiThe Thiessen polygon serviced is Ti, with Thiessen polygon region TiThere is the traffic zone of overlapping
ForP is user property in survey region；Wherein base station CiService multiple traffic zones, i.e. TiWith traffic zoneThere is intersection；
Meanwhile traffic zone ZjIt is serviced by multiple base stations, i.e. traffic zone ZjBy multiple Thiessen polygonsSegmentation；
The overlapping relation of calculation base station service range and traffic zone obtains base station CiThe X traffic zone serviced
And respective shared ratioThen traffic zone ZjCertain properties user numberEqual to the attribute sum of its Y part
It is equal to place Thiessen polygon own base station total number of persons and its proportion with the attribute number of, Y partMultiply
Product；Circular is：
Wherein,
Traffic zone ZaWith Thiessen polygon TbThe part of overlapping；
Thiessen polygon TaWith traffic zone ZbThe part of overlapping；
With Thiessen polygon TbHave in all traffic zones of overlapping,Area account for all lap areas and
Ratio；
Base station CnThe number of users of certain generic attribute；
X：The intersection for all traffic zones that certain base station is serviced；
Y：Certain traffic zone is by the intersection of different Thiessen polygon partitioning portions；
S：Region area.
Preferably, in step (31), the irregular triangle network for meeting Delaunay criterion, triangle are marked off in all the points
Shape it is each while perpendicular bisector can be formed Thiessen polygon while, the intersection point of each bisector determines the position of Thiessen polygon break
It sets.
Beneficial effects of the present invention are：The present invention obtains user's residential quarter information and population characteristic using signaling data,
It is compared with traditional manual research method, saves a large amount of manpower and materials and the time cost needed for survey of organization, and can avoid
The mistake caused by the memory error of surveyee, accuracy higher；Signaling data sample size is big, and submits number without user
According to covering user is comprehensive；In addition, collection counts user information as unit of traffic zone, of single user is free of in final result
People's information, the effective protection sensibility of individual privacy and single user's data；Using Mobile Network Operator data, without
In the case of extras, traffic zone population characteristic's information necessary to traffic programme is obtained.
Description of the drawings
Fig. 1 is the method flow schematic diagram of the present invention.
Fig. 2 is cellular base station residential subscribers' recognition methods schematic diagram of the present invention.
Fig. 3 is the base station service range Thiessen polygon example schematic diagram of the present invention.
Fig. 4 is the Thiessen polygon and traffic zone matching relationship schematic diagram of the present invention.
Specific implementation mode
As shown in Figure 1, a kind of traffic zone population characteristic's method of estimation based on signaling data, includes the following steps：
(1) residential subscribers in each cellular base station service range are obtained based on mobile phone signaling data；
(2) the residential subscribers' information got is matched with the user information of operator, obtains each cellular base station and covers
The personal information of residential subscribers within the scope of lid；
(3) correspondence based on cellular base station and traffic zone, corresponding to the cellular base station that step (2) is obtained
Residential subscribers' personal information is converted to traffic zone residential subscribers' characteristic information.
A kind of traffic zone population characteristic's method of estimation based on signaling data of the present invention, as shown in Figure 1, this method packet
It includes：
1,4G signaling datas, base station information, mobile phone user APP usage records and the traffic zone letter of survey region are obtained
Breath.
Wherein, the 4G signaling datas include the information for studying 30 days a few days ago, may include Customs Assigned Number, base station volume
Number, signal forming time etc..Wherein, the Customs Assigned Number can use IMSI number, telephone number etc. to have identification function
Information.
Wherein, the base station information may include base station number, base station name, latitude and longitude of base station etc..
Wherein, mobile phone user's APP usage records may include Customs Assigned Number, APP titles, APP usage times,
APP uses flow etc..
Wherein, the traffic zone information may include traffic zone title, traffic zone number, traffic zone position
It sets, traffic zone shape etc..
2, it is matched with base station information based on the 4G signaling datas got, obtains the residence in cellular base station service range
Live in user.
Wherein, the residential subscribers of the cellular base station may include base station number, position, Customs Assigned Number etc..
Wherein, the implementation method of the residential subscribers of the cellular base station, as shown in Fig. 2, specifically including：
21, survey region is chosen from Study dates continuous 30 days signaling datas forward, inquires daily 24 points of each base station extremely
7 recorded data collection one of next day；
If 22, in above-mentioned data set one, certain user has 20 day datas to meet condition 1 in 30 days), then it is assumed that the user lives
In in the base station service range.
Condition 1) in one day record of user, 70% data are recorded by same base station.
23, collection meter is carried out to the residential subscribers of all base stations in research range, obtains owning in each base station service range
Residential subscribers.
3, the corresponding residential subscribers of the cellular base station got and provider customer's information and APP are carried out using data
Matching, obtains cellular base station residential subscribers' personal characteristics.
Wherein, cellular base station residential subscribers personal information may include：Gender, age, occupational group and APP use preference
Deng.
Wherein, in the cellular base station coverage area personal characteristics of residential subscribers implementation method, specifically include：
31, according to the number of the base station residential subscribers, association operator phone user information generates traffic zone population
The essential attributes such as gender, age, occupation.
32, according to the number of the base station residential subscribers, associated AP P usage record data obtain user and use APP classes
Not, number, time.
33, as unit of cellular base station, collection meter is carried out to residential subscribers' information, each base station different attribute classification is obtained and lives
All kinds of APP numbers of users of the number of user and each base station and the frequency.
Wherein, different attribute classification residential subscribers may include：Gender, age bracket, occupational group etc..
4, according to cellular base station and traffic zone matching relationship, residential subscribers' personal characteristic information is distributed to corresponding and is handed over
Logical cell.
Wherein, residential subscribers' personal characteristic information accounts for the pro rate of base station service range to corresponding by corresponding traffic zone
Traffic zone.
Wherein, the cellular base station and traffic zone matching relationship method are as follows：
41, in ArcGIS using establishment Thiessen polygon tool its Thiessen polygon is exported using base station as input point
Region.These regions indicate that any of which position is all closer than to the distance of any other point input element to the distance of its relating dot
Whole region, in the present invention that is, the service range of each base station is its Thiessen polygon region, any position in the region
Distance to its association base station is all closer than the distance to any other base station.Such as Fig. 3, figure midpoint represents cellular base station, base sites
The enclosing of surrounding lines is Thiessen polygon.The specific steps are：
411 mark off the irregular triangle network (TIN) for meeting Delaunay criterion in all the points.
412 triangles it is each while perpendicular bisector can be formed Thiessen polygon while.The intersection point of each bisector determines safe
The position of gloomy polygon break.
42, the overlapping relation of calculation base station service range and traffic zone obtains all traffic zones that base station is serviced
And respective shared ratio.If base station CiThe Thiessen polygon serviced is Ti, with Thiessen polygon region TiThere is the traffic of overlapping
Cell isP is user property in survey region.Wherein base station CiService multiple traffic zones, i.e. TiWith traffic zoneIt is (false
Equipped with X) there is intersection；Meanwhile traffic zone ZjIt is serviced by multiple base stations, i.e. traffic zone ZjBy multiple Thiessen polygonsPoint
(assuming that there are Y) is cut, such as Fig. 4.
The overlapping relation of calculation base station service range and traffic zone obtains base station CiThe X traffic zone serviced
And respective shared ratio(m-th traffic zone area and involved whole X traffic zones area it
The ratio of sum is shown in formula (1)).Then traffic zone ZjCertain properties user numberEqual to the attribute sum of its Y part
It is equal to place Thiessen polygon own base station total number of persons and its proportion with the attribute number of, Y partMultiply
Product.Circular is：
Wherein,
Traffic zone ZaWith Thiessen polygon TbThe part of overlapping；
Thiessen polygon TaWith traffic zone ZbThe part of overlapping；
With Thiessen polygon TbHave in all traffic zones of overlapping,Area account for all lap areas and
Ratio；
Base station CnThe number of users of certain generic attribute；
X：The intersection for all traffic zones that certain base station is serviced；
Y：Certain traffic zone is by the intersection of different Thiessen polygon partitioning portions；
S：Region area.
The method provided by the invention for obtaining traffic zone resident population's feature, on the basis of not needing extras
Traffic zone population characteristic necessary to big traffic planning, can reduce manual operation amount, reduce cost, more efficient.
Claims (5)
1. a kind of traffic zone population characteristic's method of estimation based on signaling data, which is characterized in that include the following steps：
(1) residential subscribers in each cellular base station service range are obtained based on mobile phone signaling data；
(2) the residential subscribers' information got is matched with the user information of operator, obtains each cellular base station covering model
Enclose the personal information of interior residential subscribers；
(3) correspondence based on cellular base station and traffic zone, the inhabitation corresponding to cellular base station that step (2) is obtained
Userspersonal information is converted to traffic zone residential subscribers' characteristic information.
2. traffic zone population characteristic's method of estimation based on signaling data as described in claim 1, which is characterized in that step
(1) in, the residential subscribers in each cellular base station service range is obtained based on mobile phone signaling data and are specifically comprised the following steps：
(11) survey region is chosen from Study dates continuous several days signaling datas forward, inquires each base station daily rest period
Recorded data collection one；
(12) if in above-mentioned data set one, certain user has the data of enough number of days to meet most number in one day record of user
It is recorded according to by same base station, then it is assumed that the user inhabits in the base station service range.
3. traffic zone population characteristic's method of estimation based on signaling data as described in claim 1, which is characterized in that step
(2) in, residential subscribers' personal information acquisition methods are in cellular base station coverage area：According to the number of base station residential subscribers, system
User APP is counted using the underlying table of the information such as preference and correlation inquiry gender containing age of user, obtains user's gender, age, duty
Industry classification and APP use preference information.
4. traffic zone population characteristic's method of estimation based on signaling data as described in claim 1, which is characterized in that step
(3) in, the correspondence based on cellular base station and traffic zone, the inhabitation corresponding to cellular base station that step (2) is obtained
Userspersonal information is converted to traffic zone residential subscribers' characteristic information, specifically comprises the following steps：
(31) in ArcGIS using establishment Thiessen polygon tool its Thiessen polygon area is exported using base station as input point
Domain, these regions indicate any of which position to its relating dot distance all than to any other point input element distance closely
Whole region, the service range of each base station are its Thiessen polygon region, and any position is to its association base station in the region
Distance is all closer than the distance to any other base station；
(32) base station C is setiThe Thiessen polygon serviced is Ti, with Thiessen polygon region TiThere is the traffic zone of overlapping to beP
For user property in survey region；Wherein base station CiService multiple traffic zones, i.e. TiWith traffic zoneThere is intersection；Meanwhile it handing over
Logical cell ZjIt is serviced by multiple base stations, i.e. traffic zone ZjBy multiple Thiessen polygonsSegmentation；
The overlapping relation of calculation base station service range and traffic zone obtains base station CiThe X traffic zone servicedAnd respectively
Shared ratioThen traffic zone ZjCertain properties user numberEqual to the sum of the attribute sum of its Y part, Y
The attribute number of a part is equal to place Thiessen polygon own base station total number of persons and its proportionProduct；Specifically
Computational methods are：
Wherein,
Traffic zone ZaWith Thiessen polygon TbThe part of overlapping；
Thiessen polygon TaWith traffic zone ZbThe part of overlapping；
With Thiessen polygon TbHave in all traffic zones of overlapping,Area account for the ratios of all lap area sums
Example；
Base station CnThe number of users of certain generic attribute；
X：The intersection for all traffic zones that certain base station is serviced；
Y：Certain traffic zone is by the intersection of different Thiessen polygon partitioning portions；
S：Region area.
5. traffic zone population characteristic's method of estimation based on signaling data as described in claim 1, which is characterized in that step
(31) in, the irregular triangle network for meeting Delaunay criterion, the perpendicular bisector on each side of triangle are marked off in all the points
The side of Thiessen polygon can be formed, the intersection point of each bisector determines the position of Thiessen polygon break.
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| CN110136043A (en) * | 2019-05-17 | 2019-08-16 | 东南大学 | A kind of traffic zone estimation of population method based on position big data |
| CN111026738A (en) * | 2019-11-08 | 2020-04-17 | 福建新大陆软件工程有限公司 | Regional population monitoring method and system, electronic equipment and storage medium |
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| CN113423065A (en) * | 2021-08-25 | 2021-09-21 | 深圳市城市交通规划设计研究中心股份有限公司 | Method for determining population post data of traffic cell based on mobile phone signaling data |
| CN114037239A (en) * | 2021-10-29 | 2022-02-11 | 南京大学 | Potential model employment reachability analysis method based on multi-source big data |
| CN114139251A (en) * | 2021-11-14 | 2022-03-04 | 深圳市规划国土发展研究中心 | Integral layout method for land ports of border regions |
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| CN112566030A (en) * | 2020-12-08 | 2021-03-26 | 东南大学 | Mobile phone signaling data-based residence double-period identification method and application |
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| CN113423065A (en) * | 2021-08-25 | 2021-09-21 | 深圳市城市交通规划设计研究中心股份有限公司 | Method for determining population post data of traffic cell based on mobile phone signaling data |
| CN113423065B (en) * | 2021-08-25 | 2022-01-07 | 深圳市城市交通规划设计研究中心股份有限公司 | Method for determining population post data of traffic cell based on mobile phone signaling data |
| CN114037239A (en) * | 2021-10-29 | 2022-02-11 | 南京大学 | Potential model employment reachability analysis method based on multi-source big data |
| CN114139251A (en) * | 2021-11-14 | 2022-03-04 | 深圳市规划国土发展研究中心 | Integral layout method for land ports of border regions |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108495254B (en) | 2020-04-24 |
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