CN108495254B - Traffic cell population characteristic estimation method based on signaling data - Google Patents
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Abstract
The invention discloses a traffic cell population characteristic estimation method based on signaling data, which comprises the following steps: (1) acquiring residential users in the service range of each mobile phone base station based on the mobile phone signaling data; (2) matching the acquired resident user information with user information of an operator to obtain personal information of resident users in the coverage range of each mobile phone base station; (3) and (3) converting the personal information of the residential users corresponding to the mobile phone base station obtained in the step (2) into characteristic information of the residential users in the traffic cell based on the corresponding relationship between the mobile phone base station and the traffic cell. The invention can obtain the necessary traffic cell population characteristic information for traffic planning by using the mobile network operator data without additional equipment.
Description
Technical Field
The invention relates to the technical field of traffic big data, in particular to a traffic cell population characteristic estimation method based on signaling data.
Background
The traffic planning four-stage method is based on resident travel survey and comprises four stages of traffic generation, traffic distribution, traffic mode division and traffic volume distribution. Resident's trip survey is the basic data of traffic planning, and traditional investigation mode is to carry out the trip survey of questionnaire formula at intervals several years, and the sampling rate is lower and need consume a large amount of manpower and materials and time cost, moreover because the restriction of sample size and memory accuracy, the result that obtains can not satisfy the analysis demand. With the continuous development of data acquisition technology, traffic research data sources gradually develop from traditional questionnaires and coils to radars, microwave detectors, bayonets, GPS floating cars, electronic tags and the like. These detectors require installation of equipment on the road, require the purchase of specialized equipment, and require construction on the road, which is labor and material intensive. In addition, the traditional method carries out statistical analysis on residents from a macroscopic view, the result of the statistical analysis is greatly influenced by a sampling method, an investigation mode and the like, the effect is poor, and accurate information is difficult to obtain.
Since the 21 st century, mobile network coverage rate is becoming wider and wider, and mobile phone terminals are becoming popular basically. By 2016, China mobile phone users reach 13.2 hundred million, and a huge user base number and time span of mobile phone data provide a good foundation for information acquisition. The mobile phone data comprises large-range time and space information, and the data is reasonably utilized, so that the method has important functions on representing the traffic running state, evaluating the effects of traffic facilities and policies and making traffic management aid decisions. In addition, the real-name registration policy of the mobile phone user enables the information such as the age, the sex and the like of the user to be accurately recorded. However, the mobile phone signaling data and the user information contain personal privacy information such as the phone number and the location of the user, and cannot be directly applied.
The residential characteristics of the traffic district are used as important reference characteristics of traffic distribution in the four-phase method of traffic planning, and have important significance. At present, in the traffic field, no other method is applied to extraction of personal characteristics of travelers except for traditional questionnaires, and mobile phone operator data enable extraction of the characteristics of the travelers and analysis of travel behaviors to be possible. The method provided by the invention excavates the data value of the mobile phone, fully exerts the advantages of the mobile phone in sample size and accuracy, and makes up the defects that travel investigation consumes manpower, material resources, time and memory accuracy of an interviewee is depended on; meanwhile, the security of individual information is emphasized, the individual information is collected into information of a traffic community group, the privacy of users is prevented from being revealed, and therefore a new data acquisition method is provided for traffic planning.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method for estimating population characteristics of a traffic cell based on signaling data, which can obtain the population characteristic information of the traffic cell necessary for traffic planning by using mobile network operator data without additional equipment.
In order to solve the technical problem, the invention provides a traffic cell population characteristic estimation method based on signaling data, which comprises the following steps:
(1) acquiring residential users in the service range of each mobile phone base station based on the mobile phone signaling data;
(2) matching the acquired resident user information with user information of an operator to obtain personal information of resident users in the coverage range of each mobile phone base station;
(3) and (3) converting the personal information of the residential users corresponding to the mobile phone base station obtained in the step (2) into characteristic information of the residential users in the traffic cell based on the corresponding relationship between the mobile phone base station and the traffic cell.
Preferably, in the step (1), acquiring residential users within the service range of each mobile phone base station based on the mobile phone signaling data specifically includes the following steps:
(11) selecting signaling data of a research area for a plurality of consecutive days from a research date, and inquiring a data set I recorded in a daily rest period of each base station;
(12) if a user has enough data in the data set I, most data in the records of the user in one day are recorded by the same base station, the user is considered to be in the service range of the base station.
Preferably, in the step (2), the method for acquiring the personal information of the residential user in the coverage area of the mobile phone base station comprises the following steps: and counting the APP use preference of the user according to the serial number of the resident user of the base station, and performing correlation query on a basic table containing the information such as the age, the sex and the like of the user to obtain the information of the sex, the age, the occupation category and the APP use preference of the user.
Preferably, in the step (3), based on the correspondence between the mobile phone base station and the traffic cell, the personal information of the residential user corresponding to the mobile phone base station obtained in the step (2) is converted into the characteristic information of the residential user in the traffic cell, and the method specifically includes the following steps:
(31) in ArcGIS, a tool for creating Thiessen polygons is utilized, a base station is taken as an input point, Thiessen polygon areas of the base station are output, the areas represent all areas in which the distance from any position to the associated point of the base station is shorter than that of any other point input element, the service range of each base station is the Thiessen polygon area of the base station, and the distance from any position to the associated base station of the base station in the area is shorter than that of any other base station;
(32) let base station CiThe Thiessen polygon served is TiAnd a Thiessen polygonal area TiWith overlapping traffic zones of
P is the user attribute in the research area; wherein the base station CiServing a plurality of traffic cells, i.e. TiWith traffic districts
There is an intersection; at the same time, traffic cell ZjServed by a plurality of base stations, i.e. traffic cells ZjIs covered with a plurality of Thiessen polygons
Dividing;
calculating the overlapping relation between the service range of the base station and the traffic cell to obtain a base station CiServed X traffic cells
And the ratio of each
Then traffic cell ZjNumber of certain attribute users
The sum of the total number of attributes of the Y parts is equal to the total number of base stations of the Thiessen polygon and the ratio of the total number of base stations of the Thiessen polygon
The product of (a); the specific calculation method comprises the following steps:
wherein,
x: a collection of all traffic cells served by a certain base station;
y: a certain traffic cell is a collection of different Thiessen polygon segmented parts;
s: area of the region.
Preferably, in step (31), an irregular triangular mesh meeting the Delaunay criterion is divided among all points, the perpendicular bisector of each side of the triangle can form the side of the thieson polygon, and the intersection point of each bisector determines the position of the folding point of the thieson polygon.
The invention has the beneficial effects that: compared with the traditional manual investigation method, the method has the advantages that the signaling data is utilized to obtain the residential community information and the population characteristics of the user, so that a large amount of manpower, material resources and time cost required by the organization investigation are saved, errors caused by memory errors of the investigated people can be avoided, and the accuracy is higher; the signaling data sample size is large, and a user does not need to submit data, so that the user is covered comprehensively; in addition, the user information is collected by taking the traffic cell as a unit, and the final result does not contain the personal information of a single user, so that the personal privacy and the sensitivity of data of the single user are effectively protected; using mobile network operator data, traffic cell demographic information necessary for traffic planning is obtained without additional equipment.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention.
Fig. 2 is a schematic diagram of a method for identifying a residential subscriber of a mobile phone base station according to the present invention.
Fig. 3 is a schematic diagram of an exemplary thiessen polygon of the base station service area of the present invention.
Fig. 4 is a schematic diagram of the matching relationship between the thiessen polygon and the traffic cell according to the present invention.
Detailed Description
As shown in fig. 1, a method for estimating traffic cell population characteristics based on signaling data includes the following steps:
(1) acquiring residential users in the service range of each mobile phone base station based on the mobile phone signaling data;
(2) matching the acquired resident user information with user information of an operator to obtain personal information of resident users in the coverage range of each mobile phone base station;
(3) and (3) converting the personal information of the residential users corresponding to the mobile phone base station obtained in the step (2) into characteristic information of the residential users in the traffic cell based on the corresponding relationship between the mobile phone base station and the traffic cell.
The invention relates to a traffic cell population characteristic estimation method based on signaling data, which comprises the following steps of:
1. and acquiring 4G signaling data, base station information, APP usage records of mobile phone users and traffic cell information of the research area.
The 4G signaling data includes information about 30 days before the study day, and may include a user number, a base station number, a signal generation time, and the like. The user number may use an IMSI number, a phone number, or other information with an identification function.
The base station information may include a base station number, a base station name, a base station longitude and latitude, and the like.
The APP usage records of the mobile phone user can include a user number, an APP name, APP usage time, APP usage flow and the like.
The traffic cell information may include a traffic cell name, a traffic cell number, a traffic cell position, a traffic cell shape, and the like.
2. And matching the obtained 4G signaling data with the base station information to obtain the residential users in the service range of the mobile phone base station.
The residential users of the mobile phone base station may include a base station number, a location, a user number, and the like.
As shown in fig. 2, the implementation method of the residential subscriber of the mobile phone base station specifically includes:
21. selecting signaling data of a research area for 30 consecutive days from a research date, and inquiring a data set I recorded from 24 points of each base station to 7 points of the next day;
22. and if 20 days of 30 days of a certain user in the data set I satisfy the condition 1), the user is considered to be in the service range of the base station.
Condition 1) user's day record, 70% of the data is recorded by the same base station.
23. And counting the residential users of all base stations in the research range to obtain all the residential users in the service range of each base station.
3. And matching the obtained residential user corresponding to the mobile phone base station with the operator user information and the APP use data to obtain the personal characteristics of the residential user of the mobile phone base station.
The personal information of the residential users of the mobile phone base station can comprise: gender, age, occupation category, APP usage preferences, etc.
The method for realizing the personal characteristics of the residential users in the coverage area of the mobile phone base station specifically comprises the following steps:
31. and associating the mobile phone user information of the operator according to the serial number of the resident user of the base station to generate basic attributes of the population of the traffic community, such as gender, age, occupation and the like.
32. And associating APP use record data according to the serial number of the base station resident user to obtain the type, the times and the time of using the APP by the user.
33. And counting the information of the living users collectively by taking the mobile phone base station as a unit to obtain the number of the living users in different attribute categories of each base station and the number and frequency of the various APPs used by each base station.
Wherein, the living users with different attribute categories may include: gender, age group, occupation category, etc.
4. And distributing the personal characteristic information of the residential users to the corresponding traffic districts according to the matching relation between the mobile phone base station and the traffic districts.
And the individual characteristic information of the residential users is distributed to the corresponding traffic cells according to the proportion of the corresponding traffic cells in the service range of the base station.
The method for matching the mobile phone base station with the traffic cell comprises the following steps:
41. in ArcGIS, a Thiessen polygon area is output by using a Thiessen polygon creating tool with a base station as an input point. These areas represent all areas where any location is closer to its associated point than to any other point input element, i.e. in the present invention each base station is served by its Thiessen polygon area, and any location within this area is closer to its associated base station than to any other base station. Referring to fig. 3, the central point of the figure represents the base station of the mobile phone, and the surrounding lines of the base station point are enclosed by a thiessen polygon. The method comprises the following specific steps:
411 demarcate in all points an irregular triangular network (TIN) according to the Delaunay criterion.
The perpendicular bisectors of the sides of the triangle 412 may form the sides of the Thiessen polygon. The intersection point of each bisector determines the position of the Thiessen polygon break point.
42. And calculating the overlapping relation between the service range of the base station and the traffic cells to obtain all the traffic cells served by the base station and the ratio of the traffic cells to the traffic cells. Let base station CiThe Thiessen polygon served is TiAnd a Thiessen polygonal area TiWith overlapping traffic zones of
P is the user attribute within the study area. Wherein the base station CiServing a plurality of traffic cells, i.e. TiWith traffic districts
(assume X) there are intersections; at the same time, traffic cell ZjServed by a plurality of base stations, i.e. traffic cells ZjIs covered with a plurality of Thiessen polygons
Split (assume Y) as in fig. 4.
Calculating the overlapping relation between the service range of the base station and the traffic cell to obtain a base station CiServed X traffic cells
And the ratio of each
(the ratio of the m-th traffic cell partial area to the sum of all X traffic cell partial areas involved, see equation (1)). Then traffic cell ZjNumber of certain attribute users
The sum of the total number of attributes of the Y parts is equal to the total number of base stations of the Thiessen polygon and the ratio of the total number of base stations of the Thiessen polygon
The product of (a). The specific calculation method comprises the following steps:
wherein,
x: a collection of all traffic cells served by a certain base station;
y: a certain traffic cell is a collection of different Thiessen polygon segmented parts;
s: area of the region.
The method for acquiring the residential population characteristics of the traffic cell provided by the invention can reduce the manual workload, reduce the cost and improve the efficiency on the basis of the necessary population characteristics of the traffic cell for large traffic planning without additional equipment.
Claims (4)
1. A traffic cell population characteristic estimation method based on signaling data is characterized by comprising the following steps:
(1) acquiring residential users in the service range of each mobile phone base station based on the mobile phone signaling data;
(2) matching the acquired resident user information with user information of an operator to obtain personal information of resident users in the coverage range of each mobile phone base station;
(3) based on the corresponding relationship between the mobile phone base station and the traffic cell, converting the personal information of the residential user corresponding to the mobile phone base station obtained in the step (2) into characteristic information of the residential user of the traffic cell, which specifically comprises the following steps:
(31) in ArcGIS, a tool for creating Thiessen polygons is utilized, a base station is taken as an input point, Thiessen polygon areas of the base station are output, the areas represent all areas in which the distance from any position to the associated point of the base station is shorter than that of any other point input element, the service range of each base station is the Thiessen polygon area of the base station, and the distance from any position to the associated base station of the base station in the area is shorter than that of any other base station;
(32) let base station CiThe Thiessen polygon served is TiAnd a Thiessen polygonal area TiWith overlapping traffic zones of
P is the user attribute in the research area; wherein the base station CiServing a plurality of traffic cells, i.e. TiWith traffic districts
There is an intersection; at the same time, traffic cell ZjServed by a plurality of base stations, i.e. traffic cells ZjIs covered with a plurality of Thiessen polygons
Dividing;
calculating base station service area sumThe overlapping relation of the traffic cells obtains a base station CiServed X traffic cells
And the ratio of each
Then traffic cell ZjNumber of certain attribute users
The sum of the total number of attributes of the Y parts is equal to the total number of base stations of the Thiessen polygon and the ratio of the total number of base stations of the Thiessen polygon
The product of (a); the specific calculation method comprises the following steps:
wherein,
x: a collection of all traffic cells served by a certain base station;
y: a certain traffic cell is a collection of different Thiessen polygon segmented parts;
s: area of the region.
2. The method for estimating the population characteristics of the traffic cell based on the signaling data as claimed in claim 1, wherein in the step (1), the step of obtaining the residential users in the service range of each mobile phone base station based on the mobile phone signaling data specifically comprises the following steps:
(11) selecting signaling data of a research area for a plurality of consecutive days from a research date, and inquiring a data set I recorded in a daily rest period of each base station;
(12) if a user has enough data in the data set I, most data in the records of the user in one day are recorded by the same base station, the user is considered to be in the service range of the base station.
3. The method for estimating the population characteristics of the traffic cell based on the signaling data as claimed in claim 1, wherein in the step (2), the method for acquiring the personal information of the residential users in the coverage area of the base station of the mobile phone comprises the following steps: and counting the APP use preference of the user according to the serial number of the resident user of the base station, and performing correlation query on a basic table containing the information such as the age, the sex and the like of the user to obtain the information of the sex, the age, the occupation category and the APP use preference of the user.
4. The method as claimed in claim 1, wherein in step (31), an irregular triangular network meeting Delaunay criteria is divided among all points, the perpendicular bisector of each side of the triangle forms the side of the Thiessen polygon, and the intersection point of each bisector determines the position of the folding point of the Thiessen polygon.
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| CN110136043B (en) * | 2019-05-17 | 2023-03-14 | 东南大学 | Traffic cell population calculation 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 |
| CN112566030B (en) * | 2020-12-08 | 2022-06-07 | 东南大学 | Mobile phone signaling data-based residence double-period identification method and application |
| 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 |
| CN114153855A (en) * | 2021-11-04 | 2022-03-08 | 厦门市美亚柏科信息股份有限公司 | Real population management method, terminal device and storage medium |
| CN114139251B (en) * | 2021-11-14 | 2023-01-17 | 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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