WO2010119774A1

WO2010119774A1 - Position information analysis device and position information analysis method

Info

Publication number: WO2010119774A1
Application number: PCT/JP2010/055878
Authority: WO
Inventors: 智大永田; 一郎岡島; 博川上; 晩煕趙; 大介越智; 俊博鈴木; 基成小林; 勇輝大薮
Original assignee: 株式会社エヌ・ティ・ティ・ドコモ
Priority date: 2009-04-17
Filing date: 2010-03-31
Publication date: 2010-10-21
Also published as: JPWO2010119774A1; JP5225461B2

Abstract

With the purpose of easily obtaining a movement trajectory of a user, a position information analysis device (600) is provided with a classification unit (601) which inputs point data of a plurality of time points with respect to a plurality of users, classifies the point data for the respective users, and arranges the point data in chronological order, the point data comprising position information of a user, time point information regarding the obtained position information, and user identification information; a judgment unit (602) which judges a movement method between adjacent point data in the time series, on the basis of the point data of the plurality of time points for the respective users and previously stored route map data of public transportation; a movement trajectory derivation unit (603) which derives movement trajectory information on the map, on the basis of the movement method information between the respective point data, the position information contained in each point data, and the position data relating to at least either one of the roads and public transportation routes on the previously stored map; and a movement trajectory storage unit (604) which stores the movement trajectory information.

Description

POSITION INFORMATION ANALYSIS DEVICE AND POSITION INFORMATION ANALYSIS METHOD

The present invention relates to a position information analysis apparatus and a position information analysis method for performing analysis related to user movement (for example, derivation of a user's movement trajectory) based on position information of a mobile device carried by the user.

Conventionally, as an analysis on the movement of the user, the user's movement speed, acceleration, change amount in the movement direction, etc. are measured using an instrument such as an acceleration sensor or a speed center. Techniques have been proposed for discriminating which moving means has moved among buses, cars, etc. (referred to herein as “user moving method”) (see Patent Documents 1 and 2).

On the other hand, among the analyzes related to user movement, there is a growing need for analysis data regarding macroscopic population flow.

Japanese Patent Application Laid-Open No. 10-232992 JP 2005-222193 A

However, in order to obtain analysis data regarding population flow, it is not sufficient to determine the user's movement method, and it is necessary to obtain the user's movement trajectory.

On the other hand, it has been awaited to easily obtain analysis data on population flow without using expensive instruments such as acceleration sensors and speed centers.

In view of the above problems, an object of the present invention is to easily obtain a user's movement trajectory.

The position information analysis device according to the first aspect of the present invention is a point data including position information indicating a position of a user, time information when the position information is obtained, and user identification information of the user. A classifying unit that inputs the point data over a plurality of times for a user, classifies the data for each user, and arranges the data according to a time series; the point data for each user over the plurality of times; and public traffic stored in advance Based on the route map data of the institution, a determination unit that determines, for each user, a movement method between point data adjacent in time series, movement method information between each point data obtained by the determination, and each point data Location information included and location data regarding at least one of roads and public transport routes on a pre-stored map And a movement trajectory deriving unit for obtaining movement trajectory information on the map for each user, and a movement trajectory storage unit for saving the movement trajectory information for each derived user (first operation) 1 embodiment).

As the “point data” here, GPS positioning data obtained by a GPS positioning system or OPS data can be adopted. However, since the OPS data does not include exact position information (latitude / longitude information), for example, it is estimated that the area information where a certain user is located is located at the center of gravity of the area. Then, the point data can be obtained from the OPS data by converting the area information into the position information (latitude / longitude information) of the center of gravity of the area.

For the point data obtained relatively easily as described above, the classification unit inputs point data for a plurality of users over a plurality of times, classifies the data for each user, and arranges them in time series. Based on the point data for each user over a plurality of times obtained by the classification and the route map data of public transportation stored in advance, the determination unit moves between the point data adjacent in time series. A method is determined for each user. Further, the movement trajectory deriving unit includes at least one of movement method information between each point data obtained by the determination, position information included in each point data, and a road and a public transportation route on a prestored map. The movement trajectory information on the map is obtained for each user on the basis of the position data regarding, and the movement trajectory storage unit stores the derived movement trajectory information for each user. As described above, according to the position information analysis apparatus according to the present invention, from the point data obtained relatively easily, the movement method between the point data adjacent in time series is determined for each user, and the determination is obtained. Based on the movement method information between each point data, the position information included in each point data, and the position data regarding at least one of the road and the public transportation route on the map stored in advance, the movement trajectory information on the map For each user.

The determination unit obtains a distance and a time difference between adjacent point data in the time series in the point data for each user over the plurality of times, and determines each point based on the distance and the time difference between the point data. Based on a moving speed calculation unit that calculates a moving speed between data, the calculated moving speed between each point data, position information included in the point data, and route map data of the public transportation stored in advance In addition, it is desirable to include a movement method determination unit that determines a movement method between the point data.

By the way, in order to obtain the movement trajectory information, movement method information between adjacent point data on the time series is required. In a situation where the movement method information between the point data is acquired in advance, the present invention includes Such a positional information analysis apparatus can adopt the following second mode in which the movement method information between the point data is input and the subsequent processing is performed.

The position information analysis device according to the second aspect is point data including position information indicating a user's position, time information when the position information is obtained, and user identification information of the user, and the user covers a plurality of times. Included in each point data is an input unit for inputting the point data classified for each time and movement method information between adjacent point data in time series, and movement method information between the input point data A movement trajectory deriving unit that obtains the movement trajectory information on the map for each user based on the position information and position data relating to at least one of roads and public transportation routes on the map stored in advance; A movement trajectory storage unit that stores movement trajectory information for each user. In this case, when the input unit inputs the point data classified for each user over a plurality of times and movement method information between adjacent point data in time series, the movement trajectory deriving unit Based on the movement method information between the point data, the position information included in each point data, and the position data regarding at least one of the road and the public transportation route on the map stored in advance, the movement trajectory information on the map is obtained. Obtained for each user, and the movement trajectory storage unit saves the derived movement trajectory information for each user.

Note that both the position information analysis device according to the first aspect and the position information analysis device according to the second aspect are read out by a reading unit that reads out movement trajectory information of a plurality of users stored by the movement trajectory storage unit. It is desirable to further include an output unit that outputs statistical information based on the movement trajectory information of a plurality of users. In this case, statistical information based on the movement trajectory information of a plurality of users can be output and visualized.

By the way, with respect to the method of deriving the movement trajectory by the movement trajectory deriving unit, if the three point data adjacent in time series are the first point data, second point data, and third point data in order from the oldest, Depending on the combination of the movement method between 1 point data and the second point data and the movement method between the second point data and the third point data (that is, the combination of the movement methods before and after the second point data) There are a total of nine modes.

That is, the movement trajectory deriving unit sets the three point data adjacent in time series as the first point data, the second point data, and the third point data in order from the oldest, and in the three point data, the first point data On the map when the movement method between the second point data and the second point data is either walking, bicycle, or car, and the subsequent moving method between the second and third point data is any one of walking, bike, or car. The position information of the first, second, and third point data is corrected by moving the positions of the first, second, and third point data on the nearest road, respectively. It is desirable that the movement trajectory information is obtained by connecting the positions of the first, second, and third point data through the shortest path corresponding to the movement method between the point data.

In addition, the movement trajectory deriving unit sets the three point data adjacent on the time series in order from the oldest as the first point data, the second point data, and the third point data. In the three point data, When the movement method between the second point data and the second point data is a train, and the subsequent movement method between the second and third point data is a train, the positions of the first, second and third point data on the map Is moved to the nearest train route to correct the position information of the first, second and third point data, and the position of the first, second and third point data on the map is corrected. It is desirable that the movement trajectory information is obtained by connecting with the shortest path corresponding to the movement method between the point data.

In addition, the movement trajectory deriving unit sets the three point data adjacent on the time series in order from the oldest as the first point data, the second point data, and the third point data. In the three point data, When the movement method between the second point data and the second point data is a bus, and the subsequent movement method between the second and third point data is a bus, the position of the first, second and third point data on the map Is moved to the nearest bus route to correct the position information of the first, second and third point data, and the position of the first, second and third point data on the map is corrected. It is desirable that the movement trajectory information is obtained by connecting with the shortest path corresponding to the movement method between the point data.

In addition, the movement trajectory deriving unit sets the three point data adjacent on the time series in order from the oldest as the first point data, the second point data, and the third point data. In the three point data, When the movement method between the second point data and the second point data is either walking, bicycle, or car, and the subsequent movement method between the second and third point data is a train, the first and second points on the map The position information of each of the first, second and third point data is corrected by moving the position of each point data onto the nearest road and moving the position of the third point data onto the nearest train route. , Generating new point data on the nearest station from the second point data, and a moving method between the second point data and the new point data , Setting the same movement method as between the first and second point data, setting the movement method between the new point data and the third point data as a train, and the first point data on the map It is desirable that the movement trajectory information is obtained by connecting the positions of the second point data, the new point data, and the third point data through a shortest path according to a movement method between the point data.

In addition, the movement trajectory deriving unit sets the three point data adjacent on the time series in order from the oldest as the first point data, the second point data, and the third point data. In the three point data, When the movement method between the second point data and the second point data is either walking, bicycle, or car, and the subsequent movement method between the second and third point data is a bus, the first and second points on the map The position information of the first, second, and third point data is corrected by moving the position of each point data on the nearest road and moving the position of the third point data on the nearest bus route. , Generate new point data on the bus stop closest to the second point data, and between the second point data and the new point data The movement method is set to the same movement method as between the first and second point data, the movement method between the new point data and the third point data is set to the bus, and the first on the map is set. It is desirable to obtain the movement trajectory information by connecting the positions of the point data, the second point data, the new point data, and the third point data through the shortest path according to the movement method between the point data. .

In addition, the movement trajectory deriving unit sets the three point data adjacent on the time series in order from the oldest as the first point data, the second point data, and the third point data. In the three point data, When the movement method between the second point data and the second point data is a train, and the subsequent movement method between the second and third point data is one of walking, bicycle, and car, the first point data on the map The position information of the first, second, and third point data is corrected by moving the position on the nearest train route and moving the positions of the second and third point data on the nearest road. , Generating new point data on the nearest station from the second point data, and moving between the first point data and the new point data Set to a train, and set the movement method between the new point data and the second point data to the same movement method as between the second and third point data, and the first point data on the map and It is desirable that the movement trajectory information is obtained by connecting the positions of the new point data, the second point data, and the third point data through a shortest path according to a movement method between the point data.

In addition, the movement trajectory deriving unit sets the three point data adjacent on the time series in order from the oldest as the first point data, the second point data, and the third point data. In the three point data, When the movement method between the second point data and the second point data is a bus, and the subsequent movement method between the second and third point data is one of walking, bicycle, and car, the first point data on the map The position information of the first, second and third point data is corrected by moving the position on the nearest bus route and moving the positions of the second and third point data on the nearest road. , Generate new point data on the bus stop closest to the second point data, between the first point data and the new point data The movement method is set to a bus, the movement method between the new point data and the second point data is set to the same movement method as between the second and third point data, and the first on the map is set. Desirably, the movement trajectory information is obtained by connecting the positions of the point data, the new point data, the second point data, and the third point data through the shortest path according to the movement method between the point data. .

In addition, the movement trajectory deriving unit sets the three point data adjacent on the time series in order from the oldest as the first point data, the second point data, and the third point data. In the three point data, When the movement method between the second point data and the second point data is a bus, and the subsequent movement method between the second and third point data is a train, the position of each of the first and second point data on the map is the most. The position information of the first, second and third point data is corrected by moving on the nearest bus route and moving the position of the third point data on the nearest train route, and the second point data A new bus stop point data is generated on the bus stop closest to the bus, and the movement method between the second point data and the bus stop point data Set, generate new station point data on the nearest station from the bus stop point data, set the movement method between the bus stop point data and the station point data to walk, the station point data and the third point A movement method between data is set to a train, and the position of the first point data, the second point data, the bus stop point data, the station point data, and the third point data on the map is set to the point data. It is desirable to obtain the movement trajectory information by linking with the shortest route according to the movement method.

In addition, the movement trajectory deriving unit sets the three point data adjacent on the time series in order from the oldest as the first point data, the second point data, and the third point data. In the three point data, If the movement method between the second point data and the second point data is a train and the subsequent movement method between the second and third point data is a bus, the position of the first point data on the map is on the nearest train route. The position information of the first, second, and third point data is corrected by moving the positions of the second and third point data to the nearest bus route, and the second point data A new bus stop point data is generated on the bus stop closest to the bus, and the movement method between the bus stop point data and the second point data is Set, generate new station point data on the nearest station from the bus stop point data, set the movement method between the station point data and the bus stop point data to walk, the first point data and the station The movement method between the point data is set to a train, and the position of the first point data, the station point data, the bus stop point data, the second point data, and the third point data on the map is set to the point data. It is desirable to obtain the movement trajectory information by connecting with the shortest path according to the movement method between data.

It should be noted that the invention relating to the location information analysis apparatus can be regarded as an invention relating to the location information analysis method, and can be described as follows. The invention relating to the position information analysis method also has the same actions and effects.

A position information analysis method according to a first aspect is a position information analysis method executed in a position information analysis apparatus, the position information indicating a user's position, the time information when the position information was obtained, and the user's The point data including user identification information, wherein the point data over a plurality of times for a plurality of users is input to the position information analyzer, and is classified for each user and arranged along a time series, and A determination step of determining, for each user, a moving method between point data adjacent in time series based on point data for each user over a plurality of times and route map data of public transportation stored in advance. Movement method information between each point data obtained by the determination, position information included in each point data, A movement trajectory derivation step for obtaining movement trajectory information on the map for each user based on position data on at least one of roads and public transportation routes on the stored map, and a movement trajectory for each derived user And a movement trajectory saving step for saving information.

Also, in a situation where movement method information between point data is acquired in advance, the position information analysis method according to the following second mode is effective. That is, the position information analysis method according to the second aspect is a position information analysis method executed in the position information analysis apparatus, the position information indicating the position of the user, the time information when the position information was obtained, and the Point data including user identification information of the user, the point data classified for each user over a plurality of times, and movement method information between adjacent point data in time series are transmitted to the position information analysis apparatus. Input step to input, movement method information between each input point data, position information included in each point data, and position data related to at least one of roads and public transportation routes on a pre-stored map Based on the movement trajectory derivation step for obtaining the movement trajectory information on the map for each user, and each derived user. A movement locus storing step of storing the moving track information about The, characterized in that it comprises a.

According to the present invention, the user's movement trajectory can be easily obtained by effectively using the user's easily obtained position information.

1 is a system configuration diagram of a communication system according to first and second embodiments. FIG. It is a functional block block diagram of the positional information analyzer of 1st Embodiment. It is a flowchart which shows the positional information analysis process of 1st Embodiment. It is a flowchart which shows a moving method determination process. It is a table | surface which shows a response | compatibility with the movement method before and behind a point, and a correction process. 10 is a flowchart showing correction processes A to C. It is a figure for demonstrating the correction process AC. It is a flowchart which shows the correction processes D and E. It is a figure for demonstrating the correction processes D and E. FIG. It is a flowchart which shows the correction processes F and G. It is a figure for explaining amendment processing F and G. 10 is a flowchart showing a correction process H. It is a figure for demonstrating the correction process. It is a flowchart which shows the correction process I. It is a figure for demonstrating the correction process. It is a figure which shows an example of point data. It is a figure which shows an example of a point data table. It is a figure which shows an example of line data. It is a functional block block diagram of the positional information analyzer of 2nd Embodiment. It is a flowchart which shows the positional information analysis process of 2nd Embodiment.

Embodiments according to the present invention will be described with reference to the accompanying drawings. Where possible, the same parts are denoted by the same reference numerals, and redundant description is omitted.

[First Embodiment]
Hereinafter, as a first embodiment, a position information analysis apparatus that performs both determination of a movement method between point data adjacent in time series and derivation of a movement locus will be described.

[Configuration of communication system]
FIG. 1 is a system configuration diagram of a communication system 10 according to the present embodiment. As shown in FIG. 1, the communication system 10 includes a mobile device 100, a BTS (base station) 200, an RNC (radio control device) 300, an exchange 400, various processing nodes 700, and a management center 500. Yes. The management center 500 includes a social sensor unit 501, a petamining unit 502, a mobile demography unit 503, and a visualization solution unit 504.

The exchange 400 collects the location information of the mobile device 100 via the BTS 200 and the RNC 300. The RNC 300 can measure the position of the mobile device 100 using the delay value in the RRC connection request signal when communication connection is established with the mobile device 100. The exchange 400 can receive the position information of the mobile device 100 measured in this way when the mobile device 100 performs communication connection. The exchange 400 stores the received position information, and outputs the collected position information to the management center 500 at a predetermined timing or in response to a request from the management center 500. Here, generally, the RNC 300 is composed of about a thousand pieces, and is arranged throughout Japan. On the other hand, about 300 exchanges 400 are arranged in Japan.

The various processing nodes 700 acquire the location information of the mobile device 100 through the RNC 300 and the exchange 400, perform recalculation of the location in some cases, and collect at a predetermined timing or in response to a request from the management center 500 The obtained position information is output to the management center 500.

As described above, the management center 500 includes the social sensor unit 501, the petamining unit 502, the mobile demography unit 503, and the visualization solution unit 504. Each unit is used for position information of the mobile device 100. Perform statistical processing.

The social sensor unit 501 is a server device that collects data including position information of the mobile device 100 from each exchange 400 and various processing nodes 700 or offline. The social sensor unit 501 receives data periodically output from the exchange 400 and the various processing nodes 700, or acquires data from the exchange 400 and the various processing nodes 700 according to a predetermined timing in the social sensor unit 501. It is configured to be able to do.

The petamining unit 502 is a server device that converts data received from the social sensor unit 501 into a predetermined data format. For example, the petamining unit 502 performs a sorting process using a user ID as a key, or performs a sorting process for each area.

The mobile demography unit 503 is a server device that performs aggregation processing on the data processed in the petamining unit 502, that is, count processing for each item. For example, the mobile demography unit 503 can count the number of users located in a certain area, and can total the distribution of the located areas.

The visualization solution unit 504 is a server device that processes the data aggregated in the mobile demography unit 503 so as to be visible. For example, the visualization solution unit 504 can map the aggregated data on a map. Data processed by the visualization solution unit 504 is provided to companies, government offices or individuals, and is used for store development, road traffic surveys, disaster countermeasures, environmental countermeasures, and the like. It should be noted that the information statistically processed in this way is processed so that individuals are not specified so as not to infringe privacy.

The social sensor unit 501, the petamining unit 502, the mobile demography unit 503, and the visualization solution unit 504 are all configured by the server device as described above, and although not shown, the basic configuration of a normal information processing device Needless to say, it includes a CPU, a RAM, a ROM, an input device such as a keyboard and a mouse, a communication device that communicates with the outside, a storage device that stores information, and an output device such as a display and a printer.

[Configuration of location information analyzer]
Next, the position information analysis apparatus according to the present embodiment will be described. FIG. 2 shows a functional block configuration of the position information analysis apparatus 600. As illustrated in FIG. 2, the position information analysis apparatus 600 includes a classification unit 601, a determination unit 602, a movement locus derivation unit 603, a movement locus storage unit 604, a reading unit 605, and an output unit 606. The function of each part will be described later.

The position information in this embodiment includes position information (latitude / longitude information) indicating the position of the user shown in FIG. 16, time information (time stamp) when the position information was obtained, and a point including the user identifier of the user. Processed in the form of data. Point data for a plurality of users over a plurality of times is stored in the position information database 610. As the “point data” here, GPS positioning data obtained by a GPS positioning system or OPS data can be adopted. However, since the OPS data does not include exact position information (latitude / longitude information), for example, it is estimated that the area information where a certain user is located is located at the center of gravity of the area. Then, the point data can be obtained from the OPS data by converting the area information into the position information (latitude / longitude information) of the center of gravity of the area. On the other hand, map data representing a two-dimensional map is stored in the map database 620. In addition, movement method information between each point data obtained by determination by the determination unit 602 described later is stored in the movement method information database 630.

Outline of the correspondence between the logical configuration of FIG. 2 and the system configuration of FIG. Here, as an example, the position information analysis apparatus 600 corresponds to the mobile demography unit 503 and the visualization solution unit 504 in FIG. 1, and the position information database 610, the map database 620, and the movement method information database 630 are the same as those in FIG. This corresponds to the mining unit 502.

However, as another example, the movement trajectory storage unit 604, the reading unit 605, and the output unit 606 in the location information analysis device 600 correspond to the mobile demography unit 503 and the visualization solution unit 504 in FIG. Other components, the position information database 610, the map database 620, and the movement method information database 630 may adopt a configuration corresponding to the petamining unit 502 in FIG.

Hereinafter, functions of each unit of the position information analysis apparatus 600 of FIG. 2 will be described. The classification unit 601 reads point data over a plurality of times for a plurality of users from the position information database 610 and inputs the point data to the position information analysis apparatus 600, and a unique identifier (hereinafter “point identifier”) for each input point data. And the input point data is classified for each user and arranged in time series. It should be noted that it is not essential to assign a point identifier to individual point data, as long as the inputted individual point data can be identified by some method. For example, it may be identified by unique information included in the point data in advance, or may be identified by unique information that can be calculated from the input time to the position information analysis device 600 or input order information.

The determination unit 602 determines, for each user, a movement method between point data adjacent in time series based on point data for each user over a plurality of times and route map data of public transportation stored in advance. . The determination unit 602 includes a movement speed calculation unit 602A and a movement method determination unit 602B. The moving speed calculation unit 602A obtains a distance and time difference between adjacent point data in time series in point data for each user over a plurality of times, and based on the distance and time difference between the point data, Calculate the moving speed. The movement method determination unit 602B moves between the point data based on the calculated movement speed between the point data, the position information included in the point data, and the route map data of the public transportation stored in advance. Determine the method. Such determination processing by the determination unit 602 will be described later with reference to FIG. Note that the movement method information between the point data obtained by the determination is stored in the movement method information database 630.

The movement trajectory deriving unit 603 obtains the movement method information between the point data obtained by the determination, the position information included in each point data, and the position data related to the road and the public transportation route on the map stored in advance. Based on this, the movement trajectory information on the map is obtained for each user. The process of deriving the movement locus information of the target user by the movement locus deriving unit 603 will be described later with reference to FIGS. 3 and 5 to 15.

The movement trajectory storage unit 604 stores the derived movement trajectory information. The reading unit 605 reads the movement locus information of a plurality of users stored by the movement locus storage unit 604. The output unit 606 outputs statistical information based on the read movement trajectory information of a plurality of users.

[Location analysis processing]
Next, position information analysis processing executed by the position information analysis apparatus 600 will be described with reference to the drawings.

As shown in FIG. 3, the classification unit 601 in the position information analysis apparatus 600 reads point data for a plurality of users over a plurality of times from the position information database 610 and inputs the point data to the position information analysis apparatus 600. A point identifier is assigned to the point data, and the input point data is classified for each user and arranged in time series (step S1 in FIG. 3).

As shown in FIG. 16, the point data includes position information (latitude information and longitude information) indicating the position of the user, time information (time stamp) when the position information is obtained, and a user identifier of the user. In step S1, a point identifier is assigned, and in the position information analysis apparatus 600, for example, it is temporarily stored as a point data table in a table format as shown in FIG. Further, the classification unit 601 recognizes a plurality of point data corresponding to a series of movement histories of a certain user as one line in the point data classified for each user and arranged in time series, and is unique to each line. A unique identifier (line identifier) is assigned, line data in a table format as shown in FIG. 18A is generated, and temporarily stored in the position information analysis apparatus 600. The line data is generated as a unit between adjacent point data (one section) on the time series in one line. As shown in FIG. 18A, the line data includes a line identifier and a moving method of the corresponding section. It includes information, a point identifier of the start point of the corresponding section, and a point identifier of the end point of the corresponding section. When step S1 is completed, the information on the movement method is blank.

Next, the determination unit 602 determines a moving method between point data adjacent in time series based on the point data of the target user and the route map data of public transportation stored in advance as follows. (Step S2). That is, as illustrated in FIG. 4, first, the moving speed calculation unit 602A of the determination unit 602 determines two adjacent point data in the point data arranged in time series of the target user, and sets the two target point data. The distance between the target point data is obtained from the position information of the target point data, the time difference is obtained from the time stamp of the target point data, and the distance between the obtained target point data is divided by the time difference to Calculate (step S201 in FIG. 4). Assuming that the interval between the two adjacent point data set as the target is one “section”, the older point data (upstream in the time series) of the two point data is referred to as the “start point”. The newer point data (downstream in time series) is referred to as “end point”.

Then, the movement method determination unit 602B determines whether or not the calculated movement speed V is less than a predetermined reference speed V1 for walking determination (step S202), and the movement speed V is less than the reference speed V1. If so, the movement method between the target point data is determined to be “walking” (step S203).

When the moving speed V is not less than the reference speed V1, the moving method determination unit 602B determines whether the moving speed V is equal to or higher than the reference speed V1 and less than a predetermined reference speed V2 for bicycle determination (step S204). If the moving speed V is equal to or higher than the reference speed V1 and lower than the reference speed V2, the moving method between the target point data is determined as “bicycle” (step S205).

When the moving speed V is equal to or higher than the reference speed V2, the moving method determination unit 602B determines whether at least one of the start point and the end point is located on the train line in light of the train line map data stored in advance. (Step S206) If at least one of the start point and the end point is located on the train route, the movement method between the target point data is determined as “train” (Step S207).

When a negative determination is made in step S206, the movement method determination unit 602B determines whether at least one of the start point and the end point is located on the bus route in light of the bus route map data stored in advance (step S206). S208) If at least one of the start point and the end point is located on the bus route, the moving method between the target point data is determined to be “bus” (step S209). On the other hand, if a negative determination is made in step S208, the moving method between the target point data is determined to be “automobile” (step S210).

Then, the movement method determination unit 602B stores the movement method information between the target point data obtained by the determination in the movement method information database 630 (step S211). At this time, the movement method determination unit 602B specifically adds the movement method information obtained by the determination to the line data of FIG. 18A temporarily stored in the position information analysis apparatus 600. 18B is generated, and the generated line data of FIG. 18B (line data to which movement method information is added) is stored in the movement method information database 630 as movement method information.

The processes in steps S201 to S211 as described above are executed for the next adjacent point data in the point data arranged in time series of the target user, and thereafter, the processes in steps S201 to S211 are performed until the execution is completed for all point data. The process is repeated. Then, when the execution is completed for all point data, the processing of FIG. 4 is terminated and the processing returns to FIG.

In step S3, the movement trajectory deriving unit 603 reads map data from the map database 620, and thereafter executes the movement trajectory derivation processing in steps S4 to S6. In the present embodiment, a process for deriving a movement trajectory regarding a line to be processed using a certain line data regarding the target user as a processing target will be described.

In step S4, the movement trajectory deriving unit 603 determines a movement method before and after a certain point from the line data to be processed. In the example of processing in order from the oldest in time series for the line with line identifier L0001 in FIG. 18B, in step S4, the moving method before and after the second point data P1002 from the oldest is determined. Then, it is determined that the previous movement method is “walk” and the subsequent movement method is “bus”.

In the next step S5, the movement trajectory deriving unit 603 executes any one of nine correction processes A to I according to the combination of the previous movement method and the subsequent movement method. Here, as shown in FIG. 5, a correction process (any one of correction processes A to I) corresponding to the combination of the previous movement method and the subsequent movement method is executed. Hereinafter, each correction process will be described. In the following description, the point data to be determined in step S4 is referred to as “second point data”, the previous point data is “first point data”, and the subsequent point data is “third point data”. "

FIG. 5 shows the case where the movement method between the first and second point data is either walking, bicycle, or automobile and the movement method between the second and third point data is also walking, bicycle, or automobile. As described above, the correction process A is executed. In the correction process A, as shown in FIG. 6A, the positions of the first, second, and third point data on the map obtained from the map data are moved to the nearest road, respectively. The position information of the second and third point data is corrected (step A1). For example, when the positions of the first, second, and third point data on the map are represented by the points P1, P2, and P3 in FIGS. 7A and 7B, the arrows Q1 and Q2 in FIG. , Q3, the positions of the points P1, P2, and P3 are moved to the nearest roads, respectively, and corrected to new positions R1, R2, and R3.

When the moving method between the first and second point data is a train and the moving method between the second and third point data is also a train, the correction process B is executed as shown in FIG. In the correction process B, as shown in FIG. 6B, the positions of the first, second, and third point data on the map obtained from the map data are moved to the nearest train route, respectively. The position information of the first, second, and third point data is corrected (step B1). The correction method of such correction processing B is the same as the correction method of correction processing A described above.

When the movement method between the first and second point data is a bus and the movement method between the second and third point data is also a bus, the correction process C is executed as shown in FIG. In the correction process C, as shown in FIG. 6C, the positions of the first, second and third point data on the map obtained from the map data are moved to the nearest bus route, respectively. The position information of the first, second and third point data is corrected (step C1). The correction method of such correction processing C is the same as the correction method of correction processing A described above.

When the movement method between the first and second point data is either walking, bicycle, or automobile, and the movement method between the second and third point data is a train, correction processing D is executed as shown in FIG. Is done. In the correction process D, as shown in FIG. 8 (a), the positions of the first and second point data on the map obtained from the map data are moved to the nearest road, and the position of the third point data is the most. The position information of the first, second, and third point data is corrected by moving it on the nearest train route (step D1), and new point data (points on the station) on the nearest station from the second point data (Also referred to as “station point data” in the sense of data) (step D2), and the movement method between the second point data and the station point data is set to the same movement method as between the first and second point data. The movement method between the station point data and the third point data is set to the train (step D3). For example, when the positions of the first, second and third point data on the map are represented by points P4, P5 and P6 in FIGS. 9A and 9B, arrows Q4 and Q5 in FIG. As shown, the positions of the points P4 and P5 are moved to the nearest roads, respectively, and corrected to new positions R4 and R5. Further, as indicated by an arrow Q6 in FIG. 9B, the position of the point P6 is moved to the nearest train route and corrected to a new position R6. Then, a station point ST is generated as new point data on the nearest station from the corrected point R5, and the movement method between the point R5 and the station point ST is the same as that between the first and second point data. The method is set, and the moving method between the station point ST and the corrected point R6 is set to the train.

When the movement method between the first and second point data is walking, bicycle, or automobile, and the movement method between the second and third point data is a bus, the correction process E is executed as shown in FIG. Is done. In the correction process E, as shown in FIG. 8 (b), the positions of the first and second point data on the map obtained from the map data are moved to the nearest road, and the position of the third point data is the most. By moving to the nearest bus route, the position information of the first, second and third point data is corrected (step E1), and new point data (on the bus stop) is placed on the bus stop closest to the second point data. (Also referred to as “bus stop point data”) (step E2), and the movement method between the second point data and the bus stop point data is changed to the same movement method as between the first and second point data. Then, the movement method between the bus stop point data and the third point data is set to the bus (step E3). Such a correction method of the correction process E is the same as the correction method of the correction process D described above, and corresponds to a process in which “station” is replaced with “bus stop” in the above-described processing example of FIG.

When the movement method between the first and second point data is a train and the movement method between the second and third point data is any one of walking, bicycle, and automobile, a correction process F is executed as shown in FIG. Is done. In the correction processing F, as shown in FIG. 10 (a), the position of the first point data on the map obtained from the map data is moved to the nearest train route, and the positions of the second and third point data are moved. By moving on the nearest road, the position information of the first, second, and third point data is corrected (step F1), and new point data (points on the station) on the nearest station from the second point data. (Also referred to as “station point data” in the sense of data) (step F2), the movement method between the first point data and the station point data is set to the train, and between the station point data and the second point data The movement method is set to the same movement method as that between the second and third point data (step F3). For example, when the positions of the first, second, and third point data on the map are represented by points P7, P8, and P9 in FIGS. 11A and 11B, they are indicated by an arrow Q7 in FIG. As described above, the position of the point P7 is moved to the nearest train route and corrected to a new position R7. Further, as indicated by arrows Q8 and Q9 in FIG. 11B, the positions of the points P8 and P9 are moved to the nearest roads, respectively, and corrected to new positions R8 and R9. Then, a station point ST is generated as new point data on the station closest to the corrected point R8, the movement method between the corrected point R7 and the station point ST is set to the train, and the station point ST and The movement method between the corrected points R8 is set to the same movement method as between the second and third point data.

When the movement method between the first and second point data is a bus and the movement method between the second and third point data is any one of walking, bicycle, and automobile, a correction process G is executed as shown in FIG. Is done. In the correction process G, as shown in FIG. 10B, the position of the first point data on the map obtained from the map data is moved to the nearest bus route, and the positions of the second and third point data are respectively determined. By moving to the nearest road, the position information of the first, second, and third point data is corrected (step G1), and new point data (on the bus stop) on the nearest bus stop from the second point data. (Also called “bus stop point data”) (step G2), and the movement method between the first point data and the bus stop point data is set to the bus, and between the bus stop point data and the second point data. Is set to the same movement method as that between the second and third point data (step G3). The correction method of the correction processing G is the same as the correction method of the correction processing F described above, and corresponds to the processing in which “station” is replaced with “bus stop” in the processing example of FIG. 11 described above.

When the movement method between the first and second point data is a bus and the movement method between the second and third point data is a train, a correction process H is executed as shown in FIG. In the correction process H, as shown in FIG. 12, the positions of the first and second point data on the map obtained from the map data are moved to the nearest bus route, and the position of the third point data is moved to the nearest train. By moving on the route, the position information of the first, second and third point data is corrected (step H1), and new bus stop point data is generated on the bus stop closest to the second point data (step) H2), the movement method between the second point data and the bus stop point data is set to the bus (step H3). Then, new station point data is generated on the nearest station from the bus stop point data (step H4), the movement method between the bus stop point data and the station point data is set to walk, and the station point data and the third point are set. The movement method between data is set to a train (step H5). For example, when the positions of the first, second, and third point data on the map are represented by points P10, P11, and P12 in FIGS. 13A and 13B, the arrows Q10 and Q11 in FIG. As shown, the positions of the points P10 and P11 are moved to the nearest bus route, respectively, and are corrected to new positions R10 and R11. Further, as indicated by an arrow Q12 in FIG. 13B, the position of the point P12 is moved to the nearest train route and corrected to a new position R12. Then, a bus stop point BS is generated as new point data on the bus stop closest to the corrected point R11, and the movement method between the corrected point R11 and the bus stop point BS is set to the bus. Furthermore, a station point ST is generated as new point data on the station closest to the bus stop point BS, and the movement method between the bus stop point BS and the station point ST is set to walking, and the station point ST and the corrected point data are set. The movement method between the points R12 is set to the train.

When the movement method between the first and second point data is a train and the movement method between the second and third point data is a bus, the correction process I is executed as shown in FIG. In the correction process I, as shown in FIG. 14, the position of the first point data on the map obtained from the map data is moved to the nearest train route, and the positions of the second and third point data are moved to the nearest bus. By moving on the route, the position information of the first, second and third point data is corrected (step I1), and new bus stop point data is generated on the bus stop closest to the second point data (step 1). I2), the movement method between the bus stop point data and the second point data is set to the bus (step I3). Then, new station point data is generated on the nearest station from the bus stop point data (step I4), the movement method between the station point data and the bus stop point data is set to walking, and the first point data and the station point are set. The movement method between data is set to a train (step I5). For example, when the positions of the first, second, and third point data on the map are represented by points P13, P14, and P15 in FIGS. 15A and 15B, they are indicated by an arrow Q13 in FIG. 15B. As described above, the position of the point P13 is moved to the nearest train route and corrected to a new position R13. Further, as indicated by arrows Q14 and Q15 in FIG. 15B, the positions of the points P14 and P15 are moved to the nearest bus routes, respectively, and corrected to new positions R14 and R15. Then, a bus stop point BS is generated as new point data on the bus stop closest to the corrected point R14, and the movement method between the bus stop point BS and the point R14 is set to the bus. Further, a station point ST is generated as new point data on the station closest to the bus stop point BS, and the movement method between the station point ST and the bus stop point BS is set to walk, and the corrected point R13 and the station are set. The movement method between points ST is set to a train.

Returning to FIG. 3, after executing the correction process (any one of the correction processes A to I) according to the combination of the previous movement method and the subsequent movement method as described above, in the next step S6, the movement trajectory deriving unit In step 603, the movement trajectory information is obtained by connecting the points with the shortest path corresponding to the movement method between the point data obtained in step S5 as follows. That is, in step S6 after any of the correction processes A to C, the positions of the first, second, and third point data on the map are moved by connecting them by the shortest path according to the movement method between the point data. Find trajectory information. In step S6 after the correction process D or E, the positions of the first point data, the second point data, the new point data, and the third point data on the map are displayed on the shortest path according to the movement method between the point data. The movement trajectory information is obtained by tying. In step S6 after the correction process F or G, the positions of the first point data, the new point data, the second point data, and the third point data on the map are displayed on the shortest path according to the movement method between the point data. The movement trajectory information is obtained by tying. In step S6 after the correction process H, the position of the first point data, the second point data, the bus stop point data, the station point data, and the third point data on the map is changed to the shortest route according to the movement method between the point data. The movement trajectory information is obtained by connecting with. In step S6 after the correction process I, the positions of the first point data, the station point data, the bus stop point data, the second point data, and the third point data on the map are changed to the shortest route according to the movement method between the point data. The movement trajectory information is obtained by connecting with. As described above, for example, according to the movement method between the point data as shown by bold lines in FIGS. 7B, 9B, 11B, 13B, and 15B. “Movement trajectory information” corresponding to the shortest path is obtained.

Thereafter, the processing of steps S4 to S6 is executed in order from the oldest in the time series for each point data in the line data to be processed. When the execution is completed for all point data in the line data to be processed, an affirmative determination is made in step S7 in FIG. 3, and the process proceeds to the next step S8, where the movement locus storage unit 604 moves the movement derived by the movement locus derivation unit 603. Save trajectory information.

In the above embodiment, for the sake of simplicity, an example has been described in which one line data relating to one user is processed as a processing target. However, although not illustrated in FIG. Thus, a large number of line data related to a large number of users can be processed as processing targets. In this case, the movement trajectory information about a large number of derived line data of a large number of users is stored by the movement trajectory storage unit 604.

In step S9, the reading unit 605 reads the stored movement trajectory information of a large number of users, and the output unit 606 outputs statistical information based on the read moving trajectory information of the many users. For example, as analysis data regarding macroscopic population flow, statistical information indicating the movement trajectory of residents moving from one area to another is output. Note that the stored movement trajectory information for each user is considered so as not to be output, so that the privacy of the individual user is not violated. Thus, the process of FIG. 3 is completed.

According to the above-described embodiment, the user's movement trajectory with respect to a large number of line data of a large number of users without using an expensive instrument such as an acceleration sensor or a speed center after appropriately determining the movement method of the user. Can be easily obtained. Thereby, the analysis data (statistical information based on movement trace information of many users) regarding macroscopic population flow can be obtained.

[Second Embodiment]
By the way, in order to obtain movement trajectory information, movement method information between point data adjacent in time series is required. In a situation where movement method information between point data is acquired in advance, position information analysis is performed. The apparatus can employ the second embodiment in which stored movement method information is input and subsequent processing is performed without obtaining movement method information between point data. Hereinafter, the position information analysis apparatus according to the second embodiment will be described.

As illustrated in FIG. 19, the position information analysis apparatus 600 according to the second embodiment includes an input unit 607, a movement locus derivation unit 603, a movement locus storage unit 604, a reading unit 605, and an output unit 606. The correspondence between the logical configuration in FIG. 19 and the system configuration in FIG. 1 is the same as the correspondence relationship between the logical configuration in FIG. 2 and the system configuration in FIG. .

The input unit 607 inputs point data classified for each user over a plurality of times from the position information database 610, and inputs movement method information between adjacent point data on the time series from the movement method information database 630.

The movement trajectory deriving unit 603 relates to the movement method information between the input point data, the position information included in the input point data, and the roads on the map and public transportation routes stored in the map data DB 620 in advance. Based on the position data, the movement trajectory information on the map is obtained for each user.

The position information analysis process executed by the position information analysis apparatus 600 according to the second embodiment is the process shown in FIG. First, in step S0 of FIG. 20, the input unit 607 inputs point data classified for each user over a plurality of times from the position information database 610, and information on movement methods between adjacent point data in time series. Is input from the movement method information database 630. Then, in the next step S3, the movement trajectory deriving unit 603 reads map data including position data regarding roads and public transport routes on the map from the map data DB 620.

The subsequent processing in steps S4 to S9 is the same as the processing in steps S4 to S9 in FIG.

Also in the position information analysis apparatus according to the second embodiment as described above, the user's movement trajectory for a large number of line data of a large number of users can be easily obtained without using an expensive instrument such as an acceleration sensor or a speed center. be able to. Thereby, the analysis data (statistical information based on movement trace information of many users) regarding macroscopic population flow can be obtained.

In the first and second embodiments described above, the movement trajectory deriving unit 603 includes the movement method information between the point data, the position information included in each point data, and the road and public transportation route on the map. Although the example which calculates | requires the movement trace information on a map for each user based on the positional data regarding both was demonstrated, the positional data here should be positional data regarding both the road and the route of public transport on a map Is not essential, and may be position data relating to at least one of roads and public transportation routes on the map.

DESCRIPTION OF SYMBOLS 10 ... Communication system, 100 ... Mobile equipment, 200 ... BTS, 300 ... RNC, 400 ... Switch, 500 ... Management center, 501 ... Social sensor unit, 502 ... Petamining unit, 503 ... Mobile demography unit, 504 ... Visualization solution Unit: 600 ... Position information analyzer, 601 ... Classification unit, 602 ... Determining unit, 602A ... Movement speed calculation unit, 602B ... Movement method determination unit, 603 ... Movement locus deriving unit, 604 ... Movement locus storage unit, 605 ... Reading Part 606 ... output part 607 ... input part 610 ... location information database 620 ... map database 630 ... movement method information database 700 ... various processing nodes.

Claims

Point data including position information indicating a user's position, time information at which the position information was obtained, and user identification information of the user, the point data over a plurality of times for a plurality of users, A classification unit that classifies each user and arranges them in chronological order;
A determination unit that determines, for each user, a movement method between point data adjacent in time series based on point data for each user over the plurality of times and route map data of public transportation stored in advance; ,
Based on the movement method information between each point data obtained by the determination, the position information included in each point data, and the position data on at least one of the road and the public transportation route on the map stored in advance, A movement trajectory derivation unit for obtaining movement trajectory information on the map for each user;
A movement trajectory storage unit that saves movement trajectory information for each derived user;
A position information analyzing apparatus.
The determination unit
In the point data for each user over the plurality of times, a distance and time difference between adjacent point data in time series are obtained, and a moving speed between the point data is calculated based on the distance and time difference between the point data. A moving speed calculator,
A moving method for determining a moving method between point data based on the calculated moving speed between the point data, position information included in the point data, and route map data of the public transportation stored in advance. A determination unit;
The position information analyzer according to claim 1, comprising:
Point data including position information indicating the position of the user, time information at which the position information is obtained, and user identification information of the user, the point data classified for each user over a plurality of times, and time series An input unit for inputting movement method information between adjacent point data above,
Based on the inputted movement method information between each point data, the position information included in each point data, and the position data relating to at least one of the road and the public transportation route on the map stored in advance A movement trajectory deriving unit for obtaining the movement trajectory information for each user;
A movement trajectory storage unit that saves movement trajectory information for each derived user;
A position information analyzing apparatus.
A reading unit that reads out movement trajectory information of a plurality of users stored by the movement trajectory storage unit;
An output unit that outputs statistical information based on the read movement trajectory information of the plurality of users;
The positional information analysis apparatus according to any one of claims 1 to 3, further comprising:
The movement trajectory deriving unit
Three point data that are adjacent on the time series are designated as the first point data, the second point data, and the third point data in order from the oldest, and the movement between the first and second point data in the three point data. When the method is either walking, bicycle, or car, and the moving method between the second and third point data is any of walking, bike, or car, the first and second on the map By correcting the position information of the first, second and third point data by moving the position of the third point data to the nearest road,
Obtaining the movement trajectory information by connecting the positions of the first, second and third point data on the map by the shortest path according to the movement method between the point data;
The position information analyzing apparatus according to any one of claims 1 to 4, wherein the position information analyzing apparatus is characterized in that:
The movement trajectory deriving unit
Three point data that are adjacent on the time series are designated as the first point data, the second point data, and the third point data in order from the oldest, and the movement between the first and second point data in the three point data. When the method is a train and the subsequent movement method between the second and third point data is a train, the positions of the first, second, and third point data on the map are on the nearest train route, respectively. To correct the position information of the first, second and third point data,
Obtaining the movement trajectory information by connecting the positions of the first, second and third point data on the map by the shortest path according to the movement method between the point data;
The position information analyzing apparatus according to any one of claims 1 to 4, wherein the position information analyzing apparatus is characterized in that:
The movement trajectory deriving unit
Three point data that are adjacent on the time series are designated as the first point data, the second point data, and the third point data in order from the oldest, and the movement between the first and second point data in the three point data. If the method is a bus and the subsequent movement method between the second and third point data is a bus, the positions of the first, second, and third point data on the map are on the nearest bus route, respectively. To correct the position information of the first, second and third point data,
Obtaining the movement trajectory information by connecting the positions of the first, second and third point data on the map by the shortest path according to the movement method between the point data;
The position information analyzing apparatus according to any one of claims 1 to 4, wherein the position information analyzing apparatus is characterized in that:
The movement trajectory deriving unit
Three point data that are adjacent on the time series are designated as the first point data, the second point data, and the third point data in order from the oldest, and the movement between the first and second point data in the three point data. When the method is either walking, bicycle, or car, and the moving method between the second and third point data is a train, the positions of the first and second point data on the map are closest. By moving on the road and moving the position of the third point data on the nearest train route, the position information of the first, second and third point data is corrected, and the second point data is A new point data is generated on a nearby station, and a movement method between the second point data and the new point data is defined as the first and second points. The same movement method as that between the data, and the movement method between the new point data and the third point data is set to a train, and the first point data, the second point data, and the The movement trajectory information is obtained by connecting the new point data and the position of the third point data by the shortest path according to the movement method between the point data.
The position information analyzing apparatus according to any one of claims 1 to 4, wherein the position information analyzing apparatus is characterized in that:
The movement trajectory deriving unit
Three point data that are adjacent on the time series are designated as the first point data, the second point data, and the third point data in order from the oldest, and the movement between the first and second point data in the three point data. If the method is walking, bicycle, or car, and the subsequent moving method between the second and third point data is a bus, the positions of the first and second point data on the map are closest. By moving on the road and moving the position of the third point data on the nearest bus route, the position information of the first, second and third point data is corrected, and the second point data is A new point data is generated on a nearby bus stop, and a movement method between the second point data and the new point data is defined as the first and second points. The same movement method as that between the point data, the movement method between the new point data and the third point data is set in the bus, the first point data, the second point data on the map, and the The movement trajectory information is obtained by connecting the new point data and the position of the third point data by the shortest path according to the movement method between the point data.
The position information analyzing apparatus according to any one of claims 1 to 4, wherein the position information analyzing apparatus is characterized in that:
The movement trajectory deriving unit
Three point data that are adjacent on the time series are designated as the first point data, the second point data, and the third point data in order from the oldest, and the movement between the first and second point data in the three point data. When the method is a train and the subsequent movement method between the second and third point data is any one of walking, bicycle, and automobile, the position of the first point data on the map is on the nearest train line. The position information of the first, second, and third point data is corrected by moving the position of each of the second and third point data onto the nearest road, Generate new point data on a nearby station, set the movement method between the first point data and the new point data to a train, and The movement method between the point data and the second point data is set to the same movement method as that between the second and third point data, and the first point data, the new point data, and the second point data on the map are set. The movement trajectory information is obtained by connecting the positions of the two point data and the third point data by the shortest path according to the movement method between the point data.
The position information analyzing apparatus according to any one of claims 1 to 4, wherein the position information analyzing apparatus is characterized in that:
The movement trajectory deriving unit
Three point data that are adjacent on the time series are designated as the first point data, the second point data, and the third point data in order from the oldest, and the movement between the first and second point data in the three point data. If the method is a bus, and the subsequent movement method between the second and third point data is walking, bicycle, or car, the position of the first point data on the map is on the nearest bus route. The position information of the first, second, and third point data is corrected by moving the position of each of the second and third point data onto the nearest road, Generate new point data on a nearby bus stop, set the movement method between the first point data and the new point data to the bus, The movement method between the new point data and the second point data is set to the same movement method as between the second and third point data, and the first point data and the new point data on the map The movement trajectory information is obtained by connecting the positions of the second point data and the third point data by the shortest path according to the movement method between the point data.
The position information analyzing apparatus according to any one of claims 1 to 4, wherein the position information analyzing apparatus is characterized in that:
The movement trajectory deriving unit
Three point data that are adjacent on the time series are designated as the first point data, the second point data, and the third point data in order from the oldest, and the movement between the first and second point data in the three point data. If the method is a bus and the subsequent movement method between the second and third point data is a train, the position of each of the first and second point data on the map is moved to the nearest bus route, By moving the position of the third point data onto the nearest train route, the position information of the first, second and third point data is corrected, and a new bus stop is added from the second point data. Bus stop point data is generated, a movement method between the second point data and the bus stop point data is set in the bus, and the bus stop point is set. New station point data is generated on the nearest station from the data, the movement method between the bus stop point data and the station point data is set to walking, and the movement method between the station point data and the third point data The position of the first point data, the second point data, the bus stop point data, the station point data, and the third point data on the map according to the movement method between the point data The movement trajectory information is obtained by connecting with the shortest route.
The position information analyzing apparatus according to any one of claims 1 to 4, wherein the position information analyzing apparatus is characterized in that:
The movement trajectory deriving unit
Three point data that are adjacent on the time series are designated as the first point data, the second point data, and the third point data in order from the oldest, and the movement between the first and second point data in the three point data. When the method is a train and the subsequent movement method between the second and third point data is a bus, the position of the first point data on the map is moved to the nearest train route, and the second and third point data are moved. The position information of the first, second, and third point data is corrected by moving the position of each of the third point data onto the nearest bus route, and a new one is added on the bus stop nearest to the second point data. Bus stop point data is generated, a movement method between the bus stop point data and the second point data is set in the bus, and the bus stop point is set. Generate new station point data on the nearest station from the data, set the movement method between the station point data and the bus stop point data to walk, and move between the first point data and the station point data A method is set for a train, and the position of the first point data, the station point data, the bus stop point data, the second point data, and the third point data on the map is changed to a movement method between the point data. The movement trajectory information is obtained by connecting with the shortest route according to
The position information analyzing apparatus according to any one of claims 1 to 4, wherein the position information analyzing apparatus is characterized in that:
A location information analysis method executed in a location information analyzer,
Point data including position information indicating the position of the user, time information when the position information is obtained, and user identification information of the user, and the point data over a plurality of times for a plurality of users. A classification step that inputs to the analysis device, classifies for each user, and arranges them in time series;
A determination step of determining, for each user, a moving method between point data adjacent in time series based on the point data for each user over the plurality of times and route map data of public transportation stored in advance; ,
Based on the movement method information between each point data obtained by the determination, the position information included in each point data, and the position data on at least one of the road and the public transportation route on the map stored in advance, A movement locus deriving step for obtaining movement locus information on the map for each user;
A movement trajectory saving step for saving movement trajectory information for each derived user;
A location information analysis method comprising:
A location information analysis method executed in a location information analyzer,
Point data including position information indicating the position of the user, time information at which the position information is obtained, and user identification information of the user, the point data classified for each user over a plurality of times, and time series An input step for inputting movement method information between adjacent point data to the position information analyzer,
Based on the inputted movement method information between each point data, the position information included in each point data, and the position data relating to at least one of the road and the public transportation route on the map stored in advance A movement trajectory derivation step for obtaining the movement trajectory information for each user;
A movement trajectory saving step for saving movement trajectory information for each derived user;
A location information analysis method comprising: