JP4395596B2 - Congestion analysis system - Google Patents

Description

  The present invention relates to a system for analyzing the degree of congestion in a certain space indoors and outdoors based on a user's flow line.

When considering spaces such as expositions, exhibitions, museums, office buildings, homes, outdoor event spaces such as street corners and suburbs, and store spaces, users (mobile objects such as people and cars) In other words, it is necessary to specify various services for users such as information distribution and travel guidance according to the congestion situation. It is extremely important to provide user modeling, trend analysis, and spatial layout appropriately. In this congestion analysis, the user's flow line, that is, the temporal change in movement, is one important factor. It is thought that.
Japanese Patent Laid-Open No. 5-46591 Japanese Patent Laid-Open No. 7-220088 JP 2002-109135 A JP 2003-242333 A JP 2004-178276 A JP 2004-196553 A Japanese Patent Publication No. 5-11891

  However, a system for analyzing a customer flow line described in Patent Document 1, a system for analyzing a moving object existence probability described in Patent Document 2, a system for analyzing customer trends described in Patent Documents 3 and 4, Movement management and movement based on position information such as a system that supports store planning by measuring visitor flow described in Patent Document 5 and a person or a moving device that moves in a predetermined area such as in a building described in Patent Document 6 In conventional systems such as systems that perform analysis and distribution management in warehouses, and systems that detect consumer trends described in Patent Document 7 in time series and grasp store conditions, focus on a certain area in the space where congestion analysis is performed. No technical idea has been presented in consideration of the degree of congestion analysis from the viewpoint of moving it in the space as a “window” and capturing the movement flow of the user group in it.

  Therefore, in view of the circumstances as described above, the present invention focuses on a certain area in indoor and outdoor spaces, and analyzes the movement flow line of the user group for each attention area “window”, thereby causing congestion. It is possible to accurately identify the location where the user is moving, and by analyzing the movement flow line of the user group, it is also possible to identify the location where congestion is likely to occur regularly, and thus the degree of congestion that can analyze the degree of congestion in the entire space It is an object to provide an analysis system, a congestion degree analysis method, a congestion degree analysis program, and a recording medium thereof.

The present invention, as to solve the above problems, the first time t _0, t _1, · · ·, to obtain position information of each user for each t _n, the point to be analyzed in space it means for recording as p, means for selecting the time t _i when the most position information or the number of position information exceeding the threshold is acquired, and selecting the point p _i belonging to the analysis target space at time t _i , means for setting a region of interest in the analysis target space so that _pi is the center, a point of interest that is moved in a range including the point p _i in the analysis target space at time t _i , and points included in the region of interest at each movement means for determining the number n of the p, counted means the number n is selected the number n _i of points contained in the region of interest at that time the position w _i of the region of interest to be a maximum, and elected number n _i attention When the allowable capacity of the area is exceeded, the time t _i , the position w _i , and the number n _i are Provided is a congestion degree analysis system characterized by comprising means for registering in a database as congestion point data.

Second, all the points included in the attention area at the position w _i are removed from the set of points p belonging to the analysis target space at time t _i , and the selection of the point p _i , the setting of the attention area, and the attention are performed for the remaining points. The congestion degree analysis system is characterized in that it repeats the movement of the area, the count of the number n, the selection of the positions w _i and the number n _i , and the determination of the allowable accommodation number and the data registration.

Third, there is further provided means for acquiring the user's velocity vector simultaneously with the acquisition of the user's position, and the region of interest is acquired in a range including the point p _i in the analysis target space at time t _i. The congestion degree analysis system is characterized in that it is moved based on a vector.

Fourthly, the congestion degree analysis system further includes means for presenting the number n _i of the registered congestion point data to the user as the number of users existing at the congestion point. .

Fifth, the apparatus further comprises means for presenting a numerical value obtained by dividing the number n _i of the registered congestion point data by the allowable accommodation number to the user as the degree of congestion at the congestion point. Provide a congestion analysis system.

Sixth, an arbitrary one congestion point c _j is extracted from the registered congestion point group, and other congestion points overlapping in the analysis target space on the time axis from the time t _i of the congestion point c _j. When the time of the congestion point c _j is calculated by calculating the time change with the other congestion point searched and the time when the overlapping congestion point exists is larger than the threshold compared with the total length of time. The congestion level analysis system is characterized in that the congestion point is a regular congestion point.

  Seventhly, the congestion is further characterized by further comprising means for displaying the number of users existing at the congestion point, the degree of congestion at the congestion point, or the regular congestion point in a superimposed manner with map data. Provide a degree analysis system.

  Eighth, the allowable capacity of the attention area is calculated by multiplying the area of the attention area by the allowable congestion degree when the analysis target space is a two-dimensional space, and the analysis target space is defined as a three-dimensional space. In such a case, the congestion level analysis system is calculated by dividing the volume of the region of interest by the allowable congestion level.

Ninth, when the analysis target space is a two-dimensional space, the allowable congestion level is the number of users allowed per unit area when the analysis target space is a three-dimensional space. The congestion degree analysis system is provided.

  Tenth, the region of interest has a two-dimensional shape when the analysis target space is a two-dimensional space, and has a three-dimensional shape when the analysis target space is a three-dimensional space. The congestion level analysis system is provided.

In the eleventh aspect of the present invention, the step of acquiring position information of each user at each time t ₀ , t ₁ ,..., T _n and recording it as a point p in the analysis target space, turn much position information or the step of the location information of the number is selected the obtained time t _i that exceeds the threshold value, and selects the p _i points belonging to the analysis the space of time t _i, such that the point p _i are central A step of setting a region of interest in the analysis target space, a step of moving the region of interest within a range including the point p _i in the analysis target space at time t _i , and obtaining the number n of points p included in the region of interest at each movement A step of selecting the position w _{i of the} attention area where the counted number n is maximum and the number n _i of points included in the attention area at that time, and the selected number n _i exceeds the allowable capacity of the attention area The time t _i , the position w _i , and the number n _i are congested The present invention provides a method for analyzing the degree of congestion, comprising the step of registering in a database as point data.

Twelfth, all the points included in the attention area at the position w _i are removed from the set of points p belonging to the analysis target space at time t _i , and the selection of the point p _i , the setting of the attention area, and the attention are performed for the remaining points. The congestion degree analysis method is characterized by repeating the movement of the area, counting the number n, selecting the position w _i and the number n _i , and determining the allowable capacity and registering data.

13thly, a user's speed vector is acquired simultaneously with a user's position acquisition, and the said attention area is moved based on the acquired speed vector in the range containing point p _i in the analysis object space of time t _i . The congestion degree analyzing method is provided.

14thly, the said congestion degree analysis method characterized by presenting the number n _i of the registered congestion point data to the user as the number of users existing at the congestion point.

Fifteenth, the congestion degree analysis method characterized in that a numerical value obtained by dividing the number n _i of the registered congestion point data by the allowable capacity is presented to the user as the degree of congestion at the congestion point. provide.

Sixteenth, an arbitrary one congestion point c _j is extracted from the registered congestion point group, and another congestion point overlapping in the analysis target space on the time axis from the time t _i of the congestion point c _j. When the time of the congestion point c _j is calculated by calculating the time change with the other congestion point searched and the time when the overlapping congestion point exists is larger than the threshold compared with the total length of time. The congestion level analysis method is characterized in that the congestion point is a regular congestion point.

  Seventeenth, the congestion degree analysis method is characterized in that the number of users existing at the congestion point, the degree of congestion at the congestion point, or the regular congestion point is displayed superimposed on map data. To do.

  Eighteenthly, when the analysis target space is a two-dimensional space, the allowable capacity of the attention region is calculated by multiplying the area of the attention region by the allowable congestion degree, and the analysis target space is defined as a three-dimensional space. In such a case, the congestion degree analysis method is characterized by being calculated by dividing the volume of the region of interest by the allowable congestion degree.

  Nineteenth, the allowable congestion level is the number of users per unit area when the analysis target space is a two-dimensional space, and the number of users per unit volume when the analysis target space is a three-dimensional space. The congestion degree analyzing method is provided.

  20th, the region of interest has a two-dimensional shape when the analysis target space is a two-dimensional space, and has a three-dimensional shape when the analysis target space is a three-dimensional space. The congestion degree analysis method is provided.

  The present invention provides, in a twenty-first aspect, a congestion degree analysis program for causing a computer to execute the congestion degree analysis method, and in a twenty-second aspect, a computer-readable recording medium in which the congestion degree analysis program is recorded. .

  According to the first to third congestion analysis systems, as described above, pay attention to a certain area in the indoor / outdoor space, set it as the attention area “window”, and move the user group while moving in the space. By analyzing the movement flow line, it is possible to accurately identify the place where the congestion is occurring. By performing this comprehensively for the entire space, it becomes possible to identify the congestion point in the entire space, that is, analyze the degree of congestion.

  According to the fourth to sixth congestion analysis systems, the same effects as those of the first to third systems can be obtained, and the analysis results can be digitized and provided to the user. Can be provided to users.

  According to the seventh congestion level analysis system, the same effects as those of the first to third systems can be obtained, and the congestion is constantly performed by performing an analysis in which the movement lines of the user group are superimposed. It is also possible to specify a place where the occurrence of the problem is likely to occur, so that the degree of congestion of the entire space can be analyzed from the viewpoint of continuity.

  According to the eighth to tenth congestion analysis systems, the same effects as those of the first to ninth systems can be obtained. Even when the space is expressed as two-dimensional or three-dimensional, the congestion degree analysis is performed. Can be executed accurately, and congestion points can be identified.

  In addition, according to the 11th to 20th congestion degree analysis methods, a method is obtained in which the same effects as those of the first to 10th congestion degree analysis systems can be obtained.

  According to the 21 congestion degree analysis program and the 22nd recording medium, a computer program capable of obtaining the same effect as the 11th to 20th congestion degree analysis methods, and a flexible disk or CD on which the computer program is recorded, A recording medium such as a DVD is realized.

<Attention area "Window">
In the present invention, when performing the congestion degree analysis, as shown in FIG. 1, an area to be noted in the analysis target space is considered, and this is referred to as a “window”, and the virtual analysis target space created on the computer Set to. In other words, an actual analysis target space is virtually represented on a computer, and an attention area “window” is set in this space. At this time, when the analysis target space is expressed as a two-dimensional space, a two-dimensional window such as a rectangle or a circle can be considered, and when a three-dimensional space is used, a three-dimensional window such as a rectangular parallelepiped or a sphere can be considered. FIG. 1 shows a rectangular window in the case of a two-dimensional space as an example. In the example of FIG. 1, the position information of the user is represented in the space as a point p as will be described later.

  The “window” is used together with the movement flow line of the user group in each processing step to be described later, thereby performing the congestion degree analysis.

<Congestion analysis system>
As a system for performing the congestion degree analysis based on the “window” as described above, for example, a system having the configuration illustrated in FIG. 2 can be considered.

  The system configuration of FIG. 3 includes a sensor system 10, a database system 100, a sensor database 110, a layout database 120, a congestion information database 130, an analysis module 200, and a display 300.

  The layout database 120, which is a subsystem of the database system 100, stores initial data (which can be called layout data) such as the size (area / volume), shape, section, and object arrangement related to the analysis target space. Data is provided to all other modules. Further, the congestion information database 130, which is another subsystem, stores information related to the congestion point as an analysis result.

  The sensor system 10 uses, for example, a portable information terminal device, a mobile phone, a PDA, a GPS, a wireless LAN, proximity wireless communication, an RFID tag, a network sensor, a speed sensor, and the like to acquire the current position and speed vector of the user, It is directly given to the analysis module 200 or stored in the sensor database 110 which is a subsystem of the database system 100. At this time, the position information is expressed as a point in a virtual analysis target space on the computer and sequentially stored in the database. In the case where the analysis target space is a two-dimensional space represented by x, y coordinate axes or the like or a three-dimensional space represented by x, y, z coordinate axes, etc., it may be point data composed of position coordinates or the like according to them. Although FIG. 1 illustrates the case of two dimensions, the same applies to three dimensions. On the other hand, the speed vector composed of the speed of movement and its direction can also be obtained by calculation from position information. As for the database, independent database systems such as a user position database and a user speed database may be constructed. What is common is that in this system, time is expressed discretely in the database, and even in continuous time, data contained in a minute time space is collected and handled as one discrete time. It is. The user information such as the position / speed information can be managed by using an anonymous ID that ensures anonymity in order to protect the user's privacy. Anonymous ID is an ID determined by this system or a portable information terminal device used by a user, and means something that cannot identify an individual.

  The analysis module 200 executes analysis processing as described later using user position information / speed information, layout data, and the like from the sensor system 10 and the database system 100, and is constructed as one module constituting the system. The In this case, by inputting the output data from the sensor system 10 directly to the analysis module 200, it is possible to provide a service even if the database system 100 does not exist. In this case, it is possible to provide a service at a higher speed. It is. Further, as illustrated in FIG. 2, it is possible to increase the speed by branching the output of the sensor system 10 into two and sending it to both the analysis module 200 and the database system 100. Further, the analysis module 200 can be constructed as an analysis computer system that can operate autonomously by itself even if there is no subsystem such as the sensor system 10 and the database system 100 as described above. In this case, the analysis module 200 itself is provided with means capable of acquiring position / velocity information, means for executing various processes, means for storing various data, and the like.

  Then, the sensor system 10, the database system 100, the analysis module 200, and the display system 300 are appropriately provided with a display unit 1 such as a display, an input unit 2 such as a keyboard and a mouse, a processing program, A main storage unit (main memory) 3 for storing various data, a processing unit (CPU) 4 for executing various processes in response to processing program instructions, a communication control unit 5 for controlling data communication with the outside, and storing various data The file system 6 and the bus 7 for connecting them to each other can be provided.

<Congestion level analysis processing>
Here, the congestion degree analysis by the system as described above will be described. FIG. 4 is a flowchart of the process.

<< Step S1-1 >>
First, the time t _0, t _1, · · ·, to obtain position information of each user in the analysis target space for each t _n. This can also be said to acquire the current position of the user in the analysis target space, that is, the flow line of the user. Then, as described above, the position information is expressed as points p in the analysis target space and sequentially recorded.

<< Step S1-2 >>
When acquiring the position, if it is possible to acquire the velocity vector of the user, that is, the moving speed and its direction, it is acquired simultaneously with the position acquisition and recorded together with the position information.

<< Step S2 >>
Subsequently, the number of position information is counted every time t ₀ , t ₁ ,..., T _n , and the time t _i when the most position information is acquired or the number exceeding the preset threshold value. The time t _i when the position information is acquired is selected from the position information data group in the database.

<< Step S3 >>
Subsequently, an arbitrary point p _i belonging to the selected analysis target space at time t _i is selected, and an attention area “window” is set so that the point is the center.

  The point pi can be selected either automatically on the computer side or on the computer side according to the input of an external selection instruction.

  The window can be set automatically on the computer side to have an arbitrary shape or size, or it can be set on the computer side in response to an input of an external setting instruction. In the latter case, the user position is distributed as a point in the analysis target space. Therefore, by looking at the distribution (displayed on the display system 300 in the above system configuration, for example), the shape and size of the window are determined. Select it and enter it.

<< Step S4 >>
Subsequently, in the space to be analyzed at time t _i , the attention area is moved within a range including the selected point p _i, and the number n of the points p included in the attention area at each movement is obtained by counting.

At this time, if the velocity vectors in step S1-2 is acquired on the basis of the velocity vectors obtained in the time t _i, a region of interest, including the point p _i in the analysis target space of time t _i Move by range.

<< Step s5 >>
Next, the position w _{i of the} attention area where the obtained number n is maximum and the number n _i of points included in the attention area at that time are selected.

<< Step S6 >>
It is determined whether the selected number n _i exceeds the allowable capacity of the attention area in the analysis target space at time t _i .

  More specifically, the allowable accommodation number is calculated for the window set as described above. When the analysis target space is a two-dimensional space, the allowable accommodation number = window area × allowable. When the degree of congestion is a three-dimensional space, it can be calculated by the allowable number of accommodations = window volume / allowable congestion level.

  The allowable congestion level is the number of users allowed per unit area in a two-dimensional space and per unit volume in a three-dimensional space. More specifically, the limit value for determining how many users (how many in the case of a person, how many in the case of a moving body) per unit area or unit volume of the analysis target space is determined to be congested. Is expressed. This value is given separately from the outside depending on the purpose of use of the system.

In the system configuration, the analysis module 200 reads the area / volume of the analysis target space and the allowable congestion level from the layout database 120, calculates the allowable capacity as described above, and calculates the calculated allowable capacity. It is determined whether or not n _i exceeds.

<< Step S7 >>
When it is determined that the allowable capacity is exceeded, the triple data {time t _i , position w _i , number n _i } is registered in the database as congestion point data.

<< Step S8 >>
Processing of S3 to S7 as described above (selection of point p _i , setting of attention area, movement of attention area, count of number n, selection of position w _i and number n _i , determination of allowable accommodation number, data registration) Is repeated for the remaining points p obtained by removing all the points included in the region of interest at the position w _i from the set of points p belonging to the analysis target space at time t _i .

Thus, the specific total congestion point in the analysis target space of time t _i is completed.

<< Step S9 >>
After that, the time t _i is removed from the time set T {t ₀ , t ₁ ,..., T _n }, and the processing of steps S3 to S8 is executed for each remaining time, and T becomes empty. Sometimes the analysis process ends.

  As described above, by paying attention to a certain area in the analysis target space, it is possible to accurately identify the congestion point according to the movement flow line of the user group for each area “window”. It is possible to identify the congestion point in the whole, ie, the degree of congestion.

<< Step S10 >>
The information on the congestion point stored in the database as the analysis result can be extracted at any time based on a request from the outside such as a user.

For example, if the data obtained by digitizing the congestion point is required, there congestion point data registered {time t _i, the position w _i, the number n _i} The number n _i of the "congestion point User The number can be presented to the user, or a numerical value obtained by dividing the number n _i by the allowable capacity can be presented as the “degree of congestion at the crowded point”.

  Furthermore, the congestion information is displayed as map information by displaying the “number of users present at the crowded point” and the “degree of congestion at the crowded point” (one or both of these) superimposed on the map data. It is also possible to provide as.

<< Steps S10-1 to 10-6 >>
In this system, it is also possible to identify a place where congestion is likely to occur regularly by executing the following processing (see FIG. 5).

First, an arbitrary one congestion point c _j is taken out from the registered congestion point group (step S10-1), and overlaps in the analysis target space that has moved back and forth on the time axis from the time t _i of the congestion point c _j. Are searched for (step S10-2).

The time change with the other congested spot searched is calculated to obtain the duration of the congested spot c _j (step S10-3), and the time when the overlapping congested spot exists is compared with the total length of time.

  Then, it is determined whether or not the time is greater than a preset threshold value (step S10-4). If it is determined that the time is larger, the congestion point is set as a regular congestion point (step S10-5). .

  In this way, it is possible to identify a place where regular congestion is likely to occur, and by providing this to the user (step S10-6), the user can know the regular congestion point in the space in advance, It can be used to adjust your own action plan. In addition, the space manager can use this to manage and change the space layout, planning, scheduling, etc. more appropriately.

The figure for demonstrating this invention. The block diagram of a congestion degree analysis system. The block diagram of each subsystem in a congestion analysis system. The flowchart of a congestion degree analysis. Another flowchart of a congestion degree analysis.

Explanation of symbols

1 Display unit 2 Input unit 3 Main storage unit (main memory)
4 processor (CPU)
5 Communication Control Unit 6 File System 7 Bus 10 Sensor System 100 Database System 110 Sensor Database 120 Layout Database 130 Congestion Information Database 200 Analysis Module 300 Display System

Claims (10)

Time t _0, t _1, ···, means for acquiring position information of each user for each t _n,
Means for recording the acquired position information of the user as a point p in the analysis target space;
Means for counting the number of position information at each time t ₀ , t ₁ ,..., T _n and selecting the time t _i at which the most position information or the number of position information exceeding the threshold is acquired;
Means for selecting the points p _i belonging to the analysis target space at the selected time t _i ;
Means for setting a region of interest in the analysis target space so that the selected point p _i is the center;
It means for moving in a range including the point p _i in the set region of interest analysis target space time t _i,
Means for counting the number n of points p included in the region of interest during each movement;
Means for selecting the position w _{i of the} region of interest where the counted number n is maximum and the number n _i of points included in the region of interest at that time ;
Means for storing an area or volume of a region of interest and an allowable congestion degree that is an allowable number of users per unit area or unit volume of an analysis target space;
Means for calculating the allowable capacity of the attention area by multiplying the area of the attention area by the allowable congestion degree or dividing the volume of the attention area by the allowable congestion degree;
Means for determining whether or not the selected number n _i exceeds the calculated allowable capacity of the attention area;
If it is determined that exceeds the allowable number of accommodating three pairs of data {time t _i, the position w _i, the number n _i}, characterized in that Ru comprising means for registering in the database as a congestion point data Congestion analysis system. From the set of p analysis points belonging to object space of the storage time t _i, the position registered w _i all up except rather means a point included in the region of interest
Further comprising
For the remaining points after removal, selection of point p _i , setting of attention area, movement of attention area, counting of number n, selection of position w _i and number n _i , determination of allowable accommodation number and data registration The congestion analysis system according to claim 1, wherein the congestion degree analysis system is repeated. It means for obtaining a velocity vector of the user position acquisition of the user at the same time, and the region of interest, in a range including the point p _i in the analysis target space of time t _i, means for moving based on the speed vectors obtained
The congestion degree analysis system according to claim 1 , further comprising: The number n _i of the congestion point data registered, congestion according to any one of claims 1 to 3, characterized in that it further Ru comprising means for presenting to the user a number of users present in the congestion point Analysis system. The number n _i of the congestion point data registered, the numerical values divided by the calculated number of allowed accommodated, characterized in that it further Ru comprising means for presenting to the user as the degree of congestion in the congested point claims The congestion analysis system according to any one of 1 to 3. Means to eject the any one of the congestion point c _j from congestion point group registered,
Means for searching for another congestion point that overlaps in the analysis target space on the time axis from the time t _{i of the} extracted congestion point c _j ;
Retrieved other congestion point and means Ru determined the duration of the time change calculated by the congestion point c _j, and the time overlapping congestion locations are present compared to the length of the total time larger than the threshold, Means to make the congestion point a regular congestion point
The congestion degree analysis system according to claim 1 , further comprising: Any said degree or the stationary congestion point congestion in the number of users or the congestion point exists in the congestion point, to 4 claims, characterized in that Ru, further comprising means for displaying by overlapping with the map data 6 Crazy degree analysis system described in Crab. 2. The region of interest has a two-dimensional shape when the analysis target space is a two-dimensional space, and has a three-dimensional shape when the analysis target space is a three-dimensional space. Thru | or 7 , the congestion analysis system.   Acquire user location information using a personal digital assistant, mobile phone, PDA, GPS, wireless LAN, proximity wireless communication, RFID tag, or network sensor
The congestion degree analysis system according to any one of claims 1 to 8,   Get user's velocity vector by velocity sensor
The congestion degree analysis system according to any one of claims 1 to 9.