Station premises people flow estimation device, station premises people flow estimation method, and station premises people flow estimation program

Abstract

To provide a station yard people flow estimation device, a station yard people flow estimation method and a station yard people flow estimation program which can improve estimation accuracy of people flow between a ticket gate and a platform of a station yard.SOLUTION: A station yard people flow estimation device comprises: collecting means (control unit 11) which dividedly collects the number of users of an estimation object station considered as an object of people flow estimation at least for each used ticket gate; and first division means (control unit 11) which divides the number of users collected by the collecting means, for each platform estimated to have been used.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a station premises people flow estimation device, a station premises people flow estimation method, and a station premises people flow estimation program. [Background technology]

[0002] Within a railway station, it is expected that there will be large differences in the flow of people, that is, the number of people passing through which points within the station, depending on various conditions such as the characteristics of the station (types of trains that enter, structure of the building, etc.) and the time of day.However, in order to provide users with appropriate services in accordance with the flow of people, and to take measures against accidents and train delays that arise from excessive congestion, it is necessary to understand the state of the flow of people within the station.

[0003] Therefore, a system for estimating the flow of people within a station is known (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2020-95292 Summary of the Invention [Problem to be solved by the invention]

[0005] Since most station users move between the ticket gates and the platforms where trains depart or arrive, the flow of people within a station is not completely random, and it is expected that users will concentrate on the route between the ticket gates and the platform. Therefore, when estimating the flow of people within a station, it is important to focus on the movement of station users between the ticket gates and the platform and to estimate the flow of people between the ticket gates and the platform within the station with high accuracy. However, conventional systems did not specifically focus on the movement of station users between ticket gates and platforms, and therefore were not necessarily able to accurately estimate the flow of people between ticket gates and platforms within stations.

[0006] An object of the present invention is to provide a station premises people flow estimation device, a station premises people flow estimation method, and a station premises people flow estimation program that enable improved accuracy in estimating people flow between ticket gates and platforms within a station premises. [Means for solving the problem]

[0007] In order to solve the above problem, the invention described in claim 1 is a station premises people flow estimation device, a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a first dividing means for dividing the number of users calculated by the calculating means for each platform that the users are estimated to have used; Equipped with 、 The counting means counts the number of users by dividing the number of users into exit stations for those entering the estimated target station and by entry stations for those leaving the estimated target station in addition to the number of users using the ticket gates, The first dividing means divides the number of users counted by the counting means into each platform that is estimated to have been used, using route-specific usage ratio information, which is information that predetermines the ratio of users for each route in a section where multiple routes exist. It is characterized by the following.

[0008] The invention described in claim 2 is ,station In the on-site people flow estimation device, a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a first dividing means for dividing the number of users calculated by the calculating means for each platform that the users are estimated to have used; a second dividing means for dividing the number of users divided by the first dividing means into passages that are estimated to have been used by the users; The present invention is characterized by comprising:

[0011] Claim 3 The invention described in claim 2 In the station premises people flow estimation device described in The second dividing means is characterized in that it divides the number of users divided by the first dividing means into each passage that is estimated to have been used, using passage usage ratio information, which is information that predetermines the ratio of users for each passage when there are multiple passages between the ticket gate and the platform.

[0012] Claim 4 The invention described in claim 2 or 3 In the station premises people flow estimation device described in The apparatus is characterized by comprising a movement direction specifying means for specifying the movement direction in the passage for the number of users divided by the second dividing means for each passage that is estimated to have been used.

[0013] Claim 5 The invention described in ,station In the on-site people flow estimation device, a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a first dividing means for dividing the number of users calculated by the calculating means for each platform that the users are estimated to have used; Equipped with The counting means counts the number of users by dividing the number of users so that the counted number of users does not fall below a predetermined number.

[0014] Claim 6 The invention described in claims 1 to 5 In the station premises people flow estimation device according to any one of the above, The counting means counts the number of users by dividing the number of users by predetermined attributes in addition to the number of ticket gates used.

[0015] Claim 7 The invention described in claim 6 In the station premises people flow estimation device described in The predetermined attribute is Use the estimated target station It is characterized by including the user's age and / or gender.

[0016] Claim 8 The invention described in Station premises people flow estimation device Method for estimating people flow within a station And , a counting step of dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a dividing step of dividing the number of users counted in the counting step by platform that is estimated to have been used by the users; Including fruit, In the counting step, the number of users is counted by dividing the number of users into exit stations for those entering the estimated target station and entry stations for those leaving the estimated target station in addition to the number of users using the ticket gates; The dividing step divides the number of users counted in the counting step into each platform that is estimated to have been used, using route-specific usage ratio information, which is information that predetermines the ratio of users for each route in a section where multiple routes exist. It is characterized by: The invention described in claim 9 is a method for estimating people flow in a station premises in a station premises people flow estimation device, a counting step of dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a first division step of dividing the number of users counted in the counting step by platform that the users are estimated to have used; a second division step of dividing the number of users divided in the first division step into numbers for each passage that is estimated to have been used; The present invention is characterized by comprising: The invention described in claim 10 is a method for estimating people flow in a station premises in a station premises people flow estimation device, a counting step of dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a dividing step of dividing the number of users counted in the counting step by platform that is estimated to have been used; Including, The counting step is characterized in that the number of users is counted by dividing the number of users so that the counted number of users does not become less than a predetermined number.

[0017] The invention described in claim 11 is a station premises people flow estimation program, Computer, a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a dividing means for dividing the number of users counted by the counting means for each platform that is estimated to have been used by the users; Function as 、 The counting means counts the number of users by dividing the number of users into exit stations for those entering the estimated target station and by entry stations for those leaving the estimated target station in addition to the number of users using the ticket gates, The dividing means is characterized in that it divides the number of users counted by the counting means into each platform that is estimated to have been used, using route usage ratio information, which is information that predetermines the ratio of users for each route for sections where multiple routes exist. The invention described in claim 12 is a station premises people flow estimation program, Computer, a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a first dividing means for dividing the number of users calculated by the calculating means for each platform that the users are estimated to have used; a second dividing means for dividing the number of users divided by the first dividing means into passages that are estimated to have been used by the users; The present invention is characterized in that it functions as a The invention described in claim 13 is a station premises people flow estimation program, Computer, a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a dividing means for dividing the number of users counted by the counting means for each platform that is estimated to have been used by the users; It functions as The counting means counts the number of users by dividing the number of users so that the counted number of users does not fall below a predetermined number. [Effects of the Invention]

[0018] According to the present invention, it is possible to provide a station premises people flow estimation device, a station premises people flow estimation method, and a station premises people flow estimation program that can improve the accuracy of estimating people flow between ticket gates and platforms within a station premises. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a block diagram showing the configuration of a station premises people flow estimation system according to an embodiment. FIG. [Figure 2] 10 is a flowchart showing the flow of operations when estimating people flow in a station premises people flow estimation system according to the embodiment. [Figure 3] 10 is a flowchart showing the flow of operations when evaluating advertising value of the station premises people flow estimation system according to the embodiment. [Figure 4] FIG. 10 is a diagram showing an example of counting result information generated when estimating people flow in the station premises people flow estimation system according to the embodiment. [Figure 5] 10A and 10B are diagrams showing an example of rounding processing performed when estimating people flow in the station premises people flow estimation system according to the embodiment, where FIG. 10A shows data before processing and FIG. 10B shows data after processing. [Figure 6] 1A and 1B are diagrams showing an example of division by platform used when estimating people flow in a station premises people flow estimation system according to an embodiment, where FIG. 1A shows data before processing, and FIG. 1B shows data after processing. [Figure 7] 1A and 1B are diagrams showing an example of division into passageways used when estimating people flow in a station premises people flow estimation system according to an embodiment, where FIG. 1A shows data before processing and FIG. 1B shows data after processing. [Figure 8] FIG. 10 is a diagram showing an example of aggregation result information after adding movement direction generated when estimating people flow in the station premises people flow estimation system according to the embodiment. [Figure 9]FIG. 10 is a diagram showing an example of a people flow information provision screen generated when estimating people flow in the station premises people flow estimation system according to the embodiment. [Figure 10] FIG. 13 is a diagram showing a people flow information provision screen according to Modification 4. DETAILED DESCRIPTION OF THE INVENTION

[0020] A station premises people flow estimation system 100 according to an embodiment of the present invention will be described below with reference to Figures 1 to 10. However, the technical scope of the present invention is not limited to the illustrated examples.

[0021] [First Configuration Explanation] The station premises people flow estimation system 100 is a system for estimating people flow within a station premises and evaluating the advertising value of advertisement display locations installed within the station premises based on the estimation results.As shown in Figure 1, it is configured with a data analysis server 1, a ticket usage history information management server 2, and an operation terminal 3, and these devices are connected via a communication network N.

[0022] It should be noted that the above-mentioned servers do not necessarily have to be provided separately, and a single device may also function as multiple servers. Conversely, each of the above servers does not necessarily have to be realized by a single device, and the functions of each server may be realized by connecting multiple devices via a communication network N.

[0023] [1 Data Analysis Server] The data analysis server 1 is, for example, a computer owned by a company that manages and operates the station premises people flow estimation system 100, and as described below, estimates the people flow within the station premises based on information obtained from the ticket usage history information management server 2 and evaluates the advertising value of each advertising display location installed within the station premises. As shown in FIG. 1, the data analysis server 1 includes, for example, a control unit 11, a storage unit 12, and a communication unit 13.

[0024] [(1) Control Unit] The control unit 11 is the part that controls the operation of the data analysis server 1, and is configured with, for example, a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), etc., and controls each part of the data analysis server 1 in cooperation with the program data stored in the memory unit 12 and the CPU.

[0025] [(2) Storage section] The memory unit 12 is a part where various information required for the operation of the data analysis server 1 is stored, and is composed of, for example, an HDD (Hard Disk Drive), semiconductor memory, etc., and stores data required for the operation of the data analysis server 1, which will be described in the operation explanation below, in a manner that allows it to be read and written by the control unit 11. In addition, the memory unit 12 stores a program including various instructions to the control unit 11 for operating the data analysis server 1, and the operation of the data analysis server 1 described in the operation explanation below is performed in accordance with the program stored in the memory unit 12. Furthermore, route-specific utilization ratio information D3 and passage-specific utilization ratio information D4 are stored in the storage unit 12. The contents of this information will be described later in the explanation of the operation.

[0026] [(3) Communications Department] The communication unit 13 is a part used for communication between the data analysis server 1 and the ticket usage history information management server 2 and the operation terminal 3, and is, for example, a communication interface having a communication IC (Integrated Circuit) and a communication connector, and performs data communication via the communication network N using a predetermined communication protocol under the control of the control unit 11.

[0027] [2 Ticket usage history information management server] The ticket usage history information management server 2 is, for example, a computer owned by a company that manages and operates the station premises people flow estimation system 100, and acquires and accumulates ticket usage history information D1, which is information related to the ticket usage history of station users, and then transmits it to the data analysis server 1.

[0028] As shown in FIG. 1, the ticket usage history information management server 2 is configured to include, for example, a control unit 21, a storage unit 22, and a communication unit 23, similar to the data analysis server 1.

[0029] The configurations of the control unit 21 and the communication unit 23 are the same as those of the control unit 11 and the communication unit 13 in the data analysis server 1, respectively. The storage unit 22, like the storage unit 12 in the data analysis server 1, is configured with, for example, a HDD, a semiconductor memory, etc., and stores the ticket usage history information D1.

[0030] The ticket usage history information D1 is information relating to the usage history of IC cards as tickets at ticket gates in each railway station that can be used for people flow estimation by this system. The ticket usage history information D1 includes, for example, entry / exit information D1-1, which is information regarding whether the usage history corresponds to entry or exit; ticket gate used information D1-2, which is information regarding the ticket gate used (entry or exit); usage date information D1-3, which is information regarding the date of usage; usage time period information D1-4, which is information regarding the time period used (for example, one-hour units such as 9:00, 10:00, etc.); entry station information D1-5, which is information regarding the entry station; exit station information D1-6, which is information regarding the exit station; and attribute information D1-7, which is information regarding the attributes of the user related to the usage history.

[0031] The attribute information D1-7 also includes, for example, gender information D1-7-1, which is information relating to the gender of the user, and age information D1-7-2, which is information relating to the age of the user (teens, twenties, etc.). The attributes that can be included in the attribute information D1-7 are not limited to these two, and other attributes may also be included. Also, although it is preferable to include both gender information D1-7-1 and age information D1-7-2, it is also possible to include only either gender information D1-7-1 or age information D1-7-2, or to include neither and be composed of only other attributes. Examples of information that can be included in the attribute information D1-7 other than the gender information D1-7-1 and the age information D1-7-2 include payment information and authentication information. As payment information, for example, by utilizing the electronic money function or individual identification number included in the IC card used as a ticket, information regarding the time of payment, the amount of payment, the store where the payment was made, the means of transportation (bus, taxi, etc.) used for the payment, etc. can be obtained and stored. Furthermore, as the authentication information, information relating to the authentication history at the entrance of the building or the like may be acquired, and information relating to the place and time when the authentication was performed may be stored.

[0032] In the ticket usage history information management server 2, for example, user attribute information D2, which is information linking identification information such as an ID set for each IC card with information related to the attributes of the user of the IC card (attribute information D1-7), is stored in advance in the memory unit 22, and each time an IC card is used as a ticket at a ticket gate device installed at a station, entry / exit information D1-1, ticket gate used information D1-2, date of use information D1-3, time period of use information D1-4, entrance station information D1-5 and exit station information D1-6 related to the usage history are received by the communication unit 23 together with the identification information of the IC card used, and ticket usage history information D1 is generated by linking the acquired information with attribute information D1-7 related to the user of the IC card, and this is stored in the memory unit 22.

[0033] As a result, the memory unit 22 of the ticket usage history information management server 2 accumulates ticket usage history information D1 every time an IC card is used as a ticket at a ticket gate device installed at a station.

[0034] [3 Operation terminal] The operation terminal 3 is an information device such as a PC (Personal Computer) used by companies and the like that use this system to estimate people flow within stations, and is used to input prerequisites for estimating people flow, such as the target station and target date, and to view information related to the estimation results, as described below. As shown in Figure 1, the operation terminal 3 is configured to include, for example, a control unit 31, a memory unit 32, and a communication unit 33, similar to the data analysis server 1, and further includes a display unit 34 and an operation unit 35.

[0035] The display unit 34 includes a display such as an LCD (Liquid Crystal Display), and displays an image based on the display control signal output from the control unit 31 on the display screen.

[0036] The operation unit 35 includes, for example, a keyboard having character input keys, number input keys, and other keys associated with various functions, and receives operation input from the user of the operation terminal 3 and outputs an operation signal corresponding to the operation input to the control unit 31. The operation unit 35 may be, for example, a touch panel formed integrally with the display unit 34, and is not particularly limited as long as it can receive operation input from the user of the operation terminal 3.

[0037] [4 Communication Network] The communication network N is, for example, the Internet, a telephone line network, a mobile phone communication network, a wireless LAN communication network, etc., and connects the devices that make up the station premises people flow estimation system 100 as shown in FIG. The communication network N is not particularly limited as long as it can connect the devices constituting the station premises people flow estimation system 100 as described above and can transmit and receive data between them.

[0038] [Second operation explanation] Next, the operation of the station premises people flow estimation system 100 according to this embodiment will be described. The operation of the station premises people flow estimation system 100 is roughly divided into two steps: people flow estimation (step S1) and advertising value evaluation (step S2).

[0039] [1 Step S1: Estimating people flow] First, the operation of this system when estimating the flow of people within a station based on the ticket usage history information D1 will be described with reference to the flowchart in FIG.

[0040] When using this system to estimate the flow of people within a station, first, a company or other entity using this system uses the operation unit 35 of the operation terminal 3 to input information related to the analysis conditions, including information related to the target station and target date for estimation, and the input information is sent from the communication unit 33 to the data analysis server 1 via the communication network N (step S1-1).

[0041] The data analysis server 1 receives the information sent from the operation terminal 3 via the communication unit 13, and then acquires from the ticket usage history information management server 2 all of the ticket usage history information D1 stored in the memory unit 22 that matches the analysis conditions entered on the operation terminal 3 (step S1-2). Specifically, information relating to the target station and target date associated with the analysis conditions entered on the operation terminal 3 is sent from the data analysis server 1 to the ticket usage history information management server 2, and the ticket usage history information management server 2 extracts data matching the target station and target date from the ticket usage history information D1 stored in the memory unit 22 and then sends it to the data analysis server 1.

[0042] In the data analysis server 1 that has acquired the ticket usage history information D1 from the ticket usage history information management server 2, the control unit 11 removes personal information from the acquired ticket usage history information D1 (step S1-3). In other words, if the ticket usage history information D1 includes, as attribute information D1-7, information that can identify the user, such as the user's name and address, in addition to gender information D1-7-1 and age information D1-7-2, that information will be excluded from the ticket usage history information D1.

[0043] After excluding the personal information from the ticket usage history information D1, the control unit 11 of the data analysis server 1 then aggregates the ticket usage history information D1 (step S1-4).

[0044] Specifically, the control unit 11 counts the number of pieces of ticket usage history information D1 that have all of the following in common: entry / exit information D1-1, ticket gate usage information D1-2, usage date information D1-3, usage time period information D1-4, entry station information D1-5, exit station information D1-6, and attribute information D1-7. Information relating to the counting result is referred to as counting result information D1A, and information relating to the counted number of people included in the counting result information D1A is referred to as counted number of people information D1-8A.

[0045] An example of the counting result information D1A is shown in Figure 4. Note that Figure 4 illustrates an example of the counting result when, in step S1-2, in order to estimate the number of people flowing within the station premises of X station on October 6, 2021, information related to the usage history of IC cards as tickets on October 6, 2021 at each ticket gate device installed at X station is acquired.

[0046] Next, the control unit 11 of the data analysis server 1 performs a process (hereinafter referred to as a "rounding process") on the counting result information D1A to make the counted number of people equal to or greater than a predetermined number of people (step S1-5). That is, when the count result information D1A includes a count result in which the number of people related to the counted number-of-people information D1-8A is less than a predetermined number (for example, 10 people), the control unit 11 sums up multiple such count results to create data with a minimum number of people equal to or greater than the predetermined number. Note that this processed information is referred to as post-rounding count result information D1B, and information related to the post-rounding count number of people included in the post-rounding count result information D1B is referred to as post-rounding count number-of-people information D1-8B.

[0047] In addition, if the counting result information D1A does not include a counting result in which the number of people related to the counting number information D1-8A is less than the specified number of people, such processing is not performed, and the counting number information D1-8A becomes the counting number information D1-8B after rounding processing.

[0048] For example, the control unit 11 may compile the tally results for which the entry / exit information D1-1 is an exit and only the entry station information D1-5 is different and all other information is common, and may compile the tally results for which the entry / exit information D1-1 is an entry and only the exit station information D1-6 is different and all other information is common except the exit station information D1-6, for which the entry / exit information D1-1 is an entry.

[0049] An example of the rounding process is shown in Figure 5. In this case, as shown in Figure 5(a), there are three counting results in which the number of people in common other than the exit station information D1-6 is less than 10, so these three counting results are combined and the number of people is set to 10 or more (12 people) as shown in Figure 5(b). In addition, since there are three counting results in which the number of people in common other than the entrance station information D1-5 is less than 10, these three counting results are combined and the number of people is set to 10 or more (11 people), as shown in Figure 5(b).

[0050] When combining multiple stations into one in this way, it is possible to combine stations that are located within a specific area, such as within a specific city, town, or village.

[0051] It should be noted that, as described above, it is preferable to group together passengers who have common information other than the entrance station information D1-5 or the exit station information D1-6 in this rounding process, but this is not limited to this, and passengers who have common information other than the other information may be grouped together as long as the minimum number of passengers in the counting result can be made equal to or greater than a predetermined number. For example, although this is not preferable because it makes analysis of each user attribute difficult, it is also possible to group together passengers who have common information other than the gender information D1-7-1 or the age information D1-7-2 included in the attribute information D1-7.

[0052] Next, the control unit 11 divides the total number of people related to the rounded total result information D1B into numbers for each platform that is estimated to have been used (step S1-6).

[0053] In other words, if there are multiple lines running through the section between the railway station that is the subject of people flow estimation by this system and another specific railway station, the platform that a user will use at the railway station that is the subject of people flow estimation will be determined by which line that runs through that section that the user uses.

[0054] Therefore, the memory unit 12 of the data analysis server 1 can store route usage rate information D3, which is information related to the usage rate for each route for sections where multiple routes run in parallel, in advance, and the information can be used for division. The information after division is referred to as post-use platform division tally result information D1C, and the information relating to the total number of people after division included in the post-use platform division tally result information D1C is referred to as post-use platform division tally number of people information D1-8C.

[0055] The route usage ratio information D3 is information that defines the ratio of users for each route for the entire section where multiple routes connect specific stations, and can be created by compiling information related to the past usage history of each route and then storing it in the memory unit 12.

[0056] An example of division by platform is shown in Figure 6. In this case, for example, as shown in FIG. 6(a), in the post-rounding processing tabulation result information D1B, entry / exit information D1-1 is exit, ticket gate used information D1-2 is central ticket gate, date of use information D1-3 is October 6, 2021, time period used information D1-4 is 9:00, entrance station information D1-5 is XX station, exit station information D1-6 is XX station, gender information D1-7-1 is male, age information D1-7-2 is in their 20s, and the number of people is 60, there are two lines connecting XX station and XX station, line α and line β, If the arrival platform for line α at XX station is platform 1, the arrival platform for line β at XX station is platform 2, and the line usage ratio for the line usage ratio information D3 for trains from XX station to XX station is line α:line β = 1:2, then as shown in Figure 6(b), the number of 60 users will be divided into 1:2, and the platform usage information D1-9 will be added, and the aggregated result information D1C after platform usage division will be generated.

[0057] Next, the control unit 11 divides the post-platform-division count result information D1C into each passageway that is estimated to have been used (step S1-7). Note that the passageway in this case is not limited to a place named "passageway," but broadly includes any place that railway station users can pass through, such as a plaza or a shop inside the station.

[0058] Specifically, in a case where there are multiple passageways that can be used to travel between a specific platform and a specific ticket gate at a railway station that is the subject of people flow estimation by this system, passageway usage rate information D4, which is information relating to the usage rate of each such passageway, can be stored in advance in the memory unit 12 of the data analysis server 1, and division can be performed using this information. The information after division is referred to as post-division usage passage count result information D1D, and the information relating to the post-division count number of people included in the post-division usage passage count result information D1D is referred to as post-division usage passage count number of people information D1-8D.

[0059] The passageway usage ratio information D4 is information that defines the ratio of users of each passageway when moving from a specific platform to a specific ticket gate or when moving from a specific ticket gate to a specific platform, when there are multiple passageways between a specific platform and a specific ticket gate within the railway station that is the subject of people flow estimation by this system. The passage usage ratio information D4 may be created, for example, by collecting information on the past usage history of each passage using cameras, sensors, etc. installed in each passage, and then aggregating the information, and storing the information in the memory unit 12.

[0060] It is preferable that the per-aisle usage ratio information D4 is information created based on actual usage records as described above, but this is not limited to this. For example, the user ratio may be determined by simply apportioning it based on the number of aisles. The usage rate for each passage may also be determined according to the characteristics of the passage, for example, a passage with an escalator may be set to have a higher usage rate than a passage with only stairs.

[0061] An example of division by aisle is shown in FIG. In this case, for example, as shown in FIG. 7(a), the aggregated result information D1C after dividing the platform used is as follows: entry / exit information D1-1 is exit, used ticket gate information D1-2 is central ticket gate, use date information D1-3 is October 6, 2021, use time period information D1-4 is 9 o'clock, entry station information D1-5 is XX station, exit station information D1-6 is XX station, gender information D1-7-1 is male, age information D1-7-2 is 20s, used platform Platform information D1-9 indicates that there are 20 people on platform 1, entry / exit information D1-1 indicates exit, ticket gate information D1-2 indicates the central ticket gate, date of use information D1-3 indicates October 6, 2021, time period information D1-4 indicates the 9 o'clock hour, entry station information D1-5 indicates XX station, exit station information D1-6 indicates XX station, gender information D1-7-1 indicates male, age information D1-7-2 indicates people in their 20s, and platform information D1-9 indicates platform 2. If the information includes that the number of users in the group is 40, and there are two passages, passage a and passage b, from platform 1 to the central ticket gate, and the passage usage ratio when moving from platform 1 to the central ticket gate according to the passage usage ratio information D4 is passage a:passage b = 1:1, and there are three passages, passage c, passage d, and passage e, from platform 2 to the central ticket gate, and the passage usage ratio when moving from platform 2 to the central ticket gate according to the passage usage ratio information D4 is passage c:passage d:passage e = 1:1:2, then as shown in Figure 7(b), the number of 20 users moving from platform 1 to the central ticket gate is divided 1:1, and the number of 40 users moving from platform 2 to the central ticket gate is divided 1:1:2, and the passage usage information D1-10 is added, and the post-passage usage division aggregation result information D1D is generated.

[0062] Next, the control unit 11 identifies the direction of movement in the passage from the post-use passage division counting result information D1D (step S1-8).

[0063] In other words, since the direction of movement in a passage is constant when moving from a specific platform to a specific ticket gate using a specific passage, or when moving from a specific ticket gate to a specific platform using a specific passage, the passage usage ratio information D4 can include information regarding the direction of movement in the passage for each pattern of moving from a specific platform to a specific ticket gate using a specific passage, or moving from a specific ticket gate to a specific platform using a specific passage, and this information can be used to add movement direction information D1-11, which is information regarding the direction of movement, to each aggregation result included in the aggregation result information D1D after dividing the passages used. The information after the movement direction information D1-11 is added is referred to as count result information D1E after the movement direction is added.

[0064] FIG. 8 shows an example of the count result information D1E after adding the movement direction.

[0065] By going through the above steps S1-1 to S1-8, the number of users entering or exiting through ticket gates within the station, which is calculated from the ticket usage history information D1, can be divided by platform and passageway used.

[0066] Once step S1-8 is completed, the control unit 11 in the data analysis server 1 creates a people flow information provision screen G1, which is a screen for providing information related to the estimated results of people flow to companies and other users of this system, based on the aggregation result information D1E after adding movement direction (step S1-9).

[0067] The people flow information provision screen G1 can be transmitted, for example, from the communication unit 13 to the operation terminal 3 via the communication network N, so that companies using this system can check it, and the companies can provide it to businesses such as stores within the station and advertising businesses that post advertisements within the station.

[0068] The people flow information screen G1 includes, for example, as shown in FIG. 9, a display of the number of users per corridor G11 that displays the number of users per corridor and per usage time, a display of the number of users per attribute G12 that displays the total number of users per day by gender and age group, and a display of the number of users per OD G13 that displays the number of users per day for each departure point (ticket gate or platform) and arrival point (ticket gate or platform) within the station.

[0069] In this case, the number of users per aisle display G11 may be, for example, as shown in FIG. 9, such that bar graphs relating to two movement directions in each aisle are displayed in an overlapping manner for the number of users in each time period in each aisle.

[0070] Furthermore, the attribute-based user count display G12 may be configured by providing separate pie charts for men and women, as shown in FIG. 9, and displaying the proportions for each age group using the pie charts.

[0071] Furthermore, the number of users per OD display G13 may be a bar graph showing the number of users per day traveling between the ticket gate or platform (origin) that is the departure point and the ticket gate or platform (destination) that is the arrival point, by gender, as shown in Figure 9.

[0072] [2 Step S2: Evaluation of advertising value] Next, the operation of this system when evaluating the advertising value of advertisement posting locations installed at various locations within the station based on the estimated results of pedestrian flow within the station in step S1 will be explained using the flowchart in Figure 3.

[0073] In addition, the advertising display location in this invention is not limited to a location where a notice having some advertising purpose is posted, but is sufficient as long as it is a location where a notice having some advertising purpose is posted. For example, the surface of a store space in a station facing the aisles also falls under the category of an "advertising display location" because advertising notices such as signs with store names are posted thereon, and such advertising display locations are arranged so as to face in a direction perpendicular to the direction of movement of people in the aisles. In a store space, the advertising value of the side facing the aisle is directly linked to the value of the store space itself. Therefore, if the side facing the aisle of the store space is viewed as a place to display advertisements and its advertising value is evaluated, the value of the store space itself within the station can be evaluated.

[0074] When the aggregation result information D1E after adding the direction of movement is generated in step S1-8, the control unit 11 estimates, for each time period, the number of people who will see the advertisements posted at each of the advertisement posting locations installed in each passageway within the station, based on the aggregation result information D1E after adding the direction of movement (step S2-1).

[0075] Specifically, as described above, the counting result information D1E after adding the movement direction includes information on the number of users traveling between each ticket gate and each platform for each time period, divided by the passageway used, and further includes information on the direction of travel of the users. Therefore, the control unit 11 counts the number of users for each time period and each direction of travel in each passageway based on the counting result information D1E after adding the movement direction.

[0076] Then, first, if the advertisement display location is set up so as to face a direction parallel to the direction of movement of people in the passageway where it is installed (along one of the directions of movement and in a direction opposite to one of the directions of movement), the number of users moving in the passageway in the opposite direction to the advertisement display location per time period is estimated as the number of people who see the advertisement display location during that time period.

[0077] For example, for aisle A running in a north-south direction, if the total number of users heading north during the 9:00 a.m. hour is 1,000, and the total number of users heading south during the 9:00 p.m. hour is 2,000, then the number of people who will see the south-facing advertising display on aisle A during the 9:00 a.m. hour will be estimated to be 1,000, and the number of people who will see the north-facing advertising display on aisle A during the 9:00 a.m. hour will be estimated to be 2,000.

[0078] In addition, when an advertisement display location is set up so as to face a direction perpendicular to the direction of movement of people in the passageway where it is installed, the total number of users moving in the passageway in both directions perpendicular to the direction in which the advertisement display location faces in each time period is estimated to be the number of people who see the advertisement display location in that time period.

[0079] For example, for aisle A running in a north-south direction, if the number of users heading north during the 9:00 a.m. hour is 1,000, and the number of users heading south during the 9:00 p.m. hour is 2,000, then the number of people who will see the east-facing or west-facing advertisements posted on aisle A during the 9:00 a.m. hour is estimated to be 3,000.

[0080] Next, the control unit 11 divides the estimated number of people who view each advertising display location during each time period, calculated in step S2-1, into user attributes using the attribute information D1-7 included in the calculation result information D1E after adding the direction of movement (step S2-2).

[0081] Specifically, as described above, if the number of people who see an advertisement at a south-facing advertising display located in a north-south corridor a during the 9 o'clock hour is counted as 1,000, and if the attribute information D1-7 includes gender information D1-7-1 and age information D1-7-2, the counted 1,000 people will be divided by gender and age.

[0082] For example, 1,000 people at 9 o'clock who see an advertisement at a south-facing advertising display located on aisle A running in a north-south direction will be divided into the following groups: 80 teenage men, 80 teenage women, 100 men in their twenties, 80 women in their twenties, 100 men in their thirties, 80 women in their thirties, 80 men in their forties, 70 women in their forties, 70 men in their fifties, 60 women in their fifties, 50 men in their sixties, 40 women in their sixties, 30 men in their seventies, 30 women in their seventies, 30 men in their eighties, and 20 women in their eighties.

[0083] Next, the control unit 11 determines an evaluation for each advertising location for each time period and for each attribute, in accordance with predetermined criteria, based on the number of people who view each advertising location for each time period, which was divided by user attributes in step S2-2.

[0084] The evaluation criteria for this case may be based on the number of people who see the advertisement posted at each posting location by time period and by attribute, and each posting location may be evaluated based on the number of people who see the advertisement posted at each posting location. As an evaluation method at that time, for example, a score may be calculated based on the number of people, or the number of people may be divided into multiple ranks (for example, ranks A to F in descending order of the number of people).

[0085] For example, one possible evaluation method for a particular advertisement posting location could be as follows: if the number of people viewing the advertisement in one hour is 100 or more, it would be ranked A; if it is 80 to 100, it would be ranked B; if it is 60 to 80, it would be ranked C; if it is 40 to 60, it would be ranked D; if it is 20 to 40, it would be ranked E; and if it is 0 to 20, it would be ranked F. In this case, if the division is made as exemplified in step S2-2, the evaluation of the south-facing advertising display located in the north-south passage a in the 9 o'clock hour will be determined as follows: rank B for teenage males, rank B for teenage females, rank A for men in their 20s, rank B for women in their 20s, rank A for men in their 30s, rank B for women in their 30s, rank B for men in their 40s, rank C for women in their 40s, rank C for men in their 50s, rank C for women in their 50s, rank D for men in their 60s, rank D for women in their 60s, rank E for men in their 70s, rank E for women in their 70s, rank E for men in their 80s, and rank E for women in their 80s.

[0086] Once step S2-3 is completed, the control unit 11 in the data analysis server 1 creates an advertising value evaluation information provision screen, which is a screen for providing information related to the evaluation of the posting locations of each advertisement determined in step S2-3 to companies and others using this system (step S2-4).

[0087] The advertising value evaluation information providing screen may be a screen that displays, for example, information regarding the number of people who will see each advertising display location within a station for each time period and user attribute, which was generated by dividing in step S2-2, and information regarding the evaluation (rank, score, etc.) of each advertising display location for each time period and user attribute, which was determined in step S2-3. The advertising value information provision screen can also be transmitted, for example, from the communication unit 13 to the operation terminal 3 via the communication network N, so that companies using this system can check it, and the companies can provide it to businesses such as advertising companies that post advertisements within train stations.

[0088] [Third effect explanation] Next, the effects of the station premises people flow estimation system 100 according to this embodiment will be described.

[0089] According to the station premises people flow estimation system 100 of this embodiment, in step S1-4, the data analysis server 1 counts the number of users at the station that is the subject of people flow estimation based on the ticket usage history information D1 by counting the number of pieces of information contained in the ticket usage history information D1 that share common information, including ticket gate usage information D1-2, so that the count is divided at least by the ticket gate that was used, and then in step S1-6, the number of people related to the counting results is divided by the platform that is estimated to have been used. This allows us to grasp the number of users moving between each platform and each ticket gate, thereby improving the accuracy of estimating the flow of people between ticket gates and platforms within the station.

[0090] In addition, in step S1-4, the number of people with common entry / exit information D1-1, i.e., information regarding whether the ticket gate usage history corresponds to entry or exit, is tallied, and the number of users is tallied by dividing them into entrants (moving from the ticket gate to the platform) and exiters (moving from the platform to the ticket gate), making it possible to estimate the number of people in each direction of movement.

[0091] Furthermore, the data analysis server 1 stores route usage ratio information D3, which is information that defines the ratio of users for each route for sections where multiple routes exist, and by using this information to divide the number of users by platform that is estimated to have been used, the number of users can be easily divided by platform based on the predetermined usage ratio for each platform.

[0092] Furthermore, by further dividing the number of users divided by platform estimated to have been used in step S1-6 into the number of passageways estimated to have been used in step S1-7, the number of users who moved between each platform and each ticket gate can be determined for each passageway used, thereby further improving the accuracy of estimating the flow of people between ticket gates and platforms within the station.

[0093] Furthermore, the data analysis server 1 stores in advance passage usage ratio information D4, which is information that defines the proportion of users per passage for locations where there are multiple passages between the ticket gate and the platform, and by using this information to divide the number of users by passage that is estimated to have been used, the number of users can be easily divided by passage based on the predetermined usage ratio for each passage.

[0094] In addition, in step S1-8, by identifying the direction of movement in the corridor for the number of users divided into each corridor estimated to have been used in step S1-7, it is possible to grasp the proportion of users in each direction of movement in the corridor.

[0095] Furthermore, in the rounding process of step S1-5, the counting results of step S1-4 are combined so that they do not fall below a predetermined number, and the counting of the number of users at the station that is the target of people flow estimation is divided so that each counting result does not fall below the predetermined number. This prevents the risk of individuals being identified due to the counted number being too small.

[0096] Furthermore, in step S1-4, by aggregating the attribute information D1-7, i.e., the number of users with common attributes such as gender and age, the number of users can be aggregated by attribute, and it becomes possible to grasp the flow of people within the station not just in terms of the number of users but also the proportion of each attribute.

[0097] Furthermore, the effectiveness of advertisement posting locations is affected by the number of people who see the advertisement when it is posted. By using an estimate of the number of viewers who will see each advertisement posting location and determining an evaluation in accordance with predetermined standards, it becomes possible to not only estimate the flow of people within the station, but also to obtain information related to the evaluation of the advertisement effectiveness of each advertisement posting location based on the flow of people.

[0098] Furthermore, since the estimated number of viewers who will see each advertisement posting location is a value estimated for each time period, it is possible to determine the evaluation for each advertisement posting location for each time period, which makes it possible to change the advertisements to be posted depending on the evaluation for each time period, for example.

[0099] Furthermore, since the estimated number of viewers who will see each advertisement posting location is a value estimated for each user attribute, it is possible to determine an evaluation for each advertisement posting location for each attribute of the target viewers. This makes it possible, for example, to post advertisements that are suitable for the target attributes in each advertisement posting location.

[0100] Furthermore, when an advertisement is displayed in a position facing the opposite direction to the movement of people in the passage, the number of users moving in the opposite direction to the advertisement is estimated as the number of viewers who see the advertisement, making it possible to easily estimate the number of viewers who see the advertisement, which is displayed in a position facing the opposite direction to the movement of people in the passage.

[0101] Furthermore, when an advertisement is displayed in a direction perpendicular to the direction of people moving in the passageway, the number of users moving in the passageway in a direction perpendicular to the direction of the advertisement is estimated as the number of viewers who see the advertisement, making it possible to easily estimate the number of viewers who see the advertisement, which is displayed in a direction perpendicular to the direction of people moving in the passageway.

[0102] [Fourth Modification] Next, a modified example of the station premises people flow estimation system 100 according to this embodiment will be described.

[0103] [1 Variation 1: Change in rounding method] In the explanation of the above operation, in the rounding process of step S1-5, when the counting result information D1A includes a counting result in which the number of people related to the counting number information D1-8A is less than a predetermined number (for example, 10 people), multiple such counting results are added together to create data in which the minimum number of people is equal to or greater than the predetermined number, but the method of rounding process is not limited to this.

[0104] For example, if the counted number information D1-8A includes a counted result in which the number of people is less than a predetermined number, the number of people related to the counted result may be fixed to a predetermined value, thereby performing rounding processing without adding up multiple counted results. For example, if the counted result includes a number of people related to the counted number information D1-8A that is less than 10, it is possible to prevent the counted result from having a number of people related to the counted number information D1-8A that is less than 10 by fixing the number of people related to the counted result to 0 or 10.

[0105] Furthermore, the timing of performing the rounding process is not limited to immediately after the acquisition of the count result information D1A in step S1-4. For example, it is possible to perform rounding after acquiring the travel direction-added count result information D1E in step S1-8. In this case, by performing rounding only on groups whose final count after division is less than a predetermined number (for example, less than 10 people), and making the number of people equal to or greater than the predetermined number, the risk of identifying individuals can be reduced, while for groups for which rounding is not necessary (the final count after division is equal to or greater than the predetermined number), information on the estimated results of people flow can be provided based on accurate data close to the original ticket usage history information D1 without performing rounding.

[0106] [2 Variation 2: Change in the method for estimating the number of ad viewers] In step S2-1 of the above operation explanation, we explained that in the case where an advertisement display is set up so as to face in a direction perpendicular to the direction of movement of people in the corridor where it is installed, the total number of users moving down the corridor in both directions perpendicular to the direction in which the advertisement display is facing per time period is estimated to be the number of people who will see the advertisement display during that time period.However, it is also possible that the proportion of users moving down the corridor in a direction perpendicular to the direction in which the advertisement display is facing who see the advertisement will be lower than the proportion of users moving down the corridor in the direction opposite to the direction in which the advertisement display is facing who see the advertisement.

[0107] Therefore, if an advertisement display is set up so as to face a direction perpendicular to the direction of movement of people in the passageway where it is installed, the number of people who will see the advertisement display during that time period can be estimated by multiplying the total number of users moving along the passageway in both directions perpendicular to the direction in which the advertisement display is facing by a predetermined weighting coefficient.

[0108] In this case, for example, for aisle A running in a north-south direction, if the total number of users heading north at 9:00 a.m. is 1,000, and the total number of users heading south at 9:00 p.m. is 2,000, then the total of 3,000 people is multiplied by a predetermined weighting coefficient of 50% (0.5), or 1,500 people, to estimate the number of people who will see the east-facing or west-facing advertisements posted on aisle A at 9:00 a.m.

[0109] [3. Modification 3: Change in the target of ticket usage history information acquisition] In the explanation of the above configuration, we have described the case where the ticket usage history information D1 is information relating to the usage history of an IC card as a ticket, but the ticket usage history information D1 is information relating to the usage history of tickets at the ticket gate devices of each railway station that can be used to estimate people flow by this system, and may include entry / exit information D1-1, ticket gate usage information D1-2, usage date information D1-3, usage time period information D1-4, entrance station information D1-5, exit station information D1-6, and attribute information D1-7, and is not necessarily limited to the usage history of an IC card. For example, when a smartphone or wearable device equipped with an IC chip and a payment function is used as a ticket, information related to its usage history may be stored.

[0110] [4 Variation 4: Changes to the People Flow Information Screen] In the explanation of the above operation, in step S1-9, we have explained that the people flow information provision screen G1 shown in Figure 9 is used as the screen for providing information related to the estimated results of people flow to companies and other entities using this system, but the screens that can be used to provide information related to the estimated results of people flow are not limited to this.

[0111] For example, as shown in the people flow information provision screen G1A in FIG. 10, the direction of the arrows displayed on the station map may represent the direction of the people flow, and the color of the arrows may represent the amount of people flow.

[0112] In Figure 10, a first people flow display arrow G141 and a second people flow display arrow G142 are displayed on a station map G14, and the direction of the arrows indicates the direction of people flow, and the color of the arrows indicates the amount of people flow. The first people flow display arrow G141 and the second people flow display arrow G142 are displayed pointing in opposite directions at the same location on the station map, and their color indicates the amount of people flowing in the direction the arrow is pointing at that location within the station.

[0113] In the figure, the color of the arrows only represents light and dark, but it is preferable to represent the amount of people flowing by hue, for example, by having the arrows displayed in green when there is little people flow and gradually changing to red as the number of people increases. It is also possible to express the volume of people flowing by varying brightness and saturation, although this is not preferable since it is difficult to recognize unlike changes in hue.

[0114] The people flow information screen G1A further has a usage date input field G15 and a usage time input field G16, and is configured to display information corresponding to the input usage date and usage time. That is, the colors of the first people flow display arrow G141 and the second people flow display arrow G142 change according to the input usage date and usage time.

[0115] In addition, the people flow information screen G1A further includes a number of users per passage display G11A that displays the number of users per passage, a number of users per attribute display G12A that displays the number of users by gender and age group, and a number of users per OD display G13A that displays the number of users per departure point (ticket gate or platform) and arrival point (ticket gate or platform) within the station.

[0116] As shown in FIG. 10, the number of users per aisle display G11A displays the number of users in each aisle at the date and time entered in the usage date input field G15 and usage time input field G16 using a bar graph divided by color according to direction.

[0117] In addition, the number of users by attribute display G12A, as shown in Figure 10, displays the total number of users at the date and time entered in the usage date input field G15 and the usage time input field G16, divided by gender and age group using a single pie chart.

[0118] In addition, the OD user count display G13A, as shown in FIG. 10, displays the number of users traveling between the ticket gate or platform (origin) that is the departure point and the ticket gate or platform (destination) at the date and time entered in the usage date input field G15 and usage time input field G16 using a bar graph divided by attribute using colors.

[0119] Furthermore, the people flow information provision screen G1A displays a legend display G17 as shown in Fig. 10. The legend display G17 is a part that displays colors that serve as legends for the people flow rate indicated by the colors of the arrows of the first people flow display arrow G141 and the second people flow display arrow G142, the direction indicated by the color of the bar graph in the number of users per aisle display G11A, the attributes indicated by the color of the pie chart in the number of users per attribute display G12A, and the attributes indicated by the color of the bar graph in the number of users per OD display G13A.

[0120] While Figure 10 illustrates a case in which people flow indicator arrows are displayed for only one location within the station premises, it is also possible to use a diagram that displays a wide range of the station premises and display people flow indicator arrows for multiple locations simultaneously.Furthermore, by specifying a specific point from such a wide-range display, it is also possible to transition to a display in which the specific location is enlarged, as shown in Figure 10. [Explanation of symbols]

[0121] 100 Station pedestrian flow estimation system 1. Data analysis server (station pedestrian flow estimation device) 11 control unit (counting means, first division means, second division means, movement direction identification means) 12 Storage section 13 Communications Department 2. Ticket usage history information management server 21 Control section 22 Memory section 23 Communications Department 3 Operation terminal 31 Control Unit 32 Storage section 33 Communications Department 34 Display section 35 Control section D1 Ticket usage history information D1A Counting Result Information D1B Rounding result information D1C Usage Platform Split Post-aggregation Result Information D1D Result of aggregation after dividing the passage D1E Aggregation result information after adding movement direction D2 User attribute information D3 Route usage rate information D4 Passage usage rate information

Claims

1. a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a first dividing means for dividing the number of users calculated by the calculating means for each platform that the users are estimated to have used; Equipped with The counting means counts the number of users by dividing the number of users into exit stations for those entering the estimated target station and by entry stations for those leaving the estimated target station in addition to the number of users using the ticket gates, The first dividing means divides the number of users calculated by the calculating means into each platform that is estimated to have been used by users, using line usage ratio information, which is information that predetermines the ratio of users for each line in a section where multiple lines exist.

2. a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a first dividing means for dividing the number of users calculated by the calculating means for each platform that the users are estimated to have used; a second dividing means for dividing the number of users divided by the first dividing means into passages that are estimated to have been used by the users; A station premises people flow estimation device comprising:

3. The station premises people flow estimation device according to claim 2, characterized in that the second dividing means divides the number of users divided by the first dividing means into each passage that is estimated to have been used, using passage-by-passage usage ratio information, which is information that predetermines the ratio of users for each passage when there are multiple passages between the ticket gate and the platform.

4. 4. The station premises people flow estimation device according to claim 2 or 3, further comprising a movement direction identification means for identifying the movement direction in each passageway for the number of users divided by the second division means into each passageway that is estimated to have been used.

5. a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a first dividing means for dividing the number of users calculated by the calculating means for each platform that the users are estimated to have used; Equipped with The station premises people flow estimation device is characterized in that the counting means counts the number of users by dividing the number so that the counted number of users does not fall below a predetermined number.

6. 6. The station premises people flow estimation device according to claim 1, wherein the counting means counts the number of users by dividing the number of users by predetermined attributes in addition to the number of ticket gates used.

7. The station premises people flow estimation device according to claim 6, wherein the predetermined attributes include age and / or gender of users who use the estimation target station.

8. A method for estimating people flow within a station in a station people flow estimation device, comprising: a counting step of dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a dividing step of dividing the number of users counted in the counting step by platform that is estimated to have been used by the users; Including, In the counting step, the number of users is counted by dividing the number of users into exit stations for those entering the estimated target station and entry stations for those leaving the estimated target station in addition to the number of users using the ticket gates; The method for estimating people flow within a station is characterized in that the dividing step divides the number of users calculated in the calculating step into each platform that is estimated to have been used, using line usage ratio information, which is information that predetermines the ratio of users for each line in a section where multiple lines exist.

9. A method for estimating people flow within a station in a station people flow estimation device, comprising: a counting step of dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a first division step of dividing the number of users counted in the counting step by platform that the users are estimated to have used; a second division step of dividing the number of users divided in the first division step into passages each of which is estimated to have been used; A method for estimating people flow within a station, comprising:

10. A method for estimating people flow within a station in a station people flow estimation device, comprising: a counting step of dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a dividing step of dividing the number of users counted in the counting step by platform that is estimated to have been used; Including, The method for estimating people flow within a station, wherein the counting step includes counting the number of users by dividing the number of users so that the counted number does not fall below a predetermined number.

11. Computer, a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a dividing means for dividing the number of users counted by the counting means for each platform that is estimated to have been used by the users; It functions as The counting means counts the number of users by dividing the number of users into exit stations for those entering the estimated target station and by entry stations for those leaving the estimated target station in addition to the number of users using the ticket gates, The dividing means divides the number of users counted by the counting means into each platform that is estimated to have been used, using line usage ratio information, which is information that predetermines the ratio of users for each line in a section where multiple lines exist.

12. Computer, a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a first dividing means for dividing the number of users calculated by the calculating means for each platform that the users are estimated to have used; a second dividing means for dividing the number of users divided by the first dividing means into passages each of which is estimated to have been used; A station premises people flow estimation program characterized by functioning as a

13. Computer, a counting means for dividing and counting the number of users of a target station for estimating people flow by at least each ticket gate used; a dividing means for dividing the number of users counted by the counting means for each platform that is estimated to have been used by the users; It functions as The program for estimating people flow within a station is characterized in that the counting means divides the number of users into groups so that the counted number does not fall below a predetermined number.

Images