JP2014006743A - Estimation method, estimation program, and estimation device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To enable estimation of a situation in the surrounding of a station by using ticket examination information.SOLUTION: An estimation method causes a computer to execute the processing of: identifying the last exit spot or the last disembark spot by using a ticket on the basis of exit spot information or disembark spot information transmitted from a ticket examination processor or a fare-adjustment processor in accordance with an exit or disembark by using the ticket; determining whether the identified last exit spot or last disembark spot matches one or any of plurality of exit spot information or disembark spot information stored in correlation with the ticket; and, if there is no matching, estimating that there is someone in the identified last exit spot or last embark spot.

Description

  The present invention relates to an estimation method, an estimation program, and an estimation apparatus.

  In the event of a large-scale disaster that occurred on March 11, 2011, refugees who returned home exceeded the allowable capacity for temporary evacuation sites and decided to spend the night on the stairs and streets of the station. In the future, if a major disaster occurs, it is expected that a large number of people will gather in front of the station and cause confusion.

JP 2011-192062 A

  Now, if we can estimate the situation of people staying around the station due to difficulties in returning home, for administrative agencies in wards and cities that have jurisdiction over each station, the number of supplies to be distributed and the number of supplies This may be useful for determining the size of the shelter.

  In recent years, mobile phones, smartphones, and the like have become widespread. Therefore, if position information or the like can be acquired through communication with a mobile terminal or the like, it can be estimated that it is difficult to return home based on the distance from the home of the user of the mobile terminal or the like.

  However, in situations such as the time of the earthquake, many people try to contact family members and friends. Therefore, it is predicted that the amount of communication will increase rapidly regardless of whether it is wireless or wired, and the communication network will be overloaded. Alternatively, there is a possibility that the communication network itself cannot be used due to a power failure or the like.

  The person who stays in the vicinity of the station can guess that it is a person who got off halfway because the train was not available even though he originally wanted to go somewhere using the train The inventor noticed. Regardless of whether or not you get off the way, if you are a person who comes out of the station and stays in the vicinity of the station, the ticket gate information that the automatic ticket gate read the ticket that the person has, The inventor realized that it would be held in a system owned by the railway company.

  Therefore, an object of the present invention is to make it possible to estimate the situation around a station using ticket gate information.

  In one plan, the estimation method is based on the exit location information or the exit location information transmitted from the ticket gate processing device or the settlement processing device in response to the exit or exit using the ticket. The exit location or the last exit location is identified, and the identified last exit location or the last exit location is one of one or more exit location information or exit location information stored in association with the boarding ticket. It is determined whether or not they match, and if they do not match, the computer executes a process of estimating that there is a staying person at the identified last exit location or last get-off location.

  According to one aspect, the situation around the station can be estimated.

It is a figure which shows the structural example of the estimation system in embodiment of this invention. It is a figure for demonstrating the outline | summary of an example of the estimation method of the number of refuge persons. It is a figure which shows the hardware structural example of the estimation apparatus in embodiment of this invention. It is a figure which shows the function structural example of the estimation apparatus in embodiment of this invention. It is a flowchart for demonstrating an example of the process sequence of the estimation process of a home station. It is a figure which shows the structural example of a boarding log | history memory | storage part. It is a figure which shows an example of the count result of the first or last use frequency of the station used first or last. It is a figure which shows the structural example of a personal estimation information storage part. It is a flowchart for demonstrating an example of the process sequence of the estimation process of a work station. It is a figure which shows the example of the combination of the exit record-> entrance record within the same day. It is a figure which shows the structural example of a neighborhood station information storage part. It is a figure which shows an example of the count result of the frequency | count of staying more than predetermined time. It is a flowchart for demonstrating an example of the process sequence of the 1st estimation process of a movement capability. It is a figure which shows the structural example of a personal master memory | storage part. It is a flowchart for demonstrating an example of the process sequence of the 2nd estimation process of a movement capability. It is a flowchart for demonstrating an example of the process sequence of the estimation process of the number of refuge persons. It is a flowchart for demonstrating an example of the process sequence of a visitor extraction process. It is a flowchart for demonstrating an example of the process sequence of a visitor classification | category process. It is a figure which shows the structural example of the estimation result table corresponding to one station. It is a figure which shows the structural example of the distance storage part between stations. It is a figure which shows the structural example of a threshold value memory | storage part.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a diagram illustrating a configuration example of an estimation system according to an embodiment of the present invention. In the estimation system 1 of FIG. 1, an automatic ticket gate 20 installed at each station on each route is connected to the estimation device 10 via a network. The route to be processed in the present embodiment may be limited to a specific route or may be a plurality of routes.

  Each time the automatic ticket checker 20 reads information recorded on a passenger ticket such as a passenger ticket or a commuter pass, it transfers the entry record or the exit record to the estimation device 10. The entry record is a record indicating that the passenger has entered the station. The exit record is a record indicating that the passenger has left the station.

  The estimation apparatus 10 performs one or more executions such as estimation of the number of people who are difficult to go home or return to, etc. at each station based on entrance records and exit records transferred from each automatic ticket gate 20, information managed in advance, and the like. Computer.

  In the present embodiment, a person who is difficult to return home or return to work is referred to as a “refugee difficult person”. If there is a facility nearby that can be used as a temporary evacuation site, such as a company or school where the passenger goes on a day-to-day basis, the passenger can use the facility as an evacuation site. High nature. Therefore, the person with difficulty in evacuation in the present embodiment is a concept indicating a person who cannot go home or go to a temporary evacuation site.

  When the train passenger uses a reusable ticket such as a commuter pass, for example, an estimation device that connects an entry record and an exit record by an automatic ticket gate for the same ticket to the automatic ticket gate 10 can be accumulated. If a certain passenger is a company employee, at the time of working sunrise, an entry record at his / her nearest station and an exit record at the nearest company station are accumulated. In addition, when leaving the office, an entry record at the nearest station of the company and an exit record at the nearest station of the house are accumulated. Therefore, a station where a lot of admission records and exit records are accumulated for a certain ticket is something that is routinely used for passengers who use the ticket, such as at home, commuting to work or school. This means that there is a facility nearby.

  Here, for example, the estimating apparatus 10 estimates the number of people who have difficulty evacuating by a method as shown in FIG.

  FIG. 2 is a diagram for explaining an outline of an example of a method for estimating the number of people who have difficulty evacuating. In FIG. 2, (1) is a pie chart showing the breakdown of those leaving the station. An exit person means a person who has left the station among the users of the ticket. In the present embodiment, as shown in (1), the exits are classified into residents, commuters, and visitors. Residents are users who have the station as their nearest station. Hereinafter, the nearest station to home is referred to as “home station”. A commuter is a user who makes the station the nearest station to work. Users who use the station as their nearest station will also be included in the commuter for convenience. Hereinafter, the nearest station to commute is called “commute station”. A visitor is a user whose station does not correspond to either a home station or a commuting station.

  Residents can go home and are unlikely to become refugees. In recent years, waiting in the workplace is allowed or recommended when a disaster occurs. Therefore, it is unlikely that employees will be evacuated. On the other hand, a visitor may include a person who has difficulty in returning home or returning to work. Therefore, the estimation device 10 extracts visitors from the exits and performs classification as shown in (2) regarding the visitors.

  (2) is a pie chart showing an example of a visitor classification result. As shown in (2), the estimation apparatus 10 classifies visitors into evacuable persons, refugee reserve armies, and refugee persons. An evacuable person is a person who can go home or go home. That is, even if it is a visitor, if the distance from the said station to a home station or a work station is the distance which can generally move on foot, evacuation to a home or a workplace is possible. Therefore, some visitors can be evacuated. The reserve army for the refugee refugee is longer than the distance estimated to be able to go home (that is, the distance that can generally be moved on foot) to the home station or the work station. A person at a short station. A person who has difficulty in evacuation refers to a person whose distance from the station to his / her home station or work station exceeds the distance that can generally be moved on foot. However, a person with low mobility is generally likely to be difficult to move even if the distance is within walking distance. Therefore, such a person is also classified as a person with difficulty in evacuation. Then, the number of persons classified as difficult to evacuate, or the number of persons classified as the number of persons classified as reserve refugees who are difficult to evacuate can be estimated as the number of persons who are difficult to evacuate.

  FIG. 3 is a diagram illustrating a hardware configuration example of the estimation apparatus according to the embodiment of the present invention. The estimation device 10 in FIG. 3 includes a drive device 100, an auxiliary storage device 102, a memory device 103, a CPU 104, an interface device 105, and the like that are connected to each other via a bus B.

  A program that realizes processing in the estimation apparatus 10 is provided by the recording medium 101. When the recording medium 101 on which the program is recorded is set in the drive device 100, the program is installed from the recording medium 101 to the auxiliary storage device 102 via the drive device 100. However, the program need not be installed from the recording medium 101 and may be downloaded from another computer via a network. The auxiliary storage device 102 stores the installed program and also stores necessary files and data.

  The memory device 103 reads the program from the auxiliary storage device 102 and stores it when there is an instruction to start the program. The CPU 104 executes a function related to the estimation device 10 according to a program stored in the memory device 103. The interface device 105 is used as an interface for connecting to a network.

  An example of the recording medium 101 is a portable recording medium such as a CD-ROM, a DVD disk, or a USB memory. An example of the auxiliary storage device 102 is an HDD (Hard Disk Drive) or a flash memory. Both the recording medium 101 and the auxiliary storage device 102 correspond to computer-readable recording media.

  FIG. 4 is a diagram illustrating a functional configuration example of the estimation device according to the embodiment of the present invention. In FIG. 3, the estimation device 10 includes an entrance / exit record reception unit 11, a home station estimation unit 12, a work station estimation unit 13, a mobility estimation unit 14, a visitor extraction unit 15, a visitor classification unit 16, and the like. . Each of these units is realized by processing executed by the CPU 104 by a program installed in the estimation apparatus 10. The estimation device 10 also includes an individual master storage unit 111, a boarding history storage unit 112, an individual estimation information storage unit 113, a neighboring station information storage unit 114, an inter-station distance storage unit 115, a threshold storage unit 116, and an estimation result storage unit. 117 or the like is used. Each of these storage units can be realized by using the auxiliary storage device 102 or a storage device connected to the estimation device 10 via a network.

  The entrance / exit record receiving unit 11 receives an entrance record or an exit record transferred from the automatic ticket gate 20 at each station. The entry / exit record reception unit 11 stores the received entry record or exit record in the boarding history storage unit 112. In the boarding history storage unit 112, a set of an entry record and an exit record relating to the same ticket ID is stored in one record. In the present embodiment, a set of an entry record and an exit record for the same ticket ID is referred to as a “boarding history”. Therefore, the boarding history storage unit 112 stores a list of boarding histories. The ticket ID is an example of a ticket identifier. The boarding ticket includes an electronic card using a mobile terminal in addition to an IC card or magnetic card type commuter pass or boarding ticket. Basically, in this embodiment, the ticket ID and the user correspond one-to-one.

  The home station estimation unit 12 estimates the home station of the user of the ticket for each ticket ID based on the boarding history stored in the boarding history storage unit 112.

  The work station estimation unit 13 is based on the boarding history and the like stored in the boarding history storage unit 112 and the information stored in the neighboring station information storage unit 114 and the work of the user of the ticket for each ticket ID. Estimate the destination station. The neighboring station information storage unit 114 stores a combination of stations located in the vicinity of each other.

  The travel capability estimation unit 14 estimates the travel capability of the user of the ticket for each ticket ID based on the information stored in the personal master storage unit 111 or the boarding history stored in the boarding history storage unit 112. To do.

  The personal master storage unit 111 stores attribute information of the user of the ticket in association with each ticket ID. For example, at the time of purchasing a ticket, information applied by the user is stored in the personal master storage unit 111.

  The personal estimation information storage unit 113 stores the estimation results by the home station estimation unit 12, the work station estimation unit 13, and the movement capability estimation unit 14 in association with each ticket ID.

  The visitor extraction unit 15 uses the boarding history stored in the boarding history storage unit 112, the information stored in the personal estimation information storage unit 113, the information stored in the inter-station distance storage unit 115, the threshold stored in the threshold storage unit 116, and the like. Based on this, visitors are extracted from the exits at any station. The visitor classification unit 16 classifies the extracted visitors into those who are difficult to evacuate, reserve refugees who are difficult to evacuate, evacuable persons, and the like, and totals the number of each person for each station. The classification result and the total result are stored in the estimation result storage unit 117.

  For each combination of two stations, the inter-station distance storage unit 115 stores the distance between the stations related to the combination. The threshold value storage unit 116 stores a threshold value that defines a classification criterion for classifying a visitor as one of those who are difficult to evacuate, those who are difficult to evacuate, and those who can evacuate.

  Hereinafter, the process procedure which the estimation apparatus 10 performs is demonstrated. First, based on the boarding history storage unit 112, the personal master storage unit 111, and the like, a process for estimating a home station name, a work station name, a travel capability, and the like stored in the personal estimation information storage unit 113 for each ticket ID. explain.

  FIG. 5 is a flowchart for explaining an example of a processing procedure of home station estimation processing. The process of FIG. 5 is performed for each ticket ID. Each ticket ID may be specified based on, for example, the personal master storage unit 111 described later. The ticket ID that is the processing target in FIG. 5 is referred to as “target ticket ID”.

  In step S <b> 101, the home station estimation unit 12 reads the boarding history related to the target boarding ticket ID from all the boarding histories stored in the boarding history storage unit 112 into the memory device 103.

  FIG. 6 is a diagram illustrating a configuration example of the boarding history storage unit. As shown in FIG. 6, the boarding history storage unit 112 stores a boarding ticket ID, date, entrance station name, entrance time, exit station name, exit time, and the like for each boarding history.

  The ticket ID is a ticket ID read from the ticket by the automatic ticket gate 20 when entering or leaving. The date is the date when the ticket is read by the automatic ticket gate 20. The entrance station name is the station name of the station where the automatic ticket gate 20 that records entry for the ticket is installed. The admission time is the time when the entrance to the station was recorded by the automatic ticket gate 20 with respect to the ticket. The exit station name is the station name of the station where the automatic ticket gate 20 that records the exit for the ticket is installed. The exit time is the time when the exit from the station was recorded by the automatic ticket gate 20 with respect to the ticket.

  The boarding history stored in the boarding history storage unit 112 is based on the entrance record and the exit record received by the entrance / exit record receiving unit 11 from each automatic ticket checker 20 at each station. That is, when receiving the entrance record, the entrance / exit record receiving unit 11 adds a new record to the boarding history storage unit 112, and determines the ticket ID, entrance station name, and entrance time included in the entrance record. Store in the record. When receiving the exit record, the entrance / exit record receiving unit 11 searches for a record that includes the ticket ID included in the exit record and does not store the exit station name and the exit time. The entrance / exit record reception unit 11 stores the exit station name and exit time included in the received exit record in the corresponding record.

  In FIG. 6, the station name of each station is encoded as “AAA” for convenience. FIG. 6 shows an example in which the boarding history is stored only for one boarding ticket ID. This is because FIG. 6 shows the result read in step S101. Actually, the boarding history storage unit 112 may store a boarding history related to each ticket ID. Alternatively, the boarding history storage unit 112 may be generated for each boarding ticket ID. In FIG. 6, for the sake of convenience, the date of the previous day is given to the boarding history related to the train until the last train even after midnight. For example, it is a boarding history with an exit time of May 18 at 0:38 am or 1:00 am. However, the date of these boarding histories is strictly May 19th.

  Subsequently, the home station estimation unit 12 repeats steps S102 and S103 for the number of the read boarding history dates. FIG. 6 shows boarding histories for three days on May 16, 17, and 18. Therefore, steps S102 and S103 are repeated three times. Hereinafter, the date to be processed is referred to as “current day”.

  In step S <b> 102, the home station estimation unit 12 adds 1 to the number of times of use for the entry station name of the first entry record in the entry record on that day. The first admission record is the admission record with the earliest admission time. For May 16, 1 is added to the number of uses for “AAA”, which is the name of the entry station in the entry record of the first row. Note that the initial value of the number of uses at each station is zero.

  Subsequently, the home station estimation unit 12 adds 1 to the number of uses for the exit station name of the last exit record in the exit record of the day. The last exit record is an exit record with the latest exit time. For May 16, 1 is added to the number of uses for “AAA”, which is the exit station name in the exit record of the fourth row (S103).

  By executing step S102 for the remaining dates, 17th and 18th, the counting result of the first or last use frequency of the station used first or last on each day is shown in FIG. As shown.

  FIG. 7 is a diagram illustrating an example of a counting result of the first or last use frequency of a station used first or last. FIG. 7 shows an example in which 6 is recorded as the number of uses for the station name “AAA”. This is because, in the example of FIG. 6, the name of the first entry station and the name of the last exit station are “AAA” on any of the three days.

  Subsequently, the home station estimation unit 12 estimates the station name having the highest number of uses as the home station name for the target ticket ID, and associates the station name with the target ticket ID to store the personal estimation information storage unit. It memorize | stores in 113 (S104).

  FIG. 8 is a diagram illustrating a configuration example of the personal estimation information storage unit. In FIG. 8, the personal estimation information storage unit 113 stores a home station name, a work station name, a travel capability, and the like for each ticket ID. The home station name is an estimated value of the station name of the home station of the user of the ticket related to the ticket ID. The work station name is an estimated value of the station name of the work station of the user of the ticket related to the ticket ID. The moving ability is the moving ability of the user of the ticket related to the ticket ID.

  The moving ability is information indicating the moving speed. In this embodiment, the moving ability is expressed by values classified into three categories or stages of “high”, “medium”, and “low” according to the moving speed. The The relative relationship between the movement speeds of the respective sections of the movement ability is “low” <“medium” <“high”.

  In step S104, the name of the station having the maximum number of uses is stored for the home station name of the record for the target ticket ID.

  In FIG. 5, for each ticket ID, a station that frequently becomes an entrance station at the first use of the day and a station that frequently becomes an exit station at the last use of the day are indicated by the ticket ID. An example that is estimated to be the home station of the user of is shown. However, the home station estimation method is not limited to the method shown in FIG. For example, for each ticket ID, a station whose frequency read by the automatic ticket gate 20 is higher than a predetermined value within a predetermined number of days may be estimated as the home station of the user of the ticket ID. In this case, the number of uses may be counted for each entry station name or exit station name in the boarding history shown in FIG. However, there is a possibility that a transfer station will be selected if the number of times of use is simple. For example, as for FIG. 6, the number of times of use of the BBB station is the highest at 8 times. However, BBB station is a transfer station, not a home station. Therefore, when the station has entered another station within a predetermined time after leaving a certain station, the number of times of use may not be counted for the certain station.

  In addition, for each ticket ID, for each combination of entry station or exit station, a combination that appears most frequently within a predetermined number of days is specified, and one of the stations included in the combination is estimated to be a home station. May be. In this case, among the combinations, for example, the one having a higher appearance frequency within a predetermined number of days or the one having a higher frequency of becoming an entrance station at the first use of the day may be designated as home.

  Thus, the home station name is specified based on the number of appearances of the station name satisfying the predetermined condition among the station names included in the boarding history stored in the boarding history storage unit 112. The predetermined condition is, for example, the first entry station name of the day or the last exit station name of the day.

  Next, the work station estimation process will be described. FIG. 9 is a flowchart for explaining an example of a processing procedure of work station estimation processing. The process of FIG. 9 is performed for each ticket ID. Each ticket ID may be specified based on, for example, the personal master storage unit 111 described later. The ticket ID that is the processing target in FIG. 5 is referred to as “target ticket ID”.

  In step S <b> 111, the work station estimation unit 13 reads the boarding history related to the target ticket ID into the memory device 103 from all boarding histories stored in the boarding history storage unit 112. Here, it is assumed that the boarding history as shown in FIG. 6 has been read.

  Subsequently, the work station estimation unit 13 repeats steps S112 to S114 for the number of combinations of exit record → entrance record within the same day. A combination of an exit record on the same day and an entrance record refers to a combination of an exit record of a certain boarding history and an entry history of the boarding history and the boarding history of the next day after the boarding history. . Therefore, with respect to the list of boarding histories shown in FIG. 6, the combinations are as shown in FIG.

  FIG. 10 is a diagram illustrating an example of a combination of exit record → entrance record within the same day. In FIG. 10, for example, the record on the first line is a combination of the exit record on the first line and the entry record on the second line in FIG. Therefore, the loop of steps S112 to S114 is repeated for the number of rows in FIG. In the loop processing, a combination that is a processing target is referred to as a “target combination”. In FIG. 10, a stay time column is provided. The staying time is a value calculated by calculating the entry time-exit time.

  In step S112, the work station estimation unit 13 determines whether the exit station name and the entrance station name included in the target combination match, or whether the exit station and the entrance station are located in the vicinity of each other. judge. Whether the exit station and the entrance station are in the vicinity of each other is determined with reference to the nearby station information storage unit 114.

  FIG. 11 is a diagram illustrating a configuration example of the neighboring station information storage unit. In FIG. 11, the neighboring station information storage unit 114 stores a representative station name and a neighboring station name for each combination of stations located near each other.

  The neighboring station name is a station name of a station located in the vicinity of the station related to the representative station name. Therefore, when a record in which one of the exit station name or the entrance station name matches the representative station name and the other matches the neighborhood station name is stored in the neighborhood station information storage unit 114, in step S112, the exit station and the entrance station are nearby. Is determined to be located.

  The neighborhood refers to a walking distance. The definition of walking distance may be determined at the time of actual operation. For example, within 10 minutes of walking may be determined as walking distance.

  If the exit station name and the entrance station name included in the target combination match, or if the exit station and the entrance station are in the vicinity of each other (Yes in S112), the work station estimation unit 13 stays. It is determined whether the time is a predetermined time or more (S113). The stay time is the stay time around the station related to the exit station name. As described with reference to FIG. 10, the stay time can be calculated from the entry time-exit time of the target combination. The predetermined time is a value set as a threshold for staying time at work. For example, considering the case of working in the morning, 3 hours may be set as the predetermined time, or a value less than 3 hours or a value exceeding 3 hours may be set as the predetermined time.

  If the stay time is equal to or longer than the predetermined time (Yes in S113), the work station estimation unit 13 adds 1 to the number of stays for the exit station name (S114). If the staying time is less than the predetermined time (No in S113), step S114 is not executed. Note that the initial value of the number of stays at each station is zero.

  By executing steps S112 to S114 for each combination shown in FIG. 10, the result of counting the number of stays for the exit station name where the stay time is a predetermined time or more is as shown in FIG. 12, for example.

  FIG. 12 is a diagram illustrating an example of a counting result of the number of stays longer than a predetermined time. FIG. 12 shows an example in which the number of stays is 3 for the station name “CCC”, 1 for “FFF”, and 1 for “GGG”. The number of stays for “CCC” is based on the records in the second, fifth, and ninth lines of FIG. The number of stays for “FFF” is based on the record in the seventh row of FIG. The number of stays with respect to “GGG” is based on the record in the eighth row in FIG.

  Subsequently, the work station estimation unit 13 estimates that the station name having the maximum number of stays is the station name of the work station with respect to the target ticket ID, and associates the station name with the target ticket ID. The information is stored in the “work station name” in the estimated information storage unit 113 (FIG. 8) (S115). In the example of FIG. 12, “CCC” is the work station name.

  Next, the process for estimating the moving ability of a user of a ticket will be described. FIG. 13 is a flowchart for explaining an example of a processing procedure of the first estimation process of the moving ability.

  In step S <b> 121, the movement capability estimation unit 14 reads all records stored in the personal master storage unit 111 into the memory device 103.

  FIG. 14 is a diagram illustrating a configuration example of the personal master storage unit. In FIG. 14, the personal master storage unit 111 stores attribute information of the user of the ticket such as age, sex, and disabled person flag in association with each ticket ID. The disabled person flag is information indicating whether or not the person is disabled. The disabled person flag may be stored in the personal master storage unit 111 in association with the ticket ID when the automatic ticket checker 20 reads information corresponding to the disabled person flag from the ticket. In the present embodiment, “1” indicates that the person is disabled, and “0” indicates that the person is not disabled.

  Subsequently, the movement capability estimation unit 14 executes steps S123 to S130 for each read record. Hereinafter, the record to be processed is referred to as “target record”. In addition, the ticket ID related to the target record is referred to as “target ticket ID”.

  In step S123, the movement capability estimation unit 14 determines whether the value of the disabled person flag in the target record is 1. When the value of the disabled flag is 1 (Yes in S123), the moving ability estimation unit 14 determines that the moving ability for the target ticket ID is “low” (S124).

  When the value of the person with a disability flag is 0 (No in S123), the movement ability estimation unit 14 determines whether the value of the age of the target record is 70 or more or 10 or less (S125). When the age value of the target record is 70 or more or 10 or less (Yes in S125), the moving ability estimation unit 14 determines that the moving ability for the target ticket ID is “low” (S126).

  When the age value of the target record is not 70 or more and not 10 or less (No in S125), the mobility estimation unit 14 indicates that the gender value of the target record is male and the age value is 18 or more. It is determined whether it is 40 or less (S127). When the target record satisfies the condition (Yes in S127), the movement capability estimation unit 14 determines that the movement capability for the target ticket ID is “high” (S128).

  When the target record does not satisfy the condition (No in S127), the moving ability estimation unit 14 determines that the moving ability for the target ticket ID is “medium” (S129). Subsequent to step S124, S126, S128, or S129, the movement ability estimation unit 14 stores the movement ability of the determination result in the “movement ability” of the personal estimation information storage unit 113 in association with the target ticket ID. (S130).

  When steps S123 to S130 are executed for all the records, the processing in FIG. 13 ends.

  In addition, the movement capability with respect to each ticket ID may be estimated by the following procedure. FIG. 15 is a flowchart for explaining an example of the processing procedure of the second estimation process of the movement ability. In FIG. 15, the estimation procedure of the movement capability regarding one boarding ticket ID is shown. Therefore, the process of FIG. 15 should just be performed regarding each boarding ticket ID. Note that the ticket ID that is a processing target in FIG. 15 is referred to as a “target ticket ID”.

  In step S <b> 141, the travel capability estimation unit 14 acquires all boarding histories related to the target boarding ticket ID from the boarding history storage unit 112. Subsequently, the mobility estimation unit 14 calculates the average value of the required time in the section between the home station name and the work station name based on the acquired boarding history (S142). As the home station name and the work station name, values stored in the personal estimation information storage unit 113 in association with the target ticket ID are used. Based on the boarding history of the same date, the required time for the date is calculated by subtracting the entrance time of the station name corresponding to the home station name from the exit time of the station name corresponding to the work station name. The average value is obtained by calculating the average of the required times calculated for a plurality of days.

  Subsequently, the travel capability estimation unit 14 compares the calculated average value with the standard required time of the section, and determines the travel capability for the ticket ID based on the magnitude relationship (S143). Specifically, when the average value is shorter than the standard required time, it is determined that the moving ability for the ticket ID is “high”. When the average value is the same as the standard required time, it is determined that the moving ability corresponding to the ticket ID is “medium”. When the average value is longer than the standard required time, it is determined that the movement capability corresponding to the ticket ID is “low”.

  Note that the standard required time is not a unique value and may have a range. In addition, the standard required time may be set in advance for each section, or may be acquired using software for searching for a route between stations. Usually, such software outputs not only the route but also the required time. Therefore, the required time may be treated as a standard required time. At this time, the name of the home station and the name of the work station may be designated as the departure point and the destination as input information for the software. For the transit station, a station name included between the home station name and the work station name in the boarding history may be specified.

The second estimation method of the movement ability is based on the idea that the required time may vary depending on the movement ability at the time of transfer even in the same section. According to such an estimation method, the movement ability can be estimated based on individual differences other than age and gender.
Note that the information stored in the individual estimated upper storage unit 113 may not be automatically estimated but may be input as setting information by the user.

  Thus, the preparation process for estimating the number of people with difficulty in evacuation is completed. That is, when the above processing is completed, the estimation device 10 can estimate the number of people who have difficulty evacuating.

  FIG. 16 is a flowchart for explaining an example of the processing procedure of the estimation process of the number of people who are difficult to escape. Note that the processing of FIG. 16 may be performed, for example, at regular intervals, that is, at regular intervals. In the present embodiment, an example is shown that is performed at 10-minute intervals.

  In step S201, the visitor extraction unit 15 executes a visitor extraction process. In the visitor extraction process, visitors are extracted from the exits. Subsequently, the visitor classification unit 16 executes a visitor classification process (S202). In the visitor classification process, as shown in FIG. 2 (2), the breakdown of visitors is classified.

  Next, details of step S201 will be described. FIG. 17 is a flowchart for explaining an example of the procedure of the visitor extraction process.

  In step S211, the visitor extraction unit 15 acquires the latest boarding history from the boarding history storage unit 112 for each ticket ID stored in the personal master storage unit 111, the personal estimation information storage unit 113, or the like. Specifically, for each ticket ID, the entry time or the exit time is the latest, that is, the boarding history stored last in the boarding history storage unit 112 is acquired.

  Subsequently, the visitor extraction unit 15 performs a loop process for each acquired boarding history with respect to steps S212 to S216. In the loop processing, a boarding history that is a processing target is referred to as a “target history”, and a ticket ID related to the target history is referred to as a “target ticket ID”.

  In step S <b> 212, the visitor extraction unit 15 acquires the home station name and the work station name associated with the target ticket ID from the personal estimation information storage unit 113. Subsequently, the visitor extraction unit 15 determines whether or not an exit record is included in the target history (S213). When the exit record is not included in the target history (No in S213), since the user related to the target ticket ID is not likely to be a leaver, the loop process ends for the target history. That is, when there is no exit record in the target history, the passenger related to the target history is on board and moving, and therefore it is difficult to specify the position of the passenger.

  On the other hand, if the exit history is included in the target history (Yes in S213), the visitor extraction unit 15 determines whether the exit station name included in the exit record matches the home station name acquired in step S212. It is determined whether or not (S214). When the exit station name matches the home station name (Yes in S214), since the user related to the target ticket ID is highly likely to be a resident, the loop process ends for the target history.

  On the other hand, if the exit station name does not match the home station name (No in S214), the visitor extraction unit 15 determines whether or not the exit station name matches the work station name acquired in step S212 ( S215). When the exit station name matches the work station name (Yes in S214), since the user related to the target ticket ID is highly likely to be a worker, the loop process ends for the target history.

  On the other hand, if the exit station name does not match the work station name (No in S215), the visitor extraction unit 15 adds the visitor data including the target ticket ID and the exit station name to the visitor list (S216). ). The visitor list is a list of visitor data including the ticket ID of the user who is determined or estimated to be a visitor and the station name of the user's last exit station. Remembered.

  When the loop process is completed for all the boarding histories acquired in step S211, the process of FIG. 17 ends. When the process of FIG. 17 is completed, the visitor list includes a list of visitor data of visitors at any station.

  Next, details of step S202 in FIG. 16 will be described. FIG. 18 is a flowchart for explaining an example of the procedure of the visitor classification process.

  The visitor classification unit 16 executes a loop process for each visitor data included in the visitor list with respect to steps S221 to S229. In the loop processing, visitor data to be processed is referred to as “target data”.

  In step S <b> 221, the visitor classification unit 16 acquires from the personal estimation information storage unit 113 the home station name, the commuting station name, and the movement ability that are associated with the ticket ID included in the target data. Hereinafter, when it is simply referred to as a home station name, a commuting destination station name, or a moving ability, it refers to these values acquired in step S221.

  Subsequently, the visitor classification unit 16 determines whether or not the movement capability is “low” (S222). When the movement capability is “low” (Yes in S222), the visitor classification unit 16 needs to preferentially handle the visitor related to the target data at the station related to the exit station name included in the target data. It is determined that the person is difficult to evacuate, and the determination result is stored in the estimation result storage unit 117 (S223). The determination result is stored in the estimation result storage unit 117 in the estimation result table 117T stored for each station name.

  FIG. 19 is a diagram illustrating a configuration example of an estimation result table corresponding to one station. In FIG. 19, the estimation result table 117T has a record corresponding to the time for each time. Each record includes items such as time, the number of people staying, the number of people who are difficult to evacuate (excellent), the number of people who are difficult to evacuate, the number of reserve soldiers who are difficult to evacuate, and the number of people who can evacuate.

  The time is the time when the record is generated. That is, the time is the time when the process of FIG. 16 is executed. The number of people staying is the number of people estimated to stay at the station, and is the total value of the following items. The number of people with difficulty in evacuation (excellent) is the number of people with difficulty in evacuation who need priority treatment. “Preferential treatment” is, for example, preferential protection to an evacuation site. The number of people with difficulty in evacuation is the number of people with difficulty in evacuation excluding those with difficulty in evacuation who need priority treatment. The number of evacuable persons is the number of evacuable persons.

  Therefore, in step S223, the visitor classification unit 16 stores the items of the number of persons who have difficulty in evacuation (excellent) in the record corresponding to the current time and the stay in the estimation result table 117 corresponding to the exit station name included in the target data. 1 is added to each value of the number of people item.

  On the other hand, when the moving ability is not “low” (No in S222), the visitor classification unit 16 determines the distance between the exit station name included in the target data and the home station name or the work station name as the distance between stations. Obtained from the storage unit 115 (S224).

  FIG. 20 is a diagram illustrating a configuration example of an inter-station distance storage unit. As illustrated in FIG. 20, the inter-station distance storage unit 115 stores the distance between the stations related to the two station names for each combination of the two station names. In FIG. 20, an example of a part of information stored in the inter-station distance storage unit 115 is shown.

  Hereinafter, simply referring to “distance between stations” means the shorter one of the distance to the exit station name and the home station name and the distance to the exit station name and the work station name acquired in step S224. The reason why the distance to the exit station name and the work station name is used is to consider the possibility of evacuation to the workplace. However, when operating the estimation system 1 of the present embodiment based on the idea that a person who is out of the workplace will not return to the workplace, the “distance between stations” in the following is the exit station name and the home station name. May be a distance to.

  Subsequently, the visitor classification unit 16 determines whether or not the inter-station distance is equal to or greater than the threshold value β (S225). The value of the threshold β is acquired from the threshold storage unit 116.

  FIG. 21 is a diagram illustrating a configuration example of the threshold value storage unit. In FIG. 21, the threshold storage unit 116 stores the values of the threshold α and the threshold β. The threshold value α is a threshold value for distinguishing the evacuable person and the refugee reserve army based on the distance between stations. The threshold value β is a threshold value for distinguishing between those who are difficult to escape and those who are difficult to escape based on the distance between stations. In the example of FIG. 21, the threshold value α = 10 km and the threshold value β = 20 km.

  When the distance between stations is equal to or greater than the threshold β (Yes in S225), the visitor classification unit 16 determines that the visitor related to the target data is a person who is difficult to evacuate at the station related to the exit station name included in the target data. The determination result is stored in the estimation result storage unit 117 (S226). In other words, the visitor classification unit 16 uses the estimated result table 117T (FIG. 19) corresponding to the exit station name for each value of the number of people who are difficult to evacuate and the number of staying people in the record corresponding to the current time. 1 is added.

  On the other hand, when the distance between stations is less than the threshold β (No in S225), the visitor classification unit 16 determines whether the distance between stations is equal to or greater than the threshold α (S227). When the distance between the stations is equal to or greater than the threshold value α (Yes in S227), the visitor classification unit 16 selects the visitor related to the target data as a reserve refugee army at the station related to the exit station name included in the target data. It is determined that there is, and the determination result is stored in the estimation result storage unit 117 (S228). In other words, the visitor classification unit 16 uses the estimated value table 117T (FIG. 19) corresponding to the exit station name and the values of the reserve refugee army number item and the staying number item of the record corresponding to the current time. 1 is added to.

  On the other hand, when the distance between the stations is less than the threshold value α (No in S227), the visitor classification unit 16 identifies the visitor related to the target data as an evacuable person at the station related to the exit station name included in the target data. It is determined that there is, and the determination result is stored in the estimation result storage unit 117 (S229). In other words, the visitor classification unit 16 uses the estimated result table 117T (FIG. 19) corresponding to the exit station name for each value of the number of evacuable persons and the number of staying persons in the record corresponding to the current time. 1 is added.

  When Steps S221 to S229 are executed for all the visitor data included in the visitor list, the process in FIG. 18 ends. The classification criteria such as those who are difficult to evacuate (excellent), people who are difficult to evacuate, reserve armies who are difficult to evacuate, and those who can evacuate may not necessarily be the same as those in FIG.

  For example, when the movement ability is “low”, the determination may be made by changing the threshold values α and β instead of immediately determining that the person is difficult to escape (excellent). Specifically, before step S222, it is determined whether or not the movement capability is “low”. If the movement capability is “low”, the threshold values α and β are decreased. In addition, step S225 and subsequent steps may be executed. In this case, in step S226, it may be determined that the person is difficult to escape (excellent). Such a process may be performed when the movement capability is “medium”. When the movement ability is “medium”, the threshold decrease width may be made smaller than when the movement ability is “low”.

  Note that, as described with reference to FIG. 18, in the case where the moving ability is “low”, the form immediately determined to be a person with difficulty in evacuation (excellent) is also an example of the form in which the classification standard is changed according to the moving ability. . In this case, it can be considered that both the threshold values α and β are set to 0.

  At the end of FIG. 18, the estimation result table 117T corresponding to each station is in a state in which the value of each item is stored for the record corresponding to the current time.

  By continuously executing the processing of FIG. 16, for example, when a disaster occurs, the situation of each station can be estimated by referring to the latest record in the estimation result table 117T corresponding to each station. Based on the estimation result, the administrative agency or the like can determine the number of supplies to be distributed and the scale of the shelter to be opened.

  As described above, according to the present embodiment, the exit from each station is estimated based on the entrance record and exit record read by the automatic ticket gate 20, and the visitors are extracted from the exit. Further, based on the distance between each visitor's home station or work station and the exit station, it is estimated whether each visitor is a person who has difficulty in evacuation or the like. Therefore, when a disaster occurs, the number of people who have difficulty evacuating at each station can be estimated.

  In the present embodiment, the home station and work station of each user are estimated based on the boarding history. Therefore, at the time of purchasing a ticket, it is possible to estimate a home station, a work station, and the like without requiring an application from a user, and use it for estimating whether or not the person is an evacuated person.

  Further, the criteria for determining whether or not the person is a refugee person changes according to the moving ability of each visitor. Therefore, it is not uniform for all visitors, and it is possible to estimate whether the person is a refugee person or the like in consideration of the state of each individual. As a result, although arrival at evacuation centers, such as elderly people and children, is delayed in evacuation centers etc., it can be expected that space will be secured in advance for the number of people who should evacuate with priority.

  In the present embodiment, the mobility is estimated in advance before the disaster occurs. When a disaster occurs, it is assumed that people who are not difficult to walk will stay in the vicinity of the station to see the situation, or those who have difficulty walking will be forced to move in a hurry, etc. The Therefore, if the moving ability is estimated by some method based on the actual measurement value when a disaster occurs, the correct moving ability may not be estimated. In this embodiment, such a possibility can be reduced.

  If the student is allowed to wait or evacuate in the school, the student may be treated in the same manner as the commuter described above. In this case, the commuting station name is strictly the commuting station name. However, the estimation device 10 does not distinguish between commuting and commuting, and estimates the commuting station name based on the staying time and the like. Therefore, it is considered that commuters include commuters, with the processing procedure described above.

  Similarly, a person other than a commuter and a commuter who is attending a predetermined destination may be included in the commuter as long as standby or evacuation is permitted at the destination. . The place to go does not have to be a place belonging to any organization or organization, such as a friend's house or a home.

  In addition, when it is desired to estimate the number of people who have difficulty in returning home and the number of people who have difficulty returning home in a strict sense, the commuters need only be included in the visitors and the process may be executed.

  Further, the embodiment of the present invention may be used for estimating the status of a staying person at a bus stop or the like. In this case, information may be read from the boarding ticket by a checkout processing device or the like installed at each bus or bus stop and transferred to the estimation device 10 as an entry record or an exit record.

  In the present embodiment, the home or work place is an example of a place having a predetermined relationship for each user of the ticket. More specifically, it can be said that the place having the predetermined relationship is an evacuable place. The visitor extraction unit 15 is an example of an extraction unit. The visitor classification unit 16 is an example of a classification unit. The boarding history storage unit 112 is an example of a first storage unit. The personal estimation information storage unit 113 is an example that is an example of a second storage unit and a fourth storage unit. The inter-station distance storage unit 115 is an example of a third storage unit. The automatic ticket gate 20 is an example of a ticket gate processing device or a payment processing device.

  As mentioned above, although the Example of this invention was explained in full detail, this invention is not limited to such specific embodiment, In the range of the summary of this invention described in the claim, various deformation | transformation・ Change is possible.

1 Estimating System 10 Estimating Device 11 Entrance / Exit Record Receiving Unit 12 Home Station Estimating Unit 13 Work Station Estimating Unit 14 Mobility Ability Estimating Unit 15 Visitor Extracting Unit 16 Visitor Classifying Unit 20 Automatic Ticket Gate 100 Drive Device 101 Recording Medium 102 Auxiliary Storage device 103 Memory device 104 CPU
105 interface device 111 personal master storage unit 112 boarding history storage unit 113 personal estimation information storage unit 114 neighboring station information storage unit 115 distance between stations storage unit 116 threshold storage unit 117 estimation result storage unit B bus

Claims (8)

Based on the exit location information or the exit location information transmitted from the ticket gate processing device or the settlement processing device according to the exit or exit using the ticket, the last exit location or the last exit location using the ticket is specified. And
Determining whether the identified last exit location or last disembarkation location matches one or more exit location information or disembarkation location information stored in association with the boarding ticket;
If there is no match, it is estimated that there is a staying person at the identified last exit location or last exit location,
An estimation method in which processing is executed by a computer. Based on the exit location information or the exit location information transmitted from the ticket gate processing device or the settlement processing device according to the exit or exit using the ticket, the last exit location or the last exit location using the ticket is specified. And
The identified last exit location or last disembarkation location, and a location closest to the last exit location or the last disembarkation location among one or more exit locations or disembarkation locations stored in association with the ticket Depending on the length of the distance between, estimating the presence of a detainee at the identified last exit location or last exit location;
An estimation method in which processing is executed by a computer. Refer to the first storage unit that stores the station name of the station in association with the identifier of the ticket read from the ticket by the automatic ticket checker when leaving the station, and the last exit station for each identifier of the ticket Identify the station name of
Referring to the second storage unit that stores the station name of the nearest station of the place having a predetermined relationship with the user of the ticket for each identifier of the ticket, the station name of the last exit station is the nearest station Extract a list of ticket identifiers that do not match the station name,
The identifier of the ticket included in the extracted list is the distance stored in the third storage unit in association with the station name of the last exit station related to the identifier and the station name of the nearest station related to the identifier. An estimation method in which a computer executes a process of classifying based on the classification. The first storage unit stores the station name of the station in association with the identifier of the ticket read from the ticket by an automatic ticket gate when entering the station,
For each identifier of the ticket, the nearest station of the place is determined based on the number of appearances of the station name that satisfies a predetermined condition among the station names stored in the first storage unit in association with the identifier, and the determination The estimation method according to claim 3, wherein the computer executes a process of storing a station name indicated by a result in the second storage unit in association with an identifier of the ticket.   The estimation method according to claim 1, wherein the classifying process changes the classification standard according to information indicating a movement capability stored for each identifier of the ticket by the fourth storage unit. The first storage unit stores the station name and entry time of the station in association with the identifier of the ticket read from the ticket by the automatic ticket checker when entering from the station, and the automatic ticket checker when leaving the station Store the station name and exit time of the exit station in association with the identifier of the ticket read from the ticket by
Based on the entry time and exit time related to the identifier of the same ticket stored in the first storage unit, the moving ability relating to the identifier of the ticket is determined, and associated with the identifier of the ticket, The estimation method according to claim 5, wherein the computer executes a process of storing information indicating the movement capability in the fourth storage unit. Refer to the first storage unit that stores the station name of the station in association with the identifier of the ticket read from the ticket by the automatic ticket checker when leaving the station, and the last exit station for each identifier of the ticket Identify the station name of
Referring to the second storage unit that stores the station name of the nearest station of the place having a predetermined relationship with the user of the ticket for each identifier of the ticket, the station name of the last exit station is the nearest station Extract a list of ticket identifiers that do not match the station name,
The identifier of the ticket included in the extracted list is the distance stored in the third storage unit in association with the station name of the last exit station related to the identifier and the station name of the nearest station related to the identifier. An estimation program for causing a computer to execute a process of classifying based on the computer program. Refer to the first storage unit that stores the station name of the station in association with the identifier of the ticket read from the ticket by the automatic ticket checker when leaving the station, and the last exit station for each identifier of the ticket The last exit station is identified with reference to a second storage unit that stores the station name of the nearest station of the place having a predetermined relationship with the user of the ticket for each ticket identifier An extraction unit that extracts a list of identifiers of tickets that do not match the station name of the nearest station,
The identifier of the ticket included in the extracted list is the distance stored in the third storage unit in association with the station name of the last exit station related to the identifier and the station name of the nearest station related to the identifier. An estimation apparatus comprising: a classification unit that classifies based on the classification unit.

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