JP2018028726A - Estimation device, estimation method, and estimation program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To allow for appropriately estimating the number of users riding the same means of transportation.SOLUTION: An estimation device of the present invention includes an acquisition unit and an estimation unit. The acquisition unit acquires sensor information from a terminal device used by each user. The estimation unit estimates the number of users riding the same means of transportation based on the sensor information acquired from each terminal device. The acquisition unit, for example, acquires sensor information including positional information of each terminal device. The estimation device, for example, estimates the number of users riding the same means of transportation based on change in the positional information of each terminal device during a predetermined time period.SELECTED DRAWING: Figure 2

Description

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

  In recent years, smart devices such as smartphones and tablet terminals have become widespread. A user who uses such a terminal device such as a smart device uses an application related to navigation installed in the terminal device (hereinafter, simply referred to as “navigation app”) when moving by a moving means such as an automobile. To do.

JP 2011-76533 A

  As described above, in the case of the navigation application installed in the terminal device, information is acquired from each navigation application activated by the same moving means, unlike the car navigation device provided in the automobile. For this reason, it is difficult to estimate which information is related to which moving means from the information acquired from such a navigation application. In such a case, it is difficult to use the information acquired from the terminal device as probe traffic information because the same moving means are identified as different moving means.

  The present application has been made in view of the above, and an object thereof is to provide an estimation device, an estimation method, and an estimation program that appropriately estimate a user who rides on the same moving means.

  The estimation device according to the present application estimates an acquisition unit that acquires sensor information from each terminal device used by each user and a user who rides on the same moving unit based on the sensor information acquired from each terminal device. And an estimating unit.

  According to one aspect of the embodiment, there is an effect that it is possible to appropriately estimate a user who rides on the same moving means.

FIG. 1 is a diagram illustrating an example of an estimation process according to the embodiment. FIG. 2 is a diagram illustrating a configuration example of the estimation apparatus according to the embodiment. FIG. 3 is a diagram illustrating an example of a user information storage unit according to the embodiment. FIG. 4 is a diagram illustrating an example of the position information storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of a terminal-related information storage unit according to the embodiment. FIG. 6 is a flowchart illustrating an example of the estimation process according to the embodiment. FIG. 7 is a diagram illustrating an example of estimation based on wireless communication information according to the embodiment. FIG. 8 is a hardware configuration diagram illustrating an example of a computer that realizes the function of the estimation device.

  Hereinafter, a mode for carrying out an estimation device, an estimation method, and an estimation program according to the present application (hereinafter referred to as “embodiment”) will be described in detail with reference to the drawings. In addition, the estimation apparatus, the estimation method, and the estimation program according to the present application are not limited by this embodiment. In the following embodiments, the same portions are denoted by the same reference numerals, and redundant description is omitted.

(Embodiment)
[1. (Estimation process)
First, an example of the estimation process according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of an estimation process according to the embodiment. In the example illustrated in FIG. 1, the estimation device 100 is based on various information including position information acquired from each terminal device 10, and is a user who rides on the same moving means (such as “automobile C11” in FIG. 1). , Also referred to as “passenger user”).

  For example, position information detected by a GPS (Global Positioning System) sensor or the like may be used as the position information of the terminal device 10. Further, for example, the position information of the terminal device 10 may be position information estimated from information related to communication by a predetermined wireless LAN (Local Area Network) such as Wi-Fi (registered trademark) (Wireless Fidelity). Further, for example, the position information of the terminal device 10 may be position information estimated from information related to communication according to the communication standard of the terminal device 10 such as a third generation mobile communication system or a fourth generation mobile communication system.

  Moreover, the information acquired from each terminal device 10 is not limited to position information, and may include various information. For example, the information acquired from each terminal device 10 includes audio information, acceleration information, information about vibration, information about temperature, information about air pressure, information about humidity, information about humidity, and information about illuminance detected by each terminal device 10. Also good. Hereinafter, various information acquired from each terminal device 10 may be collectively referred to as “log information”.

  In the example illustrated in FIG. 1, symbols in “()” that follow the code “10” of each terminal device indicate identification information of the terminal device. For example, the terminal device 10 to which the reference numeral “10 (TM1)” is attached in FIG. 1 indicates that the terminal device 10 is identified by the terminal ID “TM1”. Hereinafter, the terminal device 10 identified by the terminal ID “TM1” may be referred to as a terminal device 10 (TM1). Similarly, for the other terminal devices 10, the terminal device 10 identified by the terminal ID may be described as the terminal device 10 (“terminal ID”). Note that the terminal device 10 (TM1) to the terminal device 10 (TMn) are collectively referred to as the terminal device 10 when they are described without distinction.

  FIG. 1 shows a case where log information is acquired from each terminal device 10 (TM1) to terminal device 10 (TMn). That is, in FIG. 1, when “n” is 1 million, the estimation device 100 estimates a user who rides on the same moving means for 1 million terminal devices 10.

  As illustrated in FIG. 1, the estimation system 1 includes a plurality of (for example, n) terminal devices 10 and an estimation device 100. The terminal device 10 and the estimation device 100 are connected to be communicable by wire or wireless via a predetermined communication network (not shown). Note that the estimation system 1 illustrated in FIG. 1 may include a plurality of estimation devices 100.

  The terminal device 10 is an information processing device used by a user. The terminal device 10 is realized by, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. FIG. 1 shows a case where the terminal device 10 is a smartphone. The terminal device 10 may be any device such as a wearable device as long as it can move with the user by being carried or worn by the user and can communicate with the estimation device 100. . For example, the terminal device 10 may be a smartphone in which a navigation application is installed. Hereinafter, the terminal device 10 may be referred to as a user. That is, hereinafter, the user can be read as the terminal device 10.

  The estimation device 100 is an information processing device that estimates a user who rides on the same moving unit based on sensor information acquired from each terminal device 10. In addition, the estimation device 100 uses a predetermined user group (terminal device 10 (TM1) to terminal device 10 (TMn) in FIG. 1) as an estimation target, and is a two-stage process including a first estimation process and a second estimation process. Thus, a user who rides on the same moving means is estimated. In the example of FIG. 1, the estimating apparatus 100 uses the n terminal devices 10 of the terminal device 10 (TM1) to the terminal device 10 (TMn) as the first user group, and the second user group narrowed down the first user group. Further, a user who rides on the same moving means from the second user group is estimated.

  First, the estimation device 100 acquires log information from the terminal device 10 (TM1) (step S11-1). As described above, the estimation device 100 acquires log information including position information, audio information, acceleration information, information about vibration, information about temperature, information about air pressure, information about humidity, information about humidity, and information about illuminance from the terminal device 10.

  Moreover, the estimation apparatus 100 acquires log information from the terminal device 10 (TM2) (step S11-2). Moreover, the estimation apparatus 100 acquires log information from the terminal device 10 (TM3) (step S11-3). Moreover, the estimation apparatus 100 acquires log information from the terminal device 10 (TM4) (step S11-4). Moreover, the estimation apparatus 100 acquires log information from the terminal device 10 (TM5) (step S11-5). Moreover, the estimation apparatus 100 acquires log information from the terminal device 10 (TMn) (step S11-n).

  Note that steps S11-1 to S11-n are for explaining the processing, and any of steps S11-1 to S11-n may be performed first, and each step S11-1 to S11-n is performed. May be performed multiple times. Hereinafter, when it demonstrates without distinguishing step S11-1-S11-n, it is named step S11 generically.

  And the estimation apparatus 100 estimates a 2nd user group by a 1st estimation process. For example, the estimating apparatus 100 estimates the second user group using the n terminal devices 10 from the terminal device 10 (TM1) to the terminal device 10 (TMn) from which the log information is acquired as the first user group TG11. In the example of FIG. 1, the estimation device 100 estimates the position of each terminal device 10 at a certain date and time based on the position information of each terminal device 10 at a certain date and time for the sake of simplicity. The case where a 2nd user group is estimated based on the position of each terminal device 10 in is shown.

  For example, the estimating apparatus 100 specifies (estimates) the position of each terminal apparatus 10 at the date and time DC (step S12). In the example illustrated in FIG. 1, the position information may be acquired from a date and time DC within a predetermined range (for example, within 3 seconds). Hereinafter, when “date and time D * (“ * ”is an arbitrary character)” is described, “date and time D *” may include a date and time within a predetermined range from “date and time D *”.

  The map information MP11 in FIG. 1 schematically shows the position of each terminal device 10 at the date and time DC. Moreover, the position of each terminal device 10 in the map information MP11 in FIG. 1 is indicated by its terminal ID (TM1, TM2, etc.). For example, the map information MP11 in FIG. 1 indicates that the terminal device 10 (TM7) and the terminal device 10 (TM1125) are located close to each other on the date and time DC.

  And the estimation apparatus 100 estimates the terminal device 10 located in a predetermined area in date and time DC as a 2nd user group (step S13). For example, the estimation device 100 estimates the terminal device 10 located in the area AR11 at the date and time DC as the second user group. For example, the area AR11 is assumed to be an area within a predetermined range (for example, 5 m) from the position information LC3. Hereinafter, when “position information LC * (“ * ”is an arbitrary character)” is described, “position information LC *” may include a predetermined range from “position information LC *”. In this case, the estimating apparatus 100 narrows down the terminal devices 10 located in a predetermined range from the position information LC3 at the date and time DC from the first user group TG11.

  In the example of FIG. 1, the estimation device 100 estimates the terminal device 10 located in the area AR11 in the date and time DC from the first user group TG11 as the second user group TG12. For example, the estimation apparatus 100 changes the second user group TG12 including the terminal device 10 (TM1), the terminal device 10 (TM2), the terminal device 10 (TM4), the terminal device 10 (TM338), and the like from the first user group TG11. presume. In this case, the estimation device 100 excludes the terminal device 10 that is not included in the area AR11 in the date and time DC, such as the terminal device 10 (TM3) and the terminal device 10 (TM5), by the first estimation process. As described above, the estimation apparatus 100 determines the number of terminal apparatuses 10 (for example, 100) less than 1 million from the first user group TG11 including 1 million terminal apparatuses 10 by the first estimation process. It narrows down to 2nd user group TG12 to include.

  For the sake of simplicity, FIG. 1 shows a case where the second user group that narrows down the first user group is estimated based on the position information of each terminal device 10 at the date and time DC. 100 may estimate the second user group using any information.

  For example, the estimation apparatus 100 may estimate the second user group based on the similarity of information regarding the space in the moving unit. For example, the estimation device 100 may estimate the second user group based on the information on the temperature, the information on the atmospheric pressure, the information on the humidity, or the information on the illuminance acquired from each terminal device 10. For example, the estimation device 100 may estimate the terminal device 10 having similar temperature, pressure, humidity, and illuminance as the second user group. In addition, the estimation apparatus 100 may estimate the second user group by comprehensively determining the various types of information described above.

  Then, the estimation device 100 identifies (estimates) the movement process for the terminal devices 10 included in the second user group TG12 (step S14). For example, as shown in the movement process list RT11 in FIG. 1, the estimation apparatus 100 determines the movement process of each terminal apparatus 10 based on the position information of the terminal apparatus 10 at three points in time, date / time DA, date / time DB, and date / time DC. presume.

  For example, as shown in the movement process list RT11 in FIG. 1, the estimation apparatus 100 performs the movement process of the terminal device 10 (TM1) with the position information LC1 at the date / time DA, the position information LC2 at the date / time DB, and the position information at the date / time DC. Estimated to be LC3. For example, the estimating apparatus 100 estimates that the movement process of the terminal device 10 (TM2) is the position information LC1 at the date and time DA, the position information LC2 at the date and time DB, and the position information LC3 at the date and time DC. For example, the estimating apparatus 100 estimates that the movement process of the terminal device 10 (TM4) is the position information LC1 at the date / time DA, the position information LC40 at the date / time DB, and the position information LC3 at the date / time DC. For example, the estimating apparatus 100 estimates that the movement process of the terminal device 10 (TM338) is the position information LC1 at the date and time DA, the position information LC2 at the date and time DB, and the position information LC3 at the date and time DC.

  And the estimation apparatus 100 estimates the user who rides among the terminal devices 10 contained in 2nd user group TG12 (step S15).

  In the example of FIG. 1, the movement process of the three terminal devices 10 of the terminal device 10 (TM1), the terminal device 10 (TM2), and the terminal device 10 (TM338) is as shown in the movement process list RT11 in FIG. The date and time DA coincide with the position information LC1, the date and time DB coincides with the position information LC2, and the date and time DC coincides with the position information LC3. Therefore, as shown in the riding user group TG13-1, the estimating apparatus 100 is a user who rides the three terminal devices 10 of the terminal device 10 (TM1), the terminal device 10 (TM2), and the terminal device 10 (TM338). Estimate as

  In the example of FIG. 1, since the position information LC40 in the date / time DB is different from the position information LC2 in the date / time DB of the terminal device 10 of the passenger user group TG13-1, in the example of FIG. Is not included. In FIG. 1, only the passenger user group TG 13-1 is illustrated, but the estimation device 100 is a terminal device 10 (TM4) included in the second user group TG 12 or another passenger user group including another terminal device 10. (For example, a passenger user group TG13-2 or the like) may be estimated.

  And the estimation apparatus 100 estimates the user who carries on boarding based on the association with the terminal device 10 and the user memorize | stored in the riding user group TG13-1 and the user information storage part 121. FIG. In the example of FIG. 1, as shown in the user information storage unit 121, the terminal device 10 (TM1) is associated with a user identified by the user ID “U1” (hereinafter also referred to as “user U1”). In the example of FIG. 1, as shown in the user information storage unit 121, the terminal device 10 (TM2) is associated with a user identified by the user ID “U2” (hereinafter also referred to as “user U2”). In the example of FIG. 1, as shown in the user information storage unit 121, the terminal device 10 (TM338) is associated with a user identified by the user ID “U338” (hereinafter also referred to as “user U338”).

  Therefore, in the example of FIG. 1, as illustrated in the result information RS <b> 11, the estimation apparatus 100 includes a user U3, a user U <b> 2, and a user U <b> 338 who are riding on the same moving means (for example, the car C <b> 11). presume. In addition, the estimation apparatus 100 may replace the terminal device 10 with a user and perform the above-described estimation process at the stage where the log information is acquired in step S11.

  As described above, the estimation device 100 is based on log information including position information, audio information, acceleration information, information on vibration, information on temperature, information on air pressure, information on humidity, information on humidity, and information on illuminance acquired from the terminal device 10. Thus, a user who rides in the same moving means is estimated. For example, the estimation apparatus 100 estimates a user who rides on the same moving means by performing a two-stage process of a first estimation process and a second estimation process with a predetermined user group as an estimation target. For example, the estimation apparatus 100 uses the n terminal devices 10 as the first user group, estimates a second user group that narrows down the first user group, and further selects a user who rides on the same moving means from the second user group. presume. Thereby, the estimation apparatus 100 can estimate the user who rides in the same moving means appropriately.

  In the example illustrated in FIG. 1, the estimation device 100 estimates the second user group based on the user position information at a certain time. And the estimation apparatus 100 estimates a riding user group based on the movement process in each user's predetermined period. As described above, the estimating apparatus 100 estimates the second user group based on the user position information at a certain time point that is the first accuracy information. In addition, the estimating apparatus 100 estimates the riding user group based on the movement process of each user in a predetermined period, which is information of the second accuracy that is higher than the first accuracy. Thereby, the estimation apparatus 100 can estimate the users who ride in the same moving means by narrowing down the users in two stages. As described above, the estimation apparatus 100 narrows down the target users to the second user group based on the position information at a certain time when the processing load is lower than the estimation based on the movement process information. By narrowing down the target users who use, it is possible to suppress an increase in processing load on the estimation device 100. Therefore, the estimation apparatus 100 can appropriately estimate users who ride in the same moving means while suppressing an increase in processing load by narrowing down the users in two stages as described above.

  For example, in the case where the above-mentioned passenger user estimation is not performed, a plurality of users (for example, four users) riding in the same moving unit may be identified as moving by different moving units. . For example, a case where a service providing apparatus that provides a navigation application provides a service using log information such as position information (probe data) acquired from the terminal device 10 that uses the navigation application will be described. For example, when four users are using the navigation application in each terminal device 10, even if four users are on the same moving means, each user has four It is identified as moving by moving means.

  Thus, when the above-mentioned passenger user estimation is not performed, it is difficult to capture the number of cars traveling on a predetermined road based on the position information acquired from the terminal device 10 using the navigation application. . Therefore, when the above-mentioned passenger user estimation is not performed, an error in the measurement of the number of cars or the like passing through becomes large. For example, as described above, four users who are riding in the same moving means are separately provided. If it is mistakenly identified as moving by four moving means, it will measure a large number of cars etc. that pass, and it may be determined that a non-congested road is congested . For this reason, when the above-mentioned passenger estimation is not performed, the traffic information cannot be appropriately provided in the navigation application.

  On the other hand, since the user group estimated as a fellow user by the estimation process performed by the estimation apparatus 100 is identified as being moved by one moving means, four users who are riding in the same moving means are separated. Thus, it is possible to suppress erroneous identification as being moved by four moving means. Therefore, it is possible to more accurately measure the number of cars or the like passing by using the information related to the passengers estimated by the estimation process performed by the estimation device 100, and the road is not congested. Can be reduced. Therefore, by using the information related to the passenger who is estimated by the estimation process performed by the estimation apparatus 100, it is possible to appropriately provide road traffic information such as traffic jam information in the navigation application.

  For example, when the estimation system 1 provides road traffic information to the terminal device 10, the estimation system 1 can appropriately provide road traffic information of traffic jam information to each terminal device 10. In this case, the estimation device 100 may provide road traffic information to each terminal device 10.

  Moreover, although the example mentioned above demonstrated the case where the estimation apparatus 100 performed an estimation process mainly based on the positional information acquired from the terminal device 10, the estimation apparatus 100 is the information which can be used for an estimation process. Any information may be used as long as it is present. For example, the estimation device 100 may use history information on the Internet of the user who uses each terminal device 10 for the estimation process. For example, the estimation device 100 may estimate the passengers on the basis of the similarity of the information regarding the schedule of the users who use each terminal device 10. For example, the estimating apparatus 100 may perform the estimation process by using, as the first user group, users having similar destinations and arrival times in the schedule.

  As described above, the estimation device 100 may use the audio information acquired from each terminal device 10 for the estimation process. For example, the estimation device 100 may estimate the passengers on the basis of the similarity of the information regarding the schedule of the users who use each terminal device 10. For example, the estimation device 100 may estimate the users who ride in the same moving unit based on the similarity of the voice information detected by each terminal device 10 in a predetermined period.

  Further, for example, the estimation device 100 may estimate a user who rides on the same moving means using information related to the user's utterance among the audio information detected by each terminal device 10 in a predetermined period. For example, the estimation device 100 may estimate a user who rides on the same moving means based on the content of a conversation estimated by analyzing information related to the user's utterance detected by each terminal device 10 during a predetermined period. Good. Further, for example, the estimation device 100 may estimate a user who rides on the same moving unit based on the similarity of environmental sounds included in the audio information detected by each terminal device 10 during a predetermined period. Note that the estimating apparatus 100 may analyze the speech information using various conventional techniques as appropriate. In addition, the analysis of the voice information described above often has a higher processing load on the estimation apparatus 100 than the estimation using other log information. Therefore, the estimation apparatus 100 performs the first estimation process based on other log information such as position information, and then performs the above analysis on the user's voice information included in the second user group. Passenger users may be estimated from the second user group.

  In the above example, the estimating apparatus 100 estimates the second user group TG12 from the first user group TG11, and estimates the same-passenger user TG13-1 and the like from the second user group TG12. Although the case where the user is estimated has been shown, the estimation apparatus 100 may estimate the riding user by various stages of processing. For example, the estimating apparatus 100 may estimate the passenger with a single stage process. In this case, in the example of FIG. 1, the estimating apparatus 100 may estimate the passenger user TG13-1 or the like directly from the first user group TG11. In this case, the estimating apparatus 100 may estimate the passenger TG 13-1 etc. directly from the first user group TG11 based on various types of log information (position, temperature, humidity, vibration, acceleration, voice, etc.). As described above, the estimation apparatus 100 may estimate the passenger with the use of various information at appropriate stages. For example, the estimation apparatus 100 first estimates the second user group from the first user group based on information on the in-vehicle environment such as temperature and humidity, and then based on the audio information, from the second user group to the third user group. May be estimated, and finally, the riding user may be estimated from the third user group based on the position information. As described above, the estimation apparatus 100 may estimate the passenger with a process of three or more stages. As in the above example, the estimation apparatus 100 may estimate the fellow passenger by performing processing in stages according to the type of information to be used. As described above, the estimating apparatus 100 may estimate the passenger in one stage from the first stage to the N stage. Note that the estimation apparatus 100 may estimate the riding user by using any information or performing any stage of processing as long as the riding user can be estimated. That is, the above-described steps such as the first step and the second step are divisions of conceptual processing steps, and the estimation apparatus 100 can perform any processing procedure as long as it can estimate a shared user based on the acquired information. The passengers may be estimated.

[2. Configuration of estimation device]
Next, the configuration of the estimation apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram illustrating a configuration example of the estimation apparatus 100 according to the embodiment. As illustrated in FIG. 2, the estimation apparatus 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The estimation device 100 includes an input unit (for example, a keyboard and a mouse) that receives various operations from an administrator of the estimation device 100 and a display unit (for example, a liquid crystal display) for displaying various types of information. May be.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). The communication unit 110 is connected to the network by wire or wireless, and transmits / receives information to / from the terminal device 10.

(Storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. As illustrated in FIG. 2, the storage unit 120 according to the embodiment includes a user information storage unit 121, a position information storage unit 122, and a terminal related information storage unit 123.

(User information storage unit 121)
The user information storage unit 121 according to the embodiment stores various types of information regarding the user. For example, the user information storage unit 121 stores various types of information regarding user attributes. FIG. 3 is a diagram illustrating an example of a user information storage unit according to the embodiment. The user information storage unit 121 illustrated in FIG. 3 includes items such as “user ID”, “terminal ID”, “gender”, and “age”.

  “User ID” indicates identification information for identifying a user. “Terminal ID” indicates information for identifying the terminal device 10 used by the corresponding user. When a corresponding user uses a plurality of terminal devices 10, a plurality of “terminal IDs” may be stored in the user information storage unit 121. “Gender” indicates the gender of the user identified by the user ID. “Year” indicates the age of the user identified by the user ID. The “age” may be a specific age of the user identified by the user ID, such as 35 years old.

  For example, in the example illustrated in FIG. 3, the user identified by the user ID “U1” indicates that the terminal device 10 identified by the terminal ID “TM1” is being used. In addition, the age of the user identified by the user ID “U1” is “30s”, and the gender is “male”.

  For example, in the example illustrated in FIG. 3, the user identified by the user ID “U2” includes the terminal device 10 identified by the terminal ID “TM2” and the terminal device 10 identified by the terminal ID “TM2-2”. It shows that a plurality of terminal devices 10 are used. In addition, the age of the user identified by the user ID “U2” is “20s”, and the gender is “female”.

  The user information storage unit 121 is not limited to the above, and may store various types of information according to the purpose. For example, the user information storage unit 121 may store information such as name, residence, interest, family structure, income, lifestyle, and the like.

(Position information storage unit 122)
The position information storage unit 122 according to the embodiment stores various types of information regarding the user's position. FIG. 4 is a diagram illustrating an example of the position information storage unit according to the embodiment. For example, the position information storage unit 122 stores position information acquired from the terminal device 10 of each user. The position information storage unit 122 illustrated in FIG. 4 includes items such as “terminal ID”, “date and time”, and “position information”.

  “Terminal ID” indicates information for identifying the terminal device 10. “Date and time” indicates the date and time when each piece of position information was acquired. “Position information” indicates the position information of the corresponding user at the corresponding date and time.

  For example, in the example illustrated in FIG. 4, the position information “LC1-1” of the terminal device 10 identified by the terminal ID “TM1” is acquired at the date “datetime DA-1”. That is, the location information “LC1-1” of the user who uses the terminal device 10 identified by the terminal ID “TM1” is acquired at the date “datetime DA-1”. For example, in the example illustrated in FIG. 4, the location information “LC2-1” of the terminal device 10 identified by the terminal ID “TM1” is acquired as the date “datetime DB-1”. That is, the location information “LC2-1” of the user who uses the terminal device 10 identified by the terminal ID “TM1” is acquired at the date “datetime DB-1”.

  In the example shown in FIG. 4, a date and time “date and time DA-1” and the like with a hyphen (“-”) means a date and time within a predetermined range (for example, within 5 seconds) from the date and time DA. Further, for example, the date / time DB-1, the date / time DB-2, and the like mean position information within a predetermined range from the date / time DB.

  In the example illustrated in FIG. 4, the position information LC <b> 1-1 to which a hyphen (“−”) is attached means position information within a predetermined range (for example, within 10 m) from the position information LC <b> 1. Further, for example, the position information LC2-1, LC2-2, and the like mean position information within a predetermined range from the position information LC2.

  In the example illustrated in FIG. 4, the estimation apparatus 100 sets the position information LC2-1 acquired in the date / time DB-1 and the position information LC2-2 acquired in the date / time DB-2 to the date / time close to the date / time DB. It may be estimated that the position information is close to the acquired position information LC2. In this case, the estimation device 100 may be configured such that the terminal device 10 (TM1) and the terminal device 10 (TM2) are located in the same area (location information LC2) at the same date (date DB).

  Note that the position information storage unit 122 is not limited to the above, and may store various information according to the purpose. FIG. 4 shows the case where the position information is stored in the position information storage unit 122 for each terminal ID, but the position information is not limited to each terminal ID, and may be stored, for example, in order of acquired date and time. .

(Terminal related information storage unit 123)
The terminal related information storage unit 123 according to the embodiment stores terminal related information. FIG. 5 is a diagram illustrating an example of a terminal-related information storage unit according to the embodiment. The terminal related information storage unit 123 illustrated in FIG. 5 stores various sensor information (log information) other than the position information as the terminal related information. The terminal related information storage unit 123 illustrated in FIG. 5 includes items such as “terminal ID”, “date and time”, “type”, and “data”.

  “Terminal ID” indicates information for identifying the terminal device 10. “Date and time” indicates the date and time when each terminal-related information is acquired. “Type” indicates the type of the terminal related information acquired at the corresponding date and time. For example, in the “type”, various types of acquired terminal-related information such as “voice”, “acceleration”, and “illuminance” are stored. “Data” indicates data of terminal-related information acquired at the corresponding date and time. Note that “data” shown in FIG. 5 shows symbols such as “data A” and “data B”, but actually, specific information, a file path name indicating the storage location, and the like are stored. The

  For example, in the example illustrated in FIG. 5, the data “A” of the type “voice” is acquired at the date “date and time DD-1” from the terminal device 10 identified by the terminal ID “TM1”. For example, in the example illustrated in FIG. 5, the data “B” of the type “acceleration” is acquired at the date “date DE-1” from the terminal device 10 identified by the terminal ID “TM1”.

  Note that the terminal-related information storage unit 123 is not limited to the above, and may store various information according to the purpose. For example, information related to wireless communication may be stored in the terminal related information storage unit 123. Further, FIG. 5 shows a case in which terminal related information is stored in the terminal related information storage unit 123 for each terminal ID. However, the terminal related information is not limited to each terminal ID, and is stored in order of acquired date and time, for example. May be.

(Control unit 130)
Returning to the description of FIG. 2, the control unit 130 is a controller and is stored in a storage device inside the estimation apparatus 100 by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. Various programs (corresponding to an example of an estimation program) are implemented by using the RAM as a work area. The control unit 130 is a controller, and is realized by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  As shown in FIG. 2, the control unit 130 includes an acquisition unit 131, an estimation unit 132, and a transmission unit 133, and realizes or executes information processing functions and operations described below. The internal configuration of the control unit 130 is not limited to the configuration illustrated in FIG. 2, and may be another configuration as long as the information processing described later is performed.

(Acquisition part 131)
The acquisition unit 131 acquires various types of information. For example, the acquisition unit 131 acquires various types of information from the user information storage unit 121, the position information storage unit 122, and the terminal related information storage unit 123. For example, the acquisition unit 131 acquires various types of information from the terminal device 10 used by the user. For example, the acquisition unit 131 acquires sensor information from each terminal device 10 used by each user.

  For example, the acquisition unit 131 acquires sensor information including position information regarding each terminal device 10. For example, the acquisition unit 131 acquires sensor information including audio information detected by each terminal device 10. For example, the acquisition unit 131 acquires sensor information including at least one of acceleration information detected by each terminal device 10, information about vibration, information about temperature, information about atmospheric pressure, information about atmospheric pressure, information about humidity, and information about illuminance. For example, the acquisition unit 131 acquires information related to wireless communication from each terminal device 10. For example, the acquisition unit 131 acquires history information on a predetermined network regarding each user.

  In the example of FIG. 1, the acquisition unit 131 acquires log information from n terminal devices 10 from the terminal device 10 (TM1) to the terminal device 10 (TMn). For example, the acquisition unit 131 acquires log information including position information, audio information, acceleration information, vibration information, temperature information, atmospheric pressure information, humidity information, and illuminance information from the terminal device 10.

(Estimation unit 132)
The estimation unit 132 estimates various information. For example, the estimation unit 132 estimates a user who rides on the same moving unit based on sensor information acquired from each terminal device 10. For example, the estimation unit 132 estimates a user who rides on the same moving unit based on a change in position information regarding each terminal device 10 in a predetermined period. For example, the estimation unit 132 estimates a user who rides on the same moving unit based on the similarity of changes in position information regarding each terminal device 10 in a predetermined period. For example, the estimation unit 132 estimates a user who rides on the same moving unit based on the similarity of audio information detected by each terminal device 10 in a predetermined period. For example, the estimation unit 132 estimates a user who rides on the same moving unit based on the content of audio information detected by each terminal device 10 during a predetermined period. For example, the estimation unit 132 estimates a user who rides on the same moving unit based on information related to wireless communication acquired from each terminal device 10. For example, the estimation unit 132 estimates a user who rides on the same moving unit based on history information on a predetermined network regarding each user.

  For example, the estimation unit 132 performs a first estimation process. For example, the estimation unit 132 is a second user group that is estimated as a user who rides on the same moving means among the first user group to be estimated by the first estimation process, and is more effective than the first user group. A small second user group is estimated.

  For example, the estimation unit 132 performs the second estimation process. For example, the estimation unit 132 is a passenger user group estimated to be a user who rides on the same moving means in the second user group by the second estimation process, and has a passenger user group smaller than the second user group. By estimating, the user who rides in the same moving means is estimated.

  For example, the estimation unit 132 estimates the riding user group based on the first estimation process that estimates the second user group based on the first accuracy information and the second accuracy information that is higher than the first accuracy. By the second estimation process, a user who rides on the same moving means is estimated.

  In the example of FIG. 1, the estimation unit 132 sets a predetermined user group (terminal device 10 (TM1) to terminal device 10 (TMn) in FIG. 1) as an estimation target, and performs the first estimation process and the second estimation process. The user who rides in the same moving means is estimated by the two-stage process. For example, the estimation unit 132 estimates n terminal devices 10 of the terminal device 10 (TM1) to the terminal device 10 (TMn) as a first user group, and estimates a second user group that narrows down the first user group. A user who rides on the same moving means is estimated from the second user group.

  In the example of FIG. 1, the estimation unit 132 estimates the second user group by the first estimation process. For example, the estimating apparatus 100 uses the n terminal devices 10 from the terminal device 10 (TM1) to the terminal device 10 (TMn) from which the log information is acquired as the first user group TG11 (see FIG. 1), as the second user group. Is estimated. For example, the estimation unit 132 estimates the position of each terminal device 10 at date and time DC. For example, the estimation unit 132 estimates the terminal device 10 located in a predetermined area at the date and time DC as the second user group. For example, the estimation unit 132 estimates the terminal device 10 located in the area AR11 at the date and time DC as the second user group.

  In the example of FIG. 1, the estimation unit 132 estimates the terminal device 10 located in the area AR11 in the date and time DC from the first user group TG11 as the second user group TG12. For example, the estimation unit 132 determines from the first user group TG11 to the second user group TG12 (including the terminal device 10 (TM1), the terminal device 10 (TM2), the terminal device 10 (TM4), the terminal device 10 (TM338), and the like. (See FIG. 1).

  In the example of FIG. 1, the estimation unit 132 estimates the movement process for the terminal devices 10 included in the second user group TG12. For example, as shown in the movement process list RT11 in FIG. 1, the estimation unit 132 determines the movement process of each terminal apparatus 10 based on the position information of the terminal apparatus 10 at three points of time and date DA, date and time DB, and date and time DC. presume.

  For example, as shown in the movement process list RT11 in FIG. 1, the estimation unit 132 determines that the movement process of the terminal device 10 (TM1) includes position information LC1 at date DA, position information LC2 at date DB, and position information at date DC. Estimated to be LC3. For example, the estimating unit 132 estimates that the movement process of the terminal device 10 (TM2) is the position information LC1 at the date and time DA, the position information LC2 at the date and time DB, and the position information LC3 at the date and time DC. For example, the estimating unit 132 estimates that the movement process of the terminal device 10 (TM4) is the position information LC1 at the date and time DA, the position information LC40 at the date and time DB, and the position information LC3 at the date and time DC. For example, the estimating unit 132 estimates that the movement process of the terminal device 10 (TM338) is the position information LC1 at the date and time DA, the position information LC2 at the date and time DB, and the position information LC3 at the date and time DC.

  In the example of FIG. 1, the estimation part 132 estimates the user who rides among the terminal devices 10 included in the second user group TG12. For example, as shown in the passenger user group TG13-1, the estimation unit 132 is a user who rides the three terminal devices 10 of the terminal device 10 (TM1), the terminal device 10 (TM2), and the terminal device 10 (TM338). Estimate as For example, the estimation unit 132 selects a user who rides on the basis of the association between the user and the terminal device 10 stored in the user group TG 13-1 (see FIG. 1) and the user information storage unit 121 (see FIG. 1). presume. For example, as shown in the result information RS11 (see FIG. 1), the estimation unit 132 estimates that the three users, the user U1, the user U2, and the user U338, are users who ride in the same moving means (for example, the car C11). To do.

(Transmitter 133)
The transmission unit 133 distributes various types of information to an external information processing apparatus. For example, the transmission unit 133 distributes various information to the terminal device 10. Moreover, the transmission part 133 may transmit the information regarding a passenger with an external information processing apparatus. Moreover, the transmission part 133 may transmit the information regarding a passenger on an external information processing apparatus which provides a predetermined navigation service.

[3. (Estimation process flow)
Next, the procedure of the estimation process by the estimation system 1 according to the embodiment will be described with reference to FIG. FIG. 6 is a flowchart illustrating an example of the estimation process according to the embodiment. Specifically, FIG. 6 is a flowchart illustrating an example of an estimation process using a technique that does not determine the number of clusters (number of combination information).

  As illustrated in FIG. 6, the estimation device 100 acquires log information from a terminal device used by the user (step S101). For example, the estimation device 100 acquires sensor information including user position information from the terminal device 10 used by each user. In the example of FIG. 1, the acquisition unit 131 acquires log information from n terminal devices 10 from the terminal device 10 (TM1) to the terminal device 10 (TMn).

  Moreover, the estimation apparatus 100 performs a first estimation process based on the log information acquired from each terminal apparatus 10 (step S102). For example, the estimating apparatus 100 estimates the second user group from the first user group. In the example of FIG. 1, the estimation apparatus 100 estimates the second user group TG12 from the first user group TG11.

  Thereafter, the estimation device 100 performs a second estimation process (step S103). For example, the estimating apparatus 100 estimates a fellow passenger from the second user group. In the example of FIG. 1, the estimating apparatus 100 estimates the passenger user group TG13-1 from the second user group TG12.

[4. Use of wireless communication information)
In the example described above, the case of estimating a fellow passenger using sensor information such as position information acquired from the user's terminal device 10 has been mainly described. However, the estimation apparatus 100 can be used for estimation of a fellow passenger. Any information may be used. This point will be described with reference to FIG. FIG. 7 is a diagram illustrating an example of estimation based on wireless communication information according to the embodiment. In the example illustrated in FIG. 7, grouping of terminal devices 10 using information regarding wireless communication by Bluetooth (registered trademark) between the terminal devices 10 is illustrated. In the example illustrated in FIG. 7, symbols in “()” that follow the code “10” of each terminal device indicate identification information of the terminal device. For example, the terminal device 10 to which the reference numeral “10 (TM101)” is attached in FIG. 7 indicates that the terminal device 10 is identified by the terminal ID “TM101”. Hereinafter, the terminal device 10 identified by the terminal ID “TM101” may be described as the terminal device 10 (TM101). Similarly, for the other terminal devices 10, the terminal device 10 identified by the terminal ID may be described as the terminal device 10 (“terminal ID”).

  In the example illustrated in FIG. 7, the estimation apparatus 100 estimates two groups GP11 and GP12 according to the connection status of each terminal apparatus 10. In the example illustrated in FIG. 7, only the terminal devices 10 included in the two groups GP11 and GP12 are illustrated, but it is assumed that there are a large number of terminal devices 10 that are not included in the two groups GP11 and GP12.

  In the example illustrated in FIG. 7, the terminal device 10 (TM101) and the terminal device 10 (TM102) are connected via Bluetooth as indicated by a connection line CN11-1. In the example shown in FIG. 7, the terminal device 10 (TM101) and the terminal device 10 (TM103) are connected by Bluetooth as indicated by a connection line CN11-2. In the example shown in FIG. 7, the terminal device 10 (TM102) and the terminal device 10 (TM105) are connected via Bluetooth as indicated by the connection line CN11-3. In the example shown in FIG. 7, the terminal device 10 (TM102) and the terminal device 10 (TM104) are connected via Bluetooth as indicated by a connection line CN11-4. Therefore, the estimation device 100 includes five terminal devices 10 (TM101), a terminal device 10 (TM102), a terminal device 10 (TM103), a terminal device 10 (TM104), and a terminal device 10 (TM105) as one group GP11. presume. Note that the estimation apparatus 100 may estimate the group G11 as the second user group by using the wireless communication information in the first estimation process, or use the wireless communication information in the second estimation process. As an example, the group G11 may be estimated.

  In the example shown in FIG. 7, the terminal device 10 (TM201) and the terminal device 10 (TM202) are connected by Bluetooth as indicated by a connection line CN11-5. In the example shown in FIG. 7, the terminal device 10 (TM201) and the terminal device 10 (TM203) are connected by Bluetooth as indicated by a connection line CN11-6. In the example shown in FIG. 7, the terminal device 10 (TM202) and the terminal device 10 (TM203) are connected by Bluetooth as indicated by the connection line CN11-7. Therefore, the estimation device 100 estimates the three terminal devices 10 (TM201), the terminal device 10 (TM202), and the terminal device 10 (TM203) as one group GP12. Note that the estimation apparatus 100 may estimate the group G12 as the second user group by using the wireless communication information in the first estimation process, or use the wireless communication information in the second estimation process. The group G12 may be estimated as

  Note that the above is an example, and the wireless communication information used by the estimation apparatus 100 is not limited to Bluetooth information, and is information related to various wireless communication such as Wi-Fi as long as it can be used for the estimation of the passenger. Also good.

[5. effect〕
As described above, the estimation apparatus 100 according to the embodiment includes the acquisition unit 131 and the estimation unit 132. The acquisition unit 131 acquires sensor information from each terminal device 10 used by each user. Moreover, the estimation part 132 estimates the user who rides in the same moving means based on the sensor information acquired from each terminal device 10.

  Thereby, the estimation apparatus 100 which concerns on embodiment can estimate the user who rides in the same moving means appropriately based on the sensor information acquired from each terminal device 10. FIG.

  In the estimation device 100 according to the embodiment, the acquisition unit 131 acquires sensor information including position information regarding each terminal device 10.

  Thereby, the estimation apparatus 100 which concerns on embodiment can estimate the user who rides in the same moving means appropriately based on the positional information acquired from each terminal device 10. FIG.

  Moreover, in the estimation apparatus 100 according to the embodiment, the estimation unit 132 estimates a user who rides on the same moving unit based on a change in position information regarding each terminal apparatus 10 in a predetermined period.

  Thereby, the estimation apparatus 100 which concerns on embodiment can estimate the user who rides in the same moving means appropriately based on the change of the positional information regarding each terminal device 10 in a predetermined period.

  Moreover, in the estimation apparatus 100 according to the embodiment, the estimation unit 132 estimates a user who rides on the same moving unit based on the similarity of changes in position information regarding each terminal apparatus 10 in a predetermined period.

  Thereby, the estimation apparatus 100 which concerns on embodiment can estimate the user who rides in the same moving means appropriately based on the similarity of the change of the positional information regarding each terminal device 10 in a predetermined period.

  In the estimation device 100 according to the embodiment, the acquisition unit 131 acquires sensor information including voice information detected by each terminal device 10.

  Thereby, the estimation apparatus 100 which concerns on embodiment can estimate the user who rides in the same moving means appropriately based on the sensor information containing the audio | voice information detected by each terminal device 10. FIG.

  Further, in the estimation device 100 according to the embodiment, the acquisition unit 131 estimates a user who rides on the same moving unit based on the similarity of the voice information detected by each terminal device 10 in a predetermined period.

  Thereby, the estimation apparatus 100 which concerns on embodiment can estimate the user who rides in the same moving means appropriately based on the similarity of the audio | voice information detected by each terminal device 10 in a predetermined period. .

  Moreover, in the estimation apparatus 100 according to the embodiment, the estimation unit 132 estimates a user who rides on the same moving unit based on the content of the voice information detected by each terminal apparatus 10 in a predetermined period.

  Thereby, the estimation apparatus 100 which concerns on embodiment can estimate the user who rides in the same moving means appropriately based on the content of the audio | voice information detected by each terminal device 10 in a predetermined period.

  Further, in the estimation device 100 according to the embodiment, the acquisition unit 131 includes at least one of acceleration information, information on vibration, information on temperature, information on air pressure, information on air pressure, information on humidity, and information on illuminance detected by each terminal device 10. The sensor information including is acquired.

  Thereby, the estimation apparatus 100 according to the embodiment includes sensor information including at least one of acceleration information detected by each terminal device 10, information on vibration, information on temperature, information on atmospheric pressure, information on humidity, information on humidity, and information on illuminance. By acquiring, it is possible to appropriately estimate the users who ride on the same moving means.

  In the estimation device 100 according to the embodiment, the acquisition unit 131 acquires information related to wireless communication from each terminal device 10. The estimation unit 132 estimates a user who rides on the same moving means based on information related to wireless communication acquired from each terminal device 10.

  Thereby, the estimation apparatus 100 which concerns on embodiment can estimate the user who rides in the same moving means appropriately based on the information regarding the radio | wireless communication acquired from each terminal device 10. FIG.

  In the estimation apparatus 100 according to the embodiment, the acquisition unit 131 acquires history information on a predetermined network regarding each user. The estimation unit 132 estimates users who ride in the same moving means based on history information on a predetermined network regarding each user.

  Thereby, the estimation apparatus 100 which concerns on embodiment can estimate the user who rides in the same moving means appropriately based on the historical information on the predetermined network regarding each user.

  Moreover, in the estimation apparatus 100 according to the embodiment, the estimation unit 132 is a second user group that is estimated to be a user who rides on the same moving means among the first user group to be estimated, and the first user A first estimation process for estimating a second user group that is smaller than the group, and a shared user group that is estimated to be a user who rides in the same moving means among the second user group, than the second user group A user who rides in the same moving means is estimated by the second estimation process for estimating a small number of passenger users.

  Accordingly, the estimation apparatus 100 according to the embodiment includes a first estimation process for estimating a second user group estimated as a user who rides on the same moving unit among the first user group to be estimated, and a second estimation process. The user who rides on the same moving means can be appropriately estimated by the second estimation process for estimating the user who is on the same moving means as the user who is on the same moving means.

  Moreover, in the estimation apparatus 100 according to the embodiment, the estimation unit 132 performs first estimation processing for estimating the second user group based on the first accuracy information, and second accuracy information that is higher in accuracy than the first accuracy. And the second estimation process for estimating the same-passenger user group, the users who are traveling in the same moving means are estimated.

  Thereby, the estimation apparatus 100 according to the embodiment is based on the first estimation process that estimates the second user group based on the first accuracy information and the second accuracy information that is higher than the first accuracy. By estimating the users who ride in the same moving means by the second estimation process for estimating the user group, the users who ride in the same moving means can be appropriately estimated.

[6. Hardware configuration)
The estimation apparatus 100 according to the embodiment described above is realized by a computer 1000 configured as shown in FIG. 8, for example. FIG. 8 is a hardware configuration diagram illustrating an example of a computer that realizes the function of the estimation device. The computer 1000 includes a CPU 1100, RAM 1200, ROM 1300, HDD 1400, communication interface (I / F) 1500, input / output interface (I / F) 1600, and media interface (I / F) 1700.

  The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 and controls each unit. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, a program depending on the hardware of the computer 1000, and the like.

  The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. The communication interface 1500 receives data from other devices via the network N and sends the data to the CPU 1100, and transmits data estimated by the CPU 1100 to other devices via the network N.

  The CPU 1100 controls an output device such as a display and a printer and an input device such as a keyboard and a mouse via the input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. In addition, the CPU 1100 outputs the estimated data to the output device via the input / output interface 1600.

  The media interface 1700 reads a program or data stored in the recording medium 1800 and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads such a program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. Etc.

  For example, when the computer 1000 functions as the estimation device 100 according to the embodiment, the CPU 1100 of the computer 1000 implements the function of the control unit 130 by executing a program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them. However, as another example, these programs may be acquired from other devices via the network N.

  As described above, some of the embodiments and modifications of the present application have been described in detail with reference to the drawings. However, these are merely examples, and various aspects can be made based on the knowledge of those skilled in the art including the aspects described in the disclosure line of the invention. It is possible to carry out the present invention in other forms that have been modified and improved.

[7. Others]
In addition, among the processes described in the above-described embodiments and modifications, all or a part of the processes described as being automatically performed can be manually performed, or are described as being performed manually. All or part of the processing can be automatically performed by a known method. In addition, the processing procedures, specific names, and information including various data and parameters shown in the document and drawings can be arbitrarily changed unless otherwise specified. For example, the various types of information illustrated in each drawing is not limited to the illustrated information.

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured.

  In addition, the above-described embodiments and modifications can be combined as appropriate within a range that does not contradict processing contents.

  In addition, the “section (module, unit)” described above can be read as “means” or “circuit”. For example, the acquisition unit can be read as acquisition means or an acquisition circuit.

DESCRIPTION OF SYMBOLS 1 Estimation system 100 Estimation apparatus 121 User information storage part 122 Location information storage part 123 Terminal related information storage part 130 Control part 131 Acquisition part 132 Estimation part 133 Transmission part 10 Terminal apparatus N Network

Claims (14)

An acquisition unit that acquires sensor information from each terminal device used by each user;
Based on the sensor information acquired from each terminal device, an estimation unit that estimates a user who rides on the same moving unit;
An estimation device comprising: The acquisition unit
The estimation apparatus according to claim 1, wherein the sensor information including position information regarding each terminal apparatus is acquired. The estimation unit includes
The estimation apparatus according to claim 2, wherein a user who rides in the same moving unit is estimated based on a change in position information regarding each terminal apparatus during a predetermined period. The estimation unit includes
The estimation apparatus according to claim 3, wherein a user who rides on the same moving unit is estimated based on similarity of changes in position information regarding each terminal apparatus in a predetermined period. The acquisition unit
The estimation apparatus according to claim 1, wherein the sensor information including voice information detected by each terminal device is acquired. The estimation unit includes
The estimation apparatus according to claim 5, wherein a user who rides on the same moving means is estimated based on similarity of voice information detected by each terminal apparatus during a predetermined period. The estimation unit includes
The estimation device according to claim 6, wherein a user who rides on the same moving means is estimated based on the content of the voice information detected by each of the terminal devices in a predetermined period. The acquisition unit
The sensor information including at least one of acceleration information detected by each terminal device, information about vibration, information about temperature, information about atmospheric pressure, information about humidity, and information about illuminance is acquired. The estimation apparatus of any one of -7. The acquisition unit
Obtaining information related to wireless communication from each terminal device,
The estimation unit includes
The estimation device according to any one of claims 1 to 8, wherein a user who rides on the same moving unit is estimated based on information on the wireless communication acquired from each terminal device. The acquisition unit
Obtaining historical information on a given network for each user;
The estimation unit includes
The estimation device according to any one of claims 1 to 9, wherein a user who rides on the same moving means is estimated based on history information on a predetermined network related to each user. The estimation unit includes
A first estimation process for estimating a second user group that is estimated to be a user who rides on the same moving means among the first user group to be estimated, and that is less than the first user group. And a second estimation process for estimating a shared user group that is estimated to be a user who rides in the same moving means among the second user group, and that estimates fewer shared user groups than the second user group. The estimation apparatus according to any one of claims 1 to 10, wherein a user who rides in the same moving means is estimated. The estimation unit includes
The first estimation process for estimating the second user group based on information of the first accuracy, and the second for estimating the riding user group based on information of the second accuracy that is higher than the first accuracy. The estimation apparatus according to claim 11, wherein a user who rides on the same moving unit is estimated by the estimation process. An estimation method performed by a computer,
An acquisition step of acquiring sensor information from each terminal device used by each user;
Based on the sensor information acquired from each terminal device, an estimation step for estimating a user who rides on the same moving means;
The estimation method characterized by including. An acquisition procedure for acquiring sensor information from each terminal device used by each user;
Based on the sensor information acquired from each terminal device, an estimation procedure for estimating a user who rides on the same moving means;
An estimation program for causing a computer to execute.

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