JP4981877B2 - Arrival time prediction apparatus and arrival time prediction method - Google Patents

Arrival time prediction apparatus and arrival time prediction method Download PDF

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JP4981877B2
JP4981877B2 JP2009265267A JP2009265267A JP4981877B2 JP 4981877 B2 JP4981877 B2 JP 4981877B2 JP 2009265267 A JP2009265267 A JP 2009265267A JP 2009265267 A JP2009265267 A JP 2009265267A JP 4981877 B2 JP4981877 B2 JP 4981877B2
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arrival time
information
position information
destination
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JP2011107091A (en
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哲夫 住谷
直治 山田
佳徳 礒田
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株式会社エヌ・ティ・ティ・ドコモ
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Description

  The present invention relates to an arrival time prediction apparatus and an arrival time prediction method.

  In recent years, with the improvement of the accuracy of GPS receivers that acquire the location information of mobile communication terminals, the improvement of the performance of communication devices such as mobile communication terminals, and the improvement of the communication environment, the arrival time of the destination (from the current position to the target) A service for notifying the user of the required time to the ground) is provided. For example, in the estimated arrival time notification service described in Patent Document 1, when a user of a mobile communication terminal moves to a destination using public transportation, the user of the mobile communication terminal inputs a destination, a departure time, and the like. In response to the request, the server predicts the estimated arrival time at the destination based on the route information, the timetable information, and the map information, and notifies the mobile communication terminal of the predicted arrival time.

  For example, in the method described in Patent Document 2, a speed of a user of one mobile communication terminal transmits data indicating a destination of another mobile communication terminal to a Web server and is obtained from position information of the other mobile communication terminal. Based on the vector and the map data, a moving method of the user of the other mobile communication terminal is obtained, and the estimated arrival time of the destination of the other mobile communication terminal is estimated using this moving method.

JP 2008-139033 A JP 2007-30409 A

  However, in the above-described conventional method, the user of the mobile communication terminal needs to input the destination when requesting the estimated arrival time of the destination. The destination is appropriately changed according to the behavior of the user of the mobile communication terminal. However, the destination may be a place where people come and go every day such as home, office, or school. In this case, it is troublesome for the user to input the same destination every time, and there is a problem that it takes time and effort.

  The present invention has been made to solve the above-described problems, and an object thereof is to provide an arrival time prediction apparatus and an arrival time prediction method capable of improving convenience.

  In order to solve the above-described problem, an arrival time prediction apparatus according to the present invention is an arrival time prediction apparatus that estimates an estimated arrival time at a destination of a user who owns a mobile communication terminal, and obtains position information of the mobile communication terminal. Definition based on position information acquisition means to be acquired, user information acquisition means for acquiring user information related to user behavior, position information acquired by the position information acquisition means, and user information acquired by the user information acquisition means A behavior model storage means for storing the behavior model indicating the transition order of the user's behavior, and a behavior estimation means for estimating the future behavior of the user based on the position information, the user information, the user behavior history, and the behavior model And destination setting means for automatically setting the destination according to the user's future behavior estimated by the action estimation means, and setting by the destination setting means Characterized in that it comprises an estimated time of arrival estimation means for estimating a destination arrival time of that was.

  In this arrival time prediction device, the user's future behavior is estimated based on the position information, user information, the user's behavior history and behavior model, and the user's destination is automatically set from the estimated future behavior. Estimate the estimated arrival time of the destination. Therefore, even if the user of the mobile communication terminal does not input the destination, the destination is automatically set from the user's action and the estimated arrival time is estimated, so that the user does not have to input the destination every time. This saves the user from having to input the destination. As a result, convenience can be improved.

  The user information includes area information indicating an area where the user frequently appears, life type information indicating the user's occupation, working time information indicating the user's working time, and bedtime information indicating the user's sleeping time. The behavior model is preferably defined based on at least one of area information, life type information, working time information, and bedtime information. Thus, by using at least one of area information, life type information, working time information, and bedtime information as user information, an action model that is optimal for the user can be defined. Thereby, since the estimation accuracy of future actions is improved, the accuracy of the destination can be improved.

  Further, a traffic information storage means for storing traffic information including route information of transportation and timetable information of the route, position information acquired by the position information acquisition means, and route information stored in the traffic information storage means Based on the position information, the timetable information and the user's moving method, the estimated arrival time is estimated based on the position information, the timetable information, and the user's moving method. It is preferable. In this case, since the user's moving method is taken into account, for example, the walking time to the surrounding station is prevented from being added to the estimated arrival time even though the user is already on the train. Therefore, it is possible to improve the estimation accuracy of the estimated arrival time.

  Further, it is preferable that the estimated arrival time estimation means obtains a plurality of travel routes to the destination based on the route information and estimates the estimated arrival time of the destination for each travel route. In this case, since the estimated arrival time of the destination by each of the plurality of movement routes is estimated, the user can select the movement route according to the estimated arrival time.

  The estimated arrival time estimation means periodically estimates the estimated arrival time, and if there is a change of a predetermined time or more between the estimated arrival time estimated earlier and the estimated arrival time estimated later, The estimated arrival time is preferably the estimated arrival time. In this case, for example, even when a delay occurs in the train, the estimated arrival time is updated accordingly, so that the user can be notified of the estimated arrival time.

  Moreover, it is preferable to further include area setting means for setting a place where the user stayed for the longest time in a predetermined time zone as an area where the user frequently appears based on the position information acquired by the position information acquisition means. In this case, since it is not necessary for the user to input information regarding the area in advance, the user's trouble can be further reduced.

  The present invention can be described as an invention of an arrival time prediction apparatus as described above, and can also be described as an invention of an estimated arrival time prediction method as follows. This is substantially the same invention only in different categories, and has the same operations and effects.

  That is, the arrival time estimation method according to the present invention is an arrival time prediction method for estimating the arrival time at the destination of the user possessing the mobile communication terminal, and acquires the location information of the mobile communication terminal. And a user information acquisition step that acquires user information related to the user's behavior, a user behavior defined based on the location information acquired in the location information acquisition step, and the user information acquired in the user information acquisition step. A behavior model storing step for storing a behavior model indicating a transition order of the user, a behavior estimation step for estimating a user's future behavior based on position information, user information, a user behavior history and a behavior model, and a behavior estimation step. A destination setting step for automatically setting a destination according to the estimated future behavior of the user, and a destination Characterized in that it comprises an estimated time of arrival estimation step of estimating the set arrival time of the destination in the setting step.

  According to the present invention, it is possible to estimate the estimated arrival time without inputting a destination, so that it is possible to save the operation and improve convenience.

It is a figure which shows the functional block of the arrival time prediction apparatus which concerns on one Embodiment of this invention. It is a figure which shows the hardware constitutions of an arrival time prediction apparatus. It is a figure which shows an example of the positional information stored in the positional information storage part. It is a figure which shows an example of the user information stored in the user information storage part. It is a figure which shows an example of the behavior model stored in the behavior model storage part. It is a figure which shows an example of the path | route information stored in the path | route information storage part. It is a flowchart which shows operation | movement of an arrival time prediction apparatus. It is a flowchart which shows operation | movement of an arrival time estimation part. It is a flowchart which shows operation | movement of an arrival time estimation part. It is a figure for demonstrating operation | movement of the arrival time estimation part.

  DESCRIPTION OF EMBODIMENTS Hereinafter, preferred embodiments of an arrival time prediction device and an expected arrival time prediction method according to the present invention will be described in detail with reference to the drawings.

  FIG. 1 is a diagram showing functional blocks of an arrival time prediction apparatus according to an embodiment of the present invention. The arrival time predicting apparatus 1 shown in FIG. 1 is a destination arrival scheduled time (from the current position to the destination) in response to a request from a user having a mobile communication terminal such as a mobile phone or a PDA (Personal Digital Assistant). It is a device for estimating the required time. The arrival time prediction device 1 is a server device installed in a mobile communication network, for example, and is managed by a service provider that provides a service. In addition, the arrival time prediction apparatus 1 may be comprised by one server apparatus, and may be comprised by the some server apparatus.

  FIG. 2 is a diagram illustrating a hardware configuration of the arrival time prediction apparatus. As shown in FIG. 2, the arrival time prediction device 1 includes hardware such as a CPU 11, a RAM 12 and a ROM 13 as main storage devices, a communication module 14 as a data transmission / reception device such as a network card, and an auxiliary storage device 15 such as a hard disk. It is configured as a computer equipped. When these components operate, the functions described later of the arrival time prediction device 1 are exhibited.

  Next, functions of the arrival time prediction device 1 will be described. As shown in FIG. 1, the arrival time prediction apparatus 1 includes a position information acquisition unit 101, a position information storage unit 102, a user information acquisition unit 103, a user information storage unit 104, an area setting unit 105, an action model. A storage unit 106, a behavior estimation unit 107, a route information storage unit 108, a timetable information storage unit 109, a movement method estimation unit 110, a destination setting unit 111, and a scheduled arrival time estimation unit 112 are provided. Yes. Although not shown, the arrival time prediction device 1 further includes a function for communicating with the mobile communication terminal.

  The position information acquisition unit 101 is a part that acquires position information of the mobile communication terminal. The position information acquisition unit 101 periodically acquires position information of a mobile communication terminal acquired by positioning using a GPS (Global Positioning System) or a base station (not shown). The position information includes latitude, longitude, and positioning error information. The location information acquisition unit 101 outputs the acquired location information of the mobile communication terminal to the location information storage unit 102 and the user information storage unit 104. Note that positioning of a mobile communication terminal using GPS or a base station is an existing technology, and detailed description thereof is omitted.

  The position information storage unit 102 is a part that stores the position information of the mobile communication terminal acquired by the position information acquisition unit 101. When the position information storage unit 102 receives the position information output from the position information acquisition unit 101, the position information storage unit 102 stores the position information for each user. FIG. 3 is a diagram illustrating an example of position information stored in the position information storage unit. As shown in the figure, the position information table includes an “identifier” that is a unique (non-overlapping) character string that identifies a mobile communication terminal, and a “positioning time” that indicates the time at which the position information was acquired. The “position information” obtained by positioning is stored for each user. The position information in the position information storage unit 102 is updated each time position information is output from the position information acquisition unit 101.

  The user information acquisition unit 103 is a part that acquires information about the user of the mobile communication terminal. The user information acquisition unit 103 receives and acquires user information input at the mobile communication terminal by the user of the mobile communication terminal, for example. User information input by the user includes four items of “sleeping time (sleeping time information)”, “working time (working time information)”, “life type (life type information)”, and “area (area information)”. The “area” is divided into items of “area name” and “area attribute”. “Life type” indicates a user's occupation and the like, for example, a student, a company employee, or the like. The “area name” is an area where the user frequently appears. For example, a home or a company is freely set by the user. The “area attribute” is set by the user selecting from preset items. The “area attribute” includes, for example, a company, a house, a school, and a home. The user information acquisition unit 103 outputs the acquired user information to the user information storage unit 104.

  The user information storage unit 104 is a part that stores user information of the mobile communication terminal. Upon receiving the user information output from the user information acquisition unit 103, the user information storage unit 104 stores this user information for each user. FIG. 4 is a diagram illustrating an example of user information stored in the user information storage unit. As shown in the figure, in the user information table, an “identifier” that can be linked to the identifier of the position information, the “sleeping time” of the user, the “working time” indicating the user's action time, and the user's life The “life type” indicating the type (job type) and the “area” indicating the user's life area are stored for each user. “Area” is divided into “area name”, “area attribute”, and “position information”, and “position information” is position information output from the position information acquisition unit 101, and includes latitude, Includes longitude and positioning error information. Although details will be described later, when the user information storage unit 104 receives the user information (“area”) output from the area setting unit 105, the user information storage unit 104 stores the user information in association with the corresponding user.

The area setting unit 105 is a part for setting an “area (significant area)” in the user information. The area setting unit 105 automatically sets an area when “area” is not set in association with the user in the table of the user information storage unit 104. Specifically, the area setting unit 105 refers to the user information storage unit 104 and extracts users for which “area” is not set. Then, the area setting unit 105 has the longest stay time in a predetermined time zone in which the user sets the area (for example, home; 2:00 to 6:00, company or school; 10:00 to 17:00). The place (position indicated by the position information) is set as an “area” in the user information. The determination as to whether or not the user is staying is made by a plurality of pieces of position information ((latitude 1, longitude 1, positioning error 1), (latitude 2, longitude 2, positioning error 2) acquired by the position information acquiring unit 101,... , (Latitude n, longitude n, positioning error n)), the distance d ij between any two points (latitude i, longitude i) and (latitude j, longitude j) is “d ij <positioning”. This is performed depending on whether or not “error i + positioning error j” is satisfied. At this time, if there are a plurality of pieces of position information at the same time, the position information with the smallest positioning error is set as the “area”. The area setting unit 105 outputs the set area to the user information storage unit 104 as user information.

  The behavior model storage unit 106 is a part that stores a behavior model of the user of the mobile communication terminal. The behavior model is defined based on the position information stored in the position information storage unit 102 and the “sleeping time”, “working time”, and “area” stored in the user information storage unit 104. It shows the transition order of the behavior of the user of the mobile communication terminal. Specifically, in the behavior model storage unit 106, when the area is not registered in the registered contents of “life type” and “area” stored in the user information storage unit 104, a home or company / school is stored. A behavior model that is set based on the registered case or the case where the house and the company / school are registered is stored. FIG. 5 is a diagram illustrating an example of a behavior model stored in the behavior model storage unit, and illustrates a behavior model of a user of a mobile communication terminal on weekdays.

  As shown in FIG. 5, the behavior model table shows the transition order of the user's behavior. In the figure, “1” is the time zone between the wake-up time and the start time, “2” is the time zone between the start time and the work time, and “3” is the time between the end time and the bedtime. The band “4” indicates a time period between bedtime and wake-up time. In this behavior model, the existence area (house, company, etc.), commuting route / outside commuting route, and moving / staying are defined as conditions. These conditions and the behavior immediately before the user (START, home) , Where the company, office, going to work, going to school, going home, going out (weekdays), going out (detour), on a business trip) are set to be the user's actions.

  The behavior estimation unit 107 is a part that estimates the behavior of the user of the mobile communication terminal based on the behavior model stored in the behavior model storage unit 106. The behavior estimation unit 107 refers to the user information storage unit 104 and refers to the “sleeping time”, “working time”, and “area” of the target user, and refers to the location information storage unit 102 as “location information”. And extract. Then, the behavior estimation unit 107 estimates the presence area, the daily area, the commuting route, the moving / staying state based on the information.

  The existence area indicates in which area the mobile communication terminal exists in the area registered by the user or set by the area setting unit 105. The daily area indicates a user's frequent route (route frequently used by the user) estimated based on the location information acquired from the location information storage unit 102. The commuting route indicates a moving route when the starting point and the ending point of the moving are in a specific place (for example, a home or a company) in the daily life area. Then, the behavior estimation unit 107 refers to the “life type” and “area” of the user stored in the user information storage unit 104, and selects the behavior model stored in the behavior model storage unit 106 according to the registration status. The selected and estimated various information and the immediately preceding action (behavior history) are compared with the selected action model, and the user's future action (the next action that the user will perform) is estimated. Here, the immediately preceding action indicates the user's action estimated in the process before the user of the mobile communication terminal requests the estimated arrival time of the destination, and the information indicating the immediately preceding action is, for example, It is stored in an action history storage unit (not shown).

  A more specific process of the behavior model estimation unit 107 will be described with reference to FIG. In the behavior model estimation unit 107, for example, a user whose “sleeping time” is set to “22:00 to 7:00” and “working time” is set to “9: 0 to 18:00” in the user information storage unit 104 is displayed. When staying at home until “8:00” and when leaving the home at the next time (timing) “8:15”, from the behavior model “moving to other area, commuting route, company” ”And presume that“ working ”. Further, for example, when the user stays at home from “20:00” after returning home, and the user leaves the home at “20:15”, the behavior estimation unit 107 sets “other areas, It is determined that “commuting route, moving to company” and “outing (weekdays)”. The behavior estimation unit 107 outputs behavior information regarding the estimated future behavior of the user to the destination setting unit 111. When there is no previous action, the initial state (START (see FIG. 5)) is set.

  The route information storage unit 108 is a part that stores information (traffic information) about routes of transportation facilities. The route information storage unit 108 includes a “route ID” associated with train routes and road names, “route order” indicating station names and road intersections, and their order, and “position” indicating their positions. Information "is stored. In the route information storage unit 108, extraction can be performed with reference to corresponding route information based on the current position and the destination of the mobile communication terminal. FIG. 6 is a diagram illustrating an example of route information stored in the route information storage unit 108. As shown in the figure, in the route information table, “route ID”, “route order”, and “position information” are stored. The route information is updated with a change in the route of the transportation facility.

  The timetable information storage unit 109 stores timetable information (traffic information) of transportation facilities (such as trains). The timetable information storage unit 109 stores timetable information corresponding to, for example, a train route ID. In addition, timetable information is updated with timetable revisions, such as a train.

The movement method estimation part 110 is a part which estimates the movement method of the user of a mobile communication terminal. The movement estimation means 110 estimates whether or not the user of the mobile communication terminal is moving on a train. Specifically, in the movement method estimation unit 110, the initial state is set to “other than a train”, and the position information stored in the position information storage unit 102 and the route information stored in the route information storage unit 108 are set. Based on this, a minimum bounding rectangle (MBR) group that includes two adjacent points (two pieces of position information) in the movement path is created. Then, the movement method estimation unit 110 has a predetermined distance (TH d m) from the center coordinates of the position indicated by the position information with the highest positioning accuracy among the areas in which it is determined that the mobile communication terminal last stayed in the MBR group. When the moving route and the route that are separated from each other are spatially overlapped a predetermined number of times (TH n1 times) or more and the moving speed is a predetermined speed (TH v km / s) or more, the user's moving method is “train ". The movement method estimation unit 110 stays in a predetermined area for a predetermined time (TH m h) or when the user's movement method is on a “train”, or the movement route And the route do not overlap spatially for a predetermined number of times (TH n2 times) or more, it is estimated that the user's moving method is “other than train”. The movement method estimation unit 110 outputs movement method information indicating whether or not the user's movement method is a train to the estimated arrival time estimation unit 112.

  The destination setting unit 111 is a part that sets the user's destination based on the user's future behavior estimated by the behavior estimation unit 107. When the destination setting unit 111 receives the behavior information output from the behavior estimation unit 107, the destination setting unit 111 sets a destination based on the user's behavior indicated in the behavior information. Specifically, the destination setting unit 111 sets the destination to “home” when the user's behavior estimated by the behavior estimating unit 107 corresponds to “being home”, for example. If it falls under “commuting”, the destination is set to “company”. As described above, the destination setting unit 111 automatically sets a destination associated with the user's action. The destination setting unit 111 outputs destination information indicating the set destination to the estimated arrival time estimation unit 112. Note that the destination set by the destination setting unit 111 can be changed by a user operation.

  The estimated arrival time estimation unit 112 is a part that estimates the estimated arrival time of the destination set by the destination setting unit 111. The estimated arrival time estimation unit 112 includes position information stored in the position information storage unit 102, route information stored in the route information storage unit 108, time table information stored in the time table information storage unit 109, and movement method estimation. Based on the movement method information estimated by the unit 110 and the destination information set by the destination setting unit 111, the estimated arrival time of the destination is estimated. More specifically, the estimated arrival time estimation unit 112 acquires the location information stored in the location information storage unit 102, acquires the closest station to the current location based on the location information, Based on the destination information output from the setting unit 111, the nearest station near the destination is obtained, and a plurality of route information is obtained from the nearest station and the route information stored in the route information storage unit 108. To do. Then, the estimated arrival time estimation unit 112 extracts timetable information corresponding to the acquired route information with reference to the timetable information storage unit 109, and the movement method output from the timetable information and the movement method estimation unit 110 Estimated estimated arrival time based on information. The estimated arrival time estimated in this way is held for each route.

  Further, the estimated arrival time estimation unit 112 periodically refers to the location information storage unit 102 to acquire position information to estimate the estimated arrival time, and the estimated arrival time is initially estimated from the estimated arrival time. If the time is shifted by a predetermined time (Tmin) or more, the estimated arrival time estimated later is updated as the estimated arrival time. The estimated arrival time estimation unit 112 outputs estimated arrival time information indicating the estimated arrival time estimated as described above to a transmission unit (not shown). Thereafter, arrival time prediction information is transmitted from the arrival time prediction device 1 to the mobile communication terminal. Note that the estimated arrival time estimation unit 112 performs the above-described processing when a request for estimation of estimated arrival time is received by a user operation of the mobile communication terminal (not shown).

  Next, the operation (estimated arrival time prediction method) of the arrival time prediction apparatus 1 will be described. FIG. 7 is a flowchart showing the operation of the arrival time prediction apparatus.

  As shown in FIG. 7, the user information of the user of the mobile communication terminal is acquired in advance by the user information acquisition unit 103 (step S01), and the user information is stored in the user information storage unit 104. Further, the position information of the mobile communication terminal is periodically acquired by the position information acquisition unit 101 (step S02), and the position information is stored in the position information storage unit 102.

  Next, the area setting unit 105 determines whether or not an “area” is stored for each user in the user information storage unit 104 (step S03). If it is determined that “area” is stored, the process proceeds to step S05. On the other hand, if it is not determined that “area” is set, the area setting unit 105 sets an area (significant area) (step S04). The above processing is performed before receiving a request for the estimated arrival time of the destination from the user of the mobile communication terminal. The following processing is executed when a request for estimated arrival time at the destination is received from the user of the mobile communication terminal. More specifically, request information for requesting the estimated arrival time is transmitted from the mobile communication terminal by the user's operation, and the expected processing time prediction device 1 receives this request information, whereby the following processing is performed.

  In step S <b> 05, based on the user information stored in the behavior model storage unit 106 and the positional information stored in the positional information storage unit 102, the future behavior of the user is estimated by the behavior estimation unit 107. Further, based on the position information stored in the position information storage unit 102 and the route information stored in the route information storage unit 108, it is estimated by the movement method estimation unit 110 whether or not the user is moving by train. The moving method of the user is estimated (step S06).

  Subsequently, based on the user's behavior estimated by the behavior estimation unit 107, the destination of the mobile communication terminal is set by the destination setting means (step S07). Then, the estimated arrival time estimation process for estimating the estimated arrival time of the destination set by the destination setting unit 111 is performed by the estimated arrival time estimation unit 112 (step S08). This estimated arrival time estimation process will be described with reference to FIGS. 8 and 9 are flowcharts showing the operation of the estimated arrival time estimation unit, and FIG. 10 is a diagram for explaining the operation of the estimated arrival time estimation unit. In the following description, it is assumed that the destination is set to “home” by the destination setting unit 111 and the user is present near the stations St1 and St6 shown in FIG.

  As shown in FIG. 8, in the estimated arrival time estimation process, first, a linear distance between the current position and the destination (home) is calculated based on the position information stored in the position information storage unit 102. It is determined whether or not the straight line distance is greater than or equal to a predetermined distance nkm (for example, 1 km) (step S11). If it is determined that the straight line distance is greater than or equal to the predetermined distance nkm, the process proceeds to step S12. On the other hand, if it is not determined that the straight line distance is greater than or equal to the predetermined distance nkm, the process proceeds to step S13.

  In step S12, the travel time by the car from the current location to the destination is calculated and acquired. Specifically, the travel time of the automobile route is calculated from the travel distance calculated from the route information and the position information stored in the route information storage unit 108 and the speed of the automobile. Note that the traveling speed of the automobile is obtained from the time for moving the distance between two points in the position information.

  In step S13, the walking time by walking from the current location to the destination is calculated and acquired. Specifically, the walking time is calculated from the walking distance calculated from the route information and the position information stored in the route information storage unit 108 and the walking speed of the user. In addition, a user's walking speed is calculated | required from the time which moves the distance between two predetermined points in position information.

  Next, as shown in FIG. 9, it is determined based on the movement information whether or not the user's movement method is estimated to be a train in the movement method estimation unit 110 (whether or not the user is on the train) (steps). S14). When the movement method estimation unit 110 estimates that the user's movement method is a train, the process proceeds to step S15. On the other hand, if it is not estimated by the movement method estimation unit 110 that the user's movement method is a train, the process proceeds to step S17.

  In step S15, stations around the current location are acquired based on the position information and route information. Specifically, for example, the acquisition process is performed up to four times until a nearby station is acquired, and the station acquisition range is expanded by, for example, 500 m for each retry. Then, the required time from all the acquired stations to the nearest station of the home is estimated based on the timetable information (step S16). Specifically, as shown in FIG. 10, when the nearest stations around the current location are stations St1 and St6, all patterns from the nearest stations St5 and St9 at home (station St1 → station St5, station St1 → The required time of the station St9, the station St6 → the station St5, the station St6 → the station St9) is estimated.

  On the other hand, in step S17, stations around the current location are acquired based on the position information and route information. Specifically, for example, the acquisition process is performed up to four times until a nearby station is acquired, and the station acquisition range is expanded by, for example, 500 m for each retry. Then, the time required for walking or running from the current position is estimated based on the position information for all the acquired stations (step S18). Further, the required time from all the acquired stations to the nearest station of the home is estimated based on the timetable information (step S19). Specifically, in the same manner as in step S16, when the nearest stations around the current location are stations St1 and St6, all patterns up to the nearest stations St5 and St9 at home (station St1 → station St5, station St1 → The required time of the station St9, the station St6 → the station St5, the station St6 → the station St9) is estimated. Then, the required time from the current location to the station and the required time from the station to the nearest station of the home are added together (step S20).

  Next, a straight line distance between the nearest station and the home (destination) is calculated based on the position information stored in the position information storage unit 102, and the straight line distance is not less than a predetermined distance nkm (for example, 1 km). It is determined whether or not there is (step S21). If it is determined that the straight line distance is equal to or greater than the predetermined distance nkm, the process proceeds to step S22. On the other hand, if it is not determined that the straight line distance is greater than or equal to the predetermined distance nkm, the process proceeds to step S23.

  In step S22, the travel time from the current location to the destination is calculated and acquired, and the required time obtained in step S16 or step 20 is added to the travel time to estimate the estimated arrival time. Thereby, the estimated arrival time of the destination is estimated.

  On the other hand, in step S23, the walking time by walking from the current location to the destination is calculated and acquired, the required time obtained in step S16 or step 20 is added to the walking time, and the estimated arrival time is estimated. Thereby, the estimated arrival time of the destination is estimated.

  As described above, the arrival time estimation process is performed by the estimated arrival time estimation unit 112, and the estimated arrival time of the destination is estimated. This estimated arrival time is transmitted from the estimated arrival time prediction device 1 to the mobile communication terminal as expected arrival time information. In the mobile communication terminal that has received the estimated arrival time information, for example, the estimated arrival time is displayed on the display.

  As described above, in the arrival time prediction device 1, the position information acquired by the position information acquisition unit 101, the user information acquired by the user information acquisition unit 103, the user behavior history estimated by the behavior estimation unit 107, and Based on the behavior model stored in the behavior model storage unit 106, the behavior estimation unit 107 estimates the user's future behavior, and the destination setting unit 111 automatically sets the destination of the user from the estimated future behavior. Then, the estimated arrival time estimation unit 112 estimates the estimated arrival time of the destination. Therefore, even if the user of the mobile communication terminal does not input the destination, the destination is automatically set by the destination setting unit 111 from the user's action, and the estimated arrival time is estimated by the estimated arrival time estimating unit 112. The user does not have to input the destination one by one. This saves the user from having to input the destination. As a result, convenience can be improved.

  The user information storage unit 104 includes, as user information, an area where the user frequently appears, a life type indicating the user's occupation, a working time indicating the user's working time, and a bedtime indicating the user's sleeping time. The behavior model stored in the behavior model storage unit 106 is defined based on the area, life type, working hours, and bedtime. As described above, the behavior model of the user is defined based on the area, the life type, the working hours, and the sleeping hours, so that an optimum behavior model can be obtained. Thereby, since the estimation accuracy of future actions is improved, the accuracy of the destination can be improved.

  In addition, the estimated arrival time estimation unit 112 estimates the estimated arrival time at the destination in consideration of the user's movement method estimated by the movement method estimation unit 110. The walking time to the station is prevented from being added to the estimated arrival time. Therefore, it is possible to improve the estimation accuracy of the estimated arrival time.

  Further, the estimated arrival time estimation 112 acquires a plurality of travel routes to the destination based on the route information, and estimates the estimated arrival time of the destination for each travel route. In this case, since the estimated arrival times in the plurality of movement routes are estimated by the estimated arrival time estimation unit 112, the user can select a movement route according to the estimated arrival time.

  Further, the estimated arrival time estimation unit 112 periodically estimates the estimated arrival time, and if there is a change of a predetermined time or more between the estimated arrival time estimated earlier and the estimated arrival time later, Is the estimated arrival time. Thereby, for example, even when a delay occurs in the train, the estimated arrival time is updated accordingly, so that the user can be notified of the estimated arrival time.

  In addition, since the user has an area setting unit 105 that sets the place where the user stayed the longest in a predetermined time zone as an area where the user frequently appears, based on the position information acquired by the position information acquisition unit 101, the user can It is not necessary to input information about the area in advance, and the user's trouble can be further reduced.

  The present invention is not limited to the above embodiment. For example, in the above embodiment, the arrival time prediction device 1 is a server device, but this arrival time prediction device 1 may be provided in a mobile communication terminal. In this case, the arrival time prediction device 1 displays the estimated arrival time estimated by the estimated arrival time estimation unit 112 on a display unit such as a display. At this time, the display unit may display a service screen such as a message such as “Do you want to send the estimated arrival time by e-mail?” Together with the estimated arrival time.

  Moreover, in the said embodiment, although the arrival arrival time of the destination is estimated by the request | requirement from the user of a mobile communication terminal, according to the user's future action estimated by the action estimation part 107, estimated arrival time estimation The unit 112 may automatically estimate the estimated arrival time and notify the user of the estimated arrival time. Specifically, when the user behavior estimated by the behavior estimation unit 107 is “going home” or “commuting”, the destination setting unit 111 sets the destination to “home” or “company”. Then, the estimated arrival time estimation unit 112 automatically estimates the estimated arrival time of the destination and notifies the user.

  In the above embodiment, the route information storage unit 108 and the timetable information storage unit 109 are provided independently, but the route information and the timetable information may be stored in one storage unit. .

  The arrival time prediction device 1 can of course estimate the estimated arrival time of the destination input by the user of the mobile terminal.

  DESCRIPTION OF SYMBOLS 1 ... Arrival time prediction apparatus, 101 ... Position information acquisition part (position information acquisition means), 103 ... User information acquisition part (user information acquisition means), 105 ... Area setting part (area setting means), 106 ... Behavior model storage part (Behavior model storage means), 107 ... action estimation section (behavior estimation means), 108 ... route information storage section (traffic information storage means), 109 ... timetable information storage section (traffic information storage means), 110 ... movement method estimation Unit (movement method estimation means), 111... Destination setting section (destination setting means), 112... Estimated arrival time estimation section (estimated arrival time estimation means).

Claims (7)

  1. An arrival time prediction device for estimating an estimated arrival time of a user's destination having a mobile communication terminal,
    Position information acquisition means for acquiring position information of the mobile communication terminal;
    User information acquisition means for acquiring user information relating to the user's behavior;
    An action model that stores an action model that is defined based on the position information acquired by the position information acquisition means and the user information acquired by the user information acquisition means and indicates a transition order of the user's actions Storage means;
    Based on the position information, the user information, the user's behavior history and the behavior model, behavior estimation means for estimating the future behavior of the user;
    Destination setting means for automatically setting the destination according to the user's future behavior estimated by the behavior estimation means;
    Using the position information acquired by the position information acquisition means, a movement method estimation means for estimating the movement method of the user ;
    An arrival time prediction apparatus comprising: estimated arrival time estimation means for estimating an arrival arrival time of the destination set by the destination setting means based on the position information and the user's movement method .
  2. The user information includes area information indicating an area where the user frequently appears, life type information indicating the occupation of the user, working time information indicating the working time of the user, and sleeping time information indicating the sleeping time of the user. And
    The arrival time prediction apparatus according to claim 1, wherein the behavior model is defined based on at least one of the area information, the life type information, the working time information, and the sleeping time information.
  3. Traffic information storage means for storing traffic information including route information of the transportation facility and timetable information of the route ;
    The movement method estimation means includes
    Based on the position information and the route information, a minimum rectangle group including two adjacent position information in the movement route is created, and in the minimum rectangle group, it is determined that the mobile communication terminal last stayed Among the above, when the movement route and the route that are separated by a predetermined distance or more from the center coordinates of the position indicated by the position information with the highest positioning accuracy are spatially overlapped a predetermined number of times and the moving speed is a predetermined speed or more, Estimating that the user ’s travel method is a train,
    It is estimated that the user's moving method is other than the train when staying in a predetermined area for a predetermined time or more, or when the moving route and the route do not overlap spatially for a predetermined number of times or more. The arrival time prediction apparatus according to claim 1 or 2.
  4.   4. The estimated arrival time estimating means acquires a plurality of travel routes to the destination based on the route information, and estimates the estimated arrival time of the destination for each travel route. The arrival time prediction apparatus according to the item.
  5.   The estimated arrival time estimation means periodically estimates the estimated arrival time, and when there is a change of a predetermined time or more between the estimated arrival time estimated earlier and the estimated arrival time later, 5. The arrival time prediction apparatus according to claim 1, wherein the estimated arrival time is the estimated arrival time.
  6.   The apparatus further comprises area setting means for setting, as the area where the user frequently appears, the place where the user stayed the longest in a predetermined time zone based on the position information acquired by the position information acquisition means. The arrival time prediction apparatus as described in any one of Claims 2-5.
  7. An arrival time prediction method for estimating an estimated arrival time at a destination of a user possessing a mobile communication terminal,
    A location information acquisition step of acquiring location information of the mobile communication terminal;
    A user information acquisition step of acquiring user information related to the user's behavior;
    An action model that stores an action model that is defined based on the position information acquired in the position information acquisition step and the user information acquired in the user information acquisition step and indicates a transition order of the user's actions A storage step;
    Based on the position information, the user information, the action history of the user, and the action model, an action estimation step for estimating future actions of the user;
    A destination setting step for automatically setting the destination according to the future behavior of the user estimated in the behavior estimation step;
    A movement method estimation step of estimating a movement method of the user using the position information acquired in the position information acquisition step ;
    An arrival time prediction method, comprising: an estimated arrival time estimation step for estimating an estimated arrival time of the destination set in the destination setting step based on the position information and a moving method of the user .
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