JP2015121889A - Route information processing method, device, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To output route information which is flexibly concealed by taking balance between protection of privacy information on an individual and an amount of route information into consideration.SOLUTION: An acquisition part 12 acquires trip data TD in which positions on a route from a departure point of a user to a destination are represented by a time series of point data L. A user density showing the number of users of a route obtained by making a position included in a mesh a departure point or a destination is stored in a user density storage part 20 in each mesh obtained by dividing a prescribed area into a plurality of parts. A determination part 14 determines a position on the route separate from the departure point by a first distance as a start point in accordance with the user density of a mesh including a position on the route around the departure point. The determination part 14 also determines a position on the route separate from the destination by a second distance as an end point in accordance with the user density of a mesh including a position on the route around the destination. An output part 18 outputs a time series of point data from the start point on the route to the end point as concealed trip data.

Description

  The present invention relates to a route information processing method, a route information processing device, and a route information processing program.

  In recent years, terminals equipped with GPS (Global Positioning System) such as mobile phones and car navigation systems for automobiles have become widespread. Various companies that provide users with such GPS-equipped terminals can collect a large amount of terminal location information acquired by GPS. However, since the location information includes privacy information of the user who uses the terminal, sufficient care is required when handling location information collected by a company.

  On the other hand, in order to analyze position information collected in large quantities and obtain useful information, a large amount of computer resources are required. Moreover, there is a possibility that more useful data analysis can be performed by combining with location information possessed by other companies. Therefore, it is desirable that a large-scale resource of a third party such as cloud computing (cloud) can be used as a place for data analysis and collaboration. However, it is not easy to provide location information including user privacy information to third parties such as the cloud.

  As a technique for taking privacy information into account when handling position information, a technique has been proposed in which a user ID assigned to position information is deleted or replaced with a temporary ID. In this technology, the privacy of each user is kept confidential by preventing the correspondence between the location information and the user sending the location information from becoming clear.

  In addition, a technique for protecting personal information has been proposed in a navigation system that transmits position information of a mobile object. In this system, the vehicle-mounted device does not transmit position information acquired in an area where it is estimated that the user's home position is easily identified in response to a request for position information from the roadside device. Then, the in-vehicle device transmits the vehicle position information and the like acquired after the vehicle goes out of this region to the roadside device. Thereby, the position information of the vehicle is transmitted to the roadside machine while protecting the personal information.

  In addition, a technique for protecting behavior information to be kept secret has been proposed. In this technique, a behavior pattern is analyzed from the generated behavior information, and similarity determination between the analyzed behavior pattern and the protection target behavior history pattern is performed. A protection level of behavior information is selected based on the similarity determination result, and the behavior information is protected based on the selected protection level.

JP 2012-108932 A JP 2013-8232 A

Beresford, A.R. and F.Stajano, “Location Privacy in Pervasive Computing”, IEEE Pervasive Computing Magazine, 2003, p.46-55

  However, even if the user ID assigned to the position information is deleted or replaced with a temporary ID, there are the following problems. For example, if a person who knows the address of Mr. A's home looks at the route information that is time-series position information toward Mr. A's home, it can be estimated that the route information belongs to Mr. A. . In this case, when the time information at which the position information is acquired is included in the route information, the time when Mr. A returns home is estimated. Thus, there is privacy information leaked from the route information even if the user ID is deleted or replaced with a temporary ID.

  Further, in the technology for concealing position information in a predetermined area such as the vicinity of a home, the starting point or the arrival point of the route information is concealed by deleting a part of the position information included in the route information. However, depending on whether the departure place and the arrival place are densely populated areas or depopulated areas, how much position information is deleted depends on whether the departure place or the arrival place can be concealed. For example, in a densely populated area, a departure place or an arrival place can be concealed even with a small deletion amount. On the other hand, in a depopulated area, unless a lot of position information is deleted, the departure place or the arrival place cannot be concealed. If a smaller amount of deletion may be used and if more location information is deleted than necessary, the information amount of the remaining route information is reduced. On the other hand, when the amount of deletion of the position information is reduced so that the information amount of the route information is increased, the departure place or the arrival place may not be concealed.

  Further, when applying the conventional technology for protecting behavior information to be concealed to conceal route information, it is necessary to register the behavior information to be protected in advance. When handling a large amount of route information, it is difficult to predetermine information for concealing the starting point and the arriving point of all the route information.

  In one aspect, the objective is to output route information that is concealed flexibly in consideration of the balance between the protection of personal privacy information and the amount of route information.

  In one aspect, the route information in which the position on the route from the departure place to the arrival place of the user is represented by time-series position information is acquired. The disclosed technique is a small area obtained by dividing a predetermined area into a plurality of areas, and the first area is separated from the departure place by a first distance in accordance with the passing performance of the small area including the position on the route around the departure place. A position on the route is determined as a starting point. In addition, the disclosed technology determines a position on the route that is a second distance away from the arrival point as an end point in accordance with a passing performance of a small area including a position on the route around the arrival point. The disclosed technology outputs time-series position information from the start point to the end point on the route as the output route information.

  As one aspect, there is an effect that route information that is concealed flexibly can be output in consideration of the balance between protection of personal privacy information and the amount of route information.

It is a block diagram which shows schematic structure of the trip data processing apparatus which concerns on 1st Embodiment. It is a figure which shows an example of position data. It is a figure which shows an example of trip data. It is a conceptual diagram of user density data. It is a figure which shows an example of the deletion amount according to a user density. It is a figure which shows an example of the density level for calculating | requiring the deletion amount according to a user density. It is a figure which shows an example of confidential trip data. It is a block diagram which shows schematic structure of the computer which functions as a trip data processing apparatus which concerns on 1st Embodiment. It is a flowchart which shows an example of the trip data process in 1st Embodiment. It is a flowchart which shows an example of the deletion amount determination process in 1st Embodiment. It is a flowchart which shows an example of the deletion process by a user density in 1st Embodiment. It is a figure for demonstrating deleting the point data to an intersection. It is a figure for demonstrating the update of a user density. It is a flowchart which shows an example of the deletion process by a user density in 2nd Embodiment. It is a figure for demonstrating determination of the starting point by the user density of a passing point.

  Hereinafter, an example of an embodiment according to the disclosed technology will be described in detail with reference to the drawings. In the present embodiment, for example, position data acquired by GPS mounted on a mobile terminal such as a mobile terminal owned by the user or a vehicle on which the user gets on is transmitted every moment. To do. The position data transmitted in this way is hereinafter referred to as trip data transmitted from the user.

<First Embodiment>
As shown in FIG. 1, the trip data processing apparatus 10 according to the first embodiment includes an acquisition unit 12, a determination unit 14, an update unit 16, and an output unit 18. The trip data processing device 10 is an example of a route information processing device according to the disclosed technology.

The acquisition unit 12 receives position data LD transmitted from the user every moment. The position data LD includes a user ID and point data L as shown in FIG. The point data L includes, for example, the position (latitude and longitude) of the user acquired by GPS and the acquisition time when the position is acquired. Note that the point data L or the position data LD is an example of position information of the disclosed technology. Point data L and position data LD are expressed as follows.
Point data L: {latitude, longitude, acquisition time}
Position data LD: {user ID, point data L}

  As the user ID, for example, a terminal ID for identifying a portable terminal or a device ID for identifying a device such as a car navigation device mounted on a car can be used. The position data LD can also include other information. For example, in the case of position data acquired by a device mounted on a car, information such as the speed of the car and the presence or absence of sudden braking can be included as other information.

The acquisition unit 12 acquires, from the received position data LD, trip data TD in which the point data L included in the position data LD of the same user ID is arranged in order of acquisition time, for example, as shown in FIG. That is, the trip data TD is a time-series point data L representing the position on the route from the departure point to the arrival point. The trip data is an example of route information of the disclosed technology. The trip data TD is expressed as follows.
Trip data TD: {user ID, L ₀ ,..., L _n-1 }

Note that n is the number of position data LD received by the acquisition unit 12 for the user ID. L ₀ is point data on the trip data TD corresponding to the departure place, and L _n−1 is point data on the trip data TD corresponding to the arrival place. In this way, by making trip data TD a series of point data L from the departure point to the arrival point, it is possible to analyze the movement tendency of the user such as from which location to which the user is going. Become.

  The determination unit 14 determines a position on a route that is a predetermined distance away from the departure point and the arrival point as a start point and an end point in order to conceal the departure point and the arrival point in the user's route. Specifically, data is prepared by dividing a map showing a predetermined area into a plurality of small areas. For example, the map can be divided into meshes for each predetermined latitude and longitude, and each mesh (one cell) can be made into one small region. For each mesh, the user density storage unit 20 stores the user density data UDL corresponding to the user density represented by the number of users on the route having the position included in the mesh as the departure point or the arrival point. Keep it.

  FIG. 4 shows a conceptual diagram of the user density data UDL. In the example of FIG. 4, the user density corresponding to each mesh is represented by the color (halftone dot) density of each mesh. Here, the darker the color, the higher the user density. That is, it represents that there are a large number of users whose starting point or arriving point is a position included in the dark mesh. Representing the mesh user density with the mesh color is the same in the following figures.

The user density data UDL is expressed as follows.
User density data UDL = ({mesh i range, mesh i user density ms
, Mesh i user density me}, registered user ID)
Here, the user density ms of the mesh i is the number of users on the route starting from the position included in the mesh i, and the user density me of the mesh i arrives at the position included in the mesh i. It is the number of users of the route that is the ground. The registered user ID is a list or set of user IDs already counted as the number of users in order to obtain the user density. Also, it is possible to divide the time zone like weekday day, weekday night, holiday, and so on to obtain the user density for each time zone, and create multiple user density data UDL for each time zone. Good.

  The user density is an example of the actual performance of the disclosed technology. The traffic record may be an index indicating the difficulty of specifying the position included in the small area indicated by the mesh as the personal departure point or arrival point. For example, as a traffic record, in addition to the user density, population density, presence / absence of a school, a hospital, a station, a commercial facility, or the like may be used.

  The determination unit 14 refers to the user density data UDL, and on the route that is a first distance away from the starting point according to the mesh user density ms including the starting point of the trip data TD acquired by the acquiring unit 12. Is determined as the starting point. Similarly, the determination unit 14 determines, as an end point, a position on the route that is a second distance away from the arrival location according to the mesh user density me including the arrival location of the trip data TD.

  The first distance and the second distance may be the same value. Alternatively, the first distance may be defined as the actual distance from the departure place, the second distance may be defined as the actual distance to the arrival place, the first distance is the travel time from the departure place, and the second distance is the arrival place. It may be defined by the travel time until. For example, as shown in FIG. 5, the first distance and the second distance can be determined. In the example of FIG. 5, the actual distance ds or de from the departure point or the arrival point is determined as the first distance or the second distance according to the user density of the mesh including the departure point or the arrival point. In addition, a travel time ts or te for determining the first distance or the second distance is determined by the travel time from the departure place or the arrival place. The determination unit 14 may determine the start point or the end point by using both the actual distance ds or de and the travel time ts or te, or the start point or the end point by using only one of them. You may decide. The actual distance may be a straight distance from the departure point or the arrival point, or may be a distance on the route.

Further, as illustrated in FIG. 6, the determination unit 14 may determine the density level p according to the user density of the mesh including the departure place or the arrival place. In this case, the determination unit 14 may obtain d1 and d2 by the following equation (1) using the constant α, and may randomly select ds or de from d1 to d2, for example. Similarly, the determination unit 14 may obtain t1 and t2 by the following equation (2) using the constant β, and may randomly select ts or te from t1 to t2, for example.
d1 = α × 1, d2 = α × (1 + p) (1)
t1 = β × 1, t2 = β × (1 + p) (2)

  Further, the determination unit 14 associates the trip data TD with the digital map data, and when the position on the route that is the first distance away from the departure point is closer to the departure point than the first intersection that passes through the route, the determination unit 14 The position on the intersection is determined as the starting point. Similarly, when the position on the route that is a second distance away from the arrival point is closer to the arrival point than the last passing intersection in the route, the determination unit 14 determines the position on the intersection as the end point. . This is a process for making it difficult to estimate the departure point and the arrival point from the trip data TD. Therefore, the present invention is not limited to the case where the intersection is used as a reference as described above, and it is only necessary to determine whether the vehicle is close to the departure point or the arrival point based on a point where a plurality of roads meet. The digital map data referred to here is data obtained by recording the latitude and longitude of each intersection, the latitude and longitude at regular intervals of the road connecting the intersections, information on the intersections and roads (road width, etc.), and the like.

The update unit 16 updates the user density data UDL stored in the user density storage unit 20 based on the departure place and the arrival place of the trip data TD acquired by the acquisition unit 12. Specifically, the updating unit 16, from the stored user density data UDL the user density storage unit 20, searches the mesh that contains the position indicated by the latitude and longitude of the point data L ₀ of trip data TD. Then, the update unit 16 adds 1 to the user density ms of the searched mesh. Similarly, the update unit 16 searches for a mesh including the position indicated by the latitude and longitude of the point data L _n−1 of the trip data TD, and adds 1 to the user density me of the searched mesh. Note that the updating unit 16 does not perform updating when the user density ms and me of the same mesh are already updated based on the trip data TD of the same user ID.

The output unit 18 changes the user ID of the trip data TD acquired by the acquisition unit 12 to a temporary ID. Then, as illustrated in FIG. 7, the output unit 18 deletes the point data L ₀ corresponding to the departure place from the point data L before the start point determined by the determination unit 14. Similarly, the output unit 18 deletes from the point data L next to the end point determined by the determination unit 14 to the point data L _n−1 corresponding to the arrival point. Then, the output unit 18 outputs the remaining series of point data L as secret trip data ATD in which the departure point and the arrival point are concealed.

  That is, ds or ts obtained by the determination unit 14 indicates the amount of deletion of the point data L from the departure point, and de or te indicates the amount of deletion of the point data L up to the arrival point.

  Instead of deleting the point data L from the departure point to the start point and the point data L from the end point to the arrival point, the point data L from the start point to the end point in the trip data TD is deleted. The secret trip data ATD may be generated by extracting. The confidential trip data ATD is an example of output route information according to the disclosed technology.

The secret trip data ATD is expressed as follows.
Secret trip data ATD: {temporary ID, L _p ,..., L _q }
However, 0 ≦ p ≦ q ≦ n−1

  The trip data processing apparatus 10 can be realized by, for example, a computer 40 shown in FIG. The computer 40 includes a CPU 42, a memory 44, a nonvolatile storage unit 46, an input / output interface (I / F) 47, and a network I / F 48. The CPU 42, the memory 44, the storage unit 46, the input / output I / F 47, and the network I / F 48 are connected to each other via a bus 49.

  The storage unit 46 can be realized by an HDD (Hard Disk Drive), a flash memory, or the like. A storage unit 46 as a storage medium stores a trip data processing program 50 for causing the computer 40 to function as the trip data processing device 10. In addition, the storage unit 46 includes a user density storage area 60. The CPU 42 reads the trip data processing program 50 from the storage unit 46 and expands it in the memory 44, and sequentially executes processes included in the trip data processing program 50. The trip data processing program 50 is an example of a route information processing program of the disclosed technology.

  The trip data processing program 50 includes an acquisition process 52, a determination process 54, an update process 56, and an output process 58. The CPU 42 operates as the acquisition unit 12 illustrated in FIG. 1 by executing the acquisition process 52. Further, the CPU 42 operates as the determination unit 14 illustrated in FIG. 1 by executing the determination process 54. The CPU 42 operates as the update unit 16 illustrated in FIG. 1 by executing the update process 56. Further, the CPU 42 operates as the output unit 18 illustrated in FIG. 1 by executing the output process 58.

  When the trip data processing apparatus 10 is realized by the computer 40, the user density storage area 60 is used as the user density storage unit 20 shown in FIG. As a result, the computer 40 that has executed the trip data processing program 50 functions as the trip data processing apparatus 10.

  The trip data processing apparatus 10 can be realized by, for example, a semiconductor integrated circuit, more specifically, an ASIC (Application Specific Integrated Circuit) or the like.

  Next, the operation of the trip data processing apparatus 10 according to the first embodiment will be described. When a plurality of position data LD are input to the trip data processing apparatus 10, the trip data processing shown in FIG.

  In step S10 of the trip data processing shown in FIG. 9, the acquisition unit 12 receives a plurality of input position data LD. And the acquisition part 12 acquires the trip data TD which arranged the point data L contained in the position data LD of the same user ID in order of acquisition time from the received several position data LD.

  Next, in step S12, the deletion amount determination process shown in FIG. 10 is executed.

Delete amount determining process step S120 of FIG. 10, determination unit 14 sets the point data L _n-1 set point data L ₀ of trip data TD acquired on departure s to arrival e.

  Next, in step S122, the determination unit 14 acquires the mesh Ms including the departure point s and the mesh Me including the arrival point e from the user density data UDL stored in the user density storage unit 20. .

  Next, in step S124, the determination unit 14 acquires the user density ms of the mesh Ms and the user density me of the mesh Me from the user density data UDL.

  Next, in step S126, the determination unit 14 acquires the deletion amounts ds and ts from the departure point s according to the user density ms, and the deletion amounts de and te to the arrival point e according to the user density me. To do. The function f (•) in FIG. 10 is a function for obtaining (ds, ts) or (de, te) corresponding to “•”. For example, as described above, a function for obtaining (ds, ts) or (de, te) can be defined as f (•) with reference to a table as shown in FIG. Further, as f (·), a function for obtaining a density level as shown in FIG. 6 and calculating (ds, ts) or (de, te) may be defined. Note that f (•) is not limited to these examples.

  Next, in step S128, the updating unit 16 determines whether or not the user ID of the trip data TD is included in the registered user ID of the user density data UDL. If not included, the process proceeds to step S130, and the user ID is registered in the registered user ID of the user density data UDL. Next, in step S132, the update unit 16 updates the user density data UDL by adding 1 to each of the user density ms of the mesh Ms and the user density me of the mesh Me, and determines the deletion amount. The process ends, and the process returns to the trip data process shown in FIG. On the other hand, if the user ID is included in the registered user ID of the user density data UDL, an affirmative determination is made in step S128, steps S130 and S132 are skipped, and the process returns to the trip data process.

  Next, in step S18, the deletion process based on the user density shown in FIG. 11 is executed.

  In step S180 of the deletion process based on the user density shown in FIG. 11, the determination unit 14 sets a variable Dist1 indicating the distance from the departure place s and a variable Time1 indicating the travel time from the departure place s to 0, respectively.

Next, a loop process of step S182, determination unit 14, the point data _{L i} included in the trip data TD obtained at Step S10, while incrementing the variable i from 0, the processing of steps S184~S188 Run. Here, the variable i is i = 0,..., N−1.

In step S184, determining unit 14, a variable Dist1, adds the distance position of the point data _{L i} and (latitude and longitude) and the position of the point data _{L i + 1.} The distance here may be a linear distance or a distance on a route as long as it is the same as ds obtained in step S126. Next, in step S186, determining unit 14, a variable Time1, adds the difference between the acquisition time and the point data _{L i + 1} of the acquisition time point data _{L i.} Note that Δ (a, b) in FIG. 11 indicates the difference between a and b.

Next, in step S188, the determination unit 14 determines whether Dist1 exceeds the deletion amount ds acquired in step S126 and Time1 exceeds the deletion amount ts acquired in step S126. That is, it is determined whether or not the position of the point data L _{i + 1} is a first distance away from the departure point s. If Dist1> ds and Time1> ts, the process exits the loop process of step S182 and proceeds to step S190. In the case of Dist1 ≦ ds or Time1 ≦ ts, the loop processing in step S182 is repeated until the variable i becomes n−1.

Here, the case has been described in which it is determined whether or not the position of the point data L _{i + 1} is a first distance away from the departure point s by whether or not Dist1> ds and Time1> ts, but the present invention is not limited thereto. Not. For example, the determination may be made based on whether Dist1> ds or Time1> ts. The determination method may be determined in consideration of the balance between the protection of privacy information and the information amount of the confidential trip data.

In step S190, the determination unit 14 determines the point data L _{i + 1} as the start point L1. Then, the output unit 18 receives the point data L ₀ ,..., L _i from the point data L ₀ ,..., L _n−1 included in the trip data TD to the point before the start point L1. Is deleted.

  Next, in step S192, the determination unit 14 sets a variable Dist2 indicating the distance to the arrival location e and a variable Time2 indicating the travel time to the arrival location d to 0, respectively.

Next, a loop process of step S194, determination unit 14, the point data _{L j} after the processing of step S190, while decrements the variable j from n-1, executes the processing of step S196～S200. Here, the variable j is j = i + 1,..., N−1.

In step S196, determining unit 14, a variable Dist2, adds the distance position of the point data _{L j} (the latitude and longitude) and the position of the point data _{L j-1.} Next, in step S198, determining unit 14, a variable Time2, adds the difference between the acquisition time and the point data _{L j-1} of the acquisition time point data _{L j.}

Next, in step S200, the determination unit 14 determines whether Dist2 exceeds the deletion amount de acquired in step S126 and Time2 exceeds the deletion amount te acquired in step S126. That is, it is determined whether or not the position of the point data L _j is a second distance away from the arrival point e. If Dist2> de and Time2> te, the process exits the loop process of step S194 and proceeds to step S202. In the case of Dist2 ≦ ds or Time2 ≦ ts, the loop processing in step S194 is repeated until the variable j becomes i + 1.

When determining whether the position of the point data L _j is a second distance away from the arrival point e, for example, it may be determined based on whether Dist2> de or Time2> te. This is the same as in step S188.

In step S202, the determination unit 14 determines the point data L _j−1 as the end point L2. Then, the output unit 18 generates the point data L _j ,..., From the point data series L _{i + 1} ,..., L _n−1 after the processing in step S190 to the destination after the end point L2. Delete _Ln-1 . Next, in step S204, the output unit 18 outputs a series of point data L _{i + 1} ,..., L _j−1 from the start point L1 to the end point L2 (delivered to the next processing), and FIG. Return to the trip data processing shown in FIG.

Next, in step S22, the determination unit 14 matches the point data series L _{i + 1} ,..., L _j−1 output in step S202 with the digital map data. For the matching, an existing map matching technique can be used. Then, the determination unit 14 re-determines the intersection where the point data series L _{i + 1} ,..., L _j−1 pass for the first time as the start point L1. Similarly, the determination unit 14 re-determines the intersection where the point data series L _{i + 1} ,..., L _j−1 pass last as the end point L2.

Then, as shown in FIG. 12, the output unit 18 receives points from the point data series L _{i + 1} ,..., L _j−1 output in step S204 from the departure point s to the start point L1. Delete the data. Similarly, the output unit 18 deletes point data from the point next to the end point L2 to the destination from the point data series L _{i + 1} ,..., L _j−1 .

  Next, in step S24, the output unit 18 changes the user ID of the trip data TD from which a part has been deleted to a temporary ID, and outputs the trip data ATD as the secret trip data ATD in which the departure point and the arrival point are concealed. End data processing.

  As described above, according to the trip data processing device 10 according to the first embodiment, the distance from the start point to the start point and the end point to the arrival point according to the user density of the start point and the arrival point. Determine the distance. A series of point data from the start point to the end point is set as secret trip data. That is, the point data of an amount corresponding to the user density at the departure place and the arrival place is deleted from both ends of the trip data. Therefore, it is possible to prevent the trip data and the user from being linked from the starting point and the arrival point of the trip data. On the other hand, it is possible to prevent excessive deletion or insufficient deletion of trip data according to the characteristics of the departure place and arrival place such as densely populated areas and depopulated areas. That is, it is possible to output confidential trip data that is concealed flexibly in consideration of the balance between protection of personal privacy information and the amount of trip data. According to the secret trip data output by the trip data processing apparatus 10 according to the present embodiment, it is possible to prevent the trip data and the user from being associated with each other, so that the trip data is provided to a third party such as a cloud. It becomes possible.

  In the first embodiment, the case where the user density data UDL is updated each time trip data is acquired has been described. In this case, as shown in FIG. 13, at the initial stage of trip data acquisition, the user density of any mesh can be lowered, the amount of trip data deleted can be increased, and the privacy information protection strength can be increased. In addition, the crosses in FIG. 13 indicate point data to be deleted among the point data included in the trip data. On the other hand, when the trip data acquisition amount increases and the update of the user density data UDL progresses, the number of trip data deletion amounts increases, and the information amount of the confidential trip data can be increased. Note that the trip data processing described above may be executed from a state in which the user density data UDL has been updated to some extent.

  Further, according to the first embodiment, it is not necessary to wait for accumulation of a plurality of trip data, and processing can be performed for each trip data. Therefore, the confidential trip data can be output in semi-real time. This makes it possible to output useful secret trip data even when trip data is desired to be used for traffic jam information that requires the latest information.

  In addition, according to the first embodiment, only a part of trip data is deleted, and processing such as encryption and format change is not performed. Therefore, the compatibility with the existing position data analysis technology is high.

Second Embodiment
Next, a second embodiment will be described. Since the configuration of the trip data processing device according to the second embodiment is the same as the configuration of the trip data processing device 10 according to the first embodiment, description thereof is omitted.

  Next, the operation of the trip data processing apparatus according to the second embodiment will be described. The trip data process according to the second embodiment is different from the trip data process according to the first embodiment (FIG. 9) and the deletion process based on the user density executed at step S18. Hereinafter, with reference to FIG. 14, the deletion process by the user density in the second embodiment will be described. In addition, about the process similar to the deletion process (FIG. 11) by the user density in 1st Embodiment, the same code | symbol is attached | subjected and detailed description is abbreviate | omitted.

  In the loop process of step S182, the processes of steps S184 to S210 are executed. If a negative determination is made in step S188, the process proceeds to step S206.

In step S206, determining unit 14, from the stored user density data UDL the user density storage unit 20, acquires the user density ms mesh Ms that contains point data _{L i.}

Next, in step S208, the determination unit 14 acquires the deletion amounts ds ′ and ts ′ from the departure point s according to the user density ms. The function f ′ (•) in FIG. 14 is a function for obtaining (ds ′, ts ′) corresponding to “•”. For example, as f ′ (•), (ds, ts) is obtained from a table as shown in FIG. 5, for example, and the distance between the point data _Li and the departure point and the travel time are added to (ds, ts). A function for obtaining (ds ′, ts ′) can be defined. Further, the density level as shown in FIG. 6 is acquired as f ′ (•) to obtain (ds, ts), and the distance between the point data _Li and the departure point and the travel time are added (ds ′ , Ts ′) may be defined. Note that f ′ (•) is not limited to these examples.

  Next, in step S210, when the deletion amount ds 'obtained in step S208 is smaller than the deletion amount ds obtained in step S126 (FIG. 10), the determination unit 14 replaces ds with ds'. Similarly, the determination unit 14 replaces ts with ts ′ when the deletion amount ts ′ obtained in step S208 is smaller than the deletion amount ts obtained in step S126 (FIG. 10). In steps S212 to S216, the determination unit 14 performs the same process for the end point side.

  In the vicinity of the departure point or the arrival point, when passing through a point with a higher user density than the departure point or the arrival point, the amount of deletion corresponding to the user density at the passing point is less than the amount of deletion of trip data. You may be able to. More specifically, as shown in FIG. 15, the mesh (B) including a point that passes after the start point determined according to the user density of the mesh (A) including the departure point is included. The starting point determined according to the user density may be closer to the departure point. According to the second embodiment, in such a case, the trip data remaining rate can be increased by adopting the start point determined according to the user density of the mesh (B).

  As described above, according to the trip data processing device according to the second embodiment, in addition to the effects of the first embodiment, the information amount of the confidential trip data can be increased.

  In the second embodiment, the case where the deletion amount of the trip data is sequentially replaced when the deletion amount of the passing point is smaller than the deletion amount according to the user density of the departure place or the arrival place has been described. It is not limited to this. For example, for a predetermined number of point data near the departure point or near the arrival point, a deletion amount corresponding to each point data may be obtained and the deletion amount that is the minimum may be selected.

  In the above description, the trip data processing program 50 is stored (installed) in the storage unit 46 in advance. However, the trip data processing program 50 may be provided in a form recorded on a storage medium such as a CD-ROM or DVD-ROM. Is possible.

  Regarding the above embodiment, the following additional notes are disclosed.

(Appendix 1)
On the computer,
Get the route information where the position on the route from the departure point to the arrival point of the user is represented by time-series location information,
A small area obtained by dividing the predetermined area into a plurality of areas, and a position on the route that is a first distance away from the departure point is started according to the passing performance of the small region including the position on the route around the departure point. Determined as a point, and according to the traffic performance of a small area including a position on the route around the arrival point, a position on the route that is a second distance away from the arrival point is determined as an end point,
A route information processing method for executing processing including outputting time-series position information from a start point to an end point on the route as output route information.

(Appendix 2)
The route information processing method according to claim 1, wherein when the start point and the end point are determined, the first distance and the second distance are shortened as the passing performance of the small area increases, and increases as the passing performance decreases. .

(Appendix 3)
The route information processing method according to supplementary note 1 or supplementary note 2, wherein the passage performance of the small region is defined as the number of users of a route having a position included in the small region as a departure point or an arrival point.

(Appendix 4)
The route information processing method according to any one of supplementary notes 1 to 3, further causing the computer to further update a traffic record of a small area including a departure place and an arrival place of the obtained route information.

(Appendix 5)
When determining the start point and the end point, any one of the supplementary notes 1 to 4 in which the position on the route around the departure point is the departure point, and the position on the route around the arrival point is the arrival point The route information processing method according to claim 1.

(Appendix 6)
When determining the start point and the end point, the shortest first distance among the first distances according to the traffic performance of a plurality of small areas each including a plurality of positions on the route around the departure place Based on the shortest second distance among the second distances according to the traffic records of a plurality of small areas each including a plurality of positions on the route around the destination. The route information processing method according to claim 1, wherein the end point is determined.

(Appendix 7)
When determining the start point and the end point, based on the map information, the position on the route that is a first distance away from the departure point is the departure point from the merging point of the road that first passes on the route. Is determined as a starting point, and the position on the route that is a second distance away from the arrival point is the arrival point from the confluence point of the last road that passes through the route. The route information processing method according to any one of supplementary notes 1 to 6, wherein a position on the junction is determined as an end point when the position is close to.

(Appendix 8)
An acquisition unit for acquiring the route information in which the position on the route from the departure point to the arrival point of the user is represented by time-series position information;
A small area obtained by dividing the predetermined area into a plurality of areas, and a position on the route that is a first distance away from the departure point is started according to the passing performance of the small region including the position on the route around the departure point. A determination unit that determines a position on the route that is a second distance away from the arrival point as an end point, according to a passing performance of a small area that includes a position on the route around the arrival point,
An output unit that outputs time-series position information from a start point to an end point on the route as output route information;
Route information processing apparatus including

(Appendix 9)
The route information processing apparatus according to supplementary note 8, wherein the determination unit shortens the first distance and the second distance as the passing performance of the small area increases, and increases as the passing performance decreases.

(Appendix 10)
The route information processing apparatus according to supplementary note 8 or supplementary note 9, wherein the passage performance of the small region is defined as the number of users of a route having a position included in the small region as a departure point or an arrival point.

(Appendix 11)
The route information processing apparatus according to any one of attachments 8 to 10, including an update unit that updates a traffic record of a small area including a departure place and an arrival place of the route information acquired by the acquisition unit.

(Appendix 12)
The route information processing according to any one of appendix 8 to appendix 11, wherein the determination unit uses a position on a route around the departure point as the departure point, and a position on the route around the arrival point as the arrival point. apparatus.

(Appendix 13)
The determination unit determines the start point based on the shortest first distance among the first distances according to the passing performance of a plurality of small areas each including a plurality of positions on the route around the departure place. Further, the end point is determined based on the shortest second distance among the second distances according to the passing performance of the plurality of small areas including each of the plurality of positions on the route around the arrival place. The route information processing device according to any one of to appendix 11.

(Appendix 14)
If the position on the route that is a first distance away from the departure point is closer to the departure point than the merge point of the road that first passes through the route based on the map information, the determination unit A position on the point is determined as a starting point, and if the position on the route that is a second distance away from the arrival point is closer to the arrival point than the merging point of the last road that passes through the route, the merging point 14. The route information processing apparatus according to any one of supplementary notes 8 to 13, wherein a position on the point is determined as an end point.

(Appendix 15)
On the computer,
Get the route information where the position on the route from the departure point to the arrival point of the user is represented by time-series location information,
A small area obtained by dividing the predetermined area into a plurality of areas, and a position on the route that is a first distance away from the departure point is started according to the passing performance of the small region including the position on the route around the departure point. Determined as a point, and according to the traffic performance of a small area including a position on the route around the arrival point, a position on the route that is a second distance away from the arrival point is determined as an end point,
A route information processing program for executing processing including outputting time-series position information from a start point to an end point on the route as output route information.

(Appendix 16)
The route information processing program according to supplementary note 15, wherein when the start point and the end point are determined, the first distance and the second distance are shortened as the passing performance of the small area increases, and increases as the passing performance decreases. .

(Appendix 17)
17. The route information processing program according to supplementary note 15 or supplementary note 16, wherein the traffic record of the small region is defined as the number of users of a route having a position included in the small region as a departure point or an arrival point.

(Appendix 18)
18. The route information processing program according to any one of Supplementary Note 15 to Supplementary Note 17, further causing the computer to update the passage performance of a small area including a departure place and an arrival place of the obtained route information.

(Appendix 19)
When determining the start point and the end point, any one of appendix 15 to appendix 18, wherein a position on the route around the departure point is set as the departure point, and a position on the route around the arrival point is set as the arrival point. The route information processing program according to claim 1.

(Appendix 20)
When determining the start point and the end point, the shortest first distance among the first distances according to the traffic performance of a plurality of small areas each including a plurality of positions on the route around the departure place Based on the shortest second distance among the second distances according to the traffic records of a plurality of small areas each including a plurality of positions on the route around the destination. The route information processing program according to any one of supplementary notes 15 to 18, which determines the end point.

(Appendix 21)
When determining the start point and the end point, based on the map information, the position on the route that is a first distance away from the departure point is the departure point from the merging point of the road that first passes on the route. Is determined as a starting point, and the position on the route that is a second distance away from the arrival point is the arrival point from the confluence point of the last road that passes through the route. 21. The route information processing program according to any one of Supplementary Note 15 to Supplementary Note 20, which determines a position on the merging point as an end point when close to.

DESCRIPTION OF SYMBOLS 10 Trip data processing apparatus 12 Acquisition part 14 Determination part 16 Update part 18 Output part 20 User density memory | storage part

Claims (9)

On the computer,
Get the route information where the position on the route from the departure point to the arrival point of the user is represented by time-series location information,
A small area obtained by dividing the predetermined area into a plurality of areas, and a position on the route that is a first distance away from the departure point is started according to the passing performance of the small region including the position on the route around the departure point. Determined as a point, and according to the traffic performance of a small area including a position on the route around the arrival point, a position on the route that is a second distance away from the arrival point is determined as an end point,
A route information processing method for executing processing including outputting time-series position information from a start point to an end point on the route as output route information.   2. The route information processing according to claim 1, wherein, when determining the start point and the end point, the first distance and the second distance are shortened as the passing performance of the small area increases, and increases as the passing performance decreases. Method.   The route information processing method according to claim 1 or 2, wherein the passage performance of the small area is defined as the number of users of a route having a position included in the small area as a departure place or an arrival place.   The route information processing method according to any one of claims 1 to 3, further causing the computer to further update a traffic record of a small area including a departure place and an arrival place of the obtained route information.   5. When determining the start point and the end point, a position on a route around the departure point is set as the departure point, and a position on a route around the arrival point is set as the arrival point. The route information processing method according to any one of the above.   When determining the start point and the end point, the shortest first distance among the first distances according to the traffic performance of a plurality of small areas each including a plurality of positions on the route around the departure place Based on the shortest second distance among the second distances according to the traffic records of a plurality of small areas each including a plurality of positions on the route around the destination. The route information processing method according to claim 1, wherein the end point is determined.   When determining the start point and the end point, based on the map information, the position on the route that is a first distance away from the departure point is the departure point from the merging point of the road that first passes on the route. Is determined as a starting point, and the position on the route that is a second distance away from the arrival point is the arrival point from the confluence point of the last road that passes through the route. The route information processing method according to any one of claims 1 to 6, wherein a position on the merging point is determined as an end point when close to. An acquisition unit for acquiring the route information in which the position on the route from the departure point to the arrival point of the user is represented by time-series position information;
A small area obtained by dividing the predetermined area into a plurality of areas, and a position on the route that is a first distance away from the departure point is started according to the passing performance of the small region including the position on the route around the departure point. A determination unit that determines a position on the route that is a second distance away from the arrival point as an end point, according to a passing performance of a small area that includes a position on the route around the arrival point,
An output unit that outputs time-series position information from a start point to an end point on the route as output route information;
Route information processing apparatus including On the computer,
Get the route information where the position on the route from the departure point to the arrival point of the user is represented by time-series location information,
A small area obtained by dividing the predetermined area into a plurality of areas, and a position on the route that is a first distance away from the departure point is started according to the passing performance of the small region including the position on the route around the departure point. Determined as a point, and according to the traffic performance of a small area including a position on the route around the arrival point, a position on the route that is a second distance away from the arrival point is determined as an end point,
A route information processing program for executing processing including outputting time-series position information from a start point to an end point on the route as output route information.

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