JP2015090354A - Determination device, determination program and determination method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To accurately determine whether a position detected by each of a plurality of detection parts is a position on a mutually corresponding route.SOLUTION: When only a detection frequency FA of a sensor A is a prescribed frequency F0 or more, an interpolation object is only between the positions detected by the sensor A, and when detection frequencies FA and FB of the sensors A and B are smaller than the prescribed frequency F0, in each of the sensor A and the sensor B, in-between positions detected between two consecutive detection times are configured to be more finely interpolated. Thus, the interpolation can be appropriately performed in accordance with the detection frequencies of the sensors A and B, and a determination can be accurately made whether the position detected by each of the sensor A and the sensor B is a position on a mutually corresponding route.

Description

  The present invention relates to a determination device, a determination program, and a determination method.

  The conventional trajectory data processing apparatus receives trajectory data including position data indicating the position detected by the sensor and time data of the time when the position is detected from each sensor corresponding to each of the plurality of moving objects. The trajectory data processing device determines, for example, a person's movement route and which movement method the person used based on the received trajectory data. In order to make such a determination accurately, it is important to determine whether the position detected by each sensor is a position on a path corresponding to each other. For example, consider a case where a person moves on a taxi. The trajectory data processing device receives trajectory data from a first sensor provided in a mobile phone carried by the person. The trajectory data processing device receives trajectory data from a second sensor provided in the taxi. In order to determine whether the position detected by each sensor is a position on a route corresponding to each other, the trajectory data processing device requires that the position data received from the first sensor and the second sensor be within a certain range. It is determined whether or not the position is indicated. If the detection timings of the first and second sensors are the same, the trajectory data processing device determines whether or not the positions detected by the first sensor and the second sensor at the same time are the same. As a result, the trajectory data processing apparatus can determine whether the positions detected by the first and second sensors are positions corresponding to each other.

  However, the detection timings of the first and second sensors are almost different from each other. Therefore, the time at which the first and second sensors detect the position hardly occurs at the same time. Therefore, if the locus data processing apparatus simply processes the position data and time data received from the first and second sensors, the positions detected by the first and second sensors are on paths corresponding to each other. It cannot be determined whether it is a position.

  Therefore, the conventional trajectory data processing device searches for the detection time of the other sensor located between two consecutive detection times of one sensor in each of the first and second sensors. The trajectory data processing device performs linear interpolation based on the two positions detected at two consecutive detection times of one sensor and the detection time of the other sensor, so that at one detection time of the other sensor, Estimate the position that would be detected by the sensors. Then, the trajectory data processing device determines whether the estimated position and the position detected at the detection time by the other sensor are within a certain range.

JP 2004-117079 A

However, consider a case where the moving body moves along a non-straight route such as an intersection. When the detection frequency of at least one of the sensors (first sensor) is low, the position between the two positions detected by the first sensor is interpolated based on the time at which the second sensor detects the position (normalized time). In this case, the obtained interpolation position may deviate greatly from the actual path position. Therefore, it cannot be accurately determined whether the positions detected by the first and second sensors are positions on the corresponding paths.
As one aspect, it is an object to accurately determine whether the positions detected by the plurality of detection units are positions on a corresponding path.

  In one aspect, the determination unit determines whether or not the detection frequency of at least one detection unit among a plurality of detection units that repeatedly detect the position of the moving body at a predetermined frequency is equal to or higher than a predetermined frequency. A case where the determination unit determines that the detection frequency of the at least one detection unit is equal to or higher than the predetermined frequency is a first case. A case where the determination unit does not determine that the detection frequency of the at least one detection unit is equal to or higher than a predetermined frequency is a second case.

In the first case, the position determination unit is configured to detect two detection times detected at two detection times when the detection frequency of the plurality of detection units is equal to or higher than the predetermined frequency. A first position corresponding to the reference detection time is determined between the positions.
The reference detection position is a time when a detection unit other than the one detection unit among the plurality of detection units detects a position and is positioned between the two detection times.
In the second case, the position determination unit may include a plurality of first times corresponding to at least one common time between two positions detected between two consecutive detection times by each of the plurality of detection units. Determine the position of 2. The common time is a time that is common to each of the plurality of detection units and the detection frequency is equal to or higher than the predetermined frequency between the two detection times.

  In the first case, the determination unit detects the position detected by each of the plurality of detection units based on the first position and the third position detected by the other detection unit at the reference detection time. Are positions on paths corresponding to each other. In the second case, the determination unit determines whether the positions detected by the plurality of detection units are positions on a path corresponding to each other based on the plurality of second positions.

  As one aspect, there is an effect that it is possible to accurately determine whether the position detected by each of the plurality of detection units is a position on a path corresponding to each other.

It is a figure which shows the locus | trajectory data processing system provided with the locus | trajectory data processing apparatus 10 and the some sensor 20,22 ... 24 provided corresponding to each of the some mobile body 21,23 ... 25. . 2 is a block diagram of a trajectory data processing device 10. FIG. 3 is a functional block diagram of a trajectory data processing device 10. FIG. It is a figure which shows the process based on the identity determination processing program. It is a flowchart which shows an example of the identity determination process for determining whether the position which each of several sensor 20,22 ... 24 detected is a position on a corresponding path | route. It is a flowchart which shows an example of the normalization process of step 84 of FIG. 7 is a flowchart showing an example of a normalization time determination process in step 92 of FIG. 6. (A) shows that the detection frequency FA of the sensor A is larger than the predetermined frequency F0 and the detection frequency FB (<F0) of the sensor B, and (B) shows that within a certain time received from the sensor A and the sensor B. (C) shows the trajectory data of sensor A and the trajectory data of sensor B on a map showing the locations where the mobile bodies whose positions have been detected by sensor A and sensor B have moved. (D) shows one sensor detected at the detection time of the other sensor, which is located between two consecutive detection times of one sensor in each of the two sensors A and B. In the present embodiment, (E) indicates that the interpolation target is between positions detected by the sensor A having a relatively high detection frequency, and (F) Position detected by sensor A The normalization time of the position for interpolating between the sensors indicates that the detection time t of the sensor B is 1.5 and t = 3.5, and (G) indicates the normalization time t of the position of the sensor A = 1.5. , Coordinates of interpolation positions HPA1.5 and HPA3.5 at t = 3.5, and coordinates of positions PB1.5 and PB3.5 detected by sensor B at detection time t = 1.5 and t = 3.5 FIG. (A) shows that the detection frequencies FA and FB of the sensors A and B are both smaller than the predetermined frequency F0, and (B) shows the trajectory data received from the sensors A and B within a certain time. (C) shows a state in which the trajectory data of sensor A and the trajectory data of sensor B are drawn on a map showing the locations where the moving bodies of sensor A and sensor B have moved, and (D ) Indicates the normalized time, (E) indicates specific calculation results of the detection positions and interpolation positions of the sensors A and B, and (F) indicates the position in (E) with the sensors A and B. It is a figure which shows a mode that it drew on the map which shows the place where the mobile body which detected the position moved. (A) shows that both the detection frequency FA and the detection frequency FB are equal to or higher than the predetermined frequency F0, and (B) accurately reflects the path traveled by the positions detected by the sensors A and B. (C) shows that the positions detected by the sensors A and B at two consecutive detection times are interpolated with the other detection time as the normalized time, and (D) shows It is a figure which shows making the detection time of the sensor B into normalization time.

Hereinafter, an example of an embodiment of the disclosed technology will be described in detail with reference to the drawings.
FIG. 1 shows a trajectory data processing system. The trajectory data processing system includes the trajectory data processing device 10 and a plurality of sensors 20, 22... 24 provided corresponding to the plurality of moving bodies 21, 23. Each of the plurality of sensors 20, 22... 24 detects the position of the corresponding moving body. Each of the sensors 20, 22... 24 incorporates a GPS (Global Positioning System) that periodically detects the latitude and longitude at which the sensor is located. The position is defined by latitude and longitude. Each of the plurality of sensors 20, 22,... 24 has trajectory data including position data indicating the detected position and time data indicating the time at which the position is detected, together with identification data of the sensor, the networks 12, 14. ... is transmitted to the trajectory data processing apparatus 10 via 16. For example, the sensor 20 is provided in a mobile phone 21A carried by a person 21 who is a moving body. The person 21 carries the mobile phone 21A when moving. Therefore, the mobile phone 21A moves as a result as the person 21 moves. Therefore, the sensor 20 detects the position of the mobile phone 21A, and as a result, detects the position of the person 21 who carries the mobile phone 21A. The sensor 22 is provided in the taxi 23. The sensor 22 detects the position of the taxi 23. Further, the sensor 24 is provided on the train 25. The sensor 24 detects the position of the train 25.

  The trajectory data processing device 10 is an example of a determination device according to the technique of the present disclosure. The sensors 20, 22... 24 are an example of a detection unit according to the technique of the present disclosure.

  FIG. 2 shows a block diagram of the trajectory data processing device 10. As illustrated in FIG. 2, the trajectory data processing device 10 includes a CPU (Central Processing Unit) 32, a ROM (ReAdd Only Memory) 34, and a memory (RAM (Random Access Memory)) 36. The CPU 32, ROM 34, and memory 36 are connected to each other via a bus 38. A secondary storage device 40 and a magnetic disk drive 42 are connected to the bus 38. A magnetic disk 44 is built in the magnetic disk drive 42.

  A display control unit 46, a display device 48 connected to the display control unit 46, an input device 50, and a communication control unit 52 are connected to the bus 38. As the display device 48, a liquid crystal display device (LCD), a cathode ray tube (CRT), an organic electroluminescence display device (OELD), a plasma display panel (PDP), a field emission display (FED), or the like can be applied. As the input device 50, a keyboard or a mouse can be applied.

  As described above, each of the plurality of sensors 20, 22,... 24 transmits the trajectory data to the trajectory data processing apparatus 10 via the networks 12, 14. . The communication control unit 52 of the trajectory data processing apparatus 10 receives trajectory data and identification data transmitted from each of the plurality of sensors 20, 22.

  The secondary storage device 40 is provided with a plurality of databases 40N20, 40N22, 40N24 provided corresponding to each of the plurality of sensors 20, 22... 24, and an integrated database 40M.

  The CPU 32 recognizes from which sensor the trajectory data transmitted from each of the plurality of sensors 20, 22... 24 is transmitted based on the identification data. The CPU 32 stores the trajectory data in a database corresponding to the recognized sensor among the plurality of databases 40N20, 40N22, and 40N24.

The ROM 34 stores a trajectory data processing program including an identity determination processing program. The CPU 32 reads the trajectory data processing program from the ROM 34 and develops it in the memory 36, and executes the process of the trajectory data processing program.
The ROM 34 is an example of a storage medium according to the technology of the present disclosure. The identity determination processing program is an example of a determination program according to the technique of the present disclosure.

  Although the case where the locus data processing program is read from the ROM 34 is illustrated here, it is not always necessary to store it in the ROM 34 from the beginning. For example, the trajectory data is first stored in any “portable storage medium” such as an SSD (Solid State Drive), a DVD disk, an IC card, a magneto-optical disk, or a CD-ROM that is connected to the trajectory data processing apparatus 10. A processing program may be stored. Then, the trajectory data processing device 10 may acquire and execute a trajectory data processing program from these portable storage media. Further, the trajectory data processing program may be stored in a storage unit such as another computer or server device connected to the trajectory data processing device 10 via a communication line. In this case, the trajectory data processing device 10 acquires and executes a trajectory data processing program from another computer or server device.

FIG. 3 shows functional units based on the identity determination processing program in the trajectory data processing program of the trajectory data processing device 10. As illustrated in FIG. 3, the trajectory data processing device 10 includes a data acquisition unit 62, a normalization unit 64, an identity determination unit 66, and a determination result processing unit 68.
FIG. 4 shows a process based on the identity determination processing program. The identity determination processing program includes a data acquisition process 72, a normalization process 74, an identity determination process 76, and a determination result processing process 78.
The CPU 32 operates as the units 62 to 68 in FIG. 3 by executing each of the processes 72 to 78 in FIG.
The normalization unit 64 is an example of a determination unit and a position determination unit of the technology of the present disclosure. The identity determination unit 66 is an example of a determination unit according to the technique of the present disclosure.

Next, the operation of the trajectory data processing system will be described.
As described above, each of the plurality of sensors 20, 22,... 24 transmits the trajectory data to the trajectory data processing apparatus 10 via the networks 12, 14. . The communication control unit 52 of the trajectory data processing apparatus 10 receives trajectory data and identification data transmitted from each of the plurality of sensors 20, 22. The CPU 32 of the trajectory data processing device 10 recognizes from which sensor the trajectory data transmitted from each of the plurality of sensors 20, 22... 24 is transmitted based on the identification data. CPU32 memorize | stores the said locus | trajectory data in the database corresponding to the recognized sensor in several database 40N20, 40N22 ... 40N24.

  In the present embodiment, the detection frequency at which each sensor 20, 22... 24 detects the position is stored in a corresponding database. For example, each sensor 0, 22 ... 24 transmits detection frequency data indicating the detection frequency together with the trajectory data. When the trajectory data processing device 10 receives the detection frequency data together with the trajectory data, the trajectory data processing device 10 stores the detection frequency data in a corresponding database. Further, the trajectory data processing device 10 calculates the detection frequency by calculating the interval time between the times in the time data of two continuous trajectory data stored in the database. Then, the trajectory data processing device 10 stores detection frequency data indicating the calculated detection frequency in a corresponding database. Note that the attendant may store the detection frequency data of the corresponding sensor in each database 40N20, 40N22... 40N24 of the trajectory data processing device 10 in advance. In this case, each sensor 20, 22 ... 24 does not transmit detection frequency data.

The trajectory data processing device 10 determines, for example, a person's travel route and a movement method used by the person from the trajectory data received from the plurality of sensors 20, 22. In order to make such a determination accurately, it is important to determine whether the position detected by each sensor is a position on a path corresponding to each other.

  By the way, the detection timings of the sensors 20, 22. Therefore, the time at which the sensors 20, 22... 24 detect the positions hardly occurs at the same time. Therefore, if the trajectory data processing device 10 simply processes the trajectory data received from the sensors 20, 22... 24, the positions detected by the sensors 20, 22. It cannot be determined whether it is a position.

  Therefore, the trajectory data processing device 10 interpolates the position of the moving body obtained based on the trajectory data in each of a plurality of combinations of two sensors selected from the sensors 20, 22,... The position at the same detection time is estimated. Then, the trajectory data processing device 10 determines whether the positions detected by the two sensors are positions on the corresponding paths.

  FIG. 5 shows, as a flowchart, an example of identity determination processing for determining whether the positions detected by the two sensors are positions corresponding to each other. The identity determination process starts when two of the plurality of sensors 20, 22... 24 are selected via the input device 50. Hereinafter, the two selected sensors are referred to as sensor A and sensor B.

  When the identity determination process starts, the data acquisition unit 62 acquires the trajectory data transmitted from the sensor A and the sensor B from the corresponding databases in step 82 of FIG. For example, if the sensor A is the sensor 20, the data acquisition unit 62 acquires the trajectory data transmitted from the sensor 20 from the database 40N20. If sensor B is sensor 22, data acquisition unit 62 acquires the trajectory data transmitted from sensor 22 from database 40N22.

  In step 84, the normalization unit 64 executes normalization processing. In step 86, the identity determination unit 66 determines whether the positions detected by the sensors A and B are positions on the corresponding route. If the determination result in step 86 is affirmative, the identity determination process proceeds to step 88. In step 88, the determination result processing unit 68 executes determination result processing. When the process of step 88 is executed, the identity determination process ends. If the determination result of step 86 is negative, the identity determination process skips step 88 and ends.

FIG. 6 shows an example of the normalization process in step 84 as a flowchart. In step 92 of FIG. 6, the normalization unit 64 executes a process for determining a normalization time, and in step 94, calculates the position coordinates.
The process of step 94 is an example of the content of the process of the position determination part of the technique of this indication.

FIG. 7 shows an example of a normalization time determination process in step 92 of FIG. 6 as a flowchart. In step 102 of FIG. 7, the normalization unit 64 first reads time data of two continuous trajectory data from the database corresponding to each of the sensor A and the sensor B. The normalization unit 64 calculates the detection frequency FA and the detection frequency FB of each of the sensor A and the sensor B by calculating an interval time between two continuous time data corresponding to each of the sensor A and the sensor B. To grasp. Then, the normalization unit 64 determines whether at least one of the detection frequency FA and the detection frequency FB is equal to or higher than the predetermined frequency F0. That is, the normalization unit 64 determines whether or not F0 ≦ FA or F0 ≦ FB.
The process of step 102 is an example of the content of the process of the determination unit of the technology of the present disclosure.

  If the determination result in step 102 is affirmative, the normalization time determination process proceeds to step 104. If the determination result in step 102 is negative, the normalization time determination process proceeds to step 110.

In step 104, the normalization unit 64 determines whether the detection frequency FB of the sensor B is equal to or higher than the detection frequency FA of the sensor A. That is, the normalization unit 64 determines whether FA ≦ FB.
If the determination result in step 104 is affirmative, the normalization time determination process proceeds to step 108. If the determination result in step 104 is negative, the normalization time determination process proceeds to step 106.

  In step 106, the normalization unit 64 sets the detection time of the sensor B as the normalization time. On the other hand, in step 108, the normalization unit 64 sets the detection time of the sensor A as the normalization time. In step 110, the normalization unit 64 adds the time to the detection times of the sensors A and B so that the detection frequency becomes F0 or more, and sets the normalization time.

  After the processing of steps 106, 108 and 110, the normalization time determination processing proceeds to step 112. In step 112, the normalization unit 64 outputs (stores) the normalized time to the memory 36 so that it can be used in later processing.

Next, each process of steps 106, 108, and 110 will be described in detail.
First, the process of step 106 will be described.
The normalization time determination process proceeds to step 106 when at least one of the detection frequency FA of the sensor A and the detection frequency FB of the sensor B is greater than the predetermined frequency F0 and the detection frequency FA is greater than the detection frequency FB. is there. More specifically, there are the following two cases in which the normalization time determination process proceeds to step 106. That is, first, when both the detection frequency FA and the detection frequency FB are equal to or higher than the predetermined frequency F0 and the detection frequency FA is larger than the detection frequency FB, and secondly, as shown in FIG. May be greater than the predetermined frequency F0 and greater than the detection frequency FB (<F0). In the present embodiment, the process in the first case is the same as the process in the second case. Taking the following case as an example, the processing of step 106 in the second case will be described. The detection frequency FA of the sensor A is, for example, 1, and the position is detected once per second. The detection frequency FB of the sensor B is, for example, 1/2, that is, the position is detected once every 2 seconds. The predetermined frequency F0 is 1, for example. The detection frequency FA = 1 of the sensor A is the same as the predetermined frequency F0 and is larger than the detection frequency FB = 1/2 (<F0) of the sensor B.

FIG. 8B shows specific contents of the trajectory data received from the sensor A and the sensor B within a certain time. Sensor A detects the position once per second. As shown in FIG. 8B, the trajectory data of the sensor A includes firstly, in the afternoon of the month, the day of the month, the hour, the minute, and the second (t = 1), and the position PA1 ( 10, 40). Secondly, there are ** ** ** ** minutes 2 seconds (t = 2) of ** month ** day and position PA2 (30, 40) detected at the time. The trajectory data of the sensor A includes, thirdly, ○ month ○ day afternoon ○ hour ○ minute 3 seconds (t = 3), the position PA3 (40, 30) detected at the time, and fourth, ○ There are month o day o o o o o min 4 sec (t = 4) and position PA4 (40, 10) detected at that time.
Time t = 1 and time t = 2, time t = 2 and time t = 3, and time t = 3 and time t = 4 are examples of two detection times of the technology of the present disclosure.

On the other hand, the sensor B detects the position once every 2 seconds. First, in the locus data of the sensor B, the month, the day, the afternoon, the hour, the minute, 1.5 seconds (t = 1.5), and the position PB1.5 (20, 40) detected at the time. There is. Secondly, there is a month, a month, a day, a hour, a minute, 3.5 seconds (t = 3.5), and a position PB3.5 (40, 20) detected at that time.
Each of the position PB1.5 and the position PB3.5 is an example of a third position of the technology of the present disclosure.

  FIG. 8C shows a state in which the trajectory data of sensor A and the trajectory data of sensor B are drawn on a map showing the locations where the moving bodies whose positions are detected by sensor A and sensor B have moved. As understood from FIGS. 8B and 8C, the sensor A and the sensor B do not detect the position of the moving body at the same time. Therefore, by interpolating the actually detected positions, if the positions that the sensors A and B would have detected at the same time are obtained, it is determined whether or not the obtained positions are the same. It can be determined whether the moving bodies of A and sensor B are the same.

  FIG. 8D shows an example in which the interpolation position is obtained from the trajectory data detected by each of the two sensors A and B. For example, the detection time (t = 1.5) of sensor B is located between two consecutive detection times (t = 1, t = 2) of sensor A. Therefore, when the position at the detection time t = 1.5 is linearly interpolated based on the positions PA1 and PA2 detected by the sensor A at the time t = 1 and t = 2, the interpolation position HPA1. 5 is obtained. Similarly, the detection time of sensor B (t = 3.5) is located between two consecutive detection times of sensor A (t = 3, t = 4). Therefore, if the position at the detection time t = 3.5 is linearly interpolated based on the positions PA43 and PA4 detected by the sensor A at the time t = 3 and t = 4, the interpolation position HPA3. 5 is obtained.

  Further, the detection time (t = 2, t = 3) of the sensor A is located between two consecutive detection times (t = 1.5, t = 3.5) of the sensor B. Therefore, if the position at the detection time t = 2 and t = 3 is linearly interpolated based on the positions PB1.5 and PB3.5 detected by the sensor B at the time t = 1.5 and t = 3.5, the sensor B Interpolated positions HPB2 and HPB3 that would have been detected are obtained.

  Based on the position actually detected in sensor A and the interpolation position obtained by interpolation, and the position actually detected in sensor B and the interpolation position obtained by interpolation, the moving bodies of sensor A and sensor B Can be determined whether they are the same.

  In the example shown in FIG. 8D, the distance between the position PA2 detected by the sensor A at time t = 2 and the interpolation position HPB2 of the sensor B, and the position PA3 detected by the sensor A at time t = 3. The distance between the interpolation position HPB3 of the sensor B is relatively long. Therefore, it is determined that the positions detected by the sensors A and B are not positions on the corresponding path.

  However, in reality, the positions detected by the sensors A and B are positions on the corresponding paths. In this way, in reality, the positions detected by the sensors A and B are positions on the corresponding paths, but between the positions detected by the sensors A and B at the time t = 2 and t = 3. The reason for the relatively long distance is as follows.

  The sensor A having a relatively high detection frequency for detecting positions (higher than a predetermined frequency F0 described later) can detect a relatively large number of positions. Therefore, even when a person moves along a non-straight route such as an intersection, the position detected by the sensor A reflects the non-straight route more accurately. Therefore, in order to interpolate between two positions detected by the sensor A at two consecutive detection times, the detection time of the sensor B was obtained as the time positioned between the two consecutive times. The interpolation position accurately reflects the route traveled by the person.

Here, the time at the position to be interpolated is called a normalized time.
As a time for interpolating between two positions detected at two consecutive detection times by the sensor A having a relatively high detection frequency, the detection time of a sensor having a relatively low detection frequency is obtained as a normalized time. The interpolated position accurately reflects the route traveled by the person. Note that the detection frequency at which the interpolation position accurately reflects the path traveled by the person can be determined in advance. This detection frequency is a predetermined frequency F0.

  However, the sensor B whose detection frequency for detecting the position is lower than the predetermined frequency F0 detects a relatively small number of positions. Therefore, when a person moves along a non-straight route such as an intersection, the number of positions detected by the sensor B is smaller than the number of detection positions for accurately reflecting the non-straight route. Therefore, in order to interpolate between the positions detected by the sensor B, even if the detection time of the sensor A having a high detection frequency is normalized, the obtained interpolation position does not accurately reflect the route traveled by the person. . Therefore, the difference between the interpolation position between the positions detected by the sensor B and the position obtained by the sensor A at the time corresponding to the normalization time becomes large.

Therefore, in the present embodiment, in step 106, the normalization unit 64 sets the detection time of the sensor B as the normalization time. More specifically, first, as shown in FIG. 8E, the interpolation target is between positions detected by the sensor A whose detection frequency is equal to or higher than the predetermined frequency F0. Therefore, no interpolation is performed between positions detected by the sensor B whose detection frequency is less than the predetermined frequency. As described above, since the number of positions detected by the sensor B is smaller than the number of detection positions for accurately reflecting a path that is not a straight line, the interpolation position between the positions detected by the sensor B is moved by a person. This is because the route is not accurately reflected. As shown in FIG. 8 (F), the normalization times of the positions to be interpolated between the positions detected by the sensor A are the detection times t = 1.5 and t = 3.5 of the sensor B.
Each of detection times t = 1.5 and t = 3.5 of the sensor B is an example of a reference detection time of the technology of the present disclosure.

In the calculation of the position coordinates in step 94 in FIG. 6, the normalization unit 64 calculates the coordinates of the interpolation positions HPA1.5 and HPA3.5 between the positions detected by the sensor A. The positions used for obtaining the interpolation position at the normalized time t = 1.5 are the positions PA1 (10, 40) and PA2 (30, 40) detected by the sensor A at the time t = 1 and the time t = 2. It is. The position of the X coordinate of the interpolation position HPA1.5 is calculated by the following equation (1).

In the expression (1), t1 and t2 are respectively an early time t = 1 and a later time t = 2 of two consecutive detection times. In the equation (1), x1 and x2 are X-coordinate values of the positions detected at times t1 and t2, respectively. In the equation (1), s1 is normalized time t = 1.5.
The Y coordinate position of the interpolation position HPA1.5 is also calculated in the same manner as the X coordinate.
Further, in step 94, the coordinates of the interpolation position HPA3.5 at the normalization time t = 3.5 are calculated in the same manner as described above. With the above calculation, the coordinates of the interpolation positions HPA1.5 and HPA3.5 at the normalized times t = 1.5 and t = 3.5 are as shown in FIG.
Each of the interpolation positions HPA1.5 and HPA3.5 is an example of a first position of the technique of the present disclosure.

In step 86 of FIG. 5, the identity determination unit 66 determines that the position detected by the sensor A and the sensor B is the position on the path corresponding to each other, with the distance D1 calculated as follows. It is determined whether or not the threshold value D0 is, for example, 4 or less.
The “corresponding route” includes not only a completely matching route but also a route that is separated by a certain distance. For example, when a person 21 gets on a taxi 23, the position detected by the sensor 20 provided on the mobile phone 21A carried by the person 21 and the sensor 22 provided on the taxi 23 at the same time is completely the same position. This is because it is not detected.

（２）式のｘｉは、センサＡにおける時刻ｔ＝ｉの位置であり、ｙｉは、センサＢにおける時刻ｔ＝ｉの位置である。ｉは、各正規化時刻を識別する変数である。上記例（図８（Ｆ））では、ｉ＝１は、時刻ｔ＝１．５を識別し、ｉ＝２＝Ｎは、時刻ｔ＝３．５を識別する。よって、上記距離Ｄ１の計算では、時刻ｔ＝１．５でのセンサＡにおける補間位置ＨＰＡ１．５と、時刻ｔ＝１．５においてセンサＢが検出した位置ＰＢ１．５とのユークリッド距離が用いられる。また、上記距離Ｄ１の計算では、時刻ｔ＝３．５でのセンサＡにおける補間位置ＨＰＡ３．５と、時刻ｔ＝３．５においてセンサＢが検出した位置ＰＢ３．５とのユークリッド距離が用いられる。 First, the distance D1 between the positions at the same time in the sensor A and the sensor B is calculated from the following equation (2).

In the equation (2), xi is a position at time t = i in the sensor A, and yi is a position at time t = i in the sensor B. i is a variable for identifying each normalized time. In the above example (FIG. 8F), i = 1 identifies time t = 1.5 and i = 2 = N identifies time t = 3.5. Therefore, in the calculation of the distance D1, the Euclidean distance between the interpolation position HPA1.5 in the sensor A at time t = 1.5 and the position PB1.5 detected by the sensor B at time t = 1.5 is used. . In the calculation of the distance D1, the Euclidean distance between the interpolation position HPA3.5 in the sensor A at time t = 3.5 and the position PB3.5 detected by the sensor B at time t = 3.5 is used. .

  If the distance D1 is less than or equal to the threshold value D0, the determination result in step 86 is affirmative. That is, it is determined that the persons who are the targets of the positions detected by the sensors A and B are the same. If the distance D1 is greater than the threshold value D0, the determination result in step 86 is negative. That is, it is determined that the persons who are the targets of the positions detected by the sensors A and B are not the same.

  In the above example, D1 = 0 and D1 <D0 (for example, 4). The determination result in step 86 is affirmative. That is, it is determined that the persons who are the targets of the positions detected by the sensors A and B are the same. In this case, in step 88 of FIG. 5, the determination result processing unit 68 executes the determination result processing as follows. Assume that the sensor A is a sensor 20 provided in a mobile phone 21 (see FIG. 1) carried by a person. Further, it is assumed that the sensor B is a sensor 22 provided in the taxi 23. The determination result processing unit 68 gives the label “movement by taxi” to the trajectory data transmitted by the sensor A. Specifically, the determination result processing unit 68 stores, in the integrated database 40M, the identification information of the database 40N20 (see FIG. 2) in which the trajectory data transmitted by the sensor A is stored and the “movement by taxi” data. Store it in association.

Next, the process of step 108 will be described.
First, when the normalization time determination process proceeds to step 108 and when the normalization time determination process proceeds to step 106, at least one of the detection frequency FA of sensor A and the detection frequency FB of sensor B is a predetermined frequency. It is common in that it is F0 or more. However, when the normalization time determination process proceeds to step 108, the detection frequency FB is equal to or higher than the detection frequency FA, whereas when the normalization time determination process proceeds to step 106, the detection frequency FA is higher than the detection frequency FA. It differs in that it is higher than FB.

  In the process of step 108, the interpolation target is between the positions detected by the sensor B, and the normalized time is set as the detection time of the sensor A, whereas in the process of step 106, the interpolation target is between the positions detected by the sensor A. And the difference is that the normalized time is the detection time of the sensor B. However, since the specific processing content is the same, detailed description of the processing in step 108 is omitted.

Next, the process of step 110 will be described. The normalization time determination process proceeds to step 110 when the detection frequency FA and detection frequency FB of the sensor A and sensor B are smaller than the predetermined frequency F0. Hereinafter, as shown in FIG. 9A, the detection frequencies FA and FB of the sensors A and B are both ¼ (the position is detected once every 4 seconds), and the detection frequencies FA and FB are Taking the case where the frequency is smaller than the predetermined frequency F0 (= 1) as an example, the processing of step 110 will be described.

  FIG. 9B shows specific contents of the trajectory data received from the sensor A and the sensor B within a certain time. Sensor A detects the position once every 4 seconds. As shown in FIG. 9 (B), the trajectory data of the sensor A includes, firstly, the month, the month, the afternoon, the hour, the minute, and the second at the time (t = 2), and the position PA2 ( 20, 50). Secondly, there is a time of a month, a day of a month, a time of 6 minutes (t = 6), and a position PA6 (50, 40) detected at that time. Thirdly, the trajectory data of the sensor A includes the month, the day, the afternoon, the hour, the minute, 10 seconds (t = 10), and the position (50, 0) detected at the time. It is assumed that the detection target of sensor A is located at the position (5, 55) at time t = 0.

On the other hand, the sensor B also detects the position once every 4 seconds. The trajectory data of sensor B includes, firstly, the month, the day of the month, the hour, the minute, the second (t = 1), the position (0, 50) detected at the time, and the second, the month O There are o'clock o'clock o o o min 5 sec (t = 5) and the position PB5 (40, 50) detected at that time. Thirdly, the locus data of the sensor B includes the month, the day, the afternoon, the hour, the minute, 9 seconds (t = 9), and the position PB9 (50, 20) detected at the time. Note that it is assumed that the detection target of the sensor B is located at the position (55, 5) at time t = 11.
Time t = 2 and time t = 6, time t = 6 and time t = 10, time t = 1 and time t = 5, time t = 5 and time t = 9, respectively, are two detections of the technology of the present disclosure. It is an example of time.

  FIG. 9C shows a state in which the trajectory data of sensor A and the trajectory data of sensor B are drawn on a map indicating the locations where the mobile bodies whose positions are to be detected by sensor A and sensor B have moved. . The detection frequency of sensor B is the same as the detection frequency of sensor A, but the detection timings of sensor A and sensor B are different.

  As described above, when the detection frequency FA and the detection frequency FB are smaller than the predetermined frequency F0, the number of positions detected by the sensors A and B is the number of detection positions for accurately reflecting a non-straight path. Fewer. Therefore, in each of the sensors A and B, even if interpolation is performed between two positions detected at two consecutive detection times with only the other detection time as a normalized time, the obtained interpolation position is Does not accurately reflect the route traveled by a person.

  Therefore, in the present embodiment, the normalization unit 64 is a normalization common to the sensor A and the sensor B for interpolating between the positions detected between two consecutive detection times in each of the sensor A and the sensor B. The determination time is determined so that the detection frequency is equal to or higher than the predetermined frequency F0. Thereby, in each of the sensor A and the sensor B, the position detected between two consecutive detection times can be interpolated more finely. Therefore, the error can be reduced as compared with the case of interpolating only the other detection time as the normalized time.

  There are the following two methods for determining the normalization time common to the sensor A and the sensor B so that the detection frequency is equal to or higher than the predetermined frequency F0.

  The first method is as follows. In the first step, the normalizing unit 64 acquires the minimum value (earliest time) and the maximum value (latest time) among the detection times of the sensors A and B. In the example shown in FIG. 9B, the minimum value is time t = 1, and the maximum value is time = 10. In the next step, the normalization unit 64 determines a time interval at which the detection frequency becomes the predetermined frequency F0. The time interval is 1 (second). In the next step, the normalizing unit 64 calculates a normalized time obtained by adding the determined time interval (1 second) to the minimum value. Then, the normalization unit 64 calculates the next normalization time by adding the determined time interval (1 second) to the calculated normalization time. The normalizing unit 64 repeats this until the maximum value is reached. Thereby, the normalization time is determined as shown in FIG.

The second method is as follows. In the first step, the normalizing unit 64 combines both detection times, and arranges them in ascending order except for overlapping times. Thereby, the detection times of the sensor A and the sensor B are arranged like time t = 1, 2, 5, 6, 9, 10. In the next step, the normalization unit 64 sequentially compares the nth time and the (n + 1) th time, and if the detection frequency is lower than the predetermined frequency F0, the normalization unit 64 is between the nth time and the (n + 1) th time. Are divided so that the detection frequency becomes the predetermined frequency F0. The normalizing unit 64 sets the divided time as the normalized time. Specifically, first, when n = 1, the first detection time is t = 1, the second detection time is t = 2, and the detection frequency is 1, which is the same as the predetermined frequency F0. The normalization unit 64 sets these as a common normalization time. Next, when n = 2, the second detection time is t = 2, the third detection time is t = 5, and the detection frequency is 1/3, which is lower than the predetermined frequency F0. Therefore, the normalizing unit 64 divides between t = 2 and t = 5 so that the predetermined frequency F0 is obtained. Thereby, time t = 3 and t = 4 are obtained between t = 2 and t = 5. As a result, t = 2, t = 3, t = 4, and t = 5 are obtained as normalized times. The normalizing unit 64 performs the same processing thereafter. As a result, the normalized time is determined as shown in FIG.
As illustrated in FIG. 9D, the normalized time is an example of the reference time of the technology of the present disclosure.

In the calculation of the position coordinates in step 94 in FIG. 6, the normalizing unit 64 calculates the interpolation position at the normalization time based on the positions PA2, PA6, and PA10 detected by the sensor A according to the equation (1). Thereby, the interpolation positions HPA3, HPA4, and HPA5 are calculated between the position PA2 and the position PA6. Interpolated positions HPA7, HPA8, and HPA9 are calculated between the position PA6 and the position PA10. Furthermore, the interpolation position HPA1 is also calculated. Further, the normalization unit 64 calculates the interpolation position at the normalization time according to the equation (1) based on the positions PB1, PB5, and PB9 detected by the sensor B. Thereby, the interpolation positions HPB2, HPB3, and HPB4 are calculated between the position PB1 and the position PB5. Interpolated positions HPB6, HPB7, and HPB8 are calculated between the position PB5 and the position PB9. Further, the interpolation position HPB10 is also calculated. A specific calculation result is shown in FIG. The specific calculation result shown in FIG. 9 (E) is drawn with the locus data of sensor A and the locus data of sensor B on a map showing the location where the mobile object provided with sensor A and sensor B has moved. Is as shown in FIG.
Each of the two positions corresponding to the sensor A and the sensor B at each time of time t = 1 to 10 illustrated in FIG. 9E is an example of a plurality of second positions of the technology of the present disclosure.

  In step 86 of FIG. 5, the identity determination unit 66 calculates the distance D1 by substituting the specific calculation result shown in FIG. In the above example (FIG. 9D), each of i = 1 to 10 (N = 10) identifies time t = 1 to 10. The identity determination unit 66 determines whether or not the distance D1 is equal to or less than the threshold value D0. In the above example, the distance D1 is 8.83 and is larger than the threshold value D0 (for example, 4). The determination result in step 86 is negative. That is, it is determined that the persons who are the targets of the positions detected by the sensors A and B are not the same. In this case, step 88 in FIG. 5 is skipped. The identity determination process ends.

Next, the effect of this embodiment will be described.
(First effect)
In the present embodiment, when the detection frequency FB of the sensor B is lower than the predetermined frequency F0 and the detection frequency of the sensor A is equal to or higher than the predetermined frequency F0, the object to be interpolated is between the positions detected by the sensor A. Therefore, no interpolation is performed between positions detected by the sensor B having a detection frequency less than the predetermined frequency F0. Since the number of positions detected by the sensor B is smaller than the number of detection positions for accurately reflecting a path that is not a straight line, the interpolation position between the positions detected by the sensor B is a path that the person has moved with high accuracy. It is because it does not reflect. Therefore, it is possible to determine whether or not the persons who are the targets of the positions detected by the sensors A and B are not the same without using an interpolation position that does not accurately reflect the route traveled by the person. Since the sensor A having a detection frequency equal to or higher than the predetermined frequency F0 is interpolated between two positions detected at two consecutive detection times, the obtained interpolation position accurately reflects the path on which the person has moved. Therefore, this embodiment has an effect that it is possible to accurately determine whether the positions detected by the sensors A and B are positions on the corresponding paths.

(Second effect)
In the present embodiment, when the detection frequencies FA and FB of the sensors A and B are smaller than the predetermined frequency F0, the number of positions detected by each of the sensors A and B is a detection for accurately reflecting a path that is not a straight line. Less than the number of positions. Therefore, in each of the sensors A and B, even if interpolation is performed between two positions detected at two consecutive detection times with only the other detection time as a normalized time, the obtained interpolation position is Does not accurately reflect the route traveled by a person. Therefore, in the present embodiment, the normalization unit 64 is a normalization common to the sensor A and the sensor B for interpolating between the positions detected between two consecutive detection times in each of the sensor A and the sensor B. The determination time is determined so that the detection frequency is equal to or higher than the predetermined frequency F0. Thereby, in each of the sensor A and the sensor B, the position detected between two consecutive detection times can be interpolated more finely. The identity determination unit 66 calculates the distance D1 using each position at time t = 1 to 10 in FIG. 9E, and determines whether or not the calculated distance D1 is equal to or less than the threshold value D0. Therefore, this embodiment has an effect that it is possible to accurately determine whether the positions detected by the sensors A and B are positions on the corresponding paths.

(Third effect)
When only the detection frequency FA of the sensor A is equal to or higher than the predetermined frequency F0, the object to be interpolated is only between the positions detected by the sensor A. When the detection frequencies FA and FB of the sensors A and B are smaller than the predetermined frequency F0, the positions detected between two consecutive detection times are interpolated more finely in each of the sensor A and the sensor B. Therefore, this embodiment can appropriately interpolate according to the detection frequency of sensors A and B, and whether each of the positions detected by sensors A and B is a position on the corresponding path. It has the effect that it can judge with sufficient precision.

Next, a modification of this embodiment will be described.
(First modification)
As described above, the normalized time determination process proceeds to step 106 in the following two cases. That is, first, when both the detection frequency FA and the detection frequency FB are equal to or higher than the predetermined frequency F0 and the detection frequency FA is larger than the detection frequency FB, and secondly, as shown in FIG. May be greater than the predetermined frequency F0 and greater than the detection frequency FB (<F0). The second case has already been described. In the present embodiment, the process in the first case is the same as the process in the second case.

  In the first case, the detection frequency FB is also equal to or higher than the predetermined frequency F0. Therefore, even if the detection time of sensor A is used as a time for interpolation between two positions detected by sensor B at two consecutive detection times, the obtained interpolation position is the path traveled by the person. Is accurately reflected. Therefore, in step 106, the normalization unit 64 may use the detection time of the sensor A as the normalization time, contrary to the above. The above will be described with reference to FIG.

  In the first case, as shown in FIG. 10A, both the detection frequency FA and the detection frequency FB are equal to or higher than a predetermined frequency F0. In this case, as shown in FIG. 10B, the positions detected by the sensor A and the sensor B accurately reflect the route traveled by the person.

  In the first case, as shown in FIG. 10C, the positions detected by the sensors A and B at two consecutive detection times may be interpolated with the other detection time as the normalized time. Conceivable. However, the positions detected by the sensors A and B accurately reflect the route traveled by the person. Therefore, interpolating the positions detected by the sensors A and B at two consecutive detection times means that the interpolation positions are calculated with a detection frequency more than necessary.

  Therefore, in the first case, either the detection time of sensor A or the detection time of sensor B is sufficient as the time to be normalized. In step 106, as shown in FIG. 10D, the detection time of the sensor B is set as a normalized time. Since the detection frequency of sensor A is higher than the detection frequency of sensor B, the position detected by sensor A more accurately reflects the path traveled by the person than the position detected by sensor B. Therefore, interpolation of the position detected by sensor A is performed. The position also accurately reflects the route that the person has moved. Therefore, this embodiment has the effect that it can judge more accurately whether the person who becomes the object of the position which each of sensor A and sensor B detected is the same.

  However, the detection frequency FB is also equal to or higher than the predetermined frequency F0. Therefore, even if the detection time of sensor A is used as a time for interpolation between two positions detected by sensor B at two consecutive detection times, the obtained interpolation position is the path traveled by the person. Is accurately reflected. Therefore, as a first modification, in step 106, the normalization unit 64 can set the detection time of the sensor A as the normalization time, contrary to the above.

(Second modification)
In the above embodiment, two sensors are selected, the detection frequencies of the two sensors are examined, and appropriate interpolation is performed according to the frequencies of the two sensors. The technique of the present disclosure can check the detection frequency of a plurality of sensors greater than two and perform appropriate interpolation according to the frequency of a plurality of sensors greater than two. For example, consider three sensors A, B, and C.
First, when the detection frequencies FB and FC of the sensors B and C are lower than the predetermined frequency F0 and the detection frequency of the sensor A is equal to or higher than the predetermined frequency F0, the normalization unit 64 detects the object to be interpolated between the positions detected by the sensor A. The normalized time is the detection time of sensors B and C.
When all the detection frequencies of the sensors A to C are less than the predetermined frequency F0, the normalization unit 64 sets the normalization time common to the sensors A to C in each of the sensors A to C, and the detection frequency is the predetermined frequency. It determines so that it may become more than F0.

Here, the identity determination unit 66 can determine without contradiction by determining the determination in descending order of the detection frequency. First, the sensor having the highest detection frequency is selected, and it is determined whether or not the calculated distance is equal to or less than the threshold D0 for each of the sensor and the other sensors. The distance to any two sensors for which the calculated distance is less than or equal to the threshold D0 is given as a judgment that the calculated distance is less than or equal to the threshold D0, and the calculated distance is calculated as any one sensor having the calculated distance less than or equal to the threshold D0. The determination is made that the distance of any one sensor whose distance exceeds the threshold D0 exceeds the threshold D0. Hereinafter, for the sensor whose calculated distance exceeds the threshold D0, the highest sensor is selected and given a determination. By repeating this, it is possible to give a consistent judgment to all the sensors.
For example, consider the case where the detection frequency of the sensor A is the highest among the four sensors A, B, C, D, and E. First, it is determined whether or not the calculated distances D1 to D4 are equal to or less than a threshold value D0 for each of the sensor A and the remaining sensors B, C, and D. Further, for example, consider a case where D1 and D2 are equal to or less than the threshold value D0, and D3 and D4 exceed the threshold value D0. In that case, it is determined that the calculated distances for the sensor A and the sensor B, the sensor A and the sensor C, and the sensor B and the sensor C are not more than the threshold D0, respectively, , It is determined that the calculated distances of the sensors B and D, the sensors B and E, the sensors C and D, the sensors C and E exceed the threshold D0. Finally, it is determined whether or not the distance between the sensor D and the sensor E is equal to or less than the threshold value D0, and determination of all combinations is completed.

(Third Modification)
In the above embodiment, the identity determination unit 66 calculates the distance D1 using each position at each time t = 1.5 and t = 3.5 in FIG. 8G, and the calculated distance D1 is a threshold value. It is determined whether it is D0 or less. The identity determination unit 66 calculates the distance D1 using each position at time t = 1 to 10 in FIG. 9E, and determines whether the calculated distance D1 is equal to or less than the threshold value D0. In the technology of the present disclosure, the identity determination unit 66 calculates the distance D1 using the position at any one of the times t = 1.5 and t = 3.5 in FIG. It is possible to determine whether the distance D1 is equal to or less than the threshold value D0. Further, in the technique of the present disclosure, the identity determination unit 66 determines positions corresponding to the sensor A and the sensor B at at least one time, although not all of the times t = 1 to 10 in FIG. To calculate the distance D1. The identity determination unit 66 can determine whether or not the calculated distance D1 is equal to or less than a threshold value D0. For example, the distance D1 is calculated using a position corresponding to the sensor A and the sensor B at at least one of the times t = 3, 4, 7, and 8, and whether or not the calculated distance D1 is equal to or less than the threshold value D0. Can be judged. In the technology of the present disclosure, the identity determination unit 66 includes the times t = 1, 2, 5, 6, 9, 10 and at least one time, but not all of t = 3, 4, 7, and 8. The distance D1 is calculated using the positions at, and it is possible to determine whether the calculated distance D1 is equal to or less than the threshold value D0.

  Here, the identity determination unit 66 calculates the distance D1 using the position corresponding to the sensor A and the sensor B at one time among the times t = 1 to 10, and the calculated distance D1 is equal to or less than the threshold D0. It may be determined whether or not. In this case, for example, the possibility that the error can be reduced is larger than the case where only the detection time of the sensor B is interpolated between two positions detected by the sensor A at two consecutive detection times. can do.

(Fourth modification)
In the above embodiment, when it is determined that the positions detected by the sensors A and B are not positions corresponding to each other, the identity determination process is terminated. However, the technology of the present disclosure can output (store) the determination result that the positions detected by the sensors A and B are not positions on the corresponding paths to the integrated database 40M.

(Fifth modification)
In the above embodiment, as shown in FIG. 8B, two positions detected by the sensor A at two consecutive times, for example, two positions detected at time t = 1 and time t = 2, are interpolated. When the detection frequency of the sensor A is twice or more higher than the predetermined frequency F0, the sensor A is positioned at each time of time t = 1.0, t = 1.5, t = 2.0, and t = 2.5. Is detected. In this case, the detection time (t = 1.0, t = 1.0, t = 1.5) is not the detection time (t = 1.0, t = 1.5). Even if the two positions detected at t = 2.0) are interpolated, the same effect as in the above embodiment can be obtained. In the technique of the present disclosure, the normalization unit 64 can obtain an interpolation position between two positions detected at two detection times that are not continuous but have a frequency equal to or higher than a predetermined frequency.

(Sixth Modification)
In the above embodiment, when it is determined that the position detected by each of the sensor A and the sensor B is a position on the corresponding path, the determination result processing unit 68 in step 88 of FIG. The determination result process is executed. That is, first, it is assumed that the sensor A is the sensor 20 provided in the mobile phone 21A (see FIG. 1) carried by the person 21. Further, it is assumed that the sensor B is a sensor 22 provided in the taxi 23. The determination result processing unit 68 gives the label “movement by taxi” to the trajectory data transmitted by the sensor A. However, the technique of the present disclosure deletes the position trajectory data in one of the sensor A and the sensor B, for example, the sensor A determined to be a position on the corresponding path between the position of the sensor B. Than more. As a result, it is possible to effectively utilize the storage capacity of the secondary storage device by eliminating duplicated trajectory data.

  All documents, patent applications and technical standards mentioned in this specification are to the same extent as if each individual document, patent application and technical standard were specifically and individually stated to be incorporated by reference. Incorporated by reference in the book.

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

(Appendix 1)
A determination unit that determines whether or not the detection frequency of at least one detection unit among a plurality of detection units that repeatedly detect the position of each moving body at a predetermined frequency is greater than or equal to a predetermined frequency;
In the first case where the detection frequency of the at least one detection unit is determined to be greater than or equal to the predetermined frequency, one detection unit in which the detection frequency among the plurality of detection units is greater than or equal to the predetermined frequency is Between two positions detected at two detection times at which the frequency is equal to or higher than a predetermined frequency, a detection unit other than the one detection unit among the plurality of detection units detects the position and the two detection times In a second case where a first position corresponding to a reference detection time which is a time between them is determined, and the detection frequency of the at least one detection unit is not determined to be equal to or higher than a predetermined frequency, At least one common time that is common to each of the plurality of detection units and has a detection frequency equal to or higher than the predetermined frequency, between each of two positions detected between two consecutive detection times by each of the detection units. Corresponding A position determination unit for determining a second position of the number,
In the first case, based on the first position and the third position detected by the other detection unit at the reference detection time, in the second case, based on the plurality of second positions. A determination unit that determines whether the position detected by each of the plurality of detection units is a position on a path corresponding to each other;
A determination device including:

(Appendix 2)
The determination apparatus according to appendix 1, wherein the two detection times at which the frequency is equal to or higher than a predetermined frequency are two consecutive detection times at which one detection unit with the predetermined frequency or higher detects a position.

(Appendix 3)
In the second case, the position determination unit is common to each of the plurality of detection units during each detection time between two consecutive detection times at which each of the plurality of detection units detects a position, and At least one common time at which a detection frequency is equal to or higher than the predetermined frequency is determined, and each of the plurality of detection units is determined between the two positions detected between two consecutive detection times. The determination apparatus according to Supplementary Note 1 or Supplementary Note 2, wherein a plurality of second positions corresponding to at least one common time are determined.

(Appendix 4)
In the first case, the position determination unit may include the first detection unit between each of the two positions detected by the one detection unit in each of a plurality of sets in which the two detection times are set as one set. Determine the position,
In the first case, the determination unit corresponds to a position detected by each of the plurality of detection units based on the first position and the third position in each of the plurality of sets. The determination device according to any one of supplementary notes 1 to 3, which determines whether the position is on the route.

(Appendix 5)
In the second case, each of the plurality of sets in which the two detection times are one set, and each of the plurality of positions determined between the two detection times is the position determination unit. Determine the second position,
In the second case, based on the plurality of second positions in each of the plurality of sets, the determination unit is configured such that the positions detected by the plurality of detection units are positions on a path corresponding to each other. The determination apparatus according to any one of appendix 1 to appendix 4, which determines whether or not there is any.

(Appendix 6)
When the detection frequency of the at least one detection unit is determined to be equal to or higher than the predetermined frequency, when all the detection frequencies of the plurality of detection units are equal to or higher than the predetermined frequency, or all of the plurality of detection units However, the determination device according to any one of appendices 1 to 5, wherein the detection frequency of at least one detection unit may be equal to or higher than the predetermined frequency.

(Appendix 7)
When the detection frequency of all of the plurality of detection units is equal to or higher than the predetermined frequency, and the detection frequency of the at least one detection unit is determined to be equal to or higher than the predetermined frequency, the one detection unit is The determination apparatus according to any one of supplementary notes 1 to 6, which is a detection unit having the highest detection frequency among a plurality of detection units having the detection frequency equal to or higher than the predetermined frequency.

(Appendix 8)
On the computer,
Determining whether or not the detection frequency of at least one detection unit among a plurality of detection units that repeatedly detect the position of each moving body at a constant frequency is greater than or equal to a predetermined frequency;
In the first case where the detection frequency of the at least one detection unit is determined to be greater than or equal to the predetermined frequency, one detection unit in which the detection frequency among the plurality of detection units is greater than or equal to the predetermined frequency is Between two positions detected at two detection times at which the frequency is equal to or higher than a predetermined frequency, a detection unit other than the one detection unit among the plurality of detection units detects the position and the two detection times In a second case where a first position corresponding to a reference detection time which is a time between them is determined, and the detection frequency of the at least one detection unit is not determined to be equal to or higher than a predetermined frequency, At least one common time that is common to each of the plurality of detection units and has a detection frequency equal to or higher than the predetermined frequency, between two positions detected between two detection times that each of the detection units continues. Corresponding Determining a second position of the number,
In the first case, based on the first position and the third position detected by the other detection unit at the reference detection time, in the second case, based on the plurality of second positions. A determination program for executing a process including determining whether the positions detected by each of the plurality of detection units are positions on a path corresponding to each other.

(Appendix 9)
The determination program according to appendix 8, wherein the two detection times at which the frequency is equal to or higher than the predetermined frequency are two consecutive detection times at which one detection unit having the predetermined frequency or higher detects the position.

(Appendix 10)
When determining the second position, the computer is shared by each of the plurality of detection units during each detection time between two consecutive detection times at which each of the plurality of detection units has detected the position. And at least one common time at which the detection frequency is equal to or higher than the predetermined frequency, and each of the plurality of detection units is determined between each of two positions detected between two consecutive detection times. The determination program according to appendix 8 or appendix 9, wherein the determination is made to determine a plurality of second positions corresponding to the at least one common time.

(Appendix 11)
When the first position is determined, the computer has each of the two positions detected by the one detection unit in each of a plurality of sets in which the two detection times are set as one set. To determine the position of 1
At the time of the determination, the computer detects the position detected by each of the plurality of detection units based on the first position and the third position in each of the plurality of sets in the first case. The determination program according to any one of appendix 8 to appendix 10, wherein the determination program is configured to determine whether or not the positions are on positions corresponding to each other.

(Appendix 12)
When determining the second position, the computer, in each of a plurality of sets of the two detection times as a set, between each of the two positions detected between the two detection times, Determining a plurality of second positions;
At the time of the determination, the computer, in the second case, based on the plurality of second positions in each of the plurality of sets, the paths detected by each of the plurality of detection units correspond to each other. The determination program according to any one of appendix 8 to appendix 11, which determines whether the position is an upper position.

(Appendix 13)
When the detection frequency of the at least one detection unit is determined to be equal to or higher than the predetermined frequency, when all the detection frequencies of the plurality of detection units are equal to or higher than the predetermined frequency, or all of the plurality of detection units However, the determination program according to any one of appendices 8 to 12, wherein the detection frequency of at least one detection unit may be greater than or equal to the predetermined frequency.

(Appendix 14)
When the detection frequency of all of the plurality of detection units is equal to or higher than the predetermined frequency, and the detection frequency of the at least one detection unit is determined to be equal to or higher than the predetermined frequency, the one detection unit is The determination program according to any one of supplementary notes 8 to 13, which is a detection unit having the highest detection frequency among a plurality of detection units having the detection frequency equal to or higher than the predetermined frequency.

(Appendix 15)
On the computer,
Determining whether or not the detection frequency of at least one detection unit among a plurality of detection units that repeatedly detect the position of each moving body at a constant frequency is greater than or equal to a predetermined frequency;
In the first case where the detection frequency of the at least one detection unit is determined to be greater than or equal to the predetermined frequency, one detection unit in which the detection frequency among the plurality of detection units is greater than or equal to the predetermined frequency is Between two positions detected at two detection times at which the frequency is equal to or higher than a predetermined frequency, a detection unit other than the one detection unit among the plurality of detection units detects the position and the two detection times In a second case where a first position corresponding to a reference detection time which is a time between them is determined, and the detection frequency of the at least one detection unit is not determined to be equal to or higher than a predetermined frequency, At least one common time that is common to each of the plurality of detection units and has a detection frequency equal to or higher than the predetermined frequency, between each of two positions detected between two consecutive detection times by each of the detection units. Corresponding Determining a second position of the number,
In the first case, based on the first position and the third position detected by the other detection unit at the reference detection time, in the second case, based on the plurality of second positions. And determining whether or not the positions detected by each of the plurality of detection units are positions on a path corresponding to each other.

(Appendix 16)
The determination method according to supplementary note 15, wherein the two detection times at which the frequency is equal to or higher than a predetermined frequency are two consecutive detection times at which one detection unit having the predetermined frequency or higher detects a position.

(Appendix 17)
When determining the second position, the computer is shared by each of the plurality of detection units during each detection time between two consecutive detection times at which each of the plurality of detection units has detected the position. And at least one common time at which the detection frequency is equal to or higher than the predetermined frequency, and each of the plurality of detection units is determined between each of two positions detected between two consecutive detection times. The determination method according to supplementary note 15 or supplementary note 16, wherein the determination is made to determine a plurality of second positions corresponding to the at least one common time.

(Appendix 18)
When the first position is determined, the computer has each of the two positions detected by the one detection unit in each of a plurality of sets in which the two detection times are set as one set. To determine the position of 1
At the time of the determination, the computer detects the position detected by each of the plurality of detection units based on the first position and the third position in each of the plurality of sets in the first case. The determination method according to any one of supplementary note 15 to supplementary note 17, wherein the determination is made as to whether or not the positions are on positions corresponding to each other.

(Appendix 19)
When determining the second position, the computer, in each of a plurality of sets of the two detection times as a set, between each of the two positions detected between the two detection times, Determining a plurality of second positions;
At the time of the determination, the computer, in the second case, based on the plurality of second positions in each of the plurality of sets, the paths detected by each of the plurality of detection units correspond to each other. The determination method according to any one of appendix 15 to appendix 18, which determines whether the position is an upper position.

(Appendix 20)
When the detection frequency of the at least one detection unit is determined to be equal to or higher than the predetermined frequency, when all the detection frequencies of the plurality of detection units are equal to or higher than the predetermined frequency, or all of the plurality of detection units However, the determination method according to any one of supplementary notes 15 to 19, wherein the detection frequency of at least one detection unit may be greater than or equal to the predetermined frequency.

(Appendix 21)
When the detection frequency of all of the plurality of detection units is equal to or higher than the predetermined frequency, and the detection frequency of the at least one detection unit is determined to be equal to or higher than the predetermined frequency, the one detection unit is The determination method according to any one of supplementary notes 15 to 20, which is a detection unit having the highest detection frequency among a plurality of detection units having the detection frequency equal to or higher than the predetermined frequency.

(Appendix 22)
A storage medium for storing a determination program for causing a computer to execute the following processing,
The process is
Determining whether or not the detection frequency of at least one detection unit among a plurality of detection units that repeatedly detect the position of each moving body at a constant frequency is greater than or equal to a predetermined frequency;
In the first case where the detection frequency of the at least one detection unit is determined to be greater than or equal to the predetermined frequency, one detection unit in which the detection frequency among the plurality of detection units is greater than or equal to the predetermined frequency is Between two positions detected at two detection times at which the frequency is equal to or higher than a predetermined frequency, a detection unit other than the one detection unit among the plurality of detection units detects the position and the two detection times In a second case where a first position corresponding to a reference detection time which is a time between them is determined, and the detection frequency of the at least one detection unit is not determined to be equal to or higher than a predetermined frequency, At least one common time that is common to each of the plurality of detection units and has a detection frequency equal to or higher than the predetermined frequency, between each of two positions detected between two consecutive detection times by each of the detection units. Corresponding Determining a second position of the number,
In the first case, based on the first position and the third position detected by the other detection unit at the reference detection time, in the second case, based on the plurality of second positions. And determining whether the positions detected by each of the plurality of detection units are positions on a path corresponding to each other.

DESCRIPTION OF SYMBOLS 10 Trajectory data processing apparatus 20 Sensor 22 Sensor 24 Sensor 62 Data acquisition part 64 Normalization part 66 Identity determination part 68 Determination result processing part

Claims (4)

A determination unit that determines whether or not the detection frequency of at least one detection unit among a plurality of detection units that repeatedly detect the position of each moving body at a predetermined frequency is greater than or equal to a predetermined frequency;
In the first case where the detection frequency of the at least one detection unit is determined to be greater than or equal to the predetermined frequency, one detection unit in which the detection frequency among the plurality of detection units is greater than or equal to the predetermined frequency is Between two positions detected at two detection times at which the frequency is equal to or higher than a predetermined frequency, a detection unit other than the one detection unit among the plurality of detection units detects the position and the two detection times In a second case where a first position corresponding to a reference detection time which is a time between them is determined, and the detection frequency of the at least one detection unit is not determined to be equal to or higher than a predetermined frequency, At least one common time that is common to each of the plurality of detection units and has a detection frequency equal to or higher than the predetermined frequency, between each of two positions detected between two consecutive detection times by each of the detection units. Corresponding A position determination unit for determining a second position of the number,
In the first case, based on the first position and the third position detected by the other detection unit at the reference detection time, in the second case, based on the plurality of second positions. A determination unit that determines whether the position detected by each of the plurality of detection units is a position on a path corresponding to each other;
A determination device including: On the computer,
Determining whether or not the detection frequency of at least one detection unit among a plurality of detection units that repeatedly detect the position of each moving body at a constant frequency is greater than or equal to a predetermined frequency;
In the first case where the detection frequency of the at least one detection unit is determined to be greater than or equal to the predetermined frequency, one detection unit in which the detection frequency among the plurality of detection units is greater than or equal to the predetermined frequency is Between two positions detected at two detection times at which the frequency is equal to or higher than a predetermined frequency, a detection unit other than the one detection unit among the plurality of detection units detects the position and the two detection times In a second case where a first position corresponding to a reference detection time which is a time between them is determined, and the detection frequency of the at least one detection unit is not determined to be equal to or higher than a predetermined frequency, At least one common time that is common to each of the plurality of detection units and has a detection frequency equal to or higher than the predetermined frequency, between each of two positions detected between two consecutive detection times by each of the detection units. Corresponding Determining a second position of the number,
In the first case, based on the first position and the third position detected by the other detection unit at the reference detection time, in the second case, based on the plurality of second positions. A determination program for executing a process including determining whether the positions detected by each of the plurality of detection units are positions on a path corresponding to each other. On the computer,
Determining whether or not the detection frequency of at least one detection unit among a plurality of detection units that repeatedly detect the position of each moving body at a constant frequency is greater than or equal to a predetermined frequency;
In the first case where the detection frequency of the at least one detection unit is determined to be greater than or equal to the predetermined frequency, one detection unit in which the detection frequency among the plurality of detection units is greater than or equal to the predetermined frequency is Between two positions detected at two detection times at which the frequency is equal to or higher than a predetermined frequency, a detection unit other than the one detection unit among the plurality of detection units detects the position and the two detection times In a second case where a first position corresponding to a reference detection time which is a time between them is determined, and the detection frequency of the at least one detection unit is not determined to be equal to or higher than a predetermined frequency, At least one common time that is common to each of the plurality of detection units and has a detection frequency equal to or higher than the predetermined frequency, between each of two positions detected between two consecutive detection times by each of the detection units. Corresponding Determining a second position of the number,
In the first case, based on the first position and the third position detected by the other detection unit at the reference detection time, in the second case, based on the plurality of second positions. And determining whether the positions detected by each of the plurality of detection units are positions corresponding to each other.   When the detection frequency of the at least one detection unit is determined to be equal to or higher than the predetermined frequency because the detection frequency of the plurality of detection units is equal to or higher than the predetermined frequency, the one detection unit is The determination method according to claim 3, wherein the detection unit has the highest detection frequency among the plurality of detection units.

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