Information processing apparatus

Abstract

To easily determine whether a terminal exists in the same moving body.SOLUTION: An information processing device 100 includes an acquisition part 121 for acquiring information on a traveling track from a plurality of terminals, and a determination part 124 for determining that any terminals of the plurality of terminals are moved by the same moving body on the basis of the information on the traveling track acquired by the acquisition part 121 and information on another traveling track.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information processing device. [Background technology]

[0002] Conventionally, there is a technology that determines whether a mobile terminal is present in a vehicle by determining whether the mobile terminal's moving speed is below a predetermined value and whether the mobile terminal is present within a predetermined range of the vehicle from location information received from the mobile terminal at different times (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2010-169570 [Non-patent literature]

[0004] [Non-Patent Document 1] Indexing vehicle trajectories under network constraints using string indexing (http: / / db-event.jpn.org / deim2016 / papers / 39.pdf) Summary of the Invention [Problem to be solved by the invention]

[0005] However, in the conventional technology, it is not possible to easily determine whether terminals are present in the same moving body. For example, in the conventional technology, in order to determine whether a terminal is present in a vehicle, it is necessary to constantly keep track of information about all terminals, which results in a huge processing load. Furthermore, this also causes problems such as processing capacity and cost. Thus, the above-mentioned problems are cited as examples of the problems that the present invention aims to solve. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the object, the invention described in claim 1 is characterized by having an acquisition unit that acquires driving trajectory information from a plurality of terminals, and a determination unit that determines that any of the plurality of terminals have moved by the same moving body based on the driving trajectory information acquired by the acquisition unit and other driving trajectory information. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram showing the configuration of an information processing device system according to an embodiment. [Figure 2] FIG. 2 is a diagram showing the configuration of the information processing apparatus according to the embodiment. [Figure 3] FIG. 3 is a diagram illustrating an outline of processing by the information processing device according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an outline of processing by the information processing device according to the embodiment. [Figure 5] FIG. 5 is a flowchart illustrating an example of processing by the information processing device according to the embodiment. [Figure 6] FIG. 6 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, a mode for carrying out the present invention (hereinafter referred to as an embodiment) will be described with reference to the drawings. Note that the present invention is not limited to the embodiment described below. Furthermore, in the description of the drawings, the same parts are given the same reference numerals.

[0009] [1. Information Processing System Configuration] First, the configuration of an information processing system according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing the configuration of an information processing system according to an embodiment. Fig. 1 shows an information processing system 1 as an example of the information processing system according to an embodiment.

[0010] 1, the information processing system 1 may include an in-vehicle device 10 and an information processing device 100. The in-vehicle device 10 and the information processing device 100 are connected to each other via a network N so as to be able to communicate with each other via a wired or wireless connection. The information processing system 1 shown in FIG. 1 may include any number of in-vehicle devices 10 and any number of information processing devices 100.

[0011] The in-vehicle device 10 may be a dedicated sensor device built into or externally attached to the vehicle VEx, or may be a device such as a recording device (drive recorder) installed in the vehicle VEx for crime prevention or to combat aggressive driving.

[0012] The in-vehicle device 10 may also be configured with a sensor device and a notification device. As an example, the in-vehicle device 10 may be a composite device in which a sensor device and a notification device that are independent of each other are connected to each other so that they can communicate with each other. As another example, the in-vehicle device 10 may be a single device that has a sensor function and a notification function.

[0013] Furthermore, a user can connect a predetermined sensor to a portable terminal device (for example, a smartphone, tablet terminal, notebook PC, desktop PC, PDA, etc.) that they use on a daily basis and install a predetermined application, thereby substituting the portable terminal device as the in-vehicle device 10. For example, a portable terminal device that is equipped with a predetermined sensor or to which a predetermined sensor is connected can be understood as the in-vehicle device 10 referred to here. When the portable terminal device is used as the in-vehicle device 10, it is installed, for example, on the dashboard of the vehicle VEx while driving.

[0014] The in-vehicle device 10 may also include various sensors, such as a Global Navigation Satellite System (GNSS) sensor, a Global Positioning System (GPS), an acceleration sensor, a gyro sensor, a camera, and an air pressure sensor.

[0015] The information processing device 100 may acquire various types of data based on sensor information detected by these sensors (for example, by analyzing the sensor information). For example, the information processing device 100 acquires position information from a GNSS sensor. Furthermore, for example, the information processing device 100 acquires angular velocity from a gyro sensor. Furthermore, for example, the information processing device 100 acquires video data captured from inside the vehicle VEx by a camera of the outside. Note that the information processing device 100 may acquire sensor information detected not only by sensors provided in the in-vehicle device 10 but also by sensors provided in the vehicle VEx itself.

[0016] The information processing device 100 is a device that determines whether terminals have traveled by the same moving object. For example, the information processing device 100 determines that any of a plurality of terminals have traveled by the same moving object based on the correspondence between information on a stop time and a stop place included in information on a certain travel trajectory and information on a stop time and a stop place included in information on another travel trajectory.

[0017] Here, if the in-vehicle device 10 is an edge computer that performs edge processing near the user, the information processing device 100 may be, for example, a cloud computer that performs processing on the cloud side. In other words, the information processing device 100 may be a server device.

[0018] Furthermore, in the following embodiment, an example is shown in which information processing according to the embodiment is realized in the information processing system 1 by transmitting and receiving information between the in-vehicle device 10 and the information processing device 100. However, the information processing according to the embodiment may be realized only on the edge side, i.e., by the in-vehicle device 10. In this case, the in-vehicle device 10 may be configured to behave like the information processing device 100 by, for example, an information processing program according to the embodiment.

[0019] 2. Configuration of Information Processing Device Next, an information processing device 100 according to an embodiment will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration of the information processing device 100 according to an embodiment. As shown in Fig. 2, the information processing device 100 has a communication unit 110, a storage unit 130, and a control unit 120. Each unit of the information processing device 100 will be described below.

[0020] The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the in-vehicle device 10, for example.

[0021] The storage unit 130 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 130 stores information such as travel path information, threshold values, and other information necessary for determination.

[0022] Here, the information on the travel trajectory includes information such as terminal information used to record the travel trajectory, travel ID, stop number, stop time, stop location, number of stops, stop duration, and travel distance. Furthermore, the information extracted as the stop time may be the elapsed time from the previous stop location. Note that the information stored in the storage unit 130 is not limited to the above examples.

[0023] The control unit 120 is realized using a CPU (Central Processing Unit), an NP (Network Processor), an FPGA (Field Programmable Gate Array), or the like, and executes a processing program stored in a memory. As shown in Fig. 2, the control unit 120 has an acquisition unit 121, a calculation unit 122, a threshold setting unit 123, and a determination unit 124. Each unit of the control unit 120 will be described below.

[0024] The acquisition unit 121 acquires information on travel trajectories from multiple terminals. For example, the acquisition unit 121 acquires information on stop times and stop locations from the multiple terminals. Also, for example, the acquisition unit 121 acquires information on terminal information, travel IDs, stop numbers, stop times, stop locations, the number of stops, stop durations, and travel distances from the multiple terminals.

[0025] The acquisition unit 121 acquires, from the information on the travel locus, the time that has elapsed since the vehicle stopped as the stop time. For example, the acquisition unit 121 acquires information on the stop time (the time that has elapsed since the vehicle stopped) and the stop location.

[0026] The travel locus information acquired by the acquisition unit 121 may be information recorded by a predetermined terminal for any period according to the purpose.

[0027] The calculation unit 122 calculates the number of times that information about a stop time and a stop place included in the information about the travel trajectory acquired by the acquisition unit 121 corresponds to information about a stop time and a stop place included in information about another travel trajectory. For example, the calculation unit 122 calculates the number of times that information about a stop time and a stop place included in the information about the travel trajectory acquired by the acquisition unit 121 matches information about a stop time and a stop place included in information about another travel trajectory. Details of the processing by the calculation unit 122 will be described in [3. Overview of Processing].

[0028] The threshold setting unit 123 sets a threshold for the number of times calculated by the calculation unit 122 based on the information on the travel locus acquired by the acquisition unit 121. For example, the threshold setting unit 123 sets the threshold according to the length of the travel distance among the information on the travel locus acquired by the acquisition unit 121. Details of the processing by the threshold setting unit 123 will be described in [3. Overview of Processing].

[0029] Furthermore, for example, the threshold setting unit 123 sets a threshold in accordance with the length of a stop time among the information on the travel path acquired by the acquisition unit 121.

[0030] Furthermore, for example, the threshold setting unit 123 sets a threshold in accordance with the number of stops among the information on the travel path acquired by the acquisition unit 121.

[0031] The determination unit 124 determines that any of the multiple terminals were traveling by the same moving object based on the correspondence between the information on the stop time and stop location included in the information on the travel trajectory acquired by the acquisition unit 121 and the information on the stop time and stop location included in the information on the other travel trajectory.

[0032] For example, when the number of times calculated by the calculation unit 122 exceeds a predetermined threshold, the determination unit 124 determines that any of the multiple terminals have traveled together by the same moving object. For example, the determination unit 124 determines that any of the multiple terminals have traveled together by the same moving object because the number of times calculated by the calculation unit 122 is "20" exceeds the threshold "15."

[0033] Also, for example, since the number of times "10" calculated by the calculation unit 122 does not exceed the threshold value "15", the determination unit 124 determines that any of the multiple terminals have moved by different moving bodies.

[0034] [3. Processing Overview] Next, an overview of the processing performed by the information processing device 100 will be described with reference to Fig. 3 and Fig. 4. Fig. 3 and Fig. 4 are diagrams showing an overview of the processing performed by the information processing device 100 according to the embodiment. Here, the line portions in Fig. 3(1) and Fig. 4(1) indicate the travel route, and the circle portions indicate stops. Also, Fig. 3(2) and Fig. 4(2) are display examples of travel trajectory information stored in the storage unit 130.

[0035] First, the acquisition unit 121 acquires information on the stop time, the stop place, and the travel ID included in the travel locus information. In the example of Fig. 3, the acquisition unit 121 acquires information on the stop time, the stop place, and the travel ID (Fig. 3(2)) included in the travel locus information (Fig. 3(1)).

[0036] Next, the calculation unit 122 calculates the number of times that the information on the stop time and stop location included in the information on the driving trajectory of driving ID "1" acquired by the acquisition unit 121 matches the information on the stop time and stop location included in the information on the driving trajectory of driving ID "2".

[0037] Here, a match includes not only a perfect match but also a partial match. In other words, a match may be determined even if the spatiotemporal match between multiple trajectories is partial. For example, a match may be determined even if the stop times and stop locations of one travel trajectory and another travel trajectory partially match.

[0038] Here, the match between the stop times and the stop locations may be determined with a certain degree of latitude. For example, if the difference between the stop times is within a predetermined range, the stop times may be determined to match. Specifically, if the difference between the stop times is within 5 seconds, the stop times may be determined to match.

[0039] Furthermore, for example, if the difference between the stopping locations is within a predetermined range, the stopping locations may be determined to match. Specifically, if the difference between the stopping locations is within 2.5 m, the stopping locations may be determined to match.

[0040] Furthermore, for example, the map may be divided into meshes of a predetermined unit, and the stopping locations may be determined to match if they are included in the same mesh. Specifically, the map may be divided into meshes of 2.5 m units, and the stopping locations may be determined to match if they are included in the same mesh. Note that the above-mentioned predetermined range and predetermined unit may be any period, distance, coordinates, etc., depending on the purpose.

[0041] In other words, when the information on a driving trajectory partially overlaps with the information on another driving trajectory, as shown in FIG. 4(1), the calculation unit 122 calculates the number of times that the information on the stop time and stop location included in the information on a certain driving trajectory acquired by the acquisition unit 121 matches the information on the stop time and stop location included in the information on the other driving trajectory, as shown in FIG. 4(2).

[0042] In the example of Figure 4, the start point and end point of travel ID "1" do not match the start point and end point of travel ID "2", but since the routes along the way overlap, it is calculated that the number of times that the information on the stop time and stop location included in the information on the travel trajectory of travel ID "1" acquired by the acquisition unit 121 matches the information on the stop time and stop location included in the information on the travel trajectory of travel ID "2" is seven.

[0043] This makes it possible to determine whether stop times and stop locations match even when routes partially overlap, for example.In other words, even when a person on one vehicle changes to another vehicle along the way, or when a vehicle picks up someone along the way, or when two vehicles leave or merge along the route, it is possible to perform a match determination and determine whether or not they were passengers.

[0044] Next, the threshold setting unit 123 sets a threshold based on the information on the travel locus. For example, the threshold setting unit 123 sets a threshold that increases as the travel distance increases among the information on the travel locus acquired by the acquisition unit 121. The threshold determined by the threshold setting unit 123 may be two thresholds depending on whether the travel distance is equal to or greater than a predetermined value, or multiple thresholds may be set in stages according to the travel distance.

[0045] Furthermore, for example, the threshold setting unit 123 can set a threshold according to the length of a stop time in the information on the travel locus acquired by the acquisition unit 121. For example, the threshold setting unit 123 sets a threshold such that the longer the stop time in the information on the travel locus acquired by the acquisition unit 121, the larger the threshold.

[0046] Furthermore, for example, the threshold setting unit 123 can set a threshold according to the number of stops among the information on the travel locus acquired by the acquisition unit 121. For example, the threshold setting unit 123 sets a threshold such that the greater the number of stops among the information on the travel locus acquired by the acquisition unit 121, the larger the threshold value.

[0047] In addition, when routes partially overlap, the threshold setting unit 123 may set the threshold as in the above example using information such as the travel distance, the length of stop times, the number of stops, etc. on the overlapping routes. For example, the threshold setting unit 123 sets the threshold so that the longer the travel distance on the overlapping routes among the information on the travel locus acquired by the acquisition unit 121, the larger the threshold.

[0048] Furthermore, for example, the threshold setting unit 123 sets a threshold value that increases as the stopping time on overlapping routes increases among the information on the travel locus acquired by the acquisition unit 121. Furthermore, for example, the threshold setting unit 123 sets a threshold value that increases as the number of stopping times on overlapping routes increases among the information on the travel locus acquired by the acquisition unit 121.

[0049] Here, the threshold setting unit 123 may set the threshold by using a DB that stores the relationship between the value of each piece of information included in the travel locus information and the threshold. Furthermore, the threshold set by the threshold setting unit 123 may be a predetermined value, or a predetermined ratio or proportion. For example, the threshold setting unit 123 sets the threshold to a value obtained by multiplying the number of stops acquired by the acquisition unit 121 by 0.8.

[0050] Then, if the number of times calculated by the calculation unit 122 exceeds a predetermined threshold, the determination unit 124 determines that the terminal that recorded the information on the driving trajectory of driving ID "1" and the terminal that recorded the information on the driving trajectory of driving ID "2" were traveling by the same moving object.

[0051] In the example of Figure 3, where the majority of the stop times and stop locations match, the determination unit 124 determines that the terminal that recorded the information on the travel trajectory of travel ID "1" and the terminal that recorded the information on the travel trajectory of travel ID "2" were traveling by the same moving object, because the number of times calculated by the calculation unit 122 exceeds a predetermined threshold.

[0052] On the other hand, in the example of Figure 4, where the start and end points of each driving trajectory do not match but the stop times and stop locations mostly match, the determination unit 124 determines that the terminal that recorded the information on the driving trajectory with driving ID "1" and the terminal that recorded the information on the driving trajectory with driving ID "2" were traveling by the same moving object because the number of times calculated by the calculation unit 122 exceeds a predetermined threshold.

[0053] The determination process can be performed at any timing by the determination unit 124. For example, the determination unit 124 performs the determination process when new travel locus information is registered.

[0054] [4. Flowchart] Next, processing by the information processing device 100 configured as described above will be described with reference to the flowchart in Fig. 5. The flowchart in Fig. 5 is mainly executed by the control unit 120. This flowchart can be configured as a program executed by the CPU of the control unit 120 to form an information processing program. Note that the following steps S101 to S106 can also be executed in a different order. Also, some of the following steps S101 to S106 may be omitted.

[0055] First, the acquisition unit 121 acquires information on travel loci from a plurality of terminals (step S101).

[0056] Next, the calculation unit 122 calculates the number of times that the information on the stop time and stop location included in the information on the travel trajectory acquired by the acquisition unit 121 corresponds to the information on the stop time and stop location included in other information on the travel trajectory (step S102).

[0057] Next, the threshold setting unit 123 sets a threshold for the number of times calculated by the calculation unit 122 based on the information on the travel path acquired by the acquisition unit 121 (step S103).

[0058] Next, the determination unit 124 determines whether the number of times calculated by the calculation unit 122 exceeds a threshold value (step S104). At this time, if the determination unit 124 determines that the number of times calculated by the calculation unit 122 exceeds the threshold value (step S104 "YES"), the determination unit 124 determines that any two or more terminals among the plurality of terminals have moved by the same moving object (step S105).

[0059] On the other hand, if the judgment unit 124 determines that the number of times calculated by the calculation unit 122 does not exceed the threshold value (step S104 "NO"), the judgment unit 125 determines that any of the multiple terminals have moved by different moving bodies (step S106).

[0060] [5. Effects] The information processing device 100 according to the embodiment has an acquisition unit 121 that acquires driving trajectory information from a plurality of terminals, and a determination unit 124 that determines that any of the plurality of terminals have been traveling by the same moving object based on the correspondence between the information on the stop time and stop location included in the driving trajectory information acquired by the acquisition unit 121 and the information on the stop time and stop location included in the other driving trajectory information.

[0061] This allows the information processing device 100 to easily determine whether the terminals were located in the same moving body by using the correspondence between the stop time and stop location included in the information on a certain driving trajectory and the stop time and stop location included in the information on another driving trajectory.

[0062] The information processing device 100 according to the embodiment further includes a calculation unit 122 that calculates the number of times that the information on the stop time and stop location included in the driving trajectory information acquired by the acquisition unit 121 corresponds to the information on the stop time and stop location included in other driving trajectory information, and the determination unit 124 determines that any of the multiple terminals were traveling by the same moving object when the number of times calculated by the calculation unit 122 exceeds a predetermined threshold.

[0063] This allows the information processing device 100 to easily determine whether the terminals were present in the same moving body by determining whether the number of times that the stop times and stop locations included in information on a certain driving trajectory correspond to the stop times and stop locations included in information on another driving trajectory exceeds a threshold value.

[0064] The information processing device 100 according to the embodiment further includes a threshold setting unit 123 that sets a threshold for the number of times calculated by the calculation unit 122 based on the information on the travel path acquired by the acquisition unit 121 .

[0065] This allows the information processing device 100 to easily determine whether the terminals were present in the same moving body by determining whether the number of times that the stop times and stop locations included in information on a certain driving trajectory correspond to the stop times and stop locations included in information on another driving trajectory exceeds a threshold value.

[0066] The threshold setting unit 123 of the information processing device 100 according to the embodiment sets a threshold in accordance with the length of the travel distance among the information on the travel locus acquired by the acquisition unit 121.

[0067] This allows the information processing device 100 to easily determine whether the terminals were present in the same moving body by determining whether the number of times that the stop times and stop locations included in the information on a certain driving trajectory correspond to the stop times and stop locations included in the information on another driving trajectory exceeds a threshold value according to the length of the driving distance.

[0068] The threshold setting unit 123 of the information processing device 100 according to the embodiment sets a threshold in accordance with the length of the stop time among the information on the travel path acquired by the acquisition unit 121.

[0069] This allows the information processing device 100 to easily determine whether the terminals were present in the same moving body by determining whether the number of times that the stop times and stop locations included in information on a certain driving trajectory correspond to the stop times and stop locations included in information on another driving trajectory exceeds a threshold value according to the length of the stop time.

[0070] The threshold setting unit 123 of the information processing device 100 according to the embodiment sets a threshold in accordance with the number of stops among the information on the travel path acquired by the acquisition unit 121.

[0071] This allows the information processing device 100 to easily determine whether the terminals were present in the same moving body by determining whether the number of times that the stop times and stop locations included in information on a certain driving trajectory correspond to the stop times and stop locations included in information on another driving trajectory exceeds a threshold value corresponding to the number of stops.

[0072] The acquisition unit 121 of the information processing device 100 according to the embodiment acquires, from the information on the travel path, the time elapsed since the vehicle stopped as the stop time.

[0073] As a result, the information processing device 100 can easily determine whether the terminals were in the same moving body by using the correspondence between the stop time (time elapsed since stopping) and stop location included in the information of a certain travel path and the stop time (time elapsed since stopping) and stop location included in the information of another travel path. Also, by using the time elapsed since the previous stop location, it is possible to determine whether the terminals match even if the system time settings of each terminal are different.

[0074] [6. Hardware Configuration] The information processing device 100 according to the embodiment described above is realized, for example, by a computer 1000 configured as shown in Fig. 6. Fig. 6 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 100. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0075] The CPU 1100 operates and controls each unit based on programs stored in the ROM 1300 or the HDD 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, programs that depend on the hardware of the computer 1000, and the like.

[0076] The HDD 1400 stores programs executed by the CPU 1100 and data used by the programs. The communication interface 1500 receives data from other devices via a predetermined communication network and sends the data to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the predetermined communication network.

[0077] The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse, via the input / output interface 1600. The CPU 1100 acquires data from the input devices via the input / output interface 1600. The CPU 1100 also outputs generated data to the output devices via the input / output interface 1600.

[0078] Media interface 1700 reads a program or data stored in recording medium 1800 and provides it to CPU 1100 via RAM 1200. CPU 1100 loads the program or data from recording medium 1800 onto RAM 1200 via media interface 1700 and executes the loaded program. Recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0079] For example, when the computer 1000 functions as the information processing device 100 according to the embodiment, the CPU 1100 of the computer 1000 executes programs loaded onto the RAM 1200, thereby realizing the functions of the control unit 120. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via a predetermined communication network.

[0080] [7. Other] Although one example of an embodiment of the present invention has been described above, the present invention is not limited to the above example. In other words, a person skilled in the art can implement various modifications in accordance with conventionally known knowledge without departing from the gist of the present invention. As long as such modifications still include the information processing device of the present invention, they are of course included in the scope of the present invention. [Explanation of symbols]

[0081] 1. Information Processing Systems 10 Onboard equipment 100 Information processing device 110 Communications Department 120 control section 121 Acquisition Department 122 Calculation Unit 123 Threshold setting unit 124 Judgment section 130 Storage section

Claims

[Claim 1] an acquisition unit that acquires information on driving trajectories from a plurality of terminals; a determination unit that determines that any terminals among the plurality of terminals have traveled by the same moving body based on the information on the travel locus acquired by the acquisition unit and information on other travel loci; An information processing device comprising:

Images