Information Processing Method, Information Processing Apparatus, and Information Processing Program

Abstract

This server device acquires, from a plurality of mobilities, each of position information indicating the position of the mobility, other-mobility identification information that the mobility has received from other mobilities via short-range wireless communication, and stop information indicating whether the mobility has stopped. The server device also classifies two or more mobilities that have stopped and that have mutually received identification information, among the plurality of mobilities, into the same mobility group. The server device moreover analyzes, on the basis of the position information for the two or more mobilities classified into the mobility group, stop locations at which the mobilities have stopped.

Description

Technical Field

[0001] The present disclosure relates to a technique for identifying a position where a plurality of mobilities are stopped.

Background Art

[0002] Conventionally, a Global Positioning System (GPS) has been used to measure the position of a mobility. A GPS receiver included in the mobility measures the current position by receiving GPS signals transmitted from GPS satellites. Therefore, the measurement accuracy of the position using GPS depends on the radio wave condition. For example, the radio wave condition is poor under a building, and the measurement accuracy of the position by GPS decreases.

[0003] For example, in Patent Document 1, a beacon device is installed in a waiting area and transmits a signal including a beacon device ID for identifying the beacon device to the surroundings. When a vehicle enters the waiting area, a communication terminal that moves with the vehicle receives the signal from the beacon device and transmits the beacon device ID included in the received signal and a communication terminal ID for identifying the communication terminal to a server. The server detects that a vehicle equipped with a communication terminal identified by the communication terminal ID has entered the waiting area specified by the beacon device ID by receiving the beacon device ID and the communication terminal ID.

[0004] Also, for example, in Patent Document 2, when a positioning device cannot receive four GPS signals from GPS satellites, the positioning device measures the position of the positioning device using GPS signals from a mobile terminal in a line-of-sight environment as seen from the positioning device and obtains position information.

[0005] However, in the above conventional technology, it is necessary to install equipment for accurately identifying a stop location where a mobility is stopped near the stop location, and further improvement has been required.

Prior Art Documents

Patent Documents

[0006] [Patent Document 1] Japanese Patent Application Laid-Open No. 2020-24644 [Patent Document 2] Japanese Patent Application Laid-Open No. 2019-32310 [Summary of the Invention]

[0007] The present disclosure has been made to solve the above problems, and an object thereof is to provide a technique capable of highly accurately specifying a stop location where two or more mobilities are stopped.

[0008] An information processing method according to an aspect of the present disclosure includes a computer obtaining, from a plurality of mobilities, position information indicating the position of a mobility, identification information of the other mobility received by the mobility from another mobility by short-range wireless communication, and stop information indicating whether the mobility is stopped. Among the plurality of mobilities, two or more mobilities that are stopped and have received the identification information from each other are classified into the same mobility group, and based on the position information of the two or more mobilities classified into the mobility group, a stop location where the mobility group is stopped is specified.

[0009] According to the present disclosure, it is possible to highly accurately specify a stop location where two or more mobilities are stopped. [Brief Description of the Drawings]

[0010]

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Embodiments for Carrying Out the Invention

[0011] (Knowledge underlying the present disclosure) In recent years, services for sharing bicycles among multiple users have been provided. In such services, bicycles are rented out from pre-provided parking locations and returned to the parking locations. The bicycles are equipped with GPS receivers, and the positions of the bicycles are measured using GPS signals received by the GPS receivers. A server that manages the bicycles manages the positions of the bicycles using the position information received from the bicycles.

[0012] Here, when the parking location is installed in a place with poor radio wave conditions such as under a building, the measurement accuracy of the position of the bicycle parked at the parking location decreases. In this case, it is difficult for the server to confirm whether the bicycle has been correctly returned to the predetermined parking location.

[0013] In the technology of Patent Document 1 described above, it is possible to confirm that a vehicle has entered a waiting area by a beacon device. However, when this technology is used, it is necessary to install a beacon device at each parking location and to manage the timing of replacing the battery of the beacon device.

[0014] In addition, in the technology of Patent Document 2 described above, the positioning device performs positioning using GPS signals received from other mobile terminals as pseudo-satellites. However, in this case, it is necessary to install equipment on the ground, which incurs costs for equipment installation.

[0015] In order to solve the above problems, an information processing method according to an aspect of the present disclosure includes a computer obtaining, from a plurality of mobilities, position information indicating the position of the mobility, identification information of the other mobility received by the mobility from another mobility via short-range wireless communication, and stop information indicating whether the mobility is stopped. Among the plurality of mobilities, two or more mobilities that are stopped and have received the identification information from each other are classified into the same mobility group, and based on the position information of the two or more mobilities classified into the mobility group, a stop location where the mobility group is stopped is specified.

[0016] According to this configuration, two or more mobilities that can communicate with each other via short-range wireless communication are presumed to be present at the same location and can be classified into the same mobility group. Therefore, even if the radio wave condition at the stop location is poor and there is variation in the position information of two or more mobilities stopped at the stop location, based on the position information of two or more mobilities that have received the identification information from each other via short-range wireless communication and are classified into the same mobility group, the stop location where the mobility group is stopped is specified. Therefore, the stop location where two or more mobilities are stopped can be specified with high accuracy.

[0017] In the above information processing method, in specifying the stop location, the median value of the coordinates of the two or more mobilities is calculated, the moving average within a predetermined period of the calculated median value is calculated, and a stop probability indicating the probability that the mobility group is stopped at the stop location is calculated according to the distance between the calculated moving average value and the coordinates of the stop location closest to the moving average value. When the stop probability is equal to or greater than a threshold value, the stop location closest to the moving average value may be specified as the stop location where the mobility group is stopped.

[0018] According to this configuration, the closer the distance between the moving average value of the median of the coordinates of two or more mobilities within a predetermined period and the coordinates of the stop location closest to the moving average value is, the higher the stop probability indicating the probability that the mobility group stops at the stop location becomes. Therefore, by comparing the stop probability with a threshold value, it is possible to easily identify the stop location where two or more mobilities have stopped.

[0019] Further, in the above information processing method, further, based on the plurality of position information of one mobility among the plurality of mobilities that is stopped, has not received the identification information of the other mobilities, and has variations in the plurality of position information acquired at a predetermined time interval, the stop location where the one mobility has stopped may be identified.

[0020] According to this configuration, even if the radio wave condition at the stop location is poor and there are variations in the plurality of position information of one mobility stopped at the stop location acquired at a predetermined time interval, based on the plurality of position information of the one mobility, the stop location where the one mobility has stopped is identified. Therefore, it is possible to identify the stop location where the one mobility has stopped with high accuracy.

[0021] Further, in the above information processing method, in identifying the stop location, calculate the median of the plurality of coordinates of the one mobility acquired at a predetermined time interval, calculate the moving average within a predetermined period of the calculated median, and according to the distance between the calculated moving average value and the coordinates of the stop location closest to the moving average value, calculate a stop probability indicating the probability that the one mobility has stopped at the stop location. When the stop probability is equal to or greater than a threshold value, the stop location closest to the moving average value may be identified as the stop location where the one mobility has stopped.

[0022] According to this configuration, the closer the distance between the moving average value within a predetermined period of the median value of a plurality of coordinates acquired at a predetermined time interval of mobility 1 and the coordinates of the stop location closest to the moving average value, the higher the stop probability indicating the probability that mobility 1 has stopped at the stop location. Therefore, by comparing the stop probability with a threshold value, the stop location where mobility 1 has stopped can be easily specified.

[0023] Also, in the above information processing method, further, when the identification information of any one of the two or more mobilities is acquired from a new mobility not classified into the mobility group, the new mobility is classified into the same mobility group as the two or more mobilities, and further, the stop location where the mobility group has stopped may be specified as the stop location where the new mobility has stopped.

[0024] According to this configuration, when a new mobility stops within a distance that can communicate with the mobility group by short-range wireless communication, the stop location where the mobility group has stopped is specified as the stop location where the new mobility has stopped, so the stop location where the new mobility has stopped can be easily specified.

[0025] Also, in the above information processing method, further, calculate the magnitude of the variation of the position information of the two or more mobilities classified into the mobility group, and in specifying the stop location, if the calculated magnitude of the variation is greater than a threshold value, the stop location where the mobility group has stopped may be specified based on the position information of the two or more mobilities classified into the mobility group.

[0026] That is, the fact that the variation in the position information of two or more mobilities classified into a mobility group is equal to or less than a threshold means that the positions of the two or more mobilities do not vary and that the respective position information is correctly measured. Therefore, when the variation in the position information of two or more mobilities is equal to or less than the threshold, no processing is performed to identify the stop location where the mobility group has stopped. Only when the variation in the position information of two or more mobilities is greater than the threshold, it can be determined that the radio wave condition around the stop location is poor, and processing can be performed to identify the stop location where the mobility group has stopped. As a result, the processing load on the computer can be reduced.

[0027] Further, in the above information processing method, the variation in the distance between the two or more mobilities classified into the mobility group is calculated. In identifying the stop location, when the calculated variation is greater than a threshold, the stop location where the mobility group has stopped may be identified based on the position information of the two or more mobilities classified into the mobility group.

[0028] That is, the fact that the variation in the distance between two or more mobilities classified into a mobility group is equal to or less than a threshold means that the positions of the two or more mobilities do not vary and that the respective position information is correctly measured. Therefore, when the variation in the distance between two or more mobilities is equal to or less than the threshold, no processing is performed to identify the stop location where the mobility group has stopped. Only when the variation in the distance between two or more mobilities is greater than the threshold, processing can be performed to identify the stop location where the mobility group has stopped. As a result, the processing load on the computer can be reduced.

[0029] Further, in the above information processing method, the magnitude of the variation in the distance between each of the two or more mobilities classified into the mobility group and the stopping location existing around the two or more mobilities is calculated. In identifying the stopping location, when the calculated magnitude of the variation is greater than a threshold value, the stopping location where the mobility group has stopped may be identified based on the position information of the two or more mobilities classified into the mobility group.

[0030] That is, the fact that the magnitude of the variation in the distance between each of the two or more mobilities classified into the mobility group and the stopping location existing around the two or more mobilities is equal to or less than the threshold value means that the positions of the two or more mobilities do not vary and the respective position information has been measured correctly. Therefore, when the magnitude of the variation in the distance between each of the two or more mobilities classified into the mobility group and the stopping location existing around the two or more mobilities is equal to or less than the threshold value, the process for identifying the stopping location where the mobility group has stopped is not performed, and the process for identifying the stopping location where the mobility group has stopped can be performed only when the magnitude of the variation in the distance between each of the two or more mobilities classified into the mobility group and the stopping location existing around the two or more mobilities is greater than the threshold value. As a result, the processing load on the computer can be reduced.

[0031] Further, in the above information processing method, the magnitude of the variation in the position information of the two or more mobilities classified into the mobility group is calculated. Further, when the calculated magnitude of the variation is greater than a threshold value, the location where the mobility group has stopped may be estimated based on the position information of the two or more mobilities classified into the mobility group.

[0032] According to this configuration, when the variation in the position information of two or more mobilities classified into a mobility group is greater than a threshold value, the location where the mobility group has stopped is estimated based on the position information of the two or more mobilities classified into the mobility group. As a result, it is possible to estimate not only the pre-provided stop location but also the location where the mobility group has stopped outside the stop location. For example, the position of the mobility returned at a location outside the stop location can be specified.

[0033] An information processing apparatus according to another aspect of the present disclosure includes an acquisition unit that acquires, from a plurality of mobilities, position information indicating the position of a mobility, identification information of the other mobility received by the mobility from another mobility by short-range wireless communication, and stop information indicating whether the mobility has stopped; a classification unit that classifies two or more mobilities that have stopped and have received the identification information from each other among the plurality of mobilities into the same mobility group; and a specifying unit that specifies a stop location where the mobility group has stopped based on the position information of the two or more mobilities classified into the mobility group.

[0034] According to this configuration, two or more mobilities that can communicate with each other by short-range wireless communication are presumed to be present at the same location and can be classified into the same mobility group. Therefore, even if the radio wave condition at the stop location is poor and there is variation in the position information of two or more mobilities stopped at the stop location, based on the position information of two or more mobilities that have received the identification information from each other by short-range wireless communication and are classified into the same mobility group, the stop location where the mobility group has stopped is specified. Therefore, the stop location where two or more mobilities have stopped can be specified with high accuracy.

[0035] An information processing program according to another aspect of the present disclosure causes a computer to function so as to acquire, from a plurality of mobilities, position information indicating the position of a mobility, identification information of another mobility received by the mobility from another mobility by short-range wireless communication, and stop information indicating whether or not the mobility has stopped, classify two or more mobilities that are stopped and have received the identification information from each other among the plurality of mobilities into the same mobility group, and specify a stop location where the mobility group has stopped based on the position information of the two or more mobilities classified into the mobility group.

[0036] According to this configuration, two or more mobilities that can communicate with each other by short-range wireless communication are presumed to be present at the same location and can be classified into the same mobility group. Therefore, even if the radio wave condition at the stop location is poor and there is variation in the position information of two or more mobilities stopped at the stop location, based on the position information of two or more mobilities that have received the identification information from each other by short-range wireless communication and are classified into the same mobility group, the stop location where the mobility group has stopped is specified. Thus, the stop location where two or more mobilities have stopped can be specified with high accuracy.

[0037] Embodiments of the present disclosure will be described below with reference to the accompanying drawings. Note that the following embodiments are examples of embodying the present disclosure and do not limit the technical scope of the present disclosure.

[0038] (Embodiment) FIG. 1 is a diagram showing the overall configuration of a mobility management system according to an embodiment of the present disclosure.

[0039] The mobility management system shown in FIG. 1 includes a plurality of mobilities 1 and a server device 2.

[0040] The mobility device 1 is, for example, an electric assist bicycle, which can be occupied and used by an individual during movement. The mobility device 1 is shared by a plurality of users. The mobility device 1 is driven by a user. The mobility device 1 is rented out at a predetermined parking location (stopping location) and returned at a predetermined parking location. In the urban area, a plurality of parking locations are arranged. At the parking location, a plurality of mobility devices 1 can be parked and the mobility device 1 can be charged. The parking location where it is rented out and the parking location where it is returned do not necessarily have to be the same. The mobility device 1 is communicably connected to the server device 2 via the network 3. The network 3 is, for example, the Internet.

[0041] Also, the mobility device 1 periodically transmits a mobility ID for identifying the mobility device 1 by short-range wireless communication. The short-range wireless communication is, for example, Bluetooth Low Energy (BLE), which is one of the communication modes of Bluetooth (registered trademark). The mobility device 1 broadcasts the mobility ID by short-range wireless communication. The mobility device 1 broadcasts the mobility ID, for example, every 1 second. The signal reach distance of the short-range wireless communication is, for example, 10 meters. The mobility device 1 receives the mobility ID transmitted by another mobility device. By receiving the mobility ID transmitted by another mobility device, the mobility device 1 can recognize that another mobility device exists within the signal reach range.

[0042] For example, the first mobility broadcasts the first mobility ID by short-range wireless communication, and the second mobility broadcasts the second mobility ID by short-range wireless communication. In this case, when the second mobility enters the signal reach of the short-range wireless communication of the first mobility, the first mobility receives the second mobility ID broadcast by the second mobility. At this time, since the first mobility also enters the signal reach of the short-range wireless communication of the second mobility, the second mobility receives the first mobility ID broadcast by the first mobility. In this way, the first mobility and the second mobility existing within the signal reach of the short-range wireless communication receive the mobility IDs from each other.

[0043] Note that Mobility 1 may be a bicycle without electric assist. Also, Mobility 1 may be an electric vehicle, an electric bicycle, an automobile equipped with an internal combustion engine, or a bicycle equipped with an internal combustion engine.

[0044] When a user uses Mobility 1, the user inputs reservation information for reserving the use of Mobility 1 into an information terminal (not shown). The reservation information includes a user ID for identifying the user, a start time of use, an end time of use, a lending location, and a return location. The information terminal is, for example, a smartphone, a tablet computer, or a personal computer, and is used by the user who rides on Mobility 1. The information terminal receives the input of the reservation information for reserving the use of Mobility 1 by the user. The information terminal transmits the input reservation information to the server device 2.

[0045] The server device 2 is, for example, a web server. The server device 2 receives various information from Mobility 1 and transmits various information to Mobility 1.

[0046] FIG. 2 is a diagram showing an example of the configuration of mobility in the embodiment of the present disclosure.

[0047] The mobility 1 shown in FIG. 2 includes an input unit 11, a processor 12, a position measurement unit 13, a first communication unit 14, a second communication unit 15, a drive unit 16, an electronic lock 17, and a memory 18.

[0048] The input unit 11 receives the driving operation of the mobility 1 by the user. Further, the input unit 11 receives the unlocking operation, locking operation, and return operation of the mobility 1 by the user. For example, the input unit 11 includes a numeric keypad, an unlocking button, a locking button, and a return button. The numeric keypad receives the input of a password for unlocking the mobility 1. The unlocking button receives the unlocking operation of the mobility 1 by the user after the input of the password. The locking button receives the locking operation of the mobility 1 by the user. The return button receives the return operation of the mobility 1 by the user after locking.

[0049] Note that the locking operation and unlocking operation of the mobility 1 may be performed by a two-dimensional barcode or an IC card reader or the like.

[0050] The position measurement unit 13 receives a GPS signal and measures the current position of the mobility 1 using the received GPS signal. The current position is represented by latitude and longitude. As described above, in a place with poor radio wave conditions such as under a building, there is a possibility that the measurement accuracy of the current position may decrease due to a time difference in the GPS signal or a decrease in the S / N ratio of the GPS signal.

[0051] The first communication unit 14 periodically broadcasts a mobility ID for identifying the mobility 1 by short-range wireless communication. Further, the first communication unit 14 receives the mobility ID broadcast by another mobility 1 by short-range wireless communication.

[0052] The electronic lock 17 locks and unlocks electrically.

[0053] The memory 18 is, for example, a semiconductor memory, and stores in advance a mobility ID for identifying the mobility 1.

[0054] The processor 12 is, for example, a central processing unit (CPU), and includes an unlocking unit 121, a locking unit 122, a return unit 123, and an information transmission control unit 124.

[0055] When a password is input by the user and the unlock button is pressed, the unlocking unit 121 transmits the input password and a mobility ID for identifying the mobility 1 to the server device 2 via the second communication unit 15. Further, when an unlock signal is received by the second communication unit 15, the unlocking unit 121 unlocks the electronic lock 17 of the mobility 1.

[0056] When the user presses the lock button, the locking unit 122 locks the electronic lock 17 of the mobility 1.

[0057] In this embodiment, the unlocking unit 121 and the locking unit 122 only need to be able to detect the unlocking and locking states of the electronic lock 17, and are not limited to the above configuration. Also, although the mobility 1 in this embodiment is electrically locked and unlocked by the electronic lock 17, the present disclosure is not particularly limited thereto, and the mobility 1 may not have a function of electrically locking and unlocking.

[0058] When the user presses the return button, the return unit 123 transmits a return signal indicating that the operation of the mobility 1 is terminated and the mobility 1 is to be returned to the server device 2 via the second communication unit 15.

[0059] The information transmission control unit 124 transmits, via the second communication unit 15, position information indicating the position of the mobility 1 measured by the position measurement unit 13, the mobility ID of another mobility received by the first communication unit 14, and stop information indicating whether the mobility 1 is stopped to the server device 2. Note that when the mobility ID of another mobility has not been received, the information transmission control unit 124 transmits only the position information and the stop information to the server device 2 via the second communication unit 15.

[0060] When the locking unit 122 is locked, the mobility information transmission control unit 124 determines that Mobility 1 is stopped and generates stop information indicating that Mobility 1 is stopped. Further, when the speed of Mobility 1 is 0, the mobility information transmission control unit 124 may determine that Mobility 1 is stopped and generate stop information indicating that Mobility 1 is stopped. Further, when the engine of Mobility 1 is stopped, the mobility information transmission control unit 124 may determine that Mobility 1 is stopped and generate stop information indicating that Mobility 1 is stopped. In this case, Mobility 1 is, for example, an automobile or a motorcycle. Further, when a return signal is transmitted, the mobility information transmission control unit 124 may determine that Mobility 1 is stopped and generate stop information indicating that Mobility 1 is stopped.

[0061] The second communication unit 15 transmits various information to the server device 2 and receives various information from the server device 2. The second communication unit 15 transmits a password and a mobility ID to the server device 2. The second communication unit 15 receives an unlocking signal transmitted by the server device 2. Further, the second communication unit 15 transmits a return signal to the server device 2. Further, the second communication unit 15 transmits position information indicating the position of Mobility 1, the mobility ID of another mobility received by Mobility 1 from another mobility by short-range wireless communication, and stop information indicating whether Mobility 1 is stopped to the server device 2. Note that when the mobility ID of another mobility has not been received, the second communication unit 15 transmits only the position information and the stop information to the server device 2.

[0062] The drive unit 16 is, for example, an electric motor, and rotates the wheels of Mobility 1 by driving the electric motor.

[0063] FIG. 3 is a diagram showing an example of the configuration of the server device according to the embodiment of the present disclosure.

[0064] The server device 2 shown in FIG. 3 includes a communication unit 21, a memory 22, and a processor 23.

[0065] The communication unit 21 acquires from a plurality of mobilities 1 the position information indicating the position of mobility 1, the mobility ID (identification information) of another mobility received by mobility 1 from other mobilities via short-range wireless communication, and the stop information indicating whether mobility 1 is stopped. The communication unit 21 receives from a plurality of mobilities 1 the position information of mobility 1, the mobility ID of another mobility, and the stop information of mobility 1.

[0066] In addition, the communication unit 21 transmits to the information terminal the password for unlocking the electronic lock 17 of mobility 1. The communication unit 21 receives the password and the mobility ID transmitted by mobility 1. The communication unit 21 transmits an unlocking signal to mobility 1. The communication unit 21 receives the return signal transmitted by mobility 1.

[0067] The memory 22 is, for example, a semiconductor memory or a hard disk drive, and stores mobility information and mobility group information. The mobility information is information associating the mobility ID of a mobility, the position information of the mobility, the mobility ID of another mobility received by the mobility via short-range wireless communication, and the stop information of the mobility. The mobility group information is information associating the mobility group ID for identifying a mobility group, the mobility IDs of a plurality of mobilities belonging to the mobility group, the median value of the coordinates of each mobility, and the moving average value of the median value.

[0068] The processor 23 is, for example, a CPU, and includes a mobility group classification unit 231, a variation determination unit 232, and a stop location specification unit 233.

[0069] The mobility group classification unit 231 classifies two or more mobilities 1 that are stopped and have received each other's mobility IDs among the plurality of mobilities 1 into the same mobility group. The mobility group classification unit 231 generates a mobility group ID for identifying the mobility group in which two or more mobilities 1 are classified, and stores mobility group information in which the mobility group ID is associated with the mobility IDs of two or more mobilities 1 classified into the mobility group in the memory 22.

[0070] Note that the stop information may be not only information indicating whether the mobility 1 is stopped, but also information indicating whether the mobility 1 is locked. In this case, the mobility group classification unit 231 classifies two or more mobilities 1 that are locked and have received each other's mobility IDs among the plurality of mobilities 1 into the same mobility group.

[0071] Also, the stop information may be not only information indicating whether the mobility 1 is stopped, but also information indicating whether the mobility 1 has been returned. In this case, the mobility group classification unit 231 classifies two or more mobilities 1 that have been returned and have received each other's mobility IDs among the plurality of mobilities 1 into the same mobility group.

[0072] The variation determination unit 232 calculates the magnitude of the variation in the position information of two or more mobilities 1 classified into the mobility group. The variation determination unit 232 determines whether the calculated magnitude of the variation is greater than a threshold value. Note that the magnitude of the variation is, for example, the standard deviation. The variation determination unit 232 calculates the standard deviation of the coordinates of two or more mobilities 1 classified into the mobility group, and determines whether the calculated standard deviation is greater than the threshold value. The magnitude of the variation may be, for example, the variance value.

[0073] The stop location specifying unit 233 specifies the stop location where the mobility group has stopped based on the position information of two or more mobilities 1 classified into the mobility group. When the magnitude of the variation calculated by the variation determination unit 232 is greater than the threshold value, the stop location specifying unit 233 specifies the stop location where the mobility group has stopped based on the position information of two or more mobilities 1 classified into the mobility group. The stop location is the parking location of the mobility 1, for example, the parking location where the mobility 1 is returned.

[0074] A plurality of stop locations are provided in advance. The stop location specifying unit 233 specifies the stop location where the mobility group has stopped among the plurality of pre-provided stop locations based on the position information of two or more mobilities 1 classified into the mobility group.

[0075] Specifically, the stop location specifying unit 233 calculates the median of the coordinates of two or more mobilities 1. The stop location specifying unit 233 calculates the moving average within a predetermined period of the calculated median. The stop location specifying unit 233 calculates a stop probability indicating the probability that the mobility group has stopped at the stop location according to the distance between the calculated moving average value and the coordinates of the stop location closest to the moving average value. When the stop probability is equal to or greater than the threshold value, the stop location specifying unit 233 specifies the stop location closest to the moving average value as the stop location where the mobility group has stopped.

[0076] In addition, the stop location specifying unit 233 specifies the stop location where one mobility 1 has stopped based on the plurality of position information of one mobility 1 that has stopped, has not received the mobility ID of other mobilities 1, and has variations in the plurality of position information acquired at a predetermined time interval among the plurality of mobilities 1.

[0077] Specifically, the stop location specifying unit 233 calculates the median of a plurality of coordinates acquired at a predetermined time interval for mobility 1. The stop location specifying unit 233 calculates a moving average within a predetermined period of the calculated median. The stop location specifying unit 233 calculates a stop probability indicating the probability that mobility 1 has stopped at the stop location according to the distance between the calculated moving average value and the coordinates of the stop location closest to the moving average value. When the stop probability is equal to or greater than the threshold value, the stop location specifying unit 233 specifies the stop location closest to the moving average value as the stop location where mobility 1 has stopped.

[0078] Further, when the mobility group classification unit 231 acquires any one mobility ID among two or more mobilities from a new mobility 1 not classified into the mobility group, the new mobility 1 is classified into the same mobility group as the two or more mobilities. Then, the stop location specifying unit 233 specifies the stop location where the mobility group has stopped as the stop location where the new mobility 1 has stopped.

[0079] Subsequently, the operation of the server device 2 in the embodiment of the present disclosure will be described.

[0080] FIG. 4 is a first flowchart for explaining the operation of the server device in the embodiment of the present disclosure, FIG. 5 is a second flowchart for explaining the operation of the server device in the embodiment of the present disclosure, and FIG. 6 is a third flowchart for explaining the operation of the server device in the embodiment of the present disclosure.

[0081] First, in step S1, the communication unit 21 of the server device 2 acquires position information indicating the position of mobility 1, the mobility ID of other mobilities received by mobility 1 from other mobilities via short-range wireless communication, and stop information indicating whether mobility 1 is stopped, from a plurality of mobilities 1. Each mobility 1 periodically transmits the position information, the mobility ID of other mobilities, and the stop information to the server device 2. The communication unit 21 periodically receives the position information, the mobility ID of other mobilities, and the stop information transmitted by each mobility 1. For example, the communication unit 21 receives the position information, the mobility ID of other mobilities, and the stop information transmitted by each mobility 1 every minute.

[0082] Next, in step S2, the mobility group classification unit 231 determines whether there are two or more mobilities 1 among the plurality of mobilities 1 that are stopped and have received each other's mobility IDs.

[0083] Note that the mobility group classification unit 231 can identify the stopped mobility 1 by referring to the stop information of mobility 1. Also, for example, when the first mobility receives the mobility ID of the second mobility and the second mobility receives the mobility ID of the first mobility, the mobility group classification unit 231 can identify the first mobility and the second mobility as mobilities that have received each other's mobility IDs.

[0084] Here, if it is determined that there are two or more mobilities 1 that are stopped and have received each other's mobility IDs (YES in step S2), in step S3, the mobility group classification unit 231 classifies two or more mobilities 1 that are stopped and have received each other's mobility IDs into the same mobility group.

[0085] Next, in step S4, the variation determination unit 232 calculates the standard deviation of the coordinates of two or more mobilities 1 classified into the mobility group.

[0086] In addition, when Mobility 1 cannot measure the position information and the communication unit 21 cannot acquire the position information, the mobility group classification unit 231 may read and use the position information of Mobility 1 that was last acquired from the mobility information stored in the memory 22.

[0087] Next, in step S5, the variation determination unit 232 determines whether the standard deviation is greater than the threshold value. Here, if it is determined that the standard deviation is less than or equal to the threshold value (NO in step S5), the process returns to step S1. That is, the fact that the standard deviation of the coordinates of two or more Mobilities 1 classified into the mobility group is less than or equal to the threshold value means that the positions of the two or more Mobilities 1 do not vary and the respective position information is correctly measured. Therefore, when the standard deviation of the coordinates of two or more Mobilities 1 is less than or equal to the threshold value, the process for specifying the stop location where the mobility group has stopped is unnecessary.

[0088] On the other hand, if it is determined that the standard deviation is greater than the threshold value (YES in step S5), in step S6, the stop location specifying unit 233 calculates the median of the coordinates of two or more Mobilities 1 classified into the mobility group.

[0089] Next, in step S7, the stop location specifying unit 233 calculates the moving average of the calculated median.

[0090] Next, in step S8, the stop location specifying unit 233 determines whether the moving average of the median for a predetermined period has been calculated. The predetermined period is, for example, one hour. Here, if it is determined that the moving average of the median for the predetermined period has not been calculated (NO in step S8), the process returns to step S1.

[0091] On the other hand, if it is determined that the moving average of the median for the predetermined period has been calculated (YES in step S8), in step S9, the stop location specifying unit 233 selects the stop location closest to the calculated moving average value from among a plurality of pre-provided stop locations. Note that the memory 22 stores in advance the position information (coordinates) of the plurality of pre-provided stop locations.

[0092] Next, in step S10, the stop location specifying unit 233 calculates a stop probability indicating the probability that a mobility group has stopped at the stop location according to the distance between the calculated moving average value and the coordinates of the selected stop location.

[0093] Here, a method for calculating the stop probability of the mobility group will be described.

[0094] FIG. 7 is a diagram for explaining a method for calculating the stop probability of the mobility group in the present embodiment.

[0095] The point 301 shown in FIG. 7 indicates the coordinates (x, y) of the stop location. Each of the points 311 to 315 indicates the coordinates (Ax, Ay) to (Ex, Ey) of five mobilities that have stopped and are receiving each other's mobility IDs. The point 321 indicates the moving average value (Dx, Cy) of the median of the coordinates of the five mobilities. Also, the plurality of circles indicated by dotted lines are centered on the stop location and represent positions 10 m, 20 m, 30 m, 40 m, and 50 m away from the center, respectively.

[0096] If the distance between the calculated moving average value and the coordinates of the selected stop location is 10 m or less, the stop location specifying unit 233 sets the stop probability to 100%. Also, if the distance between the calculated moving average value and the coordinates of the selected stop location is greater than 10 m and 20 m or less, the stop location specifying unit 233 sets the stop probability to 90%. In this way, for every 10 m separation between the calculated moving average value and the coordinates of the selected stop location, the stop location specifying unit 233 decreases the stop probability by 10% each time. The stop location specifying unit 233 increases the stop probability if the calculated moving average value is close to the selected stop location, and decreases the stop probability if the calculated moving average value is far from the selected stop location.

[0097] Returning to FIG. 5, next, in step S11, the stop location specifying unit 233 determines whether the calculated stop probability is equal to or greater than a threshold value. The threshold value is, for example, 80%.

[0098] Here, when it is determined that the stop probability is equal to or greater than the threshold value (YES in step S11), in step S12, the stop location specifying unit 233 specifies the selected stop location as the stop location of the mobility group.

[0099] Next, in step S13, the communication unit 21 notifies the administrators of the plurality of mobilities 1 of the stop location of the specified mobility group. At this time, the communication unit 21 transmits the stop location of the specified mobility group and the mobility IDs of the plurality of mobilities 1 classified into the mobility group to the administrator's information terminal. After the process of step S13, the process returns to step S1.

[0100] Note that after the stop probability of the mobility group is calculated, if there is no change in the plurality of mobilities constituting the mobility group, the stop location specifying unit 233 does not decrease the calculated stop probability below the previously calculated stop probability. Also, after the stop probability of the mobility group is calculated, if there is no change in the plurality of mobilities constituting the mobility group, the stop location specifying unit 233 may continue to use the calculated stop probability. Further, after the stop probability of the mobility group is calculated, the stop location specifying unit 233 may continue to use the calculated stop probability until the plurality of mobilities constituting the mobility group reach zero. Furthermore, after the stop probability of the mobility group is calculated, the stop location specifying unit 233 may continue to use the calculated stop probability until the server device 2 is restarted.

[0101] On the other hand, when it is determined that the stop probability is less than the threshold value (NO in step S11), in step S14, the communication unit 21 notifies the administrators of the plurality of mobilities 1 that the stop location of the mobility group cannot be specified. At this time, the communication unit 21 transmits information indicating that the stop location of the mobility group cannot be specified to the administrator's information terminal. After the process of step S14, the process returns to step S1.

[0102] Note that when the mobility group classification unit 231 obtains one mobility ID among two or more mobilities from a new mobility 1 that has not been classified into a mobility group, the new mobility 1 may be classified into the same mobility group as the two or more mobilities. Then, the stop location identification unit 233 may identify the stop location where the mobility group has stopped as the stop location where the new mobility 1 has stopped.

[0103] Also, in the present embodiment, the stop location identification unit 233 calculates the stop probability of the mobility group according to the distance between the calculated moving average value and the coordinates of the stop location closest to the moving average value, but the present disclosure is not particularly limited thereto. The stop location identification unit 233 may obtain the stop probability output from the prediction model by inputting the coordinates of two or more mobilities into the prediction model. The prediction model is generated by machine learning using, as teacher data, the coordinates measured by two or more mobilities existing around the stop location and the stop probability that two or more mobilities have stopped at the stop location. For example, the prediction model may be machine-learned such that when the coordinates of two or more mobilities stopped at the stop location are input, a stop probability of 100% is output, and when the coordinates of two or more mobilities not stopped at the stop location are input, a stop probability of 0% is output. Also, for example, the prediction model may be machine-learned such that when the coordinates of two or more mobilities not stopped at the stop location are input, GPS variation data is acquired, for example, every hour as the distance between the coordinates of the two or more mobilities and the coordinates of the stop location increases by 10 m, and the stop probability is decreased by 10% each time as the correct answer data.

[0104] Also, the stop location identification unit 233 may correct the stop probability using the return information indicating that each mobility has been returned. For example, among the five mobilities classified into a mobility group, if four mobilities are returned and one mobility is not returned, the return rate is 80%. Assuming that the calculated stop probability is 60% and the proportional ratio between the return rate and the stop probability is 50:50, the stop location identification unit 233 may correct the stop probability to 70%.

[0105] On the other hand, in step S2, when it is determined that the condition that there are two or more mobilities 1 that are stopped and have received each other's mobility IDs is not satisfied (NO in step S2), in step S15, the mobility group classification unit 231 determines whether there is one mobility 1 that is stopped and has not received a mobility ID among the plurality of mobilities 1.

[0106] Here, when it is determined that the condition that there is one mobility 1 that is stopped and has not received a mobility ID is not satisfied (NO in step S15), the process returns to step S1.

[0107] On the other hand, when it is determined that there is one mobility 1 that is stopped and has not received a mobility ID (YES in step S15), in step S16, the variation determination unit 232 calculates the standard deviation of a predetermined number of coordinates of the one mobility 1. For example, the variation determination unit 232 calculates the standard deviation of 10 coordinates of the one mobility 1 based on the history of the position information of the one mobility 1 stored in the memory 22.

[0108] Next, in step S17, the variation determination unit 232 determines whether the standard deviation is greater than the threshold value. Here, when it is determined that the standard deviation is less than or equal to the threshold value (NO in step S17), the process returns to step S1. That is, the fact that the standard deviation of a predetermined number of coordinates of the one mobility 1 is less than or equal to the threshold value means that the position of the one mobility 1 does not vary and the position information is correctly measured. Therefore, when the standard deviation of a predetermined number of coordinates of the one mobility 1 is less than or equal to the threshold value, the process for specifying the stop location where the one mobility is stopped is unnecessary.

[0109] On the other hand, when it is determined that the standard deviation is greater than the threshold value (YES in step S17), in step S18, the stop location specifying unit 233 calculates the median of the coordinates of the one mobility 1 acquired every predetermined time.

[0110] Next, in step S19, the stop location specifying unit 233 calculates the moving average of the calculated median value.

[0111] Next, in step S20, the stop location specifying unit 233 determines whether the moving average of the median value over a predetermined period has been calculated. The predetermined period is, for example, one hour. Here, if it is determined that the moving average of the median value over the predetermined period has not been calculated, that is, if the moving average has not reached the predetermined time (NO in step S20), the process returns to step S1.

[0112] On the other hand, if it is determined that the moving average of the median value over the predetermined period has been calculated (YES in step S20), in step S21, the stop location specifying unit 233 selects the stop location closest to the calculated moving average value among a plurality of pre-provided stop locations.

[0113] Next, in step S22, the stop location specifying unit 233 calculates a stop probability indicating the probability that mobility 1 has stopped at the stop location according to the distance between the calculated moving average value and the coordinates of the selected stop location.

[0114] Here, a method for calculating the stop probability of mobility 1 will be described.

[0115] FIG. 8 is a diagram for explaining a method for calculating the stop probability of mobility 1 in the present embodiment.

[0116] The point 401 shown in FIG. 8 indicates the coordinates (x, y) of the stop location. Each of the points 411 to 416 indicates the six coordinates (A1x, A1y) to (A6x, A6y) of mobility 1 that has stopped and has not received the mobility ID of other mobilities. The point 421 indicates the moving average value (Ax, Ay) of the median value of the coordinates of mobility 1. The plurality of circles indicated by dotted lines are centered on the stop location and represent positions 10 m, 20 m, 30 m, 40 m, and 50 m away from the center, respectively.

[0117] If the distance between the calculated moving average value and the coordinates of the selected stop location is 10 m or less, the stop probability is set to 100% by the stop location specifying unit 233. Further, if the distance between the calculated moving average value and the coordinates of the selected stop location is greater than 10 m and 20 m or less, the stop probability is set to 90% by the stop location specifying unit 233. In this way, the stop location specifying unit 233 decreases the stop probability by 10% each time the distance between the calculated moving average value and the coordinates of the selected stop location increases by 10 m. The stop location specifying unit 233 increases the stop probability if the calculated moving average value is close to the selected stop location, and decreases the stop probability if the calculated moving average value is far from the selected stop location.

[0118] Returning to FIG. 6, next, in step S23, the stop location specifying unit 233 determines whether or not the calculated stop probability is equal to or greater than a threshold value. The threshold value is, for example, 80%.

[0119] Here, if it is determined that the stop probability is equal to or greater than the threshold value (YES in step S23), in step S24, the stop location specifying unit 233 specifies the selected stop location as the stop location of mobility 1.

[0120] Next, in step S25, the communication unit 21 notifies the plurality of mobility 1 administrators of the specified stop location of mobility 1. At this time, the communication unit 21 transmits the specified stop location of mobility 1 and the mobility ID of mobility 1 to the administrator's information terminal. After the process of step S25, the process returns to step S1.

[0121] Note that after the stop probability of mobility 1 is calculated, the stop location specifying unit 233 may continue to use the calculated stop probability until mobility 1 starts moving. Furthermore, after the stop probability of mobility 1 is calculated, the stop location specifying unit 233 may continue to use the calculated stop probability until the server device 2 is restarted.

[0122] On the other hand, when it is determined that the stop probability is less than the threshold (NO in step S23), in step S26, the communication unit 21 notifies a plurality of mobility 1 administrators that the stop location of mobility 1 cannot be specified. At this time, the communication unit 21 transmits information indicating that the stop location of mobility 1 cannot be specified to the administrator's information terminal. After the process of step S26, the process returns to step S1.

[0123] In this way, two or more mobilities 1 capable of communicating with each other by short-range wireless communication are presumed to be present at the same location and can be classified into the same mobility group. Therefore, even if the radio wave condition at the stop location is poor and there is variation in the position information of two or more mobilities 1 stopped at the stop location, based on the position information of two or more mobilities 1 that receive identification information from each other by short-range wireless communication classified into the same mobility group, the stop location where the mobility group has stopped is specified. Therefore, the stop location where two or more mobilities 1 have stopped can be specified with high accuracy.

[0124] Note that since the change in the radio wave condition is not frequent, the processes of step S4 and step S5 in FIG. 4 and step S16 and step S17 in FIG. 6 may not be performed in real time, but may be performed by batch processing at regular intervals, for example, about once a week. Thereby, the processing load on the computer can be further reduced.

[0125] In addition, in the present embodiment, the stop location specifying unit 233 calculates the stop probability of mobility 1 according to the distance between the calculated moving average value and the coordinates of the stop location closest to the moving average value. However, the present disclosure is not particularly limited thereto. The stop location specifying unit 233 may obtain the stop probability output from the prediction model by inputting a plurality of coordinates for each predetermined time of mobility 1 into the prediction model. The prediction model is generated by machine learning using, as teacher data, the coordinates measured by mobility 1 existing around the stop location and the stop probability that mobility 1 has stopped at the stop location. For example, the prediction model may be machine-learned such that when the coordinates of mobility 1 stopped at the stop location are input, a stop probability of 100% is output, and when the coordinates of mobility 1 not stopped at the stop location are input, a stop probability of 0% is output. Also, for example, when the coordinates of mobility 1 not stopped at the stop location are input, the prediction model may be machine-learned to obtain GPS variation data, for example, every hour as the distance between the coordinates of mobility 1 and the coordinates of the stop location increases by 10 m, and to decrease the stop probability by 10% each time as the correct answer data.

[0126] Further, in the present embodiment, the variation determination unit 232 calculates the magnitude of the variation in the position information of two or more mobilities 1 classified into the mobility group. However, the present disclosure is not particularly limited thereto. The variation determination unit 232 may calculate the magnitude of the variation in the distances between two or more mobilities classified into the mobility group. The variation determination unit 232 may determine whether the calculated magnitude of the variation is greater than a threshold value. Note that the magnitude of the variation is, for example, the standard deviation or the variance value. The variation determination unit 232 may calculate the Euclidean distance between two points of two or more mobilities 1 classified into the mobility group and calculate the variance value of the calculated Euclidean distance. The variation determination unit 232 may determine whether the calculated variance value is greater than a threshold value. When the calculated magnitude of the variation is greater than the threshold value, the stop location specifying unit 233 may specify the stop location where the mobility group has stopped based on the position information of two or more mobilities classified into the mobility group.

[0127] Note that the variation determination unit 232 may calculate the magnitude of the variation in the distances between two or more mobilities classified into a mobility group based on the following formula (1).

[0128]

Equation

[0129] In the above formula (1), N represents the number of two or more mobilities classified into a mobility group, and the DISTANCE(Bi,Bj) function is a function that calculates the Euclidean distance between the i-th mobility and the j-th mobility among two or more mobilities classified into a mobility group.

[0130] Further, the variation determination unit 232 may calculate an outlier value using the magnitude of the variation in the distances between two or more mobilities classified into a mobility group. Then, the variation determination unit 232 may exclude the mobility corresponding to the calculated outlier value from the mobility group.

[0131] Also, the variation determination unit 232 may calculate the magnitude of the variation in the distances between each of two or more mobilities classified into a mobility group and the stopping places existing around the two or more mobilities. The variation determination unit 232 may determine whether the calculated magnitude of the variation is greater than a threshold value. Note that the magnitude of the variation is, for example, a standard deviation or a variance value. The variation determination unit 232 may calculate the Euclidean distance between each of two or more mobilities 1 classified into a mobility group and a stopping place, and calculate the variance value of the calculated Euclidean distances. The variation determination unit 232 may determine whether the calculated variance value is greater than a threshold value. When the calculated magnitude of the variation is greater than the threshold value, the stopping place specifying unit 233 may specify the stopping place where the mobility group has stopped based on the position information of the two or more mobilities classified into the mobility group.

[0132] Note that the variation determination unit 232 may calculate the magnitude of the variation in the distances between each of two or more mobilities classified into a mobility group and the stopping places existing around the two or more mobilities based on the following formula (2).

[0133] [Number]

[0134] In the above formula (2), N represents the number of two or more mobilities classified into a mobility group, and the DISTANCE(Bi) function is a function that calculates the Euclidean distance between the i-th mobility among the two or more mobilities classified into a mobility group and the stopping place.

[0135] Further, the variation determination unit 232 may calculate an outlier using the magnitude of the variation in the distances between each of two or more mobilities classified into a mobility group and the stopping places existing around the two or more mobilities. Then, the variation determination unit 232 may exclude the mobility corresponding to the calculated outlier from the mobility group.

[0136] Further, the variation determination unit 232 may obtain a determination result as to whether the stopping place is provided in a place with poor radio wave conditions by inputting the coordinates of two or more mobilities 1 classified into a mobility group into a prediction model. The prediction model is generated by machine learning using, as teacher data, the coordinates measured by two or more mobilities 1 stopped at a stopping place with good radio wave conditions, the coordinates measured by two or more mobilities 1 stopped at a stopping place with poor radio wave conditions, and the determination result as to whether the radio wave conditions are good. For example, the prediction model may be machine-learned such that when the coordinates measured by two or more mobilities 1 stopped at a stopping place with good radio wave conditions are input, a determination result that the radio wave conditions are good is output, and when the coordinates measured by two or more mobilities 1 stopped at a stopping place with poor radio wave conditions are input, a determination result that the radio wave conditions are poor is output.

[0137] Furthermore, in the present embodiment, when the magnitude of the variation in the position information of two or more mobilities classified into a mobility group is greater than a threshold value, the stop location specifying unit 233 specifies the stop location where the mobility group has stopped based on the position information of two or more mobilities classified into the mobility group. However, the present disclosure is not particularly limited thereto. When the magnitude of the variation in the position information of two or more mobilities classified into a mobility group is greater than a threshold value, the stop location specifying unit 233 may estimate the location where the mobility group has stopped based on the position information of two or more mobilities classified into the mobility group. Thereby, not only the pre-provided stop locations but also the locations where the mobility groups other than the stop locations have stopped can be estimated. For example, the positions of the mobilities returned at locations other than the stop locations can be specified.

[0138] Also, in step S9 of FIG. 4 and step S21 of FIG. 6, the stop location specifying unit 233 selects the stop location closest to the calculated moving average value among a plurality of pre-provided stop locations. However, the present disclosure is not particularly limited thereto. The stop location specifying unit 233 may select a plurality of stop locations in ascending order of proximity from the calculated moving average value among a plurality of pre-provided stop locations and present the placement probabilities to each stop location to the terminal of the operator who manages the mobility sharing service. In that case, the operator can select an appropriate stop location from the presented plurality of stop locations in consideration of the tendency of the stop positions obtained from the daily service management operations in addition to the placement probabilities obtained from the system. Thereby, the accuracy of the stop location can be improved.

[0139] In addition, in each of the above embodiments, each component may be configured by dedicated hardware or may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or a processor reading and executing a software program recorded on a recording medium such as a hard disk or a semiconductor memory.

[0140] Part or all of the functions of the apparatus according to the embodiments of the present disclosure are typically realized as an LSI (Large Scale Integration), which is an integrated circuit. These may be individually formed into one chip, or may be formed into one chip so as to include part or all of them. Further, the integration is not limited to LSI, and may be realized by a dedicated circuit or a general-purpose processor. An FPGA (Field Programmable Gate Array) that can be programmed after LSI manufacturing, or a reconfigurable processor that can reconfigure the connection and setting of circuit cells inside the LSI may be used.

[0141] Also, part or all of the functions of the apparatus according to the embodiments of the present disclosure may be realized by a processor such as a CPU executing a program.

[0142] Also, all the numbers used above are for exemplification to specifically explain the present disclosure, and the present disclosure is not limited to the exemplified numbers.

[0143] Also, the order in which each step shown in the above flowchart is executed is for exemplification to specifically explain the present disclosure, and may be in an order other than the above as long as the same effect can be obtained. Also, a part of the above steps may be executed simultaneously (in parallel) with other steps.

Industrial Applicability

[0144] The technology according to the present disclosure can specify with high accuracy a stop location where two or more mobilities are stopped, and thus is useful for a technology for specifying a position where a plurality of mobilities are stopped.

Claims

1. A computer obtains, from a plurality of mobilities, position information indicating the positions of the mobilities shared by a plurality of users, identification information of another mobility received by the mobility from the other mobility via short-range wireless communication, and stop information indicating whether the mobility is stopped, classifies two or more mobilities that are stopped and have received each other's identification information among the plurality of mobilities into the same mobility group, and identifies a stop location where the mobility group has stopped based on the position information of the two or more mobilities classified into the mobility group. An information processing method.

2. In identifying the stop location, the median of the coordinates of the two or more mobilities is calculated, a moving average within a predetermined period of the calculated median is calculated, and a stop probability indicating the probability that the mobility group has stopped at the stop location is calculated according to the distance between the calculated moving average value and the coordinates of the stop location closest to the moving average value. When the stop probability is equal to or greater than a threshold value, the stop location closest to the moving average value is identified as the stop location where the mobility group has stopped. The information processing method according to Claim 1.

3. Furthermore, based on the plurality of position information of one mobility that is stopped, has not received the identification information of the other mobility, and has variations in the plurality of position information obtained at predetermined time intervals among the plurality of mobilities, the stop location where the one mobility has stopped is identified. The information processing method according to Claim 1 or 2.

4. In identifying the stop location, the median of the plurality of coordinates obtained at predetermined time intervals of the one mobility is calculated, a moving average within a predetermined period of the calculated median is calculated, and a stop probability indicating the probability that the one mobility has stopped at the stop location is calculated according to the distance between the calculated moving average value and the coordinates of the stop location closest to the moving average value. When the stop probability is equal to or greater than a threshold value, the stop location closest to the moving average value is identified as the stop location where the one mobility has stopped. The information processing method according to Claim 3.

5. Furthermore, when the identification information of any one of the two or more mobilities is obtained from a new mobility not classified into the mobility group, the new mobility is classified into the same mobility group as the two or more mobilities. ​ Further, identify the stop location where the mobility group has stopped as the stop location where the new mobility has stopped. The information processing method according to any one of claims 1 to 4.

6. Further, calculate the magnitude of the variation in the position information of the two or more mobilities classified into the mobility group. In identifying the stop location, if the calculated magnitude of the variation is greater than a threshold value, identify the stop location where the mobility group has stopped based on the position information of the two or more mobilities classified into the mobility group. The information processing method according to any one of claims 1 to 5.

7. Further, calculate the magnitude of the variation in the distance between the two or more mobilities classified into the mobility group. In identifying the stop location, if the calculated magnitude of the variation is greater than a threshold value, identify the stop location where the mobility group has stopped based on the position information of the two or more mobilities classified into the mobility group. The information processing method according to any one of claims 1 to 5.

8. Further, calculate the magnitude of the variation in the distance between each of the two or more mobilities classified into the mobility group and the stop location existing around the two or more mobilities. In identifying the stop location, if the calculated magnitude of the variation is greater than a threshold value, identify the stop location where the mobility group has stopped based on the position information of the two or more mobilities classified into the mobility group. The information processing method according to any one of claims 1 to 5.

9. Further, calculate the magnitude of the variation in the position information of the two or more mobilities classified into the mobility group. Further, if the calculated magnitude of the variation is greater than a threshold value, estimate the location where the mobility group has stopped based on the position information of the two or more mobilities classified into the mobility group. The information processing method according to any one of claims 1 to 5.

10. An acquisition unit that acquires, from a plurality of mobilities, position information indicating the positions of the mobilities shared by a plurality of users, identification information of the other mobilities received by the mobilities from the other mobilities via short-range wireless communication, and stop information indicating whether the mobilities have stopped. A classification unit that classifies two or more mobilities that are stopped and have received the identification information from each other among the plurality of mobilities into the same mobility group; An identification unit that identifies a stop location where the mobility group has stopped based on the location information of the two or more mobilities classified into the mobility group; An information processing apparatus comprising the same.

11. Obtain from a plurality of mobilities position information indicating the positions of mobilities shared by a plurality of users, identification information of the other mobilities received by the mobilities from other mobilities by short-range wireless communication, and stop information indicating whether the mobilities are stopped, Among the plurality of mobilities, classify two or more mobilities that are stopped and have received the identification information from each other into the same mobility group, Cause a computer to function so as to identify a stop location where the mobility group has stopped based on the location information of the two or more mobilities classified into the mobility group. An information processing program.

Images