Information processing device, information processing system, information processing method, and information processing program

Abstract

To provide an information processing device, an information processing system, an information processing method, and an information processing program capable of specifying an entrance in consideration of a route toward a facility.SOLUTION: An information processing device includes: an acquisition part for acquiring travel history information on a travel history of vehicles entering from any one of a plurality of entrances associated with a facility; a region setting part for setting a vehicle-passage determination region at a position away from the facility by a predetermined distance; an extraction part for extracting an intersection of the vehicle-passage determination region and a road passing through the vehicle-passage determination region; a specification part for acquiring the number of vehicles which have passed through a predetermined range from an intersection based on the travel history information and specifying the intersections where the number of vehicles is equal to or greater than a threshold value as cluster points for entry; and a generation part which generates association information by identifying the association between the cluster point related to the entry and the entrance through which the vehicle enters the facility after passing through the cluster point based on the travel history information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, an information processing system, an information processing method, and an information processing program. [Background technology]

[0002] There is a destination acquisition system technology that acquires the entrance of a facility as the destination (see Patent Document 1). This destination acquisition system references a database that associates the site area of ​​a facility with the entrances that vehicles can enter within that site area, and if the coordinates of the facility being searched for are within the site area, it acquires the entrance associated with that site area as the destination. Furthermore, if the coordinates of the facility being searched for are not within the site area, the destination acquisition system acquires the main entrance associated with that facility as the destination. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2016-223823 Summary of the Invention [Problem to be solved by the invention]

[0004] When vehicles head to a facility, there may be a route (popular route) that a relatively large number of vehicles travel along. Even if the facility has multiple entrances, a relatively large number of vehicles traveling along the popular route may enter through the same entrance. The destination acquisition system described in Patent Document 1 does not take into consideration the case where a user enters a facility through a specific entrance after traveling a regular route, and therefore may not be able to acquire the optimal destination.

[0005] The present disclosure provides an information processing device, an information processing system, an information processing method, and an information processing program that are capable of identifying an entrance taking into consideration a route to a facility. [Means for solving the problem]

[0006] An information processing device of one embodiment includes an acquisition unit that acquires driving history information regarding a driving history of a vehicle entering a facility through one of a plurality of entrances associated with the facility; an area setting unit that sets a vehicle passage determination area at a predetermined distance from the facility; an extraction unit that extracts an intersection between the vehicle passage determination area set by the area setting unit and a road that passes through the vehicle passage determination area; an identification unit that acquires the number of vehicles that have passed within a predetermined range from the intersection extracted by the extraction unit based on the driving history information acquired by the acquisition unit, and identifies an intersection where the number of vehicles is equal to or greater than a threshold as a cluster point related to entry; and a generation unit that generates association information by identifying the association between the cluster point related to entry identified by the identification unit and an entrance through which the vehicle entered the facility after passing through the cluster point based on the driving history information acquired by the acquisition unit. [Effects of the Invention]

[0007] According to one embodiment, based on driving history information relating to the driving history of a vehicle entering a facility through one of multiple entrances associated with the facility, correlation information is generated by identifying the correlation between the cluster point relating to entry in the vehicle passage determination area corresponding to the facility and the entrance through which the vehicle entered the facility after passing through that cluster point, thereby making it possible to identify an entrance taking into account the route to the facility. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an information processing device according to an embodiment. [Figure 2] FIG. 1 is a block diagram illustrating an information processing device according to an embodiment. [Figure 3] FIG. 10 is a diagram illustrating an example of a process for identifying cluster points. [Figure 4] FIG. 10 is a diagram illustrating an example of association information. [Figure 5] 1 is a flowchart illustrating an information processing method according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] An embodiment will be described below.

[0010] In the past, route searches were sometimes performed based on link costs, but this sometimes resulted in inappropriate identification of the destination point during route searches. Therefore, the information processing device 100 of the present disclosure prepares an optimal solution for identifying the destination point as association information. This allows the information processing device 100 of the present disclosure to compensate for the lack of calculation logic used in conventional methods for identifying the destination point with data called association information.

[0011] [Overview of information processing device 100] First, an overview of an information processing device 100 according to an embodiment will be described. FIG. 1 is a diagram illustrating an information processing device 100 according to an embodiment.

[0012] The information processing device 100 may be configured, for example, as an association specifying device that specifies an association between an entrance 411 of a facility 400 and a point (e.g., cluster point 503A related to entry) that is a predetermined distance away from the facility 400 when entering the entrance 411. The information processing device 100 may also be configured as an association specifying device that specifies an association between an exit 412 of the facility 400 and a point (e.g., cluster point 503B related to exit) that is a predetermined distance away from the facility 400 when exiting from the exit 412. The information processing device 100 may be configured, for example, as a route search device that searches for a route based on the specified association. The information processing device 100 may also be configured as a registration device that registers the association in map information. The information processing device 100 is not limited to the device described above as an example, and may be configured as various other devices. The information processing device 100 may be a computer such as a server, a desktop, a laptop, a tablet, or a smartphone.

[0013] The information processing device 100 may constitute an information processing system together with the vehicle 200, the server 300, a user terminal (not shown), and the like. The information processing device 100 acquires travel history information. The travel history information may be, for example, information relating to a travel history in which the vehicle 200 entered the facility 400 through one of a plurality of entrances 411 associated with the facility 400. The information processing device 100 also sets a vehicle passage determination area 501. The vehicle passage determination area 501 may be set at a position, for example, a predetermined distance away from the facility 400 described above. The information processing device 100 extracts intersections 502 between the vehicle passage determination area 501 and roads that pass through the vehicle passage determination area 501. That is, the information processing device 100 extracts, for example, intersections 502 between the vehicle passage determination area 501 and roads that straddle the inside and outside of the vehicle passage determination area 501.

[0014] The information processing device 100 acquires the number of vehicles 200 that have passed within a predetermined range from the intersection 502 described above, based on, for example, a plurality of pieces of travel history information. In this case, for example, when the vehicle 200 travels on a road and passes through the vehicle passage determination area 501, the information processing device 100 may identify position information that is relatively close to the above-mentioned intersection 502. The position information may be, for example, information acquired by the vehicle 200 or may be included in the driving history information. The information processing device 100 may identify multiple pieces of position information that are relatively close to the above-mentioned intersection 502, for example, based on multiple pieces of driving history information. The information processing device 100 may use at least one of the identified multiple pieces of position information as a reference and acquire the number of other pieces of position information that are within a predetermined range from the reference position information. The information processing device 100 may acquire the number of vehicles 200 that have passed within a predetermined range from the above-mentioned intersection 502 using various methods other than the above-mentioned acquisition method.

[0015] The information processing device 100 identifies the intersection 502 where the number of acquired vehicles 200 is equal to or greater than a threshold as a cluster point 503A related to entry. In addition, based on the driving history information, the information processing device 100 identifies the correlation between the identified cluster point 503A related to the entry and the entrance 411 through which the vehicle entered the facility 400 after passing through the cluster point 503A, and generates correlation information. Note that the process for generating correlation information described above explains the case of entering facility 400, but similar processing can be used to identify correlations related to exit and generate correlation information when exiting facility 400 through exit 412.

[0016] For example, based on the association information, the information processing device 100 performs a route search for the facility 400. Furthermore, for example, the information processing device 100 registers the association information in map information.

[0017] [Details of the information processing device 100] Next, the information processing device 100 according to an embodiment will be described in detail. FIG. 2 is a block diagram illustrating the information processing device 100 according to an embodiment.

[0018] The information processing device 100 includes, for example, a communication unit 121, a storage unit 122, a display unit 123, and a control unit 110. The communication unit 121, the storage unit 122, and the display unit 123 may be an embodiment of an output unit. The control unit 110 includes, for example, an acquisition unit 111, an area setting unit 112, an extraction unit 113, a generation unit 115, a route search unit 116, and an output control unit 117. The control unit 110 may be configured by, for example, an arithmetic processing unit of the information processing device 100. The control unit 110 (for example, an arithmetic processing unit) may realize the functions of each unit (for example, the acquisition unit 111, the area setting unit 112, the extraction unit 113, the generation unit 115, the route search unit 116, and the output control unit 117) by, for example, appropriately reading and executing various programs stored in the storage unit 122.

[0019] The route search unit 116 may be arranged inside the information processing device 100 as described above, or may be arranged outside the information processing device 100. When the route search unit 116 is arranged outside the information processing device 100, the route search unit 116 may be arranged in the vehicle 200 or a user terminal (not shown). In this case, the information processing device 100, the vehicle 200, the server 300, the user terminal, etc. may constitute an information processing system. In other words, the route search unit 116 located outside the information processing device 100 may constitute an information processing system together with the information processing device 100, etc.

[0020] The communication unit 121 is, for example, a communication interface capable of transmitting and receiving various information to and from devices (external devices) external to the information processing device 100. The external devices may be, for example, the vehicle 200, the server 300, and a user terminal (not shown). The user terminal may be, for example, a portable terminal such as a laptop, a tablet, or a smartphone.

[0021] The storage unit 122 may store, for example, various information and programs. Examples of the storage unit 122 may be a memory, a solid state drive, a hard disk drive, etc. Note that the storage unit 122 may be, for example, a storage area or a server on a cloud.

[0022] The storage unit 122 stores map information related to a road map. The road map may be, for example, a map on which roads and facilities 400 are recorded. The road map may also be, for example, a map used for route search, route guidance, etc.

[0023] The display unit 123 is a display capable of displaying, for example, various characters, symbols, images, and the like.

[0024] The acquisition unit 111 acquires driving history information relating to a driving history in which the vehicle 200 entered the facility 400 through one of a plurality of entrances 411 associated with the facility 400. The acquisition unit 111 may also acquire driving history information relating to a driving history in which the vehicle 200 exited the facility 400 through one of a plurality of exits 412 associated with the facility 400. For example, the acquisition unit 111 may acquire the driving history information from at least one of the vehicle 200, the server 300, and a user terminal (not shown) via the communication unit 121. Alternatively, for example, when an external memory (not shown) in which the driving history information is recorded is inserted into an interface (not shown) arranged in the information processing device 100, the acquisition unit 111 may acquire the driving history information from the external memory.

[0025] The driving history information may be information that records a driving history such as position information, time information, and route information such as a departure point and a destination when the vehicle 200 is driving. The driving history information may also include various information such as CAN information and probe information related to the driving of the vehicle 200. The driving history information is acquired by the vehicle 200, for example. The vehicle 200 may transmit the driving history information to the information processing device 100 or the server 300, for example.

[0026] Here, the vehicle 200 may be equipped with a position information acquisition device such as GNSS, and may use the GNSS to acquire position information, time information, etc. Also, a route guidance device (for example, a navigation device, etc.) mounted on the vehicle 200 may acquire route information such as a departure point and a destination that is input when performing route search, route guidance, etc. The travel history information may be acquired not only by the vehicle 200 but also by a user terminal (not shown) that can be mounted on the vehicle 200. The user terminal may have, for example, a navigation function.

[0027] The area setting unit 112 sets the vehicle passage determination area 501 at a position that is a predetermined distance away from the facility 400. For example, the area setting unit 112 may set the vehicle passage determination area 501 at positions that are a predetermined distance away from the facility 400 in multiple directions. For example, the area setting unit 112 may set the vehicle passage determination area 501 in the north-south, east-west directions based on the facility 400. The vehicle passage determination area 501 may be, for example, an area that specifies at least one of a passing point (e.g., cluster point 503A related to entry) on the route that the vehicle 200 takes to reach the facility 400 and a passing point (e.g., cluster point 503B related to exit) on the route that the vehicle 200 takes after leaving the facility 400.

[0028] As a specific example, the region setting unit 112 sets a region for extracting points (such as intersections 502, which will be described later) from which the extraction unit 113, which will be described later, acquires the number of vehicles 200 heading towards the facility 400, in order to acquire the number of vehicles 200 heading towards the facility 400 in the identification unit 114, which will be described later. In other words, the region setting unit 112 sets a region for identifying, as cluster points 503, points through which the vehicles 200 heading towards the facility 400 pass, where a number of vehicles 200 equal to or greater than a threshold value passes, among points through which the vehicles 200 pass.

[0029] The vehicle passage determination area 501 may be, for example, a rectangular area (for example, a square) based on the facility 400, or may be a circular area, an elliptical area, a polygonal area, or the like. Furthermore, the vehicle passage determination area 501 is not limited to the above-mentioned example, and may be an area of ​​various shapes. The predetermined distance may be, for example, various distances that are set in advance. As an example, the area setting unit 112 may set the vehicle passage determination area 501 on a road map.

[0030] The extraction unit 113 extracts intersections 502 between the vehicle passage determination area 501 set by the area setting unit 112 and roads that pass through the vehicle passage determination area 501. The extraction unit 113 extracts, for example, intersections 502 between the vehicle passage determination area 501 and all roads that intersect with the vehicle passage determination area 501. Here, all roads may be, for example, roads that the vehicle 200 can pass through, or may include roads that only pedestrians and light vehicles can pass through in addition to roads that the vehicle 200 can pass through. As an example, the extraction unit 113 may extract an intersection 502 between the vehicle passage determination area 501 and the road on the road map.

[0031] FIG. 3 is a diagram for explaining an example of the process of identifying the cluster point 503. In FIG.

[0032] The identifying unit 114 identifies the cluster points 503 (503A, 503B) based on the number of vehicles 200 that have passed through the vicinity of the intersection 502, for example. Specifically, the identification unit 114 acquires the number of vehicles 200 that have passed within a predetermined range from the intersection 502 extracted by the extraction unit 113, for example, based on the driving history information acquired by the acquisition unit 111, and identifies the intersection 502 where the number of vehicles 200 is greater than or equal to a threshold as a cluster point 503A related to entry.

[0033] For example, the identification unit 114 may acquire position information 505 that is relatively close to the intersection 502 (e.g., closest to the intersection 502) when the vehicle 200 passes through a vehicle passage determination area 501 while traveling on a road, based on travel history information (travel history information related to entry) based on a travel history of one trip from a departure point to the facility 400. In this case, for example, when the vehicle 200 passes near the intersection 502 while traveling from the outside to the inside of the vehicle passage determination area 501, the identification unit 114 may identify position information 505 near the intersection 502. The position information 505 may be included in, for example, the travel history information. That is, as illustrated in FIG. 3 , the identification unit 114 may acquire position information 505 that is within a predetermined range 504 from the intersection 502 (not shown in FIG. 3 ). The predetermined range 504 may be, for example, a range equal to or less than a preset distance. As a specific example, the predetermined range 504 may be a range having a radius of 10 m, 20 m, 30 m, 40 m, 50 m, 80 m, or 100 m or less from a reference position (for example, the intersection 502). The identification unit 114 may acquire a plurality of pieces of position information 505 that are relatively close to the intersection 502 (for example, the closest to the intersection 502) based on the travel history information of a plurality of vehicles. The identification unit 114 may acquire the number of vehicles 200 based on the number of pieces of position information 505 that are within the predetermined range 504 from the intersection 502.

[0034] When the number of acquired vehicles 200 is equal to or greater than a threshold, the identification unit 114 may identify the intersection 502 as a cluster point 503A related to entry (see FIG. 3(A)). The threshold is, for example, a value that is set in advance, and may be set appropriately depending on the number of entries into the facility 400 that is estimated in advance. As an example, the threshold may be various values ​​such as 10 vehicles, 20 vehicles, 30 vehicles, 40 vehicles, or 50 vehicles. In other words, if the number of acquired vehicles 200 is less than the threshold, the identifying unit 114 does not need to identify the intersection 502 as the cluster point 503A (see FIG. 3(B)).

[0035] Alternatively, the identification unit 114 may use at least one of the acquired multiple pieces of position information as a reference and acquire the number of other pieces of position information that are within a predetermined range from the reference piece of position information. The identification unit 114 may acquire the total number of the reference piece of position information and the other pieces of position information as the number of vehicles 200 that have passed within the predetermined range from the intersection 502.

[0036] Note that the identification unit 114 may also identify the cluster point 503 for exiting, for example, in the same way as for entering as described above. That is, the identification unit 114 may acquire position information that is relatively close to the intersection 502 (for example, closest to the intersection 502) when the vehicle 200 passes through the vehicle passage determination area 501 while traveling on a road, based on travel history information (travel history information related to exiting) based on the travel history of one trip from the facility 400 to the destination. In this case, for example, when the vehicle 200 passes near the intersection 502 while traveling from the inside to the outside of the vehicle passage determination area 501, the identification unit 114 may identify position information near the intersection 502. The identification unit 114 may acquire multiple pieces of position information that are relatively close to the intersection 502 (for example, closest to the intersection 502) based on travel history information of multiple vehicles. The identification unit 114 may acquire the number of vehicles 200 based on the number of pieces of position information that are within a predetermined range from the intersection 502. If the number of acquired vehicles 200 is equal to or greater than a threshold, the identification unit 114 may identify the intersection 502 as a cluster point 503B related to the exit.

[0037] The generation unit 115 generates association information by specifying the association between the cluster point 503A related to entry identified by the identification unit 114 and the entrance 411 through which the user entered the facility 400 after passing the cluster point 503, based on the travel history information acquired by the acquisition unit 111. For example, the generation unit 115 specifies the entrance 411 through which the user entered the facility 400 after passing the cluster point 503, based on the travel history information of one trip when the cluster point 503 was identified. For example, the generation unit 115 specifies the association (entry-related association) between the cluster point 503 and the corresponding entrance 411 after passing the cluster point 503, and generates association information.

[0038] Furthermore, in the case of exit, similarly to the case of entry described above, the generation unit 115 may also identify the association between the exit 412 of the facility 400 and the cluster point 503B (association related to exit). That is, when the cluster point 503B related to exit is identified by the identification unit 114 based on the driving history information at the time of exit, the generation unit 115 may identify the association between the exit 412 through which the user exited the facility 400 and the cluster point 503B related to exit that the user passed after exiting from the exit 412, based on the driving history information acquired by the acquisition unit 111, and include the association in the association information.

[0039] FIG. 4 is a diagram illustrating an example of the association information.

[0040] The association information illustrated in Fig. 4 is information relating to the association between identification information (cluster ID) for identifying cluster point 503 and facility 400 (an area within the facility such as a parking lot in the example illustrated in Fig. 4) entered after passing through cluster point 503. If the facility has multiple parking lots, each parking lot has an entrance 411 and an exit 412. Therefore, the control unit 110 can, for example, identify the parking lot and thereby identify the corresponding entrance 411 and exit 412.

[0041] Specifically, the association information illustrated in FIG. 4 is information on adjusted standardized residuals. More specifically, the association information illustrated in FIG. 4 is information obtained by calculating the bias as the difference between the expected value when all input relationships are equal and the actual value. Such association information (information on adjusted standardized residuals) makes it possible to determine which data groups have significant differences. In other words, in the association information illustrated in FIG. 4, it can be said that a data group (combination of cluster location and parking area) with a large residual (large numerical value) has a larger bias than the average, that is, is used more frequently than other combinations. Therefore, it can be said that a combination with a larger numerical value indicated by the association information has a higher correlation.

[0042] In the example shown in Figure 4, for example, a vehicle 200 that has passed through cluster point 503 with cluster ID "1" subsequently enters parking lot 2 of facility 400 relatively often and enters parking lot 1 of facility 400 relatively infrequently. In this case, the association information shows that the association between cluster ID "1" and parking lot 2 is relatively high, and the association between cluster ID "1" and parking lot 1 is relatively low.

[0043] 4, for example, a vehicle 200 that has passed through cluster point 503 with cluster ID "2" subsequently enters parking lot 1 of facility 400 relatively often and enters parking lot 2 of facility 400 relatively infrequently. In this case, the association information indicates that the association between cluster ID "2" and parking lot 1 is relatively high, and the association between cluster ID "1" and parking lot 2 is relatively low.

[0044] The generation unit 115 may record the generated association information in the map information. That is, the generation unit 115 may record, for example, association information including associations related to entry in the map information stored in the storage unit 122. Furthermore, the generation unit 115 may record, for example, association information including associations related to exit in the map information stored in the storage unit 122.

[0045] The route search unit 116 performs a route search to the facility 400 based on the association information generated by the generation unit 115. That is, the route search unit 116 may perform a route search for entering and exiting the facility 400 from the departure point based on, for example, map information (e.g., map information in which association information is recorded) stored in the storage unit 122. This allows the route search unit 116 to perform a route search to the entrance 411 according to, for example, a common route toward the facility 400.

[0046] As an example, when the route search unit 116 searches for a route with facility 400 as the destination, if a cluster point 503 is associated with facility 400, the route search unit 116 searches for a route with cluster point 503 as the intermediate point and entrance 411 associated with cluster point 503 as the destination.

[0047] Specifically, when searching for a route from the departure point to facility 400, the route search unit 116 may identify a cluster point 503A related to entry that is associated with facility 400 based on map information including association information (association related to entry) generated by the generation unit 115, and search for a route from the departure point via that cluster point 503A to an entrance 411 that has a relatively high association with cluster point 503A. That is, the route search unit 116, for example, identifies a cluster point 503 that is relatively close to the departure point, relatively close in the direction of the departure point, or relatively close to a stopover point after leaving the departure point, from among one or more cluster points 503. The route search unit 116 identifies an entrance 411 that has a relatively high correlation (for example, the highest correlation) with the identified cluster point 503A, for example, based on the correlation information. The route search unit 116 searches for a route from the departure point to the identified entrance 411, for example, via the identified cluster point 503A.

[0048] As another example, when the route search unit 116 performs a route search with the facility 400 as the destination, if the cluster point 503 is included in the route candidates obtained by the route search, the route search unit 116 sets the entrance 411 associated with the cluster point 503 as the arrival point. Specifically, the route search unit 116 may search for a route from the departure point to the facility 400 based on map information including correlation information (correlation related to entry) generated by the generation unit 115, for example, and if the searched route candidate includes a cluster point 503A related to entry, it may identify an entrance 411 that has a relatively high correlation with the cluster point 503A, and search for a route from the departure point to the entrance 411 via the cluster point 503A. That is, the route search unit 116 searches for a route from the departure point to the facility 400, for example. For example, if the cluster point 503A is included in the middle of the searched route candidates, the route search unit 116 identifies an entrance 411 that has a relatively high correlation with the cluster point 503A (for example, the entrance with the highest correlation) based on the correlation information. The route search unit 116 searches for a route from the departure point to the identified entrance 411, for example, via the cluster point 503A.

[0049] Furthermore, for example, when searching for a route to entrance 411 via cluster point 503A, if there are multiple route candidates, route search unit 116 may select a route with a relatively low cost (e.g., travel cost, etc.). In this case, route search unit 116 may select, for example, the route with the lowest cost. Alternatively, route search unit 116 may present, for example, multiple routes with relatively low costs, such as multiple routes in order of lowest cost, to the user, and allow the user to select one route.

[0050] Furthermore, for example, when searching for a route to entrance 411 via cluster point 503A and there are multiple route candidates, route search unit 116 may select a route in which the number of data items included in the cluster at cluster point 503A is relatively large (for example, the number of vehicles 200 that have passed through intersection 502 between vehicle passage determination area 501 and the road). In this case, route search unit 116 may select, for example, the route in which the number of data items included in the cluster is the largest. Alternatively, route search unit 116 may present, for example, multiple routes in which the number of data items included in the cluster is relatively large, for example, multiple routes in order of the number of data items included in the cluster, to the user, and allow the user to select one route.

[0051] Furthermore, the route search unit 116 may, for example, set priorities for multiple cluster points 503A in advance, and when multiple route candidates are found when searching for a route to the entrance 411 via the cluster point 503A, select a route with a relatively high priority for the cluster point 503A. In this case, the route search unit 116 may, for example, select a route with the highest priority for the cluster point 503A. Alternatively, the route search unit 116 may present to the user, for example, multiple routes with a relatively high priority for the cluster point 503A, such as multiple routes with a high priority for the cluster point 503A in descending order of priority, starting with the route with the highest priority for the cluster point 503A, and allow the user to select one route.

[0052] Furthermore, for example, when searching for a route to entrance 411 via cluster point 503A, if there are multiple route candidates, route search unit 116 may select a route that is free of traffic jams or a route with relatively little traffic jams. In this case, route search unit 116 may acquire road traffic information (e.g., traffic jam information, etc.) from a server or the like. A route with relatively little traffic jams may be, for example, a route with a relatively short distance from the beginning to the end of traffic jams, a route with a relatively short time to pass through traffic jams, etc.

[0053] The route search unit 116 may perform a route search for exiting, similar to the route search for entering described above. The route search unit 116 may perform a route search for exiting from the facility 400 toward a destination, for example, based on map information stored in the storage unit 122 (for example, map information in which association information is recorded, etc.). That is, as an example, when searching for a route from facility 400 to a destination, the route search unit 116 may identify the exit 412 associated with facility 400 based on map information including correlation information (correlation related to exit) generated by the generation unit 115, and search for a route from that exit 412 to the destination via cluster point 503B, which has a relatively high correlation. Alternatively, as an example, the route search unit 116 may search for a route from the facility 400 to the destination based on map information including correlation information (correlation related to exits) generated by the generation unit 115, and if a cluster point 503B related to exits is included in the middle of the searched route candidates, the route search unit 116 may identify an exit 412 that has a relatively high correlation with the cluster point 503B, and search for a route from the identified exit 412 to the destination via the cluster point 503B.

[0054] The output control unit 117 may control the output unit to output at least one selected from the group of the cluster points 503 (503A, 503B) identified by the identification unit 114, the association information (association) generated by the generation unit 115, and the route searched by the route search unit 116. The output unit may be, for example, the communication unit 121, the storage unit 122, the display unit 123, etc. That is, the output control unit 117 may control the communication unit 121 to transmit at least one selected from the group of the cluster points 503 (503A, 503B), the association information (association), and the route to an external device. Here, the external device may be, for example, the server 300, the vehicle 200, a user terminal (not shown), etc. The output control unit 117 may control the storage unit 122 to store at least one selected from the group of, for example, the cluster points 503 (503A, 503B), the association information (association), and the route. The output control unit 117 may control the display unit 123 to display at least one selected from the group of, for example, the cluster points 503 (503A, 503B), the association information (association), and the route.

[0055] Furthermore, the output control unit 117 may control the output unit to output, for example, map information in which the association information is recorded. That is, the output control unit 117 may control the communication unit 121 to transmit the map information in which the association information is recorded to an external device, or may control the display unit 123 to display the map information in which the association information is recorded. As described above, the external device may be, for example, the server 300, the vehicle 200, or a user terminal (not shown), etc.

[0056] [Information processing method] Next, an information processing method according to an embodiment will be described. FIG. 5 is a flowchart illustrating an information processing method according to an embodiment.

[0057] In step ST101, the acquisition unit 111 acquires driving history information relating to a driving history in which the vehicle 200 entered the facility 400 through one of a plurality of entrances 411 associated with the facility 400. The acquisition unit 111 may also acquire driving history information relating to a driving history in which the vehicle 200 exited the facility 400 through one of a plurality of exits 412 associated with the facility 400.

[0058] In step ST102, the area setting unit 112 sets a vehicle passage determination area 501 at a position a predetermined distance away from the facility 400.

[0059] In step ST103, the extraction unit 113 extracts an intersection 502 between the vehicle passage determination area 501 set in step ST102 and a road passing through the vehicle passage determination area 501.

[0060] In step ST104, the identification unit 114 acquires the number of vehicles 200 that have passed within a predetermined range from the intersection 502 extracted in step ST103 based on the travel history information acquired in step ST101, and identifies the intersection 502 at which the number of vehicles 200 is equal to or greater than a threshold as an entry-related cluster point 503A. That is, the identification unit 114 identifies the entry-related cluster point 503A based on the entry-related travel history information. Similarly, a cluster point 503B relating to the exit is identified based on driving history information relating to the exit.

[0061] In step ST105, the generation unit 115 generates association information (entry-related association information) by identifying the association between the cluster point 503A related to entry identified in step ST104 and the entrance 411 through which the user entered the facility 400 after passing through the cluster point 503A, based on the driving history information related to entry acquired in step ST101. Similarly, when a cluster point 503B related to exit is identified based on the driving history information related to exit acquired in step ST101, the generation unit 115 may identify the correlation between the exit 412 through which the vehicle exited the facility 400 and the cluster point 503B related to exit that was passed after exiting from that exit 412 based on the driving history information, and generate correlation information (correlation information related to exit). The associated information regarding entry and the associated information regarding exit may be different pieces of information, or may be a single piece of information that combines them.

[0062] In step ST106, the generating unit 115 records the association information generated in step ST105 in the map information.

[0063] In step ST107, the route search unit 116 performs a route search for the facility 400 based on, for example, the map information in step ST106.

[0064] As an example of a route search from the departure point to the facility 400, the route search unit 116 may identify a cluster point 503A related to entry that is associated with the facility 400 based on map information, and perform a route search from the departure point via the cluster point 503A to an entrance 411 that has a relatively high correlation with the cluster point 503A. Alternatively, as an example of a route search from the departure point to the facility 400, the route search unit 116 may search for a route from the departure point to the facility 400 based on map information, and if the searched route candidate includes a cluster point 503A related to entry, it may identify an entrance 411 that has a relatively high correlation with the cluster point 503A, and search for a route from the departure point to the entrance 411 via the cluster point 503A.

[0065] As an example of a route search from facility 400 to the destination, the route search unit 116 may identify an exit 412 associated with facility 400 based on map information, and perform a route search from the exit 412 to the destination via cluster point 503B, which has a relatively high correlation. Alternatively, as an example of a route search from facility 400 to the destination, the route search unit 116 may search for a route from facility 400 to the destination based on map information, and if the searched route candidates include a cluster point 503B related to an exit, it may identify an exit 412 that has a relatively high correlation with that cluster point 503, and search for a route from the identified exit 412 to the destination via that cluster point 503B.

[0066] In step ST108, the output control unit 117 may control the output unit to output at least one selected from the group of the cluster points 503 (503A, 503B) identified in step ST104, the association information (association) generated in step ST105, the map information in which the association information is recorded in step ST106, and the route searched for in step ST107. The output unit may be, for example, the communication unit 121, the storage unit 122, the display unit 123, etc.

[0067] Each unit of the information processing device 100 described above may be realized as a function of a computer's arithmetic processing unit, etc. That is, the acquisition unit 111, area setting unit 112, extraction unit 113, generation unit 115, route search unit 116, and output control unit 117 (control unit 110) of the information processing device 100 may be realized as an acquisition function, area setting function, extraction function, generation function, route search function, and output control function (control function), respectively, by a computer's arithmetic processing unit, etc. The information processing program can cause a computer to realize each of the above-mentioned functions. The information processing program may be recorded on a non-transitory computer-readable recording medium, such as a memory, a solid-state drive, a hard disk drive, or an optical disk. The recording medium may also be referred to as a non-transitory computer-readable medium. Furthermore, as described above, each unit of the information processing device 100 may be realized by an arithmetic processing unit of a computer or the like. The arithmetic processing unit or the like is configured by, for example, an integrated circuit or the like. Therefore, each unit of the information processing device 100 may be realized as a circuit that constitutes the arithmetic processing unit or the like. That is, the acquisition unit 111, the area setting unit 112, the extraction unit 113, the generation unit 115, the route search unit 116, and the output control unit 117 (control unit 110) of the information processing device 100 may be realized as an acquisition circuit, an area setting circuit, an extraction circuit, a generation circuit, a route search circuit, and an output control circuit (control circuit) that constitute the arithmetic processing unit of a computer or the like. Furthermore, the communication unit 121, the storage unit 122, and the display unit 123 (output unit) of the information processing device 100 may be realized as a communication function, a storage function, and a display function (output function) including the functions of an arithmetic processing device, etc. Furthermore, the communication unit 121, the storage unit 122, and the display unit 123 (output unit) of the information processing device 100 may be realized as a communication circuit, a storage circuit, and a display circuit (output circuit) by being configured, for example, by an integrated circuit, etc. Furthermore, the communication unit 121, the storage unit 122, and the display unit 123 (output unit) of the information processing device 100 may be configured as a communication device, a storage device, and a display device (output device) by being configured, for example, by being configured by a plurality of devices.

[0068] The information processing device 100 can combine one or any combination of the above-mentioned multiple units. In this disclosure, the term "information" is used, but the term "information" can be replaced with "data" and the term "data" can be replaced with "information."

[0069] [Aspects and Effects of the Present Embodiment] Next, one aspect of this embodiment and the effects of each aspect will be described. Note that each aspect described below is an example at the time of filing, and this embodiment is not limited to the aspects described below. In other words, this embodiment is not limited to the aspects described below, and may be realized by appropriately combining the above-mentioned parts. Furthermore, a lower-level aspect may be able to cite any of the higher-level aspects. The effects described below are merely examples, and the effects of each aspect are not limited to those described below. Each aspect may, for example, achieve at least one of the effects described below.

[0070] (Aspect 1) An information processing device of one embodiment includes an acquisition unit that acquires driving history information regarding a driving history of a vehicle entering a facility through one of a plurality of entrances associated with the facility; an area setting unit that sets a vehicle passage determination area at a predetermined distance from the facility; an extraction unit that extracts an intersection between the vehicle passage determination area set by the area setting unit and a road that passes through the vehicle passage determination area; an identification unit that acquires the number of vehicles that have passed within a predetermined range from the intersection extracted by the extraction unit based on the driving history information acquired by the acquisition unit, and identifies an intersection where the number of vehicles is equal to or greater than a threshold as a cluster point related to entry; and a generation unit that generates association information by identifying the association between the cluster point related to entry identified by the identification unit and an entrance through which the vehicle entered the facility after passing through the cluster point based on the driving history information acquired by the acquisition unit. The information processing device can identify the correlation of entrances through which vehicles enter a facility by route (e.g., by road line) of the road leading to the facility based on the vehicle's driving history information. The information processing device can also identify passing points (e.g., cluster points) where a threshold or more of vehicles pass, and identify the correlation between the cluster points and the entrances. This allows the information processing device to select an appropriate entrance depending on the route the vehicle is traveling, even if there are multiple entrances corresponding to the facility. In other words, the information processing device can use the association information to identify an entrance that is appropriate for the route the vehicle is taking to the facility.

[0071] (Aspect 2) In one embodiment of an information processing device, the acquisition unit acquires driving history information regarding the driving history of a vehicle exiting a facility from one of multiple exits associated with the facility, and when the identification unit identifies a cluster point related to the exit based on the driving history information at the time of exit, the generation unit may identify a correlation between the exit from the facility through which the vehicle exited and the cluster point related to the exit that was passed through after exiting from that exit based on the driving history information acquired by the acquisition unit, and include the correlation information. As a result, the information processing device can identify the connectivity of entrances through which vehicles enter the facility based on the route of the road leading to the facility (e.g., by line, etc.), as well as the connectivity of exits through which vehicles exit the facility based on the route of the road after leaving the facility (e.g., by line, etc.). The information processing device can use the association information to identify an exit that is suitable for the route the vehicle will take after leaving the facility.

[0072] (Aspect 3) The information processing device according to one aspect may include a storage unit that stores map information relating to a road map, and the generation unit may record the generated association information in the map information. This allows the information processing device to perform route searches and the like using map information in which association information is recorded.

[0073] (Aspect 4) In one embodiment, the information processing system may include a route search unit that, when searching for a route from a departure point to a facility, identifies cluster points related to entry associated with the facility based on map information including correlation information generated by the generation unit, and searches for a route from the departure point via the cluster points to an entrance that has a relatively high correlation with the cluster points. The information processing system can search for a route via cluster points related to entrances. That is, the information processing system can use map information in which association information is recorded to identify an entrance that is suitable for a route when a vehicle heads from a departure point to a facility, and search for a route to that entrance. As a result, if there is a regular route to the facility that is traveled by a relatively large number of vehicles, the information processing system can search for a route to the entrance that corresponds to that route.

[0074] (Aspect 5) An information processing system according to one embodiment may be provided with a route search unit that searches for a route from a departure point to a facility based on map information including correlation information generated by a generation unit, and if the searched route candidate includes a cluster point related to entry, identifies an entrance that has a relatively high correlation with the cluster point, and searches for a route from the departure point to the entrance via the cluster point. The information processing system can search for a route via cluster points related to entrances. That is, the information processing system can use map information in which association information is recorded to identify an entrance that is suitable for a route when a vehicle heads from a departure point to a facility, and search for a route to that entrance. As a result, if there is a standard route to the facility, the information processing system can search for a route to the entrance that corresponds to that route.

[0075] (Aspect 6) In one aspect of the information processing method, a computer executes the following steps: an acquisition step of acquiring driving history information relating to the driving history of a vehicle entering a facility through one of multiple entrances associated with the facility; an area setting step of setting a vehicle passage determination area at a predetermined distance from the facility; an extraction step of extracting an intersection between the vehicle passage determination area set by the area setting step and a road that passes through the vehicle passage determination area; an identification step of acquiring, based on the driving history information acquired by the acquisition step, the number of vehicles that have passed within a predetermined range from the intersection extracted by the extraction step, and identifying an intersection where the number of vehicles is equal to or greater than a threshold as a cluster point related to entry; and a generation step of identifying, based on the driving history information acquired by the acquisition step, the correlation between the cluster point related to entry identified by the identification step and an entrance through which the vehicle entered the facility after passing through the cluster point, and generating correlation information. As a result, the information processing method may achieve the same effect as the information processing device of the above-described aspect.

[0076] (Aspect 7) An information processing program in one embodiment causes a computer to implement the following: an acquisition function that acquires driving history information regarding the driving history of a vehicle entering a facility through one of multiple entrances associated with the facility; an area setting function that sets a vehicle passage determination area at a predetermined distance from the facility; an extraction function that extracts an intersection between the vehicle passage determination area set by the area setting function and a road that passes through the vehicle passage determination area; an identification function that acquires the number of vehicles that have passed within a predetermined range from the intersection extracted by the extraction function based on the driving history information acquired by the acquisition function, and identifies intersections where the number of vehicles is greater than or equal to a threshold as cluster points related to entry; and a generation function that generates association information by identifying the association between the cluster point related to entry identified by the identification function and an entrance through which the vehicle entered the facility after passing through the cluster point based on the driving history information acquired by the acquisition function. As a result, the information processing program may achieve the same effect as the information processing device of the above-described aspect.

[0077] (Aspect 8) In one embodiment, the information processing system may include a route search unit that, when searching for a route from a facility to a destination, identifies an exit associated with the facility based on map information including correlation information generated by the generation unit, and searches for a route from the exit to the destination via cluster points with relatively high correlation. The information processing system can search for a route via cluster points for exiting a facility, similar to the route search for entering a facility. In other words, the information processing system can use map information in which association information is recorded to identify an exit that is suitable for a route when a vehicle heads from a facility to a destination, and search for a route from that exit to the destination. As a result, if there is a regular route after exiting the facility that is traveled by a relatively large number of vehicles, the information processing system can perform a route search from the exit that corresponds to that route.

[0078] (Aspect 9) An information processing system according to one embodiment may include a route search unit that searches for a route from a facility to a destination based on map information including correlation information generated by a generation unit, and if the searched route candidate includes a cluster point related to an exit, identifies an exit that has a relatively high correlation with the cluster point, and searches for a route from the identified exit to the destination via the cluster point. The information processing system can search for a route via cluster points for exiting a facility, similar to the route search for entering a facility. In other words, the information processing system can use map information in which association information is recorded to identify an exit that is suitable for a route when a vehicle heads from a facility to a destination, and search for a route from that exit to the destination. As a result, if there is a standard route after exiting the facility, the information processing system can perform a route search from the exit that corresponds to that route. [Explanation of symbols]

[0079] 100 Information processing device 110 control section 111 Acquisition Department 112 Area setting section 113 Extraction part 114 Specific section 115 Generation part 116 Route Search Unit 117 Output control section 121 Communications Department 122 Storage section 123 Display section 200 vehicles 300 servers 400 facilities 411 Entrance 412 Exit 501 Vehicle passage judgment area 502 intersection 503(503A,503B) Cluster location

Claims

1. an acquisition unit that acquires travel history information relating to a travel history of a vehicle entering a facility through any one of a plurality of entrances associated with the facility; an area setting unit that sets a vehicle passage determination area at a position a predetermined distance away from the facility; an extraction unit that extracts an intersection between the vehicle passage determination area set by the area setting unit and a road that passes through the vehicle passage determination area; an identification unit that acquires the number of vehicles that have passed within a predetermined range from the intersection extracted by the extraction unit based on the travel history information acquired by the acquisition unit, and identifies an intersection where the number of vehicles is equal to or greater than a threshold as a cluster point related to entry; a generating unit that generates association information by identifying an association between the cluster point related to entry identified by the identifying unit and an entrance through which the user entered the facility after passing through the cluster point, based on the travel history information acquired by the acquiring unit; and An information processing device comprising:

2. the acquisition unit acquires driving history information relating to a driving history in which the vehicle exited from any one of a plurality of exits associated with the facility; When the identification unit identifies a cluster point related to an exit based on the driving history information at the time of exit, the generation unit identifies a correlation between the exit through which the vehicle exited the facility and the cluster point related to an exit that the vehicle passed through after exiting the exit based on the driving history information acquired by the acquisition unit, and includes the correlation information in the correlation information. The information processing device according to claim 1 .

3. a storage unit for storing map information relating to a road map; The generating unit records the generated association information in map information.

3. The information processing device according to claim 1 or 2.

4. The information processing device according to claim 3, The system further includes a route search unit that, when searching for a route from a departure point to a facility, identifies cluster points related to entrances associated with the facility based on map information including association information generated by the generation unit, and searches for a route from the departure point to an entrance that has a relatively high association with the cluster points via the cluster points. Information processing system.

5. The system further comprises a route search unit that searches for a route from a departure point to a facility based on map information including the association information generated by the generation unit according to claim 3, and if a cluster point related to entrance is included in the searched route candidate, identifies an entrance that has a relatively high association with the cluster point, and searches for a route from the departure point to the entrance via the cluster point. Information processing system.

6. The computer an acquisition step of acquiring travel history information relating to a travel history of a vehicle entering the facility through any one of a plurality of entrances associated with the facility; an area setting step of setting a vehicle passage determination area at a position a predetermined distance away from the facility; an extraction step of extracting an intersection between the vehicle passage determination area set by the area setting step and a road passing through the vehicle passage determination area; an identification step of acquiring the number of vehicles that have passed within a predetermined range from the intersection extracted by the extraction step based on the travel history information acquired by the acquisition step, and identifying an intersection where the number of vehicles is equal to or greater than a threshold as an entry-related cluster point; a generating step of generating association information by identifying associations between the cluster points related to entry identified in the identifying step and the entrances through which the user entered the facility after passing through the cluster points, based on the travel history information acquired in the acquiring step; An information processing method that performs the above.

7. On the computer, an acquisition function for acquiring driving history information relating to a driving history in which a vehicle has entered the facility through any one of a plurality of entrances associated with the facility; an area setting function for setting a vehicle passage determination area at a position a predetermined distance away from the facility; an extraction function for extracting an intersection between the vehicle passage determination area set by the area setting function and a road passing through the vehicle passage determination area; a specifying function that obtains the number of vehicles that have passed within a predetermined range from the intersection extracted by the extracting function based on the travel history information obtained by the obtaining function, and specifies an intersection where the number of vehicles is equal to or greater than a threshold as an entry-related cluster point; a generation function that generates association information by identifying an association between the cluster point related to the entry identified by the identification function and the entrance through which the user entered the facility after passing through the cluster point, based on the travel history information acquired by the acquisition function; and An information processing program that makes this possible.

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