Information processing device

Abstract

To suppress calculation cost when executing estimation of drop-in facilities of parking vehicles.SOLUTION: A server device 1 acquires parking position information concerning each parking position from a plurality of vehicles V at a drop-in facility candidate selection section 12, and selects the candidates of facilities in which occupants of each vehicle V are estimated to have dropped in. The drop-in facility candidate selection section 12 selects a candidate of each drop-in facility on the basis of a facility (a neighbor facility) included in a first range set for a parking position held by a parking position DB22 and a parking position included in a second range set for a position of a large facility estimated by a large facility estimation section 11.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information processing device that performs a predetermined process based on information about a parking position of a vehicle. [Background technology]

[0002] It is common to estimate facilities used by a user in a vehicle such as an automobile. The results of such estimation can be used, for example, to guide the user to recommended facilities.

[0003] Patent Document 1 discloses a document that automatically identifies facilities that are estimated to have been used by a user. The invention described in this document associates estimated parking areas and stay times based on probe information with each facility and stores them as facility visit information, and estimates the facilities that the driver of the vehicle has visited based on this facility visit information. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-21847 Summary of the Invention [Problem to be solved by the invention]

[0005] As in Patent Document 1, when extracting facilities within a predetermined range based on the parking location and estimating visited facilities, the following problem occurs. For example, when searching for facilities near the parking location, in order to identify facilities such as shopping malls and amusement parks that have large parking lots and whose parking locations are far from the facility as potential stop-off facilities, it may be necessary to set a large search radius. However, setting a large search radius results in more extracted facilities, and the amount of calculation required to estimate stop-off facilities increases.

[0006] Therefore, when estimating stopover facilities for many parked vehicles, the cost of searching for nearby facilities for the number of parking positions becomes high, and the cost of estimating facilities for the number of facilities included in the search radius becomes high.

[0007] One example of a problem to be solved by the present invention is to reduce the calculation cost when estimating facilities where a parked vehicle will stop. [Means for solving the problem]

[0008] In order to solve the above problem, the invention described in claim 1 includes an acquisition unit that acquires parking position information regarding a parking position of a vehicle, and a selection unit that selects, from a plurality of facilities, candidates for a facility that is estimated to have been visited by a passenger of the vehicle, and the selection unit selects a candidate for a facility that is estimated to have been visited by a passenger of the vehicle within a first range set for the parking position indicated by the parking position information. The facilities included in and a second range set for a position of a large facility among the plurality of facilities and larger than the first range. The parking position included in and selecting the candidate vehicle based on the above. The invention described in claim 2 comprises an acquisition unit that acquires parking location information regarding the parking location of a vehicle, and a selection unit that selects candidate facilities from among a plurality of facilities that are presumed to have been visited by the vehicle's occupants, wherein the selection unit selects as the candidates facilities that are located within a first range set for the parking location indicated by the parking location information, and large facilities that are included in the plurality of facilities and that include the parking location within a second range set for the large facility, and wherein the second range is larger than the first range.

[0009] The invention described in claim 7 is an information processing method executed by an information processing device that performs a predetermined process based on information about a parking position of a vehicle, and includes an acquisition step of acquiring parking position information about the parking position of the vehicle, and a selection step of selecting, from a plurality of facilities, candidates for a facility that is presumed to have been visited by a passenger of the vehicle, wherein the selection step is performed within a first range set for the parking position indicated by the parking position information. Facilities located within, and , the plurality of facilities Included in Large facilities and the facility is designated Second Range A large facility including the parking location therein, The candidate as Selection and the second range is greater than the first range. It is characterized by the following.

[0010] The invention as set forth in claim 8 is characterized in that the information processing method as set forth in claim 7 is executed by a computer.

[0011] The invention described in claim 9 is characterized in that the information processing program described in claim 8 is stored in a computer-readable storage medium. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a schematic configuration diagram of a system including an information processing device according to an embodiment of the present invention; [Figure 2] FIG. 2 is a functional configuration diagram of the server device shown in FIG. [Figure 3] 10 is an example showing the relationship between parking locations and each facility. [Figure 4] 4 is a table summarizing the candidates selected for the parking position in FIG. 3. [Figure 5] FIG. 10 is an explanatory diagram showing a second range from a large facility. [Figure 6] This is a table summarizing parking locations within an area centered around a large facility. [Figure 7] 6 is a table showing potential stop-off facilities, data sources, and scores for the parking locations shown in Figures 3 and 5. [Figure 8] 3 is a flowchart of the operation of the server device shown in FIG. 2. [Figure 9] FIG. 10 is an explanatory diagram of a modified example of the second range. DETAILED DESCRIPTION OF THE INVENTION

[0013] An information processing device according to one embodiment of the present invention will be described below. In the information processing device according to one embodiment of the present invention, an acquisition unit acquires parking location information relating to the parking locations of multiple vehicles, and a selection unit selects candidate facilities where occupants of each vehicle are presumed to have stopped. The selection unit selects candidate facilities where each vehicle is presumed to have stopped based on a first range set for the parking location indicated by the parking location information and a second range set for the location of a large facility selected from the multiple facilities. This allows candidate stop-off facilities to be selected based not only on the first range set for the parking location but also on the second range set for the location of the large facility. Therefore, the first range is not expanded more than necessary, and the extraction of many facilities other than large facilities is prevented, thereby reducing calculation costs when estimating stop-off facilities for parked vehicles.

[0014] The selection unit may also select candidate facilities presumed to have been visited based on facilities included in the first range and parking locations included in the second range. In this way, for large facilities, it is sufficient to select only parking locations included in the second range as candidate facilities presumed to have been visited, thereby reducing the amount of calculation and suppressing calculation costs.

[0015] The system may further include a large facility estimation unit that estimates large facilities based on information on a plurality of facilities, and the selection unit may set a second range for the large facilities estimated by the large facility estimation unit. In this way, large facilities can be estimated in advance based on information on a plurality of facilities, and candidate facilities that are estimated to have been visited by the vehicle passengers can be selected based on the estimated large facilities.

[0016] The system may also include a stopover facility estimation unit that estimates stopover facilities from the candidates selected by the selection unit. In this way, it is possible to identify one facility that is estimated to have been visited by the passenger from the candidates selected by the selection unit.

[0017] The second range may also be set as a range centered on the true position of the large facility, thereby allowing the range to be set in a well-balanced manner in terms of distance from the large facility.

[0018] Furthermore, the second range may be increased or decreased for any portion based on past performance information. By doing so, if the parking locations estimated to be used for stopping at the large facility are unevenly distributed, the distance from the large facility to the outer edge of the second range can be increased or decreased depending on the uneven distribution. This improves the accuracy of selecting candidate stop-off facilities.

[0019] In addition, in an information processing method according to one embodiment of the present invention, an acquisition step acquires parking location information regarding the parking locations of each of a plurality of vehicles, and a selection step selects candidate facilities where occupants of each vehicle are presumed to have stopped. In the selection step, candidate facilities where each vehicle is presumed to have stopped are selected based on a first range set for the parking location indicated by the parking location information and a second range set for the location of a large facility selected from the plurality of facilities. In this manner, candidate stop facilities can be selected based not only on the first range set for the parking location but also on the second range set for the location of the large facility. Therefore, the first range is not expanded more than necessary, and the extraction of many facilities other than large facilities is prevented, thereby reducing calculation costs when estimating stop facilities for parked vehicles.

[0020] Furthermore, the above-described information processing method may be executed by a computer as an information processing program. By doing so, the computer can select candidate stop-off facilities based on not only a first range set for the parking position but also a second range set for the location of the large facility. Therefore, the first range is not expanded more than necessary, and the extraction of many facilities other than large facilities is prevented, thereby reducing the calculation cost when estimating stop-off facilities for a parked vehicle.

[0021] The information processing program may be stored in a computer-readable storage medium, which allows the program to be distributed as a standalone program rather than being incorporated into a device, and allows for easy version upgrades. [Example]

[0022] An information processing device according to an embodiment of the present invention will be described with reference to Figures 1 to 9. Figure 1 is a schematic diagram of a system including an information processing device according to this embodiment.

[0023] 1 includes a server device 1 as an information processing device. The server device 1 acquires probe information such as location information from a vehicle V via a wireless communication network, a network N including an interface, and performs various processes described below.

[0024] The server device 1 is a well-known server computer, and includes a computing device such as a CPU (Central Processing Unit), a storage device such as an HDD (Hard Disk Drive), and a communication device such as a network interface.

[0025] 2 shows the functional configuration of the server device 1. The server device 1 includes a large facility estimation unit 11, a candidate stop-off facility selection unit 12, a stop-off facility estimation unit 13, a facility DB 21, and a parking location DB 22.

[0026] The large facility estimation unit 11 estimates, from the facility information contained in the facility DB21, facilities that meet the following conditions, for example, as large facilities: (1) The facility genre is a specific genre (a genre generally considered to be a large facility, such as an amusement park, natural park, or shopping mall). (2) The facility has a large number of parking lots. (3) The facility has a large number of parking lot entrances (large parking area). In other words, the large facility estimation unit 11 estimates large facilities based on information on multiple facilities. Note that, without providing the large facility estimation unit 11, large facilities may be selected manually from facilities contained in the facility DB21 in advance, and information indicating a large facility (such as a mark or flag) may be added to the selected large facilities in the facility DB21.

[0027] The candidate stop-off facility selection unit 12 acquires information from the parking location DB 22 and selects candidate stop-off facilities for the vehicle parking location from nearby facilities within a predetermined range from the vehicle parking location included in the information and vehicle parking locations within a predetermined range from the true location of the large facility estimated by the large facility estimation unit 11. The true location of the large facility is the location where the large facility actually exists, such as the location of the center of the large facility. In other words, the candidate stop-off facility selection unit 12 functions as an acquisition unit that acquires parking location information regarding each parking location from multiple vehicles and as a selection unit that selects candidate facilities where occupants of each vehicle are estimated to have stopped.

[0028] The stop-off facility estimation unit 13 ranks the stop-off facility candidates selected by the stop-off facility candidate selection unit 12, and estimates a stop-off facility for the vehicle parking position.

[0029] The facility DB 21 is a database that manages facility information (facility name, facility genre, number of parking lots owned, number of parking lot entrances, etc.) for a plurality of facilities.

[0030] The parking position DB22 is a database that manages the parking position of the vehicle V. The parking position DB22 stores probe information including, for example, vehicle position (latitude and longitude) information and time information transmitted from the vehicle V. The probe information may be transmitted when the vehicle V determines that the vehicle is parked. Alternatively, the vehicle V may transmit position information and the like regardless of whether the vehicle is parked, and the server device 1 (or another server device, etc.) may determine whether the vehicle is parked, and only the probe information related to parking may be stored in the parking position DB22.

[0031] The large facility estimation unit 11, the candidate stop-off facility selection unit 12, and the stop-off facility estimation unit 13 are configured as computer programs (information processing programs) executed by, for example, a CPU of the server device 1. The facility DB 21 and the parking location DB 22 are included in the database 2.

[0032] Next, the operation of selecting candidate stop-off facilities in the candidate stop-off facility selecting unit 12 will be described with reference to FIGS.

[0033] FIG. 3 is an example showing the relationship between parking positions and each facility. FIG. 3 shows the positional relationship on a map, for example, but to simplify the drawing, only the positions of the parking positions and facilities are shown. In FIG. 3, parking positions include parking positions P1 to P4, and facilities include facilities a to g and large facility A. Here, large facility A is a facility that has been estimated as a large facility by large facility estimation unit 11. Furthermore, facilities a to g are general facilities that have not been estimated as large facilities.

[0034] First, similar to conventional stop-off location estimation operations, nearby facilities within a predetermined range from a parking location included in the parking location DB 22 are selected as stop-off facility candidates. In the example of FIG. 3, a range with a radius of several tens to several hundreds of meters is set around the parking location. The range corresponding to parking location P1 is indicated as AP1, the range corresponding to parking location P2 as AP2, the range corresponding to parking location P3 as AP3, and the range corresponding to parking location P4 as AP4. In other words, the range AP1 to AP4 is the first range set for the parking location indicated by the parking location information. For example, since facilities a to c are included in range AP1, the candidates selected for parking location P1 are facilities a to c. The same process is performed for parking locations P2 to P4. The candidates (stop-off facility candidates) selected for parking locations P1 to P4 in FIG. 3 are summarized in FIG. 4.

[0035] Next, nearby parking locations within a predetermined range from large facility A are searched for. Large facility A is then added to the list of nearby parking and stopping location candidates. Figure 5 shows a predetermined range, AA, centered on the true location of large facility A. Note that Figure 5 also shows a range AB for another large facility, large facility B (large facility B itself is assumed to be outside the illustrated range of Figure 5). In other words, ranges AA and AB are second ranges set for the location of a large facility selected from multiple facilities. In the example of Figure 5, a range with a radius of several hundred meters is set centered on large facility A. Note that the range centered on the large facility is set to be larger than the range centered on the parking location shown in Figure 3. In the case of Figure 5, range AA includes parking locations P1 to P4. The same process is performed for range AB. Figure 6 summarizes the parking locations included in the ranges centered on large facilities A and B in Figure 5.

[0036] Then, candidate stop-off facilities are determined for each parking location from the nearby facilities selected within the range centered on the parking location and the parking locations included in the range centered on the large facility. For example, in the case of parking location P1 as shown in Figures 4 and 6, facilities a to c and large facility A are candidates. In other words, candidate stop-off facilities are selected for each vehicle based on the first range and the second range.

[0037] The stop-off facility estimation unit 13 estimates stop-off facilities by scoring the candidates selected by the stop-off facility candidate selection unit 12. Scoring may be calculated using a well-known method based on the number of visits to the facility, the distance between the parking position and the actual location of the facility, the length of stay, etc.

[0038] FIG. 7 shows examples of candidate stop-off facilities (candidate stop-off facilities), data sources, and scores for parking positions P1 to P4 shown in FIG. 3 and FIG. 5. In the case of FIG. 7, for parking position P1, large facility A with the highest score is estimated to be the stop-off facility. For parking position P2, facility d with the highest score is estimated to be the stop-off facility. For parking position P3, facility g with the highest score is estimated to be the stop-off facility. For parking position P4, large facility B with the highest score is estimated to be the stop-off facility.

[0039] The above-described operation of the server device 1 is summarized in the flowchart of Fig. 8. First, the large facility estimation unit 11 extracts large facilities from the facility DB 21 (step S1).

[0040] Next, the stop-off facility candidate selection unit 12 extracts, as a first stop-off facility candidate group, facilities near the parking location group stored in the parking location DB 22 other than the large facilities extracted in the previous process (step S2). That is, the facilities included in the range AP1 to AP4 in FIG. 3 are extracted.

[0041] Next, the stop-off facility candidate selection unit 12 extracts parking positions near each large facility as a second stop-off facility candidate group (step S3), that is, extracts parking positions included in ranges AA and AB in FIG.

[0042] Next, the stop-off facility candidate selection unit 12 merges the first stop-off facility candidate group and the second stop-off facility candidate group on a parking location basis (step S4). The merged stop-off facility candidates become the stop-off facility candidates for each parking location. That is, a table like the one shown in FIG. 7 is generated. However, in this step, the scores have not yet been calculated.

[0043] Next, the stop-off facility estimation unit 13 scores the parking positions and the corresponding stop-off facility candidates (step S5). That is, the score column in FIG. 7 is filled in.

[0044] Then, the stop-off facility estimation unit 13 estimates the stop-off facility for each parking position from the scoring result (step S6).

[0045] According to this embodiment, the server device 1 has a candidate stop-off facility selection unit 12 that acquires parking position information regarding the parking positions of each of the multiple vehicles V, and selects candidate facilities that are estimated to have been stopped at by passengers of each of the vehicles V. The candidate stop-off facility selection unit 12 selects candidate stop-off facilities for each of the vehicles based on facilities (neighboring facilities) that are included in a first range set for the parking positions stored in the parking position DB 22, and parking positions that are included in a second range set for the position of the large facility estimated by the large facility estimation unit 11.

[0046] By doing this, candidate stop-off facilities can be selected based not only on the first range set for the parking location but also on the second range set for the location of the large facility. Therefore, the first range is not expanded more than necessary, and the extraction of many facilities other than large facilities is suppressed. For large facilities, only parking locations included in the second range need to be selected as candidate facilities that are estimated to have stopped off at the large facility. Therefore, calculation costs can be reduced when estimating stop-off facilities for a parked vehicle.

[0047] In particular, when estimating multiple stopover locations using batch processing or the like under the condition that the number of parking locations is greater than the number of large facilities, the computational cost of searching for nearby locations can be reduced by selecting candidate stopover facilities based on a second range starting from the true location of the large facility.

[0048] The server device 1 also includes a large facility estimation unit 11 that estimates large facilities based on the facility DB 21, and the candidate stop-off facility selection unit 12 sets a second range for the large facilities estimated by the large facility estimation unit 11. In this way, large facilities can be estimated in advance based on a plurality of facility information, and candidate facilities that are estimated to have been stopped at by the vehicle passengers can be selected based on the estimated large facilities.

[0049] The server device 1 also includes a stop-off facility estimation unit 13 that estimates a stop-off facility from the candidates selected by the stop-off facility candidate selection unit 12. In this way, it is possible to identify one facility that is estimated to have been visited by the passenger from the candidates selected by the stop-off facility candidate selection unit 12.

[0050] The second range is set with the true position of the large facility at its center, allowing the range to be set with a good balance in terms of distance from the large facility.

[0051] In the above-described embodiment, the second range is set as a range centered on the true location of the large facility. However, the second range may be increased or decreased in any part based on past performance information. That is, the server device 1 may have statistical information on parking locations where vehicles have stopped at the facility in the past, and the statistical information may be used as performance information to increase or decrease the second range in part. For example, as shown in FIG. 9, for the second range AC of a large facility C, the range in the upper part of the figure may be increased (AC1) or the range in the right part of the figure may be decreased (AC2) based on past performance information. By doing so, if the parking locations estimated to have been used for stopping at the large facility are unevenly distributed, the distance from the large facility to the outer edge of the second range can be increased or decreased depending on the unevenness. This improves the accuracy of selecting candidate stop-off facilities.

[0052] Furthermore, the first range and the second range are not limited to being circular. For example, they may be ellipses or polygons, or the map may be divided into meshes to form ranges consisting of one or more meshes. Alternatively, the true location of a large facility or a parking location does not have to be at the center of a circle. For example, the center of a circle may be shifted north, south, east, or west from the true location.

[0053] Furthermore, the present invention is not limited to the above-described embodiments. In other words, a person skilled in the art can implement various modifications in accordance with conventionally known knowledge without departing from the gist of the present invention. As long as such modifications still include the information processing device of the present invention, they are of course included in the scope of the present invention. [Explanation of symbols]

[0054] 1. Information processing equipment 2 Database 11 Large Facility Estimation Department 12 Stopover facility candidate selection department (acquisition department, selection department) 13 Stopover Facility Estimation Section 21 Facility DB 22 Parking position DB

Claims

1. an acquisition unit that acquires parking position information regarding a parking position of a vehicle; a selection unit that selects, from among a plurality of facilities, candidates for facilities that are presumed to have been visited by a passenger of the vehicle; The selection unit includes the facility included in a first range set for the parking position indicated by the parking position information; and the parking position is set relative to the location of a large facility among the plurality of facilities and is included in a second range larger than the first range.

2. An acquisition unit that acquires parking position information regarding a parking position of a vehicle; a selection unit that selects, from among a plurality of facilities, candidates for facilities that are presumed to have been visited by a passenger of the vehicle; the selection unit selects, as the candidates, facilities that are present within a first range that is set for the parking position indicated by the parking position information, and large facilities that are included in the plurality of facilities and that include the parking position within a second range that is set for the large facility; The information processing apparatus is characterized in that the second range is larger than the first range.

3. a large facility estimation unit that estimates the large facility based on information on the plurality of facilities; The information processing apparatus according to claim 1 , wherein the selection unit sets the second range for the large facility estimated by the large facility estimation unit.

4. 4. The information processing apparatus according to claim 1, further comprising a stop-off facility estimation unit that estimates a stop-off facility from the candidates selected by the selection unit.

5. The information processing apparatus according to claim 1 , wherein the second range is set as a range centered on the true position of the large facility.

6. 5. The information processing apparatus according to claim 1, wherein the second range is increased or decreased for an arbitrary portion based on past performance information.

7. An information processing method executed by an information processing device that performs a predetermined process based on information about a parking position of a vehicle, an acquisition step of acquiring parking position information relating to a parking position of the vehicle; a selection step of selecting, from a plurality of facilities, candidate facilities that are presumed to have been visited by the passenger of the vehicle; The selection step selects, as the candidates, facilities that exist within a first range that is set for the parking position indicated by the parking position information, and large facilities that are included in the plurality of facilities and that include the parking position within a second range that is set for the large facility; The information processing method, wherein the second range is larger than the first range.

8. An information processing program for causing a computer to execute the information processing method according to claim 7.

9. 9. A computer-readable storage medium storing the information processing program according to claim 8.

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