Information processing device, information processing method, and program

Abstract

To estimate in advance the number of installed object items for more efficiently retrieve arrangement positions of object items.SOLUTION: There are provided an information processing device including: an accepting unit which accepts designation of an object area on a map, and designation of the longest distance from an arbitrary position in the object area to a position where an object item is arranged; and a calculation unit which calculates a first link number indicating the number of road links contained in the object area on the basis of the map data, and a second link number indicating the number of road links being covered by the object items arranged at arbitrary positions in the object area, and estimates the number of object items arranged in the object area by dividing the first link number by the second link number.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and a program. Regarding. [Background technology]

[0002] The most efficient allocation of objects while satisfying specified conditions is called optimal allocation. For example, Patent Document 1 discloses a system that determines a vehicle allocation pattern that can reduce CO2 emissions. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2012-190237 A Summary of the Invention [Problem to be solved by the invention]

[0004] For example, when searching for a placement position of an object that satisfies a specified condition while minimizing the number of objects to be placed, it is possible to repeat the process of searching for a placement position while changing the number of objects to be placed in various ways. Therefore, for efficient search, it is desirable to estimate the number of objects to be placed in advance.

[0005] Therefore, an object of the present invention is to provide a technique that makes it possible to estimate in advance the number of objects to be installed in order to more efficiently search for the placement positions of the objects. [Means for solving the problem]

[0006] An information processing device according to one embodiment of the present invention has a receiving unit that receives a designation of a target area on a map and a designation of the longest distance from any position within the target area to a position where an object is to be placed, and a calculation unit that calculates, based on map data, a first link number indicating the number of road links included in the target area and a second link number indicating the number of road links covered by an object placed at any position in the target area, and estimates the number of the objects to be placed in the target area by dividing the first link number by the second link number. Effect of the Invention

[0007] According to the present invention, it is possible to provide a technique that makes it possible to estimate in advance the number of objects to be installed in order to more efficiently search for the placement positions of the objects. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of a search system according to an embodiment of the present invention. [Diagram 2] FIG. 11 is a diagram illustrating an example of a process for searching for a placement position of an object. [Diagram 3] FIG. 2 is a diagram illustrating an example of a hardware configuration of an information processing device. [Figure 4] FIG. 2 is a diagram illustrating an example of a functional block configuration of an information processing device. [Diagram 5] 11 is a flowchart illustrating an example of a processing procedure performed by an information processing device. [Figure 6] FIG. 2 is a diagram for explaining the number of road links covered by one object. [Figure 7] FIG. 2 is a diagram for explaining a branch of a road link. [Figure 8] FIG. 13 is a diagram for explaining a process of searching for a position at which to place an object. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described with reference to the accompanying drawings, in which the same reference numerals denote the same or similar configurations.

[0010] <System configuration> 1 is a diagram showing an example of a search system according to the present embodiment. The search system 1 includes an information processing device 10 and a terminal 20. The information processing device 10 and the terminal 20 are connected via a wireless or wired communication network N and can communicate with each other.

[0011] The terminal 20 is a terminal used by a user of the search system 1, and displays various screens related to the processing executed by the information processing device 10. The terminal 20 may be any terminal, such as a smartphone, a tablet terminal, a mobile phone, a personal computer (PC), a notebook PC, a personal digital assistant (PDA), or a home game device.

[0012] The information processing device 10 performs "optimal placement" to place objects most efficiently while satisfying specified conditions. The objects to be optimally placed by the information processing device 10 may be any objects, and examples of such objects include devices (AEDs (Automated External Defibrillators), fire extinguishers, trash cans, etc.), waiting areas for personnel (security guards, guides, etc.), stalls (stores, food trucks, etc.), taxis, bases (delivery bases, charging spots, etc.), water pipes, and sewer pipes.

[0013] In this embodiment, the conditions that can be specified are the range of the area on the map where the objects are to be placed (hereinafter referred to as the "target area"), and the longest distance from any position in the target area to the position where the objects are to be placed. In other words, the optimal placement performed by the information processing device 10 is to search for positions to place the objects so as to minimize the number of objects to be placed while satisfying the condition that the distance from any position in the target area to the objects is equal to or less than the longest distance. Note that "minimum" means the smallest number among the numbers searched for by the information processing device 10, and does not mean the smallest number as a true value.

[0014] FIG. 2 is a diagram showing an example of a process for searching for a placement position of an object. It is assumed that there are minute roads not shown in FIG. 2. T1 to T27 indicate the positions where the objects are placed, and the lines indicate the roads. Here, it is assumed that area A10 is specified as the target area, and 500 m is specified as the maximum distance. In this case, the information processing device 10 searches for positions where the objects are placed so that the number of objects to be placed is minimized within a range that satisfies the condition that the objects are present within 500 m of any road in area A10.

[0015] When searching for placement positions that satisfy the specified conditions while minimizing the number of objects to be placed, it is possible to repeat the process of searching for placement positions while increasing or decreasing the number of objects to be placed. For example, assume that area A is specified as the target area and 500 m is specified as the maximum distance. In this case, the information processing device 10 searches for placement positions of the objects while changing the number of objects in various ways, such as when 200 objects are placed, when 100 objects are placed, when 120 objects are placed, and so on.

[0016] On the other hand, in this embodiment, in order to perform a more efficient search, the information processing device 10 estimates in advance the optimal number of objects to be placed in the target area based on the range and maximum distance of the specified target area. In other words, the information processing device 10 can perform a search after estimating the number of objects to be placed, and therefore can more efficiently search for the placement positions of the objects.

[0017] <Hardware configuration> 3 is a diagram showing an example of a hardware configuration of the information processing device 10. The information processing device 10 has a processor 11 such as a CPU (Central Processing Unit) or a GPU (Graphical Processing Unit), a memory (e.g., a RAM (Random Access Memory) or a ROM (Read Only Memory)), a storage device 12 such as a HDD (Hard Disk Drive) and / or an SSD (Solid State Drive), a network IF (Network Interface) 13 for wired or wireless communication, an input device 14 for accepting input operations, and an output device 15 for outputting information. The input device 14 is, for example, a keyboard, a touch panel, a mouse, and / or a microphone. The output device 15 is, for example, a display, a touch panel, and / or a speaker.

[0018] The information processing device 10 may be configured with one or more physical servers, or may be configured using a virtual server operating on a hypervisor, or may be configured using a cloud server.

[0019] <Function block configuration> FIG. 4 is a diagram showing an example of a functional block configuration of the information processing device 10. The information processing device 10 includes a storage unit 100, a reception unit 101, a calculation unit 102, and a search unit 103. The storage unit 100 can be realized by using a storage device 12 included in the information processing device 10. The reception unit 101, the calculation unit 102, and the search unit 103 can be realized by the processor 11 of the information processing device 10 executing a program stored in the storage device 12. The program can be stored in a storage medium. The storage medium storing the program may be a non-transitory computer readable medium. The non-transitory storage medium is not particularly limited, and may be, for example, a storage medium such as a Universal Serial Bus (USB) memory or a Compact Disc Read-Only Memory (CD-ROM).

[0020] The storage unit 100 stores map data 100a. The map data 100a includes road data representing roads on a map. The road data is expressed as a combination of "nodes" indicating points such as intersections and nodes on roads, and "road links" indicating road sections connecting the nodes. The map data 100a also includes data indicating the lengths of the road links. The length of the road link may be a length on the map (e.g., 1 cm) or an actual distance in real space (e.g., 1 km).

[0021] The receiving unit 101 receives, from a user, a designation of the range of a target area on a map and a designation of the maximum distance from any position within the target area to a position where an object is to be placed.

[0022] The calculation unit 102 calculates the number of road links included in a specified target area (hereinafter referred to as "the total number of road links in the target area" and "the first number of links") and the number of road links covered by an object placed at an arbitrary position in the target area within a specified range of the longest distance (hereinafter referred to as "the number of road links covered by one object" and "the second number of links") based on the map data 100a, and estimates the number of objects to be placed in the target area by dividing the total number of road links in the target area (the first number of links) by the number of road links covered by one object (the second number of links). Note that the number of road links covered by one object means a value estimated by using a formula to be described later on, which is the number of road links existing within a range of the longest distance or less from an arbitrary position in the target area (i.e., the position where the object is placed). The calculation unit 102 may also acquire the total number of road links in the target area by searching the map data 100a. In addition, the calculation unit 102 may calculate the number of road links covered by one object based on the specified longest distance, the total number of road links in the target area, the number of nodes indicating the number of nodes connecting the road links included in the target area, and the total distance of all road links included in the target area.

[0023] The search unit 103 searches for positions in the target area for placing the plurality of objects, the number of which is estimated by the calculation unit 102, in such a way as to satisfy the conditions.

[0024] <Processing Procedure> FIG. 5 is a flowchart showing an example of a processing procedure performed by the information processing device 10.

[0025] In step S10, the information processing device 10 accepts, from the terminal 20 (or from the user), a designation of a target area on a map and a designation of the longest distance from any position in the target area to a position where an object is to be placed. For example, the information processing device 10 may refer to map data 100a and display a map on the screen of the terminal 20. The information processing device 10 may also accept an area designated on the map displayed on the terminal 20 as the target area. The information processing device 10 may also accept a distance inputted on the screen of the terminal 20 as the longest distance.

[0026] In step S11, the information processing device 10 estimates the number of objects to be placed in the target area. A specific method for estimating the number of objects to be placed will be described below.

[0027] The length of the road links included in the target area is different for each road link, and the number of road links branching off from one end point (i.e., node) of the road link also varies depending on the road link. In other words, the above-mentioned "number of road links covered by one object" will vary depending on the position where the object is placed. However, if the number of road links included in the target area is huge and the specified longest distance is much longer than the length of one road link, it is expected that the number of "number of road links covered by one object" will be a similar number to some extent. Therefore, in this embodiment, in order to make the calculation easier, the average value of the length of the road links included in the target area and the average value of the number of road links branching off from one end point of the road links included in the target area are calculated, and the length of each road link included in the target area and the number of branches at the end points of each road link are assumed to be the same as the average values, thereby calculating the "number of road links covered by one object."

[0028] When tracing road links to reach a specified maximum distance from the object's position, the average number of nodes passed through can be calculated using the following formulas (1) and (2). First, the average length b of the road links can be expressed by the following formula (1). [Number] Here, p represents the total distance of the roads included in the target area. e represents the total number of all road links included in the target area.

[0029] Next, when tracing the road links until reaching the longest distance q from the position of the object, the average number m of nodes passed through can be expressed by the following formula (2). [Number] Here, q represents the longest distance specified by the user. That is, the average number m of nodes passed through can be calculated by the longest distance ÷ the average length of the road links. Here, a represents the attenuation rate, and it can take a value of 0 < a ≤ 1. In actual roads, due to reasons such as one end of a road link being a dead end or the road link having a loop structure, the average number m of nodes passed through does not necessarily equal the longest distance ÷ the average length of the road links. Therefore, by multiplying by the attenuation rate a, it becomes possible to adjust the average number m of nodes passed through to a value closer to that of the actual road. The value of a may be determined by the user according to the situation of the road links in the target area, or it may be a predetermined value.

[0030] For example, assume that the specified longest distance q = 360 m and the average length b of the road links = 80 m. Also, for the sake of convenience in explanation, assume a = 1. In this case, q ÷ b × a = 4.5, and since the decimal part is removed by the floor function, m = 4. That is, when the average length b of the road links is 80 m, the average number m of nodes passed through when tracing the road links from the position of the object to a position 360 m ahead is 4.

[0031] Fig. 6 shows the total number of all road links connected by branching one road link (i.e., the number of road links covered by one object) when the road links are traced from the object position to the longest distance q. Point S in Fig. 6 indicates an arbitrary position in the object area where the object is located, and q indicates the longest distance specified by the user. Furthermore, L1 indicates a road link, and N1, N2-1, N2-2, N3-1 to N3-4, and N4-1 to N4-8 indicate nodes. In this embodiment, point S is assumed to be located at an arbitrary position on the link.

[0032] Here, it is assumed that the average number of nodes passed through when tracing the road link from the point S to the longest distance q is four. It is also assumed that each road link branches into two on average at each end point (i.e., each node). In this case, as shown in FIG. 6, the road link L1 branches into two at the node N1. The two branched road links branch into two at the nodes N2-1 and N2-2, respectively. Each branched road link further branches into two at the nodes N3-1 to N3-4. Therefore, the road link L1 branches into eight. The road link further branches at the nodes N4-1 to N4-8, but the ends of the road links branched at the nodes N4-1 to N4-8 are outside the range of the longest distance q from the point S, so they are not counted in this embodiment.

[0033] Furthermore, the logic link L1 has the other end point (node ​​N5), and road links branch off from node N5 in a similar manner. Therefore, within the range of the maximum distance q from the object position S, one road link L1 branches off into 8 x 2 = 16. Therefore, the number of road links existing within the range of the maximum distance q from the object position S can be estimated to be 1 + 2 x (2 + 4 + 8) = 29.

[0034] The above explanation will be expressed by a formula. The number r of road links covered by one object can be expressed by the following formula (3).

number

[0035] In formula (3), ((e / n)a-1) indicates how many road links branch off from one end point (node) of a road link. Here, e / n is the total number of road links in the target area divided by the total number of nodes, and therefore indicates how many road links are connected to one node. Therefore, by subtracting 1 from e / n, it is possible to determine how many road links branch off from one end point of a road link.

[0036] Using FIG. 7, the fact that the number of road links branching off from one road link can be obtained by subtracting 1 from the number of road links connected to one node will be described. In the example of A in FIG. 7, three road links L10, L11, and L12 are connected to one node N11. Therefore, one road link L10 branches off into two road links L11 and L12 (i.e., a value obtained by subtracting 1 from the number of road links connected to one node, which is 3) at the node N11. Similarly, in the example of B in FIG. 7, four road links L20, L21, L22, and L23 are connected to one node N21. Therefore, one road link L20 branches off into three road links L21, L22, and L23 (i.e., a value obtained by subtracting 1 from the number of road links connected to one node, which is 4) at the node N21.

[0037] In addition, on actual roads, the value of e / n may be larger than the actual value due to reasons such as one end of a road link being a dead end, the road link having a ring structure, etc. Therefore, by multiplying e / n by the attenuation rate a, it is possible to adjust the value (e / n) indicating how many road links are connected to one node to a value closer to that of an actual road.

[0038] The example in FIG. 6 mentioned above corresponds to a specific example in which e / n=3 and a=1 in formula (3). In this example, road link L1 branches into two at node N1, which is the first node passed through, and these "two" correspond to ((e / n)a-1) in formula (3). In addition, the two branched road links branch into a total of four at nodes N2-1 and N2-2, which are the second nodes passed through, and these "four" correspond to ((e / n)a-1) in formula (3). 2 In addition, the four branched road links branch into a total of eight at nodes N3-1 to N3-4, which are the third nodes passed through, and these "eight" correspond to ((e / n)a-1) in formula (3). 3 In addition, in formula (3), the classification object is ((e / n)a-1) m-1 Up to ((e / n)a-1) m is not counted because the road links (not shown) branching from nodes N4-1 to N4-8, which are the m-th nodes passed through, are not counted because one of their end points (nodes) is not within the longest distance q. Also, the total is doubled in formula (3) because road link L1 has the other end point (node ​​N5), and the same number of road links branch off and are derived from node N5. Note that formula (3) omits the count of the road link (road link L1 in FIG. 6) where point S is located, but a formula in which 1 is added without omitting the count may be used.

[0039] Next, the number x of objects to be placed in the target area can be expressed by the following equation (4).

number

[0040] Here, by transforming equations (1) to (4) according to the formula for the sum of a geometric progression, equation (5) can be derived.

number

[0041] In step S12, the information processing device 10 searches for positions to place the number of objects estimated in step S11 so as to satisfy the condition that the distance from any position in the target area to the objects is equal to or less than the longest distance.

[0042] FIG. 8 is a diagram for explaining a process of searching for a position to place an object. It is assumed that there are fine roads not shown in FIG. 8. First, the search unit 103 initially places the number of objects (eight objects T1 to T8 in the example of FIG. 8) estimated in the processing procedure of step S11 in the object area randomly or according to a predetermined criterion. Next, the search unit 103 calculates an area (hereinafter referred to as a "cover area") represented by tracing road links within the longest distance from the object for each of the placed objects. The cover areas TA1 to TA8 indicate areas represented by tracing road links within the longest distance from the objects T1 to T8, respectively. In other words, the cover areas TA1 to T8 respectively mean ranges in which the objects T1 to T81 can be reached within the longest distance.

[0043] Next, the search unit 103 searches for positions in the target area to place the number of objects estimated by the calculation unit 102 so as to satisfy a condition. The condition may be that the overlapping portion of the calculated cover areas for each object is minimized, and that the road links included in the target area are included in one of the cover areas for each object. For example, in the example of FIG. 8, the search unit 103 searches for positions T1 to T8 to place the eight objects so that all road links in the target area A10 are included in one of the cover areas TA1 to TA8 of each object, and the overlapping portion of each cover area is minimized.

[0044] Any algorithm may be used for the search, and for example, quantum annealing, k-means method, simulated annealing, etc. may be used. A search algorithm that combines a plurality of these algorithms may be used. The search unit 103 may use these search algorithms to search for a position to place an object by changing the position of each object so that the value of an evaluation function that represents the size of an overlapping portion of the areas of each object when a road link included in the target area is included in any of the areas of each object is minimized. For example, the search unit 103 may repeat a process of moving a position to place an object within a predetermined distance from the current position, recalculating the evaluation function, and adopting the movement when the value of the evaluation function becomes small, and may end the process when a convergence condition is satisfied or the number of repetitions reaches a threshold value. The search unit 103 may also move the object by changing the moving direction or moving distance when the value of the evaluation function becomes large by the recalculation or when a predetermined condition is satisfied.

[0045] When the search unit 103 cannot search for positions to place multiple objects in the target area so as to satisfy the condition, the search unit 103 may repeat the search while changing the number of objects to be placed. For example, when the search unit 103 cannot satisfy the condition that all road links in the target area A10 are included in any of the covered areas of each object, the search unit 103 may increase the number of objects to be placed by 1 and perform the search again.

[0046] <Summary> According to the embodiment described above, the information processing device 10 estimates in advance the number of objects to be placed in the target area based on the range of the specified target area and the specified maximum distance. This enables the information processing device 10 to more efficiently search for the placement positions of the objects.

[0047] In the map data 100a, roads are composed of combinations of road links and nodes. In this embodiment, the information processing device 10 estimates the number of objects to be placed in the target area by considering the number of road links and the number of nodes existing in the target area, and therefore, it becomes possible to search for the placement positions of the objects by considering the road links and nodes.

[0048] The above-described embodiments are intended to facilitate understanding of the present invention, and are not intended to limit the present invention. The flow charts, sequences, elements included in the embodiments, and their arrangements, materials, conditions, shapes, sizes, etc. are not limited to those illustrated, and can be changed as appropriate. In addition, configurations shown in different embodiments can be partially replaced or combined with each other. [Explanation of symbols]

[0049] 1 Search system, 10 Information processing device, 11 Processor, 12 Storage device, 13 Network IF, 14 Input device, 15 Output device, 20 Terminal, 100 Storage unit, 100a Map data, 101 Reception unit, 102 Calculation unit 102 Search unit

Claims

1. a reception unit that receives a designation of a target area on a map and a designation of a maximum distance from an arbitrary position within the target area to a position where an object is to be placed; a calculation unit that calculates, based on map data, a first number of links indicating the number of road links included in the target area and a second number of links indicating the number of road links covered by objects placed at any positions in the target area, and estimates the number of the objects to be placed within the target area by dividing the first number of links by the second number of links; An information processing device having the above configuration.

2. A search unit that searches for positions to place the estimated number of objects in the target area so as to satisfy a condition. The information processing device according to claim 1 .

3. the search unit calculates, for each of the plurality of objects, an area represented by tracing road links within the longest distance from the object; The condition is that the overlapping portion of the calculated areas for each of the objects is minimized, and a road link included in the object area is included in any of the areas for each of the objects. The information processing device according to claim 2 .

4. the calculation unit calculates the second number of links based on the longest distance, the first number of links, a number of nodes indicating the number of nodes connecting road links included in the target area, and a total distance of all road links included in the target area. The information processing device according to claim 1 .

5. An information processing method performed by an information processing device, receiving a designation of a target area on a map and a designation of a maximum distance from any position within the target area to a position where an object is to be placed; a step of calculating a first number of links indicating the number of road links included in the target area and a second number of links indicating the number of road links covered by an object placed at an arbitrary position in the target area based on map data, and estimating the number of the objects to be placed within the target area by dividing the first number of links by the second number of links; An information processing method comprising:

6. receiving a designation of a target area on a map and a designation of a maximum distance from any position within the target area to a position where an object is to be placed; a step of calculating a first number of links indicating the number of road links included in the target area and a second number of links indicating the number of road links covered by an object placed at an arbitrary position in the target area based on map data, and estimating the number of the objects to be placed within the target area by dividing the first number of links by the second number of links; A program for causing a computer to execute the following.

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