Traffic volume estimation device and traffic volume estimation method

Abstract

A traffic volume estimation device (1) is provided with: an extraction unit (12) that extracts at least one related area related to a target area; and an estimation unit (13) that estimates the volume of traffic pertaining to the number of people passing through the target area on the basis of the size of each at least one related area and the number of people estimated to be present in each at least one related area. The extraction unit (12) may extract at least one related area each including a part of the target area. The extraction unit (12) may extract at least one related area on the basis of position information observed in the target area.

Description

Traffic volume estimation device and traffic volume estimation method

[0001] One aspect of the present disclosure relates to a traffic volume estimation device and a traffic volume estimation method for estimating traffic volume related to the number of people passing through a target area.

[0002] The following Patent Document 1 discloses an information distribution system that identifies the traffic volume of pedestrians passing through a collection area according to the time of day.

[0003] JP 2017-142749 A

[0004] In the above information distribution system, it is not possible to estimate the traffic volume of a collection area from a perspective other than the collection area. For example, it is not possible to estimate the traffic volume of a collection area based on areas related to the collection area. Therefore, it is desirable to estimate the traffic volume of a target area, which is a target area, based on areas related to the target area.

[0005] A traffic volume estimation device according to one aspect of the present disclosure includes an extraction unit that extracts at least one or more associated areas related to a target area, and an estimation unit that estimates traffic volume related to the number of people passing through the target area based on the size of each of the at least one or more associated areas and the number of people estimated to be present in each of the at least one or more associated areas.

[0006] In this aspect, the traffic volume of the target area is estimated based on at least one or more related areas related to the target area. That is, the traffic volume of the target area can be estimated based on areas related to the target area.

[0007] According to one aspect of the present disclosure, traffic volume in a target area can be estimated based on areas related to the target area.

[0008] 18 is a diagram showing an example of a system configuration of a traffic volume estimation system including a traffic volume estimation device according to an embodiment. FIG. 19 is a diagram showing an example of a functional configuration of a traffic volume estimation device according to an embodiment. FIG. 19 is a diagram showing an example of an advertisement viewable area in Ginza. FIG. 20 is a diagram showing an example of a related area extracted based on the advertisement viewable area of ​​FIG. 3. FIG. 21 is a diagram showing the width and height of the related area of ​​FIG. 4. FIG. 21 is a diagram showing an example of an advertisement viewable area in Kanamecho. FIG. 22 is a diagram showing an example of a related area extracted based on the advertisement viewable area of ​​FIG. 6. FIG. 22 is a diagram showing the width and height of the related area of ​​FIG. 23. FIG. 24 is a diagram showing an example of an advertisement viewable area in Shibuya. FIG. 25 is a diagram showing an example of a related area extracted based on the advertisement viewable area of ​​FIG. 26. FIG. 26 is a diagram showing the width and height of the related area of ​​FIG. 27. FIG. 28 is a diagram showing an example of an advertisement viewable area in Shibuya. FIG. 28 is a diagram showing an example of a related area extracted based on the advertisement viewable area of ​​FIG. 27. FIG. 29 is a diagram showing the width and height of the related area of ​​FIG. 30. Fig. 20 is a diagram showing an example of a result of rotating the point cloud of Fig. 19. Fig. 21 is a diagram showing an example of a mesh extracted based on the advertisement viewable area of ​​Fig. 3. Fig. 22 is a diagram showing an example of the hardware configuration of a computer used in the traffic volume estimation device according to the embodiment.

[0009] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the description of the drawings, the same elements are designated by the same reference numerals, and duplicate explanations will be omitted. Furthermore, the embodiments of the present disclosure in the following description are specific examples of the present invention, and the present invention is not limited to these embodiments unless otherwise specified to limit the present invention.

[0010] Fig. 1 is a diagram showing an example of the system configuration of a traffic volume estimation system 3 including a traffic volume estimation device 1 according to an embodiment. As shown in Fig. 1, the traffic volume estimation system 3 includes the traffic volume estimation device 1 and at least one or more terminals 2. The traffic volume estimation device 1 and each terminal 2 are communicatively connected to each other via a network such as a mobile communication network, and can transmit and receive information to and from each other.

[0011] The traffic volume estimation device 1 is a computer device that estimates traffic volume related to the number of people passing through a target area, which is a target area (region, area, section).

[0012] The area is indicated by, for example, a predetermined region on a two-dimensional map. The target area is an area for which traffic volume is to be estimated. The target area may be an advertising viewable (visible) area, which is an area where outdoor advertisements can be viewed (seen). The target area may also be a collection of meshes (small areas) where outdoor advertisements can be viewed.

[0013] In this embodiment, the traffic volume is N ａ，ｔ It is expressed as follows: Traffic volume N ａ，ｔ is the number of people passing through the advertisement viewable area per hour at outdoor advertisement location a and estimated time t. Outdoor advertisement location a is the location where the outdoor advertisement is installed (e.g., Kanamecho, Shibuya, Ginza, etc.). For example, outdoor advertisement location a∈{Kanamecho, Shibuya, Ginza, ...}. Estimated time t is the aggregate value for the time when traffic volume is estimated (e.g., 2:00 to 3:00 when t=2). For example, estimated time t∈{0, 1, 2, 3, ..., 23}.

[0014] The traffic volume estimation device 1 will be described in detail later.

[0015] The terminal 2 is a computer device such as a mobile communication terminal or a laptop computer that performs mobile communication. In this embodiment, the terminal 2 is assumed to be a smartphone, but is not limited to this. The terminal 2 is carried by the user of the terminal 2. The terminal 2 is equipped with a Global Positioning System (GPS) and uses the GPS to acquire GPS data, which is current location information (date, time, latitude, longitude, etc.) of the terminal 2. The location information of the terminal 2 can also be considered location information of the user of the terminal 2. Note that the terminal 2 may acquire current location information based on base station information without using GPS. In this embodiment, for convenience, location information is referred to as GPS data. The terminal 2 may acquire GPS data as appropriate and transmit the acquired GPS data to the traffic volume estimation device 1 as appropriate. When transmitting the GPS data to the traffic volume estimation device 1, the terminal 2 may transmit identification information that identifies the terminal itself. The terminal 2 may also have other sensors or functions that are included in a typical smartphone.

[0016] 2 is a diagram illustrating an example of the functional configuration of the traffic volume estimation device 1 according to the embodiment. As illustrated in FIG. 2, the traffic volume estimation device 1 includes a storage unit 10, an acquisition unit 11, an extraction unit 12 (extraction unit), and an estimation unit 13 (estimation unit).

[0017] Although it is assumed that each functional block of the traffic volume estimation device 1 functions within the traffic volume estimation device 1, this is not a limitation. For example, some of the functional blocks of the traffic volume estimation device 1 may function within a computer device different from the traffic volume estimation device 1 and connected to the traffic volume estimation device 1 via a network, while appropriately transmitting and receiving information with the traffic volume estimation device 1. Furthermore, some functional blocks of the traffic volume estimation device 1 may be omitted, multiple functional blocks may be integrated into one functional block, or one functional block may be separated into multiple functional blocks.

[0018] Hereinafter, each function of the traffic volume estimation device 1 shown in FIG. 2 will be described.

[0019] The storage unit 10 stores any information used in calculations in the traffic volume estimation device 1 and the results of calculations in the traffic volume estimation device 1. The information stored by the storage unit 10 may be referenced by each function of the traffic volume estimation device 1 as needed.

[0020] The acquisition unit 11 acquires (receives, inputs) information via the communication device 1004 or the input device 1005 described below, and may store the acquired information in the storage unit 10, or output it to the extraction unit 12 or the estimation unit 13.

[0021] The acquisition unit 11 acquires GPS data from at least one or more terminals 2, and stores the data in the storage unit 10. The acquisition unit 11 may acquire identification information along with the GPS data from the terminals 2, and store the GPS data for each terminal 2 based on the identification information. In this embodiment, to simplify the explanation, hereinafter, explanations regarding processing for each terminal 2 will be omitted as processing for terminal 2, as appropriate.

[0022] The acquisition unit 11 acquires information specifying the target area, information specifying the location a of the outdoor advertisement, and information specifying the estimated time t, and may store the acquired information in the storage unit 10 or output the acquired information to the extraction unit 12 or the estimation unit 13. The extraction unit 12 and the estimation unit 13 perform subsequent processing based on this information as appropriate.

[0023] The extraction unit 12 extracts at least one associated area related to the target area. The extraction unit 12 may extract at least one associated area each including a part of the target area. The extraction unit 12 may store associated area information related to the extracted at least one associated area in the storage unit 10 or output the information to the estimation unit 13.

[0024] Figure 3 is a diagram showing an example of an advertisement viewing area in Ginza. In Figure 3, a map of Ginza shows multiple meshes, each represented by small squares with patterns, mainly along the roads. A collection of these meshes is the advertisement viewing area (target area).

[0025] Fig. 4 is a diagram showing an example of a related area extracted based on the advertisement viewable area of ​​Fig. 3. The areas indicated by two ellipses in Fig. 4 indicate two related areas related to the advertisement viewable area of ​​Fig. 3 extracted by the extraction unit 12. The extraction method by the extraction unit 12 will be described in detail later.

[0026] 5 is a diagram showing the width and height of the related areas in FIG. 4. More specifically, the width and height of one of the two related areas are d ａ，ｗ，１ and d ａ，ｈ，１ The width and height of the other side are d ａ，ｗ，２ and d ａ，ｈ，２ is.

[0027] Fig. 6 is a diagram showing an example of an advertisement viewing area in Kanamecho. As in Fig. 3, Fig. 6 shows a map of Kanamecho with multiple meshes mainly along roads, and a collection of these meshes is the advertisement viewing area (target area).

[0028] Fig. 7 is a diagram showing an example of a related area extracted based on the advertisement viewable area of ​​Fig. 6. As in Fig. 4, the areas indicated by two ellipses in Fig. 7 indicate two related areas related to the advertisement viewable area of ​​Fig. 6, extracted by the extraction unit 12.

[0029] 8 is a diagram showing the width and height of the related areas in FIG. 7. More specifically, the width and height of one of the two related areas are d ａ，ｗ，１ and d ａ，ｈ，１ The width and height of the other side are d ａ，ｗ，２ and d ａ，ｈ，２ is.

[0030] Fig. 9 is a diagram showing an example of an advertisement viewing area in Shibuya. As in Fig. 3, Fig. 9 shows a map of Shibuya with multiple meshes mainly along roads, and a collection of these meshes is the advertisement viewing area (target area).

[0031] Fig. 10 is a diagram showing an example of a related area extracted based on the advertisement viewable area of ​​Fig. 9. As in Fig. 4, an area indicated by one ellipse in Fig. 10 indicates one related area related to the advertisement viewable area of ​​Fig. 9, extracted by the extraction unit 12.

[0032] 11 is a diagram showing the width and height of the related area in FIG. 10. More specifically, the width and height of the related area are d ａ，ｗ，１ and d ａ，ｈ，１ is.

[0033] The extraction unit 12 may extract at least one related area based on GPS data (location information) observed in the target area. The extraction unit 12 may extract at least one related area, each of which includes a portion of the location indicated by the GPS data observed in the target area. The extraction unit 12 may extract at least one related area based on clustering of the locations indicated by the GPS data observed in the target area. Details of the extraction method used by the extraction unit 12 will be described later.

[0034] The estimation unit 13 estimates the traffic volume related to the number of people passing through the target area based on the size of each of at least one or more related areas and the number of people estimated to be present in each of at least one or more related areas. The size of the related area may be based on the maximum width of the related area. The number of people estimated to be present in the related area may be based on the number of people estimated to be present in the target area, GPS data observed in the target area, and GPS data observed in the related area. The estimation unit 13 may estimate the number of viewers of the outdoor advertisement in the target area based on the traffic volume. Details of the estimation method used by the estimation unit 13 will be described later.

[0035] The estimation unit 13 may output the estimation result. More specifically, the estimation unit 13 may output (transmit) the estimation result to another device via a communication device 1004 described later, or may output (display, output as sound) the estimation result via an output device 1006 described later.

[0036] Next, examples of the processing executed by the traffic volume estimation device 1 will be described with reference to FIGS.

[0037] 12 is a flowchart showing an example of a process (traffic volume estimation method) executed by the traffic volume estimation device 1. First, the extraction unit 12 extracts the area population n ａ，ｔ , , , and (Step S1) Details of step S1 will be explained below.

[0038] Population in the area n ａ，ｔ is the number of people in the advertisement viewable area at the outdoor advertising location a and estimated time t.

[0039] The extraction unit 12 may specify the advertisement viewable area based on, for example, mesh information stored in advance by the storage unit 10. Fig. 13 is a diagram showing an example of a table of mesh information. As shown in Fig. 13, the mesh information associates an advertisement name that identifies an outdoor advertisement with a mesh number that identifies a mesh. The mesh information may further be associated with a set of latitudes and longitudes (e.g., the latitudes and longitudes of each of the four vertices of a square) for specifying the range and position of the mesh.

[0040] The extraction unit 12 extracts the population n ａ，ｔ is calculated by existing techniques such as those disclosed in the following reference document: Reference: WO 2020 / 095480

[0041] 14 is a diagram showing an example of a table of area population information. As shown in Fig. 14, the area population information associates the advertisement name, mesh number, holiday flag indicating whether the observation day was a holiday or not, observation time, and population in the mesh area.

[0042] is the percentage of the population within the advertisement viewable area at the outdoor advertising location a and the estimated time t who walk faster than a certain speed k. The speed k may be determined in advance based on a typical walking speed of a person (e.g., 1.9 m / s). is the proportion of the population slower than a certain speed k within the advertising viewable area at outdoor advertising location a and estimated time t. is the average speed (m / s) of people faster than a certain speed k within the advertisement viewable area at outdoor advertising location a and estimated time t. is the average speed (m / s) of people slower than a certain speed k within the advertisement viewable area at outdoor advertising location a and estimated time t.

[0043] As described above, the GPS data may be acquired by the acquisition unit 11, or may be stored in advance by the storage unit 10. Fig. 15 is a diagram showing an example of a table of GPS data. As shown in Fig. 15, the GPS data associates the observation date and time, the observation latitude, and the observation longitude. The GPS data shown in Fig. 15 may be data observed within s km (kilometers) around location a of the outdoor advertisement.

[0044] The extraction unit 12 may calculate movement information including movement speed (m / s) based on the GPS data. FIG. 16 is a diagram showing an example of a movement information table. As shown in FIG. 16 , the movement information corresponds to the date and time when the GPS data was observed, the latitude when the GPS data was observed, the longitude when the GPS data was observed, the time difference (seconds) from the previous record, the previous record latitude which is the latitude of the previous record, the previous record longitude which is the longitude of the previous record, the movement distance (m) which is the distance between the coordinates determined by the latitude and longitude of the previous record, and the movement speed (m / s). For each record (one record) of the movement information, the extraction unit 12 calculates the time difference, movement distance, and movement speed based on a comparison with the previous record.

[0045] The extraction unit 12, based on the calculated moving speed, , , and may be calculated.

[0046] 12, after step S1, the extraction unit 12 extracts advertisements that are in the advertisement viewable area from one month's worth of GPS data (step S2). The extraction unit 12 performs the extraction based on the latitude and longitude.

[0047] Fig. 17 is a diagram showing an example of location points indicated by GPS data observed in the advertisement viewable area of ​​Fig. 3. The points shown in Fig. 17 correspond to the GPS data observed in the advertisement viewable area extracted by extraction unit 12 in step S2.

[0048] Returning to FIG. 12 , following step S2, the extraction unit 12 performs clustering on the GPS data using Dirichlet Process GMM (step S3). The number of classes may be an estimation target. The extraction unit 12 may determine the number of related areas based on the clustering results. FIG. 18 is a diagram showing an example of the results of clustering the points in FIG. 17 . As shown in FIG. 18 , the points in FIG. 17 are clustered into two point groups, an upper half and a lower half. The Dirichlet Process GMM is expressed, for example, by the following equation:

[0049] 12, following step S3, the extraction unit 12 sets the value of a repeat control variable i to 1 (step S4) in order to perform a loop of the processes of steps S5 to S7 for each clustered class (class 1, class 2, class 3, ...). Note that i also serves as an ID for identifying the related area.

[0050] Following step S4, the extraction unit 12 performs principal component analysis on the data included in class i (step S5). Fig. 19 is a diagram showing an example of the results of principal component analysis of the clustered point clouds of Fig. 18. As shown in Fig. 19, as a result of principal component analysis of the point clouds of the classes in the upper half of Fig. 18, eigenvectors 1 and 2 are extracted.

[0051] Returning to FIG. 12, following step S4, the extraction unit 12 calculates the distance between the rotated point groups with the largest width between the vertical and horizontal axes as d ｗ , d ｈ 20 is a diagram showing an example of the result of rotating the point cloud of FIG. 19. As shown in FIG. 20, the extraction unit 12 determines the maximum width value (value between points) of the result of rotating the point cloud of FIG. 19 about 45 degrees to the left as d ａ，ｗ，ｉ The maximum vertical width (value between points) is estimated as d ａ，ｈ，ｉ It is estimated that...

[0052] 12, after step S6, the extraction unit 12 divides the population in the area proportionally for each number of points obtained by the observation clustering (step S7). For example, if the population in the area where advertisements can be viewed is n ａ，ｔ is "50000", the total number of GPS data observed within the advertisement viewable area is "31000", and the number of GPS data included in the class i to be estimated is "12000", the extraction unit 12 extracts "19354.839", which is the result of the formula "50000*(12000 / 31000)", and assigns it to the population n ａ，ｔ，ｉ Calculate (estimate) as follows.

[0053] Following step S7, the extraction unit 12 determines whether i is greater than the number of GPS observations within the advertisement viewable area (step S8). If it is determined in step S8 that i is not greater (S8: NO), the extraction unit 12 increments the value of i by 1 and returns to step S5.

[0054] On the other hand, if it is determined in step S8 that the number of classes is larger than the number of classes in the observation data (S8: YES), the process loop of steps S5 to S7 is terminated, and the estimation unit 13 calculates the traffic volume (step S9). Details of step S9 will be described below.

[0055] The estimation unit 13 calculates the traffic volume using the following formula.

[0056] D ａ，ｉ is expressed by the following formula: ａ，ｉ = max(d ａ，ｗ，ｉ , d ａ，ｈ，ｉ ) D ａ，ｉ is the distance across the relevant area, and the maximum value is used for the distance across the relevant area.

[0057] θ ｓｌｏｗ is the slow parameter. ｆａｓｔ is a fast parameter. ｓｌｏｗ and θ ｆａｓｔFor example, machine learning may be performed to set a coefficient that minimizes the mean square error with the correct answer data. The correct answer data may be a value counted through a traffic survey of people who actually passed through the advertisement viewable area. ｓｌｏｗ and θ ｆａｓｔ is a parameter that does not change depending on the location of the outdoor advertisement and the estimated time.

[0058] The above N ａ，ｔ Among the formulas, indicates the population of slow people in the relevant area (ID is i). ａ，ｔ Among the formulas, corresponds to the calculation of the number of slow people changing places. ａ，ｔ Among the formulas, indicates the population of high-speed people in the relevant area (ID is i). ａ，ｔ Among the formulas, corresponds to the calculation of the number of high-speed people changes.

[0059] The estimation unit 13 may further calculate (estimate) the number of viewers of the outdoor advertisement in the target area based on the traffic volume calculated (estimated) in step S9.

[0060] The estimation unit 13 first calculates IMP, which is the amount of traffic coming and going within the advertisement viewable area during the advertisement distribution time, based on the following formula: IMP = population within area + (traffic volume - population within area) / 3600 * distribution time (s)

[0061] A supplement to the above formula: The population within an area is the population that exists within the ad-viewable area on average during a time period (the population that exists within the ad-viewable area at a steady rate). When defining the IMP of the area's population, one way of thinking is that if an advertisement is delivered for even one second, there will be more people than the population within the ad-viewable area. Traffic volume is the amount of people traveling within the ad-viewable area in one hour. When defining the IMP of traffic volume, one way of thinking is that if an advertisement is delivered for one hour, the IMP will be equal to the traffic volume. In the above formula, "(traffic volume - population within area) / 3600" indicates the population that newly flows into the area per second.

[0062] The estimation unit 13 then calculates V-imp, which is the number of people who will view the advertisement within the advertisement distribution time, based on the following formula: V-imp=IMP*α where α is a parameter that indicates the number of people who will view the advertisement relative to the number of people passing through the advertisement viewable area. One method for determining this parameter is to conduct a questionnaire survey of passersby and calculate and determine the ratio of ad viewers to passersby (for example, α=0.44).

[0063] As described above, the estimation unit 13 estimates IMP or V-imp based on two pieces of data: the population in the area and the traffic volume.

[0064] Another method for calculating traffic volume will be described below. For example, traffic volume can be calculated using the following formula:

[0065] D ａ is expressed by the following formula: ａ = (d ａ，ｗ +d ａ，ｈ ) / 2D ａ is the crossing distance of the ad viewable area. ａ is, for example, the east-west distance of the advertisement viewable area (for example, the above d ａ，ｗ ) and the north-south distance (for example, the above d ａ，ｈ ) is the average value.

[0066] The above N ａ，ｔ Among the formulas, indicates the population of slow-moving people in the advertisement viewing area. ａ，ｔ Among the formulas, indicates the population of fast viewers in the ad viewing area.

[0067] The above N ａ，ｔ The following explains the problem with calculations using the formula. When placing outdoor advertisements, the advertisement viewable area can take various shapes depending on the location of the outdoor advertisement. For example, the shapes of the advertisement viewable area shown in Figure 3, Figure 6 and Figure 9 can be mentioned. For example, if an intersection is included in the shape of the advertisement viewable area shown in Figure 3, it is thought possible to divide it into two (to extract two related areas), but ａ，ｔThis is not taken into consideration in the formula of FIG. 21. FIG. 21 is a diagram showing an example of a mesh extracted based on the advertisement viewable area of ​​FIG. 3. ａ，ｔ In the formula, the crossing distance of a person passing through the advertisement viewing area in FIG. 21 is approximated by the mesh shown in FIG. 21 (using the average length and width). In order to improve the estimation accuracy, it is necessary to measure the crossing distance more precisely. ａ，ｔ In the formula, the calculation of the crossing distance becomes problematic and it is not possible to take into account the complex shape of the advertisement viewable area.

[0068] On the other hand, in traffic volume estimation by the traffic volume estimation device 1, as described above, the accuracy of estimating traffic volume and the number of viewers is improved by accurately calculating the crossing distance. For example, as shown in Fig. 4, in consideration of the case where two roads intersect, the area is divided into two (two related areas are extracted) to achieve more precise calculation of the crossing distance. More specifically, in traffic volume estimation by the traffic volume estimation device 1, the crossing distance is approximated by the maximum length of two (not limited to two, but one or more) related areas, thereby more accurately calculating the crossing distance.

[0069] Next, the effects of the traffic volume estimation device 1 according to the embodiment will be described.

[0070] The traffic volume estimation device 1 includes an extraction unit 12 that extracts at least one related area related to a target area, and an estimation unit 13 that estimates traffic volume related to the number of people passing through the target area based on the size of each of the at least one related area and the number of people estimated to be present in each of the at least one related area. With this configuration, the traffic volume of the target area is estimated based on at least one related area related to the target area. In other words, the traffic volume of the target area can be estimated based on areas related to the target area.

[0071] The extraction unit 12 of the traffic volume estimation device 1 may extract at least one or more related areas, each of which includes a part of the target area. With this configuration, it is possible to more accurately estimate the traffic volume of the target area based on at least one or more related areas, each of which includes a part of the target area.

[0072] The extraction unit 12 of the traffic volume estimation device 1 may extract at least one related area based on GPS data (location information) observed in the target area. With this configuration, it is possible to more accurately estimate the traffic volume of the target area based on at least one related area based on the GPS data observed in the target area.

[0073] The extraction unit 12 of the traffic volume estimation device 1 may extract at least one or more related areas, each of which includes a part of the location indicated by the GPS data observed in the target area. With this configuration, it is possible to more accurately estimate the traffic volume in the target area based on the at least one or more related areas, each of which includes a part of the location indicated by the GPS data observed in the target area.

[0074] The extraction unit 12 of the traffic volume estimation device 1 may extract at least one related area based on clustering of positions indicated by GPS data observed in the target area. With this configuration, it is possible to more accurately estimate the traffic volume of the target area based on the at least one related area based on clustering of positions indicated by GPS data observed in the target area.

[0075] The size of the related area may be based on the maximum width of the related area. This configuration allows for more accurate estimation of traffic volume in the target area based on the maximum width of the related area.

[0076] The number of people estimated to be present in the related area may be based on the number of people estimated to be present in the target area, GPS data observed in the target area, and GPS data observed in the related area. With this configuration, it is possible to more accurately estimate the traffic volume in the target area based on the number of people estimated to be present in the target area, GPS data observed in the target area, and GPS data observed in the related area.

[0077] The target area may be an area where outdoor advertisements can be viewed (advertisement viewable area). With this configuration, it is possible to estimate the traffic volume in the advertisement viewable area.

[0078] The estimation unit 13 of the traffic volume estimation device 1 may estimate the number of viewers of the outdoor advertisement in the target area based on the traffic volume. With this configuration, it is possible to estimate the number of viewers of the outdoor advertisement in the target area.

[0079] The traffic volume estimation device 1 relates to area division (extraction of relevant areas) for estimating the number of viewers of an advertisement. The traffic volume estimation device 1 can estimate the number of viewers (IMP) of an outdoor advertisement in a situation where accurate demographic data is not available. The traffic volume estimation device 1 divides an advertisement viewable area (extracts relevant areas) to estimate traffic volume. The traffic volume estimation device 1 uses logic for dividing an advertisement viewable area (extracts relevant areas) for traffic volume estimation. The traffic volume estimation device 1 divides an advertisement viewable area (extracts relevant areas) and calculates (estimates) IMP or V-imp by finding traffic volume for each divided area (relevant area).

[0080] The traffic volume estimation device 1 of the present disclosure may have the following configuration.

[0081] [1] A traffic volume estimation device comprising: an extraction unit that extracts at least one related area related to a target area; and an estimation unit that estimates traffic volume related to the number of people passing through the target area based on the size of each of the at least one related area and the number of people estimated to be present in each of the at least one related area.

[0082] [2] The traffic volume estimation device according to [1], wherein the extraction unit extracts the at least one related area, each of which includes a part of the target area.

[0083] [3] The traffic volume estimation device according to [1] or [2], wherein the extraction unit extracts the at least one related area based on position information observed in the target area.

[0084] [4] The traffic volume estimation device according to any one of [1] to [3], wherein the extraction unit extracts the at least one related area, each of which includes a part of a position indicated by the position information observed in the target area.

[0085] [5] The traffic volume estimation device according to any one of [1] to [4], wherein the extraction unit extracts the at least one related area based on clustering of positions indicated by position information observed in the target area.

[0086] [6] The traffic volume estimation device according to any one of [1] to [5], wherein the size of the relevant area is based on a maximum width of the relevant area.

[0087] [7] The traffic volume estimation device according to any one of [1] to [6], wherein the number of people estimated to be present in the related area is based on the number of people estimated to be present in the target area, location information observed in the target area, and location information observed in the related area.

[0088] [8] The traffic volume estimation device according to any one of [1] to [7], wherein the target area is an area where outdoor advertisements can be viewed.

[0089] [9] The traffic volume estimation device according to any one of [1] to [8], wherein the estimation unit estimates the number of viewers of the outdoor advertisement in the target area based on the traffic volume.

[0090] The block diagrams used to explain the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of hardware and / or software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (e.g., wired, wireless, etc.) and these multiple devices. The functional block may also be realized by combining software with the single device or multiple devices.

[0091] Functions include, but are not limited to, judgment, determination, assessment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

[0092] For example, the traffic volume estimation device 1 according to an embodiment of the present disclosure may function as a computer that performs processing of the traffic volume estimation method of the present disclosure. Fig. 22 is a diagram illustrating an example of a hardware configuration of the traffic volume estimation device 1 according to an embodiment of the present disclosure. The traffic volume estimation device 1 described above may be physically configured as a computer including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.

[0093] In the following description, the term "apparatus" may be interpreted as a circuit, a device, a unit, etc. The hardware configuration of the traffic volume estimation apparatus 1 may be configured to include one or more of the devices shown in the drawings, or may be configured to exclude some of the devices.

[0094] Each function of the traffic volume estimation device 1 is realized by loading specified software (programs) onto hardware such as a processor 1001 and a memory 1002, causing the processor 1001 to perform calculations, control communication via a communication device 1004, and control at least one of reading and writing data in the memory 1002 and the storage 1003.

[0095] The processor 1001 controls the entire computer by running, for example, an operating system. The processor 1001 may be configured by a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc. For example, the above-mentioned acquisition unit 11, extraction unit 12, estimation unit 13, etc. may be realized by the processor 1001.

[0096] The processor 1001 also reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002 and executes various processes in accordance with the programs. The programs used are those that cause a computer to execute at least some of the operations described in the above-described embodiments. For example, the acquisition unit 11, extraction unit 12, and estimation unit 13 may be implemented by a control program stored in the memory 1002 and running on the processor 1001, and similar implementations may be made for other functional blocks. While the above-described various processes have been described as being executed by one processor 1001, they may also be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The programs may also be transmitted from a network via a telecommunications line.

[0097] The memory 1002 is a computer-readable recording medium and may be configured by, for example, at least one of a read-only memory (ROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a random access memory (RAM), etc. The memory 1002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 1002 can store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to an embodiment of the present disclosure.

[0098] Storage 1003 is a computer-readable recording medium, and may be composed of at least one of, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc. Storage 1003 may also be referred to as an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, a server, or other appropriate medium including at least one of memory 1002 and storage 1003.

[0099] The communication device 1004 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, a communication module, etc. The communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc. to realize at least one of frequency division duplex (FDD) and time division duplex (TDD). For example, the above-mentioned acquisition unit 11, extraction unit 12, estimation unit 13, etc. may be realized by the communication device 1004.

[0100] The input device 1005 is an input device (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives input from the outside. The output device 1006 is an output device (e.g., a display, a speaker, an LED lamp, etc.) that outputs to the outside. Note that the input device 1005 and the output device 1006 may be integrated into one device (e.g., a touch panel).

[0101] Furthermore, each device, such as the processor 1001 and the memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between each device.

[0102] The traffic volume estimation device 1 may also be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

[0103] Notification of information is not limited to the aspects / embodiments described in this disclosure, and may be performed using other methods.

[0104] Each aspect / embodiment described in the present disclosure may be applied to at least one of systems using LTE (Long Term Evolution), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), FRA (Future Radio Access), NR (New Radio), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, UWB (Ultra-Wide Band), Bluetooth (registered trademark), or other suitable systems, and next-generation systems enhanced based on these. Furthermore, a combination of multiple systems (e.g., a combination of at least one of LTE and LTE-A with 5G, etc.) may also be applied.

[0105] The order of the procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be changed unless it is consistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0106] Input and output information may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be sent to another device.

[0107] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0108] The aspects / embodiments described in this disclosure may be used alone, in combination, or switched depending on the implementation. Notification of predetermined information (e.g., notification that "X is true") is not limited to explicit notification, but may be implicit (e.g., not notifying the predetermined information).

[0109] Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure.

[0110] Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

[0111] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then these wired and / or wireless technologies are included within the definition of transmission media.

[0112] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0113] In addition, terms explained in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings.

[0114] As used in this disclosure, the terms "system" and "network" are used interchangeably.

[0115] Furthermore, the information, parameters, etc. described in this disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information.

[0116] The names used for the above parameters are not limiting in any way, and furthermore, the mathematical formulas etc. using these parameters may differ from those explicitly disclosed in this disclosure.

[0117] As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching a table, database, or other data structure), ascertaining, and the like. "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like, all of which are considered to be "determining." "Determining" and "determining" may also include resolving, selecting, choosing, establishing, comparing, and the like, all of which are considered to be "determining." In other words, "judgment" and "decision" can include regarding some action as having been "judged" or "decided." Also, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

[0118] The terms "connected," "coupled," or any variation thereof, refer to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "access." As used in this disclosure, two elements may be considered to be "connected" or "coupled" to each other using one or more wires, cables, and / or printed electrical connections, as well as electromagnetic energy having wavelengths in the radio frequency range, microwave range, and optical (both visible and invisible) range, as some non-limiting and non-exhaustive examples.

[0119] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0120] As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed or that the first element must in some way precede the second element.

[0121] The "means" in the configuration of each of the above devices may be replaced with "part," "circuit," "device," etc.

[0122] When the terms "include," "including," and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, when the term "or" is used in this disclosure, it is not intended to be an exclusive or.

[0123] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0124] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different."

[0125] 1...traffic volume estimation device, 2...terminal, 3...traffic volume estimation system, 10...storage unit, 11...acquisition unit, 12...extraction unit, 13...estimation unit, 1001...processor, 1002...memory, 1003...storage, 1004...communication device, 1005...input device, 1006...output device, 1007...bus.

Claims

1. An extraction unit that extracts at least one or more related areas related to the target area, and an estimation unit that estimates the traffic volume regarding the number of people passing through the target area based on the size of each of the at least one or more related areas and the number of people estimated to exist in each of the at least one or more related areas. A traffic volume estimation device comprising the above.

2. The traffic volume estimation device according to claim 1, wherein the extraction unit extracts the at least one or more related areas each containing a part of the target area.

3. The traffic volume estimation device according to claim 1, wherein the extraction unit extracts the at least one or more related areas based on the position information observed in the target area.

4. The traffic volume estimation device according to claim 1, wherein the extraction unit extracts the at least one or more related areas each containing a part of the position indicated by the position information observed in the target area.

5. The traffic volume estimation device according to claim 1, wherein the extraction unit extracts the at least one or more related areas based on the clustering of the position indicated by the position information observed in the target area.

6. The traffic volume estimation device according to claim 1, wherein the size of the related area is based on the maximum width of the related area.

7. The traffic volume estimation device according to claim 1, wherein the number of people estimated to exist in the related area is based on the number of people estimated to exist in the target area, the position information observed in the target area, and the position information observed in the related area.

8. The traffic volume estimation device according to claim 1, wherein the target area is an area where outdoor advertisements can be viewed.

9. The traffic volume estimation device according to claim 1, wherein the estimation unit estimates the number of viewers of the outdoor advertisement in the target area based on the traffic volume.

10. An extraction step in which a computer extracts at least one or more related areas related to a target area, and an estimation step in which the computer estimates a traffic volume regarding the number of people passing through the target area based on the size of each of the at least one or more related areas and the number of people estimated to be present in each of the at least one or more related areas. A traffic volume estimation method including these steps.

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