Management device

Abstract

To improve the accuracy of estimating the number of visitors to the facility. [Solution] The management device acquires the passenger count parameter of the first reserved vehicle, calculates the average number of passengers in the first reserved vehicle during the target period using the passenger count parameter of each first reserved vehicle, identifies the number of provisional visitors by referring to correlation information using the number of first reserved vehicles, and estimates the number of visitors by correcting the number of provisional visitors based on the average number of passengers in the first reserved vehicle and the average number of passengers in the second reserved vehicle.

Description

Technical Field

[0001] This disclosure relates to a management device.

Background Art

[0002] For example, Japanese Unexamined Patent Application Publication No. 2003-6376 discloses a prediction method for predicting the number of visitors to a leisure area. In this prediction method, a plurality of road sensors are installed on a road, the number of vehicles passing through is detected by these road sensors, and the number of visitors is estimated based on the number of passing vehicles.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the above prediction method, although a vehicle has passed through a road sensor, the vehicle may not go to the leisure area. Therefore, there may arise a problem that the estimation accuracy of the number of visitors is low.

[0005] This disclosure has been made to solve the above problems, and an object of this disclosure is to improve the estimation accuracy of the number of visitors to a facility.

Means for Solving the Problems

[0006] A management device for managing a facility having charging equipment and a plurality of vehicles that can be charged by the charging equipment, wherein each of the plurality of vehicles is equipped with a detection device for detecting an occupancy parameter relating to the number of occupants of the vehicle, the management device comprises a calculation device for estimating the number of visitors to the facility during a target period, and a memory, the memory containing, among the plurality of vehicles, the number of at least one first reserved vehicle that has reserved the use of the charging equipment during the target period, the number of at least one second reserved vehicle that has reserved the use of the charging equipment during each of a plurality of specific periods prior to the target period, and the number of visitors to the facility during each specific period. The system stores correlation information showing a correlation with the number of visitors to the facility, and information that allows for the calculation of the average number of passengers in the second reserved vehicle during a plurality of predetermined periods prior to the target period. The calculation device acquires the passenger number parameter of the first reserved vehicle, calculates the average number of passengers in the first reserved vehicle during the target period using the passenger number parameter of each of the first reserved vehicle, identifies the number of provisional visitors by referring to the correlation information using the number of first reserved vehicles, and estimates the number of visitors by correcting the number of provisional visitors using the average number of passengers in the first reserved vehicle and the average number of passengers in the second reserved vehicle. [Effects of the Invention]

[0007] According to this disclosure, it is possible to improve the accuracy of estimating the number of visitors to a facility. [Brief explanation of the drawing]

[0008] [Figure 1] This figure shows an example of the configuration of the estimation system in this disclosure. [Figure 2] This is a functional block diagram of the estimation device in this disclosure. [Figure 3] This is a flowchart showing the processing of the estimation device in this disclosure. [Modes for carrying out the invention]

[0009] The embodiments of this disclosure will be described in detail below with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals, and their descriptions will not be repeated.

[0010] Figure 1 shows an example configuration of the estimation system 500 of this disclosure. The estimation system 500 comprises a plurality of electric vehicles 200, a facility 300, and a management device 350 that manages the plurality of vehicles 200 and the facility 300.

[0011] Each of the multiple vehicles 200 is, for example, an electric vehicle and is rechargeable by a charging facility 302. Each of the multiple vehicles 200 has a detection device 210 for detecting an occupancy parameter relating to the number of occupants of the vehicle. In this disclosure, the detection device 210 includes a plurality of weight sensors 202.

[0012] Multiple weight sensors 202 are installed on multiple seats in the vehicle 200. For example, if the vehicle 200 has four seats, four weight sensors 202 are installed on each of the four seats. The weight values ​​detected by the multiple weight sensors 202 correspond to an example of the number of occupants parameter. However, other parameters may be used as long as the management device 350 can identify the number of occupants in the vehicle. The detection device 210 may be, for example, a camera capable of capturing images of all occupants in the vehicle 200. In this case, the number of occupants parameter becomes the image data of the images captured by the camera.

[0013] The occupant parameters detected by the detection devices 210 in each vehicle 200 are transmitted to the management device 350 via the network NW.

[0014] Facility 300 has charging facilities 302 and a shop 304 (for example, a restaurant). Customers arrive at Facility 300 (shop 304) by vehicle 200 and by means other than vehicle 200. Means other than vehicle 200 include walking, train, bus, and vehicles that have not reserved the use of charging facilities 302. Charging facilities 302 consists of, for example, at least one charger.

[0015] Facility 300 provides a reservation site (not shown) via the internet or other means for users to reserve charging equipment 302. For example, if a customer plans to visit with vehicle 200, the customer reserves the use of charging equipment 302. For example, the customer inputs reservation information, including the future period (usage period) for which they will use charging equipment 302, from an information processing device (not shown) (for example, the customer's mobile terminal). The usage period includes, for example, the date on which charging equipment 302 will be used. Management device 350 acquires the reservation information entered into the information processing device. The target period can be determined, for example, by the manager of store 304, and is the period during which store 304 is in business. Hereinafter, a vehicle that has reserved the future use of charging equipment 302 will also be referred to as the "first reserved vehicle." A vehicle that has reserved the use of charging equipment 302 in a period prior to the target period (past period) will also be referred to as the "second reserved vehicle."

[0016] The management device 350 estimates the number of visitors to the facility 300 during the target period. The management device 350 has a CPU (Central Processing Unit) 351, a memory 352, and an interface 353. The CPU 351 performs various controls. Various information is stored in the memory 352. The interface 353 communicates with external devices (for example, a vehicle 200). The CPU 351 corresponds to the “arithmetic unit” in this disclosure.

[0017] Figure 2 is a functional block diagram of the management device 350. The management device 350 includes a temporary visitor count identification unit 102, a crew count identification unit 104, a correction coefficient identification unit 106, a multiplication unit 108, and a storage unit 110.

[0018] The storage unit 110 stores vehicle count information A, correlation information B, and passenger number information C, etc. Vehicle count information A is information indicating the number of first reserved vehicles, of which at least one vehicle has reserved the use of the charging equipment 302 during the target period, out of a plurality of vehicles 200. The management device 350 updates the vehicle count information A in the storage unit 110 each time it acquires reservation information.

[0019] The correlation information B in FIG. 2 is information in a period before the target period (past period). The past period is, for example, a period before the day before the start time of the target period. Also, the past period is divided into a plurality of specific periods. The specific period is, for example, one day. At least two of the plurality of specific periods may be different. The correlation information B shows a plurality (14 in the example of FIG. 2) of correlations between the number of at least one second reserved vehicle that reserved the use of the charging facility 302 in one past specific period and the number of visitors to the facility 300 in that one specific period. The correlation information B is created, for example, based on past statistics (such as actual measurements or questionnaires).

[0020] In the correlation information B of FIG. 2, the horizontal axis indicates the number of past second reserved vehicles, and the vertical axis indicates the number of past visitors. Note that, as will be described later, the number of past visitors corresponds to the "temporary number of visitors". In the correlation information B of FIG. 2, 14 (a plurality of) plots B1 are shown. That is, the correlation information B in FIG. 2 shows the correlation information for 14 days in the past period. Also, a function B2 is created from the plurality of plots B1.

[0021] The passenger number information C is information capable of calculating the average number of passengers in the second reserved vehicle in a plurality of predetermined periods before the target period (past period). In the present disclosure, the predetermined period is, for example, one day, and the predetermined period and the above-mentioned specific period may be the same or different. At least two of the plurality of predetermined periods may be different. In the example of FIG. 2, 10 (a plurality of) plots C1 are shown. That is, the passenger number information C in FIG. 2 shows the average number of passengers in the second reserved vehicle for 10 days in the past. In the example of FIG. 2, the average value of the average number of passengers for 10 days is about "1.2 persons".

[0022] FIG. 3 is a flowchart of the estimated number of visitors by the management device 350. The management device 350 executes this estimation process at a predetermined cycle (for example, every 1 hour) on the day to which the target period belongs. The provisional visitor number identification unit 102 acquires the number information A from the storage unit 110 (step S2). Then, the provisional visitor number identification unit 102 refers to the correlation information B using the number information A to identify the provisional visitor number (step S4). For example, the provisional visitor number identification unit 102 inputs the number information A into the function B2 to derive the provisional visitor number. Thus, based on the past correlation, the provisional visitor number to the facility 300 in the target period can be estimated.

[0023] Also, the passenger number identification unit 104 acquires a weight value from at least one weight sensor 202 of the vehicle 200 (step S6). The passenger number identification unit 104 identifies the number of passengers in the vehicle 200 as the number of weight values greater than a predetermined threshold value (for example, 15 kg). Thus, for example, it is possible to prevent luggage (lighter than the above threshold value) placed on the vehicle 200 from being identified as the number of passengers.

[0024] Also, the passenger number identification unit 104 calculates the average number of passengers in the first reserved vehicle during the target period using the weight value of each of the first reserved vehicles (step S8). Here, the average number of passengers in the first reserved vehicle is "3 persons". Note that these 3 persons are indicated by the plot C2 in FIG. 2.

[0025] The correction coefficient identification unit 106 identifies a correction coefficient (2.5) by, for example, dividing the average number of passengers in the first reserved vehicle (3 persons) by the average number of passengers in the second reserved vehicle (1.2 persons). Then, the multiplication unit 108 multiplies the provisional visitor number by the correction coefficient to calculate and output the number of visitors.

[0026] In this way, the management device 350 estimates the number of hypothetical visitors using correlation information B, which shows the correlation between reserved vehicles (second reserved vehicles) and the actual number of visitors in the past for multiple specific periods. Furthermore, as shown in the passenger information C in Figure 2, in the past, the average number of passengers in reserved vehicles (second reserved vehicles) was 1.2, but when certain conditions are met, the average number of passengers in reserved vehicles (first reserved vehicles) may be higher (3 people in the example in Figure 2). These predetermined conditions are, for example, conditions in which the number of visitors to the area including facility 300 is higher than during normal periods (periods when the predetermined conditions are not met), such as when there is a festival in the area. In this case, it is expected that not only the number of visitors to facility 300 by vehicle 200, but also the number of visitors by means other than vehicle 200 (train, walking, etc.) will be higher than during normal periods.

[0027] Therefore, the management device 350 estimates the number of visitors by correcting the number of provisional visitors based on the average number of passengers in the first reserved vehicle and the average number of passengers in the second reserved vehicle. Specifically, the management device 350 estimates the number of visitors by multiplying the number of provisional visitors by a correction coefficient. As a result, for example, even if the target period is a period in which predetermined conditions are met, the management device 350 can accurately estimate the number of visitors to the facility 300.

[0028] Next, a modified example will be described. As a first modified example, the memory (storage unit 110) further stores second correlation information showing the correlation between the number of visitors to facility 300 during each of several second specific periods prior to the target period and the sales at facility 300 during each second specific period. In the second correlation information, for example, the horizontal axis of correlation information B shows the number of past visitors, and the vertical axis shows the sales at facility 300 during the past. The management device 350 may use the estimated number of visitors and refer to the second correlation information to estimate the sales at the facility during the target period. With such a configuration, not only the number of visitors to facility 300 but also the sales of the facility (store 304) can be estimated.

[0029] As a second modification, the memory (storage unit 110) may store the home location information of a facility related to the home of the user (customer) of the first reserved vehicle (home-related facility) and the facility location information of facility 300. The home-related facility may be not only the home but also an interchange near the home. The management device 350 then notifies the administrator of the management device 350 (for example, the administrator of facility 300) of the first information if the distance between the home location and the location of facility 300 is greater than a predetermined threshold. The first information is information indicating that the first reserved vehicle will travel a long distance. This allows, for example, the administrator of facility 300 to recognize that the customer has traveled a long distance in the first reserved vehicle to visit facility 300. Therefore, for example, the administrator of facility 300 can perform processing corresponding to the customer who has traveled a long distance (for example, preparing a large meal or drink). Furthermore, the management device 350 may also notify the administrator of the management device 350 of the first information if the distance between the location of the first reserved vehicle and the location of the facility 300 when the use of the charging equipment 302 is reserved is greater than a predetermined threshold.

[0030] Furthermore, as a third modification, the memory (storage unit 110) may further store multiple locations of the first reserved vehicle that is in motion. The management device 350 generates second information based on the location of the home-related facilities of the user of the first reserved vehicle, these multiple locations, and the location of the facility 300, and notifies the administrator of the management device 350 of this second information. The second information indicates whether the first reserved vehicle heading towards the facility 300 is traveling towards the home-related facilities or away from them. This second information is notified to the administrator of the management device 350. This allows the administrator to perform processing for the user of the first reserved vehicle traveling away from the home-related facilities (for example, preparing a large meal). It also allows the administrator to perform processing for the user of the first reserved vehicle traveling away from the home-related facilities (for example, preparing souvenirs).

[0031] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of this disclosure is indicated by the claims rather than by the description of the embodiments above, and all modifications within the meaning and scope equivalent to the claims are intended to be included. [Explanation of Symbols]

[0032] 200 vehicles, 300 facilities, 350 control devices.

Claims

[Claim 1] A management device for managing a facility having charging equipment and a plurality of vehicles that can be charged by said charging equipment, Each of the aforementioned plurality of vehicles is equipped with a detection device for detecting an occupancy parameter related to the number of occupants of the vehicle, The aforementioned control device is A computing device for estimating the number of visitors to the facility during the target period, Equipped with memory, The aforementioned memory is Of the aforementioned multiple vehicles, the number of at least one first reserved vehicle that has reserved the use of the charging equipment during the aforementioned period, Correlation information showing the correlation between the number of at least one second reserved vehicle that reserved the use of the charging equipment during each of several specific periods prior to the aforementioned target period and the number of visitors to the facility during that specific period, The system stores information that allows for the calculation of the average number of passengers in the second reserved vehicle during a plurality of predetermined periods prior to the aforementioned target period. The aforementioned computing device is The passenger count parameter of the first reserved vehicle is obtained, Using the passenger capacity parameters for each of the first reserved vehicles, the average number of passengers in the first reserved vehicle during the target period is calculated. Using the number of the first reserved vehicles, and referring to the correlation information, the number of provisional visitors is determined. A management device that estimates the number of visitors by correcting the number of provisional visitors using the average number of passengers in the first reserved vehicle and the average number of passengers in the second reserved vehicle.

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