Management device, mobile store robot, program, and method for searching for a route for a mobile store

Abstract

To provide a management device, mobile shop robot, moving route search method, and program that can search for a moving route that improves sales capacity.SOLUTION: A management device includes: a real cost map calculation unit configured to calculate an expected profit amount according to products and services sold at a mobile shop for each route section; a moving route search unit configured to search for a moving route with the highest total expected profit amount based on the expected profit amount for each route section; an expected sales amount calculation unit configured to calculate an expected sales amount for each route section; and an expected cost calculation unit configured to calculate an expected cost amount for each route section. The real cost map calculation unit calculates the expected profit amount by subtracting the expected cost amount from the expected sales amount. The expected sales amount calculation unit refers to a relationship based on past number of users by attribute and purchase history, for each route section, predicts purchases from current number of users by attribute for each route section, and calculates the expected sales amount.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a technique for searching for a route for a mobile object, and in particular to a mobile store that provides products and services to users. [Background technology]

[0002] Conventionally, there is a technology for a system that generates an operation plan for a mobile store (see, for example, Patent Document 1). According to this technology, a user transmits a mobile store that he or she wishes to visit to a server as a visit request, and the mobile store is controlled to move to a specified location. There is also a technique for acquiring purchase information of a product or service by a user from a first mobile store and transmitting the purchase information of the user to a second mobile store (see, for example, Patent Document 2). Furthermore, there is a technique in which, after business hours of a specific store, a mobile vehicle carrying merchandise from the specific store is parked at a pre-specified sales location for a predetermined period of time to sell the merchandise (see, for example, Patent Document 3).

[0003] Another prior art is a mobile store management device that reduces the burden on users when purchasing products (see, for example, Patent Document 4). According to this technology, a management device that manages a mobile store that sells products by autonomously traveling along aisles in a specified area has a seating information acquisition unit that acquires seating information indicating the seating position of a user who is seated at an office, a route determination unit that determines the route the mobile store will take based on the seating position indicated by the seating information, and a route notification unit that notifies the mobile store of the determined route. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2019-139371 A [Patent Document 2] JP 2020-119006 A [Patent Document 3] Special Publication No. 2020-126559 [Patent Document 4] Patent Publication No. 2022-093927 Summary of the Invention [Problem to be solved by the invention]

[0005] According to the above-mentioned Patent Documents 1 to 3, a vehicle is assumed as the mobile store. On the other hand, according to Patent Document 4, a mobile robot is assumed as the mobile store. When a mobile robot is used as a mobile store, it is expected to increase the convenience of access to the mobile store as an advantage for the user. In this case, although the loading capacity is limited compared to a vehicle, it can move through narrow spaces. Also, the mobile store can enter not only outdoor roads but also corridors inside a facility (for example, in front of the security gate of an office).

[0006] In response to this, the inventors of the present application have considered whether it would be possible to improve the sales power of mobile stores as an advantage for the sellers of goods and services. In other words, they have considered whether it would be possible to search for a travel route that would improve the sales power of a mobile store.

[0007] Therefore, an object of the present invention is to provide a management device, a mobile store robot, a program, and a method that are capable of searching for a travel route that will improve sales power. [Means for solving the problem]

[0008] According to the present invention, there is provided a management device for searching a route for a mobile store, comprising: a real cost map calculation means for calculating an expected profit amount according to the products and services sold at the mobile store for each route section; a route search means for searching for a route that will maximize the total expected profit amount based on the expected profit amount for each route section; The present invention is characterized by having the following.

[0009] According to another embodiment of the management device of the present invention, an expected sales amount calculation means for calculating an expected sales amount for each route section; an estimated cost calculation means for calculating an estimated cost for each route section; and The real cost map calculation unit calculates the expected profit by subtracting the expected cost from the expected sales. It is also preferable.

[0010] According to another embodiment of the management device of the present invention, A means for estimating the number of users by attribute for each travel section; A purchase history database that stores the purchase history information of the user at the mobile store; having The expected sales amount calculation means calculates an expected sales amount from the current number of users by attribute based on the past number of users by attribute and purchase history for each route section. It is also preferable.

[0011] According to another embodiment of the management device of the present invention, The method for estimating the number of users by attribute estimates the number of users by attribute based on the location information of mobile devices owned by an unspecified number of people and the subscriber attributes. It is also preferable.

[0012] According to another embodiment of the management device of the present invention, When the upper limit sales amount calculated from the saleable goods and services exceeds the expected sales amount, the movement route search means re-searches for a movement route with the smallest expected cost amount among movement routes that are equal to or greater than the upper limit sales amount. It is also preferable.

[0013] According to another embodiment of the management device of the present invention, The mobile store further includes a communication resource allocation calculation means for calculating a communication resource allocation amount according to a position of the mobile store, The expected cost calculation means increases the expected cost as the communication resource allocation amount increases. It is also preferable.

[0014] According to another embodiment of the management device of the present invention, The estimated cost calculation means increases the estimated cost as the number of mobile terminals located within the route section increases. It is also preferable.

[0015] According to another embodiment of the management device of the present invention, The communication resource allocation calculation means controls network slicing of the wireless access network so as to reduce the communication resource allocation when the mobile store is moving and to increase the communication resource allocation when the mobile store is parked. It is also preferable.

[0016] According to another embodiment of the management device of the present invention, the management device is capable of communicating with a communication resource management device of a radio access network that allocates communication resources between the mobile store and a radio base station; The communication resource allocation calculation means For each route section, the MCS (Modulation and Coding Scheme) of the mobile store communicating with the wireless base station is recorded. Calculate communication resource allocation based on past MCS values ​​for the route section where the mobile store is located It is also preferable.

[0017] According to another embodiment of the management device of the present invention, The travel route search means calculates the population density for each route section from the total number of users for each travel section estimated by the attribute-specific user number estimation means, and searches for route sections other than the route sections in which the population density is equal to or less than a predetermined threshold as travel routes. It is also preferable.

[0018] According to another embodiment of the management device of the present invention, The mobile store is a self-propelled mobile store robot. It is also preferable.

[0019] According to the present invention, there is provided a self-propelled mobile store robot that searches for a movement path, comprising: For each route section The mobile store robot itself A real cost map calculation means for calculating an expected profit amount according to the product or service to be sold; a route search means for searching for a route that will maximize the total expected profit amount based on the expected profit amount for each route section; The present invention is characterized by having the following.

[0020] According to the present invention, there is provided a program for causing a computer to function to search for a travel route of a mobile store, the program comprising: a real cost map calculation means for calculating an expected profit amount according to the products and services sold at the mobile store for each route section; a route search means for searching for a route that will maximize the total expected profit amount based on the expected profit amount for each route section; The present invention is characterized in that it causes a computer to function.

[0021] According to the present invention, there is provided a method for searching a route for a mobile store, comprising the steps of: The device is A first step of calculating an expected profit amount according to products and services sold at the mobile store for each route section; A second step of searching for a travel route that will maximize the total amount of expected profit based on the expected profit amount for each route segment; The present invention is characterized by carrying out the following steps. Effect of the Invention

[0022] According to the management device, mobile store robot, program, and method of the present invention, it is possible to search for a travel route that improves sales power. [Brief description of the drawings]

[0023] [Figure 1] FIG. 1 is a system configuration diagram according to the present invention. [Diagram 2] FIG. 2 is a functional configuration diagram of a mobile store robot according to the present invention. [Diagram 3] FIG. 2 is a functional configuration diagram of a management device according to the present invention. [Figure 4] FIG. 2 is an explanatory diagram showing sales information according to a route section in the present invention. [Diagram 5] FIG. 13 is an explanatory diagram showing the control of a moving path in the present invention. [Figure 6] 4 is a flowchart of the management device of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0024] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0025] FIG. 1 is a diagram showing a system configuration according to the present invention. According to the system of FIG. 1, a mobile store 1, a mobile terminal 2, a management device 3, and a communication resource management device 4 communicate with each other via a network.

[0026] [Mobile store 1] The mobile store 1 is capable of moving to sell products and services to users. The mobile store 1 will be described as a self-propelled mobile store robot (smart mobility), but it may of course be a vehicle store that is moved manually. The route assumed by the present invention may be a road on which general vehicles run, or may be, for example, a passageway within a facility. It is sufficient if it is a route on which an unspecified number of third parties pass and where the mobile store 1 can pass and park.

[0027] [Mobile device 2] The mobile terminals 2 are held by an unspecified number of third parties located around the route. For example, they may be smartphones that people carry when they go out, and may not be related to the services of the mobile store 1. It is preferable that the mobile terminals 2 are for all subscribers who have a contract with a specific communication carrier and have agreed to the acquisition of location information.

[0028] [Management device 3] The management device 3 can search for a route that will increase the expected sales amount so as to increase the sales of the products and services of the mobile store. In the case of a mobile store robot, the management device 3 makes the robot autonomously travel along the route and automatically sell the products and services. Furthermore, the management device 3 can instruct the mobile store 1 on a travel route via the network, and can also collect the number of stays of the mobile terminal 2 in each route section. The technology for searching for a travel route by the management device 3 can also be incorporated into the mobile store robot itself, which has path planning. This allows the mobile store robot to travel completely autonomously by itself.

[0029] [Communication resource management device 4] The communication resource management device 4 allocates communication resources of a wireless access network between the mobile store 1 and a wireless base station. According to the present invention, the communication resource allocation to the base station communicating with the mobile store 1 is controlled in response to an instruction from the management device 3. The wireless area of ​​the communication resources is not limited to outdoors, but may be indoors, or may be usable both outdoors and indoors.

[0030] FIG. 2 is a functional configuration diagram of a mobile store robot according to the present invention.

[0031] 2, the mobile store 1 includes a product mounting unit 101, a wireless communication unit 102, a wireless quality acquisition unit 103, a current position acquisition unit 104, a status acquisition unit 105, an image capture unit 106, a route information storage unit 107, a sound collection unit 108, a dialogue processing unit 109, an operation planning unit 110, an operation control unit 111, a purchase processing unit 112, and a purchase display unit 113. These functional components are realized by executing a program that causes a computer mounted in the mobile store to function. The process flow of these functional components can also be understood as a control method for the mobile store.

[0032] [Product loading section 101] The product loading unit 101 is a container for loading products. Of course, it may be a shelf or a box, or a box with a door at the opening. It may also be something that keeps the loaded products warm or cold. These products may be provided to the user manually, or may be provided by a control device such as an arm robot. Of course, the product mounting unit 101 may be a container that provides a service.

[0033] [Wireless communication unit 102] The wireless communication unit 102 is a wireless communication module for communicating with base stations and access points, and communicates with the management device 3 via a Radio Access Network (RAN) or the Internet. Specifically, the wireless communication unit 102 communicates wirelessly with base stations that support wireless communication methods such as 4G (fourth generation mobile communication system) and 5G (fifth generation mobile communication system), which are currently in practical use, and 6G (sixth generation mobile communication system), which is expected to be put to practical use in the future.

[0034] [Radio quality acquisition unit 103] The wireless quality acquisition unit 103 acquires the wireless quality in the wireless communication unit 102 .

[0035] [Current position acquisition unit 104] If the current position acquisition unit 104 is outdoors, it measures the position using, for example, a Global Positioning System (GPS).If the current position acquisition unit 104 is indoors, it may measure the absolute position using, for example, an Indoor Messaging System (IMES).

[0036] [Status Acquisition Unit 105] The status acquisition unit 105 acquires status data such as remaining battery power, temperature, and moving speed from various sensors mounted on the mobile store 1.

[0037] [Imaging unit 106] The imaging unit 106 is, for example, a camera that captures images of the periphery of the mobile store 1. For example, it may be a camera that captures an image of the area ahead in the traveling direction of the mobile store 1. The imaging unit 106 may also include a movement mechanism for moving the camera. By controlling the movement mechanism, images can be captured not only in the forward direction in the traveling direction, but also to the left and right, and above and below.

[0038] [Route information storage unit 107] The route information storage unit 107 stores the information on the travel route received from the management device 3 .

[0039] [Audio recording unit 108] The sound pickup unit 108 is a microphone that picks up sounds around the mobile store 1.

[0040] [Dialogue processing unit 109] The dialogue processing unit 109 has a dialogue with the user by voice or text, which can make the user feel a sense of familiarity and increase the user's willingness to purchase. The dialogue processing unit 109 speaks a dialogue generated by the dialogue processing unit 109 in response to the user's voice collected by the sound collection unit 108.

[0041] [Motion planning unit 110] The operation planner 110 plans the next operation for the mobile store 1. When moving along a moving route stored in the route information storage unit 107, the motion planning unit 110 uses the following information to plan a motion suited to the surrounding environment. The current location acquired by the current location acquisition unit 104 The state of the mobile store 1 acquired by the state acquisition unit 105 Image captured by the imaging unit 106 For example, when there is an obstacle ahead, the motion planning unit 110 plans a motion so as to move along a route that avoids the obstacle at an appropriate moving speed. Furthermore, when the operation planning unit 110 detects the following information in order for a user to purchase a product, it causes the mobile store 1 to temporarily stop. The captured image acquired by the imaging unit 106 indicates that the user is raising his / her hand or approaching A specific statement by a user is detected based on the sound picked up by the sound pickup unit 108. Then, the operation planning unit 110 performs control to open the door of the product mounting unit 101 so that the user can remove the product.

[0042] [Operation control unit 111] The action control unit 111 executes the action determined by the action planning unit 110 . The operation control unit 111 controls the mobile store 1 to move forward, backward, turn right or left, or stop. The operation control unit 111 also controls a movement mechanism that moves the camera to change the orientation of the camera, and opens and closes the doors of the shelves of the product mounting unit 101.

[0043] [Purchase Processing Unit 112] The purchase processing unit 112 promptly performs personal authentication of the user and product identification in order to process the purchase of a product or service. By quickly completing the purchase process, an increase in the amount of sales per unit time can be expected, and user satisfaction can be improved. For example, information on face authentication or fingerprint authentication (for example, when picking up a product from a product shelf) is sent to the management device 3 to perform purchaser authentication as the personal authentication of the user. Alternatively, an IC card reader or a QR code (registered trademark) reader installed in the mobile store 1 may be used to read user identification information from a QR code displayed on the user's IC card, smartphone, or the like. The purchase processing unit 112 may also transmit image analysis information of the product picked up by the user to the management device 3 to recognize the product. Furthermore, an RFID reader or a barcode reader installed in the mobile store 1 may be used to recognize the product by reading an RFID tag or a barcode attached to the product.

[0044] [Purchase display section 113] The purchase display unit 113 displays a notice to the user when it receives a notice of completion of the payment from the management device 3. For example, the purchase display unit 113 may display the following information on the display. -Information identifying the purchasing user (e.g., registered name and membership number) Information about products (e.g. product name, product price, product discount rate) -Information indicating payment completion (e.g. voice or sound effect)

[0045] FIG. 3 is a functional configuration diagram of the management device in the present invention.

[0046] The management device 3 is, for example, a server existing on a cloud, and searches for travel routes of one or more mobile stores 1 and manages various information. The management device 3 includes an operation monitoring unit 301, a location / communication quality / power consumption storage unit 302, a personal information database 303, a purchaser authentication unit 304, a product information database 305, a product recognition unit 306, a settlement unit 307, a purchase history database 308, a dialogue generation unit 309, a location information storage unit 310, an attribute-specific user number estimation unit 311, a projected sales amount calculation unit 312, a total communication resource usage estimation unit 313, a communication resource allocation calculation unit 314, a projected cost calculation unit 315, a real cost map calculation unit 316, a map information storage unit 317, a movement route search unit 318, and a movement route distribution unit 319. These functional components are realized by executing a program that causes a computer installed in the management device to function. The process flow of these functional components can also be understood as a movement route search method in a mobile store.

[0047] [Operation Monitoring Department 301] The operation monitoring unit 301 monitors the operation of one or more mobile stores 1. The operation monitoring unit 301 manages the location information, status information, and video (including images) received in real time, linking them to the ID (identifier) ​​of each mobile store 1. This information may be received and updated at intervals of, for example, one second. The operation monitoring unit 301 analyzes, in particular, the location information, status information, and video, and issues an alert to a system supervisor when it detects a failure in a mobile store 1.

[0048] [Location / communication quality / power consumption storage unit 302] The location / communication quality / power consumption storage unit 302 stores, for each mobile store 1 ID, location information, wireless communication quality information, MCS (Modulation and Coding Scheme) information (described later), and power consumption information between locations in association with each other.

[0049] [Personal Information Database 303] The personal information database 303 stores attribute information in addition to personal information required for personal authentication. Examples of attribute information include gender, age, family structure, etc. It is also preferable to store product and service preferences and the strength or weakness of motivation to purchase at the mobile store 1.

[0050] [Purchaser Authentication Section 304] The purchaser authentication unit 304 executes personal authentication of the purchaser. For example, the personal authentication may be performed by comparing the face image of the purchaser captured by the imaging unit 106 with the facial feature information stored in the personal information database 303.

[0051] [Product Information Database 305] The product information database 305 stores information on products and services that may be provided by the mobile store 1. For example, the database stores information such as product genre, product name, and product price. It is also preferable to store appearance data that indicates the appearance of the product.

[0052] [Product recognition section 306] The product recognition unit 306 identifies the product or service selected by the user (e.g., picked up). For example, the product may be identified by comparing the product image captured by the imaging unit 106 with the product appearance data stored in the product information database 305.

[0053] [Payment Department 307] The settlement unit 307 acquires information indicating the purchasing user identified by the purchaser authentication unit 304 and information indicating the product identified by the product recognition unit 306, and executes the settlement process. After the settlement process is completed, the settlement unit 307 notifies the mobile store 1 of the completion of the settlement process.

[0054] [Purchase History Database 308] The purchase history database 308 stores history information of purchases made by the user at the mobile store 1 . After the payment process is completed by payment unit 307, purchase history database 308 stores the user's purchase log as history information.

[0055] [Dialogue Generation Unit 309] The dialogue generation unit 309 generates a dialogue between the user and the mobile store 1 in order to increase the user's desire to purchase. For example, the dialogue generation unit 309 generates a dialogue introducing recommended products and a dialogue thanking the user for paying attention to the mobile store 1.

[0056] [Location information storage unit 310] The location information storage unit 310 stores the history of location information of the portable terminal 2. For example, the location information of the GPS mounted on the portable terminal 2 is stored in association with time.

[0057] [User Attribute Estimation Department 311] The attribute-specific user number estimation unit 311 estimates the number of users by user attribute for each movement section. Specifically, the attribute-specific user number estimation unit 311 estimates the number of users by attribute from the position information and subscriber attributes of the portable terminals 2 carried by an unspecified number of people.

[0058] The attribute-specific user number estimation unit 311 performs map matching with the map information stored in the map information storage unit 317 based on the history of location information stored in the location information storage unit 310, and counts the number of users on roads and indoor facilities. Map matching is a process in which location information obtained by GPS, which may contain errors, is corrected using map information to place the location on a road, and is used in car navigation systems, etc. It is preferable to determine that a mobile terminal 2 staying in a building along a road is indoors based on the average amount of movement per single time. It is also preferable to be able to determine whether the method of movement of a mobile terminal 2 outdoors is walking or by vehicle based on the magnitude of the average amount of movement. The attribute-based user number estimation unit 311 estimates the number of users by, for example, gender, age, family structure, and monthly data usage fee category.

[0059] Here, a mobile store robot equipped with a POS (Point of Sales) is assumed as the mobile store. Compared to vehicles that run on general roads, a mobile store robot can move through narrow spaces and can enter not only outdoors such as pedestrian streets, but also inside offices and facilities (in front of security gates). This is expected to improve the convenience of users' access to the mobile store 1. The route section along which the mobile store robot travels is adjacent to offices, schools, apartment buildings, commercial buildings, hotels, hospitals, etc., and the attributes of the users, such as age and gender, differ depending on the attributes of the location. In other words, even if the number of users is the same, it is expected that the purchasing rate of products and services will differ greatly. The attribute-specific user number estimation unit 311 estimates the number of users of each user attribute for each travel section along which the mobile store 1 can make sales.

[0060] FIG. 4 is an explanatory diagram showing sales information according to route sections in the present invention. According to FIG. 4, the attribute-specific user number estimation unit 311 estimates the number of users for each user attribute for each route section, for example, as follows. Route section 51: Road Route section 52: Office area Route section 53: School area

[0061] [Expected sales amount calculation unit 312] The expected sales amount calculation unit 312 calculates the expected sales amount for each route section. The expected sales amount calculation unit 312 calculates the expected sales amount from the current number of users by attribute, based on the past number of users by attribute and purchase history (past unit price and purchase rate), for each route section. Number of users (by attribute) x (purchase rate x unit price) = expected sales However, the present invention is not limited to this, and may be implemented using a supervised machine learning engine. The machine learning engine is trained, for example, for each route section, using the number of users by attribute in the past as an explanatory variable and the sales amount in the past as a target variable. Then, the expected sales amount can be predicted by inputting the current number of users by attribute.

[0062] The expected sales amount calculation unit 312 analyzes the number of users for each route section (location attribute) in the attribute-specific user number estimation unit 311 and the attribute information of the purchase history for that route section stored in the purchase history database 308. This allows the unit 312 to estimate the relationship between the number of users, loaded products, and sales amount for each user attribute, and calculate the expected sales amount. In addition, the expected sales calculation unit 312 may classify the estimated results of the relationship between the number of users by attribute and the sales amount by day of the week and time period, and calculate the expected sales amount according to the day of the week and time period when the mobile store 1 is operated. Furthermore, the expected sales amount calculation unit 312 may utilize the purchase waiting time in calculating the expected sales amount. This is because it is expected that if the purchase waiting time becomes too long, the willingness to use the service will decrease. The purchase waiting time may be calculated by measuring the time from when the target user waits in a queue at the mobile store 1 until the purchase process is completed, for example.

[0063] According to FIG. 4 mentioned above, the expected sales amount is calculated for each route section (road 51, office area 52, school area 53) for a certain time period. For example, when popular sweets on SMS are loaded onto the mobile store 1, the purchase rate (number of purchasers ÷ number of users × 100) of teenage females is significantly higher than that of users with other attributes. In this case, the expected sales amount for the estimated 900 teenage female users in the school area 53 is 27,000 yen, which is expected to account for the majority of the sales amount. By dividing the route into sections in this way, it is expected that the expected sales amount can be calculated more accurately by user attribute.

[0064] [Total Communication Resource Usage Estimation Division 313] The total communication resource usage estimation unit 313 estimates the total communication resource usage for each base station.

[0065] [Communication resource allocation calculation unit 314] The communication resource allocation calculation unit 314 calculates the communication resource allocation amount according to the location of the mobile store 1.

[0066] For example, when the mobile store 1 is traveling, position information and status information for operational monitoring are transmitted from the mobile store 1 to the management device 3, requiring only a relatively small amount of communication resources. On the other hand, when the mobile store 1 is in the middle of a purchase process, high-resolution images for purchaser authentication and product recognition are transmitted from the mobile store 1 to the management device 3, requiring a relatively large amount of communication resources. Furthermore, when the wireless communication quality of the mobile store 1 is poor, a large number of communication resources are required to ensure transmission quality. This is because the worse the wireless communication quality is, the lower the frequency utilization efficiency (the number of information bits that can be transmitted per Hz) is.

[0067] The communication resource allocation amount calculation unit 314 may record the MCS (Modulation and Coding Scheme) of the mobile store in communication with the wireless base station for each route section, or may calculate the communication resource allocation amount from the past MCS value of the route section in which the mobile store is located. The frequency utilization efficiency is represented by MCS, which is defined as a combination of a modulation scheme and a coding rate. The position / communication quality / power consumption storage unit 302 stores the MCS in association with the wireless communication quality. This makes it possible to calculate the required communication resource allocation amount according to the behavior of the mobile store 1 and the wireless communication quality.

[0068] Furthermore, the communication resource allocation calculation unit 314 may be unable to allocate all of the desired communication resources due to a lack of communication resources available for allocation at the base station depending on the total communication resource usage for each base station estimated by the total communication resource usage estimation unit 313, resulting in a deterioration in transmission quality. The deterioration in transmission quality leads to an increase in the time required for each user's purchase process, and also leads to an increase in purchase waiting time.

[0069] For example, the maximum throughput value can be estimated as follows: MCS28 frequency efficiency = 5.5547 System bandwidth: 100MHz UPlink rate: 40% Percentage of radio resources available for data transmission: 97% Overhead: 14% Maximum throughput value = 5.5547 x 100M x 0.4 x 0.97 x (1-0.14) = about 185Mbps Under these conditions, if 180 Mbps is expected for UPlink communications other than those of mobile store 1, the communication resource allocation to mobile store 1 will be 5 Mbps. In that case, if the communication resource allocation required for operation monitoring is 1 Mbps and the communication resource allocation required for purchase processing is 30 Mbps, for example, it will be impossible to allocate the communication resources required for purchase processing, which will lead to an increase in the time required for purchase processing.

[0070] In response to this, the communication resource allocation calculation unit 314 controls network slicing of the wireless access network so as to reduce the communication resource allocation amount when the mobile store 1 is moving and to increase the communication resource allocation amount when the mobile store 1 is parked. Network slicing is a method of virtually dividing a network, and here, the slice in which the mobile store 1 is moving and the slice in which the mobile store 1 is parked are set to be different.

[0071] [Estimated Cost Calculation Unit 315] The expected cost calculation unit 315 calculates the expected cost for each route section. The expected cost calculation unit 315 calculates, for each route section (including locations where the mobile store 1 can make sales), the expected cost when the mobile store 1 passes through that route section and sells the product or service.

[0072] The expected cost calculation unit 315 calculates the electricity fee as the cost, for example, based on the history data of the power consumption stored in the position / communication quality / power consumption storage unit 302. The power consumption may be calculated according to the gradient between each position stored in the position / communication quality / power consumption storage unit 302. At this time, since the power consumption differs between the uphill and downhill gradients, the power consumption may be calculated for each direction of movement between each position. Furthermore, since the electricity fee may differ depending on the time of day, the expected cost may be calculated depending on the time of day.

[0073] Further, the expected cost calculation unit 315 may be configured to increase the expected cost as the communication resource allocation amount increases. This is the expected cost of network control expected to secure the communication resources calculated by the communication resource allocation calculation unit 314. Here, the network control cost may be the required conditions and data size when securing a band by network slicing. For example, when the communication resource allocation calculation unit 314 can allocate communication resources that satisfy the required conditions (e.g., throughput) without performing any special processing, the expected cost calculation unit 315 assumes that the network control cost is zero. On the other hand, when special processing is required, such as performing beamforming control of the base station to improve the MCS or performing network route control, the network control cost required for the processing may be assumed and utilized.

[0074] Furthermore, the estimated cost calculation unit 315 may be configured to increase the estimated cost as the number of mobile terminals located within the route section increases.

[0075] [Real cost map calculation unit 316] The real cost map calculation unit 316 calculates the expected profit amount according to the products and services sold at the mobile store for each route section. This is an essential functional unit of the present invention. Specifically, the real cost map calculation unit 316 may calculate the expected profit by subtracting the expected cost calculated by the expected cost calculation unit 315 from the expected sales calculated by the expected sales calculation unit 312 for each route section. Estimated profit = Estimated sales - Estimated expenses

[0076] Here, simply speaking, it is assumed that the more people travel along the route section of the mobile store 1, the higher the expected sales amount will be. However, people who are indoors or in a car or train are unlikely to use the mobile store 1. Therefore, it is preferable for the attribute-specific user number estimation unit 311 to extract only people who are walking as users who are likely to make a purchase. In addition, the more people who communicate a large amount of data, the higher the network control costs become. Therefore, roads with many people who are highly motivated to use the mobile store 1 and few other people can be considered as profitable roads.

[0077] [Map information storage section 317] The map information storage unit 317 stores map information of a route along which the mobile store 1 may travel as map data. Map data is provided as link data that divides branching points into multiple parts as nodes, and defines the parts between each node as links (route sections). This link data consists of data such as the link's unique link ID (identifier), link length, position information of the link's start and end points (nodes), angle (direction), passage width, and passage type.

[0078] [Route Search Unit 318] The travel route search unit 318 searches for a travel route that will maximize the total expected profit amount, based on the expected profit amount for each route section calculated by the real cost map calculation unit 316. This is also an essential functional unit of the present invention.

[0079] There are two patterns for route search: -Search for a route to determine a destination - Search for a route without a specific destination In searching for a travel route that determines a destination, for example, in the case of stopping for a certain period of time at a specified park and selling at mobile store 1, it is assumed that the destination is already determined and sales will be made at mobile store 1 during the journey to the destination, and it is possible to search for a travel route that is expected to generate the most profit. When searching for a route without a set destination, for example, it is possible to search for a route that is expected to generate the most profit within a specified sales time (e.g., 3 hours).

[0080] The travel route search unit 318 can also apply a graph-based algorithm such as Dijkstra's algorithm to the travel route that is the shortest distance connecting the start point and the end point. This is a best-first search algorithm for solving a single-start shortest route problem from edge weights (expected profit amounts) in graph theory.

[0081] FIG. 5 is an explanatory diagram showing the control of the movement path in the present invention.

[0082] FIG. 5(a) illustrates the search for a travel route to determine a destination. According to FIG. 5(a), a search is made for a travel route from departure point A to destination point F that is expected to bring about the most profit. As sales information for each route section, the real cost map calculation unit 316 calculates the expected profit amount. Here, the travel route A->B->C->F is searched for as the travel route that is expected to bring about the most profit. It is also preferable to exclude routes that do not allow arrival at the destination by a specified time, taking into consideration the travel time and purchase processing time for each route section.

[0083] FIG. 5(b) shows a route search without a specific destination. According to Fig. 5(b), for simplification, we assume that the total travel time and purchase processing time for all travel sections is expected to be 20 minutes. For example, when searching for the most profitable travel route in 1 hour, the route A->B->C->A is searched. In addition, when searching for a travel route, the same road may be passed several times. In this case, since a profit is expected to decrease depending on the number of times the same road is passed, it is also preferable to search for a travel route after reflecting the profit decrease due to the number of times the road is passed.

[0084] Furthermore, the travel route search unit 318 may change the travel route by comparing the expected profit amount for each travel section with the actual profit amount in real time.

[0085] Furthermore, the travel route search unit 318 may set the expected profit amount for each travel section to a probabilistic value rather than a fixed value. For example, when there is a travel section where a high profit is expected with a low probability and a travel section where a moderate profit is expected with a high probability, the travel route search unit 318 may determine which travel route to select by determining the value of the probability by comparing with the actual value.

[0086] Furthermore, the travel route searching unit 318 may take into account the influence of weather and change the travel route depending on the weather.

[0087] Furthermore, the travel route search unit 318 may wait in a specific travel section and purposely delay passing through another travel section. This is to allow the target travel section to pass through during a specific time period when the profits in that travel section tend to increase significantly.

[0088] Furthermore, the travel route searching unit 318 may impose some constraints on the route search. The movement route search unit 318 may calculate the population density for each route section from the total number of users for each movement section estimated by the attribute-specific user number estimation unit 311, and search for route sections other than the route sections whose population density is equal to or less than a predetermined threshold as movement routes. For example, this is because there is a concern that if an infectious disease spreads, people will gather near the mobile store 1, creating a crowded environment.

[0089] When the upper limit sales amount calculated from the saleable goods and services exceeds the expected sales amount, the travel route search unit 318 may re-search for a travel route with the lowest expected cost among travel routes that are equal to or greater than the upper limit sales amount. In the case of a mobile store robot, the loading capacity is significantly limited compared to vehicles, so there are cases where products run out of stock while traveling along a route. In this case, the sales limit is reached and there is no profit even if the robot continues to move beyond that, and the costs of electricity and other expenses related to the movement only increase.

[0090] FIG. 5(c) shows a route search that takes into account the upper sales amount for the travel route that determines the destination in FIG. 5(a). Here, if the upper limit sales amount is set to 20,000 yen, the most profitable route A->B->C->F will have a total sales amount of 29,000 yen, which exceeds the upper limit sales amount. In addition, the cost for the route A->B->C->F is 3,000 yen. In this case, therefore, the route A->C->F is searched again, since the sales amount is 22,000 yen, which exceeds the upper limit of 20,000 yen, and the cost is only 2,000 yen.

[0091] [Route Distribution Division 319] The travel route distribution unit 319 transmits the travel route data searched by the travel route search unit 318 to the mobile store 1. Furthermore, the travel route distribution unit 319 may make the travel route data available to the user via an app or the like. By making the travel route data available, the user can know where the mobile store 1 is planning to travel from now on, which is expected to promote purchases. In this case, not only the travel route but also the products and inventory carried by the mobile store 1 may be made available. Also, the user may be able to indicate his / her intention to purchase by specifying a time period and a route section while viewing the travel route data. It is also preferable to adjust the travel speed of the mobile store 1 based on this intention, for example, so that the mobile store 1 can travel along the route section during the target time period.

[0092] FIG. 6 is a flow chart of the management device of the present invention.

[0093] FIG. 6 shows the flow of processing by the travel route search unit 318 using the real cost map calculation unit 316. (S11) First, the starting point of the mobile store robot 1 is acquired. The starting point is assumed to be, for example, a point where the mobile store robot 1 is to be loaded with goods. (S12) Next, it is determined whether or not the reserved movement route of the mobile store robot 1 is a search for a movement route that determines a destination. (S13) If the search is for a travel route that determines a destination, the destination of the mobile store robot 1 is acquired, and the process proceeds to S15. (S14) If the search is for a route without a specified destination, the sales hours of mobile store 1 are obtained, and the process proceeds to S15. (S15) A route that will maximize the total amount of expected profit is searched for. (S16) It is determined whether the expected sales amount for the searched travel route exceeds an upper sales amount limit. (S17) If S16 is determined to be false (the upper limit sales amount is not exceeded), the process proceeds to S18. If S16 is determined to be true (the upper limit sales amount is exceeded), the process re-searches for a route with the lowest expected cost that is equal to or greater than the upper limit sales amount, and proceeds to S18. (S18) The mobile store robot 1 is notified of the route it has found. (S19) The real cost map calculation unit 316 continues to monitor whether there is a change in the cost map. A change in the cost map is, for example, a change in the expected profit amount for each travel route due to a change in the weather or a comparison with the actual profit amount in real time. (S20) If there is a change in the cost map, the movement route is searched again. (S21) Then, the movement route distribution unit 319 notifies the mobile store robot 1 of the re-searched movement route. The processes of S19 to S21 are repeated until the destination is reached or the sales period ends.

[0094] As described above in detail, the management device, mobile store robot, program, and method of the present invention make it possible to search for a travel route that will improve sales power.

[0095] Furthermore, this will enable, for example, "mobile stores to explore routes that will improve sales power," which will contribute to Goal 9 of the United Nations-led Sustainable Development Goals (SDGs), which is to "build resilient infrastructure, promote sustainable industrialization and foster innovation."

[0096] Regarding the various embodiments of the present invention described above, various changes, modifications, and omissions within the scope of the technical idea and perspective of the present invention can be easily made by those skilled in the art. The above description is merely an example and is not intended to be restrictive in any way. The present invention is limited only by the scope of the claims and their equivalents. [Explanation of symbols]

[0097] 1 Mobile store 101 Product loading section 102 Wireless Communication Department 103 Wireless quality acquisition unit 104 Current position acquisition unit 105 Status acquisition unit 106 Imaging unit 107 Route information storage section 108 Sound pickup section 109 Dialogue processing unit 110 Motion Planning Section 111 Motion control section 112 Purchase Processing Unit 113 Purchase display section 2. Mobile devices 3 Management device 301 Operation Monitoring Department 302 Location, communication quality, and power consumption storage section 303 Personal Information Database 304 Purchaser Authentication Department 305 Product Information Database 306 Product recognition department 307 Payment Department 308 Purchase History Database 309 Dialogue Generation Unit 310 Location information storage unit 311 User Count Estimation Department by Attribute 312 Projected Sales Calculation Department 313 Total Communication Resource Usage Estimation Department 314 Communication resource allocation calculation unit 315 Estimated Cost Calculation Department 316 Real Cost Map Calculation Unit 317 Map information storage section 318 Travel Route Search Department 319 Travel Route Distribution Department 4. Communication Resource Management Device

Claims

1. A management device that searches for a moving route of a mobile store, a real cost map calculation means for calculating an expected profit amount according to the products and services sold at the mobile store for each route section; a route search means for searching for a route that will maximize the total expected profit amount based on the expected profit amount for each route section; A management device comprising:

2. an expected sales amount calculation means for calculating an expected sales amount for each route section; an estimated cost calculation means for calculating an estimated cost for each route section; Further comprising: The real cost map calculation unit calculates the expected profit by subtracting the expected cost from the expected sales.

2. The management device according to claim 1.

3. A means for estimating the number of users by attribute for each travel section; A purchase history database that stores the user's purchase history information at the mobile store; having The expected sales amount calculation means calculates an expected sales amount from the current number of users by attribute based on the past number of users by attribute and purchase history for each route section.

3. The management device according to claim 2.

4. The method for estimating the number of users by attribute estimates the number of users by attribute based on the location information and subscriber attributes of mobile devices owned by an unspecified number of people.

4. The management device according to claim 3.

5. When the upper limit sales amount calculated from the saleable goods and services exceeds the expected sales amount, the movement route search means re-searches for a movement route with the smallest expected cost amount among movement routes that are equal to or greater than the upper limit sales amount.

3. The management device according to claim 2.

6. The mobile store further includes a communication resource allocation calculation means for calculating a communication resource allocation amount according to a position of the mobile store, The expected cost calculation means increases the expected cost as the communication resource allocation amount increases.

3. The management device according to claim 2.

7. The estimated cost calculation means increases the estimated cost as the number of mobile terminals located within the route section increases.

7. The management device according to claim 6.

8. The communication resource allocation calculation means controls network slicing of the wireless access network so as to reduce the communication resource allocation when the mobile store is moving and to increase the communication resource allocation when the mobile store is parked.

7. The management device according to claim 6.

9. the management device is capable of communicating with a communication resource management device of a radio access network that allocates communication resources between the mobile store and a radio base station; The communication resource allocation calculation means For each route section, the MCS (Modulation and Coding Scheme) of the mobile store communicating with the wireless base station is recorded. Calculate communication resource allocation from past MCS values ​​in the route section where the mobile store is located 9. The management device according to claim 6, wherein the management device is a device that performs a control process.

10. The travel route search means calculates a population density for each route section from the total number of users for each travel section estimated by the attribute-specific user number estimation means, and searches for route sections other than the route sections in which the population density is equal to or less than a predetermined threshold as travel routes.

4. The management device according to claim 3.

11. The mobile store is a self-propelled mobile store robot.

2. The management device according to claim 1.

12. A self-propelled mobile store robot that searches for a path of movement, a real cost map calculation means for calculating an expected profit amount according to the product or service sold by the mobile store robot for each route section; a route search means for searching for a route that will maximize the total expected profit amount based on the expected profit amount for each route section; A mobile store robot comprising:

13. A program for causing a computer to function to search for a travel route of a mobile store, a real cost map calculation means for calculating an expected profit amount according to the products and services sold at the mobile store for each route section; a route search means for searching for a route that will maximize the total expected profit amount based on the expected profit amount for each route section; A program for causing a computer to function.

14. A method for searching a route for a mobile store, comprising: The device is A first step of calculating an expected profit amount according to products and services sold at the mobile store for each route section; A second step of searching for a travel route that will maximize the total amount of expected profit based on the expected profit amount for each route section; A travel route search method comprising the steps of:

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