Information processing device, information processing method, and recording medium

Abstract

An information processing device according to one aspect of the present disclosure comprises: an acquisition means for acquiring information, regarding a delivery route to be used for a delivery that is the prediction target, indicating the status of the delivery route; a prediction means for, by inputting the information indicating the status of the delivery route to a trained model that has been trained using the relationship between information indicating the status of the delivery route in past delivery and the required delivery time when a delivery means is used, predicting the required delivery time when each of a plurality of delivery means is used; and an output means for performing output based on the prediction result.

Description

Information processing device, information processing method, and recording medium

[0001] The present disclosure relates to an information processing device, an information processing method, and a recording medium.

[0002] In the business of delivering goods, there are problems such as labor shortages and restrictions on working hours, so it is desirable to improve the time efficiency of product delivery.

[0003] Another method for calculating the required travel time is to use a technique for calculating the required travel time from the start point to the end point of a route.

[0004] For example, Patent Document 1 discloses a system that identifies an optimal route based on the unique attributes and constraints of a user's vehicle.

[0005] Special table number 2019-501385

[0006] However, there may be multiple candidate means for delivering goods. Furthermore, deliveries may be made by means other than automobiles, such as light vehicles or walking. Therefore, the system disclosed in Patent Document 1 may have difficulty providing sufficient information for a delivery entity to select a time-efficient delivery means.

[0007] One object of the present disclosure is to provide an information processing device, an information processing method, and an information processing program that can assist a delivery entity in making deliveries using delivery means that are highly time-efficient.

[0008] An information processing device in one aspect of the present disclosure includes an acquisition means for acquiring information indicating the status of a delivery route used for a delivery that is the target of prediction, a prediction means for predicting the delivery time required when using each of a plurality of delivery means by inputting the information indicating the status of the delivery route into a trained model that has learned the relationship between information indicating the status of the delivery route in past deliveries and the delivery time required when the delivery means is used, and an output means for producing an output based on the prediction result.

[0009] An information processing method in one aspect of the present disclosure obtains information indicating the status of a delivery route used for a delivery to be predicted, and inputs the information indicating the status of the delivery route into a trained model that has learned the relationship between information indicating the status of the delivery route in past deliveries and the delivery time when a delivery means is used, thereby predicting the delivery time when each of multiple delivery means is used, and outputting based on the prediction results.

[0010] In one aspect of the present disclosure, a recording medium records a program that causes a computer to execute a process of obtaining information indicating the status of a delivery route used for a delivery that is the target of prediction, inputting the information indicating the status of the delivery route into a trained model that has learned the relationship between information indicating the status of the delivery route in past deliveries and the delivery time required when a delivery means is used, thereby predicting the delivery time required when each of multiple delivery means is used, and producing an output based on the prediction result.

[0011] According to the present disclosure, it is possible to support a delivery entity in making deliveries using a delivery means that is highly time-efficient.

[0012] 1 is a first block diagram showing an example of a configuration of an information processing system according to the present disclosure. FIG. 1 is a first block diagram showing an example of a configuration of an information processing device according to the present disclosure. FIG. 2 is a first example of a screen displayed by a terminal device according to the present disclosure. FIG. 3 is a first flowchart showing an example of an operation of an information processing device according to the present disclosure. FIG. 4 is a second example of a screen displayed by a terminal device according to the present disclosure. FIG. 5 is a third example of a screen displayed by a terminal device according to the present disclosure. FIG. 6 is a sixth example of a screen displayed by a terminal device according to the present disclosure. FIG. 7 is a block diagram showing an example of a hardware configuration of an information processing device according to the present disclosure.

[0013] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In each drawing and each embodiment described in the specification, similar components are given the same reference numerals, and detailed description thereof will not be repeated.

[0014] First Embodiment The information processing system 10 can support, for example, a service that sells products over the Internet, in delivering products related to accepted orders in a highly time-efficient manner. An example of a usage example of the information processing system 10 will be described. First, a customer places an order for a product over the Internet using the customer terminal device 20. When the product order is accepted, information indicating that the order has been placed is sent from the EC system 40 to the information processing device 100. The information processing device 100 predicts the time required to deliver the product ordered by the customer and outputs information based on the prediction result. The base terminal device 30 displays information based on the prediction result output by the information processing device 100. An employee at the base checks the content displayed by the base terminal device 30 and prepares for delivery of the product based on the displayed information. After delivery, the customer receives the product. Note that the usage example of the information processing system 10 is not limited to the example shown here.

[0015] (Configuration Example) Hereinafter, a configuration example of the information processing system 10 will be described with reference to FIG. 1. FIG. 1 is a block diagram showing an example of the configuration of the information processing system 10 in the present disclosure. The information processing system 10 includes at least a customer terminal device 20, a base terminal device 30, an EC (Electronic Commerce) system 40, and an information processing device 100. The information processing device 100 is connected to the customer terminal device 20, the base terminal device 30, and the EC system 40. Note that each function of the information processing device 100 may be included in the EC system 40.

[0016] The customer terminal device 20 is a terminal device operated by a customer. The customer terminal device 20 accesses an EC site on the Internet and accepts an operation to purchase a product. Note that the customer terminal device 20 may access the EC site from an application installed on the customer terminal device 20 and accept an operation to purchase a product.

[0017] For example, the customer terminal device 20 has an interface that accepts operations from an operator. In one example, the customer terminal device 20 has at least one of a touch panel and physical buttons. Note that examples of the interface provided in the customer terminal device 20 are not limited to those exemplified here. Note that the operator of the customer terminal device 20 may be the same person as the customer, or may be a person who operates the customer terminal device 20 on behalf of the customer.

[0018] Furthermore, the customer terminal device 20 notifies the operator based on the output of the information processing device 100. For example, the customer terminal device 20 includes a means for providing visual or audio notification. In one example, the notification means provided in the customer terminal device 20 is at least one of a display, a speaker, and a printing function. Note that examples of the notification means provided in the customer terminal device 20 are not limited to those exemplified here.

[0019] For example, the customer terminal device 20 is an electronic device such as a smartphone, a tablet terminal, a PC (Personal Computer), etc. Note that examples of the customer terminal device 20 are not limited to those exemplified here.

[0020] The base terminal device 30 is a terminal device operated by an employee at the base responsible for the delivery for which the delivery time is to be predicted. For example, the base terminal device 30 notifies the operator based on the output of the information processing device 100. In one example, the base terminal device 30 is an electronic device equipped with at least one of a display, a speaker, and a printing function. Note that examples of the functions equipped in the base terminal device 30 are not limited to those exemplified here. Note that, in one example, the operator of the base terminal device 30 is an employee at the base where the base terminal device 30 is operated.

[0021] A base is a facility that holds inventory of products. In one example, a base is a facility such as a store or warehouse.

[0022] Delivery is when an ordered product is delivered to a customer. For example, delivery can mean the customer picking up the product at a base, or the product being delivered from the base to a location specified by the customer.

[0023] In the following, a delivery for which the required delivery time is to be predicted will be referred to as a delivery to be predicted.

[0024] For example, the base terminal device 30 is an electronic device such as a smartphone, a tablet terminal, a PC, a cash register, etc. Note that examples of the base terminal device 30 are not limited to those exemplified here.

[0025] The EC system 40 is a system that manages an EC site. For example, when the customer terminal device 20 receives an operation to purchase a product, the EC system 40 accepts an order for the product. The EC system 40 also transmits information related to the order to the information processing device 100. The information related to the order may include information related to the customer's address, and information on the type and quantity of the ordered product.

[0026] An example of each configuration of the information processing device 100 will be described using FIG. 2. FIG. 2 is a block diagram showing an example of the configuration of the information processing device 100 in the present disclosure. The information processing device 100 includes an acquisition unit 110, a prediction unit 120, and an output unit 130. The acquisition unit 110 acquires information indicating the status of the delivery route. The prediction unit 120 predicts the delivery time required by multiple delivery means. The output unit 130 outputs based on the results predicted by the prediction unit 120.

[0027] The required delivery time is, for example, the time required to travel between the delivery base and the location specified by the customer by the means of transportation used for delivery. Note that the required delivery time may include time other than the time required for travel.

[0028] For example, the location designated by the customer is the location designated by the customer to receive the product when the product is delivered from the base, or the location designated by the customer as the location designated by the customer to depart when the customer goes to the base to receive the product.

[0029] The acquisition unit 110 acquires information indicating the status of a delivery route for a delivery to be predicted. For example, the acquisition unit 110 acquires information indicating the status of a delivery route from a database (not shown). Here, the delivery to be predicted is, for example, a delivery in which a product ordered by the EC system 40 is delivered to a customer.

[0030] Here, the information indicating the status of the delivery route includes at least one of information indicating the extent of the status and information indicating the extent of the status. The information indicating the status of the delivery route also includes information indicating the delivery route. For example, the information indicating the delivery route is information indicating the route between the start point and the end point of the delivery.

[0031] In one example, the information indicating the status of the delivery route includes at least one of information indicating a constant status of the delivery route and information indicating a variable status of the delivery route.

[0032] Information indicating a constant state of the delivery route is information indicating a state that is unlikely to change on the delivery route.

[0033] For example, the information indicating the consistency of the delivery route is information indicating the dimensions of the road. In one example, the information indicating the consistency of the delivery route includes at least one of information indicating the width of the road and information indicating the shape of the road. Note that examples of information indicating the consistency of the delivery route are not limited to those exemplified here.

[0034] For example, the information indicating the consistency of the delivery route is information about areas and structures set based on traffic-related rules such as traffic regulation standards. In one example, the information indicating the consistency of the delivery route includes at least one of information about school zones, information indicating the location of crosswalks, information indicating the number of crosswalks, information indicating the location of railroad crossings, information indicating the number of railroad crossings, information indicating the location of traffic lights, and information indicating the time required to wait at a traffic light with a constant switching interval. Note that examples of information indicating the consistency of the delivery route are not limited to those exemplified here.

[0035] Information indicating a fluctuating situation on a delivery route is information indicating a situation that is likely to change on the delivery route.

[0036] For example, information indicating a changing status of a delivery route is information regarding people and objects on the road, other than fixtures on the road and surrounding land. In one example, information indicating a changing status of a delivery route includes at least one of information regarding people on the road and information regarding objects on the road. Here, information regarding people on the road includes at least one of information indicating the presence or absence of people on the road and information indicating the number of people on the road. Furthermore, information regarding objects on the road includes at least one of information indicating the presence or absence of objects on the road, information indicating the number of objects on the road, and information indicating the size of objects on the road. Note that examples of information indicating a changing status of a delivery route are not limited to those exemplified here.

[0037] The acquisition unit 110 may acquire, as information indicating the status of the delivery route, the result of an external device (not shown) estimating the number of people on the road based on radio waves emitted from a mobile device near the road. The acquisition unit 110 may also estimate the number of people on the road based on radio waves emitted from a mobile device near the road, and acquire the estimation result as information indicating the status of the delivery route. Note that examples of methods for acquiring information indicating the status of the delivery route are not limited to those exemplified here.

[0038] For example, the information indicating the changing status of the delivery route is information regarding events taking place on the road and the surrounding land. In one example, the information indicating the changing status of the delivery route includes at least one of information indicating the status of construction work on or near the road and information indicating the status of events taking place on or near the road. Here, the information indicating the status of construction work near the road is information indicating the status of construction work taking place within a predetermined range from the road. The predetermined range is set appropriately depending on the scale, type, and equipment used in the construction work. Here, the information indicating events taking place on or near the road is information indicating the status of festivals, rallies, and the like taking place on the road or within a predetermined range from the road. Note that examples of events are not limited to those exemplified here. The predetermined range is set appropriately depending on the scale, type, and equipment used in the event, the number of people mobilized for the event, and the like. Note that examples of information indicating the changing status of the delivery route are not limited to those exemplified here.

[0039] For example, information indicating a changing status of a delivery route is information on a status that changes appropriately depending on road conditions. In one example, information indicating a changing status of a delivery route is information indicating the time required to wait at a traffic light whose switching interval changes depending on road conditions. Note that examples of information indicating a changing status of a delivery route are not limited to those exemplified here.

[0040] The acquisition unit 110 may acquire, as information indicating the status of the delivery route, the results of an analysis of an image including information indicating the status of the delivery route by an external device (not shown). Alternatively, instead of acquiring the analysis results of an image including information indicating the status of the delivery route from an external device, the acquisition unit 110 may analyze an image including information indicating the status of the delivery route and acquire the analysis results as information indicating the status of the delivery route. In one example, the image including information indicating the status of the delivery route is a satellite image, an image collected by a drive recorder, or an image collected by a surveillance camera attached to a traffic light. Examples of images including information indicating the status of the delivery route are not limited to those exemplified here.

[0041] The prediction unit 120 inputs information indicating the status of the delivery route into a trained model to predict the delivery time required when each of multiple delivery means is used. For example, the prediction unit 120 inputs information indicating the status of the delivery route into a trained model that has learned the relationship between information indicating the status of the delivery route in past deliveries and the delivery time required when a delivery means is used, and predicts the delivery time required when that delivery means is used. The trained model is a model that has learned the relationship between information indicating the status of the delivery route in deliveries and the delivery time required when a delivery means is used, for multiple types of delivery means. Here, the information indicating the status of the delivery route is an explanatory variable, and the delivery time required is a target variable.

[0042] The prediction unit 120 may predict the required delivery time using a trained model that has learned the relationship between information on the status of the delivery route and the required delivery time for each delivery means.

[0043] Here, the delivery means refers to a means of transportation that can be used by employees of the base station in charge of delivery and customers when making the delivery that is the target of prediction. In one example, the delivery means is a truck, motorcycle, car, bicycle, walking, etc. However, examples of delivery means are not limited to those exemplified here.

[0044] For example, the means of transportation available to employees at the base responsible for delivery is identified based on the type of means of transportation deployed at the base. For example, if trucks and bicycles are deployed at the base, the trucks and bicycles will be the delivery means. Note that information indicating the types of means of transportation deployed at the base may be pre-recorded in a database (not shown).

[0045] For example, the means of transportation available to employees of a base responsible for delivery is identified based on the skills of the employees. In one example, the means of transportation available to employees of a base responsible for delivery is identified based on the type of driver's license held by the employee who is available to engage in delivery. In one example, if an employee who holds a license that allows him or her to drive a truck is attached to the base, a truck will be one of the delivery means. Note that information indicating the type of driver's license held by the employee may be recorded in advance in a database (not shown).

[0046] The means of transportation available to the customer is identified based on, for example, information previously registered by the customer. For example, if the customer has previously registered a bicycle in the EC system 40 as information indicating the means of transportation available to the customer, the bicycle will be one of the delivery means.

[0047] Furthermore, the delivery means available to the employees of the base responsible for delivery and the customer may be identified based on whether or not they are capable of transporting the product to be delivered.

[0048] For example, delivery vehicles that can be used by employees of the delivery base and customers are identified based on the dimensions of the product to be delivered. In one example, if the width and height of the product to be delivered meet predetermined standards set for each delivery vehicle, the delivery vehicle is determined to be a delivery vehicle that can transport the product. Delivery vehicles that are determined to be capable of transporting the product are identified as usable delivery vehicles.

[0049] For example, delivery vehicles that can be used by employees of the delivery base and customers are identified based on the weight of the product to be delivered. In one example, if the weight of the product to be delivered meets a predetermined standard set for each delivery vehicle, the delivery vehicle is determined to be a delivery vehicle that can transport the product. Delivery vehicles that are determined to be capable of transporting the product are identified as usable delivery vehicles.

[0050] For example, delivery means that can be used by employees of the base station in charge of delivery and customers are identified based on the equipment required to transport the goods to be delivered. In one example, if the goods to be delivered are goods that need to be frozen, a delivery means equipped with refrigeration equipment is determined to be a delivery means capable of transporting the goods. Furthermore, if the goods to be delivered are goods that need to be refrigerated, a delivery means equipped with refrigeration equipment is determined to be a delivery means capable of transporting the goods. Furthermore, if the goods to be delivered are goods that need to be kept warm, a delivery means equipped with warming equipment is determined to be a delivery means capable of transporting the goods. A delivery means determined to be capable of transporting the goods is identified as a usable delivery means. Note that examples of the attributes of the goods to be delivered and the equipment required to transport the goods are not limited to those exemplified here.

[0051] The prediction unit 120 may acquire information indicating means of transportation that can be used by employees and customers at the base in charge of delivery for the delivery that is the target of prediction. The information indicating means of transportation that can be used by employees and customers at the base in charge of delivery for the delivery that is the target of prediction may be identified by an external device (not shown). The prediction unit 120 may identify means of transportation that can be used instead of acquiring information indicating means of transportation that can be used by employees and customers at the base in charge of delivery for the delivery that is the target of prediction. Each component of the information processing device 100 other than the prediction unit 120 may acquire information indicating means of transportation that can be used for the delivery that is the target of prediction or identify the means of transportation.

[0052] In one example, the prediction unit 120 inputs information indicating the status of the delivery route for the delivery to be predicted into the trained model, thereby predicting the time required for delivery by truck and the time required for delivery by motorcycle.

[0053] For example, the status of the delivery route may change the travel speed, frequency of stops, and stop duration of the delivery vehicle. Changes in the travel speed, frequency of stops, and stop duration of the delivery vehicle are expected to increase the travel time of the delivery vehicle. In other words, the status of the delivery route is expected to affect the prediction results of the travel time of the delivery vehicle. Therefore, information indicating the status of the delivery route can be used as an explanatory variable of a trained model that predicts the travel time of the delivery vehicle.

[0054] The information processing device 100 can obtain highly accurate prediction results by predicting the required delivery time using information indicating the status of the delivery route.

[0055] For example, if the width of a road on a delivery route is narrow, a section including that road is a section where the delivery vehicle may slow down or stop. The degree of deceleration, the frequency of deceleration, and whether or not stopping is required are assumed to affect the time required for the delivery vehicle to pass through that section. Furthermore, the width of the road is assumed to affect the degree of deceleration, the frequency of deceleration, and whether or not stopping is required. In other words, the width of the road is assumed to affect the time required for the delivery vehicle to travel. Therefore, information indicating the width of the road can be used as an explanatory variable of a trained model that predicts the time required for the delivery vehicle to travel.

[0056] In one example, if the shape of a road on a delivery route includes a corner, a section including that road is a section where the delivery vehicle may slow down or stop. The degree of deceleration, the frequency of deceleration, and whether or not stopping is required are assumed to affect the time required for the delivery vehicle to pass through that section. The shape of the road is also assumed to affect the degree of deceleration, the frequency of deceleration, and whether or not stopping is required. In other words, the shape of the road is assumed to affect the time required for the delivery vehicle to travel. Therefore, information indicating the shape of the road can be used as an explanatory variable of a trained model that predicts the time required for the delivery vehicle to travel. Note that an example of the shape of a road included in a section where the delivery vehicle may slow down or stop may be a curved shape, and is not limited to the example given here.

[0057] For example, if a school zone is set on a road on a delivery route, the section including that road is a section where the delivery vehicle may slow down or stop. The degree of deceleration and the need to stop are assumed to affect the time required for the delivery vehicle to pass through that section. Furthermore, the school zone is assumed to affect the degree of deceleration and the need to stop. In other words, the school zone is assumed to affect the time required for the delivery vehicle to travel. Therefore, information about the school zone can be used as an explanatory variable of a trained model that predicts the time required for the delivery vehicle to travel.

[0058] In one example, if a road on a delivery route has a pedestrian crossing, the section including the road is a section where the delivery vehicle may slow down or stop. The degree of deceleration, the frequency of deceleration, and whether or not stopping are assumed to affect the time required for the delivery vehicle to pass through the section. Furthermore, the location and number of pedestrian crossings are assumed to affect the degree of deceleration, the frequency of deceleration, and whether or not stopping is required. In other words, the location and number of pedestrian crossings are assumed to affect the time required for the delivery vehicle to travel. Therefore, information indicating the location of pedestrian crossings and information indicating the number of pedestrian crossings can be used as explanatory variables of a trained model that predicts the time required for the delivery vehicle to travel.

[0059] In one example, if a road on a delivery route includes a railroad crossing, the section including the road is a section where the delivery vehicle may slow down or stop. The degree of deceleration, the frequency of deceleration, and whether or not a stop is required are assumed to affect the time required for the delivery vehicle to pass through the section. In addition, the location and number of railroad crossings are assumed to affect the degree of deceleration, the frequency of deceleration, and whether or not a stop is required. In other words, the location and number of railroad crossings are assumed to affect the time required for the delivery vehicle to travel. Therefore, information indicating the location of railroad crossings and information indicating the number of railroad crossings can be used as explanatory variables of a trained model that predicts the time required for the delivery vehicle to travel.

[0060] In one example, if a road on a delivery route has a traffic light, the section including that road is a section where the delivery vehicle may slow down or stop. The degree of deceleration, the frequency of deceleration, and whether or not stopping are assumed to affect the time required for the delivery vehicle to pass through that section. In addition, the location of the traffic light and the time required to wait at the light are assumed to affect the degree of deceleration, the frequency of deceleration, and whether or not stopping is required. In other words, the location of the traffic light is assumed to affect the time required for the delivery vehicle to travel. Therefore, information indicating the location of the traffic light and information indicating the time required to wait at the light can be used as explanatory variables of a trained model that predicts the time required for the delivery vehicle to travel.

[0061] In one example, if there is a person on a road along a delivery route, a section including that road is a section where the delivery vehicle may slow down or stop. The degree of deceleration, the frequency of deceleration, and whether or not stopping is required are assumed to affect the time required for the delivery vehicle to pass through that section. Furthermore, the presence or absence of people on the road and the number of people on the road are assumed to affect the degree of deceleration, the frequency of deceleration, and whether or not stopping is required. In other words, the location of traffic lights is assumed to affect the time required for the delivery vehicle to travel. Therefore, information about people on the road can be used as an explanatory variable for a trained model that predicts the time required for the delivery vehicle to travel.

[0062] In one example, if an object is present on a road on a delivery route, a section including that road is a section where the delivery vehicle may slow down or stop. The degree of deceleration, the frequency of deceleration, and whether or not a stop is required are assumed to affect the time required for the delivery vehicle to pass through that section. Furthermore, the presence or absence of objects on the road, the number of objects on the road, and the size of the objects on the road are assumed to affect the degree of deceleration, the frequency of deceleration, and whether or not a stop is required. In other words, the location of traffic lights is assumed to affect the time required for the delivery vehicle to travel. Therefore, information about objects present on the road can be used as an explanatory variable of a trained model that predicts the time required for the delivery vehicle to travel.

[0063] In one example, if an event is taking place on a road on a delivery route and on the surrounding land, the section including the road is a section where the delivery vehicle may slow down or stop. The degree of deceleration, the frequency of deceleration, and whether or not a stop is required are assumed to affect the time required for the delivery vehicle to pass through the section. Furthermore, the status of construction work on or near the road and the status of events taking place on or near the road are assumed to affect the degree of deceleration, the frequency of deceleration, and whether or not a stop is required. In other words, the status of construction work on or near the road and the status of events taking place on or near the road are assumed to affect the time required for the delivery vehicle to travel. Therefore, information about events taking place on the road on the delivery route and on the surrounding land can be used as an explanatory variable of a trained model that predicts the time required for the delivery vehicle to travel.

[0064] The prediction unit 120 may predict the required delivery time by adding the time required for preparation to deliver the items ordered by the customer to the time required for travel by the delivery vehicle predicted by the trained model. In one example, the prediction unit 120 acquires information indicating the time required for preparation to deliver the item, which is set for each item, from a database (not shown). The prediction unit 120 may predict the time required for preparation to deliver the ordered item instead of acquiring information indicating the time required for preparation to deliver the item from a database (not shown).

[0065] In one example, the time required to prepare the product for delivery is the time required for at least one of picking up the product, packing the product, and loading the product onto the delivery vehicle. Note that examples of the estimated time required to prepare the product ordered by the customer for delivery are not limited to those exemplified here.

[0066] In addition, the prediction unit 120 may train the trained model to learn the delivery means actually used in the delivery for which the delivery time required was predicted and the actual delivery time required when using that delivery means.

[0067] The output unit 130 performs output based on the prediction result of the prediction unit 120. For example, the output unit 130 outputs to a terminal device an instruction to perform a display based on the prediction result of the prediction unit 120. In one example, the output unit 130 outputs an instruction to perform a display based on the prediction result of the prediction unit 120 to at least one of the customer terminal device 20 and the base terminal device 30.

[0068] In one example, the output unit 130 outputs to at least the base terminal device 30 an instruction to display, for multiple delivery means that can be used for the delivery that is the subject of the prediction, the delivery time required if each of the delivery means is used.

[0069] FIG. 3 is a diagram showing an example of a screen displayed by the base terminal device 30 based on instructions from the output unit 130 in the present disclosure. For example, the base terminal device 30 displays the name of a delivery means in association with the required delivery time for that delivery means. In one example, FIG. 3 displays "truck" as the name of the delivery means and "40 minutes" as the required time for delivery by "truck." In another example, FIG. 3 displays "motorcycle" as the name of the delivery means and "20 minutes" as the required time for delivery by "motorcycle." Note that the displayed content of the delivery means and the required delivery time for that delivery means is not limited to those exemplified here.

[0070] The output unit 130 may transmit instructions to display different modes to the customer terminal device 20 and the base terminal device 30. Examples of display modes will be described in detail in the section on modified examples.

[0071] The output unit 130 may output to the printer an instruction to print content based on the prediction result of the prediction unit 120. In one example, the output unit 130 outputs to the printer an instruction to print content similar to the screen example in FIG.

[0072] The output unit 130 may also output an instruction to notify by voice the content based on the prediction result of the prediction unit 120. In one example, the output unit 130 outputs an instruction to the base terminal device 30 to output from a speaker a voice content notifying the name of the delivery means in association with the required delivery time.

[0073] Note that the output examples of the output unit 130 are not limited to those exemplified here, and a combination of multiple outputs may also be used.

[0074] (Operation Example) An operation example of the information processing device 100 will be described below with reference to Fig. 4. Fig. 4 is a flowchart showing an example of the operation of the information processing device 100 according to the present disclosure.

[0075] First, the acquisition unit 110 acquires information indicating the status of the delivery route (S110). Specifically, the acquisition unit 110 acquires at least one of information indicating a fixed status of the delivery route and information indicating a variable status of the delivery route from a database (not shown).

[0076] Next, the prediction unit 120 inputs the information indicating the status of the delivery route into the trained model, and predicts the delivery time when each of the multiple delivery means is used (S120). Specifically, the prediction unit 120 inputs the information indicating the status of the delivery route acquired by the acquisition unit 110 into the trained model that has learned the relationship between the information indicating the status of the delivery route and the delivery time for each delivery means in past deliveries, and predicts the delivery time for each delivery means.

[0077] Next, the output unit 130 performs output based on the prediction result of the prediction unit 120 (S130). Specifically, the output unit 130 outputs an instruction to the terminal device to perform display based on the prediction result of the prediction unit 120.

[0078] The information processing device 100 can support the delivery entity in making deliveries using delivery means that are highly time-efficient, because the information processing device 100 predicts and outputs the delivery times required when using each of a plurality of delivery means.

[0079] (Modification) A modification of the information processing device 100 will be described. This modification is an example of a case where the information processing device 100 accepts a selection of a product delivery method from the customer terminal device 20 and outputs information based on the accepted selection to the base terminal device 30. This modification may be applied to not only the first embodiment but also other embodiments and modifications to the extent that no contradiction occurs.

[0080] Here, the delivery method refers to a method in which the customer goes to the base to pick up the product, or a method in which the product is delivered from the base to a location specified by the customer. In a product delivery method in which the customer goes to the base to pick up the product, a means of transportation that the customer can use is used as the delivery means. Also, in a delivery method in which the product is delivered from the base to a location specified by the customer, a means of transportation that the base's employees can use is used as the delivery means.

[0081] The output unit 130 outputs an instruction to display a display that accepts the selection of a delivery method based on the prediction result of the prediction unit 120. For example, the output unit 130 transmits an instruction to the customer terminal device 20 to display a display that accepts the selection of a delivery method. The information processing device 100 acquires information indicating the selection result of the delivery method that has been accepted by the customer terminal device 20 from the customer terminal device 20. Note that the output unit 130 may acquire the information indicating the selection result of the delivery method, or any unit of the information processing device 100 other than the output unit 130 may acquire the information.

[0082] In one example, the output unit 130 sends an instruction to the customer terminal device 20 to display a display that accepts selection of the delivery method for the product in the delivery that is the target of prediction: a delivery method in which the customer goes to the base to pick up the product, or a delivery method in which the product is delivered from the base to a location specified by the customer.

[0083] FIG. 5 is a diagram illustrating an example of a screen displayed by the customer terminal device 20 based on an instruction from the output unit 130 in the present disclosure. In one example, FIG. 5 displays "Pick up at store" as a delivery method in which the customer picks up the product at the base. Also, "Pick up at home" is displayed as a delivery method in which the product is delivered from the base to a location designated by the customer. In one example, the operator of the customer terminal device 20 touches an area on the screen corresponding to the delivery method, causing the information processing device 100 to perform a process of accepting the selection of the delivery method. Note that examples of the display content indicating the delivery method are not limited to those exemplified here. Furthermore, the selection of the delivery method may be accepted via an interface such as a physical button on the customer terminal device 20, and the specific means are not limited to those exemplified here.

[0084] Furthermore, the output unit 130 may transmit an instruction to the customer terminal device 20 to display the required delivery time when each delivery method is used, in association with the delivery method. For example, based on an instruction from the information processing device 100, the customer terminal device 20 displays the required delivery time when a delivery means available for a certain delivery method is used as the required delivery time when that delivery method is used. For example, based on an instruction from the information processing device 100, the customer terminal device 20 displays the required delivery time in association with the delivery method, in association with the delivery method. In one example, in Figure 5, "60 minutes" is displayed as the required time for "pick up at store."

[0085] The output unit 130 also outputs an instruction to the customer terminal device 20 to display at least one of the upper and lower limits of the required delivery time for each delivery method. For example, the customer terminal device 20 may display at least one of the upper and lower limits of the required delivery time for each delivery method for the delivery to be predicted based on the instruction from the output unit 130. In one example, the customer terminal device 20 displays, as the required delivery time when a delivery method is used, the range between the required delivery time when the delivery method with the longest required delivery time is used and the required delivery time when the delivery method with the shortest required delivery time is used, among the delivery means available for use in a certain delivery method. In one example, in FIG. 5, "20 to 40 minutes" is displayed as the required delivery time for "pick up at home." Note that examples of the display content for the delivery means and the required delivery time for that delivery means are not limited to those exemplified here.

[0086] Furthermore, the output unit 130 performs output based on the delivery method selected by the customer. For example, the output unit 130 outputs to the base terminal device 30 an instruction to display a notification of the delivery method selected by the operator of the customer terminal device 20.

[0087] 6 is a diagram showing an example of a screen that the base terminal device 30 displays based on an instruction from the output unit 130 when a delivery method in which the product is delivered from the base to a location designated by the customer is selected as the delivery method in the present disclosure. For example, the base terminal device 30 displays a display indicating that the delivery method in which the product is delivered from the base to a location designated by the customer has been selected as the delivery method. In one example, in FIG. 6, the text "Pick up at home selected" is displayed. Note that examples of the display indicating the selected delivery method are not limited to those exemplified here.

[0088] Furthermore, the base terminal device 30 displays the name of the delivery means in association with the required delivery time for that delivery means. In one example, in FIG. 6, "truck" is displayed as the name of the delivery means. Furthermore, "40 minutes" is displayed as the required delivery time for delivery by "truck." In another example, in FIG. 6, "motorcycle" is displayed as the name of the delivery means. Furthermore, "20 minutes" is displayed as the required delivery time for delivery by "motorcycle." Note that examples of displays showing delivery means and the required delivery time for that delivery means are not limited to those exemplified here.

[0089] Furthermore, when outputting based on the delivery method selected by the customer, the output unit 130 may output a display of delivery means selectable by the operator of the base terminal device 30. For example, the output unit 130 outputs to the base terminal device 30 an instruction to display a message accepting the selection of a delivery means. The information processing device 100 acquires, from the base terminal device 30, information indicating the selection result of the delivery method accepted by the base terminal device 30. Note that the output unit 130 may acquire the information indicating the selection result of the delivery method, or any unit of the information processing device 100 other than the output unit 130 may acquire the information.

[0090] 6, when the operator of the base terminal device 30 touches the area on the screen corresponding to "truck," a process is performed to accept the selection of a truck as the delivery means. Also, when the operator of the base terminal device 30 touches the area on the screen corresponding to "motorcycle," a process is performed to accept the selection of a motorcycle as the delivery means.

[0091] When the output unit 130 receives the selection of a delivery means, it outputs a display of the required delivery time if that delivery means is used. For example, when the output unit 130 receives the selection of a delivery means from the base terminal device 30, it outputs an instruction to the customer terminal device 20 to display the required delivery time if that delivery means is used.

[0092] FIG. 7 is a diagram showing an example of a screen that the customer terminal device 20 displays based on an instruction from the output unit 130 when a selection of a delivery means is accepted from the base terminal device 30 in the present disclosure. Note that FIG. 7 is an example of a screen that the customer terminal device 20 displays when "motorcycle" is selected in FIG. 6. For example, the customer terminal device 20 displays a display indicating the required delivery time. In one example, in FIG. 7, "Required time: 20 minutes" is displayed as a display indicating the required delivery time when using "motorcycle," which is the delivery means selected and accepted from the base terminal device 30. Note that examples of the display content indicating the required delivery time are not limited to those exemplified here.

[0093] When the information processing device 100 receives a selection of a delivery means from the base terminal device 30 and outputs an instruction to the customer terminal device 20 to display the required delivery time when that delivery means is used, the information processing device 100 can notify the customer of a more accurate required delivery time because the information processing device 100 causes the customer terminal device 20 to display the required delivery time when using the delivery means selected by the base employee.

[0094] Note that even when the delivery method is limited to only the delivery method of delivering the product from the base to a location specified by the customer, the output unit 130 may output to the base terminal device 30 an instruction to display the name of the delivery means in association with the delivery time required for that delivery means, as exemplified in Fig. 6. Furthermore, the output unit 130 may output an output that displays the delivery means so that the operator of the base terminal device 30 can select it. Furthermore, when the output unit 130 receives a selection of a delivery means from the base terminal device 30, it may output to the customer terminal device 20 an instruction to display the delivery time required for using that delivery means, as exemplified in Fig. 7.

[0095] FIG. 8 is a diagram showing an example of a screen that the base terminal device 30 displays based on an instruction from the output unit 130 when a delivery method in which the customer comes to the base to pick up the product is selected as the delivery method in the present disclosure. For example, the base terminal device 30 displays a message indicating that a delivery method in which the customer comes to the base to pick up the product has been selected. In one example, in FIG. 8 , the message "Store pickup selected" is displayed as a message indicating that a delivery method in which the customer comes to the base to pick up the product has been selected. Note that examples of the display content indicating that a delivery method in which the customer comes to the base to pick up the product has been selected are not limited to those exemplified here.

[0096] The base terminal device 30 may also display text including instructions to the base employee. For example, the output unit 130 outputs to the base terminal device 30 an instruction to display an instruction to complete preparations for delivery of the ordered product by the time the customer comes to the base to pick up the product. In one example, in FIG. 8 , the text "Please make product A ready for delivery in 60 minutes" is displayed. Note that examples of the display content indicating an instruction to prepare for delivery of the ordered product are not limited to those exemplified here.

[0097] Here, "product A" is an example of information for identifying the ordered product. In one example, the information for identifying the product is the name of the product. Note that the information for identifying the product may also be an ID (Identifier) ​​assigned to manage the product on the system, and is not limited to the example given here.

[0098] Furthermore, "60 minutes" is an example of information indicating the time when the customer will come to the base to pick up the product in the delivery that is the target of prediction. In one example, the time when the customer will come to the base to pick up the product is the time required for the customer to travel along the delivery route using a means of transportation that is available to the customer. In another example, the time when the customer will come to pick up the product at the base may be the time when the customer wishes to pick up the product. Note that examples of the time when the customer will come to pick up the product at the base are not limited to those exemplified here.

[0099] The information processing device 100 can provide the delivery entity with information that will be helpful in determining the delivery method and delivery means. This is because, when the information processing device 100 receives a selection of a delivery method from the customer terminal device 20, it causes the customer terminal device 20 to display the required delivery time for each delivery method. Also, when the information processing device 100 receives a selection of a delivery means from the base terminal device 30, it causes the base terminal device 30 to display the required delivery time for each delivery means.

[0100] When a delivery method in which the customer goes to a base to pick up the product is selected as the delivery method, the output unit 130 may output an instruction to display items recommended to the customer to the customer terminal device 20. For example, when a delivery method in which the customer goes to a base to pick up the product is selected as the delivery method, the output unit 130 outputs an instruction to the customer terminal device 20 to display information indicating items recommended to the customer, which information is generated based on information indicating the delivery route and the surrounding conditions of the start point and end point of the delivery route.

[0101] In one example, the output unit 130 acquires information indicating items to be recommended to the customer from a database (not shown). The output unit 130 may also acquire information indicating the delivery route and the conditions around the start and end points of the delivery route, and generate information indicating items to be recommended to the customer based on the acquired information.

[0102] For example, the items recommended to the customer are items to bring depending on the situation. In one example, the information indicating the delivery route and the conditions around the start and end points of the delivery route is weather information. In one example, when rain is forecast in an area including the delivery route and at least one of the start and end points of the delivery route, information indicating a recommendation to bring an umbrella is generated as the information indicating the items recommended to the customer. In this case, the output unit 130 outputs an instruction to display a message recommending that the customer bring an umbrella. Note that examples of the information indicating the delivery route and the conditions around the start and end points of the delivery route are not limited to those exemplified here. Furthermore, the items recommended to the customer are not limited to those exemplified here.

[0103] For example, the item recommended to the customer is a means of transportation appropriate to the situation. In one example, the information indicating the delivery route and the conditions around the start and end points of the delivery route is weather information. In one example, when rainfall is forecast in an area including the delivery route and at least one of the start and end points of the delivery route, information indicating the use of an automobile as a means of transportation is generated as the information indicating the item recommended to the customer. In this case, the output unit 130 outputs an instruction to display a message recommending the use of an automobile as a means of transportation to the customer. Note that examples of the information indicating the delivery route and the conditions around the start and end points of the delivery route are not limited to those exemplified here. Furthermore, the items recommended to the customer are not limited to those exemplified here.

[0104] FIG. 9 is a diagram showing an example of a screen displayed by the customer terminal device 20 based on an instruction from the output unit 130 in the present disclosure. For example, the customer terminal device 20 displays a location where the customer will receive the product. In one example, in FIG. 9, "Musashi-Kosugi Store" is displayed as the location where the customer will receive the product. The customer terminal device 20 also displays recommendations to the customer. In FIG. 9, "We recommend bringing an umbrella" and "We recommend coming by car" are displayed as recommendations to the customer. Note that the displays showing recommendations to the customer are not limited to those exemplified here.

[0105] When a customer goes to a base to pick up a product, the information processing device 100 can provide information that will be helpful for the customer in making preparations. This is because, when a delivery method in which the customer goes to a base to pick up the product is selected as the delivery method, the information processing device 100 displays on the customer terminal device 20 items recommended to the customer based on information indicating the delivery route and the conditions around the start and end points of the delivery route.

[0106] (Second embodiment) A second embodiment will be described below. This embodiment is an example in which an information processing device specifies a delivery route for a delivery that is the target of prediction. Note that, among the terms used in the second embodiment, the terms used in the first embodiment have the same meaning as the terms used in the first embodiment, unless otherwise specified. Note that this embodiment may be applied to other embodiments or modified examples to the extent that no contradiction occurs.

[0107] (Configuration Example) The information processing system of this embodiment includes an information processing device 200 instead of the information processing device 100 in the configuration of FIG.

[0108] An example of each configuration of the information processing device 200 will be described using FIG. 10 . FIG. 10 is a block diagram showing an example configuration of the information processing device 200 in the present disclosure. The information processing device 200 includes a delivery information acquisition unit 210, a delivery route identification unit 220, an acquisition unit 230, a prediction unit 240, and an output unit 250. The delivery information acquisition unit 210 acquires information indicating the positions of the start and end points of the delivery route and information regarding available delivery means. The delivery route identification unit 220 identifies a delivery route based on the information indicating the positions of the start and end points of the delivery route. The acquisition unit 230 acquires information indicating the status of the delivery route. The prediction unit 240 predicts the delivery time required by multiple delivery means. The output unit 250 performs output based on the results predicted by the prediction unit 240.

[0109] Note that the operation of the acquisition unit 230 is similar to that of the acquisition unit 110 in the first embodiment, and therefore a detailed description thereof will be omitted here. Also, the operation of the prediction unit 240 is similar to that of the prediction unit 120 in the first embodiment, and therefore a detailed description thereof will be omitted here. Also, the operation of the output unit 250 is similar to that of the output unit 130 in the first embodiment, and therefore a detailed description thereof will be omitted here.

[0110] The delivery information acquisition unit 210 acquires information indicating the positions of the start point and the end point of the delivery route for the delivery that is the target of prediction. For example, when the EC system 40 accepts an order for a product, the delivery information acquisition unit 210 acquires information indicating the positions of the start point and the end point of the delivery route from the EC system 40.

[0111] Here, the location of the starting point of the delivery route is the location of the departure point of the delivery means for the delivery that is the target of prediction. For example, when a customer receives a product via delivery, the starting point of the delivery route is the base station responsible for delivery. Also, when a customer goes to the base station to receive the product, the starting point of the delivery route is a location designated by the customer. In one example, the starting point of the delivery route is the base station responsible for delivery or the customer's home. Note that examples of the starting point of the delivery route are not limited to those exemplified here.

[0112] Here, the location of the end point of the delivery route is the location of the product pick-up location. The product pick-up location is the location designated by the customer where the product is to be delivered. For example, if the customer receives the product via delivery, the end point of the delivery route is the location designated by the customer. Also, if the customer goes to a base to pick up the product, the end point of the delivery route is the base responsible for delivery. In one example, the end point of the delivery route is the customer's home or the base responsible for delivery. Note that examples of the end point of the delivery route are not limited to those exemplified here.

[0113] Note that information indicating the location of a place specified by a customer, which is used as information indicating the location of the start point or end point of a delivery route, is registered in advance in the EC system 40. In one example, information indicating the customer's address is input in advance from the customer terminal device 20 to the EC system 40 as information indicating the location of a place specified by a customer. Note that information indicating the location of a place specified by a customer may also be input from the customer terminal device 20 to the EC system 40 when accepting an order for a product.

[0114] The delivery information acquisition unit 210 acquires the result of determining the base that will be the start point or end point of the delivery route as information indicating the location of the start point or end point of the delivery route. In one example, the base that is closest to the location specified by the customer is determined as the base that will be the start point or end point of the delivery route. The delivery information acquisition unit 210 may also determine the base that will be the start point or end point of the delivery route.

[0115] In one example, the information indicating the locations of the start and end points of the delivery route includes at least one of information indicating the addresses of the start and end points of the delivery route and information indicating the latitude and longitude of the start and end points of the delivery route. Note that examples of the information indicating the locations of the start and end points of the delivery route are not limited to those exemplified here.

[0116] Furthermore, the delivery information acquisition unit 210 acquires information indicating the type of delivery means. For example, the delivery information acquisition unit 210 acquires information indicating delivery means that can be used for the delivery that is the target of prediction. In one example, the delivery information acquisition unit 210 acquires information indicating delivery means that can be used by customers and employees at base locations for the delivery that is the target of prediction from the EC system 40.

[0117] The delivery information acquisition unit 210 may acquire information indicating delivery means available to customers and employees at base locations for deliveries that are the subject of prediction from a database (not shown). The delivery information acquisition unit 210 may also acquire information indicating delivery means available to customers and information indicating delivery means available to employees at base locations from different sources.

[0118] The delivery route identification unit 220 identifies a delivery route based on information indicating the locations of the start point and end point of the delivery route. For example, the delivery route identification unit 220 identifies a route that travels between the start point and end point of the delivery route. In one example, the delivery route identification unit 220 identifies a delivery route that has the shortest travel time using a known route search technology.

[0119] Note that the delivery route may differ for each delivery means. This is because there may be delivery means that cannot travel along a route specified for a certain delivery means due to factors such as the width of the road, the height of structures on the road, and traffic regulations. Therefore, the delivery route determination unit 220 may determine a delivery route for each delivery means. For example, if a truck or a motorcycle can be used as the delivery means for the delivery to be predicted, the delivery route determination unit 220 determines the shortest delivery route when a truck is used and the shortest delivery route when a motorcycle is used. Note that examples of delivery routes determined by the delivery route determination unit 220 are not limited to the shortest route.

[0120] (Operation Example) An operation example of the information processing device 200 will be described below with reference to Fig. 11. Fig. 11 is a flowchart showing an example of the operation of the information processing device 200 according to the present disclosure.

[0121] First, the delivery information acquisition unit 210 acquires information indicating the positions of the start point and the end point of the delivery route for the delivery to be predicted (S210). Specifically, when the EC system 40 accepts an order for a product, the delivery information acquisition unit 210 acquires information indicating the positions of the start point and the end point of the delivery route from the EC system 40.

[0122] The delivery information acquisition unit 210 also acquires information about the delivery means to be used in the delivery that is the target of prediction (S210). Specifically, the delivery information acquisition unit 210 acquires information indicating the delivery means that can be used by the customer and employees of the base station in the delivery that is the target of prediction from the EC system 40.

[0123] Next, the delivery route specification unit 220 specifies a delivery route based on the information indicating the positions of the start point and end point of the delivery route (S220). Specifically, the delivery route specification unit 220 specifies a passable route between the start point and end point of the delivery route.

[0124] Next, the acquisition unit 230 acquires information indicating the status of the delivery route identified by the delivery route identification unit 220 (S230). Specifically, the acquisition unit 230 acquires at least one of information indicating the status of a fixed delivery route and information indicating the status of a variable delivery route from a database (not shown).

[0125] Next, the prediction unit 240 inputs the information indicating the status of the delivery route into the trained model, and predicts the required delivery time when each of the multiple delivery means is used (S240). Specifically, the prediction unit 240 inputs the information indicating the status of the delivery route acquired by the acquisition unit 230 into the trained model that has learned the relationship between the information indicating the status of the delivery route and the delivery time required for each delivery means in past deliveries, and predicts the required delivery time for each delivery means.

[0126] Next, the output unit 250 performs output based on the result predicted by the prediction unit 240 (S250). Specifically, the output unit 250 outputs to the terminal device an instruction to perform display based on the prediction result of the prediction unit 240. For example, the terminal device is at least one of the customer terminal device 20 and the base terminal device 30.

[0127] The information processing device 200 can support the delivery entity in making deliveries using delivery means that are highly time-efficient, because the information processing device 100 predicts and outputs the delivery times required when using each of a plurality of delivery means.

[0128] (Third embodiment)

[0129] A third embodiment will be described below. This embodiment is an example in which an information processing device determines the content of an incentive to be awarded depending on the selection of a delivery method. Note that, among the terms used in the third embodiment, the terms used in the first and second embodiments have the same meanings as those used in the first and second embodiments, unless otherwise specified. Note that this embodiment may be applied to other embodiments or modified examples to the extent that no contradiction occurs.

[0130] (Configuration Example) The information processing system of this embodiment includes an information processing device 300 instead of the information processing device 100 in the configuration of FIG.

[0131] An example of each component of the information processing device 300 will be described using FIG. 12 . FIG. 12 is a block diagram showing an example of the component of the information processing device 300 in the present disclosure. The information processing device 300 includes an acquisition unit 310, a prediction unit 320, an incentive determination unit 330, and an output unit 340. The acquisition unit 310 acquires information indicating the status of the delivery route. The prediction unit 320 predicts the delivery time required for multiple delivery means. The incentive determination unit 330 determines an incentive to be given to the customer depending on the selection of the delivery method and delivery means. The output unit 340 performs output based on the result of the prediction by the prediction unit 320 and information indicating the incentive determined by the incentive determination unit 330.

[0132] The operation of the acquisition unit 310 is similar to that of the acquisition unit 110 in the first embodiment, and therefore a detailed description thereof will be omitted here. The operation of the prediction unit 320 is similar to that of the prediction unit 120 in the first embodiment, and therefore a detailed description thereof will be omitted here.

[0133] The incentive determination unit 330 determines an incentive to be given to a customer in the delivery that is the prediction target. For example, the incentive determination unit 330 determines an incentive to be given to a customer in accordance with the selection of a delivery method or delivery means to be used in the delivery that is the prediction target. In one example, the incentive determination unit 330 determines whether or not to give an incentive to a customer in accordance with the selection of a delivery method or delivery means, and the content of the incentive.

[0134] For example, the incentive determination unit 330 determines the incentive to be given to the customer in accordance with the selection of the delivery means based on the content previously set by an employee at the base. In one example, the incentive determination unit 330 determines the incentive based on information indicating the delivery method or delivery means for which the incentive will be given to the customer when selected and information indicating the content of the incentive depending on the selection of the delivery method or delivery means. Note that, in one example, the information indicating the delivery method or delivery means for which the incentive will be given to the customer when selected and the information indicating the content of the incentive depending on the selection of the delivery method or delivery means are input by the operator of the base terminal device 30.

[0135] The incentive determination unit 330 may determine the incentive to be given to the customer based on information indicating incentives that are preset for each delivery method and delivery means, which is obtained from the EC system 40. In one example, the incentive determination unit 330 obtains information from the EC system 40 that is preset for each delivery method or delivery means and indicates incentives to be given to the customer in accordance with the selection of the delivery method or delivery means. The incentive determination unit 330 determines the incentive indicated by the obtained information as the incentive to be given to the customer in the delivery that is the target of prediction.

[0136] The incentive determination unit 330 may determine the content of the incentive based on the result of the prediction by the prediction unit 320. For example, the prediction unit 320 determines that an incentive will be given to the customer when the delivery method or delivery means that has the shortest predicted delivery time is selected.

[0137] The output unit 340 performs output based on the prediction result of the prediction unit 320 and the incentive determined by the incentive determination unit 330. For example, the output unit 340 transmits to the customer terminal device 20 an instruction to display a message accepting the selection of a delivery method in association with information indicating the content of the incentive to be given to the customer if the delivery method is selected. The information processing device 300 acquires information indicating the selection of the delivery method received from the customer terminal device 20. Note that the output unit 340 may acquire the information indicating the content of the selected delivery method, or the information may be acquired by a device other than the output unit 340.

[0138] In one example, the output unit 340 sends an instruction to the customer terminal device 20 to display a display accepting selection of the delivery method for the product in the delivery that is the target of prediction, either a delivery method in which the customer goes to a base to pick up the product, or a delivery method in which the product is delivered from the base to a location specified by the customer, in association with information indicating the content of the incentive to be given to the customer if each delivery method is selected.

[0139] FIG. 13 is a diagram showing an example of a screen displayed by the customer terminal device 20 based on an instruction from the output unit 340 in the present disclosure. FIG. 13 shows an example of a case in which the customer terminal device 20 displays, in addition to the display in FIG. 5 of the first embodiment, a display indicating the content of the incentive to be given to the customer when each delivery method is used. In FIG. 13, "Free Sweets B" is displayed as the content of the incentive to be given to the customer when the "Pick up at store" delivery method is selected. Note that the content of the incentive to be given to the customer when the delivery method is selected may be a discount on the product price or the issuance of a coupon, and is not limited to the examples shown here.

[0140] Furthermore, the output unit 340 performs output based on the delivery method selected by the customer. For example, the output unit 340 outputs to the base terminal device 30 an instruction to display a notification of the delivery method selected by the operator of the customer terminal device 20.

[0141] In one example, when a delivery method in which the product is delivered from the base to a location designated by the customer is selected as the delivery method, the output unit 340 outputs an instruction to the base terminal device 30 to display content similar to that shown in Figure 6. Furthermore, the output unit 340 may output an instruction to the base terminal device 30 to display content similar to that shown in Figures 7 and 8. Note that the operation of the output unit 340 in this case is similar to that of the output unit 130 in the first embodiment, and therefore detailed description thereof will be omitted.

[0142] 14 is a diagram showing an example of a screen that the base terminal device 30 displays based on an instruction from the output unit 340 when a delivery method for delivering a product from a base to a location designated by a customer is selected as the delivery method in the present disclosure. For example, when a delivery method for delivering a product to a location designated by a customer is selected, the base terminal device 30 may output to the base terminal device 30 an instruction to display an instruction to complete preparations to provide the customer with a service corresponding to the incentive content, in addition to the content similar to that shown in FIG.

[0143] In one example, in addition to the display content of FIG. 8, a character string "Please make snack B available for delivery within 60 minutes" is displayed in FIG. 14. Here, "sweets B" is displayed as the content of the incentive to be given to the customer when a delivery method of delivering the product from the base to a location designated by the customer is selected in FIG. 14. Note that examples of the display content instructing the customer to complete preparations to provide the service corresponding to the content of the incentive are not limited to those exemplified here.

[0144] The output unit 340 may also transmit to the customer terminal device 20 an instruction to display information indicating the content of the incentive corresponding to the delivery means to be used in the delivery that is the target of prediction. For example, the output unit 340 outputs to the customer terminal device 20 an instruction to display a display accepting the selection of a delivery method in association with a display indicating the content of the incentive corresponding to the delivery means that may be used if the delivery method is selected.

[0145] 15 is a diagram showing an example of a screen displayed by the customer terminal device 20 based on an instruction from the output unit 340 in the present disclosure. Fig. 15 shows an example of a case where the delivery method in which the customer goes to a base to pick up the product allows the delivery means to be an automobile or on foot, and the delivery method in which the product is delivered from the base to a location designated by the customer allows two types of delivery means to be used. For example, the customer terminal device 20 displays a display for accepting the selection of a delivery method as many times as the number of types of delivery means available for the delivery method.

[0146] In one example, in FIG. 15 , "Pick up at store" is displayed as a character string indicating a delivery method in which the customer goes to a base to pick up the product. The "Pick up at store" display is displayed twice, the same number as the number of available delivery means for the delivery method in which the customer goes to a base to pick up the product. In one example, in FIG. 15 , "Pick up at store," which is a display corresponding to the available delivery means "car," is displayed in association with the delivery means name "car" and the required delivery time for "car" (20 minutes). In another example, in FIG. 15 , "Pick up at store," which is a display corresponding to the available delivery means "walking," is displayed in association with the incentive content for the delivery means "walking," "Receive candy B as a gift." Note that examples of displays indicating the delivery method, delivery means name, required delivery time, and incentive content are not limited to those exemplified here. Furthermore, the number of displays indicating delivery methods is not limited to the number exemplified here.

[0147] In one example, in FIG. 15 , "Pick up at home" is displayed as a character string indicating the delivery method for delivering the product from the base to the location specified by the customer. Furthermore, two "Pick up at home" indications are displayed, the same number as the number of delivery means available for the delivery method for delivering the product from the base to the location specified by the customer. In one example, in FIG. 15 , indications corresponding to a delivery means with a delivery time required of "20 minutes" and a delivery means with a delivery time required of "40 minutes" are displayed. In one example, in FIG. 15 , an indication corresponding to a delivery means with a delivery time required of "40 minutes" is displayed in association with the incentive content corresponding to that delivery means, "5% discount on product price." Note that examples of indications indicating the delivery method, delivery time required, and incentive content are not limited to those exemplified here. Furthermore, the number of indications indicating delivery methods is not limited to the number exemplified here.

[0148] (Operation Example) An operation example of the information processing device 300 will be described below with reference to Fig. 16. Fig. 16 is a flowchart showing an example of the operation of the information processing device 300 according to the present disclosure.

[0149] First, the acquisition unit 310 acquires information indicating the status of the delivery route (S310). Specifically, the acquisition unit 310 acquires at least one of information indicating the status of a fixed delivery route and information indicating the status of a variable delivery route from a database (not shown).

[0150] Next, the prediction unit 320 inputs the information indicating the status of the delivery route into the trained model, and predicts the delivery time when each of the multiple delivery means is used (S320). Specifically, the prediction unit 320 inputs the information indicating the status of the delivery route acquired by the acquisition unit 310 into the trained model that has learned the relationship between the information indicating the status of the delivery route and the delivery time for each delivery means in past deliveries, and predicts the delivery time for each delivery means.

[0151] Next, the incentive determination unit 330 determines an incentive to be given to the customer in the delivery that is the prediction target (S330). Specifically, the incentive determination unit 330 determines an incentive to be given to the customer when each of the delivery methods and delivery means that may be used in the delivery that is the prediction target is used.

[0152] The output unit 340 performs output based on the result predicted by the prediction unit 320 and the incentive determined by the incentive determination unit 330 (S340). Specifically, the output unit 340 transmits to the customer terminal device 20 an instruction to display a display accepting the selection of a delivery method in association with information indicating the content of the incentive to be given to the customer when the delivery method is selected.

[0153] The information processing device 300 can assist the delivery entity in making deliveries using delivery means that are highly time-efficient. This is because the information processing device 300 predicts and outputs the delivery time required when using each of multiple delivery means. Furthermore, the information processing device 300 can increase the likelihood that the delivery company can use a delivery method and delivery means that are convenient for them. This is because the information processing device 300 can determine incentives for each delivery method and delivery means that may be used in the delivery that is the subject of the prediction, and can guide the customer's selection.

[0154] (Hardware Configuration) The procedures described in each of the above embodiments can be realized by a program that causes a computer functioning as the information processing devices 100, 200, and 300 to realize the functions of the information processing devices 100, 200, and 300. Fig. 17 is a block diagram showing an example of the hardware configuration of a computer 400 that realizes the information processing devices 100, 200, and 300 according to the present disclosure. The computer 400 includes a processor 410, a memory 420, an auxiliary storage device 430, a communication interface 440, and an input / output interface 450. The memory 420 includes a RAM (Random Access Memory) 421 and a ROM (Read Only Memory) 422.

[0155] In one example, the processor 410 executes the program 500 using the RAM 421 .

[0156] In one example, the processor 410 is at least one of a central processing unit (CPU) and a graphics processing unit (GPU). Note that the processor 410 may be any other processor and is not limited to the examples given here.

[0157] Here, the program 500 is a program that causes a computer to function as each unit of the device shown in each of the above embodiments.

[0158] The program 500 may be recorded in the ROM 422 or may be stored in the auxiliary storage device 430 .

[0159] The communication interface 440 communicates with external devices.

[0160] The input / output interface 450 is connected to a device that receives information input to the information processing device and a device that outputs information from the information processing device.

[0161] The functions of the respective units of the devices described in the above embodiments are realized by the processor 410 executing the program 500. The processor 410 may also realize the functions of the respective units of the devices described in the above embodiments by reading out into RAM a program or data stored on a recording medium attached to a drive device or the like.

[0162] The configurations described as a single device in the above embodiments may be distributed across multiple devices. For example, the information processing devices 100, 200, and 300 may be realized by multiple computer devices using cloud computing technology or the like.

[0163] The present disclosure has been described above using the above-described embodiments and modifications as exemplary examples. However, the present disclosure is not limited to these embodiments and modifications. The present disclosure may include embodiments to which various modifications or applications that would be apparent to a person skilled in the art are applied within the scope of the present disclosure. Furthermore, the present disclosure may include embodiments in which the matters described herein are appropriately combined or substituted as necessary. For example, matters described using a specific embodiment may also be applied to other embodiments to the extent that no contradiction occurs.

[0164] (Supplementary Note) Part or all of the present disclosure may be described as in the following supplementary note. However, the present disclosure is not necessarily limited to the aspects of this supplementary note. (Supplementary Note 1) An information processing device comprising: an acquisition means for acquiring information indicating the status of a delivery route used for a delivery to be predicted; a prediction means for predicting the delivery time required for each of a plurality of delivery means by inputting the information indicating the status of the delivery route into a trained model that has learned the relationship between information indicating the status of the delivery route in past deliveries and the delivery time required for each delivery means; and an output means for performing an output based on the prediction result. (Supplementary Note 2) The information processing device according to Supplementary Note 1 further comprises a delivery route identification means for identifying a delivery route based on information indicating the positions of a start point and an end point of the delivery route for the delivery and information indicating the type of delivery means. (Supplementary Note 3) The information processing device according to Supplementary Note 2, wherein the delivery route identification means identifies the delivery route based on information indicating the positions of a base responsible for the delivery and a location specified by the customer, and information indicating means of transportation available to employees of the base and the customer. (Supplementary Note 4) The information processing device of any one of Supplements 1 to 3, wherein the prediction means predicts the required delivery time by adding the time required to prepare for delivery of the products to be delivered in the delivery to be predicted to the prediction result of the trained model. (Supplementary Note 5) The information processing device of any one of claims 1 to 4, wherein the trained model is a trained model that has learned the relationship between information indicating a constant delivery route in past deliveries and the required delivery time. (Supplementary Note 6) The information processing device of any one of Supplements 1 to 5, wherein the trained model is a trained model that has learned the relationship between information indicating a variable delivery route in past deliveries and the required delivery time. (Supplementary Note 7) The information processing device of any one of Supplements 1 to 6, wherein the output means outputs to the terminal device an instruction to display the required delivery times when each of a plurality of delivery means available for the delivery is used. (Supplementary Note 8) The information processing device of any one of Supplements 1 to 7, wherein the output means outputs to the terminal device a display that accepts selection of a delivery means to be used in the delivery.(Supplementary Note 9) The information processing device according to any one of Supplements 1 to 6, wherein the output means outputs to the customer's terminal device an instruction to display a display accepting a selection of whether to use a delivery method in which the customer picks up the product or a delivery method in which the product is delivered to a location designated by the customer. (Supplementary Note 10) The information processing device according to Supplementary Note 9, wherein, when a delivery method in which the product is delivered to a location designated by the customer is selected, the output means outputs to the terminal device of the base responsible for delivery an instruction to display a display accepting a selection of a delivery means to be used for the delivery. (Supplementary Note 11) The information processing device according to Supplementary Note 10, wherein, when a delivery means is selected, the output means outputs to the customer's terminal device an instruction to display a display indicating a delivery time if the selected delivery means is used. (Supplementary Note 12) The information processing device according to any one of claims 9 to 11, further comprising incentive determination means for determining an incentive to be given to the customer in accordance with the selection of the delivery method. (Supplementary Note 13) The information processing device according to Supplementary Note 12, wherein the incentive determination means determines an incentive to be given to the customer in accordance with the selection of the delivery means. (Supplementary Note 14) The information processing device according to Supplementary Note 13, wherein the incentive determination means determines an incentive based on the delivery time predicted by the prediction means. (Supplementary Note 15) The information processing device according to Supplementary Note 12, wherein the output means outputs to the customer's terminal device an instruction to associate a display accepting the selection of a delivery method with a display indicating the content of an incentive to be given to the customer if each delivery method is selected. (Supplementary Note 16) The information processing device according to any of Supplements 9 to 15, wherein the output means outputs to the customer's terminal device an instruction to display at least one of a lower limit and an upper limit of the delivery time for each delivery method. (Supplementary Note 17) The information processing device according to any of Supplements 9 to 16, wherein the output means, when a delivery method in which the customer goes to pick up the product is selected, outputs to the customer's terminal device an instruction to display recommendations to the customer based on information indicating the delivery route, and the surrounding conditions of the start point and end point of the delivery route.(Supplementary Note 18) An information processing method which obtains information indicating the status of a delivery route for a delivery that is the target of prediction, inputs the information indicating the status of the delivery route into a trained model which has learned the relationship between information indicating the status of the delivery route in past deliveries and the delivery time required for each delivery means, thereby predicting the time required for delivery when each of a plurality of delivery means is used, and produces an output based on the prediction result. (Supplementary Note 19) A recording medium having recorded thereon a program which causes a computer to execute the processes of obtaining information indicating the status of the delivery route for a delivery that is the target of prediction, inputs the information indicating the status of the delivery route into a trained model which has learned the relationship between information indicating the status of the delivery route in past deliveries and the delivery time required for each delivery means, thereby predicting the time required for delivery when each of a plurality of delivery means is used, and producing an output based on the prediction result.

[0165] Furthermore, some or all of the configurations described in Supplementary Notes 2 to 16, which are dependent on Supplementary Note 1, may also be dependent on Supplementary Notes 17 and 18 in the same dependent relationship as Supplementary Notes 2 to 16. Furthermore, not limited to Supplementary Notes 1, 17, and 18, some or all of the configurations described as Supplements may be made dependent on various hardware, software, various recording means for recording software, or systems, within the scope of each of the above-mentioned embodiments.

[0166] REFERENCE SIGNS LIST 10 Information processing system 20 Customer terminal device 30 Base terminal device 40 EC system 100 Information processing device 110 Acquisition unit 120 Prediction unit 130 Output unit 200 Information processing device 210 Delivery information acquisition unit 220 Delivery route identification unit 230 Acquisition unit 240 Prediction unit 250 Output unit 300 Information processing device 310 Acquisition unit 320 Prediction unit 330 Incentive determination unit 340 Output unit 400 Computer 410 Processor 420 Memory 421 RAM 422 ROM 430 Auxiliary storage device 440 Communication interface 450 Input / output interface 500 Program

Claims

1. An information processing device comprising: an acquisition means for acquiring information indicating the status of a delivery route used for a delivery that is the subject of prediction; a prediction means for predicting the delivery time required when using each of a plurality of delivery means by inputting the information indicating the status of the delivery route into a trained model that has learned the relationship between information indicating the status of the delivery route in past deliveries and the delivery time required when the delivery means is used; and an output means for producing an output based on the prediction result.

2. The information processing device according to claim 1, further comprising a delivery route specification means for specifying a delivery route based on information indicating the positions of the start and end points of the delivery route and information indicating the type of delivery means.

3. An information processing device as described in claim 2, wherein the delivery route determination means determines the delivery route based on information indicating the locations of the base responsible for the delivery and the location specified by the customer, and information indicating the means of transportation available to employees of the base and the customer.

4. An information processing device according to any one of claims 1 to 3, wherein the prediction means predicts the required delivery time by adding the time required to prepare for delivery of the goods to be delivered in the delivery to be predicted to the prediction result of the trained model.

5. An information processing device according to any one of claims 1 to 4, wherein the trained model is a trained model that has learned the relationship between information indicating the state of a fixed delivery route in past deliveries and the required delivery time.

6. An information processing device according to any one of claims 1 to 5, wherein the trained model is a trained model that has learned the relationship between information indicating the fluctuating conditions of delivery routes in past deliveries and the required delivery time.

7. An information processing device according to any one of claims 1 to 6, wherein the output means outputs to a terminal device an instruction to display the required delivery time when using each of a plurality of delivery means that are available for the delivery.

8. An information processing device according to any one of claims 1 to 7, wherein said output means outputs to a terminal device a display that accepts selection of a delivery means to be used for said delivery.

9. An information processing device according to any one of claims 1 to 6, wherein the output means outputs to the customer's terminal device an instruction to display a message accepting the selection of which delivery method to use for the delivery: a delivery method in which the customer picks up the product in person, or a delivery method in which the product is delivered to a location designated by the customer.

10. An information processing device as described in claim 9, wherein the output means outputs, when a delivery method for delivering the product to a location designated by the customer is selected, instructions to display a message accepting the selection of the delivery means to be used for the delivery to a terminal device at the base responsible for the delivery.

11. An information processing device according to claim 10, wherein said output means, when a delivery means is selected, outputs to said customer's terminal device an instruction to display the required delivery time if the selected delivery means is used.

12. An information processing device according to any one of claims 9 to 11, further comprising incentive determination means for determining an incentive to be given to a customer in accordance with the selection of a delivery method.

13. The information processing device according to claim 12, wherein said incentive determination means determines an incentive to be given to a customer depending on the delivery means selected.

14. The information processing device according to claim 13, wherein said incentive determination means determines an incentive based on the delivery time predicted by said prediction means.

15. An information processing device according to claim 12, wherein said output means outputs to said customer's terminal device an instruction to display a message accepting the selection of a delivery method in association with a message indicating the content of the incentive to be given to the customer if each delivery method is selected.

16. An information processing device according to any one of claims 9 to 15, wherein said output means outputs to said customer's terminal device an instruction to display at least one of the upper and lower limits of the required delivery time for each delivery method.

17. An information processing device according to any one of claims 9 to 16, wherein the output means, when a delivery method in which the customer goes to pick up the product is selected, outputs to the customer's terminal device instructions to display recommendations to the customer based on information indicating the delivery route, the starting point of the delivery route, and the conditions around the end point of the delivery route.

18. An information processing method that obtains information indicating the status of a delivery route for a delivery that is the target of prediction, inputs the information indicating the status of the delivery route into a trained model that has learned the relationship between information indicating the status of delivery routes for past deliveries and the delivery time required for each delivery means, thereby predicting the delivery time required when using each of multiple delivery means, and produces output based on the prediction results.

19. A recording medium having recorded thereon a program that causes a computer to execute the following process: obtain information indicating the status of the delivery route for the delivery to be predicted; input the information indicating the status of the delivery route into a trained model that has learned the relationship between information indicating the status of the delivery route for past deliveries and the delivery time required for each delivery means, thereby predicting the delivery time required when using each of multiple delivery means; and outputting based on the prediction results.

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