JP7499683B2 - Information processing device - Google Patents

Description

The present invention relates to a technology for determining the usage fees for mobility services.

Sharing mobility services, such as car sharing, bicycle sharing, and kick scooter sharing, are rapidly becoming popular. In this sharing mobility service, when a user requests a facility (such as an available shared car) and the necessary facility is in short supply, a commonly used method is to present nearby available facilities as an alternative. However, such a method does not necessarily meet the user's needs, and may force the user to travel to a facility that is far away.

For this reason, various efforts are being made to optimize the matching of supply and demand for this type of transportation service. For example, Patent Document 1 discloses a system in which, when a car station corresponding to a member's destination is highly congested, an alternative car station that is a closer travel distance is presented to the member, and a discount is applied to members who use the presented alternative car station according to the increased travel time compared to using the car station at the destination.

JP 2012-215921 A

However, the content of the benefits to be given to users, such as discounts on usage fees, must be decided appropriately by the business operator or the user.

The present invention aims to provide a mechanism for appropriately determining the benefits to be given to users in mobility services.

To solve the above problem, the present invention provides an information processing device comprising: a first calculation unit that calculates an expected amount of revenue that a provider providing a mobility service can obtain from a user when the user uses the facilities of the provider for a certain period of time; a second calculation unit that calculates an expected amount of revenue that can be probabilistically expected by the provider providing the facilities for the mobility service during the certain period of time; a generation unit that uses the calculated expected amount of revenue and the difference between the expected amount of revenue to generate presentation information including information regarding benefits that the user can obtain when using the facilities; and a transmission unit that transmits the generated presentation information to the communication terminal of the user.

The present invention makes it possible to appropriately determine the benefits to be given to users in mobility services.

FIG. 1 is a block diagram showing an example of the overall configuration of a sharing mobility system 1 according to one embodiment of the present invention. FIG. 2 is a block diagram showing an example of a hardware configuration of a user terminal 10 according to the embodiment. FIG. 2 is a block diagram showing an example of a hardware configuration of a server device 30 according to the embodiment. FIG. 2 is a block diagram showing an example of a functional configuration of a server device 30 according to the embodiment. 10 is a diagram illustrating an example of facility information stored in a storage unit 35 of the server device 30 according to the embodiment. FIG. 10 is a diagram illustrating an example of user information stored in a storage unit 35 of the server device 30 according to the embodiment. FIG. 10 is a flowchart illustrating an operation of the server device 30 according to the embodiment. FIG. 11 is a diagram illustrating a plurality of route candidates calculated by the server device 30 according to the embodiment. 10 is a diagram illustrating an example of presented information presented to a user on the user terminal 10 according to the embodiment. FIG.

[composition]
FIG. 1 is a diagram showing an example of a sharing mobility system 1 according to the present embodiment. The sharing mobility system 1 includes a plurality of user terminals 10 each functioning as a communication terminal used by a user who uses a vehicle (here, an automobile), a plurality of carport devices 20 installed in a carport where a vehicle that can be used is parked, and a server device 30 managed by a business that provides mobility services to users through the sharing mobility system 1. The server device 30 functions as an information processing device according to the present invention. The vehicle and the carport are facilities of a business that provides mobility services to users. The network 2 connects the user terminals 10, the carport device 20, and the server device 30 to each other so that they can communicate with each other. The network 2 is, for example, a local area network (LAN) or a wide area network (WAN), or a combination thereof, and includes a wired section or a wireless section. The network 2 is preferably, for example, a network that complies with a fifth-generation mobile communication system, but is not necessarily limited to this.

In the sharing mobility system 1, a user operates his/her user terminal 10 to request the use of a vehicle from an arbitrary departure point to an arbitrary destination. This request is sent from the user terminal 10 to the server device 30 via the network 2. The server device 30 identifies a vehicle that is available in the vicinity of the departure point, and calculates a route from the carport in which the vehicle is parked (referred to as the departure carport) to an available carport in which the vehicle can be parked in the vicinity of the destination (referred to as the destination carport). The server device 30 generates and transmits to the user terminal 10 information (referred to as presented information) regarding the vehicle that the user should board, the route from the departure carport to the destination carport, and the usage fee, etc. The user can learn details of the transportation service to be used by viewing the presented information output on the user terminal 10.

This sharing mobility system 1 uses so-called dynamic pricing, in which the vehicle usage fee for users varies. One of the features of this embodiment is that it determines an appropriate usage fee depending on the situation of the operator providing the mobility service and the situation of the user using that mobility service.

Figure 2 is a diagram showing an example of the hardware configuration of a user terminal 10. The user terminal 10 is, for example, a computer such as a smartphone, a mobile phone, a tablet, a wearable terminal, or a personal computer. The user terminal 10 is physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a positioning device 1007, and a bus connecting these. In the following description, the word "device" can be interpreted as a circuit, a device, a unit, etc. The hardware configuration of the user terminal 10 may be configured to include one or more of the devices shown in the figure, or may be configured to exclude some of the devices.

Each function of the user terminal 10 is realized by loading a specific software (program) onto hardware such as the processor 1001 and memory 1002, causing the processor 1001 to perform calculations, control communications via the communication device 1004, and control at least one of the reading and writing of data in the memory 1002 and storage 1003.

The processor 1001, for example, operates an operating system to control the entire computer. The processor 1001 may be configured with a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, registers, etc. Also, for example, a baseband signal processing unit, a call processing unit, etc. may be realized by the processor 1001.

The processor 1001 reads out programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and executes various processes according to these. The programs used are those that cause a computer to execute at least some of the operations described below. The functional blocks of the user terminal 10 may be realized by a control program stored in the memory 1002 and running on the processor 1001. The various processes may be executed by one processor 1001, or may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The programs may be transmitted from the network 2 to the user terminal 10 via a telecommunications line.

The memory 1002 is a computer-readable recording medium, and may be composed of at least one of, for example, a ROM (Read Only Memory), an EPROM (Erasable Programmable ROM), an EEPROM (Electrically Erasable Programmable ROM), a RAM (Random Access Memory), etc. The memory 1002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 1002 can store executable programs (program codes), software modules, etc. for implementing the method according to this embodiment.

Storage 1003 is a computer-readable recording medium, and may be composed of at least one of, for example, an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc. Storage 1003 may also be called an auxiliary storage device. Storage 1003 stores a performance evaluation program and a group of sheet music data described below.

The communication device 1004 is hardware (transmitting/receiving device) for communicating between computers via at least one of a wired network and a wireless network, and is also called, for example, a network device, a network controller, a network card, a communication module, etc. The communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc., to realize at least one of, for example, Frequency Division Duplex (FDD) and Time Division Duplex (TDD). For example, a transmitting/receiving antenna, an amplifier unit, a transmitting/receiving unit, a transmission path interface, etc. may be realized by the communication device 1004. The transmitting/receiving unit may be implemented as a transmitting unit or a receiving unit that is physically or logically separated.

The input device 1005 is an input device (e.g., a key, a microphone, a switch, a button, a sensor, etc.) that accepts input from the outside. The output device 1006 is an output device (e.g., a display, a speaker, an LED lamp, etc.) that performs output to the outside. Note that the input device 1005 and the output device 1006 may be integrated into one structure (e.g., a touch screen).

The positioning device 1007 is a positioning means for measuring the position of the user terminal 10, such as a GPS (Global Positioning System) unit.

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

The user terminal 10 may also be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

Figure 3 is a diagram showing the hardware configuration of server device 30. The hardware configuration of server device 30 may be configured to include one or more of the devices shown in Figure 3, or may be configured to exclude some of the devices. In addition, server device 30 may be configured by communicating with multiple devices each having a different housing.

The server device 30 is physically configured as a computer device including a processor 3001, a memory 3002, a storage 3003, a communication device 3004, and a bus connecting these. Each function of the server device 30 is realized by loading a specific software (program) onto hardware such as the processor 3001 and the memory 3002, causing the processor 3001 to perform calculations, control communication by the communication device 3004, and control at least one of reading and writing data in the memory 3002 and the storage 3003. The processor 3001, the memory 3002, the storage 3003, the communication device 3004, and the bus connecting these are similar in terms of hardware to the processor 1001, the memory 1002, the storage 1003, the communication device 1004, and the bus connecting these described for the user terminal 10, and therefore a description thereof will be omitted. However, the communication device 3004 does not have to be hardware for communicating according to a wireless communication standard, but may be hardware (transmitting/receiving device) for communicating between computers via the network 2 according to any wired communication standard.

The carport device 20 is physically configured as a computer device including a processor, memory, storage, communication devices, input devices, output devices, and buses connecting these, similar to the user terminal 10 and server device 30. Each function of the carport device 20 is realized by loading specific software (programs) onto hardware such as the processor and memory, causing the processor to perform calculations, control communication via the communication devices, and control at least one of reading and writing data in the memory and storage.

FIG. 4 is a block diagram showing an example of the functional configuration of the server device 30. As shown in FIG. 4, the server device 30 realizes the functions of an acquisition unit 31, a route calculation unit 32, a first calculation unit 33, a storage unit 35, a second calculation unit 34, a generation unit 36, and a transmission unit 37.

The acquisition unit 31 acquires various information such as requests, notifications, or location information from the user terminal 10 or the carport device 20 via the network 2.

The route calculation unit 32 identifies a vehicle that is available near the departure point specified by the user, and calculates one or more candidate routes from the carport in which the vehicle is parked (called the departure carport) to an available carport in which the vehicle can be parked (called the destination carport) near the destination specified by the user.

The first calculation unit 33 calculates the expected revenue PP that the operator can obtain from a user when the user uses the facilities of the operator providing the mobility service (here, the vehicles parked in each carport and available for use) for a certain period of time. Specifically, a standard fee called the normal fee P is determined in advance for each unit of time (e.g., one hour) when using one vehicle, and the first calculation unit 33 multiplies this normal fee P by the vehicle usage time H to calculate the expected revenue PP (expected revenue PP = normal fee P x usage time H).

The second calculation unit 34 calculates the expected revenue EP that can be probabilistically expected by the operator by providing the equipment for a mobility service in a certain period of time. Specifically, the second calculation unit 34 performs a demand forecast for each facility and each future period based on the usage history of each facility, and further statistically calculates the operator's revenue for each facility and each future period based on the usage history of each facility (for example, the average of the revenue for each facility and each past period is set as the revenue for each facility and each future period), and sets this as the expected revenue EP. The demand forecast for each facility (prediction of the probability of receiving reservations or use from users) and the calculation of the expected revenue may be realized using machine learning such as deep learning.

The memory unit 35 stores facility information for each facility, user information for each user, and map and traffic information.

As shown in FIG. 5, the facility information includes a facility ID that identifies each facility (vehicle or carport), the location of each facility, the regular fee for each facility, and information regarding the usage history of each facility.

As shown in FIG. 6, the user information includes a user ID that identifies each user, attributes of each user, and information regarding the means by which the user pays the usage fee.

The map and traffic information includes information on the location of each road included in the area where the mobile service is provided, the direction of travel and the number of lanes on each road, and information on traffic lights on each road, as well as information on congestion and accidents on each road within the area. The map and traffic information may also include information on traffic volume sensed by a specified sensing device in each area, and statistical information from a macro perspective on how vehicles on the road move depending on conditions such as date and time. This map and traffic information is used to calculate the vehicle's route and the time required for the vehicle to travel that route. Note that well-known algorithms such as the Dijkstra algorithm and the A* (A-Star) algorithm are used to calculate the vehicle's route and the time required for the vehicle to travel that route.

The generation unit 36 uses the difference between the expected revenue PP calculated by the first calculation unit 33 and the expected revenue EP calculated by the second calculation unit 34 (difference = expected revenue PP - expected revenue EP) to determine a benefit that the user will receive when using the equipment, and generates presentation information including information about the benefit. The benefit here refers to the discount amount D on the normal fee P x usage time H described above. In other words, the user can use the operator's equipment by paying the operator a fee (called the usage fee) that is the normal fee P x usage time H minus the discount amount D. The method of determining the discount amount D, which is the benefit, using the difference between the expected revenue PP and the expected revenue EP will be described in detail later.

The transmission unit 37 transmits various information such as requests, notifications, or the above-mentioned presentation information to the user terminal 10 or the carport device 20 via the network 2.

[motion]
Next, the operation of the server device 30 will be described. The procedures of each process shown in FIG. 7 are described in a program implemented in the server device 30. In the following description, when the server device 30 is described as the subject of processing, this specifically means that the processor 3001 performs calculations by loading a specific software (program) onto hardware such as the processor 3001 and memory 3002, and controls communication by the communication device 3004 and reading and/or writing of data in the memory 3002 and storage 3003, thereby executing processing. The same applies to the user terminal 10 and the carport device 20.

In FIG. 7, the server device 30 (acquisition unit 31) acquires a request for boarding from the user via the network 2 from the user terminal 10 (step S11). This request includes information such as the user's user ID, the departure point specified by the user, the desired departure date and time, intermediate points, the desired arrival date and time at the intermediate points, the destination, and the desired arrival date and time at the destination, but the information about intermediate points is not essential.

Based on the information included in the request, the server device 30 (route calculation unit 32) identifies an available vehicle near the departure point, and calculates two or more candidate routes from the carport where the vehicle is parked (called the departure carport) via the intermediate point to an available carport where the vehicle can be parked near the destination (called the destination carport) (step S12). The candidate routes include each position indicating the route, as well as the scheduled date and time when the vehicle will pass each position on the route.

Here, FIG. 8 is a conceptual diagram illustrating a group of route candidates calculated by the server device 30 (route calculation unit 32). Route candidate R1 represents a route from a departure carport S1 near a departure point specified by the user (for example, the user's current location U) to a destination carport G1 near a destination G specified by the user. Route candidate R2 represents a route from the departure carport S1 to the destination carport G1, which is different from route candidate R1. Route candidate R3 represents a route from a departure carport S2 near a departure point specified by the user to a destination carport G2 near a destination G specified by the user. Note that any one of these route candidates is the route that has the smallest distance that the user travels from the departure point to the destination (here, the distance on the route candidate from each departure carport to the destination carport), the smallest time required for the user to travel (here, the vehicle usage time H expected when traveling on the route candidate from each departure carport to the destination carport), or the smallest fee required for the user to travel (here, the normal fee P for the vehicle at each departure carport x the above-mentioned usage time H). Here, we assume that route candidate R1 is the route that the user travels the shortest distance from the departure point to the destination. In other words, route candidate R1 is the route that places the least burden on the user. On the other hand,

Next, the server device 30 (first calculation unit 33) calculates the expected revenue PP that the business operator will earn from the user when the user uses the vehicle rented from the departure carport for the time required to travel from the departure carport to the destination carport for each route candidate (step S13). Specifically, the server device 30 (first calculation unit 33) multiplies the normal fee P determined for a vehicle parked in the departure carport by the usage time H from the departure carport to the destination carport for each route candidate to calculate the expected revenue PP. In this way, the expected revenue PP is calculated for each of the route candidates R1, R2, and R3 illustrated in FIG. 8.

Next, the server device 30 (second calculation unit 34) calculates the expected profit EP that the business operator can expect probabilistically for each route candidate over the time required for the user to reach the destination carport from the starting carport (step S14). Specifically, based on the usage history of the vehicle parked in the starting carport, the server device 30 (second calculation unit 34) calculates the average value of the past profits of the vehicle over the time required for the user to reach the destination carport from the starting carport, and calculates the expected profit EP for the time required from the starting carport to the destination carport based on this average value. As a result, the expected profit EP is calculated for each of the route candidates R1, R2, and R3 illustrated in FIG. 8.

The server device 30 (generation unit 36) uses the difference between the expected revenue amount PP calculated by the first calculation unit 33 and the expected revenue amount EP calculated by the second calculation unit 34 for each route candidate (expected revenue amount PP - expected revenue amount EP) to determine the benefit that the user can obtain (i.e., discount amount D from regular fee P x usage time H), and generates presentation information including information regarding the benefit (step S15).

The process of steps S13 to S15 will now be described in more detail. First, the estimated profit PP, expected profit EP, and the difference between them (estimated profit PP-expected profit EP) of the route candidates R1, R2, and R3 are assumed as follows:
Route candidate R1
Expected profit amount PP = 5000 yen, expected profit amount EP = 4000 yen, difference (expected profit amount PP - expected profit amount EP) = 1000 yen Route candidate R2
Expected profit amount PP = 5000 yen, expected profit amount EP = 500 yen, difference (expected profit amount PP - expected profit amount EP) = 4500 yen Route candidate R3
Projected profit PP = 8,800 yen, expected profit EP = 5,000 yen, difference (projected profit PP - expected profit EP) = 3,800 yen

Here, a route candidate with a large difference (expected revenue PP - expected revenue EP) means that the expected revenue EP is small compared to the expected revenue PP, and therefore can be said to be a route that uses equipment with relatively low demand (i.e. vehicles that have a high probability of having been used in the past). On the other hand, a route candidate with a small difference (expected revenue PP - expected revenue EP) means that the expected revenue EP is large compared to the expected revenue PP, and therefore can be said to be a route that uses equipment with relatively high demand (vehicles that have a high probability of having been used in the past).

The generation unit 36 calculates the difference (here, the absolute value of the difference) between the difference (projected profit amount PP - expected profit amount EP) between any two route candidates from the group of route candidates. In this case, it is as follows.
Difference between the price difference (PP-EP) of route candidate R1 and the price difference (PP-EP) of route candidate R2: |1000 yen-4500 yen|=3500 yen Difference between the price difference (PP-EP) of route candidate R1 and the price difference (PP-EP) of route candidate R3: |1000 yen-3800 yen|=2800 yen Difference between the price difference (PP-EP) of route candidate R2 and the price difference (PP-EP) of route candidate R3: |4500 yen-3800 yen|=700 yen

The generation unit 36 determines the discount amount D to be presented to the user based on the difference between these differences (expected profit amount PP - expected profit amount EP). Specifically, for example, when two route candidates are presented to the user, the difference between these differences becomes the maximum value of the discount amount D. At this time, the generation unit 36 determines the discount amount D to be presented to the user based on the difference between the difference between the route candidate that is the smallest in the distance the user travels from the departure point to the destination (here, the distance on the route candidate from each departure carport to the destination carport), the time required for the user to travel (here, the vehicle usage time H expected when traveling on the route candidate from each departure carport to the destination carport), or the fee required for the user to travel (here, the normal fee P for the vehicle at each departure carport x the above-mentioned usage time H) and the difference between the differences for the other route candidates. In other words, the server device 30 (generation unit 36) determines the benefit and generates the presentation information based on the difference between the difference between the price difference for route candidate R1 (first route), which corresponds to the route candidate with the shortest distance (here, the distance on the route candidate from each starting carport to the destination carport) that the user travels from the departure point to the destination, and the price difference for the other route candidates R2 and R3 (second routes).

For example, when route candidate R1 is presented as the first route and route candidate R2 is presented as the second route, the difference between route candidate R1's difference (expected profit PP - expected profit EP) and route candidate R2's difference (expected profit PP - expected profit EP), 3500 yen, becomes the maximum discount amount D for route candidate R2, which uses equipment with relatively low demand. The generation unit 36 multiplies the difference between route candidate R1's difference (expected profit PP - expected profit EP) and route candidate R2's difference (expected profit PP - expected profit EP), 3500 yen, by a predetermined coefficient (a coefficient of 1 or less, called a profit margin, here 0.3, for example), to obtain 3500 yen x 0.3 = 1050 yen, which is the discount amount D for route candidate R2's expected profit PP = 8800 yen, and presents 8800 yen - 840 yen = 7960 yen as the usage fee. This can encourage users to use route candidate R3, which has relatively low demand.

When three or more route candidates are presented, the generation unit 36 calculates the discount amount D in the same way as in the case of two route candidates described above. For example, when route candidate R1 is presented as the first route, route candidate R2 is presented as the second route, and route candidate R3 is presented as the third route, the difference between route candidate R1 (expected profit amount PP - expected profit amount EP) and route candidate R2 (expected profit amount PP - expected profit amount EP), which is 3,500 yen, becomes the maximum discount amount for route candidate R2 that uses equipment with relatively low demand. Also, the difference between route candidate R1 (expected profit amount PP - expected profit amount EP) and route candidate R3 (expected profit amount PP - expected profit amount EP), which is 2,800 yen, becomes the maximum discount amount for route candidate R3 that uses equipment with relatively low demand. The generation unit 36 multiplies the difference between route candidate R1 (estimated revenue PP - expected revenue EP) and route candidate R2 (estimated revenue PP - expected revenue EP), which is 3,500 yen, by a predetermined profit margin (for example, 0.3), and determines 3,500 yen x 0.3 = 1,050 yen as the discount amount D for route candidate R2's expected revenue PP = 5,000 yen, and presents 5,000 yen - 1,050 yen = 3,950 yen as the usage fee. The generation unit 36 also multiplies the difference between route candidate R1 (projected revenue PP - expected revenue EP) and route candidate R3 (projected revenue PP - expected revenue EP), 2800 yen, by a predetermined profit rate (for example, 0.3), to obtain 2800 yen x 0.3 = 840 yen as the discount amount D for route candidate R3's projected revenue PP = 8800 yen, and presents 8800 yen - 840 yen = 7960 yen as the usage fee. This makes it possible to encourage users to use route candidates R2 and R3, which have relatively low demand.

Then, the server device 30 (transmission unit 37) transmits the generated presentation information to the user terminal 10 via the network 2 (step S16). The user can learn the details of the transportation service that can be used by the user by viewing the presentation information output on the user terminal 10. FIG. 9 is an example of the presentation information when, for example, route candidate R1 is presented as the first route and route candidate R2 is presented as the second route. As illustrated in FIG. 9, for route candidate R1, a usage fee of 5,000 yen is presented, which is obtained by subtracting a discount amount D = 0 yen from a normal fee P x usage time H = 5,000 yen. Also, for route candidate R2, a usage fee of 3,950 yen is presented, which is obtained by subtracting a discount amount D = 1,050 yen from a normal fee P x usage time H = 5,000 yen. In FIG. 9, when the user selects the soft button labeled "Map", a map of the carport is displayed on the user terminal 10.

The user can select one of the route candidates displayed as presented information and specify to the server device 30 the use of the vehicle corresponding to that route candidate. After that, through a predetermined process, the user can use the vehicle that he or she specified.

According to the embodiment described above, the reward given to the user is determined based on the difference between the expected profit and the anticipated profit of each facility provided for the mobility service, so that the operator can grant the reward within an appropriate range. In addition, the user is presented with at least presented information regarding a first route from among the candidate route groups, which corresponds to either the route with the least distance traveled by the user, the least time required for the user to travel, or the least cost required for the user to travel, so that it is possible to present information that takes into account the burden on the user when traveling to the destination.

[Modification]
The present invention is not limited to the above-described embodiment. The above-described embodiment may be modified as follows. In addition, two or more of the following modifications may be combined and implemented.

[Modification 1]
In the above embodiment, the first route used for comparing the multiple route candidates is the route that has the smallest distance traveled by the user, the smallest time required for the user to travel, or the smallest fare required for the user to travel among the calculated route candidates. However, the first route is not limited to this example. The generating unit 36 may set any route candidate among the multiple route candidates as the first route, and set a route candidate different from the first route as the second route. In other words, the generating unit 36 may generate presentation information based on the difference between the difference (the difference between the expected profit amount PP and the expected profit amount EP) when the user travels along the first route among the multiple routes and the difference (the difference between the expected profit amount PP and the expected profit amount EP) when the user travels along the second route different from the first route.

The first route may be a route candidate calculated based on the user's movement history as having a probability of the user passing through the route equal to or greater than a threshold value. The user's movement history may be, for example, a history of position data measured by the positioning function of the user terminal 10, transmitted from the user terminal 10 to the server device 30 and stored in the storage unit 35 of the server device 30 as user information exemplified in FIG. 6. The generation unit 36 calculates, for each route candidate, the probability (possibility) that the user was on the route candidate in the past based on this movement history. This makes it possible to identify route candidates including routes that the user usually frequently uses. In this way, the route candidate including the route that the user usually frequently uses becomes the first route, and the route candidate different from the first route becomes the second route. That is, the generation unit 36 generates presentation information based on the difference between the difference (the difference between the expected profit amount PP and the expected profit amount EP) when the user travels a first route that is calculated to be more than or equal to a threshold based on the user's travel history, and the difference (the difference between the expected profit amount PP and the expected profit amount EP) when the user travels a second route different from the first route. This makes it possible to present to the user presentation information about a group of route candidates including route candidates that the user is familiar with, taking into account the user's travel orientation.

[Modification 2]
The second route compared with the first route may be a route that uses a facility with relatively low demand, that is, a route with the largest difference between the estimated profit amount PP and the expected profit amount EP when traveling along the second route among the multiple route candidates. This makes it possible to present presented information regarding route candidates that use facilities with relatively low demand to the user.

[Modification 3]
The profit rate described in the embodiment may be dynamically changed. In other words, the generating unit 36 may multiply the difference between the amount of difference (the difference between the expected profit amount PP and the expected profit amount EP) when the user travels along a first route among a plurality of route candidates and the amount of difference (the difference between the expected profit amount PP and the expected profit amount EP) when the user travels along a second route by a profit rate equivalent to a coefficient that varies according to certain conditions, to determine the discount amount D when the user uses the facility.

The generating unit 36 may use the profit margin calculated by machine learning. For example, if the coefficient corresponding to the above-mentioned profit margin is made smaller, the discount amount D becomes smaller, so that the profit for the business operator becomes larger, while the user is less motivated to use the presented facility when the discount amount D becomes smaller. Conversely, if the coefficient corresponding to the above-mentioned profit margin is made larger, the discount amount D becomes larger, so that the profit for the business operator becomes smaller, while the user may be motivated to use the presented facility when the discount amount D becomes larger. Therefore, the generating unit 36 may perform machine learning using information on the profit margin and the usage history of the facility as training data, generate an algorithm that optimizes the profit margin to improve the user's behavior change rate, and determine the profit margin according to the algorithm. The behavior change rate here is the ratio at which the user uses the facility presented by the presented information in response to the presentation of the presented information, and can be identified from the presentation history of the presented information and the usage history of the facility. This is expected to optimize the balance between the profit of the business operator based on the profit margin and the ratio at which the facility presented to the user is used based on the profit margin.

In addition, for example, when the difference in the distance traveled by the user when comparing the first route and the second route in the presented information is large, the discount amount D for the route candidate with the larger travel distance must be increased by increasing the coefficient corresponding to the profit rate described above, otherwise the user will not be motivated to select the route candidate with the larger travel distance. Conversely, when the difference in the distance traveled by the user when comparing the first route and the second route in the presented information is small, even if the coefficient corresponding to the profit rate described above is reduced, it is expected that the user will make the decision to select the route candidate with the larger travel distance. This is not limited to the difference in the distance traveled by the user when comparing the first route and the second route, but also applies to, for example, the difference in the time required for the user to travel when comparing the first route and the second route in the presented information, or the difference in the fare required for the user to travel when comparing the first route and the second route in the presented information. Therefore, machine learning may be performed using, as training data, information on the profit margin and any of the following: the difference in the distance traveled by the user when comparing the first route and the second route in the presented information, the difference in the time required for the user to travel when comparing the first route and the second route in the presented information, or the difference in the fare required for the user to travel when comparing the first route and the second route in the presented information, to generate an algorithm that optimizes the profit margin to improve the user's behavioral change rate, and the profit margin may be determined according to the algorithm. This is expected to optimize the balance between the operator's profit based on the profit margin and the rate at which the facilities presented to the user based on the profit margin are used.

The machine learning techniques used in the present invention may include, for example, reinforcement learning such as bandit algorithms, optimization based on greedy algorithms based on user requests at a certain moment or over a certain time span, or application of optimization methods as combinatorial problems.

[Modification 4]
The present invention is not limited to automobiles, but can be applied to various types of transportation services such as motorcycles and kick scooters. In addition, when moving via multiple types of transportation services, such as moving to a carport using a motorcycle and then using an automobile from the carport, the generation unit 36 may calculate the expected profit amount PP and the expected profit amount EP as described above for each transportation service, and generate the presentation information using the difference between them. In this case, the generation unit 36 may generate an algorithm for optimizing the profit rate for improving the user's behavior change rate by machine learning using the above-mentioned profit rate and information on the user's facility usage history for multiple types of transportation services as training data, and may determine the profit rate according to the algorithm.

[Modification 5]
The benefits given to the user are not limited to a discount on the fee, but may also include the granting of value information replaceable with money, called points, to the user, a kickback of such value information to the user, a gift to the user, or the presentation of a special campaign to the user.

[Modification 6]
In the above embodiment, the server device 30 is exemplified as an example of an information processing device according to the present invention, but the present invention can be applied to any information processing device that realizes the functional blocks exemplified in FIG.

[Other Modifications]
The block diagrams used in the description of the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of at least one of hardware and software. The method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one device that is physically or logically coupled, or may be realized using two or more devices that are physically or logically separated and directly or indirectly connected (for example, using wires, wirelessly, etc.). The functional blocks may be realized by combining the one device or the multiple devices with software.

Functions include, but are not limited to, judgement, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, regard, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs the transmission function is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on the method of realization for either of these.

The notification of information is not limited to the aspects/embodiments described in the present disclosure, and may be performed using other methods. For example, the notification of information may be performed by physical layer signaling (e.g., Downlink Control Information (DCI), Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, broadcast information (Master Information Block (MIB), System Information Block (SIB))), other signals, or a combination of these. In addition, the RRC signaling may be called an RRC message, and may be, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, etc.

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

The processing steps, sequences, flow charts, etc. of each aspect/embodiment described in this disclosure may be reordered unless inconsistent. For example, the methods described in this disclosure present elements of various steps using an example order and are not limited to the particular order presented.

Information, etc. may be output from a higher layer (or a lower layer) to a lower layer (or a higher layer). It may also be input/output via multiple network nodes.

The input and output information may be stored in a specific location (e.g., memory) or may be managed using a management table. The input and output information may be overwritten, updated, or added to. The output information may be deleted. The input information may be transmitted to another device.

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

Each aspect/embodiment described in the present disclosure may be used alone, in combination, or switched according to execution. In addition, notification of predetermined information (e.g., notification that "X is true") is not limited to being done explicitly, but may be done implicitly (e.g., not notifying the predetermined information).
Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described in the present disclosure. The present disclosure can be implemented in modified and altered forms without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the description of the present disclosure is intended to be illustrative and does not have any limiting meaning on the present disclosure.

Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.
Additionally, software, instructions, information, etc. may be transmitted or received over a transmission medium. For example, if the software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and/or wireless technologies (such as infrared, microwave, etc.), then these wired and/or wireless technologies are included within the definition of transmission media.

The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, the data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.
In addition, the terms described in this disclosure and the terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, at least one of the channel and the symbol may be a signal (signaling). Also, the signal may be a message. Also, a component carrier (CC) may be called a carrier frequency, a cell, a frequency carrier, etc.

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

In addition, the information, parameters, etc. described in the present disclosure may be represented using absolute values, may be represented using relative values from a predetermined value, or may be represented using other corresponding information. For example, a radio resource may be indicated by an index.
The names used for the above-mentioned parameters are not limiting in any way. Furthermore, the formulas etc. using these parameters may differ from those explicitly disclosed in this disclosure. The various channels (e.g., PUCCH, PDCCH, etc.) and information elements may be identified by any suitable names, and therefore the various names assigned to these various channels and information elements are not limiting in any way.

In this disclosure, terms such as "Mobile Station (MS)", "user terminal 10", "User Equipment (UE)", "terminal", etc. may be used interchangeably.
A mobile station may also be referred to by those skilled in the art as a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable terminology.

The user terminal 10 or the carport device 20 may be referred to as a transmitting device, a receiving device, a communication device, etc.

The terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, search, inquiry (e.g., searching in a table, database, or other data structure), ascertaining, and the like. "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like. Additionally, "judgment" and "decision" can include considering resolving, selecting, choosing, establishing, comparing, etc., to have been "judged" or "decided." In other words, "judgment" and "decision" can include considering some action to have been "judged" or "decided." Additionally, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

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

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

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

When the terms "include," "including," and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising." Additionally, the term "or," as used in this disclosure, is not intended to be an exclusive or.

In this disclosure, where articles have been added through translation, such as a, an, and the in English, this disclosure may include that the nouns following these articles are in the plural form.

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

1...Sharing mobility system, 2...Network, 10...User terminal, 1001...Processor, 1002...Memory, 1003...Storage, 1004...Communication device, 1005...Input device, 1006...Output device, 1007...Positioning device, 20...Carport device, 30...Server device, 31...Acquisition unit, 32...Route calculation unit, 33...First calculation unit, 34...Second calculation unit, 35...Storage unit, 36...Generation unit, 37...Transmission unit, 3001...Processor, 3002...Memory, 3003...Storage, 3004...Communication device.

Claims (10)

a first calculation unit that calculates an expected amount of revenue that a provider providing a mobile service can obtain from a user when the user uses the facility of the provider for a certain period of time;
a second calculation unit that calculates an expected profit amount that can be probabilistically expected by the business operator by providing the facility for the mobility service during the certain period;
a generating unit that generates presentation information including information on a benefit that the user can receive when the user uses the facility, using the calculated difference between the estimated profit amount and the expected profit amount;
a transmitting unit that transmits the generated presentation information to the communication terminal of the user. The first calculation unit and the second calculation unit
performing the calculation for the facilities used by the user when traveling along each of a plurality of routes;
The generation unit is
The information processing device according to claim 1, characterized in that the presentation information is generated based on the difference between the fare difference when the user travels a first route among the multiple routes and the fare difference when the user travels a second route different from the first route. 3. The information processing device according to claim 2, wherein the first route is a route in which at least one of a distance traveled by the user, a time required for the user to travel, and a fee required for the user to travel is the smallest. The information processing device according to claim 2 , wherein the first route is a route that is calculated based on the user's movement history as being more likely to be taken by the user than a threshold value. The second pathway includes:
The information processing device according to claim 3 or 4, characterized in that the route is the route in which the difference in fare for traveling along the route is the largest among the plurality of routes. The generation unit is
The information processing device according to any one of claims 2 to 5, characterized in that the benefit is calculated as a discount on the usage fee when the user uses the facility by multiplying the difference between the difference when the user travels along the first route and the difference when the user travels along the second route by a coefficient that varies depending on certain conditions. The information processing device according to claim 6 , wherein the generation unit uses the coefficients calculated by machine learning. The information processing device according to claim 7 , wherein the generation unit uses the coefficients calculated by machine learning using the coefficients and information on a usage history of the facility as training data. The information processing device according to claim 7, characterized in that the generation unit uses the coefficient calculated by machine learning using as training data the coefficient and information regarding a difference in distance traveled by the user when comparing the first route and the second route, a difference in time required for the user to travel, or a difference in fare required for the user to travel. The information processing device according to claim 7 , wherein the generation unit uses the coefficients calculated by machine learning using the coefficients and information on a usage history of the facility in a plurality of types of mobility services as training data.

Images