Information processing device, information processing method, and program

Abstract

This invention provides an information processing device, information processing method, and program that can estimate user satisfaction with services provided by transportation operators without directly asking users about their travel purpose. [Solution] The system has a memory for storing a program and a processor for executing processing according to the program. The memory stores user information of a user who moves using a means of transport, movement history information of an information processing terminal, and a service list which is a list of multiple service sets that are combinations of ancillary services and the value provided. The processor estimates the purpose of the move and the desired value, which is the value sought by the user, based on the user information and movement history information. By comparing the desired value with the value provided, it selects a service set from the service list that includes ancillary services corresponding to the desired value, calculates the degree of match between the desired value and the value provided, and outputs the degree of match as the user's satisfaction with the ancillary services.

Description

Technical Field

[0001] The present disclosure relates to a technique for evaluating a mobility service, which is a service for transporting people or objects using a means of transportation.

Background Art

[0002] Public services such as affairs or projects conducted by a country or a local government are related to the topography of the area where the service is provided, the historical and cultural background, and the attributes of the users who use the service. Therefore, it is ideal that public services are optimally designed based on these contents. Public services may include, in a broad sense, those conducted by the private sector. For example, mobility services are used by many people, and if the provision of the service is delayed, a large economic loss will occur, so it is considered to be included in public services.

[0003] In recent years, the Digital Agency, one of the administrative agencies in Japan, has proposed a smart city concept for the purpose of putting people at the center or enhancing the regional well-being or QoL (Quality of Life) of citizens. This is to aim for public service design that emphasizes how to increase the value enjoyed by users who use public services.

[0004] For example, when considering designing a mobility service that increases user satisfaction, the direction of the added value that the service should aim for changes depending on the combination of multiple types of mobility services and the purpose of the movement. For example, when a mobility service is often used for commuting or going to school, connecting between bases in a short time and performing mass transportation are the directions to aim for in service design. On the other hand, when a mobility service is often used for shopping or sightseeing, connecting so as to tour between bases and on-demand transportation are the directions to aim for in service design. On-demand transportation is a transportation method in which a means of transportation is dispatched in response to a reservation from a user.

[0005] As mentioned above, unless mobility services are designed to address the purpose of travel, it will be difficult to significantly increase user satisfaction. Therefore, it is necessary to evaluate how much satisfaction a mobility service provides to users and to utilize the evaluation results in service design. One example of a method to directly evaluate user satisfaction is to gather user satisfaction information through questionnaires. Researchers sample multiple users from a large number of users who have actually used the mobility service being evaluated. The researchers then directly ask the sampled users about their satisfaction levels to obtain responses indicating satisfaction. In addition to satisfaction, researchers can also ask the subjects about their motivations or purposes for using the mobility service.

[0006] The method of gathering satisfaction information from users through surveys has the advantage of directly understanding users' subjective satisfaction with the transportation service being evaluated. However, it has the disadvantage of requiring significant effort and expense in designing, conducting, and analyzing the survey content. Furthermore, the more survey items there are, the greater the number of questions and the greater the burden on users who answer the survey. Therefore, there are limitations on the frequency of the survey, such as once a year. Also, the burden increases with the number of transportation services being evaluated, so there are limitations on the number of transportation services that can be evaluated.

[0007] One way to reduce the burden on researchers and users is to indirectly evaluate user satisfaction. One example of an indirect method for evaluating user satisfaction is to use information such as the location history of a terminal device carried by the user (see, for example, Patent Document 1). The system disclosed in Patent Document 1 acquires location history information from the user's terminal device and estimates the effectiveness of introducing a mobility service from the difference between the travel time without using the mobility service and the travel time with using the mobility service for movement between two points. [Prior art documents] [Patent Documents]

[0008] [Patent Document 1] Japanese Patent Publication No. 2021-149337 [Overview of the project] [Problems that the invention aims to solve]

[0009] The system disclosed in Patent Document 1 estimates that the shorter the travel time between two points for a user, the greater the effect of introducing a mobility service. However, shorter travel time does not necessarily lead to greater user satisfaction. For example, if the purpose of travel is shopping or sightseeing, reducing travel time may not be important. The system disclosed in Patent Document 1 estimates the effect of introducing a mobility service without directly interviewing users, but it is difficult to determine how satisfied users are with the mobility service from information obtained from terminal devices.

[0010] One of the purposes included in this disclosure is to provide an information processing device, information processing method, and program that can estimate a user's satisfaction with services provided by a transportation operator without directly asking the user about their purpose of travel. [Means for solving the problem]

[0011] An information processing device according to one aspect of the present disclosure includes a memory for storing a program and a processor for executing processing according to the program, wherein the memory stores user information, which is information about a user who travels using means of transport provided by a transport operator, and travel history information of an information processing terminal carried by the user, and stores a service list, which is a list of multiple service pairs, which are combinations of ancillary services, which are services attached to the means of transport, and value provided, which is value provided to the user by the ancillary services, and the processor, by executing the program, estimates the purpose of travel and the desired value, which is value sought by the user for the purpose of travel, based on the user information and the travel history information, and by comparing the desired value with the value provided, selects a service pair from the service list that includes the ancillary services corresponding to the desired value, determines the degree of match between the desired value and the value provided in the selected service pair, and outputs the degree of match as the user's satisfaction with the ancillary services included in the selected service pair. [Effects of the Invention]

[0012] According to one aspect of this disclosure, the user's purpose of travel and desired value can be estimated and related ancillary services can be identified without directly asking the user about their purpose of travel. Therefore, the degree of match between the identified ancillary services and the estimated desired value is output as the user's satisfaction level. [Brief explanation of the drawing]

[0013] [Figure 1] This is a block diagram showing an example configuration of a mobile support system having an information processing device according to Example 1. [Figure 2] This is a block diagram showing an example configuration of an information processing device according to Example 1. [Figure 3] This is a diagram illustrating the configuration of the information processing device according to Example 1. [Figure 4]It is a diagram showing an example of information on a moving purpose and a desired value stored in the storage unit shown in FIG. 2. [Figure 5] It is a diagram showing another example of information on a moving purpose and a desired value stored in the storage unit shown in FIG. 2. [Figure 6] It is a diagram showing another example of information on a moving purpose and a desired value stored in the storage unit shown in FIG. 2. [Figure 7] It is a diagram showing an example of a table used in combination with the table shown in FIG. 6. [Figure 8] It is a diagram showing an example of a service candidate list and a provided value candidate list stored in the storage unit shown in FIG. 2. [Figure 9] It is a diagram showing an example of user information stored in the storage unit shown in FIG. 2. [Figure 10] It is a diagram showing an example of the hardware configuration of the control unit shown in FIG. 2. [Figure 11] It is a sequence diagram showing the procedure from an evaluation request to obtaining the user's satisfaction with an attached service in the mobile support system according to the first embodiment. [Figure 12] It is a sequence diagram showing an example of an operation of obtaining the user's satisfaction from various viewpoints including the user's satisfaction with an attached service by the information processing apparatus according to the first embodiment. [Figure 13] It is a flowchart showing an example of a procedure for creating a service list stored in the storage unit shown in FIG. 2. [Figure 14] It is a diagram showing an example of the service list created in step S410 shown in FIG. 13. [Figure 15] It is a flowchart showing an example of a procedure for the information processing apparatus according to the first embodiment to estimate the movement of each user in one day. [Figure 16] It is a flowchart showing an example of a procedure for the information processing apparatus according to the first embodiment to estimate the movement of each user in one day. [Figure 17] It is a diagram showing an example of movement history information stored in the storage unit shown in FIG. 2. [Figure 18]In the process of step S507 shown in FIG. 15, it is a table showing an example of additional information created based on movement history information. [Figure 19] It is a diagram showing an example when a plurality of movement events are represented in a hierarchical structure. [Figure 20] It is a diagram showing an output example of the means of movement, the purpose of movement, and the desired value for each movement estimated by the estimation unit shown in FIG. 2. [Figure 21] It is a flowchart showing an example of the operation procedure by the determination unit shown in FIG. 2. [Figure 22] It is a block diagram showing a configuration example of the information processing apparatus according to the second embodiment. [Figure 23] In the second embodiment, it is a diagram for explaining the case where the estimation unit shown in FIG. 22 machine-learns a learning model for estimating the movement of a user with user information and movement history information as inputs.

Mode for Carrying Out the Invention

[0014] An example of the information processing apparatus of the present embodiment will be described with reference to the drawings. The information processing apparatus of the present embodiment is a device that notifies a transportation business operator of the degree of match between the value provided by a transportation business operator that operates means of movement such as a bus or a taxi and the value that a user who uses the means of movement demands from the transportation business operator. The transportation business operator is an operator of a public transportation organization that provides a movement service using the means of movement to users. Specific examples of the present disclosure content are shown in the drawings to be referred to, but these examples are for understanding the present disclosure. The present disclosure is not limited within the scope of the drawings.

Examples

[0015] <Overview of the Movement Support System> The configuration of the mobility support system having the information processing device of this embodiment 1 will be described. Figure 1 is a block diagram showing an example configuration of the mobility support system having the information processing device according to embodiment 1. The mobility support system 10 has an information processing device 1, transportation terminals 2-1 to 2-p (where p is any integer of 1 or more), and information processing terminals 3-1 to 3-q (where q is any integer of 1 or more). The information processing device 1 is a computer such as a personal computer (PC) or a server. The information processing device 1 communicates with each of the transportation terminals 2-1 to 2-p and the information processing terminals 3-1 to 3-q via a network 100. A server 30 is connected to the network 100. The network 100 is, for example, a network including the Internet.

[0016] <Transportation terminal 2-1~2-p> Transportation terminals 2-1 to 2-p are information processing devices operated by transportation operators that operate means of transport such as buses or taxis. Transportation terminals 2-1 to 2-p are, for example, PCs or smartphones. Hereinafter, the code of any transportation terminal among transportation terminals 2-1 to 2-p will be denoted as 2-h (where h is any integer from 1 to p). Transportation terminal 2-h is used by the operator when the transportation operator registers information about its services with the information processing device 1. Transportation terminal 2-h is also used by the operator when the transportation operator requests user evaluations of its services from the server 30 and the information processing device 1. In this embodiment 1, it is assumed that each of several different transportation operators owns one transportation terminal 2-h. Each of the several different transportation operators may be a company that operates different types of means of transport, such as buses or taxis, or they may be companies that operate the same type of means of transport. For example, if the same type of means of transport is buses, then the several different transportation operators may be different companies, such as AAA Bus Company and BBB Bus Company.

[0017] <Information Processing Terminal 3-1~3-q> Information processing terminals 3-1 to 3-q are portable information processing devices carried by users utilizing means of transportation. Examples of information processing terminals 3-1 to 3-q include smartphones. Hereafter, the code of any information processing terminal among 3-1 to 3-q will be denoted as 3-r (where r is any integer from 1 to q).

[0018] <Server 30> Server 30 is an information processing device that provides predetermined services to the user of information processing terminal 3-r. This embodiment 1 describes a case where Server 30 is an information processing device that provides a location notification service to notify the user of the location of information processing terminal 3-r on Earth. Server 30 stores map information in which the latitude, longitude, and altitude of any location on Earth are registered. Server 30 provides application software programs dedicated to the location notification service to information processing terminals 3-1 to 3-q.

[0019] When Server 30 receives a request from a transportation operator to evaluate their services via Transportation Terminal 2-h, it requests permission from the user via Information Processing Terminal 3-r to provide location information to Information Processing Device 1. Server 30 assigns a unique identifier (IDentifier) ​​to each user who grants permission. Server 30 also sends a questionnaire form to the user via Information Processing Terminal 3-r to obtain user information, which is information about the user. User information includes, for example, demographic information such as place of residence, place of work, occupation, age, gender, hobbies, and preferences. User information may also include psychographic information such as personality and behavioral tendencies. When Server 30 receives the questionnaire response from the user via Information Processing Terminal 3-r, it provides the Information Processing Device 1 with a dataset containing the UID assigned to the user and user information. If the number of users who can grant permission is small, Server 30 may collect a commission fee from the transportation operator in advance, convert the commission fee into discount coupons for various products, and use the discount coupons as an incentive to ask for cooperation from users who cannot grant permission.

[0020] <Configuration of Information Processing Device 1> The configuration of the information processing device 1 will now be described. Figure 2 is a block diagram showing one example configuration of the information processing device according to Embodiment 1. The information processing device 1 includes a storage unit 4, a control unit 5, an input unit 6, an output unit 7, a communication unit 8, and a drive 9. The storage unit 4 has storage areas 11 to 15. The control unit 5 includes an estimation unit 21 and a determination unit 22.

[0021] The storage unit 4 is a storage device such as an HDD (Hard Disk Drive) or SSD (Solid State Drive). The input unit 6 is an input device such as a keyboard, mouse, or touch panel. The output unit 7 is an output device such as a display for displaying information or a speaker for outputting sound. The communication unit 8 has a communication circuit for communicating with other devices by wire or wireless. The communication unit 8 sends and receives data with other devices according to a communication protocol such as IP (Internet Protocol). The drive 9 is a device that reads and writes data to the recording medium 90. The recording medium 90 is an optical disc such as a CD (Compact Disc) or DVD (Digital Versatile Disc).

[0022] Figure 3 is a diagram illustrating the configuration of the information processing device according to Embodiment 1. The storage unit 4 and the control unit 5 will be described in detail. (A) The memory area 11 stores user information of users who use means of transportation such as buses or taxis, corresponding to their UIDs. The user information includes at least one of the following: the user's place of residence, place of work, occupation, age, gender, hobbies, and preferences. The dataset containing the UIDs and user information is provided to the information processing device 1 from the server 30 as described above. (B) The memory area 12 stores movement history information, which is a history of location information over a predetermined period of time acquired from the information processing terminals 3-1 to 3-q carried by the user, in correspondence with the UID. The predetermined period of time is, for example, one day (24 hours). Location information is information about changes in location over time. Location information is, for example, GPS data measured by GPS (Global Positioning System). GPS data is data that includes information about location and time on Earth. Location on Earth is latitude, longitude, and altitude. Location information is not limited to GPS data. If the information processing terminal 3-r is a smartphone, the location information may be calculated by the information processing terminal 3-r based on the strength of radio waves received by the information processing terminal 3-r from three or more different wireless base stations. The following explanation will be based on the case where the location information is GPS data. As will be explained later, movement history information is provided to the memory area 12 from the server 30.

[0023] (C) Memory area 13 stores a service candidate list, which lists multiple candidates for ancillary services, which are services attached to a means of transportation, and a value provision candidate list, which lists multiple candidates for value provided, which is the value provided to the user by the ancillary services. The multiple candidates for ancillary services include, for example, the operation schedule of the means of transportation, special tickets using the means of transportation, and payment methods for the use of the means of transportation. Specific examples of operation schedules, special tickets, and payment methods will be explained for the case where the transportation operator is a bus company. An example of an operation schedule is an increase in the number of services running in the morning. A special ticket is, for example, a pass that allows unlimited boarding and alighting for one day at multiple bus stops set up in a predetermined area. A payment method is, for example, a contactless payment method in which the user completes payment of the fare simply by holding the information processing terminal 3-r over a payment terminal installed at the entrance or exit of the bus. Specific examples of multiple candidate value provision are congestion reduction, reduction of travel time, or an increase in the number of travel options.

[0024] (D) Memory area 14 stores a service list in which multiple service sets are registered. A service set is a combination of an ancillary service selected from multiple ancillary services stored in memory area 13 and a value provided selected from multiple value provided stored in memory area 13. Service sets are selected by the administrator of a transport operator by operating the transport terminal 2-h. A service list may be registered in memory area 14 for each of the multiple transport operators, or one or more service sets from each of the multiple transport operators may be described in a single service list and registered in memory area 14. The following explanation will describe the case where a service list is registered in memory area 14 for each of the multiple transport operators. (E) Memory area 15 stores a table in which multiple value elements are registered for desired value, which is the value that the user seeks from the means of transportation for each of the multiple travel purposes. Desired value is deterministically defined in advance for each travel purpose, and in memory area 15, the desired value is stored and managed for each travel purpose. Travel purposes include commuting or shopping. If the travel purpose is commuting, for example, reduced travel time and reduced congestion are registered as value elements that constitute the desired value. If the travel purpose is shopping, for example, increased sightseeing options and route flexibility are registered as value elements that constitute the desired value. Information combining travel purpose and desired value may be stored in memory area 15 independently of the user, or information combining travel purpose and desired value may be stored in memory area 15 in response to the user. Specific examples of the information stored in memory area 15 will be explained later.

[0025] (F) The estimation unit 21 estimates the user's means of transportation, purpose of transportation, and desired value corresponding to the purpose of transportation, based on the user information stored in the memory area 11 and the travel history information stored in the memory area 12, corresponding to the UID. An example of the estimation method is described below. For example, if the estimation unit 21 determines that the user has moved from their place of residence to their place of work based on the user information's place of residence and place of work information and the travel history information, it estimates that the purpose of transportation is commuting. The estimation unit 21 refers to a table stored in the memory area 15 and estimates the desired value corresponding to the estimated purpose of transportation. The estimation unit 21 also calculates the travel speed from the time and distance taken from the user's place of residence to their place of work, based on the user information's place of residence and place of work information and the travel history information. The estimation unit 21 determines the travel route from the user's place of residence to their place of work, based on the user information's place of residence and place of work information and the travel history information. The estimation unit 21 estimates the means of transportation used by the user for transportation based on the calculated travel speed and the determined travel route. The estimation unit 21 transmits the estimation results, including information on the estimated means of transportation, purpose of transportation, and desired value, to the determination unit 22.

[0026] (G) When the determination unit 22 receives the estimation result from the estimation unit 21, it refers to the information stored in the memory area 14 and obtains a service list corresponding to the estimated means of transportation from the memory area 14. The determination unit 22 extracts ancillary services corresponding to the desired value from the service list by comparing the estimated desired value with the value provided by each service set in the service list. The determination unit 22 then selects a service set from the service list that includes the extracted ancillary services. The determination unit 22 determines the degree of agreement between the value provided by the service set selected from the service list and the desired value estimated by the estimation unit 21.

[0027] The determination unit 22 may evaluate the estimation results from perspectives other than those of determining each user's satisfaction with the ancillary services being evaluated. In this embodiment 1, the determination unit 22 may calculate the average satisfaction level of all users for each item of means of transportation, purpose of transportation, and ancillary services. Specifically, after each of the above items is estimated by the estimation unit 21 in correspondence with the UID, the determination unit 22 calculates a statistically averaged value of the data of all users for each item through statistical processing, and outputs each calculated value as satisfaction to the transportation terminal 2-h.

[0028] One possible perspective is to evaluate the average satisfaction level of all users who use the transportation method being evaluated. In this case, the determination unit 22 obtains data on travel using the transportation method being evaluated from the data of all users and calculates a statistically averaged value of the degree of match between the desired value recorded in each obtained data and the value provided. Another perspective is to evaluate the average satisfaction level of all users who have the transportation purpose being evaluated in the estimated travel. In this case, the determination unit 22 obtains data including the travel where the transportation purpose being evaluated is estimated from the data of all users and calculates a statistically averaged value of the degree of match between the desired value recorded in each obtained data and the value provided. Another perspective is to evaluate the average satisfaction level of all users who use the ancillary service being evaluated. In this case, the determination unit 22 obtains data where the ancillary service being evaluated is estimated from the data of all users and calculates a statistically averaged value of the degree of match between the desired value recorded in each obtained data and the desired value of the ancillary service being evaluated.

[0029] As described above, the determination unit 22, in accordance with the UID, calculates a statistical average of the degree of match between the desired value and the value provided for all users individually for each of the means of transportation, purpose of transportation, and ancillary services, thereby obtaining an index that shows user satisfaction from multiple different perspectives. User satisfaction with the means of transportation serves as an index for transportation operators to understand the current situation. User satisfaction with the purpose of transportation serves as an index for transportation operators that takes into account the entire transportation service, including their own transportation services, such as transfers between their means of transportation and those of other companies. In other words, user satisfaction with the purpose of transportation serves as an index for transportation operators to understand the direction of service design that can be strengthened through cooperation with other companies. User satisfaction with ancillary services serves as an index for transportation operators to understand the direction of service design that they should strengthen.

[0030] <Specific examples of information stored in memory area 15> A specific example of the information stored in memory area 15 will be explained with reference to Figure 4. Figure 4 shows an example of information on travel purpose and desired value stored in the memory unit shown in Figure 2. Before an evaluation request is made by a transportation operator, information on travel purpose and desired value is stored in memory area 15.

[0031] The table shown in Figure 4 registers desired value corresponding to the purpose of travel. Desired value is represented by multiple value elements and the score of each value element. The table shown in Figure 4 will be explained in detail. The dashed box in the first column of the table shows multiple types of travel purposes. Examples of travel purposes include commuting, going to school, going home, shopping, business trips, travel to tourist destinations, and travel during sightseeing. Examples of value elements that make up desired value include punctuality, reduced travel time, reduced travel costs, avoidance of congestion, and ease of movement. Hereafter, the multiple value elements that make up desired value will be referred to as a group of value elements.

[0032] The dashed box in the second row shows the multiple value elements that make up the desired value and the score for each value element, in the case where the purpose of travel is "commuting". Specifically, the value element "Time Accuracy" is assigned a score of "3". The value element "Reduced Travel Time" is assigned a score of "3". The value element "Reduced Travel Cost" is assigned a score of "1". The value element "Avoidance of Congestion" is assigned a score of "3". The value element "Accessibility" is assigned a score of "1". These scores are numerical values ​​defined by the Likert scale. In the Likert scale, evaluation is defined numerically on a 5-point scale from 1 to 5. The closer the score is to 5, the higher the degree to which the user desires that value element. The Likert scale improves the accuracy of evaluation compared to a 3-point evaluation scale and reduces the computational load compared to an evaluation scale with 6 or more points.

[0033] In Figure 4, we focus on the desired value for a single travel objective. Here, let S be the number of value elements that constitute the desired value. S is an integer greater than or equal to 2. Assuming an S-dimensional vector space (value space) with each of the S value elements as an axis, the desired value can be represented as a vector with each of the S value elements as an axis and the score assigned to each value element as a point on the axis. In other words, the desired value for each travel objective is represented as a vector weighted according to the Likert scale for each value element. Hereafter, we will refer to the information containing multiple value elements and the score of each value element as a value element group, and the value element group in the vector space as a value element point group.

[0034] Figure 4 shows an example where each value element is scored using a Likert scale, but the method for determining the score assigned to each value element is not limited to the Likert scale. There may be only one value element for the desired value corresponding to the travel purpose. Among multiple value elements, there may be a value element with a score of zero. In the example shown in Figure 4, the desired value is uniquely determined for each travel purpose, regardless of the user's individuality.

[0035] <Example 1 of information stored in memory area 15> Figure 5 shows another example of information on travel purpose and desired value stored in the memory unit shown in Figure 2. The memory area 15 may store the table shown in Figure 5 instead of the table shown in Figure 4. The table shown in Figure 5 has an additional column for UID in the first column compared to the table shown in Figure 4. As shown in Figure 5, a score is registered for each value element group for each travel purpose, corresponding to each UID from 1 to n (where n is an integer of 1 or more). In the example shown in Figure 4, the individual user's tendencies are not reflected in the desired value, but in the example shown in Figure 5, the individual user's tendencies are reflected in the desired value for each travel purpose. Therefore, the estimation unit 21 can more accurately predict the user's subjective desired value by using the table shown in Figure 5.

[0036] Even with the same travel purpose, the desired values ​​that users prioritize can differ. Figure 5 illustrates this with a specific example, focusing on the case where the travel purpose is "commuting." User UID=1 has a time punctuality score of 3 and a travel cost reduction score of 1. In contrast, user UID=n has a time punctuality score of 4 and a travel cost reduction score of 3. It can be seen that user UID=n places more importance on time punctuality and travel cost reduction than user UID=1. When there is a strong tendency for users to consider the same travel purpose to differ in importance, the table shown in Figure 5 is more effective than the table shown in Figure 4.

[0037] An example of how to create the table shown in Figure 5 is described below. For example, the estimation unit 21 directly determines the score assigned to each value element shown in Figure 5 by obtaining responses from the user to a questionnaire in which questions to be answered on a Likert scale are pre-written. The method for determining the score of each value element is not limited to a questionnaire. The estimation unit 21 may also compare an optimal behavior model, which has been determined in advance for each travel purpose, with travel history information from GPS data, and determine the score of each value element according to predetermined rules based on the comparison results.

[0038] <Example 2 of information stored in memory area 15> Figure 6 shows another example of information regarding the purpose of movement and desired value, which is stored in the memory unit shown in Figure 2. Figure 7 shows an example of a table used in combination with the table shown in Figure 6. The memory area 15 may store the tables shown in Figures 6 and 7 instead of the table shown in Figure 4.

[0039] Figure 6 is a table where multiple types of personas (PsTs) are assumed, representing fictional character profiles, and the desired value for each travel purpose is scored for each type of PsT. Figure 7 is a table showing that n users, each assigned UID=1 to n, are assigned to multiple types of PsTs. In Figure 7, k is any integer from 1 to n. The number of types of PsTs is, for example, 5 to 10. Figure 7 shows the case where there are 10 types of PsTs, from PA to PJ. Figure 6 shows the travel purpose and desired value for types PA and PJ as PsTs. In the case of Figure 6, a list is needed to refer to which type of PsT a user belongs to, as shown in Figure 7. In the cases of Figures 6 and 7, the classification granularity is finer than the method using the table in Figure 4, but coarser than the method using the table in Figure 5, and the classification granularity is between that of Figures 4 and 5. The tables in Figures 6 and 7 are effective when the number of users is enormous.

[0040] A specific example of how each user is assigned to a Type PsT is described below. The estimation unit 21 presents the user with a questionnaire containing questions suitable for type classification, assigns the user a Type PsT based on the answers obtained from the user, and registers the Type PsT in the table shown in Figure 7 in the storage area 15, corresponding to the UID. Alternatively, the estimation unit 21 may assign each user to one of several Type PsTs based on user information according to a predetermined classification pattern. Furthermore, the estimation unit 21 may compare the optimal behavior model, which has been determined in advance for each travel purpose, with the travel history information from GPS data, and assign each user to one of several Type PsTs based on the comparison result according to a predetermined rule.

[0041] <Specific examples of information stored in memory area 13> A specific example of the information stored in memory area 13 will be explained with reference to Figure 8. Figure 8 shows an example of a service candidate list and a value proposition candidate list stored in the memory unit shown in Figure 2. Before an evaluation request is made by a transportation operator, the service candidate list and the value proposition candidate list are stored in memory area 13.

[0042] As shown in Figure 8, the service candidate list lists ancillary services actually provided by transport operators and ancillary services that are likely to be provided as candidates. The ancillary services listed as candidates are not limited to those provided by one transport operator, but may be provided by multiple transport operators. An ancillary service is described for each candidate number CDN=1 to m (where m is an integer of 2 or greater), and a list of candidate value propositions is registered after the ancillary services. In Figure 8, j is any integer from 1 to m. As shown in Figure 8, the list of candidate value propositions lists the same value elements as the value elements of the desired value explained with reference to Figures 4 to 6 as candidates. The scores of the multiple value elements that make up the value proposition are assigned by the transport operator that selected the ancillary services. Therefore, the score description column in the table shown in Figure 8 is blank.

[0043] From the service candidate list shown in Figure 8, the transportation operator requesting the evaluation selects ancillary services, and a score is assigned to each value element. This creates a service list to be stored in the memory area 14. It is desirable that many candidate ancillary services be registered in the list from the beginning so that various transportation operators can refer to the service candidate list. However, it is difficult to prepare a list in which all ancillary services are registered. Therefore, the administrator of the information processing device 1 can add new ancillary services as candidates. In this case, the estimation unit 21 adds a row to the table shown in Figure 8 by adding 1 to the last candidate number CDN=m, resulting in candidate number CDN=m+1. As will be explained later, new ancillary services may also be added to the service list by the transportation operator at the stage when the service list is created.

[0044] <Specific examples of information stored in memory area 11> A specific example of user information stored in memory area 11 will be explained with reference to Figure 9. Figure 9 is a diagram showing an example of user information stored in the memory unit shown in Figure 2. Figure 9 shows that n users have given permission to use GPS data and user information to evaluate the service. The table shown in Figure 9 describes age, gender, place of residence, place of work (or school), occupation, hobbies, and preferences, corresponding to UIDs from UID=1 to n. The user information shown in Figure 9 is just one example.

[0045] <Example of hardware configuration for control unit 5> The hardware configuration of the control unit 5 shown in Figure 2 will be explained. Figure 10 shows an example of the hardware configuration of the control unit shown in Figure 2. The control unit 5 has a memory 51 for storing a program and a processor 52 for executing processing according to the program. The processor 52 is an arithmetic circuit such as a CPU (Central Processing Unit), MPU (Micro Processing Unit), or GPU (Graphics Processing Unit). The processor 52 may be any other semiconductor device as long as it is the entity that performs the predetermined processing. The memory 51 is a non-volatile memory such as flash memory. The functions of the estimation unit 21 and the determination unit 22 are executed when the processor 52 executes the program. The memory 51 is read from the storage unit 4 by the processor 52 and stores the data necessary for arithmetic processing.

[0046] Furthermore, some or all of the functions of the control unit 5 may be executed by a dedicated circuit such as an ASIC (Application Specific Integrated Circuit). Also, although the explanation was given for the case with one processor 52, multiple processors 52 may be provided in the information processing device 1. In this case, the functions of the control unit 5 may be executed by multiple processors 52.

[0047] <Other device configurations> The hardware configuration examples for each device, server 30, transportation terminals 2-1 to 2-p, and information processing terminals 3-1 to 3-q, are the same as those described with reference to Figures 2 and 3, so a detailed explanation is omitted.

[0048] <System Configuration Variations> In this embodiment 1, the device that provides user information to the information processing device 1 is described as a server 30 that provides application software programs to the information processing terminal 3-r. However, the configuration of the server 30 is not limited to this case. The server 30 may, for example, be a device that provides services such as selling and delivering goods in response to requests received from users via the information processing terminal 3-r. The server 30 may also be a device that provides reservation services for event tickets to users, or a device that provides e-commerce services. In this case, other servers not shown in the figure may provide map information and user location information to the information processing device 1. Furthermore, the information processing device 1 may pre-store map information and user information in the storage area 11 of the storage unit 4. In this case, the server 30 may not be provided. For the purpose of explanation, the memory 51 and the storage unit 4 were described as separate configurations as storage means for storing information, but the memory 51 and the storage unit 4 may be in an integrated configuration.

[0049] <Overall operation of the mobility support system 10> The operation of the mobility support system 10 of this embodiment 1 will be described. Figure 11 is a sequence diagram showing the procedure from the evaluation request to determining the user's satisfaction with the ancillary services in the mobility support system according to embodiment 1. In step S101, the memory area 15 stores a table in which information combining the purpose of travel and the desired value is registered. In step S102, the memory area 13 stores a list of service candidates and a list of value to be provided candidates.

[0050] The operator of the transportation company operates the transportation terminal 2-h to input a request for user evaluation of the company's ancillary services. When the instruction to request user evaluation is input to the transportation terminal 2-h, it transmits evaluation request information, which is information requesting evaluation, to the server 30 (step S201). In step S202, the server 30 stores the evaluation request information received from the transportation terminal 2-h. In step S203, the transportation terminal 2-h transmits the evaluation request information to the information processing device 1. When the estimation unit 21 receives the evaluation request information from the transportation terminal 2-h, the storage area 13 provides the service candidate list and the value provision candidate list to the transportation terminal 2-h (step S204).

[0051] In step S205, when the transportation terminal 2-h receives the service candidate list and the value provision candidate list from the information processing device 1, it displays the service candidate list and the value provision list. The operator of the transportation company operates the transportation terminal 2-h to select the ancillary service they wish to have evaluated from the service candidate list, select the value provision that matches the ancillary service from the value provision list, and input a score for each value element. The transportation terminal 2-h creates a service set that combines the selected ancillary service and the value provision including the score, and transmits the created service set to the storage area 14. In step S206, when the storage area 14 receives service sets from each of the transportation terminals 2-1 to 2-p, it stores a service list listing these multiple service sets. In this case, if the storage area 14 receives a service list containing multiple service sets from each transportation terminal 2-h, it may store a service list for each transportation company. In the following explanation, for simplicity, we will describe the case where there is only one transportation company that has requested the evaluation.

[0052] In step S207, the user of the information processing terminal 3-r operates the information processing terminal 3-r to send permission information granting permission to use location information and the answers to the questionnaire to the server 30. In step S208, when the server 30 receives the permission information and the answers to the questionnaire from the information processing terminal 3-r, it assigns a UID to the user and extracts user information from the answers to the questionnaire. The server 30 sends the dataset of UID and user information to the storage area 11 of the storage unit 4. In step S209, the storage area 11 stores the dataset of UID and user information.

[0053] In step S210, the server 30 acquires GPS data from each of the information processing terminals 3-r from information processing terminals 3-1 to 3-q. For example, the server 30 acquires GPS data from the information processing terminals 3-r at a fixed interval tp every day. The interval tp is, for example, 1 minute. Every day, at a predetermined time Tpd, the server 30 transmits one day's worth of GPS data for each UID to the storage area 12 of the storage unit 4. The time Tpd is, for example, midnight. In step S211, the storage area 12 stores one day's worth of GPS data corresponding to the UID. Once the storage area 12 has stored one day's worth of GPS data corresponding to the UID, it transmits storage completion information to the estimation unit 21 indicating that data storage is complete. Hereinafter, the history information of a predetermined time for each user's GPS data will be referred to as movement history information. In this embodiment, the predetermined time is 1 day (24 hours).

[0054] In step S212, when the estimation unit 21 receives the storage completion information from the storage unit 4, it queries each UID in order from the registered UIDs to the respective storage areas 11 and 12. In step S213, storage area 12 uses the queried UID as the search target and transmits the movement history information stored in association with the search target UID to the estimation unit 21. In step S214, storage area 11 uses the queried UID as the search target and transmits the user information stored in association with the search target UID to the estimation unit 21.

[0055] In step S215, the estimation unit 21 estimates the means of transportation used by the user based on the user information received from the storage area 11 and the travel history information received from the storage area 12. In step S216, the estimation unit 21 estimates the purpose of travel based on the user information and the travel history information. The estimation unit 21 queries the storage area 15 for the estimated purpose of travel. In step S217, when the storage area 15 receives a query for the purpose of travel from the estimation unit 21, it refers to the stored table, reads out the desired value information corresponding to the purpose of travel, and transmits it to the estimation unit 21. In step S218, the estimation unit 21 transmits the estimated means of travel, purpose of travel, and desired value information corresponding to the UID to the determination unit 22.

[0056] In step S219, the determination unit 22 queries the memory area 14 for ancillary services corresponding to the estimated desired value. In step S220, the memory area 14 reads a service set, which is a combination of ancillary services and the value provided, from the service list and transmits it to the determination unit 22. In step S221, when the determination unit 22 receives the service set from the memory area 14, it calculates the degree of match between the desired value estimated by the estimation unit 21 and the value provided included in the received service set. The calculated degree of match indicates the user's satisfaction with the ancillary service being evaluated. A higher degree of match means that the user is satisfied.

[0057] Figure 12 is a sequence diagram showing an example of the operation of the information processing device according to Embodiment 1, which seeks to achieve overall user satisfaction from various perspectives for services provided by a transportation operator.

[0058] (Average satisfaction level of all users who use the mode of transportation being evaluated) In step S301, the determination unit 22 calculates the statistical average of the above-mentioned degree of matching for all users who used the means of transportation under evaluation, based on the data of all users who used the means of transportation under evaluation. In step S302, the determination unit 22 transmits the information of the statistical average of the degree of matching for the means of transportation under evaluation to the transportation terminal 2-h.

[0059] (Average satisfaction level of all users who use the ancillary services being evaluated) In step S303, the determination unit 22 calculates the statistical average of the above-mentioned degree of matching for all users who used the ancillary service under evaluation, based on the data of all users who used the ancillary service under evaluation. In step S304, the determination unit 22 transmits the information of the statistical average of the above-mentioned degree of matching for the ancillary service under evaluation to the transportation terminal 2-h.

[0060] (Average user satisfaction with transportation integration) In step S305, the determination unit 22 calculates the average satisfaction level of all users with transportation arrangements that include travel using the transportation method under evaluation in the travel route. Specifically, the determination unit 22 performs statistical processing on all users regarding the degree of match based on travel data that includes travel events using the transportation method under evaluation. In step S306, the determination unit 22 transmits the statistical average value of the degree of match for travel that includes travel events using the transportation method under evaluation to the transportation terminal 2-h. For example, consider a case where the transportation method under evaluation is a bus, and a user transfers from a bus to a taxi on their way home. In this case, the travel route home consists of travel events using a bus and travel events using a taxi. Thus, travel that includes travel events using the transportation method under evaluation becomes the subject of the degree of match calculation by the determination unit 22.

[0061] (Other examples of information provided to transportation operators) In step S307, the determination unit 22 performs a matching analysis to determine the distribution of travel purposes for each ancillary service and the matching variance within the same travel event. In step S308, the determination unit 22 transmits the matching analysis results for the ancillary service being evaluated to the transportation terminal 2-h. In this way, the information processing device 1 provides the transportation operator with information that can be used to analyze the factors contributing to user satisfaction and to provide hints for service design.

[0062] In step S309, when the transportation terminal 2-h receives information on multiple degrees of matching from the information processing device 1, it performs a current situation analysis and simulation to predict user satisfaction. If the transportation terminal 2-h has a service redesign function, it repeatedly performs the processing after the evaluation request to the information processing device 1 to verify the service (step S310).

[0063] <Operation of Information Processing Device 1> (Specific example of the process in steps S204 to S205 shown in Figure 11) This section describes the operation by which the information processing device 1 creates a service list containing the service set selected by the transportation operator. Here, the explanation assumes that the transportation operator is XX Bus Company. Figure 13 is a flowchart showing an example of the procedure for creating a service list stored in the memory unit shown in Figure 2.

[0064] An operator of XX Bus Company operates their transportation terminal 2-h to establish a communication connection between the transportation terminal 2-h and the information processing device 1. In step S401, when the estimation unit 21 of the information processing device 1 receives a connection request from the transportation terminal 2-h, it establishes a communication connection with the transportation terminal 2-h. In step S402, the estimation unit 21 provides the transportation terminal 2-h with two lists: a service candidate list and a value provision candidate list. The operator of XX Bus Company operates the transportation terminal 2-h to select an ancillary service provided by their company from the service candidate list, select a value provision from the value provision candidate list for the selected ancillary service, and input the score for each value element of the selected value provision. The operation of the estimation unit 21 in response to input from the transportation terminal 2-h will be described below.

[0065] The estimation unit 21 sets candidate number CDN to 1 in the service candidate list (step S403) and determines whether the ancillary service with candidate number CDN=1 has been selected as an ancillary service of XX Bus Company (step S404). If the determination in step S404 shows that the ancillary service with candidate number CDN=1 has not been selected as an ancillary service of XX Bus Company, the estimation unit 21 adds 1 to candidate number CDN (step S405) and returns to the process in step S404. On the other hand, if the ancillary service with candidate number CDN=1 has been selected as an ancillary service of XX Bus Company, the estimation unit 21 proceeds to the process in step S406. In step S406, the estimation unit 21 creates a service set including the ancillary service, the value provided, and the score, once the score for each value element of the value provided by XX Bus Company has been input for the ancillary service with candidate number CDN=1. The estimation unit 21 creates a service list of XX Bus Company by listing the created service sets.

[0066] In step S407, the estimation unit 21 determines whether the candidate number CDN has reached the maximum value of the candidate number, m. If the result of the determination in step S407 is that candidate number CDN ≠ m, the estimation unit 21 adds 1 to candidate number CDN (step S405) and returns to the process in step S404. On the other hand, if the result of the determination in step S407 is that candidate number CDN = m, the estimation unit 21 proceeds to the process in step S408. In step S408, the estimation unit 21 determines whether there is a request for additional ancillary services from the transportation terminal 2-h.

[0067] If the determination in step S408 indicates a request for additional ancillary services, the estimation unit 21 receives information on the ancillary services, value provided, and score from the transportation terminal 2-h, and creates a service set based on the received information. The estimation unit 21 then adds the created service set to the service list of XX Bus Company (step S409). The estimation unit 21 executes the process in step S409 according to the number of ancillary services to be added. If the determination in step S408 indicates no request for additional ancillary services or if the addition of ancillary services is completed, the estimation unit 21 stores the service list of XX Bus Company in the storage area 14 of the storage unit 4 (step S410). In this way, a service list listing service sets of ancillary services, value provided, and score is stored in the storage area 14 for each of the multiple transportation companies.

[0068] Figure 14 shows an example of a service list created in step S410 shown in Figure 13. The list shown in Figure 14 is stored in memory area 14 as the service list for XX Bus Company. In Figure 14, multiple ancillary services are described in the first column, indicated by the dashed box. If the ancillary service is "increase in the number of morning buses," the expected effect is congestion avoidance. Therefore, as shown in Figure 14, the score of the value element "congestion avoidance" is 3.

[0069] The value provided by ancillary services is represented by a point in a space common to the vector space (value space) explained with reference to Figure 4. As in the case of Figure 4, let S be the number of value elements that make up the value provided. Assuming an S-dimensional vector space with each of the S value elements as an axis, the value provided is represented by a vector with each of the S value elements as an axis and the score assigned to each value element as a point on the axis.

[0070] Operators of XX Bus Company can add or remove service sets from the service list and modify scores in accordance with the ancillary services currently offered by their company. Operators of XX Bus Company may also register ancillary services in the service list that are not currently offered to users but may be offered in the future. In this case, XX Bus Company can obtain simulation results from the information processing device 1 showing how satisfied users would be if they were offered the unprovided ancillary services.

[0071] The desired value explained with reference to Figure 4 and the offered value shown in Figure 14 are represented in the same value space. Therefore, the determination unit 22 can extract ancillary services of the offered value that approximate the desired value by comparing the scores of multiple value elements of both the desired value and the offered value. For example, the scores of each value element of the multiple value elements when the purpose of travel is "shopping" as shown in Figure 4 are similar to the scores of each value element of the multiple value elements when the ancillary service is "contactless payment" as shown in Figure 14. If the estimation unit 21 estimates the user's purpose of travel as "shopping," the determination unit 22 extracts "contactless payment" as an ancillary service corresponding to the desired value. The method for determining the approximation between the group of value elements representing the desired value and the group of value elements representing the offered value is not limited. For example, the determination unit 22 compares the respective group of value elements of the desired value and the offered value. The determination unit 22 determines that the values ​​are similar if the number of value elements with the same score is greater than or equal to a predetermined threshold Kth, and determines that they are not similar if the number of value elements with the same score is less than the threshold Kth.

[0072] (Specific example of the process shown in steps S211 to S218 in Figure 11) The procedure for the information processing device 1 to estimate the daily movement of each user based on user information and movement history information is described below. Figures 15 and 16 are flowcharts showing an example of the procedure for the information processing device according to Embodiment 1 to estimate the daily movement of each user.

[0073] Each information processing terminal 3-r in information processing terminals 3-1 to 3-q acquires GPS data at regular intervals tp once it starts using the location notification service. Each information processing terminal 3-r sequentially transmits the GPS data acquired at regular intervals tp to the server 30. The server 30 receives GPS data from each information processing terminal 3-r at regular intervals tp and stores one day's worth of GPS data for each information processing terminal 3-r. The server 30 assigns a UID to the movement history information, which is one day's worth of GPS data for each information processing terminal 3-r. The server 30 then transmits the movement history information of each information processing terminal 3-r, with the assigned UID, to the information processing device 1 at midnight, when the date changes from the day the GPS data was acquired to the next day. The information processing device 1 stores the movement history information of each information processing terminal 3-r along with the UID in the storage area 12 of the storage unit 4. The storage area 12 transmits a data storage completion signal to the estimation unit 21, indicating that the storage of the movement history information of each information processing terminal 3-r has been completed.

[0074] In step S501 shown in Figure 15, the estimation unit 21 receives a data saving completion signal from the storage area 12. In step S502, the estimation unit 21 acquires map information from the server 30. In step S503, the estimation unit 21 sets the UID to be evaluated to 1. In step S504, the estimation unit 21 uses UID=1 as a search key to acquire GPS data corresponding to UID=1 from the storage area 12. Here, the estimation unit 21 acquires GPS data sequentially, starting from the time T when the position was measured, which is 00:01 AM.

[0075] Figure 17 shows an example of movement history information stored in the memory unit shown in Figure 2. The table in Figure 17 shows an example of the state in which each user's movement history information is transferred from the server 30 to the information processing device 1 and stored in the memory area 12 of the memory unit 4. The "20240301" written at the top of the table in Figure 17 means that the date the GPS data was acquired is March 1, 2024. In the table in Figure 17, latitude and longitude information is recorded for each time T when the position was measured, corresponding to the UID from UID=1 to n. The GPS data in Figure 17 does not include altitude information, but it may include altitude information.

[0076] Note that while Figure 17 shows all users' GPS data corresponding to their UIDs and in chronological order of time T, the method of recording GPS data is not limited to the method shown in Figure 17. As long as latitude, longitude, and time T are associated with each UID, the method of recording GPS data does not have to be the method shown in Figure 17. Also, the period tp for server 30 to acquire GPS data from each of the information processing terminals 3-1 to 3-q is not limited to 1 minute. The time Tpd for server 30 to transfer the movement history information of each terminal to the information processing device 1 is not limited to midnight. The administrator of the information processing device 1 may freely set the period tp and time Tpd, taking into consideration factors such as the position resolution and the amount of GPS data required for movement estimation.

[0077] Let's return to the explanation of the flow shown in Figure 15. In step S505, the estimation unit 21 determines the user's movement based on GPS data acquired from the memory area 12. Specifically, the estimation unit 21 determines the user's actions, such as movement between different locations and dwell time at the same location, from multiple GPS data. For example, the estimation unit 21 determines whether there is a dwell time of more than a predetermined threshold time in one movement path. The threshold time is, for example, 15 seconds to 10 minutes. If the estimation unit 21 determines that there is a dwell time at point XY3, which is in the middle of the movement path from point XY1 to point XY2, it separates the movement along this movement path into two movements. Of the two separated movements, the first is the movement from point XY1 to point XY3, and the second is the movement from point XY3 to point XY2. In this way, when one movement is separated into multiple movements, each separated movement will be referred to as a movement event. Furthermore, the procedure described below will be explained in the case where the estimation unit 21 determines that there are multiple movement events.

[0078] In step S506, the estimation unit 21 determines whether the time T of the acquired GPS data for the user with UID=1 is T=Tend. Tend is the time when the location information was last measured during the day. In other words, Tend means 23:59. If the result of the determination in step S506 is T≠Tend, the estimation unit 21 returns to the process in step S504. If the result of the determination in step S506 is T=Tend, the estimation unit 21 proceeds to the process in step S507.

[0079] In step S507, the estimation unit 21 stores additional information about the determined movement in the storage unit 4, corresponding to the target UID. The additional information includes information on multiple movement events and one or more dwell times. For example, based on the movement history information, the estimation unit 21 assigns a different identifier to each of the multiple movement events in order to identify each movement event, and creates a table that records information on the dwell time between movement events and the position fluctuations during dwell time. Position fluctuations refer to the amount of change in position relative to the dwell location. In step S508, the estimation unit 21 compares the multiple movement events with map information and estimates the means of transportation used by the user for each of the multiple movement events. Specific examples of the estimation method will be described later.

[0080] In step S509, the estimation unit 21 retrieves user information corresponding to the target UID from the storage area 11. In step S510, the estimation unit 21 estimates the user's purpose of travel based on the user information retrieved from the storage area 11 and the processing result of step S505. If a single trip is classified into multiple travel events, the estimation unit 21 estimates the purpose of travel for each travel event. For example, if the estimation unit 21 refers to the user information and determines that location XY1 corresponds to the user's place of residence and location XY2 corresponds to the user's place of commute, it estimates the purpose of travel from location XY1 to location XY2 to be "commuting". In step S511, the estimation unit 21 refers to a table stored in the storage area 15 and identifies the desired value corresponding to the estimated purpose of travel. Specifically, the estimation unit 21 reads a group of value elements corresponding to the purpose of travel and the score of each value element from the table stored in the storage area 15.

[0081] In step S512, the estimation unit 21 estimates a hierarchical structure of multiple movement events based on the movement purpose estimated for each of the multiple movement events. The hierarchical structure is explained below. Assume that point XY1 is the starting point of the movement, point XY2 is the destination, and that the user stays at point XY3, which is along the movement path from point XY1 to point XY2. The movement from point XY1 to point XY3 is denoted as movement event OD1, and the movement from point XY3 to point XY2 is denoted as movement event OD2. OD1 and OD2 are different identifiers for each movement or movement event. In this case, the movement from the starting point to the destination is represented in a hierarchical structure with movement event OD1 as the upper level and movement event OD2 as the lower level. When the movement of a user from the starting point to the destination is classified into multiple movement events, the multiple movement events are represented in a step-like manner from the upper to the lower levels. When a hierarchical structure is represented by a graph with the vertical axis representing the hierarchy and the horizontal axis representing time, the length along the horizontal axis between the upper and lower levels of the hierarchy corresponds to the dwell time at point XY3. Specific examples of hierarchical structures will be explained later.

[0082] In step S513, the estimation unit 21 performs corrections on the overall movement and multiple movement events to reflect the influence of the movement purpose on each other. A specific example of this process will be explained later. Note that the processes in steps S512 and S513 are not mandatory. If the estimation unit 21 does not separate the user's movement into multiple movement events, it may omit the processes in steps S512 and S513.

[0083] In step S514, the estimation unit 21 associates the target UID and transmits the estimation result to the determination unit 22. The estimation result is information about the estimated movement, the purpose of the movement, and the desired value. If the movement is classified into multiple movement events, the estimation result is information about the means of movement, the purpose of the movement, and the desired value for each movement event. Alternatively, instead of directly transmitting the estimation result to the determination unit 22, the estimation unit 21 may store the estimation result in the storage unit 4 and notify the determination unit 22 that the estimation result has been stored in the storage unit 4. In step S515, the estimation unit 21 determines whether UID = UIDend or not. UIDend is the last number of the UID assigned to the user. In this embodiment, UIDend = n. If the result of the determination in step S515 is UID ≠ UIDend, the estimation unit 21 adds 1 to the UID (step S516) and returns to the process in step S504. If the result of the determination in step S515 is UID=UIDend, the estimation unit 21 terminates the process.

[0084] (A specific example of the process in step S507 shown in Figure 15) Figure 18 is a table showing an example of additional information created based on the movement history information in the process of step S507 shown in Figure 15. Figure 18 shows an example of additional information when a portion of a user's movement is separated into v movement events based on the movement history information of the user with UID=k. k is any integer from 1 to n. v is an integer of 2 or more. As shown in Figure 18, the movement of the user with UID=k is classified into multiple movement events OD1 to ODv, and GPS data is recorded in the table corresponding to each movement event OD. In steps S508 shown in Figure 15 and step S510 shown in Figure 16, the estimation unit 21 utilizes the additional information shown in Figure 18 when estimating the means of movement and the purpose of movement.

[0085] The data area for the additional information shown in Figure 18 contains time-series information on the latitude and longitude between the departure point (O) and destination (D) of the movement. Furthermore, for each location of the departure point (O) and destination (D), data on the time spent and data on the positional fluctuations of latitude and longitude are also included. Latitude positional fluctuation is the amount of change in position in the latitudinal direction. Longitude positional fluctuation is the amount of change in position in the longitude direction. In Figure 18, latitude positional fluctuation is denoted as ΔLa, and the value of latitude positional fluctuation converted to distance (in meters) is shown. Similarly, longitude positional fluctuation is denoted as ΔLo, and the value of longitude positional fluctuation converted to distance (in meters) is shown. At the departure point (O1) of movement event OD1, the time spent was 10 hours and 05 minutes, the longitude positional fluctuation was 10.2 m, and the latitude positional fluctuation was 2.7 m. The departure point (O1) of the movement event OD1 is presumed to be the user's place of residence, given that the movement started at 8:31.

[0086] In step S507, the estimation unit 21 extracts information on the dwell time and position fluctuations of the departure point (O) and destination (D) of the movement from the user's movement history information. For example, as a method for estimating the dwell time, the estimation unit 21 estimates the dwell time as the time when the latitude and longitude do not change over time. Alternatively, as a method for determining the user's behavior, a threshold distance may be set in advance for the likelihood of movement per unit time. In this case, the estimation unit 21 determines that the movement is dwelling if the amount of position fluctuation per unit time is less than or equal to the threshold, and determines that the movement is moving if the amount of position fluctuation per unit time is greater than the threshold. The method for measuring the dwell time and determining the user's behavior are not limited to these methods. The method for measuring the dwell time and determining the user's behavior may be defined by publicly available methods. For each UID, the estimation unit 21 creates additional information using the movement history information associated with the UID. The estimation unit 21 stores the created additional information in the storage area 12. The information added to the movement history information is information that characterizes the user's actions before and after movement. Therefore, by using this additional information, the estimation unit 21 can more easily grasp the user's behavioral tendencies, and the accuracy of estimating the purpose of movement improves.

[0087] (A specific example of the process in step S508 shown in Figure 16) In step S508, the estimation unit 21 compares the travel history information shown in Figure 18 with the map information to estimate the mode of transportation used by the user. An example of the estimation method is described below. When the estimation unit 21 determines that travel has occurred between two points, it calculates the average speed of the mode of transportation along the travel route. If the calculated average speed is less than or equal to a predetermined threshold speed Vth, and the travel route matches a predetermined bus route BL for route buses, the estimation unit 21 estimates the mode of transportation to be a bus. On the other hand, if the calculated average speed is greater than the threshold speed Vth, or if the travel route is different from the bus route BL, the estimation unit 21 estimates the mode of transportation to be a taxi.

[0088] (Specific example of the process in step S510 shown in Figure 16) In step S510, the estimation unit 21 refers to the travel history information, user information, and map information shown in Figure 18 to estimate the user's travel purpose. User information includes, for example, information on place of residence, place of work, occupation, hobbies, and preferences. An example of the estimation method is described below. The estimation unit 21 compares information on two points, the departure point and the destination of the travel, with the map information to determine buildings or facilities at the two points. Based on the information on buildings or facilities at the two determined points and the user information, the estimation unit 21 estimates the user's travel purpose. For example, if the departure point is "place of residence" and the destination is "place of work," the estimation unit 21 estimates the travel purpose to be "commuting." If the departure point is "place of residence," the destination is "gym," and the user's hobby is "exercise," the estimation unit 21 estimates the travel purpose to be "hobby."

[0089] (A specific example of the process in step S511 shown in Figure 16) In step S511, the estimation unit 21 refers to the tables stored in the memory area 15 and identifies the desired value corresponding to the travel purpose estimated in step S510. In this embodiment 1, there are three types of tables stored in the memory area 15: the table shown in Figure 4, the UID-specific table shown in Figure 5, and the persona-specific tables shown in Figures 6 and 7. Each of the three types of tables contains information on the desired value for each travel purpose.

[0090] When the estimation unit 21 uses the table shown in Figure 4, it identifies the desired value corresponding to the estimated travel purpose and reads the value elements that constitute the desired value and the score of each value element from the table. When the estimation unit 21 uses the table shown in Figure 5, it uses the UID and travel purpose as search keys to identify the desired value corresponding to the UID and travel purpose and reads the value elements that constitute the desired value and the score of each value element from the table. The case where the estimation unit 21 uses the tables shown in Figures 6 and 7 will be explained. The estimation unit 21 refers to the table shown in Figure 7 and selects the persona type PsT using the UID as the search key. Next, the estimation unit 21 uses the confirmed type PsT and travel purpose as search keys to identify the desired value corresponding to type Pst and travel purpose in the table shown in Figure 6. Then, the estimation unit 21 reads the multiple value element groups that constitute the identified desired value and the score of each value element from the table shown in Figure 6.

[0091] (Specific example of the process shown in steps S512 to S513 in Figure 16) The multiple travel events recorded in the table shown in Figure 18 do not necessarily form a series relationship based on a single travel purpose. A series relationship is one in which, even if a travel event is separated into multiple travel events due to a dwell time during the journey, the multiple travel events do not have any travel purposes other than a common travel purpose. For example, if a user experiences a dwell time due to changing modes of transport during their journey from their workplace to their home, the estimation unit 21 separates the journey into multiple travel events, but the travel purpose of these multiple travel events is "returning home."

[0092] An example of a case where multiple movement events are not related in a series will be explained with reference to Figure 19. Figure 19 is a diagram that shows an example of a case where multiple movement events are represented in a hierarchical structure. The upper part of Figure 19 is a graph in which the horizontal axis is time T, and the vertical axis shows the location and dwell time of the user at each time T from T1 to T6. The lower part of Figure 19 is a diagram created based on the graph in the upper part, representing the user's movement in a hierarchical structure.

[0093] The upper graph in Figure 19 shows a time-series representation of a user's journey home from work via a hospital and a shopping center (SC). Figure 19 illustrates a case where a user visited a hospital for a medical examination and shopped at an SC along their route home from work. The user's overall movement can be categorized into three events: travel from work to hospital (times T2-T1), travel from hospital to SC (times T4-T3), and travel from SC to residence (times T6-T5). The time spent at the hospital (times T3-T2) is 1 hour. The time spent at the SC (times T5-T4) is 1 hour.

[0094] The multiple movement events shown in the upper graph of Figure 19 are arranged in a step-like fashion, with movement events OD1 to OD3 each on different levels, as shown in the hierarchical structure of the lower part of Figure 19. In the hierarchical structure, the overall movement OD4 is represented at the lowest level. The movement trajectories of the three movement events OD1 to OD3 overlap with the movement trajectory of movement OD4. The hierarchical structure is a nested structure in which multiple movement events OD1 to OD3 are fitted into the large frame of movement OD4 without overlapping with other events. The purpose of movement event OD1 is "medical examination" at the hospital. The purpose of movement event OD2 is "shopping". The purpose of movement events OD3 and OD4 is "returning home". However, as mentioned above, since the movement trajectories of movement events OD1 and OD2 overlap with the movement trajectory of movement OD4, movement events OD1 and OD2 also include "returning home" as a purpose of movement.

[0095] Since the multiple movement events OD1 and OD2 have different movement objectives than the overall movement OD4, it is considered that movement OD4 and each of the multiple movement events OD1 to OD3 influence each other's desired value groups. Therefore, when a single movement is represented in a hierarchical structure composed of multiple movement events, it is desirable for the estimation unit 21 to perform corrections that reflect the influence of other movements or the movement objectives of movement events OD on the desired value of the movement and each movement event OD. An example of the correction performed by the estimation unit 21 is described below.

[0096] For a movement or movement event ODi, the group of value elements consisting of multiple value elements j is denoted as {VODij}. In this case, for each movement event OD1 to OD3, the group of value elements for the desired value when influenced by the movement events of other movements or movement events is expressed by equations (1) to (3). For movement OD4, the group of value elements for the desired value when influenced by other movement events is expressed by equation (4).

[0097] {VOD1j}final={VOD1j}initial+f*[{VOD4j}initial-{VOD1j}initial] ···(1) {VOD2j}final={VOD2j}initial+f*[{VOD4j}initial-{VOD2j}initial] ···(2) {VOD3j}final={VOD3j}initial+f*[{VOD4j}initial-{VOD3j}initial] ···(3)

[0098] {VOD4j}final={VOD4j}initial+g*(T2-T1) / (T6-T1)*[{VOD1j}initial-{VOD4j}initial]+g*(T4-T3) / (T6-T1)*[{VOD2j}initial-{VOD4j}initial]+g*(T6-T5) / (T6-T1)*[{VOD3j}initial-{VOD4j}initial] ...(4)

[0099] In equations (1) to (4), "initial" refers to the value of the value element before it is affected by the purpose of other movements or movement events. "Final" refers to the value of the value element after it has been affected by the purpose of other movements or movement events. f and g are weight constants. The weight constants f and g are arbitrary values ​​in the range of 0 to 1. The weight constant f is determined by the degree to which the purpose of the overall movement OD4 has an influence on movement events OD1 to OD3. The weight constant g is determined by the degree to which the purpose of movement events OD1 to OD3 has an influence on the overall movement OD4. The larger the values ​​of the weight constants f and g, the greater the influence on the desired value of the movement or movement event being sought.

[0100] Equations (1) to (3) show that each value element of the desired value for each movement event OD1 to OD3 reflects the influence of the movement purpose of movement OD4. Equation (4) shows that each value element of the desired value of the overall movement OD4 reflects the influence of the movement purposes of each of the multiple movement events OD1 to OD3. Therefore, the accuracy of estimating the user's desired value is improved. Whether the weight constants f and g are set to the "same value" or "different values" is determined by whether or not the primary purpose of "returning home" is considered equivalent to the secondary purpose of "medical examination" or "shopping" on the way home. The correction method described above is just one example, and the correction method is not limited to the method described above. If there is a correction model that is more suitable for the actual situation, it is desirable for the estimation unit 21 to adopt that correction model.

[0101] (Specific example of the estimation result in step S514 shown in Figure 16) Figure 20 shows an example of the output of the means of transportation, purpose of travel, and desired value for each travel, estimated by the estimation unit shown in Figure 2. Travel OD1 to OD3 shown in Figure 20 do not correspond to travel events OD1 to OD3 shown in Figure 19. As shown in Figure 20, the means of transportation, purpose of travel, and desired value are estimated for each travel of Travel OD1 to OD3. If it is estimated that multiple means of transportation were used by the user for a single travel OD, different means of transportation are listed in each of the multiple lines of the same travel OD, as shown in Figure 20. For example, in the case of travel OD1, the purpose of travel and desired value are listed for each of the two means of transportation: XX bus and YY taxi. In the case of travel OD2, four types of means of transportation are estimated. In the case of travel OD3, one type of means of transportation is estimated.

[0102] (Specific example of the process shown in steps S219 to S221 in Figure 11) The operation of the determination unit 22 in steps S219 to S221 shown in Figure 11 will be explained. Here, the explanation is given for the case where multiple means of movement are estimated by the estimation unit 21, as shown in Figure 20, but only one means of movement may be estimated. Figure 21 is a flowchart showing an example of the operation procedure by the determination unit shown in Figure 2.

[0103] In step S601, the determination unit 22 receives the estimation result from the estimation unit 21. In step S602-1, the determination unit 22 extracts the desired value corresponding to the estimated means of transportation from the estimation result. A specific example will be explained with reference to Figure 20. If the means of transportation is estimated to be "XX bus" by the estimation unit 21, in Figure 20, the determination unit 22 extracts the desired value corresponding to the means of transportation "XX bus" for each of the travel events OD1 and OD2. Furthermore, if the purpose of travel is estimated to be "returning home" by the estimation unit 21, the determination unit 22 extracts the desired value corresponding to the means of transportation "XX bus" for travel event OD1. In this way, the determination unit 22 extracts the user's desired value from the estimation result. The value elements representing the desired value can be seen in the value space as a number of points that represent the value that the user seeks from the ancillary service being evaluated. Here, the case where the determination unit 22 extracts the desired value from the table shown in Figure 20 using the means of transportation and the purpose of travel as extraction conditions has been explained, but the extraction conditions may be either the means of transportation or the purpose of travel.

[0104] In step S602-2, the determination unit 22 obtains a service list corresponding to the estimated means of transportation from the storage area 14. In step S603, the determination unit 22 compares the extracted desired value with the value provided by each service set in the service list and extracts ancillary services corresponding to the desired value. The specific processing method is explained below. As described above, the value element group representing the desired value is perceived in the value space as a number of points that represent the value that the user seeks from the ancillary service being evaluated. Similar to the desired value, the value element group representing the value provided is perceived in the value space as a number of points that represent the value that the transportation operator provides to the user. Therefore, the determination unit 22 extracts ancillary services with a value that approximates the desired value from the service list by making an approximate determination between the value element point group representing the desired value and the value element point group representing the value provided by each service set in the same value space. In step S604, the determination unit 22 selects a service set containing the extracted ancillary services from the service list.

[0105] In step S605, the determination unit 22 determines the degree of match between the value provided in the service set selected from the service list and the desired value estimated by the estimation unit 21. Specifically, the determination unit 22 assumes a vector space common to the desired value and the value provided, and uses a predetermined calculation formula to calculate the average distance between the value element point group representing the desired value and the value element point group representing the value provided. The calculation formula is, for example, formula (5).

[0106]

number

[0107] In equation (5), i is the readout point for the score assigned to the value element of the desired value in the vector space. j is the readout point for the score assigned to the value element of the offered value in the vector space. a, b, ..., X are the dimensions of the multiple value elements in the vector space. X corresponds to the final dimension. Note that equation (5) shows the case where the degree of match between the desired value and the offered value is expressed as an average distance defined by the Euclidean distance, but the formula for calculating the degree of match is not limited to equation (5).

[0108] When the value element point cluster representing desired value and the value element point cluster representing the value provided perfectly coincide, the user's desired value is met. In this case, it means the user is highly satisfied. On the other hand, when the value element point cluster representing desired value and the value element point cluster representing the value provided do not coincide, and the distance between these point clusters is large, the user's desired value is not met. In this case, it means the user is less satisfied.

[0109] Equation (5) is an example in which the average distance of all points in each value element point group is used to quantify the degree of agreement between the desired value and the value provided. The degree of agreement obtained by equation (5) represents the Euclidean distance between each point in the value element point group representing the desired value and the value term point group representing the value provided. The obtained degree of agreement represents the user's satisfaction with the ancillary service being evaluated. In step S606, the determination unit 22 outputs the degree of agreement obtained in step S605 to the transportation terminal 2-h as the user's satisfaction with the ancillary service being evaluated.

[0110] (Specific examples of the processes in steps S301 to S308 shown in Figure 12) Referring to Figure 11, we have explained a case where the determination unit 22 calculates the average distance between the value element point cloud of the desired value and the value element point cloud of the provided value in a common value space as the user's satisfaction with the ancillary services. However, user satisfaction may be determined from a different perspective.

[0111] For example, consider a case where a transportation operator evaluates which of several ancillary services is most effective for the majority of users. In this case, in step S303 shown in Figure 12, the determination unit 22 calculates the statistical average of the degree of agreement for all users for each of the multiple ancillary services being evaluated, according to the flow shown in Figure 21. In step S304, the determination unit 22 transmits the statistical average of the degree of agreement for all users for each of the multiple ancillary services to the transportation terminal 2-h as information indicating the average satisfaction level of all users for each of the multiple ancillary services. The transportation terminal 2-h displays the information indicating the average satisfaction level of all users for each of the multiple ancillary services. By referring to the information displayed by the transportation terminal 2-h, the operator of the transportation operator can determine which of the multiple ancillary services is most effective for the majority of users. This information is useful for the transportation operator in considering what kind of ancillary services to design and provide to users.

[0112] Let's consider the case where we evaluate user satisfaction with transportation coordination that includes travel using the transportation method under evaluation in the travel route. In this case, in step S305, the determination unit 22 extracts all travel events including travel using the transportation method under evaluation from, for example, the table shown in Figure 20, and reads out the value elements of the desired value of the extracted travel. The determination unit 22 also extracts the value elements of the value of ancillary services provided by the transportation operator operating the transportation method under evaluation from, for example, the table shown in Figure 14. Then, using the value elements of the desired value and the value elements of the provided value, the determination unit 22 calculates the statistical average of the degree of match for all users whose travel route includes travel using the transportation method under evaluation, according to the flow shown in Figure 21. In step S306, the determination unit 22 transmits the statistical average of the degree of match for all users whose travel route includes travel using the transportation method under evaluation to the transportation terminal 2-h as information indicating user satisfaction with transportation coordination. By referring to the information displayed on the transportation terminal 2-h, operators of the transportation service can determine which other modes of transportation the evaluated mode of transport should be linked to increase or decrease user satisfaction.

[0113] Furthermore, the determination unit 22 analyzes the factors influencing the satisfaction results by obtaining, for example, the frequency distribution for each user, in addition to the user satisfaction level for each evaluation target. Several examples of how the information processing device 1 performs evaluation and analysis from multiple perspectives in order to obtain information to be provided to transportation operators are described in (1) to (3) below.

[0114] (1) Average satisfaction level of all users with means of transportation (Perspective 1: Average user satisfaction with ancillary services) The determination unit 22 calculates the statistical average of the above degree of agreement for all users who used the ancillary service under evaluation, based on data from all users who used the ancillary service under evaluation. This allows transportation operators to obtain information that represents the average satisfaction level of all users of the ancillary services they provide. This information is useful for transportation operators in considering what kind of ancillary services they should design and provide to users. (Perspective 2: Average user satisfaction with a particular transportation provider) The determination unit 22 calculates the statistical average of the above degree of matching for all users who use all ancillary services provided by a specific transportation operator, based on data from all users who use all of these ancillary services. This allows transportation operators to obtain information that represents the average level of user satisfaction with their company.

[0115] (2) User satisfaction with transportation integration (Perspective: Average satisfaction level of all users per travel purpose or per travel) The determination unit 22 calculates the statistical average of the degree of matching for each travel purpose or each trip, based on the data of all users whose travel routes, including travel using the means of transportation under evaluation, are recorded. For example, in the table shown in Figure 20, if we focus on the travel purpose "returning home" when the means of transportation is a bus, the means of transportation for travel OD1 can be a bus or a taxi. Therefore, the determination unit 22 extracts data for travel purposes that include travel events using the means of transportation under evaluation from the data of all users. Also, in the table shown in Figure 20, if we focus on travel OD1, the means of transportation can be a bus or a taxi. Travel OD1 can be considered a trip in which the user transferred between two means of transportation. Therefore, if a trip consists of multiple travel events and the means of transportation under evaluation is used in at least one of the travel events, the determination unit 22 extracts data for the target trip from the data of all users. This allows transportation operators to obtain information that represents the average satisfaction level of all users who used multiple means of transportation, including their own, for a given travel event or travel purpose. This information will help transportation operators consider how their ancillary services can be integrated with services provided by other transportation operators. Furthermore, this information will help transportation operators consider whether they should design and provide services that align with users' desired value for their travel purposes.

[0116] (3)Analysis (Perspective 1: Distribution of degree of compliance with ancillary services) The determination unit 22 calculates a frequency distribution showing the degree of matching for each user who has used the ancillary service being evaluated. By using this information, the transportation operator can analyze the needs for ancillary services on a user-by-user basis. (Perspective 2: Distribution of movement events in relation to means of transportation) The determination unit 22 determines the distribution of travel events and the trend of desired value for each mode of transportation. By using this information, transportation operators can analyze the direction of the services they should provide.

[0117] Furthermore, the users whose satisfaction is measured are not limited to any one or more users, but may be specific one or more users. It is possible to narrow down the target users by using the persona type PsT. For example, a transportation company might narrow down the target users to those whose hobby is "castle visiting" and evaluate their satisfaction with an ancillary service for a "special ticket that allows repeated use of multiple types of transportation in areas where castles were built."

[0118] The output results of the information processing device 1 are transmitted to the transportation terminal 2-h via the network 100. Transportation operators can verify the effectiveness of ancillary services currently being implemented and predict the effectiveness of ancillary services they plan to adopt in the future. In addition to transmitting the output results to the transportation terminal 2-h, the information processing device 1 may also store them in the storage unit 4. The estimation unit 21 may improve the estimation accuracy by comparing the output results stored in the storage unit 4 with the results of interviews with users. Furthermore, the national or local government may use the output results stored in the storage unit 4 as basic data to predict the impact on surrounding mobility services and optimize regional urban planning.

[0119] According to the information processing device 1 of this embodiment, user information and user travel history information can be acquired, and the degree of matching for each ancillary service can be determined as user satisfaction. The information processing device 1 of this embodiment can evaluate and analyze user satisfaction with ancillary services in short time cycles while minimizing the burden on transportation operators and users. Transportation operators do not need to conduct intermittent surveys with users and can continuously acquire information necessary for service improvement from the information processing device 1. Therefore, transportation operators can continuously and effectively improve the services they provide to users. In addition, local governments, urban consultants, and block developers responsible for regional urban planning can efficiently and sustainably develop optimal transportation infrastructure, attract transportation infrastructure operators, and plan transportation infrastructure.

[0120] The information processing device 1 of this embodiment 1 has a memory 51 for storing a program and a processor 52 for executing processing according to the program. The memory 51 stores user information, which is information about users who travel using means of transportation provided by transportation operators, and travel history information of the information processing terminal 3-r carried by the user. The memory 51 stores a service list, which is a list of multiple service pairs, which are combinations of ancillary services, which are services attached to the means of transportation, and value provided, which is the value provided to the user by the ancillary services. The processor 52 executes the following processing by executing the program. Based on the user information and travel history information, the processor 52 estimates the purpose of travel and the desired value, which is the value that the user seeks for the purpose of travel. The processor 52 selects a service pair from the service list that includes ancillary services corresponding to the desired value by comparing the desired value and the value provided. The processor 52 calculates the degree of match between the desired value and the value provided included in the selected service pair. The processor 52 outputs the degree of match as the user's satisfaction with the ancillary services included in the selected service pair.

[0121] According to this embodiment 1, the user's travel purpose and desired value are estimated from user information and travel history information. By comparing the estimated desired value with the value provided by the ancillary services offered by the transportation operator, the ancillary services corresponding to the estimated travel purpose are identified. For example, if the user's travel purpose is "commuting" and the user wants to avoid congestion and delays during their commute, the value the user seeks is "avoiding congestion" and "reducing travel time." On the other hand, the ancillary services offered by the transportation operator have a defined value intended by the transportation operator. For example, the transportation operator might implement the ancillary service of "increasing the number of services" to avoid congestion and delays during commuting hours. In this case, the value intended by the ancillary service is "avoiding congestion" and "reducing travel time." User satisfaction is highest when the value the user seeks for their travel purpose matches the value intended by the ancillary services offered by the transportation operator. By comparing the user's desired value for their travel purpose with the value provided by the ancillary services, the ancillary services corresponding to the user's travel purpose are identified. Therefore, even without directly asking users about their purpose of travel through surveys or other means, the degree to which identified ancillary services match the estimated desired value is output as user satisfaction. [Examples]

[0122] This second embodiment is a configuration in which the information processing device 1 does not pre-store information combining the purpose of movement and desired value, as described in the first embodiment of the mobility support system 10. The configuration of the mobility support system in this second embodiment will be described with reference to the figures. In this second embodiment, the same reference numerals are used for the same components as in the first embodiment, and their detailed descriptions are omitted.

[0123] Figure 22 is a block diagram showing an example configuration of an information processing device according to Embodiment 2. In Embodiment 2, the estimation unit 21a estimates the desired value corresponding to the travel purpose based on the learning model, user information stored in memory area 11, and user travel history information stored in memory area 12. In addition to user information and travel history information, the estimation unit 21a may also use additional information shown in Figure 18 to estimate the desired value. The additional information includes history information for each of the multiple travel events, dwell time, location fluctuations of the departure point, and location fluctuations of the destination. In Embodiment 2, the additional information is used to estimate the desired value.

[0124] Figure 23 illustrates the case in Example 2 where the estimation unit shown in Figure 22 uses user information and movement history information as input to train a learning model that estimates the user's movement. The estimation unit 21a is equipped with an AI (Artificial Intelligence) engine that trains the learning model. The estimation unit 21a uses user information obtained from memory area 11, movement history information obtained from memory area 12, and additional information as input to train the learning model to output the purpose of movement and a set of value elements corresponding to the desired value of the purpose of movement.

[0125] If sufficient training data and training time are available, the estimation unit 21a trains a learning model for each UID. If the training data or training time is insufficient, the estimation unit 21a may train a learning model for each persona type PsT. After training the learning model, the estimation unit 21a is implemented in the control unit 5. After being implemented in the control unit 5, the estimation unit 21a estimates the purpose of travel and desired value when new user information, travel history information, and additional information are input corresponding to the UID.

[0126] In Embodiment 1, the memory unit 4 stored information such as the combination of travel purpose and desired value shown in Figure 4 in the memory area 15. In the information processing device 1 of Embodiment 2, the estimation unit 21a estimates the travel purpose and desired value from user information, travel history information, and additional information using machine learning with training data. According to Embodiment 2, the information processing device 1 does not need to pre-store information combining travel purpose and desired value, as explained with reference to Figures 4 to 7, in the memory unit 4.

[0127] The embodiments described above are illustrative for explaining the present invention and are not intended to limit the scope of the invention to those embodiments only. Those skilled in the art can implement the present invention in various other forms without departing from the scope of the invention.

[0128] Furthermore, the embodiments described above include the following items. However, the items included in these embodiments are not limited to those listed below.

[0129] (Item 1) Memory for storing programs, A processor that performs processing according to the aforementioned program, The aforementioned memory is The system stores user information, which is information about users who travel using means of transportation provided by transportation operators, and travel history information of information processing terminals carried by the users. The system stores a service list, which is a list of multiple service pairs, each consisting of an ancillary service (a service provided to the means of transport) and a value proposition (a value provided to the user by the ancillary service). The processor executes the program, Based on the user information and the travel history information, the purpose of travel and the desired value that the user seeks for that purpose of travel are estimated. By comparing the desired value with the value provided, the service set including the ancillary services corresponding to the desired value is selected from the service list. The degree of agreement between the desired value and the value provided included in the selected service set is determined. The degree of agreement is output as the user's satisfaction with the ancillary services included in the selected service set. Information processing device.

[0130] (Item 2) In the information processing device described in item 1, Each of the two values, the desired value and the offered value, is composed of multiple value elements, and these multiple value elements are identical. Information processing device. This makes it easier to determine the degree to which the value that users seek matches the value that can be obtained from the services provided by transportation operators.

[0131] (Item 3) In the information processing device described in item 2, Each of the aforementioned value elements is assigned a score based on a numerical value defined on the Likert scale. Information processing device. This assigns a numerical score to each of the multiple value elements, on a 5-point scale. In this case, the accuracy of the evaluation is improved compared to when there are 3 evaluation levels, and the computational load is reduced compared to when there are 6 or more evaluation levels.

[0132] (Item 4) In the information processing device described in item 3, The aforementioned processor, In a vector space with each of the aforementioned multiple value elements as an axis, the score assigned to each of the multiple value elements is treated as a point on the axis, and the average distance between the value element point group representing the desired value and the value element point group representing the value provided is calculated, and the calculated average distance is defined as the degree of match. Information processing device. Since the value element point clusters representing desired value and the value element point clusters representing provided value are arranged in a common vector space, the degree of agreement between desired value and provided value can be determined for each value element by comparing the distance between two points located on a common axis.

[0133] (Item 5) In the information processing device described in item 3, The aforementioned processor, If the user stays for a predetermined threshold time or longer between the departure point and destination of the aforementioned movement, the movement is separated into multiple movement events, and the purpose of the movement and the desired value are estimated for each separated movement event. The desired value of the aforementioned movement and the desired value of each of the aforementioned multiple movement events are corrected to reflect the mutual influence of the movement objectives. Information processing device. The desired value of each individual movement event among multiple movement events reflects the influence of the overall movement's purpose, and the desired value of the overall movement reflects the influence of the purpose of each of the multiple movement events. Therefore, the accuracy of estimating the user's desired value is improved.

[0134] (Item 6) In the information processing device described in any one of items 1 to 5, The aforementioned processor, If the user remains in the area between the departure point and destination of the aforementioned movement for a predetermined threshold time or longer, the movement is separated into multiple movement events. The dwell time and the amount of change in position during dwell time between the two separated movement events are determined. Information processing device. Additional information, including dwell time and changes in position during dwell time, characterizes the user's behavior before and after movement. Therefore, it becomes easier to understand the user's behavioral tendencies from this additional information, improving the accuracy of estimating their movement purpose.

[0135] (Item 7) In the information processing device described in any one of items 1 to 6, The aforementioned processor, Based on the user information and the movement history information, the means of movement is estimated. If the user remains in the area between the departure point and destination of the aforementioned movement for a predetermined threshold time or longer, the movement is separated into multiple movement events. The system calculates the degree of match for at least one of several items, including the means of movement, the purpose of movement, and the movement event, and outputs the calculated degree of match as the user satisfaction level corresponding to the at least one item. Information processing device. This allows us to determine user satisfaction from various perspectives based on the user's movement history information.

[0136] (Item 8) In the information processing device described in any one of items 1 to 7, The aforementioned memory is For each of the multiple users, the user information and the movement history information are stored in correspondence with the user identifier, which is the identifier of the user. Information processing device. This allows the processor to determine the satisfaction level of each user with respect to the ancillary services being evaluated, even if there are multiple users utilizing the transportation services provided by the transport operator.

[0137] (Item 9) In the information processing device described in any one of items 1 to 8, The user information includes at least one of the following: the user's place of residence, place of work, occupation, age, gender, hobbies, and preferences. The aforementioned ancillary services include at least one of the following: scheduling the operation of the means of transport, selling tickets for events using the means of transport, and payment methods for the use of the means of transport. Information processing device. This makes it easier for the processor to estimate the user's departure or destination for travel, as well as any ancillary services selected by the user, based on user information.

[0138] (Item 10) In the information processing device described in any one of items 1 to 9, The aforementioned memory is The system stores a list of candidate service services and a list of candidate value propositions. The aforementioned processor, When an ancillary service is selected from the service candidate list and a value proposition is selected from the value proposition candidate list in relation to the aforementioned transportation operator, a service set including the selected ancillary service and the selected value proposition is created. Information processing device. Transportation operators select ancillary services from a list of service candidates, and the value proposition corresponding to these ancillary services is selected from a list of value proposition candidates. Therefore, transportation operators do not need to consider the value proposition corresponding to the ancillary services they provide, which reduces the burden when evaluating user satisfaction.

[0139] (Item 11) In an information processing device described in any one of items 1 to 10, The aforementioned memory is The service list is stored for each of the multiple aforementioned transportation operators, The aforementioned processor, Based on the user information and the travel history information, the means of transportation used by the user is estimated. From among the multiple service lists, select the service list of the transport operator that corresponds to the estimated means of transport. Information processing device. This allows each of the multiple transportation operators to pre-register a service list containing the ancillary services they offer.

[0140] (Item 12) In the information processing device described in any one of items 1 to 11, The aforementioned memory is A table is stored in which multiple value elements constituting the desired value corresponding to the aforementioned purpose of movement are registered. The aforementioned processor, Based on the user information and the movement history information, the purpose of the movement is estimated, and the desired value is extracted from the table to represent the multiple value elements corresponding to the estimated purpose of the movement. Information processing device. Since memory stores a table that selects the desired value based on the purpose of the move, the processor only needs to select the desired value from the estimated purpose of the move. This reduces the processing load on the processor. [Explanation of Symbols]

[0141] 1 Information processing device, 2-1~2-p Transportation terminal, 3-1~3-q Information processing terminal, 4 Storage unit, 5 Control unit, 6 Input unit, 7 Output unit, 8 Communication unit, 9 Drive, 10 Mobility support system, 11~15 Memory area, 21, 21a Estimation unit, 22 Judgment unit, 30 Server, 51 Memory, 52 Processor, 90 Recording medium, 100 Network.

Claims

1. Memory for storing programs, A processor that performs processing according to the aforementioned program, The aforementioned memory is The system stores user information, which is information about users who travel using means of transportation provided by transportation operators, and travel history information of information processing terminals carried by the users. The system stores a service list, which is a list of multiple service pairs, each consisting of an ancillary service (a service provided to the means of transport) and a value proposition (a value provided to the user by the ancillary service). The processor executes the program, Based on the user information and the travel history information, the purpose of travel and the desired value that the user seeks for that purpose of travel are estimated. By comparing the desired value with the value provided, the service set including the ancillary services corresponding to the desired value is selected from the service list. The degree of agreement between the desired value and the value provided included in the selected service set is determined. The degree of agreement is output as the user's satisfaction with the ancillary services included in the selected service set. Information processing device.

2. In the information processing apparatus according to claim 1, Each of the two values, the desired value and the offered value, is composed of multiple value elements, and these multiple value elements are identical. Information processing device.

3. In the information processing apparatus according to claim 2, Each of the aforementioned value elements is assigned a score based on a numerical value defined on the Likert scale. Information processing device.

4. In the information processing apparatus described in claim 3, The aforementioned processor, In a vector space with each of the aforementioned multiple value elements as an axis, the score assigned to each of the multiple value elements is treated as a point on the axis, and the average distance between the value element point group representing the desired value and the value element point group representing the value provided is calculated, and the calculated average distance is defined as the degree of match. Information processing device.

5. In the information processing apparatus described in claim 3, The aforementioned processor, If the user stays for a predetermined threshold time or longer between the departure point and destination of the aforementioned movement, the movement is separated into multiple movement events, and the purpose of the movement and the desired value are estimated for each separated movement event. The desired value of the aforementioned movement and the desired value of each of the aforementioned multiple movement events are corrected to reflect the mutual influence of the movement objectives. Information processing device.

6. In the information processing apparatus according to claim 1, The aforementioned processor, If the user remains in the area between the departure point and destination of the aforementioned movement for a predetermined threshold time or longer, the movement is separated into multiple movement events. The dwell time and the amount of change in position during the dwell time between the two separated movement events are determined. Information processing device.

7. In the information processing apparatus according to claim 1, The aforementioned processor, Based on the user information and the movement history information, the means of movement is estimated. If the user remains in the area between the departure point and destination of the aforementioned movement for a predetermined threshold time or longer, the movement is separated into multiple movement events. The system calculates the degree of match for at least one of several items, including the means of movement, the purpose of movement, and the movement event, and outputs the calculated degree of match as the user satisfaction level corresponding to the at least one item. Information processing device.

8. In the information processing apparatus according to claim 1, The aforementioned memory is For each of the multiple users, the user information and the movement history information are stored in correspondence with the user identifier, which is the identifier of the user. Information processing device.

9. In the information processing apparatus according to claim 1, The user information includes at least one of the following: the user's place of residence, place of work, occupation, age, gender, hobbies, and preferences. The aforementioned ancillary services include at least one of the following: scheduling the operation of the means of transport, selling tickets for events using the means of transport, and payment methods for the use of the means of transport. Information processing device.

10. In the information processing apparatus according to claim 1, The aforementioned memory is The system stores a list of candidate service services and a list of candidate value propositions. The aforementioned processor, When an ancillary service is selected from the service candidate list and a value proposition is selected from the value proposition candidate list in relation to the aforementioned transportation operator, a service set including the selected ancillary service and the selected value proposition is created. Information processing device.

11. In the information processing apparatus according to claim 1, The aforementioned memory is The service list is stored for each of the multiple aforementioned transportation operators, The aforementioned processor, Based on the user information and the travel history information, the means of transportation used by the user is estimated. From among the multiple service lists, select the service list of the transport operator that corresponds to the estimated means of transport. Information processing device.

12. In the information processing apparatus according to claim 1, The aforementioned memory is A table is stored in which multiple value elements constituting the desired value corresponding to the aforementioned purpose of movement are registered. The aforementioned processor, Based on the user information and the movement history information, the purpose of the movement is estimated, and the desired value is extracted from the table to represent the multiple value elements corresponding to the estimated purpose of the movement. Information processing device.

13. An information processing method performed by an information processing device, Based on user information, which is information about users who travel using means of transportation provided by transportation operators, and travel history information from information processing terminals carried by the users, the purpose of travel and the desired value, which is the value that the user seeks for said purpose of travel, are estimated. A service list is a list in which multiple service pairs are registered, which are combinations of ancillary services, which are services attached to the means of transportation, and value provided, which is the value provided to the user by the ancillary services. The desired value and the value provided are compared with this service list. As a result of the comparison, the service set including the ancillary services corresponding to the desired value is selected from the service list. The degree of agreement between the desired value and the value provided included in the selected service set is determined. The degree of agreement is output as the user's satisfaction with the ancillary services included in the selected service set. Information processing methods.

14. On the computer, Based on user information, which is information about users who travel using means of transportation provided by transportation operators, and travel history information from information processing terminals carried by the users, the purpose of travel and the desired value, which is the value that the user seeks for said purpose of travel, are estimated. A service list is a list in which multiple service pairs are registered, which are combinations of ancillary services, which are services attached to the means of transportation, and value provided, which is the value provided to the user by the ancillary services. The desired value and the value provided are compared with this service list. As a result of the comparison, the service set including the ancillary services corresponding to the desired value is selected from the service list. The degree of agreement between the desired value and the value provided included in the selected service set is determined. The degree of agreement is output as the user's satisfaction with the ancillary services included in the selected service set. A program to be executed.

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