Information processing system and information processing method, information processing device, and program for information processing system

Abstract

The present disclosure relates to an information processing system and an information processing method, an information processing device, and a program for the information processing system that make it possible to appropriately arrange for a taxi at timing desired by a user, even without an operation by the user. According to the present invention, a camera for detecting the actions or behavior of a user is provided at a restaurant, the actions or behavior of the user are inferred by analysis of images captured by the camera, and the inference results are acquired as behavior progress information. The time at which the user will finish a meal at the restaurant and get into a taxi is predicted on the basis of the behavior progress information, conditions for a taxi to be dispatched are determined as dispatch conditions on the basis of the prediction results, the taxi is dispatched on the basis of the determined dispatch conditions, and the user is notified when the dispatch is complete. The present disclosure can be applied to a taxi dispatch system.

Description

Information processing system, information processing method for information processing system, information processing device, and program

[0001] The present disclosure relates to an information processing system, an information processing method for the information processing system, an information processing device, and a program, and in particular to an information processing system that enables a user to arrange a taxi at an appropriate timing as desired, an information processing method for the information processing system, an information processing device, and a program.

[0002] A technology has been proposed for arranging a taxi based on user operations to correct delays in a planned trip or based on changes in the GPS location of a user-owned terminal (see Patent Document 1).

[0003] Japanese Patent Application Laid-Open No. 2022-101514

[0004] However, with the technology of Patent Document 1, if a delay occurs in a planned schedule and the timing for arranging a taxi is delayed, the taxi cannot be arranged at the desired timing unless the user performs an operation to arrange a taxi at the desired timing.

[0005] Furthermore, when dispatching a taxi based on changes in the GPS location of a user's device, even if it is possible to determine from the change in location that a delay has occurred in the planned trip, it is not possible to determine whether or not the timing is right for the user to dispatch a taxi. As a result, there is a risk that a taxi cannot be dispatched at the time the user desires.

[0006] The present disclosure has been made in consideration of such circumstances, and in particular, enables a user to arrange a taxi at an appropriate timing as desired.

[0007] An information processing system, an information processing device, and a program according to one aspect of the present disclosure are an information processing system, an information processing device, and a program that include a user behavior prediction unit that predicts the behavior of a user based on the user's behavior progress information, a dispatch condition determination unit that determines the conditions for dispatching a taxi as dispatch conditions based on the prediction results of the user behavior prediction unit, and a dispatch unit that dispatches the taxi based on the dispatch conditions.

[0008] An information processing method of an information processing system according to one aspect of the present disclosure is an information processing method for an information processing system including a user behavior prediction process that predicts the behavior of a user based on the user's behavior progress information, a dispatch condition determination process that determines the conditions for a taxi to be dispatched as dispatch conditions based on the prediction results of the user behavior prediction section, and a dispatch process that dispatches the taxi based on the dispatch conditions.

[0009] In one aspect of the present disclosure, a user's behavior is predicted based on the user's behavioral progress information, and based on the prediction results, the conditions for dispatching a taxi are determined as dispatch conditions, and the taxi is dispatched based on the dispatch plan.

[0010] 1 is a diagram illustrating an overview of the present disclosure. FIG. ... example configuration of an information processing system according to a preferred embodiment of the present disclosure. FIG. 2 is a diagram illustrating an example arrangement of store sensors. FIG. 3 is a diagram illustrating user attribute information. FIG. 4 is a diagram illustrating user behavior plan information. FIG. 5 is a diagram illustrating the operation of a user behavior engine. FIG. 6 is a flowchart illustrating store reservation outbound vehicle allocation processing. FIG. 7 is a diagram illustrating an example display of a user terminal in store reservation outbound vehicle allocation processing. FIG. 8 is a flowchart illustrating return vehicle allocation processing. FIG. 9 is a flowchart illustrating predicted end time prediction processing. FIG. 10 is a diagram illustrating an example display of a user terminal in return vehicle allocation processing. FIG. 11 is a diagram illustrating an example display of a user terminal in return vehicle allocation processing. FIG. 12 is a diagram illustrating vehicle allocation innovations. FIG. 13 is a diagram illustrating an example configuration of a general-purpose computer.

[0011] Preferred embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0012] Hereinafter, embodiments of the present technology will be described in the following order.

[0013] 1. Overview of the present disclosure 2. Preferred embodiment 3. Vehicle allocation innovation 4. Example of implementation by software

[0014] <<1. Overview of the Present Disclosure>> The present disclosure is directed to, in particular, enabling a user to arrange a taxi at an appropriate timing as desired. Therefore, first, an overview of the present disclosure will be described.

[0015] For example, consider a case where a user entertains three business partners at a restaurant together with three people from his or her own company, including himself or herself.

[0016] In this case, for example, as shown in the top row of Figure 1, "(1) Make a reservation at a restaurant for, for example, six people (including your company and business partners) through a reservation site," in process 1, user H operates a mobile terminal 1 such as a smartphone to access a reservation site and make a reservation at a restaurant for six people, including three people from his company and three people from business partners, on a specified date and time.

[0017] At this time, information such as the name and address of the company to which the user belongs is registered on the reservation site during the reservation procedure, or, if the user is a repeat customer, is registered in advance.

[0018] Next, in the middle section of Figure 1, it is written "(2) Taxi dispatch proposal" and further, as shown by the notation "Would you like two taxis to be arranged for the XXX Company driveway at 18:30?", in process 2, the reservation site is linked to the taxi company's server 2, and server 2 proposes to the user to arrange a taxi required for travel to the restaurant based on the reservation date and time of the restaurant, and a taxi is arranged accordingly.

[0019] Furthermore, in the lower part of Figure 1, it is written "(3) Before the reservation time, dispatch taxis to the company's pre-set location," and as shown by the dispatch of taxis 3-1 to 3-n, in process 3, when the reservation date and time arrives, server 2 arranges for the reserved number of taxis 3-1 to 3-n to arrive at the driveway of XXX Company at a time that includes the travel time to the restaurant. Three people from the company, including the user, and three business partners travel to the restaurant in taxis 3 arranged in this way.

[0020] Next, as written in the upper part of Figure 2, "(4) Sensor detects signs of end of meal," the restaurant is equipped with a sensor 4 such as a camera that detects the behavior of customers, and in process 4, the timing of the end of the meal is detected from the behavior of six people including the user and the manner in which food is served, sensed by sensor 4, for example, whether or not the customer gets up to go to the toilet when the meal is over, and whether or not dessert, tea, etc. have been served after the meal.

[0021] Then, when the timing of finishing the meal is detected, the server 2 is notified, and as process 5, the server 2 suggests to the user's mobile terminal 1 how to arrange taxis for the return journey, as shown in the lower left part of Figure 2 as "(5) Will you need three or six taxis for the return journey?"

[0022] Then, when a response is made regarding the arrangements for a taxi for the return journey and the taxi arrangement is approved, as indicated in the lower right part of Figure 2 as "(6) If approved, a taxi will be arranged and payment for meals and drinks will be made," arrangements for a taxi for the return journey and payment for meals and drinks will be made as process 6.

[0023] Next, in the upper part of Figure 3, as indicated by "(7) Once payment is completed, a taxi is dispatched," in process 7, once payment for the restaurant 5 is completed, the server 2 arranges for a taxi 3 for the return journey.

[0024] Then, in the middle section of Figure 3, as indicated by "(8) When the taxi arrives, you will be notified," in process 8, when taxis 3-11 to 3-m are dispatched as arranged and arrive in front of the restaurant, the server 2 notifies the user's mobile terminal 1 that taxis 3-11 to 3-m have arrived in front of the restaurant 5.

[0025] According to the present disclosure, through the above series of processes, when a user makes a reservation at a restaurant, the number of taxis to reserve for the outbound journey and the location are suggested based on the reservation time, and when the reservation is made in accordance with the suggestions, a taxi is dispatched to pick up the user on the reservation date and time.

[0026] Furthermore, when the group, including the user, arrives at the reserved restaurant in the dispatched taxi and begins to eat and drink, their behavior is sensed by a sensor installed in the restaurant, and signs that the meal has ended are detected from the sensing results.

[0027] When the end of the meal is detected, the number of taxis to reserve for the return journey is suggested, and if the taxi arrangement is approved in accordance with the suggestion, the taxi is reserved, the bill for the meal is settled, and the taxi for the return journey is arranged. Then, when the arranged taxi arrives at the restaurant, a notification of the taxi's arrival is sent to the user's mobile device.

[0028] This allows the user to simply make a reservation at a restaurant, and suggestions will be made regarding taxi arrangements for the outbound and return journeys, and once the taxi arrangements are complete, the bill will be settled.

[0029] At this time, particularly in restaurants, the behavior of a group including the user is detected by sensors, and when signs of completion are detected based on the sensing results, the number of taxis for the return journey is suggested, and if a taxi for the return journey is approved, the taxi is arranged and the bill is settled.

[0030] As a result, according to the present disclosure, the user can receive suggestions such as reservation dates and times and the optimal number of taxis without having to take any active action to arrange a taxi, making it possible to easily realize the reservation procedure for arranging a taxi. Furthermore, once the procedure for arranging a taxi is completed, it becomes possible to arrange a taxi at an appropriate time as desired by the user.

[0031] <<2. Preferred Embodiment>> Next, with reference to FIG. 4, a configuration example of an information processing system that realizes the taxi dispatch system of the present disclosure will be described.

[0032] The information processing system 101 in FIG. 4 is made up of a user terminal 111, a taxi management server 112, a store terminal 113, a store sensor 114, a settlement server 115, and taxis 116-1 to 116-m.

[0033] The user terminal 111 is, for example, a smartphone carried by the user. The user terminal 111 is provided with a touch panel 121, which presents necessary information to the user and accepts operation inputs from the user.

[0034] The user terminal 111 has installed thereon a taxi store reservation application 122 that is used when making a reservation for a store such as a restaurant or when arranging a taxi linked to a store reservation.

[0035] When the taxi shop reservation app 122 receives input of information related to shop reservations, information related to payment when using the shop, and various information related to taxi arrangements through user operation of the touch panel 121, it accesses the shop terminal 113, the payment server 115, and the taxi management server 112 according to the respective purposes, and executes shop reservation processing, payment processing when using the shop, taxi arrangement processing, etc. At this time, the taxi shop reservation app 122 controls the touch panel 121 to present information related to shop reservations, information related to payment when using the shop, and various information related to taxi arrangements.

[0036] When the user terminal 111 makes a reservation for a store, the taxi management server 112 proposes and accepts taxi arrangements for the use of the store, and then dispatches the taxis 116-1 to 116-m by transmitting information such as the destination and time based on the various procedures for taxi arrangements that have been accepted.

[0037] More specifically, the taxi management server 112 is composed of a taxi reservation management unit 131 , a database 132 , a taxi number prediction engine 133 , a taxi dispatch engine 134 , and a user behavior engine 135 .

[0038] When the user terminal 111 makes a reservation for a store, the taxi reservation management unit 131 proposes dispatching a taxi to use the reserved store, accepts the reservation for the taxi, and registers the accepted reservation details in the database 132. Furthermore, when signs of the end of an event at the store are detected, the taxi reservation management unit 131 proposes and accepts dispatching a taxi for the return trip. Furthermore, when signs of the end of an event at the store are detected, the taxi reservation management unit 131 supplies and displays information to be presented to the user on the user terminal 111, such as a reminder to pay the bill and the arrival of the dispatched taxi, based on instructions from the taxi dispatch engine 134.

[0039] The database 132 stores user attribute information 151, which is attribute information of the user who made the reservation, and user action plan information 152, which is information about the store where the user has made the reservation, as information required for reserving a taxi provided by the taxi reservation management unit 131. Details of the user attribute information 151 and the user action plan information 152 will be described later with reference to Figs. 6 and 7.

[0040] The taxi number prediction engine 133 predicts the number of taxis required based on the user attribute information 151 and user action plan information 152 registered in the database 132, and supplies the prediction result to the taxi dispatch engine 134.

[0041] The taxi dispatch engine 134 plans taxi dispatch for the outbound journey based on the user attribute information 151 and user action plan information 152 registered in the database 132 and the information on the number of taxis supplied from the taxi number prediction engine 133, and dispatches taxis 116-1 to 116-m.

[0042] The taxi dispatch engine 134 sets the dispatch conditions, which are the conditions required for dispatching, such as the dispatch time, the number of vehicles to be dispatched, and destination information, based on the predicted event end time supplied from the user behavior engine 135, the information on the user attribute information 151 and the user behavior plan information 152 registered in the database 132, and the information on the number of taxis supplied from the taxi number prediction engine 133. The taxi dispatch engine 134 then plans the dispatch of taxis for the return trip based on the dispatch conditions, registers this as dispatch plan information, and dispatches taxis 116-1 to 116-m based on the registered dispatch plan information when the specified dispatch time arrives.

[0043] The taxi dispatch engine 134 proposes the planned taxi dispatch plan information by supplying it to the user terminal 111 via the taxi reservation management unit 131, and registers the dispatch plan information when approval is obtained based on the proposed taxi dispatch plan information. When a predetermined dispatch time arrives, the taxi dispatch engine 134 dispatches a taxi 116 in accordance with the registered dispatch plan information.

[0044] At this time, the taxi dispatch engine 134 has a function of individually communicating with each of the taxis 116-1 to 116-m, and issues dispatch instructions and keeps track of the running location of each taxi 116 based on the instructions.

[0045] Therefore, when the taxi dispatch engine 134 determines based on the dispatch plan information that the taxi 116 has completed its journey to the store, it may, if necessary, notify the user terminal 111 via the taxi reservation management unit 131 that the taxi 116 has arrived and present information to guide the user to the taxi 116.

[0046] Furthermore, when the taxi dispatch engine 134 determines based on the dispatch plan information that the taxi 116 has completed its movement to the pick-up location, it may, if necessary, notify the store terminal 113 that the taxi 116 has arrived and display information to the store staff encouraging them to guide the customer to the taxi 116.

[0047] The user behavior engine 135 generates parameters to be used for predicting the predicted event end time based on the user behavior progress information and meal provision information supplied from the store terminal 113. The user behavior engine 135 predicts the predicted event end time based on the parameters for predicting the predicted event end time, and supplies the prediction result to the taxi dispatch engine 134.

[0048] The prediction of the predicted event end time by the user behavior engine 135 will be described in detail later with reference to FIG.

[0049] The store terminal 113 is a terminal device provided in each store, and is managed and operated by a store manager or store clerk.

[0050] The store terminal 113 includes a store reservation management unit 171 , a user behavior progress acquisition unit 172 , a meal provision information acquisition unit 173 , a payment processing unit 174 , and a touch panel 175 .

[0051] The store reservation management unit 171 accepts a reservation from the user terminal 111 and stores it as accepted reservation information.

[0052] The user behavior progress acquisition unit 172 estimates the user's behavior from the sensing results (sensor information) of the store sensor 114, which detects the behavior of users and groups of users who visit the store, and acquires the estimated user behavior as behavior progress.

[0053] More specifically, if the store sensor 114 is a camera, the user behavior progress acquisition unit 172 analyzes the user's movements and actions through image recognition processing based on captured images and acquires the analyzed movements and actions as user behavior progress information. User behavior progress information is, for example, the user's movements and actions themselves. Here, the user's movements and actions refer to the actions taken at the end of an event or immediately before the event. If the event is a dinner party at a restaurant, the user's movements include, for example, getting up to go to the restroom, drinking tea after the meal, taking out their wallet, putting on their jacket, and other actions taken when finishing their meal and about to leave the restaurant or immediately before the event. Furthermore, the user behavior progress information may include, as necessary, not only the user's movements and actions but also information such as the type of party the user is hosting and the number of people attending the party.

[0054] The food provision information acquisition unit 173 acquires information about the food currently being served, such as the category of the food being served (appetizer, main course, dessert, etc.), based on image information captured by the store sensor 114. In this example, the event is a dinner party at a restaurant, but if the event is, for example, a live event or a viewing event, the information would be about whether the ending credits are being shown.

[0055] The user behavior progress acquisition unit 172 and the meal provision information acquisition unit 173 repeatedly acquire the above-mentioned information at predetermined time intervals and provide it to the user behavior engine 135 of the taxi management server 112.

[0056] At this time, at least one of the user behavior progress acquisition unit 172 and the meal provision information acquisition unit 173 also repeatedly acquires, at predetermined time intervals, information on the elapsed time from the event start time and, if there is a change in the scheduled end time, information on the changed scheduled end time, and provides this information to the user behavior engine 135 of the taxi management server 112. Information related to changes in the scheduled end time is, for example, information that is changed by the user operating the touch panel 121 of the user terminal 111, or information that is changed by the store staff operating the touch panel 175 of the store terminal 113.

[0057] As a result, the user behavior engine 135 repeatedly predicts the predicted event end time, which is the time when the meal will end, at predetermined time intervals based on the user behavior progress information and meal provision information supplied from the user behavior progress acquisition unit 172 and the meal provision information acquisition unit 173.

[0058] The payment processing unit 174 executes payment for the food and drink in cooperation with the payment server 115. At this time, the payment processing unit 174 may execute payment processing in cooperation with the user terminal 111 as necessary.

[0059] The touch panel 175 accepts operational inputs from the store staff required for various processes performed at the store terminal 113, and displays the results of various processes to the store staff.

[0060] The store sensor 114 is composed of a sensor, such as a camera installed in the store, that acquires information that can detect the progress of a user's behavior. For example, if the store sensor 114 is a camera, it is set at multiple locations in the store 201 as shown in Figure 5, and acquires information that becomes the progress of user behavior of all customers who visit the store, including users of user terminals 111 present in the store, and supplies this information to the store terminal 113.

[0061] 5, store sensors 114-1 to 114-6 are installed in the corners of the ceiling, etc., in a configuration that overlooks the entire store 201 from multiple angles. In the example of FIG. 5, six store sensors 114-1 to 114-6 are installed, but this is just one example, and any other number of store sensors 114 may be installed.

[0062] The payment server 115 is, for example, a server managed and operated by a financial institution, etc. The payment server 115 includes a payment engine 191, and controls the payment engine 191 to execute payment processing related to payment of usage fees at the store terminal 113, etc.

[0063] <User Attribute Information> Next, with reference to FIG. 6, an example of the configuration of the user attribute information 151 registered in the database 132 will be described.

[0064] User attribute information 151 is a database that functions as a customer ledger for users, and as shown in Figure 6, it consists of the user's user ID, user name, affiliation such as the name of the company to which the user belongs, and the address of the company to which the user belongs.

[0065] In FIG. 6, from the left, a user ID column, a user name column, an affiliation column, and an address column are provided as user attribute information.

[0066] Also, in Figure 6, from top to bottom, "0001," "0002," "0003," etc. are registered as user IDs, "User A," "User B," "User C," etc. are registered as user names, "Company P," "Company Q," and "Company R" are registered as affiliations, and "100-1 △△-cho, XX-ku, Tokyo," "10-10 □□-cho, XX-ku, Tokyo," and "123-5 ◇◇-cho, ▽▽-shi, Kanagawa Prefecture" are registered as addresses.

[0067] That is, the user with user ID "0001" is registered as having the user name "User A" and belonging to "Company P" with an address of "100-1, △△cho, XX-ku, Tokyo." The user with user ID "0002" is registered as having the user name "User B" and belonging to "Company Q" with an address of "10-10, □□cho, XX-ku, Tokyo." The user with user ID "0003" is registered as having the user name "User C" and belonging to "Company R" with an address of "123-5, ◇◇cho, ▽▽-shi, Kanagawa Prefecture."

[0068] By registering such user attribute information 151 in the database 132, it can not only be used as customer management information, but also, once registered, when making a store reservation, the user's affiliation can be recognized simply by presenting the user ID. Therefore, for example, it can be used for route searches for dispatching a taxi, as a pick-up location when dispatching a taxi.

[0069] <User Action Plan Information> Next, with reference to FIG. 7, an example of the structure of the user action plan information 152 registered in the database 132 will be described.

[0070] The user behavior plan information 152 is a database of information related to a user's behavior plan, such as when the user makes a restaurant reservation, and as shown in Figure 7, it consists of a reservation ID, user ID, reserved store: store location, reservation date and time, breakdown of number of people making the reservation (our company, business partner), and number of vehicles to be dispatched (our company, business partner).

[0071] In Figure 7, from left to right, there are a reservation ID column, a user ID column, a reservation store: store location column, a reservation date and time column, a breakdown of the number of people making a reservation (our company, business partner) column, and a number of vehicles to be dispatched (our company, business partner) column.

[0072] 7, from top to bottom, "0001," "0002," "0003," ... are registered as reservation IDs, "0001," "0002," "0003," ... are registered as user IDs, and "AA Yakiniku Restaurant: 1-1-1 ▲▲cho, ●●-ku, Tokyo," "BB Sushi: 1234 ■■cho, XX-ku, Tokyo," ... are registered as reservation store: store locations. Also, "202401291700," "202401101900," ... are registered as reservation dates and times, (3, 4), (2, 5), ... are registered as reservation number breakdowns (company, business partner), and (2, 5), (1, 2), ... are registered as vehicle dispatch numbers (company, business partner).

[0073] In other words, the user action plan information with reservation ID "0001" is based on a reservation made by the user with user ID "0001", and it is registered that the restaurant "AA Yakiniku Restaurant" located at "1-1-1 ▲▲cho, ●●-ku, Tokyo" has been reserved from 17:00 on January 29, 2024, and that the reservation is for three people from our company and four people from a business partner, with one taxi being dispatched for the three people from our company and one taxi for the four people from the business partner.

[0074] In addition, the user action plan information for reservation ID "0002" is based on a reservation made by the user with user ID "0002", and it shows that the restaurant "BB Sushi", located at "1234 ■■-cho, XX-ku, Tokyo", has been reserved from 19:00 on January 10, 2024, and that the reservation is for two people from the company and five people from a business partner, with one taxi being dispatched for the two people from the company and two taxis for the five people from the business partner.

[0075] By registering such user action plan information 152, reservations can be managed and the destination can be recognized simply by presenting the reservation ID, so that it can be used, for example, as the destination when dispatching a taxi, for route searches related to dispatching a taxi, etc.

[0076] <Prediction of predicted event end time by user behavior engine> Next, prediction of predicted event end time by the user behavior engine 135 will be described.

[0077] As shown in the lower part of Figure 8, the user behavior engine 135 generates prediction parameters for predicting the event end time T(t) based on behavior progress information for the elapsed time t from the start of the reservation at the store, which is supplied from the user behavior progress acquisition unit 172 of the store terminal 113, and meal provision information supplied from the meal provision information acquisition unit 173.

[0078] Here, the prediction parameters for predicting the event end time T(t) are the action progress parameter Ph(t), the event progress parameter Pf(t), the time parameter Pt(t), and the event parameter Pi(t).

[0079] The behavior progress parameter Ph(t) is a parameter that indicates the presence or absence and frequency of behavior that occurs immediately before the end of the event, i.e., the end of use of the store (end of the event), based on behavior progress information for the elapsed time t from the start of reservation at the store, supplied by the user behavior progress acquisition unit 172.

[0080] Actions that occur immediately before the end of the store (end of the event) are actions that occur immediately before the end of the meal, such as getting up to go to the bathroom, taking out your wallet, or starting to put on your jacket, if the store is a restaurant or the like and the event is a meal, as in this example.

[0081] The event progress parameter Pf(t) is a parameter that indicates the progress of the event.In this case, since the store is a restaurant, it is a parameter that indicates the meal provision status based on the meal provision information at the time t elapsed since the start of reservations at the store, which is supplied from the meal provision information acquisition unit 173.

[0082] The food serving status as an indication of the progress of an event indicates the overall progress of the meal event at a restaurant, such as, for example, in the case of a course meal, the type of dishes (appetizer, main course, dessert, or after-meal tea) that have been served up to the elapsed time t, or, if there are 10 dishes in total to be served, how many dishes have been served.

[0083] The time parameter Pt(t) is the start time of the event, the time elapsed since the start of the event, and the scheduled end time. Note that the start time and scheduled end time here refer to, for example, the reservation time at the time of booking the use of the store. In the case where the end time is extended after the event has started due to a request from the user, the time parameter Pt(t) is information such as the extended end time.

[0084] The event parameters Pi(t) are parameters that indicate the content of the event, such as information indicating the type of event, or, if the event type is a meal, information specifying the food category, course, or single dish. If the event is a live event, the event parameters Pi(t) may also include information such as the number of participants and the venue.

[0085] Next, the user behavior engine 135 generates prediction parameters consisting of an action progress parameter Ph(t), an event progress parameter Pf(t), a time parameter Pt(t), and an event parameter Pi(t) at a predetermined time interval, and then predicts the event end time T(t) at the current time t by calculating, for example, a function f(Ph(t), Pf(t), Pt(t), Pi(t)), as shown in the upper part of Figure 8.

[0086] Here, the function f(Ph(t), Pf(t), Pt(t), Pi(t)) is a function obtained in advance from a model or statistical results for predicting the predicted event end time T(t) when these prediction parameters are input.

[0087] More specifically, the function f(Ph(t), Pf(t), Pt(t), Pi(t)) may be a function that calculates the probability that the event will actually end at a number of candidate event end times Tc1, Tc2, ... that are set from the current time t, and sets the candidate event end time with a probability equal to or higher than a predetermined probability, for example, 90% or higher, as the event end time T(t).

[0088] More specifically, for example, if the start time of an event is 19:00, candidate event end times are set to 20:00, 20:30, 21:00, etc., which are a predetermined time after the start time of 19:00. The probability that the event will end at each of the candidate event end times, 20:00, 20:30, and 21:00, is calculated, and the candidate event end time that meets or exceeds a predetermined reference value (e.g., 90%) is set as the predicted event end time. Furthermore, if there are multiple candidate event end times that meet or exceed the reference value, the one with the highest probability is set as the predicted event end time.

[0089] The progress rate may be calculated from the relationship between the predicted event end time and the elapsed time from the event start time to the current time. That is, the progress rate is the ratio of the elapsed time from the event start time to the current time to the total time from the event start time to the predicted event end time. Therefore, the predicted event end time and the progress rate can be treated almost equally, so the predicted event end time and the progress rate may be used together, or either one may be used.

[0090] The user behavior engine 135 generates the above-mentioned prediction parameters each time behavior progress information from the user behavior progress acquisition unit 172 of the store terminal 113 and meal provision information from the meal provision information acquisition unit 173 are supplied at predetermined time intervals, and by inputting them into the above-mentioned function f, repeats the process of predicting the predicted event end time and supplies it to the taxi dispatch engine 134.

[0091] In addition, since the behavior progress information from the user behavior progress acquisition unit 172 of the store terminal 113 and the meal provision information from the meal provision information acquisition unit 173 are both information used to generate prediction parameters to be input into the above-mentioned function f, in the following, the meal provision information will be treated as part of the behavior progress information as necessary.

[0092] Furthermore, in the above, we have described an example in which the user behavior engine 135 predicts the predicted event end time based on prediction parameters consisting of all of the behavior progress parameter Ph(t), event progress parameter Pf(t), time parameter Pt(t), and event parameter Pi(t). However, it is also possible to simply predict the predicted event end time using only a portion of the prediction parameters.

[0093] That is, the user behavior engine 135 may use at least one of the behavior progress parameter Ph(t), the event progress parameter Pf(t), the time parameter Pt(t), and the event parameter Pi(t) as prediction parameters to simply predict the predicted end time of the event.

[0094] The taxi dispatch engine 134 sets, as dispatch conditions, conditions necessary for dispatching a taxi, including the predicted event end time, the number of taxis predicted by the taxi number prediction engine 133, and the destination location. Then, based on the dispatch conditions, the taxi dispatch engine 134 takes into consideration the preparation time, which includes the time required for user consent processing and payment processing, and the time required to move a taxi to a store, and controls the taxi reservation management unit 131 to supply, to the user terminal 111, information prompting the user to check taxi dispatch plan information for the number of taxis predicted by the taxi number prediction engine 133 and to process payment, when the time reaches the preparation time before the predicted event end time.

[0095] Then, when the user confirms (approves) the taxi dispatch plan information via the user terminal 111 and is notified of the completion of the payment process, the taxi dispatch engine 134 arranges for the taxi 116 to travel to the store based on the dispatch plan information.

[0096] As described above, the progress rate can be calculated from the relationship between the predicted event end time and the time elapsed since the event start time. Therefore, the taxi dispatch engine 134 may control the taxi reservation management unit 131 based on the progress rate instead of the event end time, and supply information to the user terminal 111 prompting confirmation of taxi arrangements and payment processing for the number of taxis predicted by the taxi number prediction engine 133.

[0097] Furthermore, the user behavior engine 135 may be configured, for example, as a DNN (Deep Neural Network) generated by machine learning, and may perform processing similar to the calculation processing expressed by the function f(Ph(t), Pf(t), Pt(t), Pi(t)) based on the behavior progress parameter Ph(t), the event progress parameter Pf(t), the time parameter Pt(t), and the event parameter Pi(t).

[0098] When the user behavior engine 135 is configured with a DNN, the user behavior engine 135 may generate parameters to be used for predicting the predicted event end time based on the user behavior progress information and the meal provision information, and may use the generated parameters as input data and output the predicted event end time. Alternatively, the user behavior engine 135 may use the user behavior progress information and the meal provision information itself as input data and output the predicted event end time.

[0099] Furthermore, the user behavior engine 135 may feed back the acquired user behavior progress information and meal provision information, along with the corresponding actual end time, as training data and repeat further learning; this repeated learning process can further improve prediction accuracy.

[0100] <Store Reservation Outbound Vehicle Dispatch Processing> Next, the store reservation outbound vehicle dispatch processing will be described with reference to the flowchart of FIG.

[0101] In step S31, the taxi shop reservation application 122 determines whether or not the user has operated the touch panel 121 to request a shop reservation.

[0102] If it is determined in step S31 that a store reservation has been requested, the process proceeds to step S32.

[0103] In step S32, the taxi shop reservation app 122 controls the touch panel 121 to display an input screen for shop reservations, such as that shown in the left part of Figure 10, and when various information is entered, the entered information is notified to the taxi management server 112 and the shop terminal 113 of the shop where the reservation is desired as shop taxi reservation registration information.

[0104] 10, a user information field 220 is provided at the top, in which the user ID, user name, and affiliation are written. This information may be pre-registered information only, or the user may input the information by operating the touch panel 121.

[0105] Below the user information column 220, there is, from top to bottom, a store input column 221 labeled "Store" where the name of the store to be reserved is registered, a date and time input column 222 labeled "Date and Time" where the date and time of the reservation is entered, and a company number input column 213 labeled "Company number of people" where the number of people participating from the company, including the user, is entered.

[0106] Furthermore, below that are provided input fields 214 and 215 for inputting the number of people at business partners XX Company and △△ Company, respectively, labeled "Number of people at XX Company" and "Number of people at △△ Company," and a button 216 labeled "OK" that is operated to indicate completion of the operation.

[0107] For example, when a user operates touch panel 121 to input the store name, date and time, number of employees in the company, and number of business partners in the store input field 221, date and time input field 222, number of employees in the company input field 213, and number of business partners input fields 214 and 215, respectively, and then operates button 216, the information is notified to the taxi reservation management unit 131 of the taxi management server 112 as store taxi reservation registration information.

[0108] As shown in Figure 10, the user ID, user name, and affiliation are entered as "0001," "User A," and "Company P," respectively, the store name is entered as "YYYya," the date and time is entered as "2024-01-01 19:00," the number of employees in the company is entered as "5," the number of employees at business partner Company XX is entered as 4, and the number of employees at Company △△ is entered as 3, and then button 216 is pressed.

[0109] In step S51, the taxi reservation management unit 131 determines whether or not store taxi reservation registration information has been notified. For example, if store taxi reservation registration information has been notified by the processing of step S32, the processing proceeds to step S52.

[0110] In step S52, the taxi reservation management unit 131 registers the user attribute information 151 and the user action plan information 152 in the database 132 based on the store taxi reservation registration information.

[0111] 10, the user ID, user name, and affiliation are registered as "0001," "User A," and "Company P," respectively, as user attribute information 151. However, this does not apply to users who have already been registered.

[0112] Furthermore, a new reservation ID is set, and the set reservation ID is associated with the user ID, and the store name is set to "YYY store," the date and time is set to "2024-01-01 19:00," the number of employees in the company is set to "5," and the number of employees at business partner company XX is set to 4 and the number of employees at company △△ is set to 3, which are registered in the user action plan information 152. The name of the business partner and the number of business partners may be input by the user operating the touch panel 121.

[0113] Furthermore, for the store location, search results obtained by searching for the store name may be registered.

[0114] In step S53, the taxi number prediction engine 133 accesses the user behavior plan information 152 in the database 132, calculates the predicted number of taxis required based on the information on the number of employees of the company and the number of business partners, and registers the calculation result in the user behavior plan information 152 in the database 132.

[0115] For example, if the number of passengers per taxi is N, the number of people in the company is L, and the number of business partners is M, the taxi number prediction engine will predict the number of vehicles for the company to be (L / N+1) and the number of vehicles for business partners to be (M / N+1).

[0116] In this case, the number of passengers N per taxi may not be the number of passengers that can be accommodated according to the vehicle inspection registration, but may be the number of passengers that can be accommodated comfortably with some space to spare.

[0117] In step S54, the taxi number prediction engine 133 calculates the dispatch time based on the reservation time of the store, such as the company's address or the address of the client. For example, if the meal at the store starts at 7:00 PM and travel time to the store is approximately 30 minutes, the taxi number prediction engine 133 sets the dispatch time to 6:20 PM, taking into account boarding and disembarking times, etc. At this time, the taxi number prediction engine 133 also calculates the fare for arrangement. Furthermore, the address of the client may be searched for by the client's company name, for example, "Company X" or "Company XX."

[0118] In step S55, the taxi reservation management unit 131 generates a confirmation screen for arranging a taxi based on the user action plan information 152 and the prediction result of the taxi number prediction engine 133, and supplies it to the user terminal 111.

[0119] In step S33, when the user terminal 111 receives a confirmation screen regarding taxi arrangements from the taxi reservation management unit 131, it displays it on the touch panel 121 and presents it to the user.

[0120] An example of a confirmation screen for taxi arrangement is confirmation screen 230 in Fig. 10. In confirmation screen 230 in Fig. 10, below user information field 220, there is written "Arrangements will be made as follows. Is this OK?", and below that, there are a destination field 231 under the heading "Destination," and time and number of taxis fields 232 to 234 under the headings "Arrangements to our company: ¥3,000," "Arrangements to company X: ¥5,000," and "Arrangements to company Y: ¥1,500," in which the arranged time and number of taxis are written. Below that, there are displayed, from left to right, buttons 235 labeled "OK" and "Back" that are pressed to confirm the confirmation, and a button 236 that is operated to return to the previous image, i.e., display screen 211.

[0121] In the example of Figure 10, the destination column 231 is written as "YYYya", the time number column 232 is written as "2 vehicles at 18:30", the time number column 233 is written as "1 vehicle at 18:00", and the time number column 234 is written as "1 vehicle at 18:30".

[0122] That is, the confirmation screen 230 in FIG. 10 presents information that confirms that the destination is "YYY Company," two vehicles will be arranged for the company at 18:30 for a fare of 3,000 yen, one vehicle will be arranged for XY Company at 18:00 for a fare of 5,000 yen, and one vehicle will be arranged for △△ Company at 18:30 for a fare of 1,500 yen.

[0123] If changes are necessary, the user operates the touch panel 121 to change the information in the destination field 231 and the time / number of vehicles fields 232 to 234 .

[0124] In step S34, when the touch panel 121 is operated, for example, when the button 235 labeled "OK" in Figure 10 is pressed, the taxi shop reservation app 122 notifies the taxi reservation management unit 131 of information indicating that confirmation has been completed.

[0125] In step S56, the taxi reservation management unit 131 registers the information regarding the confirmed taxi dispatch in the taxi arrangement engine 134, and executes the payment of the taxi fare by communicating with the payment server 115.

[0126] In step S57, the taxi reservation management unit 131 generates a display screen indicating that the payment has been completed, and notifies the user terminal 111 of this.

[0127] In step S34, the taxi shop reservation application 122 of the user terminal 111 controls the touch panel 121 to display a display screen indicating that the payment notified by the taxi management server 112 has been completed.

[0128] The display screen notifying the completion of the payment from the taxi management server 112 is, for example, the display screen 241 in FIG.

[0129] On the display screen 241 of Figure 10, from the top, under the user information column 220, it is written "Arrangements completed," "Payment completed from your registered credit card," "Arrangements to our company: ¥3,000," "Arrangements to XX Company: ¥5,000," "Arrangements to △△ Company: ¥1,500," "Total: ¥9,500," and "Billing address: XX Corporate Card."

[0130] This will display the completion of payment for the taxi arrangement, the breakdown of each item, the total amount, and information about the card company to which the bill will be sent.

[0131] In step S58, the taxi dispatch engine 134 determines whether the registered dispatch time has arrived, and if the dispatch time has arrived, the process proceeds to step S59.

[0132] In step S59, the taxi dispatch engine 134 dispatches the registered number of taxis 116 to go to the registered locations as pick-up vehicles.

[0133] Also, in response to the processing of step S32, in step S71, the store reservation management unit 171 of the store terminal 113 determines whether or not store taxi reservation registration information has been notified, and for example, if store taxi reservation registration information has been notified by the processing of step S31, the processing proceeds to step S72.

[0134] In step S72, the store reservation management unit 171 acquires information from the store input field 221, date and time input field 222, company number input field 213, and business partner number input fields 214 and 215 on the display screen 211 of FIG.

[0135] In step S73, the store reservation management unit 171 identifies the reservation date and time and the number of people from the information in the store input field 221, date and time input field 222, company number of people input field 213, and business partner number of people input fields 214 and 215 on the display screen 211 of Figure 10, and registers the reservation.

[0136] In steps S36, S60, and S74, it is determined whether or not an instruction to end the process has been issued. If an instruction to end the process has not been issued, the process returns to steps S31, S51, and S71, respectively, and the subsequent steps are repeated. If an instruction to end the process has been issued in steps S36, S60, and S74, the process ends.

[0137] In addition, if there is no store reservation in step S31, the processing of steps S32 to S35 is skipped. If there is no store taxi reservation registration information in steps S51 and S71, the processing of steps S52 to S59 and steps S72 to S73 are skipped. Furthermore, if it is not time to dispatch a vehicle in step S58, the processing of step S59 is skipped.

[0138] Through the above processing, a reservation for the store desired by the user is realized based on the store taxi reservation registration information. At this time, the taxi management server 112 registers the user attribute information 151 and the user behavior plan information 152 in the database 132. Furthermore, based on the user attribute information 151 and the user behavior plan information 152 registered in the database 132, the number of taxis 116 to be dispatched, the dispatch time, and the pick-up location are planned and registered. At this time, the fare for the taxis 116 is also paid. Then, when the set dispatch time arrives, the registered number of taxis 116 are dispatched to the pick-up location.

[0139] As a result, a user can simply make a reservation for a store and also arrange for a taxi to go to the reserved store. Also, according to the reservation time, taxis 116 for the number of people in the company and business partners can be arranged to be dispatched to the locations specified as the respective pick-up locations at the appropriate time.

[0140] <Return Vehicle Allocation Processing> Next, the return vehicle allocation processing will be described with reference to the flowchart of FIG.

[0141] In step S101, the user behavior progress acquisition unit 172 and the meal provision information acquisition unit 173 in the store terminal 113 determine whether a predetermined time has elapsed.

[0142] In step S101, when a predetermined time has elapsed, the process proceeds to step S102.

[0143] In step S102, the user behavior progress acquisition unit 172 performs image recognition based on images of users inside the store sensed by the store sensor 114 to acquire user behavior progress information, such as the presence or absence and frequency of behaviors that occur just before the end of a meal, such as an increase in the number of people standing up, taking out their wallets, or starting to put on their jackets.

[0144] In step S103, the meal provision information acquisition unit 173 acquires meal provision information consisting of the meal provision status indicating the overall progress of the dining event at the restaurant, such as the type of food served (appetizer, main course, or dessert) and, if there are 10 dishes served in total, how many dishes have been served, by performing image recognition processing based on images of users in the restaurant sensed by the store sensor 114. This information may include not only information about customers sensed by the store sensor 114, but also information about kitchen workers and information manually entered by room attendants on a terminal.

[0145] In step S104, the user behavior progress acquisition unit 172 and the meal provision information acquisition unit 173 respectively transmit the user behavior progress information and the meal provision information to the user behavior engine 135 of the taxi management server 112 in association with the current time t.

[0146] In step S121 , the user behavior engine 135 determines whether or not user behavior progress information and meal provision information have been supplied from the store terminal 113 .

[0147] In step S121, if the user action progress information and meal provision information have been supplied, the process proceeds to step S122.

[0148] In step S122, the user behavior engine 135 acquires the supplied user behavior progress information and meal provision information.

[0149] In step S123, the user behavior engine 135 generates a behavior progress parameter Ph(t), an event progress parameter Pf(t), a time parameter Pt(t), and an event parameter Pi(t) for predicting the expected end time T(t) based on the supplied user behavior progress information and meal provision information.

[0150] In step S124, the user behavior engine 135 executes a predicted end time prediction process to predict a predicted end time based on the generated behavior progress parameter Ph(t), event progress parameter Pf(t), time parameter Pt(t), and event parameter Pi(t), and predicts the predicted event end time T(t) at the current time t.

[0151] Here, the predicted end time prediction process will be described with reference to the flowchart of FIG.

[0152] In step S181, the user behavior engine 135 sets a predetermined number of end time candidates.

[0153] In step S182, the user behavior engine 135 calculates the probability that the meal, which is an event at the restaurant, will end at each of the candidate end times.

[0154] In step S183, the user behavior engine 135 determines whether or not there is an end time candidate with a predetermined probability (for example, 90%) or higher among the end time candidates.

[0155] In step S183, if there is an end time candidate with a predetermined probability (for example, 90%) or higher among the end time candidates, the process proceeds to step S184.

[0156] In step S184, the user behavior engine 135 updates the end time candidate with the highest probability among the end time candidates with a predetermined probability (e.g., 90%) or higher as the predicted end time (predicted event end time) T(t) at the current time t, and supplies this to the taxi dispatch engine 134. Then, the taxi dispatch engine 134 sets the conditions necessary for dispatching taxis, including the predicted event end time, the number of taxis predicted by the taxi number prediction engine 133, and the destination location, as dispatch conditions.

[0157] On the other hand, if it is determined in step S183 that there is no end time candidate with a predetermined probability (for example, 90%) or higher, the process proceeds to step S185.

[0158] In step S185, the user behavior engine 135 supplies the end time set at the time of reservation as the predicted end time T(t) at the current time t to the taxi dispatch engine 134. Then, the taxi dispatch engine 134 sets the conditions necessary for dispatching a taxi, including the predicted event end time, the number of taxis predicted by the taxi number prediction engine 133, and the destination location, as dispatch conditions.

[0159] Now, let us return to the description of the flowchart in FIG.

[0160] In step S125, the taxi dispatch engine 134 determines whether the current time t is the dispatch dispatch time that is the time before either the predicted end time of the event based on the dispatch conditions or the end time specified by the user, by the amount of time required for confirming the dispatch of a taxi and for the dispatched taxi to arrive.

[0161] If it is determined in step S125 that it is time to arrange for vehicle dispatch, the process proceeds to step S126.

[0162] In step S126, the taxi dispatch engine 134 plans to dispatch a taxi for the return journey based on the dispatch conditions.

[0163] In principle, for the return journey, the same number of taxis as for the outbound journey will be dispatched in front of the reserved store. Therefore, the same number of taxis will be prepared for the company and the client based on the dispatch plan information registered for the outbound journey.

[0164] In step S127, the taxi dispatch engine 134 notifies the return route dispatch plan information to the taxi reservation management unit 131 and the store terminal 113. In response to this, the taxi reservation management unit 131 notifies the return route dispatch plan information to the user terminal 111. At this time, information prompting the user to pay may also be notified.

[0165] In step S151, the taxi shop reservation application 122 determines whether or not the return route dispatch plan information has been notified from the taxi management server 112.

[0166] In step S151, if the return trip vehicle allocation plan information has been notified, the process proceeds to step S152.

[0167] In step S152, the taxi shop reservation application 122 controls the touch panel 121 to present the return route dispatch plan information notified by the taxi management server 112, for example, on the confirmation screen 251 of FIG.

[0168] In the confirmation screen 251 of Figure 13, below the user information column 220, from the top, it is written, "The end time is approaching. Taxis for your return journey will be arranged as follows. Is this OK? Please modify as necessary.", and below that are provided a pick-up time column 261 which reads "Pick-up time", and number columns 262 to 264 which list the numbers of vehicles to be arranged, with "Arrangements to our company: 3,000 yen", "Arrangements to XXXX company: 5,000 yen", and "Arrangements to △△ company: 1,500 yen", respectively, and below that are displayed buttons 265 which are written, from the left, as "OK" and "Back" to be pressed to approve the confirmation, and a button 266 which is operated to return to the previous image.

[0169] In the example of Figure 13, the pick-up time column 261 is marked "21:00", the number of vehicles column 262 is marked "2 vehicles", the number of vehicles column 263 is marked "1 vehicle", and the number of vehicles column 264 is marked "1 vehicle".

[0170] That is, the confirmation screen 230 in Figure 13 presents information confirming that the pick-up time, which is the predicted end time of the event, is "21:00," that two vehicles have been arranged for our company, with the fare being 3,000 yen, that one vehicle has been arranged for company X, with the fare being 5,000 yen, and that one vehicle has been arranged for company YY, with the fare being 1,500 yen.

[0171] If changes are necessary, the user operates the touch panel 121 to change the information in the pick-up time field 261 and the number of vehicles fields 262 to 264 .

[0172] 13 is substantially the predicted event end time predicted by the user behavior engine 135, the presentation of the pick-up time can also be considered as a presentation of the predicted event end time to the user. That is, in the case of the confirmation screen 230 of FIG. 13, the user can see the pick-up time and recognize that the predicted event end time is 9:00 PM.

[0173] Furthermore, since the predicted event end time is a time predicted from the current progress status, the progress rate calculated from the relationship between the current time and the elapsed time from the event start time may be presented instead of or in addition to the pick-up time, which is the predicted event end time.

[0174] In step S153, the taxi shop reservation application 122 determines whether the touch panel 121 has been operated and the return trip dispatch plan information has been approved as is without any modifications.

[0175] In step S153, for example, if the information in the pick-up time field 261 and the number of vehicles fields 262 to 264 is operated and corrected, the process proceeds to step S154.

[0176] In step S154 , the taxi shop reservation application 122 accepts a correction to the return route dispatch plan information in accordance with the operation content of the touch panel 121 .

[0177] In step S155, the taxi shop reservation application 122 notifies the taxi reservation management unit 131 of the taxi management server 112 of information related to the correction of the return route dispatch plan information.

[0178] In step S128, the taxi reservation management unit 131 outputs information related to the correction of the return route dispatch plan information to the taxi dispatch engine 134. The taxi dispatch engine 134 determines whether or not the return route dispatch plan information has been corrected. In this case, since the return route dispatch plan information has been corrected, it is determined in step S128 that a correction has been made, and the process returns to step S126.

[0179] In step S126, the taxi dispatch engine 134 modifies the return trip vehicle dispatch plan information based on the information related to the modification of the return trip vehicle dispatch plan information.

[0180] Then, the processes of steps S127 and S151 to S153 are performed again. Then, in step S153, if the return trip vehicle allocation plan information is approved without any correction, the process proceeds to step S156.

[0181] In step S156, the taxi shop reservation application 122 executes accounting processing for the taxi fare based on the return route dispatch plan information, and presents the processing result as, for example, a notification screen 271 as shown in FIG.

[0182] On the notification screen 271 of Figure 13, from the top, under the user information column 220, it is written "Arrangements completed," "Payment completed from your registered credit card," "Arrangements to our company: ¥3,000," "Arrangements to XX Company: ¥5,000," "Arrangements to △△ Company: ¥1,500," "Total: ¥9,500," and "Billing address: XX Corporate Card."

[0183] In step S157, the taxi shop reservation application 122 notifies the taxi reservation management unit 131 of the taxi management server 112 that the return route dispatch plan information has been approved.

[0184] In step S158, the taxi shop reservation application 122 determines whether the user has operated the touch panel 121 to instruct the shop to pay.

[0185] If it is determined in step S158 that a payment instruction has been issued, the process proceeds to step S159.

[0186] In step S159, the taxi shop reservation app 122 executes the shop payment process using the payment engine 191 in the payment server 115 by exchanging data with the payment processing unit 174 of the shop terminal 113. At this time, the shop terminal 113 also performs the payment process in steps S107 and S108.

[0187] In step S160, the taxi shop reservation application 122 determines whether the return route dispatch plan information has been approved and the payment process for the bill has been completed.

[0188] If it is determined in step S160 that the return trip vehicle allocation plan information has been approved and that the payment process for the bill has been completed, the process proceeds to step S161.

[0189] In step S161, the taxi shop reservation application 122 notifies the taxi management server 112 that the return route dispatch plan information has been approved and that the payment process for the bill has been completed.

[0190] On the other hand, if it is notified in step S157 that the return vehicle allocation plan information has been approved, it is determined in step S128 that the return vehicle allocation plan information has been approved, and the process proceeds to step S129.

[0191] In step S129, the taxi dispatch engine 134 determines whether or not the user terminal 111 has notified the user that payment has been completed.

[0192] When the processing in step S161 indicates that the return trip vehicle allocation plan information has been approved and that the payment processing for the bill has been completed, it is determined in step S128 that no corrections have been made to the return trip vehicle allocation plan information, and furthermore, it is determined in step S129 that the payment processing for the bill has been completed, so the processing proceeds to step S130.

[0193] In step S130, the taxi dispatch engine 134 instructs the taxis 116 to dispatch vehicles based on the return vehicle dispatch plan information. In response to this dispatch instruction, the number of taxis 116 set in the return vehicle dispatch plan information starts moving to the store.

[0194] In step S131, the taxi dispatch engine 134 determines, by communication with the taxi 116 or the like, whether or not the taxi has arrived at the store that is the pick-up location, and repeats the same process until the taxi arrives.

[0195] If it is determined in step S131 that the number of taxis 116 according to the return trip vehicle allocation plan information has arrived at the pickup location, the process proceeds to step S132.

[0196] In step S132, the taxi dispatch engine 134 notifies the user terminal 111 of the arrival of the taxi via the taxi reservation management unit 131, and also notifies the shop terminal 113.

[0197] In step S162, the taxi shop reservation application 122 determines whether or not the taxi management server 112 has notified the user that a taxi has arrived, and repeats the same process until the notification is received.

[0198] Then, in step S162, if the taxi management server 112 notifies the user that a taxi has arrived, the process proceeds to step S163.

[0199] In step S163, the taxi shop reservation app 122 controls the touch panel 121 to display, for example, a notification screen 281 as shown in FIG. 14 , notifying the user that a taxi has arrived, thereby informing the user that a taxi for the return trip has arrived.

[0200] In the notification screen 281 of Figure 14, below the user information column 220, from the top of the figure, it is written, "The following taxi for your return trip has arrived, so please come to your car.", and below that is a pick-up time column 291 written as "Pick-up time", and vehicle number columns 292 to 294 written as the number of vehicles to be arranged, each written as "Arrange for our company", "Arrange for XXXX company", and "Arrange for XX company", and below that is a button 295 written as "OK" to be pressed to approve the confirmation.

[0201] In the example of Figure 14, the pick-up time column 291 is marked "21:00", the number of vehicles column 292 is marked "2 vehicles", the number of vehicles column 293 is marked "1 vehicle", and the number of vehicles column 294 is marked "1 vehicle".

[0202] That is, the notification screen 281 in FIG. 14 presents information confirming that the approved pick-up time is "21:00," that two vehicles have been arranged for the company, one for company X, and one for company YY, and further shows that the taxi 116 indicated has arrived.

[0203] In addition, in the processing of step S127, the return trip vehicle allocation plan information is also notified to the store terminal 113.

[0204] Therefore, in step S105, the store reservation management unit 171 determines whether or not the return route dispatch plan information has been notified from the taxi management server 112, and if it is determined that the information has been notified, the processing proceeds to step S106.

[0205] In step S106, the store reservation management unit 171 controls the touch panel 175 to display the return trip vehicle allocation plan information. This display allows the store staff to recognize that the meal event is nearing its end from the information on the pick-up time, and can, for example, casually suggest to the user, who is a customer, that they pay the bill.

[0206] In step S107, the store reservation management unit 171 determines whether or not a payment using the user terminal 111 has been instructed, and if a payment has been instructed, the process proceeds to step S108.

[0207] In step S108, the payment processing unit 174 cooperates with the payment engine 191 of the payment server 115 to execute payment processing for the transaction using the user terminal 111.

[0208] In step S109, the shop reservation management unit 171 determines whether or not the taxi management server 112 has notified the shop reservation management unit 171 that a taxi has arrived.

[0209] Then, in step S109, if the taxi management server 112 notifies the user that a taxi has arrived, the process proceeds to step S110.

[0210] In step S110, the store reservation management unit 171 controls the touch panel 175 to display a notification screen similar to that shown in Figure 14, which notifies the store staff that a taxi has arrived for the customer's return trip.

[0211] This will notify store staff that a taxi has arrived for the return journey, allowing the store staff to inform the user, who is a customer, that a taxi has arrived and guide them outside the store.

[0212] In steps S111, S133, and S164, it is determined whether or not an instruction to end has been given. If it is determined that an instruction to end has not been given, the process returns to steps S101, S121, and S151, and the subsequent processes are repeated.

[0213] Furthermore, in step S101, if the predetermined time has not elapsed, the processes of steps S102 to S104 are skipped. In step S105, if the return trip vehicle dispatch plan information has not been notified, the process of step S106 is skipped. In step S107, if payment is not instructed, the process of step S108 is skipped. In step S109, if the arrival has not been notified, the process of step S110 is skipped.

[0214] In step S121, if the user behavior progress information and meal provision information are not transmitted, the processes of steps S122 to S124 are skipped. In step S125, if it is not time to arrange for vehicle dispatch, the processes of steps S126 and S127 are skipped. In step S129, if it is determined that payment has not been completed, the processes of steps S130 to S132 are skipped.

[0215] In step S151, if the return trip vehicle allocation plan information has not been notified, steps S152 to S157 are skipped. In step S158, if payment is not instructed, step S159 is skipped. In step S160, if the return trip vehicle allocation plan has not been approved or the payment process for payment has not been completed, steps S161 to S163 are skipped.

[0216] Through the above processing, user behavior progress information and meal provision information acquired by the store sensor 114 are supplied from the store terminal 113 at predetermined time intervals, and the user behavior engine 135 of the taxi management server 112 generates parameters for predicting the scheduled end time of the event from the user behavior progress information and meal provision information, and repeatedly predicts the scheduled end time of the event based on the generated parameters.

[0217] Therefore, it is possible to calculate an appropriate predicted end time of the event based on the user's behavior in the store. Furthermore, the predicted end time of the event continues to change depending on the user's behavior, the pace of serving food, etc. until the current time t approaches the time before the predicted end time by the amount of time required for various procedures.

[0218] Then, based on an appropriate predicted end time of the event, the return route dispatch plan information is generated at a timing that takes into consideration the time required for the user to approve the return route dispatch plan information, the time required for payment, and the time required for the taxi to arrive at the store after dispatch.

[0219] This makes it possible to generate return trip vehicle dispatch plan information for dispatching a taxi for the return trip at an appropriate timing.

[0220] Furthermore, even if the return trip vehicle dispatch plan information is revised, the return trip vehicle dispatch plan information is generated again at a timing that takes into consideration the time required for the user to approve the return trip vehicle dispatch plan information, the time required for payment, and the time required for the taxi to arrive at the store after dispatch, making it possible to flexibly dispatch a return trip taxi according to the user's situation.

[0221] Furthermore, the return trip dispatch plan information is notified not only to the user terminal 111 but also to the store terminal 113, so that store staff can know when customers are leaving the store, and can prompt them to pay, thereby smoothly guiding customers through their actions until they leave the store.

[0222] Furthermore, when a taxi arrives at the store on the way home, the user terminal 111 and the store terminal 113 are notified, so that customers can smoothly board a taxi on the way home. In addition, even if a customer accidentally misses the notification that a taxi has arrived, the store staff can follow up, so that the customer can be guided to a taxi at the appropriate time.

[0223] In the above description, the predicted event end time is presented to the user terminal 111 and the store terminal 113 only when the return vehicle dispatch plan information is presented in the pick-up time field 261 of the confirmation screen 251 in Fig. 13, but it may be displayed at all times only on the user terminal 111 of the event organizer. In this case, the progress rate may also be displayed together with the predicted event end time.

[0224] As described above, the present disclosure makes it possible to appropriately arrange a taxi at a timing desired by the user without any active operation by the user.

[0225] <<3. Improvements in Vehicle Allocation>> The taxi dispatch engine 134 plans the allocation of the plurality of taxis 116-1 to 116-m, but the allocation plan may be improved to increase the utilization rate of the taxis 116.

[0226] For example, as shown in FIG. 15, consider a case where there are three groups of passengers, groups Gp, Gq, and Gr, each of which has a contract to use taxis 116-X, 116-Y, and 116-Z exclusively.

[0227] At this time, the action plan of group Gp is ​​to travel from location A to location B from time t0 to t1, to eat at location B from time t1 to t2, and to travel from location B to location C from time t2 to t3.

[0228] Furthermore, the behavior plan of group Gq is to travel from position D to E from time t0 to t1, from position E to F from time t1 to t2, and from position F to G from time t2 to t3.

[0229] Furthermore, the action plan of group Gr is sightseeing such as walking without the need for a vehicle at location B from time t0 to t1, a tour from location B to H to B from time t1 to t2, and a meal at location B from time t2 to t3.

[0230] In this case, as shown in FIG. 15, the taxi 116-X is in a waiting state from time t1 to t2, and the taxi 116-Z is in a waiting state from time t0 to t1 and from time t2 to t3.

[0231] That is, the taxi 116-X is in a waiting state from time t1 to time t2, and the taxi 116-Z is in a waiting state from time t0 to time t1 and from time t2 to time t3.

[0232] In such a case, the taxi dispatch engine 134 creates a dispatch plan to pick up the guests of group Gr and make a tour from location B to H to B between times t1 and t2 when taxi 116-X is in a waiting state, as shown in FIG. 16.

[0233] With this type of vehicle allocation plan, three groups can be served by just two taxis 116-X and 116-Y, eliminating waiting time, which allows taxi 116-Z to pick up completely different passengers during this time, thereby improving the overall utilization rate.

[0234] <<4. Example of Execution by Software>> The above-described series of processes can be executed by hardware, but can also be executed by software. When the series of processes is executed by software, the program that constitutes the software is installed from a recording medium into a computer that is built into dedicated hardware, or into, for example, a general-purpose computer that can execute various functions by installing various programs.

[0235] 17 shows an example of the configuration of a general-purpose computer. This computer has a built-in CPU (Central Processing Unit) 1001. An input / output interface 1005 is connected to the CPU 1001 via a bus 1004. A ROM (Read Only Memory) 1002 and a RAM (Random Access Memory) 1003 are connected to the bus 1004.

[0236] The input / output interface 1005 is connected to an input unit 1006 including input devices such as a keyboard and a mouse through which a user inputs operation commands, an output unit 1007 that outputs a processing operation screen and images of processing results to a display device, a storage unit 1008 including a hard disk drive or the like that stores programs and various data, and a communication unit 1009 including a LAN (Local Area Network) adapter or the like that executes communication processing via a network typified by the Internet. Also connected is a drive 1010 that reads and writes data from / to a removable storage medium 1011 such as a magnetic disk (including a flexible disk), an optical disk (including a CD-ROM (Compact Disc-Read Only Memory) and a DVD (Digital Versatile Disc)), a magneto-optical disk (including an MD (Mini Disc)), or a semiconductor memory.

[0237] The CPU 1001 executes various processes in accordance with a program stored in a ROM 1002 or a program read from a removable storage medium 1011 such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, installed in a storage unit 1008, and loaded from the storage unit 1008 into a RAM 1003. The RAM 1003 also stores data necessary for the CPU 1001 to execute various processes as appropriate.

[0238] In a computer configured as described above, the CPU 1001 performs the above-described series of processes by, for example, loading a program stored in the memory unit 1008 into the RAM 1003 via the input / output interface 1005 and the bus 1004 and executing it.

[0239] The program executed by the computer (CPU 1001) can be provided by being recorded on a removable storage medium 1011 such as a package medium, for example. The program can also be provided via a wired or wireless transmission medium such as a local area network, the Internet, or digital satellite broadcasting.

[0240] In a computer, a program can be installed in the storage unit 1008 via the input / output interface 1005 by inserting a removable storage medium 1011 into the drive 1010. The program can also be received by the communication unit 1009 via a wired or wireless transmission medium and installed in the storage unit 1008. Alternatively, the program can be installed in advance in the ROM 1002 or the storage unit 1008.

[0241] The program executed by the computer may be a program that processes in chronological order according to the order described in this specification, or may be a program that processes in parallel or at the required timing, such as when called.

[0242] 17 realizes the functions of the CPUs of the user terminal 111, taxi management server 112, shop terminal 113, and settlement server 115 in FIG.

[0243] In this specification, a system refers to a collection of multiple components (devices, modules (components), etc.), regardless of whether all of the components are contained in the same housing. Therefore, multiple devices housed in separate housings and connected via a network, and a single device with multiple modules housed in a single housing, are both systems.

[0244] Furthermore, the embodiments of the present disclosure are not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the present disclosure.

[0245] For example, the present disclosure can be configured as a cloud computing system in which a single function is shared and processed collaboratively by multiple devices via a network.

[0246] Furthermore, each step described in the above flowchart can be executed by one device, or can be shared and executed by a plurality of devices.

[0247] Furthermore, when one step includes multiple processes, the multiple processes included in that one step can be executed by one device or can be shared and executed by multiple devices.

[0248] The present disclosure may also be configured as follows. <1> An information processing system comprising: an action progress information acquisition unit that acquires action progress information of a user; a user action prediction unit that predicts the user's action based on the action progress information; a dispatch condition determination unit that determines conditions for dispatching a taxi as dispatch conditions based on the prediction result of the user action prediction unit; and a dispatch unit that dispatches the taxi based on the dispatch conditions. <2> The information processing system described in <1>, wherein the action progress information is the user's actions. <3> The information processing system described in <2>, wherein the user's actions include getting up to go to the bathroom and taking out one's wallet. <4> The information processing system described in <1>, wherein the action progress information is time information set for an event hosted by the user. <5> The information processing system described in <4>, wherein the time information set for the event hosted by the user includes the start time of the event, the elapsed time from the start time, and the end time of the event. <6> The information processing system described in <1>, wherein the action progress information is information indicating the progress of the event hosted by the user. <7> The information processing system described in <6>, wherein the information indicating the progress of the event hosted by the user includes, if the event is a course meal, the types of dishes, including appetizers, main courses, and desserts, and information indicating the end of the event. <8> The information processing system described in <1>, wherein the behavior progress information is information indicating the content of the event hosted by the user. <9> The information processing system described in <8>, wherein the information indicating the content of the event includes a dinner party at a restaurant and a live event. <10> The user behavior prediction unit predicts an end time of the event hosted by the user or a progress rate of the event based on the behavior progress information, and the dispatch unit dispatches the taxi based on the end time of the event hosted by the user or the progress rate of the event predicted by the user behavior prediction unit.<11> The information processing system described in <10>, wherein the dispatch unit generates a dispatch plan for the taxis based on the end time of the event hosted by the user or the progress rate of the event, and dispatches the taxis based on the dispatch plan when approval of the dispatch plan from the user is obtained. <12> The information processing system described in <11>, wherein the dispatch unit generates the dispatch plan for the taxis based on the end time of the event hosted by the user or the progress rate of the event, generates the dispatch plan for the taxis at a timing that takes into consideration the time required for approval of the dispatch plan from the user, and starts processing to obtain approval of the dispatch plan from the user. <13> The information processing system described in <11> further includes a presentation unit that presents to the user the end time of the event hosted by the user or the progress rate of the event, as well as the vehicle dispatch plan, predicted by the user behavior prediction unit, and accepts operational input for approval or rejection and correction, and when approval of the end time or the progress rate and the vehicle dispatch plan is accepted through the operational input, the vehicle dispatch unit dispatches the taxis based on the vehicle dispatch plan. <14> The information processing system described in <13>, wherein when the modification to at least one of the end time or the progress rate, and the vehicle dispatch plan is accepted through the operation input, the vehicle dispatch unit regenerates the vehicle dispatch plan for the taxis based on the modification; the presentation unit presents to the user the end time of the event hosted by the user, predicted by the user behavior prediction unit, or the progress rate of the event, and the regenerated vehicle dispatch plan, and accepts the operation input for approval or disapproval and the modification; and when approval of the end time or the progress rate, and the regenerated vehicle dispatch plan is accepted through the operation input, the vehicle dispatch unit dispatches the taxis based on the vehicle dispatch plan for which approval has been accepted.<15> The information processing system described in <14>, wherein the presentation unit presents the time when the user will be picked up by the taxi based on the end time or the progress rate, presents the number of taxis to be dispatched based on the dispatch plan, and accepts the operation input for approval or disapproval of the pick-up time and the number of taxis, and for the correction. <16> The information processing system described in <1>, wherein the user behavior prediction unit is configured by a DNN (Deep Neural Network) based on machine learning. <17> The information processing system described in <16>, wherein the user behavior prediction unit re-learns by feeding back training data made up of the behavior progress information used to predict the user's behavior and actual behavior of the user corresponding to the behavior progress information. <18> An information processing method for an information processing system, comprising: a behavior progress information acquisition process for acquiring user behavior progress information, a user behavior prediction process for predicting the user's behavior based on the behavior progress information, a user behavior prediction process for determining conditions for a taxi to be dispatched as dispatch conditions based on a prediction result of the user behavior prediction process, and a dispatch process for dispatching the taxi based on the dispatch conditions. <19> An information processing device comprising: a user behavior prediction unit for predicting the user's behavior based on user behavior progress information, a dispatch condition determination unit for determining conditions for a taxi to be dispatched as dispatch conditions based on a prediction result of the user behavior prediction unit, and a dispatch unit for dispatching the taxi based on the dispatch conditions. <20> A program for causing a computer to function as a user behavior prediction unit for predicting the user's behavior based on user behavior progress information, a dispatch condition determination unit for determining conditions for a taxi to be dispatched as dispatch conditions based on the prediction result of the user behavior prediction unit, and a dispatch unit for dispatching the taxi based on the dispatch conditions.

[0249] DESCRIPTION OF SYMBOLS 101 Information processing system, 111 User terminal, 112 Taxi management server, 113 Store terminal, 114, 114-1 to 114-6 Store sensors, 115 Payment server, 121 Touch panel, 122 Taxi store reservation application, 131 Taxi reservation management unit, 132 Database, 133 Taxi number prediction engine, 134 Taxi dispatch engine, 135 User behavior engine, 171 Store reservation management unit, 172 User behavior progress acquisition unit, 173 Meal provision information acquisition unit, 174 Payment processing unit, 175 Touch panel, 201 Store

Claims

1. An information processing system comprising: a behavioral progress information acquisition unit that acquires user behavioral progress information; a user behavior prediction unit that predicts the user's behavior based on the behavioral progress information; a dispatch condition determination unit that determines the conditions for dispatching a taxi as dispatch conditions based on the prediction results of the user behavior prediction unit; and a dispatch unit that dispatches the taxi based on the dispatch conditions.

2. The information processing system according to claim 1, wherein the action progress information is the user's actions recognized based on sensor information.

3. The information processing system according to claim 2, wherein the user's actions include standing up to go to the toilet and taking out a wallet.

4. The information processing system according to claim 1, wherein the action progress information is time information set for an event held by the user.

5. The information processing system according to claim 4, wherein the time information set for the event organized by the user includes a start time of the event, an amount of time elapsed since the start time, and an end time of the event.

6. The information processing system according to claim 1, wherein the action progress information is information indicating the progress of an event held by the user.

7. The information processing system of claim 6, wherein the information indicating the progress of the event hosted by the user includes, if the event is a course meal, the type of food including appetizer, main course, and dessert, and information indicating the end of the event.

8. The information processing system according to claim 1, wherein the action progress information is information indicating the content of an event held by the user.

9. The information processing system according to claim 8, wherein the information indicating the content of the event includes a dinner party at a restaurant and a live event.

10. The information processing system of claim 1, wherein the user behavior prediction unit predicts the end time of an event hosted by the user or the progress rate of the event based on the behavior progress information, and the dispatch unit dispatches the taxi based on the end time of the event hosted by the user or the progress rate of the event predicted by the user behavior prediction unit.

11. The information processing system described in claim 10, wherein the dispatch unit generates a dispatch plan for the taxis based on the end time of the event hosted by the user or the progress rate of the event, and when the user's approval for the dispatch plan is obtained, dispatches the taxis based on the dispatch plan.

12. The information processing system described in claim 11, wherein the dispatch unit generates the dispatch plan for the taxis based on the end time of the event hosted by the user or the progress rate of the event, and generates the dispatch plan for the taxis at a timing that takes into account the time required to obtain approval for the dispatch plan from the user, and starts the process of obtaining approval for the dispatch plan from the user.

13. The information processing system of claim 11, further comprising a presentation unit that presents to the user the end time of the event hosted by the user or the progress rate of the event, as well as the dispatch plan, predicted by the user behavior prediction unit, and accepts operational input for approval or rejection and correction, and when approval of the end time or the progress rate and the dispatch plan is accepted through the operational input, the dispatch unit dispatches the taxis based on the dispatch plan.

14. The information processing system of claim 13, wherein when the modification to at least one of the end time or the progress rate and the dispatch plan is accepted through the operation input, the dispatch unit regenerates the dispatch plan for the taxis based on the modification; the presentation unit presents to the user the end time of the event hosted by the user predicted by the user behavior prediction unit or the progress rate of the event, and the regenerated dispatch plan, and accepts the operation input for approval or disapproval and the modification; and when approval of the end time or the progress rate and the regenerated dispatch plan is accepted through the operation input, the dispatch unit dispatches the taxis based on the dispatch plan for which approval has been accepted.

15. The information processing system of claim 14, wherein the presentation unit presents the time when the user will be picked up by the taxi based on the end time or the progress rate, presents the number of taxis to be dispatched based on the dispatch plan, and accepts the operation input for approval or disapproval of the pick-up time and the number of taxis, and for the correction.

16. The information processing system according to claim 1, wherein the user behavior prediction unit is configured by a DNN (Deep Neural Network) based on machine learning.

17. The information processing system described in claim 16, wherein the user behavior prediction unit re-learns by feeding back training data consisting of the behavior progress information used to predict the user's behavior and the actual user behavior corresponding to the behavior progress information.

18. An information processing method for an information processing system, comprising: a behavioral progress information acquisition process for acquiring user behavioral progress information; a user behavior prediction process for predicting the user's behavior based on the behavioral progress information; a dispatch condition determination process for determining the conditions for dispatching a taxi as dispatch conditions based on the prediction results of the user behavior prediction process; and a dispatch process for dispatching the taxi based on the dispatch conditions.

19. An information processing device comprising: a user behavior prediction unit that predicts the behavior of a user based on the user's behavior progress information; a dispatch condition determination unit that determines the conditions for dispatching a taxi as dispatch conditions based on the prediction results of the user behavior prediction unit; and a dispatch unit that dispatches the taxi based on the dispatch conditions.

20. A program that causes a computer to function as a user behavior prediction unit that predicts the user's behavior based on the user's behavior progress information, a dispatch condition determination unit that determines the conditions for dispatching a taxi as dispatch conditions based on the prediction results of the user behavior prediction unit, and a dispatch unit that dispatches the taxi based on the dispatch conditions.

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