JP6987703B2 - Policy decision system and policy decision method - Google Patents

Description

The present invention relates to a policy decision system and a policy decision method for determining measures.

Patent Document 1 discloses a mobile terminal device equipped with functions of electronic money and a commuter pass. Patent Document 2 discloses that a fare calculation device such as an automatic ticket gate whose validity has been verified for calculating a fare between two stations can be used to calculate an out-of-route fare settlement fare. Patent Document 3 discloses an electronic money settlement system that enables refund of the remaining amount of an IC card with an electronic money function once charged. Patent Document 4 discloses an estimation method for estimating the situation around a station by using ticket gate information.

Japanese Unexamined Patent Publication No. 2009-265997 Japanese Unexamined Patent Publication No. 2010-003180 Japanese Unexamined Patent Publication No. 2010-086334 Japanese Unexamined Patent Publication No. 2014-006743

When an influx outside the target area flows into a specific area within the target area, there is a concern that the population density of the specific area will temporarily increase, congestion will occur in the specific area, and a large amount of garbage will be generated. However, in the above-mentioned conventional technique, the measures to be taken for the occurrence of traffic congestion and the increase of garbage in a specific area are not considered.

An object of the present invention is to present effective measures in a specific area.

The policy-determining system and the policy-determining method, which are one aspect of the invention disclosed in the present application, include a policy-determining system composed of one or more computers having a processor for executing a program and a storage device for storing the program. As a measure determination method, the storage device corresponds to a plurality of measure proposals that specify a solution method for solving a problem in a specific area in a target area, a target value for problem solution, and a degree of solution of the problem. The attached problem solving information, cost information for storing the target value of the cost required for solving the problem, the predicted amount of the problem, the supplyable amount for the problem for each of the plurality of policy proposals, and the above. It remembers the estimated cost when the measure plan is executed, and the processor corresponds to the supplyable amount for the problem for each of the plurality of measure plans based on the solution method in the measure plan. The amount of decrease in the predicted amount of the problem is calculated, the target value for solving the problem corresponding to the ratio of the amount of decrease to the predicted amount of the problem is specified, and the degree of resolution corresponding to the specified target value is determined. For each of the first specific process specified from the problem solving information and the plurality of measures, the second specification to specify the target value of the cost corresponding to the estimated cost when the measure is executed from the cost information. For each of the processing and the plurality of measures, the measures are based on the degree of solution of the problem specified by the first specific processing and the target value of the cost specified by the second specific processing. A calculation process for calculating the cost-effectiveness of a proposal, and a selection process for selecting two or more specific policy proposals with relatively high cost-effectiveness calculated by the calculation process from the plurality of policy proposals. Output processing to send two or more specific measure proposals selected by the selection process to the terminals of residents in the target area, and measure proposals selected from the two or more specific measure proposals from the terminal. It is characterized by receiving and executing a decision process of deciding a measure by a majority decision.
The policy-determining system and the policy-determining method, which are other aspects of the invention disclosed in the present application, are a policy-determining system composed of one or more computers having a processor for executing a program and a storage device for storing the program. In addition, as a measure determination method, the storage device sets a plurality of measure proposals that specify a solution method for solving a problem in a specific area in a target area, a target value for problem solution, and a degree of solution of the problem. The associated problem-solving information, the cost information for storing the target value of the cost required for solving the problem, the predicted amount of the problem, and the supplyable amount for the problem for each of the plurality of policy proposals. The estimated cost when the measure plan is executed is stored, and the processor responds to the supplyable amount for the problem for each of the plurality of measure plans based on the solution method in the measure plan. The amount of decrease in the predicted occurrence amount of the problem is calculated, the target value for solving the problem corresponding to the ratio of the decrease amount to the predicted occurrence amount of the problem is specified, and the degree of resolution corresponding to the specified target value is determined. , The first specific process specified from the problem solving information, and the target value of the cost corresponding to the estimated cost when the measure plan is executed for each of the plurality of measure plans is specified from the cost information. For each of the specific processing and the plurality of measures, the above-mentioned problem is solved by the first specific processing, and the target value of the cost specified by the second specific processing is used. A calculation process for calculating the cost-effectiveness of a measure plan, and a selection process for selecting two or more specific measure plans with a relatively high cost-effectiveness calculated by the calculation process from the plurality of measure plans. , An output process that outputs two or more specific measure proposals selected by the selection process, and a specific computer in the computer group that manages the means of transportation by executing the output process, which is a visitor from outside the target area. The usage amount data and the usage amount data when the visitor uses the transportation means into the specific area by having a detector in the specific area capable of short-range communication with the terminal and the specific processor in the specific computer. When the acquisition process of acquiring donation information to the target area from the visitor's terminal and storing it in a specific storage device in the specific computer, and when the detector detects the visitor's terminal. It is characterized by executing a transmission process of transmitting the donation information from the specific storage device to the storage device. do.

According to a typical embodiment of the present invention, effective measures in a specific area can be presented. Issues, configurations and effects other than those described above will be clarified by the description of the following examples.

FIG. 1 is an explanatory diagram showing an activation example 1 by a measure decision system. FIG. 2 is an explanatory diagram showing an activation example 2 by the measure decision system. FIG. 3 is an explanatory diagram showing a system configuration example of the measure decision system. FIG. 4 is a block diagram showing an example of the hardware configuration of the computer shown in FIG. FIG. 5 is an explanatory diagram showing a hardware configuration example of the management system of the railway company shown in FIG. FIG. 6 is an explanatory diagram showing an example of the stored contents of the railway information DB shown in FIGS. 3 and 5. FIG. 7 is an explanatory diagram showing an example of the stored contents of the local government information DB shown in FIG. FIG. 8 is an explanatory diagram showing an example of the stored contents of the fund information DB shown in FIG. FIG. 9 is an explanatory diagram showing an example of the stored contents of the sponsor company information DB. FIG. 10 is a sequence diagram showing an example of a ticket reservation purchase sequence. FIG. 11 is a sequence diagram showing an example of a donation acquisition sequence. FIG. 12 is a sequence diagram showing an example of a measure determination sequence. FIG. 13 is an explanatory diagram showing an example of problem solving KPI data. FIG. 14 is an explanatory diagram showing an example of measure proposal data. FIG. 15 is an explanatory diagram showing cost KPI data. FIG. 16 is a flowchart showing an example of a measure plan determination processing procedure by the analyzer shown in step S1207 of FIG.

Hereinafter, the measure decision system in this embodiment will be described with reference to the attached drawings. The policy decision system is to use donations from people who visit a specific area within the target area from outside the target area (hereinafter, visitors) to use donations to cover the target area together with the residents of the target area (hereinafter, local people). It is a local citizen participation type system that decides measures to solve the problems that occur in the target area due to the visit of visitors. In this embodiment, a railroad is taken as an example of a means of transportation for a visitor, and a donation from a visitor is described as an additional charge to the railroad fare. However, the means of transportation for visitors is not limited to railways, but may be other means of transportation such as buses, ships, and airplanes. Further, the means of visit is not limited to the means of transportation, and may be an event such as a concert or a sport held in the target area. In this case, the donation may be added to the transportation fare or the event ticket.

<Example of activation by policy decision system>
FIG. 1 is an explanatory diagram showing an activation example 1 by a measure decision system. The railway network 100 is a means of transportation for the train 109 to move. Train 109 stops at stations 101 and 102 on the railway network. There are ticket gates 103 at stations 101 and 102, and visitors 104 can pass through. The visitor 104 has a mobile terminal 105. If the visitor 104 has purchased a ticket from the station 101 to the station 102 in advance, the mobile terminal 105 of the visitor 104 holds information indicating that the ticket has been purchased. When the visitor 104 passes through the ticket gate 103 of the station 101, by short-range communication (for example, RFID) with the ticket gate 103, the railway company management system 302 (see FIG. 3) enters the visitor 104. Judge permission. If admission is permitted, the railway company's management system 302 opens the ticket gate 103 to allow the visitor 104 to pass through.

If the visitor 104 has not purchased a ticket from the station 101 to the station 102 in advance, the management system 302 of the railway company will use the mobile terminal during short-distance communication between the mobile terminal 105 of the visitor 104 and the ticket gate 103. Obtain the amount of the initial fare from the amount charged in 105.

The visitor 104 gets on at the station 101 and gets off at the station 102. The visitor 104 passes through the ticket gate of the station 102. When the visitor 104 passes through the ticket gate 103 of the station 101, the railway company's management system 302 determines the exit permission of the visitor 104 by short-range communication between the mobile terminal 105 of the visitor 104 and the ticket gate 103. do. If the exit is permitted, the railway company's management system 302 opens the ticket gate 103 and allows the visitor 104 to pass through. At this time, the management system 302 of the railway company acquires donations from the mobile terminal 105 of the visitor 104 via the ticket gate 103. Regarding the donation of donations, it is assumed that the visitor 104 has set the permission to acquire the donation on the mobile terminal 105 of the visitor 104 in advance.

If the visitor 104 has not purchased a ticket from the station 101 to the station 102 in advance, the management system 302 of the railway company will use the mobile terminal during short-distance communication between the mobile terminal 105 of the visitor 104 and the ticket gate 103. From the amount charged in 105, the difference between the fare from station 101 to station 102 minus the initial fare and the donation are obtained. Donations from the visitor 104 are pooled from the railway company's management system 302 to a fund 120 such as an NPO (Nonprofit Organization) corporation.

The station 102 exists in the central 110, which is an example of a specific area in the target area of the local people 130. In the central 110, there are accommodation facilities 111 such as hotels, commercial stores 112, commercial buildings 113, office buildings 114, and event venues 115 such as halls, arenas, and stadiums for visitors 104 and locals to visit. exist.

FIG. 2 is an explanatory diagram showing an activation example 2 by the measure decision system. Activation example 2 shows an example in which a problem occurs when a visitor 104 visits on the day when the event is held at the event venue 115. Since the number of visitors 104 to the central 110 increases rapidly on the day of the event, traffic jams occur in the central 110, garbage around the event venue 115 increases, and the locals 130 are between the central 110 and the central 110. There is a problem that it interferes with the movement of the.

Therefore, using the donations pooled in advance in the fund 120, the fund 120 proposes a plurality of measures to solve problems in a specific area in the target area based on the demand forecast on the date of the event. suggest. Multiple measures include, for example, the operation of a temporary bus that transports visitors 104 between the station 102 and the event venue 115, an increase in the frequency of garbage collection at the central 110, and a shared office for locals 130 (central area). The opening of the gate (outside 110) and the provision of a discount service for the accommodation expenses of the previous night visitors 104 to alleviate the congestion at the station 102 can be mentioned. The local people 130 vote on a plurality of proposed measures, and the measure with the largest number of votes is executed.

In this way, the use of the pooled donations is determined by the locals 130, and the pooled donations are used for the area, so the pooled donations are for the locals 130 to live comfortably. Equally returned to the development of the city. In addition, with the intervention of the fund 120, which formulates urban development measures for residents, it will be possible to propose a mechanism in which residents who do not use the railroad can voluntarily participate in the changes in the city due to the increase in visitors by 104.

In addition, the more visitors 104 visit, the more comfortable the city will continue to develop. For example, pooled donations are used to avoid undesired situations for locals, such as sudden and temporary traffic jams in the city caused by a large number of visitors 104 and the loss of aesthetics due to littering of garbage. That is, it is reduced that the number of visitors 104 increases, which makes the city rather inconvenient and unattractive for the locals 130.

In addition, the choice of the locals 130 will reveal the "usage" that will improve the city. For example, based on the demand forecast of the city, the service provider of the fund 120 will "run a temporary bus", "increase the frequency of garbage collection", "open a shared office for locals 130 for free", etc. for a short period of time. We propose multiple uses for spans. Finally, the residents vote for the proposal to determine how the pooled donations will be used.

In addition, by introducing the policy decision system, it is expected that the local people 130 will take action to improve the city by themselves while involving the local business. For example, a service provider of Fund 120 encourages locals 130 to propose how to use the pooled donations, and more culturally, such as "travel expenses for instructors called from big cities" and "workshops for citizens". Residents will be able to propose how to use the long-term span so that they can develop. The changes in the city will change for each 130 locals, and the railway will become familiar as a supporter of the maturity of the city. The pooled donations will be returned to the community, revitalizing local businesses and supporting the continued development of the city.

<System configuration example of policy decision system>
FIG. 3 is an explanatory diagram showing a system configuration example of the measure decision system. The policy decision system 300 includes an analyzer 301, a management system 302, a public system 303, an operation system 304, a sponsor company system 305, a mobile terminal 105 of a visitor 104, a digital signage 363, an in-vehicle voice interface 362, and a mobile of a local citizen 130. The terminal 361 is communicably connected via a network 310 such as the Internet. The system is one computer or two or more computers that cooperate with each other. That is, the measure decision system 300 is composed of one or more computers.

The analyzer 301 is a computer that predicts the demand of the central area 110 and analyzes the measures to be proposed to the local people 130. The management system 302 is a specific computer system in which a railway company manages a railway network or a station. The management system 302 has a railway information DB 320 that stores railway information. Further, the management system 302 is communicably connected to the ticket gate 103. The ticket gate 103 is a detector in a specific area capable of short-range communication with the terminal 105 of a visitor from outside the target area.

The public system 303 is a computer system managed by the local government in the area. The public system 303 is connected to a population transition DB 331 that stores the population transition of the area, a traffic information DB 332 that stores the traffic information of the area, and a local government information DB 333 that stores the local government information of the area. The public system 303 is also connected to a surveillance camera 330 that monitors the central area 110.

The operation system 304 is a computer system operated by a service provider which is a fund 120. The operation system 304 is connected to the fund information DB 340 that stores the fund 120 information. The sponsor company system 305 is a computer system managed by a sponsor company that sponsors the area. The sponsor company system 305 is connected to the sponsor company information DB 350 that stores information about the sponsor company (sponsor company information). The supporting companies are, for example, a temporary bus operating company, an accommodation facility 111, a shared office operating company, and a garbage cleaning company.

The digital signage 363 is a display device installed in the area and displaying a measure plan from the operation system 304. The in-vehicle voice interface 362 is provided in a car owned by a local citizen 130, for example, and outputs a voice output of a measure plan from the operating system 304. For example, the in-vehicle voice interface 362 controls the operation system 304, and when the measure plan is the free opening of the shared office, the in-vehicle voice interface 362 guides the position of the shared office of the nearby free opening by voice from the current position of the car. The mobile terminal 361 of the local people 130 is a terminal owned by the local people 130 such as a smartphone, and displays a measure plan from the operation system 304, or accepts a selection of the displayed measure plan and sends it to the operation system 304. do.

<Computer hardware configuration example>
FIG. 4 is a block diagram showing an example of the hardware configuration of the computer shown in FIG. The computer 400 has a processor 401, a storage device 402, an input device 403, an output device 404, and a communication interface (communication IF) 405. The processor 401, the storage device 402, the input device 403, the output device 404, and the communication IF 405 are connected by the bus 406. The processor 401 controls the computer 400. Processor 401 executes the program. The storage device 402 serves as a work area for the processor 401. Further, the storage device 402 is a non-temporary or temporary recording medium for storing various programs and data. Examples of the storage device 402 include a ROM (Read Only Memory), a RAM (Random Access Memory), an HDD (Hard Disk Drive), and a flash memory. The input device 403 inputs data. The input device 403 includes, for example, a keyboard, a mouse, a touch panel, a numeric keypad, and a scanner. The output device 404 outputs data. The output device 404 includes, for example, a display and a printer. The communication IF 405 connects to the network 310 and transmits / receives data.

<Hardware configuration example of management system 302>
FIG. 5 is an explanatory diagram showing a hardware configuration example of the management system 302 of the railway company shown in FIG. The management system 302 includes a donation management device 501, an income management device 502, an operation management device 503, a reservation management device 504, a ticket gate 103, and a railway information DB 320. The donation management device 501, the income management device 502, the operation management device 503, the reservation management device 504, the ticket gate 103, and the railway information DB 320 are connected by the bus 505.

The donation management device 501 is a computer that manages donations from visitors 104. The income management device 502 is a computer that manages income from purchasing a ticket. The income management device 502 holds personal information including the customer's credit card and bank account number, and can settle the payment when the customer purchases a ticket, for example. The operation management device 503 is a computer that manages the operation of the train 109. The reservation management device 504 is a computer that manages boarding dates, flights, and seat reservations. The railway information DB 320 includes a donation management device 501, an income management device 502, an operation management device 503, and a reservation management device 504, such as usage history, usage forecast, fare, flight and seat ticket information, customer information, and donations. It is a database that stores the information used.

The visitor 104 communicates with the reservation management device 504 using the mobile terminal 105, reserves and purchases a ticket by designating the flight and seat of the date and time to board, and stores the reserved ticket information in the mobile terminal 105. Store in device 402. Similarly, the reservation management device 504 stores the ticket information in the railway information DB 320. The ticket gate 103 transmits the ticket information to the reservation management device 504 by short-range communication with the mobile terminal 105. If the ticket information from the ticket gate 103 matches the ticket information in the railway information DB 320, the reservation management device 504 opens the ticket gate 103 and passes the visitor 104.

<Example of stored contents of railway information DB 320>
FIG. 6 is an explanatory diagram showing an example of the stored contents of the railway information DB 320 shown in FIGS. 3 and 5. In FIG. 6, the usage forecast will be described as railway information. The usage forecast is generated based on the pre-purchased ticket information. The railway information DB 320 stores the station 601 used, the type 602 used, the number of people 603, and the scheduled date and time of use 604 as usage forecasts. The station 601 is a station that the user uses (gets on or off). The usage type 602 is a type (boarding or disembarking) in which the station 601 is used. The number of people 603 is the number of users who use the usage type 602 at the usage station 601. The scheduled use date and time 604 is the date and time when the user uses the station 601.

<Local government information DB333>
FIG. 7 is an explanatory diagram showing an example of the stored contents of the local government information DB 333 shown in FIG. In FIG. 7, the congestion status on the target route from the station 102 to the event venue 115 is input in advance by the administrator as local government information. The local government information DB 333 stores the event 701, the traffic volume 702 in front of the station, the signal time 703, the number of intersections 704, and the expected utilization rate 705 of the street parking lot as the congestion status. Event 701 is information that identifies an event held in a specific area. The traffic volume 702 in front of the station is the number of vehicles passing in front of the station 102 per hour. The signal time 702 is the average value of the waiting time of the signal existing on the target path. The number of intersections 703 is the number of intersections on the target route. The expected utilization rate of the street parking lot 705 is the expected utilization rate of the street parking lot existing on the target route.

<Fund information DB340>
FIG. 8 is an explanatory diagram showing an example of the stored contents of the fund information DB 340 shown in FIG. The fund information DB 340 stores the district name 801 and the event occurrence date 802, the number of voters 803, the selection measure plan 804, the voter's measure plan usage status 805, and the satisfaction level 806 as the fund information. .. The district name 801 is the district where the event occurred. Events include events. Congestion may occur in the area other than the event. The event occurrence date 802 is the date when the event occurred. The number of voters 803 is the number of locals 130 who voted for the selection of the policy plan. The selection measure plan 804 is a measure plan selected as a result of voting. The voter's policy proposal usage status 805 is the number of voters who used the selective policy plan 804. Satisfaction level 806 is an average value of satisfaction levels transmitted from the voter's mobile terminal 105.

<Supporting company information DB350>
FIG. 9 is an explanatory diagram showing an example of the stored contents of the sponsor company information DB 350. In FIG. 9, a bus operating company will be described as an example of a supporting company. The sponsor company information DB 350 stores the company name 901, the number of owned units 902, the size / capacity 903, the planned use 904, and the operation rate history 905 as the sponsor company information. The company name 901 is the company name of the bus operating company. The number of buses owned is the number of buses owned by the bus operating company with the company name 901. The size / capacity 903 is the size and capacity of the bus owned by the bus operating company with the company name 901. Scheduled use 904 is the number of people scheduled to use each day. The occupancy rate history 905 is the monthly occupancy rate of the bus operating company with the company name 901.

<Example of ticket reservation purchase sequence>
FIG. 10 is a sequence diagram showing an example of a ticket reservation purchase sequence. The visitor 104 makes a reservation operation for the mobile terminal 105 of the visitor 104 (step S1001). When the mobile terminal 105 receives the reservation operation (step S1001), the mobile terminal 105 transmits the information input in the reservation operation to the reservation management device 504 as a reservation request (step S1002). Upon receiving the reservation request, the reservation management device 504 executes a provisional reservation process for the departure / arrival date / time, the boarding / alighting station, and the seat specified in the reservation request (step S1003). The reservation management device 504 transmits the disembarkation station information obtained in the provisional reservation process (step S1003) to the donation management device 501 (step S1004).

When the donation management device 501 receives the disembarkation station information (step S1004), the donation management device 501 determines whether or not the donation is set for the disembarkation station (step S1005). The donation setting is a setting for acquiring a donation from the mobile terminal 105 of the visitor 104 when the visitor 104 passes through the ticket gate 103 of the getting-off station. Donation settings are set for each station. The donation management device 501 returns the determination result of the donation setting to the reservation management device 504 (step S1006).

When the reservation management device 504 receives the determination result, if the determination result has the donation setting, the reservation management device 504 transmits the fare and the donation information in the case of the reservation request (step S1002) to the mobile terminal 105 (step S1007). As a result, the mobile terminal 105 displays fare and donation information.

The visitor 104 sees the fare and donation information displayed on the mobile terminal 105, and performs a purchase operation such as inputting the credit card number of the visitor 104 to the mobile terminal 105 (step S1008). When the mobile terminal 105 accepts the purchase operation, the mobile terminal 105 sends the reservation management device 504 the payment information for confirming the departure / arrival date / time, the boarding / alighting station, and the purchase of the seat specified in the reservation request (step S1002). Transmit (step S1009).

When the reservation management device 504 receives the payment information, it communicates with, for example, the income management device 502 or the server of the credit card company (holding personal information including the credit card number and the bank account number of the visitor 104) to process the payment. And issue a ticket ID (step S1010). The reservation management device 504 transmits information on the visitor 104, ticket ID, arrival date and time, getting-off station, and donation (hereinafter referred to as donation information) to the donation management device 501 (step S1011).

Upon receiving the donation information, the donation management device 501 records the donation information in the storage device 402 (step S1012), and notifies the reservation management device 504 of the completion of the recording (step S1013). Upon receiving the notification of the completion of recording (step S1013), the reservation management device 504 transmits the fare information to the income management device 502 (step S1014).

Upon receiving the fare information, the income management device 502 notifies the reservation management device 504 of the completion of recording (step S1016). Upon receiving the notification of the completion of recording, the reservation management device 504 executes the reservation process based on the processing content of the provisional reservation process (step S1003) to generate ticket information (step S1017).

Ticket information includes, for example, ticket ID, departure / arrival date / time, boarding / alighting station, seat, fare and donation information. The reservation management device 504 transmits the ticket information to the mobile terminal 105 (step S1018). The mobile terminal 105 records the ticket information in the storage device 402 (step S1019) and displays the ticket information (step S1020). As a result, the visitor 104 can confirm the ticket information.

<Example of donation acquisition sequence>
FIG. 11 is a sequence diagram showing an example of a donation acquisition sequence. The visitor 104 in FIG. 11 is the visitor 104 in which the ticket information is recorded in the mobile terminal 105 in FIG. At the station 102 where the train gets off, the visitor 104 touches the mobile terminal 105 on the ticket gate 103 (step S1101). The mobile terminal 105 transmits a participation request to the ticket gate 103 by short-range communication with the ticket gate 103 (step S1102).

The entry request includes the ticket ID in the ticket information, the arrival date and time, and the information of the getting-off station. Upon receiving the entry request, the ticket gate 103 executes the entry availability determination based on the entry request (step S1103). For example, if the information of the getting-off station in the entry request identifies the station where the ticket gate 103 is installed and the arrival time is after the current time, the ticket gate 103 determines that the entry is permitted.

When the ticket gate 103 determines that the entry is permitted, the ticket gate 103 transmits the ticket ID included in the entry request to the donation management device 501 (step S1104). When the donation management device 501 receives the ticket ID from the ticket gate 103, the donation management device 501 searches for donation information having a ticket ID that matches the received ticket ID (step S1105). When the donation information matching the ticket ID is searched, the donation management device 501 transmits the donation information matching the ticket ID to the operation system 304 (step S1107).

The operation system 304 records the received donation information in the storage device 402 (step S1107), and notifies the donation management device 501 of the completion of recording the donation information (step S1108). The donation management device 501 records the information of the remitted donation in the storage device 402 (step S1109), and notifies the ticket gate 103 of the completion of the donation remittance processing (step S1110).

Upon receiving the processing completion, the ticket gate 103 transmits the entry permission to the mobile terminal 105 (step S1112), and the mobile terminal 105 records the entry (step S1113). Further, when the ticket gate 103 receives the processing completion, it records the participation (step S1111), opens the ticket gate 103, and permits the visitor 104 to participate (step S1114).

As described with reference to FIGS. 10 and 11, the payment amount of the ticket purchased by the visitor 104 is recorded in the income management device 502 at the time of purchasing the ticket, and the donation donated by the visitor 104 is recorded at the time of purchasing the ticket. , Recorded in the donation management device 501. When the visitor 104 actually participates from the getting-off station, the donation is transferred from the donation management device 501 to the operation system 304.

In addition, the purchase of the ticket will be settled by credit, and the donation will be paid out from the electronic money charged in the mobile terminal 105 when the ticket gate 103 of the getting off station is entered. May be sent to the donation management device 501 via the ticket gate 103.

<Example of policy decision sequence>
FIG. 12 is a sequence diagram showing an example of a measure determination sequence. The analysis device 301 transmits an analysis source data request to the reservation management device 504 (step S1201). The analysis source data request includes, for example, the target date and time and the target station. Upon receiving the analysis source data request, the reservation management device 504 accesses the railway information DB 320, collects the target date and time and the number of entries corresponding to the target station 601 as analysis source data (step S1201), and the analysis device 301. (Step S1203).

Similarly, the analyzer 301 sends an analysis source data request to the public system 303 (step S1204). The analysis source data request includes, for example, the target event. Upon receiving the analysis source data request, the public system 303 accesses the municipal information DB 333 and analyzes the traffic volume in front of the station, the signal time, the number of intersections, and the expected utilization rate of the street parking lot of the entry corresponding to the target event. It is collected as source data (step S1205) and returned to the analyzer 301 (step S1206).

Also, not shown. The analyzer may send an analysis source data request to the sponsoring company system 305. When the sponsor company system 305 receives the analysis source data request, it accesses the local government information DB 333, collects the past actual data as the analysis source data, and returns it to the analysis device 301.

After that, when the analyzer 301 receives the analysis source data, it executes the demand forecast and determines the measure plan (step S1208). The result of the demand forecast is the forecast occurrence amount of the problem. The demand forecast may be a known process. Further, the analyzer 301 may execute the demand forecast, or may acquire the result of the demand forecast executed by another computer. The details of step S1208 will be described later. The analyzer 301 transmits a plurality of determined measure proposals to the operation system 304 (step S1208).

When the operation system 304 receives the plurality of measure proposals from the analyzer 301, the operation system 304 distributes the plurality of measure proposals to the mobile terminal 105 of the local people 130 and displays the plurality of measure proposals (step S1209). Further, the operation system 304 may also transmit and display a plurality of measure proposals to the digital signage 363. The local people 130 select one of the plurality of policy proposals for the mobile terminal 361 and perform a voting operation (step S1210). The mobile terminal 361 transmits the voting result to the operating system 304 (step S1211).

The operation system 304 receives the voting results, aggregates them, determines the measure to execute the measure plan of the maximum number of votes (step S1212), and transmits the guidance notification of the decided measure to the mobile terminal 105 (step S1213). After that, the operation system 304 transmits a measure execution request to the sponsor company system 305 by the operation of the administrator of the operation system 304 (step S1214). The sponsor company system 305 executes the measure (step S1215). For example, if the sponsoring company is a bus operating company and the decided measure is "temporary bus free operation", the sponsoring company will execute the temporary bus free operation. The sponsor company system 305 transmits a measure execution notification to the operation system 304 (step S1215).

The operation system 304 collects the effect of the measure (step S1216) and transmits it to the analyzer 301 (step S1217). For example, if the measure is "free temporary bus operation", the measure effect is the number of temporary buses, the number of passengers, and the occupancy rate, and if the measure is "increased garbage collection frequency", the measure effect is the garbage collection vehicle. If the measure is "free opening of shared offices to locals", the effect of the measure is the number of shared offices and the occupancy rate of shared offices, and the measure is "visit the night before". In the case of "Providing a discount service for accommodation facilities of the person", the effect of the measure is the number of visitors of the previous night 104. Further, the public system 303 may transmit the image from the surveillance camera 330 during the implementation of the measure to the analyzer 301 as the result of the measure.

The analysis device 301 receives and analyzes the measure result (step S1218), and returns the analysis result to the reservation management device 504 or the public system 303 (step S1219). The analyzer 301 identifies, for example, the number of people in the center 110 during the implementation of the measure from the video of the surveillance camera 330. The analyzer 301 compares the number of people in the center 110 during the implementation of the measure with the number of people in normal times. For example, if the comparison result is less than the number of people in normal times, it can be seen that the implementation of the measures was effective. Further, when the comparison result is larger than the number of people in normal times, the analyzer 301 uses the recommendation information that the measures should be strengthened according to the increased number of people as the analysis result, and the reservation management device 501, the public system 303, and the operation system. Return to 304, and the sponsoring company system 305.

For example, if the measure is "free temporary bus operation" and the comparison result is larger than the number of people in normal times, the analyzer 301 generates proposal information that the number of temporary bus operations should be increased, and as an analysis result. Return to the operating system 304 and the sponsoring company system 305.

<Example of policy proposal determination processing by analyzer 301>
Next, an example of the measure plan determination process by the analyzer 301 will be described with reference to FIGS. 13 to 16. FIG. 13 is an explanatory diagram showing an example of problem solving KPI (Key Performance Indicator) data. The problem-solving KPI data 1300 is a data table showing problem-solving information that defines the problem-solving degree for each problem-solving KPI, and is possessed by the analyzer 301. The problem-solving KPI indicates the target value of the problem-solving, and the problem-solving degree indicates the rank of the problem-solving KPI. The higher the value of the problem solving degree, the higher the achievement effect of the problem solving KPI.

FIG. 14 is an explanatory diagram showing an example of measure proposal data. The measure plan data 1400 is a data table having one or more measure plans for each of a plurality of types of measure plans (three types A to C in FIG. 14), and is possessed by the analyzer 301. In FIG. 14, in the measure plan X # (X is a measure plan type A to C, # is a number), the smaller the number # is, the more effective the measure plan is.

FIG. 15 is an explanatory diagram showing cost KPI data. The cost KPI data 1500 is a data table showing cost information associated with the cost rank for each cost KPI, and is owned by the analyzer 301. The cost KPI is the target value of the cost required to solve the problem. Regarding the cost rank, C is the lowest rank, that is, the policy plan with the highest cost, and AAA is the highest rank, that is, the policy plan with the lowest cost.

FIG. 16 is a flowchart showing an example of a measure proposal determination processing procedure by the analyzer 301 shown in step S1207 of FIG. First, the analyzer 301 acquires the predicted inflow / outflow information of the visitor 104 as the predicted generation amount of the problem (step S1601). Specifically, for example, the analyzer 301 acquires the analysis source data (the target date and time and the number of entries corresponding to the target station 601) acquired from the railway information DB 320 as the predicted inflow / outflow information.

Next, the analyzer 301 determines whether or not the predicted inflow / outflow information of the visitor 104 acquired in step S1601 is normal or higher (step S1602). If it is normal or higher (step S1602: Yes), it is predicted that congestion will occur (step S1603), and if it is not normal or higher (step S1602: No), it is predicted that congestion will not occur (step S1604), and processing is performed. To finish.

For example, the analyzer 301 determines whether or not the number of people getting on and off the predicted inflow / outflow information acquired in step S1601 is 150% or more of the number of people getting on and off the target station 102 in normal times. do. If it is 150% or more (step S1602: Yes), the analyzer 301 predicts that congestion will occur (step S1603), and if it is not 150% or more (step S1602: No), it predicts that congestion will not occur (step S1604). ), End the process.

When it is predicted that a traffic jam will occur (step S1603), the analyzer 301 executes the first specific process for specifying the problem solving degree for each of the measure proposals A to C from the measure proposal data 1400 (step S1605). Specifically, for example, the analyzer 301 selects a measure plan one by one from the measure plan types A to C. In this case, the analyzer 301 may select the measure proposals A1, B1, and C1 having the smallest number #, or may select the measure proposal having the smallest number # among the available measure proposals. For example, based on the data acquired from the sponsor company information DB 350, if the number of temporary buses that can be operated is 7, the measure plan B1 cannot be selected. In this case, the analyzer 301 selects the measure plan B2. It will be.

Then, the analyzer 301 specifies the degree of problem solving for each measure plan selected for each measure plan type. For example, when the measure plan A1 is selected, the analyzer 301 calculates, for example, the number of vacant rooms a11 based on the number of vacant rooms of the accommodation facility 111 on the day before the target day as the supplyable amount for the problem, and from the past actual data. Acquire the number of people a12 to change from the same day to the previous day. The analyzer 301 compares the number of people who can stay a11 with the number of people a12 to be changed on the previous day, and acquires the smaller number as the reduced number. Then, the analyzer 301 calculates the ratio of the reduced number of people to the predicted inflow / outflow number of the day, and specifies the degree of resolution according to the calculated ratio from the problem solving KPI data 1300. In this example, it is assumed that the resolution level 5 is specified for the measure plan A1.

Further, when the measure plan B2 is selected, the analyzer 301 acquires, for example, the number of operable temporary buses on the day as the supplyable amount for the problem, and the maximum number of operational units and the maximum number of temporary buses per one. The reduced number of passengers is calculated by multiplying the number of passengers. Then, the analyzer 301 calculates the ratio of the reduced number of people to the predicted inflow / outflow number of the day, and specifies the degree of resolution according to the calculated ratio from the problem solving KPI data 1300. In this example, it is assumed that the resolution level 4 is specified for the measure plan B2.

Furthermore, acquisition if measures proposed C1 is selected, as the suppliable amount for problems, for example, a seat number c11 of possible share of office provided in the day, and the estimated number of persons c12 utilizing day share office from the past record data do. The analyzer 301 compares the number of seats c11 with the estimated number of people c12, and acquires the smaller number as the reduced number of people. Then, the analyzer 301 calculates the ratio of the reduced number of people to the predicted inflow / outflow number of the day, and specifies the degree of resolution according to the calculated ratio from the problem solving KPI data 1300. In this example, it is assumed that the resolution level 4 is specified for the measure plan C1.

Next, the analyzer 301 executes a second specific process for specifying the cost rank for each measure plan (step S1606). Specifically, for example, in the case of the measure A1, the analyzer 301 multiplies the discount amount of the 20% discount of the accommodation facility 111 per person by the reduced number of people specified in the measure A1 in step S1605. Then, as the predicted cost when the measure plan A1 is executed, the cost a required for the measure plan A1 is calculated. Then, the analyzer 301 refers to the cost KPI data 1500, specifies the cost KPI that satisfies the calculated cost a, and specifies the cost rank corresponding to the specified cost KPI. For example, if the cost a is 850,000 yen, the cost rank is "C".

Further, in the case of the measure plan B2, the analyzer 301 multiplies the fare per person by the reduced number of people specified in the measure plan B2 in step S1605, and as a predicted cost when the measure plan B2 is executed. Calculate the cost b required for the measure plan B2. Then, the analyzer 301 refers to the cost KPI data 1500, specifies the cost KPI that satisfies the calculated cost b, and specifies the cost rank corresponding to the specified cost KPI. For example, if the cost b is 420,000 yen, the cost rank is "AA".

Further, in the case of the measure plan C1, the analyzer 301 multiplies the cost per seat in the shared office by the reduced number of people specified in the measure plan C1 in step S1605, and as a predicted cost when the measure plan C1 is executed. , Calculate the cost c required for the measure plan C1. Then, the analyzer 301 refers to the cost KPI data 1500, specifies the cost KPI that satisfies the calculated cost c, and specifies the cost rank corresponding to the specified cost KPI. For example, if the cost c is 590,000 yen, the cost rank is "A".

Next, the analyzer 301 executes a calculation process for calculating cost effectiveness for each measure plan (step S1607). In this example, the lower the cost-effectiveness index value, the higher the cost-effectiveness. Specifically, for example, in the case of the measure plan A1, the analyzer 301 multiplies the resolution 5 of the measure plan A1 by the maximum cost of "90,000 yen" in the cost rank C. Calculate the cost-effectiveness index value "450.0". Further, in the case of the measure plan B2, the analyzer 301 multiplies the solution degree 4 of the measure plan B2 by the maximum cost of "450,000 yen" in the cost rank AA to obtain a cost-effectiveness index. The value "180.0" is calculated. Further, in the case of the measure plan C1, the analyzer 301 multiplies the solution degree 4 of the measure plan C1 and the maximum cost of "60,000 yen" in the cost rank A to obtain a cost-effectiveness index. The value "240.0" is calculated.

Then, the analyzer 301 executes a selection process for selecting, for example, a higher-level measure proposal, which is relatively cost-effective, and ends the process (step S1608). Specifically, for example, the analyzer 301 selects the top two policy proposals B2 and C1 having low cost-effectiveness index values as policy proposals to be proposed to the local people 130. If there are multiple policy proposals to be selected, three or more may be selected.

In this way, the analyzer 301 can automatically select a low-cost but highly effective measure plan and propose it to the local people 130. Therefore, the local people 130 vote on a plurality of proposed measures, and the measure with the largest number of votes is executed.

In this way, the use of the pooled donations is determined by the locals 130, and the pooled donations are used for the area, so the pooled donations are for the locals 130 to live comfortably. Equally returned to the development of the city. In addition, with the intervention of the fund 120, which formulates urban development measures for residents, it will be possible to propose a mechanism in which residents who do not use the railroad can voluntarily participate in the changes in the city due to the increase in visitors by 104.

In addition, the more visitors 104 visit, the more comfortable the city will continue to develop. For example, pooled donations are used to avoid undesired situations for locals, such as sudden and temporary traffic jams in the city caused by a large number of visitors 104 and the loss of aesthetics due to littering of garbage. That is, it is reduced that the number of visitors 104 increases, which makes the city rather inconvenient and unattractive for the locals 130.

In addition, the choice of the locals 130 will reveal the "usage" that will improve the city. For example, based on the demand forecast of the city, the service provider of the fund 120 will "run a temporary bus", "increase the frequency of garbage collection", "open a shared office for locals 130 for free", etc. for a short period of time. We propose multiple uses for spans. Finally, the residents vote for the proposal to determine how the pooled donations will be used.

In addition, with the introduction of the policy decision system 300, it is expected that the local people 130 themselves will take actions to improve the city while involving local businesses. For example, a service provider of Fund 120 encourages locals 130 to propose how to use the pooled donations, and more culturally, such as "travel expenses for instructors called from big cities" and "workshops for citizens". Residents will be able to propose how to use the long-term span so that they can develop. The changes in the city will change for each 130 locals, and the railway will become familiar as a supporter of the maturity of the city. The pooled donations will be returned to the community, revitalizing local businesses and supporting the continued development of the city.

It should be noted that the present invention is not limited to the above-mentioned examples, but includes various modifications and equivalent configurations within the scope of the attached claims. For example, the above-mentioned examples have been described in detail in order to explain the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to those having all the described configurations. Further, a part of the configuration of one embodiment may be replaced with the configuration of another embodiment. Further, the configuration of another embodiment may be added to the configuration of one embodiment. In addition, other configurations may be added, deleted, or replaced with respect to a part of the configurations of each embodiment.

Further, each configuration, function, processing unit, processing means, etc. described above may be realized by hardware by designing a part or all of them by, for example, an integrated circuit, and the processor realizes each function. It may be realized by software by interpreting and executing the program to be executed.

Information such as programs, tables, and files that realize each function is recorded in a storage device such as a memory, a hard disk, an SSD (Solid State Drive), or an IC (Integrated Circuit) card, an SD card, or a DVD (Digital Versail Disc). It can be stored in a medium.

In addition, the control lines and information lines show what is considered necessary for explanation, and do not necessarily show all the control lines and information lines necessary for mounting. In practice, it can be considered that almost all configurations are interconnected.

104 Visitor 105 Mobile terminal 109 Train 110 Central area 111 Accommodation facility 112 Commercial store 113 Commercial building 114 Office building 115 Event venue 120 Fund 130 Locals 300 Policy decision system 301 Analytical device 302 Management system 303 Public system 304 Operation system 305 Supporting company System 330 Surveillance camera 361 Mobile terminal 362 In-vehicle voice interface 363 Digital signage 501 Reservation management device 501 Reservation management device 502 Revenue management device 503 Operation management device 504 Reservation management device 1300 Problem solving KPI data 1400 Measure plan data 1500 Cost KPI data

Claims (6)

It is a policy decision system composed of one or more computers having a processor for executing a program and a storage device for storing the program.
The storage device includes a plurality of measure proposals that specify a solution method for solving a problem in a specific area in a target area, problem-solving information that associates a problem-solving target value with a problem-solving degree, and a problem-solving information. Cost information that stores the target value of the cost required for solving the problem, the predicted amount of the problem, the supplyable amount for each of the plurality of measures, and the case where the measure is executed. I remember the estimated cost,
The processor
For each of the plurality of measures, based on the solution method in the measures , the amount of decrease in the predicted amount of the problem corresponding to the supplyable amount for the problem is acquired, and the said amount with respect to the predicted amount of the problem is obtained. identify the target value of eliminating the problem that falls under the rate of decrease, the resolving degree corresponding to the target value identified, a first identification processing for identifying from the problem resolution information,
For each of the plurality of measure proposals, a second specific process for specifying the target value of the cost corresponding to the estimated cost when the measure proposal is executed from the cost information, and
For each of the plurality of measures, the cost of the measure is based on the degree of solving the problem specified by the first specific process and the target value of the cost specified by the second specific process. Calculation processing to calculate the effect and
An election process that selects two or more specific measure proposals with relatively high cost-effectiveness calculated by the calculation process from the plurality of measure proposals.
Output processing for transmitting two or more specific measure proposals selected by the selection processing to the terminals of residents in the target area, and
A decision process that receives a measure plan selected from the above two or more specific measure plans from the terminal and decides the measure by majority vote.
A policy decision system characterized by executing. It is a policy decision system composed of one or more computers having a processor for executing a program and a storage device for storing the program.
The storage device includes a plurality of measure proposals that specify a solution method for solving a problem in a specific area in a target area, problem-solving information that associates a problem-solving target value with a problem-solving degree, and a problem-solving information. Cost information that stores the target value of the cost required for solving the problem, the predicted amount of the problem, the supplyable amount for each of the plurality of measures, and the case where the measure is executed. I remember the estimated cost,
The processor
For each of the plurality of measures, based on the solution method in the measures, the amount of decrease in the predicted amount of the problem corresponding to the supplyable amount for the problem is acquired, and the said amount with respect to the predicted amount of the problem is obtained. The first specific process for specifying the problem-solving target value corresponding to the rate of decrease and specifying the resolution degree corresponding to the specified target value from the problem-solving information.
For each of the plurality of measure proposals, a second specific process for specifying the target value of the cost corresponding to the estimated cost when the measure proposal is executed from the cost information, and
For each of the plurality of measures, the cost of the measure is based on the degree of solving the problem specified by the first specific process and the target value of the cost specified by the second specific process. Calculation processing to calculate the effect and
An election process that selects two or more specific measure proposals with relatively high cost-effectiveness calculated by the calculation process from the plurality of measure proposals.
Output processing that outputs two or more specific measure proposals selected by the selection processing, and
And run
A specific computer in the group of computers that manages the means of transportation has a detector in the specific area capable of short-range communication with a terminal of a visitor from outside the target area.
The specific processor in the specific computer
A specific storage device in the specific computer by acquiring the usage amount data when the visitor uses the transportation means into the specific area and the donation information to the target area from the visitor's terminal. Acquisition process to be stored in
When the detector detects the terminal of the visitor, the transmission process of transmitting the donation information from the specific storage device to the storage device, and
A policy decision system characterized by executing. The measure determination system according to claim 1 or 2.
The processor
Execute a selection process to select a measure plan that satisfies the supplyable amount from the measure plan group for each measure plan type.
The first specific process is characterized in that the processor specifies the degree of resolution from the problem-solving information for each of the plurality of policy proposals selected for each measure proposal type by the selection process. Decision system. The measure determination system according to claim 1 or 2.
In the output process, the processor is a measure determination system characterized in that the two or more specific measure proposals are transmitted to a display device installed in the target area. It is a measure decision method by a measure decision system composed of one or more computers having a processor for executing a program and a storage device for storing the program.
The storage device includes a plurality of measure proposals that specify a solution method for solving a problem in a specific area in a target area, problem-solving information that associates a problem-solving target value with a problem-solving degree, and a problem-solving information. Cost information that stores the target value of the cost required for solving the problem, the predicted amount of the problem, the supplyable amount for each of the plurality of measures, and the case where the measure is executed. I remember the estimated cost,
The processor
For each of the plurality of measures, based on the solution method in the measures, the amount of decrease in the predicted amount of the problem corresponding to the supplyable amount for the problem is acquired, and the said amount with respect to the predicted amount of the problem is obtained. The first specific process for specifying the problem-solving target value corresponding to the rate of decrease and specifying the resolution degree corresponding to the specified target value from the problem-solving information.
For each of the plurality of measure proposals, a second specific process for specifying the target value of the cost corresponding to the estimated cost when the measure proposal is executed from the cost information, and
For each of the plurality of measures, the cost of the measure is based on the degree of solving the problem specified by the first specific process and the target value of the cost specified by the second specific process. Calculation processing to calculate the effect and
An election process that selects two or more specific measure proposals with relatively high cost-effectiveness calculated by the calculation process from the plurality of measure proposals.
Output processing for transmitting two or more specific measure proposals selected by the selection processing to the terminals of residents in the target area, and
A decision process that receives a measure plan selected from the above two or more specific measure plans from the terminal and decides the measure by majority vote.
A measure decision method characterized by executing. It is a measure decision method by a measure decision system composed of one or more computers having a processor for executing a program and a storage device for storing the program.
The storage device includes a plurality of measure proposals that specify a solution method for solving a problem in a specific area in a target area, problem-solving information that associates a problem-solving target value with a problem-solving degree, and a problem-solving information. Cost information that stores the target value of the cost required for solving the problem, the predicted amount of the problem, the supplyable amount for each of the plurality of measures, and the case where the measure is executed. I remember the estimated cost,
The processor
For each of the plurality of measures, based on the solution method in the measures, the amount of decrease in the predicted amount of the problem corresponding to the supplyable amount for the problem is acquired, and the said amount with respect to the predicted amount of the problem is obtained. The first specific process for specifying the problem-solving target value corresponding to the rate of decrease and specifying the resolution degree corresponding to the specified target value from the problem-solving information.
For each of the plurality of measure proposals, a second specific process for specifying the target value of the cost corresponding to the estimated cost when the measure proposal is executed from the cost information, and
For each of the plurality of measures, the cost of the measure is based on the degree of solving the problem specified by the first specific process and the target value of the cost specified by the second specific process. Calculation processing to calculate the effect and
An election process that selects two or more specific measure proposals with relatively high cost-effectiveness calculated by the calculation process from the plurality of measure proposals.
Output processing that outputs two or more specific measure proposals selected by the selection processing, and
And run
A specific computer in the group of computers that manages the means of transportation has a detector in the specific area capable of short-range communication with a terminal of a visitor from outside the target area.
The specific processor in the specific computer
A specific storage device in the specific computer by acquiring the usage amount data when the visitor uses the transportation means into the specific area and the donation information to the target area from the visitor's terminal. Acquisition process to be stored in
When the detector detects the terminal of the visitor, the transmission process of transmitting the donation information from the specific storage device to the storage device, and
A measure decision method characterized by executing.

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