Program and Information Processing Device

Abstract

To propose a traffic measure or a policy target considering a situation of each region.SOLUTION: A program allows a computer to function as: acquisition means 54 for acquiring at least relevant data regarding regional traffic means; calculation means 56 for calculating a score value corresponding to each element of a regional traffic score associated with each of a plurality of traffic measures according to the relevant data; extracting means 58 for extracting a regional traffic measure on the basis of the score value corresponding to each element of the regional traffic score; and output means 60 for outputting information indicating the extracted regional traffic measure.SELECTED DRAWING: Figure 3

Description

Technical Field

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[0001] The present invention relates to a program and an information processing apparatus.

Background Art

[0002] Conventionally, techniques for realizing evidence-based policy making (EBPM) have been known. For example, a technique for analyzing existing administrative services with existing statistical methods to propose new policies is known.

[0003] Regarding this, Patent Document 1 discloses a technique capable of automatically proposing traffic measures to be taken for a problem to a user.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, with the technique described in Patent Document 1, it is not possible to propose traffic measures or policy targets (problems) taking into account the circumstances of each region (for example, the low operation rate of public transportation, the frequent delays of public transportation due to strong winds, etc.).

[0006] The present invention has been made in view of such problems, and an object thereof is to provide a program and an information processing apparatus capable of proposing traffic measures or policy targets taking into account the circumstances of each region.

Means for Solving the Problems

[0007] To solve the above problems, the program according to the first aspect of the present invention causes a computer to function as an acquisition means for acquiring relevant data relating to at least local transportation methods, a calculation means for calculating score values ​​corresponding to each element of a local transportation score associated with a plurality of transportation measures according to the relevant data, an extraction means for extracting local transportation measures based on the score values ​​corresponding to each element of the local transportation score, and an output means for outputting information indicating the extracted local transportation measures.

[0008] Furthermore, in a second aspect of the present invention, the extraction means prioritizes extracting transportation measures that improve the score value of the elements of the regional transportation score that are associated with the element with the lowest score value.

[0009] Furthermore, in a third aspect of the present invention, the computer functions as a receiving means that receives an extraction request for extracting the transportation policies of the region, which includes a policy objective corresponding to any element of the regional transportation score, and the extraction means extracts the transportation policies of the region based on the elements of the regional transportation score that are associated with the policy objective included in the received extraction request.

[0010] Furthermore, the program according to the fourth aspect of the present invention causes a computer to function as an acquisition means for acquiring relevant data relating to at least local transportation methods, a calculation means for calculating score values ​​corresponding to each element of a local transportation score associated with a plurality of policy objectives according to the relevant data, an extraction means for extracting the policy objectives of the region based on the score values ​​corresponding to each element of the local transportation score, and an output means for outputting information indicating the extracted policy objectives of the region.

[0011] Furthermore, in a fifth aspect of the present invention, the extraction means prioritizes extracting policy objectives that are associated with the element with the lowest score among the elements of the regional traffic score and that improve the score.

[0012] Furthermore, in a sixth aspect of the present invention, the computer functions as a receiving means that receives an extraction request for extracting policy objectives for the region, which includes a transportation policy corresponding to any element of the regional transportation score, and the extraction means extracts the policy objectives for the region based on the elements of the regional transportation score that are associated with the transportation policy included in the received extraction request.

[0013] Furthermore, the information processing device according to the seventh aspect of the present invention includes: an acquisition means for acquiring relevant data relating to at least local transportation methods; a calculation means for calculating score values ​​corresponding to each element of a local transportation score associated with a plurality of transportation measures, according to the relevant data; an extraction means for extracting local transportation measures based on the score values ​​corresponding to each element of the local transportation score; and an output means for outputting information indicating the extracted local transportation measures.

[0014] Furthermore, an information processing device according to the eighth aspect of the present invention includes: an acquisition means for acquiring relevant data relating to at least local transportation methods; a calculation means for calculating score values ​​corresponding to each element of a local transportation score associated with a plurality of policy objectives, according to the relevant data; an extraction means for extracting the policy objectives of the region based on the score values ​​corresponding to each element of the local transportation score; and an output means for outputting information indicating the extracted policy objectives of the region. [Effects of the Invention]

[0015] According to the present invention, it is possible to propose transportation policies or policy objectives that take into account the specific circumstances of each region. [Brief explanation of the drawing]

[0016] [Figure 1] This is a block diagram showing an example of the overall configuration of the proposed system according to this embodiment of the present invention. [Figure 2] This block diagram shows an example of the hardware configuration of the server device shown in Figure 1. [Figure 3]It is a block diagram showing an example of the functional configuration of the proposed system according to this embodiment. [Figure 4] It is a diagram showing an example of the correspondence relationship between each element of the regional traffic score and traffic measures and policy goals. [Figure 5] In the proposed system according to this embodiment, it is a flowchart showing an example of the processing flow for proposing regional traffic measures. [Figure 6] It is a diagram showing an example of the selection screen according to this embodiment. [Figure 7] It is a diagram showing an example of the proposed screen for traffic measures according to this embodiment. [Figure 8] In the proposed system according to this embodiment, it is a flowchart showing an example of the processing flow for proposing regional policy goals. [Figure 9] It is a diagram showing an example of the selection screen according to this embodiment. [Figure 10] It is a diagram showing an example of the proposed screen for policy goals according to this embodiment.

Mode for Carrying Out the Invention

[0017] Hereinafter, embodiments of the present invention (hereinafter referred to as "this embodiment") will be described with reference to the accompanying drawings. For ease of understanding of the description, the same reference numerals are given to the same components and steps in each drawing as much as possible, and duplicate descriptions are omitted.

[0018] <Overall Configuration> FIG. 1 is a block diagram showing an example of the overall configuration of the proposed system 1 according to the present embodiment of the present invention.

[0019] As shown in FIG. 1, the proposed system 1 includes a server device 10 and a plurality of terminal devices 12. These devices are configured to be able to communicate with each other via a communication network NT such as the Internet or a telephone line network.

[0020] The server device 10 is an information processing device (computer) that generates various types of information to be provided to users. For example, these users may include those belonging to local governments (administration), transportation companies, corporations, educational institutions, and various other organizations.

[0021] Terminal devices 12 are information processing devices owned by each user. Examples of terminal devices 12 include mobile phones, smartphones, tablets, and personal computers.

[0022] <Hardware Configuration> Figure 2 is a block diagram showing an example of the hardware configuration of the server device 10 shown in Figure 1.

[0023] As shown in Figure 2, the server device 10 comprises a control device 20, a communication device 26, and a storage device 28. The control device 20 is mainly composed of a CPU (Central Processing Unit) 22 and memory 24.

[0024] In the control device 20, the CPU 22 executes a predetermined program stored in the memory 24 or storage device 28, thereby functioning as various functional means. Details of these functional means will be described later.

[0025] The communication device 26 consists of a communication interface and the like for communicating with external devices. The communication device 26, for example, sends and receives various types of information with the terminal device 12.

[0026] The storage device 28 is composed of a hard disk or the like. The storage device 28 stores various programs and information necessary for executing processing in the control device 20, as well as information on the processing results.

[0027] The server device 10 can be implemented using an information processing device such as a dedicated or general-purpose server computer. Furthermore, the server device 10 may consist of a single information processing device or multiple information processing devices distributed across the communication network NT. Also, Figure 2 only shows a portion of the main hardware configuration of the server device 10; the server device 10 may have other configurations that are generally found in servers. Similarly, the hardware configuration of the multiple terminal devices 12 may be similar to that of the server device 10, except for the inclusion of, for example, operating means and display devices.

[0028] <Functional configuration> (Specific example 1) Figure 3 is a block diagram showing an example of the functional configuration of the proposed system 1 according to this embodiment.

[0029] As shown in Figure 3, for example, the server device 10 in the proposed system 1 has a functional configuration comprising a storage means 50, a receiving means 52, an acquisition means 54, a calculation means 56, an extraction means 58, and an output means 60.

[0030] The memory means 50 stores related data 50A, score calculation information 50B, transportation policy response information 50C, policy objective response information 50D, and user information 50E.

[0031] Related data 50A includes data acquired by acquisition means 54. This data includes, for example, data relating to regional transportation. Examples of regional areas include prefectures and municipalities. Examples of data relating to regional transportation (related data) include flow data, company data, administrative data, and user surveys. For example, flow data includes transportation methods and link information, associated with link IDs for each link connecting each node (e.g., stations, bus stops, intersections) in the section (range) where transportation operators operate their transportation services. Examples of transportation methods include taxis, buses, trains, ships, and airplanes. Link information includes, for example, link names (e.g., route names or road names), directions (departure node and arrival node), link length (e.g., distance), location information (e.g., latitude and longitude of each node), travel speed, travel time, fares, transport capacity, number of users, carbon dioxide emissions, and delay rates. Company data includes the names and locations of companies within the region, the number of employees, etc. Administrative data includes the names and locations of local government agencies and the number of employees within the region. User surveys include, for example, the results of surveys regarding modes of transportation.

[0032] Score calculation information 50B includes formulas used to calculate each element of the regional transport score from relevant data. Examples of these elements of the regional transport score include transport efficiency, operation rate, accuracy, utilization rate, and public transport coverage rate. The regional transport score for transport efficiency is calculated, for example, based on the cost (fuel) and carbon dioxide emissions required to transport users a predetermined distance (e.g., 1 km). The regional transport score for operation rate is calculated, for example, based on the frequency of operations per predetermined period (e.g., 1 day). The regional transport score for accuracy is calculated, for example, based on the accuracy of departure and arrival times (minimal delays). The regional transport score for utilization rate is calculated, for example, based on the occupancy rate of the mode of transport (number of users / number of people that can be transported). The public transport coverage rate is calculated, for example, based on the operating area (territory) of public transport within the region.

[0033] Information 50C related to transportation policies includes the correlation (strength) between each transportation policy and each element of the regional transportation score. The higher the correlation value, the stronger the relationship (connection) between the transportation policy and each element of the regional transportation score. This correlation is, for example, a value between -1.00 and 1.00. Examples of such transportation policies include setting free days, increasing railway lines, increasing bus lines, and raising railway tracks. For example, if the correlation between a certain transportation policy and the first element of the regional transportation score is positive, implementing that transportation policy will increase the score value of that first element. For example, if the correlation between a certain transportation policy and the second element of the regional transportation score is negative, implementing that transportation policy will decrease the score value of that second element.

[0034] Policy objective-related information 50D includes the correlation (strength) between each policy objective and each element of the regional transportation score. A higher correlation value indicates a stronger relationship (connection) between the policy objective and each element of the regional transportation score. This correlation is, for example, a value between -1.00 and 1.00. Examples of policy objectives include employment support, education support, medical and nursing care support, promotion of going out, tourism promotion, environmental contribution, and infrastructure development. For example, if the correlation between a certain policy objective and the first element of the regional transportation score is positive, implementing that policy objective will increase the score value of that first element. For example, if the correlation between a certain policy objective and the second element of the regional transportation score is negative, implementing that policy objective will decrease the score value of that second element.

[0035] User information 50E includes each user's user ID, login ID, password, username, affiliated organization, proposed region, etc. Affiliated organization includes, for example, the organization name and job title. Proposed region includes the region the user is proposing to. This proposed region is, for example, pre-registered by the user.

[0036] The reception means 52 is a functional means that receives various requests (e.g., selection inputs) from the terminal device 12 held by the user. In this embodiment, the reception means 52 receives an extraction request that includes a policy objective corresponding to any element of the regional transportation score, as an extraction request for extracting regional transportation policies. For example, the reception means 52 receives a selection input of a policy objective such as employment support, education support, or medical / nursing care support from the terminal device 12 as an extraction request.

[0037] The acquisition means 54 is a functional means for acquiring various types of data. In this embodiment, the acquisition means 54 acquires at least data related to local transportation (related data). For example, the acquisition means 54 acquires this data at a predetermined timing (for example, when a user logs in). The acquisition means 54 stores the acquired data as related data in related data 50A. Furthermore, the acquisition means 54 may automatically collect relevant data from external big data using AI functions or the like. The relevant data may include information about local facilities, topography, population, etc.

[0038] The calculation means 56 is a functional means for associating each element of the regional transportation score with multiple transportation measures and policy objectives, and for calculating the score value of each element. In this embodiment, the calculation means 56 calculates the score value corresponding to each element of the regional transportation score that is associated with each of the multiple transportation measures, according to the related data 50A. For example, the calculation means 56 calculates the score value of each element of the regional transportation score (transportation efficiency, operation rate, accuracy, utilization rate, public transport coverage rate, etc.) by referring to the related data 50A and score calculation information 50B. The score value of each element is, for example, a value between 0 and 100.

[0039] Next, the calculation means 56 refers to the transportation policy-related information 50C and associates each element of the regional transportation score with multiple transportation policies. For example, if the value indicating the relationship between the first element of the regional transportation score and a certain transportation policy is "greater than -0.01 and less than 0.01", the calculation means 56 does not associate the first element of the regional transportation score with the transportation policy. On the other hand, for example, if the value indicating the relationship between the second element of the regional transportation score and a certain transportation policy is "less than or equal to -0.01" or "greater than or equal to 0.01", the calculation means 56 associates the second element of the regional transportation score with the transportation policy.

[0040] Furthermore, in this embodiment, the calculation means 56 refers to the policy objective-related information 50D and associates each element of the regional traffic score with a plurality of policy objectives. For example, if the value indicating the relationship between the first element of the regional traffic score and a certain policy objective is "greater than -0.01 and less than 0.01", the calculation means 56 does not associate the first element of the regional traffic score with a certain policy objective. On the other hand, for example, if the value indicating the relationship between the second element of the regional traffic score and a certain policy objective is "less than or equal to -0.01" or "greater than or equal to 0.01", the calculation means 56 associates the second element of the regional traffic score with a certain policy objective.

[0041] Figure 4 shows an example of the correspondence between each element of the regional transportation score and transportation policies and policy objectives.

[0042] As shown in the data correspondence relationship 70 in Figure 4, each element of the regional transportation score (transportation efficiency, operation rate, accuracy, utilization rate, public transport coverage rate, etc.) is associated with transportation policies and policy objectives. For example, transportation cost, an element of the regional transportation score, is associated with transportation policies such as setting free days, increasing railway lines, increasing bus lines, and raising railway tracks. Also, for example, operation rate, an element of the regional transportation score, is associated with policy objectives such as employment support, education support, medical and nursing care support, promotion of going out, tourism promotion, environmental contribution, and infrastructure development.

[0043] Returning to Figure 3, the extraction means 58 is a functional means for extracting various types of information. In this embodiment, the extraction means 58 extracts regional transportation policies based on the regional transportation score. For example, the extraction means 58 prioritizes extracting transportation policies that improve the score value of the element that has the lowest score among the elements of the regional transportation score. Specifically, the extraction means 58 extracts the transportation policy (e.g., setting free days, railway elevation) that has the lowest score among the elements of the regional transportation score. Subsequently, the extraction means 58 prioritizes extracting transportation policies (e.g., railway elevation) from the extracted transportation policies in which the relationship between the element and the transportation policy is positive or above a certain value. This makes it possible to extract (output) transportation policies that can improve the score value corresponding to the element, regardless of whether or not the user has submitted an extraction request that includes policy objectives.

[0044] Furthermore, in this embodiment, the extraction means 58 extracts regional transportation measures based on the elements of the regional transportation score associated with the policy objectives included in the extraction request received by the receiving means 52. For example, the extraction means 58 refers to the policy objective-related information 50D and extracts the element (e.g., utilization rate) that has the highest correlation with the policy objective (e.g., tourism promotion) from among the elements of the regional transportation score (e.g., transport efficiency, operation rate, accuracy, utilization rate, public transport coverage rate) associated with the policy objective (e.g., tourism promotion) included in the extraction request. Subsequently, the extraction means 58 extracts transportation measures (e.g., setting free days, increasing railway lines, increasing bus lines, elevated railway lines) associated with the element (e.g., utilization rate) for which the correlation between the element and the transportation measure is positive or above a certain value (e.g., setting free days).

[0045] The output means 60 is a functional means that outputs various information to the terminal device 12. In this embodiment, the output means 60 outputs information (suggestion screen) showing regional transportation policies extracted by the extraction means 58 to the terminal device 12.

[0046] <Flowchart for processing proposals for transportation policies> Figure 5 is a flowchart showing an example of the processing flow for proposing regional transportation policies in the proposal system 1 according to this embodiment. The processing of the following steps begins, for example, when a user logs into the proposal system 1 and selects the transportation policy proposal menu. Note that the order and content of the following steps can be changed as appropriate.

[0047] (Step SP10) The acquisition means 54 refers to the proposed region in the user information 50E and acquires data on the means of transportation for the region where the transportation policy is proposed. Subsequently, the acquisition means 54 stores the acquired data as related data in related data 50A. Then, the process moves on to the process in step SP12.

[0048] (Step SP12) The calculation means 56 refers to related data 50A and score calculation information 50B to calculate the score values ​​for each element of the regional transportation score (transportation efficiency, operation rate, accuracy, utilization rate, public transportation coverage rate, etc.). Next, the calculation means 56 refers to transportation policy related information 50C to associate each element of the regional transportation score with multiple transportation policies. Next, the calculation means 56 refers to policy objective related information 50D to associate each element of the regional transportation score with multiple policy objectives. Then, the process moves on to the processing in step SP14.

[0049] (Step SP14) The output means 60 outputs (displays) a selection screen on the user's terminal device 12, which allows the user to select policy objectives necessary for extracting regional transportation policies.

[0050] Figure 6 shows an example of the selection screen 80 according to this embodiment.

[0051] As shown in Figure 6, the selection screen 80 is provided with a policy objective selection area 82 and a proposal start button 84. The policy objective selection area 82 displays a pull-down menu for selecting one policy objective from several. Note that the policy objective selection area 82 may allow the selection of multiple policy objectives. The "Start Proposal" button 84 is used to initiate the proposal of transportation policies based on the selected policy objective.

[0052] Returning to Figure 5, the process moves on to step SP16.

[0053] (Step SP16) The reception means 52 receives an extraction request to extract regional transportation policies. For example, if the user selects a policy objective on the selection screen and then presses the "Start Proposal" button, the reception means 52 receives the extraction request. The process then proceeds to step SP18.

[0054] (Step SP18) The extraction means 58 determines whether the policy objective selected by the user in step SP16 (e.g., employment support) is associated with an element of the regional transportation score. For example, if the selected policy objective is associated with any element (one or more elements) of the regional transportation score in step SP12, the extraction means 58 affirms the determination. If the determination is affirmative, the process proceeds to step SP20. On the other hand, if the determination is negative, the process terminates the series of processes shown in Figure 5. In this case, the output means 60 may output (display) to the terminal device 12 held by the user that it is impossible to propose a transportation policy.

[0055] (Step SP20) The extraction means 58 refers to the policy objective-related information 50D and extracts the element (e.g., public transport coverage rate) that has the highest correlation with the selected policy objective from among the elements of the regional transport score associated with that policy objective. Then, the process moves on to the processing in step SP22.

[0056] (Step SP22) The extraction means 58 refers to the transportation policy-related information 50C and extracts transportation policies (e.g., increase in railway lines, increase in bus lines) that are associated with the elements of the regional transportation score extracted in step SP20 (e.g., public transport coverage rate), and whose relationship with the element is above a certain value (e.g., increase in bus lines). Then the process moves on to the processing in step SP24.

[0057] (Step SP24) The output means 60 outputs (displays) the traffic policy proposal screen to the terminal device 12 held by the user.

[0058] Figure 7 shows an example of the traffic policy proposal screen 90 according to this embodiment.

[0059] As shown in Figure 7, the proposal screen 90 is provided with a proposal information area 92 and a complete button 94. The proposed information area 92 shows the transportation policies extracted in step SP22. The "Complete" button 94 is used to close the proposal screen 90 and return to the transportation policy proposal menu.

[0060] Then, the process concludes with the series of steps shown in Figure 5.

[0061] (Specific example 2) In the specific example 1 described above, the proposed system 1 was shown as proposing local transportation policies, but it could also be used to propose local policy objectives.

[0062] For example, the reception means 52 accepts an extraction request that includes a transportation measure corresponding to any element of the regional transportation score, as an extraction request for extracting regional policy objectives. For example, the reception means 52 accepts an extraction request from the terminal device 12 for selecting a transportation measure such as setting a free day, increasing railway lines, or increasing bus lines.

[0063] Furthermore, for example, the extraction means 58 extracts regional policy objectives based on the score values ​​corresponding to each element of the regional transportation score. For example, the extraction means 58 prioritizes extracting policy objectives that are associated with the element with the lowest score value among the elements of the regional transportation score and that improve that score value. Specifically, the extraction means 58 extracts policy objectives (e.g., employment support, education support, medical and nursing care support, environmental contribution, infrastructure development) associated with the element with the lowest score value among the elements of the regional transportation score. Subsequently, the extraction means 58 prioritizes extracting policy objectives (e.g., infrastructure development) from the extracted policy objectives where the relationship between the element and the policy objective is positive or above a certain value. This makes it possible to extract (output) policy objectives that can improve the score value corresponding to the element, regardless of whether or not the user has submitted an extraction request that includes transportation policies.

[0064] Furthermore, the extraction means 58 extracts regional policy objectives based on the elements of the regional transportation score associated with the transportation policies included in the extraction request received by the reception means 52. For example, the extraction means 58 refers to the transportation policy-related information 50C and extracts the element (e.g., utilization rate) that has the highest correlation with the transportation policy (e.g., setting free days) from among the elements of the regional transportation score (e.g., transportation efficiency, accuracy, utilization rate) associated with the transportation policy (e.g., setting free days) included in the extraction request. Subsequently, the extraction means 58 extracts policy objectives (e.g., employment support, education support, medical / nursing care support, promotion of going out, tourism promotion, environmental contribution) associated with the element (e.g., utilization rate) for which the correlation between the element and the policy objective is positive or above a certain value (e.g., promotion of going out, tourism promotion).

[0065] Furthermore, the output means 60 outputs information indicating the policy objectives of the extracted region. For example, the output means 60 outputs information indicating the policy objectives of the region extracted by the extraction means 58 (suggestion screen) to the terminal device 12.

[0066] <Processing flow for policy objective proposals> Figure 8 is a flowchart illustrating an example of the process flow for proposing regional policy objectives in the proposal system 1 according to this embodiment. The following steps begin, for example, when a user logs into the proposal system 1 and selects the policy objective proposal menu. The order and content of the following steps can be changed as appropriate.

[0067] (Steps SP30 to SP32) The processing in steps SP30 to SP32 is the same as the processing in steps SP10 to SP12 described above, so the explanation will be omitted. Then, the process moves on to step SP34.

[0068] (Step SP34) The output means 60 outputs (displays) a selection screen on the user's terminal device 12, which allows the user to select the transportation measures necessary to extract regional policy objectives.

[0069] Figure 9 shows an example of the selection screen 100 according to this embodiment.

[0070] As shown in Figure 9, the selection screen 100 includes a transportation policy selection area 102 and a proposal start button 104. The transportation policy selection area 102 displays a pull-down menu for selecting one transportation policy from several options. Note that the transportation policy selection area 102 may allow for the selection of multiple transportation policies. The "Start Proposal" button 104 is used to initiate the proposal of policy objectives based on the selected transportation measures.

[0071] Returning to Figure 8, the process moves on to step SP36.

[0072] (Step SP36) The reception means 52 receives an extraction request to extract regional policy objectives. For example, if the user selects a transportation policy on the selection screen and then presses the "Start Proposal" button, the reception means 52 receives the extraction request. The process then proceeds to step SP38.

[0073] (Step SP38) The extraction means 58 determines whether the transportation policy selected by the user in step SP36 (e.g., setting a free day) is associated with an element of the regional transportation score. For example, if the selected transportation policy is associated with any element (one or more elements) of the regional transportation score in step SP32, the extraction means 58 affirms the determination. If the determination is affirmed, the process proceeds to the process in step SP40. On the other hand, if the determination is denied, the process terminates the series of processes shown in Figure 8. In this case, the output means 60 may output (display) to the terminal device 12 held by the user that it is impossible to propose a policy objective.

[0074] (Step SP40) The extraction means 58 refers to the transportation policy-related information 50C and extracts the element (e.g., utilization rate) that has the highest correlation with the selected transportation policy from among the elements of the regional transportation score associated with the selected transportation policy. Then, the process moves on to the process of step SP42.

[0075] (Step SP42) The extraction means 58 extracts policy objectives (e.g., employment support, education support, medical and nursing care support, promotion of going out, tourism promotion, environmental contribution) that are associated with the elements of the regional transportation score extracted in step SP40, and for which the relationship between the element and the policy objective is above a certain value (e.g., promotion of going out, tourism promotion). Then, the process moves on to the processing in step SP44.

[0076] (Step SP44) The output means 60 outputs (displays) the policy objective proposal screen to the terminal device 12 held by the user.

[0077] Figure 10 shows an example of a policy objective proposal screen 110 according to this embodiment.

[0078] As shown in Figure 10, the proposal screen 110 is provided with a proposal information area 112 and a complete button 114. The proposed information area 112 shows the policy objectives extracted in step SP42. The "Complete" button 114 is used to close the proposal screen 110 and return to the policy objective proposal menu.

[0079] Then, the process concludes with the series of steps shown in Figure 8.

[0080] <Effects> In this embodiment, the computer functions as an acquisition means 54 for acquiring relevant data relating to at least local transportation methods, a calculation means 56 for calculating score values ​​corresponding to each element of the local transportation score associated with multiple transportation policies according to the relevant data, an extraction means 58 for extracting local transportation policies based on the score values ​​corresponding to each element of the local transportation score, and an output means 60 for outputting information indicating the extracted local transportation policies.

[0081] This configuration allows for the output of information indicating local transportation policies based on a regional transportation score corresponding to relevant data on local transportation methods, thus enabling the proposal of transportation policies that take into account the specific circumstances of each region.

[0082] Furthermore, in this embodiment, the extraction means 58 prioritizes extracting transportation measures that are associated with elements of the regional transportation score that have low score values ​​and that improve those score values.

[0083] This configuration allows for the prioritization of outputting transportation measures that improve low score values ​​among the elements of the regional transportation score, thus enabling the proposal of transportation measures that take into account the specific circumstances of each region.

[0084] Furthermore, in this embodiment, the computer functions as a receiving means 52 that receives extraction requests for extracting regional transportation policies, which include policy objectives corresponding to any element of the regional transportation score. The extraction means 58 then extracts regional transportation policies based on the elements of the regional transportation score associated with the policy objectives included in the received extraction requests.

[0085] This configuration allows for the output of regional transportation policies based on elements of regional transportation scores associated with policy objectives included in the extraction request, thus enabling the proposal of transportation policies that take into account the specific circumstances of each region.

[0086] Furthermore, in this embodiment, the computer functions as an acquisition means 54 for acquiring relevant data on at least local transportation methods, a calculation means 56 for calculating score values ​​corresponding to each element of the local transportation score which is associated with a plurality of policy objectives according to the relevant data, an extraction means 58 for extracting local policy objectives based on the score values ​​corresponding to each element of the local transportation score, and an output means 60 for outputting information indicating the extracted local policy objectives.

[0087] This configuration allows for the output of information indicating regional policy objectives based on a regional transportation score corresponding to relevant data on local transportation methods, thus enabling the proposal of policy objectives that take into account the specific circumstances of each region.

[0088] Furthermore, in this embodiment, the extraction means 58 prioritizes extracting policy objectives that are associated with elements of the regional traffic score that have low score values ​​and that improve those score values.

[0089] This configuration allows for the prioritization of policy objectives that improve low-scoring elements of the regional transportation score, thus enabling the proposal of policy objectives that take into account the specific circumstances of each region.

[0090] Furthermore, in this embodiment, the computer functions as a receiving means 52 that receives extraction requests for extracting regional policy objectives, which include transportation measures corresponding to any element of the regional transportation score. The extraction means 58 then extracts regional policy objectives based on the elements of the regional transportation score associated with the transportation measures included in the received extraction requests.

[0091] This configuration allows for the output of regional policy objectives based on elements of regional transportation scores associated with transportation policies included in the extraction request, thus enabling the proposal of policy objectives that take into account the specific circumstances of each region.

[0092] <Variation> It should be noted that the present invention is not limited to the embodiments described above. That is, any design modifications made to the above embodiments by those skilled in the art are also included within the scope of the present invention, as long as they retain the features of the present invention. Furthermore, the elements of the above embodiments and the modifications described later can be combined to the extent that it is technically possible, and any combination thereof is also included within the scope of the present invention, as long as it retains the features of the present invention.

[0093] For example, in the above embodiment, the extraction means 58 was described as preferentially extracting transportation measures that improve the score value, which are associated with the element with the lowest score value among the elements of the regional transportation score. However, it is not limited to this. For example, the extraction means 58 may preferentially extract transportation measures that worsen the score value. In this case, the output means 60 may suggest not to implement the extracted transportation measures.

[0094] Furthermore, in the above embodiment, the extraction means 58 was described as preferentially extracting policy objectives that improve the score value, which are associated with the element with the lowest score value among the elements of the regional traffic score. However, it is not limited to this. For example, the extraction means 58 may preferentially extract policy objectives that worsen the score value. In this case, the output means 60 may suggest not to implement the extracted policy objectives.

[0095] Furthermore, in the above embodiment, the extraction means 58 was described as extracting the element that has the highest correlation with the policy objective among the elements of the regional traffic score associated with the policy objective included in the extraction request. However, multiple elements that have a high correlation with the policy objective may be extracted.

[0096] Furthermore, in the above embodiment, the extraction means 58 was described as extracting the element that has the highest relationship with the transportation policy among the elements of the regional transportation score associated with the transportation policy included in the extraction request. However, multiple elements that have a high relationship with the transportation policy may be extracted. [Explanation of Symbols]

[0097] 10…Server device (computer) 12…Terminal device 50...Memory means 52…Method of Reception 54…Acquisition means 56...Calculation method 58...Extraction means 60…Output means

Claims

1. Computers, A means of obtaining relevant data, at least regarding local transportation methods. A calculation means for calculating score values ​​corresponding to each element of the regional transportation score, which is associated with multiple transportation policies, according to the aforementioned related data. An extraction means for extracting regional transportation policies based on the score values ​​corresponding to each element of the regional transportation score, Output means for outputting information indicating the transportation policies of the extracted region, To make it function as, The extraction means prioritizes extracting transportation measures that improve the score value of the elements of the regional transportation score that are associated with the element with the lowest score value. program.

2. The aforementioned computer, A receiving means that accepts an extraction request for extracting transportation policies for the aforementioned region, which includes a policy objective corresponding to any element of the aforementioned regional transportation score. To make it function as, The extraction means extracts the regional transportation policies based on the elements of the regional transportation score that correspond to the policy objectives included in the received extraction request. The program according to claim 1.

3. Computers, A means of obtaining relevant data, at least regarding local transportation methods. A calculation means for calculating score values ​​corresponding to each element of a regional transportation score that is associated with multiple policy objectives, in accordance with the aforementioned related data. An extraction means for extracting policy objectives for the region based on the score values ​​corresponding to each element of the aforementioned regional transportation score, Output means for outputting information indicating the policy objectives of the extracted region, To make it function as, The extraction means prioritizes extracting policy objectives that are associated with elements of the regional traffic score that have low score values, and that improve those score values. program.

4. The aforementioned computer, A receiving means that accepts an extraction request for extracting policy objectives for the aforementioned region, which includes a transportation policy corresponding to any element of the aforementioned regional transportation score. To make it function as, The extraction means extracts the policy objectives of the region based on the elements of the regional transportation score that are associated with the transportation policies included in the received extraction request. The program according to claim 3.

5. A means of obtaining relevant data, at least regarding local transportation methods, A calculation means for calculating score values ​​corresponding to each element of a regional transportation score associated with multiple transportation policies, based on the aforementioned related data, An extraction means for extracting regional transportation policies based on score values ​​corresponding to each element of the aforementioned regional transportation score, An output means that outputs information indicating the transportation policies of the extracted region, Equipped with, The extraction means prioritizes extracting transportation measures that improve the score value of the elements of the regional transportation score that are associated with the element with the lowest score value. Information processing device.

6. A means of obtaining relevant data, at least regarding local transportation methods, A calculation means for calculating score values ​​corresponding to each element of the regional transportation score that is associated with multiple policy objectives, in accordance with the aforementioned related data, An extraction means for extracting policy objectives for the region based on the score values ​​corresponding to each element of the aforementioned regional transportation score, An output means that outputs information indicating the policy objectives of the extracted region, Equipped with, The extraction means prioritizes extracting policy objectives that are associated with elements of the regional traffic score that have low score values, and that improve those score values. Information processing device.

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