Presentation device and presentation method

Abstract

In a presentation device (10), an execution unit (15b) executes each of linked simulations using a prescribed parameter. A revision unit (15c) revises the parameter using the difference between a predicted value obtained by the executed simulations and a measured value corresponding to said predicted value.

Description

Presentation device and presentation method

[0001] The present invention relates to a presentation device and a presentation method.

[0002] In recent years, technologies for linking multiple heterogeneous simulations in digital twins (DTs), which recreate real spaces in cyberspace, have been disclosed (see Non-Patent Documents 1 to 3).

[0003] "Car Navi Time starts providing flood warning spots and hazard maps," [online], September 2022, Navi Time Japan, [accessed August 10, 2023], Internet<URL:https: / / travel.watch.impress.co.jp / docs / news / 1443854.html> “Parameter Estimation Method for People Flow Simulation”, [online], 2017, DEIM Forum 2017 P5-4, [Retrieved August 10, 2023], Internet<URL:https: / / db-event.jpn.org / deim2017 / papers / 146.pdf> “Time-series simulation of flood evacuation behavior by foot and car,” [online], March 2023, Lightech Co., Ltd. [Retrieved July 31, 2023], Internet<URL:https: / / www.mlit.go.jp / plateau / use-case / uc22-039 / >

[0004] However, with conventional technology, it can be difficult to link multiple simulations in real time without reducing the accuracy of the predicted DT created using the simulation results. For example, when multiple different simulations are repeatedly run on a current DT and the prediction results are used in real time to predict the future as a predicted DT, the execution results of each simulator and the correction results of the simulation parameters cannot be exchanged between simulators in real time. As a result, it has been difficult to obtain prediction results without reducing the prediction accuracy.

[0005] The present invention has been made in consideration of the above, and aims to link multiple simulations in real time without reducing the accuracy of the predicted DT created using the simulation results.

[0006] In order to solve the above-mentioned problems and achieve the objectives, the presentation device of the present invention is characterized by having an execution unit that executes each of the linked simulations using predetermined parameters, and a correction unit that corrects the parameters using the difference between the predicted value obtained by each executed simulation and the actual measured value corresponding to the predicted value.

[0007] According to the present invention, it is possible to link multiple simulations in real time without reducing the accuracy of the predicted DT created using the results of the simulations.

[0008] FIG. 1 is a diagram for explaining an overview of the presentation device of this embodiment. FIG. 2 is a diagram for explaining an overview of the presentation device of this embodiment. FIG. 3 is a schematic diagram illustrating a general configuration of the presentation device of this embodiment. FIG. 4 is a diagram illustrating an example of a data structure of a DB. FIG. 5 is a diagram for explaining the data structure of the DB. FIG. 6 is a diagram illustrating an example of a screen display of results. FIG. 7 is an example of a screen display of presentation processing results. FIG. 8 is a flowchart showing the presentation processing procedure. FIG. 9 is a flowchart showing the presentation processing procedure. FIG. 10 is a flowchart showing the presentation processing procedure. FIG. 11 is a flowchart showing the presentation processing procedure. FIG. 12 is a diagram for explaining the presentation processing. FIG. 13 is a diagram illustrating an example of a computer that executes a presentation program.

[0009] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. Note that the present invention is not limited to this embodiment. In addition, in the description of the drawings, the same parts are designated by the same reference numerals.

[0010] [Outline of Presentation Device] The presentation device of this embodiment executes a plurality of simulations in cooperation with each other on a current DT (actually measured DT), thereby generating and presenting a predicted DT.

[0011] In this case, the presentation device periodically acquires actual measured values, compares the actual measured values ​​with the predicted values ​​output by each simulation, and updates the parameters of each simulation to reduce the difference. The output predicted values ​​and the updated parameters are stored in a database (DB). Each simulation is executed using the latest parameters obtained via the DB and the predicted results of other simulations linked to it.

[0012] In this way, the presentation device allows each simulation to obtain the predicted results and the latest simulation parameters in real time, making it possible to present the predicted DT without reducing the prediction accuracy.

[0013] 1 and 2 are diagrams for explaining an overview of the presentation device of this embodiment. For example, in FIG. 1 and FIG. 2, a case is illustrated in which multiple simulations, namely, simulation A predicting the spread of flooding (whether or not flooding will occur at each point) and simulation B predicting the evacuation (walking) status of evacuees, are executed in real time in cooperation with each other via a database.

[0014] Specifically, as illustrated in Figure 1(a), the presentation device avoids route 1, which is predicted to cause flooding to spread, and presents route 2, which allows evacuees at current location A to evacuate to shelter B, as a predicted DT.

[0015] In this case, the databases are configured as an actual measurement database for storing actual measured values ​​and a predicted database for storing predicted values. Specifically, as shown in Fig. 1(b), the databases include an actual measurement moving object database for storing actual measured values ​​of information about evacuees (agents), a predicted moving object database for storing predicted values ​​and parameters related to evacuees, a measured environment database for storing actual measured values ​​related to map information and flood conditions, and a predicted environment database for storing predicted values ​​and parameters related to flood conditions.

[0016] As shown in FIG. 2(a), actual measurement values ​​such as the location information of evacuees are acquired and stored in the actual measurement DB, and data that realizes the actual measurement DT is generated and displayed on the display.

[0017] First, Simulation A predicts the spread of flooding, i.e., whether or not there will be flooding at each point. The prediction results of Simulation A, i.e., whether or not there will be flooding at each point, are stored in the predicted environment DB. When Simulation A is run, the flooding speed stored in the predicted environment DB is used as a parameter, as shown in Figure 2(b) as an example.

[0018] Furthermore, as shown in Figure 2(c), Simulation B uses the prediction results of Simulation A and the walking speed parameter to predict the walking conditions of evacuees, such as their location information and route. As a result, as shown in Figure 1(a), Route 1, which includes a point where flooding is predicted, is avoided, and Route 2 is presented as the optimal evacuation route.

[0019] Here, if the walking speed of the evacuee used as a parameter for simulation B has changed due to injury, fatigue, etc., the corrected walking speed is stored in the predicted moving object DB. Specifically, as shown in Fig. 2(d), the walking speed is calculated using the actual measured value of the pedestrian position information acquired from the sensor and the predicted value of the pedestrian position information obtained by simulation B, and the value in the predicted moving object DB is corrected so as to reduce the difference between the two.

[0020] Furthermore, if the flooding speed used as a parameter of simulation A changes, the corrected flooding speed is stored in the predicted environment DB. Specifically, as shown in Figure 2(e), the predicted value of whether or not there is flooding, which is the prediction result of simulation A, and the actual measured value of whether or not there is flooding are used to calculate the flooding speed, which is a parameter, and correct the value in the predicted environment DB so as to reduce the difference between the two.

[0021] In this way, by periodically acquiring actual measurements and correcting the parameters required for the simulation, it becomes possible to link multiple simulations and execute them in real time while maintaining accuracy.

[0022] [Configuration of Presentation Device] Fig. 3 is a schematic diagram illustrating the overall configuration of a presentation device according to the present embodiment. As illustrated in Fig. 3, the presentation device 10 according to the present embodiment is realized by a general-purpose computer such as a personal computer, and includes an input unit 11, an output unit 12, a communication control unit 13, a storage unit 14, and a control unit 15.

[0023] The input unit 11 is realized using input devices such as a keyboard, a mouse, a sensor, etc., and inputs various instruction information such as a command to start processing, actual measured values ​​obtained by a sensor, etc. to the control unit 15 in response to input operations by an operator. The output unit 12 is realized by a display device such as a liquid crystal display, a printing device such as a printer, etc. For example, the output unit 12 displays the results of a presentation process described below.

[0024] The communication control unit 13 is realized by a NIC (Network Interface Card) or the like, and controls communication between the control unit 15 and external devices via telecommunication lines such as a LAN (Local Area Network) or the Internet. For example, the communication control unit 13 controls communication between the control unit 15 and a management device or the like that manages various types of information.

[0025] The storage unit 14 is realized by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 14 stores in advance the processing program that operates the presentation device 10 and data used during execution of the processing program, or temporarily stores the data each time processing is performed. The storage unit 14 may be configured to communicate with the control unit 15 via the communication control unit 13.

[0026] In this embodiment, the storage unit 14 stores an actual measurement DB 14a and a predicted DB 14b used in the presentation process described below. The actual measurement DB 14a stores actual measurement values ​​used in the presentation process. The actual measurement DB 14a includes, for example, a measured moving object DB 14c and a measured environment DB 14d. The predicted DB 14b stores predicted values ​​generated and used in the presentation process. The predicted DB 14b includes, for example, a predicted moving object DB 14e and a predicted environment DB 14f.

[0027] Here, Fig. 4 is a diagram illustrating an example of the data structure of the DB. Fig. 5 is a diagram for explaining the data structure of the DB. The measured moving object DB 14c stores measured values ​​of information related to evacuees (agents). Specifically, as illustrated in Fig. 4(a), the information includes information items such as the agent name of the evacuee, agent attributes, time, location information consisting of latitude and longitude, walking speed, etc.

[0028] The predicted moving object DB 14e also stores predicted values ​​and parameters based on the simulation B (pedestrian simulation) regarding evacuees. Specifically, as shown in Fig. 4B, the predicted moving object DB 14e includes the same information items as those in the measured moving object DB 14c shown in Fig. 4A.

[0029] As will be described later, in the presentation process, for example, location information is used as a comparison element, and the actual measured value of the comparison element is compared with the predicted value by simulation B (pedestrian simulation), and walking speed is used as the parameter of simulation B to be corrected.

[0030] The measured environment DB 14d also stores map information, road information, and measured values ​​related to the flooding situation. The map information and road information are obtained, for example, from the Internet and stored in advance. Specifically, as shown in FIG. 4C, the information includes information items such as the area number, time, influencing factors, and flooding speed for each area.

[0031] The predicted environment DB 14f also stores predicted values ​​and parameters from a flood simulation A. Specifically, as shown in Fig. 4(d), the predicted environment DB 14f includes the same information items as the measured environment DB 14d shown in Fig. 4(c).

[0032] As will be described later, in the presentation process, for example, the presence or absence of flooding in each area and other environmental parameters are used as influencing factors, and the actual measured values ​​of the influencing factors are compared with the predicted values ​​from Simulation A (flooding simulation), and the flooding speed is used as the parameter of Simulation A to be corrected.

[0033] In addition, the agents (evacuees) in the above-mentioned measured moving object DB 14c and predicted moving object DB 14e are identified by their agent names. Furthermore, as shown in Fig. 5(a), the position information of each agent is specified by its latitude and longitude on a map.

[0034] Furthermore, each area in the measured environment DB 14d and the predicted environment DB 14f is identified by an area number that identifies each area obtained by dividing a map into meshes, as shown in Fig. 5(a). In this case, the latitude and longitude for each area number are managed in the area DB, as shown in Fig. 5(b). This allows the location information of evacuees to be linked to the areas on the map.

[0035] Returning to the description of FIG. 3 , the control unit 15 is realized using a CPU (Central Processing Unit), an NP (Network Processor), an FPGA (Field Programmable Gate Array), or the like, and executes a processing program stored in memory. As a result, the control unit 15 functions as an acquisition unit 15a, an execution unit 15b, a correction unit 15c, and a presentation unit 15d, as exemplified in FIG. 3 , and executes the presentation process. Note that these functional units may each be implemented in different hardware, or some of them may be implemented in different hardware. The control unit 15 may also include other functional units.

[0036] The acquisition unit 15a acquires predetermined measured values ​​and predetermined parameters used in each of the linked simulations. For example, the acquisition unit 15a acquires, via the input unit 11 or the communication control unit 13, the agent's position information, the actual measured values ​​measured by sensors such as whether or not each area is flooded, map information, road information, etc. from the actual measurement DB 14a.

[0037] The acquisition unit 15a stores the actual measurement values ​​obtained by the sensors in the actual measurement DB 14a of the storage unit 14. The acquisition unit 15a also acquires predetermined parameters used for each of the linked simulators from the prediction DB 14b, which will be described later.

[0038] 6 is a diagram illustrating the presentation process. In the example shown in FIG. 6, the acquisition unit 15a acquires an actual measurement value A, such as location information and water level information, from sensor A, and acquires an actual measurement value B from sensor B. Based on the acquired data, data for presenting the actual measurement DT is generated and stored in the actual measurement DB 14a. The presentation unit 15d, which will be described later, displays the actual measurement DT on the display (output unit 12).

[0039] Returning to the explanation of Fig. 3, the execution unit 15b executes each of the linked simulations using predetermined parameters. The execution unit 15b is realized, for example, by a simulator for each simulation. In the examples shown in Figs. 1, 2, and 6, the execution unit 15b is realized by simulator A that executes simulation A and simulator B that executes simulation B.

[0040] 6, the execution unit 15b (simulators A and B) acquires initial parameters from Initial Parameters the first time, executes simulations A and B using these parameters, and outputs predicted values ​​A and B. From the second time onwards, the execution unit 15b acquires parameters corrected by the correction unit 15c (described later) from Dynamic Parameters, executes simulations A and B using these parameters, and outputs predicted values ​​A and B.

[0041] Based on the obtained data, data for presenting the predicted DT is generated and stored in the prediction DB 14b. The presenting unit 15d (described later) displays the predicted DT on the display (output unit 12).

[0042] The initial parameters and dynamic parameters are stored in, for example, the prediction DB 14b of the storage unit 14.

[0043] The simulation unit 15b may also execute each simulation using predicted values ​​obtained from each executed simulation or actual measured values ​​corresponding to the predicted values. In the example shown in Fig. 2, the predicted values ​​of the presence or absence of flooding, etc. outputted in simulation A in Fig. 2(b) are used when executing simulation B in Fig. 2(c).

[0044] Furthermore, the execution unit 15b stores the predicted values ​​obtained by executing each simulation in the prediction DB 14b of the storage unit 14.

[0045] Returning to the description of Fig. 3, the correction unit 15c corrects the parameters used in each simulation using the difference between the predicted value obtained by each executed simulation and the actual measurement value corresponding to the predicted value. Specifically, as illustrated in Fig. 6, the correction unit 15c compares the actual measurement value acquired from the actual measurement DB 14a with the predicted value acquired from the prediction DB 14b, and calculates optimal simulation parameters from the difference between the actual measurement value and the predicted value.

[0046] The correction unit 15c continuously performs such parameter correction processing and stores the corrected parameters in the storage unit 14. In the example shown in Fig. 6, the dynamic parameters in the storage unit 14 are updated every time the parameters are corrected.

[0047] For example, in the example shown in Figure 2(e), the predicted value of inundation from Simulation A is compared with the actual measured value of inundation, and the inundation speed is corrected as a parameter. That is, for example, for the presence or absence of inundation at each point, the inundation speed is corrected so as to eliminate the discrepancy between the actual measured value at the same time and the predicted value of the simulation result.

[0048] 2(d), the walking speed is corrected as a parameter by comparing the comparison factors, such as the location information of the evacuees, which are the predicted values ​​of Simulation B, with the actual measured values ​​of the comparison factors. That is, for example, the walking speed is corrected so as to eliminate the discrepancy between the actual measured value at the same time and the predicted value of the simulation result for the location information of the evacuees.

[0049] In this case, the correction unit 15c estimates the cause of the discrepancy in the comparison elements using, for example, the comparison elements and detailed information about the evacuee other than the comparison elements, such as walking speed and direction of movement, and corrects the walking speed so as to eliminate the estimated cause of the discrepancy.

[0050] As described above, the storage unit 14 stores the predicted values ​​and corrected parameters of each simulation, which allows the execution unit 15b to easily refer to the storage unit 14 and use the predicted values ​​and latest parameters of other simulations when executing each linked simulation.

[0051] 3, the presentation unit 15d presents the presentation process result. Specifically, the presentation unit 15d displays the actual measurement DT or the predicted DT, which is the linked simulation result, on the output unit 12.

[0052] Here, Fig. 7 shows an example of a screen display of the results of the presentation process. Specifically, Fig. 7 shows a case where a flood simulation and a simulation of evacuees' walking are linked, with Fig. 7(a) illustrating an example of the measured DT and Fig. 7(b) illustrating an example of the predicted DT. In this case, as shown in Fig. 7(b), even if there is a change in walking speed due to fatigue or injury or a change in the rate at which the flood area spreads, it is possible to avoid flooded areas and present the evacuees with an optimal route by correcting the parameters.

[0053] [Presentation Process] Next, the presentation process by the presentation device 10 according to the present embodiment will be described with reference to Fig. 8 to Fig. 12. Fig. 8 to Fig. 11 are flowcharts showing the procedure of the presentation process. Fig. 12 is a diagram for explaining the presentation process.

[0054] First, a procedure for presenting the measured DT is illustrated in Fig. 8. The flowchart in Fig. 8 starts, for example, when the user performs an operation input to instruct the start of the procedure.

[0055] First, the acquisition unit 15a acquires various actual measurement values ​​from sensors, the Internet, etc. via the input unit 11 or the communication control unit 13 (step S1).

[0056] The acquisition unit 15a converts each actual measurement value into a predetermined format so as to be consistent with the current DT data, and stores the converted data in the actual measurement DB 14a (steps S2 to S3).

[0057] Then, the presentation unit 15d visualizes and presents the measured DT based on the DT data in the measurement DB 14a (step S4), thereby completing the series of processes.

[0058] Next, the first execution procedure of the linked simulation is illustrated in Fig. 9. The flowchart in Fig. 9 starts, for example, when the user performs an operation input to instruct the start of the simulation.

[0059] First, the simulation unit 15b acquires the initial parameters of each simulation from the Initial Parameters shown in FIG. 6 and sets them as Dynamic Parameters (step S11).

[0060] Then, the simulation unit 15b executes each simulation to generate predicted values ​​for a predetermined time t1 (for example, 5 minutes) from the present (step S12).

[0061] The execution unit 15b converts each predicted value into a predetermined format to generate DT data for each time period (step S13). The execution unit 15b also stores the DT data for a predetermined time t2 from the current time in the prediction DB 14b (step S14).

[0062] Then, the presentation unit 15d visualizes and presents the predicted DT based on the DT data in the prediction DB 14b (step S15).

[0063] If there is DT data for the next time t2 hours (e.g., 1 second, t2<t1) after the current time (Yes in step S16), the presenter 15d returns to step S14. On the other hand, if there is no DT data for the next time t2 hours after the current time (No in step S16), the presenter 15d ends the series of processes.

[0064] 10 illustrates an example of a procedure for executing the linked simulation from the second time onward. The flowchart in FIG. 10 starts, for example, when the first processing shown in FIG. 9 is completed.

[0065] First, the correction unit 15c acquires actual measurement values ​​from the actual measurement DB 14a and estimates values ​​from the estimate DB 14b among the DT data for the previous simulation time (step S21).

[0066] Next, if there is a difference between the actual measured value and the predicted value of the acquired DT data (step S22, Yes), the correction unit 15c calculates a parameter to correct the difference and stores it in the memory unit 14, for example, as a Dynamic Parameter (step S23).

[0067] The simulation unit 15b then acquires the latest parameters for each simulation from the Dynamic Parameter (step S24).Then, the simulation unit 15b executes each simulation in the same manner as the first simulation shown in FIG. 9, thereby generating predicted values ​​for a predetermined time period t1 from the present (step S12).

[0068] The execution unit 15b converts each predicted value into a predetermined format to generate DT data for each time period (step S13). The execution unit 15b also stores the DT data for a predetermined time t2 from the current time in the prediction DB 14b (step S14).

[0069] Then, the presentation unit 15d visualizes and presents the predicted DT based on the DT data in the prediction DB 14b (step S15).

[0070] If there is DT data for the next time t2 hours after the current time (Yes in step S16), the presenter 15d returns the process to step S14. On the other hand, if there is no DT data for the next time t2 hours after the current time (No in step S16), the presenter 15d ends the series of processes.

[0071] Fig. 11 illustrates a detailed processing procedure for parameter correction shown in steps S21 to S23 in Fig. 10. Similar to the flowchart in Fig. 10, the flowchart in Fig. 11 starts, for example, when the first processing shown in Fig. 9 is completed.

[0072] Specifically, the correction unit 15c first acquires the actual measured value from the actual moving object DB 14c and the predicted value from the predicted moving object DB 14e for a predetermined comparison element for each agent (Step S31). If the difference (deviation) between the actual measured value and the predicted value of the comparison element is less than a predetermined threshold (Step S32, Yes), the correction unit 15c proceeds to Step S41.

[0073] On the other hand, if the difference (deviation) between the actual value and the predicted value of this comparison element is equal to or greater than a predetermined threshold (No in step S32), the correction unit 15c corrects the parameter to eliminate the deviation. In this case, the comparison element is, for example, location information, and the parameter to be corrected is, for example, walking speed.

[0074] First, the correction unit 15c causes the execution unit 15b to suspend the execution of the simulation (step S33). The correction unit 15c also estimates the cause of the deviation in the comparison factor. For example, the correction unit 15c makes the estimation using the comparison factor and detailed information about the moving object (agent) other than the comparison factor, such as walking speed and movement direction. The correction unit 15c then sets simulation parameters for each agent based on the estimated cause of the deviation in the comparison factor (step S34). The correction unit 15c also updates the predicted value of the comparison factor in the predicted moving object DB 14e (step S35).

[0075] Next, the corrector 15c acquires the actual measured values ​​of the influencing factors for each area from the actual environment DB 14d and the predicted values ​​from the predicted environment DB 14f (Step S41). If the difference (deviation) between the actual measured values ​​and the predicted values ​​of the influencing factors is less than a predetermined threshold (Yes in Step S42), the corrector 15c proceeds to Step S46.

[0076] On the other hand, if the difference (deviation) between the actual measured value and the predicted value of this influencing factor is equal to or greater than the predetermined threshold (No in step S42), the corrector 15c corrects the parameter. In this case, the influencing factor is, for example, whether or not each area is flooded, and the corrected parameter is, for example, the flooding speed.

[0077] First, the corrector 15c causes the simulator 15b to suspend the execution of the simulation (step S43). Then, the corrector 15c sets the simulation parameters according to the actual measurement environment (step S44). The corrector 15c also updates the predicted values ​​of the influencing factors in the predicted environment DB 14f (step S45).

[0078] Thereafter, the correcting unit 15c causes the executing unit 15b to resume the execution of the simulation (step S46), thereby completing the series of processes and starting the execution of the next simulation (step S24 in FIG. 10).

[0079] In this way, in the presentation process, the processes of "simulation to calculate the future," "collection of comparison data (actual values ​​and predicted values) from the actual DT / predicted DT," and "parameter correction through comparison" are repeated for each of the multiple linked simulations, as shown in Fig. 12. This makes it easy to generate a predicted DT from the linked simulations in real time without reducing the prediction accuracy.

[0080] As described above, in the presentation device 10 of this embodiment, the execution unit 15b executes each of the linked simulations using predetermined parameters, and the correction unit 15c corrects the parameters using the difference between the predicted value obtained by each executed simulation and the actual measurement value corresponding to the predicted value.

[0081] Specifically, the execution unit 15b executes each of the linked simulations by further using the predicted values ​​or the actual measured values ​​corresponding to the predicted values.

[0082] This makes it possible to execute linked simulations in real time without reducing the prediction accuracy of the predicted DT created using the simulation results.

[0083] Furthermore, the predicted values ​​and the corrected parameters are stored in the storage unit 14. This makes it possible to easily link a plurality of simulations.

[0084] [Program] A program written in a computer-executable language may be created to execute the processes executed by the presentation device 10 according to the above embodiment. In one embodiment, the presentation device 10 can be implemented by installing a presentation program that executes the above presentation process as package software or online software on a desired computer. For example, by executing the presentation program on an information processing device, the information processing device can function as the presentation device 10. The information processing device referred to here includes desktop and notebook personal computers. Other examples of information processing devices include mobile communication terminals such as smartphones, mobile phones, and PHS (Personal Handyphone Systems), as well as slate terminals such as PDAs (Personal Digital Assistants). The functions of the presentation device 10 may also be implemented on a cloud server.

[0085] 13 is a diagram showing an example of a computer that executes a presentation program. The computer 1000 includes, for example, a memory 1010, a CPU 1020, a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, and a network interface 1070. These components are connected by a bus 1080.

[0086] The memory 1010 includes a ROM (Read Only Memory) 1011 and a RAM 1012. The ROM 1011 stores a boot program such as a BIOS (Basic Input Output System). The hard disk drive interface 1030 is connected to a hard disk drive 1031. The disk drive interface 1040 is connected to a disk drive 1041. A removable storage medium such as a magnetic disk or optical disk is inserted into the disk drive 1041. The serial port interface 1050 is connected to a mouse 1051 and a keyboard 1052, for example. The video adapter 1060 is connected to a display 1061, for example.

[0087] Here, the hard disk drive 1031 stores, for example, an OS (Operating System) 1091, an application program 1092, a program module 1093, and program data 1094. The various pieces of information described in the above embodiments are stored in the hard disk drive 1031 or the memory 1010, for example.

[0088] The presentation program is stored in the hard disk drive 1031 as, for example, a program module 1093 in which instructions to be executed by the computer 1000 are written. Specifically, the program module 1093 in which each process executed by the presentation device 10 described in the above embodiment is written is stored in the hard disk drive 1031.

[0089] Data used for information processing by the presentation program is stored as program data 1094, for example, in the hard disk drive 1031. Then, the CPU 1020 reads the program module 1093 and the program data 1094 stored in the hard disk drive 1031 into the RAM 1012 as necessary, and executes each of the above-described procedures.

[0090] The program module 1093 and program data 1094 related to the presentation program are not limited to being stored in the hard disk drive 1031, and may be stored in, for example, a removable storage medium and read by the CPU 1020 via the disk drive 1041. Alternatively, the program module 1093 and program data 1094 related to the presentation program may be stored in another computer connected via a network such as a LAN or a WAN (Wide Area Network), and read by the CPU 1020 via the network interface 1070.

[0091] Although the present invention has been described above as an embodiment, the present invention is not limited to the description and drawings that form part of the disclosure of the present invention. In other words, other embodiments, examples, and operational techniques that can be made by those skilled in the art based on the present invention are all included in the scope of the present invention.

[0092] REFERENCE SIGNS LIST 10 Presentation device 11 Input unit 12 Output unit 13 Communication control unit 14 Storage unit 14a Actual measurement DB 14b Prediction DB 14c Actual measurement moving object DB 14d Actual measurement environment DB 14e Prediction moving object DB 14f Prediction environment DB 15 Control unit 15a Acquisition unit 15b Execution unit 15c Correction unit 15d Presentation unit

Claims

1. A presentation device comprising: an execution unit that executes each of linked simulations using predetermined parameters; and a correction unit that corrects the parameters using the difference between a predicted value obtained by each executed simulation and an actual value corresponding to the predicted value.

2. The presentation device according to claim 1, further comprising a storage unit for storing the predicted values ​​and the corrected parameters.

3. The presentation device according to claim 1, wherein the execution unit executes each simulation by further using the predicted value or an actual measurement value corresponding to the predicted value.

4. A presentation method executed by a presentation device, comprising: an execution step of executing each of the linked simulations using predetermined parameters; and a correction step of correcting the parameters using the difference between a predicted value obtained by each executed simulation and an actual measurement value corresponding to the predicted value.

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