JP2004287708A - Road closing state predicting/reporting system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To make it possible for regional residents and an autonomy or the like to facilitate sufficient proactive measures by predicting in advance the closing of roads due to snow or rain and the isolation of a certain region, and reporting it to the region. <P>SOLUTION: This system is provided with a road modeling means for modeling the connecting state of roads in a predetermined region with nodes and branches, a simulator means for predictively calculating snow depth or rainfall in a designated time at observation points arranged on the branch, and for operating virtual blocking means arranged at the both edges of the branch when the predicted value exceeds an allowable value, a road system searching means for successively searching paths passing through the nodes and branches in a predetermined range, and for detecting the branch where the blocking means are put in operating states and a road closing predicting and reporting means for detecting the road section corresponding to the branch where the blocking means are put in the operating state as a closed road, and for reporting the road closing prediction to the region having the closed road. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention predicts when a road will be unusable and will be closed due to snowfall (snowfall) or rainfall, and reports future road closures and district closures to areas affected by the road closure. Further, the present invention relates to a road closure state prediction / notification system which is used for disaster prevention in advance by local residents, local governments, NPOs (Nonprofit Organizations), and the like.
[0002]
[Prior art]
Conventionally, for monitoring and forecasting snowfall and rainfall, meteorological observation information such as AMeDAS collected by regional meteorological observatories, and weather information for road condition monitoring collected from major arterial roads by the Ministry of Land, Infrastructure, Transport and Tourism are used. ing.
This information is collected as numerical data and image data at regular time intervals to report the current snowfall, rainfall, roads, rivers, etc., and to report future snowfall, rainfall, river flooding, etc. It is used to make predictions, and various warnings, warnings, and the like are issued according to these prediction values.
In addition, police and fire departments in charge of the district take precautionary measures such as closing roads to prevent accidents and guiding evacuation of nearby residents according to the predicted snowfall and rainfall. I have.
[0003]
Note that there are a large number of systems for monitoring and predicting the amount of snowfall and rainfall, such as the rainfall / snowfall prediction device described in Patent Document 1.
Further, a road condition observation system for observing a road surface condition such as the amount of snow on a road and freezing is known as Patent Document 2.
[0004]
[Patent Document 1]
JP-A-10-239452
[Patent Document 2]
JP 2000-346957 A
[0005]
[Problems to be solved by the invention]
As described above, various systems for monitoring and predicting the amount of snow and rainfall have conventionally existed, and there are also systems for observing the amount of snow on a road and predicting the state of a road surface thereafter. It does not predict when the road will be closed, such as when the road will be closed.
On the other hand, at present, for major arterial roads such as expressways and general national roads, measures are taken to warn when snowfall or rainfall exceeds a certain value and to close the road as necessary. However, no prediction / reporting system has been proposed for a mountainous remote place where traffic and logistics are completely shut off from the surroundings due to the closure of a road, for example.
In particular, these areas often have a single route to the urban area where the nearest hospitals, nursing homes, public facilities such as police and fire departments, and eating and drinking facilities are located. It will seriously affect the lives of local residents, including those who require care and caregivers.
[0006]
For this reason, there is a strong demand for inhabitants in remote mountainous areas to appropriately and promptly obtain prediction information of road closure due to snowfall or rainfall. In addition, for the local government where the district is located, these forecast information should be provided at an early stage in order to guide evacuation of the residents of the district, secure advance transportation and transportation means, and carry out food and various supplies promptly and appropriately. It is required to obtain.
Therefore, the present invention has been made to solve the above-mentioned problems, and by predicting in advance the closure of a road due to snowfall and rainfall and the isolation of a certain area due to it and reporting to the relevant area, the residents of the area and It is an object of the present invention to provide a road closure state prediction / notification system that allows local governments to take sufficient precautionary measures.
[0007]
[Means for Solving the Problems]
In order to solve the above problem, the invention described in claim 1 is a system for predicting that a road will be closed within a designated time due to snowfall or rainfall, and for notifying,
Road modeling means for modeling the connection state of roads in a predetermined area to be predicted by nodes and branches, and predicting and calculating snow depth or rainfall within a specified time at observation points arranged on the branches When it is determined that the value exceeds the allowable value, simulator means for operating virtual blocking means arranged at both ends of the branch, and a path through nodes and branches in a predetermined area are sequentially searched for, and the blocking means A road system search means for detecting a branch in which the operating state is detected, and a road section in which the blocking means detects a road section corresponding to the branch in the operating state as a closed road, and reports a road closing forecast to an area having the closed road. Closing prediction notification means.
[0008]
According to a second aspect of the present invention, in the road closure state prediction / notification system according to the first aspect,
Means for detecting, as a closed area, an area in which road traffic depends only on the closed road, and for notifying an area having the closed area of an area close forecast.
[0009]
According to a third aspect of the present invention, in the road closure state prediction / notification system according to the first aspect,
The nodes and branches of the road modeled by the road modeling unit are stored as information in a database, and the database, the simulator unit, the road system search unit, and the road closure prediction notification unit include a local government or the like. This is realized by a server provided in.
[0010]
According to a fourth aspect of the present invention, in the road closure state prediction / notification system according to the second aspect,
The nodes and branches of the road modeled by the road modeling unit are stored as information in a database, and the database, the simulator unit, the road system search unit, and the district closure prediction notification unit include a higher-level local government or the like. This is realized by a server provided in.
[0011]
According to a fifth aspect of the present invention, in the road closure state prediction / notification system according to the third or fourth aspect,
The database stores measures to be executed by the lower-level local governments when a road closing forecast or a district closing forecast is issued to the lower-level local governments or the like.
These measures include, for example, ensuring that the sick or care recipients living in the district where the road closure forecast or district closure forecast is reported are thoroughly informed of the road closure information and the district closure information, Measures such as evacuation guidance are included.
For this reason, as described in claim 6, it is desirable that the database store the location information of a sick person or a care recipient who lives in the corresponding district.
[0012]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
First, FIG. 1 is a system configuration diagram of the present embodiment. In FIG. 1, reference numeral 10 denotes, for example, a higher-level local government such as a prefectural government, and a client / server type LAN (Local Area Network) 11 is constructed in the prefectural government where the department in charge of the road is located. The LAN 11 is composed of, for example, Ethernet (registered trademark), and includes a road closure state prediction monitoring server 12 as a main server, which is a center of the road closure state prediction / notification system according to the present invention, and a personal computer or the like as a client. , A database server 14 and a database 15 connected to the road closure state prediction monitoring server 12 by a high-speed channel, and a router 13.
[0013]
The main function of the road closure state prediction monitoring server 12 will be described. The server 12 sequentially collects snow depth (snow volume) data of a plurality of weather observation points described later, and a database 15 managed by a database server 14. Forecast calculation of the snow depth at a weather observation point after a specified time using the data described later in this section (time-dependent snow depth data, road node definition data, road branch definition data, road branch state data, route area data, etc.) Then, it is determined whether the predicted snow depth exceeds the allowable value. If the allowable value is exceeded, the road section corresponding to the weather station and the area related to the road section are determined in the future. It is determined that the road is a closed road / closed area, and the corresponding lower level local government 20 is notified of a road closed / area closed forecast.
[0014]
As described above, the road closed state prediction / monitoring server 12 may have a function of predicting, monitoring, and notifying the closed state of a road or a district based on snow depth data, and is not necessarily a dedicated server. That is, the function may be added to the existing server of the road department in charge of the higher-level local government 10, and the road closure state prediction monitoring server 12 may include a WWW (World Wide Web) server, a mail server, and a file server in addition to the function. Etc. may be provided.
The specific operation and main functions of the road closure state prediction monitoring server 12 and the specific contents of the database 15 will be described later in detail.
Although not shown, a private company as an assistant service provider commissioned by a higher-level local government has a road closure state prediction monitoring server 12, a database server 14, a database 15, terminals 16, 17 and the like. You may undertake the work of a local government.
[0015]
Next, reference numeral 50 denotes a meteorological observation system provided at a regional meteorological observatory of the Meteorological Agency, which is an unmanned meteorological observation device such as a so-called AMeDAS radar, a snowfall (snow depth) gauge, a rain gauge, a wind direction / wind speed gauge, and a thermometer. This system collects observation data (image data and numerical data) at regular time intervals, and analyzes and processes them by a server (not shown).
Among the observation data collected by the meteorological observation system 50, particularly the snow depth data can be collected by the road closure state prediction monitoring server 12 of the upper level local government 10 via the router 13 and the WAN (Wide Area Network) 91. (Arrow a).
Here, the configuration of the WAN 91 is preferably a VPN (Virtual Private Network) connection for encrypting and transmitting data on the Internet, for example, but a conventional packet communication network or the like may be used.
[0016]
Reference numeral 60 denotes a road monitoring system in which a local station of the Ministry of Land, Infrastructure, Transport and Tourism installs and manages various sensors on main arterial roads. This system 60 includes temperature, wind direction / speed, rainfall, traffic congestion, etc. Is also measured. Therefore, the road closure state prediction monitoring server 12 of the upper level local government 10 can collect the snow depth data of the weather observation point measured by the road monitoring system 60 via the router 13 and the WAN 92 (arrow b).
[0017]
Reference numeral 70 denotes a system monitoring and control system installed at a central command center or an electric power company.
As is well known, this system 70 constantly monitors the state of equipment at various electric stations and the amount of electricity in the system, and performs various control operations and protection operations for the purpose of stable supply of power and early recovery in the event of an accident. The project predicts incoming and outgoing water at hydropower plants, and measures snowfall and precipitation around the dam lake as data used for the prediction.
Therefore, the road closure state prediction monitoring server 12 of the upper level local government 10 can collect the snow depth data of the weather observation point measured by the system monitoring control system 70 via the router 13 and the dedicated line 95 (arrow c). .
Although not shown, data collected by the River Bureau of the Ministry of Land, Infrastructure, Transport and Tourism can also be used as snow depth data, and all possible snow depth data is used to improve prediction accuracy. It is desirable to do.
[0018]
On the other hand, reference numeral 20 denotes a lower-level local government such as a municipality, a county, or the like, which is a destination to which a road closure / district closure forecast (arrow x) reported from the higher-level local government 10 via the WAN 94 is described. That is, the village itself where the roads and districts are expected to be closed in the future, and the municipalities such as municipalities to which the village belongs correspond.
[0019]
A LAN 21 is constructed in the lower level local government 20 in the same manner as the upper level local government 10, and a server 22 that receives and processes the road closure / district closure forecast transmitted from the upper level local government 10, and a router 23 connected to the WAN 94. , A plurality of terminals 26, 27,...
Furthermore, a plurality of notification devices 29 are connected to the LAN 21 via a control device 28. These notification devices 29 notify the local residents by hearing or sighting the road closure / district closure forecast by voice or text, such as a speaker or a panel display installed outdoors. These notification devices 29 are driven by the control device 28.
[0020]
A WWW server or a mail server may be added to the LAN 21 in the lower level local government 20, and these functions may be added to the server 22. Further, a sick / care-requiring person location database or database server resident in the lower level local government 20 may be provided as necessary.
The terminals 26, 27,... Can display the road closure / district closure forecast received by the server 22. If some of the terminals are installed in a local government public information center, a resident center, a library, or the like, These terminals 26, 27,... Can also be used as a kind of notification device for staff and residents of the lower-level local government 29.
Note that reference numerals 30 and 40 in FIG. 1 indicate other lower-level municipalities belonging to the higher-level municipalities 10, and the internal configuration thereof is the same as that of the lower-level municipalities 20.
[0021]
Reference numeral 80 denotes a police station or a fire department that has jurisdiction over the lower municipalities 20, 30, 40,..., And the servers inside are connected to the router 13 of the upper municipal government 10 via the WAN 93. Here, a single police station / fire station 80 is shown, but a plurality may be provided depending on the number of lower-level local governments.
The road closure / district closure forecast created by the road closure state prediction monitoring server 12 of the upper level local government 10 is transmitted to the corresponding lower level local governments 20, 30, 40,... -Also transmitted to the fire department 80 (arrow y). This will enable the police and fire department to lead the police and fire departments to more thoroughly disseminate forecasts to residents in closed areas, guide evacuation of sick people and care recipients, and carry out work for transporting food and supplies and snow removal. it can.
[0022]
Next, the contents of the database 15 provided in the upper level local government 10 will be described.
FIG. 2 is a conceptual diagram showing the contents of the database 15, and each database will be described below.
[0023]
First, the snow depth instantaneous value database 15a stores current snow depth data collected from each weather observation point such as the weather observation system 50, the road monitoring system 60, and the system monitoring control system 70. The snow depth prediction value database 15b stores snow depth prediction value data after a specified time that is predicted and calculated by the road closure state prediction monitoring server 12.
These two databases 15a and 15b may be integrated as a snow depth database.
[0024]
The road node definition database 15d and the road branch definition database 15c are generated by the following road modeling function. The road connection state in the prediction target area is associated with the nodes and branches used in the analysis of the power system. It is converted and made into a database.
[0025]
Hereinafter, a method of defining a road node and a road branch by the road modeling function will be described with reference to FIG.
FIG. 3 is a map of the prediction target area. It is assumed that there are national roads X and Y, prefectural road Z, other roads, and towns A, B, C, and D. The connection state of the roads in this area is shown. Think about modeling.
Here, it is empirically assumed that the city C has a small amount of snow and has many roads, and it is easy to remove snow. Therefore, it is considered that road closure or district closure due to snowfall does not occur, and this city C is defined as a slug node. I do.
[0026]
Then, in the area shown in the upper part of FIG. 3, the towns A, B, and C are respectively road nodes A, B, and C (slug nodes), and the national roads X, Y, and the prefectural road Z are road branches X, respectively. ₁ , X ₂ , Y ₁ , Y ₂ , Z ₁ , Z ₂ Can be replaced by It is needless to say that other municipalities and roads included in the upper region of FIG. 3 may be replaced with further road nodes and road branches.
As a result, the area in the upper part of FIG. 3 is converted into a model composed of road nodes and road branches as shown in the lower part. For example, village D is a road branch Y between road nodes A and B. ₁ Road traffic is road branch Y ₁ It becomes recognizable that it depends only on this.
In addition, such a road branch Y of the village D ₁ Is stored in the route district database 15f in FIG.
[0027]
It is also assumed that virtual circuit breakers are installed at both ends of each road branch. The operation of these virtual circuit breakers will be described later, but in the example of FIG. ₁ Virtual circuit breaker VS at both ends of ₁ , VS ₂ Shall be installed.
Further, road branch Y ₁ , A snow depth sensor SP such as a snow gauge is installed at at least one place, and the place constitutes a weather observation point.
[0028]
The road node definition database 15d and the road branch definition database 15c are obtained by converting the actual connection relation of roads into road nodes and road branches as described above, and store the position information of the weather observation points with the road branch. They are stored in association with each other.
In addition, for each road branch, a snow depth allowable value (a snow depth allowable value that is a threshold value for issuing a road closing / district closing forecast) within a range that does not lead to road closure is also stored. It can be set in stages depending on whether a road closure / district closure forecast is issued as a warning or a more tense warning.
Further, in the road branch definition database 15c, it is also possible to set time information such as a calculation time interval of the snow depth prediction value and how many hours later the prediction is performed. These definition data can be an original database such as a road closure prediction calculation definition database.
[0029]
Returning to FIG. 2 again, the road branch status database 15e determines whether the road branch is closed or not closed (opened) by snow and the state of the virtual circuit breaker on this road branch (blocked or conductive). ) And stored as a road branch state.
That is, when the road branch is closed due to snow, the state of the virtual circuit breaker is set to “blocked”, and when not closed, the state is stored as “conductive” in the road branch state database 15e. In other words, the road branch is regarded as a transmission and distribution line in the power system, and the amount of snow at the weather observation point is regarded as, for example, electric power (power consumption). When the electric power exceeds the allowable value, the circuit breaker operates to change the transmission and distribution line. It is considered that the power supply to the meteorological observation point will be cut off by the cutoff, and the road is closed due to snow cover.
[0030]
In addition, the route district database 15f defines and stores districts that are isolated in connection with the closure of the road branch, such as the aforementioned village D. In the example of FIG. ₁ It is a database that contains the relationship between and Village D.
The weather observation point database 15g is provided when the position information of the weather observation points is not stored in the road branch state database 15e described above, but is held as an independent database. When the number of weather observation points is large or the number of observation points is expected to increase, it is useful to construct such an independent database 15g.
[0031]
The weather information database 15h stores the weather information of each weather observation point one by one. The actual value of the snow depth, the rainfall amount, the actual value such as the temperature, the current value, and the rainfall amount A predicted value such as temperature is stored.
As described above, since the instantaneous value and predicted value of the snow depth are stored in the instantaneous snow depth database 15a and the predicted snow depth database 15b, the weather information database 15h mainly stores weather information other than the snow depth. You. These weather information, such as temperature, can be used for prediction of snow depth as needed.
[0032]
The forecast history database 15i stores the history (including those currently being issued) of road closure and district closure forecasts, including the stage (advisory, warning), target road information, and target district information. It is. This forecast history is used to analyze road closures and district closures, to plan and correct future road plans, expansions, detours, and snow removal plans (including running snowplows and installing road heating equipment). Is done.
[0033]
The sick person / need-to-care person location database 15j stores addresses, addresses (hospitals or hospitalized destinations), names, telephone numbers, e-mail addresses, symptoms, and the like of sick and resident-needed persons living in the area while considering privacy. It is a database and is provided for promptly and reliably providing information to road closures and district closure forecasts, and for taking necessary measures such as evacuation guidance.
The forecast occurrence countermeasure database 15k is a database of preventive measures and related information to be taken by local residents and local governments when a road closure / district closure forecast is generated. In addition to information such as which area to send a visual report to, notification information to the police and fire departments 80 and other agencies (notification departments, etc.), evacuation guidance for the sick and others mentioned above, food and various supplies Stores priority measures for carrying in, snow removal and snow melting, and routes.
[0034]
The system status database 151 stores various data necessary for constantly monitoring and managing the status of the entire road closure status prediction / notification system.
[0035]
Next, the overall function of the present embodiment will be described with reference to the conceptual diagram of FIG.
In FIG. 4, a road modeling function SA is a function of modeling an actual road connection state by a road node and a road branch for each region in a predetermined range, and creating a road node definition database 15d and a road branch definition database 15c. In addition, by this function, the route district database 15f is also substantially created.
[0036]
The snow depth simulator function SB predicts the snow depth at a weather observation point after a specified time, determines whether or not the predicted value exceeds a snow depth allowable value, and if it does, responds to the weather observation point. This is a function of interrupting the virtual circuit breaker on the road branch to be performed and notifying the state change thereof to the following road system search function SC.
[0037]
The road system search function SC sequentially searches the connection state of the road branch based on the road node definition database 15d and the road branch definition database 15c, and determines the state of the road branch (virtual circuit breaker) based on the road branch state database 15f. Is a function of detecting a change in the road branch, and detecting a district related to the road branch from the route district database 15f, that is, a function of detecting a predicted closed road section and a closed district.
[0038]
The road closure / district closure prediction notification function SD performs various countermeasures stored in the above-mentioned forecast occurrence countermeasure database 15k, such as a notification to a future closed road and a closed district detected by the road system search function SC. Function.
[0039]
Next, among the above functions, the specific contents of the main snow depth simulator function SB, the road system search function SC, and the road closure / area closure prediction notification function SD will be described in detail with reference to FIGS. These functions are mainly executed by the road closure state prediction monitoring server 12 of the upper level local government 10.
[0040]
First, FIG. 5 is a flowchart of the snow depth simulator function SB. This process is started, for example, every five minutes.
First, the current snow depth is collected and input from weather observation points such as the weather monitoring system 50 and the road monitoring system 60, and stored in the snow depth instantaneous value database 15a (step S1).
Next, for each weather observation point, 10 pieces of past snow depth data every 5 minutes in the database 15a are read (S2).
[0041]
Next, an average approximation linear expression is calculated from the ten snow depth data (S3), and the snow depth at a weather observation point after a designated time is predicted and calculated from the linear expression (S4). Note that a neural network or the like can be used for the prediction calculation.
The specified time is set by the road branch definition database 15c as described above, and can be set arbitrarily, for example, up to six hours later.
The calculated snow depth prediction value is stored in the snow depth prediction value database 15b for each weather observation point (S5).
[0042]
Next, a corresponding weather observation point is searched for each road branch stored in the road branch definition database 15c (S6). Here, the weather observation point is stored in the road branch definition database 15c in association with the road branch, or stored in the weather observation point database 15g provided independently.
Then, it is determined whether or not the predicted snow depth at the weather observation point of interest exceeds an allowable value (S7). The allowable value can be set arbitrarily and stepwise by the road branch definition database 15c as described above.
[0043]
If the result of the determination does not exceed the permissible value, the process ends as there is no risk of road closure after the designated time (S8 NO).
If the permissible value is exceeded, the virtual circuit breaker of the road branch where the weather observation point is located is closed for each weather observation point, and this state is stored in the road branch state database 15e (S8 YES, S9). Therefore, the road is closed after the designated time.
Then, the roadway system search function SC is activated by attaching the weather observation point exceeding the allowable value and the primary key of the road branch (S10). This notifies the road system search function SC that the state of the virtual circuit breaker, in other words, the road branch state has changed.
[0044]
FIG. 6 is a flowchart of the road system search function SC. Starting from the slug node C (C city area) in FIG. 3, the road connection state is sequentially searched using the road branch definition database 15c, the road node definition database 15d, and the road branch state database 15e (S11). To this search method, system search logic used in power flow calculation of the power system can be applied.
As a result of the search, it is determined whether or not the road branch state (the state of the virtual circuit breaker) has changed based on the state at the time of the previous calculation (S12).
If the route has not changed (NO in S12), the process ends assuming that there is no danger of road closure, and another route is searched for.
[0045]
As a result of searching for another route, if the road branch state (the state of the virtual circuit breaker) has changed based on the state at the time of the previous calculation (S12 YES), the state of the virtual circuit breaker changes to the road closed state. It is determined that there has been a change, and the road branch state in the road branch state database 15e is updated to a new search result state ("closed" or "open") (S13).
[0046]
Next, the road branch whose state has changed, that is, the road branch whose road closure is predicted, is specified with reference to the road branch definition database 15c, and the district associated with this road branch is closed with the road closure. The area is searched from the route area database 15f (S14).
Then, the area information is notified to the road closure / area closure prediction notification function (S15).
[0047]
FIG. 7 is a flowchart of the road closure / district closure prediction notification function SD.
Upon receiving notification of the district information from the road system search function SC, the closed road and the closed district are reported to the lower municipalities where these roads and districts are located and the police stations and fire departments in charge as road closure and district closure forecasts. (S21). The notification destination at that time is stored in advance in the forecast occurrence countermeasure database 15k.
At the same time, the history of the road closure / district closure forecast is stored in the forecast history database 15i.
[0048]
Next, the lower municipalities and NPOs pre-store information in the forecast database 15k, such as reporting to residents living in closed areas, guiding evacuation of sick and care recipients, bringing in food and supplies, and prioritizing snow removal and snow melting. Perform the various measures that have been taken. Here, the location of the sick person or the like is stored in the sick person / need-care person location database 15j.
In addition to the notification to the local residents, the lower-level local government 20 or the like in FIG. 1 notifies the notification via the notification device 29, transmits the notification to a related person's personal computer or mobile phone as an e-mail using a mail server, or transmits the information to the WWW server. Web distribution may be used.
[0049]
FIG. 8 is a diagram showing a specific example of a search and detection process for a closed road / closed area according to this embodiment.
In (a), the predicted snow depth after the designated time is equal to or less than the allowable value, and the road branch Y ₁ Virtual circuit breaker VS ₁ , VS ₂ Is in a conductive state (the circuit breaker VS ₁ , VS ₂ Is indicated by a broken line).
In (b), since the snow depth prediction value exceeds the allowable value, the virtual circuit breaker VS is operated by the snow depth simulator function SB. ₁ , VS ₂ Works, road branch Y ₁ Are cut off from the road nodes A and B. In this state, the road system search function SC is activated.
In (c), a plurality of road systems are searched along the arrow starting from the slug node C, and as a result, the road branch Y ₁ Is detected.
In (d), the road branch definition database 15c and the road node definition database 15d use the road branch Y. ₁ Is detected as the national road Y between the towns A and B.
In (e), the road branch database 15f indicates that the road branch Y is a closed road. ₁ Village D will be detected as a closed area related to.
[0050]
In the above-described embodiment, the road closure and the district closure due to snow cover have been described. However, the present invention can be applied to the road closure and the district closure due to rainfall in a similar manner.
[0051]
【The invention's effect】
As described above, according to the present invention, road closures due to snow and rain can be predicted in advance and district closures can be reported to local residents, municipalities, police, and the like. It is possible to provide a sufficient time allowance for protection and care for a person requiring care, snow removal work, and the like. In particular, if snow removal and melting operations are performed quickly and effectively, road closures and district closures can be avoided. This will reduce the economic and time loss caused by countermeasures falling behind, secure the health and safety of the sick and needy, and increase the efficiency of administration and the safety of residents, thereby improving the reliability of local governments. We can expect to do it.
Further, according to the present invention, even if there is no actual snowfall or rainfall, a road closure / district closure forecast can be issued simply by giving the snow depth data and the rainfall amount data to the road closure state prediction monitoring server in a simulated manner. It can also be used as a disaster training system in local governments.
[Brief description of the drawings]
FIG. 1 is a system configuration diagram of the present embodiment.
FIG. 2 is an explanatory diagram of a database in FIG. 1;
FIG. 3 is an explanatory diagram of a road modeling function.
FIG. 4 is a conceptual diagram showing overall functions of the embodiment.
FIG. 5 is a flowchart of a snow depth simulator function according to the embodiment.
FIG. 6 is a flowchart of a road system search function according to the embodiment.
FIG. 7 is a flowchart of a road closure / area closure prediction notification function according to the embodiment.
FIG. 8 is a diagram showing a specific example of a search and detection process for a closed road / closed area according to the present embodiment.
[Explanation of symbols]
10: Top local governments
11: LAN
12: Road closed state prediction monitoring server
13: Router
14: Database server
15: Database
15a: Snow depth instantaneous value database
15b: Snow depth prediction value database
15c: Road branch definition database
15d: Road node definition database
15e: Road branch state database
15f: Route district database
15g: Meteorological observation point database
15h: Weather information database
15i: Forecast history database
15j: Database for the location of sick and care recipients
15k: Forecast countermeasures database
151: System state database
16, 17: Terminal
20, 30, 40: Lower-level local governments
21: LAN
22: Server
23: Router
26, 27: Terminal
28: Control device
29: Notification device
50: Meteorological observation system
51: Unmanned weather observation device
60: Road monitoring system
70: System monitoring and control system
80: Police station, fire station
91-94: WAN
95: Dedicated line
VS ₁ , VS ₂ ： Virtual circuit breaker
SP: Snow depth sensor

Claims (6)

In the system that predicts that the road will be closed within the designated time due to snow or rainfall,
Road modeling means for modeling the connection state of roads in a predetermined area to be predicted by nodes and branches,
Predicted calculation of snow depth or rainfall within a specified time at observation points arranged on the branch, and when it is determined that the predicted value exceeds the allowable value, virtual blocking means arranged at both ends of the branch Simulator means for operating
Road system search means for sequentially searching for a route passing through a node and a branch in a predetermined area to detect a branch in which the blocking means is in operation;
Road closure prediction reporting means for detecting a road section corresponding to the branch in which the blocking means is in operation as a closed road, and reporting a road closure forecast to an area having the closed road;
A road closure state prediction / notification system comprising: The road closure state prediction / notification system according to claim 1,
Means for detecting an area in which road traffic is dependent only on the closed road as a closed area, and for notifying the area having the closed area or a competent administrative agency of a district closing forecast;
A road closure state prediction / notification system comprising: The road closure state prediction / notification system according to claim 1,
Nodes and branches of the road modeled by the road modeling means are stored as information in a database,
The road closure state prediction, wherein the database, the simulator means, the road system search means, and the road closure prediction notification means are realized by a server provided in a higher-level local government or a contracted private company. -Notification system. The road closure state prediction / notification system according to claim 2,
Nodes and branches of the road modeled by the road modeling means are stored as information in a database,
The road closure state prediction, wherein the database, the simulator means, the road system search means, and the district closure prediction notification means are realized by a server provided in a higher-level local government or a contracted private company. -Notification system. The road closure state prediction / notification system according to claim 3 or 4,
Road closure characterized in that the database stores measures to be performed by the lower municipalities or other organizations when a road closure forecast or a district closure forecast is issued to the lower municipalities or other organizations. State prediction and notification system. The road closure state prediction / notification system according to claim 5,
A road closure state prediction / notification system, wherein the database stores location information of a sick person or a person requiring care in a district where a road closure forecast or a district closure forecast is reported.

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