JP2018092467A - Disaster occurrence probability calculating system and method, operation control apparatus, program, and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a disaster occurrence probability calculating system capable of accurately calculating a probability of occurrence of a disaster to assist decision making of a road administrator or the like.SOLUTION: The disaster occurrence probability calculating system includes: an acquiring unit for acquiring a quantity of state related to traffic and hazard map information; an influence degree calculating unit for calculating a degree of influence of the quantity of state related to traffic and a degree of influence of the hazard map information on occurrence of a disaster, based on the quantity of state related to traffic and the hazard map information upon occurrence of the disaster; and a disaster occurrence probability calculating unit for calculating a probability of occurrence of a disaster based on the degree of influence of the quantity of state related to traffic and the degree of influence of the hazard map information, and the current quantity of state related to traffic and current hazard map information.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a disaster probability calculation system, a disaster probability calculation method, an operation control device, a program, and a recording medium.

  For example, on an expressway, a road administrator performs traffic control operations such as traffic volume control based on traffic information such as traffic jams, traffic regulations, and traffic accidents. Patent Document 1 describes a road traffic control support system using a simulator as a system for supporting decision making of lane operation by a road administrator.

  In road traffic control, the probability of occurrence of natural disasters or traffic accidents due to the current state of roads, etc. is calculated, and the calculation results are presented to road managers, etc. There is a demand for a system that can implement advance deployment of a car or a supervisor, alerting a traveling vehicle using an information board installed on a road, and the like. Patent Document 2 describes a forecasting device that learns a traffic accident pattern that occurred in the past and predicts the current tendency of traffic accidents.

JP 2008-059390 A JP 2014-035639 A

  The forecasting device described in Patent Document 2 predicts the occurrence of a traffic accident based on the correlation between any of the traffic accident patterns that occurred in the past and the situation at the time of the forecast calculation. However, forecasts based on correlation with any past traffic accident pattern, that is, forecasts based on correlation with a certain traffic accident pattern, have room for improvement in the accuracy of the forecast. May hinder decisions.

  Aspects of the present invention include a disaster probability calculation system, a disaster probability calculation method, an operation control device, a program, which can accurately calculate the probability of a disaster and support decision making by a road administrator, etc. And it aims at providing a recording medium.

  According to the first aspect of the present invention, based on the acquisition unit that acquires the state quantity and hazard map information relating to traffic, and the state quantity and hazard map information relating to the traffic when a disaster occurs, , An influence degree calculation unit for calculating an influence degree of the state quantity relating to the traffic and an influence degree of the hazard map information, an influence degree of the state quantity relating to the traffic and an influence degree of the hazard map information, and the current state relating to the traffic There is provided a disaster probability calculation system including a disaster probability calculation unit that calculates a disaster probability based on the amount and the hazard map information.

  According to the first aspect of the present invention, the state quantity and hazard map information relating to traffic when a disaster has occurred in the past are acquired, so that the state quantity and hazard map information relating to traffic at the time of the past disaster occurrence are The degree of influence that contributes to the occurrence of is calculated. Then, by acquiring the state quantity and hazard map information related to the current traffic, the possibility of disaster occurrence is calculated based on the state quantity and hazard map information related to the current traffic and the calculated degree of influence. . Therefore, the road manager or the like can make a decision for preventing the occurrence of damage or suppressing the damage to the minimum based on the calculated possibility of disaster occurrence.

  In the first aspect of the present invention, the acquisition unit acquires a state quantity related to weather, and the influence degree calculation part calculates an influence degree of the state quantity related to the weather with respect to the occurrence of the disaster, and the disaster occurrence is possible The sex calculation unit may calculate the probability of occurrence of the disaster based on the influence degree of the state quantity related to the weather and the current state quantity related to the weather.

  By acquiring the state quantity related to the weather, the influence degree is calculated in consideration of not only the state quantity related to the traffic but also the state quantity related to the weather. This improves the accuracy of the calculated possibility of disaster occurrence.

  In the first aspect of the present invention, the acquisition unit acquires a state quantity related to terrain, and the influence calculation unit calculates an influence degree of the state quantity related to the terrain with respect to occurrence of a disaster, and the disaster can be generated. The sex calculation unit may calculate the probability of occurrence of the disaster based on the influence degree of the state quantity related to the terrain and the current state quantity related to the terrain.

  By acquiring the state quantity related to the terrain, the influence degree is calculated in consideration of not only the state quantity related to the traffic but also the state quantity related to the terrain. This improves the accuracy of the calculated possibility of disaster occurrence.

  In the first aspect of the present invention, the acquisition unit may acquire maintenance information, and the disaster possibility calculation unit may correct the disaster possibility based on the maintenance information.

  For example, when maintenance such as road construction is performed on a traffic facility, the possibility of a disaster may fluctuate. Maintenance information is acquired, and the calculated possibility of disaster is corrected based on the maintenance information, so that the accuracy of the possibility of disaster is improved.

  In the first aspect of the present invention, when a new disaster occurs and the state quantity when the disaster occurs is updated, the influence degree calculation unit may newly calculate the influence degree.

  When a new disaster occurs, the state quantity acquired by the acquisition unit when a disaster has occurred in the past is updated. By calculating the degree of influence each time the state quantity is updated, the accuracy of the probability of occurrence of a disaster is improved.

  In the first aspect of the present invention, the disaster probability calculation unit sets a weight for each of the state quantity and the hazard map information based on the degree of influence calculated by the degree of influence calculation unit, The disaster occurrence probability is calculated by adding the weighted state quantity calculated by multiplying the current state quantity by the weight and the weighted hazard map information calculated by multiplying the hazard map information by the weight. May be.

  Based on the degree of impact on the disaster, the state quantity and hazard map information are weighted, and the possibility of disaster occurrence is calculated by calculating the possibility of disaster from the added value of the weighted weighted state quantity and the weighted hazard map information. Is calculated with high accuracy.

  In the first aspect of the present invention, the acquisition unit may acquire information related to a disaster type, and the influence degree calculation unit may calculate the influence degree for each disaster type.

  For example, information on disaster types such as traffic accidents, landslides, and inundation is acquired, and the degree of impact is calculated for each disaster type. Sex can be calculated. Therefore, road managers etc. make appropriate decisions to prevent damage from occurring or to minimize damage based on the possibility of disasters calculated for each type of disaster. be able to.

  In the first aspect of the present invention, the disaster probability calculation unit calculates the disaster probability for each disaster type based on the degree of influence calculated for each disaster type, You may provide the output control part which produces | generates the output data which can switch and display the possibility of disaster occurrence calculated for every disaster type for every said disaster type.

  The possibility of disaster occurrence is switched and displayed for each type of disaster, so road managers etc. can make decisions appropriately by looking at the possibility of disaster occurrence displayed on the output device for each type of disaster. it can.

  In the first aspect of the present invention, there may be provided an output control unit that generates output data for encouraging driving that avoids the occurrence of a disaster for a moving body that passes through the point where the probability of occurrence of the disaster is high.

  By generating output data that prompts driving that avoids the occurrence of a disaster, the driver of the mobile object can perform driving that avoids the occurrence of a disaster by looking at the output data. For example, the driver can reduce the traveling speed of the moving body, increase the distance from the preceding moving body, or select a route that bypasses a point where the possibility of disaster occurrence is high. This prevents damage from occurring.

  The 1st aspect of this invention WHEREIN: You may provide the driving control command production | generation part which produces | generates the driving control command which avoids generation | occurrence | production of a disaster with respect to the mobile body which passes the point with the said high possibility of a disaster occurrence.

  By generating an operation control command that avoids the occurrence of a disaster, a mobile body equipped with an automatic operation system or an operation assist system may perform an operation that avoids the occurrence of a disaster based on the operation control command. it can. For example, the moving body can reduce the traveling speed of the moving body, increase the distance from the preceding moving body, or select a route that bypasses a point where a disaster is likely to occur. This prevents damage from occurring.

  1st aspect of this invention WHEREIN: The said acquisition part acquires the SNS information regarding the posting sentence on a social networking service, The SNS information analysis part which acquires positional information and disaster information from the said SNS information, The said positional information An output control unit that outputs output data for displaying the disaster information to an output device at a position on a map indicated by

  For example, when a user of a social networking service is near a disaster site and SNS information including disaster information is transmitted from a mobile terminal possessed by the user, the location information of the disaster site is obtained by acquiring the SNS information. Disaster information is quickly acquired. By displaying the disaster information at a position on the map indicated by the position information, the road manager or the like can appropriately make a decision by looking at the display.

  1st aspect of this invention WHEREIN: The said acquisition part acquires the image information attached to the said contribution text, The said SNS information analysis part analyzes the said image information, and the image of the said image information is a disaster scene. When it is determined whether the image is an image of the disaster site, the output control unit outputs the image as disaster information to a position on the map indicated by the position information. Also good.

  When a user of a social networking service near the disaster site acquires an image of the disaster site using the camera function of the mobile terminal, and the SNS information including the image is transmitted from the mobile terminal, the SNS information is acquired. As a result, the situation at the disaster site can be quickly grasped. By displaying the image as disaster information at a position on the map, a road administrator or the like can appropriately make a decision by viewing the display.

  According to the second aspect of the present invention, the disaster can occur when the vehicle is mounted on a mobile body and passes through the point having a high possibility of disaster occurrence calculated by the disaster possibility calculation system of the first aspect. An operation control device that performs operation control to avoid the occurrence of a disaster in accordance with an operation control command output from the performance calculation system is provided.

  According to the second aspect of the present invention, the mobile body equipped with the automatic driving system or the driving assistance system is operated so as to avoid the occurrence of a disaster based on the driving control command output from the disaster possibility calculation system. Can be implemented. For example, the moving body can reduce the traveling speed of the moving body, increase the distance from the preceding moving body, or select a route that bypasses a point where a disaster is likely to occur.

  According to the third aspect of the present invention, the state quantity and hazard map information related to traffic is acquired, and the occurrence of a disaster is based on the state quantity and the hazard map information related to the traffic when a disaster occurs. Calculating the degree of influence of the state quantity relating to the traffic and the degree of influence of the hazard map information; the degree of influence of the state quantity relating to the traffic and the degree of influence of the hazard map information; the state quantity relating to the current traffic and the hazard A disaster probability calculation method including calculating a disaster probability based on map information is provided.

  According to the fourth aspect of the present invention, the computer is configured to acquire a disaster based on the acquisition unit for acquiring the traffic state quantity and hazard map information, and the traffic state quantity and the hazard map information when a disaster occurs. The degree of influence of the state quantity relating to the traffic and the degree of influence of the hazard map information, the degree of influence of the state quantity relating to the traffic and the degree of influence of the hazard map information, A program is provided for functioning as a disaster probability calculation unit that calculates the probability of a disaster based on a state quantity related to traffic and the hazard map information.

  According to the fifth aspect of the present invention, the computer uses the acquisition unit that acquires the state quantity and hazard map information related to traffic, and the state quantity and hazard map information related to the traffic when a disaster occurs, The degree of influence of the state quantity relating to the traffic and the degree of influence of the hazard map information, the degree of influence of the state quantity relating to the traffic and the degree of influence of the hazard map information, There is provided a recording medium on which a program for causing a function to function as a disaster occurrence possibility calculating unit that calculates the possibility of a disaster occurrence based on a state quantity related to traffic and the hazard map information is recorded.

  According to an aspect of the present invention, a disaster occurrence possibility calculation system, a disaster occurrence possibility calculation method, an operation control device, which can calculate the possibility of a disaster with high accuracy and support decision making by a road administrator or the like, A program and a recording medium are provided.

FIG. 1 is a hardware configuration diagram illustrating an example of a disaster probability calculation system according to the first embodiment. FIG. 2 is a functional block diagram illustrating an example of a disaster probability calculation system according to the first embodiment. Drawing 3 is a mimetic diagram of the state quantity about the weather memorized by the weather information storage part concerning a 1st embodiment. FIG. 4 is a flowchart illustrating an example of a disaster probability calculation method according to the first embodiment. FIG. 5 is a diagram illustrating an example of the influence degree calculated by the influence degree calculation unit according to the first embodiment. FIG. 6 is a diagram illustrating an example of a display screen showing an output result of the disaster probability calculation system according to the first embodiment. FIG. 7 is a diagram illustrating an example of a display screen showing an output result of the disaster probability calculation system according to the first embodiment. FIG. 8 is a modification of the functional block diagram illustrating an example of the disaster probability calculation system according to the first embodiment. FIG. 9 is a flowchart illustrating an example of a disaster probability calculation method according to the second embodiment. FIG. 10 is a functional block diagram illustrating an example of a disaster probability calculation system according to the third embodiment. FIG. 11 is a modification of the functional block diagram of the disaster probability calculation system according to the fourth embodiment. FIG. 12 is a flowchart illustrating an example of a disaster probability calculation method according to the fourth embodiment. FIG. 13 is a hardware configuration diagram illustrating an example of a disaster occurrence prediction system according to the fifth embodiment. FIG. 14 is a functional block diagram illustrating an example of a disaster occurrence prediction system according to the fifth embodiment. FIG. 15 is a flowchart illustrating a method for controlling the operation of a moving object by the disaster probability calculation system according to the fifth embodiment. FIG. 16 is a diagram illustrating an example of a display screen showing an output result of the disaster probability calculation system according to the fifth embodiment. FIG. 17 is a functional block diagram illustrating an example of a disaster probability calculation system according to the sixth embodiment. FIG. 18 is a flowchart illustrating an example of a disaster occurrence possibility calculation method including SNS information analysis according to the sixth embodiment. FIG. 19 is a diagram illustrating an example of a display screen showing an output result of the disaster probability calculation system according to the sixth embodiment. FIG. 20 is a flowchart showing a modification of the disaster occurrence possibility calculation method including SNS information analysis according to the sixth embodiment. FIG. 21 is a diagram illustrating an example of a display screen showing an output result of the disaster probability calculation system according to the seventh embodiment.

  Hereinafter, a disaster probability calculation system according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. In addition, this invention is not limited by this embodiment, and when there are two or more embodiments, what comprises combining each embodiment is also included.

<First Embodiment>
A first embodiment will be described. FIG. 1 is a hardware configuration diagram illustrating an example of a disaster probability calculation system 100 according to the present embodiment. The disaster possibility calculation system 100 is disposed, for example, in a traffic control center on an expressway or a general road.

  In this embodiment, disasters are natural disasters such as earthquakes or tsunamis, human disasters such as traffic accidents or aircraft falls, and equipment disasters caused by inadequate or aging facilities such as the collapse of tunnels and bridges. Means at least one. Disasters also include secondary disasters such as earthquake fires, landslides, faults, liquefaction, and building collapse. The possibility of a disaster means the possibility of a disaster such as a natural disaster or a traffic accident.

  As shown in FIG. 1, the disaster possibility calculation system 100 includes an information processing apparatus 1 and a sensor 2 that detects a state quantity and outputs detection information including the state quantity to the information processing apparatus 1. The disaster possibility calculation system 100 includes an input device 3 and an output device 4 connected to the information processing device 1. The disaster possibility calculation system 100 may include a communication device, and information communication may be performed with an external device via the communication device.

  The sensor 2 detects and collects traffic information including state quantities relating to traffic and weather information including state quantities relating to weather. In the present embodiment, the sensor 2 includes a traffic information sensor that detects and collects traffic information on the road and its surroundings, and a weather information sensor that detects and collects weather information on the road and its surroundings. The sensor 2 is installed on a road, for example.

  State quantities related to traffic include traffic volume on the road, traffic regulation (lane regulation or speed regulation, etc.), road surface temperature, traffic jam information (vehicle density or traveling speed, etc.), and time information (commuting hours, daytime, nighttime, weekdays) , Holidays, etc.). The state quantity related to the weather includes at least one of rainfall, snowfall, snow cover, fog, tornado, wind force, wind direction, temperature, humidity, and brightness (daytime brightness, nighttime brightness, etc.).

  The sensor 2 outputs to the information processing apparatus 1 traffic information including the collected state quantities relating to traffic and weather information including the state quantities relating to the weather. A weather radar system may be used as the sensor 2 that collects weather information.

  The information processing apparatus 1 acquires and manages a plurality of information such as traffic information and weather information collected by the sensor 2. Further, the information processing apparatus 1 performs information processing based on information that is acquired or managed. The information processing apparatus 1 includes a central processing unit (CPU) 5, a read only memory (ROM) 6, a random access memory (RAM) 7, and a drive device 8. A ROM 6 that is a non-volatile memory stores a program that is executed in the information processing of the information processing apparatus 1. The program is loaded from the ROM 6 onto the working memory of the RAM 7 and is read and executed by the CPU 5.

  Note that a program executed in information processing may be transmitted from the server to the information processing apparatus 1 and installed.

  Note that a program executed in information processing may be recorded in the recording medium 9 </ b> A and installed in the information processing apparatus 1 via the drive device 8. The recording medium 9A may be a recording medium for recording information optically, electrically, or magnetically such as a CD-ROM, a flexible disk, or a magneto-optical disk, or may be electrically such as a ROM or a flash memory. It may be a semiconductor memory that records information in the memory.

  The output device 4 includes a flat panel display such as a liquid crystal display (LCD) or an organic electroluminescence display (OLED), and displays display data generated by the information processing device 1. In the present embodiment, the output device 4 is a large display that can be seen by, for example, a plurality of personnel in a traffic control center. The output device 4 includes a display board installed on the road, a monitor installed in the service area, a portable terminal such as a smartphone possessed by a worker, a monitor installed in each vehicle traveling on the road, etc. including. Further, the output device 4 may switch and display a plurality of display data displayed on the display screen of the output device 4 based on the input information from the input device 3. The output device 4 may output video data, character data, or the like, or may include a speaker that outputs audio data.

  The input device 3 is operated by a road administrator or the like and generates input information when operated. Input information generated by the input device 3 is output to the information processing device 1. The input device 3 includes, for example, a personal computer or a portable device. Note that the input device 3 may include a touch sensor provided on the display screen of the output device 4. That is, the output device 4 may include a touch panel integrated with the input device 3. Further, the display data displayed on the output device 4 may be selectively switched by the operator operating the input device 3.

  Further, the information processing apparatus 1 may be connected to the external database 9B. The external database 9B can store not only the above-mentioned program but also traffic information and weather information.

  Next, the information processing apparatus 1 according to the present embodiment will be described. FIG. 2 is a functional block diagram illustrating an example of the information processing apparatus 1 according to the present embodiment. As illustrated in FIG. 2, the information processing apparatus 1 includes an information storage unit 10, an information analysis unit 20, and an output control unit 30.

  The information storage unit 10 includes a traffic information storage unit 11, a weather information storage unit 12, a hazard map information storage unit 13, and a disaster information storage unit 14. The function of the information storage unit 10 is realized by, for example, the ROM 7 or the external database 9B. The information storage unit 10 includes a storage area provided in a memory, for example.

  The traffic information storage unit 11 is connected to a sensor 2 that detects traffic information installed on a road or the like via a communication network such as the Internet. The traffic information storage unit 11 acquires and stores traffic information acquired in real time by the sensor 2 from the sensor 2. The traffic information storage unit 11 acquires and stores traffic information input by the road manager or the like via the input device 3.

  The sensor 2 includes a sensor capable of detecting traffic such as a vehicle sensor and a sensor capable of detecting road temperature. The traffic information detected by the sensor 2 includes traffic volume and road surface temperature. The traffic information input by the road manager or the like via the input device 3 includes control information. The control information includes regulation information, traffic jam information, and accident information.

  The traffic information storage unit 11 stores traffic information and identification information indicating a point where the traffic information is acquired in association with each other. The point where the traffic information is acquired is, for example, at least one of the point where the traffic volume is acquired, the point where the road surface temperature is acquired, the point where the regulation occurs, the point where the traffic jam occurs, and the point where the accident occurs. Including. The point identification information is information that can identify the point, and includes absolute position information such as the latitude and longitude of the point.

  Thus, in this embodiment, the traffic information storage unit 11 stores the state quantity related to the current traffic, which is real-time data, and the identification information of the point about the state quantity related to the traffic in association with each other. Further, the traffic information storage unit 11 stores the state quantity related to the current traffic, which is real-time data, and the time information indicating the time when the state quantity related to the traffic is acquired.

  The weather information storage unit 12 is connected to the sensor 2 that detects weather information installed on a road or the like via a communication network such as the Internet. The weather information storage unit 12 acquires and stores weather information acquired by the sensor 2 in real time from the sensor 2. The weather information storage unit 12 acquires and stores traffic information input by the road manager or the like via the input device 3.

  The sensor 2 includes a sensor capable of detecting rainfall, such as a rain gauge, a sensor capable of detecting snow, a sensor capable of detecting temperature, and the like. The weather information detected by the sensor 2 includes at least one of rainfall, snowfall, snow cover, fog, wind force, wind direction, temperature, and humidity. The weather information input by the road manager or the like via the input device 3 includes weather information of a specific area.

  The weather information storage unit 12 stores weather information and identification information indicating a point from which the weather information is acquired in association with each other. The point identification information is information that can identify the point, and includes absolute position information such as the latitude and longitude of the point.

  The meteorological information acquisition unit 12 may acquire a map related to meteorological information such as rainfall, which is created by an organization such as the Japan Meteorological Agency, from an external server, and may store a state quantity related to the weather for each point. That is, the weather information acquisition unit 12 may periodically acquire and store weather information distributed from the outside via a communication line.

  As described above, in the present embodiment, the weather information storage unit 12 stores the state quantity related to the current weather, which is real-time data, and the point identification information about the state quantity related to the weather in association with each other. Further, the weather information storage unit 12 stores the state quantity related to the current weather, which is real-time data, and time information indicating the time when the state quantity related to the weather is acquired.

  The hazard map information storage unit 13 acquires and stores hazard map information that is created by an institution such as the Ministry of Land, Infrastructure, Transport and Tourism, a local government, or a company and indicates the damage scale or the degree of risk for each region predicted for a specific disaster. To do. The hazard map information storage unit 13 stores information on the damage scale or risk of natural disasters such as tsunamis, floods, earth and sand disasters, earthquake disasters, and volcanic disasters in association with the identification information of each point. The hazard map may be any map that shows the damage scale and risk level for each area related to a specific disaster, and includes a disaster prevention map of the area.

  As described above, in the present embodiment, the hazard map information storage unit 13 stores the damage level information indicating at least one of the damage scale and the risk level and the identification information of the point about the damage level information in association with each other.

  The disaster information storage unit 14 stores past disaster information. The past disaster information is information regarding disasters that have occurred in the past. As described above, in this embodiment, disasters include natural disasters, traffic accidents, and secondary disasters. The disaster information storage unit 14 includes, as disaster information, the type of disaster, the time when the disaster occurred, the extent of the disaster, the state quantity related to traffic when the disaster occurred in the past, and the state related to the weather when the disaster occurred in the past The amount is stored in association with the identification information of the point where the disaster occurred.

  Thus, in the present embodiment, the disaster information storage unit 14 stores the state quantity related to traffic when a disaster has occurred in the past and the point identification information about the state quantity related to the traffic in association with each other. Further, the disaster information storage unit 14 stores the state quantity related to the weather when a disaster has occurred in the past and the point identification information about the state quantity related to the weather in association with each other.

  In the present embodiment, the traffic information storage unit 11 stores a state quantity related to traffic acquired by the sensor 2 as a standardized numerical value, for example, a numerical value from 1 to 5, for each point. Similarly, the weather information storage part 12 memorize | stores the state quantity regarding the weather acquired with the sensor 2 for every point as a standardized numerical value, for example, the numerical value of 5 steps | paragraphs from 1 to 5.

  FIG. 3 is a schematic diagram illustrating an example of a state quantity related to the weather stored in the weather information storage unit 12. FIG. 3 shows an example in which the rainfall amount acquired by the sensor 2 and the identification information of the point where the rainfall amount is acquired are associated and stored. An area is divided into a plurality of points in a matrix based on the point identification information. The meteorological information storage unit 12 stores the rainfall amounts at each of the plurality of points in association with the points based on the identification information of the points at which the rainfall amounts have been acquired. As shown in FIG. 3, rainfall is stored in the weather information storage unit 12 as standardized numerical values from 1 to 5. Larger numbers indicate more rainfall. FIG. 3 shows an example in which the rainfall amount and a plurality of points are linked and stored, but the weather information storage unit 12 has a plurality of state quantities related to other weather such as a snowfall amount or a wind speed and a plurality of points. The point is linked and stored.

  Similarly, the traffic information storage unit 11 stores a state quantity related to traffic such as the traffic volume or the traveling speed of the traveling vehicle and a plurality of points in association with each other.

  In addition, the traffic information storage part 11 may memorize | store the value of the state quantity acquired with the sensor 2 as it is for every point. Similarly, the weather information storage part 12 may memorize | store the value of the state quantity acquired with the sensor 2 as it is for every point.

  Next, the information analysis unit 20 and the output control unit 30 according to the present embodiment will be described. As illustrated in FIG. 2, the information analysis unit 20 includes an acquisition unit 21 that extracts and acquires information stored in the information storage unit 10, and an influence calculation unit 22 that calculates the degree of influence of the acquired information on a disaster. A disaster probability calculation unit 23 that calculates the probability of disaster based on the calculated degree of influence and current information. The function of the information analysis unit 20 is realized by the CPU 5, the RAM 6, the ROM 7, and the like.

  The acquisition unit 21 acquires a state quantity related to the current traffic, a state quantity related to the current weather, hazard map information, and past disaster information from the information storage unit 10. The acquisition unit 21 outputs the acquired information to the influence degree calculation unit 22.

  The degree-of-influence calculation unit 22 acquires a state quantity related to the current traffic, a state quantity related to the current weather, hazard map information, and past disaster information from the acquisition unit 21. The influence degree calculation unit 22 calculates the influence degree with respect to the disaster based on the acquired information, and outputs it to the disaster occurrence possibility calculation unit 23.

  In the present embodiment, the influence degree calculation unit 22 calculates the influence degree of the state quantity related to traffic and the influence degree of the hazard map information on the occurrence of the disaster based on the state quantity related to the traffic and the hazard map information when the disaster occurs. calculate. Moreover, the influence degree calculation part 22 calculates the influence degree of the state quantity regarding the weather with respect to the occurrence of the disaster based on the state quantity related to the weather and the hazard map information when the disaster occurs.

  The disaster occurrence possibility calculation unit 23 is based on the degree of influence on the disaster calculated for each state quantity and hazard map information output from the influence degree calculation unit 22 and the current state quantity relating to traffic and weather. Calculate the probability of disaster occurrence. Further, the disaster possibility calculation unit 23 outputs the calculated disaster possibility to the output control unit 30.

  In the present embodiment, the disaster probability calculation unit 23 relates to the state quantity impact level and the hazard map information impact level calculated by the impact level calculation unit 22 and the current traffic level acquired by the acquisition unit 21. Based on the state quantity and the hazard map information, the possibility of disaster occurrence is calculated. In addition, the disaster possibility calculation unit 23 is configured to calculate the influence amount of the state quantity related to the weather and the influence degree of the hazard map information calculated by the influence degree calculation unit 22, the state quantity related to the current weather acquired by the acquisition unit 21, and Based on the hazard map information, the possibility of disaster occurrence is calculated.

  The output control unit 30 processes the information on the possibility of disaster occurrence input from the disaster possibility calculation unit 23 and generates data that can be output by the output device 4. The output control unit 30 is connected to the information analysis unit 20. The function of the output control unit 30 is realized by the CPU 5, the RAM 6, the ROM 7, and the like.

  The data generated by the output control unit 30 is transmitted to the output device 4. For example, the output control unit 30 generates display data displayed on the display screen of the output device 4, audio data output from a speaker, and the like, and transmits the generated data to the output device 4. The output device 4 operates based on output data (display data or audio data) transmitted from the output control unit 30.

  Next, a disaster probability calculation method in the disaster probability calculation system 100 according to the present embodiment will be described. FIG. 4 is a flowchart illustrating an example of a disaster probability calculation method according to the present embodiment.

  The acquisition unit 21 acquires past disaster information from the disaster information storage unit 14 (step S110). In the present embodiment, the acquisition unit 21 obtains, as past disaster information from the disaster information storage unit 14, a state quantity related to traffic when a disaster has occurred in the past, a state quantity related to weather, a type of disaster that occurred, and a degree of disaster And identification information of the point where the disaster occurred. When the disaster is a traffic accident, the extent of the disaster means the number of accidents, the number of casualties, the recovery time, the road surface destruction level, and the like.

  Moreover, the acquisition part 21 acquires hazard map information from the hazard map information storage part 13 (step S120). In the present embodiment, the acquisition unit 21 acquires hazard map information for each disaster type. The hazard map information includes a numerical value or a color indicating the damage scale or risk of occurrence of a disaster. For example, in the hazard map, when the possibility of flooding is indicated in five levels, the acquisition unit 21 acquires a numerical value of five levels from 1 to 5 for each point as hazard map information.

  Further, the acquisition unit 21 acquires a state quantity related to the current traffic from the traffic information storage unit 11. Moreover, the acquisition part 21 acquires the state quantity regarding the present weather from the weather information storage part 12 (step S130). The acquisition unit 21 transmits the acquired state quantity, hazard map information, and the like to the influence degree calculation unit 22.

  Based on the state quantity related to the traffic when the disaster occurred in the past, the state quantity related to the weather when the disaster occurred in the past, and the hazard map information transmitted from the acquisition unit 21, the influence degree calculation unit 22 The degree of influence of the state quantity relating to traffic, the degree of influence of the state quantity relating to the weather, and the degree of influence of the hazard map information are calculated.

  In the present embodiment, the impact calculation unit 22 obtains a comprehensive evaluation value related to the degree of disaster based on one or more information obtained by the obtaining unit 21 and indicating the degree of disaster when a disaster has occurred in the past. Calculate (step S140). A comprehensive evaluation value regarding the degree of disaster is calculated for each disaster case. For example, when the number of accidents and the number of casualties are acquired as information indicating the degree of disaster, the impact calculation unit 22 standardizes information on the number of accidents and evaluates it in five stages from 1 to 5 (the larger the numerical value, The number of accidents is large), information on the number of casualties is standardized and evaluated on a scale of 1 to 5 (the larger the number, the greater the number of casualties), and the average value of these standardized values is calculated for comprehensive evaluation Value. The comprehensive evaluation value may be the maximum standardized value.

  The impact calculation unit 22 includes a comprehensive evaluation value relating to the calculated degree of disaster, a state quantity relating to traffic when the disaster occurs, a state quantity relating to the weather when the disaster occurs, and hazard map information of the disaster occurrence point Based on the above, multivariate analysis such as multiple regression analysis or principal component analysis is performed, and the degree of influence of the state quantity related to traffic, the state quantity related to the weather, and the hazard map information on the comprehensive evaluation value is calculated (step S150).

  The influence degree is a concept including at least one of a contribution rate, a contribution degree, and a correlation value. The degree of influence is calculated as a larger value as the contribution to the comprehensive evaluation value is higher or the correlation with the occurrence of a disaster is higher.

  In other words, in the present embodiment, the influence degree calculation unit 22 calculates the influence degree that the state quantity related to traffic, the state quantity related to the weather, and the hazard map information affect the degree of the disaster based on the past disaster information. The degree of influence is calculated for each element of the state quantity related to the traffic volume, the state quantity related to the weather, and the hazard map information.

  Moreover, in this embodiment, the influence degree calculation part 22 calculates an influence degree for every kind of disaster. The hazard map information is used with reference to the hazard map corresponding to the calculated disaster type.

  FIG. 5 is a diagram illustrating an example of the influence degree calculated by the influence degree calculation unit 22 according to the present embodiment. FIG. 5 shows an example in which the degree of influence is calculated for each type of disaster, such as traffic accidents, landslides, and inundation.

  An example of calculating the degree of influence on a traffic accident will be described. The degree-of-influence calculation unit 22 obtains state quantities relating to traffic when a traffic accident has occurred in the past, state quantities relating to weather when a traffic accident has occurred in the past, and hazard map information at the point of occurrence of the traffic accident as individual traffic Acquired for each accident case (accident A, accident B, accident C). In the example illustrated in FIG. 5, for each of the accident A, the accident B, and the accident C, the traveling speed of the traveling vehicle is acquired as the state quantity related to traffic, and the rainfall amount, the snow cover amount, and the wind force are acquired as the state quantities related to the weather. . The influence calculation unit 22 calculates the influence on the comprehensive evaluation value based on the acquired state quantity and hazard map information.

  The same applies to landslides and inundation. For example, when calculating the degree of influence on landslides, the degree-of-impact calculation unit 22 determines the state quantities related to traffic when landslides occurred in the past, the state quantities related to weather when landslides occurred in the past, and the locations where landslides occurred. Hazard map information is acquired for each individual landslide case. The influence calculation unit 22 calculates the influence on the comprehensive evaluation value based on the acquired state quantity and hazard map information.

  In this way, for each of a plurality of types of disaster, the impact calculation unit 22 has a state quantity related to traffic when the disaster has occurred in the past, a state quantity related to the weather when the disaster has occurred in the past, and its Hazard map information at a disaster occurrence point is acquired for each individual disaster case. The influence degree calculation unit 22 calculates the influence degree with respect to the comprehensive evaluation value for each of a plurality of disaster types, based on the acquired state quantity and hazard map information. That is, the degree of influence of the state quantity and the degree of influence of the hazard map information are calculated for each type of disaster. The influence degree calculation unit 22 outputs the calculated influence degree to the disaster occurrence possibility calculation unit 23.

  The disaster possibility calculation unit 23 includes the influence of the state quantity relating to traffic, the influence degree of the state quantity relating to the weather and the influence degree of the hazard map information, the state quantity relating to the current traffic, the state quantity relating to the current weather, and the hazard map. Based on the information, the possibility of disaster occurrence is calculated (step S160).

  In the present embodiment, the disaster possibility calculation unit 23 sets weights for each of the traffic state quantity, the weather state quantity, and the hazard map information based on the influence degree calculated by the influence degree calculation unit 22. To do. The weight is set so as to increase as the degree of influence increases.

  The disaster possibility calculation unit 23 calculates the weighted state quantity (weighted state quantity) by multiplying the weight set for the state quantity related to the traffic by the state quantity related to the current traffic. Further, the disaster possibility calculation unit 23 calculates the weighted state quantity (weighted state quantity) by multiplying the weight set for the state quantity related to the weather by the state quantity related to the current weather. The disaster possibility calculation unit 23 multiplies the hazard map information by the weight set for the hazard map information to calculate weighted hazard map information (weighted hazard map information).

  The disaster possibility calculation unit 23 calculates the possibility of disaster by adding the weighted state quantity related to the traffic, the weighted state quantity related to the weather, and the weighted hazard map information. The probability of disaster occurrence indicates that the greater the numerical value, the higher the probability of disaster occurrence at that point.

  Of the weighted state quantities related to the current traffic, the weighted state quantities related to the current weather, and the weighted hazard map information, the one that shows the largest value may be the possibility of occurrence of a disaster at that point. .

  The disaster probability calculated by the disaster probability calculation unit 23 is output to the output control unit 30 (step S170).

  The output control unit 30 generates output data so that the possibility of disaster occurrence at each point is displayed on a map, for example, and transmits the output data to the output device 4.

  FIG. 6 is a diagram illustrating a display example of the display screen of the output device 4 according to the present embodiment. As shown in FIG. 6, the output control unit 30 displays the map data of a certain region including the road and the possibility of occurrence of a disaster (possibility of occurrence of a traffic accident) at each of a plurality of points on the road at the same time. The output device 4 is controlled. FIG. 6 shows that the traffic accident occurrence level at point A (section A) on the road is 10 out of 10 levels, and the traffic accident occurrence level at point B (B section) on the road is out of 10 levels. 6 is an example in which the level of the possibility of occurrence of a traffic accident at point C (C section) of the road is 6 out of 10 levels.

  Further, the output control unit 30 can generate output data capable of switching and displaying the possibility of occurrence of a disaster calculated for each type of disaster for each type of disaster. For example, the output control unit 30 can generate a plurality of maps displaying the possibility of disaster occurrence at each point for each disaster type.

  FIG. 7 is a diagram illustrating a display example of the display screen of the output device 4 according to the present embodiment. As shown in FIG. 7, the output control unit 30 displays an input unit 300 for switching and displaying the possibility of disaster for each disaster type on the display screen of the output device 4. The operation input unit 300 includes a plurality of buttons provided for each disaster type. In the present embodiment, the buttons select a first button 301 for selecting “traffic accident”, a second button 302 for selecting “landslide”, and “flood” among the types of disasters. The third button 303 is included.

  For example, when the first button 301 indicating “traffic accident” is selected by the user, the output control unit 30 displays a map indicating the possibility of a disaster relating to “traffic accident” on the display screen of the output device 4. Thus, the output device 4 is controlled. Further, when the second button 302 indicating “landslide” is selected, the output control unit 30 outputs so that a map indicating the possibility of occurrence of a disaster related to “landslide” is displayed on the display screen of the output device 4. The apparatus 4 is controlled. Further, when the third button 303 indicating “flooding” is selected, the output control unit 30 outputs so that a map indicating the possibility of occurrence of a disaster related to “flooding” is displayed on the display screen of the output device 4. The apparatus 4 is controlled. As described above, the output control unit 30 can switch and display the possibility of disaster occurrence calculated for each disaster type on the output device 6 for each disaster type.

  As described above, according to the present embodiment, the possibility of occurrence of a disaster (possibility of occurrence of a traffic accident) for each point according to real-time information can be quantified based on past disaster information and hazard map information. It can support decision making in traffic control. Further, by accumulating past disaster information and setting a weight for each data or using it for calculation of a hazard map, it is possible to improve the accuracy of calculating the probability of disaster occurrence.

  For example, a road administrator or the like can arrange materials necessary for recovery in advance and confirm a response procedure for recovery based on the possibility of occurrence of a disaster displayed on the output device 4. In addition, a simulation such as traffic regulation is performed in advance so that the occurrence of a disaster can be avoided before the occurrence of the disaster, and measures are taken based on the result, thereby making it possible to avoid the disaster and minimize the damage. Thus, according to the present embodiment, decision making by a road manager or the like can be supported.

  In addition, by calculating the possibility of disaster occurrence for each disaster type and enabling switching display, road managers can efficiently and efficiently grasp the occurrence of various types of disasters that may occur. Can do.

  In the above-described embodiment, both the state quantity related to traffic and the state quantity related to weather are acquired by the acquisition unit 21, and the influence degree calculation and the disaster are calculated based on both the state quantity related to traffic and the state quantity related to weather. It was decided to calculate the possibility of occurrence. The state quantity related to the weather may not be acquired by the acquisition unit 21. The influence degree calculation unit 22 calculates the influence degree of the state quantity related to the traffic and the influence degree of the hazard map information based on the state quantity related to the traffic and the hazard map information when the disaster occurs, and the disaster possibility calculation unit 23 May calculate the possibility of occurrence of a disaster based on the degree of influence of the state quantity relating to traffic and the degree of influence of the hazard map information, and the state quantity relating to the current traffic and the hazard map information.

  In the above-described embodiment, the disaster probability calculation system 100 includes the information storage unit 10. As illustrated in FIG. 8, part or all of the information storage unit 10 may be provided in a cloud or the like outside the disaster probability calculation system 10. For example, the information analysis unit 20 and the information storage unit 10 of the disaster probability calculation system 100 may perform information communication via a communication network 18 such as the Internet. The information storage unit 10 may be connected to the external server 9C. The same applies to the following embodiments.

Second Embodiment
A second embodiment will be described. In addition, the same code | symbol is attached | subjected to the member which has the same function as embodiment mentioned above, and detailed description is abbreviate | omitted.

  FIG. 9 is a flowchart illustrating an example of a disaster probability calculation method according to the present embodiment. For example, when a new disaster occurs, past disaster information stored in the disaster information storage unit 14 is updated. When a new disaster occurs, for example, the state quantity related to traffic when a disaster has occurred in the past, which is stored in the disaster information storage unit 14, is updated. In the present embodiment, an example will be described in which the impact level calculation unit 22 newly calculates the impact level when a new disaster occurs and the state quantity when the disaster occurs is updated.

  When a new disaster occurs, the disaster information is stored in the disaster information storage unit 14. Past disaster information stored in the disaster information storage unit 14 is updated (step S100).

  The acquisition unit 21 acquires past disaster information from the disaster information storage unit 14 (step S110). Moreover, the acquisition part 21 acquires hazard map information from the hazard map information storage part 13 according to the above-mentioned embodiment (step S120), and the state regarding the present traffic from the traffic information storage part 11 and the weather information storage part 12 The quantity and the state quantity relating to the current weather are acquired (step S130).

  The influence calculation unit 22 calculates a comprehensive evaluation value related to the degree of the disaster based on the past disaster information acquired by the acquisition unit 21 (step S140). The influence calculation unit 22 gives the comprehensive evaluation value based on the comprehensive evaluation value related to the calculated degree of disaster, the state quantity included in the updated past disaster situation, and the hazard map information of the disaster occurrence point. An influence degree is newly calculated (step S150B).

  The disaster possibility calculation unit 23 calculates the possibility of disaster based on the influence degree of the state quantity and the influence degree of the hazard map information, and the current state quantity and the hazard map information (step S160). The disaster probability calculated by the disaster probability calculation unit 23 is output to the output control unit 30 (step S170).

  As described above, according to the present embodiment, since the influence degree is calculated based on the latest past state quantity, the accuracy of the possibility of occurrence of a disaster calculated based on the influence degree is improved. Further, every time a new disaster occurs and the disaster information stored in the disaster information storage unit 14 is updated, the degree of influence is newly calculated, thereby improving the accuracy of the possibility of disaster occurrence.

<Third Embodiment>
A third embodiment will be described. In addition, the same code | symbol is attached | subjected to the member which has the same function as embodiment mentioned above, and detailed description is abbreviate | omitted.

  In the present embodiment, an example in which the acquisition unit 21 acquires a state quantity related to terrain will be described. FIG. 10 is a functional block diagram showing an example of the disaster probability calculation system 100 according to the present embodiment.

  As illustrated in FIG. 10, the information storage unit 10 includes a terrain information storage unit 15 that stores terrain information. The terrain information stored in the terrain information storage unit 15 includes a state quantity related to the terrain. The state quantity related to the terrain includes, for example, lane information indicating the presence / absence of a lane and the number of lanes (1 lane, 2 lanes, etc.), slope information indicating the presence / absence of a slope and the degree of slope (down 10 [%] or less), Curve information indicating presence / absence and degree of curve (curve radius within 1000 [m], etc.), road surface information indicating friction coefficient or material of the road surface (such as asphalt A or asphalt B), presence / absence of tunnel, topography near tunnel entrance, And tunnel information indicating the topography near the exit of the tunnel.

  The acquisition unit 21 acquires a state quantity related to current traffic, a state quantity related to current weather, a state quantity related to current terrain, hazard map information, and past disaster information from the information storage unit 10.

  The influence degree calculation unit 22 calculates the influence degree of the state quantity related to the traffic and the influence degree of the hazard map information with respect to the occurrence of the disaster based on the state quantity related to the traffic and the hazard map information when the disaster occurs. Moreover, the influence degree calculation part 22 calculates the influence degree of the state quantity regarding the weather with respect to the occurrence of the disaster based on the state quantity related to the weather and the hazard map information when the disaster occurs. Moreover, the influence degree calculation part 22 calculates the influence degree of the state quantity regarding the terrain with respect to the occurrence of the disaster based on the state quantity and the hazard map information regarding the terrain when the disaster occurs.

  The disaster possibility calculation unit 23 includes the state quantity influence level and the hazard map information influence level calculated by the influence level calculation unit 22, the current traffic state quantity and the hazard map acquired by the acquisition unit 21. Based on the information, the possibility of disaster occurrence is calculated. In addition, the disaster possibility calculation unit 23 is configured to calculate the influence amount of the state quantity related to the weather and the influence degree of the hazard map information calculated by the influence degree calculation unit 22, the state quantity related to the current weather acquired by the acquisition unit 21, and Based on the hazard map information, the possibility of disaster occurrence is calculated. In addition, the disaster possibility calculation unit 23 is configured to calculate the influence amount of the state quantity related to the terrain calculated by the influence degree calculation unit 22 and the influence degree of the hazard map information, the state quantity related to the current terrain acquired by the acquisition unit 21, and Based on the hazard map information, the possibility of disaster occurrence is calculated.

  As described above, in the present embodiment, the state quantity related to the terrain stored in the terrain information storage unit 15 is used to calculate the degree of influence in the disaster occurrence possibility calculation unit 23 together with the state quantity related to traffic and weather. The degree of influence on the comprehensive evaluation value is calculated for each terrain information. Further, the terrain information and the influence degree of the terrain information are used for calculating the possibility of disaster occurrence. By taking into account the state quantities related to the terrain, the accuracy of the possibility of disasters is improved.

  In addition, in this embodiment, the acquisition part 21 acquires the state quantity regarding a traffic and the state quantity regarding a topography, and does not need to acquire the state quantity regarding a weather. The influence degree calculation unit 22 and the disaster possibility calculation unit 23 may perform the calculation process using the state quantity related to traffic and the state quantity related to topography without using the state quantity related to the weather.

<Fourth embodiment>
A fourth embodiment will be described. In addition, the same code | symbol is attached | subjected to the member which has the same function as embodiment mentioned above, and detailed description is abbreviate | omitted.

  In the present embodiment, an example in which the acquisition unit 21 acquires maintenance information will be described. FIG. 11 is a functional block diagram illustrating an example of the disaster probability calculation system 100 according to the present embodiment.

  As illustrated in FIG. 11, the information storage unit 10 includes a maintenance information storage unit 16. The maintenance information storage unit 16 collects and stores maintenance information of a traffic facility such as a road input by a road administrator or the like via the input device 3. The maintenance information includes the latest maintenance execution date at each point, the content of the maintenance, the period until the next maintenance, the confirmation result at the time of patrol, and the like. Maintenance includes road construction or road repair. Further, the maintenance information may include not only road maintenance but also information on maintenance (construction or repair etc.) of surrounding facilities or equipment. For example, when a breakwater is provided around the road, maintenance information on the breakwater may be stored in the maintenance information storage unit 16. In addition, the maintenance information includes traffic regulation information (lane regulation or speed regulation) associated with maintenance.

  FIG. 12 is a flowchart illustrating an example of a disaster probability calculation method according to the present embodiment. According to the above-described embodiment, the acquisition unit 21 acquires past disaster information from the disaster information storage unit 14 (step S110). Moreover, the acquisition part 21 acquires hazard map information from the hazard map information storage part 13 (step S120). Moreover, the acquisition part 21 acquires the state quantity regarding the present traffic, and the state quantity regarding the present weather from the traffic information storage part 11 and the weather information storage part 12 (step S130). The influence degree calculation unit 22 calculates a comprehensive evaluation value related to the degree of disaster (step S140). The influence degree calculation unit 22 calculates the influence degree based on the comprehensive evaluation value regarding the calculated degree of disaster, the state quantity when the disaster occurs, and the hazard map information of the disaster occurrence point (step S150). .

  The acquisition unit 21 acquires and stores maintenance information at each point from the maintenance information storage unit 16 (step S152). Then, the acquisition unit 21 transmits the acquired maintenance information to the disaster occurrence possibility calculation unit 23.

  The disaster probability calculation unit 23 calculates a maintenance coefficient based on the maintenance information acquired from the acquisition unit 21. The maintenance coefficient is a coefficient that is calculated for each disaster type and corrects the probability of disaster occurrence by multiplying the probability of disaster occurrence that is calculated later.

  For example, in the maintenance information, if there is a point where a certain period of time has passed since the latest maintenance execution date, the maintenance coefficient for a disaster such as “collapse due to earthquake” at that point is a high numerical value (eg, “3” in three stages). ). Further, when there is a point that satisfies a certain condition in the confirmation result at the time of patrol, the maintenance coefficient for the disaster at that time is calculated as a high numerical value (for example, “3” in three stages). In the maintenance information, if there is a point where a breakwater is provided in the vicinity, the maintenance factor for disasters such as “tsunami” or “flood” at that point is calculated as a low value (eg, “1” in three stages). The

  For a point where the maintenance coefficient is a high numerical value, the disaster probability calculation unit 23 further calculates the disaster probability calculated by multiplying the current state quantity and the hazard map information by a weight according to the degree of influence. The possibility of occurrence of a disaster in consideration of maintenance information is calculated by correcting by multiplying by a maintenance coefficient corresponding to the maintenance information.

  Here, the disaster possibility calculation unit 23 multiplies a coefficient corresponding to the maintenance information only to the possibility of a disaster relating to a disaster that is strongly related to the maintenance information. As a disaster strongly related to the maintenance information, for example, there is a possibility that a disaster related to a ground collapse due to an earthquake or a collapse of a building such as a tunnel may occur.

  The disaster probability calculated by the disaster probability calculation unit 23 is output to the output control unit 30 (step S170).

  As described above, according to the present embodiment, it is possible to calculate the possibility of disaster occurrence with higher accuracy by using the maintenance information for calculating the possibility of disaster occurrence.

<Fifth Embodiment>
A fifth embodiment will be described. In addition, the same code | symbol is attached | subjected to the member which has the same function as embodiment mentioned above, and detailed description is abbreviate | omitted.

  FIG. 13 is a hardware configuration diagram illustrating an example of the disaster occurrence prediction system 100 according to the present embodiment. As shown in FIG. 13, in the present embodiment, the disaster probability calculation system 100 is connected to a moving body 40 such as a vehicle traveling on a road via a communication network 18 such as the Internet. The moving body 40 is equipped with an operation control device 50. The operation control device 50 includes, for example, an ECU (Engine Control Unit). The operation control device 50 includes, for example, a CPU 41, a RAM 42, and a ROM 43.

  The moving body 40 includes an output device 45 including a display device or a speaker. The output device 45 is disposed in the cab of the moving body 40. When the output device 45 includes a display device, the driver of the moving body 40 can see display data displayed on the output device 45. When the output device 45 includes a speaker, the driver of the moving body 40 can hear the audio data output from the output device 45.

  FIG. 14 is a functional block diagram illustrating an example of the disaster occurrence prediction system 100 according to the present embodiment. As illustrated in FIG. 14, the operation control device 50 includes an operation state acquisition unit 51, an operation control unit 52, a communication unit 53, and an output control unit 54.

  The driving state acquisition unit 51 acquires the driving state of the moving body 40. The driving state includes at least one of the traveling speed, acceleration, and steering angle of the moving body 40. The traveling speed of the moving body 40 is detected by a speed sensor installed on the moving body. The acceleration of the moving body 40 is detected by an acceleration sensor installed on the moving body. The steering angle of the moving body 40 is detected by a steering angle sensor installed on the moving body. The driving state acquisition unit 51 acquires the driving state of the moving body 40 from these sensors.

  The operation control unit 52 generates and outputs a control signal for controlling the moving body 40 to control driving of various actuators installed in the moving body 40, or to operate an automatic operation system and an operation mounted on the moving body 40. The assist system or the constant speed traveling system is controlled.

  The communication unit 53 acquires a control command transmitted from the outside of the moving body 40 via the communication network 18. The communication unit 53 outputs the acquired control command to the operation control unit 52.

  The output control unit 54 generates information to be output to the output device 45 installed in the moving body 40 and transmits the information to the output device 45.

  The information processing apparatus 1 of the disaster possibility calculation system 100 includes an operation control command generation unit 60. The operation control command generation unit 60 generates a control command for the moving body 40 using the possibility of occurrence of a disaster calculated by the information analysis unit 20. In the present embodiment, the operation control command generation unit 60 generates an operation control command that avoids the occurrence of a disaster for the moving body 40 that passes through a point where there is a high possibility of a disaster.

  FIG. 15 is a flowchart showing an operation control method for the moving body 40 by the disaster possibility calculation system 100 according to the present embodiment.

  According to the above-described embodiment, the information analysis unit 20 of the disaster possibility calculation system 100 calculates the possibility of disaster occurrence at each point (step S160).

  The possibility of disaster occurrence at each point calculated by the information analysis unit 20 is output to the operation control command generation unit 60. The operation control command generation unit 60 uses the acquired disaster occurrence probability at each point to extract a point having a high possibility of disaster occurrence (step S210). For extraction of points with a high probability of disaster, a preset threshold value may be used, and a point with a high probability of a disaster that exceeds the set threshold value is selected. Extract as

  Then, the operation control command generation unit 60 uses a detection information of a position detection device such as a GPS (Global Positioning System) receiver mounted on each moving body 40 to detect a point where the disaster is likely to occur and its surroundings. The moving body 40 that travels is specified (step S220).

  The operation control command generation unit 60 generates an operation control command for the moving body 40 that travels at or around a point where a disaster is highly likely to occur. The operation control command is a command for avoiding the occurrence of a disaster with respect to the moving body 40 passing through a point where the possibility of the occurrence of a disaster is high or in the vicinity thereof. The operation control command is, for example, a command for forcibly reducing the traveling speed of the moving body 40 to 50 [km / h] or less, and the inter-vehicle distance between the moving body 40 and the moving body 40 preceding the moving body 40 is a fixed distance. It includes at least one of a command to forcibly extend the above and a command to forcibly travel a route that detours a point where there is a high possibility of a disaster.

  The generated driving control command is output from the information processing device 1 to the communication unit 53 of the driving control device 50 of the moving body 40 that travels at the point. The communication unit 53 outputs the acquired operation control command to the operation control unit 52.

  When the communication unit 53 receives the operation control command, the operation control unit 52 calculates the probability of occurrence of a disaster when passing through a point having a high probability of disaster occurrence calculated by the disaster possibility calculation system 100 or the vicinity thereof. According to the operation control command output from the system 100, the operation of the moving body 40 is controlled so that the occurrence of a disaster is avoided. The operation control unit 52 generates an operation control command for avoiding the occurrence of a disaster for the moving body 40 that passes through a point where the possibility of a disaster is high. The operation control unit 52 controls the throttle actuator or the brake actuator, for example, and performs the operation based on the operation control command. For example, when a command for forcibly increasing the inter-vehicle distance to a certain distance or more is received, the operation control unit 52 uses the inter-vehicle distance radar installed in the moving body 40 to calculate the inter-vehicle distance and relative speed with the preceding moving body 40. Based on the acquired command, the deceleration of the moving body 40 is calculated so that the inter-vehicle distance becomes larger than the command value, and the brake actuator of the moving body 40 is operated.

  When the communication unit 53 receives the operation control command, the output control unit 54 controls the output device 45 installed in the moving body 40 so that the occurrence of a disaster is avoided. The output control unit 54 generates output data that urges the mobile body 40 that passes through a point where there is a high possibility of a disaster or the vicinity thereof to avoid the occurrence of a disaster. The output control unit 54 displays, for example, display data indicating that a command for forcibly dropping the speed to 50 [km / h] or less is displayed on the display device, or forcibly increases the inter-vehicle distance to a certain distance or more. Output data for outputting audio data indicating that the sound is to be output from the speaker is generated and transmitted to the output device 45.

  In addition, when the communication unit 53 receives an operation control command, the output control unit 54 travels to a point where a disaster is likely to occur with respect to the mobile body 40 passing through a point where the possibility of a disaster is high or around it. Output data to be avoided is generated and displayed on the output device 45.

  FIG. 16 is a diagram illustrating a display example of the output device 45 according to the present embodiment. As shown in FIG. 16, a route with a high possibility of disaster occurrence is displayed in a specific color. In the example illustrated in FIG. 16, “Route 16” and “Route 33” are displayed as routes having a high possibility of disaster occurrence. The driver of the moving body 40 viewing the display screen of the output device 45 travels by determining the travel route of the moving body 40 so as to avoid “Route 16” and “Route 33”. This avoids disasters and avoids traffic jams.

  As described above, according to the present embodiment, using the possibility of disaster occurrence calculated by the information analysis unit 20 of the disaster occurrence possibility calculation system 100, the vehicle travels at or near a point where the possibility of disaster occurrence is high. Operation control of the moving body 40 can be performed, and the occurrence of a disaster can be prevented in advance.

  The disaster possibility calculation system 100 outputs an output control command to the output device 45 of the moving body 40 without issuing an operation control command to the moving body 40 that travels at or around a point where the possibility of a disaster is high. May be generated and output to the communication unit 53 of the moving body 40. For example, to display characters such as “Please reduce the speed because traffic accidents are likely to occur” or “Please increase the distance between vehicles because traffic accidents are likely to occur” on the display of the car navigation system Output control command is generated. The output control unit 54 of the moving body 40 performs output control to the output device 45 installed in the moving body 40 when the communication unit 53 receives the output control command.

<Sixth Embodiment>
A sixth embodiment will be described. In addition, the same code | symbol is attached | subjected to the member which has the same function as embodiment mentioned above, and detailed description is abbreviate | omitted.

  FIG. 17 shows the disaster occurrence possibility prediction system of this embodiment. In addition, the same code | symbol is attached | subjected to the member which has the same function as embodiment mentioned above, and detailed description is abbreviate | omitted.

  As shown in FIG. 17, in this embodiment, the information storage part 10 has the SNS information storage part 17 which collects and memorize | stores the SNS information regarding the posting text on a social networking service (SNS). The information analysis unit 20 includes an acquisition unit 21 that acquires SNS information from the SNS information storage unit 17, and an SNS information analysis unit 24 that acquires position information and disaster information from the SNS information acquired by the acquisition unit 21.

  In SNS, an unspecified number of users can transmit their own comments as posted texts via the SNS site server 9D. The information storage unit 10 includes an SNS information storage unit 17 that acquires and stores such SNS post text. The SNS information storage unit 17 communicates with an external SNS site server 9D via the Internet, and collects and stores posted sentences described by a large number of contributors.

  The information analysis unit 20 includes an SNS information analysis unit 24 that analyzes the SNS information output from the SNS information storage unit 17. The SNS information analysis unit 24 acquires location information attached as data to the posted text, and identifies a disaster occurrence location based on the location information. The SNS information analysis unit 24 estimates the content and scale of the disaster by analyzing the content of the posted text. The SNS information analysis unit 24 outputs an SNS information analysis result including disaster information to the output control unit 30.

  The output control unit 30 outputs, to the output device 4, output data that displays the disaster information obtained from the SNS information analysis result at the position on the map indicated by the position information of the posted sentence specified based on the SNS information.

  FIG. 18 is a flowchart illustrating an example of a disaster probability calculation method including SNS information analysis according to the present embodiment.

  The SNS information storage unit 17 sets an extraction condition for extracting a posted sentence that satisfies the set constant condition (step S310). For example, the keyword “traffic accident” is set as the extraction condition. The extraction condition including the keyword is input via the input device 3 by a road administrator or the like.

  The SNS information storage unit 17 extracts and acquires a posted sentence satisfying the set extraction condition from the SNS site server 9D (step S320). The SNS information storage unit 17 collects and stores document data of a posted sentence including the keyword based on the registered keyword.

  Note that the SNS information storage unit 17 may acquire SNS information not only from the external SNS site server 9D but also from an SNS site server provided in the disaster probability calculation system 100. For example, when the road administrator has an SNS site server, the SNS information storage unit 17 may acquire SNS information from the SNS site server.

  The SNS information storage unit 17 simultaneously acquires GPS information indicating the location information of the posted point along with the document data of the posted text. The SNS information storage unit 17 outputs the collected SNS information to the acquisition unit 21. The SNS information acquired by the acquisition unit 21 is output to the SNS information analysis unit 24.

  The SNS information analysis unit 24 analyzes the disaster occurrence location, the type of disaster, the scale of the disaster, and the like from the acquired information on the posted text (step S330). Specifically, the SNS information analysis unit 24 acquires information such as a disaster occurrence location, a disaster type, and a disaster scale by text mining the acquired posted text.

  Moreover, the SNS information analysis part 24 may acquire position information by text mining. For example, the SNS information analysis unit 24 may acquire a text such as “˜interchange” or “˜road (road)” and specify the position on the map. The SNS information analysis unit 24 outputs the SNS information analysis result to the output control unit 30.

  The output control unit 30 specifies the display position on the map based on the position information included in the SNS information analysis result, and displays display data for displaying the SNS information analysis result such as the content and scale of the disaster on the map. Generate. The output control unit 30 outputs the generated display data to the output device 4 (step S340).

  FIG. 19 is a diagram illustrating a display example of the output device 4 according to the present embodiment. As shown in FIG. 19, a plot point 56 indicating position information where a posted sentence satisfying the extraction condition is posted is displayed on the map. Display data 57 indicating disaster information including the contents and scale of the disaster is also displayed on the map. A position where a lot of plot points 56 are dense can be recognized as a disaster occurrence place because the reliability of the SNS information is high.

  Further, the SNS information analysis unit 24 may determine the reliability of disaster information based on the number of SNS information (number of posted texts) of disaster information in a specific area, and may display the map by changing the color or icon. . The SNS information analysis unit 24 determines that the reliability of the SNS information is higher as the number of posted sentences is larger, and changes the color or icon.

  As explained above, by using SNS with high real-time characteristics, disaster information is sent to road managers etc. earlier than patrol cars etc. go to the site and confirm the disaster situation after receiving a report of the occurrence of a disaster. Shared. Therefore, prompt decision making by a road manager or the like can be supported.

  Such information may be displayed not only on the monitor provided in the traffic control center but also on the monitor in the service area of the expressway. As a result, not only the road manager but also the general public who uses the road is quickly provided with information.

  Next, an example of processing when an image is attached to a posted message will be described with reference to the flowchart of FIG. Similar to the processing described with reference to FIG. 18, the extraction condition is set (step S310), and the posted text is extracted (step S320).

  When an image is attached to the posted text, the acquiring unit 21 acquires image information attached to the posted text. The SNS information analysis unit 24 analyzes the image information acquired by the acquisition unit 21 (step S330).

  The SNS information analysis unit 24 analyzes the image information and determines whether the image of the image information is an image of a disaster site (step S332).

  If it is determined in step S332 that the image is an image of a disaster site (step S332: Yes), the output control unit 30 outputs image information as disaster information to the output device 4 at the position on the map indicated by the position information. Output (step S340). For example, on the display screen shown in FIG. 19, the output device 4 displays image information as disaster information at a position on the map indicated by the position information.

  On the other hand, when it is determined in step S332 that the image is not a disaster site image (step S332: No), the output control unit 30 does not output the image information to the output device 4 (step S342).

  Thus, by displaying the image information, the state of the disaster site can be confirmed at a remote place.

<Seventh embodiment>
A seventh embodiment will be described. In addition, the same code | symbol is attached | subjected to the member which has the same function as embodiment mentioned above, and detailed description is abbreviate | omitted.

  In the first to sixth embodiments described above, the example of calculating the possibility of disaster occurrence has been described. When a disaster such as a traffic accident actually occurs, a support article or a support vehicle for supporting the disaster site is transferred to the disaster site. The information processing apparatus 1 can simulate the optimum route and the optimum procedure for arranging the assistance article or the assistance vehicle.

  The information processing apparatus 1 uses, for example, disaster information (location, content, scale, etc.) of an actual disaster site and current traffic information (traffic volume, traffic jam information, closed section information, etc.) around the disaster site. Based on this, an optimal route and an optimal procedure for transferring the support article or the support vehicle to the disaster site are calculated.

  For example, support vehicles or support items arranged to support traffic accident sites are ambulances, tow trucks for removing accident vehicles, crane cars, construction machinery for repairing roads damaged by traffic accidents, repair Examples include materials (gravel, asphalt material, etc.), medical devices, lifesaving equipment, medicines, clothing, and blankets.

  For example, when an accident caused by snow on an expressway occurs and a support vehicle or support article is needed to respond to the accident, for example, from a computer system mounted on an emergency vehicle rushed to the accident site Request data for requesting a support vehicle or support article is output to the information processing apparatus 1. The request data includes the article data indicating the support article or the support vehicle required at the accident site, the target quantity data indicating the target quantity of the support article or the support vehicle, and the desired arrival time indicating the desired arrival time of the support article or the support vehicle. Contains data.

  The transfer of the support article or the support vehicle is started. The acquisition unit 21 acquires arrangement status data indicating the arrangement status of each of a plurality of support articles or support vehicles. The output control unit 30 causes the output device 4 to display article data.

  FIG. 21 is a diagram illustrating a display example of the output device 4 according to the present embodiment. As shown in FIG. 21, the output control unit 30 causes the output device 4 to display item data 60 for displaying article data in association with arrangement status data. The item data 60 includes article data (such as antifreezing agents), actual amount data (secured amount), target amount data (target amount), expected arrival time data (arrival prediction), belonging data (affiliation), and the like. The item data 60 includes traffic data indicating the status of the transfer route of the support article or the support vehicle, planned route data indicating the planned route of the support article or the support vehicle, and the like.

  The arrangement status data includes position information indicating the position of the support article or the support vehicle. In the present embodiment, the position information of the support article or the support vehicle is indicated by an icon 61. FIG. 21 shows an example in which four support vehicles (support articles) including a transport vehicle, a crane vehicle, a tow truck, and a snowplow for transporting an antifreezing agent are traveling toward a disaster site (accident site).

  The output control unit 30 causes the output device 4 to display the position information and the item data 44 in association with each other. Accordingly, it is possible to quickly recognize which support vehicle is transporting which support article and how much. In addition, it is possible to quickly recognize which support vehicle is currently where and when it is likely to arrive.

  The output control unit 30 causes the output device 4 to display the position information of the support vehicle in real time. The output control unit 30 sequentially updates the position information of the support vehicle to the latest position information, and causes the output device 4 to display the latest position information of the support vehicle. Further, the output control unit 30 causes the output device 4 to display the update time information 62 indicating the update time when the position information of the support vehicle is updated.

In each of the above-described embodiments, when the possibility of a disaster is high or when a disaster actually occurs, the output control unit 30 generates display data based on disaster-time information necessary at the time of a disaster, The information at the time of disaster can be output to a portable terminal owned by a worker or a display board of a road via the network, and can be held by a worker, a road user, or the like. Here, the disaster information is, for example, as described below.
1. 1. Personnel resource management information-input using input device 3 2. Logistic support (material transportation) information-input using the input device 3 3. Weather information, wind direction information, earthquake information, tsunami information-input from sensor 2 or input device 3 4. Information on road damage caused by disaster (camera image, landslide, restoration status, etc.) Information-Input using the input device 3 5. State quantity information about traffic-input from sensor 2 6. Simulation information on traffic flow-input from input device 3 7. In-road response status (recovery progress status) information-input using input device 3 Task management information-input using input device 3 9. FAX image information etc.-Input using the input device 3

  Then, the output control unit 30 selects only information necessary for decision making from the disaster-related information and generates display data, and the disaster-related information is transmitted to the portable terminal owned by the worker via the network. It can be output on a road display board and shared with workers and road users. That is, since the output device 4 is arranged at different positions in each place, the necessary disaster information is also different. Therefore, priorities are assigned in advance to the disaster-related information for each output device 4, and only high priority information is selected and displayed.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are also included in the scope of the invention described in the claims and the scope thereof.

DESCRIPTION OF SYMBOLS 1 ... Information processing apparatus, 2 ... Sensor, 3 ... Input device, 4 ... Output device, 5 ... CPU, 6 ... RAM, 7 ... ROM, 8 ... Drive apparatus, 9A ... Recording medium, 9B ... External database, 9C ... External Server, 9D ... SNS site server, 10 ... information storage unit, 11 ... traffic information storage unit, 12 ... meteorological information storage unit, 13 ... hazard map information storage unit, 14 ... disaster information storage unit, 15 ... terrain information storage unit, DESCRIPTION OF SYMBOLS 16 ... Maintenance information storage part, 17 ... SNS information storage part, 18 ... Communication network, 20 ... Information analysis part, 21 ... Acquisition part, 22 ... Influence degree calculation part, 23 ... Disaster possibility calculation part, 24 ... SNS information Analysis unit, 30 ... output control unit, 40 ... moving body, 41 ... CPU, 42 ... RAM, 43 ... ROM, 45 ... output device, 50 ... operation control device, 51 ... operation state acquisition unit, 52 ... operation control unit, 3 ... communication unit, 54 ... output control unit, 56 ... plot point, 57 ... display data, 60 ... item data, 61 ... icon 62 ... update time information, 100 ... disaster possibility calculation system.

Claims (16)

An acquisition unit for acquiring traffic state quantities and hazard map information;
Based on the state quantity related to the traffic and the hazard map information when a disaster occurs, an influence degree calculating unit that calculates the influence degree of the state quantity related to the traffic and the influence degree of the hazard map information with respect to the occurrence of the disaster;
Based on the current state quantity and the hazard map information on the traffic and the hazard map information, the disaster possibility calculation section that calculates the possibility of disaster occurrence, based on the current state quantity and the hazard map information on the traffic,
Disaster probability calculation system with The acquisition unit acquires a state quantity related to weather,
The influence calculation unit calculates the influence of the state quantity related to the weather on the occurrence of a disaster,
The disaster possibility calculation unit calculates the disaster possibility based on the influence degree of the state quantity related to the weather and the current state quantity related to the weather,
The disaster occurrence possibility calculation system according to claim 1. The acquisition unit acquires a state quantity related to terrain,
The influence calculation unit calculates the influence of the state quantity related to the terrain with respect to the occurrence of a disaster,
The disaster occurrence possibility calculation unit calculates the disaster occurrence possibility based on the influence degree of the state quantity related to the terrain and the current state quantity related to the terrain.
The disaster occurrence possibility calculation system according to claim 1 or 2. The acquisition unit acquires maintenance information,
The disaster occurrence possibility calculating unit corrects the disaster occurrence possibility based on the maintenance information.
The disaster occurrence possibility calculation system according to any one of claims 1 to 3. When a new disaster occurs and the state quantity at the time of the disaster is updated, the impact calculation unit newly calculates the impact,
The disaster occurrence possibility calculation system according to any one of claims 1 to 4. The disaster probability calculation unit sets a weight for each of the state quantity and the hazard map information based on the degree of influence calculated by the influence degree calculation unit, and sets the weight to the current state quantity. Calculating the probability of occurrence of the disaster by adding the weighted state quantity calculated by multiplication and the weighted hazard map information calculated by multiplying the hazard map information by the weight.
The disaster occurrence possibility calculation system according to any one of claims 1 to 5. The acquisition unit acquires information on the type of disaster,
The impact calculation unit calculates the impact for each disaster type.
The disaster occurrence possibility calculation system according to any one of claims 1 to 6. The disaster probability calculation unit calculates the disaster probability for each disaster type based on the degree of influence calculated for each disaster type,
An output control unit that generates output data that can be switched and displayed for each type of disaster, the possibility of disaster occurrence calculated for each type of disaster;
The disaster possibility calculation system according to claim 7. An output control unit that generates output data that urges driving that avoids the occurrence of a disaster for a mobile body that passes through a point where the possibility of occurrence of the disaster is high,
The disaster occurrence possibility calculation system according to any one of claims 1 to 7. An operation control command generation unit that generates an operation control command for avoiding the occurrence of a disaster for a moving body that passes through a point where the possibility of occurrence of the disaster is high,
The disaster occurrence possibility calculation system according to any one of claims 1 to 9. The acquisition unit acquires SNS information related to a posted message on a social networking service,
From the SNS information, an SNS information analysis unit that acquires location information and disaster information;
An output control unit that outputs output data for displaying the disaster information at a position on a map indicated by the position information to an output device,
The disaster occurrence possibility calculation system according to any one of claims 1 to 7. The acquisition unit acquires image information attached to the posted text,
The SNS information analysis unit analyzes the image information to determine whether the image of the image information is a disaster scene image,
When it is determined that the image is an image of the disaster site, the output control unit outputs the image as disaster information to a position on the map indicated by the position information.
The disaster possibility calculation system according to claim 11.   The possibility of the occurrence of a disaster when the vehicle is mounted on a mobile body and passes through the point having a high possibility of a disaster occurrence calculated by the disaster occurrence possibility calculation system according to any one of claims 1 to 12. An operation control device that performs operation control to avoid the occurrence of a disaster according to an operation control command output from a calculation system. Obtaining state quantities and hazard map information about traffic;
Based on the state quantity related to the traffic and the hazard map information when a disaster occurs, calculating the degree of influence of the state quantity related to the traffic and the degree of influence of the hazard map information on the occurrence of a disaster;
Calculating the probability of occurrence of a disaster based on the degree of influence of the state quantity relating to the traffic and the degree of influence of the hazard map information, and the current state quantity relating to the traffic and the hazard map information;
Method for calculating the possibility of disasters including Computer
An acquisition unit for acquiring traffic state quantities and hazard map information;
Based on the state quantity related to the traffic and the hazard map information when a disaster occurs, an influence degree calculating unit that calculates the influence degree of the state quantity related to the traffic and the influence degree of the hazard map information with respect to the occurrence of the disaster;
Based on the current state quantity and the hazard map information on the traffic and the hazard map information, the disaster possibility calculation section that calculates the possibility of disaster occurrence, based on the current state quantity and the hazard map information on the traffic,
Program to function as. Computer
An acquisition unit for acquiring traffic state quantities and hazard map information;
Based on the state quantity related to the traffic and the hazard map information when a disaster occurs, an influence degree calculating unit that calculates the influence degree of the state quantity related to the traffic and the influence degree of the hazard map information with respect to the occurrence of the disaster;
Based on the current state quantity and the hazard map information on the traffic and the hazard map information, the disaster possibility calculation section that calculates the possibility of disaster occurrence, based on the current state quantity and the hazard map information on the traffic,
A recording medium on which a program for functioning as a recording medium is recorded.

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