Road Disaster Response Support System, Program, and Road Management Method

Abstract

Conventionally, the road was visually inspected from patrols etc., and it was determined whether to respond to road disasters in the event of a disaster or the like by observing the actual road conditions. However, there was a problem that it took time and effort to make a judgment only by visual patrol, and it was difficult to respond quickly. 【Solution means】 An information acquisition unit that acquires information related to disasters, an analysis unit that analyzes two or more pieces of information acquired by the information acquisition unit, and a determination unit that determines the necessity of road disaster response from part or all of the results analyzed by the analysis unit, A road opening unit that registers a pre-formulated road opening plan and formulates an implementation plan for road opening, and a robotics unit in which a disaster response robot performs a road opening operation using artificial intelligence analysis and robotics technology, A road disaster response support system, program, and road management method, characterized by comprising:

Description

Technical Field

[0001] The present invention relates to a road disaster response support system, a program, and a road management method for restoring and managing roads in the event of disasters such as earthquakes.

Background Art

[0002] In the event of a large-scale disaster such as an earthquake, road administrators carry out emergency restoration (road opening) for the passage of emergency vehicles and Self-Defense Force vehicles engaged in disaster countermeasures, and then carry out road disaster responses such as emergency restoration and full restoration. Emergency vehicles are vehicles defined by the Basic Law on Disaster Countermeasures, the Road Traffic Law, etc. For example, fire trucks, ambulances, disaster restoration work vehicles, doctor cars, road patrol cars, wrecker trucks, vehicles of administrative agencies, vehicles of electric power companies, gas companies, and telephone companies, disaster countermeasure vehicles (drainage pump trucks, lighting trucks, disaster countermeasure headquarters vehicles, standby support vehicles, satellite communication vehicles, information collection vehicles, disaster countermeasure vehicles with drones, etc.), material transport vehicles, evacuation buses, etc.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, roads have been visually inspected from patrols or helicopters, and the actual road conditions have been observed to determine whether to carry out road disaster responses such as emergency restoration and emergency restoration in the event of disasters such as earthquakes. However, there has been a problem that it takes time and effort to make a judgment based only on visual patrols, and it is difficult to respond quickly. Road disaster response mainly includes grasping the overall situation and issuing orders for the system, formulating basic policies for disaster response, commanding and ordering restoration (emergency restoration, emergency restoration, full restoration), and public notification. Specifically, it includes information collection immediately after a disaster occurs, ensuring communication and liaison immediately after a disaster occurs, establishing an operation system, responding to the government headquarters and related ministries and agencies, conducting emergency inspections of roads and facilities immediately after a disaster occurs, securing disaster prevention equipment and materials, securing restoration equipment and materials, implementing emergency restoration work, implementing emergency recovery work, implementing full restoration work, imposing traffic restrictions on roads, ensuring road traffic, taking measures to prevent secondary disasters, implementing emergency restoration of lifeline facilities, providing support to local governments, responding to affected persons, and responding to spontaneous support such as volunteers, etc.

Means for Solving the Problem

[0005] The above problems can be solved by an invention comprising the following configuration. [1] An information acquisition unit that acquires information on meteorological conditions and information on patrol conditions, an analysis unit that analyzes the meteorological conditions and patrol conditions obtained from the information acquired by the information acquisition unit, a determination unit that determines the necessity of road disaster response from the results analyzed by the analysis unit, and a road opening unit that registers a pre-established road opening plan and formulates an implementation plan for road opening. The determination unit determines the necessity of road disaster response, the analysis unit judges the severity of the road disaster from the results analyzed, and when the road disaster is severe due to an earthquake of less than intensity 6 or a wide-area disaster, among the information on vehicle driving conditions, information on optical fiber survey conditions, information on satellite survey conditions, and information on road service conditions, one or more pieces of information are acquired by the information acquisition unit, the acquired one or more pieces of information are analyzed by the analysis unit, and the determination unit determines the necessity of road disaster response from the analyzed results. When road disaster response is required, the pre-established road opening plan is registered with the road opening unit, and the road opening unit formulates the implementation plan for road opening based on the road opening plan registered with the road opening unit and two or more pieces of information acquired by the information acquisition unit or the results analyzed by the analysis unit. A road disaster response support system characterized by this. The system described in [2][1], comprising a robotics unit in which a disaster response robot performs road opening operations using artificial intelligence analysis and robotics technology, and based on the implementation plan or the road opening plan of the road opening, using the artificial intelligence analysis and the robotics technology, the disaster response robot performs road opening operations by the robotics unit. A road disaster response support system characterized by this. [3] A program for causing a computer to function as the road disaster response support system described in [1] or [2]. [4] A road management method using a computer, wherein the computer acquires information on weather conditions and information on patrol conditions via a network, analyzes the weather conditions and the patrol conditions obtained from the acquired information, determines the necessity of road disaster response from the analyzed results, judges the severity of the road disaster from the analyzed results, and when the road disaster is severe due to an earthquake of intensity 6- or higher or a wide-area disaster, acquires one or more pieces of information among information on vehicle driving conditions, information on optical fiber survey conditions, information on satellite survey conditions, and information on road service conditions via the network, analyzes using the acquired one or more pieces of information, determines the necessity of road disaster response from the analyzed results, and when road disaster response is required, registers a pre-established road opening plan in advance, and performs an implementation plan for road opening based on the registered road opening plan and the acquired two or more pieces of information or the analyzed results. A road management method characterized by this. [5] The road management method of [4], characterized in that based on the implementation plan or the road opening plan of the road opening, a disaster response robot performs road opening operations via a network using artificial intelligence analysis and robotics technology. [6] The road management method described in [4] or [5], characterized in that by using a large language model to collect data on the Internet and perform learning on disaster countermeasures regardless of the language type, the road opening plan, the implementation plan for road opening, or the road opening operations are continuously improved. [Effect of the Invention]

[0006] The present invention can quickly respond to road disasters during disasters such as earthquakes.

Brief Explanation of Drawings

[0007]

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Modes for Carrying Out the Invention

[0008] Hereinafter, with reference to the drawings, an embodiment of the road disaster response support system of the present invention will be described. It should be noted that the embodiment described below does not unduly limit the content of the present disclosure described in the claims. Also, not all of the configurations described in this embodiment are essential constituent elements of the present disclosure. In addition, each individual configuration constituting the feature group can also be an invention.

[0009] FIG. 1 is a system configuration diagram of a road disaster response support system 600 according to the present invention. The road disaster response support system 600 includes an information acquisition unit 610 that acquires information on patrol status, information on optical fiber survey status, information on satellite survey status, information on weather status, and information on vehicle driving status, a patrol status, an optical fiber survey status, a satellite survey status, a weather status, and a vehicle driving status obtained from the information acquired by the information acquisition unit 610, and an analysis unit 620 that analyzes the vehicle driving status, and a determination unit 630 that comprehensively determines the necessity of road disaster response from the results analyzed by the analysis unit 620. The road disaster response support system 600 of the embodiment is communicably connected to a patrol status providing server 100, an optical fiber survey status providing server 200, a satellite survey status providing server 300, a weather status providing server 400, and a vehicle driving status providing server 500 through a network NW. In order to grasp the patrol status, only one vehicle Vh and terminal device TM are shown in FIG. 1, but a plurality of vehicles Vh and terminal devices TM may be connected to the network NW. In order to grasp the disaster situation and the like, only one fixed-point camera CAM is shown in FIG. 1, but a plurality of fixed-point cameras CAM may be connected to the network NW.

[0010] The terminal device TM, the fixed-point camera CAM, the patrol status providing server 100, the optical fiber survey status providing server 200, the satellite survey status providing server 300, the weather status providing server 400, the vehicle driving status providing server 500, and the road disaster response support system 600 communicate via the network NW. The network NW includes, for example, some or all of a WAN (Wide Area Network), a LAN (Local Area Network), the Internet, a provider device, a wireless base station, a dedicated line, a satellite line, and the like. Note that the communication method may be not only via the network NW but also data transfer via a memory card. Also, data may be downloaded and uploaded via the network NW.

[0011] The terminal device TM is used by a user who rides in the vehicle Vh. The terminal device TM is a mobile phone such as a smartphone or a tablet terminal. The terminal device TM may be a communication-type drive recorder or a stationary in-vehicle device mounted on the vehicle Vh, or may be equipped with an image analysis function by AI (artificial intelligence). The terminal device TM incorporates a road patrol application that cooperates with the patrol situation providing server 100. The terminal device TM has a positioning device such as a GPS (Global Positioning System) receiver, a communication device for connecting to the network NW, a G-sensor (acceleration sensor), an input / output device such as a camera and a touch panel, and a processor such as a CPU (Central Processing Unit).

[0012] Figure 2 is a flowchart showing an example of the flow of patrol. The terminal device TM starts collecting position information, acceleration information, video, etc. (S2) by pressing the patrol start button of the road patrol application (S1). After the patrol ends, by pressing the patrol end button of the road patrol application (S3), the terminal device TM transmits the position information, acceleration information, video, etc. to the patrol situation providing server 100 (S4). Based on the measurement information transmitted from the terminal device TM, the patrol situation providing server 100 determines the presence or absence of unevenness on the road surface and specifies the position of the road surface determined to be uneven. Also, based on the transmitted video / images, it determines the damage situation of the road surface and specifies the position of the road surface determined to be a risk location.

[0013] The fixed-point camera CAM is installed on buildings, roadside columns, poles, etc. around locations prone to waterlogging such as roads (expressways, main arterial roads, roads with heavy traffic, main bus routes, roads connecting schools, public facilities, and emergency hospitals, roads along mountains and in mountainous areas), underpasses (under roads that are dug down at intersections), roads along rivers, and roads along the sea. The fixed-point camera CAM is a live camera, web camera, network camera, etc. that can communicate. The fixed-point camera CAM may be a small unmanned aerial vehicle camera such as a communication-type drive recorder or a drone, or may be equipped with an image analysis function by AI (artificial intelligence). The fixed-point camera CAM incorporates a camera app that communicates with the patrol situation providing server 100. The fixed-point camera CAM has a lens, an image sensor, a positioning device such as a GPS (Global Positioning System) receiver, a communication device for connecting to the network NW, and a processor such as a CPU (Central Processing Unit).

[0014] FIG. 3 is a flowchart showing the flow of an example of the fixed-point camera CAM. The fixed-point camera CAM periodically or intermittently collects road conditions (S5), and periodically or intermittently automatically transmits video, position information, date and time information, etc. to the patrol situation providing server 100 (S6). Based on the video and images transmitted from the fixed-point camera CAM, the patrol situation providing server 100 determines the damage condition of the road surface, etc., and identifies the position determined as a risk location.

[0015] The patrol situation providing server 100 provides the patrol situation to the road disaster response support system 600 via the network NW. The provided patrol situation is information for each road, including some or all of those that cause disaster situations and obstacles to vehicle passage, such as road damage, road subsidence, roadbed outflow, roadway collapse, pavement damage, side ditch damage, unevenness of the road surface, liquefaction phenomenon, snow accumulation, snow quality, freezing on the road surface, collapsed buildings, vehicle passing records, power outages, earthquake damage, tsunami damage, typhoon damage, volcanic eruption damage, volcanic activity damage, tornado damage, landslides, rockfalls, earth and sand outflows, slope collapses, tunnel collapses, road shoulder collapses, fallen trees, falling rocks, road washouts, bridge total losses, river breaches, river floods, inundation, thick fog, avalanches, ground blizzards, the presence or absence of accident vehicles and stranded vehicles, etc. FIG. 4 is a diagram showing an example of the patrol situation, and the road damage location 110 is displayed in black on the map.

[0016] The optical fiber survey status providing server 200 utilizes optical fiber sensing technology that uses an optical fiber as a sensor. It receives backscattered light from the communication optical fiber contained in the cable laid on roads or the like, detects a vibration pattern corresponding to the driving status of vehicles on roads or the like based on the backscattered light, and obtains the driving status of vehicles on roads or the like and the surrounding road conditions, etc. from the detected vibration pattern and the learning model (information from a camera or the like connected to the optical fiber may also be used). The optical fiber survey status providing server 200 provides the optical fiber survey status to the road disaster response support system 600 via the network NW. The provided optical fiber survey status is information for each road, including some or all of the vehicle passing records, traffic volume, traffic congestion, sudden stops of vehicles, traffic accidents, snow accumulation on the road surface, collapses in tunnels, accidents, power outages, water leakage / water cut-off, earthquake prediction information, earthquake damage, tsunami damage, typhoon damage, volcanic eruption damage, tornado damage, optical fiber interruption / disconnection locations, etc., disaster situations (including images of the road taken) and obstacles to vehicle passage, etc. FIG. 5 is a diagram showing an example of the optical fiber survey status, and the collapse location 210 in the tunnel is displayed in black on the map.

[0017] The satellite survey status providing server 300 utilizes satellite remote sensing technology observed by artificial satellites equipped with SAR (Synthetic Aperture Radar), optical sensors, microwave sensors, etc. It obtains road conditions, vehicle conditions, etc. from the difference before and after a disaster using the data (scattering intensity values, phase information, polarization information, etc.) and images (optical images, SAR images, etc.) observed by the artificial satellite. Moreover, it may be something that compares and detects road conditions, vehicle conditions, etc. before and after a disaster through AI (artificial intelligence) analysis, or something that detects and detects road conditions, vehicle conditions, etc. during a disaster through AI (artificial intelligence) analysis. The satellite survey status providing server 300 provides the satellite survey status to the road disaster response support system 600 via the network NW. The provided satellite survey status is information for each road, including some or all of the following that may cause disaster situations or impede vehicle passage: collapsed buildings, landslides, earth slumps, earth flows, slope collapses, tunnel collapses, road damage, roadway collapses, shoulder collapses, fallen trees, rockfalls, total bridge damage, river breaches, river floods, inundation, avalanches, vehicle traffic records, land subsidence, power outages, water leakage / water cut-off, earthquake prediction information, earthquake damage, tsunami damage, typhoon damage, volcanic eruption damage, tornado damage, forest damage, crop damage, and the presence or absence of accident vehicles / stalled vehicles, etc. FIG. 6 is a diagram showing an example of the satellite survey status, and the location 310 where a landslide has occurred is shown in black on the map.

[0018] The weather condition providing server 400 provides the weather condition to the road disaster response support system 600 via the network NW. The provided weather condition is information for each region, including some or all of the following: time, weather (sunny / rainy / snowy, etc.), temperature, rainfall, snowfall, snow depth, wind speed, special warnings (heavy rain / storm / high tide / waves / heavy snow / blizzard) and warnings (heavy rain / storm / flood / heavy snow / blizzard, etc.), recorded short-term heavy rain information, landslide disaster warning information, earthquake prediction information, earthquake information, tsunami information, volcanic eruption information, information on volcanic activity, typhoon information, tornado information, disaster situation (including images of the road taken), etc. FIG. 7 is a diagram showing an example of the weather condition, and the warning 410 and seismic intensity 420 are shown in characters and numbers.

[0019] The vehicle driving status providing server 500 utilizes the sensing technology of automobiles and acquires various data such as the vehicle driving status and the surrounding road conditions from vehicles such as connected cars. The vehicle driving status providing server 500 provides the vehicle driving status to the road disaster response support system 600 via the network NW. The provided vehicle driving status is information for each road obtained from vehicles such as private cars, taxis, buses, and trucks (including electric vehicles), including some or all of the following that may cause disaster situations or impede vehicle passage: temperature, sudden braking locations, skidding locations, tire spinning locations, tire locking locations, ABS activation locations, waterlogging locations, power outages, earthquake damage, tsunami damage, typhoon damage, volcanic eruption damage, tornado damage, river flooding, liquefaction phenomena, obstacles on the road, collapsed buildings, landslides, slope collapses, tunnel collapses, total bridge losses, road damage, and identification of impassable areas, obtained from vehicle sensors, etc.; power outages, earthquake damage, tsunami damage, typhoon damage, volcanic eruption damage, tornado damage, river flooding, liquefaction phenomena, obstacles on the road, obtained from camera images, etc.; collapsed buildings, landslides, slope collapses, tunnel collapses, total bridge losses, road damage, and identification of impassable areas, obtained from three-dimensional data, etc.; vehicle passing records (including by regular vehicle and large vehicle types), traffic volume, traffic congestion, passing speed, average speed, acceleration, obtained from probe information (including ETC2.0), etc.; presence or absence of rainfall or snowfall, obtained from the wiper operation status, etc. In addition, data may be acquired by autonomous driving technology (sensing technology for autonomous vehicles), or disaster situations and vehicle obstruction information may be detected by AI (artificial intelligence) analysis. FIG. 8 is a diagram showing an example of the vehicle driving status. Locations 510 where there is no vehicle passing record are displayed in black on the map.

[0020] The information acquisition unit 610 operating in the road disaster response support system 600 acquires the patrol status from the patrol status providing server 100, the optical fiber survey status from the optical fiber survey status providing server 200, the satellite survey status from the satellite survey status providing server 300, the meteorological status from the meteorological status providing server 400, and the vehicle driving status from the vehicle driving status providing server 500 via the network NW. The patrol status provided by the patrol status providing server 100 is stored as patrol information 640. The optical fiber inspection status provided by the optical fiber inspection status providing server 200 is stored as optical fiber inspection information 650. The satellite survey status provided by the satellite survey status providing server 300 is stored as satellite survey information 660. The weather status provided by the weather status providing server 400 is stored as weather information 670. The vehicle driving status provided by the vehicle driving status providing server 500 is stored as vehicle driving information 680. Furthermore, the information acquisition unit 610 may be provided with information regarding the load service status. The information regarding the load service status is information for each road, mainly information managed by load service operators (such as the Japan Automobile Federation) (information by a load service management system, etc.), including rescue requests (date and time, location, rescue content, etc.), rescue requests due to abnormal weather (date and time, location, rescue content, etc.), rescue requests due to disasters (date and time, location, rescue content, etc.), battery run-up, key confinement, gas shortage, flat tire, wheel detachment / falling, flooding / submerging, pulling out from snowy roads / mud, accidents, slippage, disaster / disaster situation (including images of the road taken), towing / conveying of vehicles, removal / towing / conveying of abandoned vehicles, removal / towing / conveying of disaster-stricken vehicles, removal / towing / conveying of accident vehicles, road conditions (including images of the road taken), traffic conditions, EV charging support, vehicle inspection results, etc., and may include some or all of them. The load service status is stored as load service information. Note that the information acquired by the information acquisition unit 610 may be only part of the information on patrol status, optical fiber inspection status, satellite survey status, weather status, vehicle driving status, and load service status.

[0021] The analysis unit 620 operating in the road disaster response support system 600 analyzes the patrol information 640, optical fiber inspection information 650, satellite survey information 660, weather information 670, and vehicle driving information 680 obtained from the information acquired by the information acquisition unit 610 for each piece of information, and stores the analysis results as analysis results 690. The stored analysis results 690 can be confirmed by map display, list display, etc. Further, the analysis unit 620 may also analyze the load service information. Furthermore, the analysis unit 620 may be provided with an analysis function and an analytical function using AI (artificial intelligence). An example of AI (artificial intelligence) is as follows. By inputting the image data of the analysis target of the road captured from each information (patrol information, optical fiber survey information, satellite survey information, weather information, vehicle running information, load service information) acquired by the information acquisition unit into the image data of the learning target where the road was captured and the learning model in which the disaster situation of the road was machine-learned using the learning data, the road disaster situation is output, and based on the measurement data (date and time, address, latitude and longitude, seismic intensity, weather data, landslide disaster data, each sensing data, acceleration, vibration, vehicle data, probe data, three-dimensional data, etc.) included in each information, the severity of the road disaster situation (earthquakes with a seismic intensity of less than 6, wide-area disasters such as floods, snow disasters, volcanic activities, landslides, etc.) is analyzed, and based on the analyzed result, the information acquired by the information acquisition unit is complemented and corrected. A road disaster response support system characterized by this. By inputting the image data of the analysis target of the road captured from each acquired information (patrol information, optical fiber survey information, satellite survey information, weather information, vehicle running information, load service information) into the image data of the learning target where the road was captured and the learning model in which the disaster situation of the road was machine-learned using the learning data, the road disaster situation is output, and based on the measurement data (date and time, address, latitude and longitude, seismic intensity, weather data, landslide disaster data, each sensing data, acceleration, vibration, vehicle data, probe data, three-dimensional data, etc.) included in each information, the severity of the road disaster situation (earthquakes with a seismic intensity of less than 6, wide-area disasters such as floods, snow disasters, volcanic activities, landslides, etc.) is analyzed, and based on the analyzed result, the acquired information is complemented and corrected. A road management method characterized by this. Note that the information analyzed by the analysis unit 620 may also be only a part of the information among the patrol information 640, optical fiber survey information 650, satellite survey information 660, weather information 670, vehicle running information 680, and load service information.

[0022] The determination unit 630 operating in the road disaster response support system 600 comprehensively determines the necessity for road disaster response from part or all of the analysis results 690 for each piece of information (which may include road service information) analyzed by the analysis unit 620, and stores it as the judgment result 695. The stored judgment result 695 can be confirmed through map display, list display, etc. Also, the determination unit 630 may be equipped with an analysis function, judgment function, and decision function using AI (artificial intelligence). Furthermore, the road disaster response support system 600 may be provided with an information providing unit that provides part or all of the analysis results 690, judgment results 695, etc. to the outside. By providing the information providing unit, the effect of widely publicizing public awareness and other aspects of road disaster response can be obtained.

[0023] Figure 9 is a flowchart showing an example of the flow of the road disaster response support system 600. The information acquisition unit 610 periodically (for example, every few [min]) acquires the patrol situation from the patrol situation providing server 100 (S10). The information acquisition unit 610 periodically (for example, every few [min]) acquires the optical fiber survey situation from the optical fiber survey situation providing server 200 (S11). The information acquisition unit 610 periodically (for example, every few [min]) acquires the satellite survey situation from the satellite survey situation providing server 300 (S12). The information acquisition unit 610 periodically (for example, every few [min]) acquires the weather situation from the weather situation providing server 400 (S13). The information acquisition unit 610 periodically (for example, every few [min]) acquires the vehicle driving situation from the vehicle driving situation providing server 500 (S14). Then, the analysis unit 620 extracts road damage locations, etc. from the patrol information 640 (S15). The analysis unit 620 extracts traffic performance, etc. from the optical fiber survey information 650 (S16). The analysis unit 620 extracts locations where landslides have occurred, etc. from the satellite survey information 660 (S17). The analysis unit 620 extracts earthquake and tsunami information, etc. from the weather information 670 (S18). The analysis unit 620 extracts areas where driving is impossible, etc. from the vehicle driving information 680 (S19). Next, based on the results of the above analysis, the determination unit 630 comprehensively determines the necessity for road disaster response (S20). Furthermore, information from road users and residents (disaster information, damage information, rescue information, restoration information, etc.) using SNS (Social Networking Service), as well as information from the government (police, fire department, Self-Defense Forces, etc.), infrastructure providers (communications, electricity, gas, water supply, sewerage, etc.), transportation providers (railways, buses, ferries, airplanes, etc.), construction and civil engineering companies (including construction industry associations), delivery companies, tourism companies (hotels, inns, tourist facilities, road stations, etc.), and designated public institutions (Disaster Countermeasures Basic Law) (disaster information, damage information, rescue information, restoration information, etc.), and information from the government's extraordinary disaster countermeasures headquarters and emergency disaster countermeasures headquarters may be provided to the road disaster response support system 600.

[0024] FIG. 10 is a diagram showing an example of the judgment criteria in the determination unit 630. When a tsunami occurs (1 element) 631, when a landslide occurs and the optical fiber is disconnected (2 elements) 632, when there is road damage and collapsed buildings and there is no vehicle traffic record (3 elements) 633, when a heavy rain warning is issued and the tires spin due to landslide and the vehicle cannot move forward and the traffic congestion is severe (4 elements) 634, when a heavy snow warning is issued and there is snow accumulation on the road surface and the ABS is activated and the traffic congestion is severe and there are a large number of parked vehicles (5 elements) 635, etc., the determination unit 630 makes a determination on road disaster response. Furthermore, for some or all of the judgment result 695 determined by the determination unit 630, the analysis result 690, and each piece of information (patrol information, optical fiber survey information, satellite survey information, weather information, vehicle driving information, road service information, etc.) acquired by the information acquisition unit, through the information providing unit (described in paragraph 0022), etc., there may be provided a mail notification function to road administrators, a data providing function to a road information board system, a data providing function to a road restoration visualization map (a map that unifies and displays on a web map, etc., the road restoration status, main disaster-stricken locations, disaster situation, road traffic restrictions, intercity travel time, vehicle speed data, vehicle passing records, population mesh data, etc.), a data providing function to a car navigation system, a data providing function to an autonomous driving system, a data providing function to MaaS (Mobility as a Service), an information providing function to the administration (police, fire department, Self-Defense Forces, etc.) and the mass media, and an information disclosure function to road users and residents (such as a homepage or a smartphone app) (it is not necessarily required to go through the information providing unit). An example of the information disclosure function to road users and residents is as follows. One or more pieces of information acquired by the information acquisition unit, or the result analyzed by the analysis unit, or the necessity of road disaster response determined by the determination unit, or the implementation plan of road opening formulated by the road opening unit (described in paragraph 0029), or the restoration status by the robotics unit (described in paragraph 0030), or the prediction of the necessity of road disaster response by the prediction unit (described in paragraph 0026), etc. are transmitted to a mobile terminal device (mobile phone, smartphone, tablet terminal, notebook personal computer, game machine, etc.) or a fixed terminal device (desktop computer, smart TV, set-top box, digital signage, kiosk terminal, car navigation, car display audio, etc.). A road disaster response support system characterized by this.

[0025] The road disaster response support system 600 may be provided with an improvement unit that improves part or all of the analysis result 690, the judgment result 695, the judgment criteria in the decision unit 630 (an example of the judgment criteria is described in FIG. 10), etc. It can be improved by importing various data (data, images) related to disasters, etc. into the road disaster response support system 600, and the effect of improving the accuracy of road disaster response can be obtained by providing the improvement unit. An example of the process is as follows. Input various data (data, images) related to disasters, etc. into the improvement unit → Refer to the history of the analysis result 690, the judgment result 695, etc. → Analysis, analysis, etc. by the improvement unit → Improvement result by the improvement unit → Feedback (review of accuracy improvement, etc.). The various data include, for example, hypothesis data, verification data, sample data, teacher data, past data, current data, future data (future data related to large-scale disasters that occur once in several decades or not at all, data related to large-scale disasters that may occur in the future, data related to large-scale disasters that humanity has never experienced before, etc.). Also, the improvement unit may be provided with an analysis function, an analysis function, and an improvement function by AI (artificial intelligence). An example of AI (artificial intelligence) is as follows. The image data of the analysis target of the road taken from each information (patrol information, optical fiber survey information, satellite survey information, meteorological information, vehicle running information, road service information) acquired by the information acquisition unit is input into the learning target image data of the road taken and the learning model in which the disaster situation of the road is machine-learned by the learning data, and the road disaster situation is output. Based on the measurement data (date and time, address, latitude and longitude, seismic intensity, meteorological data, landslide disaster data, each sensing data, acceleration, vibration, vehicle data, probe data, three-dimensional data, etc.) included in each information, the output road disaster situation is complemented and corrected, and the road disaster response support system is characterized by being provided with an improvement unit that improves the result analyzed by the analysis unit, the judgment criteria in the decision unit, or the result determined by the decision unit. The image data of the road to be analyzed, which is captured from each piece of acquired information (patrol information, optical fiber survey information, satellite survey information, meteorological information, vehicle driving information, road service information), is input into the learning model in which the machine learning is performed on the learning target image data of the road where the road is captured and the disaster situation of the road by the learning data, and the road disaster situation is output. Based on the measurement data (date and time, address, latitude and longitude, seismic intensity, meteorological data, landslide disaster data, each sensing data, acceleration, vibration, vehicle data, probe data, three-dimensional data, etc.) included in each piece of information, the output road disaster situation is complemented and corrected to improve the analyzed result, judgment criterion, or determined result. A road management method characterized by this.

[0026] The road disaster response support system 600 may include a prediction unit that predicts the necessity of road disaster response by referring to the history such as the analysis result 690 and the judgment result 695. By providing the road disaster response support system 600 with a prediction unit, the effect of being able to prepare, plan, and train for road disaster response in advance can be obtained. An example of the flow is as follows. Input various data (data, images, etc.) related to disasters into the prediction unit → Refer to the history such as the analysis result 690 and the judgment result 695 → Analysis and analysis by the prediction unit → Prediction result by the prediction unit → Action (planning, training, etc.). The various data include, for example, hypothesis data, verification data, sample data, teacher data, past data, current data, future data (future data related to large-scale disasters that occur once in several decades or not at all, data related to large-scale disasters that may occur in the future, data related to large-scale disasters that humanity has never experienced so far), and the like. Also, the prediction unit may be equipped with an analysis function, an analysis function, and a prediction function by AI (artificial intelligence).

[0027] The road disaster response support system 600 can exert its effect with one or more elements among the patrol situation, optical fiber survey situation, satellite survey situation, meteorological situation, vehicle driving situation, and road service situation. Furthermore, by having two or more elements, a synergistic effect can be obtained. As one specific example, a wide range of information (changes in wide-area infrastructure and transportation networks) is obtained through satellite survey status (satellite remote sensing technology), and local information (local changes in road facilities and roads, etc.) is obtained through optical fiber survey status (optical fiber sensing technology), enabling both wide-area and local monitoring. Next, by adding vehicle driving status (automobile sensing technology), diverse and advanced road and surrounding conditions can be grasped, maximizing the advantages of each other and obtaining a synergistic effect. And, by being able to quickly carry out road disaster response (grasping the overall situation, issuing system orders, commanding restoration, public notification, etc.), disasters can be minimized, and emergency restoration, emergency restoration, and full restoration according to the disaster situation become possible, and early recovery of the disaster-stricken area can be expected.

[0028] The road disaster response support system 600 may be the embodiment described below. By the analysis unit judging the severity of the road disaster (earthquakes with a seismic intensity of less than 6, wide-area disasters such as floods, snow disasters, volcanic activities, landslides, etc.), the effect can be obtained that while suppressing the cost of the system, a rapid response according to the road disaster situation becomes possible. An information acquisition unit that acquires information regarding weather conditions and information regarding patrol status, an analysis unit that analyzes the weather conditions and patrol status obtained from the information acquired by the information acquisition unit, and a determination unit that determines the necessity of road disaster response from the results analyzed by the analysis unit. The determination unit determines the necessity of road disaster response, the analysis unit judges the severity of the road disaster from the results analyzed, and when the road disaster is severe, among the information regarding vehicle driving status, information regarding optical fiber survey status, information regarding satellite survey status, and information regarding road service status, one or more pieces of information are acquired by the information acquisition unit, the acquired one or more pieces of information are analyzed by the analysis unit, and the determination unit determines the necessity of road disaster response from the analyzed results. A road disaster response support system characterized by this. A road management method using a computer, wherein the computer acquires information on weather conditions and information on patrol conditions via a network, analyzes the weather conditions and the patrol conditions obtained from the acquired information, determines the necessity for road disaster response from the analyzed results, judges the severity of the road disaster from the analyzed results, and when the road disaster is severe, acquires, via the network, one or more pieces of information among information on vehicle driving conditions, information on optical fiber survey conditions, information on satellite survey conditions, and information on road service conditions, analyzes using the acquired one or more pieces of information, and determines the necessity for road disaster response from the analyzed results.

[0029] The road disaster response support system 600 may include a road opening department that registers a pre-established road opening plan and formulates an implementation plan for road opening. By providing the road disaster response support system 600 with a road opening department, an effect can be obtained in which road opening can be performed promptly during a disaster. In normal disasters, the process is emergency restoration → full restoration, but in large-scale disasters, etc., it is necessary to perform emergency restoration (road opening) before emergency restoration. Road opening means quickly performing minimum rubble removal, etc., and opening a rescue route by means of simple step repair, etc., for the passage of emergency vehicles, etc. for life-saving and rescue activities, emergency material support, and restoration. Road managers formulate a road opening plan in advance, and a road opening base (a disaster prevention base such as a base for support troops, a gathering place for materials and equipment), a road opening route (a wide-area movement route, an access route, a route within the disaster area), a timeline (a specific action plan), etc. are planned. In road opening, confirmation of the disaster situation, secondary disaster risk assessment, emergency measures immediately after the disaster occurrence (traffic control, etc.), formulation of an implementation plan for road opening (including calculation of the optimal route), and road opening work are carried out. An example embodiment of the road opening department in the road disaster response support system 600 is as follows. Register the pre-determined road opening plan with the road opening department (it doesn't matter whether it is registered before or after the disaster), and the road opening department shall formulate the implementation plan for road opening based on the road opening plan registered with the road opening department and two or more pieces of information obtained by the information acquisition department or the results analyzed by the analysis department. A road disaster response support system (including a road management method) characterized by this. In addition, the road opening department may be equipped with analysis functions, analysis functions, and planning functions by AI (artificial intelligence). An example of AI (artificial intelligence) is as follows. Input the image data of the analysis target of the road taken from each piece of information (patrol information, optical fiber survey information, satellite survey information, meteorological information, vehicle traffic information, road service information) obtained by the information acquisition department into the image data of the learning target of the road and the learning model in which machine learning is performed on the disaster situation of the road by the learning data, output the road disaster situation, and based on the measurement data (date and time, address, latitude and longitude, seismic intensity, meteorological data, landslide disaster data, each sensing data, acceleration, vibration, vehicle data, probe data, three-dimensional data, etc.) included in each piece of information, complement and correct the output road disaster situation. When road disaster response is required, register the pre-determined road opening plan with the road opening department, and the road opening department shall formulate the implementation plan for road opening based on the road opening plan registered with the road opening department and two or more pieces of information obtained by the information acquisition department or the results analyzed by the analysis department or the complemented and corrected road disaster situation. A road disaster response support system characterized by this. Analyze the image data of the road captured from each piece of acquired information (patrol information, optical fiber survey information, satellite survey information, meteorological information, vehicle driving information, road service information) as the image data of the learning target where the road was captured, and input it into the learning model in which the machine learning is performed on the disaster situation of the road using the learning data, so as to output the road disaster situation. Based on the measurement data (date and time, address, latitude and longitude, seismic intensity, meteorological data, landslide disaster data, each sensing data, acceleration, vibration, vehicle data, probe data, three-dimensional data, etc.) included in each piece of information, complement and correct the output road disaster situation. When road disaster response is required, register the pre-established road opening plan in advance, and perform the implementation plan of road opening from the registered road opening plan and two or more pieces of information acquired by the information acquisition unit or the analyzed results or the complemented and corrected road disaster situation. A road management method characterized by this. In addition, it is also possible to formulate the implementation plan of road opening by the road opening department from the information acquired by the robotics department (described in paragraph 0030) for the pre-established road opening plan (the road opening plan registered in the road opening department).

[0030] The road disaster response support system 600 may include a robotics department in which a robot (mainly a disaster response robot) performs road opening work using AI (artificial intelligence) and robotics technology. Calculate which roads should be opened preferentially through optimal route analysis by AI (artificial intelligence), and use robotics technology for the robot to perform road opening work. In the road opening work, the pre-established road opening plan registered in the road opening department or the implementation plan of road opening formulated by the road opening department, the information acquired by the robotics department (disaster, damage situation, meteorological situation, road situation, traffic situation, impassable situation, rescue situation, recovery situation, obstacle information, terrain information, progress information of road opening, latest on-site information, etc.), etc., perform optimal route analysis by AI (artificial intelligence), etc. (The robot does not necessarily have to be an autonomous robot). The robotics section can achieve the following effects. By utilizing autonomous robots and the like, rapid operations can be carried out without relying on human hands. Also, by performing autonomous operations with robots, the dispatch of workers to dangerous areas can be minimized. Furthermore, through the cooperation of large heavy machinery, small robots, drones, etc., efficient obstacle removal and the like become possible. An example embodiment of the robotics section in the road disaster response support system 600 is as follows (each robot is connected to the network NW). A road opening plan (road opening plan registered in the road opening section) or an implementation plan for road opening, using artificial intelligence analysis and robotics technology, is characterized in that a disaster response robot (large heavy machinery, autonomous driving heavy machinery, small robot, humanoid robot, quadruped walking robot, snake robot, multi-legged robot, mole robot, transformable robot, multi-joint robot, crawler robot, autonomous excavation robot, small unmanned flying robot, underwater exploration robot, rescue robot, etc.) performs road opening work by the robotics section in a road disaster response support system (including a road management method). An example of robotics technology (including disaster response robots) is as follows. Autonomous driving heavy machinery (such as bulldozers and excavators) is remotely or autonomously controlled to perform obstacle removal, step repair, etc. It cooperates with radio-controlled rubble removal robots, etc. to remove small-scale rubble. Quadruped walking robots or drones, etc. are utilized to support the reconnaissance of the disaster area and the lightweight removal of obstacles. Furthermore, the progress of road opening is analyzed in real time by AI (artificial intelligence), and the optimal work instructions for the robots are automatically adjusted. In addition, a plurality of different robots (autonomous driving heavy machinery, small robots, drones, etc.) are integrally controlled to perform optimal work distribution. An example of AI (Artificial Intelligence) is as follows. Calculation of road opening routes and determination of priorities (Dijkstra's algorithm, reinforcement learning, multi-agent, etc.) by route optimization AI. Identification of obstacles by drone-robot sensors and generation of 3D maps (convolutional neural networks, PointNet, etc.) by image recognition AI. Control of autonomous driving heavy machinery, cooperative work of small robots, automatic obstacle avoidance and path planning (imitation learning, reinforcement learning, deep reinforcement learning, multi-agent, Simultaneous Localization and Mapping, etc.) by robotics control AI. Dynamic route update AI (machine learning, Long Short-Term Memory, etc.), work monitoring by AI (convolutional neural networks, Long Short-Term Memory, Transformer, etc.). An example of input data and output data in robotics technology and AI (Artificial Intelligence) analysis is as follows. Route optimization AI: Input data (road network data, obstacle data, real-time traffic data, priority route information, weather and land number data, etc.) → Output data (optimal road opening route, emergency passage route, work instruction list, etc.). Image recognition AI: Input data (drone video, LiDAR point cloud data, past disaster data, etc.) → Output data (obstacle map, determination of obstacle types, work priority map, etc.). Robotics control AI: Input data (work area map, obstacle information, robot state data, terrain data, etc.) → Output data (robot work plan, movement route instruction, obstacle removal operation, etc.). Work monitoring AI: Input data (work video data, robot work log, weather information, etc.) → Output data (progress report, anomaly detection alert, work optimization instruction, etc.). By leveraging large language models, it is possible to continuously enhance road opening plans, road opening implementation plans, and road opening operations regardless of the language. In particular, it is effective for understanding pre-established road opening plans, learning disaster countermeasures using vast amounts of data on the Internet, and making real-time decisions for disaster response. An example of leveraging large language models is as follows: complementing and optimizing road opening plans and road opening implementation plans, learning global disaster countermeasure data on the Internet, providing real-time support for robots, and making real-time use of disaster data.

[0031] The road disaster response support system 600 continuously monitors disasters, damage, and recovery situations, updates each piece of information in real time, and re-updates at regular intervals using the latest data and information.

[0032] <Hardware Configuration> Figure 11 shows an example of the hardware configuration of the terminal device TM, fixed-point camera CAM, and patrol situation providing server 100, optical fiber survey situation providing server 200, satellite survey situation providing server 300, weather situation providing server 400, vehicle driving situation providing server 500, and road disaster response support system 600. This figure shows an example where the terminal device TM is a mobile phone such as a smartphone. The terminal device TM has a configuration in which, for example, a CPU 701, a RAM 702, a ROM 703, a secondary storage device 704 such as a flash memory, a touch panel 705, and a wireless communication module 706 are interconnected by an internal bus or a dedicated communication line. Application programs such as a road patrol app are downloaded via the network NW and stored in the secondary storage device 704. The fixed-point camera CAM has a configuration in which, for example, a CPU 901, a RAM 902, a ROM 903, a secondary storage device 904 such as a flash memory, a lens / image sensor 905, and a communication device 906 are interconnected by an internal bus or a dedicated communication line. Application programs such as a camera app are downloaded via the network NW and stored in the secondary storage device 904. Each server has a configuration in which, for example, a NIC 801, a CPU 802, a RAM 803, a ROM 804, a secondary storage device 805 such as a flash memory or an HDD, and a drive device 806 are interconnected by an internal bus or a dedicated communication line. A portable storage medium such as an optical disk is mounted on the drive device 806. A program stored in the secondary storage device 805 or the portable storage medium mounted on the drive device 806 is expanded into the RAM 803 by a DMA controller (not shown) or the like and executed by the CPU 802, thereby realizing the functional units of each server. The patrol information 640, the optical fiber survey information 650, the satellite survey information 660, the weather information 670, the vehicle running information 680, the analysis result 690, and the judgment result 695 are stored in the secondary storage device 805. Note that each server may be a cloud computing system.

[0033] As described above, the embodiments for implementing the present invention have been described using the embodiments. However, the present invention is not limited to such embodiments, and various modifications and substitutions can be made without departing from the gist of the present invention.

Explanation of Reference Numerals

[0034] 100: Patrol Situation Providing Server 200: Optical Fiber Survey Situation Providing Server 300: Satellite Survey Situation Providing Server 400: Weather Situation Providing Server 500: Vehicle Running Situation Providing Server 600: Road Disaster Response Support System 610: Information Acquisition Unit 620: Analysis Unit 630: Decision Unit 640: Patrol Information 650: Optical Fiber Survey Information 660: Satellite Survey Information 670: Weather Information 680: Vehicle Running Information 690: Analysis Result 695: Judgment Result

Claims

1. an information acquisition unit that acquires information related to weather conditions and information related to patrol situations; an analysis unit that analyzes the weather conditions and the patrol conditions obtained from the information acquired by the information acquisition unit; A decision unit that decides the necessity of road disaster response based on the results of the analysis by the analysis unit; a road clearance department that registers road clearance plans that have been formulated in advance and formulates implementation plans for road clearance; The determination unit determines the need for road disaster response, The severity of the road disaster is judged from the results of the analysis by the analysis unit, and if the road disaster is severe due to an earthquake of seismic intensity 6 or more or a wide-area disaster, one or more pieces of information among information on vehicle driving conditions, information on optical fiber survey conditions, information on satellite survey conditions, and information on road service conditions are acquired by the information acquisition unit, the acquired one or more pieces of information are analyzed by the analysis unit, and the necessity of road disaster response is determined by the decision unit from the analysis results, A road disaster response support system characterized in that, when a road disaster response is required, the road opening plan formulated in advance is registered in the road opening unit, and an implementation plan for the road opening is made in the road opening unit based on the road opening plan registered in the road opening unit and two or more pieces of information acquired by the information acquisition unit or the results of analysis by the analysis unit.

2. 2. The system of claim 1, The facility will have a robotics department where disaster response robots will carry out road clearance work using artificial intelligence analysis and robotics technology. A road disaster response support system characterized in that, based on the road clearance implementation plan or the road clearance plan, the disaster response robot performs road clearance work using the analysis by the artificial intelligence and the robotics technology through the robotics department.

3. A program for causing a computer to function as the road disaster response support system according to claim 1 or 2.

4. A road management method using a computer, comprising: The computer acquires information regarding weather conditions and information regarding patrol situations via a network, Analyzing the weather conditions and patrol conditions obtained from the acquired information, Based on the analyzed results, the need for road disaster response will be determined, The severity of the road disaster is judged from the results of the analysis, and if the road disaster is severe due to an earthquake of seismic intensity 6 or more or a wide-area disaster, one or more pieces of information regarding vehicle driving conditions, optical fiber survey conditions, satellite survey conditions, and road service conditions are acquired via the network, and the acquired one or more pieces of information are analyzed, and the necessity of road disaster response is determined from the analysis results; A road management method characterized in that, when a road disaster response is required, a road opening plan prepared in advance is registered, and an implementation plan for road opening is made based on the registered road opening plan and the two or more pieces of information acquired or the analyzed results.

5. The road management method according to claim 4, A road management method characterized in that a disaster response robot performs road clearance work via a network using artificial intelligence analysis and robotics technology based on the road clearance implementation plan or the road clearance plan.

6. The road management method according to claim 4 or 5, A road management method characterized by using a large-scale language model to collect data on the Internet and learn disaster prevention measures regardless of language type, thereby continuously improving the road clearance plan, the road clearance implementation plan, or the road clearance work.

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