US-12619253-B2 - Unmanned vehicle management system and unmanned vehicle management method

US12619253B2US 12619253 B2US12619253 B2US 12619253B2US-12619253-B2

Abstract

An unmanned vehicle management system according to an aspect includes: a collection unit configured to collect video data acquired by an unmanned vehicle and natural disaster data related to natural disasters from information sources; a storage unit configured to store the video data and the natural disaster data; an analysis unit configured to extract feature amounts of the video data and the natural disaster data, and predict a high-risk area where a risk of natural disaster occurrence is higher than in other areas; a prediction unit configured to compare the video data and the natural disaster data collected during a disaster with the video data and the natural disaster data collected during normal times, and predict a disaster occurrence area where a disaster will occur; and a deployment unit configured to determine deployment of the unmanned vehicle and a rescuer based on the high-risk area and the disaster occurrence area.

Inventors

Yoshiaki Konishi

Assignees

MITSUBISHI ELECTRIC CORPORATION

Dates

Publication Date: 20260505
Application Date: 20240214

Claims (17)

1 . An unmanned vehicle management system comprising: a data collection device configured to collect video data acquired by an unmanned vehicle and natural disaster data in a monitored area acquired by information sources including at least one of a satellite device, a weather radar device, and a sensor device deployed in the monitored area; a data storage device configured to store the video data and the natural disaster data; an data analysis device configured to extract a feature value of the video data and extract a feature value of the natural disaster data, and predict a high-risk area where a risk of natural disaster occurrence is higher than in other areas based on the extracted feature value of the video data and the extracted feature value of the natural disaster data; a disaster prediction device configured to compare the video data and the natural disaster data collected during a disaster with the video data and the natural disaster data collected during normal times, and predict a disaster occurrence area where a disaster might occur; and an unmanned vehicle control device configured to determine deployment of the unmanned vehicle and a rescuer based on the high-risk area and the disaster occurrence area.
2 . The unmanned vehicle management system according to claim 1 , wherein the unmanned vehicle control device is configured to, when a disaster occurs, determine to deploy the unmanned vehicle and the rescuer in the high-risk area and the disaster occurrence area.
3 . The unmanned vehicle management system according to claim 1 , wherein the data collection device is configured to collect residential area data regarding an area where a resident is present, the data storage device is configured to store the residential area data, and the unmanned vehicle control device is configured to, when a disaster occurs, determine to deploy the unmanned vehicle and the rescuer in the disaster occurrence area where the resident is present.
4 . The unmanned vehicle management system according to claim 1 , wherein the data storage device is configured to store information indicating a rescue area where a disaster victim has been rescued in the past, and the unmanned vehicle control device is configured to determine to preferentially deploy the unmanned vehicle and the rescuer in the rescue area.
5 . The unmanned vehicle management system according to claim 1 , wherein the unmanned vehicle control device is configured to determine to deploy a first unmanned vehicle in an area where the rescuer has been deployed, deploy a second unmanned vehicle on an evacuation route from the area where the rescuer has been deployed to an evacuation site, and p 2 deploy a third unmanned vehicle in an area where a secondary disaster is expected to occur around the area where the rescuer has been deployed, and the disaster prediction device is configured to predict an occurrence of a disaster based on video data acquired by the first unmanned vehicle, predict an occurrence of a disaster on the evacuation route based on video data acquired by the second unmanned vehicle, and predict an occurrence of a secondary disaster based on video data acquired by the third unmanned vehicle.
6 . The unmanned vehicle management system according to claim 5 , comprising: an information provision device configured to be worn by the rescuer, wherein the information provision device is configured to, based on a direction in which the rescuer is looking, switch information based on the video data acquired by the first unmanned vehicle, information based on the video data acquired by the second unmanned vehicle, and information based on the video data acquired by the third unmanned vehicle, and superimpose the switched information onto a video or scenery.
7 . The unmanned vehicle management system according to claim 1 , wherein the unmanned vehicle control device is configured to determine to deploy a plurality of unmanned vehicles in each of the high-risk area and the disaster occurrence area, the plurality of unmanned vehicles are configured to acquire an amount of moisture in a ground using an optical sensor, while moving in parallel.
8 . The unmanned vehicle management system according to claim 1 , wherein the unmanned vehicle control device is configured to determine to deploy in the high-risk area, the disaster occurrence area, or a residential area where a resident is present, a fourth unmanned vehicle having a relay function to relay a signal from a base station fixedly installed, and the unmanned vehicle deployed in the high-risk area, the disaster occurrence area, or the residential area is configured to transmit video data to the base station via the fourth unmanned vehicle.
9 . An unmanned vehicle management method comprising: collecting video data acquired by an unmanned vehicle and natural disaster data in a monitored area acquired by information sources including at least one of a satellite device, a weather radar device, and a sensor device deployed in the monitored area; storing the video data and the natural disaster data; extracting a feature value of the video data and extracting a feature value of the natural disaster data, and predicting a high-risk area where a risk of natural disaster occurrence is higher than in other areas based on the extracted feature value of the video data and the extracted feature value of the natural disaster data; comparing the video data and the natural disaster data collected during a disaster with the video data and the natural disaster data collected during normal times, and predicting a disaster occurrence area where a disaster might occur; and determining deployment of the unmanned vehicle and a rescuer based on the high-risk area and the disaster occurrence area.
10 . The unmanned vehicle management method according to claim 9 , further comprising: when a disaster occurs, determining to deploy the unmanned vehicle and the rescuer in the high-risk area and the disaster occurrence area.
11 . The unmanned vehicle management method according to claim 9 , further comprising: collecting residential area data regarding an area where a resident is present; storing the residential area data; and when a disaster occurs, determining to deploy the unmanned vehicle and the rescuer in the disaster occurrence area where the resident is present.
12 . The unmanned vehicle management method according to claim 9 , further comprising: storing information indicating a rescue area where a disaster victim has been rescued in the past; and determining to deploy the unmanned vehicle and the rescuer in the rescue area.
13 . The unmanned vehicle management method according to claim 9 , further comprising: deploying a first unmanned vehicle in an area where the rescuer has been deployed; deploying a second unmanned vehicle on an evacuation route from the area where the rescuer has been deployed to an evacuation site; deploying a third unmanned vehicle in an area where a secondary disaster is expected to occur around the area where the rescuer has been deployed; predicting an occurrence of a disaster based on video data acquired by the first unmanned vehicle; predicting an occurrence of a disaster on the evacuation route based on video data acquired by the second unmanned vehicle; and predicting an occurrence of a secondary disaster based on video data acquired by the third unmanned vehicle.
14 . The unmanned vehicle management method according to claim 13 , further comprising: based on a direction in which the rescuer is looking, switching information based on the video data acquired by the first unmanned vehicle, information based on the video data acquired by the second unmanned vehicle, and information based on the video data acquired by the third unmanned vehicle, and superimposing the switched information onto a video or scenery.
15 . The unmanned vehicle management method according to claim 9 , further comprising: determining to deploy a plurality of unmanned vehicles in each of the high-risk area and the disaster occurrence area; and acquiring, by the plurality of unmanned vehicles, an amount of moisture in a ground using an optical sensor, while the plurality of unmanned vehicle are moving in parallel.
16 . The unmanned vehicle management method according to claim 9 , further comprising: determining to deploy in the high-risk area, the disaster occurrence area, or a residential area where a resident is present, a fourth unmanned vehicle having a relay function to relay a signal from a base station fixedly installed, and transmitting video data from the unmanned vehicle deployed in the high-risk area, the disaster occurrence area, or the residential area to the base station via the fourth unmanned vehicle.
17 . An unmanned vehicle management system comprising: an data analysis device configured to extract a feature value of video data acquired by an unmanned vehicle and a feature value of natural disaster data in a monitored area acquired by information sources including at least one of a satellite device, a weather radar device, and a sensor device deployed in the monitored area, and predict a high-risk area where a risk of disaster occurrence is higher than in other areas based on the extracted feature value of the video data and the extracted feature value of the natural disaster data; a disaster prediction device configured to compare the natural disaster data and the video data collected during a disaster with the natural disaster data and the video data collected during normal times, and predict a disaster occurrence area where a disaster might occur; and an unmanned vehicle control device configured to determine deployment of an unmanned vehicle and a rescuer based on of the high-risk area and the disaster occurrence area.

Description

This application is a U.S. continuation application of International Application No. PCT/JP2022/016613, filed on Mar. 31, 2022, the contents of which are incorporated herein by reference. TECHNICAL FIELD The present disclosure relates to an unmanned vehicle management system and an unmanned vehicle management method. BACKGROUND ART Conventionally, techniques for using unmanned vehicles for the purpose of understanding disaster situations, for example, have been known. For example, a disaster activity support system described in Patent Document 1 supports disaster activities using mobile objects by communicating information with a terminal mounted on a mobile object that moves to a site and performs disaster activities when a disaster occurs. The disaster activity support system collects from the terminal local information acquired by the mobile object, calculates an activity point of the mobile object and a travel route from the current location to the activity point, based on the local information and map information, and transmits a result of the calculation to the terminal as instruction information. A system described in Patent Document 2 is a system for inspecting water facilities that are difficult for workers to reach, and the system transmits an operation control signal generated by a control device to a drone and displays data acquired by the drone. An information processing device described in Patent Document 3 combines a plurality of first captured images captured by a plurality of flying objects, and controls the flight of the plurality of flying objects based on an operation for changing a first image range that is the image range of the composite image. PRIOR ART DOCUMENTS Patent Documents [Patent Document 1] Japanese Patent Application Publication No. 2013-134663 [Patent Document 2] Japanese Patent Application Publication No. 2021-64878 [Patent Document 3] Japanese Patent Application Publication No. 2019-115012 SUMMARY OF THE INVENTION Problems to be Solved by the Invention In order to avoid or reduce disasters during natural disasters, for example, it is necessary to appropriately deploy unmanned vehicles and rescuers in areas with high disaster risk. However, Patent Documents 1 to 3 do not describe appropriate deployment of unmanned vehicles and rescuers. The present disclosure has been made to solve the above-described problems, and has an object to provide an unmanned vehicle management system, an unmanned vehicle management method, a data storage device, a data analysis device, a disaster prediction device, an unmanned vehicle control device, and an information provision device, which can appropriately deploy unmanned vehicles and rescuers during a disaster. Means for Solving the Problems An unmanned vehicle management system according to a first aspect includes: a collection unit configured to collect video data acquired by an unmanned vehicle and natural disaster data related to natural disasters from information sources; a storage unit configured to store the video data and the natural disaster data collected by the collection unit; an analysis unit configured to extract feature amounts of the video data and the natural disaster data collected by the collection unit, and predict a high-risk area where a risk of natural disaster occurrence is higher than in other areas; a prediction unit configured to compare the video data and the natural disaster data collected during a disaster with the video data and the natural disaster data collected during normal times, and predict a disaster occurrence area where a disaster will occur; and a deployment unit configured to determine deployment of the unmanned vehicle and a rescuer based on the high-risk area and the disaster occurrence area. An unmanned vehicle management method according to a second aspect includes: a step of collecting video data acquired by an unmanned vehicle and natural disaster data related to natural disasters from information sources; a step of storing the video data and the natural disaster data; a step of extracting feature amounts of the video data and the natural disaster data, and predicting a high-risk area where a risk of natural disaster occurrence is higher than in other areas; a step of comparing the video data and the natural disaster data collected during a disaster with the video data and the natural disaster data collected during normal times, and predicting a disaster occurrence area where a disaster will occur; and a step of determining deployment of the unmanned vehicle and a rescuer based on the high-risk area and the disaster occurrence area. A data storage device according to a third aspect is a data storage device in an unmanned vehicle management system. The unmanned vehicle management system includes: a collection unit configured to collect video data acquired by an unmanned vehicle and natural disaster data related to natural disasters from information sources; an analysis unit configured to extrac