JP7707900B2 - Information processing device, information processing method, and program - Google Patents

Description

The present disclosure relates to an information processing device, an information processing method, and a program.

Patent Document 1 discloses a flooding detection device. The flooding detection device obtains a detection result of flooding of the road on which the vehicle is traveling, based on multiple types of driving condition data related to the vehicle's traveling. The flooding detection device also obtains meteorological information including at least one of rainfall information indicating the actual amount of rainfall in the area on which the vehicle is traveling and rainfall forecast information indicating the forecast amount of rainfall. The flooding detection device then detects flooding of the road using the detection result and the meteorological information.

JP 2021-43910 A

The purpose of this disclosure is to grasp the flooding situation on roads in real time.

An information processing device according to a first aspect of the present disclosure includes:
Obtaining first information relating to water levels in a given area collected by a satellite;
determining a predetermined area in which a vehicle can determine whether or not a road is flooded based on the first information;
determining whether or not a road is flooded within the specified area based on second information relating to whether or not a road is flooded, the second information being collected by vehicles traveling within the specified area;
The control unit executes the above.

An information processing method according to a second aspect of the present disclosure includes:
1. A computer-implemented information processing method, comprising:
Obtaining first information relating to water levels in a given area collected by a satellite;
determining a predetermined area in which a vehicle can determine whether or not a road is flooded based on the first information;
determining whether or not a road is flooded within the specified area based on second information relating to whether or not a road is flooded, the second information being collected by vehicles traveling within the specified area;
Includes.

A program according to a third aspect of the present disclosure includes:
A program for causing a computer to execute an information processing method,
The information processing method includes:
Obtaining first information relating to water levels in a given area collected by a satellite;
determining a predetermined area in which a vehicle can determine whether or not a road is flooded based on the first information;
determining whether or not a road is flooded within the specified area based on second information relating to whether or not a road is flooded, the second information being collected by vehicles traveling within the specified area;
Includes.

This disclosure makes it possible to grasp the flooding situation on roads in real time.

FIG. 1 is a diagram showing a schematic configuration of an observation system according to an embodiment. FIG. 2 is a diagram showing an example of a flooding situation in a given area. FIG. 3 is a block diagram illustrating an example of a functional configuration of the observing server. FIG. 4 is a diagram showing an example of a table configuration of geographic information held in the geographic information database. FIG. 5 is a sequence diagram showing the flow of information processing in the observation system.

Let us consider a case where flooding conditions are observed using an artificial satellite. In this case, the artificial satellite collects information on water levels to observe the flooding conditions. Meanwhile, artificial satellites have a set number of recurrent days. Therefore, after an artificial satellite has collected information on the water level of a certain area once, the timing when it can collect information on the water level of that area again is when the artificial satellite is in the sky above that area. In other words, after an artificial satellite has collected information on the water level of a certain area once, the timing when it can collect information on the water level of that area again is after the number of recurrent days has passed. This makes it difficult for an artificial satellite to constantly collect information on the water level of the same area. Therefore, it is difficult to grasp the flooding conditions in real time using an artificial satellite.

Next, consider a case where flooding conditions are observed using a vehicle. In this case, the flooding conditions of a road are observed by performing information processing on information related to whether or not the road is flooded that is collected by the vehicle. In this case, if an area for determining whether or not the road is flooded is not specified by the vehicle, information related to whether or not the road is flooded that is collected by vehicles outside that area will also be subject to information processing, which may increase calculation costs.

The information processing device according to the present disclosure is an information processing device for observing the flooding status of roads. A control unit of the information processing device according to the present disclosure acquires first information. The first information is information relating to water levels in a specified area collected by an artificial satellite. The control unit of the information processing device determines a specified area in which the presence or absence of flooding is identified by a vehicle based on the first information. Then, the control unit identifies the presence or absence of flooding within the specified area based on second information. Here, the second information is information relating to the presence or absence of flooding of roads collected by a vehicle traveling within the specified area.

As described above, the information processing device according to the present disclosure determines a predetermined area. Then, the information processing device identifies the presence or absence of flooding based on the second information collected by a vehicle in the predetermined area. As a result, after the satellite collects the first information, the vehicle collects the second information until it becomes possible to collect the first information again. Then, based on the second information, it is possible to identify the presence or absence of flooding of roads in the predetermined area. Furthermore, by identifying the predetermined area based on the first information, it is possible to reduce the calculation cost for the information processing device to process the second information. As a result, it is possible to grasp the flooding status of roads in real time.

Specific embodiments of the present disclosure are described below with reference to the drawings. The dimensions, materials, shapes, and relative positions of the components described in the present embodiment are not intended to limit the technical scope of the present disclosure unless otherwise specified.

<Embodiment>
An observation system 1 according to this embodiment will be described with reference to Figures 1 and 2. Figure 1 is a diagram showing a schematic configuration of the observation system 1 according to this embodiment. The observation system 1 includes an artificial satellite 100, an observation server 200, and a vehicle 300. In the observation system 1, the artificial satellite 100, the observation server 200, and the vehicle 300 are connected to each other by a network N1. The network N1 may be, for example, a WAN (Wide Area Network), which is a global public communication network such as the Internet, or a telephone communication network such as a mobile phone.

(artificial satellite)
The artificial satellite 100 is an artificial satellite that detects water levels. The artificial satellite 100 is, for example, a synthetic aperture radar satellite (SAR satellite). The artificial satellite 100 observes the elevation of the earth's surface by irradiating radio waves onto the earth's surface. Specifically, the artificial satellite 100 can observe the elevation of the land that has been irradiated with radio waves by the reflected waves of the radio waves irradiated onto the land. Here, a case is assumed where the land that has been irradiated with radio waves is flooded. In this case, the artificial satellite 100 observes the elevation of the land that has been irradiated with radio waves plus the depth of the flooded water as the elevation. In addition, the artificial satellite 100 can observe the water level of a river, for example, based on the reflection of the radio waves irradiated onto the river. The artificial satellite 100 transmits information on the observed elevation of the land and the water level of the river (hereinafter, sometimes referred to as "observation information") to the observation server 200 via the network N1.

The artificial satellite 100 is an artificial satellite with a fixed recurrent period. Therefore, the timing when the artificial satellite 100 can observe the elevation and water level of a specific region is when the artificial satellite 100 is located above the specific region.

(vehicle)
The vehicle 300 is a vehicle that exists within a predetermined area. The vehicle 300 transmits information about the traveling state of the vehicle 300 (hereinafter, sometimes referred to as "vehicle information") to the observation server 200 via the network N1. In this embodiment, the vehicle information is information including the traveling speed of the vehicle 300, the depression amount of the accelerator pedal, and the like.

(Observation server)
The observation server 200 is a server for observing the flooding situation. The observation server 200 receives observation information from the artificial satellite 100 via the network N1. Based on the observation information, the observation server 200 identifies a point where flooding is currently occurring in a specified area (hereinafter, may be referred to as a "flooded point"). A method in which the observation server 200 grasps the flooding situation in a specified area based on the observation information will be described in detail later.

Figure 2 is a diagram showing an example of a flooding situation in a specified region. A part of the specified region is shown in Figure 2. Also, in Figure 2, an area consisting of flooded points (hereinafter, sometimes referred to as a "flooded area") is shown by a shaded area. In the example shown in Figure 2, flooding has occurred due to a river overflowing.

By receiving observation information about a specific region from the artificial satellite 100, the observation server 200 can grasp the flooding status of the specific region at the time when the artificial satellite 100 makes an observation. However, if the artificial satellite 100 is not present above the specific region, the artificial satellite 100 cannot transmit the observation information about the specific region to the observation server 200. Therefore, it is difficult for the observation server 200 to grasp the flooding status in real time based on the observation information received from the artificial satellite 100.

The observation server 200 also receives vehicle information from the vehicle 300 via the network N1. The observation server 200 can determine whether or not a road is flooded based on the vehicle information. Details of how the observation server 200 determines whether or not a road is flooded based on the vehicle information will be described later.

Here, assume that the observation server 200 acquires vehicle information for all vehicles 300 present within a specified area and determines whether roads within the specified area are flooded. In this case, the calculation cost for the observation server 200 to grasp the flooding status of roads within the specified area increases compared to the case of determining whether roads within a portion of the specified area are flooded.

The observation server 200 then determines an area (hereinafter sometimes referred to as an "observation area") in which the presence or absence of flooding of roads within a specified region can be determined by vehicles based on the observation information and on flooded locations within the specified region. Details of how the observation server 200 determines the observation area will be described later. The observation server 200 then determines the presence or absence of flooding of roads within the observation area based on vehicle information of the vehicle 300 traveling within the determined observation area.

The observation server 200 includes a computer having a processor 210, a main memory unit 220, an auxiliary memory unit 230, and a communication interface (communication I/F) 240. The processor 210 is, for example, a CPU (Central Processing Unit) or a DSP (Digital Signal Processor). The main memory unit 220 is, for example, a RAM (Random Access Memory). The auxiliary memory unit 230 is, for example, a ROM (Read Only Memory). The auxiliary memory unit 230 is, for example, a HDD (Hard Disk Drive) or a disk recording medium such as a CD-ROM, a DVD disk, or a Blu-ray disk. The auxiliary memory unit 230 may also be a removable medium (portable storage medium). Here, examples of removable media include a USB memory or an SD card. The communication I/F 240 is, for example, a LAN (Local Area Network) interface board or a wireless communication circuit for wireless communication.

In the observation server 200, the auxiliary memory unit 230 stores an operating system (OS), various programs, various information tables, and the like. In the observation server 200, the processor 210 can load the programs stored in the auxiliary memory unit 230 into the main memory unit 220 and execute them to realize various functions as described below. However, some or all of the functions of the observation server 200 may be realized by hardware circuits such as ASICs or FPGAs. Note that the observation server 200 does not necessarily have to be realized by a single physical configuration, and may be configured by multiple computers that work together.

(Functional configuration)
Next, the functional configuration of the observation server 200 constituting the observation system 1 according to this embodiment will be described with reference to Fig. 3 and Fig. 4. Fig. 3 is a block diagram showing an example of the functional configuration of the observation server 200.

The observation server 200 includes a control unit 201, a communication unit 202, and a geographic information database 203 (geographic information DB 203). The control unit 201 has a function of performing arithmetic processing for controlling the observation server 200. The control unit 201 can be realized by a processor 210 in the observation server 200. The communication unit 202 has a function of connecting the observation server 200 to a network N1. The communication unit 202 can be realized by a communication I/F 240 in the observation server 200.

The geographic information DB 203 has a function of storing geographic information. The geographic information is information relating to the geography of an area including a specific region (hereinafter, sometimes referred to as a "wide area"). The geographic information DB 203 can be realized by the auxiliary memory unit 230 in the observation server 200.

Figure 4 is a diagram showing an example of a table configuration of geographic information stored in the geographic information DB 203. As shown in Figure 4, a position field, an attribute field, an elevation field, a dangerous water level field, and a danger level field are input. Information for identifying each position in the wide area included in the geographic information is input in the position field. For example, latitude and longitude are input in the position field. The attributes of each position input in the position field are input in the attribute field. Specifically, if land (including roads or buildings, etc.) exists at the position input in the position field, "land" is input in the attribute field. Also, if a river exists at the position input in the position field, "river" is input in the attribute field.

In the elevation field, data on the elevation of the land at the position entered in the position field corresponding to the elevation field is entered. Here, if "land" is entered in the attribute field corresponding to the elevation field, data is entered into the elevation field. If "river" is entered in the attribute field corresponding to the elevation field, no data is entered into the elevation field.

The danger water level field is entered with the water level of a river that may flood at the position entered in the position field corresponding to the danger water level field. The water level at which flooding may occur is determined in advance based on the height of the levees built on the river, etc. Here, if "river" is entered in the attribute field corresponding to the danger water level field, data is entered into the danger water level field. If "land" is entered in the attribute field corresponding to the danger water level field, no data is entered into the danger water level field.

The risk field contains multiple levels of risk of flooding for the land at the location entered in the location field corresponding to the risk field. Here, if "land" is entered in the attribute field corresponding to the risk field, data is entered into the risk field. If "river" is entered in the attribute field corresponding to the risk field, no data is entered into the risk field.

The control unit 201 receives observation information from the artificial satellite 100 by the communication unit 202. The control unit 201 identifies flooded points in a specified area based on the geographic information stored in the geographic information DB 203 and the observation information received from the artificial satellite 100. Specifically, the control unit 201 compares the elevation of each position in the geographic information with the elevation of each position in the observation information. At this time, if flooding occurs at a certain position, the elevation of the position in the observation information is added with the depth of the flooded water. Therefore, if flooding occurs at a certain position, the elevation of the position in the observation information is higher than the elevation of the position in the geographic information. Therefore, the control unit 201 determines that flooding occurs at a certain position when the elevation in the observation information is higher than the elevation in the geographic information by a predetermined value or more. In this way, the control unit 201 identifies flooded points in a specified area and identifies flooded areas.

The control unit 201 determines the observation area based on the flooded area (flooded point). Specifically, the control unit 201 determines the observation area within a specified region to include points with a lower elevation than the flooded area based on the geographic information stored in the geographic information DB 203. Specifically, the control unit 201 acquires points with a lower elevation than the flooded area within the specified region based on the geographic information. The control unit 201 then determines the observation area to include points with a lower elevation than the flooded area. In this way, by determining the observation area to include points with a lower elevation than the flooded area, it is possible to determine the observation area to include areas where new flooding is likely to occur. In this case, the observation area may be divided into two areas that do not overlap with each other.

In the example shown in FIG. 2, the observation area is determined within a specified region. However, the observation server 200 does not necessarily have to determine the observation area within the specified region. In other words, the observation server 200 may determine the observation area outside the specified region. In this case, the observation server 200 acquires the elevation of each point in the wide area using the geographic information stored in the geographic information DB 203. Here, the wide area also includes areas other than the specified region. Therefore, the observation server 200 can also acquire the elevation of each point in the areas other than the specified region. Then, the observation server 200 sets the observation area outside the specified region by identifying points outside the specified region that have an elevation lower than the flooded area.

The control unit 201 repeatedly receives location information including the current location of the vehicle 300 from the vehicle 300 via the communication unit 202. This allows the control unit 201 to grasp the current location of the vehicle 300. Then, the control unit 201 identifies the vehicle 300 (hereinafter, sometimes referred to as the "target vehicle 300") traveling within the observation area based on the location information. Then, the control unit 201 transmits request information to the target vehicle 300 via the communication unit 202. Here, the request information is information for requesting the target vehicle 300 to transmit vehicle information. When the target vehicle 300 receives the request information from the observation server 200 via the network N1, it transmits the vehicle information to the observation server 200.

The control unit 201 determines whether or not roads in the observation area are flooded based on vehicle information collected by the target vehicle 300 traveling within the observation area. Here, if the road is flooded, the water on the road will hinder the acceleration of the vehicle 300 even if the accelerator pedal of the vehicle 300 is depressed. In other words, if the road is flooded, the speed of the vehicle 300 will not increase compared to when the road is not flooded, even if the accelerator pedal of the vehicle 300 is depressed. Therefore, the control unit 201 determines whether or not roads are flooded by comparing the speed of the vehicle 300 predicted from the amount of depression of the accelerator pedal of the vehicle 300 in the vehicle information of the vehicle 300 with the actual speed of the vehicle 300. In this way, the control unit 201 determines whether or not roads in the observation area are flooded based on the vehicle information.

The control unit 201 does not necessarily need to determine whether or not a road is flooded in the observation area based on the traveling speed of the vehicle 300 and the amount of depression of the accelerator pedal, as long as the information is related to the traveling state of the vehicle 300 whose values change in relation to whether or not the road is flooded. The control unit 201 may determine whether or not a road is flooded in the observation area based on, for example, the effectiveness of the brakes of the vehicle 300. The control unit 201 may also determine whether or not a road is flooded in the observation area based on the traveling speed of the vehicle 300, the amount of depression of the accelerator pedal, and other information related to the traveling state of the vehicle 300.

(Information processing flow)
Next, the flow of information processing in the observation system 1 will be described with reference to FIG.
1 is a sequence diagram showing the flow of information processing in the observation system 1. The processes executed by the satellite 100, the observation server 200, and the vehicle 300 are executed by the control unit of the satellite 100, the control unit 201, and the control unit of the vehicle 300, respectively.

In the observation system 1, the artificial satellite 100 acquires observation information based on the reflected waves of the radio waves irradiated to the Earth's surface (S11). The artificial satellite 100 transmits the observation information to the observation server 200 (S12).

The observation server 200 identifies a flooded area (flooded point) based on the observation information received from the artificial satellite 100 (S13). Next, the observation server 200 determines an observation area based on the flooded area (S14). Next, the observation server 200 identifies a target vehicle 300 traveling within the observation area from among a plurality of vehicles 300 traveling within a specified region (S15). Next, the observation server 200 transmits request information to the target vehicle 300 (S16).

When the target vehicle 300 receives the request information, it transmits the vehicle information to the observation server 200 (S17). Then, the observation server 200 determines whether or not there is flooding on roads in the observation area based on the received vehicle information (S18).

Here, the request information includes information indicating the observation area (e.g., information including the latitude and longitude of each point on the boundary of the observation area). This enables the vehicle 300 to grasp the observation area. Then, when the vehicle 300 receives the request information, it repeatedly transmits vehicle information until the vehicle 300 is located outside the observation area. In other words, the vehicle 300 transmits vehicle information for each point to which the vehicle 300 has traveled to the observation server 200. This enables the observation server 200 to identify the presence or absence of flooding on roads at each point within the observation area.

As described above, the observation system 1 determines the observation area based on the observation information. Then, the observation system 1 determines whether or not there is flooding based on the vehicle information collected by the target vehicle 300. This allows the observation server 200 to determine whether or not there is flooding on roads within the observation area based on the vehicle information of the target vehicle 300 after the artificial satellite 100 has collected the observation information until it is possible to collect observation information again. Furthermore, by determining the observation area based on the observation information, it becomes possible to reduce the calculation cost for the observation server 200 to process the vehicle information. As a result, it becomes possible to grasp the flooding situation on the roads in real time.

(Modification)
In this embodiment, the artificial satellite 100 is a synthetic aperture radar satellite. However, the artificial satellite 100 does not necessarily have to be a synthetic aperture radar satellite. Any known artificial satellite can be adopted as the artificial satellite 100 as long as it is capable of collecting information on the water level on the ground. The artificial satellite 100 may be, for example, a satellite having a camera for imaging the earth's surface. In this case, the observation server 200 grasps the flooding situation in a predetermined area by, for example, performing image recognition processing based on the image captured by the artificial satellite 100. Even in this way, it is possible to grasp the flooding situation of roads in real time.

In this embodiment, the observation server 200 identifies flooded points in a predetermined region based on the observation information and identifies a flooded area. Meanwhile, the observation server 200 may identify an area where flooding is expected (hereinafter, may be referred to as a "prediction area") instead of a flooded area. Specifically, the observation server 200 acquires a dangerous water level at each position of the river from the geographic information held in the geographic information DB 203. When there is a position where the water level of the river is at a dangerous water level, the observation server 200 identifies land within a predetermined range from the position as a prediction area. Then, the observation server 200 determines an observation area based on the prediction area instead of a flooded area. In this way, even if flooding does not actually occur at the time when the artificial satellite 100 collects the observation information, the target vehicle 300 transmits vehicle information to the observation server 200 in the observation area. Then, when flooding actually occurs in the observation area, the target vehicle 300 transmits vehicle information indicating that flooding has occurred to the observation server 200. In this way, when flooding actually occurs, the observation server 200 can grasp that flooding has occurred in the observation area. In this way, it is also possible to grasp the flooding situation of roads in real time.

In addition, in this embodiment, the observation server 200 determines the observation area based on the elevation information in the geographic information held in the geographic information DB 203. However, the observation server 200 does not necessarily have to determine the observation area based on the elevation information in the geographic information held in the geographic information DB 203. The observation server 200 may determine the observation area, for example, based on the risk level of each location in the geographic information held in the geographic information DB 203. Specifically, when there is a point around the flooded area where the risk level is equal to or higher than a predetermined level, the observation server 200 determines the area including the point as the observation area. Even in this way, it is possible to determine the observation area so as to include areas where new flooding is likely to occur.

In addition, in this embodiment, the observation server 200 determines whether or not the road is flooded based on the vehicle information. However, the observation server 200 does not necessarily need to determine whether or not the road is flooded based on the vehicle information. The observation server 200 may, for example, receive information including an image of the surroundings of the target vehicle 300 captured by the target vehicle 300 (hereinafter, sometimes referred to as "image information"). In this case, the observation server 200 performs image recognition processing based on the image included in the image information to determine whether or not the road on which the target vehicle 300 is traveling is flooded. In this way, the observation server 200 determines whether or not the road is flooded based on the image information. Even in this way, it is possible to grasp the flooding situation of the road in real time.

In addition, in this embodiment, the observation server 200 receives vehicle information from the target vehicle 300 by transmitting request information to the target vehicle 300. However, the observation server 200 does not necessarily have to transmit request information to the target vehicle 300 in order to receive vehicle information from the target vehicle 300. For example, the observation server 200 may repeatedly receive vehicle information from all vehicles 300 in a specified area. In this case, after identifying the target vehicle 300, the observation server 200 may extract the vehicle information received from the target vehicle 300 from the vehicle information received from all vehicles 300 in the specified area and identify whether or not the road is flooded. Even in this way, the calculation cost can be lower than when the observation server 200 identifies whether or not the road is flooded based on the vehicle information received from all vehicles 300 in the specified area.

<Other embodiments>
The above-described embodiment is merely an example, and the present disclosure may be modified as appropriate without departing from the spirit and scope of the present disclosure. Furthermore, the processes and means described in the present disclosure may be freely combined and implemented as long as no technical contradiction occurs.

Furthermore, a process described as being performed by one device may be shared and executed by multiple devices. Alternatively, a process described as being performed by different devices may be executed by one device. In a computer system, the hardware configuration (server configuration) by which each function is realized can be flexibly changed.

The present disclosure can also be realized by supplying a computer program that implements the functions described in the above embodiments to a computer, and having one or more processors of the computer read and execute the program. Such a computer program may be provided to the computer by a non-transitory computer-readable storage medium that can be connected to the system bus of the computer, or may be provided to the computer via a network. Non-transitory computer-readable storage media include any type of medium suitable for storing electronic instructions, such as, for example, a magnetic disk (such as a floppy disk or a hard disk drive (HDD)), an optical disk (such as a CD-ROM, a DVD disk, or a Blu-ray disk), a read-only memory (ROM), a random access memory (RAM), an EPROM, an EEPROM, a magnetic card, a flash memory, or an optical card.

1. Observation system 100. Artificial satellite 200. Observation server 201. Control unit 202. Communication unit 203. Geographic information DB
300...vehicle

Claims (14)

An information processing device including a storage unit and a control unit,
The storage unit stores geographic information including a dangerous water level at each position of a river;
The control unit is
Obtaining first information collected by a satellite, the first information including information on water levels of rivers in a given area;
Obtaining the dangerous water level included in the stored geographic information from the storage unit;
Based on the acquired first information and the dangerous water level , a position where the water level of the river included in the first information is at the dangerous water level is identified as a position where flooding is predicted in the specified area;
determining an area within a predetermined range from the identified location where flooding is predicted as a predetermined area for determining whether or not a road is flooded by a vehicle;
determining whether or not a road is flooded within the specified area based on second information relating to whether or not a road is flooded, the second information being collected by vehicles traveling within the specified area;
Run
The control unit is
Identifying vehicles traveling within the predetermined area based on a current position of the vehicles;
Transmitting third information to the identified vehicle to instruct the vehicle to transmit the second information; and
Further execute
Information processing device. The first information further includes information regarding a water level of flooded land;
The control unit is
Identifying a point where flooding occurs in the specified area based on the first information;
determining a predetermined area based on the location where the flooding occurs;
The information processing device according to claim 1 . The control unit is
determining the predetermined area further based on information regarding an elevation of a region including the predetermined region;
3. The information processing device according to claim 1 or 2 . The control unit is
determining the predetermined area based on information regarding a risk of flooding in an area including the predetermined area;
3. The information processing device according to claim 1 or 2 . The second information is information regarding a traveling state of a vehicle traveling within the specified area.
The information processing device according to claim 1 . The second information is an image of the surroundings of a vehicle captured by a vehicle traveling within the specified area.
The information processing device according to claim 1 . 1. A computer-implemented information processing method, comprising:
storing geographic information including a dangerous water level at each position of the river;
Obtaining first information collected by a satellite, the first information including information on water levels of rivers in a given area;
Obtaining the dangerous water level included in the stored geographic information;
Identifying a position where the water level of the river included in the first information is at the dangerous water level as a position where flooding is predicted in the specified area based on the acquired first information and the dangerous water level;
determining an area within a predetermined range from the identified location where flooding is predicted as a predetermined area for determining whether or not a road is flooded by a vehicle;
determining whether or not a road is flooded within the specified area based on second information relating to whether or not a road is flooded, the second information being collected by vehicles traveling within the specified area;
Including,
Identifying vehicles traveling within the predetermined area based on a current position of the vehicles;
Transmitting third information to the identified vehicle to instruct the vehicle to transmit the second information; and
Further comprising:
Information processing methods. The first information further includes information regarding a water level of flooded land;
In the information processing method,
Identifying a point where flooding occurs in the specified area based on the first information;
determining a predetermined area based on the location where the flooding occurs;
The information processing method according to claim 7 . determining the predetermined area further based on information regarding an elevation of a region including the predetermined region;
9. The information processing method according to claim 7 or 8 . determining the predetermined area based on information regarding a risk of flooding in an area including the predetermined area;
9. The information processing method according to claim 7 or 8 . The second information is information regarding a traveling state of a vehicle traveling within the specified area.
The information processing method according to any one of claims 7 to 10 . The second information is an image of the surroundings of a vehicle captured by a vehicle traveling within the specified area.
The information processing method according to any one of claims 7 to 10 . A program for causing a computer to execute an information processing method,
The information processing method includes:
storing geographic information including a dangerous water level at each position of the river;
Obtaining first information collected by a satellite, the first information including information on water levels of rivers in a given area;
Obtaining the dangerous water level included in the stored geographic information;
Based on the acquired first information and the dangerous water level , a position where the water level of the river included in the first information is at the dangerous water level is identified as a position where flooding is predicted in the specified area;
determining an area within a predetermined range from the identified location where flooding is predicted as a predetermined area for determining whether or not a road is flooded by a vehicle;
determining whether or not a road is flooded within the specified area based on second information relating to whether or not a road is flooded, the second information being collected by vehicles traveling within the specified area;
Including,
Identifying vehicles traveling within the predetermined area based on a current position of the vehicles;
Transmitting third information to the identified vehicle to instruct the vehicle to transmit the second information; and
Further comprising:
program. The first information further includes information regarding a water level of flooded land;
In the information processing method,
Identifying a point where flooding occurs in the specified area based on the first information;
determining a predetermined area based on the location where the flooding occurs;
The program according to claim 13 .