Route search device, route search system, route search method, and program

Abstract

In order to search for a suitable route, including regions where vehicles cannot pass, a route search device according to the present invention includes: a traffic information generating means for generating road traffic information by using sensor information relating to the road acquired by a sensor information acquisition device; a disaster range identifying means for identifying a disaster range by using a terrain change obtained on the basis of measurement results by a terrain measurement device; and a route searching means for searching for a route to a prescribed site by using the disaster range and the traffic information.

Description

Technical Field

[0001] The present invention relates to a route, particularly a route related to disasters.

Background Art

[0002] When a disaster occurs, an investigation of the disaster situation is carried out. For example, Patent Document 1 describes a technique related to the investigation of the disaster situation. The disaster countermeasure support method described in Patent Document 1 uses a synthetic aperture radar mounted on a satellite to grasp the disaster situation. Also, a route is searched using an image acquired from a vehicle. For example, Patent Document 2 describes a technique related to route search. The route search device described in Patent Document 2 determines the state of a road using an image acquired from a vehicle and searches for a route using the result of the determination.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] Since the technique described in Patent Document 1 is a technique using a synthetic aperture radar, there are cases where detailed states such as roads cannot be determined. Since the technique described in Patent Document 2 is a technique using an image acquired from a vehicle, a route cannot be searched for areas where vehicles cannot pass. An object of the present invention is to provide a route search device that searches for an appropriate route including areas where vehicles cannot pass.

Means for Solving the Problems

[0005] The route search device according to one aspect of the present invention is A traffic information generation means generates road traffic information using road-related sensor information acquired by a sensor information acquisition device, A means for identifying the extent of a disaster, which uses changes in the ground surface obtained based on the measurement results of a ground surface measuring device to identify the extent of the disaster, A route search means that uses disaster area and traffic information to search for a route to a predetermined point. Includes.

[0006] A pathfinding system in one embodiment of the present invention is The above-mentioned route search device, The pathfinding device includes a sensor information acquisition device that outputs sensor information. Includes.

[0007] A pathfinding method in one embodiment of the present invention is: Using the sensor information related to the road acquired by the sensor information acquisition device, road traffic information is generated. The extent of the disaster is identified using the ground surface changes obtained based on the measurement results from the ground surface measurement device. Using disaster area data and traffic information, a route to a designated location is searched.

[0008] A pathfinding method in one embodiment of the present invention is: The pathfinding device executes the above pathfinding method, The sensor information acquisition device outputs sensor information to the pathfinding device.

[0009] A recording medium in one embodiment of the present invention is The process involves generating road traffic information using road-related sensor information acquired by a sensor information acquisition device. A process to identify the extent of the disaster using changes in the ground surface obtained based on the measurement results of the ground surface measurement device, A process that uses the disaster area and traffic information to search for a route to a predetermined point. Record the program that causes the computer to execute. [Effects of the Invention]

[0010] According to the present invention, it is possible to achieve the effect of searching for an appropriate route including an area where the vehicle cannot pass.

Brief Description of the Drawings

[0011] [Figure 1] It is a block diagram showing an example of the configuration of a route search system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the configuration of a route search system according to the first embodiment. [Figure 3] It is a diagram showing the departure point and the destination used for the explanation. [Figure 4] It is a diagram showing an example of a route during a disaster. [Figure 5] It is a flowchart showing an example of the operation of a route search device according to the first embodiment. [Figure 6] It is a block diagram showing an example of the hardware configuration of a route search device. [Figure 7] It is a block diagram showing an example of the configuration of a route search system according to the second embodiment. [Figure 8] It is a diagram for explaining the route searched by the route search unit based on the prediction of the disaster area. [Figure 9] It is a flowchart showing an example of the operation of a route search device according to the second embodiment. [Figure 10] It is a block diagram showing an example of the configuration of a route search device according to the third embodiment. [Figure 11] It is a block diagram showing an example of the configuration of a route search system according to the fourth embodiment.

Modes for Carrying Out the Invention

[0012] Next, embodiments of the present invention will be described with reference to the drawings. However, each embodiment of the present invention is not limited to the description in each drawing. Also, the embodiments can be combined as appropriate.

[0013] <Terms> A "sensor information acquisition device" is a device equipped with a predetermined sensor that acquires sensor information related to a structure and its surroundings. For example, the structure may include at least one of the following: a road, a bridge, a slope, a dike, a pier, a revetment, and a runway. Sensor information will be explained later. The sensor information acquisition device may be a device mounted on or towed by a mobile body, or it may be a fixed device. For example, the mobile body may be a vehicle, an unmanned aerial vehicle (drone), or a person. A mobile device may be, for example, a dashcam. A fixed device may be, for example, a fixed camera. A fixed camera used as a sensor information acquisition device is not limited to a camera with a fixed shooting direction, but may also be a camera whose shooting direction and shooting position can be changed within a certain range.

[0014] "Sensor information" refers to information acquired using a predetermined sensor to determine the condition of a structure and its surroundings. For example, the sensor may include a camera, speedometer, accelerometer, angle meter, or distance meter. The acquired information may include, for example, images, speed, acceleration, angle, or distance. For example, the sensor information may be images or measured acceleration captured by a drive recorder mounted on a vehicle traveling on a structure such as a road or bridge. Alternatively, if the sensor is LIDAR (Light Detection and Ranging), the sensor information may be distance information. The sensor information may include multiple pieces of information. These multiple pieces of information may include, for example, an image and acceleration, or multiple images such as a video. However, the sensor information is not limited to images, speed, acceleration, and distance; it may be any information that can be used for route searching. In other words, the sensor is not limited to a camera, speedometer, accelerometer, angle meter, or distance meter.

[0015] Furthermore, sensor information may include information different from the information acquired by the sensor. For example, sensor information may include information related to the acquisition of sensor information. Information related to the acquisition of sensor information may include, for example, the acquisition time or the acquisition location. Hereinafter, information related to the acquisition of sensor information will be referred to as "acquisition-related information." Alternatively, sensor information may include information related to the sensor information acquisition device or information related to the sensor. Information related to the sensor information acquisition device may include, for example, the device name, mounting location, or orientation of the sensor information acquisition device. Alternatively, information related to the sensor may include, for example, the sensor specifications. Hereinafter, information related to the sensor information acquisition device and information related to the sensor will be collectively referred to as "acquisition device information."

[0016] Furthermore, the sensor information may include information related to a mobile body equipped with the sensor information acquisition device. The mobile body is, for example, a vehicle. Information related to the mobile body is, for example, the vehicle's model number or vehicle type. Hereinafter, information related to the mobile body will be referred to as "mobile body information". Furthermore, the sensor information may include information related to the operation of the mobile body equipped with the sensor information acquisition device. In the case of a vehicle, information related to the operation of the mobile body is, for example, information related to the operation of the accelerator pedal, brake pedal, shift lever, steering wheel, wipers, turn signals, and opening and closing doors. Hereinafter, information related to the operation of the mobile body will be referred to as "operation information". Alternatively, the sensor information may include information related to the surroundings of the sensor information acquisition device in the acquisition of sensor information. For example, information related to the surroundings may include weather, temperature, humidity, illuminance, congestion level, or sound. Hereinafter, information related to the surroundings will be referred to as "surroundings information". Alternatively, the sensor information may include information added by the operator performing the acquisition work. Information added by the operator is, for example, the operator's comments. Hereinafter, information added by the operator will be referred to as "additional information".

[0017] In the following explanation, the information contained in sensor information, excluding the information acquired by the sensor, will be collectively referred to as "related information." The information contained in sensor information includes at least one of the following: acquisition related information, acquisition device information, mobile object information, operation information, surrounding information, and additional information. Thus, sensor information may include related information in addition to the information acquired by the sensor. However, related information may be treated as separate information from the information acquired by the sensor. For example, a single file may store the information acquired by the sensor and the related information as separate data. However, in the following explanation, sensor information will be described as including related information.

[0018] This section explains specific examples of the correspondence between a sensor information acquisition device, a sensor, and sensor information. For example, if the sensor information acquisition device is a drive recorder, the sensor is a camera, and the sensor information is, for example, an image. If the sensor information acquisition device is an accelerometer, the sensor is an accelerometer, and the sensor information is acceleration. A sensor information acquisition device may be equipped with multiple sensors. In this case, the multiple sensors may be multiple sensors of the same type, or multiple types of sensors. Examples of multiple types of sensors include a camera, an accelerometer, and an angle meter. In the following explanation, a drive recorder, a camera, and an image will be used as examples of a sensor information acquisition device, a sensor, and sensor information, respectively. A vehicle will be used as an example of a moving object.

[0019] Synthetic Aperture Radar (SAR) is a type of radar that uses a moving projectile to transmit and receive radio waves, acquiring images equivalent to those obtained with an antenna with a large aperture. Hereafter, Synthetic Aperture Radar (SAR) will be referred to as "SAR." Resolution in radar observations improves as the antenna size increases. However, there are limits to the size of antennas that can be mounted on artificial satellites and other vessels. Therefore, SAR uses an antenna with a small actual aperture length and transmits and receives radio waves while in flight to improve resolution in the direction of travel. In other words, SAR artificially "synthesizes" apertures to create a virtually large antenna. The projectile is not limited to any projectile that can carry SAR; any projectile is acceptable. For example, projectiles can be artificial satellites, aircraft, or unmanned aerial vehicles (drones).

[0020] SAR outputs an image as a measurement result. Hereafter, the image as a measurement result will be referred to as a "SAR image". Each embodiment can analyze "changes in the ground surface" using the SAR image. Hereafter, changes in the ground surface may also be simply referred to as "ground surface changes". For example, each embodiment can analyze changes in the height of the ground surface between two time points by using two SAR images taken at the same location but at different times as a change in the ground surface. Alternatively, each embodiment can analyze changes in the intensity of the ground surface as a change in the ground surface.

[0021] The method for analyzing changes in height and intensity according to each embodiment is not particularly limited. Each embodiment may use any method for analysis. For example, each embodiment may use techniques such as change extraction, time-series interferometry, or coherent change extraction. Alternatively, each embodiment may perform machine learning using past SAR images as training data, and apply the SAR images to the analysis model generated as a result of the machine learning to analyze changes in the ground surface. The analysis of changes in the ground surface is not limited to the analysis of changes in ground surface height and changes in ground surface intensity, but may include other analyses. For example, other analyses may include at least one of the analysis of the factors causing changes in the ground surface and the analysis of the magnitude of risks based on changes in the ground surface. Thus, SAR is a device that measures the ground surface in order to obtain measurement results for analyzing changes in the ground surface.

[0022] However, in each embodiment, the device for acquiring measurement results to analyze changes in the Earth's surface, that is, the device for measuring the Earth's surface, is not limited to SAR. Examples of devices for measuring the Earth's surface include optical sensors or laser measuring instruments mounted on artificial satellites, aircraft, or unmanned aerial vehicles (drones). Each embodiment may analyze changes in the Earth's surface using the measurement results of such a device or system for measuring the Earth's surface. The measurement results are, for example, optical images. In the following description, these devices or systems for measuring the Earth's surface will be collectively referred to as "Earth surface measuring devices."

[0023] Some ground surface measurement devices analyze "changes in the ground surface" using measurement results and output the "changes in the ground surface" as a result of the analysis. In other words, ground surface measurement devices may output measurement results, or they may output changes in the ground surface as an analysis result. Therefore, to avoid complexity in the following explanation, unless otherwise specified, the above cases will be grouped together, and the devices in each embodiment will be described as acquiring changes in the ground surface obtained based on the measurement results of the ground surface measurement device. In the following explanation, SAR and SAR images will be used as examples of ground surface measurement devices and measurement results.

[0024] Some SAR devices can acquire measurement results using multiple frequencies (multispectral). Hereafter, devices that can acquire measurement results using multispectral data will be referred to as "multispectral measuring devices." By using measurement results using multispectral data, it is possible to analyze not only changes in the ground surface but also the type of ground surface. Therefore, each embodiment may analyze the type of ground surface using the measurement results of SAR using multispectral data and use the analyzed type of ground surface. Note that the type of ground surface is determined in accordance with the frequency used. For example, the type of ground surface includes at least one of the following: water surface, mud, garbage, dry soil, grassland, forest, farmland, and snow cover. Thus, the type of ground surface is one of the analysis results of the measurement results of the ground surface. Therefore, in the following explanation, unless a specific distinction is necessary, the term "change in the ground surface" will include the type of ground surface. In other words, the change in the ground surface in the following explanation may include the type of ground surface.

[0025] Measurement results from ground measurement devices such as SAR cover a fairly wide area. Therefore, analysis using measurement results from ground measurement devices such as SAR can acquire information on changes in the ground surface over a fairly wide area. Also, SAR measures the ground surface from a certain altitude. Therefore, ground measurement devices such as SAR can measure the ground surface even when disasters have occurred. However, the accuracy of analysis results using measurement results obtained by SAR is often in the range of a meter. For determining the condition of roads and other surfaces, an accuracy of a few centimeters to a dozen centimeters is often desirable. In contrast, the accuracy of determination using sensor information obtained from a dashcam is in the range of a few centimeters to a few tens of centimeters. However, dashcams cannot acquire sensor information for areas where vehicles cannot pass.

[0026] Therefore, it is desirable to achieve at least a degree of accuracy comparable to that of searching using sensor information, and furthermore, to search for routes that include areas where sensor information cannot be acquired, such as areas where vehicles cannot pass. Each embodiment of the present invention searches for an appropriate route using changes in the ground surface obtained based on the measurement results of a ground surface measuring device and sensor information acquired by a sensor information acquisition device, as described below.

[0027] <First Embodiment> First, the configuration of the route search system 80 according to the first embodiment will be described with reference to the drawings. Figure 1 is a block diagram showing an example of the configuration of the route search system 80 according to the first embodiment. The route search system 80 includes a route search device 10, a drive recorder 20, a SAR 30, a display device 40, and an information providing device 50. The number of each component in Figure 1 is an example and is not limited to the number shown in Figure 1. For example, the route search system 80 may include multiple drive recorders 20.

[0028] The drive recorder 20 outputs sensor information to the route search device 10. The drive recorder 20 is mounted on a vehicle, for example, and acquires sensor information such as the road the vehicle is traveling on. The sensor information is, for example, an image of the road. The drive recorder 20 then outputs the acquired sensor information to the route search device 10. However, the means of transport for the drive recorder 20 is not limited to a vehicle. For example, the drive recorder 20 may be mounted on a mobile body other than a vehicle. A mobile body other than a vehicle is, for example, an unmanned aerial vehicle (drone). Alternatively, a person or the like may carry the drive recorder 20. Furthermore, in this embodiment, a device that can be fixed at any location, such as a fixed camera, and capable of acquiring and outputting sensor information may be included as the drive recorder 20.

[0029] The route search system 80 is not limited to one, but may include multiple drive recorders 20. In this case, the means of transport for each drive recorder 20 may differ in at least part. For example, the route search system 80 may include a drive recorder 20 mounted on a vehicle and a drive recorder 20 fixed in a predetermined position.

[0030] SAR30 outputs measurement results or changes in the ground surface to the pathfinding device 10. For example, SAR30 outputs a SAR image, which is the measurement result, to the pathfinding device 10. In this case, the pathfinding device 10 can use the SAR image acquired from SAR30 to analyze the "changes in the ground surface". SAR30 may output a SAR image within a pre-set range, or it may output a SAR image within a range requested by the pathfinding device 10. The pre-set range may be, for example, the imaging range or the measurement range.

[0031] Alternatively, SAR30 may output "surface changes" as a result of analyzing the SAR image to the pathfinding device 10. In this case as well, SAR30 may output surface changes within a preset range, or surface changes within a range requested by the pathfinding device 10. The preset range is, for example, the analysis range. SAR30 may also measure the surface using multispectral analysis. In this case, SAR30 may output the multispectral measurement results, or it may output the type of surface analyzed using the multispectral measurement results.

[0032] The display device 40 displays the information output by the route search device 10. The information output by the route search device 10 is, for example, a route. The display device 40 can be any device that displays the information output by the route search device 10. The display device 40 can be installed in any location where it can be installed. Alternatively, the display device 40 may be a portable device such as a mobile phone, smartphone, or tablet, rather than a device installed in a predetermined location. For example, the display device 40 may be a display unit included in a local government's disaster support system. Alternatively, the display device 40 may be a device installed in a vehicle equipped with a drive recorder 20. A device installed in a vehicle is, for example, a car navigation system. Alternatively, the display device 40 may be a device carried individually by a user, for example, a smartphone. Furthermore, the display device 40 may be a device included in any of the devices, or a device that includes other devices. For example, the display device 40 may be included in the route search device 10. Alternatively, the display device 40 may be a device that includes the route search device 10.

[0033] The information providing device 50 provides the information requested by the route search device 10. The information providing device 50 can be any device that provides the information requested by the route search device 10. Users of the route search device 10 should decide which information to obtain from the information providing device 50 and the information necessary for route searching in the route search device 10. For example, the information providing device 50 may provide the route search device 10 with map information such as roads. Alternatively, the information providing device 50 may provide the route search device 10 with disaster-related information. Hereinafter, disaster-related information will be referred to as "disaster information".

[0034] Furthermore, disaster information is not limited. Disaster information can be any information as long as it is relevant to the disaster in question. For example, disaster information may include information related to the disaster that has occurred, such as the extent of the damage, secondary disasters, and past disaster information. Alternatively, disaster information may include weather-related information such as rainfall area, rainfall amount, rain cloud information, wind direction, wind speed, snowfall area, and snow depth. Rain cloud information may include, for example, the location, extent, and direction of movement of rain clouds. Alternatively, disaster information may include earthquake-related information such as the epicenter, seismic intensity, and aftershock situation. Alternatively, disaster information may include information related to social infrastructure, such as power outages, water outages, or suspension of city gas supply. Alternatively, disaster information may include maps related to the disaster. For example, maps related to the disaster may include hazard maps, evacuation shelter maps, or maps of available stores. Disaster information may also include information on structures with high risk. For example, structures with high risk may include tunnels and bridges.

[0035] The route search device 10 searches for a route from a specified starting point to a destination. To do this, the route search device 10 acquires sensor information from the drive recorder 20. For example, the route search device 10 acquires road images from the drive recorder 20. The route search device 10 may acquire sensor information from the drive recorder 20, or it may acquire sensor information from a device that stores the sensor information acquired by the drive recorder 20. However, in the following explanation, as an example, the route search device 10 will be described as acquiring sensor information from the drive recorder 20.

[0036] The route search device 10 then generates traffic information. "Traffic information" is information indicating whether or not a moving object can travel on a road. A moving object is, for example, a vehicle or a person. If there are multiple roads, the traffic information indicates whether or not a moving object can travel on at least some of the roads. In this embodiment, "road" is not limited to roads on the ground, as long as at least one of vehicles and people can travel on it. For example, a road may be a road on a bridge or a road on an elevated structure. Furthermore, when generating traffic information, the condition of road-related structures such as pavement, bridge piers, elevated structures, and tunnels may also be taken into consideration.

[0037] Traffic information may include information relating to whether a moving object can travel on structures other than roads. For example, traffic information may include information relating to whether a person can travel on pedestrian-accessible stairs, pedestrian bridges, walkways on top of embankments or levees, paths in parks, promenades, farm roads, or piers. Traffic information may be generated using information relating to multiple structures. Structures include, for example, roads and bridges. However, in the following explanation, traffic information will be described as information relating to whether a moving object can travel on a road, as an example.

[0038] Traffic information is not particularly limited as long as it relates to whether or not a moving object can travel on a road, and may include any information. For example, traffic information may include at least one of the following: information indicating the area of ​​the road that a moving object can travel on, and information indicating the area of ​​the road that a moving object cannot travel on. Hereinafter, information indicating the area of ​​the road that a moving object can travel on will be called the "passable area," and information indicating the area of ​​the road that a moving object cannot travel on will be called the "impassable area."

[0039] Furthermore, the passable and impassable areas are not limited to areas of roads that are completely passable and areas of roads that are completely impassable, respectively. The passable and impassable areas may be determined based on the likelihood that a moving object can travel on the road. Hereinafter, the likelihood that a moving object can travel on the road will be referred to as "passability." Passability can be expressed, for example, as a probability. For example, the route search device 10 may use sensor information to determine the passability of a road and designate areas of roads with a passable probability or higher as passable areas, and other road areas as impassable areas. A predetermined passability is, for example, 60%.

[0040] Traffic information may include multiple areas, at least one of which is a passable area and the other is a non-passable area. In other words, traffic information may include one or more areas, at least one of which is a passable area and the other is a non-passable area. Furthermore, at least one of the passable area and the non-passable area may include the passability of the roads included in the area. If at least one of the passable area and the non-passable area includes multiple roads, that area may include multiple passability corresponding to each of those roads. For example, if at least one of the passable area and the non-passable area includes multiple roads, that area may include the passability of each road included in the area.

[0041] The route search device 10 cannot determine whether an area is passable or impassable in areas where sensor information cannot be acquired. Hereinafter, areas where sensor information cannot be acquired will be referred to as "unacquired areas." However, it is preferable for the route search device 10 to search for a route while avoiding areas where it is unclear whether or not it is passable. Therefore, the route search device 10 may include unacquired areas in the impassable areas. In the following explanation, unless otherwise specified, impassable areas will be considered to include unacquired areas. However, the treatment of unacquired areas is not limited to this. Unacquired areas may be included in passable areas, or they may be treated separately from passable and impassable areas.

[0042] Furthermore, the pathfinding device 10 acquires SAR images from the SAR 30 and analyzes changes in the ground surface using the acquired SAR images. Alternatively, the pathfinding device 10 acquires changes in the ground surface from the SAR 30, which are the result of analyzing the SAR images acquired by the SAR 30. In other words, although the main subject of the analysis differs, the pathfinding device 10 acquires changes in the ground surface, which are the result of analysis using the measurement results of the SAR 30. The measurement results of the SAR 30 are, for example, SAR images. Then, the pathfinding device 10 identifies the extent of the disaster using the acquired changes in the ground surface. The pathfinding device 10 may identify not just one, but multiple disaster areas. Hereafter, the extent of the disaster will also be referred to as the "disaster area".

[0043] The pathfinding device 10 may acquire SAR images or changes in the ground surface from the SAR 30, or it may acquire SAR images or changes in the ground surface from a device that stores SAR images or changes in the ground surface. However, in the following description, as an example, the pathfinding device 10 will be described as acquiring SAR images or changes in the ground surface from the SAR 30.

[0044] The route search device 10 then searches for a route to a predetermined point (destination) on a road used by a moving object, based on traffic information and the disaster area. The moving object is, for example, a vehicle or a person. The route search device 10 may search for routes corresponding to each of multiple moving objects. The routes are, for example, a route for vehicles and a route for people. Alternatively, the route search device 10 may search for a route corresponding to all of the multiple moving objects. The route is, for example, a route that can be used by both vehicles and people. The starting point and destination of the route are not particularly limited. For example, in the case of a route used for distributing supplies, the starting point is the location of the supply storage facility, and the destination is the location of the supply distribution site. Or, in the case of an evacuation route, the starting point is the current location of each evacuee, and the destination is, for example, an evacuation center.

[0045] The route search device 10 then outputs the searched route to a predetermined device. The predetermined device is, for example, a display device 40. The route search device 10 may start operating in response to any condition. For example, when it receives a disaster warning from a disaster warning device (not shown), the route search device 10 may search for a route. Alternatively, the route search device 10 may search for a route in response to a request from a user or the like. The route search device 10 may obtain from a user or the like at least one of the roads, moving objects, starting point, and destination for the route search. For example, the route search device 10 may obtain from a user or the like an evacuation center as the destination. However, the route search device 10 may have already obtained in advance at least one of the roads, moving objects, starting point, and destination for the route search.

[0046] The route search device 10 may repeat the route search not just once, but at predetermined intervals or at predetermined timings. For example, the route search device 10 may reacquire sensor information every hour and repeat the route search. Alternatively, the route search device 10 may re-execute the route search when it reacquires at least one of new sensor information and new changes in the ground surface. Alternatively, the route search device 10 may search for a route corresponding to the user's request when a request is made by the user. If multiple users request a route, the route search device 10 may execute at least some of its operations in parallel in multiple searches.

[0047] Figure 2 is a conceptual diagram showing an example of the configuration of a route search system 80 according to the first embodiment. The route search system 80 in Figure 2 includes a computer 810 as an example of a route search device 10, a drive recorder 820 as an example of a drive recorder 20, and a SAR system 830 including an artificial satellite and a ground station as an example of a SAR 30. Furthermore, the route search system 80 in Figure 2 includes a terminal device 840 as an example of a display device 40. Furthermore, the route search system 80 in Figure 2 includes a vehicle 850 as an example of a mobile body carrying the drive recorder 820.

[0048] Furthermore, the route search system 80 in Figure 2 includes a network 880 as a communication path connecting each device and system. The network 880 is a communication path that interconnects each device and system. There are no particular restrictions on the network 880 as long as it can connect each device and system. For example, the network 880 may be the internet, a public telephone line, or a combination thereof. Note that the information providing device 50 is omitted in Figure 2.

[0049] The configuration of the route search system 80 shown in Figure 2 is an example. The number of each component is not limited to the example shown in Figure 2. For example, the route search system 80 may include one, two, or four or more drive recorders 820. Alternatively, at least some of the drive recorders 820 may not be mounted on the vehicle 850. For example, the route search system 80 may include a fixed camera as a drive recorder 820. Note that in Figure 2, the drive recorders 820 are shown outside the vehicle 850 for ease of understanding. However, the drive recorders 820 may be mounted inside the vehicle 850.

[0050] Vehicle 850 travels on the road equipped with a drive recorder 820. The drive recorder 820 is mounted on vehicle 850 and acquires sensor information from roads and bridges along the route vehicle 850 travels on, and outputs the acquired sensor information to computer 810. For example, the drive recorder 820 acquires images and acceleration data. Computer 810 acquires sensor information from the drive recorder 820 and uses the acquired sensor information to generate traffic information.

[0051] Furthermore, the computer 810 acquires SAR images from the SAR system 830 and analyzes changes in the ground surface using the acquired SAR images. However, the computer 810 may also acquire changes in the ground surface from the SAR system 830. In other words, the computer 810 acquires changes in the ground surface as a result of the analysis using the SAR images acquired by the SAR system 830. Then, the computer 810 identifies the disaster area using the changes in the ground surface. Then, the computer 810 searches for a route to a predetermined point using traffic information and the disaster area. Then, the computer 810 outputs the searched route to the terminal device 840. The terminal device 840 displays the route acquired from the computer 810.

[0052] There are no particular restrictions on the specific devices that make up the computer 810, drive recorder 820, SAR system 830, terminal device 840, and vehicle 850 included in the route search system 80. Generally available products and systems may be used as the computer 810, drive recorder 820, SAR system 830, terminal device 840, and vehicle 850. Therefore, detailed explanations of these are omitted.

[0053] Next, the configuration of the route search device 10 will be described with reference to Figure 1. The route search device 10 includes a traffic information generation unit 110, a disaster area identification unit 120, a route search unit 130, and a route output unit 140. The traffic information generation unit 110 generates road traffic information using road-related sensor information acquired by a sensor information acquisition device. The sensor information acquisition device is, for example, a drive recorder 20. The disaster area identification unit 120 identifies the disaster area using ground surface changes obtained based on the measurement results of a ground surface measurement device. The ground surface measurement device is, for example, a SAR 30. The route search unit 130 searches for a route to a predetermined point using the disaster area and traffic information. The route output unit 140 outputs the searched route.

[0054] The traffic information generation unit 110 acquires sensor information from the drive recorder 20. The traffic information generation unit 110 may acquire multiple types of sensor information. These multiple types of sensor information may include, for example, images and acceleration. The traffic information generation unit 110 may acquire sensor information from multiple drive recorders 20, not just one. In this case, the traffic information generation unit 110 may acquire the same type of sensor information from multiple drive recorders, or it may acquire different types of sensor information. Alternatively, the traffic information generation unit 110 may acquire a different number of sensor information from each of the multiple drive recorders 20. For example, the traffic information generation unit 110 may acquire images from all of the multiple drive recorders 20. Alternatively, the traffic information generation unit 110 may acquire images from some of the drive recorders 20 and acceleration from the other drive recorders 20. Alternatively, the traffic information generation unit 110 may acquire images from some of the drive recorders 20, acquire acceleration from another set of drive recorders 20, and acquire images and acceleration from the remaining drive recorders 20.

[0055] The traffic information generation unit 110 then uses the sensor information to generate traffic information for a predetermined moving object on a road. The predetermined moving object is, for example, a vehicle or a person. The traffic information is, for example, information that includes at least one of a passable area and an impassable area. For example, if a drive recorder 20 is mounted on a vehicle, the point where sensor information was acquired is the point where the vehicle equipped with the drive recorder 20 was able to move. Therefore, the traffic information generation unit 110 may use the position information included in the sensor information to determine the acquisition location of the sensor information, and define the area including the determined acquisition location of the sensor information as the passable area. The area including the acquisition location of the sensor information is, for example, an area within a predetermined range from the acquisition location of the sensor information. Note that the sensor information may be information acquired before the disaster occurred. Therefore, the traffic information generation unit 110 may refer to the acquisition time included in the sensor information and use sensor information after the disaster occurred. Note that the area in which the traffic information generation unit 110 generates traffic information is not limited to roads, and traffic information may be generated in areas other than roads where a moving object can pass. Areas other than roads include, for example, vacant lots or factory sites.

[0056] Alternatively, the traffic information generation unit 110 may generate road traffic information based on the state of road congestion obtained using sensor information. For example, the traffic information generation unit 110 may use sensor information to determine the state of road congestion, including the state in which moving objects such as vehicles are stopped, and determine a predetermined range of area including the point where congestion is occurring as an impassable area. For example, the traffic information generation unit 110 may use images, acceleration, or operation information to determine the state of road congestion, including the state in which moving objects such as vehicles are stopped, and determine a predetermined range of area including the point where congestion is occurring as an impassable area. Alternatively, the traffic information generation unit 110 may determine a predetermined range of area including the point where congestion is not occurring as an passable area. For example, if sensor information is acquired from multiple drive recorders 20, the traffic information generation unit 110 determines the state of congestion at the acquisition locations of the multiple sensor information and determines the range of congestion using the acquisition locations of the sensor information in which congestion has been determined to be occurring. The traffic information generation unit 110 may then determine the determined area where congestion occurs as an impassable area. Alternatively, the traffic information generation unit 110 may determine the area excluding the congestion area as an passable area.

[0057] The traffic information generation unit 110 may use sensor information to determine the passability of a road and include the determined passability in the traffic information. For example, if it is determining the state of congestion, the traffic information generation unit 110 may use the determined congestion state to determine the passability. Alternatively, if the sensor information is an image of a road with heavy rain or many puddles, the traffic information generation unit 110 may use the sensor information to determine the passability of moving objects such as vehicles. Areas with low passability are areas where it is highly likely that moving objects cannot pass. Therefore, the traffic information generation unit 110 may designate areas where the passability is lower than a predetermined value as impassable areas.

[0058] Furthermore, the traffic information generation unit 110 may generate traffic information using information acquired from the information providing device 50. For example, the traffic information generation unit 110 may acquire road-related information from an external device and use the acquired information to determine at least one of the passable area and the impassable area. Road-related information includes, for example, road closures or information about traffic signal malfunctions or outages. Alternatively, the traffic information generation unit 110 may include information acquired from the information providing device 50 in the traffic information. For example, the traffic information generation unit 110 may acquire map information from the information providing device 50 and associate the generated traffic information with the map information. For example, the traffic information generation unit 110 may define the traffic information as information that associates at least one of the passable area and the impassable area with the map information.

[0059] Alternatively, the traffic information generation unit 110 may use information related to the road posted on the internet or other networks by people living near the road or people traveling on the road. Hereinafter, information related to the road posted by people living near the road or people traveling on the road will be referred to as "posted road information". Note that "posted road information" may also be historical information within a certain time range. For example, the traffic information generation unit 110 may generate traffic information using posted road information posted on a social networking service (SNS). For example, people living near the road or people traveling on the road may post images of congested roads or comments about road congestion on SNS. Hereinafter, information related to congestion, such as images and comments, will be referred to as "congestion information". Alternatively, people traveling on the road may post information about road closures on SNS. Hereinafter, information related to road closures will be referred to as "road closure information".

[0060] Therefore, the traffic information generation unit 110 may acquire road information posted on social media at a predetermined point, road, or area via an information providing device 50 or the like, and generate traffic information based on the acquired road information posted on social media. The posted road information may be, for example, congestion information or road closure information. For example, the traffic information generation unit 110 may use the road information posted on social media to determine at least one of a passable area and an impassable area. Furthermore, the traffic information generation unit 110 may use the road information posted on social media to determine passability.

[0061] The traffic information generation unit 110 then outputs the generated traffic information to the route search unit 130. The traffic information generation unit 110 may also output the sensor information used to generate the traffic information to the route search unit 130. The traffic information generation unit 110 may output at least one of the sensor information and the traffic information to the route output unit 140. The traffic information generation unit 110 may also output the information acquired from the information providing device 50 to at least one of the route search unit 130 and the route output unit 140.

[0062] The disaster area identification unit 120 acquires SAR images from the SAR 30 in the area to be searched for a path. The disaster area identification unit 120 may request the SAR 30 to provide SAR images of the area to be acquired. Alternatively, the disaster area identification unit 120 may acquire SAR images of a pre-specified area from the SAR 30. Then, the disaster area identification unit 120 analyzes changes in the ground surface using the acquired SAR images. Alternatively, the disaster area identification unit 120 may acquire changes in the ground surface corresponding to the area to be acquired from the SAR 30. In this case as well, the disaster area identification unit 120 may request the SAR 30 to provide changes in the ground surface of the area to be acquired. Thus, although the main body of the analysis differs, the disaster area identification unit 120 acquires changes in the ground surface, which are the result of analysis using the measurement results of a ground surface measuring device. The ground surface measuring device is, for example, the SAR 30. The measurement results are, for example, SAR images.

[0063] The disaster area identification unit 120 then identifies the disaster area using changes in the ground surface. For example, in the case of a flood, the ground surface rises due to inundation. Alternatively, in the case of a landslide or road collapse, the ground surface falls. Therefore, the disaster area identification unit 120 may identify the area where the change in the ground surface exceeds a predetermined threshold as the disaster area. The disaster area identification unit 120 may also change the threshold used for identification depending on the type of disaster being identified. For example, the disaster area identification unit 120 may use a different threshold value for determining floods or inundation than the threshold used for determining road collapse.

[0064] The disaster area identification unit 120 may identify not just one, but multiple disaster areas. In this case, the disaster area identification unit 120 may identify multiple disaster areas for each type of disaster. That is, the disaster area identification unit 120 may identify a disaster area corresponding to each of the multiple disasters. The multiple disasters are, for example, flooding and landslides caused by heavy rain. In this case, the disaster area identification unit 120 may identify multiple disaster areas for at least some of the disasters. Alternatively, the disaster area identification unit 120 may identify a disaster area where one type of disaster is occurring and a disaster area where multiple types of disasters are occurring.

[0065] Furthermore, surface measurement devices such as multispectral measuring devices may be able to provide measurement results that allow for the analysis of the type of surface. In this case, the disaster area identification unit 120 may analyze the type of surface using information acquired from SAR 30. Alternatively, the disaster area identification unit 120 may acquire the type of surface from SAR 30. The disaster area identification unit 120 may then identify the disaster area using the surface changes, other information, and the type of surface. Other information may include, for example, map information. For example, when identifying the disaster area of ​​a flood, the disaster area identification unit 120 may identify the disaster area as the area where the surface changes are greater than a threshold and the type of surface is water. Alternatively, the disaster area identification unit 120 may identify the flood area as the area that is land in normal times according to map information and where the type of surface is water. The area that is land is, for example, an area that is not a river, swamp, or pond.

[0066] Furthermore, the disaster area identification unit 120 may include disaster-related information in the disaster area. For example, the disaster area identification unit 120 may include at least one of the following in the disaster area: the type of disaster, the probability of the disaster occurring, and the degree of disaster risk. Hereinafter, the probability of the disaster occurring will be referred to as "disaster possibility." For example, the disaster area identification unit 120 may use changes in the ground surface (and, if possible, the type of ground surface) to determine at least one of the disaster type, disaster possibility, and degree of risk. For example, in the case of a flood, the changes in the ground surface will be elevated over almost the entire disaster area. On the other hand, in the case of landslides and slope failures, the changes in the ground surface will include areas that become lower and areas that become higher. Thus, the changes in the ground surface differ for each type of disaster. Therefore, the disaster area identification unit 120 may use changes in the ground surface to determine the type of disaster. The disaster area identification unit 120 may also use the type of ground surface to determine the type of disaster.

[0067] Alternatively, areas with significant surface changes are more likely to experience disasters than areas with smaller changes. Therefore, the disaster area identification unit 120 may use surface changes to determine the likelihood of a disaster. For example, the disaster area identification unit 120 may assign a higher likelihood of disaster to areas with significant surface changes than to areas with small surface changes. Alternatively, areas with significant surface changes can be estimated to be at higher risk than areas with small changes. Therefore, the disaster area identification unit 120 may use surface changes to determine the degree of risk. For example, the disaster area identification unit 120 may assign a higher degree of risk to areas with significant surface changes than to areas with small surface changes. The disaster area identification unit 120 may include at least one of the disaster type, likelihood of disaster, and degree of risk in the disaster area.

[0068] The disaster area identification unit 120 then outputs the identified disaster area to the route search unit 130. The disaster area output by the disaster area identification unit 120 may include at least one of the disaster type, disaster probability, and risk level. The disaster area identification unit 120 may also output the changes in the ground surface used to identify the disaster area to the route search unit 130. The disaster area identification unit 120 may also output at least one of the disaster area and the changes in the ground surface to the route output unit 140.

[0069] The route search unit 130 uses the disaster area and traffic information to search for a route to a predetermined point (destination). For example, the route search unit 130 may use the disaster area and traffic information to search for a route to a predetermined point (destination) while avoiding roads that are dangerous or impassable. In this case, the route search unit 130 may receive a request for a destination point from a user or the like and search for a route to the requested point. The destination point is, for example, an evacuation center. The destination may not be a specific point but an area of ​​a certain size. That is, the route search unit 130 may search for a route to an area of ​​a certain size rather than a specific point. Furthermore, in addition to the destination, the route search unit 130 may receive a designation of a departure point from a user or the like. That is, the route search unit 130 may search for a route from the designated departure point to the destination. In this case, the route search unit 130 may search for a route in which at least one of the departure point and destination of the route to be searched is an area. A route in which at least one of the origin and destination is an area is a route from a point to an area, a route from an area to a point, or a route from one area to another. For example, the route search unit 130 may search for a route from the user's current location to an area outside the disaster area. However, for the sake of clarity in the following explanation, we will describe the search as searching for a route to a predetermined point, including the case of an area.

[0070] The method used by the route search unit 130 to search for a route is not particularly limited. The route search unit 130 may use any method to search for a route. For example, the route search unit 130 may use Dijkstra's algorithm, the Bellman-Ford algorithm, or the Floyd-Warshall algorithm. Alternatively, the route search unit 130 may acquire candidate routes and then search for a route from the acquired route candidates using the disaster area and traffic information. Hereinafter, candidate routes will be referred to as "route candidates." In this case, the method used by the route search unit 130 to acquire route candidates is not particularly limited. The route search unit 130 may use any method to acquire route candidates. For example, the route search unit 130 may acquire route candidates from a user or a predetermined device. For example, the route search unit 130 may acquire multiple route candidates from a user or the like and then search for a route from the acquired route candidates. Alternatively, the route search unit 130 may obtain route candidates from a user or other source, requested by the user, from a device (not shown).

[0071] Alternatively, the route search unit 130 may extract route candidates using predetermined information. For example, the route search unit 130 may obtain the origin and destination from a predetermined device, obtain map information from the information providing device 50, and extract route candidates connecting the origin and destination from the roads included in the map information. The predetermined device is, for example, the user's terminal device. The method by which the route search unit 130 extracts route candidates connecting the origin and destination is not particularly limited. For example, the route search unit 130 may use a method commonly used for route searching. A method commonly used for route searching is, for example, the method described above.

[0072] The route search unit 130 then searches for a route using traffic information and the disaster area. For example, a route that is included in the passable area and not in the disaster area is one of the routes that can be safely traveled. Hereinafter, a route that can be safely traveled will be called a "recommended route". For example, the route search unit 130 may search for a route that is included in the passable area and not in the disaster area as a recommended route. However, the recommended route is not limited to the above and may be any other route. For example, the recommended route may be a route that is included in the passable area, is at least a predetermined distance from the disaster area, and passes through a designated point. The predetermined distance is, for example, 100 meters. The designated point is, for example, a rest area. Alternatively, the route search unit 130 may search for a route that avoids the impassable area and the disaster area. That is, the route search unit 130 may remove routes that are included in at least one of the impassable area and the disaster area from the route candidates and use the remaining route candidates as routes.

[0073] Alternatively, if the disaster area identification unit 120 has acquired the type of ground surface, the route search unit 130 may search for a route using the type of ground surface in addition to the traffic information and the disaster area. For example, areas where the ground surface is water, snow, debris, or mud are likely to be difficult to pass through. Therefore, the route search unit 130 may search for a route from among the routes searched using the traffic information and the disaster area that does not include areas of water, snow, debris, or mud.

[0074] The route search unit 130 may further search for a route that satisfies predetermined conditions, such as conditions requested by users of the route, from among the routes searched using traffic information and the disaster area. For example, the route search unit 130 may search for the shortest distance route or the route with the shortest travel time from among the routes searched using traffic information and the disaster area. The route search unit 130 may search for more than one route. For example, the route search unit 130 may search for a predetermined number of routes starting from the shortest distance route, or routes with a distance shorter than a predetermined length route. Alternatively, the route search unit 130 may search for a predetermined number of routes starting from the shortest travel time route, or routes with a travel time shorter than a predetermined time route.

[0075] The predetermined conditions are not limited to the distance or time conditions mentioned above. For example, the route search unit 130 may search for a route that passes through at least one of a shelter, a rest area, and a shop, a route where rest areas are located at intervals shorter than a predetermined distance, or a route where the elevation difference is within a predetermined range. In this case, the route search unit 130 may acquire necessary information from the information providing device 50. For example, the route search unit 130 may acquire information on the location of shelters, rest areas, or shops from the information providing device 50 and search for a route that passes through shelters, rest areas, or shops. Alternatively, the route search unit 130 may acquire a topographic map from the information providing device 50 and use the acquired topographic map to determine the elevation difference of the route. The route search unit 130 may then search for a route that satisfies the elevation difference conditions requested by the user. A route that satisfies the elevation difference conditions requested by the user is, for example, a route with an elevation difference smaller than the requested elevation difference.

[0076] The route search unit 130 may calculate route-related information. The route-related information calculated by the route search unit 130 is not particularly limited. The route search unit 130 may calculate any information as route-related information. For example, route-related information may include the location of each point on the route, the length of the route or the length of each section included in the route, the elevation difference of the route, and the types of roads included in the route. Each point on the route may be, for example, the starting point, destination, and intermediate points. The type of road is not limited, but may include, for example, whether or not it is paved, the type of pavement, and the road classification. The road classification may be, for example, a national road, a prefectural road, a municipal road, or a main road or a local road.

[0077] The route search unit 130 may determine at least one of the passability, disaster possibility, and risk level of the searched route based on the passability including the traffic information and at least one of the disaster possibility and risk level included in the disaster area. The method used by the route search unit 130 to determine the passability, disaster possibility, and risk level of the route is not particularly limited. The route search unit 130 may use any method for determination.

[0078] For example, the route search unit 130 may use the lowest passability among the passability of the roads included in the route as the passability of the route. Alternatively, the route search unit 130 may use the highest disaster probability among the disaster probability of the roads included in the route as the disaster probability of the route. Alternatively, the route search unit 130 may use the highest risk level among the risk levels of the roads included in the route as the risk level of the route. However, the route search unit 130 may determine passability, disaster probability, or risk level different from those described above. For example, the route search unit 130 may determine the range of passability of the roads included in the route as passability. The range of passability of a road is, for example, the range between the maximum and minimum passability values ​​of the roads included in the route. In this way, the route search unit 130 may determine a range rather than a specific value as at least one of the passability, disaster probability, and risk level of the route.

[0079] The route search unit 130 may further search for a preferred route from a plurality of routes searched based on traffic information and disaster area, using at least one of the passability, disaster possibility, and risk level of the route. For example, the route search unit 130 may search for a predetermined number of routes from the routes searched based on traffic information and disaster area that have a higher probability of passability than a predetermined value, or routes that have a higher probability of passability. Alternatively, the route search unit 130 may search for a predetermined number of routes from the routes searched based on traffic information and disaster area that have a lower probability of disaster than a predetermined value, or routes that have a lower probability of disaster. Alternatively, the route search unit 130 may search for a predetermined number of routes from the routes searched based on traffic information and disaster area that have a lower risk level than a predetermined value, or routes that have a lower risk level.

[0080] The route search unit 130 may search for a route that satisfies the passability requirements requested by the user, based on the determined passability of the route. A route that satisfies the passability requirements requested by the user is, for example, a route with a higher passability than the requested passability. Alternatively, the route search unit 130 may search for a route that satisfies the disaster risk requirements requested by the user, based on the determined disaster risk of the route. A route that satisfies the disaster risk requirements requested by the user is, for example, a route with a lower disaster risk than the requested disaster risk. Alternatively, the route search unit 130 may search for a route that satisfies the risk level requirements requested by the user, based on the determined risk level of the route. A route that satisfies the risk level requirements requested by the user is, for example, a route with a lower risk level than the requested risk level. The route search unit 130 may search for a route using any two or all of the passability, disaster risk, and risk level.

[0081] The route search unit 130 may search for a route using road information posted on social media. For example, the route search unit 130 may search for multiple routes based on traffic information and the disaster area, acquire road information posted on social media related to each of the multiple routes, and search for a passable route based on the acquired information. The posted road information may be, for example, congestion information or road closure information. Alternatively, the route search unit 130 may use the congestion information of the route in the road information posted on social media to search for a route with less congestion. Alternatively, the route search unit 130 may use the road closure information of the route in the road information posted on social media to search for a route that is not closed.

[0082] If the route search unit 130 finds multiple routes as a result of the search, it may set a priority for each of the obtained routes. The information used by the route search unit 130 to set the priority is not particularly limited. The route search unit 130 may use any information as the information used to set the priority. For example, the route search unit 130 may set the priority based on at least one of the following: disaster area, traffic information, route passability, route disaster possibility, route risk, ground surface type, SNS posted road information, and information related to the calculated route. For example, the route search unit 130 may give a higher priority to routes with a high passability. Alternatively, the route search unit 130 may give a higher priority to routes with a low disaster possibility or routes with a low risk. Alternatively, the route search unit 130 may give a higher priority to routes with a short length or routes with a small elevation difference. Alternatively, the route search unit 130 may use multiple pieces of information to set the priority for routes. Multiple pieces of information could be, for example, a weighted average of passability and risk, or a weighted average of length and elevation difference.

[0083] The route search unit 130 does not have any particular limitations on the route it searches for. For example, it may search for evacuation routes in the event of a disaster, or for disaster investigation routes to investigate the disaster situation, or for supply routes to deliver relief supplies in the event of a disaster.

[0084] An example of the route search operation of the route search device 10 will be explained with reference to the drawing. Figure 3 is a diagram showing the starting point and destination used in the explanation. Figure 3 includes four vertical roads and two horizontal roads. The vertical roads are divided into three sections by the horizontal roads. Hereafter, these three sections will be referred to as the "upper, central, and lower sections." The horizontal roads are divided into five sections by the vertical roads. Hereafter, these five sections will be referred to as the "first, second, third, fourth, and fifth sections from the right." Figure 3 also uses arrows to indicate the route. The route shown with two arrows in Figure 3 is the shortest route from the starting point to the destination, and it is the route with the fewest changes of direction. Therefore, as a normal route when no disaster has occurred, the route in Figure 3 is one of the desirable routes.

[0085] Figure 4 shows an example of a route during a disaster. In the case of Figure 4, the traffic information generation unit 110 generates traffic information including impassable areas using sensor information. In Figure 4, the traffic information generation unit 110 uses sensor information to determine that the two upper sections and one central section are impassable areas. The disaster area identification unit 120 identifies the disaster area using changes in the ground surface. The area in the lower right of Figure 4 is the identified disaster area. The route search unit 130 then searches for a route that avoids the impassable areas included in the traffic information and the disaster area, as shown by the four arrows in Figure 4. Return to the explanation referring to Figure 1.

[0086] If no recommended routes exist, the route search unit 130 may search for a route that passes through at least one of the impassable area and the disaster area. In this case, for example, the route search unit 130 determines at least one of the passability, disaster possibility, and risk level of the route candidates based on the traffic information and the disaster area. Then, the route search unit 130 may search for a route from the route candidates based on the determined passability, disaster possibility, and risk level.

[0087] As an example in this case, the route search unit 130 may search for the route candidate with the highest probability of passage, a predetermined number of route candidates starting from the one with the highest probability of passage, or route candidates with a passability higher than a predetermined value. Alternatively, the route search unit 130 may search for the route candidate with the lowest probability of disaster, a predetermined number of route candidates starting from the one with the lowest probability of disaster, or route candidates with a disaster probability lower than a predetermined value. Alternatively, the route search unit 130 may search for the route candidate with the lowest degree of danger, a predetermined number of route candidates starting from the one with the lowest degree of danger, or route candidates with a danger level lower than a predetermined value. Alternatively, the route search unit 130 may search for a route from route candidates based on passability, disaster probability, and danger level, or any two or all of them. However, if there are no recommended routes, the route search unit 130 may output information indicating that there are no recommended routes without searching for a route. In the following description, the route output by the route search unit 130 will include information indicating that there are no routes.

[0088] The route search unit 130 then outputs the searched route to the route output unit 140. The route search unit 130 may also output information related to the route. Information related to the route may include, for example, the length of the route and the elevation difference. The route search unit 130 may output at least one of the traffic information and the disaster area used to search the route, along with the searched route. Alternatively, the route search unit 130 may output at least one of the passability of the route, the likelihood of disaster, and the degree of danger, along with the searched route. The route search unit 130 may also output information obtained from the information providing device 50 for searching the route, along with the searched route. For example, the information obtained from the information providing device 50 may include information on facilities along the route, map information, or disaster information. Facilities along the route may include, for example, shelters, rest areas, or shops. When searching for multiple routes, the route search unit 130 may output at least one of the following for each of the multiple routes: priority, route-related information, traffic information, disaster area, passability, risk level, and information obtained from the information providing device 50. The route search unit 130 may also output sensor information used to generate traffic information and changes in the ground surface used to identify the disaster area, in association with the route. For example, the route search unit 130 may output an image containing sensor information, in association with the route.

[0089] At least one of the traffic information generation unit 110, the disaster area identification unit 120, and the route search unit 130 may use a predetermined image recognition system. In this embodiment, the image recognition system is not particularly limited. For example, image recognition includes recognition using a judgment model, recognition using another method, and recognition combining the two. For example, a user may perform machine learning using information collected in advance as training data, and generate a judgment model that extracts candidate regions as a result of the machine learning. The information collected in advance may be, for example, road images or SAR images. The user may then store the generated judgment model in the route search device 10.

[0090] For example, if a judgment model generated using sensor information is stored, the traffic information generation unit 110 applies the acquired sensor information to the stored judgment model to generate traffic information. Alternatively, if a judgment model generated using SAR images is stored, the disaster area identification unit 120 applies the acquired SAR images to the stored judgment model to identify the disaster area. Alternatively, if a judgment model generated using traffic information and the disaster area is stored, the route search unit 130 applies the acquired traffic information and the disaster area to the stored judgment model to search for a route.

[0091] Furthermore, when using image recognition, at least one of the traffic information generation unit 110, the disaster area identification unit 120, and the route search unit 130 may calculate the likelihood of the image recognition result. Furthermore, at least one of the traffic information generation unit 110, the disaster area identification unit 120, and the route search unit 130 may determine the rank of the calculated likelihood. The rank may be, for example, high / medium / low likelihood. At least one of the traffic information generation unit 110, the disaster area identification unit 120, and the route search unit 130 may output at least one of the likelihood and rank to the route output unit 140.

[0092] The route output unit 140 outputs the route obtained from the route search unit 130 to a predetermined device. The predetermined device is, for example, a display device 40. The route output unit 140 may output information other than the route along with the route. For example, the route output unit 140 may output the priority of the route along with the route. The route output unit 140 may output changes in the ground surface in association with the route. The route output unit 140 may output sensor information in association with the route. For example, the route output unit 140 may output an image containing sensor information in association with the route. The route output unit 140 may output at least one of the passability of the route, the possibility of disaster, and the degree of danger along with the route. The route output unit 140 may output information related to the route. Information related to the route is, for example, the length of the route and the elevation difference. The route output unit 140 may output information obtained from the information providing device 50 in association with the route. Information obtained from the information providing device 50 is, for example, disaster information or map information. Alternatively, the route output unit 140 may output the measurement time of the SAR30 measurement results, which analyzes changes in the ground surface. The SAR30 measurement may have a longer acquisition cycle than the sensor information acquisition by the drive recorder 20. Therefore, the route search device 10 may output the acquisition time or measurement time of the SAR30 measurement results as temporal information related to route determination for the user or others.

[0093] The display device 40 displays the information output by the route output unit 140. The information output by the route output unit 140 is, for example, a route. The timing at which the display device 40 displays the information is not particularly limited. The display device 40 may display the information at any time. For example, the display device 40 may start displaying information in response to a request from a user. For example, the display device 40 obtains the departure point and destination from the user, and when it receives a request for a route corresponding to the obtained departure point and destination, it requests the route search device 10 for a route corresponding to the departure point and destination. The display device 40 then displays the route obtained from the route search device 10.

[0094] Furthermore, the display device 40 may display route-related information in response to requests from users or others. For example, the display device 40 may display at least one of the route length, elevation difference, and the types of roads included in the route in response to requests from users or others. The display device 40 may change the route-related information being displayed in response to requests from users or others. Alternatively, if the route search device 10 uses a judgment model, the display device 40 may display the likelihood or rank of the judgment using the judgment model in response to requests from users or others. In these cases, the display device 40 may request the route search device 10 to display information, or it may acquire information in advance and change the display in response to requests.

[0095] Next, the operation of the route search device 10 according to the first embodiment will be described with reference to the drawings. Figure 5 is a flowchart showing an example of the operation of the route search device 10 according to the first embodiment. The route search device 10 generates road traffic information using sensor information acquired from the drive recorder 20 (step S201). The route search device 10 identifies the disaster area using changes in the ground surface obtained based on the measurement results of the SAR 30 (step S202). Then, the route search device 10 searches for a route to a predetermined destination using the traffic information and the disaster area (step S203). Then, the route search device 10 outputs the searched route to a predetermined device. The predetermined device is, for example, a display device 40.

[0096] The route search device 10 configured as described above searches for an appropriate route. The reason is as follows: The route search device 10 includes a traffic information generation unit 110, a disaster area identification unit 120, and a route search unit 130. The traffic information generation unit 110 generates road traffic information using road-related sensor information acquired by a sensor information acquisition device. The sensor information acquisition device is, for example, a drive recorder 20. The disaster area identification unit 120 identifies the disaster area using ground surface changes obtained based on the measurement results of a ground surface measurement device. The ground surface measurement device is, for example, a SAR 30. The route search unit 130 searches for a route to a predetermined point using the disaster area and traffic information.

[0097] The traffic information generation unit 110 generates road traffic information using sensor information. The traffic information includes, for example, information that includes at least one of the passable area and the impassable area. Because the traffic information generation unit 110 uses sensor information, it can generate traffic information with an accuracy of several centimeters to tens of centimeters. The disaster area identification unit 120 uses changes in the ground surface obtained based on the measurement results of the ground surface measuring device, so it can identify the disaster area, including areas where vehicles cannot pass. Therefore, the route search unit 130 can search for a route using sensor information that can achieve the above accuracy, at least in areas where sensor information has been acquired. Furthermore, the route search unit 130 can use changes in the ground surface to search for a route that includes areas where vehicles cannot pass. Based on this configuration, the route search device 10 searches for an appropriate route.

[0098] The route search unit 130 may search for a recommended route. The recommended route may be a route that is included in the passable area included in the traffic information and does not include the disaster area. The passable area included in the traffic information is an area that can be traveled by moving objects such as vehicles. The disaster area is an area that is highly likely to be dangerous. Therefore, the route search unit 130 can search for a passable route that avoids dangerous areas. The traffic information generation unit 110 may use sensor information to determine road congestion and generate traffic information based on the determined congestion. In this case, the route search device 10 can search for a route taking into account the congestion that is occurring.

[0099] The route search unit 130 may search for a route based on the passability included in the traffic information. Passability is the possibility of being able to travel on a road. The possibility of being able to travel on a road is, for example, a probability. A route with a higher passability is preferable. Therefore, for example, the route search unit 130 can search for a route with a passability higher than a predetermined threshold as an appropriate route. The route search unit 130 may also search for a route based on at least one of the possibility of disaster and the degree of danger included in the disaster area. Possibility of disaster is the possibility that a disaster is occurring. The possibility of a disaster occurring is, for example, a probability. The degree of danger is the degree of danger at that point or area. A route that passes through areas where no disaster has occurred and is safe is preferable. Therefore, for example, the route search unit 130 can use at least one of the possibility of disaster and the degree of danger to search for a more appropriate route, such as a route that passes through areas with a low possibility of disaster or a route that passes through areas with a low degree of danger.

[0100] The route search unit 130 may search for a route using posted road information. For example, the route search unit 130 may search for a route using posted road information posted on social media. For example, a person traveling along a route may upload images of the route or comments about the route's condition to social media. In this case, the route search unit 130 may use social media to determine the route's condition and then search for a route using the determined condition. The traffic information generation unit 110 may generate traffic information using posted road information posted on social media. In this case, the traffic information generation unit 110 can generate more appropriate traffic information. The route search unit 130 can then use the traffic information generated in this way to search for a more appropriate route.

[0101] The route search unit 130 may set route priorities. If the route search unit 130 searches for multiple routes, users can use the priorities to select a route to use from among the multiple routes. In other words, the route search device 10 can generate priorities, which are information that users can use as a reference when selecting a route to use from among multiple routes. The sensor information may also be sensor information acquired from a sensor information acquisition device mounted on a mobile body. In this case, the route search device 10 can search for routes available to the mobile body. The mobile body is, for example, a vehicle. The sensor information acquisition device is, for example, a drive recorder 20.

[0102] The route search unit 130 may search for a route that satisfies predetermined conditions. The predetermined conditions are not limited, but may include, for example, at least one of the following: distance, time, rest areas, shops, and elevation differences. The route search unit 130 may also include, as predetermined conditions, at least one of the following: shelters to be passed through and dangerous structures. When using a route, users may want to use a route that satisfies predetermined conditions. For example, users may not only want to travel along a route, but also want to use certain facilities. Therefore, the route search unit 130 may search for a route that satisfies predetermined conditions. For example, the route search unit 130 may search for a route shorter than a predetermined distance, a route shorter than a predetermined time, a route that passes through a rest area or shop, and a route where the elevation difference is within a predetermined range. Alternatively, the route search unit 130 may search for at least one of the following: a route that passes through a predetermined shelter, and a route that does not pass through dangerous structures. In this case, the route search device 10 can search for a route that improves user convenience.

[0103] The route search device 10 may include a route output unit 140 that outputs a route. In this case, the route search device 10 can output the route to a predetermined device using the route output unit 140. The predetermined device is, for example, a display device 40. The route output unit 140 may also output changes in the ground surface in association with the route. Alternatively, the route output unit 140 may also output sensor information in association with the route. For example, the route output unit 140 may output an image containing sensor information in association with the route. This information is useful for users when using the route. In this way, the route search device 10 can output information that is useful when using the route.

[0104] The route search system 80 includes the route search device 10, a sensor information acquisition device, a ground surface measurement device, and a display device 40. The sensor information acquisition device is, for example, a drive recorder 20. The ground surface measurement device is, for example, a SAR 30. The route search device 10 operates as described above. The sensor information acquisition device outputs sensor information to the route search device. The ground surface measurement device outputs ground surface changes to the route search device 10. The display device 40 displays the route output by the route search device 10. Based on the above configuration, the route search system 80 can provide a route to a user or the like.

[0105] Next, the hardware configuration of the route search device 10 will be described. Each component of the route search device 10 may be made up of hardware circuits. Alternatively, each component of the route search device 10 may be made up of multiple devices connected via a network. For example, the route search device 10 may be made up using cloud computing. Alternatively, multiple components of the route search device 10 may be made up of a single piece of hardware.

[0106] Alternatively, the route search device 10 may be implemented as a computer device including a CPU (Central Processing Unit), ROM (Read Only Memory), and RAM (Random Access Memory). In addition to the above configuration, the route search device 10 may also be implemented as a computer device including a network interface circuit (NIC).

[0107] Figure 6 is a block diagram showing an example of the hardware configuration of the route search device 10. The route search device 10 includes a CPU 610, ROM 620, RAM 630, storage device 640, and NIC 650, and constitutes a computer device. The CPU 610 reads a program from at least one of the ROM 620 and the storage device 640. The CPU 610 then controls the RAM 630, storage device 640, and NIC 650 based on the program it has read. The computer, including the CPU 610, controls these components and realizes the functions of the traffic information generation unit 110, the disaster area identification unit 120, the route search unit 130, and the route output unit 140, as shown in Figure 1.

[0108] When implementing each function, the CPU 610 may use at least one of the RAM 630 and the storage device 640 as a temporary storage medium for programs and data. Alternatively, the CPU 610 may read programs contained in a storage medium 690, which stores programs in a computer-readable format, using a storage medium reader (not shown). Or, the CPU 610 may receive programs from an external device (not shown) via the NIC 650, store them in at least one of the RAM 630 and the storage device 640, and operate based on the stored programs.

[0109] ROM 620 stores programs executed by the CPU 610 and fixed data. ROM 620 is, for example, a P-ROM (Programmable-ROM) or flash ROM. RAM 630 temporarily stores at least one of the programs executed by the CPU 610 and data. RAM 630 is, for example, a D-RAM (Dynamic-RAM). Storage device 640 stores data and programs that the pathfinding device 10 stores long-term. Storage device 640 may also operate as a temporary storage device for the CPU 610. Storage device 640 is, for example, a hard disk drive, a magneto-optical disk drive, an SSD (Solid State Drive), or a disk array device.

[0110] ROM 620 and storage device 640 are non-transitory recording media. On the other hand, RAM 630 is a volatile recording media. The CPU 610 can operate based on programs stored in at least one of ROM 620, storage device 640, and RAM 630. In other words, the CPU 610 can operate using at least one of a non-volatile recording media and a volatile recording media.

[0111] The NIC650 relays data exchange with external devices (not shown) via the network. The NIC650 is, for example, a LAN (Local Area Network) card. Furthermore, the NIC650 may use wireless technology as well as wired connections. The route search device 10 configured in this way can achieve the same effects as the route search device 10 in Figure 1. This is because the CPU 610 of the route search device 10 can implement the same functions as the route search device 10 in Figure 1 based on a program.

[0112] <Second Embodiment> Next, a second embodiment will be described with reference to the drawings. Figure 7 is a block diagram showing an example of the configuration of a route search system 82 according to the second embodiment. The route search system 82 has the same configuration as the route search system 80, except that it includes a route search device 12 instead of a route search device 10. Therefore, a detailed explanation of the configuration other than the route search device 12 will be omitted.

[0113] The route search device 12 includes a route search unit 132 instead of the route search unit 130, and further includes a disaster area prediction unit 150. The traffic information generation unit 110 and the disaster area identification unit 120 operate in the same manner as in the first embodiment. The route search unit 132 operates in the same manner as the route search unit 130, except that it uses the prediction made by the disaster area prediction unit 150. Furthermore, the route output unit 140 operates in the same manner as the route output unit 140 of the first embodiment, except that it outputs the operational results of the route search unit 132 and the disaster area prediction unit 150. Therefore, the explanation below will omit as appropriate the same explanation as in the first embodiment and will focus on the disaster area prediction unit 150. Note that the route search device 12 may be configured using the hardware shown in Figure 6.

[0114] The disaster area prediction unit 150 uses the history of surface changes acquired by the disaster area identification unit 120 to predict changes in the ground surface at a predetermined future point in time. The history may be, for example, time-series information. The disaster area prediction unit 150 then uses the predicted changes in the ground surface to identify the disaster area at the predetermined point in time. The disaster area is, for example, the area of ​​a flood. The method for identifying the disaster area using the predicted changes in the ground surface in the disaster area prediction unit 150 may be the same identification method as that used by the disaster area identification unit 120. The disaster area prediction unit 150 may use any future point in time as the predetermined point in time. For example, the disaster area prediction unit 150 may use a point in time requested by a user or the like as the predetermined point in time. Alternatively, the disaster area prediction unit 150 may use multiple predetermined points in time.

[0115] Furthermore, the disaster area prediction unit 150 may predict traffic information at a predetermined time using the history of sensor information. For example, the disaster area prediction unit 150 may predict areas that are impassable. When making predictions at multiple predetermined time points, the disaster area prediction unit 150 may predict different targets at least some of the predetermined time points. For example, the disaster area prediction unit 150 may predict the disaster area for one predetermined time point and traffic information for another predetermined time point. Alternatively, the disaster area prediction unit 150 may predict the disaster area for one predetermined time point and predict both the disaster area and traffic information for another predetermined time point.

[0116] The configuration for storing the history of changes in the ground surface and the history of sensor information is not particularly limited. For example, the disaster area prediction unit 150 may store at least one of the history of changes in the ground surface and the history of sensor information. Alternatively, a storage unit (not shown) may store at least one of the history of changes in the ground surface and the history of sensor information. Alternatively, an external device (not shown) may store at least one of the history of changes in the ground surface and the history of sensor information.

[0117] The method used by the disaster area prediction unit 150 to predict the disaster area and traffic information is not particularly limited. For example, the disaster area prediction unit 150 may predict at least one of the disaster area and traffic information by applying a predetermined statistical prediction method to at least one of the history of changes in the ground surface and the history of sensor information. Examples of statistical prediction methods include autoregressive models, moving averages, or exponential averages. Alternatively, the disaster area prediction unit 150 may use a prediction model generated using machine learning that uses at least one of past changes in the ground surface and sensor information as training data. Furthermore, the disaster area prediction unit 150 may predict at least one of the timing of secondary disaster occurrence and the extent of secondary disaster at a predetermined time based on at least one of the history of changes in the ground surface and the history of sensor information.

[0118] The disaster area prediction unit 150 may predict at least one of the disaster area and traffic information at a predetermined time using the history of surface type in addition to the history of surface changes and the history of sensor information. The history of surface type is, for example, the history of water surface. The disaster area is, for example, the area of ​​flooding. Alternatively, the disaster area prediction unit 150 may predict at least one of the disaster area and traffic information at a predetermined time using information obtained from the information providing device 50, etc., in addition to the history of surface changes and the history of sensor information. The information obtained from the information providing device 50, etc., is, for example, disaster information. In its prediction, the disaster area prediction unit 150 may also use land-related information such as elevation, topography, and geology of each area.

[0119] The disaster area prediction unit 150 may change the method used to predict at least one of the disaster area and traffic information depending on the type of disaster. The types of disasters are, for example, floods or earthquakes. For example, in the case of a flood, the disaster area and the impassable area will be the area flooded by the flood. Therefore, the disaster area prediction unit 150 predicts at least one of the disaster area and traffic information based on the history of changes in the ground surface (and the history of the type of ground surface, if available). In this case, the disaster area is, for example, the area of ​​the flood. On the other hand, in the case of an earthquake, the progress of recovery will differ not only in terms of changes in the ground surface but also in terms of the condition of the road surface damage caused by the earthquake. The condition of the road surface damage is, for example, cracks, potholes, and subsidence. Therefore, in the case of an earthquake, the disaster area prediction unit 150 may predict at least one of the disaster area and traffic information based on the road surface damage condition predicted based on the history of sensor information, in addition to the prediction of changes in the ground surface determined based on the history of changes in the ground surface.

[0120] The route search unit 132 searches for a route at a predetermined time using at least one of the predicted disaster area and predicted traffic information. The predetermined time is the time when the disaster area, etc., is predicted. The route search unit 132 may also search for a route using at least one of the predicted timing of secondary disasters and the extent of secondary disasters. If the disaster area prediction unit 150 predicts disaster areas, etc., at multiple predetermined time points, the route search unit 132 may search for routes at multiple predetermined time points.

[0121] Figure 8 is a diagram illustrating the route searched by the route search unit 132 based on the predicted disaster area. Figure 8 shows the disaster area predicted by the disaster area prediction unit 150 after a predetermined time from Figure 4. The predetermined time is, for example, 12 hours later. The disaster area is, for example, the area where the ground surface changes significantly. As shown in Figure 8, the disaster area prediction unit 150 predicts that the disaster area after the predetermined time will be smaller than the disaster area in Figure 4. The route search unit 132 searches for a route using the predicted disaster area. As a result, the route search unit 132 searches for a route indicated by the four arrows in Figure 8. The route indicated by the four arrows in Figure 8 is shorter than the route indicated by the four arrows in Figure 4, due to the reduction in the disaster area.

[0122] The disaster area prediction unit 150 may predict the timing of road reopening using at least one of the history of surface changes and the history of sensor information. The method by which the disaster area prediction unit 150 predicts the reopening time is not particularly limited. For example, the disaster area prediction unit 150 predicts the likelihood of road reopening at a given time based on a prediction of surface changes made using the history of surface changes and a prediction of road conditions made using the history of sensor information. For example, the disaster area prediction unit 150 predicts passability as a likelihood of reopening. For example, the disaster area prediction unit 150 may predict the likelihood of reopening using a prediction model generated as a result of machine learning using the history of past surface changes and the history of past sensor information as training data. The disaster area prediction unit 150 may then define the reopening time as the time when the likelihood of road reopening exceeds a predetermined value. The time when the likelihood of road reopening exceeds a predetermined value is, for example, the time when passability exceeds 90%. The route search unit 132 may then use the reopening time to search for a route that includes the reopened road.

[0123] For example, if there are no recommended routes, the route search device 12 may use the recovery times to predict when at least one route will become a recommended route. The method used by the route search device 12 to predict when a route will become a recommended route is not particularly limited. The route search device 12 may use any method to predict when a route will become a recommended route. For example, the recovery time of a route is the recovery time of the road with the latest recovery time among the recovery times of each road that makes up the route. Therefore, first, the disaster area prediction unit 150 predicts the recovery time of each road. Then, the route search unit 132 uses the predicted recovery times of each road to predict the recovery time of each candidate route to a predetermined destination. Then, the route search unit 132 can search for the recovery time of the candidate route with the earliest recovery time among the predicted candidate route recovery times to determine when at least one route will become a recommended route. Furthermore, the route search unit 132 may search for the candidate route with the earliest recovery time as the route (recommended route) for that recovery time.

[0124] The disaster area prediction unit 150 may acquire information related to road restoration work, such as the local government's restoration plan, from a predetermined device, and use the acquired information related to restoration work to predict the timing of road restoration. The restoration plan is not particularly limited. For example, if the damage is fallen trees, the restoration plan may be a plan for removing fallen trees. Alternatively, if the damage is cracks in the road, the restoration plan may be a road repair plan. Alternatively, if the damage is a road sinkhole, the restoration plan may be a road repair plan. The route search unit 132 may search for a route based on the predicted timing of road restoration.

[0125] It should be noted that the predictions made by the disaster area prediction unit 150 may contain errors. Therefore, the route search unit 132 searches for based on the prediction may actually be impassable. In this case, the route search device 12 may output sensor information related to the route searched based on the prediction to a predetermined device via the route output unit 140. The predetermined device is, for example, a display device 40. In this case, users may determine whether or not to use the route (the route searched based on the prediction) by referring to the outputted sensor information to determine the status of the route searched based on the prediction.

[0126] Furthermore, it is conceivable that among the sensor information already acquired by the drive recorder 20, there may be unacquired sensor information related to the route explored based on the prediction. For example, after the route search device 12 has acquired the sensor information used for prediction, the vehicle equipped with the drive recorder 20 may be traveling along the route explored based on the prediction, or in the vicinity of the route. Alternatively, the drive recorder 20, which is a fixed camera, may have acquired sensor information for the route explored based on the prediction. In such cases, the route search device 12 may acquire the sensor information for the route explored based on the prediction and output it to the display device 40 or the like.

[0127] For example, the route search device 12 may use the traffic information generation unit 110 to query the drive recorder 20 to see if there is any unacquired sensor information related to the predicted route, and if there is, it may acquire the unacquired sensor information. The route search device 12 may then output the newly acquired sensor information to a predetermined device via the route output unit 140. The predetermined device is, for example, a display device 40. Users may, in the same manner as above, check the outputted sensor information and judge the feasibility of the predicted route. The sensor information is, for example, an image. The route search device 12 may also use the newly acquired sensor information to perform prediction and route search again. In this way, the route search device 12 may repeat prediction and route search.

[0128] The route search device 12 may acquire new sensor information using the traffic information generation unit 110 at a predetermined predicted time. The route search device 12 may then output the newly acquired sensor information to a predetermined device. The predetermined device is, for example, a display device 40. Users may refer to the outputted sensor information to determine whether the predicted route is passable as predicted. In this case, the disaster area prediction unit 150 may predict when sensor information will become available along that route. The route search device 12 may then output the time when sensor information will become available to the predetermined device via the route output unit 140. Users may then formulate a plan to acquire sensor information by referring to the displayed time.

[0129] Next, the operation of the route search device 12 according to the second embodiment will be described with reference to the drawings. Figure 9 is a flowchart showing an example of the operation of the route search device 12 according to the second embodiment. The traffic information generation unit 110 generates traffic information using sensor information acquired by the drive recorder 20 (step S201). The disaster area identification unit 120 determines the disaster area using ground surface changes obtained based on the measurement results of the SAR 30 (step S202).

[0130] The disaster area prediction unit 150 predicts the disaster area at a predetermined time using the history of changes in the ground surface (step S215). The disaster area prediction unit 150 may also predict the disaster area at a predetermined time using the history of sensor information. The disaster area prediction unit 150 may also predict traffic information at a predetermined time using at least one of the history of changes in the ground surface and the history of sensor information. Then, the route search unit 132 searches for a route at a predetermined time using the predicted disaster area (step S216). The route search unit 132 may also search for a route at a predetermined time using the predicted traffic information. Then, the route output unit 140 outputs the route at a predetermined time to a predetermined device (step S204). The predetermined device is, for example, a display device 40. Note that the route search unit 132 may also search for a route after step S202, similar to the operation described with reference to Figure 5.

[0131] The path search device 12 according to the second embodiment can search for an appropriate path at a predetermined time in addition to the effects of the first embodiment. The reason for this is as follows: Compared to the path search device 10, the path search device 12 includes a path search unit 132 instead of a path search unit 130, and further includes a disaster area prediction unit 150. The disaster area prediction unit 150 predicts the disaster area at a predetermined time using the history of ground surface changes. The path search unit 132 searches for a path at a predetermined time using the predicted disaster area. In this way, the path search device 12 can search for a path at a predetermined time using the above configuration.

[0132] The disaster area prediction unit 150 may predict traffic information at a predetermined time using the history of sensor information. The route search unit 132 may search for a route at a predetermined time using the predicted traffic information. In this case, the route search device 12 can search for a more appropriate route using at least one of the history of ground surface changes and the history of sensor information.

[0133] The disaster area prediction unit 150 may predict the timing of road restoration. Furthermore, the route search unit 132 may use the restoration timing to search for a route. In this case, the route search device 12 can search for a route that takes into account the predicted road restoration timing. The route search unit 132 may also predict the timing when at least one route will become a recommended route. In this case, if there is no recommended route, the route search device 12 can predict the timing when a recommended route will become available as the road is restored. The route output unit 140 may output the timing when at least one route will become a recommended route, as well as the recommended route itself. In this way, the route search device 12 can provide users and others with information related to the prediction.

[0134] <Third Embodiment> The route search device 10 may store the searched route in a storage unit (not shown) and output it in response to a request from a user or the like. Alternatively, the route search device 10 may be equipped with a display unit (not shown) and display the route on the display unit. In these cases, the route search device 10 does not need to include a route output unit 140. Therefore, a third embodiment will be described as the above-described case.

[0135] Figure 10 is a block diagram showing an example of the configuration of a route search device 13 according to a third embodiment. The route search device 13 includes a traffic information generation unit 110, a disaster area identification unit 120, and a route search unit 130. The traffic information generation unit 110 generates road traffic information using road-related sensor information acquired by a sensor information acquisition device. The sensor information acquisition device is, for example, a drive recorder 20. The disaster area identification unit 120 identifies the disaster area using ground surface changes obtained based on measurement results from a ground surface measurement device. The ground surface measurement device is, for example, a SAR 30. The route search unit 130 searches for a route to a predetermined point using the traffic information and the disaster area. The route search device 13 may be configured using the hardware configuration shown in Figure 6. The route search device 13 configured as described above can search for an appropriate route, similar to the route search device 10.

[0136] <Fourth Embodiment> The route search system 80 may not include the information providing device 50. Therefore, an example of such a configuration will be described as the fourth embodiment. Figure 11 is a block diagram showing an example configuration of the route search system 84 according to the fourth embodiment. The route search system 84 includes a route search device 10, a sensor information acquisition device 21, a ground surface measurement device 31, and a display device 40. The route search device 10 includes a traffic information generation unit 110, a disaster area identification unit 120, a route search unit 130, and a route output unit 140. The route search device 10 operates similarly to the route search device 10 of the first embodiment, except that it does not acquire information from the information providing device 50. The route search device 10 according to the fourth embodiment may be configured using the hardware configuration shown in Figure 6.

[0137] In the route search system 84 configured in this way, the route search device 10 operates as already described. That is, the route search device 10 generates traffic information using sensor information acquired by the sensor information acquisition device 21. The sensor information acquisition device 21 is, for example, a drive recorder 20. The route search device 10 then acquires ground surface changes obtained based on the measurement results of the ground surface measurement device 31. The route search device 10 then identifies the disaster area using the ground surface changes. The ground surface measurement device 31 is, for example, a SAR 30. The route search device 10 then searches for a route to a predetermined point based on the traffic information and the disaster area. The route search device 10 then outputs the route. The sensor information acquisition device 21 outputs sensor information to the route search device 10. The ground surface measurement device 31 outputs measurement results to the route search device 10. The display device 40 then acquires the route from the route search device 10 and displays it. The route search system 84 configured in this way can obtain the same effects as the route search system 80.

[0138] Some or all of the above embodiments may also be described as follows, but are not limited to the following:

[0139] (Note 1) A traffic information generation means generates road traffic information using road-related sensor information acquired by a sensor information acquisition device, A means for identifying the extent of a disaster, which uses changes in the ground surface obtained based on the measurement results of a ground surface measuring device to identify the extent of the disaster, A route search means that uses disaster area and traffic information to search for a route to a predetermined point. A pathfinding device that includes [a specific component].

[0140] (Note 2) The route search means searches for a recommended route as the route. The route search device described in Appendix 1.

[0141] (Note 3) The recommended route is one that is included in the passable area described in the traffic information and is not included in the disaster area. The route search device described in Appendix 2.

[0142] (Note 4) The traffic information generation means uses sensor information to determine road congestion and generates traffic information based on the determined congestion. A route search device as described in any one of the items 1 to 3 of the appendix.

[0143] (Note 5) The route search means searches for a route based on the passability included in the traffic information, and at least one of the possibility of disaster and the degree of risk included in the disaster area. A route search device as described in any one of the items 1 to 4 of the appendix.

[0144] (Note 6) Includes disaster area prediction means that predicts the extent of a disaster at a predetermined point in time using the history of changes in the ground surface, The route search means searches for a route at a predetermined time using the predicted disaster area. A route search device as described in any one of the items 1 to 5 of the appendix.

[0145] (Note 7) The disaster area prediction means predicts traffic information at a predetermined point in time using the history of sensor information. The route search means searches for a route at a predetermined time using predicted traffic information. The route search device described in Appendix 6.

[0146] (Note 8) Disaster extent prediction method predicts the timing of road repair, The route search method uses the road repair schedule to search for a route. A route search device as described in Appendix 6 or 7.

[0147] (Note 9) The route search means predicts when at least one route will become the recommended route. A route search device as described in any one of the appendices 6 to 8.

[0148] (Note 10) The route search method searches for a route using the posted road information. A route search device as described in any one of the appendices 1 to 9.

[0149] (Note 11) The route search method searches for a route using road information posted on a social networking service. The route search device described in Appendix 10.

[0150] (Note 12) The traffic information generation means generates traffic information using road information posted on social networking services. The route search device described in Appendix 11.

[0151] (Note 13) The route search means sets a priority for the route. A route search device as described in any one of the appendices 1 to 12.

[0152] (Note 14) Sensor information is sensor information obtained from a sensor information acquisition device mounted on a mobile object. A route search device as described in any one of the appendices 1 to 13.

[0153] (Note 15) The route search means searches for a route that satisfies predetermined conditions. A route search device as described in any one of the appendices 1 through 14.

[0154] (Note 16) The specified conditions include at least one of the following: distance, time, rest areas, shops, and elevation differences. The route search device described in Appendix 15.

[0155] (Note 17) The specified conditions include at least one of the shelters and hazardous structures that pass through. The route search device described in Appendix 16.

[0156] (Note 18) Route output means for completing a route A route search device as described in any one of the appendices 1 to 17, including the following:

[0157] (Note 19) The route output means outputs at least one of ground surface changes and sensor information in relation to the route. The route search device described in Appendix 18.

[0158] (Note 20) A route output means that outputs the time when at least one route becomes the recommended route and the recommended route. A route search device as described in any one of the appendices 2 to 17, including the following:

[0159] (Note 21) A route search device described in any one of the items 1 to 20 of the appendix, The pathfinding device includes a sensor information acquisition device that outputs sensor information. A route search system that includes this.

[0160] (Note 22) Using the sensor information related to the road acquired by the sensor information acquisition device, road traffic information is generated. The extent of the disaster is identified using the ground surface changes obtained based on the measurement results from the ground surface measurement device. Using disaster area and traffic information, a route to a designated point is searched. Route search method.

[0161] (Note 23) The route search device executes the route search method described in Appendix 22, The sensor information acquisition device outputs sensor information to the path search device. Route search method.

[0162] (Note 24) The process involves generating road traffic information using road-related sensor information acquired by a sensor information acquisition device. A process to identify the extent of the disaster using changes in the ground surface obtained based on the measurement results of the ground surface measurement device, A process that uses the disaster area and traffic information to search for a route to a predetermined point. A recording medium that stores programs that cause a computer to execute.

[0163] Although the present invention has been described above with reference to embodiments, the present invention is not limited to the above embodiments. Various modifications to the structure and details of the present invention can be made, as can be understood by those skilled in the art within the scope of the present invention. [Explanation of symbols]

[0164] 10. Pathfinding device 12. Pathfinding device 13. Pathfinding device 20 Dashcams 21 Sensor Information Acquisition Device 30 SAR 31 Ground measurement device 40 Display device 50 Information provision device 80 Route Search Systems 82 Route Search Systems 84 Route Search Systems 110 Traffic information generation section 120 Disaster Area Identification Department 130 Route Search Unit 132 Route Search Unit 140 Route Output Section 150 Disaster Area Prediction Department 610 CPU 620 ROM 630 RAM 640 Storage device 650 NIC 810 Computer 820 Dashcam 830 SAR System 840 Terminal devices 850 vehicles 880 Network

Claims

1. A traffic information generation means generates road traffic information using road-related sensor information acquired by a sensor information acquisition device, A means for identifying the extent of a disaster, which uses changes in the ground surface obtained based on the measurement results of a ground surface measuring device to identify the extent of the disaster, A route search means that searches for a route to a predetermined point using the disaster area and the traffic information. Includes, The aforementioned sensor information acquisition device is a device mounted on a vehicle traveling on a road. The aforementioned sensor information is an image of the road after the disaster occurred. The aforementioned surface measurement device is a synthetic aperture radar mounted on an artificial satellite. The disaster area identification means acquires an image of the area to be searched for along the path from the synthetic aperture radar as a measurement result, analyzes the ground surface changes using the acquired image, identifies the disaster area using the analyzed ground surface changes, and further, Includes disaster area prediction means that predicts the extent of a disaster at a predetermined point in time using the history of ground surface changes, The disaster extent prediction means acquires information related to road restoration work from a predetermined device, predicts the timing of road restoration using the acquired information related to restoration work, and predicts the disaster extent at the predetermined time based on the predicted restoration timing. The route search means searches for the route at the predetermined time using the predicted disaster area. Route search device.

2. The route search means searches for a recommended route as the route. The pathfinding device according to claim 1.

3. The recommended route is the route that is included in the passable area described in the traffic information and is not included in the disaster area. The pathfinding device according to claim 2.

4. The traffic information generation means uses the sensor information to determine road congestion and generates traffic information based on the determined congestion. A route search device according to any one of claims 1 to 3.

5. The route search means searches for the route based on the passability included in the traffic information and at least one of the possibility of disaster and the degree of risk included in the disaster area. A pathfinding device according to any one of claims 1 to 4.

6. A pathfinding device according to any one of claims 1 to 5, The path search device is equipped with a sensor information acquisition device that outputs the sensor information. A route search system that includes this.

7. Using the sensor information related to the road acquired by the sensor information acquisition device, road traffic information is generated. The extent of the disaster is identified using the ground surface changes obtained based on the measurement results from the ground surface measurement device. Using the aforementioned disaster area and traffic information, a route to a predetermined point is searched. The aforementioned sensor information acquisition device is a device mounted on a vehicle traveling on a road. The aforementioned sensor information is an image of the road after the disaster occurred. The aforementioned surface measurement device is a synthetic aperture radar mounted on an artificial satellite. In identifying the disaster area, the measurement results include obtaining an image of the area to be searched for along the path from the synthetic aperture radar, analyzing the ground surface changes using the obtained image, identifying the disaster area using the analyzed ground surface changes, and further, Using the aforementioned history of ground surface changes, the extent of the disaster at a predetermined time is predicted, and further, information related to road restoration work is obtained from a predetermined device, the timing of road restoration is predicted using the obtained information related to restoration work, and the extent of the disaster at the predetermined time is predicted based on the predicted restoration timing. Using the predicted disaster area, the route at the predetermined time is searched. Route search method.

8. The route search device performs the route search method described in claim 7, The sensor information acquisition device outputs the sensor information to the path search device. Route search method.

9. The process involves generating road traffic information using road-related sensor information acquired by a sensor information acquisition device. A process to identify the extent of the disaster using changes in the ground surface obtained based on the measurement results of the ground surface measurement device, A process to search for a route to a predetermined point using the aforementioned disaster area and the aforementioned traffic information. Have the computer run it, The aforementioned sensor information acquisition device is a device mounted on a vehicle traveling on a road. The aforementioned sensor information is an image of the road after the disaster occurred. The aforementioned surface measurement device is a synthetic aperture radar mounted on an artificial satellite. The process for identifying the disaster area involves obtaining an image of the area to be searched for along the path from the synthetic aperture radar as a measurement result, analyzing the ground surface changes using the obtained image, and identifying the disaster area using the analyzed ground surface changes, and further, This process includes predicting the extent of a disaster at a predetermined point in time using the aforementioned history of surface changes. The process for predicting the extent of the disaster involves obtaining information related to road restoration work from a predetermined device, predicting the timing of road restoration using the obtained information related to restoration work, and predicting the extent of the disaster at the predetermined time based on the predicted restoration timing. The process of searching for the aforementioned path is a process of searching for the aforementioned path at a predetermined time using the predicted disaster area. program.

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