Road survey method

Abstract

To provide an orthoimage creation system and an orthoimage creation method for easily investigating a road state at the time of repair construction when repairing a road, and to provide a survey marker and a road investigation method used therefor.SOLUTION: The ortho-image creation method includes a coordinate acquisition step of acquiring three dimensional coordinates of a plurality of survey markers 6, a photographing step of photographing a plurality of photographed images of the plurality of survey markers 6 by a UAV (UnmannedAerialVehicle) 3 flying at an altitude of 20 meters or less above the ground so that each survey marker 6 is included in at least two photographed images, and an ortho-image creation step of creating an ortho-image based on the three dimensional coordinates of each feature point acquired in the coordinate acquisition step and the plurality of photographed images photographed in the photographing step.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to an orthoimage creation system and method for creating orthoimages based on images taken from the sky by, for example, an unmanned aerial vehicle, and an anti-aircraft sign and road inspection method used therein. [Background technology]

[0002] Conventionally, when damage such as cracks occurs on the surface of the asphalt pavement that makes up the surface layer of a road, the road needs to be repaired.

[0003] In order to repair a road, various investigations are conducted, such as investigating the road condition at the time of commencement of repair work and the positions of planar elements including road edges and lane markings. For example, investigations are conducted into the locations of cracks on the road and the amount of cracks. Conventionally, investigations into the condition of cracks have been conducted visually by inspectors, but the work of inspecting the road and detecting cracks by each inspector is extremely cumbersome. Therefore, instead of inspectors detecting cracks, road conditions are sometimes investigated using a dedicated road surface property measurement vehicle (see Patent Document 1). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2018-123510 Summary of the Invention [Problem to be solved by the invention]

[0005] When inspecting road conditions using a dedicated road surface condition measurement vehicle, the vehicle must be driven, but on narrow roads, the vehicle cannot drive and it is impossible to inspect the road conditions.

[0006] In addition, the positions of planar elements, including road edges and lane markings, in the repair area where repairs are to be performed, are surveyed. Conventionally, a large number of planar positions on the road edges and lane markings are surveyed, and planar elements, including road edges and lane markings, are mapped based on each planar position. Therefore, in order to map the planar elements, it is necessary to survey a large number of planar positions, which is very cumbersome.

[0007] If there is a manhole in the repair area, an investigation is conducted into the manhole adjustment height. The investigation into the manhole adjustment height involves investigating the adjustment height (the difference in elevation between the elevation at the time of repair work commencement and the elevation of the repair plan surface) for each position in the longitudinal and transverse directions of the manhole.

[0008] Conventionally, the elevation of each horizontal position around the manhole is detected based on the vertical and horizontal sections of the road that pass through each horizontal position, and the adjustment height is calculated from the difference in elevation between that elevation and the elevation of the repair plan surface. Therefore, it is necessary to detect the elevation of each horizontal position based on the vertical and horizontal sections of the road for each manhole, which is very cumbersome.

[0009] The present invention has been made with an eye on such problems, and aims to provide an orthoimage creation system, an orthoimage creation method, and an anti-aircraft sign and road survey method to be used therein, which make it possible to easily survey the road condition at the time of starting road repair work when repairing the road. [Means for solving the problem]

[0010] In order to solve the above problems, the present invention takes the following measures.

[0011] In other words, the orthoimage creation system of the present invention is characterized by comprising a coordinate storage means for storing three-dimensional coordinates for a plurality of feature points, a captured image storage means for storing a plurality of captured images for the plurality of feature points taken by an unmanned aerial vehicle or model aircraft flying at an altitude of 20 meters or less above the ground so that each feature point is included in at least two captured images, and an orthoimage creation means for creating an orthoimage based on the three-dimensional coordinates of each feature point stored in the coordinate storage means and the plurality of captured images stored in the captured image storage means.

[0012] The orthoimage creation method of the present invention is characterized by comprising a coordinate acquisition step of acquiring three-dimensional coordinates for a plurality of feature points, a photographing step of taking a plurality of photographic images for the plurality of feature points using an unmanned aerial vehicle or a model aircraft flying at an altitude of 20 meters or less above the ground so that each feature point is included in at least two photographic images, and an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired by the coordinate acquisition step and the plurality of photographic images taken by the photographing step.

[0013] As a result, the orthoimage creation system and orthoimage creation method of the present invention create orthoimages based on multiple images taken by an unmanned aerial vehicle or model aircraft flying at an altitude of 20 meters or less above the ground, making it possible to create orthoimages that clearly show the condition of the road surface and the location of planar elements around the road.The orthoimages created by the present invention make it possible to clearly identify areas where cracks have occurred or where patching has occurred on the road.Therefore, since there is no need to run a dedicated road surface property measurement vehicle to investigate the condition of cracks on the road surface, it is possible to investigate road conditions regardless of road width.

[0014] Furthermore, in the orthoimages created by the present invention, the positions of planar elements including road edges, lane markings, etc. can be clearly identified. Therefore, since it is not necessary to conduct surveys at a large number of planar positions in order to plot planar elements including road edges, lane markings, etc., planar elements can be easily plotted based on the orthoimages.

[0015] Furthermore, the orthoimage created by this invention makes it possible to detect the longitudinal and transverse planar positions of the area surrounding the manhole. Therefore, after identifying the longitudinal and transverse planar positions of the area surrounding the manhole, the elevation of each planar position can be extracted from the point cloud data acquired by the 3D scanning device. Therefore, there is no need to create longitudinal and transverse road sections for each manhole in order to detect the elevation of each longitudinal and transverse planar position of the area surrounding the manhole. Therefore, it is possible to easily detect the manhole adjustment height.

[0016] In the orthoimage creation system of the present invention, the feature points are anti-aircraft markers installed on the ground at the time of photographing by the unmanned aerial vehicle or the model aircraft, and the coordinate storage means stores the three-dimensional coordinates of the anti-aircraft markers obtained by a total station, a satellite-based positioning system, and a three-dimensional scanning device.

[0017] In the orthoimage creation method of the present invention, the feature points are anti-aircraft markers installed on the ground at the time of photographing in the photographing step, and the coordinate acquisition step is characterized in that the three-dimensional coordinates of the anti-aircraft markers are acquired by a total station, a satellite-based positioning system, and a three-dimensional scanning device.

[0018] As a result, the orthoimage creation system and orthoimage creation method of the present invention can create orthoimages based on images taken by an unmanned aerial vehicle or a model aircraft, making it possible to create orthoimages that clearly show the condition of the road surface and the positions of planar elements around the road.

[0019] In the orthoimage creation system of the present invention, the feature points are predetermined points within the images taken by the unmanned aerial vehicle or the model aircraft, and the coordinate storage means stores the three-dimensional coordinates of the predetermined points extracted from the three-dimensional coordinated point cloud data obtained for each point within the photographed image.

[0020] In the orthoimage creation method of the present invention, the feature points are specified points within an image taken by the unmanned aerial vehicle or the model aircraft, and the coordinate acquisition step is characterized in that the three-dimensional coordinates of the specified points are acquired from three-dimensionally coordinated point cloud data acquired for each point within the captured image.

[0021] As a result, the orthoimage creation system and orthoimage creation method of the present invention can create orthoimages based on images taken by an unmanned aerial vehicle or a model aircraft, making it possible to create orthoimages that clearly show the condition of the road surface and the positions of planar elements around the road.

[0022] The airborne marker according to the present invention is an airborne marker used in the orthoimage creation system according to the present invention, and is characterized in that it is in the form of a sticker with an adhesive layer formed on the back side, which makes it possible to easily fix the airborne marker to the installation location.

[0023] The anti-aircraft marker according to the present invention is an anti-aircraft marker used in the orthoimage creation method according to the present invention, and is characterized in that it is in the form of a sticker with an adhesive layer formed on the back side, which makes it possible to easily fix the anti-aircraft marker to the installation location.

[0024] The road survey method of the present invention is characterized by comprising: a coordinate acquisition step for acquiring three-dimensional coordinates of a plurality of feature points; a photographing step for taking a plurality of photographic images for the plurality of feature points using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground so that each feature point is included in at least two photographic images; an orthoimage creation step for creating an orthoimage based on the three-dimensional coordinates of each feature point acquired by the coordinate acquisition step and the plurality of photographic images taken by the photographing step; a display step for displaying the orthoimage on a display unit; a derivation step for dividing the survey area into a plurality of survey ranges in the orthoimage displayed on the display unit and deriving a crack rate or patching rate for each of the plurality of survey ranges; and a road condition display step for displaying the road condition by adding a color to the orthoimage displayed on the display unit according to the magnitude of the crack rate or patching rate of each survey range derived by the derivation step.

[0025] As a result, the road inspection method of the present invention creates an orthoimage based on multiple images taken by an unmanned aerial vehicle or model aircraft flying at an altitude of 20 meters or less above the ground, making it possible to create an orthoimage that clearly identifies the condition of the road surface and the positions of planar elements around the road. The orthoimage created by the present invention makes it possible to clearly identify areas where cracks have occurred on the road or areas where patching has occurred. Therefore, since there is no need to run a dedicated road surface property measurement vehicle to inspect the crack condition of the road surface, it is possible to inspect the road condition regardless of the road width.

[0026] The road survey method of the present invention is characterized by comprising a coordinate acquisition step of acquiring three-dimensional coordinates for a plurality of feature points; a photographing step of taking a plurality of photographic images for the plurality of feature points using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground so that each feature point is included in at least two photographic images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired by the coordinate acquisition step and the plurality of photographic images taken by the photographing step; a display step of displaying the orthoimage on a display unit; and a planar element mapping step of tracing planar elements in the orthoimage displayed on the display unit to map the planar elements.

[0027] As a result, the road survey method of the present invention creates an orthoimage based on multiple images taken by an unmanned aerial vehicle or model aircraft flying at an altitude of 20 meters or less above the ground, making it possible to create an orthoimage that clearly identifies the condition of the road surface and the positions of planar elements around the road.The orthoimage created by the present invention makes it possible to clearly identify the positions of planar elements, including road edges and lane markings.Therefore, since it is not necessary to survey a large number of points to map planar elements, including road edges and lane markings, it is possible to easily map planar elements based on the orthoimage.

[0028] The road survey method of the present invention is characterized by comprising a coordinate acquisition step of acquiring three-dimensional coordinates for a plurality of feature points; a photographing step of taking a plurality of photographic images for the plurality of feature points using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground so that each feature point is included in at least two photographic images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired by the coordinate acquisition step and the plurality of photographic images taken by the photographing step; a display step of displaying the orthoimage on a display unit; a point cloud data acquisition step of acquiring point cloud data of an area including the periphery of a manhole in the orthoimage; and an elevation difference derivation step of deriving the elevation difference between the elevation of the periphery of the manhole in the orthoimage displayed on the display unit and the elevation of the periphery of the manhole on a repair planning screen.

[0029] As a result, the road survey method of the present invention creates an orthoimage based on multiple images taken by an unmanned aerial vehicle or model aircraft flying at an altitude of 20 meters or less above ground, making it possible to create an orthoimage that clearly identifies the condition of the road surface and the location of planar elements around the road. The orthoimage created by the present invention makes it possible to detect the longitudinal and transverse planar positions of the area around the manhole. Therefore, after identifying the longitudinal and transverse planar positions of the area around the manhole, it is possible to extract the elevation of each planar position from the point cloud data of the area including the area around the manhole. Therefore, there is no need to create longitudinal and transverse road sections for each manhole to detect the elevation of each longitudinal and transverse planar position of the area around the manhole. Therefore, it is possible to easily detect the adjusted manhole height.

[0030] The road survey method of the present invention is characterized by comprising a coordinate acquisition step of acquiring three-dimensional coordinates for a plurality of feature points; a photographing step of taking a plurality of photographic images for the plurality of feature points using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground so that each feature point is included in at least two photographic images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired by the coordinate acquisition step and the plurality of photographic images taken by the photographing step; a point cloud data acquisition step of acquiring point cloud data of an area within the orthoimage; a display step of displaying the orthoimage on a display unit; a designation step of designating two designated points spaced apart from each other in the orthoimage displayed on the display unit; and a distance display step of displaying the distance between the two designated points when the two designated points are designated by the designation step.

[0031] As a result, the road inspection method of the present invention creates an orthoimage based on multiple images taken by an unmanned aerial vehicle or model aircraft flying at an altitude of 20 meters or less above the ground, and by associating the orthoimage with point cloud data of the area within the orthoimage, it is possible to clearly determine the positions of planar elements including road edges and lane markings and other dividing lines, while also displaying, for example, the distance between two specified points in the area surrounding the road in the orthoimage. Therefore, even if an inspector does not measure the distance between two specified points in the area surrounding the road, the distance between the two specified points can be easily detected by specifying the two specified points on the display unit displaying the orthoimage.

[0032] The road survey method of the present invention is characterized by comprising a coordinate acquisition step of acquiring three-dimensional coordinates for a plurality of feature points; a photographing step of taking a plurality of photographic images for the plurality of feature points using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground so that each feature point is included in at least two photographic images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired by the coordinate acquisition step and the plurality of photographic images taken by the photographing step; a point cloud data acquisition step of acquiring point cloud data of an area within the orthoimage; a display step of displaying the orthoimage on a display unit; a designation step of designating a specified range within the orthoimage displayed on the display unit; and an area display step of displaying the area of ​​the specified range when the specified range is designated by the designation step.

[0033] As a result, the road inspection method of the present invention creates an orthoimage based on multiple images taken by an unmanned aerial vehicle or model aircraft flying at an altitude of 20 meters or less above the ground, and by associating the orthoimage with point cloud data of the area within the orthoimage, it is possible to clearly determine the positions of planar elements including road edges and lane markings and other dividing lines, and to display, for example, the area of ​​a specified range within the road surrounding area within the orthoimage. Therefore, even if an inspector does not measure the area of ​​the specified range within the road surrounding area, the area of ​​the specified range can be easily detected by specifying the specified range on the display unit displaying the orthoimage. [Effects of the Invention]

[0034] As described above, according to the present invention, by creating an orthoimage based on multiple images taken by an unmanned aerial vehicle or model aircraft flying at an altitude of 20 meters or less above the ground, it is possible to create an orthoimage that clearly identifies the condition of the road surface and the location of planar elements around the road. The orthoimage created by the present invention clearly identifies the locations of planar elements, including cracked areas and patched areas on the road, road edges, and lane markings, and can detect the longitudinal and transverse planar positions around manholes. The road survey method of the present invention allows the distance between two specified points to be easily detected by specifying two specified points on a display unit displaying an orthoimage. The road survey method of the present invention allows the area of ​​a specified range to be easily detected by specifying a specified range on a display unit displaying an orthoimage. [Brief explanation of the drawings]

[0035] [Figure 1] 1 is a diagram showing a schematic configuration of an orthoimage creation system according to an embodiment of the present invention. [Figure 2] FIG. 10 is a diagram showing a state in which a plurality of anti-aircraft signs are installed near both ends of a road when the road is photographed from above. [Figure 3] FIG. [Figure 4] FIG. 10 is a diagram illustrating a state in which an anti-aircraft marker is included in two captured images. [Figure 5] FIG. 1 is a diagram illustrating a method for creating an orthoimage in an orthoimage creation device. [Figure 6] FIG. 10 is a diagram showing a state in which an orthoimage is displayed on a display unit. [Figure 7] FIG. 1 is an enlarged view of a road surface on which cracks have formed. [Figure 8] FIG. 1 is an enlarged view of a road surface on which cracks have formed. [Figure 9] An enlarged view of the road surface where cracks have formed. [Figure 10] A close-up view of the road surface with a manhole. [Figure 11] FIG. 1 is a diagram illustrating the tape used to evaluate the detection of cracks formed on the road surface. [Figure 12] FIG. 12 is a diagram showing the state in which the tape of FIG. 11 is attached to the road surface. [Figure 13] FIG. 13 is a diagram showing an orthoimage of the road surface of FIG. 12. [Figure 14] FIG. 1 is a diagram illustrating a method for investigating the crack condition of a road surface. [Figure 15] FIG. 10 is a diagram showing a survey area in an orthoimage displayed on a display unit. [Figure 16] FIG. 16 is an enlarged view of part A within the survey area shown in FIG. 15. [Figure 17] FIG. 10 is a diagram showing the results of investigating the road surface conditions for each survey area in the entire survey area. [Figure 18] 10A and 10B are diagrams illustrating a method for investigating the positions of planar elements around a road. [Figure 19] FIG. 10 is a diagram showing a survey area in an orthoimage displayed on a display unit. [Figure 20] This is an ortho-CAD plan view of the orthoimage. [Figure 21] This is a diagram in which planar elements around the road have been traced on the ortho-CAD plan view of Figure 20. [Figure 22] This is a diagram illustrating planar elements of the entire survey area. [Figure 23] FIG. 1 is a diagram illustrating an investigation method for repairing the area around a manhole. [Figure 24] FIG. 10 is a diagram showing a survey area in an orthoimage displayed on a display unit. [Figure 25] FIG. 1 is a schematic diagram illustrating a longitudinal section plan. [Figure 26] FIG. 1 is a schematic diagram illustrating a cross-sectional plan. [Figure 27] FIG. 10 is a diagram showing the elevation of a predetermined position around a manhole displayed. [Figure 28] FIG. 10 is a diagram showing the adjustment heights of each position around the manhole. [Figure 29]FIG. 10 is a diagram illustrating a method for investigating the distance between specified points on the road surface. [Figure 30] FIG. 10 is a diagram showing a state in which the distance between specified points on the road surface is displayed. [Figure 31] FIG. 10 is a diagram illustrating a method for investigating the area of ​​a specified range on a road surface. [Figure 32] FIG. 10 is a diagram showing a state in which the area of ​​a specified range on the road surface is displayed. DETAILED DESCRIPTION OF THE INVENTION

[0036] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. An orthoimage creation system 1 according to the embodiment of the present invention includes a total station 2 installed at a known point (for example, a reference point), a UAV 3 (Unmanned Aerial Vehicle) that is an unmanned aerial vehicle serving as an imaging device, a 3D scanner 4 (three-dimensional scanning device) installed at the known point, and an orthoimage creation device 10 in which the total station 2, the UAV 3, and the 3D scanner 4 are wirelessly connected.

[0037] The total station 2 emits distance measurement light toward each point on the road surface, receives the light reflected at each point, and acquires the three-dimensional coordinates of each point relative to a known point based on the number of times the light wave oscillates from emission to reception, and supplies the three-dimensional coordinates to the orthoimage creation system 10. In this embodiment, the total station 2 is used to acquire the three-dimensional coordinates of multiple anti-aircraft signs 6.

[0038] The UAV 3 has an imaging device, and captures images of the road surface from above, acquires imaging data, and supplies the imaging data to the orthoimage creation device 10.

[0039] The 3D scanner 4 emits laser light to acquire three-dimensional coordinated point cloud data (a set of elevations with planar position coordinates) of each point on the road surface, and supplies the point cloud data to the orthoimage creation system 10. The 3D scanner 4 emits line laser light, for example, vertically and horizontally, toward the measurement object (road surface), and measures the time it takes for the laser pulse to travel back and forth between the measurement point on the measurement object and the sensor, thereby determining the distance to the measurement point. In this embodiment, the 3D scanner 4 is used to acquire three-dimensional coordinates (point cloud data) of each point in an area including a repair location where road repair work is to be performed, at the time of repair work commencement. The point cloud data acquired by the 3D scanner 4 is data at positions spaced, for example, at intervals of 25 cm or less. In this embodiment, the 3D scanner 4 acquires point cloud data at positions spaced, for example, at intervals of 5 mm.

[0040] As shown in FIG. 1, the orthoimage creation device 10 is configured, for example, by a microcomputer, and includes a CPU, a ROM storing a program that controls the operation of the orthoimage creation device 10, and a RAM that temporarily stores data used when executing the program.

[0041] The orthoimage creation device 10 has a coordinate storage unit 11, a captured image storage unit 12, an orthoimage creation unit 13, and a display control unit 14. The orthoimage creation device 10 also has a display unit 5 such as a display screen.

[0042] The coordinate storage unit 11 stores three-dimensional coordinates of characteristic points such as a plurality of anti-aircraft signs 6 acquired by the total station 2 separately.

[0043] The captured image storage unit 12 stores a plurality of images of a road taken from above by a UAV 3 flying at a substantially constant altitude above the road. When taking images, the UAV 3 flies at an altitude of 20 meters or less above the ground, for example, at an altitude of 5 to 20 meters, and preferably at an altitude of 5 to 15 meters.

[0044] When photographing a road from the sky using a UAV 3, as shown in FIG. 2, a plurality of anti-aircraft signs 6 are installed near both ends of the road as a plurality of feature points. The multiple anti-aircraft signs 6 are installed along the edges of the road (in the longitudinal direction of the road), for example, at intervals of 5 to 15 meters. The multiple anti-aircraft signs 6 are installed with consideration given to the creation of an orthoimage by connecting multiple photographed images taken from the sky. The anti-aircraft signs 6 are feature points for which three-dimensional coordinates are provided, and are used as assessment points. Note that when connecting multiple photographed images to create an orthoimage, feature points other than the anti-aircraft signs 6 that are included in the multiple photographed images but for which three-dimensional coordinates are not provided may also be used.

[0045] As shown in FIG. 3, the anti-aircraft sign 6 is a square plate-like member. The anti-aircraft sign 6 has a pattern that clearly identifies its center position. The anti-aircraft sign 6 has an adhesive layer formed on its back surface, and is in the form of a sticker with a backing paper attached to cover the adhesive layer. By removing the backing paper and attaching the sign to the road, it can be easily fixed to the installation location. Therefore, when using the anti-aircraft sign 6, the backing paper covering the adhesive layer is removed and the back side of the anti-aircraft sign 6 is attached to the road surface. The anti-aircraft sign 6 of this embodiment is, for example, a 9 cm x 9 cm square, but the type, shape, size, pattern, etc. of the anti-aircraft sign 6 are not limited thereto.

[0046] As shown in Fig. 4, the multiple images captured by the UAV 3 are captured so that each anti-aircraft sign 6 is included in at least two of the captured images. Therefore, at least one common anti-aircraft sign 6 is captured in two adjacent captured images. Note that Fig. 4 illustrates a case where the anti-aircraft sign 6 is included in all of the captured images, but the multiple images captured by the UAV 3 may be captured so that either the anti-aircraft sign 6 or a feature point other than the anti-aircraft sign 6 is included in at least two of the captured images.

[0047] The orthoimage creation unit 13 creates an orthoimage based on the three-dimensional coordinates of the anti-aircraft signs 6 stored in the coordinate storage unit 11 and the multiple captured images stored in the captured image storage unit 12. Specifically, the orthoimage creation unit 13 performs SfM (Structure from Motion) analysis or the like on the data for the multiple captured images to connect two adjacent captured images based on the common anti-aircraft signs 6 captured in those images, thereby creating an orthoimage. Note that if there is a vehicle on the road in the captured image used to create the orthoimage, it is possible to automatically recognize the vehicle (by automatic image recognition) and replace the area around the vehicle on the road with an image of the road without the vehicle in another captured image, thereby creating an orthoimage without the vehicle on the road.

[0048] The display control unit 14 displays the orthoimage created by the orthoimage creation unit 13 on the display unit 5. The user can perform an operation to designate a predetermined position within the image displayed on the display unit 5 by pressing the display surface 5a of the display unit 5. For example, in a state where the orthoimage created by the orthoimage creation unit 13 is displayed on the display unit 5, the user can perform an operation to designate a predetermined position by pressing a predetermined position within the orthoimage displayed on the display surface 5a of the display unit 5.

[0049] (Creating orthoimages) A method for creating an orthoimage in the orthoimage creation device 10 will be described with reference to FIG.

[0050] In step S1 (coordinate acquisition step), the total station 2 acquires three-dimensional coordinates, i.e., planar positions (latitude, longitude) and altitude (height), for multiple predetermined positions around the repair area where road repairs are to be performed, i.e., predetermined positions where multiple anti-aircraft signs 6 will be installed.

[0051] In step S2 (photographing step), the road is photographed from above by the UAV 3 flying at an altitude of 20 meters or less above the ground. When the photographing is performed, a plurality of anti-aircraft markers 6 are installed in advance at a plurality of predetermined positions surveyed in step S1. Therefore, a plurality of photographed images are taken of the plurality of anti-aircraft markers 6 so that each anti-aircraft marker 6 is included in at least two photographed images.

[0052] In step S3 (orthoimage creation step), an orthoimage is created based on the three-dimensional coordinates acquired in step S1 and the multiple captured images taken in step S2.

[0053] In step S4 (display step), the orthoimage is displayed on the display unit 5 as shown in Fig. 6. In this embodiment, the ground pixel size of the orthoimage is 5 mm or less.

[0054] 7 to 9 are enlarged views of a road surface on which cracks have formed. Fig. 10 is an enlarged view of a road surface on which a manhole is located. In this way, in the orthoimage created by the orthoimage creation device 10 of this embodiment, it is possible to clearly identify cracks formed on the road surface, and also to clearly identify the type of manhole based on the letters and symbols written on the manhole cover.

[0055] In addition, when investigating crack conditions on road surfaces, conventionally, when road conditions are investigated using a dedicated road surface property measurement vehicle, it is possible to detect cracks of about 1 mm width formed on the road surface. Therefore, an evaluation was conducted to determine whether the orthoimages created by the present invention can detect cracks of about 1 mm width formed on the road surface in the same way as a dedicated road surface property measurement vehicle.

[0056] For the above evaluation, 1mm-, 2mm-, and 3mm-wide tapes were used and attached to the road surface to simulate cracks of 1mm, 2mm, and 3mm in width, as shown in Figures 11 and 12. After that, the road with the simulated cracks formed was photographed from above by a UAV3 flying at an altitude of 20 meters or less above the ground, and an orthoimage was created.

[0057] Figure 13 shows an orthoimage of a road with simulated cracks formed on it, and it was found that the orthoimage created by the present invention can detect simulated cracks of 1 mm, 2 mm, and 3 mm width formed on the road surface. Therefore, the orthoimage created by the present invention can detect cracks of about 1 mm width formed on the road surface.

[0058] (Road survey method using orthoimages) The orthoimages created by the orthoimage creation device 10 as described above are used for various surveys that are carried out when road repairs are carried out.

[0059] In this embodiment, using orthoimages created by the orthoimage creation device 10, we will explain a road survey method when conducting (1) an investigation into the condition of cracks on the road surface, (2) an investigation into the location of planar elements around the road including areas where repairs will be performed, (3) an investigation for repairing the area around a manhole, (4) an investigation into the distance between two specified points on the road surface, and (5) an investigation into the area of ​​a specified range on the road surface.

[0060] (Road Survey Method 1) The method for investigating the crack condition on the road surface will be explained with reference to FIG.

[0061] In the investigation of the crack condition of the road surface, the areas where cracks have formed on the road surface, including the repair areas where road repairs will be carried out, and the crack rate and patching rate in those areas are investigated.

[0062] After the orthoimage is displayed in steps S1 to S4 described above, in step S5, the crack condition of the road surface is investigated based on the orthoimage displayed on the display unit 5. Specifically, the investigation area of ​​the road displayed on the display unit 5 is divided into a plurality of investigation ranges, and the crack rate and patching rate of the road surface are investigated for each investigation range.

[0063] 15 illustrates the survey area in the orthoimage displayed on the display unit 5. In this embodiment, the survey area is divided into survey ranges of 50 cm x 50 cm, and for each survey range, a survey of the crack rate and a survey of the patching rate are conducted as a survey of the crack condition. In this embodiment, the survey of the crack rate involves a survey of the crack amount (quantity of cracks) for each survey range.

[0064] FIG. 16 is an enlarged view of portion A within the survey area shown in FIG. 15, showing the state of the area divided into multiple survey ranges. For each survey range, FIG. 16 distinguishes between the following states: no cracks and a patching rate of 25% or less, a linear crack state (a state with one crack), a planar crack state (a state with two or more cracks), a patching rate of 25 to 75%, and a patching rate of 75% or more. While FIG. 16 distinguishes the road surface state for each survey range using different patterns, the road surface state for each survey range may also be displayed using different colors.

[0065] In step S6 (road condition display step), the results of investigating the crack condition of the road surface for each investigation range in the entire investigation area are displayed on the display unit 5, as shown in Fig. 17. In Fig. 17, the investigation ranges for linear crack conditions, planar crack conditions, patching rates of 25 to 75%, and patching rates of 75% or more may be displayed, for example, in different colors. Furthermore, the investigation ranges for linear crack conditions and planar crack conditions may be displayed, for example, in different colors, from the investigation ranges for patching rates of 25 to 75% and patching rates of 75% or more.

[0066] (Road Survey Method 2) The method for investigating the positions of planar elements around a road will be described with reference to FIG.

[0067] When investigating the locations of planar elements around the road, the locations of planar elements including the edges of the road including repair areas where road repairs will be performed, road deformations, dividing lines such as white painted areas on the road surface indicating lanes, and lines indicating the locations of manholes, etc. are investigated.

[0068] After the orthoimage is created by steps S1 to S4 described above, in step S8 (planar element plotting step), tracing of planar elements around the road is performed manually or automatically (auto-trace processing) based on the orthoimage displayed on the display unit 5. Specifically, tracing of planar elements is performed on the road displayed on the display unit 5, including, for example, road edges, road deformations, division lines such as white painted parts on the road surface that indicate lanes, and lines indicating the positions of manholes, etc.

[0069] Figure 19 illustrates the survey area in the orthoimage displayed on the display unit 5. Figure 20 is an ortho-CAD plan view of the orthoimage shown in Figure 6, and Figure 21 shows a diagram in which planar elements around the road have been traced on the ortho-CAD plan view of Figure 20. An ortho-CAD plan view is a plan view created by converting an orthoimage into 2D CAD. Therefore, in Figure 21, lines indicating the positions of planar elements around the road have been added to the ortho-CAD plan view corresponding to the orthoimage of Figure 20.

[0070] In step S8, as shown in FIG. 22, a tracing process is performed on planar elements around the roads in the entire survey range, and the planar elements are plotted and displayed on the display unit 5.

[0071] (Road Survey Method 3) The investigation method for repairing the area around the manhole will be explained based on Figure 23.

[0072] In a survey to repair the area around a manhole, the height (adjustment height) to be adjusted so that the elevation of the area around the manhole matches the elevation of the repair plan surface is investigated. Therefore, the adjustment height of the area around the manhole is the difference in elevation between the elevation of the area around the manhole at the time of repair work and the elevation of the repair plan surface. The adjustment height of the area around the manhole is investigated by investigating the difference in elevation between two locations, upstream and downstream in the longitudinal direction of the manhole, and the difference in elevation between two locations, upstream and downstream in the transverse direction of the manhole.

[0073] Fig. 24 illustrates a survey area in the orthoimage displayed on the display unit 5. The survey area in Fig. 24 includes one manhole and the surrounding area of ​​the manhole.

[0074] After the orthoimage is displayed in steps S1 to S4 described above, longitudinal and cross-sectional planning is performed in step S9, and plan data showing the repair plan for repairing the road is acquired.

[0075] The repair plan includes longitudinal and transverse plans, and after longitudinal planning along the longitudinal direction of the road is performed, transverse planning along the transverse direction at multiple locations on the road is performed to obtain a repair plan surface to be used when repairing. Therefore, the repair plan surface includes plan surface data indicating the longitudinal plan surface and plan surface data indicating multiple transverse plan surfaces.

[0076] A longitudinal plan includes a plan for the elevation of each point on a line along the longitudinal direction of the road in the center of the road. For example, Figure 25 shows a longitudinal plan surface for the elevation of each point on a line along the center of the road. In Figure 25, a repair area requiring a repair plan is located between an unrepaired area on the left side and an unrepaired area on the right side. The repair area in Figure 25 is shown with elevation changes based on point cloud data and a longitudinal plan surface.

[0077] The longitudinal section plan shown in Figure 25 is obtained by connecting the elevations at each position on a line along the center of the road, after the elevations at each position on the line along the center of the road are planned taking into consideration the flatness of the road, etc. The positions on the line along the center of the road are, for example, every 10 m or every 20 m.

[0078] In longitudinal planning, elevations at each position on a line along the center of the road are planned, followed by cross-sectional planning. Cross-sectional planning is a plan for elevations at each point on a line along the cross-sectional direction of the road at each position on the line along the center of the road. For example, Figure 26 shows a cross-sectional planning surface for elevations at each point on a line along the cross-sectional direction of the road at point a in Figure 25. In Figure 26, a repair location requiring a repair plan is located between the left edge and the right edge of the road. The cross-sectional planning surface is also shown at the repair location, along with elevation changes based on point cloud data. Figure 26 illustrates the slope of the road for easy understanding.

[0079] The cross-section planning surface is obtained by planning for each position on the line along the center of the road shown in Figure 25, taking into consideration the gradient of the slope that slopes downward from the elevation of the center of the road toward both ends of the road. For example, when planning a cross-section of a road, it is generally designed so that the slope slopes downward at a predetermined gradient from the center of the road toward the ends of the road.

[0080] For example, in the cross-sectional plan of FIG. 26 , the elevation of the road center at point a on the longitudinal plan of FIG. 25 decreases to point a1 along a slope that slopes downward at a predetermined gradient toward both ends of the road. The elevation then decreases along connecting surfaces that connect point a1 to the left and right ends of the road. Therefore, when repairs are made based on the cross-sectional plan, the surface layer of the asphalt pavement formed at the repaired area is connected to the concrete sections at the left and right ends of the road without any steps. Note that the cross-sectional plan of FIG. 26 is an example of a cross-sectional plan, and cross-sectional planning methods are not limited to this. Therefore, the cross-sectional plan may be designed, for example, so that slopes that slope downward at different gradients from the road center toward the road edges are connected.

[0081] By connecting the cross-sectional plan surfaces at each position on the line along the center of the road obtained as described above in the longitudinal direction, a repair plan surface for repairing the road surface is obtained.

[0082] In step S10 (point cloud data acquisition step), point cloud data of each point on the road surface is acquired by the 3D scanner 4. The point cloud data acquired by the 3D scanner 4 is converted into a three-dimensional TIN model (irregular triangular network), which is a collection of triangular planes connected at vertices, and data corresponding to the latitude, longitude, and altitude of each point on the road surface can be derived. Even if point cloud data of each point in the survey area has not been acquired by the 3D scanner 4, data corresponding to the latitude, longitude, and altitude of each point can be derived.

[0083] In step S11 (altitude difference derivation step), by pressing and specifying a predetermined position around the manhole based on the orthoimage displayed on the display surface 5a of the display unit 5, the planar position (latitude, longitude) of the predetermined position is displayed as shown in Fig. 27. Therefore, by changing the position specified around the manhole in the orthoimage displayed on the display surface 5a of the display unit 5, two planar positions, one on the upstream side and one on the downstream side in the longitudinal direction of the manhole, and two planar positions, one on the upstream side and one on the downstream side in the transverse direction of the manhole, are detected.

[0084] The elevation of each position around the manhole at the time repair work begins is derived based on the detected planar position of each position around the manhole, and the elevation of that planar position is derived based on the point cloud data acquired by the 3D scanner 4. In this embodiment, using the orthoimage and the point cloud data acquired by the 3D scanner 4, the elevation of all planar positions in the orthoimage can be derived based on the point cloud data acquired by the 3D scanner 4. The elevation of each position on the repair plan surface is extracted from the plan surface data indicating the repair plan surface acquired in step S9.

[0085] Next, the elevation difference between the elevation of each location around the manhole at the time of repair work commencement and the elevation of each location on the repair plan is calculated as the adjustment height. Therefore, two adjustment heights, one upstream and one downstream of the manhole in the longitudinal direction, and two adjustment heights, one upstream and one downstream of the manhole in the transverse direction, are calculated. Figure 28 shows that the adjustment heights for each location around the manhole are a1 cm, a2 cm, a3 cm, and a4 cm, respectively. Therefore, a1 cm is the adjustment height on the upstream side of the manhole in the transverse direction, a2 cm is the adjustment height on the upstream side of the manhole in the longitudinal direction, a3 cm is the adjustment height on the downstream side of the manhole in the transverse direction, and a4 cm is the adjustment height on the downstream side of the manhole in the longitudinal direction.

[0086] (Road Survey Method 4) A method for investigating the distance between two specified points on the road surface will be described with reference to FIG.

[0087] In investigating the distance between two specified points on the road surface, when various distances are required for road repair, the distances are investigated based on the orthoimage displayed on the display unit 5. Distances required for road repair include, for example, the length of the road repair section, the width of the road, and the length of a specified area on the road surface.

[0088] In step S101 (point cloud data acquisition step), point cloud data of each point on the road surface around the repair location where road repair is to be performed is acquired by the 3D scanner 4. The point cloud data acquired by the 3D scanner 4 is converted into a three-dimensional TIN model (irregular triangular network), which is a collection of triangular planes connected at vertices, and data corresponding to the latitude, longitude, and altitude of each point on the road surface can be derived. Even if point cloud data of each point in the survey area has not been acquired by the 3D scanner 4, data corresponding to the latitude, longitude, and altitude of each point can be derived.

[0089] In step S102 (coordinate acquisition step), based on the point cloud data acquired in step S101, three-dimensional coordinates, i.e., planar positions (latitude, longitude) and altitudes (height), are acquired for a plurality of predetermined positions around the repair location where road repair is to be performed, i.e., predetermined positions where a plurality of anti-aircraft signs 6 will be installed. The three-dimensional coordinates of the plurality of predetermined positions may be acquired by a total station 2.

[0090] In step S103 (photographing step), the road is photographed from above by the UAV 3 flying at an altitude of 20 meters or less above the ground. When photographing is performed, a plurality of anti-aircraft markers 6 are installed in advance at a plurality of predetermined positions whose three-dimensional coordinates have been acquired in step S102. Therefore, a plurality of photographed images are taken of the plurality of anti-aircraft markers 6 so that each anti-aircraft marker 6 is included in at least two photographed images.

[0091] In step S104 (orthoimage creation step), an orthoimage is created based on the three-dimensional coordinates acquired in step S102 and the multiple captured images taken in step S103. At this time, the orthoimage created in step S104 is associated with the point cloud data acquired in step S101. That is, each point in the orthoimage is associated with the three-dimensional coordinates of the point cloud data, and each point on the orthoimage corresponds to a planar position (latitude, longitude) and an altitude (height).

[0092] In step S105 (display step), the orthoimage is displayed on the display unit 5 as shown in FIG. 6. In step S106 (distance display step), by pressing and specifying two designated points on the road surface on the orthoimage displayed on the display surface 5a of the display unit 5, the distance between the designated points is displayed. For example, as shown in FIG. 30, when two designated points A1 and A2 at an intersection are specified, the distance between the designated points A1 and A2 is displayed. Therefore, when a road is photographed from the sky by a UAV 3 flying at an altitude of 20 meters or less above the ground in step S103 (photographing step), even if various distances required for road repair are not measured, the distances between various designated points within the orthoimage can be detected by changing the positions of the two designated points on the road surface in the orthoimage displayed on the display surface 5a of the display unit 5.

[0093] (Road Survey Method 5) The method for investigating the area of ​​a specified range on the road surface will be explained with reference to FIG.

[0094] In the survey of the area of ​​a specified range on the road surface, when the areas of various regions are required for road repair, the areas of those regions are surveyed based on the orthoimage displayed on the display unit 5. The areas required for road repair include, for example, the area of ​​the road repair portion.

[0095] In step S101 (point cloud data acquisition step), point cloud data of each point on the road surface around the repair location where road repair is to be performed is acquired by the 3D scanner 4. The point cloud data acquired by the 3D scanner 4 is converted into a three-dimensional TIN model (irregular triangular network), which is a collection of triangular planes connected at vertices, and data corresponding to the latitude, longitude, and altitude of each point on the road surface can be derived. Even if point cloud data of each point in the survey area has not been acquired by the 3D scanner 4, data corresponding to the latitude, longitude, and altitude of each point can be derived.

[0096] In step S102 (coordinate acquisition step), based on the point cloud data acquired in step S101, three-dimensional coordinates, i.e., planar positions (latitude, longitude) and altitudes (height), are acquired for a plurality of predetermined positions around the repair location where road repair is to be performed, i.e., predetermined positions where a plurality of anti-aircraft signs 6 will be installed. The three-dimensional coordinates of the plurality of predetermined positions may be acquired by a total station 2.

[0097] In step S103 (photographing step), the road is photographed from above by the UAV 3 flying at an altitude of 20 meters or less above the ground. When photographing is performed, a plurality of anti-aircraft markers 6 are installed in advance at a plurality of predetermined positions whose three-dimensional coordinates have been acquired in step S102. Therefore, a plurality of photographed images are taken of the plurality of anti-aircraft markers 6 so that each anti-aircraft marker 6 is included in at least two photographed images.

[0098] In step S104 (orthoimage creation step), an orthoimage is created based on the three-dimensional coordinates acquired in step S102 and the multiple captured images taken in step S103. At this time, the orthoimage created in step S104 is associated with the point cloud data acquired in step S101. That is, each point in the orthoimage is associated with the three-dimensional coordinates of the point cloud data, and each point on the orthoimage corresponds to a planar position (latitude, longitude) and an altitude (height).

[0099] In step S105 (display step), the orthoimage is displayed on the display unit 5 as shown in FIG. 6. In step S108 (area display step), by specifying a specified range of the road surface on the orthoimage displayed on the display surface 5a of the display unit 5, the area of ​​the specified range is displayed as shown in FIG. 32. For example, as shown in FIG. 32, when a specified range (shaded area) indicating the upper part of an intersection is specified, the area of ​​the specified range is displayed. Therefore, when a road is photographed from the sky by a UAV 3 flying at an altitude of 20 meters or less above the ground in step S103 (photographing step), even if measurements of various areas required for road repair are not performed, the areas of various regions within the orthoimage can be detected by changing the position of the specified range of the road surface in the orthoimage displayed on the display surface 5a of the display unit 5.

[0100] The orthoimage creation system 1 of this embodiment includes a coordinate memory unit 11 that stores three-dimensional coordinates for multiple anti-aircraft signs 6, a captured image memory unit 12 that stores multiple captured images of multiple anti-aircraft signs 6 taken by a UAV 3 flying at an altitude of 20 meters or less above the ground so that each anti-aircraft sign 6 is included in at least two captured images, and an orthoimage creation unit 13 that creates an orthoimage based on the three-dimensional coordinates of each anti-aircraft sign 6 stored in the coordinate memory unit 11 and the multiple captured images stored in the captured image memory unit 11.

[0101] The orthoimage creation method of this embodiment includes a coordinate acquisition step of acquiring three-dimensional coordinates for multiple anti-aircraft signs 6, a photographing step of capturing multiple images of the multiple anti-aircraft signs 6 using a UAV 3 flying at an altitude of 20 meters or less above the ground so that each anti-aircraft sign 6 is included in at least two photographed images, and an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired in the coordinate acquisition step and the multiple photographed images captured in the photographing step.

[0102] As a result, the orthoimage creation system 1 and orthoimage creation method of this embodiment create orthoimages based on multiple images captured by a UAV 3 flying at an altitude of 20 meters or less above the ground, making it possible to create orthoimages that clearly show the condition of the road surface and the location of planar elements around the road.The orthoimages created in this embodiment make it possible to clearly identify areas where cracks have occurred or where patching has occurred on the road.Therefore, since there is no need to run a dedicated road surface property measurement vehicle to investigate the crack condition of the road surface, it is possible to investigate road conditions regardless of road width.

[0103] Furthermore, in the orthoimage created in this embodiment, the positions of planar elements including road edges and lane markings can be clearly identified. Therefore, since it is not necessary to conduct surveys at a large number of planar positions in order to plot planar elements including road edges and lane markings, it is possible to easily plot planar elements based on the orthoimage.

[0104] Furthermore, the orthoimage created in this embodiment can detect the vertical and horizontal plane positions of the area surrounding the manhole. Therefore, after identifying the vertical and horizontal plane positions of the area surrounding the manhole, the elevation of each plane position can be extracted from the point cloud data acquired by the 3D scanning device. Therefore, there is no need to create road vertical and horizontal sections for each manhole in order to detect the elevation of each vertical and horizontal plane position of the area surrounding the manhole. Therefore, the manhole adjustment height can be easily detected.

[0105] In the orthoimage creation system 1 of this embodiment, an anti-aircraft marker 6 installed on the ground is used when taking photographs using the UAV 3, and the coordinate memory unit 11 stores the three-dimensional coordinates of the anti-aircraft marker 6 acquired by the total station 2.

[0106] In the orthoimage creation method of this embodiment, an aerial marker 6 installed on the ground is used during photography in the photography step, and the three-dimensional coordinates of the aerial marker 6 are acquired by the total station 2 in the coordinate acquisition step.

[0107] As a result, the orthoimage creation system 1 and orthoimage creation method of this embodiment make it possible to provide three-dimensional coordinates to the orthoimage based on the three-dimensional coordinates of the anti-aircraft sign 6 contained in the image captured by the UAV 3.

[0108] The road survey method of this embodiment includes a coordinate acquisition step of acquiring the three-dimensional coordinates of multiple anti-aircraft signs 6; a photographing step of taking multiple photographic images of multiple anti-aircraft signs 6 using a UAV 3 flying at an altitude of 20 meters or less above the ground so that each anti-aircraft sign 6 is included in at least two photographic images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each anti-aircraft sign 6 acquired in the coordinate acquisition step and the multiple photographic images taken in the photographing step; a display step of displaying the orthoimage on a display unit 5; a derivation step of dividing the survey area into multiple survey ranges in the orthoimage displayed on the display unit 5 and deriving the crack rate or patching rate for each of the multiple survey ranges; and a road condition display step of displaying the road condition by adding a color to the orthoimage displayed on the display unit 5 according to the magnitude of the crack rate or patching rate of each survey range derived in the derivation step.

[0109] As a result, the road inspection method of this embodiment creates an orthoimage based on multiple images taken by a UAV3 flying at an altitude of 20 meters or less above the ground, making it possible to create an orthoimage that clearly identifies the condition of the road surface and the location of planar elements around the road.The orthoimage created in this embodiment makes it possible to clearly identify areas of the road where cracks have occurred and areas where patching has occurred.Therefore, since there is no need to run a dedicated road surface property measurement vehicle to inspect the condition of cracks on the road surface, it is possible to inspect road conditions regardless of road width.

[0110] The road survey method of this embodiment includes a coordinate acquisition step of acquiring three-dimensional coordinates for multiple anti-aircraft signs 6, a photographing step of taking multiple images of multiple anti-aircraft signs 6 using a UAV 3 flying at an altitude of 20 meters or less above the ground so that each anti-aircraft sign 6 is included in at least two photographed images, an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each anti-aircraft sign 6 acquired in the coordinate acquisition step and the multiple photographed images taken in the photographing step, a display step of displaying the orthoimage on the display unit 5, and a planar element mapping step of tracing planar elements in the orthoimage displayed on the display unit 5 to map the planar elements.

[0111] As a result, the road survey method of this embodiment creates an orthoimage based on multiple images taken by a UAV3 flying at an altitude of 20 meters or less above the ground, making it possible to create an orthoimage that clearly identifies the condition of the road surface and the location of planar elements around the road.The orthoimage created by this invention makes it possible to clearly identify the location of planar elements, including road edges and lane markings.Therefore, since it is not necessary to survey a large number of planar positions in order to map planar elements, including road edges and lane markings, it is possible to easily map planar elements based on the orthoimage.

[0112] The road survey method of this embodiment includes a coordinate acquisition step for acquiring three-dimensional coordinates for multiple anti-aircraft signs 6, a photographing step for taking multiple photographed images of multiple anti-aircraft signs 6 using a UAV 3 flying at an altitude of 20 meters or less above the ground so that each anti-aircraft sign 6 is included in at least two photographed images, an orthoimage creation step for creating an orthoimage based on the three-dimensional coordinates of each anti-aircraft sign 6 acquired in the coordinate acquisition step and the multiple photographed images taken in the photographing step, a display step for displaying the orthoimage on a display unit 5, a point cloud data acquisition step for acquiring point cloud data of an area including the periphery of the manhole in the orthoimage, and an elevation difference derivation step for deriving the elevation difference between the elevation of the periphery of the manhole in the orthoimage displayed on the display unit 5 and the elevation of the periphery of the manhole on the repair plan surface.

[0113] As a result, the road inspection method of this embodiment creates an orthoimage based on multiple images taken by a UAV3 flying at an altitude of 20 meters or less above ground, making it possible to create an orthoimage that clearly identifies the condition of the road surface and the location of planar elements around the road. The orthoimage created by this invention makes it possible to detect the planar positions of the longitudinal and transverse directions around the manhole. Therefore, after identifying the planar positions of the longitudinal and transverse directions around the manhole, the elevation of each planar position can be derived based on point cloud data of the area including the manhole. Therefore, there is no need to create road longitudinal and transverse sections for each manhole to detect the elevation of each planar position of the longitudinal and transverse directions around the manhole. Therefore, it is possible to easily detect the manhole adjustment height.

[0114] The road survey method of this embodiment is characterized by comprising a coordinate acquisition step of acquiring three-dimensional coordinates for multiple anti-aircraft signs 6, a photographing step of taking multiple photographic images of multiple anti-aircraft signs 6 using a UAV3 flying at an altitude of 20 meters or less above the ground so that each anti-aircraft sign 6 is included in at least two photographic images, an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each anti-aircraft sign 6 acquired in the coordinate acquisition step and the multiple photographic images taken in the photographing step, a point cloud data acquisition step of acquiring point cloud data of an area including multiple anti-aircraft signs 6, a display step of displaying the orthoimage on the display unit 5, a designation step of designating two designated points spaced apart from each other in the orthoimage displayed on the display unit 5, and a distance display step of displaying the distance between the two designated points when two designated points are designated in the designation step.

[0115] As a result, the road inspection method of the present invention creates an orthoimage based on multiple images taken by a UAV 3 flying at an altitude of 20 meters or less above the ground, and by associating the orthoimage with point cloud data of the area within the orthoimage, it is possible to clearly determine the positions of planar elements including road edges and lane markings, and to display, for example, the distance between two specified points in the area surrounding the road in the orthoimage. Therefore, even if an inspector does not measure the distance between two specified points in the area surrounding the road, the distance between the two specified points can be easily detected by specifying the two specified points on the display unit 5 displaying the orthoimage.

[0116] The road survey method of the present invention is characterized by comprising a coordinate acquisition step of acquiring three-dimensional coordinates for a plurality of anti-aircraft signs 6; a photographing step of taking a plurality of photographed images of a plurality of anti-aircraft signs 6 using a UAV 3 flying at an altitude of 20 meters or less above the ground so that each anti-aircraft sign 6 is included in at least two photographed images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each anti-aircraft sign 6 acquired in the coordinate acquisition step and the plurality of photographed images taken in the photographing step; a point cloud data acquisition step of acquiring point cloud data of an area including a plurality of anti-aircraft signs 6; a display step of displaying the orthoimage on a display unit 5; a designation step of designating a specified range within the orthoimage displayed on the display unit 5; and an area display step of displaying the area of ​​the specified range when the specified range is designated in the designation step.

[0117] As a result, the road inspection method of the present invention creates an orthoimage based on multiple images taken by a UAV 3 flying at an altitude of 20 meters or less above the ground, and by associating the orthoimage with point cloud data of the area within the orthoimage, it is possible to clearly determine the positions of planar elements including road edges and lane markings and other dividing lines, and to display, for example, the area of ​​a specified range within the road surrounding area within the orthoimage. Therefore, even if an inspector does not measure the area of ​​the specified range within the road surrounding area, the area of ​​the specified range can be easily detected by specifying the specified range on the display unit 5 displaying the orthoimage.

[0118] The above describes an embodiment of the present invention, but the specific configuration of each part is not limited to the above-described embodiment, and various modifications are possible within the scope of the spirit of the present invention.

[0119] In the above embodiment, an orthoimage is created based on images captured from above the road by a UAV 3 flying at a nearly constant altitude. However, the present invention also includes creating an orthoimage based on images captured from above the road by a UAV 3 flying at different altitudes less than 20 meters above the ground. In the above embodiment, the 3D coordinates of the anti-aircraft markers 6 installed around the road are acquired using a total station 2. However, the 3D coordinates of the anti-aircraft markers 6 installed around the road may be acquired using a GNSS (Global Navigation Satellite System), a positioning system using satellites such as GPS. The 3D coordinates of the anti-aircraft markers 6 installed around the road may be acquired by scanning using a 3D scanner 4. In the above embodiment, the anti-aircraft markers 6 have a pattern that clearly identifies the central position used as the evaluation point. However, the anti-aircraft markers 6 may have a pattern that identifies a position other than the central position, and the position other than the central position may be used as the evaluation point. In the above embodiment, multiple anti-aircraft markers 6 are installed along the edge of the road (longitudinal direction of the road) at intervals of, for example, 5 to 15 meters, but the arrangement of multiple anti-aircraft markers 6 is arbitrary. Therefore, multiple anti-aircraft markers 6 may be installed along the width direction of the road at intervals of, for example, 1 meter or less. In step S1 (coordinate acquisition step), the total station 2 acquires three-dimensional coordinates for predetermined positions where multiple anti-aircraft markers 6 are installed. However, if three-dimensional coordinates for the predetermined positions have already been acquired, those three-dimensional coordinates may be acquired instead. In the above embodiment, plate-shaped anti-aircraft markers 6 are installed on the road surface. However, instead of using plate-shaped anti-aircraft markers 6, a pattern similar to the anti-aircraft markers 6 may be formed on the road surface using any material, such as paint. For example, a pattern similar to the anti-aircraft markers 6 may be formed by spraying a paint of a different color from the asphalt surface onto the asphalt surface of the road, with the same shape as the white part of the anti-aircraft marker 6 in FIG. 3. When anti-aircraft signs are formed on the road surface using any material such as paint, the type, shape, size, pattern, etc. of the anti-aircraft sign are also arbitrary.

[0120] In the above embodiment, the road was photographed by an unmanned aerial vehicle (including a camera) flying at an altitude of 20 meters or less above the ground, but the road may also be photographed by a model aircraft (including a camera) flying at an altitude of 20 meters or less above the ground. In the present invention, an unmanned aerial vehicle is an airplane, rotorcraft, airship, etc. that cannot carry a person and can fly by remote control or automatic piloting, such as a drone (multicopter), radio-controlled aircraft, etc. Furthermore, a model aircraft is, for example, a multicopter, radio-controlled aircraft, etc., that weighs less than 200 grams, which is the total weight of the aircraft body and the battery weight.

[0121] In the above embodiment, an anti-aircraft sign 6 installed on the ground at the time of shooting is used as a feature point for connecting multiple captured images, and the three-dimensional coordinates of the anti-aircraft sign 6 are each acquired by the total station 2. However, if a specific point in an image captured by the UAV 3 is used as a feature point for connecting multiple captured images, and three-dimensional coordinated point cloud data for each point in the captured image including the specific point has already been acquired by scanning with the 3D scanner 4, the three-dimensional coordinates of the specific point may be acquired from that point cloud data.

[0122] In the above embodiments, examples of the method for creating an orthoimage and the method for road surveying have been described, but the order of step S1 and step S2 may be reversed in Figures 5, 14, 18, and 23. Therefore, it is possible to capture an image after acquiring the three-dimensional coordinates of the anti-aircraft sign 6, and also possible to acquire the three-dimensional coordinates of the anti-aircraft sign 6 after capturing the image.

[0123] In the above embodiments, examples of a method for creating an orthoimage and a road survey method have been described. However, in Figures 29 and 31, the order of steps S102 and S103 may be reversed. Therefore, it is possible to capture an image after acquiring the three-dimensional coordinates of the anti-aircraft sign 6, and it is also possible to acquire the three-dimensional coordinates of the anti-aircraft sign 6 after capturing the image. Furthermore, in Figures 29 and 31, the order of steps S101 and S103 may be reversed. Therefore, it is possible to acquire point cloud data of an area including multiple anti-aircraft signs 6 before capturing an image of the area including multiple anti-aircraft signs 6, but it is also possible to acquire point cloud data of an area including multiple anti-aircraft signs 6 after capturing an image of the area including multiple anti-aircraft signs 6.

[0124] In the above embodiment, the following surveys are conducted using orthoimages created by the orthoimage creation device 10: a survey of the crack condition on the road surface, a survey of the position of planar elements around the road, a survey to repair the area around a manhole, a survey of the distance between two specified points on the road surface, and a survey of the area of ​​a specified range on the road surface. However, the orthoimages created by the orthoimage creation device 10 may be used for other surveys. [Explanation of symbols]

[0125] 1 Orthoimage creation system 2. Total Station 3 UAV (unmanned aerial vehicle) 4. 3D scanner (3D scanning device) 5 Display section 6 Anti-aircraft markings 10 Orthoimage creation device 11 Photographed image storage unit (photographed image storage means) 12 Orthoimage creation unit (orthoimage creation means) 13 Coordinate storage unit (coordinate storage means) 14 Display control unit

Claims

1. a coordinate storage means for storing three-dimensional coordinates of a plurality of feature points; a captured image storage means for storing a plurality of captured images taken by an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground, in such a manner that each of the plurality of feature points is included in at least two of the captured images; and an orthoimage creation means for creating an orthoimage based on the three-dimensional coordinates of each feature point stored in the coordinate storage means and the plurality of photographed images stored in the photographed image storage means.

2. the feature points are anti-aircraft markers installed on the ground at the time of photographing by the unmanned aerial vehicle or the model aircraft; The orthoimage creation system according to claim 1, characterized in that the coordinate storage means stores three-dimensional coordinates of the anti-aircraft markers acquired by either a total station, a satellite-based positioning system, or a three-dimensional scanning device.

3. the feature points are predetermined points within an image captured by the unmanned aerial vehicle or the model aircraft, The orthoimage creation system according to claim 1, characterized in that the coordinate storage means stores the three-dimensional coordinates of a specified point extracted from the three-dimensional coordinated point cloud data obtained for each point in the captured image.

4. a coordinate acquisition step of acquiring three-dimensional coordinates of a plurality of feature points; an imaging step of capturing a plurality of images using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground, such that each of the plurality of feature points is included in at least two of the captured images; An orthoimage creation method comprising an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired in the coordinate acquisition step and the plurality of captured images acquired in the photographing step.

5. the feature point is an anti-aircraft sign installed on the ground at the time of photographing in the photographing step, The orthoimage creation method according to claim 4, characterized in that in the coordinate acquisition step, the three-dimensional coordinates of the anti-aircraft sign are acquired by any one of a total station, a satellite-based positioning system, and a three-dimensional scanning device.

6. the feature points are predetermined points within an image captured by the unmanned aerial vehicle or the model aircraft, The orthoimage creation method according to claim 4, characterized in that in the coordinate acquisition step, three-dimensional coordinates of a specified point are acquired from three-dimensional coordinated point cloud data acquired for each point in the captured image.

7. An anti-aircraft marker used in the orthoimage creation system according to claim 2, An anti-aircraft sign characterized by being in the form of a sticker with an adhesive layer formed on the back side.

8. An anti-aircraft sign used in the orthoimage creation method according to claim 5, An anti-aircraft sign characterized by being in the form of a sticker with an adhesive layer formed on the back side.

9. a coordinate acquisition step of acquiring three-dimensional coordinates of a plurality of feature points; an imaging step of capturing a plurality of images using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground, such that each of the plurality of feature points is included in at least two of the captured images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired in the coordinate acquisition step and the plurality of photographed images taken in the photographing step; a display step of displaying the orthoimage on a display unit; A derivation step of dividing the survey area in the orthoimage displayed on the display unit into a plurality of survey ranges and deriving a crack rate or a patching rate for each of the plurality of survey ranges; a road condition display step of displaying the road condition by adding a color to the orthoimage displayed on the display unit according to the magnitude of the crack rate or patching rate of each survey area derived in the derivation step.

10. a coordinate acquisition step of acquiring three-dimensional coordinates of a plurality of feature points; an imaging step of capturing a plurality of images using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground, such that each of the plurality of feature points is included in at least two of the captured images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired in the coordinate acquisition step and the plurality of photographed images taken in the photographing step; a display step of displaying the orthoimage on a display unit; a planar element mapping step of tracing planar elements in the orthoimage displayed on the display unit to map the planar elements.

11. a coordinate acquisition step of acquiring three-dimensional coordinates of a plurality of feature points; an imaging step of capturing a plurality of images using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground, such that each of the plurality of feature points is included in at least two of the captured images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired in the coordinate acquisition step and the plurality of photographed images taken in the photographing step; a point cloud data acquisition step of acquiring point cloud data of an area including a periphery of the manhole in the orthoimage; a display step of displaying the orthoimage on a display unit; A road survey method characterized by comprising an elevation difference derivation step of deriving the elevation difference between the elevation of the area surrounding the manhole in the orthoimage displayed on the display unit and the elevation of the area surrounding the manhole on the repair plan surface.

12. a coordinate acquisition step of acquiring three-dimensional coordinates of a plurality of feature points; an imaging step of capturing a plurality of images using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground, such that each of the plurality of feature points is included in at least two of the captured images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired in the coordinate acquisition step and the plurality of photographed images taken in the photographing step; a point cloud data acquisition step of acquiring point cloud data of an area including the plurality of feature points; a display step of displaying the orthoimage on a display unit; a designation step of designating two designated points spaced apart from each other in the orthoimage displayed on the display unit; a distance display step of displaying the distance between the two designated points when the two designated points are designated in the designation step.

13. a coordinate acquisition step of acquiring three-dimensional coordinates of a plurality of feature points; an imaging step of capturing a plurality of images using an unmanned aerial vehicle or a model aerial vehicle flying at an altitude of 20 meters or less above the ground, such that each of the plurality of feature points is included in at least two of the captured images; an orthoimage creation step of creating an orthoimage based on the three-dimensional coordinates of each feature point acquired in the coordinate acquisition step and the plurality of photographed images taken in the photographing step; a point cloud data acquisition step of acquiring point cloud data of an area including the plurality of feature points; a display step of displaying the orthoimage on a display unit; A designation step of designating a designated range within the orthoimage displayed on the display unit, a step of displaying an area of ​​the designated range when the designated range is designated in the designation step;

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