Virtual transportation route proposing method and virtual transportation route proposing system

Abstract

To provide a method for proposing a virtual transportation route together with a range of interference with a large vehicle and a load before actually transporting the load, and a proposing system therefor.SOLUTION: A virtual transportation route proposing method acquires three-dimensional point cloud data and image data along a transportation route for transporting a load, and a three-dimensionally modeled vehicle model, replaces a portion in the three-dimensional point cloud data corresponding to a road surface with three-dimensional road surface data based on the three-dimensional point cloud data and the image data, replaces portions in the three-dimensional point cloud data corresponding to a plurality of artificial structures with a plurality of pieces of three-dimensional structure data to generate three-dimensional route data, sets a virtual transportation route in the three-dimensional road surface data, moves the vehicle model along the virtual transportation route to calculate an interference range between the vehicle model and the three-dimensional route data, and proposes the virtual transportation route provided with the interference range.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to a method and system for proposing a virtual transportation route for transporting a load. [Background technology]

[0002] In recent years, the use of natural energy has been attracting attention, and wind power generation facilities are being constructed in coastal areas and mountainous regions. The construction of wind power generation facilities, particularly in mountainous regions, requires the transport of large components that make up the wind turbine over land. A wind turbine is composed of a cylindrical, upright tower, a nacelle mounted on the top of the tower, and multiple blades (vanes) rotatably attached to the nacelle. Among the components of a wind turbine, the blades are particularly long, generally measuring 40 meters or more, with some exceeding 60 meters. A transportation device equipped with a cantilever-supported hoisting mechanism has been proposed for transporting the blades (Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-243805 Summary of the Invention [Problem to be solved by the invention]

[0004] However, even when using a transportation device with a hoisting mechanism such as that described in Patent Document 1, transporting wind turbine components on narrow roads or winding roads in mountainous areas can be difficult. In some cases, it may be necessary to widen the road or cut down trees along the transportation route. Therefore, experienced transport workers must carry out surveys and use road registers and accompanying floor plans to create plans for widening and cutting down trees before actually transporting the wind turbine components. Similar difficulties can also arise when transporting relatively large loads other than wind turbine components.

[0005] SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide a method and system for proposing a virtual transportation route together with the extent of interference with a large vehicle and a load before actually transporting the load. [Means for solving the problem]

[0006] The present invention has been made to solve at least some of the above-mentioned problems, and can be realized as the following aspects or application examples.

[0007] One aspect of the virtual transportation route proposing method according to the present invention is to Acquire three-dimensional point cloud data and image data along a transport route for transporting the cargo, and a vehicle model that is a three-dimensional model of a large vehicle transporting the cargo and the cargo loaded on the vehicle; based on the three-dimensional point cloud data and the image data, replacing a portion of the three-dimensional point cloud data corresponding to a road surface with three-dimensional road surface data that has been three-dimensionally modeled, and replacing a portion of the three-dimensional point cloud data corresponding to a plurality of artificial structures with a plurality of three-dimensional structure data that have been three-dimensionally modeled, thereby generating three-dimensional route data; a virtual transportation route connecting at least two reference points in the three-dimensional road surface data; moving the vehicle model along the virtual transportation route to calculate an interference range between the vehicle model and the three-dimensional route data; The virtual transportation route including the interference range is proposed.

[0008] One aspect of the virtual transportation route proposal system according to the present invention is to an acquisition unit that acquires three-dimensional point cloud data and image data along a transport route for transporting the load, and a vehicle model that is a three-dimensional model of a large vehicle that transports the load and the load loaded on the vehicle; a generation unit that generates three-dimensional route data by replacing a portion of the three-dimensional point cloud data corresponding to a road surface with three-dimensional road surface data that has been three-dimensionally modeled, and by replacing a portion of the three-dimensional point cloud data corresponding to a plurality of artificial structures with a plurality of three-dimensional structure data that have been three-dimensionally modeled, based on the three-dimensional point cloud data and the image data; a setting unit that sets a virtual transportation route connecting at least two reference points in the three-dimensional road surface data; a movement processing unit that moves the vehicle model multiple times along the virtual transportation route; an interference range calculation unit that calculates an interference range between the vehicle model and the three-dimensional route data; a proposal unit that proposes the virtual transportation route including the interference range; The present invention is characterized by comprising: [Effects of the Invention]

[0009] According to the virtual transportation route proposing method and system of the present invention, it is possible to propose multiple virtual transportation routes together with the range of interference with large vehicles and cargo before actually transporting the cargo. In particular, according to the present invention, the person performing the transportation work can determine the actual transportation route after accurately understanding the range of interference with artificial structures and non-artificial structures, thereby improving work efficiency. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a schematic configuration diagram of a virtual transportation route proposing system according to an embodiment of the present invention; [Figure 2] FIG. 10 is a schematic diagram illustrating an example of a vehicle model with the blade lowered. [Figure 3] FIG. 2 is a schematic diagram illustrating an example of three-dimensional route data. [Figure 4] FIG. 10 is a schematic diagram for explaining an example in which an interference range is displayed on map data. [Figure 5] 1 is a flowchart of a method for proposing a virtual transportation route according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Preferred embodiments of the present invention will be described in detail below with reference to the drawings. Note that the embodiments described below do not unduly limit the content of the present invention as defined in the claims. Furthermore, not all of the configurations described below are necessarily essential components of the present invention.

[0012] 1. Virtual transportation route proposal system The virtual transportation route proposal system of this embodiment is characterized by comprising: an acquisition unit that acquires three-dimensional point cloud data and image data along a transportation route for transporting cargo, and a vehicle model that is a three-dimensional model of a large vehicle transporting the cargo and the cargo loaded on the vehicle; a generation unit that generates three-dimensional route data based on the three-dimensional point cloud data and the image data by replacing a portion of the three-dimensional point cloud data corresponding to the road surface with three-dimensional road surface data that is a three-dimensional model, and by replacing a portion of the three-dimensional point cloud data corresponding to a plurality of artificial structures with three-dimensional structure data that is a three-dimensional model; a setting unit that sets a virtual transportation route connecting at least two reference points in the three-dimensional road surface data; a movement processing unit that moves the vehicle model multiple times along the virtual transportation route; an interference range calculation unit that calculates the interference range between the vehicle model and the three-dimensional route data; and a proposal unit that proposes the virtual transportation route that includes the interference range.

[0013] A virtual transportation route proposing system 10 according to this embodiment (hereinafter simply referred to as "proposing system 10") will be described with reference to Figs. 1 to 4. Fig. 1 shows the proposing system according to this embodiment. FIG. 2 is a schematic diagram illustrating an example of a vehicle model 65 with a blade 64 lowered, FIG. 3 is a schematic diagram illustrating an example of three-dimensional route data 50, and FIG. 4 is a schematic diagram illustrating an example of an interference range displayed on map data 57.

[0014] As shown in FIG. 1, the proposed system 10 includes, for example, a processing unit 20, a storage unit 30, an operation unit 32, and a display unit 34. The proposed system 10 is, for example, a computer device, and may be a tablet-type terminal or may be configured by interconnecting multiple server devices. The processing unit 20 includes, for example, a processor such as a central processing unit (CPU), a graphics processing unit (GPU), or a neural processing unit (NPU). The processing unit 20 can execute programs stored in the storage unit 30. The storage unit 30 is, for example, a storage medium such as a read-only memory (ROM), a random access memory (RAM), or a hard disk drive (HDD). The operation unit 32 is, for example, a user interface such as a mouse, a touch panel, or a keyboard. The display unit 34 is, for example, a liquid crystal display (LCD) or another known display device (e.g., an organic electroluminescence (EL) display), and may include various user interfaces (graphical user interfaces (GUIs)) as part of the operation unit 32. The proposed system 10 may include a communication interface for high-speed data communication with an external system. In the example of FIG. 1, the external system is an MMS 40 (Mobile Mapping Service). In this example, the proposed system 10 is connected to a mobile terminal 46, but the present invention is not limited to this. In addition, a part or all of the proposed system 10 may be provided on a cloud via the Internet.

[0015] The processing unit 20 includes at least an acquisition unit 21, an assignment unit 21a, a generation unit 21b, a setting unit 21c, an interference range calculation unit 24, and a proposal unit 28. The processing unit 20 may further include, for example, a movement processing unit 22, a determination unit 23, an output control unit 26, and a repetitive execution unit 27. Note that in this embodiment, the term "unit" does not simply mean a physical means, but also includes cases where the function of the "unit" is realized by a program. Furthermore, the function of one "unit" may be realized by two or more physical means or programs.

[0016] In the example shown in Figures 1 to 4, the acquisition unit 21 acquires three-dimensional point cloud data and image data along the transportation route for transporting the cargo, and a vehicle model 65 that is a three-dimensional model of the vehicle transporting the cargo and the cargo loaded on the vehicle.

[0017] The 3D point cloud data and image data can be generated by a mobile measuring device that measures the road surface and surrounding features along the planned actual transportation route. Examples of the mobile measuring device include a vehicle-type MMS 40 equipped with a measuring instrument 42 or an unmanned aerial vehicle such as a drone. The MMS 40 can be a commercially available, well-known mobile mapping system. The measuring instrument 42 includes, for example, a Global Navigation Satellite System (GNSS) receiver, an Inertial Measurement Unit (IMU), and an odometer for obtaining position data for the MMS 40, a laser scanner for obtaining 3D point cloud data, and a camera for capturing images of features. The laser scanner can be LIDAR (Laser Imaging Detection and Ranging), a remote sensing technology using laser light. The 3D point cloud data can also be obtained not only from the MMS 40, but also from, for example, manual surveying results or publicly available map information provided on the Internet.

[0018] As shown in FIG. 2 , the vehicle model 65 is three-dimensional data created based on the shape of an actual large vehicle transporting a load, such as a blade 64. Examples of large vehicles include large automobiles, so-called trucks, and trailer-type vehicles equipped with a towed vehicle. The load is a large load that protrudes from the vehicle, such as a blade used in a wind turbine of a wind power generation facility. In this embodiment, a vehicle transporting a blade is described, but this is not limited to this. The vehicle model 65 preferably reflects the size and shape of the actual vehicle 60 and blade 64. However, to improve processing speed, the vehicle model 65 may be, for example, 50 cm to 100 cm larger than the actual size, or may be a box-shaped model reflecting the maximum width, maximum length, and maximum height. By making the vehicle model 65 larger than the actual size, not only can processing speed be improved but also interference can be avoided during actual transportation even if there is a difference between the feature data and the actual feature. The vehicle model 65 includes, for example, a trailer-type vehicle 60 equipped with a towing vehicle 61 carrying a driver and a towed vehicle 62 carrying a blade 64; a drive mechanism 63 installed on the towed vehicle 62; and a blade 64 supported by the drive mechanism 63 so as to be able to be raised and / or swiveled horizontally. The state of the blade 64 in the vehicle model 65 is one example, and the blade 64 may be generated to be able to stand up and / or swivel horizontally relative to the vehicle 60, depending on the actual vehicle to be used. Multiple vehicle models with different angles between the vehicle model 65 and the blade 64 may also be prepared. The drive mechanism 63 supports the blade 64 and includes a drive unit that changes the blade 64 from a lowered state in which the blade 64 extends substantially horizontally to a state in which the blade 64 is raised, for example, at 60 degrees relative to the horizontal plane, and a drive unit that changes the free end of the blade 64 to a state in which the blade 64 is rotated horizontally, for example, by 30 degrees to the left and right. Wind turbine towers are also long members, but are generally transported after being cut into transportable lengths, and are not transported using the drive mechanism 63. In contrast, the blade 64 cannot cut, and therefore the interference range is wider when the blade 64 is lowered than when the tower is lowered, so measures such as the drive mechanism 63 and cutting down trees in the interference range are necessary. The three-dimensional point cloud data and the vehicle model 65 are stored in the storage unit 30, for example.

[0019] The assigning unit 21a assigns attributes to at least a portion of the three-dimensional point cloud data acquired by the acquiring unit 21. The assigning unit 21a may determine the attributes using image data. Attributes are set based on the type of object present around the transportation route, such as natural objects and artificial structures. Attributes of artificial structures include, for example, road surfaces, slopes, curbs, white lines, gutters, road signs, guardrails, pedestrian bridges, power lines, utility poles, traffic lights, bridges, and buildings. Attributes of natural objects include, for example, trees and natural ground. The assigning unit 21a may automatically assign attributes to the coordinates of the feature data included in the three-dimensional route data 50 according to each feature, using, for example, artificial intelligence that has previously performed machine learning for each attribute using image training data. Examples of the artificial intelligence include a deep neural network using semantic segmentation. Attributes may also be assigned manually to each feature data in response to instructions from the operation unit 32 operated by the person performing the transportation work. By assigning attributes to the three-dimensional point cloud data by the assigning unit 21a, it becomes possible to recognize whether the feature in the interference range is, for example, a tree or a slope.

[0020] The assigning unit 21a may assign attributes to the three-dimensional route data 50 generated by the generating unit 21b, which will be described later.

[0021] As shown in Fig. 3, the generation unit 21b generates three-dimensional route data 50. The three-dimensional route data 50 includes, for example, feature data such as a road surface 51, a slope 54 adjacent to the road surface 51, a building 55a, a utility pole 55b, and a tree 56, based on an actual transportation route. The three-dimensional route data 50 may further include feature data of natural objects and artificial structures to which attributes have been assigned. Based on the three-dimensional point cloud data and the image data, the generation unit 21b replaces a portion of the three-dimensional point cloud data corresponding to the road surface 51 with three-dimensional modeled three-dimensional road surface data, and replaces portions of the three-dimensional point cloud data corresponding to a plurality of artificial structures with a plurality of three-dimensional modeled three-dimensional road surface data. The three-dimensional route data 50 is generated by replacing the data with three-dimensional structural data (e.g., slope 54, building 55a, utility pole 55b). Three-dimensional point cloud data is a collection of multiple points arranged in three dimensions and can represent the shape of an object. Each point in the three-dimensional point cloud data has three-dimensional coordinate values ​​and attributes. Three-dimensional modeling involves converting point cloud data into data containing surface components. Well-known three-dimensional modeling techniques, such as Delaunay triangulation, alpha shape, and box modeling, can be used. The three-dimensional road surface data in the three-dimensional route data 50 can be mesh data. Many artificial structures, such as road surfaces 51 and buildings 55a, are relatively stylized. Simplifying the point cloud data by creating a three-dimensional model of the data makes it easier to reduce the data weight, contributing to high-speed processing in the proposed system 10. Therefore, the three-dimensional model of a building 55a can be simplified compared to its actual shape, and the shapes of parts that do not face the road can be omitted. On the other hand, the shapes of natural objects, such as trees 56, are irregular and can be left as point cloud data.

[0022] The generating unit 21b may estimate the types of each of the multiple artificial structures from the three-dimensional point cloud data and the image data, select multiple pieces of three-dimensional structure data generated in advance that correspond to the estimated types, and replace part of the three-dimensional point cloud data with the selected pieces of three-dimensional structure data. The estimation of the type of artificial structure may be performed in parallel with the assignment of attributes by the assigning unit 21a. Since artificial structures are often standardized, converting them into three-dimensional data in advance speeds up the processing by the generating unit 21b.

[0023] The setting unit 21c sets a virtual transportation route 52 connecting at least two reference points in the three-dimensional road surface data. The two reference points are, for example, a start reference point 53a and an end reference point 53b shown in FIG. 4. Because the actual transportation route is a long distance from the port to the wind turbine installation site, the virtual transportation route 52 in the three-dimensional route data 50 may be a portion of the actual transportation route divided into multiple sections. In this embodiment, an example is shown in which the virtual transportation route 52 (shown by a dotted line) is set between the start reference point 53a and the end reference point 53b. The setting unit 21c may set multiple reference points (passing points) through which the vehicle model 65 passes between the start reference point 53a and the end reference point 53b. The setting unit 21c may set the reference points and the virtual transportation route 52 in response to instructions from the operation unit 32 operated by the person performing the transportation work, or the reference points and the virtual transportation route 52 may be automatically set by artificial intelligence taking into account the width of the road surface 51 and the positions of the feature data. For example, the setting unit 21c may select some of the multiple pass points automatically set between the start reference point 53a and the end reference point 53b, and then connect the pass points so that the selected pass points are passed through. The more selectable pass points between the start reference point 53a and the end reference point 53b, the more virtual transportation routes 52 can be set. The setting unit 21c may generate and set the virtual transportation routes 52 using a known machine learning optimization algorithm. In this case, reinforcement learning may be performed to obtain a high evaluation using, for example, distance or time as an evaluation value. Examples of optimization algorithms that can be used include breadth-first search, depth-first search, and Dijkstra's algorithm. The setting unit 21c may prepare multiple virtual transportation routes 52 in advance, and a different virtual transportation route 52 may be selected from them by the iterative execution unit 27 (described later). Furthermore, a smooth virtual transportation route 52 may be set so that it passes through multiple pass points located in positions where the vehicle model 65 can travel using artificial intelligence that has learned actual vehicle driving through machine learning.

[0024] The movement processing unit 22 moves the vehicle model 65 multiple times along the virtual transportation route 52 in the three-dimensional route data 50, for example, as shown in FIG. 3. The movement processing unit 22 may also execute the movement processing with the vehicle model 65 in a state where it has undergone horizontal turning deformation or vertical deformation. The movement processing unit 22 can simulate actual transportation by moving the vehicle model 65 along the three-dimensional coordinate values ​​of the virtual transportation route 52 on the road surface 51 of the three-dimensional route data 50 acquired by the acquisition unit 21, for example, through input operations from the operation unit 32. For this reason, it is preferable that the tires of the vehicle 60 of the vehicle model 65 can be operated in a manner similar to that of the actual vehicle 60, and that the towing vehicle 61 and towed vehicle 62 can also be operated in a manner similar to that of the actual vehicle 60. Furthermore Furthermore, artificial intelligence that has learned actual vehicle driving through machine learning may be used to make the vehicle model 65 travel smoothly along the virtual transportation route 52 on the road surface 51 in a manner similar to actual driving. The movement processing unit 22 may be a part of the interference range calculation unit 24 described later.

[0025] The determination unit 23, for example, executes processing in the movement processing unit 22 to determine whether or not feature data included in the three-dimensional route data 50 interferes with the vehicle model 65. When the vehicle model 65 is moved along the virtual transportation route 52, for example, the blade 64 makes a large turn at a curve in a mountain road or an intersection in an urban area, and there are locations where the vehicle model 65, particularly the blade 64, comes into contact with feature data, such as a slope 54, a building 55a, or a utility pole 55b in the three-dimensional structure data, or a tree 56 in the point cloud data as a natural object. In this case, the determination unit 23 determines that "interference occurs." The presence or absence of interference may be determined based on overlap between three-dimensional data, or based on overlap in two dimensions when the three-dimensional route data 50 is viewed from above.

[0026] The interference range calculation unit calculates the interference range between the vehicle model 65 and the three-dimensional route data. The movement processing unit 22 may execute the movement of the vehicle model 65, and the determination unit 23 may determine whether or not the vehicle model 65 interferes with the feature data in the three-dimensional route data. Because the feature data is assigned attributes, the interference range calculation unit 24 can determine which attribute the feature data in the interference range has. The interference range calculation unit 24 may calculate the amount of trees 56 cut in a cutting range 58 within the interference range and the widening area of ​​a widening range 59 for widening the road within the interference range of the slope 54. Similarly, the interference range calculation unit 24 may calculate the number of construction sites for removing or relocating utility poles, traffic lights, etc. within the interference range to which attributes of utility poles, traffic lights, etc. have been assigned. By calculating the range of interference with the three-dimensional structure data and other point cloud data, the interference range calculation unit 24 can clarify the attributes and range of features interfering with the vehicle 60 and the blade 64 before the blade 64 is actually transported. This allows accurate planning of road widening and tree cutting 56 without relying on the experience of the person performing the transport work. Such planning supports the person performing the transport work. This support reduces the need to avoid sudden interference during transport, resulting in improved work efficiency.

[0027] The interference range calculation unit 24 may obtain the expected cost for the amount of felling per unit area and the expected cost for the area to be widened per unit area from the memory unit 30, and calculate the cost for the amount of felling in the dataset and the cost for the area to be widened.

[0028] The output control unit 26 can output the interference range calculated by the interference range calculation unit 24 to, for example, the storage unit 30, the display unit 34, or an external device. The output control unit 26 outputs the interference range calculated by the interference range calculation unit 24 to, for example, the display unit 34. It can be made possible to determine whether the output interference range is three-dimensional structure data or three-dimensional point cloud data. In addition, attributes of the interfering features may be output. This makes it easier for the person performing the transportation work to recognize the interfering object.

[0029] As shown in FIG. 4, the display unit 34 may display the interference range (cutting range 58, widening range 59). By displaying the interference range together with the map data 57 on the display unit 34, the person performing the transportation work can easily grasp the interference range. In addition, the interference range output from the output control unit 26 can be displayed on the display unit 34 superimposed on the three-dimensional route data 50, and the interference range may also be displayed on the display unit 34 as a cross-sectional view or a longitudinal section. Such output information may also be printed on paper media. By outputting the interference range, for example, the construction plan can be easily explained to residents and managers of features (national and local governments), and the cross-sectional view and longitudinal section can be used for designing additional construction work. The output control unit 26 may output the interference range to an external device, such as a mobile terminal 46 or a car navigation system. The display unit 34 and a display device such as the mobile terminal 46 can display the above-mentioned simulated data on the virtual transportation route 52. The travel route of the rated vehicle 60 may be displayed as a curve. The driver of the vehicle 60 may perform transportation work while viewing the travel route displayed on the display unit 34, the mobile terminal 46, or the like.

[0030] The storage unit 30 can store three-dimensional point cloud data, image data, three-dimensional route data 50, and a virtual transportation route 52. The storage unit 30 can store, for example, multiple three-dimensional structure data. The three-dimensional structure data stored in the storage unit 30 is a three-dimensional model of commonly used artificial structures installed around roads. For example, it is a three-dimensional model of multiple utility poles of different heights, multiple curbs of different lengths, multiple road gutters of different widths, road signs, etc. The storage unit 30 stores a dataset of the virtual transportation route 52 and the interference range output by the output control unit 26. The dataset is stored in association with the interference range when the vehicle model 65 travels along the virtual transportation route 52 set by the setting unit 21c. The dataset may also include attributes of the interference range.

[0031] The repetitive execution unit 27 repeatedly executes the process from setting the virtual transportation route 52 to storing the data set a predetermined number of times. The repetitive execution unit 27 can set a virtual transportation route 52 that is different from the virtual transportation route 52 that has already been set in the previous execution. Thus, a data set corresponding to the predetermined number of times repeated by the repetitive execution unit 27 is obtained. The predetermined number of times may be set to, for example, several hundred times.

[0032] The proposing unit 28 proposes a virtual transportation route 52 including an interference range. Since a large number of data sets are obtained by the repetitive execution unit 27 executing the process a predetermined number of times, the proposing unit 28 can narrow down the number of data sets from the data sets by taking into consideration the attributes of the interfering objects, and propose multiple virtual transportation routes 52. The conditions for narrowing down the number of data sets can be set by the person performing the transportation work. For example, since it may be more difficult to obtain permission to move or remove an artificial structure than a natural object, a virtual transportation route 52 that interferes less with the three-dimensional structure data may be proposed. Furthermore, since it may be difficult to remove a natural object in a location designated as a nature conservation area, a virtual transportation route 52 that interferes less with the three-dimensional point cloud data may be proposed.

[0033] The display unit 34 can display, for example, a start reference point 53a and an end reference point 53b on the map data in addition to the displays described in the output control unit 26. The display unit 34 may also display the attributes, felling volume, widening area, and cost stored in the storage unit 30 for each of the multiple virtual transportation routes 52.

[0034] According to the proposed system 10 of this embodiment, before actually transporting a load, for example, a blade, it is possible to propose a plurality of virtual transportation routes 52 together with the amount of trees to be cut and the area of ​​road widening that will require cutting down trees and widening the road due to interference with the vehicle and the blade. In particular, according to the proposed system 10 of this embodiment, the person performing the transportation work can determine the actual transportation route after accurately understanding the range of interference between artificial structures and non-artificial structures, thereby improving work efficiency.

[0035] 2. Virtual transportation route proposal method The method for proposing a virtual transportation route according to this embodiment acquires three-dimensional point cloud data and image data along a transportation route for transporting a load, and a vehicle model that is a three-dimensional model of a large vehicle that transports the load and the load loaded on the vehicle, and based on the three-dimensional point cloud data and the image data, replaces a portion of the three-dimensional point cloud data that corresponds to a road surface with three-dimensional road surface data that is a three-dimensional model, and replaces portions of the three-dimensional point cloud data that correspond to a plurality of artificial structures with three-dimensional structure data that is a three-dimensional model, thereby generating three-dimensional route data, sets a virtual transportation route that connects at least two reference points in the three-dimensional road surface data, moves the vehicle model along the virtual transportation route, and generates three-dimensional route data for the vehicle. The interference range between both models and the three-dimensional route data is calculated, and the virtual transportation route including the interference range is proposed.

[0036] An example of a method for proposing a virtual transportation route 52 using the proposal system 10 described with reference to Figures 1 to 4 will be described with reference to the flowchart of Figure 5. Figure 5 is a flowchart of the method for proposing a virtual transportation route 52 according to this embodiment.

[0037] As shown in FIG. 5, the method for proposing a virtual transportation route 52 (hereinafter simply referred to as the "proposing method") includes at least a step (S10) of acquiring data, etc., a step (S30) of generating three-dimensional route data, a step (S40) of setting the virtual transportation route 52, a step (S50) of calculating the interference range, and a step (S80) of proposing the virtual transportation route 52. The proposing method may further include a step (S20) of assigning attributes, a step (S60) of storing the data set, and a step (S70) of repeating the process a predetermined number of times. The proposing method may be executed by, for example, having the processing unit 20 execute a program stored in the storage unit 30. Alternatively, the proposing method may be executed according to a program received from an external device via a communication interface. For example, the proposing method may be executed for each section by dividing a long transportation route into multiple sections.

[0038] S10: In the step of acquiring data, the acquisition unit 21 acquires three-dimensional point cloud data and image data along the transport route for transporting the cargo, and a vehicle model 65 that is a three-dimensional model of a large vehicle transporting the cargo and the cargo loaded on the vehicle. The three-dimensional point cloud data, image data, and vehicle model 65 data can be acquired from, for example, the storage unit 30 and the MMS 40. The cargo is, for example, a blade used in a wind turbine of a wind power generation facility. In this embodiment, a vehicle that transports blades will be described, but the present invention is not limited to this.

[0039] In the step of S20: assigning attributes, the assigning unit 21a assigns attributes to at least a portion of the three-dimensional point cloud data. The assigning unit 21a assigns attributes to, for example, natural objects and artificial structures using, for example, image data. The assignment of attributes may be performed automatically using, for example, artificial intelligence, or may be performed directly by a person performing transportation work using the operation unit 32. S20 may be performed in parallel with S30, or some of the processing may be performed after S30 to assign attributes to the three-dimensional route data 50.

[0040] S30: In the step of generating three-dimensional route data 50, the generation unit 21b replaces a portion of the three-dimensional point cloud data corresponding to the road surface 51 with three-dimensional road surface data that has been three-dimensionally modeled, and replaces portions of the three-dimensional point cloud data corresponding to a plurality of man-made structures with three-dimensional structure data that has been three-dimensionally modeled, based on the three-dimensional point cloud data and image data, thereby generating three-dimensional route data. The three-dimensional road surface data in the three-dimensional route data 50 can be mesh data. By three-dimensionally modeling the point cloud data of the man-made structures to reduce the data weight, the processing speed of S30 can be increased. On the other hand, the point cloud data of irregular natural objects, such as trees 56, can be used as is to accurately calculate the interference range in S50.

[0041] In the step of replacing the data with three-dimensional structure data, the generation unit 21b estimates the types of each of the multiple artificial structures from the three-dimensional point cloud data and image data, and selects from the storage unit 30 multiple pieces of pre-generated three-dimensional structure data corresponding to the estimated types to replace part of the three-dimensional point cloud data. In S20, the type of the artificial structure may be estimated in addition to assigning an attribute. For example, if the artificial structure is estimated to be a utility pole 55b, a three-dimensional model of the utility pole 55b with a height determined from the point cloud data or image data is selected from multiple utility poles 55b of different heights that have been pre-modeled three-dimensionally, and the three-dimensional point cloud data at the corresponding location is replaced with the three-dimensional point cloud data.

[0042] S40: The step of setting the virtual transportation route 52 is performed by the setting unit 21c using the three-dimensional A virtual transportation route 52 connecting at least two reference points is set in the road surface data. S40 is repeatedly executed a predetermined number of times by S70, which will be described later. A different virtual transportation route 52 is set each time S40 is repeatedly executed. The setting unit 21c, for example, uses artificial intelligence to select multiple passing points set between the start reference point 53a and the end reference point 53b, and sets the virtual transportation route 52 to connect them. It is preferable that the setting unit 21c sets the virtual transportation route 52 so that there is minimal interference with surrounding feature data when the vehicle model 65 travels.

[0043] S50: In the step of calculating the interference range, the movement processing unit 22 moves the vehicle model 65 along the virtual transportation route 52, and the interference range calculation unit 24 calculates the interference range between the vehicle model 65 and the three-dimensional route data. More specifically, the step of calculating the interference range may be composed of, for example, a step of moving the vehicle model 65, a step of determining interference, and a step of calculating the interference range.

[0044] In the step of moving the vehicle model 65, the movement processing unit 22 can move the vehicle model 65 along the virtual transportation route 52 set in the three-dimensional route data 50, for example. This step places the vehicle model 65 in the same three-dimensional coordinate system as the three-dimensional route data 50, and makes it possible to simulate the movement of the vehicle model 65 in the same way as the movement of an actual large vehicle and its cargo. This step is not greatly affected by the experience of the transportation operator.

[0045] In the interference determination step, the determination unit 23 determines whether or not, for example, three-dimensional structure data (buildings 55a, utility poles 55b, slopes 54, etc.) and three-dimensional point cloud data other than three-dimensional structure data (trees 56, natural ground, etc.) included in the three-dimensional route data 50 interfere with the vehicle model 65 when the vehicle model 65 moves. Since artificial structures are three-dimensionally modeled, the processing of S40 and S50 can be accelerated. Since natural objects are processed as three-dimensional point cloud data, their shapes are close to their actual shapes, allowing for accurate interference determination. If it is determined that the three-dimensional structure data and the three-dimensional point cloud data interfere with the vehicle model 65, the step of calculating the interference range is executed. On the other hand, if it is determined that the feature data does not interfere with the vehicle model 65, the step of calculating the interference range is not executed, and S60 is executed.

[0046] The step of calculating the interference range is a step in which the interference range calculation unit 24 calculates the range of interference with the vehicle model 65 in the three-dimensional route data 50. The interference range calculation unit 24 may calculate, for example, the overlap between the vehicle model 65 and feature data in a planar view as the interference range, or may calculate the overlap between the vehicle model 65 and feature data in three dimensions as the interference range. The interference range may also be calculated for each attribute of the feature data, and for example, the area and expected construction costs may also be calculated for each attribute. The step of calculating the interference range may calculate the interference range by dividing the data into three-dimensional structure data and three-dimensional point cloud data. The person performing the transportation work can determine the actual transportation route after accurately understanding the interference range between artificial structures and non-artificial structures, thereby improving work efficiency.

[0047] S60: In the step of storing the data set, the processing unit 20 stores a data set of the virtual transportation route 52 set in S40 and the interference range calculated in S50 in the storage unit 30. By repeatedly executing each step in S70, which will be described later, multiple data sets of the virtual transportation route 52 and the interference range are stored in the storage unit 30.

[0048] S70: In the step of determining whether the process has been repeated a predetermined number of times, the processing unit 20 determines whether S40 to S60 have been executed a predetermined number of times. If S70 is "NO", the processing unit 20 sets a virtual transportation route 52 different from the already set virtual transportation route 52 and executes the process from setting the virtual transportation route 52 (S40) to storing the data set (S60) a predetermined number of times. If S70 is "YES", S80 is executed.

[0049] In the step S80, the proposal unit 28 proposes a virtual transportation route 52 having the interference range stored in S60. In S80, the output control unit 26 may output multiple data sets to, for example, the display unit 34, the mobile terminal 46, or a printer (not shown) in response to a command from the proposal unit 28. The proposal method in S80 may be a set of numerical data, such as the area and volume of the interference range of the three-dimensional structure data and other three-dimensional point cloud data, and three-dimensional data of the virtual transportation route 52, or two-dimensional or three-dimensional data overlaid on a map. Furthermore, the display unit 34 may display a video of the vehicle model 65 moving along each virtual transportation route 52 and the interference range that occurs as the vehicle model 65 moves. While a virtual transportation route 52 with the smallest interference range is generally desirable, the person performing the transportation work can review the proposal in S80 and select, for example, a virtual transportation route 52 with fewer three-dimensional structure data within the interference range. This is because removing artificial structures is often more difficult than removing natural objects. It is also preferable to take into consideration, for example, areas designated as nature conservation areas where it is difficult to obtain permission to cut down trees 56, or areas where slopes 54 are prone to collapse, in the proposed virtual transportation route 52. For this reason, it is preferable to propose multiple data sets so that the person performing the transportation work can make a selection.

[0050] According to the method for proposing a virtual transportation route of this embodiment, it is possible to propose multiple virtual transportation routes 52 along with the range of interference with large vehicles and loads before actually transporting the load, such as a blade. In particular, the proposed method allows the person performing the transportation work to determine the actual transportation route after accurately understanding the range of interference with artificial structures and non-artificial structures, thereby improving work efficiency. [Explanation of symbols]

[0051] 10...Proposed system, 20...Processing unit, 21...Acquisition unit, 21a...Assignment unit, 21b...Generation unit, 21c...Setting unit, 22...Movement processing unit, 23...Determination unit, 24...Interference range calculation unit, 26...Output control unit, 27...Repeated execution unit, 28...Proposal unit, 30...Memory unit, 32...Operation unit, 34...Display unit, 40...MMS, 42...Measuring instrument, 46...Mobile terminal, 50...Three-dimensional route data, 51...Road surface, 52...Virtual transportation route, 53a...Start reference point, 53b...End reference point, 54...Slope, 55a...Building, 55b...Telephone pole, 56...Trees, 57...Map data, 58...Logging range, 59...Widening range, 60...Vehicle, 61...Towing vehicle, 62...Towed vehicle, 63...Drive mechanism, 64...Blade, 65...Vehicle model

Claims

1. Acquire three-dimensional point cloud data and image data along a transport route for transporting the cargo, and a vehicle model that is a three-dimensional model of a large vehicle transporting the cargo and the cargo loaded on the vehicle; based on the three-dimensional point cloud data and the image data, replacing a portion of the three-dimensional point cloud data corresponding to a road surface with three-dimensional road surface data that has been three-dimensionally modeled, and replacing a portion of the three-dimensional point cloud data corresponding to a plurality of artificial structures with a plurality of three-dimensional structure data that have been three-dimensionally modeled, thereby generating three-dimensional route data; a virtual transportation route connecting at least two reference points in the three-dimensional road surface data; moving the vehicle model along the virtual transportation route to calculate an interference range between the vehicle model and the three-dimensional route data; A method for proposing a virtual transportation route, comprising: proposing the virtual transportation route including the interference range.

2. The virtual transportation route proposing method according to claim 1, The method for proposing a virtual transportation route is characterized in that the step of replacing with three-dimensional structure data includes estimating the types of the plurality of artificial structures from the three-dimensional point cloud data and the image data, selecting the plurality of three-dimensional structure data generated in advance corresponding to the estimated types, and replacing part of the three-dimensional point cloud data.

3. 3. The method for proposing a virtual transportation route according to claim 1 or 2, A method for proposing a virtual transportation route, wherein the three-dimensional road surface data is mesh data.

4. 3. The method for proposing a virtual transportation route according to claim 1 or 2, A method for proposing a virtual transportation route, wherein the load is a blade used in a wind turbine of a wind power generation facility.

5. an acquisition unit that acquires three-dimensional point cloud data and image data along a transport route for transporting the load, and a vehicle model that is a three-dimensional model of a large vehicle that transports the load and the load loaded on the vehicle; a generation unit that generates three-dimensional route data by replacing a portion of the three-dimensional point cloud data corresponding to a road surface with three-dimensional road surface data that has been three-dimensionally modeled, and by replacing a portion of the three-dimensional point cloud data corresponding to a plurality of artificial structures with a plurality of three-dimensional structure data that have been three-dimensionally modeled, based on the three-dimensional point cloud data and the image data; a setting unit that sets a virtual transportation route connecting at least two reference points in the three-dimensional road surface data; a movement processing unit that moves the vehicle model multiple times along the virtual transportation route; an interference range calculation unit that calculates an interference range between the vehicle model and the three-dimensional route data; a proposal unit that proposes the virtual transportation route including the interference range; A virtual transportation route proposing system comprising:

6. 6. The virtual transportation route proposing system according to claim 5, A virtual transportation route proposing system, characterized in that the load is a blade used in a wind turbine of a wind power generation facility.

Images