Road surface measurement device

Abstract

Without using GNSS, the road surface measurement device is driven autonomously to collect image data with minimal blurring and misalignment. [Solution] The road surface measurement device comprises a trolley, an imaging device, and a control device. The control device autonomously drives the trolley and acquires multiple image data of the road surface captured by the imaging device. The road surface measurement device includes a porous pitot tube for detecting the wind direction relative to the straight-ahead direction of the trolley, and the control device controls the road surface measurement device using the wind direction information detected by the porous pitot tube.

Description

[Technical Field]

[0001] This disclosure relates to a road surface measurement device. [Background technology]

[0002] There is a technology that generates a three-dimensional road surface model by acquiring multiple image data obtained by photographing the road surface while a trolley is running, for purposes such as inspecting road surface irregularities and damage, and then combining these image data.

[0003] For example, Patent Document 1 discloses a control device that acquires multiple captured images containing depth information by photographing the travel surface of a moving object using multiple stereo imaging means, matches feature points extracted from each stereo captured image, and overlaps the acquired multiple captured images to connect them in the width direction of the travel surface. [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2019-164138 [Overview of the project] [Problems that the invention aims to solve]

[0005] Here, by making the device for collecting image data (road surface measurement device) autonomous, it becomes possible to automatically collect image data used to generate a three-dimensional road surface model. To improve the accuracy of the three-dimensional road surface model described above, it is important to acquire high-resolution image data by suppressing blur in the captured images, and to acquire road surface image data by having the road surface measurement device travel without deviating significantly from the desired target travel path. For example, by utilizing a GNSS (Global Navigation Satellite System) such as GPS (Global Positioning System), the road surface measurement device can be made to travel autonomously along the target measurement path. However, if GNSS is not installed, or in environments where satellite signals cannot be received, such as inside a tunnel, there is a risk that the road surface measurement device will deviate from its travel path or experience significant shaking during travel.

[0006] This disclosure has been made in view of the above-mentioned issues, and the purpose of this disclosure is to provide a road surface measurement device that can autonomously drive without using GNSS and collect image data with less blurring and deviation. [Means for solving the problem]

[0007] To solve the above problems, according to one aspect of this disclosure, a road surface measuring device is provided, comprising a trolley, an imaging device, and a control device, wherein the control device acquires a plurality of image data of the road surface captured by the imaging device while the trolley autonomously travels, and the control device includes a porous pitot tube for detecting the wind direction relative to the straight-ahead direction of the trolley, and the control device controls the road surface measuring device using the wind direction information detected by the porous pitot tube. [Effects of the Invention]

[0008] As explained above, this disclosure makes it possible to collect image data with minimal blurring and misalignment by autonomously driving a road surface measurement device without using GNSS. [Brief explanation of the drawing]

[0009] [Figure 1] It is a diagram shown to explain the overall outline of a road surface measurement system using a road surface measurement device according to an embodiment of the present disclosure. [Figure 2] It is an explanatory diagram of the road surface measurement device according to the first embodiment seen from the side. [Figure 3] It is an explanatory diagram of the road surface measurement device according to the first embodiment seen from above. [Figure 4] It is a block diagram showing a configuration example of a measurement system according to the first embodiment. [Figure 5] It is a flowchart of road surface measurement processing by the processing unit of the control device according to the first embodiment. [Figure 6] It is a flowchart of autonomous driving control processing by the autonomous driving control unit of the control device according to the first embodiment. [Figure 7] It is a flowchart of self-position estimation processing by the self-position estimation unit of the control device according to the first embodiment. [Figure 8] It is a flowchart of imaging device driving processing by the imaging device driving unit of the control device according to the first embodiment. [Figure 9] It is an explanatory diagram showing the overlapping rate (image overlapping rate) of the shooting ranges of two pieces of image data captured in time series. [Figure 10] It is an explanatory diagram showing the overlapping rate (image overlapping rate) of the shooting ranges of two pieces of image data captured in time series. [Figure 11] It is an explanatory diagram showing the reference distance range and shooting timing of the moving distance of the carriage. [Figure 12] It is a flowchart of data processing by the data processing unit of the information processing device according to the first embodiment. [Figure 13] It is a flowchart of autonomous driving control processing by the autonomous driving control unit of the control device according to the second embodiment. [Figure 14] It is an explanatory diagram showing the measurement points of the traveling locus and turning angle of the road surface measurement device. [Figure 15] It is a diagram exemplifying a part of the measurement points of the turning angle of the road surface measurement device. [Modes for carrying out the invention]

[0010] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the attached drawings. In this specification and the drawings, components having substantially the same configuration are denoted by the same reference numerals, and redundant descriptions will be omitted.

[0011] <<Overview of the Road Surface Measurement System>> First, we will describe the overall overview of the road surface measurement system using the road surface measurement device described herein.

[0012] Figure 1 is a diagram illustrating an example of a road surface measurement system. In the example shown in Figure 1, the road surface measurement system 1 comprises a road surface measurement device 10 equipped with an imaging device and an information processing device 100 that is communicatively connected to the road surface measurement device 10. The road surface measurement device 10 and the information processing device 100 are communicatively connected, for example, via wired or wireless communication means.

[0013] The road surface measurement device 10 captures images of the road surface R, which is the target of measurement, using an imaging device to generate image data Img_α (α=1,2···M) (where M is the number of imaging devices 21), and transmits the generated image data Img_α to the information processing device 100 sequentially or after the completion of imaging. The information processing device 100 acquires the image data Img_α and generates a road surface model, which is three-dimensional data showing the unevenness of the road surface, based on the acquired image data Img_α.

[0014] For example, the road surface measurement device 10 divides road R into three regions D1 to D3 and takes images of the road surface. The road surface measurement device 10 generates time-series image data Img_α while autonomously driving through each region D1 to D3. To ensure that the entire measurement range of road R is not missed from the shooting range, adjacent regions D1 to D3 are set to partially overlap.

[0015] The road surface measurement device 10 has multiple imaging devices arranged along a direction (left-right direction) perpendicular to the direction of movement (front-back direction). Each of the multiple imaging devices photographs the road surface while the road surface measurement device 10 autonomously travels through each region D1 to D3, generating multiple image data Img_α. The multiple imaging devices are installed so that the shooting ranges P1 to P6 of adjacent imaging devices partially overlap, so that the entirety of each region D1 to D3 is not left out of the shooting range.

[0016] The movement speed of the road surface measurement device 10 is set so that the time-series image data Img_α generated by each imaging device partially overlap. In other words, the shooting range at time t_n partially overlaps with the shooting range at the previous time t_n-1 and the next time t_n+1. At this time, an overlap rate, which is the ratio of the area where the two time-series image data Img_α overlap to the total area of ​​the shooting range, is set in advance. The overlap rate is set to, for example, 40-80%, but is not particularly limited.

[0017] In Figure 1, an example is shown where the road R to be measured extends in a straight line and the road surface measurement device 10 travels in a straight line. However, the shape of the road to be measured may be curved, and the example is not limited to the road surface measurement device 10 traveling in a straight line. Furthermore, the method of dividing the measurement area, the order of travel within the area, and the path of the road surface measurement device 10 are not limited to the example above. The number of imaging devices is also not particularly limited.

[0018] The information processing device 100 extracts feature points from multiple acquired image data Img_α and performs a feature point matching process to align the feature points between the image data Img_α. The feature point matching process is performed, for example, using SfM (Structure from Motion) processing. The information processing device 100 also synthesizes the multiple image data Img_α through the feature point matching process to generate a road surface model that shows information about the unevenness of the road surface. The generation of the road surface model is performed, for example, using MVS (Multi-View Stereo) processing.

[0019] <<First Embodiment>> Next, a road surface measuring device according to the first embodiment of this disclosure will be described.

[0020] <Overall configuration of the road surface measurement device> Figures 2 and 3 are explanatory diagrams showing an example configuration of the road surface measurement device 10. Figure 2 is a side view of the road surface measurement device 10, and Figure 3 is a top view of the road surface measurement device 10. In Figures 2 and 3, the basic forward direction of the road surface measurement device 10 is indicated as "forward," and the backward direction as "rear." Hereafter, the longitudinal, lateral, and height directions of the road surface measurement device 10 are indicated relative to the "forward" and "rear" directions.

[0021] The road surface measurement device 10 generates multiple image data Img_α of the road surface to be measured and transmits the generated image data Img_α to the information processing device 100. The road surface measurement device 10 according to this embodiment is configured to be able to move on the road surface unmanned (autonomous driving). The road surface measurement device 10 comprises a trolley 3, an imaging unit 5, a surrounding condition detection unit 7, a porous pitot tube 35, and a control device 50.

[0022] The bogie 3 comprises a frame 11, wheels 13 (13F, 13R), a power source 15, and a steering device 17. The wheels 13 (13F, 13R), the power source 15, and the steering device 17 correspond to the drive devices that move the position of the road surface measuring device 10. The frame 11 forms the skeleton of the bogie 3. The structure and overall shape of the frame 11 shown in Figures 2 and 3 are merely examples, and the configuration of the frame 11 is not particularly limited. The wheels 13 each have left and right front wheels 13F and rear wheels 13R.

[0023] The drive source 15 outputs a driving force to rotate the rear wheel 13R. A drive motor is a typical example of the drive source 15, but it is not particularly limited to any other device capable of outputting power to rotate the rear wheel 13R.

[0024] The steering device 17 adjusts the steering angle of the front wheels 13F. An example of the steering device 17 is a steering device configured such that a motor rotates a pinion gear, and the rotation of the pinion gear moves a rack left and right, but the configuration of the steering device 17 is not particularly limited.

[0025] The trolley 3 is not particularly limited in its specific configuration, as long as it can support the imaging unit 5 and the surrounding situation detection unit 7 and can move while adjusting its direction of movement. For example, the trolley 3 does not need to have four wheels 13; it may have three, or five or more. Also, the wheels 13 that are rotationally driven by the power output from the drive source 15 may be the front wheels 13F, or all of the front wheels 13F and rear wheels 13R may be rotationally driven. Furthermore, the drive source 15 may consist of four drive motors, each driving one of the four wheels 13.

[0026] Furthermore, the wheel whose steering angle is adjusted by the steering device 17 may be the rear wheel 13R, or it may be all of the front wheels 13F and rear wheels 13R. If four drive motors drive each of the four wheels 13, and the direction of travel of the road surface measuring device can be adjusted by controlling the output of the drive motors, the steering device can be omitted.

[0027] Furthermore, the trolley 3 is equipped with a wheel speed sensor 41. The wheel speed sensor 41 outputs a sensor signal corresponding to the rotational speed of the rear wheel 13R. The wheel speed sensor 41 may also output a sensor signal corresponding to the rotational speed of the front wheel 13F.

[0028] The imaging unit 5 is equipped with multiple imaging devices 21a to 21f (hereinafter collectively referred to as imaging devices 21 unless otherwise specified), illumination lamps 25a to 25f (hereinafter collectively referred to as illumination lamps 25 unless otherwise specified), and a reflector 23, and is located at the rear of the trolley 3.

[0029] Multiple imaging devices 21 are equipped with image sensors such as CCD (Charge Coupled Device) or CMOS (Complementary Metal-Oxide Semiconductor) and generate image data Img_α of the road surface. The imaging devices 21 are arranged along the left-right direction of the trolley 3. Each imaging device 21 is installed with a uniform height and installation angle (direction of shooting). In the road surface measurement device 10 of this embodiment, six imaging devices 21a to 21f are arranged at equal intervals along the left-right direction of the trolley 3. Each imaging device 21 is installed with its shooting direction facing the road surface. The imaging devices 21 are installed so that the shooting ranges of adjacent imaging devices 21 overlap.

[0030] However, the installation positions and angles of the multiple imaging devices 21 may be non-uniform, as long as the degree of overlap of the imaging ranges of adjacent imaging devices 21 is maintained. For example, the imaging directions of the left and right imaging devices may be directed towards the center. Also, the number of imaging devices 21 is not limited to six. Furthermore, the imaging devices 21 do not have to be arranged at equal intervals. However, by arranging the imaging devices 21 at equal intervals, the relative positional relationship of the image data generated by adjacent imaging devices 21 becomes the same, making calculations easier.

[0031] The imaging device 21 photographs the road surface at set time intervals and outputs the generated image data Img_α(α=1,2···M) to the processing unit 51. The time interval for photography is set considering the set range of the trolley 3's movement speed, so that the shooting ranges of the time-series image data Img_α(α=1,2···M) from each imaging device 21 overlap with each other. In other words, the time-series image data Img_α(α=1,2···M) acquired by the processing unit 51 overlap vertically and horizontally. This allows the imaging device 21 to photograph the entire road surface being measured without any omissions.

[0032] The illumination lamp 25 is a light source for illuminating the road surface to be measured, which is captured by the imaging device 21. In the road surface measurement device 10 of this embodiment, the light emitted from the illumination lamp 25 is reflected by the reflector 23 to illuminate the road surface to be measured. The number of illumination lamps 25 is not particularly limited, as long as the brightness (illuminance or brightness) of the road surface captured by each imaging device 21 is uniform. Furthermore, the means for illuminating the road surface to be measured is not limited to the configuration example of this embodiment and may have any configuration.

[0033] The surrounding conditions detection unit 7 has at least one sensor capable of detecting the conditions around the road surface measurement device 10. In this embodiment, the surrounding conditions detection unit 7 has distance measuring sensors 31a, 31b (hereinafter collectively referred to as distance measuring sensor 31 unless otherwise specified) and camera sensors 33a, 33b (hereinafter collectively referred to as camera sensor 33 unless otherwise specified). The distance measuring sensor 31 may be, for example, a LiDAR (Light Detection and Ranging), but may also be a radar sensor or an ultrasonic sensor. The camera sensor 33 has an image sensor such as a CCD or CMOS and generates image data.

[0034] In the road surface measurement device 10 shown in Figures 2 and 3, the distance measuring sensors 31a and 31b are installed with the central axis of their measurement ranges facing the left and right front of the road surface measurement device 10, respectively. The distance measuring sensors 31a and 31b are installed to detect objects and other targets mainly to the left and right of the road surface measurement device 10. In addition, the camera sensors 33a and 33b are installed with the center of their shooting ranges facing the front of the road surface measurement device 10, respectively. The camera sensors 33a and 33b are installed to capture a wide area in front of the road surface measurement device 10.

[0035] The perforated Pitot tube 35 is a sensor that detects the wind direction relative to the straight-line direction of the trolley 3. The wind direction represents the angle of the wind direction relative to the front-rear direction (straight-line direction) of the trolley 3. For example, when the trolley 3 is traveling in a straight line in a windless state, the wind detected by the perforated Pitot tube 35 is along the straight-line direction of the trolley 3, so the wind direction is 0 degrees. Similarly, when the trolley 3 is traveling in a straight line in a state where there is no influence of crosswinds, such as when measuring the road surface inside a tunnel, the wind direction is also 0 degrees. When the trolley 3 is turning, the straight-line direction of the trolley 3 is tangential to the turning circle, while the direction of movement of the trolley 3 is in the turning direction, so the wind direction corresponding to the turning angle of the trolley 3 is detected.

[0036] The perforated pitot tube 35 has a configuration that allows for the measurement of wind direction by utilizing the pressure difference between at least the central hole of the perforated pitot tube 35 and the surrounding holes. The perforated pitot tube 35 may be, for example, a known 5-hole perforated pitot tube, but is not limited to a 5-hole perforated pitot tube as long as it has a configuration that allows for the detection of the pressure difference between the central hole of the perforated pitot tube 35 and the holes to its left and right. The perforated pitot tube 35 is installed with its tip, which has multiple holes for taking in air, facing forward in the front-rear direction of the trolley 3.

[0037] The porous Pitot tube 35 comprises, for example, a metal tube having multiple holes, a pressure sensor that detects the pressure in each hole, and a microcomputer that controls the pressure sensors. The microcomputer determines the pressure difference between the central hole and the surrounding holes from the detected pressure, calculates the wind direction based on information showing the relationship between the differential pressure and the wind direction (which is set in advance), and outputs the wind direction information to the control device 50.

[0038] The control device 50 comprises one or more processors having the function of automatically moving the trolley 3 and the function of controlling the imaging device 21, and one or more storage devices connected to the one or more processors in a communicative manner. The control device 50 also comprises a communication interface for communicating with the information processing device 100. The control device 50 is connected to various sensors and electronic control devices provided in the road surface measurement device 10 in a communicative manner.

[0039] <Control device> Next, we will explain the control device 50 provided in the road surface measurement device 10.

[0040] (Control device configuration) Figure 4 is a block diagram showing an example configuration of the road surface measurement system 1. The control device 50 comprises a processing unit 51, a storage unit 53, and a communication unit 57. The processing unit 51 is configured with one or more processors such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit), and various peripheral components. Part or all of the processing unit 51 may be configured with updatable firmware, or it may be a program module executed by commands from the CPU, etc.

[0041] The processing unit 51 functions as a device that realizes the functions described below by having one or more processors execute a computer program. The computer program is a computer program that causes the processor to execute the operations that the processing unit 51 is to perform, as described later. The computer program executed by the processor may be recorded on a recording medium that functions as a memory 53 provided in the control unit 50, or it may be recorded on a recording medium built into the processing unit 51 or on any recording medium that can be attached externally to the control unit 50.

[0042] Recording media for storing computer programs may include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs, DVDs (Digital Versatile Discs), and Blu-ray®; magneto-optical media such as floppy disks; memory elements such as RAM (Random Access Memory) and ROM (Read Only Memory); flash memory such as USB (Universal Serial Bus) memory and SSDs (Solid State Drives); and other media capable of storing programs.

[0043] The processing unit 51 is connected to the drive power source 15, steering device 17, imaging device 21, illumination lamp 25, distance measuring sensor 31, camera sensor 33, porous pitot tube 35, wheel speed sensor 41, input unit 81, and notification unit 83 in a communication manner.

[0044] The input unit 81 accepts input operations from the user. The input unit 81 is configured to include at least one of the following: a keyboard, mouse, touchpad, and microphone. However, the type of input unit 81 is not particularly limited.

[0045] The notification unit 83 is the part that provides predetermined notifications to the user. The notification unit 83 is configured to include, for example, at least one of a display device and a speaker. However, the type of notification unit 83 is not particularly limited.

[0046] The memory unit 53 is composed of one or more memory elements such as RAM or ROM that are connected to the processing unit 51 in a communicative manner. However, the type and number of memory units 53 are not particularly limited. The memory unit 53 stores computer programs executed by the processing unit 51, various parameters used in arithmetic processing, detection data, calculation results, and other information. A portion of the memory unit 53 is used as the work area of ​​the processing unit 51.

[0047] The communication unit 57 is an interface for the processing unit 51 to communicate with the information processing device 100. The communication unit 57 may be an interface for communicating with the information processing device 100, for example, via mobile communication, but the method of communication with the information processing device 100 is not particularly limited.

[0048] Furthermore, the control device 50 includes an acceleration sensor 43, an angular velocity sensor 45, a GNSS sensor 47, and a map data storage unit 55, all of which are communicated with the processing unit 51. Note that some or all of the acceleration sensor 43, angular velocity sensor 45, GNSS sensor 47, and map data storage unit 55 may be provided separately from the control device 50.

[0049] The acceleration sensor 43 outputs sensor signals corresponding to the acceleration in each of the three axes along the longitudinal, lateral, and vertical directions of the road surface measurement device 10. The angular velocity sensor 45 outputs sensor signals corresponding to the angular velocity around each of the three axes along the longitudinal, lateral, and vertical directions of the road surface measurement device 10. Note that the acceleration sensor 43 and the angular velocity sensor 45 may be integrated as an IMU sensor (inertial measurement unit), or they may be individually provided sensors.

[0050] The GNSS sensor 47 receives satellite signals from positioning satellites such as GPS satellites and transmits the position information of the road surface measuring device 10 included in the satellite signals to the processing unit 51. The position information may be latitude and longitude information. The GNSS sensor 47 may also be configured to receive satellite signals from satellite systems other than GPS satellites.

[0051] The map data storage unit 55 is composed of a memory element such as RAM or ROM, or a storage medium such as an HDD, CD, DVD, SSD, USB flash drive, or storage device, which is connected to the processing unit 51 in a communicative manner. The map data stored in the map data storage unit 55 is associated with latitude and longitude information, and the processing unit 51 can identify the position of the road surface measurement device 10 on the map data based on the latitude and longitude information of the road surface measurement device 10 transmitted from the GNSS sensor 47.

[0052] The processing unit 51 performs the process of having the imaging device 21 photograph the road surface and transmitting the generated image data to the information processing device 100. The processing unit 51 includes an acquisition unit 61, a turning angle calculation unit 63, an autonomous driving control unit 65, a self-position estimation unit 67, and an imaging device drive unit 69. Each of these units is a function realized by the execution of a computer program by one or more processors. However, some or all of the acquisition unit 61, turning angle calculation unit 63, autonomous driving control unit 65, self-position estimation unit 67, and imaging device drive unit 69 may be configured using analog circuits.

[0053] The acquisition unit 61 acquires image data generated by the imaging device 21. The acquisition unit 61 acquires image data generated by the imaging device 21 at set time intervals. The acquisition unit 61 also acquires detection data or sensor signals (hereinafter collectively referred to as "detection information") output from the distance measuring sensor 31, camera sensor 33, porous Pitot tube 35, wheel speed sensor 41, acceleration sensor 43, angular velocity sensor 45, and GNSS sensor 47. The acquisition unit 61 acquires detection information output from each sensor at predetermined sampling periods.

[0054] The rotation angle calculation unit 63 calculates the rotation angle θ of the trolley 3 based on the wind direction information detected by the porous Pitot tube 35. The rotation angle θ of the trolley 3 represents the angle formed by the direction of movement of the trolley 3 with respect to the front-rear direction (straight-line direction) of the trolley 3. When the trolley 3 is moving straight, the rotation angle θ of the trolley 3 is 0 degrees. When the trolley 3 is rotating, the angle formed by the direction of movement of the trolley 3 with respect to the tangential direction of the rotation circle corresponds to the rotation angle θ. The rotation angle calculation unit 63 calculates the rotation angle θ of the trolley 3 based on information showing the relationship between the detected wind direction and the rotation angle θ. For example, the detected wind direction may be used as the rotation angle θ of the trolley 3, but other calculation methods may also be set.

[0055] The autonomous driving control unit 65 controls the autonomous driving of the trolley 3. Autonomous driving refers to a state in which the trolley 3 moves along a predetermined target path by controlling the drive of the power source 15 and the steering device 17 based on detected information by the processor, etc.

[0056] For example, the autonomous driving control unit 65 moves the trolley 3 along the measurement path based on the position information of the road surface measurement device 10 detected by the GNSS sensor 47 and the information of the measurement path set on the map data. As long as the GNSS sensor 47 is in an area where it can receive satellite signals, the autonomous driving control unit 65 can move the trolley 3 along the pre-set measurement path using the position information detected by the GNSS sensor 47.

[0057] On the other hand, in areas where satellite signals cannot reach or are difficult to receive, such as inside tunnels, the position information detected by the GNSS sensor 47 cannot be used. Therefore, when measuring the road surface in such areas, the autonomous driving control unit 65 moves the trolley 3 according to the guide information detected by the distance measuring sensor 31. Guide information refers to three-dimensional objects installed along the road, such as side walls, curbs, and guardrails, which can serve as a reference when moving the trolley 3 along the direction in which the road extends. For example, the autonomous driving control unit 65 performs the process of moving the trolley 3 along the road while maintaining the distance between such guide information and the road surface measurement device 10 at a predetermined set distance.

[0058] The road surface measurement device 10 of this embodiment is configured on the premise that the detection accuracy of objects and the measurement accuracy of the distance to objects measured by the distance measuring sensor 31 are higher than the measurement accuracy of objects and the distance to objects measured by the camera sensor 33. However, the priority of the sensors used by the autonomous driving control unit 65 may differ depending on the measurement accuracy of each sensor. In addition, if the autonomous driving control unit 65 is unable to move the trolley 3 along the guide information detected using the distance measuring sensor 31 or the camera sensor 33, it may move the trolley 3 along a predetermined path based on the position of the road surface measurement device 10 (self-position, odometry information) estimated by the self-position estimation unit 67.

[0059] The self-position estimation unit 67 estimates odometry information, including the position of the road surface measurement device 10 on a predetermined three-dimensional coordinate system (hereinafter also referred to as "self-position"). For example, the self-position estimation unit 67 calculates the change in the position of the road surface measurement device 10 (self-position) relative to the position of the road surface measurement device 10 when the measurement process starts, based on time-series data of the moving speed of the trolley 3, acceleration in the three axes, and angular velocity around the three axes detected by the wheel speed sensor 41, acceleration sensor 43, and angular velocity sensor 45.

[0060] The position of the road surface measurement device 10 indicates, for example, the position of the road surface measurement device 10 on a predetermined three-dimensional coordinate system with the starting position of the measurement process as the origin. The position of the road surface measurement device 10 may be the position of a reference position (x0, y0, z0) arbitrarily set within the road surface measurement device 10, for example, the position of the center of gravity of the road surface measurement device 10, or the reference position of any of the imaging devices 21 among the plurality of imaging devices 21a to 21f.

[0061] The imaging device drive unit 69 controls the drive of the imaging device 21. The imaging device drive unit 69 performs imaging by the imaging device 21 when the rotation angle θ of the trolley 3 is less than a predetermined threshold, and prohibits imaging by the imaging device 21 when the rotation angle θ of the trolley 3 is greater than or equal to a predetermined threshold.

[0062] Furthermore, if the rotation angle θ is greater than or equal to a predetermined threshold, and the distance traveled by the trolley 3 from the position where the previous image was taken exceeds a predetermined reference distance range in which the overlap rate of the shooting ranges of the two image data captured in time series is within a predetermined reference range, the imaging device drive unit 69, based on the information of the trajectory of the trolley 3, moves the trolley 3 backward to a predetermined position in which the overlap rate of the shooting ranges is within a predetermined reference range and takes an image, and then resumes the process of taking an image with the imaging device 21 when the rotation angle θ is less than a predetermined threshold.

[0063] (Processing operation of the control device) Up to this point, the basic configuration of the control device 50 has been described. Next, the processing operations of the processing unit 51 of the control device 50 will be described.

[0064] Figure 5 is a flowchart showing an example of the operation of the road surface measurement process by the processing unit 51. First, the autonomous driving control unit 65 acquires information about the measurement route (step S11). The measurement route includes information about at least the measurement start position and the measurement end position. When the trolley 3 is autonomously driven using the position information output from the GNSS sensor 47, the autonomous driving control unit 65 sets the current position of the road surface measurement device 10 as the measurement start position, acquires information about the measurement end position, and sets the measurement route from the measurement start position to the measurement end position along the road by referring to map data.

[0065] Furthermore, when the trolley 3 is autonomously driven using guide information (such as side walls) detected by the distance measuring sensor 31 or the camera sensor 33, the autonomous driving control unit 65 sets the distance from the road surface measuring device 10 to the guide information. This distance serves as the reference for the driving position when the trolley 3 is autonomously driven. The information for setting the measurement path may be specified by the user.

[0066] Next, the autonomous driving control unit 65 performs autonomous driving control to automatically move the trolley 3 (step S13).

[0067] Figure 6 is a flowchart showing an example of the processing operation of autonomous driving control. The autonomous driving control unit 65 acquires information on the current position (x,y) and direction of movement of the road surface measurement device 10 (step S21). If the position information (latitude and longitude information) output from the GNSS sensor 47 is valid, the autonomous driving control unit 65 acquires the position information output from the GNSS sensor 47. The autonomous driving control unit 65 also determines the direction of movement as the vector connecting the position of the road surface measurement device 10 on the map data in the previous calculation cycle (t_n-1) and the position of the road surface measurement device 10 on the map data in the current calculation cycle (t_n).

[0068] Alternatively, when the trolley 3 is autonomously driven using the distance measuring sensor 31 or the camera sensor 33, for example, the autonomous driving control unit 65 acquires information on the current position (x,y) of the road surface measuring device 10 on a predetermined two-dimensional coordinate system, based on the distance information from the road surface measuring device 10 to the guide information and the odometry information estimated by the self-position estimation unit 67, which will be described later. The autonomous driving control unit 65 also acquires information on the direction of movement of the trolley 3 from the odometry information estimated by the self-position estimation unit 67.

[0069] Next, the autonomous driving control unit 65 sets the drive amount for the power source 15 and the steering device 17 (step S23). For example, the autonomous driving control unit 65 sets the drive amount for the power source 15 so that the moving speed of the trolley 3, calculated based on the detection information of the wheel speed sensor 41, becomes the target speed. The autonomous driving control unit 65 also sets the angular velocity of the change in steering angle (steering angular velocity) based on the information of the current direction of movement of the trolley 3 and the information of the measured path, and sets the drive amount for the steering device 17 according to the steering angular velocity.

[0070] Next, the autonomous driving control unit 65 controls the drive of the drive source 15 and the steering device 17 according to the drive amount set in step S33 (step S25). The autonomous driving control unit 65 repeatedly performs the above autonomous driving control until the measurement of the road surface within the measurement range is completed.

[0071] Returning to Figure 5, while the autonomous driving control unit 65 performs autonomous driving control of the trolley 3, the self-position estimation unit 67 performs self-position estimation processing (step S15).

[0072] Figure 7 is a flowchart showing an example of the self-position estimation process operation by the self-position estimation unit 67. The self-position estimation unit 67 records the starting position (step S31). The starting position is the reference position used when calculating the self-position of the road surface measurement device 10. For example, the self-position estimation unit 67 records the position coordinates of the reference position (x0, y0, z0) of the road surface measurement device 10 at the start of the measurement process as the starting position. Note that the reference position to be recorded does not need to be specified by specific latitude and longitude information, and may be recorded as any point in any three-dimensional coordinate system (for example, the origin of the three-dimensional coordinate system).

[0073] However, when the self-position estimation unit 67 estimates odometry information by further considering the position information on the map data output from the GNSS sensor 47, it may record the latitude and longitude information of the reference position (x0, y0) of the road surface measurement device 10 as the x and y coordinates of the starting position.

[0074] Next, the self-position estimation unit 67 acquires detection information output from the wheel speed sensor 41, acceleration sensor 43, and angular velocity sensor 45 (step S33). The detection information from the acceleration sensor 43 includes information indicating the acceleration in the three axes along the longitudinal, lateral, and height directions of the road surface measurement device 10. The detection information from the angular velocity sensor 45 includes information indicating the angular velocity around the three axes along the longitudinal, lateral, and height directions of the road surface measurement device 10.

[0075] Next, the self-position estimation unit 67 calculates odometry information including the self-position of the road surface measuring device 10 based on the acceleration and angular velocity information obtained from the detection information of the wheel speed sensor 41, acceleration sensor 43, and angular velocity sensor 45 acquired in the current calculation cycle, and the position information of the road surface measuring device 10 calculated in the previous calculation cycle (step S35). For example, the self-position estimation unit 67 calculates the position of the road surface measuring device 10 on a three-dimensional coordinate system with the starting position recorded in step S31 as the origin.

[0076] The self-position estimation unit 67 may correct the position and orientation of the road surface measurement device 10 based on measurement data from at least one of the distance measuring sensor 31 and the camera sensor 33. For example, the self-position estimation unit 67 may correct the position of the road surface measurement device 10 based on the distance between the road surface measurement device 10 and a stationary object detected by the distance measuring sensor 31 or the camera sensor 33, and the change in the position (direction) of the stationary object as seen from the road surface measurement device 10 over time.

[0077] Furthermore, the self-position estimation unit 67 may correct the position of the road surface measurement device 10 based on the position information output from the GNSS sensor 47. For example, the self-position estimation unit 67 may correct the position of the road surface measurement device 10 based on the time change of the position information output from the GNSS sensor 47.

[0078] Next, the self-position estimation unit 67 records the data of the position (self-position coordinates) P_n(x_n,y_n) of the road surface measurement device 10 calculated in the current calculation cycle (t_n) in the storage unit 53 (step S37). The self-position estimation unit 67 repeatedly performs the above self-position estimation process until the measurement of the road surface within the measurement range is completed.

[0079] Returning to Figure 5, while the autonomous driving control unit 65 performs autonomous driving control of the trolley 3, the imaging device drive unit 69 performs the process of photographing the road surface with the imaging device 21 (step S17).

[0080] Figure 8 is a flowchart showing an example of the imaging device drive processing operation by the imaging device drive unit 69. The imaging device drive unit 69 performs imaging with the imaging device 21 at a predetermined position (step S41). For example, at the starting position of the autonomous driving control of the trolley 3, the imaging device drive unit 69 controls the drive of the imaging device 21 with the set imaging conditions and photographs the road surface. The time counter t at this time is set to 1. The imaging device drive unit 69 stores the image data Img_α generated by the imaging device 21 in the storage unit 53 along with the information of the imaging device 21 number α (α=1,2···M).

[0081] At this time, the stored image data Img_α is recorded in association with the value of the time counter t. The storage unit 53 stores information on the relative positions of each imaging device 21a to 21f with respect to the reference position (x0, y0, z0) of the road surface measurement device 10. Therefore, based on the position of the reference position (x0, y0, z0) of the road surface measurement device 10 on a predetermined three-dimensional coordinate system, it is possible to identify the position of the imaging device 21 that generated each image data Img_α at each time t (hereinafter also referred to as the "shooting position").

[0082] Next, the imaging device drive unit 69 determines that the distance L traveled by the trolley 3 from the previous shooting position is within a predetermined reference distance range (L min ≦L≦L maxDetermine whether it has entered (step S43). The predetermined reference distance range is the minimum value L of the moving distance L at which the overlapping rate of the shooting ranges of two pieces of image data Img_α(t_n) and Img_α(t_n+1) taken in time series is within the predetermined reference range. min and the maximum value L max are defined.

[0083] Figs. 9 to 11 are diagrams shown to explain the reference distance range of the moving distance L of the carriage 3. For example, as shown in Fig. 9, it is assumed that the overlapping rate (image overlapping rate) of the shooting ranges of two pieces of image data Img_α(t_n) and Img_α(t_n+1) taken in time series is set to 60-80%. In this case, as shown in Fig. 10, as the moving distance L of the carriage 3 after acquiring the image data Img_α(t_n) at time t_n increases, the image overlapping rate decreases.

[0084] When the ratio of the moving distance L to the length Lp of the shooting range of the image data Img_α along the moving direction of the carriage 3 is 0 (L = 0), the image overlapping rate is 100%. When the ratio of the moving distance L to the length Lp of the shooting range of the image data Img_α along the moving direction of the carriage 3 exceeds 1 (L > Lp), the image overlapping rate is 0%. And, for example, when the image overlapping rate is 60-80% as the shooting condition, the predetermined reference distance range is set to 0.2×Lp ≤ L ≤ 0.4×Lp. The minimum value L of the moving distance L min and the maximum value L max may be set to any appropriate values according to the accuracy of the matching process or the like.

[0085] From the above, the imaging device driving unit 69 may determine in step S43 whether the moving distance L of the carriage 3 from the previous shooting position is equal to or greater than the minimum value L of the moving distance. min If it is determined that the moving distance L of the carriage 3 from the previous shooting position has not entered the predetermined reference distance range (L

[0086] When the imaging device driving unit 69 does not determine that the moving distance L of the carriage 3 from the previous shooting position has entered the predetermined reference distance range (L min ≤ L ≤ L max ), (S43 / No), when the moving distance L is within the predetermined reference distance range (L min ≤ L ≤ Lmax The determination is repeated until the distance L is within a predetermined reference distance range (L). Then, the imaging device drive unit 69 determines that the movement distance L is within a predetermined reference distance range (L min ≦L≦L max If it is determined that the vehicle has entered the area (S43 / Yes), it is determined whether the rotation angle θ of the trolley 3, which is determined based on the wind direction information detected by the porous pitot tube 35, is less than a predetermined threshold θ0 (step S45).

[0087] The predetermined threshold θ0 for the turning angle θ is a threshold for determining whether the trolley 3 is moving in a straight line without swinging from side to side, and may be set to any appropriate value depending on the resolution of the image data Img_α obtained by the imaging device 21. The predetermined threshold θ0 may be set to, for example, 5 degrees, but is not limited to this value.

[0088] If the imaging device drive unit 69 determines that the rotation angle θ of the trolley 3 is less than a predetermined threshold θ0 (S45 / Yes), it performs imaging with the imaging device 21 (step S47). At this time, the imaging device drive unit 69 advances the time counter t by 1 (plus 1). The imaging device drive unit 69 records the image data Img_α generated by the imaging device 21, along with the information of the imaging device 21 number α (α=1,2···M), associating it with the value of the time counter t.

[0089] On the other hand, if the imaging device drive unit 69 does not determine that the rotation angle θ of the trolley 3 is less than a predetermined threshold θ0 (S45 / No), then the distance L of the trolley 3 moved from the shooting position at the previous time t is within a predetermined reference distance range (L min ≦L≦L max Step S49 determines whether the distance traveled L from the previous shooting position exceeds the maximum value L of the travel distance. max You may also determine whether or not it exceeds a certain value.

[0090] The imaging device drive unit 69 determines that the distance L traveled by the trolley 3 from the shooting position at the previous time t is within a predetermined reference distance range (L min ≦L≦L maxIf it is not determined that the distance L of the trolley 3 moved from the shooting position at the previous time t exceeds a predetermined reference distance range (L min ≦L≦L max When the rotation angle θ of the trolley 3 becomes less than a predetermined threshold θ0 before exceeding (S45 / Yes), imaging is performed by the imaging device 21 (step S47).

[0091] In the example shown in Figure 11, even if the travel distance L of the trolley 3 falls within a predetermined reference distance range (0.2 ≤ L ≤ 0.4), imaging by the imaging device 21 is not performed until the rotation angle θ of the trolley 3 falls below a predetermined threshold (5 degrees). When the rotation angle θ of the trolley 3 falls below the predetermined threshold (5 degrees) (L / Lp = 0.3), imaging by the imaging device 21 is performed.

[0092] On the other hand, the imaging device drive unit 69 ensures that the rotation angle θ of the trolley 3 does not fall below a predetermined threshold θ0, and that the distance L traveled by the trolley 3 from the shooting position at the previous time t is within a predetermined reference distance range (L min ≦L≦L max If it is determined that the value exceeds (S49 / Yes), proceed to step S51.

[0093] In step S51, the imaging device drive unit 69 moves the trolley 3 backward to a predetermined position where the overlap rate with the shooting range of the previously captured image data Img_α(t_n) is within a predetermined reference range, based on the information of the trajectory of the trolley 3's movement, and then performs the shooting (step S51). For example, the imaging device drive unit 69 determines that the distance L the trolley 3 has moved from the shooting position at the previous time t is within a predetermined reference distance range (L min ≦L≦L max If it is determined that the value exceeds (S49 / Yes), a command is generated to reverse the trolley 3. When a command to reverse the trolley 3 is generated, the autonomous driving control unit 65 controls the torque of the drive source 15 and the steering angle of the wheels 13 by going back to the previous calculation cycle, and reverses the trolley 3 to follow the estimated result of the trolley 3's own position.

[0094] For example, the steering angle of the wheel 13 is set to a stored value by going back to the previous calculation cycle. Also, the amount of drive of the drive force source 15 is adjusted to a negative value of the stored value by going back to the previous calculation cycle. As a result, the autonomous driving control unit 65 can move the trolley 3 backward along the path it has traveled.

[0095] The target position for reversing the trolley 3 is determined when the distance L traveled by the trolley 3 from the shooting position at the previous time t falls within a predetermined reference distance range (L min ≦L≦L max The position is not particularly limited as long as it falls within the specified range. However, the minimum distance traveled is L. min By moving backward to the corresponding position, the deviation from the straight-line direction at the previous shooting position can be reduced. On the other hand, the maximum value of the movement distance L max By moving the trolley 3 backward to the corresponding position, the time lost in restarting the trolley 3's movement can be reduced.

[0096] When the trolley 3 is moved backward to perform the shooting, the trolley 3 is in a stopped state. As a result, blurring of the obtained image data Img_α is reduced. At this time, the imaging device drive unit 69 advances the time counter t by 1 (plus 1), and records the image data Img_α generated by the imaging device 21, along with the information of the imaging device 21 number α (α=1,2···M), associating it with the value of the time counter t.

[0097] The autonomous driving control unit 65 reverses the trolley 3, and then resumes autonomous driving of the trolley 3 after the road surface has been photographed by the imaging device drive unit 69. After the imaging device drive unit 69 performs the photography process in step S47 or step S51, it returns to step S43 and repeatedly performs the processes of each of the steps described above.

[0098] Returning to Figure 5, while the autonomous driving control, self-position estimation, and imaging processes of the trolley 3 described above are being executed, the autonomous driving control unit 65 determines whether or not the measurement of the measurement range has been completed (step S19). For example, the autonomous driving control unit 65 determines that the measurement has been completed when the road surface measurement device 10 reaches the measurement end position. Alternatively, the autonomous driving control unit 65 may determine that the measurement has been completed when an emergency stop operation is performed by the user or the like.

[0099] If the autonomous driving control unit 65 does not determine that the measurement is complete (S19 / No), it returns to step S13 and continues autonomous driving control of the road surface measurement device 10. On the other hand, if the autonomous driving control unit 65 determines that the measurement is complete (S19 / Yes), it terminates the autonomous driving control process. At this time, the self-position estimation unit 67 terminates the self-position estimation process of the trolley 3, and the imaging device drive unit 69 terminates the imaging device drive process.

[0100] <Information Processing Device> Next, the information processing device 100 will be described.

[0101] (Configuration of information processing device) As shown in Figure 4, the information processing device 100 includes a communication unit 101, a data processing unit 103, and a storage unit 105. The communication unit 101 is an interface for the data processing unit 103 to communicate with the control device 50. The communication unit 101 may be an interface for communicating with the control device 50, for example, via mobile communication, but the method of communication with the control device 50 is not particularly limited.

[0102] The data processing unit 103 is comprised of one or more processors, such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit), and various peripheral components. Part or all of the processing unit 51 may be composed of updatable components such as firmware, or it may be a program module executed by commands from the CPU, etc.

[0103] The data processing unit 103 functions as a device that realizes the functions described below by having one or more processors execute a computer program. The computer program is a computer program that causes the processor to execute the operations that the data processing unit 103 should perform, as described later. The computer program executed by the processor may be recorded on a recording medium that functions as a memory unit 105 provided in the information processing device 100, or it may be recorded on a recording medium built into the data processing unit 103 or on any recording medium that can be attached externally to the information processing device 100.

[0104] Recording media for storing computer programs may include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs, DVDs, and Blu-ray®; magneto-optical media such as floppy disks; memory elements such as RAM and ROM; flash memory such as USB memory and SSDs; and other media capable of storing programs.

[0105] The storage unit 105 is composed of one or more memory elements such as RAM or ROM, or a storage medium such as an HDD or SSD, which are connected to the data processing unit 103 in a communicative manner. However, the type and number of storage units 105 are not particularly limited. The storage unit 105 stores computer programs executed by the data processing unit 103, various parameters used in arithmetic processing, detection data, calculation results, and other information. A portion of the storage unit 105 is used as a work area.

[0106] The data processing unit 103 acquires image data Img_α from the road surface measurement device 10, extracts feature points from the image data Img_α (α=1,2···M), matches the feature points using SfM processing, and aligns the image data Img_α (α=1,2···M). The data processing unit 103 also generates a three-dimensional road surface model that reflects data indicating the unevenness of the road surface that appeared as feature points in the aligned image data Img_α (α=1,2···M).

[0107] Figure 12 is a flowchart showing an example of the model generation process operation by the data processing unit 103. The flowchart below shows an example in which the control device 50 sequentially transmits image data Img_α captured by the imaging device 21 to the information processing device 100.

[0108] The data processing unit 103 acquires image data Img_α (α=1,2···M) transmitted from the control device 50 (step S61). In this embodiment, the road surface measurement device 10 is equipped with six imaging devices 21a to 21f, and the data processing unit 103 acquires image data Img_α (α=1,2···6) generated by each imaging device 21a to 21f at the current shooting time (t_n). The data processing unit 103 stores the acquired image data Img_α (α=1,2···6) in the storage unit 105.

[0109] Next, the data processing unit 103 extracts feature points from the acquired image data Img_α (α=1,2···M) (step S63). Feature points may be points where the change in brightness (feature) between adjacent pixels of the image data Img_α exceeds a predetermined threshold, but other feature quantities may also be used. The method for extracting feature points from image data may be a conventionally known method, so a detailed explanation is omitted.

[0110] Next, the data processing unit 103 performs a process to match the extracted feature points among the image data Img_α (α=1,2···M) (step S65). This matching process includes not only matching feature points among the image data Img_α (α=1,2···M) acquired at the current shooting time (t_n), but also matching feature points among the image data Img_α (α=1,2···M) taken at previous times and stored in the storage unit 105. The process of matching feature points among image data can be performed using conventionally known methods, so a detailed explanation is omitted.

[0111] Next, the data processing unit 103 uses the image data Img_α (α=1,2···M) aligned by feature point matching processing to construct three-dimensional point cloud data reconstructed by the principle of triangulation and generate a road surface model (step S67). In this embodiment, the data processing unit 103 constructs three-dimensional point cloud data and generates a road surface model by MVS (Multi-View Stereo) processing. However, the method for generating a road surface model composed of three-dimensional point cloud data is not particularly limited.

[0112] Next, the data processing unit 103 determines whether or not to terminate the model generation process (step S69). For example, the data processing unit 103 may determine to terminate the model generation process when a predetermined time has elapsed since the control device 50 stopped transmitting image data Img_α. Alternatively, the data processing unit 103 may determine to terminate the model generation process when the control device 50 transmits a signal indicating the end of measurement.

[0113] If the data processing unit 103 does not determine that it is time to terminate the model generation process (S69 / No), it returns to step S61 and continues the model generation process. On the other hand, if the data processing unit 103 determines that it is time to terminate the model generation process (S69 / Yes), it terminates the model generation process.

[0114] As described above, the road surface measurement device 10 according to this embodiment is equipped with a porous pitot tube 35 for detecting the wind direction relative to the straight-ahead direction of the trolley 3, and the control device 50 controls the imaging device 21 to take pictures using the wind direction information detected by the porous pitot tube 35. In this embodiment, the control device 50 detects the rotation angle θ of the trolley 3 based on the wind direction information detected by the porous pitot tube 35, takes pictures using the imaging device 21 when the rotation angle θ is less than a predetermined threshold θ0, and prohibits taking pictures using the imaging device 21 when the rotation angle θ is greater than or equal to a predetermined threshold θ0.

[0115] This prevents the road surface from being photographed while the front of the trolley 3 swings from side to side as it moves forward, due to the rotational velocity generated in the trolley 3 by increasing the movement speed of the road surface measurement device 10. Furthermore, since the road surface measurement device 10 is not configured to correct the direction of travel of the trolley 3 based on the detection results of the acceleration sensor installed on the trolley 3, it is possible to increase the movement speed and collect only image data with less blur, thereby shortening the time required to collect image data of the road surface within the measurement range. In addition, since the wind direction is detected using a porous pitot tube 35, the rotational angle θ of the trolley 3 can be detected at short intervals, and even if the movement speed of the trolley 3 is increased, image data without blur can be obtained.

[0116] Furthermore, in the road surface measurement device 10 according to this embodiment, the control device 50 has a configuration in which, when the turning angle θ is greater than or equal to a predetermined threshold θ0, and the distance L traveled by the trolley 3 from the position where the previous image was taken exceeds a reference distance range in which the overlap rate of the shooting ranges of two image data captured in time series is within a predetermined reference range, the control device 50 moves the trolley 3 backward to a predetermined position in which the overlap rate of the shooting ranges is within a predetermined reference range, based on the information of the trajectory of the trolley 3, takes an image, and then resumes the process of taking an image with the imaging device 21 when the turning angle θ is less than a predetermined threshold θ0.

[0117] As a result, when the turning angle θ of the trolley 3 remains above a predetermined threshold θ0 and the overlap rate of the two image data captured in time series falls below a desired range, the road surface measurement device 10 automatically reverses to an appropriate position to take images and can continue autonomous driving. Therefore, it is possible to prevent a shortage of image data within the shooting range.

[0118] <<2. Second Embodiment>> Next, a road surface measuring device according to a second embodiment of this disclosure will be described.

[0119] The road surface measurement device according to the second embodiment has a configuration that corrects the path of the trolley 3 using information on the turning angle θ of the trolley 3 detected by the porous pitot tube 35. This embodiment is configured to suppress deviations in the path of the trolley 3 by utilizing the fact that the update cycle of the measured value of the porous pitot tube 35 is shorter than the update cycle of the measured value of the distance measuring sensor 31, which can measure the distance from surrounding guide information as information on the running position of the road surface measurement device 10.

[0120] For example, in a LiDAR, which is one form of the distance measuring sensor 31, the amount of energy per point of the light emitted by the LiDAR decreases or the number of emitted points decreases as the sampling frequency increases. For this reason, in order to guarantee the measurement accuracy of the area around the road surface measuring device 10 by the distance measuring sensor 31, the upper limit of the sampling frequency of the LiDAR is limited to, for example, about 10 Hz. With a high-performance LiDAR, it is possible to secure the amount of light emitted even if the sampling frequency is high, but this is undesirable because it increases costs.

[0121] In contrast, the sampling frequency of the porous Pitot tube 35 can be set to approximately 100 Hz, allowing for the acquisition of 10 times more detection data per unit time compared to LiDAR. Therefore, in this embodiment, by correcting the path of the trolley 3 using the measured value of the porous Pitot tube 35, it becomes possible to correct the path of the trolley 3 at a shorter interval than the update cycle of the measured value of the distance measuring sensor 31.

[0122] The autonomous driving control process performed by the control device 50 of the road surface measurement device 10 according to this embodiment will be described in detail below.

[0123] Figure 13 is a flowchart showing an example of the autonomous driving control processing operation by the autonomous driving control unit 65. In the following explanation, it will be assumed that the movement speed v of the trolley 3 is constant. The movement speed v of the trolley 3 does not have to be constant, but there is little need to change the movement speed v, and autonomous driving control is made easier by keeping the movement speed v constant.

[0124] First, the autonomous driving control unit 65 receives a command to execute autonomous driving control processing using the porous Pitot tube 35 and starts executing autonomous driving control processing using the porous Pitot tube 35 (step S71). For example, autonomous driving control processing using the porous Pitot tube 35 may be executed from the time measurement starts, or it may be started at any point during measurement.

[0125] Next, the autonomous driving control unit 65 obtains the turning angle θ of the trolley 3, which is determined based on the wind direction information detected by the porous pitot tube 35 (step S73). Next, the autonomous driving control unit 65 integrates the turning angles θ and sets the drive amount of the steering device 17 so that the integrated value Σθ converges to zero (step S75). For example, the autonomous driving control unit 65 takes a turning angle θ that tilts to the left with respect to the direction of travel as a positive value and integrates the turning angles θ measured at a predetermined sampling period. The resulting integrated value Σθ indicates the angle at which the front-rear direction of the trolley 3 is tilted with respect to the reference line (target travel path) set as the planned travel path of the trolley 3 at each measurement point. The autonomous driving control unit 65 feedback-controls the steering angular velocity of the wheels 13 of the trolley 3 so that the integrated value Σθ converges to zero, and moves the trolley 3 along the reference line.

[0126] Figures 14 and 15 are diagrams illustrating the autonomous driving control by the autonomous driving control unit 65. Figure 14 shows the driving trajectory and measurement points of the turning angle θ of the road surface measurement device 10 (carriage 3). Figure 15 is a diagram illustrating some of the measurement points p of the turning angle θ of the road surface measurement device 10 (carriage 3).

[0127] As shown in Figure 15, assume that at times t_0, t_1, and t_2, the turning angles θ of the trolley 3 measured at measurement points p(t_0), p(t_1), and p(t_2) are 0, θ1, and θ2, respectively. In this case, the integrated value Σθ0 of the turning angle θ at measurement point p(t_0) is 0, the integrated value Σθ1 of the turning angle θ at measurement point p(t_1) is 0+θ1, and the integrated value Σθ2 of the turning angle θ at measurement point p(t_2) is 0+θ1+θ2. The autonomous driving control unit 65 feedback-controls the steering angular velocity of the steering device 17 so that the integrated value Σθ at each time t_0, t_1, and t_2 converges to zero. The convergence of the integrated value Σθ to zero means that the trajectory of the trolley 3 lies on the reference line (target driving path) C. The feedback control may be, for example, PID control, but is not limited to this.

[0128] Returning to Figure 13, the autonomous driving control unit 65 controls the drive of the drive source 15 and the steering device 17 according to the set drive amount (step S77).

[0129] Next, the autonomous driving control unit 65 calculates the deviation De of the position of the trolley 3 from the reference line C based on the integrated value Σθ of the turning angle θ and the moving speed v of the trolley 3 (step S79).

[0130] As shown in Figure 15, the deviation amount De of the position of the trolley 3 from the reference line C at each measurement point p(t_0), p(t_1), and p(t_2) can be obtained by integrating the values ​​of the moving speed v × sin(turning angle θ) at each measurement point p(t_0), p(t_1), and p(t_2). If the deviation amount De0 at measurement point p(t_0) is set to 0, then the deviation amount De1 at measurement point p(t_1) is v × sinθ1 + 0, and the deviation amount De2 at measurement point p(t_2) is v × sinθ2 + De1. If the feedback calculation of the drive amount of the steering device 17 calculated in step S75 is effective, the deviation amount De approximates to zero.

[0131] Returning to Figure 13, the autonomous driving control unit 65 then determines whether the measurement value of the distance sensor 31 has been updated (step S81). If the autonomous driving control unit 65 does not determine that the measurement value of the distance sensor 31 has been updated (S81 / No), it proceeds to step S85. On the other hand, if the autonomous driving control unit 65 determines that the measurement value of the distance sensor 31 has been updated (S81 / Yes), it calculates the actual measurement value of the deviation width De of the position of the trolley 3 from the reference line C based on the measurement value of the distance sensor 31 and overwrites the deviation width De calculated in step S79 with the actual measurement value (step S83).

[0132] As described above, the update cycle of the measurement values ​​of the distance measuring sensor 31 is longer than the update cycle of the measurement values ​​of the porous pitot tube 35, while the accuracy of the measurement values ​​of the distance measuring sensor 31 is assumed to be high. In other words, the autonomous driving control unit 65 monitors the deviation width De of the position of the trolley 3 from the reference line C based on the measurement value of the porous pitot tube 35 until the measurement value of the distance measuring sensor 31 is updated, and when the measurement value of the distance measuring sensor 31 is updated, it overwrites the deviation width De with the actual measurement value obtained from the measurement value of the distance measuring sensor 31 to ensure the accuracy of the deviation width De based on the measurement value of the porous pitot tube 35.

[0133] As shown in Figure 14, if L_0 is the distance from the road edge such as a side wall to the reference line C, L_act is the distance from the road surface measuring device 10 measured by the distance measuring sensor 31 to the road edge such as a side wall, and L_ugv is the distance from the center line of the trolley 3 to the position of the distance measuring sensor 31, then the deviation De of the position of the trolley 3 from the reference line C can be expressed by the following formula. De = L_0 - (L_act + L_ugv) The autonomous driving control unit 65 overwrites the displacement width De, which was calculated based on the measurement value of the porous pitot tube 35, with the measured value of the displacement width De calculated based on the above formula.

[0134] Next, the autonomous driving control unit 65 determines whether the deviation width De of the position of the trolley 3 from the reference line C is less than or equal to a predetermined threshold De_thr (step S85). The predetermined threshold De_thr defines the allowable range of the deviation width De of the position of the trolley 3 from the reference line C, and may be set to any appropriate value depending on the allowable range of the feature point matching process of multiple image data or the accuracy of the road surface model.

[0135] If the autonomous driving control unit 65 determines that the deviation amount De of the position of the trolley 3 from the reference line C is less than or equal to a predetermined threshold De_thr (S85 / Yes), it returns to step S73 and repeats the processing of each step described above. On the other hand, if the autonomous driving control unit 65 does not determine that the deviation amount De of the position of the trolley 3 from the reference line C is less than or equal to a predetermined threshold De_thr (S85 / No), it executes a process to forcibly return the trolley 3 to the reference line C based on the measurement value of the distance measuring sensor 31 (step S87).

[0136] For example, the autonomous driving control unit 65 sets the drive amount of the steering device 17 so that the value measured by the distance measuring sensor 31 is the value expected when the trolley 3 is traveling on the reference line C. At this time, the imaging device drive unit 69 may interrupt the imaging process and return the trolley 3 to the position on the reference line C corresponding to the position of the trolley 3 at the time the imaging was taken, when the deviation amount De of the position of the trolley 3 from the reference line C is less than or equal to a predetermined threshold De_thr.

[0137] Next, the autonomous driving control unit 65 resumes autonomous driving control using the porous Pitot tube 35 (step S89). At this time, the autonomous driving control unit 65 resets the recorded values ​​of the turning angle θ, the integrated value of the turning angle Σθ, and the displacement width De, then resumes autonomous driving control using the porous Pitot tube 35, and returns to step S73 to repeat the processing of each step described above. The autonomous driving control unit 65 repeatedly executes the above autonomous driving control until the measurement of the road surface within the measurement range is completed.

[0138] In the road surface measurement device 10 and road surface measurement system according to this embodiment, processing operations other than autonomous driving control processing can be the same as those of the road surface measurement device 10 and road surface measurement system according to the first embodiment, so a detailed explanation will be omitted.

[0139] As described above, in the road surface measurement device 10 according to this embodiment, the control device 50 has a configuration that detects the turning angle θ of the trolley 3 based on the wind direction information detected by the porous pitot tube 35 and provides feedback control of the trolley 3's movement so that the integrated value Σθ of the turning angle θ converges to zero. This makes it possible to correct the path of the trolley 3 at a shorter cycle than when correcting the path of the trolley 3 using the measured value of the distance sensor 31. Therefore, the left-right shift of the acquired image data is reduced, and the accuracy of the feature point matching process of multiple image data, and consequently the accuracy of the generated road surface model, can be improved.

[0140] Furthermore, in the road surface measurement device 10 according to this embodiment, the control device 50 detects the rotation angle θ of the trolley based on wind direction information detected by the porous pitot tube 35, calculates the deviation width De of the position of the trolley 3 from the target travel path based on the rotation angle θ and the movement speed v of the trolley 3, and if the deviation width De exceeds a predetermined threshold De_thr, the control device 50 moves the trolley 3 to a position where the deviation width De is less than or equal to the predetermined threshold De_thr without using the rotation angle θ information. As a result, if the deviation width De exceeds the allowable range, the trolley 3 is forcibly returned to the reference line C, thereby suppressing a large lateral deviation of the acquired image data.

[0141] Furthermore, the road surface measurement device 10 according to this embodiment includes a distance measuring sensor 31 capable of measuring the relative position of the trolley 3 from objects around it, and the control device 50 obtains an actual value of the displacement width De of the trolley 3's position from the reference line C based on the measurement value of the distance measuring sensor 31, and overwrites the displacement width De with the actual value. As a result, when a measurement value with relatively high measurement accuracy is obtained from the distance measuring sensor 31, the displacement width De is updated with the actual value obtained from that measurement value, thereby ensuring the accuracy of the calculation of the displacement width De using the measurement value of the porous pitot tube 35.

[0142] While preferred embodiments of the present disclosure have been described in detail above with reference to the attached drawings, the present disclosure is not limited to such examples. It is clear to any person with ordinary skill in the art to which the present disclosure pertains that various modifications or alterations may be conceived within the scope of the technical idea set forth in the claims, and these will naturally also be understood to fall within the technical scope of the present disclosure.

[0143] For example, in each of the above embodiments, an example was described in which the target travel path (reference line) of the trolley 3 is a straight line. However, in this disclosure, the target travel path (reference line) of the trolley 3 may be a curve. In this case, the difference between the expected turning angle θ when the trolley 3 is traveled along the target travel path can be replaced with the turning angle θ in each of the above embodiments, and the processing described in each embodiment can be executed. For example, in the second embodiment, instead of integrating the turning angle θ and setting the drive amount of the steering device 17 so that the integrated value Σθ converges to zero, the autonomous driving control unit 65 feedback-controls the steering angular velocity of the wheels 13 of the trolley 3 so that the integrated value Σθ converges to an angle corresponding to the curvature of the reference line, and moves the trolley 3 along the reference line.

[0144] Furthermore, while the measurement systems of each of the above embodiments were configured with a road surface measurement device that primarily acquires image data and an information processing device that primarily performs data processing, connected in a communicative manner, the technology of this disclosure is not limited to the above examples. Some of the functions of the data processing unit of the information processing device may be provided in the road surface measurement device. Alternatively, the information processing device may be mounted on the road surface measurement device, or all of the functions of the data processing unit of the information processing device may be provided in the control device of the road surface measurement device, and the measurement system may consist only of the road surface measurement device.

[0145] Furthermore, the technology of this disclosure can also be realized as a control method executed by the control device described above, an information processing method executed by the information processing device described above, a computer program that causes a computer to function as at least one of the control device and the information processing device described above, and a non-temporary tangible recording medium on which the computer program is recorded. [Explanation of Symbols]

[0146] 1: Road surface measurement system 3: Dolly 5: Imaging Department 7: Surroundings detection unit 10: Road surface measurement device 21: Imaging device 31: Distance measuring sensor 35: Porous Pitot tube 50: Control device 100: Information Processing Device

Claims

1. A road surface measurement device comprising a trolley, an imaging device, and a control device, wherein the control device autonomously drives the trolley and acquires a plurality of image data of the road surface captured by the imaging device, The trolley is equipped with a porous Pitot tube for detecting the wind direction relative to the straight-ahead direction of travel, The control device controls the road surface measuring device using wind direction information detected by the porous Pitot tube. Road surface measurement device.

2. The control device is Based on the wind direction information detected by the porous Pitot tube, the rotation angle of the trolley is detected. When the rotation angle is less than a predetermined threshold, the imaging device performs imaging. When the rotation angle exceeds the predetermined threshold, the imaging device is prohibited from taking photographs. The road surface measuring device according to claim 1.

3. The control device is When the rotation angle is greater than or equal to the predetermined threshold, and the distance traveled by the trolley from the position where the previous image was taken exceeds the reference distance range in which the overlap rate of the shooting ranges of the two image data captured in time series falls within a predetermined reference range, Based on the information of the trajectory of the trolley's movement, the trolley is moved backward to a predetermined position where the overlap rate of the shooting range falls within the predetermined reference range, and after taking a photograph, the process of taking a photograph with the imaging device is resumed when the rotation angle is less than the predetermined threshold. The road surface measuring device according to claim 2.

4. The control device is Based on the wind direction information detected by the porous Pitot tube, the rotation angle of the trolley is detected. The trolley's movement is controlled by feedback so that the cumulative value of the turning angle converges to zero. The road surface measuring device according to claim 1.

5. The control device is Based on the wind direction information detected by the porous Pitot tube, the rotation angle of the trolley is detected. Based on the turning angle and the trolley's movement speed, the deviation of the trolley's position from the target travel path is calculated, and if the deviation exceeds a predetermined threshold, the trolley is moved to a position where the deviation is less than or equal to the predetermined threshold, without using the turning angle information. The road surface measuring device according to claim 1.

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