JP7195185B2 - Road surface condition measuring device, road surface condition measuring system, road surface condition measuring method, and road surface condition measuring program - Google Patents

Description

The present invention relates to a road surface condition measuring device, a road surface condition measuring system, a road surface condition measuring method, and a road surface condition measuring program that manage position information in association with road surface condition measurement data.

A system for diagnosing the soundness of a road surface is called a road surface condition measurement system. The road surface condition measurement system uses a road surface image showing the road surface to measure cracks, ruts, and evenness of the road surface. Normally, a road surface condition measurement system stores road surface condition measurement data in association with a distance traveled from a point where measurement was started. Therefore, when linking the road surface property measurement data with the measurement location, it is necessary to separately manage the measurement start point and the measurement route.

Patent Literature 1 discloses a measurement vehicle equipped with a position information measurement unit that acquires position information and a road surface condition measurement unit that measures road surface conditions.

JP 2018-147353 A

In Patent Literature 1, the road surface condition measurement data and position information acquired by the measurement vehicle cannot be effectively used for management and analysis of the road surface condition measurement data.

An object of the present invention is to facilitate management and analysis of road surface condition measurement data.

The road surface condition measuring device of the present invention includes:
an image forming unit that forms an image of the road surface as a road surface image using a line image captured by a line camera that is mounted on a measurement vehicle traveling on the road surface and captures the image of the road surface;
an area defining unit that divides the road surface image into a plurality of unit images;
Based on the road surface image, a road surface condition in each unit image of the plurality of unit images is detected, and the unit image, road surface condition data representing the road surface condition of the unit image, the time when the unit image was captured, and the unit. a road surface condition detection unit that generates unit road surface condition information in which position and orientation information including the position of the road surface captured in the image and the orientation of the measurement vehicle that captured the unit image are associated with each other.

According to the road surface condition measuring apparatus of the present invention, road surface condition measurement data can be managed in association with highly accurate position and orientation information, so management and analysis of road surface condition measurement data can be facilitated.

1 is a configuration diagram of a road surface condition measuring system according to Embodiment 1; FIG. The block diagram of a road surface property measurement unit. The block diagram of a road surface property measurement unit. 1 is a functional configuration diagram of a road surface condition measuring device according to Embodiment 1; FIG. 4 is a flowchart of road surface condition measurement processing according to the first embodiment; FIG. FIG. 4 is a diagram obtained by dividing a road surface image into a plurality of unit images according to the first embodiment; 4 is a schematic diagram showing an example of unit road surface condition information according to Embodiment 1. FIG. An example of a function for allowing a user to input a road surface type in Embodiment 1. FIG. An example of a function for allowing a user to input a road surface type in Embodiment 1. FIG. 4 is an example of a variable function of determination parameters according to the road surface type according to the first embodiment; 4 shows an example of a road surface condition screen displayed by a map superimposing unit according to Embodiment 1. FIG. FIG. 10 is another example of a road surface condition screen displayed by the map superimposing unit according to Embodiment 1; FIG. An example of a road surface condition trace according to Embodiment 1. FIG.

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings. In each figure, the same reference numerals are given to the same or corresponding parts. In the description of the embodiments, the description of the same or corresponding parts will be omitted or simplified as appropriate.

Embodiment 1.
*** Configuration description ***
FIG. 1 is a diagram showing the configuration of a road surface condition measuring system 500 according to this embodiment.
A road surface condition measuring system 500 includes a measurement vehicle 200 and a road surface condition measuring device 100 . The road surface condition measurement system 500 is a device that measures items such as cracks, rutting, and evenness of the road surface, and diagnoses the soundness of the road surface. The road surface condition measurement system 500 is composed of a measurement vehicle 200 that measures road surface conditions, and a road surface condition measurement device 100 that edits road surface condition measurement data 301 acquired by the measurement vehicle 200 and outputs it as a form.
Specifically, for cracks, it is necessary to count the number of cracks on the road surface within a 50 cm square, so image acquisition is performed using a line camera. Rutting to check the unevenness of the cross section of the road surface and flatness to check the degree of flatness in the direction of travel of the road surface generally use a laser scanner that measures the distance to the object.

The measurement vehicle 200 includes a position/orientation measurement unit 210 and a road surface condition measurement unit 220 . The measurement vehicle 200 acquires measurement vehicle acquisition data 300 . A position and orientation measurement unit 210 mounted on the measurement vehicle 200 is called an MMS (mobile mapping system). The position and orientation measurement unit 210 is also called an MMS measurement unit.
A position and orientation measurement unit 210 is a group of devices for acquiring position and orientation measurement data 302 . The position and orientation measurement data 302 is data necessary for creating a road map, and is also called MMS measurement data.
The road surface condition measurement unit 220 is a device group for acquiring the road surface condition measurement data 301 . The road surface condition measurement data 301 is data necessary for inspecting the road surface condition.
The position/orientation measurement data 302 and the road surface property measurement data 301 contain measurement times. The measurement time is the time when the measurement for obtaining the data was performed.

The road surface condition measuring apparatus 100 connects a plurality of line images included in the road surface condition measurement data 301 to generate a road surface image. A line image is an image obtained by photographing a road surface with a narrow width. The road surface condition measuring device 100 may be mounted on the measurement vehicle 200 or may be mounted on a computer other than the measurement vehicle 200 .

The road surface condition measuring apparatus 100 also performs post-processing on the position and orientation measurement data 302 to generate post-process data 303 . Post-processing data 303 is also referred to as MMS post-processing data. The position and orientation measurement data 302 and the post-processing data 303 are also collectively referred to as mapping measurement data. Note that the process of generating the post-processed data 303 may be performed by the position and orientation measurement unit 210 of the measurement vehicle 200 . Further, the process of generating post-processed data 303 may be performed by a computer separate from measurement vehicle 200 and road surface condition measuring apparatus 100 .
The road surface condition measurement device 100 associates the road surface condition measurement data 301, the position/orientation measurement data 302, and the post-processing data 303 with each other using the respective measurement times.

Here, the configuration of the position and orientation measurement unit 210 will be described.
The position and orientation measurement unit 210 includes devices such as a receiver, a laser scanner, a line camera, and an IMU (inertial measurement unit). The receiver receives positioning signals transmitted from positioning satellites. The data obtained by the receiver is called positioning observation data. The laser scanner irradiates a laser beam around the road surface to measure the relative distance and relative azimuth with respect to features around the road surface. The data obtained by the laser scanner is called feature distance and direction data. The line camera takes pictures of the road surface. An image obtained by the line camera is called a photographed image. IMU is an abbreviation for inertial measurement unit. The IMU measures the angular velocity and acceleration of measurement vehicle 200 . The data obtained by the IMU is called inertial measurement data.
The position and orientation measurement data 302 includes positioning observation data, feature distance and direction data, captured images, and inertial measurement data.

The configuration of the road surface condition measurement unit 220 will be described based on FIGS. 2 and 3. FIG.
The road surface condition measurement unit 220 includes a high precision laser 331 , a line camera 332 , a laser illumination 333 and a displacement meter 334 .
The high-precision laser 331 irradiates laser light toward each point on the road surface to measure the relative distance and relative azimuth with respect to each point on the road surface. The data obtained by the high-precision laser 331 is called road surface distance and direction data. From the road surface distance and direction data, the rutting state of the road surface properties can be obtained.
The line camera 332 is mounted on the measurement vehicle 200 traveling on the road surface and captures an image of the road surface. The line camera 332 photographs the road surface line by line with a narrow width. An image obtained by the line camera 332 is called a line image. A road surface image is an image obtained by connecting a plurality of line images. A road surface image obtained from the line camera 332 and the laser illumination 333 can be used to acquire the state of cracks in the road surface properties.
A displacement meter 334 measures the distance to the road surface. Data obtained by the displacement meter 334 is called road surface distance data. From the road surface distance data, the flatness of the road surface properties can be obtained.
The road surface condition measurement data 301 includes road distance and direction data, a road surface image, and road surface distance data.

The measurement vehicle 200 is equipped with a position and orientation measurement unit 210 such as MMS, and measures accurate position and orientation information at each GPS time. Therefore, in the road surface condition measurement system 500, the position and orientation information can be specified from the measurement time of the road surface condition measurement data. That is, in the road surface condition measurement system 500, highly accurate position and orientation information obtained by MMS can be combined with road surface condition measurement data such as the road vertical and cross slope, the amount of rutting, and the road surface image. Therefore, in the road surface condition measurement system 500, it is possible to superimpose the road surface condition measurement data and the map information by fusing the road surface condition measurement data and the MMS measurement data.

A functional configuration of the road surface condition measuring device 100 according to the present embodiment will be described with reference to FIG.

The road surface condition measuring device 100 is a computer. The road surface condition measuring device 100 includes a processor 910 and other hardware such as a memory 921 , an auxiliary storage device 922 , an input interface 930 , an output interface 940 and a communication device 950 . The processor 910 is connected to other hardware via signal lines and controls these other hardware.

The road surface condition measuring device 100 includes an image collecting unit 110, an image forming unit 120, an area defining unit 130, a road surface condition detecting unit 140, a map superimposing unit 150, and a storage unit 160 as functional elements. The storage unit 160 stores road surface condition measurement data 301 , position/orientation measurement data 302 , post-processing data 303 , map information 161 , and unit road surface condition information 162 .

The functions of the image acquisition unit 110, the image formation unit 120, the area definition unit 130, the road surface condition detection unit 140, and the map superimposition unit 150 are implemented by software. The storage unit 160 is provided in the memory 921 .

Processor 910 is a device that executes a road surface property measurement program. The road surface condition measurement program is a program that implements the functions of the image collection unit 110 , the image formation unit 120 , the area definition unit 130 , the road surface condition detection unit 140 and the map superimposition unit 150 .
The processor 910 is an IC (Integrated Circuit) that performs arithmetic processing. A specific example of the processor 910 is a CPU (Central Processing
Unit), DSP (Digital Signal Processor), and GPU (Graphics Processing Unit).

The memory 921 is a storage device that temporarily stores data. A specific example of the memory 921 is SRAM (Static Random Access Memory) or DRAM (Dynamic Random Access Memory).
Auxiliary storage device 922 is a storage device that stores data. A specific example of the auxiliary storage device 922 is an HDD. Also, the auxiliary storage device 922 may be a portable recording medium such as an SD (registered trademark) memory card, CF, NAND flash, flexible disk, optical disk, compact disk, Blu-ray (registered trademark) disk, or DVD. Note that HDD is an abbreviation for Hard Disk Drive. SD® is an abbreviation for Secure Digital. CF is an abbreviation for CompactFlash®. DVD is an abbreviation for Digital Versatile Disk.

The input interface 930 is a port connected to an input device such as a mouse, keyboard, or touch panel. The input interface 930 is also used as a port connected to a recording device for acquiring road surface condition measurement data. The input interface 930 is specifically a USB (Universal Serial Bus) terminal. The input interface 930 may be a port connected to a LAN (Local Area Network).
The output interface 940 is a port to which a cable of an output device such as a display is connected. The output interface 940 is specifically a display port or HDMI (registered trademark) (High Definition Multimedia Interface) terminal. The display is specifically an LCD (Liquid Crystal Display).

Communication device 950 has a receiver and a transmitter. The communication device 950 is wirelessly connected to a communication network such as a LAN, the Internet, or a telephone line. The communication device 950 is specifically a communication chip or a NIC (Network Interface Card).

The road surface condition measurement program is read into processor 910 and executed by processor 910 . The memory 921 stores not only the road surface condition measurement program but also an OS (Operating System). The processor 910 executes the road surface condition measurement program while executing the OS. The road surface condition measurement program and OS may be stored in the auxiliary storage device 922 . The road surface condition measurement program and OS stored in the auxiliary storage device 922 are loaded into the memory 921 and executed by the processor 910 . Part or all of the road surface condition measurement program may be incorporated in the OS.

The road surface condition measuring device 100 may include a plurality of processors that substitute for the processor 910 . These multiple processors share the execution of the road surface condition measurement program. Each processor, like the processor 910, is a device that executes a road surface condition measurement program.

Data, information, signal values and variable values that are used, processed or output by the road surface condition measurement program are stored in the memory 921, the auxiliary storage device 922, or the register or cache memory within the processor 910. FIG.

The "part" of each part of the image collecting part 110, the image forming part 120, the area defining part 130, the road surface condition detecting part 140, and the map superimposing part 150 may be read as "processing", "procedure" or "process". In addition, "processing" of image collection processing, image formation processing, area definition processing, road surface condition detection processing, and map superimposition processing should be read as "program", "program product", or "computer-readable recording medium recording the program". may
The road surface condition measurement program causes the computer to execute each process, each procedure, or each process, where the above "part" is read as "process,""procedure," or "process." Moreover, the road surface property measuring method is a method performed by the road surface property measuring device 100 executing a road surface property measuring program.
The road surface condition measurement program may be provided by being stored in a computer-readable recording medium. Also, the road surface condition measurement program may be provided as a program product.

***Description of operation***
FIG. 5 is a flowchart of road surface condition measurement processing S100 according to the present embodiment.
The road surface condition measurement device 100 uses road surface condition measurement data 301 measured by the road surface condition measurement unit 220 and position/orientation measurement data 302 measured by the position/orientation measurement unit 210 to analyze the road condition. Processing S100 is performed.
The road surface condition measurement process S100 includes an image acquisition process S110, an image formation process S120, an area definition process S130, a road surface condition detection process S140, and a map superimposition process S150.

In step S<b>110 , the image collection unit 110 collects line images of the road surface captured by the line camera 332 . Specifically, the road surface condition measuring device 100 acquires the road surface condition measurement data 301 measured by the road surface condition measuring unit 220 via the communication device 950 or the input interface 930 and stores it in the memory 921 . The road surface property measurement data 301 includes a line image of the road surface captured by the line camera 332 . The image acquisition unit 110 acquires line images stored in the memory 921 .

In step S<b>120 , the image forming section 120 forms the image of the road surface as the road surface image 21 using the line image captured by the line camera 332 . Specifically, the image forming section 120 bundles the line images to form the road surface image 21 of 4 meters square.

In step S<b>130 , the area defining section 130 divides the road surface image 21 into a plurality of unit images 22 . Specifically, the area definition unit 130 detects the white lines 211 on the road surface, and divides the road surface image 21 into a plurality of unit images 22 based on the detected white lines 211 . That is, the area definition unit 130 divides the road surface image 21 into a plurality of unit images 22 based on the detected white line 211 . The area definition unit 130 detects the white line 211 from the road surface image 21 by the automatic white line extraction process. Then, the area definition unit 130 identifies the area inside the white line 211 in the road surface image 21 as the area from which data is to be acquired. The area definition unit 130 divides the area from which data is to be acquired into a plurality of unit images 22 . Specifically, the unit image 22 is a 50 cm square image.

FIG. 6 shows part of a diagram in which the road surface image 21 according to the present embodiment is divided into a plurality of unit images 22. As shown in FIG.
In the road surface image 21 of FIG. 6, the road surface image 21 is divided into a plurality of unit images 22 with the right end of the white line 211 of the road surface image 21 as a reference.

In step S<b>140 , the road surface condition detection unit 140 detects the road surface condition in each unit image 22 of the plurality of unit images based on the road surface image 21 . The road surface condition detection unit 140 then generates unit road surface condition information 162 in which the unit image 22 , road surface condition data 221 representing the road surface condition of the unit image 22 , and position/orientation information 222 are associated with each other. The position/orientation information 222 includes the time when the unit image 22 was captured, the position of the road surface captured in the unit image, and the attitude of the measurement vehicle that captured the unit image. Specifically, the road surface condition detection unit 140 detects cracks in the road surface as the road surface condition. The road surface condition detection unit 140 then generates unit road surface condition information 162 including the unit image 22 , the number of cracks in the unit image 22 , and the position and orientation information 222 of the unit image 22 . The process of detecting the number of cracks in the unit image 22 is also called automatic crack processing.

FIG. 7 is a schematic diagram showing an example of the unit road surface condition information 162 according to this embodiment.
The unit road surface condition information 162 is associated with the unit image 22 , the road surface condition data 221 of the unit image 22 , and the position/orientation information 222 . Note that the position/orientation information 222 in the unit road surface condition information 162 may represent any position in the unit image 22 as long as the unit image 22 can be specified. Further, the unit road surface condition information 162 may be configured in any format as long as the unit image 22, the road surface condition data 221, and the position/orientation information 222 can be associated with each other.

Here, an outline of the crack automatic processing will be described.
In the detection of cracks by binarization, one crack may be over-detected as multiple cracks due to factors such as color unevenness in photographing the road surface, roughness of the grain size of the road surface, coarse aggregate, or white lines. In addition, due to erroneous detection caused by factors such as stains or coarse aggregate, road surface properties such as the number of cracks may not be accurately grasped.
Therefore, in the present embodiment, automatic crack processing is performed as follows.
(1) Calculate the feature amount of the road surface image, determine the road surface type such as asphalt or concrete, determine the size of the aggregate particle size of the road surface, and determine the determination parameters for extracting cracks.
(2) For the crack areas extracted by binarizing the road surface image, the area of each area, the distance between the areas, and the difference in the angle (inclination) between the areas are integrated and determined. A crack area extracted as a crack area can be detected as one crack.
(3) Coarse aggregate regions are extracted from the ratio of the area of a region with luminance lower than the background luminance extracted by binarizing the road surface image to the area of the circle circumscribing that region, and excluded from the crack region.
(4) For various determination parameters used for crack extraction, create information such as a large number of learning images, that is, correct data, for various road surface conditions, and update the determination parameters by learning, so that various road surface conditions can be obtained. To be able to cope with changes or shooting conditions of a road surface.

Further, in (1) above, a function may be provided to allow the user to input the road surface type in the road surface image 21 .
8 and 9 are diagrams showing an example of a function for allowing the user to input the road surface type in this embodiment.
The road surface property detection unit 140 displays on the display a road surface type selection screen 141 that allows the user to select a road surface type. The user designates the range of the road surface image 21 and designates the road surface type via the road surface type selection screen 141 . The road surface condition detection unit 140 determines a determination parameter for detecting the number of cracks based on the designated road surface type. Further, when other is specified, the road surface condition detection unit 140 may cause the user to specify road surface information such as drainage, water permeability, and water retention through the road surface type selection screen 141 . The road surface condition detection unit 140 may determine determination parameters from these road surface information.
Further, the road surface condition detection unit 140 may automatically determine the road surface type from the road surface image 21 .
The road surface condition detection unit 140 determines determination parameters based on the road surface type specified by the user or the automatically determined road surface type.

FIG. 10 is a diagram showing an example of a variable function of determination parameters according to the road surface type according to the present embodiment.
As shown in FIG. 10, the magnitude of the crack detection error and the impact of road stains differ for each road surface type, such as concrete, asphalt mixture, and porous asphalt mixture. The road surface condition detection unit 140 determines determination parameters so as to absorb the difference in the effects of crack detection errors and road stains.

In step S<b>150 , the map superimposing unit 150 acquires the map position data 61 representing the position in the map information 161 via the input interface 930 . The map superimposing unit 150 extracts the road surface unit image 22 including the position represented by the map position data 61 , the road surface condition data 221 , and the position/orientation information 222 from the unit road surface condition information 162 as the road surface display information 23 . Then, the map superimposing unit 150 superimposes the information included in the road surface display information 23 on the map information 161 and displays it on the display.
The map superimposing unit 150 superimposes the unit image 22 including the position represented by the map position data 61 on the map information 161 and displays it. Alternatively, the map superimposing unit 150 superimposes the road surface condition data 221 and the position/orientation information 222 in the unit image 22 including the position represented by the map position data 61 on the map information 161 for display.
Specifically, it is as follows.

FIG. 11 is a diagram showing an example of road surface condition screen 62 displayed by map superimposing section 150 according to the present embodiment.
The map superimposing unit 150 displays the map information 161 on the display and prompts the user to input the map position data 61 representing the position on the map. Based on the map position data 61 , the map superimposing unit 150 extracts the information of the unit images 22 around the position represented by the map position data 61 from the unit road surface condition information 162 as the road surface display information 23 . The range to be extracted based on the map position data 61 may be set in advance. Alternatively, the map superimposing unit 150 acquires the range specified by the user as the map position data 61, and extracts the information of the unit image 22 in the range specified by the user from the unit road surface condition information 162 as the road surface display information 23. may
The map superimposing unit 150 superimposes the extracted road surface display information 23 on the map information 161 to generate the road surface condition screen 62 .

In FIG. 11 , the map superimposing unit 150 displays a road surface condition screen 62 in which the road surface condition data 221 included in the road surface display information 23 is superimposed on the map information 161 . The map superimposing unit 150 superimposes the road surface condition data 221 included in the road surface display information 23 including the map position data 61 specified by the user on the map information 161 .

FIG. 12 is a diagram showing another example of the road surface condition screen 62 displayed by the map superimposing unit 150 according to this embodiment.
In FIG. 12 , the map superimposing unit 150 displays a road surface condition screen 62 in which the unit images 22 included in the road surface display information 23 are superimposed on the map information 161 . As a specific example, the measurement vehicle 200 may travel over a wide area such as an airport. Even if the user designates an arbitrary position or range of the airport as the map position data 61, the map superimposing unit 150 converts the information of the unit image 22 of the position or range designated by the user into the unit road surface display information 23. It can be extracted from the property information 162 . The map superimposing unit 150 then superimposes the road surface image 21 obtained by connecting the unit images 22 based on the position and orientation information 222 included in the road surface display information 23 on the map information 161 to display the road surface condition screen 62 .

Based on the map position data 61 and the unit road surface condition information 162, the map superimposing unit 150 also generates a road surface condition trace 63 representing the distribution of the road surface condition data 221 of the road surface including the position represented by the map position data 61. You may
Specifically, when the user acquires the map position data 61 and the display request for the road surface condition trace 63, the map superimposing unit 150 generates the road surface condition trace 63 and displays it on the display.

FIG. 13 is a diagram showing an example of the road surface condition trace 63 according to this embodiment.
In FIG. 13, the map superimposing unit 150 displays a road surface condition trace 63 representing the distribution of the number of cracks. When an arbitrary position or range in the map information 161 is specified by the user, the map superimposing section 150 extracts the information of the unit image 22 of the position or range specified by the user from the unit road surface condition information 162 as the road surface display information 23. do. Based on the road surface display information 23, the map superimposing unit 150 displays, as a specific example, a road surface condition trace 63 representing the distribution of the number of cracks.

***Description of the effects of the present embodiment***
Since the road surface condition measurement system according to the present embodiment is equipped with MMS, highly accurate position information can be added to the road surface condition measurement data. Therefore, according to the road surface condition measurement system according to the present embodiment, the compatibility with the map information is very high, and the road surface condition measurement data can be superimposed on the map information. Therefore, according to the road surface condition measuring system according to the present embodiment, it becomes easy to manage and analyze data.

In the road surface condition measurement system according to the present embodiment, highly accurate position information is added to road surface condition measurement data such as cracks, ruts, and evenness measured by the road surface condition measurement system. Thus, in the road surface condition measurement system according to the present embodiment, the measured road surface condition measurement data can be superimposed on the map. Therefore, in the road surface condition measuring system according to the present embodiment, it is possible to instantaneously output road surface condition data at an arbitrary point on a map designated by the user, that is, measurement results such as cracks, ruts, and flatness. Become.

In the road surface condition measuring system according to the present embodiment, a map is displayed on a display device such as a PC (personal computer) included in the road surface condition measuring system or a navigation system display. Then, when an arbitrary point is selected on the map displayed on the display device, the road surface condition information of the selected point is superimposed on the map and output. Alternatively, the road surface condition information at the point is output as a road surface condition trace. Since the road surface condition measurement system according to the present embodiment has such road surface condition data analysis software, management and analysis of the road surface condition measurement data are facilitated.

***Other Configurations***
<Modification 1>
In the present embodiment, the number of cracks is used as an example of the road surface condition data. However, rutting or evenness measurement results may be used as the road surface condition data. That is, a plurality of these road surface properties may be displayed on the road surface property screen. Alternatively, the distribution of any of the road conditions may be displayed as a road condition trace.

<Modification 2>
In this embodiment, the functions of the image collection unit 110, the image formation unit 120, the area definition unit 130, the road surface condition detection unit 140, and the map superimposition unit 150 are implemented by software. As a modification, the functions of the image collection unit 110, the image formation unit 120, the area definition unit 130, the road surface condition detection unit 140, and the map superimposition unit 150 may be realized by hardware.

The road surface condition measuring device 100 has an electronic circuit in place of the processor 910 .
The electronic circuit is a dedicated electronic circuit that implements the functions of the image collecting section 110 , the image forming section 120 , the area defining section 130 , the road surface condition detecting section 140 and the map superimposing section 150 .
Electronic circuits are specifically single circuits, compound circuits, programmed processors, parallel programmed processors, logic ICs, GAs, ASICs or FPGAs. GA is an abbreviation for Gate Array. ASIC is an abbreviation for Application Specific Integrated Circuit. FPGA is an abbreviation for Field-Programmable Gate Array.
The functions of the image collecting unit 110, the image forming unit 120, the area defining unit 130, the road surface condition detecting unit 140, and the map superimposing unit 150 may be realized by one electronic circuit, or may be realized by being distributed among a plurality of electronic circuits. may be
As another modification, part of the functions of the image collection unit 110, the image formation unit 120, the area definition unit 130, the road surface condition detection unit 140, and the map superimposition unit 150 are realized by electronic circuits, and the rest of the functions are realized by software. may be Also, part or all of the functions of the image collection unit 110, the image formation unit 120, the area definition unit 130, the road surface condition detection unit 140, and the map superimposition unit 150 may be realized by firmware.

Each of the processor and electronic circuitry is also called processing circuitry. In other words, in the road surface condition measuring device 100, the functions of the image acquisition unit 110, the image forming unit 120, the area definition unit 130, the road surface condition detection unit 140, and the map superimposing unit 150 are realized by the processing circuitry.

In the above embodiment, each part of the road surface condition measuring device has been described as an independent functional block. However, the configuration of the road surface condition measuring device does not have to be the configuration of the above-described embodiment. The functional blocks of the road surface condition measuring device may have any configuration as long as they can implement the functions described in the above embodiments. Moreover, the road surface condition measuring device may be a system composed of a plurality of devices instead of one device.
Moreover, it is also possible to combine a plurality of portions of the first embodiment. Alternatively, one portion of this embodiment may be implemented. In addition, this embodiment may be implemented as a whole or partially in any combination.
In other words, it is possible to freely combine parts of the first embodiment, modify arbitrary constituent elements of the first embodiment, or omit arbitrary constituent elements from the first embodiment.

The above-described embodiments are essentially preferable examples, and are not intended to limit the scope of the invention, the scope of applications of the invention, or the scope of applications of the invention. Various modifications can be made to the above-described embodiments as required.

21 road surface image, 22 unit image, 23 road surface display information, 211 white line, 221 road surface condition data, 222 position and orientation information, 61 map position data, 62 road surface condition screen, 63
Road surface condition trace 100 Road surface condition measuring device 110 Image collecting unit 120 Image forming unit 130 Area defining unit 140 Road surface condition detecting unit 141 Road surface type selection screen 150 Map superimposing unit 160 Storage unit 161 Map information 162 unit road surface condition information 200 measurement vehicle 210 position and orientation measurement unit 220 road surface condition measurement unit 300
Measurement Vehicle Acquisition Data 301 Road Condition Measurement Data 302 Position and Orientation Measurement Data 303 Post-Processing Data 331 High Precision Laser 332 Line Camera 333 Laser Illumination 334 Displacement Meter 500 Road Condition Measurement System 910 Processor 921 Memory , 922 auxiliary storage device, 930 input interface, 940 output interface, 950 communication device, S100 road surface condition measurement processing.

Claims (10)

a line camera mounted on a measurement vehicle running on a road surface, and an image forming unit that forms an image of the road surface as a road surface image using a line image captured by the line camera that captures the image of the road surface;
an area defining unit that divides the road surface image into a plurality of unit images;
Based on the road surface image, a road surface condition in each unit image of the plurality of unit images is detected, and road surface condition data representing the road surface condition of the unit image is detected . a road surface condition detection unit that generates unit road surface condition information in which position and orientation information including any of the positions and the orientation of the measurement vehicle that captured the unit image is associated with the time at which the unit image was captured. A road surface condition measuring device. The road surface condition measuring device includes:
acquiring map position data representing a position in map information via an input interface, extracting a unit image of a road surface including the position represented by the map position data, road surface condition data, and position and orientation information as road surface display information; 2. The road surface condition measuring apparatus according to claim 1, further comprising a map superimposing unit for superimposing information included in said road surface display information on said map information. The map superimposing unit
3. The road surface condition measuring apparatus according to claim 2, wherein a unit image including the position represented by the map position data is superimposed on the map information and displayed. The map superimposing unit
4. The road surface condition measuring apparatus according to claim 2, wherein the road surface condition data and position/orientation information in a unit image including the position represented by the map position data are superimposed on the map information and displayed. The map superimposing unit
5. A road surface condition trace representing a distribution of road surface condition data of a road surface including a position represented by said map position data is generated based on said map position data and said unit road surface condition information. 1. The road surface property measuring device according to 1. The road surface condition detection unit
Detecting cracks in the road surface as the road surface condition, and generating the unit road surface condition information including the unit image, the number of cracks in the unit image, and the position and orientation information of the unit image. Item 6. The road surface condition measuring device according to any one of Item 5. The area definition unit
The road surface condition measuring device according to any one of claims 1 to 6, wherein the road surface image is divided into a plurality of unit images based on the detected white lines. A measuring vehicle that travels on a road surface, the measuring vehicle comprising a road surface condition measuring unit that measures the road surface condition of the road surface, and a position and orientation measuring unit that measures the position and orientation of the measuring vehicle;
a road surface condition measurement device that analyzes the road surface condition using the road surface condition measurement data measured by the road surface condition measurement unit and the position and orientation measurement data measured by the position and orientation measurement unit;
The road surface condition measuring device includes:
an image forming unit that forms an image of the road surface as a road surface image using a line image captured by a line camera included in the road surface condition measurement unit;
an area defining unit that divides the road surface image into a plurality of unit images;
Based on the road surface image, a road surface condition in each unit image of the plurality of unit images is detected, and road surface condition data representing the road surface condition of the unit image is detected . a road surface condition detection unit that generates unit road surface condition information in which position and orientation information including any of the positions and the orientation of the measurement vehicle that captured the unit image is associated with the time at which the unit image was captured. road surface condition measurement system. The image forming unit is a line camera mounted on a measurement vehicle traveling on a road surface, and forms the image of the road surface as a road surface image using the line image captured by the line camera that images the road surface,
a region definition unit dividing the road surface image into a plurality of unit images;
A road surface condition detection unit detects a road surface condition in each unit image of the plurality of unit images based on the road surface image, and generates a unit image, road surface condition data representing the road surface condition of the unit image, and the unit image. A road surface that generates unit road surface condition information in which position and orientation information including any position on the road surface imaged in and the orientation of the measurement vehicle that imaged the unit image are associated with the time when the unit image was imaged Property measurement method. Image forming processing for forming an image of the road surface into a road surface image using a line image captured by a line camera mounted on a measurement vehicle traveling on the road surface and capturing the road surface;
an area defining process for dividing the road surface image into a plurality of unit images;
Based on the road surface image, a road surface condition in each unit image of the plurality of unit images is detected, and road surface condition data representing the road surface condition of the unit image is detected . a road surface condition detection process for generating unit road surface condition information in which position and orientation information including any position and the orientation of the measurement vehicle that captured the unit image is associated with the time at which the unit image was captured; A road surface condition measurement program to be executed by a road surface condition measurement device.

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