A method for automatically measuring the flatness and longitudinal profile elevation of a road

Abstract

The application discloses a kind of road full section flatness and longitudinal section elevation automatic measurement methods, comprising steps S1: laser long baseline is generated by laser launch platform, to be used as the reference line of road full section flatness measurement;Step S2: target point moving platform moves and receives horizontal laser beam emitted by laser launch platform, carries out road full section scanning;Step S3: by 3D high-precision surface scanning data splicing, the full section flatness of a certain road section is obtained, and the spot position information of the starting point and the end point area of target point moving platform is used to calculate the longitudinal section elevation of a certain road section;Step S4: the international flatness index of road full section and longitudinal section elevation are calculated, and the road flatness defect position is automatically positioned according to IRI threshold value.The road full section flatness and longitudinal section elevation automatic measurement method disclosed by the application solves the problem that the measurement accuracy of current road flatness and elevation is low, and the system error cannot be eliminated in time.

Description

Technical Field

[0001] This invention belongs to the fields of traffic engineering and automation, and specifically relates to an automatic measurement method for the full-section flatness and longitudinal profile elevation of roads based on BeiDou positioning and laser long baseline. Background Technology

[0002] Road smoothness inspection is a crucial component of traffic engineering and road management, improving road construction quality, optimizing resource allocation, and enhancing traffic comfort and road safety. However, existing methods for measuring road smoothness and longitudinal profile elevation generally employ short-range measurements, making it difficult to eliminate systematic errors effectively and promptly, resulting in low measurement accuracy and a range of traffic and road problems. Therefore, high-precision automatic measurement of full-section road smoothness and longitudinal profile elevation has significant application value and importance. Summary of the Invention

[0003] The main objective of this invention is to provide an automatic method for measuring the overall road surface smoothness and longitudinal profile elevation. This method involves constructing a laser transmitter and emitting a horizontal laser beam, setting up a target station to perform a 3D surface scan of the road surface, mounting a laser target on the target station to image the laser beam, calculating the overall road surface smoothness based on the 3D surface scan results and the BeiDou positioning information of the target station, and calculating the longitudinal profile elevation based on the laser beam imaging spot position information and the BeiDou positioning information of the target station. Finally, the method automatically locates the smoothness defects based on abrupt changes in overall road surface smoothness. This invention achieves continuous automatic measurement of overall road surface smoothness and longitudinal profile elevation, and automatically locates the positions of overall road surface smoothness defects, significantly improving measurement accuracy and efficiency, and solving the problems of low measurement accuracy and the inability to promptly eliminate system errors in current road surface smoothness and elevation measurements.

[0004] To achieve the above objectives, this invention provides an automatic method for measuring the overall road cross-section smoothness and longitudinal profile elevation, comprising the following steps:

[0005] Step S1: Generate a long laser baseline using a laser transmitter to serve as a reference line for measuring the smoothness of the entire road cross-section;

[0006] Step S2: Move the target moving station and receive the horizontal laser beam emitted by the laser transmitter to perform a full-section scan of the road;

[0007] Step S3: Obtain the full cross-sectional flatness of a certain road section by stitching together 3D high-precision surface scanning data, and calculate the longitudinal profile elevation of a certain road section using the spot position information of the starting and ending areas of the target moving station;

[0008] Step S4: Move the laser transmitter, repeat steps S2 and S3, and stitch together the full-section smoothness and longitudinal elevation of each road section according to the Beidou positioning information to calculate the International Roughness Index (IRI) and longitudinal elevation of the full-section road, and automatically locate the location of road smoothness defects according to the IRI threshold.

[0009] As a further preferred technical solution to the above technical solution, step S1 is specifically implemented as follows:

[0010] Step S1.1: Assemble the laser emitter (including tilt sensor), power supply and telescopic support into a laser emission platform;

[0011] Step S1.2: Adjust the laser emitter so that the tilt sensor angle it includes is horizontal;

[0012] Step S1.3: Turn on the laser emitter and generate a horizontal laser beam to serve as a baseline for measuring the smoothness of the entire road section.

[0013] As a further preferred technical solution to the above technical solution, for step S2:

[0014] The target moving stage includes a laser target surface, a target imaging component, an image processing card, a sub-millimeter-level 3D high-precision surface scanning module, a laser ranging module, a signal control and processing module (including a BeiDou high-precision positioning module), a hub motor (including a motor encoder), a supplementary light, and a mobile power supply. It uses stepped test blocks and calibrates the sub-millimeter-level 3D high-precision surface scanning module based on the data obtained from the laser ranging module. It records the BeiDou positioning information corresponding to the starting position of the target moving stage and the position information of the laser spot in the laser target surface. The target moving stage moves along the longitudinal section of the road and records the 3D high-precision surface scanning data and the position information of the laser spot in the laser target surface.

[0015] As a further preferred technical solution to the above technical solution, step S2 is specifically implemented as follows:

[0016] Step S2.1: Adjust the position of the target moving stage so that the laser long baseline spot is in the center area of ​​the laser target surface. Place stepped test blocks on the four single-point laser ranging modules. Correct the 3D high-precision surface scanning module based on the single-point laser ranging results. Correct the 0.01mm-level accuracy of the 3D high-precision surface scanning module. The calculation method is as follows:

[0017] If the elevation difference Δh is obtained using a stepped test block, then the elevation difference measured by the m-th single-point laser ranging module is... for:

[0018]

[0019] in, The elevation measured by the m-th single-point laser ranging module at the first position (preferably 5mm) of the stepped test block is given. The elevation difference measured by the sub-millimeter-level 3D high-precision surface scanning module at the second position (preferably 3mm) of the stepped test block is the elevation measured by the m-th single-point laser ranging module at the corresponding position of the m-th single-point laser ranging module. for:

[0020]

[0021] in, The elevation is measured by the sub-millimeter-level 3D high-precision surface scanning module at the first position of the stepped test block corresponding to the m-th single-point laser ranging module. Given the elevation measured by the sub-millimeter-level 3D high-precision surface scanning module at the second position of the stepped test block corresponding to the m-th single-point laser ranging module, the correction coefficient of the measurement value within a single area of ​​the 3D high-precision surface scanning module is calculated. for:

[0022]

[0023] For correction coefficient The measurements are performed continuously a preset number of times (preferably 10 times), and the average value is taken as the final result for each region after processing with a one-dimensional Gaussian smoothing filter. The filter function is:

[0024]

[0025] Where u is The mean, σ is The variance;

[0026] Step S2.2: Record the BeiDou positioning information O corresponding to the starting position of the target moving station. s A color image of the laser target surface is acquired through a target imaging component. The image is then converted to grayscale based on the laser color gamut channel components. The OTSU algorithm is used for image segmentation, and the Canny operator is employed for edge detection. Finally, least-squares ellipse fitting is used to obtain the coordinates (X, Y) of the center point of the laser spot at the starting point of the laser baseline in the target surface color image. zs ,Y zs The system acquires data from a sub-millimeter level 3D high-precision surface scanning module and records its RGB image. RGB (x,y) and corresponding depth data f D (x,y), where f D (x,y) is based on the four regions where the laser ranging is located. After correction, it becomes f′ D (x,y);

[0027] Step S2.3: Control the hub motor to rotate, and the target moving stage moves at a constant speed along the longitudinal section of the road. The hub motor encoder triggers the 3D high-precision surface scanning module to acquire data at preset intervals (preferably 0.4 meters) to obtain sequence image data f. RGB (x,y,t), f′ D (x,y,t) and the coordinates of the center point of the laser target spot (X) z ,Y z ,t).

[0028] As a further preferred technical solution to the above technical solution, step S3 is specifically implemented as follows:

[0029] Step S3.1: Use the f obtained by the 3D high-precision surface scanning module RGB (x,y,t) data and f RGB The image feature matching is performed on (x, y, t-1). The SIFT operator is used for feature point extraction during image feature matching. After matching, f′ is calculated based on the matching position. D (x,y,t) and f′ D By splicing together (x,y,t-1), the overall cross-sectional smoothness of a certain road section can be obtained;

[0030] Step S3.2: Record the coordinates (X) of the center point of the laser target spot at the end of a certain road segment. ze ,Y ze ), through the coordinates of the center point of the light spot at the starting point (X) zs ,Y zs The longitudinal profile elevation of a certain road section is calculated.

[0031] Step S3.3: Record the BeiDou positioning information of the target mobile station position at the end of a certain road segment. e .

[0032] As a further preferred technical solution to the above technical solution, step S4 is specifically implemented as follows:

[0033] Step S4.1: Move the laser emitter and update the BeiDou positioning information corresponding to the starting position of the target point. s The coordinates of the center point of the light spot at the starting point (X) zs ,Y zs ), data from the 3D high-precision surface scanning module f RGB (x,y) and f D (x,y);

[0034] Step S4.2: Repeat steps S2.3 to S3.3 until the road inspection endpoint is reached, and calculate the overall road cross-section smoothness and longitudinal profile elevation;

[0035] Step S4.3: Calculate the smoothness index using the measured full-section smoothness data according to the International Roughness Index (IRI) calculation formula, and automatically locate the road smoothness defects based on the IRI threshold. Attached Figure Description

[0036] Figure 1 This is a flowchart of an automatic measurement method for the overall flatness and longitudinal elevation of a road according to the present invention.

[0037] Figure 2 This is a schematic diagram of the structure of a laser transmitter for an automatic measurement method of road cross-section smoothness and longitudinal profile elevation according to the present invention.

[0038] Figure 3 This is a schematic diagram of the target moving platform of the automatic measurement method for the full cross-section flatness and longitudinal section elevation of a road according to the present invention.

[0039] Figure 4 This is a cross-sectional view of the target moving platform of the automatic measurement method for the full cross-section smoothness and longitudinal profile elevation of a road according to the present invention.

[0040] The attached reference numerals include: 11, laser emitter; 12, power supply; 13, telescopic support; 21, laser target surface; 22, target imaging component; 23, image processing card; 24, sub-millimeter level 3D high-precision surface scanning module; 25, laser ranging module; 26, signal control and processing module; 27, hub motor; 28, supplementary light; 29, mobile power supply. Detailed Implementation

[0041] The following description is intended to disclose the present invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art. The basic principles of the invention defined in the following description can be applied to other embodiments, modifications, improvements, equivalents, and other technical solutions that do not depart from the spirit and scope of the invention.

[0042] In a preferred embodiment of the present invention, those skilled in the art should note that roads and other features involved in the present invention can be considered prior art.

[0043] Preferred embodiment.

[0044] like Figure 1-4 As shown, this invention discloses an automatic measurement method for the smoothness of the entire road cross-section and the elevation of the longitudinal profile, comprising the following steps:

[0045] Step S1: Generate a long laser baseline using a laser transmitter to serve as a reference line for measuring the smoothness of the entire road cross-section;

[0046] Step S2: Move the target moving station and receive the horizontal laser beam emitted by the laser transmitter to perform a full-section scan of the road;

[0047] Step S3: Obtain the full cross-sectional flatness of a certain road section by stitching together 3D high-precision surface scanning data, and calculate the longitudinal profile elevation of a certain road section using the spot position information of the starting and ending areas of the target moving station;

[0048] Step S4: Move the laser transmitter, repeat steps S2 and S3, and stitch together the full-section smoothness and longitudinal elevation of each road section according to the Beidou positioning information to calculate the International Roughness Index (IRI) and longitudinal elevation of the full-section road, and automatically locate the location of road smoothness defects according to the IRI threshold.

[0049] Specifically, step S1 is implemented as follows:

[0050] Step S1.1: Assemble the laser emitter 11 (including the tilt sensor), the power supply 12, and the telescopic bracket 13 into a laser emitting platform;

[0051] Step S1.2: Adjust the laser emitter 11 so that the tilt sensor angle it includes is horizontal;

[0052] Step S1.3: Turn on the laser emitter 11 and generate a horizontal laser beam to serve as a baseline for measuring the smoothness of the entire road section.

[0053] More specifically, for step S2:

[0054] The target moving stage includes a laser target surface 21, a target imaging component 22, an image processing card 23, a sub-millimeter-level 3D high-precision surface scanning module 24, a laser ranging module 25, a signal control and processing module 26 (including a Beidou high-precision positioning module), a hub motor 27 (including a motor encoder), a supplementary light 28, and a mobile power supply 29. It uses stepped test blocks and calibrates the sub-millimeter-level 3D high-precision surface scanning module 24 based on the data obtained from the laser ranging module 25. It records the Beidou positioning information corresponding to the starting position of the target moving stage and the position information of the laser spot in the laser target surface. The target moving stage moves along the longitudinal section of the road and records the 3D high-precision surface scanning data and the position information of the laser spot in the laser target surface.

[0055] Furthermore, step S2 is specifically implemented as follows:

[0056] Step S2.1: Adjust the position of the target moving stage so that the laser long baseline spot is in the center area of ​​the laser target surface. Place stepped test blocks on the four single-point laser ranging modules. Correct the 3D high-precision surface scanning module based on the single-point laser ranging results. Correct the 0.01mm-level accuracy of the 3D high-precision surface scanning module. The calculation method is as follows:

[0057] If the elevation difference Δh is obtained using a stepped test block, then the elevation difference measured by the m-th single-point laser ranging module is... for:

[0058]

[0059] in, The elevation measured by the m-th single-point laser ranging module at the first position (preferably 5mm) of the stepped test block is given. The elevation difference measured by the sub-millimeter-level 3D high-precision surface scanning module at the second position (preferably 3mm) of the stepped test block is the elevation measured by the m-th single-point laser ranging module at the corresponding position of the m-th single-point laser ranging module. for:

[0060]

[0061] in, The elevation is measured by the sub-millimeter-level 3D high-precision surface scanning module at the first position of the stepped test block corresponding to the m-th single-point laser ranging module. Given the elevation measured by the sub-millimeter-level 3D high-precision surface scanning module at the second position of the stepped test block corresponding to the m-th single-point laser ranging module, the correction coefficient of the measurement value within a single area of ​​the 3D high-precision surface scanning module is calculated. for:

[0062]

[0063] For correction coefficient The measurements are performed continuously a preset number of times (preferably 10 times), and the average value is taken as the final result for each region after processing with a one-dimensional Gaussian smoothing filter. The filter function is:

[0064]

[0065] Where u is The mean, σ is The variance;

[0066] Step S2.2: Record the BeiDou positioning information O corresponding to the starting position of the target moving station. s A color image of the laser target surface is acquired through a target imaging component. The image is then converted to grayscale based on the laser color gamut channel components. The OTSU algorithm is used for image segmentation, and the Canny operator is employed for edge detection. Finally, least-squares ellipse fitting is used to obtain the coordinates (X, Y) of the center point of the laser spot at the starting point of the laser baseline in the target surface color image. zs ,Y zs The system acquires data from a sub-millimeter level 3D high-precision surface scanning module and records its RGB image.RGB (x,y) and corresponding depth data f D (x,y), where f D (x,y) is based on the four regions where the laser ranging is located. After correction, it becomes f′ D (x,y);

[0067] Step S2.3: Control the hub motor to rotate, and the target moving stage moves at a constant speed along the longitudinal section of the road. The hub motor encoder triggers the 3D high-precision surface scanning module to acquire data at preset intervals (preferably 0.4 meters) to obtain sequence image data f. RGB (x,y,t), f′ D (x,y,t) and the coordinates of the center point of the laser target spot (X) z ,Y z ,t).

[0068] Furthermore, step S3 is specifically implemented as follows:

[0069] Step S3.1: Use the f obtained by the 3D high-precision surface scanning module RGB (x,y,t) data and f RGB The image feature matching is performed on (x, y, t-1). The SIFT operator is used for feature point extraction during image feature matching. After matching, f′ is calculated based on the matching position. D (x,y,t) and f′ D By splicing together (x,y,t-1), the overall cross-sectional smoothness of a certain road section can be obtained;

[0070] Step S3.2: Record the coordinates (X) of the center point of the laser target spot at the end of a certain road segment. ze ,Y ze ), through the coordinates of the center point of the light spot at the starting point (X) zs ,Y zs The longitudinal profile elevation of a certain road section is calculated.

[0071] Step S3.3: Record the BeiDou positioning information of the target mobile station position at the end of a certain road segment. e (Used when several road sections are pieced together).

[0072] Preferably, step S4 is specifically implemented as follows:

[0073] Step S4.1: Move the laser emitter and update the BeiDou positioning information corresponding to the starting position of the target point. s The coordinates of the center point of the light spot at the starting point (X) zs ,Y zs ), data from the 3D high-precision surface scanning module f RGB (x,y) and f D(x,y);

[0074] Step S4.2: Repeat steps S2.3 to S3.3 until the road inspection endpoint is reached, and calculate the overall road cross-section smoothness and longitudinal profile elevation;

[0075] Step S4.3: Calculate the smoothness index using the measured full-section smoothness data according to the International Roughness Index (IRI) calculation formula, and automatically locate the road smoothness defects based on the IRI threshold.

[0076] It is worth mentioning that the technical features such as roads involved in this patent application should be regarded as prior art. The specific structure, working principle, and possible control methods and spatial arrangement methods of these technical features can be adopted using conventional choices in the field, and should not be regarded as the inventive point of this patent. This patent will not be further elaborated in detail.

[0077] For those skilled in the art, modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this invention should be included within the protection scope of this invention.

Claims

1. An automatic measurement method for the overall cross-sectional smoothness and longitudinal profile elevation of a road, characterized in that, Includes the following steps: Step S1: Generate a long laser baseline using a laser transmitter to serve as a reference line for measuring the smoothness of the entire road cross-section; Step S2: Move the target moving station and receive the horizontal laser beam emitted by the laser transmitter to perform a full-section scan of the road; For step S2: The target moving stage includes a laser target surface, a target imaging component, an image processing card, a sub-millimeter-level 3D high-precision surface scanning module, a laser ranging module, a signal control and processing module, a hub motor, a supplementary light, and a mobile power supply. It uses stepped test blocks and calibrates the sub-millimeter-level 3D high-precision surface scanning module based on the data obtained from the laser ranging module. It records the BeiDou positioning information corresponding to the starting position of the target moving stage and the position information of the laser spot in the laser target surface. The target moving stage moves along the longitudinal section of the road and records the 3D high-precision surface scanning data and the position information of the laser spot in the laser target surface. Step S3: Obtain the full cross-sectional flatness of a certain road section by stitching together 3D high-precision surface scanning data, and calculate the longitudinal profile elevation of a certain road section using the spot position information of the starting and ending areas of the target moving station; Step S4: Move the laser transmitter, repeat steps S2 and S3, and stitch together the full-section smoothness and longitudinal elevation of each road section according to the Beidou positioning information to calculate the International Smoothness Index (IRI) and longitudinal elevation of the full-section road, and automatically locate the road smoothness defects according to the IRI threshold.

2. The method for automatically measuring the overall road cross-section smoothness and longitudinal profile elevation according to claim 1, characterized in that, Step S1 is specifically implemented as follows: Step S1.1: Assemble the laser emitter, power supply, and telescopic support into a laser emitting platform; Step S1.2: Adjust the laser emitter so that the tilt sensor angle it includes is horizontal; Step S1.3: Turn on the laser emitter and generate a horizontal laser beam to serve as a baseline for measuring the smoothness of the entire road section.

3. The method for automatically measuring the overall road cross-section smoothness and longitudinal profile elevation according to claim 2, characterized in that, Step S2 is specifically implemented as follows: Step S2.1: Adjust the position of the target moving stage so that the laser long baseline spot is in the center area of ​​the laser target surface. Place stepped test blocks on the four single-point laser ranging modules. Correct the 3D high-precision surface scanning module based on the single-point laser ranging results. Correct the 0.01mm-level accuracy of the 3D high-precision surface scanning module. The calculation method is as follows: Elevation difference was obtained using stepped test blocks. Then the first Each single-point laser ranging module corresponds to the elevation difference measured. for: ； in, For the first The elevation measured by a single-point laser ranging module at the first position of the stepped test block. For the first The elevation measured by a single-point laser ranging module at the second position on the stepped test block, and the sub-millimeter-level 3D high-precision surface scanning module at the [missing information]. The elevation difference measured at the corresponding position by each single-point laser ranging module for: ； in, For sub-millimeter level 3D high-precision surface scanning modules in the first The elevation measured at the first position of the stepped test block corresponding to each single-point laser ranging module. For sub-millimeter level 3D high-precision surface scanning modules in the first The elevation measured at the second position of the stepped test block corresponding to each single-point laser ranging module is used to calculate the correction coefficient of the measurement value within a single area of ​​the 3D high-precision surface scanning module. for: ； For correction coefficient The measurement was performed a preset number of times, and the average value was taken as the final result for each region after processing with a one-dimensional Gaussian smoothing filter. The filtering function is: ； in, for The mean, for The variance; Step S2.2: Record the BeiDou positioning information corresponding to the starting position of the target traverse station. A color image of the laser target surface is acquired through a target imaging component. The image is then converted to grayscale based on the laser color gamut channel components. The OTSU algorithm is used for image segmentation, and the Canny operator is used for edge detection. Finally, the coordinates of the center point of the laser spot at the starting position of the laser baseline in the color image of the target surface are obtained using least squares ellipse fitting. Data was acquired from a sub-millimeter level 3D high-precision surface scanning module, and its RGB images were recorded. and corresponding depth data ,in, Based on the four areas where laser ranging is located After correction ; Step S2.3: Control the hub motor to rotate, and the target moving stage moves at a constant speed along the longitudinal section of the road. The hub motor encoder triggers the 3D high-precision surface scanning module at preset intervals to collect data and obtain sequence image data. , and the coordinates of the center point of the laser target spot .

4. The method for automatically measuring the overall road cross-section smoothness and longitudinal profile elevation according to claim 3, characterized in that, Step S3 is specifically implemented as follows: Step S3.1: Obtained using a 3D high-precision surface scanning module Data and During image feature matching, the SIFT operator is used for feature point extraction. After matching, the feature points are determined based on the matching positions. and By splicing the sections together, the overall cross-sectional flatness of a certain road segment can be obtained; Step S3.2: Record the coordinates of the center point of the laser target spot at the end of a certain road segment. By using the coordinates of the center point of the light spot at the starting point position... The longitudinal profile elevation of a certain road segment is calculated; Step S3.3: Record the BeiDou positioning information of the target mobile station at the end of a certain road segment. .

5. The method for automatically measuring the overall road cross-section smoothness and longitudinal profile elevation according to claim 4, characterized in that, Step S4 is specifically implemented as follows: Step S4.1: Move the laser emitter and update the BeiDou positioning information corresponding to the starting position of the target point moving station. Coordinates of the center point of the light spot at the starting point Data from the 3D high-precision surface scanning module and ; Step S4.2: Repeat steps S2.3 to S3.3 until the road inspection endpoint is reached, and calculate the overall road cross-section smoothness and longitudinal profile elevation; Step S4.3: Calculate the smoothness index using the measured smoothness data of the entire road section according to the International Roughness Index (IRI) calculation formula, and automatically locate the road smoothness defects based on the IRI threshold.

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