A method for measuring road rut depth

Abstract

This invention belongs to the field of road rut depth measurement technology and discloses a method for measuring road rut depth. The method involves obtaining a scaling factor and installation deviation angle through experimental calibration; acquiring images, cropping images, preprocessing images, extracting the center line of the light stripe, and transforming coordinates to obtain a cross-sectional profile curve; calculating the envelope based on the coordinates of each point on the cross-sectional profile curve; calculating the rut depth separately for the left and right sides of the cross-section, and combining this with the calibrated installation deviation angle to obtain the rut depth. This method effectively solves the problem of accuracy loss in rut depth calculation results caused by angular errors during installation. Furthermore, this invention can simultaneously calculate the rut depth of the left and right wheel tracks, simplifying manual operation and meeting current industry standards. This invention is simple to implement, has higher accuracy, and meets application requirements.

Description

Technical Field

[0001] This invention relates to the field of road rut depth measurement technology, and in particular to a method for measuring road rut depth. Background Technology

[0002] After years of rapid development, my country's highway transportation network has continuously expanded, reaching a total mileage of 5.4368 million kilometers by the end of 2023. However, most of the roads built in the early stages have entered the middle and late stages of their life cycle, and the pressure on road maintenance is increasing year by year. The highway network has generally entered the maintenance phase, and China's road network is gradually shifting from large-scale new road construction to large-scale maintenance of existing roads. Research and engineering practice show that, from a life-cycle perspective, the proportion of highway maintenance investment in total highway investment will far exceed the investment made during the design and construction phases. Therefore, how to conduct efficient, economical, and timely maintenance and management of highway pavements to keep roads in good condition is of paramount importance for improving road lifespan, maintaining traffic efficiency, and saving maintenance costs.

[0003] Ruts are the tire marks left by vehicles on the road surface. Automated rut detection can be achieved using the following devices: (1) Beam-type multi-sensor: Multiple distance sensors on the same reference plane measure the relative elevation of different positions on the cross section, with no fewer than 13 sensors. (2) Scanning laser sensor: One or more laser emitters scan the road cross section at high speed to obtain continuous cross section curves. (3) Optical imaging: Data is acquired using a line laser emitter and a high-speed image acquisition device. The rut depth is determined by analyzing the light deformation.

[0004] The Chinese patent "CN117888429A A Road Rutting Anomaly Detection System and Method Based on Line Structured Light" describes a road rutting anomaly detection system and method based on line structured light, including a longitudinal ranging sensor, a two-dimensional line array camera, and a line structured light generator. The method includes acquiring road rutting data images, filtering out abnormal rutting from the road rutting data images according to a pre-set threshold, performing data verification on the abnormal rutting to obtain a data verification structure, and determining the evaluation model to which the road rutting data image belongs based on the data verification results. However, it does not provide a detailed description of the calibration of the rutting depth measurement equipment or the numerical calculation methods.

[0005] The solution described in Chinese patent "CN119129407A A method, device, system, and storage medium for predicting road rut depth" primarily trains a neural network model optimized based on a genetic algorithm to train on road rut data, thereby achieving the goal of predicting rut depth through rut depth data. This differs from the solution in this paper, which uses an envelope method to automatically calculate the rut depth of the left and right wheel tracks. Summary of the Invention

[0006] The purpose of this invention is to provide a method for measuring rut depth on road surfaces, which consists of two stages: calibration of the rut depth measuring equipment and numerical calculation of the rut depth. This method can reduce numerical calculation errors caused by errors during the installation of the measuring equipment, and can also solve the need for automatic calculation of rut depth in the left and right wheel tracks, meeting the relevant requirements of industry standards for rut depth measurement.

[0007] The technical solution of the present invention is as follows: a method for measuring road rut depth, comprising installing a road rut depth measuring device and obtaining the size scaling factor and installation deviation angle through experimental calibration;

[0008] Acquire images; adjust the exposure mode of the industrial camera to "automatic exposure" and use hard triggering to take pictures and store the images;

[0009] Image cropping; cropping the image based on the "region of interest" result;

[0010] Image preprocessing; binarization and morphological processing of the cropped image;

[0011] Extract the center line of the light stripe; traverse column by column to extract the range of the light stripe and calculate the row number where the center line of the light stripe is located;

[0012] Coordinate transformation: Based on the center pixel value of the light stripe, camera intrinsic parameters, the "size scaling factor" obtained from calibration, and the "laser triangulation" formula, coordinate transformation is performed to obtain the road cross-section profile curve;

[0013] Envelope calculation: Calculate the envelope line based on the coordinates of each point on the road cross-section profile curve.

[0014] The rut depth is calculated by performing calculations on the left and right sides of the road cross section based on a set center threshold, and then combining the calibrated installation deviation angle to obtain the rut depth.

[0015] The road rut depth measuring equipment includes a red light laser, a red light filter, a near-infrared enhanced industrial camera, and matching cables;

[0016] A red light filter is mounted on the surface of the lens of a near-infrared enhanced industrial camera. CAM represents the near-infrared enhanced industrial camera, LAS is the red light laser, A is the intersection of the optical axis of the red light laser and the optical axis of the near-infrared enhanced industrial camera, the horizontal plane containing the intersection of the optical axis of the near-infrared enhanced industrial camera and the red light laser is the reference plane, O is the position of the near-infrared enhanced industrial camera lens, H is the height of the near-infrared enhanced industrial camera lens from the reference plane, β is the angle between the near-infrared enhanced industrial camera and the reference plane, and α is the angle between the red light laser and the reference plane.

[0017] For a point C on the ground, draw a perpendicular line from that point to the reference plane, with the foot of the perpendicular at B. h is the distance between the point and the reference plane; x is the offset dimension of point C in the image plane; f is the camera focal length; k is the conversion factor; and p is the offset pixel of point C in the image plane.

[0018] The relationship between ground deformation and changes in camera imaging pixel position can be obtained using the following formula;

[0019]

[0020] The method for calculating the size scaling factor is as follows:

[0021] Step A. Extract the rut plate region from the rut plate image;

[0022] Step B. Image cropping; the cropped image ensures that the rutted slab is within the smallest bounding rectangle of the cropped image area;

[0023] Step C. Measure the corresponding pixels of the highest and lowest areas of the rutted surface based on the cropped image;

[0024] Step D. Substitute Perform calculations;

[0025] Step E. Calculate the distance between the point obtained in Step D and the baseline surface, and the true depth h of the rut. real The quotient between the two values ​​is used to calculate the size scaling factor k′;

[0026]

[0027] h1 represents the distance between the point calculated in step D of the i-th experiment and the baseline surface, where i is an integer from 1 to n.

[0028] The method for calculating the calibrated installation deviation angle is as follows:

[0029] Step A. Extract the laser line region from the still image;

[0030] Step B. Measure the row and column pixels at the leftmost and rightmost ends of the laser line area;

[0031] Step C. Calculate the x and y coordinates of the leftmost and rightmost pixels of the laser line; the x coordinates are obtained by measurement, and the y coordinates are calculated using the laser triangulation formula.

[0032] Step D. Calculate the calibrated installation deviation angle using the angle calculation formula;

[0033]

[0034] Where angle represents the calibrated installation deviation angle; x represents the horizontal coordinate of the pixel, y represents the vertical coordinate of the pixel, and the left and right points are distinguished by different indices left and right.

[0035] The static image is an image of a level ground without significant undulations; the rut image is obtained by capturing images with a near-infrared enhanced industrial camera. During the capture process, the laser line must pass through the horizontal areas at both ends and the concave area in the middle of the rut to ensure the accuracy of the reference values. Several images of the rut are captured repeatedly to avoid the influence of random errors. The rut used in the calibration process is a self-made experimental material with horizontal ends and a concave middle, used to simulate the shape of actual ruts.

[0036] The region of interest is calculated as follows: based on the 80mm standard measurement of the rut board, the upper and lower boundary ranges of the red laser line within the imaging area are calculated, and the region of interest for subsequent image cropping is based on this boundary range.

[0037] The calculation of the rut depth is as follows:

[0038] 1) Traverse the endpoints of the envelope point by point, and set the first point as the segment start point. p The next point is set as the end point of the segment. p ;

[0039] 2) Calculate the distance between the starting point and the ending point of the segment. envelope ;

[0040]

[0041] 3) Calculate the angle between the line segment formed by the starting and ending points of the segment and the horizontal direction. envelope ;

[0042] 4) Traverse every point on the center line of the light stripe between the start and end points of the segment, and perform the following calculations:

[0043] 4.1) Calculate the value md at this point. p The area of ​​the parallelogram formed by the cross product of the vectors formed by the starting and ending points of the segment is given by the following formula:

[0044]

[0045] 4.2) Calculate point md p perpendicular distance to the envelope vertical ;

[0046] distance vertical =cross / distanceenvelope

[0047] 4.2) Calculate point md p Vertical distance to the envelope upright Considering the calibrated installation error angle, ensure that the direction of rut depth calculation is perpendicular to the road.

[0048] distance upright =distance vertical / cos(angle envelope -angle)

[0049] 4.3) Calculate the vertical distance from the center line of the light stripe to the envelope at each point between the start and end points of the segment until the maximum distance is found, which is taken as the rut depth of the segment.

[0050] The beneficial effects of this invention are as follows: This invention proposes equipment installation deviation angles and dimensional scaling factors. By calibrating the angular deviations existing during equipment installation and the dimensional scaling factors involved in the formula calculation, the installation deviation angles and dimensional scaling factors can be easily solved, improving the measurement accuracy of rut depth. Simultaneously, through a piecewise solution algorithm based on envelope lines, combined with equipment installation error angle parameters, the rut depths of the left and right wheel tracks can be calculated simultaneously, better meeting industry standard requirements and application needs.

[0051] For data acquisition equipment that requires separate installation of cameras and laser lines, the method described in this invention can effectively solve the problem of accuracy loss in rut depth calculation results caused by angular errors during installation. Simultaneously, this invention can calculate the rut depth of both left and right wheel tracks, simplifying manual operation and meeting current industry standards. This invention is simple to implement, offers higher accuracy, and meets application requirements. Attached Figure Description

[0052] Figure 1 Schematic diagram of the installation of road rut depth measuring equipment;

[0053] Figure 2 A flowchart of the calibration process;

[0054] Figure 3 This is a flowchart of the numerical calculation process for rut depth.

[0055] Figure 4 This is a static image illustration.

[0056] Figure 5 This is a schematic diagram of an image containing ruts.

[0057] Figure 6 This is the effect of image binarization.

[0058] Figure 7 To achieve the desired effect after morphological processing, a kernel size of (5,5) was selected.

[0059] Figure 8 Extracting the effect from the center of the light stripe.

[0060] Figure 9 This is the result after coordinate transformation.

[0061] Figure 10 This is a diagram illustrating the architecture of the wheel rut measurement method. Detailed Implementation

[0062] A method for measuring road rut depth involves installing a road rut depth measuring device and obtaining the size scaling factor and installation deviation angle through experimental calibration.

[0063] Acquire images; adjust the exposure mode of the industrial camera to "automatic exposure" and use hard triggering to take pictures and store the images;

[0064] Image cropping; cropping the image based on the "region of interest" result;

[0065] Image preprocessing; binarization and morphological processing of the cropped image;

[0066] Extract the center line of the light stripe; traverse column by column to extract the range of the light stripe and calculate the row number where the center line of the light stripe is located;

[0067] Coordinate transformation: Based on the center pixel value of the light stripe, camera intrinsic parameters, the "size scaling factor" obtained from calibration, and the "laser triangulation" formula, coordinate transformation is performed to obtain the cross-sectional profile curve;

[0068] Envelope calculation: Calculate the envelope line based on the coordinates of each point on the cross-sectional profile curve.

[0069] The rut depth is calculated by performing calculations on the left and right sides of the cross section based on a set center threshold, and then combining the calibrated installation deviation angle to obtain the rut depth.

[0070] Furthermore, the method for measuring road rut depth mentioned in this invention employs an "optical imaging" method, based on the "laser triangulation" principle. The measuring equipment consists of a red laser line, a near-infrared enhanced industrial camera, a lens, and matching cables.

[0071] Figure 1 The diagram shows the installation of the road rut depth measuring device of the present invention.

[0072] CAM stands for Near Infrared Enhanced Industrial Camera, LAS stands for Red Line Laser, A is the intersection of the optical axis of the line laser and the optical axis of the near infrared enhanced industrial camera, the horizontal plane containing the intersection of the optical axis of the near infrared enhanced industrial camera and the line laser is the reference plane, O is the position of the lens of the near infrared enhanced industrial camera, H is the height of the lens of the near infrared enhanced industrial camera from the reference plane, β is the angle between the near infrared enhanced industrial camera and the reference plane, and α is the angle between the line laser and the reference plane.

[0073] For a point C on the ground, draw a perpendicular line from that point to the reference line, with the foot of the perpendicular at B. Let h be the distance between point C and the reference plane. Let x be the offset dimension of point C in the image plane, f be the camera focal length, k be the conversion factor, and p be the offset pixels of point C in the image plane.

[0074] The relationship between ground deformation and changes in camera image pixel position can be obtained using the following formula.

[0075]

[0076] Figure 2 This is a flowchart illustrating the calibration process for the rut depth measuring device in this invention. This calibration process allows for the determination of the calibrated size scaling factor. It also resolves the issue of non-horizontal line laser imaging caused by angular errors during installation.

[0077] 1) Step 1: Image Acquisition. This part includes acquiring still images and rut slab images.

[0078] A still image refers to an image obtained by photographing a level ground with no significant undulations; such as Figure 4 As shown,

[0079] A rut board is a self-made experimental material used in experiments. It is horizontal at both ends and concave in the middle to simulate the shape of actual ruts.

[0080] During the image capture process of the rut slab, the laser line must pass through the horizontal areas at both ends and the concave area in the middle of the rut slab to ensure the accuracy of the baseline values. Ten images should be captured repeatedly to avoid the influence of random errors. Figure 5 As shown;

[0081] 2) Step Two: Calculate the coefficients. This part includes calculating the size scaling factor (based on the rut slab image) and the installation deviation angle (based on the static image);

[0082] 2.1) The scaling factor is calculated as follows: A. Extract the rut area from the rut image. B. Image cropping. C. Measure the corresponding pixels of the highest (horizontal) and lowest (bottom of the groove) areas of the rut in the cropped image. D. Substitute... Perform the calculation. E. Calculate the quotient between the distance between the point obtained in step D and the baseline surface and the actual depth of the rut slab, and calculate the size scaling factor k′; such as Figure 6 As shown;

[0083]

[0084] 2.2) The installation deviation angle is calculated as follows: A. Extract the laser line area from the static image. B. Measure the row and column pixels at the leftmost and rightmost ends of the laser line area. C. Calculate the x and y coordinates of the leftmost and rightmost pixels of the laser line. The x-coordinate is obtained through measurement, and the y-coordinate is calculated using the laser triangulation formula. D. Calculate using the angle calculation formula.

[0085]

[0086] Here, angle represents the installation deviation angle. x represents the horizontal coordinate of the pixel, y represents the vertical coordinate of the pixel, and left and right coordinates are used to distinguish between the two points.

[0087] The region of interest is calculated as follows: the upper and lower boundaries of the laser line within the imaging area are calculated based on the 80mm standard measurement of the rut plate, and this range is used as the region of interest for subsequent image cropping.

[0088] Figure 3 This is a flowchart of the numerical calculation of rut depth in the technical solution of this invention; as shown. Figure 6 — Figure 9 As shown;

[0089] Step 1: Image Acquisition. Set the industrial camera's exposure mode to "auto exposure" and use hard triggering to take and store the image.

[0090] Step 2: Image cropping. Based on the obtained "region of interest" result, crop the image.

[0091] Step 3: Image preprocessing. The image undergoes binarization and morphological processing.

[0092] Step 4: Extract the center line of the light stripe. Traverse each column to extract the range of the light stripe and calculate the row number where the center line is located.

[0093] Step 5: Coordinate Transformation. Based on the center pixel value of the light stripe, camera intrinsic parameters, the "size scaling factor" obtained from calibration, and the "laser triangulation" formula, coordinate transformation is performed to obtain the cross-sectional profile curve.

[0094] Step Six: Envelope Calculation. Calculate the envelope line based on the coordinates of each point on the cross-sectional profile curve.

[0095] Step 7: Rut Depth Calculation. Based on the set center threshold, perform the following calculations for the left and right sides of the cross-section respectively:

[0096] 7.1) Traverse the endpoints of the envelope point by point. Set the first point as the segment start point. p The next point is set as the end point of the segment. p ).

[0097] 7.2) Calculate the distance between the starting point and the ending point of the segment. envelope );

[0098] 7.3) Calculate the angle between the starting point and the ending point of the segment. envelope );

[0099] 7.4) Traverse every point on the centerline of the light stripe between the start and end points of the segment, and perform the following calculations:

[0100] 7.5) Calculate the point (md) p The cross product of the vectors formed by the starting and ending points of the segment is the area of ​​the parallelogram formed by these two vectors, as shown in the following formula:

[0101]

[0102] 7.6) Calculate point md p perpendicular distance to the envelope vertical ).

[0103] distance vertical =cross / distance envelope

[0104] 7.7) Calculate point md p Vertical distance to the envelope upright This part needs to take into account the installation error angle obtained from the calibration to ensure that the direction of the rut depth calculation is perpendicular to the road.

[0105] distance upright =distance vertical / cos(angle envelope -angle)

[0106] 7.8) Calculate the vertical distance from the center line of the light stripe to the envelope at each point between the start and end points of the segment until the maximum distance is found, and use this distance as the rut depth of the segment.

Claims

1. A method for measuring the depth of road ruts, characterized in that, Install road rut depth measuring equipment and obtain the size scaling factor and installation deviation angle through experimental calibration; Acquire images; adjust the exposure mode of the industrial camera to "auto exposure" and use hard triggering to take pictures and store the images; Image cropping; cropping the image based on the "region of interest" result; Image preprocessing; Binarize and perform morphological processing on the cropped image; Extract the center line of the light stripe; traverse column by column to extract the range of the light stripe and calculate the row number where the center line of the light stripe is located; Coordinate transformation: Based on the center pixel value of the light stripe, camera intrinsic parameters, the "size scaling factor" obtained from calibration, and the "laser triangulation" formula, coordinate transformation is performed to obtain the road cross-section profile curve; Envelope calculation: Calculate the envelope line based on the coordinates of each point on the road cross-section profile curve. Rut depth calculation: Based on the set center threshold, the rut depth is calculated separately for the left and right sides of the road cross section, and combined with the calibrated installation deviation angle to obtain the rut depth. The road rut depth measuring equipment includes a red light laser, a red light filter, a near-infrared enhanced industrial camera, and matching cables; A red light filter is mounted on the surface of the lens of a near-infrared enhanced industrial camera. CAM represents the near-infrared enhanced industrial camera, LAS is the red light laser, A is the intersection of the optical axis of the red light laser and the optical axis of the near-infrared enhanced industrial camera, the horizontal plane containing the intersection of the optical axis of the near-infrared enhanced industrial camera and the red light laser is the reference plane, O is the position of the near-infrared enhanced industrial camera lens, H is the height of the near-infrared enhanced industrial camera lens from the reference plane, β is the angle between the near-infrared enhanced industrial camera and the reference plane, and α is the angle between the red light laser and the reference plane. For a point C on the ground, draw a perpendicular line from that point to the reference plane, with the foot of the perpendicular at B. h is the distance between the point and the reference plane; x is the offset dimension of point C in the image plane; f is the camera focal length; k is the conversion factor; and p is the offset pixel of point C in the image plane. The relationship between ground deformation and changes in camera imaging pixel position can be obtained using the following formula; The method for calculating the calibrated installation deviation angle is as follows: Step A. Extract the laser line region from the still image; Step B. Measure the row and column pixels at the leftmost and rightmost ends of the laser line area; Step C. Calculate the x and y coordinates of the leftmost and rightmost pixels of the laser line; the x coordinates are obtained by measurement, and the y coordinates are calculated using the laser triangulation formula. Step D. Calculate the calibrated installation deviation angle using the angle calculation formula; Where angle represents the calibrated installation deviation angle; x represents the horizontal coordinate of the pixel, y represents the vertical coordinate of the pixel, and the left and right points are distinguished by different indices left and right.

2. The method for measuring road rut depth according to claim 1, characterized in that, The method for calculating the size scaling factor is as follows: Step A. Extract the rut plate region from the rut plate image; Step B. Image cropping; the cropped image ensures that the rutted slab is within the smallest bounding rectangle of the cropped image area; Step C. Measure the corresponding pixels of the highest and lowest areas of the rutted surface based on the cropped image; Step D. Substitute Perform calculations; Step E. Calculate the distance between the point obtained in Step D and the baseline surface, and the true depth h of the rut. real The quotient between the two values ​​is used to calculate the size scaling factor k′; h1 represents the distance between the point calculated in step D of the i-th experiment and the baseline surface, where i is an integer from 1 to n.

3. The method for measuring road rut depth according to claim 1, characterized in that, The static image is an image of a level ground without significant undulations; the rut image is obtained by capturing images with a near-infrared enhanced industrial camera. During the capture process, the laser line must pass through the horizontal areas at both ends and the concave area in the middle of the rut to ensure the accuracy of the reference values. Several images of the rut are captured repeatedly to avoid the influence of random errors. The rut used in the calibration process is a self-made experimental material with horizontal ends and a concave middle, used to simulate the shape of actual ruts.

4. The method for measuring road rut depth according to claim 1, characterized in that, The region of interest is calculated as follows: based on the 80mm standard measurement of the rut board, the upper and lower boundary ranges of the red laser line within the imaging area are calculated, and the region of interest for subsequent image cropping is based on this boundary range.

5. The method for measuring road rut depth according to claim 1, characterized in that, The calculation of the rut depth is as follows: 1) Traverse the endpoints of the envelope point by point, and set the first point as the segment start point. p The next point is set as the end point of the segment. p ; 2) Calculate the distance between the starting point and the ending point of the segment. envelope ; 3) Calculate the angle between the line segment formed by the starting and ending points of the segment and the horizontal direction. envelope ; 4) Traverse every point on the center line of the light stripe between the start and end points of the segment, and perform the following calculations: 4.1) Calculate the value md at this point. p The area of ​​the parallelogram formed by the cross product of the vectors formed by the starting and ending points of the segment is given by the following formula: 4.2) Calculate point md p perpendicular distance to the envelope vertical ; distance vertical =cross / distance envelope 4.2) Calculate point md p Vertical distance to the envelope upright Considering the calibrated installation error angle, ensure that the direction of rut depth calculation is perpendicular to the road. distance upright =distance vertical / cos(angle envelope -angle) 4.3) Calculate the vertical distance from the center line of the light stripe to the envelope at each point between the start and end points of the segment until the maximum distance is found, which is taken as the rut depth of the segment.

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