Method for identifying and detecting waterlogged road section based on three-dimensional elevation data

Abstract

The invention discloses a waterlogged road section identification and detection method based on three-dimensional elevation data, and the method comprises the steps: scanning the surface three-dimensional elevation of an asphalt pavement through pavement identification equipment, and obtaining a pavement elevation data set; dividing the asphalt pavement into a plurality of evaluation units along the driving direction, and respectively calculating the minimum value and the average value of the pavement elevation of the left side line and the right side line of each evaluation unit; determining a drainage sideline of each evaluation unit; retrieving the pavement elevation data set to determine the minimum value of the evaluation unit to obtain the lowest point elevation beta; calculating a water accumulation risk point in the sideline of each evaluation unit in the asphalt pavement; calculating the pavement ponding condition in the evaluation unit, and if the total ponding area S is abnormal or the total number of adjacent ponding risk points is abnormal, determining that a ponding area exists in the evaluation unit; if the water accumulation problem exists in the position of the evaluation unit, the problem should be treated. The test method provided by the invention can quantitatively determine the road surface ponding road section, provides a scientific basis for the identification and treatment decision of the road surface ponding road section, and can scientifically and quantitatively determine the road surface ponding road section.

Description

Technical Field

[0001] The present invention relates to the field of road engineering, and in particular to a method for identifying and detecting flooded road sections based on three-dimensional elevation data. Background Art

[0002] When a car travels on a highway, it relies primarily on friction between the tires and the road surface. When a car brakes, friction between the tires and the road surface is a significant factor affecting stopping distance. However, due to factors such as construction and road surface alignment, some roads may experience water accumulation, significantly impacting driving safety.

[0003] With the increasing emphasis on highway safety, it is essential to treat flooded sections of roads in order to improve driving safety. This has also become a consensus in engineering practice. Therefore, it is necessary to identify flooded sections of roads in order to determine the treatment sections.

[0004] However, there is currently a lack of effective and scientific methods for identifying flooded sections of road. In engineering practice, manual inspections of waterlogged areas after heavy rain are often used. This method is subject to interference from weather and personnel, and its accuracy and effectiveness are subject to significant controversy. Therefore, there is an urgent need to develop a method for identifying and detecting flooded sections on asphalt roads that can provide scientific data, effectively and accurately identify flooded sections, and provide a scientific basis for determining these areas. Summary of the Invention

[0005] In response to the above problems, the present invention aims to provide a method for identifying and detecting flooded road sections based on three-dimensional elevation data.

[0006] To achieve this technical objective, the present invention provides a method for identifying and detecting flooded road sections based on three-dimensional elevation data, with the following specific steps:

[0007] S1. Scan the surface three-dimensional elevation α of the asphalt pavement with the interval a and accuracy b through the pavement recognition equipment. ij , obtain the road elevation dataset;

[0008] S2, the asphalt pavement is divided into several evaluation units along the driving direction, the segmentation spacing c, respectively, calculate the minimum and average pavement elevations of the left and right sidelines of each evaluation unit, the average elevation of the first sideline of the evaluation unit is recorded as γ1, the average elevation of the second sideline of the evaluation unit is recorded as γ2;

[0009] S3. Determine the drainage edge of each evaluation unit. If γ1<γ2, the first edge is the drainage edge of the evaluation unit; if γ1>γ2, the second edge is the drainage edge of the evaluation unit.

[0010] S4, searching the road elevation data set to determine the minimum value of the evaluation unit to obtain the lowest point elevation β;

[0011] S5. Calculate the water risk points within the edge of each evaluation unit in the asphalt pavement. If the α ij ≤β, it is considered that there is a waterlogging risk point in the assessment unit;

[0012] S6. Calculate the road waterlogging situation within the evaluation unit. If the total waterlogged area S is abnormal, or the total number of adjacent waterlogging risk points is abnormal, it is considered that there is a waterlogging area within the evaluation unit; that is, there is a waterlogging problem at the location of the evaluation unit and it should be treated.

[0013] As a preference, in step S1, 1≤i≤m, 1≤j≤n, where m is the number of points taken in the transverse direction of the road surface, and n is the number of points taken in the driving direction of the road surface; i=road width / interval a, j=road length / interval a; the road elevation dataset is [α 11 , α mn ];

[0014] The road surface recognition equipment is a 3D point cloud device with an accuracy of 1.0mm; the adjacent surface 3D elevation α ij The minimum interval c between them is less than or equal to 10 cm.

[0015] Preferably, in step S3, if γ1=γ2, a new segmentation spacing c should be selected, the evaluation units should be re-segmented, and the road surface drainage edge should be recalculated.

[0016] Preferably, the value range of the segmentation spacing c is 5-100m;

[0017] When the asphalt pavement is a normal cross-slope section, the division spacing c of each evaluation unit is selected as 100m; when the asphalt pavement is a cross-slope changing section, the division spacing c of each evaluation unit is selected as 5m.

[0018] As a preference, in step S4, the first edge line of the evaluation unit [α 1k ,α 1（k+d） ]、Second edge line [α mj ,α m（k+d） ], so the lowest point elevation β=min[α 1k ,α 1（k+d） ]or min[α mj ,α m（k+d） ].

[0019] As a preference, in step S5, the unit edge [α 21 , α m-1、n ] to screen out waterlogging risk points from the data set.

[0020] Preferably, in step S6, if the total waterlogged area S is greater than a preset value, the total waterlogged area S is considered abnormal; if the number of adjacent and mutually contacting waterlogged risk points within the evaluation unit is greater than or equal to 4, the total number of adjacent waterlogged risk points is considered abnormal.

[0021] As a preference, when α ij When -max[γ1,γ2] is greater than the threshold, it indicates that there is a protruding foreign object at the position of the point.

[0022] The beneficial effects of the present invention are as follows: the method of the present invention obtains three-dimensional elevation data of the road surface through a three-dimensional point cloud device and can analyze and process to discover abnormal areas. At the same time, the method can quantitatively determine the sections of road surface with waterlogging, provide a scientific basis for the identification and treatment decisions of sections of road surface with waterlogging, and can scientifically and quantitatively determine the sections of road surface with waterlogging; it can discover abnormal areas in advance before rainfall, and provide data guidance for the daily maintenance of roads. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is the elevation data table of the present invention;

[0024] Figure 2 Schematic diagram of the present invention. DETAILED DESCRIPTION

[0025] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0026] like Figure 1 As shown, the specific embodiment of the present invention is a method for identifying and detecting flooded road sections based on three-dimensional elevation data, and the specific steps are as follows:

[0027] S101, using road surface recognition equipment to scan the surface three-dimensional elevation α of the asphalt road surface at interval a and accuracy b ij , obtain the road elevation dataset; 1≤i≤m, 1≤j≤n, where m is the number of points taken in the transverse direction of the road, and n is the number of points taken in the driving direction of the road; i=road width / interval a, j=road length / interval a; the road elevation dataset is [α 11 , α mn ];

[0028] The road surface recognition equipment is a 3D point cloud device with an accuracy of 1.0mm; the adjacent surface 3D elevation α ij The minimum interval c between them is less than or equal to 10 cm.

[0029] S102: Divide the asphalt pavement into a plurality of evaluation units along the driving direction, with a division spacing of c. Calculate the minimum and average pavement elevations for the left and right sidelines of each evaluation unit. Record the average elevation of the first sideline of the evaluation unit as γ1, and the average elevation of the second sideline of the evaluation unit as γ2. The division spacing c ranges from 5 to 100 m.

[0030] When the asphalt pavement is a normal cross-slope section, the division spacing c of each evaluation unit is selected as 100m; when the asphalt pavement is a cross-slope changing section, the division spacing c of each evaluation unit is selected as 5m.

[0031] S103. Determine the drainage edge of each evaluation unit. If γ1<γ2, the first edge is the drainage edge of the evaluation unit; if γ1>γ2, the second edge is the drainage edge of the evaluation unit; if γ1=γ2, a new segmentation spacing c should be selected, the evaluation unit should be re-split and selected, and the road surface drainage edge should be recalculated.

[0032] S104, search the road elevation data set to determine the minimum value of the evaluation unit to obtain the lowest point elevation β; [α 1k ,α 1（k+d） ]、Second edge line [α mj ,α m（k+d） ], so the lowest point elevation β=min[α 1k ,α 1（k+d） ]or min[α mj ,α m（k+d） ].

[0033] S105, calculate the water risk point within each evaluation unit edge in the asphalt pavement. If the α ij ≤β, it is considered that there is a waterlogging risk point in the evaluation unit; within the unit edge [α 21 , α m-1、n ] to screen out waterlogging risk points from the data set.

[0034] S106. Calculate the road surface waterlogging situation within the assessment unit. If the total waterlogging area S is abnormal, or the total number of adjacent waterlogging risk points is abnormal, it is considered that there is a waterlogging area within the assessment unit; that is, there is a waterlogging problem at the location of the assessment unit and treatment should be carried out. Each waterlogging risk point is calculated as 0.01m 2 Calculation, default value = 0.06m 2 If the total water accumulation area S is greater than 0.06m 2 When , the total waterlogging area S is considered abnormal; if the number of adjacent and contacting waterlogging risk points in the evaluation unit is greater than or equal to 4, the total number of adjacent waterlogging risk points is considered abnormal.

[0035] S107, when αij When -max[γ1,γ2] is greater than the threshold, it indicates that there is a protruding foreign object at the location.

[0036] Example 1

[0037] Identification and evaluation of a flooded road section on a certain highway. An elevation test was conducted on a section of a certain highway pavement, and the results are shown in the table. According to the table, there are many water risk points and water accumulation points on this highway pavement. First, the elevation of the road edge lines on both sides was determined. It can be determined that the left side is the drainage edge line. By comparing it with the elevation of the lowest point of the drainage marking line (1mm), a total of 7 risk water accumulation points were identified, of which 4 risk water accumulation points are adjacent, meeting the identification criteria for water accumulation points. Therefore, there is a water accumulation point on the road section. To ensure driving safety, it is recommended to deal with this section. See for details. Figure 1 Table 1: Elevation data of a certain road surface.

[0038] The testing method provided by the present invention can quantitatively determine road flooding sections, provide a scientific basis for road flooding section identification and treatment decision-making, and can scientifically and quantitatively determine road flooding sections.

[0039] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any minor modifications, equivalent replacements, and improvements made to the above embodiments based on the technical essence of the present invention shall be included in the scope of protection of the technical solution of the present invention.

Claims

1. A method for identifying and detecting flooded road sections based on three-dimensional elevation data, characterized in that: The specific steps are as follows: S1. Scan the surface three-dimensional elevation α of the asphalt pavement with the interval a and accuracy b through the pavement recognition equipment. ij , obtain the road elevation dataset; S2, the asphalt pavement is divided into several evaluation units along the driving direction, the segmentation spacing c, respectively, calculate the minimum and average pavement elevations of the left and right sidelines of each evaluation unit, the average elevation of the first sideline of the evaluation unit is recorded as γ1, the average elevation of the second sideline of the evaluation unit is recorded as γ2; S3. Determine the drainage edge of each evaluation unit. If γ1<γ2, the first edge is the drainage edge of the evaluation unit; if γ1>γ2, the second edge is the drainage edge of the evaluation unit. S4, searching the road elevation data set to determine the minimum value of the evaluation unit to obtain the lowest point elevation β; S5. Calculate the water risk points within the edge of each evaluation unit in the asphalt pavement. If the α ij ≤β, it is considered that there is a waterlogging risk point in the assessment unit; S6. Calculate the road waterlogging situation within the evaluation unit. If the total waterlogged area S is abnormal, or the total number of adjacent waterlogging risk points is abnormal, it is considered that there is a waterlogging area within the evaluation unit; that is, there is a waterlogging problem at the location of the evaluation unit and it should be treated.

2. The method for identifying and detecting flooded road sections based on three-dimensional elevation data according to claim 1, characterized in that: In step S1, 1≤i≤m, 1≤j≤n, where m is the number of points taken in the transverse direction of the road surface, and n is the number of points taken in the driving direction of the road surface; i = road surface width / interval a, j = road surface length / interval a; the road surface elevation dataset is [α 11 , α mn ]; The road surface recognition equipment is a three-dimensional point cloud device with an accuracy of 1.0mm; Adjacent surface 3D elevation α ij The minimum interval c between them is less than or equal to 10 cm.

3. The method for identifying and detecting flooded road sections based on three-dimensional elevation data according to claim 1, characterized in that: In step S3, if γ1=γ2, a new segmentation spacing c should be selected, the evaluation unit should be re-segmented, and the road surface drainage edge should be recalculated.

4. The method for identifying and detecting flooded road sections based on three-dimensional elevation data according to claim 1, characterized in that: Among them, the segmentation The value range of spacing c is 5-100m; When the asphalt pavement is a normal cross slope section, the segmentation interval c of each evaluation unit is selected as 100m; When the asphalt pavement has a cross-slope variation section, the segmentation spacing c of each evaluation unit is selected as 5m.

5. The method for identifying and detecting flooded road sections based on three-dimensional elevation data according to claim 2, characterized in that: In step S4, the first edge of the evaluation unit [α 1k ,α 1（k+d） ]、Second edge line [α mj ,α m（k+d） ], so the lowest point elevation β=min[α 1k ,α 1（k+d） ]or min[α mj ,α m（k+d） ].

6. The method for identifying and detecting flooded road sections based on three-dimensional elevation data according to claim 5, characterized in that: In step S5, the unit edge [α 21 , α m-1、n ] to screen out waterlogging risk points from the data set.

7. The method for identifying and detecting flooded road sections based on three-dimensional elevation data according to claim 6, characterized in that: In step S6, if the total waterlogging area S is greater than the preset value, the total waterlogging area S is considered abnormal; if the number of adjacent and contacting waterlogging risk points in the evaluation unit is greater than or equal to 4, the total number of adjacent waterlogging risk points is considered abnormal.

8. The method for identifying and detecting flooded road sections based on three-dimensional elevation data according to any one of claims 1 to 7, characterized in that: When α ij When -max[γ1,γ2] is greater than the threshold, it indicates that there is a protruding foreign object at the position of the point.

Images