Road surface condition index generation system and generation method

Abstract

This invention discloses a pavement condition index (PCI) generation system and method, belonging to the field of road engineering technology. The system includes a DXF graphic preprocessing module, a centerline identification and definition module, a layer identification and defect extraction module, an automatic defect mapping module, a dynamic segmentation module for statistical range, and a PCI calculation and export module. It can preprocess original inspection drawings to form a DXF format file containing a centerline layer, a pavement edge layer, and a defect layer; establish a centerline model; form a defect basic database; establish a mapping relationship with specified standards; automatically divide road segments according to selected station numbers; fuse data with defect data; and then calculate the PCI value. The pavement condition index generation system and method provided by this invention have the advantages of high work efficiency, simplified procedures and convenient control, and flexible data processing.

Description

Technical Field

[0001] This invention relates to a road surface condition index generation system and method, belonging to the field of road engineering technology. Background Technology

[0002] In the design process of road maintenance projects, the Pavement Condition Index (PCI) is needed to provide a basis for maintenance plans. Currently, the statistical process for PCI typically involves manually dividing road sections on CAD drawings using measurement data, collecting data on different defects, and finally manually calculating the PCI index. This entire manual process is highly repetitive and wastes a significant amount of time and energy for engineering technicians, resulting in high labor and time costs.

[0003] The process of segmenting road sections, statistically analyzing road defects, and calculating PCI indices urgently needs to be automated. Summary of the Invention

[0004] To address the problems of cumbersome and inefficient acquisition of PCI indicators in existing technologies, this invention provides a road surface condition index generation system and method to solve the above problems.

[0005] To solve the above technical problems, the present invention includes the following technical solutions:

[0006] A road surface condition index generation system, comprising:

[0007] The DXF graphic preprocessing module is used to set the road centerline, the scope of the defect detection, and the defect graphics in the original inspection drawings as independent layers, forming a centerline layer, a road edge layer, and a defect layer, and saves the converted drawings in DXF format.

[0008] The centerline identification and definition module generates a centerline model based on the centerline layer. The centerline in the centerline model is a continuous, directional line that includes the start point, end point, total length, and initial station number.

[0009] The layer recognition and disease extraction module has a preset standard disease type name. By traversing the disease layer information, it performs text feature-based matching analysis between the standard disease type name and the layer name, calculates the geometric attributes of the disease type, and stores the disease layer name, disease graphics, geometric attributes, and station number in a structured manner to form a basic disease database.

[0010] The automatic disease mapping module can establish a mapping relationship between the disease names in the standard selected by the user and the data in the basic disease database.

[0011] The statistical range dynamic segmentation module can segment the road surface based on the station number input by the user to form road segment segments, calculate the area of ​​each road segment segment, and assign the disease data in the disease base database to the corresponding road segment segment according to the corresponding station number.

[0012] The PCI calculation and export module can automatically calculate the pavement condition index (PCI) of each road segment based on the road segmentation results, the selected road technical condition assessment standards, and the established mapping relationship, and generate a PCI evaluation table.

[0013] The present invention also provides a method for generating a road condition index using the aforementioned road condition index generation system, comprising the following steps:

[0014] Step 1: Obtain the original inspection drawings. The DXF graphic preprocessing module sets the road centerline, the scope of the defect detection, and the defect graphics as independent layers, forming a centerline layer, a road edge layer, and a defect layer, and saves them as DXF format graphic files.

[0015] Step 2: The centerline identification and definition module generates a centerline model based on the centerline layer;

[0016] Step 3: The layer recognition and disease extraction module traverses the disease layer information, performs text feature-based matching analysis between the standard disease type name and the layer name, calculates the geometric attributes of the disease type, and stores the disease layer name, disease graphics, geometric attributes, and station number in a structured manner to form a basic disease database.

[0017] Step 4: The automatic disease mapping module establishes a mapping relationship between the disease names in the standard selected by the user and the data in the basic disease database.

[0018] Step 5: The dynamic segmentation module of the statistical scope divides the road surface into segments based on the station number input by the user, calculates the area of ​​each segment, and assigns the defect data in the defect database to the corresponding segment according to the corresponding station number.

[0019] Step Six: The PCI Calculation and Export module automatically calculates the pavement condition index (PCI) for each road segment based on the road segmentation results, the user-selected standards, and the established mapping relationships, and generates a PCI evaluation table.

[0020] Furthermore, the specific workflow of the centerline identification and definition module in step two includes the following steps:

[0021] Call DXF format graphics files;

[0022] Read the geometric elements of the centerline layer;

[0023] Analyze the connection relationships and order between the geometric elements;

[0024] Construct a digital centerline model with continuous, directional lines;

[0025] Calculate the starting point coordinates, ending point coordinates, and total length of the centerline model;

[0026] The user determines the starting station number value;

[0027] The centerline parameters are stored in a structured manner.

[0028] Furthermore, in step three, the specific workflow of the layer recognition and disease extraction module includes:

[0029] Call DXF format graphics files;

[0030] Read all layer names;

[0031] Output layer list;

[0032] The standard disease type name is matched with the layer name in the layer list based on text features to find the corresponding disease layer.

[0033] Extract geometric elements from the disease layer;

[0034] Calculate the geometric properties of geometric elements;

[0035] Calculate the station number of the element by extracting the vertex coordinates of the element;

[0036] The data is stored in a structured manner according to the format of layer, geometric attribute, station number, and coordinate.

[0037] Because the present invention employs the above technical solution, it has the following advantages and positive effects compared with the existing method of manually counting diseases and calculating PCI:

[0038] (1) High work efficiency. This method uses a program to read and process DXF graphics. Only the DXF graphics need to be processed in a certain format to quickly complete disease statistics, PCI evaluation and table generation. The work efficiency is high, and the workload of normal manual statistics can be completed in two minutes.

[0039] (2) Simplified process and convenient control. The work that was originally scattered in multiple stages such as CAD operation, data sorting, and table calculation is integrated into one system, which simplifies the overall operation process.

[0040] (3) Flexible data processing. The algorithm accurately identifies and defines the road centerline and collects the corresponding station numbers of all defects. By inputting different segment station numbers, the system can automatically re-segment, calculate the area, and evaluate PCI. This realizes the dynamic adjustment of the statistical range and the need for rapid response analysis, without the need for tedious manual statistics and calculations. Attached Figure Description

[0041] Figure 1 This is a flowchart of a road surface condition index generation method according to an embodiment of the present invention;

[0042] Figure 2 This is a flowchart of the centerline identification and definition module in one embodiment of the present invention;

[0043] Figure 3 This is a flowchart illustrating the workflow of the layer recognition and disease extraction module in one embodiment of the present invention.

[0044] Figure 4 This is a flowchart illustrating the automatic disease mapping module in one embodiment of the present invention.

[0045] Figure 5 This is a flowchart of the statistical range dynamic segmentation module in one embodiment of the present invention;

[0046] Figure 6 This is a flowchart illustrating the PCI calculation and export module in one embodiment of the present invention.

[0047] Figure 7 This is a schematic diagram of road segmentation in one embodiment of the present invention;

[0048] Figure 8 This is a PCI evaluation table in one embodiment of the present invention. Detailed Implementation

[0049] The road surface condition index generation system and method provided by the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer from the following description. It should be noted that the accompanying drawings are all in a very simplified form and use non-precise scales, and are only used to facilitate and clarify the illustration of the embodiments of the present invention.

[0050] Example 1

[0051] This embodiment provides a dynamic segmentation and statistical system for road defects based on DXF graphic data. DXF (Drawing Exchange Format) is a vector data file format used to enable data exchange between AutoCAD and other CAD software. The system includes a DXF graphic preprocessing module, a centerline identification and definition module, a layer identification and defect extraction module, an automatic defect mapping module, a dynamic segmentation module for statistical range, and a PCI calculation and export module.

[0052] The DXF image preprocessing module primarily transforms the original inspection drawings into a format easily processed by the system. The original inspection drawings are CAD drawings containing a plan view of road surface defects, including topographical data, road centerlines, defect detection areas, and defect graphics. The generation of the original inspection drawings can utilize existing technologies, which will not be elaborated upon here. The DXF image preprocessing module can identify or draw the road centerline, placing it on a separate layer and naming it the "Centerline Layer." It can also process the detection area into closed polylines, placing them on a separate layer and naming it the "Road Edge Line Layer." Furthermore, the DXF image preprocessing module can convert the processed CAD drawings into DXF format, for example, saving DWG format as DXF.

[0053] The centerline identification and definition module can call the DXF graphics file processed by the DXF graphics preprocessing module, identify all geometric elements (such as straight lines and arc segments) within the centerline layer, and automatically construct a continuous, directional digital centerline model by analyzing the connection relationships and order of these geometric elements. The digital centerline model accurately records the starting coordinates, ending coordinates, and total length of the centerline. Users can also select the physical starting point of the centerline (such as point A or point B on the graphic) as the logical starting point (station 0) for stationing calculation, and can set the initial stationing value for this logical starting point.

[0054] The layer recognition and defect extraction module has pre-defined standard defect type names, such as "linear cracks," "network cracks," and "ruts." This module can call DXF graphics files processed by the DXF graphics preprocessing module. By traversing all layer information in the DXF graphics file, it performs text feature-based matching analysis between the standard defect type names and the layer names. For example, by checking if the layer name contains defect type keywords or conforms to specific naming rules (such as "layer name-defect name"), the module automatically selects the layer representing different pavement defects. Users can also confirm or manually adjust based on the automatic matching results. The module then reads the geometric elements (closed or open polylines) in the user-selected defect layers. For each extracted defect geometric element, the system calculates its key geometric attributes, including length and / or area. Finally, the module structures and stores the extracted defect layer names, geometric attributes (length, area), station numbers, and geometric vertex coordinates to form a basic defect database for subsequent modules to access. As an example, area calculation prioritizes using the precise area data stored within the graphic element itself (such as extended data); if this is not available, it is calculated using a geometric filling algorithm. As another example, the layer recognition and disease extraction module, combined with the centerline defined in the digital centerline model, calculates the spatial position of each disease element relative to the starting point of the centerline, i.e., the station number.

[0055] The automatic disease mapping module can automatically establish a mapping relationship between disease types and graphic layers. Users can select evaluation standards, such as ministerial or local standards, and predefine disease type names based on the selected standards. The automatic disease mapping module can then perform text feature-based matching analysis between the predefined standard disease type names and disease layer names in the disease database. By checking whether the layer names contain disease type keywords or conform to specific naming rules (such as "layer name-disease name"), the system automatically recommends the most likely corresponding layer for each disease type. Users can confirm or manually adjust based on the automatic matching results to ultimately determine the mapping relationship from disease type to specific graphic layer. This mapping relationship will guide subsequent PCI calculations.

[0056] The dynamic segmentation module for the statistical range primarily uses user-input station numbers to dynamically and accurately segment the road detection range and calculate its area. Users can input one or more segment station numbers. The module first obtains closed polylines from the road edge layer, representing the total detection range or road area. Then, based on the digital centerline defined by the centerline recognition module, it generates a geometric cutting line perpendicular to the centerline at each user-specified segment station location. Using these cutting lines, the area represented by the closed polylines in the road edge layer is geometrically segmented, resulting in multiple sub-region polylines, i.e., road segmentation. The module accurately calculates the area of ​​each road segment, prioritizing the use of area data from the original graphic entities or employing a geometric filling algorithm to ensure accuracy. Simultaneously, the system assigns disease data from the disease database to the corresponding road segment based on the station number. The module stores the segmentation results (segment start and end station numbers, segment area) and the disease data assigned to each segment.

[0057] PCI is a highway term, short for Pavement Condition Index, used to characterize the integrity of pavement structure. The index ranges from 0 to 100, with higher values ​​indicating better road conditions. The PCI calculation and export module primarily uses dynamic segmentation results and defect data, automatically calculating the PCI for each road segment based on selected road technical condition assessment standards (such as ministerial or local standards). The module reads the area of ​​each segment and the data (area or length) of various defects within that segment from the database. According to the assessment standards, it calculates the damage density of each defect within the corresponding segment. Combining the standard's built-in damage type-density-deduction curve (supporting table lookup and interpolation), it determines the individual deduction value for each defect. Based on the standard formula, considering the weight of defect category and individual defect's impact on overall road condition, it performs multi-level weighted calculations to obtain the total deduction value (DP) for each segment. Finally, the PCI value for that road segment is calculated using PCI = 100 - DP. The system can also automatically assess road condition levels (e.g., excellent, good, average, poor, or A, B, C, D, etc.) based on PCI values ​​and road classifications (e.g., expressways, arterial roads). After calculation, the system will export detailed results including segment information, density of each defect, deduction details, weights, total deduction value, PCI value, and road condition level, according to a preset table template format, generating a PCI evaluation table that meets design requirements.

[0058] Example 2

[0059] A method for generating a road surface condition index, using the road surface condition index generation system in Example 1, such as... Figure 1 As shown, the method for generating the road surface condition index includes the following steps:

[0060] Step 1: Obtain the original inspection drawings. The DXF graphic preprocessing module sets the road centerline, the scope of the defect detection, and the defect graphics as independent layers, forming a centerline layer, a road edge layer, and a defect layer, and saves them as DXF format graphic files.

[0061] Step 2: The centerline identification and definition module generates a centerline model based on the centerline layer;

[0062] Step 3: The layer recognition and disease extraction module traverses the disease layer information, performs text feature-based matching analysis between the standard disease type name and the layer name, calculates the geometric attributes of the disease type, and stores the disease layer name, disease graphics, geometric attributes, and station number in a structured manner to form a basic disease database.

[0063] Step 4: The automatic disease mapping module establishes a mapping relationship between the disease names in the standard selected by the user and the data in the basic disease database.

[0064] Step 5: The dynamic segmentation module of the statistical scope divides the road surface into segments based on the station number input by the user, calculates the area of ​​each segment, and assigns the defect data in the defect database to the corresponding segment according to the corresponding station number.

[0065] Step Six: The PCI Calculation and Export module automatically calculates the pavement condition index (PCI) for each road segment based on the road segmentation results, the user-selected standards, and the established mapping relationships, and generates a PCI evaluation table.

[0066] In one specific embodiment, Figure 2 This demonstrates the specific workflow of the centerline identification and definition module in step two, which includes the following steps:

[0067] Call DXF format graphic files; read geometric elements of the centerline layer; analyze the connection relationship and order between geometric elements; construct a continuous, directional digital centerline model; calculate the starting coordinates, ending coordinates, and total length of the centerline model; allow the user to determine the starting station number; and store the centerline parameters in a structured manner.

[0068] It should be noted that the centerline identification and definition module reads all geometric elements within the specified centerline layer of the DXF drawing file. These geometric elements include straight lines, arcs, and smooth curves. By analyzing the connection relationships and order of these geometric elements, it automatically constructs a continuous, directional digital centerline model. This digital centerline model accurately records the starting point coordinates, ending point coordinates, and total length of the centerline. The station number can be determined by the user. For example, the user can select the physical starting point of the centerline (such as point A or point B on the drawing) as the logical starting point for station number calculation (station number 0). The user can also set the initial station number value for this logical starting point. The final generated digital centerline model and its defined starting point will serve as the benchmark for all subsequent spatial positioning and dynamic segmentation of defects.

[0069] In one specific embodiment, such as Figure 3 As shown, step three specifically includes the following steps: calling the DXF format graphic file; reading all layer names; outputting the layer list; performing text feature-based matching analysis between the standard disease type names and the layer names in the layer list to find the corresponding disease layers; extracting geometric elements from the disease layers; calculating the geometric attributes of the geometric elements (line length and area of ​​the graphic); extracting the vertex coordinates of the elements and calculating the station number of the elements; and storing the data in a structured format according to the format of layer, geometric attribute, station number, and coordinates.

[0070] It should be noted that the predefined standard disease type names in the system are given by users based on national, ministerial, industry, and even enterprise standards. These names will correspond to specific standards selected by the user later. During text feature-based matching analysis, the layer identification and disease extraction module automatically selects the layer representing different pavement diseases by checking if the layer name contains disease type keywords or conforms to specific naming rules (such as "layer name-disease name"). Users can confirm or manually adjust the automatic matching results. For each extracted disease geometric element, the system calculates its key geometric attributes: the length for lines and the area for closed regions. Area calculation prioritizes using the precise area data stored within the graphic element itself (such as extended data); if not, it is calculated using a geometric filling algorithm. Simultaneously, combined with the centerline, the spatial position of each disease element relative to the centerline's starting point, i.e., the station number, is calculated. Finally, the extracted disease layer names, geometric attributes (length, area), station numbers, and geometric vertex coordinates are structured and stored to form a basic disease database for subsequent modules to access.

[0071] In one specific embodiment, such as Figure 4As shown, in step four, the specific workflow of the automatic disease mapping module is as follows: It calls up the disease layer list; receives the user-selected assessment criteria (national standard or surface standard) and road grade information; loads a predefined list of standard disease types based on the selected criteria; and establishes a mapping relationship between disease types and disease graphic layers under specific criteria based on text feature matching analysis. By checking whether the layer name contains disease type keywords or conforms to specific naming rules (such as "layer name-disease name"), the system automatically recommends the most likely corresponding layer for each disease type. Users can confirm or manually adjust based on the automatic matching results to ultimately determine the mapping relationship from disease type to specific graphic layer. This mapping relationship will guide subsequent PCI calculations.

[0072] In one specific embodiment, Figure 5 This demonstrates the main workflow of the dynamic segmentation module for statistical range in step five. The dynamic segmentation module can access data from the road edge line, center-connected model, segment station numbers, and the defect database to obtain closed polylines defined by the road edge line layer (representing the total detection range or road area). Based on the station numbers provided by the user, it generates a geometric cutting line perpendicular to the center line, performing geometric segmentation on the area represented by the road edge line polyline to obtain multiple sub-region polylines, i.e., road segmentation. It can accurately calculate the area of ​​each road segment. It assigns defect data from the defect base database generated by the defect extraction module to the corresponding road segment based on their station numbers. It stores the segmentation results (segment start and end station numbers, segment area) and the defect data assigned to each segment. When calculating the area of ​​a road segment, it prioritizes using the area data of the original graphic entity or uses a geometric filling algorithm to ensure accuracy. Figure 7 As shown in the figure, the dividing line divides the road edge into three segments.

[0073] In one specific embodiment, Figure 6This section demonstrates the main workflow of the PCI calculation and export module in step six. The PCI calculation and export module primarily calculates the Pavement Condition Index (PCI) for each road segment based on road segmentation and defect data, according to selected road technical condition assessment standards (such as ministerial or local standards). The system first reads the area of ​​each segment and the data (area or length) of various defects within that segment from the database; according to the assessment standards, it calculates the damage density of each defect within the corresponding segment; combining the standard's built-in damage type-density-deduction curve (supporting table lookup and interpolation calculations), it determines the individual deduction value for each defect; based on the standard formula, considering the weight of defect category and individual defect's impact on the overall road condition, it performs multi-level weighted calculations to obtain the total deduction value (DP) for each segment; finally, it calculates the PCI value for that road segment using PCI = 100 - DP. The system can also automatically assess road condition levels (e.g., Excellent, Good, Average, Poor, or A, B, C, D, etc.) based on PCI values ​​and road classifications (e.g., expressways, arterial roads). After calculation, the system will export detailed results including segment information, density of each defect, deduction details, weights, total deductions, PCI values, and road condition levels, according to a preset table template, generating a PCI evaluation table that meets design requirements. Figure 8 As shown in the table, the evaluation table provides an example of PCI evaluation for the road segment from K0+000.000 to K0+400.000 in a certain project.

[0074] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0075] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A road surface condition index generation system, characterized in that, include: The DXF graphic preprocessing module is used to set the road centerline, the scope of the defect detection, and the defect graphics in the original inspection drawings as independent layers, forming a centerline layer, a road edge layer, and a defect layer, and saves the converted drawings in DXF format. The centerline identification and definition module generates a centerline model based on the centerline layer. The centerline in the centerline model is a continuous, directional line that includes the start point, end point, total length, and initial station number. The layer recognition and disease extraction module has a preset standard disease type name. By traversing the disease layer information, it performs text feature-based matching analysis between the standard disease type name and the layer name, calculates the geometric attributes of the disease type, and stores the disease layer name, disease graphics, geometric attributes, and station number in a structured manner to form a basic disease database. The automatic disease mapping module can establish a mapping relationship between the disease names in the standard selected by the user and the data in the basic disease database. The statistical range dynamic segmentation module can segment the road surface based on the station number input by the user to form road segment segments, calculate the area of ​​each road segment segment, and assign the disease data in the disease base database to the corresponding road segment segment according to the corresponding station number. The PCI calculation and export module can automatically calculate the pavement condition index (PCI) of each road segment based on the road segmentation results, the selected road technical condition assessment standards, and the established mapping relationship, and generate a PCI evaluation table.

2. A method for generating a road condition index using the road condition index generation system as described in claim 1, characterized in that, Includes the following steps: Step 1: Obtain the original inspection drawings. The DXF graphic preprocessing module sets the road centerline, the scope of the defect detection, and the defect graphics as independent layers, forming a centerline layer, a road edge layer, and a defect layer, and saves them as DXF format graphic files. Step 2: The centerline identification and definition module generates a centerline model based on the centerline layer; Step 3: The layer recognition and disease extraction module traverses the disease layer information, performs text feature-based matching analysis between the standard disease type name and the layer name, calculates the geometric attributes of the disease type, and stores the disease layer name, disease graphics, geometric attributes, and station number in a structured manner to form a basic disease database. Step 4: The automatic disease mapping module establishes a mapping relationship between the disease names in the standard selected by the user and the data in the disease basic database. Step 5: The dynamic segmentation module of the statistical scope divides the road surface into segments based on the station number input by the user, calculates the area of ​​each segment, and assigns the defect data in the defect database to the corresponding segment according to the corresponding station number. Step Six: The PCI Calculation and Export module automatically calculates the pavement condition index (PCI) for each road segment based on the road segmentation results, the user-selected standards, and the established mapping relationships, and generates a PCI evaluation table.

3. The method for generating road surface condition index as described in claim 2, characterized in that, The specific workflow of the centerline identification and definition module in step two includes the following steps: Call DXF format graphics files; Read the geometric elements of the centerline layer; Analyze the connection relationships and order between the geometric elements; Construct a digital centerline model with continuous, directional lines; Calculate the starting point coordinates, ending point coordinates, and total length of the centerline model; The user determines the starting station number value; The centerline parameters are stored in a structured manner.

4. The method for generating road surface condition index as described in claim 3, characterized in that, In step three, the specific workflow of the layer recognition and disease extraction module includes: Call DXF format graphics files; Read all layer names; Output layer list; The standard disease type name is matched with the layer name in the layer list based on text features to find the corresponding disease layer. Extract geometric elements from the disease layer; Calculate the geometric properties of geometric elements; Calculate the station number of the element by extracting the vertex coordinates of the element; The data is stored in a structured manner according to the format of layer, geometric attribute, station number, and coordinate.

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