Road maintenance road construction sequence determination method, system, equipment and medium

Abstract

The invention provides a road maintenance road construction sequence determination method, system and device and a medium, and belongs to the technical field of road maintenance, and the method comprises the following steps: obtaining image data of a road section to be maintained, and inputting the image data into a pavement defect detection model, detecting the category, position and severity of the pavement defect by using a pavement defect detection model; the to-be-maintained area is partitioned according to the types and the positions of the pavement defects, and a plurality of sub-areas are obtained; the actual passing area of the to-be-maintained area before plugging is obtained; setting a passing speed threshold value of the road section to be maintained after blocking, and calculating the maximum passing area of the road section to be maintained after each sub-region is blocked in combination with the actual passing area; and determining a maintenance sequence of the plurality of sub-regions according to the maximum traffic area and the pavement defect severity, and carrying out region-by-region maintenance on the plurality of sub-regions according to the maintenance sequence. According to the invention, the traffic jam condition during road maintenance can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of highway maintenance, and in particular relates to a method, system, equipment and medium for determining a road construction sequence for highway maintenance. Background Art

[0002] With the rapid economic development, especially the increase in traffic demand, highway construction has been significantly promoted worldwide. Especially in China, highway construction not only supports the rapid economic growth, but also promotes the urbanization process. By the end of 2023, the total mileage of highways in my country will reach more than 5.4 million kilometers. However, due to factors such as traffic flow and environment, the long-term work of the road surface will be damaged. After the road surface is damaged, repeated passage of vehicles will cause serious damage to the road and affect traffic safety. Therefore, it is particularly important to timely maintain the damaged road surface defects.

[0003] At present, after road surface defects are detected, when the road surface defects are maintained, the area that needs maintenance will be blocked as a whole, and then maintenance will be carried out; however, when using this method for blocking, if the blocked area is large, it will cause large-scale congestion during peak traffic hours, thereby affecting the normal operation of traffic. Summary of the invention

[0004] In order to overcome the above-mentioned problem of large-scale road congestion during highway maintenance, the present invention provides a method for determining a road construction sequence for highway maintenance, comprising the following steps:

[0005] Acquire image data of the road section to be maintained, analyze the image data using a road surface defect detection model, and obtain identification information of the area to be maintained on the road section to be maintained, wherein the identification information includes the categories, locations, and severity of multiple road surface defects in the area to be maintained; partition the area to be maintained according to the categories and locations of the multiple road surface defects to obtain multiple sub-areas;

[0006] Obtaining the peak traffic flow and maximum lane capacity of the road section to be maintained before the maintenance area is blocked, and determining the actual traffic area of ​​the road section to be maintained before the maintenance area is blocked according to the peak traffic flow and maximum lane capacity;

[0007] Setting a speed threshold of the road section to be maintained after the maintenance area is blocked, and calculating the maximum traffic area of ​​the road section to be maintained after each sub-area is blocked, based on the actual traffic area and the speed threshold;

[0008] The maintenance sequence of the multiple sub-areas is determined according to the maximum traffic area and the severity of the road surface defects, and the multiple sub-areas are maintained region by region according to the maintenance sequence.

[0009] Preferably, the step of determining the actual traffic area of ​​the road section to be maintained before the maintenance area is blocked according to the peak traffic flow and the maximum lane capacity comprises the following steps:

[0010] Obtain the road length of the road section to be maintained before it is blocked; calculate the lane occupancy coefficient according to the road length of the road section to be maintained before it is blocked, the traffic flow and the maximum lane capacity;

[0011] The road width, road length and lane occupancy coefficient of the road section to be maintained before blocking are obtained to determine the actual traffic area of ​​the road section to be maintained before blocking.

[0012] Preferably, the calculation of the maximum traffic area of ​​the road section to be maintained after each sub-area is blocked comprises the following steps:

[0013] The area of ​​the sub-region is obtained, and the traffic area of ​​the road section to be maintained after blocking is determined based on the difference between the actual traffic area of ​​the road section to be maintained before blocking and the area of ​​the sub-region;

[0014] The traffic capacity saturation corresponding to the traffic area of ​​the road section to be maintained after blocking is obtained, and the maximum traffic area corresponding to the traffic speed threshold after the sub-area is blocked is determined according to the traffic area of ​​the road section to be maintained after blocking and the corresponding traffic capacity saturation.

[0015] Preferably, determining the maintenance order of multiple sub-areas according to the maximum traffic area and the severity of road surface defects comprises the following steps:

[0016] The severity of the road surface defects in each sub-area is graded from severe to mild, and a value is assigned to each grade;

[0017] The weighted sum of the maximum traffic area and the severity level of the road surface defects after the blockage of each sub-area is performed;

[0018] The weighted sum values ​​are sorted from largest to smallest, and each sub-region is maintained in this order.

[0019] Preferably, the weighted sum of the maximum traffic area and the severity level of the road surface defects after blocking each sub-area is performed, which is specifically performed by the following formula:

[0020] Q=ω1A i +ω2D i ;

[0021] Where Q is the weighted sum value; ω1 is the weight of the maximum traffic area, ω2 is the weight of the severity level of the road surface defect, and A is i is the maximum traffic area of ​​the ith sub-area, D iis the score of the severity level of the road surface defect in the i-th sub-area.

[0022] Preferably, the method for acquiring the pavement defect detection model is: acquiring a pavement defect data set, inputting data in the pavement defect data set into a convolutional neural network model FasterR-CNN, training Faster R-CNN, and obtaining the pavement defect detection model.

[0023] Preferably, the step of acquiring image data of the road section to be maintained, analyzing the image data by means of a road surface defect detection model, and obtaining identification information of the area to be maintained on the road section to be maintained comprises the following steps:

[0024] Obtain image data of the road section to be maintained through drones;

[0025] The image data is preprocessed using image processing technology, specifically: denoising the image data, enhancing contrast, and adjusting resolution.

[0026] The preprocessed image data is input into the pavement defect detection model, and the image is analyzed by the pavement defect detection model to detect multiple pavement defects in the area to be maintained;

[0027] Classify multiple pavement defects and annotate the defect type, location, and severity.

[0028] The present invention also provides a highway maintenance road construction sequence determination system, comprising:

[0029] A partitioning module is used to obtain image data of the road section to be maintained, analyze the image data through a road surface defect detection model, and obtain identification information of the area to be maintained on the road section to be maintained, wherein the identification information includes the categories, locations and severity of multiple road surface defects in the area to be maintained; and partition the area to be maintained according to the categories and locations of the multiple road surface defects to obtain multiple sub-areas;

[0030] An actual traffic area acquisition module is used to obtain the peak traffic flow and maximum lane capacity of the road section to be maintained before the maintenance area is blocked, and determine the actual traffic area of ​​the road section to be maintained before the maintenance area is blocked according to the peak traffic flow and maximum lane capacity;

[0031] A maximum traffic area acquisition module is used to set a traffic speed threshold of the road section to be maintained after the maintenance area is blocked, and calculate the maximum traffic area of ​​the road section to be maintained after each sub-area is blocked, based on the actual traffic area and the traffic speed threshold;

[0032] The maintenance sequence confirmation module is used to determine the maintenance sequence of multiple sub-areas according to the maximum traffic area and the severity of road surface defects, and to perform maintenance on the multiple sub-areas one by one according to the maintenance sequence.

[0033] The present invention also provides a computer device, characterized in that it includes a memory and a processor; the memory stores a computer program, and the processor is used to run the computer program in the memory to execute the method for determining the highway maintenance road construction sequence.

[0034] The present invention also provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor to execute the method for determining the road construction sequence of highway maintenance.

[0035] The method, system, device and medium for determining the construction sequence of highway maintenance provided by the present invention have the following beneficial effects:

[0036] The present invention can detect the categories, locations and severity of multiple road surface defects by using a road surface defect detection model; the maintenance area of ​​the road section to be maintained can be partitioned according to the categories and locations of the multiple road surface defects to obtain multiple sub-areas; this process can decompose the overall area to be maintained into multiple small areas, thereby reducing the area of ​​each blockage and reducing traffic congestion; the maximum traffic area corresponding to the sub-area blocked each time can be determined by the actual traffic area and the speed threshold; the maintenance order of multiple sub-areas can be determined by the maximum traffic area and the severity of the road surface defects. Through this process, different sub-areas can be maintained one by one, and traffic congestion can be improved while ensuring traffic safety, so that vehicles can pass smoothly during peak traffic hours. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiment of the present invention and its design scheme, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 A flowchart of a method for determining a road construction sequence for highway maintenance according to an embodiment of the present invention;

[0039] Figure 2 This is a status diagram of the overall blocking of the area to be maintained;

[0040] Figure 3 A state diagram for dividing the area to be maintained into multiple sub-areas;

[0041] Figure 4State diagram of the first maintenance sub-area. DETAILED DESCRIPTION

[0042] In order to enable those skilled in the art to better understand the technical solution of the present invention and implement it, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the scope of protection of the present invention.

[0043] In the description of the present invention, it is to be understood that the terms “center”, “longitudinal”, “lateral”, “length”, “width”, “thickness”, “up”, “down”, “front”, “back”, “left”, “right”, “vertical”, “horizontal”, “top”, “bottom”, “inside”, “outside”, “axial”, “radial”, “circumferential”, etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the technical solutions of the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0044] In addition, the terms "first", "second", etc. are used for descriptive purposes only and are not to be understood as indicating or implying relative importance. In the description of the present invention, it should be noted that, unless otherwise clearly specified or limited, the terms "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. In the description of the present invention, unless otherwise specified, "plurality" means two or more, which will not be described in detail here.

[0045] Example

[0046] The present invention provides a method for determining the construction sequence of a highway maintenance road, specifically as follows Figure 1 As shown, the following steps are included:

[0047] Step 1: Obtain image data of the road section to be maintained, analyze the image data through the pavement defect detection model, and obtain identification information of the area to be maintained on the road section to be maintained. The identification information includes the category, location and severity of multiple pavement defects in the area to be maintained; divide the area to be maintained according to the category and location of multiple pavement defects to obtain multiple sub-areas. Specifically, the steps are as follows:

[0048] (1) Obtain a pavement defect dataset, input the data in the pavement defect dataset into a convolutional neural network model, train Faster R-CNN, and obtain a pavement defect detection model.

[0049] The pavement defect dataset of the present invention is a Kaggle dataset of a public data platform.

[0050] Faster R-CNN (Region-based Convolutional Neural Network) is a convolutional neural network model for target detection. It can simultaneously realize object positioning (i.e., detecting the location of the object) and classification (i.e., identifying the category of the object). Faster R-CNN is developed on the basis of R-CNN (Region-based CNN) and Fast R-CNN. The main innovation is the introduction of the Region Proposal Network (RPN) to replace the traditional method of manually selecting region proposals, thereby greatly improving the detection efficiency. The Region Proposal Network (RPN) is one of the key innovations of Faster R-CNN. RPN scans the feature map of the entire image in a sliding window manner to generate a set of candidate regions (i.e., region proposals). These region proposals are regions that may contain targets. RPN generates candidate regions by classifying the foreground / background of these regions. After generating the candidate regions, the ROI pooling (Region of Interest Pooling) operation converts these candidate regions into fixed-size feature maps, and further classification and regression processing is performed through the fully connected layer. In the feature map after ROI pooling, the classifier is responsible for identifying the object category in each candidate region, and the regressor is responsible for adjusting the position of the candidate box so that it surrounds the object more accurately.

[0051] The present invention divides the road surface defect data set into a training set and a validation set at a ratio of 9:1, and inputs the image data in the training set into Faster R-CNN to train Faster R-CNN. When training Faster R-CNN, the loss function used usually includes two parts: one is the classification loss (classification accuracy), and the other is the regression loss (frame prediction accuracy). After the training is completed, the validation set is used to evaluate the accuracy of the model. The present invention uses the evaluation indicators mAP (meanAverage Precision), Precision, and Recall to evaluate the accuracy of the model, and finally obtains a road surface defect detection model.

[0052] (2) Obtain image data of the road section to be maintained, analyze the image data using a road surface defect detection model, and obtain identification information of the area to be maintained on the road section to be maintained, the identification information including the category, location, and severity of multiple road surface defects in the area to be maintained. Specifically, the steps include:

[0053] Image data of the road section to be maintained is obtained through equipment such as drones or cameras. The obtained image data needs to have sufficient resolution and clarity so that the subsequent defect detection model can accurately identify problems on the road surface.

[0054] After the image data is acquired, it is necessary to use image processing technology (such as OpenCV, image enhancement algorithms, etc.) to preprocess the image, including denoising, contrast enhancement, cropping the region of interest, adjusting the resolution, etc., to ensure that the image data is suitable for the input defect detection model. Image preprocessing can improve the quality of the image, remove unnecessary background or noise, and maintain or enhance the visibility of road defects in the image.

[0055] The preprocessed image data is input into the pavement defect detection model, and the pavement defect detection model is used to analyze the image and detect multiple pavement defects in the area to be maintained; the detected pavement defects are classified (such as cracks, potholes, potholes, etc.), and the location (such as coordinate boxes) and severity of the defects are marked. The output results of the pavement defect detection model are used to obtain the specific defect type, defect location and defect severity on the road section to be maintained. During the highway maintenance process, different types of defects have different corresponding treatment methods. The following are different highway defects and their corresponding maintenance measures:

[0056] Rutting: Rutting is the subsidence or plastic deformation of the road surface caused by traffic loads, usually occurring on roads with heavy traffic and high speeds. Rutting usually needs to be repaired by excavation, milling or adding a new layer, and cold or hot regeneration when necessary.

[0057] Cracks: Cracks are cracks in the road surface caused by factors such as temperature changes, loads, and material aging. Common types of cracks include transverse cracks, longitudinal cracks, and web cracks. Crack repair can be done by filling (grouting) or adding a sealing layer.

[0058] Potholes: Potholes are local damage caused by damage to the road base, water infiltration, climate factors (such as freeze-thaw effects), etc. Potholes often form depressions of varying depths on the roadway. Methods for repairing potholes include milling and cleaning the damaged parts, adding new materials and compacting them, repairing the base, etc. Potholes usually need to be dealt with immediately after they are discovered. If potholes are not repaired in time, the road surface may deteriorate further, thus affecting traffic safety.

[0059] Warping or undulating road surface: Uneven or undulating road surface is usually caused by poor construction quality, high temperature, traffic load and other factors, resulting in uneven deformation of the road surface. Repair of warping usually requires milling and resurfacing the road surface, or local cold recycling and overlay.

[0060] Loose surface: Loose surface refers to the loss of particles due to wear of cement concrete pavement or asphalt pavement, which is common in asphalt pavement. Repair methods include re-paving the surface layer, or deep sealing treatment, spraying adhesive, etc.

[0061] Settlement: Settlement refers to the phenomenon of partial sinking of the road surface due to uneven foundation settlement, improper construction, etc. It is usually repaired by strengthening the roadbed, repairing the base, and adding pavement.

[0062] The present invention can detect the specific type and specific location of the road surface defects of the road section to be maintained by inputting the acquired image data of the road section to be maintained into the road surface defect detection model.

[0063] (3) The maintenance area of ​​the road section to be maintained is divided into multiple sub-areas according to various road surface defects.

[0064] After the specific type and specific location of the road surface defects of the road section to be maintained are detected, the maintenance area of ​​the road section to be maintained is divided into multiple sub-areas. The present invention divides the maintenance area ( Figure 2 A region in the figure is the overall blocking region) divided into multiple sub-regions. Figure 3 (1), (2), (3), (4) and (5) shown in Figure 2 The A region in the figure is divided into multiple sub-regions, wherein non-adjacent sub-regions can be of the same type, for example, Figure 3 (1) and (5) in .

[0065] Step 2: Obtain the peak traffic flow and maximum lane capacity of the road section to be maintained before the maintenance area is blocked, and determine the actual traffic area of ​​the road section to be maintained before the maintenance area is blocked based on the peak traffic flow and maximum lane capacity. The specific steps include the following:

[0066] The road length of the maintenance area of ​​the road section to be maintained before being blocked is obtained; and the lane occupancy coefficient is calculated according to the road length of the maintenance area of ​​the road section to be maintained before being blocked, the traffic flow and the maximum lane capacity.

[0067] Use distance measuring tools or GPS tracking systems to accurately measure the length of the road corresponding to the maintenance area of ​​the road section to be maintained.

[0068] Traffic flow data is an important basis for measuring the traffic conditions of a road section. Traffic flow data usually refers to the number of vehicles passing through a lane per unit time, usually expressed in vehicles per hour (vph). Specifically, the traffic flow data within the length of the road corresponding to the maintenance area can be used to monitor the traffic flow of the road section in real time using the traffic sensors of the traffic monitoring system (such as road surface sensors, video surveillance, and traffic radar).

[0069] The maximum lane capacity refers to the maximum number of vehicles that a lane can accommodate under ideal conditions, and is usually determined based on factors such as lane width, type, and speed. For a single lane on an ordinary highway, the maximum lane capacity is generally between 2,000 and 2,500 vehicles per hour (the capacity will vary depending on the region and road section).

[0070] The lane occupancy coefficient is a coefficient used to adjust the traffic area, which usually represents the proportion of lanes actually occupied. The calculation of the lane occupancy coefficient can help traffic management departments evaluate the traffic density of road sections, so as to make corresponding maintenance or improvement decisions to ensure smooth and safe traffic. The specific calculation formula is as follows:

[0071] Lane occupancy factor = traffic flow ÷ maximum lane capacity;

[0072] (2) Obtain the road width, road length and lane occupancy coefficient of the road section to be maintained before blocking to determine the actual traffic area of ​​the road section to be maintained before blocking. The calculation formula of the actual traffic area is as follows:

[0073] S = H × L × α;

[0074] Where H and L are the total road width and total road length of the road section to be maintained before blocking, and α is the lane occupancy coefficient.

[0075] Step 3: Set the speed threshold of the road section to be maintained after blocking, and calculate the maximum traffic area of ​​each sub-area after blocking based on the actual traffic area and the speed threshold.

[0076] In traffic management and maintenance projects, the speed threshold after a road blockage is a key factor used to determine whether traffic can maintain a relatively smooth flow after a road is closed or partially closed. This threshold is usually determined based on factors such as the road design type, traffic flow, degree of blockage, and surrounding environment. The speed threshold settings for different road types are as follows:

[0077] Urban roads: For main roads or busy roads in cities, we hope that traffic will be smooth after being blocked, and the speed threshold is usually set at 20-30 km / h. This speed can ensure that vehicles can maintain a certain degree of smoothness under heavy traffic conditions.

[0078] Suburban roads or secondary roads: For secondary roads or suburban roads with low traffic volume, the speed threshold can usually be set at 30-40 km / h, which can ensure that traffic is not too congested in most cases.

[0079] Expressways or trunk roads: For blockages on expressways or trunk roads, the speed threshold is usually set at 60 km / h or above. The blockage has little impact on traffic, and vehicles can maintain a higher speed.

[0080] Calculating the maximum traffic area of ​​the road section to be maintained after each sub-area is blocked includes the following steps:

[0081] The area of ​​the sub-region is obtained, and the traffic area of ​​the road section to be maintained after blocking is determined based on the difference between the actual traffic area of ​​the road section to be maintained before blocking and the area of ​​the sub-region.

[0082] The traffic capacity saturation corresponding to the traffic area of ​​the road section to be maintained after blocking is obtained, and the maximum traffic area corresponding to the traffic speed threshold after blocking of the sub-area is determined according to the traffic area of ​​the road section to be maintained after blocking and the corresponding traffic capacity saturation. The details are as follows:

[0083] The traffic capacity saturation refers to the ratio of the actual flow rate after the maintenance section is blocked to the theoretical maximum flow rate. Assuming that the traffic capacity of the maintenance section is proportional to the traffic area after its blocking, the maximum traffic area is calculated in the following way:

[0084]

[0085] In the formula, A i is the maximum traffic area of ​​the ith sub-area, S i is the maximum traffic area of ​​the ith sub-area, V i is the capacity saturation of the ith sub-area, v u is the speed threshold, and n is the number of lanes.

[0086] Step 4: Determine the maintenance sequence of multiple sub-areas according to the maximum traffic area and the severity of road surface defects, and perform maintenance on multiple sub-areas one by one according to the maintenance sequence. The specific steps include:

[0087] (1) The severity of the road surface defects in each sub-area is graded in order from heavy to light, and each grade is assigned a value, as shown in Table 1. As can be seen from Table 1, each type of defect is divided into 5 grades, from 1 (lightest) to 5 (heaviest), indicating the severity of the defect. The higher the grade, the greater the impact of the defect on traffic safety, driving comfort and road surface structure. According to the severity of the defect, each grade is assigned a corresponding value (0-5). The larger the value, the more serious the defect and the greater the impact. According to the grade of each defect type in each sub-area, combined with the degree of impact of each defect type, it can be obtained

[0088] Table 1 Pavement defect classification table

[0089]

[0090] The system can provide a scientific basis for road maintenance and repair to determine whether immediate repair, priority repair or regular maintenance is needed. Through this classification, road defects can be quantitatively evaluated in different sections and sub-areas, providing intuitive and systematic data support for maintenance management.

[0091] (2) The weighted sum of the maximum traffic area and the severity level of the road surface defects after the blockage of each sub-area is calculated using the following formula:

[0092] Q=ω1A i +ω2D i ;

[0093] Where Q is the weighted sum value; ω1 is the weight of the maximum traffic area, ω2 is the weight of the severity level of the road surface defect, and A is i is the maximum traffic area of ​​the ith sub-area, D i is the score of the severity level of the road surface defect in the i-th sub-area.

[0094] (3) Sort the weighted sum values ​​in descending order, and maintain each sub-area in this order.

[0095] For example, Figure 3 After calculating the sub-areas in the above calculation method, the plugging maintenance sequence is: (1), (3), (2), (5) and (4), among which the plugging status of sub-area (1) is shown in Figure 4 .

[0096] The present invention also provides a highway maintenance road construction sequence determination system, comprising:

[0097] A partitioning module is used to obtain image data of the road section to be maintained, analyze the image data through a pavement defect detection model, and obtain identification information of the area to be maintained on the road section to be maintained, the identification information includes the category, location and severity of multiple pavement defects in the area to be maintained; partition the area to be maintained according to the category and location of multiple pavement defects to obtain multiple sub-areas;

[0098] The actual traffic area acquisition module is used to obtain the peak traffic flow and maximum lane capacity of the road section to be maintained in the maintenance area before it is blocked, and determine the actual traffic area of ​​the road section to be maintained in the maintenance area before it is blocked according to the peak traffic flow and maximum lane capacity;

[0099] The maximum traffic area acquisition module is used to set the traffic speed threshold of the road section to be maintained after the maintenance area is blocked, and calculate the maximum traffic area of ​​the road section to be maintained after each sub-area is blocked based on the actual traffic area and the traffic speed threshold;

[0100] The maintenance sequence confirmation module is used to determine the maintenance sequence of multiple sub-areas according to the maximum traffic area and the severity of road surface defects, and to maintain the multiple sub-areas one by one according to the maintenance sequence.

[0101] The present invention also provides a computer device, characterized in that it includes a memory and a processor; the memory stores a computer program, and the processor is used to run the computer program in the memory to execute the method for determining the road construction sequence of highway maintenance.

[0102] The present invention also provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor to execute the method for determining the road construction sequence of highway maintenance.

[0103] From the above description, it can be seen that the present invention can detect the categories, locations and severity of multiple road surface defects by using a road surface defect detection model; the maintenance area of ​​the road section to be maintained can be partitioned according to the categories and locations of multiple road surface defects to obtain multiple sub-areas; this process can decompose the overall area to be maintained into multiple small areas, thereby reducing the area of ​​each blockage and reducing traffic congestion; the maximum traffic area corresponding to the sub-area blocked each time can be determined by the actual traffic area and the speed threshold; the maintenance order of multiple sub-areas can be determined by the maximum traffic area and the severity of the road surface defects. Through this process, different sub-areas can be maintained one by one, and traffic congestion can be improved while ensuring traffic safety, so that vehicles can pass smoothly during peak traffic hours.

[0104] The above embodiments are only preferred specific implementation methods of the present invention, and the protection scope of the present invention is not limited thereto. Any simple changes or equivalent replacements of the technical solutions that can be obviously obtained by any technician familiar with the field within the technical scope disclosed in the present invention belong to the protection scope of the present invention.

Claims

1. A method for determining the construction sequence of a highway maintenance road, characterized in that: The steps include: Acquire image data of the road section to be maintained, analyze the image data using a road surface defect detection model, and obtain identification information of the area to be maintained on the road section to be maintained, wherein the identification information includes the category, location, and severity of multiple road surface defects in the area to be maintained; The maintenance area is divided into multiple sub-areas according to the types and locations of multiple road surface defects; Obtaining the peak traffic flow and maximum lane capacity of the road section to be maintained before the maintenance area is blocked, and determining the actual traffic area of ​​the road section to be maintained before the maintenance area is blocked according to the peak traffic flow and maximum lane capacity; Setting a speed threshold of the road section to be maintained after the maintenance area is blocked, and calculating the maximum traffic area of ​​the road section to be maintained after each sub-area is blocked, based on the actual traffic area and the speed threshold; The maintenance sequence of the multiple sub-areas is determined according to the maximum traffic area and the severity of the road surface defects, and the multiple sub-areas are maintained region by region according to the maintenance sequence.

2. The method for determining the construction sequence of a highway maintenance road according to claim 1, characterized in that: The method of determining the actual traffic area of ​​the road section to be maintained before blocking the area to be maintained according to the peak traffic flow and the maximum lane capacity comprises the following steps: Obtain the road length of the road section to be maintained before it is blocked; calculate the lane occupancy coefficient according to the road length of the road section to be maintained before it is blocked, the traffic flow and the maximum lane capacity; The road width, road length and lane occupancy coefficient of the road section to be maintained before blocking are obtained to determine the actual traffic area of ​​the road section to be maintained before blocking.

3. The method for determining the construction sequence of a highway maintenance road according to claim 2, characterized in that: The step of calculating the maximum traffic area of ​​the road section to be maintained after each sub-area is blocked comprises the following steps: The area of ​​the sub-region is obtained, and the traffic area of ​​the road section to be maintained after blocking is determined based on the difference between the actual traffic area of ​​the road section to be maintained before blocking and the area of ​​the sub-region; The traffic capacity saturation corresponding to the traffic area of ​​the road section to be maintained after blocking is obtained, and the maximum traffic area corresponding to the traffic speed threshold after the sub-area is blocked is determined according to the traffic area of ​​the road section to be maintained after blocking and the corresponding traffic capacity saturation.

4. The method for determining the construction sequence of a highway maintenance road according to claim 3, characterized in that: The method of determining the maintenance order of the plurality of sub-areas according to the maximum traffic area and the severity of the road surface defects comprises the following steps: The severity of the road surface defects in each sub-area is graded from severe to mild, and a value is assigned to each grade; The weighted sum of the maximum traffic area and the severity level of the road surface defects after the blockage of each sub-area is performed; The weighted sum values ​​are sorted from largest to smallest, and each sub-region is maintained in this order.

5. The method for determining the construction sequence of a highway maintenance road according to claim 4, characterized in that: The weighted sum of the maximum traffic area and the severity level of the road surface defects after blocking each sub-area is specifically calculated using the following formula: Q6ω1A i +ω2D i 100. Where Q is the weighted sum value; ω1 is the weight of the maximum traffic area, ω2 is the weight of the severity level of the road surface defect, and A is i is the maximum traffic area of ​​the ith sub-area, D i is the score of the severity level of the road surface defect in the i-th sub-area.

6. The method for determining the construction sequence of a highway maintenance road according to claim 1, characterized in that: The method for obtaining the pavement defect detection model is as follows: obtaining a pavement defect data set, inputting data in the pavement defect data set into a convolutional neural network model FasterR-CNN, training FasterR-CNN, and obtaining the pavement defect detection model.

7. The method for determining the construction sequence of a highway maintenance road according to claim 1, characterized in that: The method of acquiring image data of the road section to be maintained and analyzing the image data by a road surface defect detection model to obtain identification information of the area to be maintained on the road section to be maintained includes the following steps: Obtain image data of the road section to be maintained through drones; The image data is preprocessed using image processing technology, specifically: removing noise from the image data, enhancing contrast, and adjusting resolution. The preprocessed image data is input into the pavement defect detection model, and the image is analyzed by the pavement defect detection model to detect multiple pavement defects in the area to be maintained; Classify multiple pavement defects and annotate the defect type, location, and severity.

8. A highway maintenance road construction sequence determination system, characterized in that: include: A partitioning module is used to obtain image data of the road section to be maintained, analyze the image data through a road surface defect detection model, and obtain identification information of the area to be maintained on the road section to be maintained, wherein the identification information includes the category, location and severity of multiple road surface defects in the area to be maintained; The maintenance area is divided into multiple sub-areas according to the types and locations of multiple road surface defects; An actual traffic area acquisition module is used to obtain the peak traffic flow and maximum lane capacity of the road section to be maintained before the maintenance area is blocked, and determine the actual traffic area of ​​the road section to be maintained before the maintenance area is blocked according to the peak traffic flow and maximum lane capacity; A maximum traffic area acquisition module is used to set a traffic speed threshold of the road section to be maintained after the maintenance area is blocked, and calculate the maximum traffic area of ​​the road section to be maintained after each sub-area is blocked, based on the actual traffic area and the traffic speed threshold; The maintenance sequence confirmation module is used to determine the maintenance sequence of multiple sub-areas according to the maximum traffic area and the severity of road surface defects, and to perform maintenance on the multiple sub-areas one by one according to the maintenance sequence.

9. A computer device, characterized in that: It comprises a memory and a processor; the memory stores a computer program, and the processor is used to run the computer program in the memory to execute the method for determining the road construction sequence of highway maintenance as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor to execute the method for determining the road construction sequence of highway maintenance according to any one of claims 1-7.

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