Method and device for determining optimal road repair solution

Abstract

The application provides a road repair optimal scheme determination method and device, the method comprises the following steps: acquiring multiple images of a damaged road and position coordinates corresponding to the multiple images; according to the shooting order of the multiple images of the damaged road and the position coordinates corresponding to the multiple images, a complete topographic image of the damaged road is spliced; the complete topographic image of the damaged road is subjected to metacell processing, and the damage range and damage depth of each damaged area are marked; the metacell processing is unit processing of the complete topographic image of the damaged road according to a preset size; the damage range and damage depth of the each damaged area are planned based on a metacell algorithm, and an optimal repair scheme of the damaged road is acquired. The method can improve the planning efficiency of the road repair optimal scheme.

Description

Technical Field

[0001] This application relates to the field of road repair technology, and in particular to a method, apparatus, electronic device and readable storage medium for determining the optimal road repair solution. Background Technology

[0002] Drones can acquire high-resolution images and pictures, and are characterized by low cost and low-altitude flight unaffected by clouds and fog, making them widely used in disaster monitoring, road damage assessment, and other fields.

[0003] In existing technologies, the determination of the optimal road repair plan using UAV imagery still mainly relies on manual surveying and calculation. The method involves manually marking the location of the damaged area after acquiring images of the road damage using a UAV, and then performing manual calculations to obtain the optimal road repair plan. This approach has low planning efficiency, and the calculated result is not necessarily the optimal solution, resulting in low accuracy and causing work delays.

[0004] In summary, improving the planning efficiency of optimal road repair solutions is an urgent problem that needs to be solved. Summary of the Invention

[0005] To solve the above-mentioned technical problems, or at least partially solve them, this application provides a method for determining the optimal road repair scheme, which solves the problem of low planning efficiency of the optimal road repair scheme.

[0006] To achieve the above objectives, the technical solutions provided in this application are as follows:

[0007] In a first aspect, embodiments of this application provide a method for determining the optimal road repair solution, the method comprising:

[0008] Obtain multiple images of the damaged road and the corresponding location coordinates of the multiple images;

[0009] Based on the shooting order of multiple images of the damaged road and the corresponding position coordinates of the multiple images, a complete topographic image of the damaged road is obtained by stitching them together;

[0010] The complete topographic image of the damaged road is subjected to meta-cell processing to mark the damage range and depth of each damaged area; the meta-cell processing is to perform unitization processing on the complete topographic image of the damaged road according to a preset size;

[0011] The meta-cell algorithm is used to plan the damage range and depth of each damaged area to obtain the optimal repair scheme for the damaged road.

[0012] As an optional implementation of this application, the step of acquiring multiple images of the damaged road and the corresponding location coordinates of the multiple images includes:

[0013] The damaged roads are divided into a first preset number of damaged road segments according to a preset method.

[0014] At least a first preset number of drones are used to photograph the first preset number of damaged road sections, and multiple images and the location coordinates corresponding to the multiple images are obtained.

[0015] As an optional implementation of this application, before performing meta-cell processing on the complete topographic image of the damaged road and marking the damage range and depth of each damaged area, the method further includes:

[0016] Image preprocessing is performed on the complete topographic image of the damaged road to determine each damaged area of ​​the road.

[0017] As an optional implementation of this application, the step of performing meta-cell processing on the complete topographic image of the damaged road and marking the damage range and depth of each damaged area includes:

[0018] The complete topographic image of the damaged road is divided according to a preset size, and the complete topographic image of the damaged road is divided into a second preset number of cells;

[0019] Obtain the damage range and damage depth of each damaged area;

[0020] Using the second preset number of cells as a background, mark the damage range and damage depth of each damaged area.

[0021] As an optional implementation of this application, the step of planning the damage range and depth of each damaged area based on the meta-cell algorithm to obtain the optimal repair scheme for the damaged road includes:

[0022] The damage range and depth of each damaged area are planned according to the first preset rule to obtain the optimal repair plan for the damaged road; the first preset rule is to repair the damaged road based on the principle of minimizing material usage;

[0023] or;

[0024] The damage range and depth of each damaged area are planned according to the second preset rule to obtain the optimal repair scheme for the damaged road; the second preset rule is to repair the damaged road based on the principle of the shortest repair time.

[0025] As an optional implementation of this application, the step of planning the damage range and depth of each damaged area according to a first preset rule to obtain the optimal repair plan for the damaged road includes:

[0026] The preset size of the meta-cell and the parameters of the target road segment to be repaired are determined; the parameters of the target road segment to be repaired include: the length and width of the target road segment to be repaired;

[0027] The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route;

[0028] Based on the number of damaged areas along each repair route, determine the material usage for each damaged area;

[0029] The total material usage for each repair route is determined based on the number of damaged areas in each repair route and the material usage for each damaged area.

[0030] The first target repair route is determined as the optimal repair scheme for the damaged road, and the first target repair route is the repair route corresponding to the minimum total material usage.

[0031] As an optional implementation of this application, the step of planning the damage range and depth of each damaged area according to a second preset rule to obtain the optimal repair plan for the damaged road includes:

[0032] The preset size of the meta-cell and the parameters of the target road segment to be repaired are determined; the parameters of the target road segment to be repaired include: the length and width of the target road segment to be repaired;

[0033] The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route;

[0034] Based on the number of damaged areas along each repair route, determine the material usage for each repair route and the start time for each repair route.

[0035] Determine the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient;

[0036] Wherein, the first weighting coefficient is the weight of the number of damaged areas in each repair route, the second weighting coefficient is the weight of the material usage in each repair route, and the third weighting coefficient is the weight of the operation entry time in each repair route.

[0037] The total workload of each repair route is determined based on the number of damaged areas, the first weighting coefficient, the material usage of each repair route, the second weighting coefficient, the operation entry time of each repair route, and the third weighting coefficient.

[0038] The second target repair route is determined as the optimal repair scheme for the damaged road, and the second target repair route is the repair route corresponding to the shortest repair time.

[0039] Secondly, embodiments of this application provide a road repair optimal solution determination device, comprising:

[0040] The acquisition module is used to acquire multiple images of the damaged road and the corresponding location coordinates of the multiple images;

[0041] The stitching module is used to stitch together multiple images of the damaged road according to the shooting order and the corresponding position coordinates of the multiple images to obtain a complete topographic image of the damaged road;

[0042] A labeling module is used to perform meta-cell processing on the complete topographic image of the damaged road, and to label the damage range and damage depth of each damaged area; the meta-cell processing is to perform unitization processing on the complete topographic image of the damaged road according to a preset size;

[0043] The planning module is used to plan the damage range and depth of each damaged area based on the meta-cell algorithm, and obtain the optimal repair plan for the damaged road.

[0044] As an optional implementation of this application, the acquisition module is specifically used for:

[0045] The damaged roads are divided into a first preset number of damaged road segments according to a preset method.

[0046] At least a first preset number of drones are used to photograph the first preset number of damaged road sections, and multiple images and the location coordinates corresponding to the multiple images are obtained.

[0047] As an optional implementation of this application, the apparatus further includes:

[0048] The preprocessing module is used to perform image preprocessing on the complete topographic image of the damaged road to determine the various damaged areas of the damaged road.

[0049] As an optional implementation of this application, the marking module is specifically used for:

[0050] The complete topographic image of the damaged road is divided according to a preset size, and the complete topographic image of the damaged road is divided into a second preset number of cells;

[0051] Obtain the damage range and damage depth of each damaged area;

[0052] Using the second preset number of cells as a background, mark the damage range and damage depth of each damaged area.

[0053] As an optional implementation of this application, the planning module includes:

[0054] The first planning unit is used to plan the damage range and depth of each damaged area according to a first preset rule, and to obtain the optimal repair plan for the damaged road; the first preset rule is to repair the damaged road based on the principle of minimizing material usage;

[0055] or;

[0056] The second planning unit is used to plan the damage range and damage depth of each damaged area according to the second preset rule, and obtain the optimal repair scheme for the damaged road; the second preset rule is to repair the damaged road based on the principle of the shortest repair time.

[0057] As an optional implementation of this application, the first planning unit is configured to:

[0058] The preset size of the meta-cell and the parameters of the target road segment to be repaired are determined; the parameters of the target road segment to be repaired include: the length and width of the target road segment to be repaired;

[0059] The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route;

[0060] Based on the number of damaged areas along each repair route, determine the material usage for each damaged area;

[0061] The total material usage for each repair route is determined based on the number of damaged areas in each repair route and the material usage for each damaged area.

[0062] The first target repair route is determined as the optimal repair scheme for the damaged road, and the first target repair route is the repair route corresponding to the minimum total material usage.

[0063] As an optional implementation of this application, the second planning unit is specifically used for:

[0064] The preset size of the meta-cell and the parameters of the target road segment to be repaired are determined; the parameters of the target road segment to be repaired include: the length and width of the target road segment to be repaired;

[0065] The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route;

[0066] Based on the number of damaged areas along each repair route, determine the material usage for each repair route and the start time for each repair route.

[0067] Determine the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient;

[0068] Wherein, the first weighting coefficient is the weight of the number of damaged areas in each repair route, the second weighting coefficient is the weight of the material usage in each repair route, and the third weighting coefficient is the weight of the operation entry time in each repair route.

[0069] The total workload of each repair route is determined based on the number of damaged areas, the first weighting coefficient, the material usage of each repair route, the second weighting coefficient, the operation entry time of each repair route, and the third weighting coefficient.

[0070] The second target repair route is determined as the optimal repair scheme for the damaged road, and the second target repair route is the repair route corresponding to the shortest repair time.

[0071] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the road repair optimal solution determination method described in the first aspect or any embodiment of the first aspect.

[0072] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for determining the optimal road repair scheme as described in the first aspect or any embodiment of the first aspect.

[0073] The method for determining the optimal road repair scheme provided in this application first acquires multiple images of the damaged road and their corresponding location coordinates, then stitches them together to obtain a complete topographic image of the damaged road. The complete topographic image of the damaged road is then processed into a meta-cell model to mark the damage range and depth of each damaged area. The meta-cell model involves dividing the complete topographic image of the damaged road into units according to a preset size. Finally, based on the damage range and depth of each damaged area, the optimal repair scheme for the damaged road is obtained. Because the damage range and depth of each damaged area are planned using a meta-cell algorithm, the problem of low planning efficiency for the optimal road repair scheme caused by manual operation is avoided, further improving the planning accuracy of the optimal road repair scheme. Attached Figure Description

[0074] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0075] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0076] Figure 1 This is a flowchart illustrating a method for determining the optimal road repair solution in one embodiment;

[0077] Figure 2 This is a flowchart illustrating the method for determining the optimal road repair solution in another embodiment;

[0078] Figure 3 This is a schematic diagram illustrating a method for determining the optimal road repair solution in one embodiment.

[0079] Figure 4 This is a schematic diagram of the structure of a road repair optimal solution determination device in one embodiment;

[0080] Figure 5 This is a schematic diagram of the structure of the electronic device described in the embodiments of this application. Detailed Implementation

[0081] To better understand the above-mentioned objectives, features, and advantages of this application, the solution of this application will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0082] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this application may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some embodiments of this application, and not all embodiments.

[0083] The terms "first" and "second" and other relational terms used in the specification and claims of this application are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0084] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner. Furthermore, in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0085] In one embodiment, such as Figure 1 As shown, a method for determining the optimal road repair solution is provided, which includes the following steps:

[0086] S11. Obtain multiple images of the damaged road and the corresponding location coordinates of the multiple images.

[0087] Specifically, the process involves using drones to photograph damaged roads, with the drones flying along the road's contours to take pictures. Additionally, the drones need to be equipped with a positioning module, a lidar ranging module, a communication module, and photographing equipment. The positioning module determines the coordinates of each image, the lidar ranging module measures and determines the three-dimensional structural information of each image, the photographing equipment captures multiple images of the damaged road, and the communication module transmits each image, its coordinates, and its three-dimensional structural information back to the ground receiving device.

[0088] In some embodiments, step S11 (obtaining multiple images of the damaged road and the corresponding location coordinates of the multiple images) can be implemented through the following steps S111-S112, referring to... Figure 2 As shown:

[0089] S111. Divide the damaged road into a first preset number of damaged road segments according to a preset method.

[0090] The preset methods include, but are not limited to, preset length, preset area, etc. The first preset quantity can be determined according to the actual situation. For example, the first preset quantity can be 3, 5, 8, etc., and there is no specific restriction here.

[0091] Specifically, depending on the actual situation, the road segments are divided according to a certain length or a certain area, thus dividing the damaged road into several segments.

[0092] S112. Based on at least a first preset number of drones, take pictures of the first preset number of damaged road sections to obtain multiple images and the location coordinates corresponding to the multiple images.

[0093] Specifically, when a damaged road is divided into several sections, at least a number of drones are needed to photograph these sections, acquiring multiple road images and their corresponding location coordinates. Simultaneously photographing each section improves planning efficiency.

[0094] For example, when a damaged road is divided into 5 sections, at least 5 drones are needed to photograph each section, obtaining multiple road images and the corresponding location coordinates for each image. Assuming one of the sections has a curve, 2 or 3 drones can be deployed to photograph this section. It should be noted that images can be repeated, but no images can be omitted.

[0095] S12. Based on the shooting order of multiple images of the damaged road and the corresponding position coordinates of the multiple images, a complete topographic image of the damaged road is obtained by stitching them together.

[0096] Specifically, the ground receiving device stitches together the received images according to the shooting order and the location coordinates of each image to restore the complete environmental landscape of the damaged road.

[0097] As an optional implementation of this application, before performing step S13 (performing meta-cell processing on the complete topographic image of the damaged road and marking the damage range and depth of each damaged area), the following steps may also be performed:

[0098] Image preprocessing is performed on the complete topographic image of the damaged road to determine each damaged area of ​​the road.

[0099] Specifically, because the characteristics of roads are quite prominent, both road boundaries and road surface conditions can be identified through pixel mutations.

[0100] For example, the edges of each damaged region can be determined based on the location where the pixel value changes abruptly. In an image, since pixels are discrete, the Sobel operator or Canny operator is used to approximate the gradient value of each pixel in the entire image, where points with gradients significantly greater than those of neighboring pixels are considered edges.

[0101] S13. Perform meta-cell processing on the complete topographic image of the damaged road, and mark the damage range and damage depth of each damaged area.

[0102] The meta-cell processing involves dividing the complete terrain image of the damaged road into units according to a preset size. The preset size can be a grid with dimensions such as 10cm*10cm, 20cm*20cm, or 50cm*50cm. The selection of the preset size depends on the data processing capability of the ground receiving device, which specifically includes computing power, computational accuracy, and computational efficiency. Computing power is mainly determined by the CPU's frequency and number of cores. Under the same partitioning method, a higher-spec CPU has faster computational efficiency; therefore, in this embodiment, computing power is a prerequisite. Under this premise, computational accuracy and efficiency need to be determined based on the CPU specifications of the existing computer host. If the accuracy requirement is too high, the computational efficiency will decrease.

[0103] The damage range can be understood as the damaged area. In this embodiment, since the shape of each damaged area is not fixed, the damage range is determined, and the repair route is planned based on the damage range. The damage depth is used to determine the volume of filling material during repair.

[0104] Specifically, the identified roads and damaged areas are digitized and saved according to the actual geographical location and the geographic coordinates bound to the image. The saved data includes the coordinates of the road edge and the coordinates of the damaged area.

[0105] In some embodiments, step S13 (performing meta-cell processing on the complete topographic image of the damaged road and marking the damage range and depth of each damaged area) can be implemented in the following manner:

[0106] a. Divide the complete topographic image of the damaged road according to a preset size, and determine that the complete topographic image of the damaged road is divided into a second preset number of cells.

[0107] The preset size can be a grid of 10cm*10cm, 20cm*20cm, 50cm*50cm, etc. The preset quantity can be tens, hundreds, thousands, etc., depending on the actual needs on site; no specific limit is imposed here.

[0108] Specifically, the complete topographic image of the damaged road is divided according to a preset size, and the complete topographic image of the damaged road is divided into several cells.

[0109] b. Obtain the damage range and damage depth of each damaged area.

[0110] Specifically, based on pixel mutation, the damage range of each damaged area can be initially determined. Since areas within the cell range need to be repaired, the damage range of each damaged area can be further determined. The three-dimensional information corresponding to each image is determined by measuring the distance between the sensor transmitter and the target object using a lidar ranging module. LiDAR, short for laser detection and ranging system, analyzes the magnitude of reflected energy, amplitude, frequency, and phase of the reflected wave spectrum by measuring the propagation distance between the sensor transmitter and the target object, thereby presenting precise three-dimensional structural information of the target object. In this embodiment, the communication module of the ground receiving device receives each image, the corresponding position coordinates of each image, and the corresponding three-dimensional information for each image. The three-dimensional information for each image includes the damage depth of each damaged area.

[0111] c. Using the second preset number of cells as the background, mark the damage range and damage depth of each damaged area.

[0112] Specifically, using cells of a preset size as a background, the extent and depth of damage in each damaged area are marked.

[0113] S14. Based on the meta-cell algorithm, plan the damage range and damage depth of each damaged area to obtain the optimal repair scheme for the damaged road.

[0114] Specifically, each small unit is considered as a metacell. The characteristic state of each metacell may be different. It only exchanges data with the surrounding cells, and finally deduces the macroscopic state of the complete landform of the damaged road.

[0115] For example, refer to Figure 3 As shown, taking a damaged section of highway as an example, the demonstration shows how to plan a road that can be temporarily used by vehicles. Circles filled with a grid pattern represent the damaged area, and rectangles filled with small dots represent access points for work (e.g.,...). Figure 3 For example, Figure 3The diagram contains access points 1, 2, 3, 4, and 5. The rectangular area represents the optimal repair route obtained through planning. The task is to find a section of this route that meets certain length and width requirements while minimizing the cost of repairing the damaged area. In practice, the optimal repair solution depends on specific requirements, such as the principle of minimizing material usage or the principle of minimizing repair time. Each principle involves different factors and their corresponding weights. The principle of minimizing repair time disregards material costs and focuses solely on repair speed; the principle of minimizing material usage aims to save materials as much as possible.

[0116] In some embodiments, step S14 (planning the damage range and depth of each damaged area based on the meta-cell algorithm to obtain the optimal repair scheme for the damaged road) can be implemented in the following manner A or B:

[0117] A. Based on the first preset rule, plan the damage range and damage depth of each damaged area to obtain the optimal repair plan for the damaged road.

[0118] The first preset rule is to repair the damaged road based on the principle of using the least amount of materials.

[0119] Specifically, the principle of minimum material usage needs to consider the number of damaged areas and the amount of material required for each damaged area. Therefore, the total material usage for each repair route can be expressed by the following formula (1):

[0120]

[0121] Among them, C total C represents the total material usage for each repair route, where i represents the i-th damaged area. i This represents the amount of material used in the i-th damaged area.

[0122] In some embodiments, method A (planning the damage range and depth of each damaged area according to a first preset rule to obtain the optimal repair solution for the damaged road) can be implemented through the following steps:

[0123] Determine the preset size of the meta-cells and the parameters of the target road section to be repaired.

[0124] The parameters of the target road segment to be repaired include: the length and the width of the target road segment to be repaired.

[0125] Specifically, the preset grid size can be 10cm*10cm, 20cm*20cm, 50cm*50cm, etc. The length of the target repair section is less than the length of the damaged road, and the width of the target repair section is less than the width of the damaged road section.

[0126] The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route.

[0127] For example, suppose a damaged road is 1000 meters long and 200 meters wide; we need to determine an optimal road that is 500 meters long and 100 meters wide. We traverse the network sequentially along the horizontal and vertical directions of the element cells, moving one element cell at a time by default. When encountering a more severely damaged area, we can move multiple element cells as needed. During the traversal, we determine the number of damaged areas for each repair route.

[0128] Based on the number of damaged areas along each repair route, determine the material usage for each damaged area.

[0129] Specifically, the number of cells falling on the grid can be determined based on the extent of each damaged area, thus obtaining the area of ​​each damaged area. Furthermore, the area of ​​each damaged area is multiplied by the damage depth to obtain the material usage of each damaged area.

[0130] The total material usage for each repair route is determined based on the number of damaged areas along each repair route and the material usage for each damaged area.

[0131] The first target repair route is determined as the optimal repair scheme for the damaged road, and the first target repair route is the repair route corresponding to the minimum total material usage.

[0132] For example, assuming there are three repair routes that meet the requirements for the length and width of the target repair section, the final first target repair route is determined according to the principle of minimum material usage.

[0133] B. Based on the second preset rule, plan the damage range and damage depth of each damaged area to obtain the optimal repair plan for the damaged road.

[0134] The second preset rule is to repair the damaged road based on the principle of minimizing repair time.

[0135] Specifically, the principle of minimizing repair time needs to consider the following factors: the number of damaged areas, the amount of materials used for each repair route, and the work entry time for each repair route. The work entry time includes the time it takes for materials to reach the repair site and the time it takes for personnel to reach the repair site. In addition, the weighting factors corresponding to each factor need to be considered. Therefore, the total workload of each repair route can be expressed by the following formula (2):

[0136] V total =ax+by+cz formula (2)

[0137] Among them, V total denoted by , x represents the total workload of each repair route, y represents the number of damaged areas in each repair route, z represents the start time of the operation for each repair route, a represents the weight of the number of damaged areas in each repair route, b represents the weight of the material usage in each repair route, and c represents the weight of the start time of the operation for each repair route.

[0138] In some embodiments, method B (planning the damage range and depth of each damaged area according to a second preset rule to obtain the optimal repair solution for the damaged road) can be implemented through the following steps:

[0139] Determine the preset size of the meta-cells and the parameters of the target road section to be repaired.

[0140] The parameters of the target road segment to be repaired include: the length and the width of the target road segment to be repaired.

[0141] The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route.

[0142] Based on the number of damaged areas along each repair route, determine the material usage for each repair route and the start time for each repair operation.

[0143] Specifically, first, determine the material usage for each damaged area; second, determine the material usage for each repair route; in addition, simultaneously determine the work entry time for each damaged area, and then determine the work entry time for each repair route.

[0144] Determine the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient.

[0145] Wherein, the first weighting coefficient is the weight of the number of damaged areas in each repair route, the second weighting coefficient is the weight of the material usage in each repair route, and the third weighting coefficient is the weight of the operation entry time in each repair route.

[0146] The total workload of each repair route is determined based on the number of damaged areas, the first weighting coefficient, the material usage of each repair route, the second weighting coefficient, the operation entry time of each repair route, and the third weighting coefficient.

[0147] The second target repair route is determined as the optimal repair scheme for the damaged road, and the second target repair route is the repair route corresponding to the shortest repair time.

[0148] For example, assuming there are three repair routes that meet the requirements for the length and width of the target repair section, the final second target repair route is determined according to the principle of the shortest repair time.

[0149] Applying the embodiments of this application, the method for determining the optimal road repair scheme provided in this application first acquires multiple images of the damaged road and the corresponding location coordinates of the multiple images, stitches them together to obtain a complete topographic image of the damaged road, performs meta-cell processing on the complete topographic image of the damaged road, and marks the damage range and damage depth of each damaged area. The meta-cell processing involves unitizing the complete topographic image of the damaged road according to a preset size. Finally, based on the damage range and damage depth of each damaged area, a planning process is performed to obtain the optimal repair scheme for the damaged road. Because the planning of the damage range and damage depth of each damaged area is based on a meta-cell algorithm, the problem of low planning efficiency of the optimal road repair scheme caused by human operation is avoided, further improving the planning accuracy of the optimal road repair scheme.

[0150] In one embodiment, such as Figure 4 As shown, a road repair optimal solution determination device 400 is provided, comprising:

[0151] The acquisition module 410 is used to acquire multiple images of the damaged road and the location coordinates corresponding to the multiple images;

[0152] The stitching module 420 is used to stitch together a complete topographic image of the damaged road based on the shooting order of multiple images of the damaged road and the corresponding position coordinates of the multiple images;

[0153] The marking module 430 is used to perform meta-cell processing on the complete topographic image of the damaged road, marking the damage range and damage depth of each damaged area; the meta-cell processing is to perform unitization processing on the complete topographic image of the damaged road according to a preset size;

[0154] The planning module 440 is used to plan the damage range and damage depth of each damaged area based on the meta-cell algorithm, and obtain the optimal repair scheme for the damaged road.

[0155] As an optional implementation of this application, the acquisition module 410 is specifically used for:

[0156] The damaged roads are divided into a first preset number of damaged road segments according to a preset method.

[0157] At least a first preset number of drones are used to photograph the first preset number of damaged road sections, and multiple images and the location coordinates corresponding to the multiple images are obtained.

[0158] As an optional implementation of this application, the apparatus further includes:

[0159] The preprocessing module is used to perform image preprocessing on the complete topographic image of the damaged road to determine the various damaged areas of the damaged road.

[0160] As an optional implementation of this application, the marking module 430 is specifically used for:

[0161] The complete topographic image of the damaged road is divided according to a preset size, and the complete topographic image of the damaged road is divided into a second preset number of cells;

[0162] Obtain the damage range and damage depth of each damaged area;

[0163] Using the second preset number of cells as a background, mark the damage range and damage depth of each damaged area.

[0164] As an optional implementation of this application, the planning module 440 includes:

[0165] The first planning unit is used to plan the damage range and depth of each damaged area according to a first preset rule, and to obtain the optimal repair plan for the damaged road; the first preset rule is to repair the damaged road based on the principle of minimizing material usage;

[0166] or;

[0167] The second planning unit is used to plan the damage range and damage depth of each damaged area according to the second preset rule, and obtain the optimal repair scheme for the damaged road; the second preset rule is to repair the damaged road based on the principle of the shortest repair time.

[0168] As an optional implementation of this application, the first planning unit is configured to:

[0169] The preset size of the meta-cell and the parameters of the target road segment to be repaired are determined; the parameters of the target road segment to be repaired include: the length and width of the target road segment to be repaired;

[0170] The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route;

[0171] Based on the number of damaged areas along each repair route, determine the material usage for each damaged area;

[0172] The total material usage for each repair route is determined based on the number of damaged areas in each repair route and the material usage for each damaged area.

[0173] The first target repair route is determined as the optimal repair scheme for the damaged road, and the first target repair route is the repair route corresponding to the minimum total material usage.

[0174] As an optional implementation of this application, the second planning unit is specifically used for:

[0175] The preset size of the meta-cell and the parameters of the target road segment to be repaired are determined; the parameters of the target road segment to be repaired include: the length and width of the target road segment to be repaired;

[0176] The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route;

[0177] Based on the number of damaged areas along each repair route, determine the material usage for each repair route and the start time for each repair route.

[0178] Determine the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient;

[0179] Wherein, the first weighting coefficient is the weight of the number of damaged areas in each repair route, the second weighting coefficient is the weight of the material usage in each repair route, and the third weighting coefficient is the weight of the operation entry time in each repair route.

[0180] The total workload of each repair route is determined based on the number of damaged areas, the first weighting coefficient, the material usage of each repair route, the second weighting coefficient, the operation entry time of each repair route, and the third weighting coefficient.

[0181] The second target repair route is determined as the optimal repair scheme for the damaged road, and the second target repair route is the repair route corresponding to the shortest repair time.

[0182] Applying the embodiments of this application, the road repair optimal solution determination device provided in this application first acquires multiple images of the damaged road and the corresponding location coordinates of the multiple images, stitches them together to obtain a complete topographic image of the damaged road, performs meta-cell processing on the complete topographic image of the damaged road, and marks the damage range and damage depth of each damaged area. The meta-cell processing involves processing the complete topographic image of the damaged road into units according to a preset size. Finally, based on the damage range and damage depth of each damaged area, a plan is made to obtain the optimal repair solution for the damaged road. Since the damage range and damage depth of each damaged area are planned based on the meta-cell algorithm, the problem of low planning efficiency of the optimal road repair solution caused by human operation is avoided, and the planning accuracy of the optimal road repair solution is further improved.

[0183] Specific limitations regarding the device for determining the optimal road repair solution can be found in the limitations of the method for determining the optimal road repair solution described above, and will not be repeated here. Each module in the aforementioned device for determining the optimal road repair solution can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor of the electronic device in hardware form, or stored in the processor of the electronic device in software form, so that the processor can call and execute the corresponding operations of each module.

[0184] This application also provides an electronic device. Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 5 As shown, the electronic device provided in this embodiment includes a memory 51 and a processor 52. The memory 51 stores computer programs; the processor 52 executes the steps of any embodiment of the road repair optimal solution determination method provided in the above method embodiments when the computer program is invoked. The electronic device includes a processor, a memory, a communication interface, a display screen, and an input device connected via a system bus. The processor of the electronic device provides computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. When the computer program is executed by the processor, it implements a road repair optimal solution determination method. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen. The input device of the electronic device can be a touch layer covering the display screen, or buttons, a trackball, or a touchpad provided on the casing of a computer device, or an external keyboard, touchpad, or mouse, etc.

[0185] Those skilled in the art will understand that Figure 5The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific electronic devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0186] In one embodiment, the road repair optimal solution determination device provided in this application can be implemented in the form of a computer, and the computer program can be used in, for example... Figure 5 The electronic device shown operates on this device. The memory of the electronic device can store the various program modules that make up the device for determining the optimal road repair solution for a specific client type, such as... Figure 4 The acquisition module 410, splicing module 420, marking module 430, and planning module 440 are shown. The computer program comprised of these modules causes the processor to execute the steps in the road repair optimal solution determination method for the electronic device of the various embodiments of this application described in this specification.

[0187] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for determining the optimal road repair solution provided in the above-described method embodiments.

[0188] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code.

[0189] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0190] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0191] Computer-readable media include both permanent and non-permanent, removable and non-removable storage media. Storage media can store information using any method or technology; the information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media do not include transient computer-readable media, such as modulated data signals and carrier waves.

[0192] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0193] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement this disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for determining the optimal road repair solution, characterized in that, The method includes: Obtain multiple images of the damaged road and the corresponding location coordinates of the multiple images; Based on the shooting order of multiple images of the damaged road and the corresponding position coordinates of the multiple images, a complete topographic image of the damaged road is obtained by stitching them together; The complete topographic image of the damaged road is subjected to meta-cell processing to mark the damage range and depth of each damaged area; the meta-cell processing is to perform unitization processing on the complete topographic image of the damaged road according to a preset size; The meta-cell algorithm is used to plan the damage range and depth of each damaged area to obtain the optimal repair plan for the damaged road; wherein, The meta-cellular algorithm is used to plan the damage range and depth of each damaged area to obtain the optimal repair plan for the damaged road, including: The preset size of the meta-cell and the parameters of the target road segment to be repaired are determined; the parameters of the target road segment to be repaired include: the length and width of the target road segment to be repaired; The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route; Based on the number of damaged areas along each repair route, determine the material usage for each damaged area; Based on the number of damaged areas in each repair route and the amount of material used in each damaged area, the target repair route is determined as the optimal repair plan for the damaged road.

2. The method according to claim 1, characterized in that, The process of acquiring multiple images of the damaged road and the corresponding location coordinates of the multiple images includes: The damaged roads are divided into a first preset number of damaged road segments according to a preset method. At least a first preset number of drones are used to photograph the first preset number of damaged road sections, and multiple images and the location coordinates corresponding to the multiple images are obtained.

3. The method according to claim 1, characterized in that, Before performing meta-cell processing on the complete topographic image of the damaged road and marking the damage extent and depth of each damaged area, the method further includes: Image preprocessing is performed on the complete topographic image of the damaged road to determine each damaged area of ​​the road.

4. The method according to claim 1, characterized in that, The process of performing meta-cell processing on the complete topographic image of the damaged road, and marking the damage range and depth of each damaged area, includes: The complete topographic image of the damaged road is divided according to a preset size, and the complete topographic image of the damaged road is divided into a second preset number of cells; Obtain the damage range and damage depth of each damaged area; Using the second preset number of cells as a background, mark the damage range and damage depth of each damaged area.

5. The method according to claim 1, characterized in that, The meta-cellular algorithm is used to plan the damage range and depth of each damaged area to obtain the optimal repair plan for the damaged road, including: The damage range and depth of each damaged area are planned according to the first preset rule to obtain the optimal repair plan for the damaged road; the first preset rule is to repair the damaged road based on the principle of minimizing material usage; or; The damage range and depth of each damaged area are planned according to the second preset rule to obtain the optimal repair scheme for the damaged road; the second preset rule is to repair the damaged road based on the principle of the shortest repair time.

6. The method according to claim 5, characterized in that, The step of planning the damage range and depth of each damaged area according to a first preset rule to obtain the optimal repair plan for the damaged road includes: The preset size of the meta-cell and the parameters of the target road segment to be repaired are determined; the parameters of the target road segment to be repaired include: the length and width of the target road segment to be repaired; The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route; Based on the number of damaged areas along each repair route, determine the material usage for each damaged area; The total material usage for each repair route is determined based on the number of damaged areas in each repair route and the material usage for each damaged area. The first target repair route is determined as the optimal repair scheme for the damaged road, and the first target repair route is the repair route corresponding to the minimum total material usage.

7. The method according to claim 5, characterized in that, The step of planning the damage range and depth of each damaged area according to the second preset rule to obtain the optimal repair plan for the damaged road includes: The preset size of the meta-cell and the parameters of the target road segment to be repaired are determined; the parameters of the target road segment to be repaired include: the length and width of the target road segment to be repaired; The complete topographic image of the damaged road is traversed according to a preset size to obtain the number of damaged areas for each repair route; Based on the number of damaged areas along each repair route, determine the material usage for each repair route and the start time for each repair route. Determine the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient; Wherein, the first weighting coefficient is the weight of the number of damaged areas in each repair route, the second weighting coefficient is the weight of the material usage in each repair route, and the third weighting coefficient is the weight of the operation entry time in each repair route. The total workload of each repair route is determined based on the number of damaged areas, the first weighting coefficient, the material usage of each repair route, the second weighting coefficient, the operation entry time of each repair route, and the third weighting coefficient. The second target repair route is determined as the optimal repair scheme for the damaged road, and the second target repair route is the repair route corresponding to the shortest repair time.

8. A device for determining the optimal road repair solution, characterized in that, include: The acquisition module is used to acquire multiple images of the damaged road and the corresponding location coordinates of the multiple images; The stitching module is used to stitch together multiple images of the damaged road according to the shooting order and the corresponding position coordinates of the multiple images to obtain a complete topographic image of the damaged road; A labeling module is used to perform meta-cell processing on the complete topographic image of the damaged road, and to label the damage range and damage depth of each damaged area; the meta-cell processing is to perform unitization processing on the complete topographic image of the damaged road according to a preset size; The planning module is used to plan the damage range and depth of each damaged area based on the meta-cell algorithm, and to obtain the optimal repair plan for the damaged road; wherein, The planning module is specifically used for: determining the preset size of the meta-cells and the parameters of the target repair section; the parameters of the target repair section include: the length and width of the target repair section; traversing the complete topographic image of the damaged road according to the preset size to obtain the number of damaged areas for each repair route; determining the material usage for each damaged area based on the number of damaged areas for each repair route; and determining the target repair route as the optimal repair scheme for the damaged road based on the number of damaged areas for each repair route and the material usage for each damaged area.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the method for determining the optimal road repair scheme as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, implements the method for determining the optimal road repair scheme as described in any one of claims 1 to 7.

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