Intelligent analysis system based on expressway low-carbon reconstruction and extension planning

Abstract

The invention relates to the technical field of data analysis, in particular to an intelligent analysis system based on expressway low-carbon reconstruction and extension planning, which comprises an acquisition layer, an analysis layer and a construction layer, the expressway reconstruction and extension area is uploaded through the collection layer, environment parameters are synchronously collected in the expressway reconstruction and extension area, and the analysis layer synchronously receives the environment parameters of the expressway reconstruction and extension area. According to the method, the expressway reconstruction and extension area is segmented, obstacle identification is carried out on each segmented sub-area, reconstruction and extension recommendation index analysis of the segmented sub-areas is realized, the segmented sub-areas are selected according to an analysis result, and finally an expressway reconstruction and extension path is limited based on a selection result. Therefore, the development of the expressway reconstruction and extension planning work has lower requirements on workers, and expressway reconstruction and extension planning can be carried out on the expressway reconstruction and extension area more intelligently, accurately and reasonably.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and particularly to an intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways. Background Art

[0002] The low-carbon reconstruction and expansion planning of expressways focuses on energy conservation, emission reduction and sustainable development. By optimizing the route design to reduce land occupation, adopting new environmental protection materials to reduce energy consumption, and using intelligent transportation systems to improve traffic efficiency, reduce vehicle idling and congestion. It is committed to minimizing the impact on the environment while improving the highway performance.

[0003] The invention patent with the application number 202410428239.2 discloses a safety intelligent control system for expressway reconstruction and expansion construction operation areas, including: intelligent monitoring terminals, intelligent warning terminals and cloud platforms; intelligent monitoring terminals: used to obtain the operation area information of the target area and upload it to the cloud platform; where the target area refers to the actual expressway reconstruction and expansion construction operation area; cloud platform: used to receive the operation area information collected by the intelligent monitoring terminals, analyze the operation area information to obtain an analysis result; issue a warning message based on the analysis result; and issue a response instruction to the intelligent warning terminal based on the warning message; intelligent warning terminal: used to control warning devices according to the response instruction to give warning prompts to drivers and operators in the operation area; where the warning devices include: alarm bells, warning lights or intelligent display signs.

[0004] This application aims to solve the problem that: "The control strategies for expressway reconstruction and expansion operation areas disclosed in the prior art mainly provide warning information for drivers based on the location information of the construction operation area and provide warning information for operators when entering the operation area, realizing double-layer active safety protection; in the process of safety control in the prior art, only the sign information set in the construction operation area is used to remind vehicles to limit speed, and the vehicle speed limit cannot be reasonably regulated, and when an emergency occurs, the upstream incoming vehicles cannot be reminded, and the operators cannot be warned. The operators, operation vehicles, operation equipment, etc. are in a traditional scattered management state, resulting in low safety control efficiency and high safety risks in the expressway operation area."

[0005] However, most of the existing expressway reconstructions and expansions establish project teams for the reconstruction and expansion work, and design the reconstructed and expanded expressways through project team meetings and decision-making. This method has poor efficiency and is limited by the experience of the staff in the project team. If "low-carbon" is to be considered during the expressway reconstruction and expansion process, the artificial planning and design often have even worse benefits.

[0006] Therefore, we propose an intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways. Summary of the Invention

[0007] In view of the above-mentioned disadvantages of the prior art, the present invention provides an intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways, which solves the technical problems raised in the above-mentioned background art.

[0008] To achieve the above objectives, the present invention is realized through the following technical solutions:

[0009] An intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways includes: a collection layer, an analysis layer, and a construction layer;

[0010] The reconstruction and expansion area of the expressway is uploaded through the collection layer, and environmental parameters are collected synchronously in the reconstruction and expansion area of the expressway. The analysis layer synchronously receives the environmental parameters of the reconstruction and expansion area of the expressway, analyzes the reconstruction and expansion recommendation index of each area in the reconstruction and expansion area of the expressway based on the environmental parameters of the reconstruction and expansion area of the expressway. The construction layer further receives the reconstruction and expansion recommendation index of each area in the reconstruction and expansion area of the expressway in the analysis layer, selects the area in the reconstruction and expansion area of the expressway based on the recommendation indication, determines the reconstruction and expansion path of the expressway with the selected area, and finally outputs the reconstruction and expansion path of the expressway;

[0011] The analysis layer includes a marking module, an analysis module, and a decision-making module. The marking module is used to mark the entrance and exit ends of the expressway in the reconstruction and expansion area of the expressway. The analysis module is used to analyze the reconstruction and expansion recommendation index of each area in the reconstruction and expansion area of the highway. The decision-making module is used to receive the analysis results of the reconstruction and expansion recommendation index of each area in the analysis module and apply the analysis results to decide on the selected area where the expressway is located;

[0012] The marking module is wirelessly interconnected with a collection module. The collection module is wirelessly interconnected with a segmentation module and an upload module. The marking module is wirelessly interconnected with an analysis module and a decision-making module. The decision-making module is wirelessly interconnected with a receiving module. The receiving module is wirelessly interconnected with a construction module and an output module;

[0013] The analysis logic of the reconstruction and expansion recommendation index of each area in the reconstruction and expansion area of the highway in the analysis module is expressed as:

[0014]

[0015] Where: K(α) is the reconstruction and expansion recommendation index of area α in the reconstruction and expansion area of the highway; q is the number of underground pipeline nodes in the area; S is the occupied area of obstacles; is the complexity of the area where the obstacle is located, which is the contour of the obstacle in area α; M is the number of underground pipelines in the area; ω α is the weight;

[0016] Among them, the larger the calculated value of K(α), the more suitable the area α is as the area where the expressway is located. Conversely, it means that the area α is less suitable as the area where the expressway is located. The weight ω α is determined based on the obstacle type in the environmental parameters;

[0017] The complexity of the area where the obstacle is located as represented by the contour of the obstacle in the area α The calculation formula is:

[0018]

[0019] In the formula: L is the contour length of the obstacle in the area α; m is the total number of vertices on the contour of the obstacle in the area α; θ j and θ j+1 are the included angles between the j-th and (j + 1)-th vertices.

[0020] Furthermore, the acquisition layer includes an upload module, an analysis module, and an acquisition module. The upload module is used to upload the information of the expressway reconstruction and expansion area. The segmentation module is used to receive the information of the expressway reconstruction and expansion area uploaded by the upload module, determine the expressway reconstruction and expansion area based on the information of the expressway reconstruction and expansion area, and segment the expressway reconstruction and expansion area. The acquisition module is used to receive the segmentation result of the expressway reconstruction and expansion area in the segmentation module and acquire the environmental parameters corresponding to each segmented area;

[0021] Among them, the information of the expressway reconstruction and expansion area uploaded by the upload module is no less than three sets of position coordinates. After the segmentation module receives the information of the expressway reconstruction and expansion area, it connects the adjacent position coordinates included in the information of the expressway reconstruction and expansion area to construct a closed planar graph. The area defined by the closed planar graph is the expressway reconstruction and expansion area.

[0022] Furthermore, a segmentation logic for the expressway reconstruction and expansion area is set in the segmentation module, and the segmentation module performs segmentation processing on the expressway reconstruction and expansion area based on the segmentation logic;

[0023] The segmentation logic for the expressway reconstruction and expansion area is expressed as:

[0024] Obtain the width of the expressway in the expressway reconstruction and expansion area, and use the width of the expressway as the spacing between adjacent axes in the segmentation axis network;

[0025] Draw the axis network and cover the drawn axis network on the surface of the closed planar graph corresponding to the expressway reconstruction and expansion area;

[0026] Use 1 / 10 to 1 / 20 of the width of the expressway as the axis network movement unit, and translate the axis network on the surface of the closed planar graph longitudinally and horizontally;

[0027]

[0028] In the formula: ε is the determination value; n is the total number of grids on the edge position of the closed planar figure after being divided by the axis network and including the closed planar figure; (s in ) i is the area occupied by the closed planar figure in the i-th grid; W is the width of the highway;

[0029] Among them, after each movement of the axis network on the surface of the closed planar figure, the determination value ε is obtained based on the above formula. When the maximum determination value is selected, the movement result of the axis network on the surface of the closed planar figure is used as the division of the highway reconstruction and expansion area.

[0030] Furthermore, the acquisition module is integrated by a multi-spectral camera carried by a drone. After the highway reconstruction and expansion area is divided, the actual coordinates of each sub-area are further obtained. Taking the center coordinates of the sub-area in the actual coordinates of each sub-area as the environmental parameter acquisition position, the environmental parameter acquisition operation of each sub-area is performed;

[0031] Among them, after the acquisition module acquires the environmental parameters of each sub-area, the environmental parameters of each sub-area are synchronously marked with different marks according to the coordinates used in the acquisition stage, and then the storage operation is performed. The environmental parameters include: obstacle type, obstacle area, contour of the area where the obstacle is located, and underground pipeline distribution information. The obstacle types include: buildings, structures, vegetation, lakes, rivers, canyons, and mountains.

[0032] Furthermore, during the operation stage of the marking module, when marking the entrance end and the exit section of the highway in the highway reconstruction and expansion area, each sub-area obtained by dividing the highway reconstruction and expansion area is used as the marking target, and the marking operation is manually performed by the system-end user;

[0033] During the operation stage of the analysis module, the highway reconstruction and expansion accuracy is set. Based on the set highway reconstruction and expansion accuracy, the sub-areas in the highway reconstruction and expansion area are recombined. The recombined area is denoted as the recombined area. Taking the recombined area as the analysis target, based on the analysis logic of the reconstruction and expansion recommendation index, a unique sub-area is captured in each recombined area as the optional highway route area;

[0034] Among them, the sub-area with the largest reconstruction and expansion recommendation index in each recombined area is the capture target. The highway reconstruction and expansion accuracy takes the sub-areas in the highway reconstruction and expansion area as the smallest unit, then the recombined area is expressed as x 2 , where x represents the number of sub-areas on the edge of the recombined area.

[0035] Furthermore, the weight ω α is obtained through the following formula:

[0036]

[0037] Where: τ α is the removal cost of the obstacle in area α determined based on the obstacle type in the environmental parameters;

[0038] Among them, the removal cost τ of the obstacle in area α determined based on the obstacle type in the environmental parameters α is user-defined by the system-side user.

[0039] Furthermore, during the operation phase of the decision module, the highway entrance and exit ends marked in the highway reconstruction and expansion area are obtained in the annotation module, the entrance end and the exit section are connected in the highway reconstruction and expansion area, and the reorganized areas penetrated by the connection line in the highway reconstruction and expansion area are further captured;

[0040] During the operation phase of the decision module, a screening interval for the reconstruction and expansion recommendation index is set, and all reorganized areas in the highway reconstruction and expansion area that meet the screening interval are captured based on the reconstruction and expansion recommendation index;

[0041] The results of capturing the reorganized areas twice are recorded as Grab1 and Grab2;

[0042] When Grab1 ∈ Grab2, the sub-area with the largest reconstruction and expansion recommendation index in each reorganized area included in Grab1 is used as the highway passing area;

[0043] When, the sub-area with the largest reconstruction and expansion recommendation index in the reorganized area corresponding to Grab1 ∩ Grab2 and the reorganized areas that are the nearest neighbors and meet the screening interval in each reorganized area included in Grab1-(Grab1 ∩ Grab2) is used as the highway passing area;

[0044] Among them, when the decision module determines the area where the highway is located, the set of each highway passing area is used as the area where the highway is located.

[0045] Furthermore, the construction layer includes a receiving module, a construction module, and an output module. The receiving module is used to analyze the area where the highway is located obtained during the operation of the analysis layer. The construction module is used to traverse each highway passing area included in the area where the highway is located, select a point in each highway passing area, and connect the selected points adjacent to each other to construct a highway reconstruction and expansion path. The output module is used to receive the highway reconstruction and expansion path constructed in the construction module and output the highway reconstruction and expansion path;

[0046] The highway reconstruction and expansion path output by the operation of the output module is targeted at the mobile computer device held by the system-side user, and the system-side user reads the highway reconstruction and expansion path on the mobile computer device;

[0047] Among them, the highway reconstruction and expansion path is output in the form of a set of position coordinates of each node on the path.

[0048] Furthermore, the operation of selecting points in the area passed by the highway in the construction module follows:

[0049] Identify the location of obstacles in the corresponding sub-region of the area passed by the high-speed path, and select a point far from the center point of the obstacle within the sub-region as the selected point.

[0050] Adopting the technical solution provided by the present invention, compared with the known public technology, it has the following beneficial effects:

[0051] The present invention provides an intelligent analysis system based on highway low-carbon reconstruction and expansion planning. During the operation of the system, "reconstruction and expansion low-carbon" is incorporated into the considerations of the reconstruction and expansion planning at the stage of highway reconstruction and expansion. By dividing the highway reconstruction and expansion area and identifying obstacles in each divided sub-region, the analysis of the reconstruction and expansion recommendation index of the divided sub-regions is realized, so as to select the divided sub-regions based on the analysis results, and finally limit the highway reconstruction and expansion path based on the selection results, making the development of highway reconstruction and expansion planning work less demanding on staff, and more intelligent, accurate and reasonable in planning the highway reconstruction and expansion area. Description of the Drawings

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0053] Figure 1 It is a schematic structural diagram of an intelligent analysis system based on highway low-carbon reconstruction and expansion planning;

[0054] Figure 2 It is a schematic diagram of the highway reconstruction and expansion area division logic in the present invention;

[0055] Figure 3 It is a schematic diagram of the highway reconstruction and expansion path output logic in the present invention. Detailed Embodiments

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0057] The following further describes the present invention with reference to embodiments.

[0058] Embodiment 1:

[0059] An intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways in this embodiment, as Figure 1 shown, includes: an acquisition layer, an analysis layer, and a construction layer;

[0060] The reconstruction and expansion area of the expressway is uploaded through the acquisition layer, and environmental parameters are collected synchronously in the reconstruction and expansion area of the expressway. The analysis layer synchronously receives the environmental parameters of the reconstruction and expansion area of the expressway, analyzes the reconstruction and expansion recommendation indexes of each area in the reconstruction and expansion area of the expressway based on the environmental parameters of the reconstruction and expansion area of the expressway. The construction layer further receives the reconstruction and expansion recommendation indexes of each area in the reconstruction and expansion area of the expressway in the analysis layer, selects the area in the reconstruction and expansion area of the expressway based on the recommendation indication, determines the reconstruction and expansion path of the expressway with the selected area, and finally outputs the reconstruction and expansion path of the expressway;

[0061] The acquisition layer includes an upload module, an analysis module, and a collection module. The upload module is used to upload the information of the reconstruction and expansion area of the expressway. The segmentation module is used to receive the information of the reconstruction and expansion area of the expressway uploaded by the upload module, determine the reconstruction and expansion area of the expressway based on the information of the reconstruction and expansion area of the expressway, segment the reconstruction and expansion area of the expressway, and the collection module is used to receive the segmentation results of the reconstruction and expansion area of the expressway in the segmentation module and collect the environmental parameters corresponding to each segmented area;

[0062] Among them, the information of the reconstruction and expansion area of the expressway uploaded by the upload module operation is no less than three groups of position coordinates. After the segmentation module operation receives the information of the reconstruction and expansion area of the expressway, it is connected adjacent to each other based on the position coordinates included in the information of the reconstruction and expansion area of the expressway to construct a closed planar graph. The area defined by the closed planar image is the reconstruction and expansion area of the expressway;

[0063] There is a reconstruction and expansion area segmentation logic set in the segmentation module, and the segmentation module performs segmentation processing on the reconstruction and expansion area of the expressway based on the segmentation logic;

[0064] The reconstruction and expansion area segmentation logic is expressed as:

[0065] Obtain the width of the expressway in the reconstruction and expansion area of the expressway, and use the width of the expressway as the spacing between adjacent axes in the division axis network;

[0066] Draw an axis network and cover the drawn axis network on the surface of the closed planar graph corresponding to the reconstruction and expansion area of the expressway;

[0067] Use 1 / 10 to 1 / 20 of the width of the expressway as the axis network movement unit, and translate the axis network on the surface of the closed planar graph longitudinally and horizontally;

[0068]

[0069] In the formula: ε is the determination value; n is the total number of grids on the closed planar graph whose edge positions after being divided by the axis network include the closed planar graph; (s in ) i is the area occupied by the closed planar graph in the i-th grid; W is the width of the expressway;

[0070] Among them, after each movement of the axis network on the surface of the closed planar graph, the determination value ε is obtained based on the above formula. When the maximum determination value is selected, the movement result of the axis network on the surface of the closed planar graph is used for the division of the reconstruction and expansion area of the expressway;

[0071] Through the above logical formula, the final result of the movement of the axis network on the surface of the closed planar graph is further defined, ensuring the optimal configuration of the axis network and the surface of the closed planar graph, so as to improve the accuracy of the final output of the expressway reconstruction and expansion path by the system.

[0072] The analysis layer includes a marking module, an analysis module, and a decision-making module. The marking module is used to mark the entrance and exit ends of the expressway in the reconstruction and expansion area of the expressway. The analysis module is used to analyze the reconstruction and expansion recommendation index of each area in the reconstruction and expansion area of the highway. The decision-making module is used to receive the analysis results of the reconstruction and expansion recommendation index of each area in the analysis module and apply the analysis results to decide and select the area where the expressway is located;

[0073] The analysis logic of the reconstruction and expansion recommendation index of each area in the analysis module for the reconstruction and expansion area of the highway is expressed as:

[0074]

[0075] In the formula: K(α) is the reconstruction and expansion recommendation index of area α in the reconstruction and expansion area of the highway; q is the number of underground pipeline nodes in the area; S is the occupied area of obstacles; is the complexity of the area where the obstacle is located in the contour of the obstacle in area α; M is the number of underground pipelines in the area; ω α is the weight;

[0076] Among them, the larger the calculated value of K(α), the more suitable the area α is as the area where the highway is located. On the contrary, it means that the area α is less suitable as the area where the highway is located, and the weight ω α is determined based on the obstacle type in the environmental parameters;

[0077] The complexity of the area where the obstacle is located as shown by the contour of the obstacle in area α The calculation formula is:

[0078]

[0079] In the formula: L is the contour length of the obstacle in area α; m is the total number of vertices on the contour of the obstacle in area α; θ j and θ j+1 are the included angles of the j-th and j + 1-th vertices;

[0080] The weight ω α is obtained through the following formula:

[0081]

[0082] In the formula: τ α is the removal cost of the obstacle in area α determined based on the obstacle type in the environmental parameters;

[0083] Among them, the removal cost τ of the obstacle in area α determined based on the obstacle type in the environmental parameters α is user-defined by the system-end user;

[0084] Through the above logical formula, the reconstruction and expansion recommendation index of each area in the highway reconstruction and expansion area is calculated, so as to provide support for the construction of the highway reconstruction and expansion path finally output by the system.

[0085] During the operation stage of the decision-making module, the marked highway entrance and exit ends in the highway reconstruction and expansion area are obtained in the marking module, and a line is connected between the entrance and exit sections in the highway reconstruction and expansion area, and further the reorganized areas penetrated by the connected line in the highway reconstruction and expansion area are captured;

[0086] During the operation stage of the decision-making module, a reconstruction and expansion recommendation index screening range is set, and all reorganized areas in the highway reconstruction and expansion area that meet the screening range are captured based on the reconstruction and expansion recommendation index;

[0087] The results of the two captures of the reorganized areas are recorded as Grab1 and Grab2;

[0088] When Grab1 ∈ Grab2, the sub-area with the largest reconstruction and expansion recommendation index in each reorganized area included in Grab1 is used as the area through which the highway passes;

[0089] When it is, the sub-region with the largest reconstruction and expansion recommendation index in the reconstructed region corresponding to Grab1∩Grab2 and the reconstructed regions that are the nearest neighbors and meet the screening interval in Grab1-(Grab1∩Grab2) is used as the highway passing region;

[0090] Among them, when the decision-making module decides on the region where the highway is located, the set of highway passing regions is used as the region where the highway is located;

[0091] The construction layer includes a receiving module, a construction module, and an output module. The receiving module is used to analyze the region where the highway is located obtained by the operation of the analysis layer. The construction module is used to traverse each highway passing region included in the region where the highway is located, select a point in each highway passing region, and connect the selected points adjacent to each other to construct a highway reconstruction and expansion path. The output module is used to receive the highway reconstruction and expansion path constructed by the construction module and output the highway reconstruction and expansion path;

[0092] The highway reconstruction and expansion path output by the operation of the output module takes the mobile computer device held by the system-side user as the output target, and the system-side user reads the highway reconstruction and expansion path on the mobile computer device;

[0093] Among them, the highway reconstruction and expansion path is output in the form of a set of position coordinates of each node on the path;

[0094] The operation of selecting a point in the highway passing region in the construction module is subject to:

[0095] Identify the location of the obstacles in the sub-region corresponding to the highway path passing region, and select a point far from the center point of the obstacle within the sub-region as the selected point;

[0096] The annotation module is wirelessly interactively connected to a collection module. The collection module is wirelessly interactively connected to a segmentation module and an upload module. The annotation module is wirelessly interactively connected to an analysis module and a decision-making module. The decision-making module is wirelessly interactively connected to a receiving module. The receiving module is wirelessly interactively connected to a construction module and an output module.

[0097] In this embodiment, the uploading module runs to upload the information of the highway reconstruction and expansion area. The segmentation module synchronously receives the information of the highway reconstruction and expansion area uploaded by the uploading module, determines the highway reconstruction and expansion area based on the information of the highway reconstruction and expansion area, divides the highway reconstruction and expansion area, and the acquisition module further receives the segmentation result of the highway reconstruction and expansion area in the segmentation module, acquires the environmental parameters corresponding to each divided area, and then the annotation module annotates the entrance and exit ends of the highway in the highway reconstruction and expansion area. The analysis module synchronously analyzes the reconstruction and expansion recommendation index of each area in the highway reconstruction and expansion area. The decision-making module runs later to receive the analysis result of the reconstruction and expansion recommendation index of each area in the analysis module, applies the analysis result to decide and select the area where the highway is located, and then runs through each highway passing area included in the area where the highway is located through the receiving module's analysis layer. Select a point in each highway passing area, connect the selected points adjacent to each other to construct a highway reconstruction and expansion path. Finally, the output module receives the highway reconstruction and expansion path constructed by the construction module and outputs the highway reconstruction and expansion path;

[0098] Through the operation of the system in the above embodiment, an intelligent highway reconstruction and expansion design system that can comprehensively consider "low-carbon reconstruction and expansion" is brought to highway reconstruction and expansion, providing support for highway reconstruction and expansion design planning, effectively reducing the dependence on manual labor in the development of highway reconstruction and expansion planning and design work, and being more reasonable and efficient compared to manual planning and design;

[0099] See Figure 2 As shown, based on the letter label of the drawing sheet in the figure, the process of the axis network moving on the surface of the closed planar figure corresponding to the highway reconstruction and expansion area is shown, so that the axis network optimally covers the surface of the closed planar figure corresponding to the highway reconstruction and expansion area, thereby improving the accuracy of the highway reconstruction and expansion path output by the system;

[0100] See Figure 3 As shown, based on the arrow indication in the figure, from left to right, the connection line (dashed line) of the entrance and exit ends of the highway, the determined recombination area (a rectangle composed of four rectangles), the sub-areas in the highway reconstruction and expansion area, the selection points (points in the rectangle), and finally the highway reconstruction and expansion path obtained by connecting with a curve are shown.

[0101] Embodiment 2:

[0102] At the specific implementation level, on the basis of Embodiment 1, this embodiment further specifically describes a kind of intelligent analysis system based on highway low-carbon reconstruction and expansion planning with reference to Figure 1 As shown for further specific illustration of the intelligent analysis system based on highway low-carbon reconstruction and expansion planning in Embodiment 1:

[0103] The acquisition module is integrated by a multi - spectral camera carried by a drone. After the highway reconstruction and expansion area is segmented, the real - world coordinates of each sub - area are further obtained. Taking the center coordinates of each sub - area in the real - world coordinates of the sub - area as the environmental parameter acquisition position, the environmental parameter acquisition operation of each sub - area is performed;

[0104] Among them, after the acquisition module acquires the environmental parameters of each sub - area, it simultaneously marks the environmental parameters of each sub - area with the coordinates used in the acquisition stage, and then performs the storage operation. The environmental parameters include: obstacle type, obstacle area, contour of the area where the obstacle is located, and underground pipeline distribution information. The obstacle types include: buildings, structures, vegetation, lakes, rivers, canyons, and mountains.

[0105] Through the above settings, further operational data support is provided for the system in the above - mentioned Embodiment 1, ensuring the stable operation of the system in Embodiment 1 and outputting the highway reconstruction and expansion path.

[0106] As Figure 1 shown, during the operation stage of the annotation module, when annotating the highway entrance and exit sections in the highway reconstruction and expansion area, each sub - area obtained by segmentation in the highway reconstruction and expansion area is used as the annotation target, and the annotation operation is manually performed by the system - side user;

[0107] During the operation stage of the analysis module, the highway reconstruction and expansion accuracy is set. Based on the set highway reconstruction and expansion accuracy, the sub - areas in the highway reconstruction and expansion area are re - combined. The recombined area is denoted as the recombination area. Taking the recombination area as the analysis target, based on the analysis logic of the reconstruction and expansion recommendation index, a unique sub - area is captured in each recombination area as the optional highway path area;

[0108] Among them, the sub - area with the largest reconstruction and expansion recommendation index in each recombination area is the capture target. The highway reconstruction and expansion accuracy takes the sub - areas in the highway reconstruction and expansion area as the smallest unit, and the recombination area is denoted as x 2 , where x represents the number of sub - areas on the edge of the recombination area.

[0109] Through the above settings, the specific composition logic of the recombination area is further defined, providing the necessary operational data support for the operation of the system in the above - mentioned Embodiment 1.

[0110] In summary, during the operation of the system in the above embodiments, "low-carbon reconstruction and expansion" was incorporated into the considerations of the reconstruction and expansion plan during the highway reconstruction and expansion stage. By dividing the highway reconstruction and expansion area, identifying obstacles in each divided sub-area, and analyzing the reconstruction and expansion recommendation index of the divided sub-areas, the divided sub-areas were selected based on the analysis results. Finally, the highway reconstruction and expansion path was limited based on the selection results, making the implementation of the highway reconstruction and expansion plan less demanding on staff and more intelligent, accurate, and reasonable in planning the highway reconstruction and expansion area.

[0111] The above embodiments are only used to illustrate the technical solutions of the present invention, not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways, characterized in that, Including: A collection layer, an analysis layer, and a construction layer; The highway reconstruction and expansion area is uploaded through the collection layer, and environmental parameters are collected synchronously in the highway reconstruction and expansion area. The analysis layer synchronously receives the environmental parameters of the highway reconstruction and expansion area, analyzes the reconstruction and expansion recommendation indexes of each area in the highway reconstruction and expansion area based on the environmental parameters of the highway reconstruction and expansion area. The construction layer further receives the reconstruction and expansion recommendation indexes of each area in the highway reconstruction and expansion area in the analysis layer, selects the area in the highway reconstruction and expansion area based on the recommendation indication, determines the highway reconstruction and expansion path with the selected area, and finally outputs the highway reconstruction and expansion path; The analysis layer includes a marking module, an analysis module, and a decision-making module. The marking module is used to mark the entrance and exit ends of the highway in the highway reconstruction and expansion area. The analysis module is used to analyze the reconstruction and expansion recommendation indexes of each area in the highway reconstruction and expansion area. The decision-making module is used to receive the analysis results of the reconstruction and expansion recommendation indexes of each area in the analysis module and apply the analysis results to decide on the selected area where the highway is located; There is a reconstruction and expansion recommendation index analysis logic set in the analysis module, and the analysis module analyzes each area in the highway reconstruction and expansion area based on the reconstruction and expansion recommendation index analysis logic.

2. The intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways according to claim 1, characterized in that, The collection layer includes an upload module, a segmentation module, and a collection module. The upload module is used to upload the highway reconstruction and expansion area information. The segmentation module is used to receive the highway reconstruction and expansion area information uploaded by the upload module, determine the highway reconstruction and expansion area based on the highway reconstruction and expansion area information, segment the highway reconstruction and expansion area, and the collection module is used to receive the highway reconstruction and expansion area segmentation results of the segmentation module and collect the environmental parameters corresponding to each segmented area; Among them, the highway reconstruction and expansion area information uploaded by the upload module is no less than three sets of position coordinates. After the segmentation module receives the highway reconstruction and expansion area information, it is connected adjacent to each other based on the position coordinates included in the highway reconstruction and expansion area information to construct a closed planar graph. The area defined by the closed planar graph is the highway reconstruction and expansion area.

3. An intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways according to claim 2, characterized in that, There is a highway reconstruction and expansion area segmentation logic set in the segmentation module, and the segmentation module performs segmentation processing on the highway reconstruction and expansion area based on the segmentation logic; The highway reconstruction and expansion area segmentation logic is expressed as: Obtain the highway width in the highway reconstruction and expansion area, and use the highway width as the spacing between adjacent axes in the segmentation axis network; Draw the axis network and cover the drawn axis network on the surface of the closed planar graph corresponding to the highway reconstruction and expansion area; Use 1 / 10 to 1 / 20 of the highway width as the axis network movement unit, and translate the axis network on the surface of the closed planar graph longitudinally and horizontally; Where: ε is the determination value; n is the total number of grids on the edge position of the closed planar figure after being divided by the axis network, including the grids of the closed planar figure; (s in ) i is the area occupied by the closed planar figure in the i-th grid; W is the width of the highway; Among them, after each movement of the axis network on the surface of the closed planar graph, the judgment value ε is obtained based on the above formula, and when the maximum judgment value is selected, the movement result of the axis network on the surface of the closed planar graph is used for the segmentation of the highway reconstruction and expansion area.

4. An intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways according to claim 2, characterized in that, The acquisition module is integrated by a multi-spectral camera carried by a drone. After the highway reconstruction and expansion area is segmented, the real coordinates of each sub-area are further obtained. The center coordinates of the sub-area in the real coordinates of each sub-area are used as the environmental parameter acquisition positions, and the environmental parameter acquisition operations for each sub-area are performed; Among them, after the acquisition module acquires the environmental parameters of each sub-area, it synchronously differentiates and marks the environmental parameters of each sub-area with the coordinates used in the acquisition stage, and then performs the storage operation. The environmental parameters include: obstacle type, obstacle area, contour of the area where the obstacle is located, and distribution information of underground pipelines. The obstacle types include: buildings, structures, vegetation, lakes, rivers, canyons, and mountains.

5. An intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways according to claim 1, characterized in that, During the operation stage of the annotation module, when annotating the entrance and exit sections of the highway in the highway reconstruction and expansion area, each sub-area obtained by segmentation in the highway reconstruction and expansion area is used as the annotation target, and the annotation operation is manually performed by the system-end user; During the operation stage of the analysis module, the highway reconstruction and expansion accuracy is set. Based on the set highway reconstruction and expansion accuracy, the sub-areas in the highway reconstruction and expansion area are recombined. The recombined area is denoted as the recombination area. Taking the recombination area as the analysis target, based on the analysis logic of the reconstruction and expansion recommendation index, the unique sub-area is captured in each recombination area as the optional highway route area; Among them, the sub-region with the largest reconstruction and expansion recommendation index in each recombination region is the capture target. The accuracy of highway reconstruction and expansion takes the sub-region in the highway reconstruction and expansion region as the smallest unit. Then the recombination region is expressed as x 2 , where x represents the number of sub-regions on the edge of the recombination region.

6. The intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways according to claim 1, wherein, The analysis logic of the reconstruction and expansion recommendation index for each area in the highway reconstruction and expansion area in the analysis module is expressed as: Where: K(α) is the recommended reconstruction and expansion index of area α in the highway reconstruction and expansion area; q is the number of regional underground pipeline nodes; S is the occupied area of obstacles; is the complexity of the area where the obstacle is located in the contour of the obstacle in area α; M is the number of regional underground pipelines; ω α is the weight; Among them, the larger the calculated value of K(α), the more suitable the area α is as the area where the highway is located. On the contrary, it means that the area α is less suitable as the area where the highway is located, and the weight ω α is determined based on the obstacle type in the environmental parameters; The complexity of the area where the obstacle is located, as represented by the contour of the obstacle in region α The calculation formula is: Where: L is the contour length of the obstacle in region α; m is the total number of vertices on the contour of the obstacle in region α; θ j and θ j+1 are the included angles of the j-th and (j + 1)-th vertices; The weight ω α is obtained by the following formula: ω α = |τ α / S| -1 ; Where: τ α is the removal cost of the obstacle in region α determined based on the obstacle type in the environmental parameters; Among them, the removal cost τ of the obstacle in region α is determined based on the obstacle type in the environmental parameters. α It is user-defined by the system-side user.

7. An intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways according to claim 1, characterized in that, During the operation stage of the decision-making module, the entrance and exit sections of the highway marked in the highway reconstruction and expansion area are obtained in the annotation module. The entrance and exit sections are connected by a line in the highway reconstruction and expansion area, and further, the recombination areas penetrated by the line in the highway reconstruction and expansion area are captured; During the operation stage of the decision-making module, the reconstruction and expansion recommendation index screening interval is set, and all recombination areas in the highway reconstruction and expansion area that meet the screening interval are captured based on the reconstruction and expansion recommendation index screening area; The results of capturing the recombination areas twice are denoted as Grab1 and Grab2; When Grab1 ∈ Grab2, the sub-area with the largest reconstruction and expansion recommendation index in each recombination area included in Grab1 is used as the highway route area; When it is, the sub-region with the largest reconstruction and expansion recommendation index among the reconstructed regions corresponding to Grab1 ∩ Grab2 and the reconstructed regions that are the nearest neighbors and meet the screening interval of each reconstructed region included in Grab1 - (Grab1 ∩ Grab2) is used as the highway passing region; Among them, when the decision-making module decides on the area where the highway is located, the set of each highway route area is used as the area where the highway is located.

8. An intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways according to claim 1, characterized in that, The construction layer includes a receiving module, a construction module, and an output module. The receiving module is used to obtain the area where the highway is located obtained by the operation of the analysis layer. The construction module is used to traverse each highway route area included in the area where the highway is located, select a point in each highway route area, and connect the selected points adjacent to each other to construct the highway reconstruction and expansion path. The output module is used to receive the highway reconstruction and expansion path constructed by the construction module and output the highway reconstruction and expansion path; The highway reconstruction and expansion path output by the operation of the output module is targeted at the mobile computer device held by the system-end user, and the system-end user reads the highway reconstruction and expansion path on the mobile computer device; Among them, the highway reconstruction and expansion path is output in the form of a set of the position coordinates of each node on the path.

9. An intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways according to claim 8, characterized in that, The operation of selecting points in the areas passed by the highway in the construction module is subject to: Identify the location of obstacles in the corresponding sub-areas of the areas passed by the highway path, and select a point far from the center point of the obstacle within the sub-area as the selected point.

10. An intelligent analysis system based on the low-carbon reconstruction and expansion planning of expressways according to claim 1, characterized in that, The annotation module is connected to the acquisition module through wireless network interaction. The acquisition module is connected to the segmentation module and the upload module through wireless network interaction. The annotation module is connected to the analysis module and the decision-making module through wireless network interaction. The decision-making module is connected to the receiving module through wireless network interaction. The receiving module is connected to the construction module and the output module through wireless network interaction.

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