Progressive optimization method for dense constraint environment railway line scheme group, medium and equipment

Abstract

This invention relates to the field of intelligent route selection technology, and particularly to a progressive optimization method, medium, and device for railway route schemes in densely constrained environments. The method includes: constructing a multi-constraint fused geographic grid model that integrates spatial constraints and auxiliary data of the research area; generating an initial route search graph network including vertex and edge sets based on the multi-constraint fused geographic grid model; using spatial conflict as the driving force, progressively optimizing the network based on the initial route search graph network and the set of active edges to obtain a final candidate route graph network; and using a breadth-first search method to search for candidate paths based on the final candidate route graph network, and ranking each candidate path according to cost indicators to output the top N candidate paths as the preferred scheme group. This invention effectively solves the problems of existing methods in constrained and coupled scenarios, such as difficulty in systematically evaluating conflicts, exhaustively exploring feasible solutions, and easily causing repeated rework of schemes.

Description

Technical Field

[0001] This invention relates to the field of intelligent route selection technology, and in particular to a progressive optimization method, medium, and equipment for railway route scheme grouping in densely constrained environments. Background Technology

[0002] Currently, land transportation construction often requires traversing areas with highly interwoven existing infrastructure and strict ecological and cultural control requirements. Although such environments do not have significant topographical undulations, route layout is constrained by multiple spatial constraints such as high-voltage corridors, underground pipelines, existing transportation corridors, ecological protection red lines, and noise-sensitive areas. The freedom of choice of routes is significantly reduced, and route selection decisions face a complex trade-off between engineering compliance, safety margin, and economy.

[0003] Traditional human-computer interactive route selection relies on engineers' experience, which makes it difficult to systematically evaluate conflicts and exhaustively explore feasible solutions in constrained and coupled scenarios, easily leading to repeated rework of solutions. Existing automated methods mainly fall into two categories: one is based on grid cost maps, which has low computational efficiency and generates paths that lack engineering feasibility; the other adopts a point-by-point obstacle avoidance strategy, which has low search efficiency when dealing with multi-source constraints, is prone to getting trapped in local optima, and usually outputs a single solution, failing to support the actual needs of multi-solution comparison and flexible decision-making.

[0004] Therefore, it is necessary to provide a new progressive optimization method for railway line schemes in densely constrained environments to solve the above-mentioned technical problems. Summary of the Invention

[0005] The main objective of this invention is to provide a progressive optimization method for railway line schemes in densely constrained environments, aiming to solve the problems of existing methods in constrained and coupled scenarios, such as difficulty in systematically evaluating conflicts, exhaustively exploring feasible solutions, and easily causing repeated rework of schemes.

[0006] To achieve the above objectives, the present invention proposes a progressive optimization method for railway line scheme groups in densely constrained environments, comprising the following steps: S1: Construct a multi-constraint fusion geographic grid model that integrates spatial constraints and auxiliary data of the research area; S2: Generate an initial route search graph network based on a multi-constraint fusion geographic grid model, including a vertex set and an edge set, wherein: the vertex set includes the starting point S and the ending point T given by the route selection task, and the edge set is an adjacency matrix and is an empty set; S3: Construct a straight line between the starting point S and the ending point T as an initial trial connection, and perform spatial obstacle collision detection on the initial trial connection. If there is no collision, output the initial trial connection as the route optimization result between the starting point S and the ending point T; if there is a collision, mark the initial trial connection as an active edge and add it to the active edge set. Enter S4; S4: Based on the initial route search graph network and the set of active edges, perform point placement operations according to the geometry of obstacles to obtain the initial candidate point set. and the initial candidate point set A progressive network optimization process is used to obtain the final candidate route map network; S5: Based on the final candidate route map network, a breadth-first search method is used to search for candidate paths, and the candidate paths are sorted according to the cost index. The top N candidate paths are then output as the preferred solution group.

[0007] Optionally, S1 includes: S1.1 Divide the study area of ​​the line to be selected into a square cell grid with a side length of d, and set the row and column index for each cell; S1.2 Construct a structured attribute set for each grid, where: the structured attribute set includes the spatial constraint elements, engineering auxiliary data, wired routing flags, and a list of associated constraints corresponding to the grid; the spatial constraint elements include high-voltage corridors, underground pipelines, existing traffic corridors, ecological protection red lines, and noise and vibration sensitive areas; the engineering auxiliary data includes bridge engineering costs, tunnel engineering costs, land unit prices, and roadbed earthwork engineering costs; if a grid falls into an absolutely prohibited crossing area or the local slope exceeds the maximum limit slope, the wired routing flag is false, otherwise the wired routing flag is true; the list of associated constraints includes the spatial constraint types corresponding to each grid and the control thresholds required by existing specifications. S1.3. Generate buffer regions for each spatial constraint type based on the control thresholds required by existing specifications and spatial constraint types; S1.4. Mark the corresponding spatial constraint type and control threshold of all grids covered by the buffer area to obtain a multi-constraint fusion geographic grid model.

[0008] Optionally, S4 includes: S4.1 Extract the set of active edges One of the active edges in the middle is used as the current edge. Extracting the obstacle set of the current edge based on a multi-constraint fusion geographic network model. ;in: This represents the number of obstacles corresponding to the current edge; S4.2. Traverse each obstacle on the current edge and perform point placement operations according to the geometry of the obstacle to obtain a set of candidate points including the left side. Right-side alternative point set Pair set of alternative intersection points initial candidate point set ; S4.3 Traversing the initial candidate point set For each candidate point in the initial candidate point set Construct tentative edges and evaluate their validity. Remove candidate points corresponding to tentative edges that fail the validity check, resulting in a preliminary candidate point set. Mark tentative edges that fail the validity check and have spatial conflicts as active edges and add them to the active edge set. In the middle; among which: tentative connections with a slope less than or equal to the maximum restricted slope and that do not cross the absolutely prohibited crossing zone are considered to pass the validity judgment; for the left candidate point set and the right-side alternative point set For each of the candidate points, construct two tentative edges: and For the alternative intersection pair set For each of the candidate points, construct three tentative edges: , and ;in: For the left-side candidate point set Or the right-side alternative point set alternative locations, Number the alternative sites; For alternative intersection pairs The Middle The left point of each intersection pair For alternative intersection pairs The Middle The rightmost point of each intersection pair; S4.4. Based on the dual objectives of cost and risk, the tournament ranking criterion is used to select and retain the left-hand candidate point set after the initial screening. Right-side alternative point set Pair set of alternative intersection points Select K high-quality candidate points and add the retained high-quality candidate points to the network point set. ; S4.5, construct the mesh set Each high-quality candidate point is added to the vertex set, and the tentative edges corresponding to each high-quality candidate point are added to the adjacency matrix to obtain the final candidate route graph network; where: if there is no effective connection between the starting point S and the ending point T, the adjacency matrix is ​​assigned an invalid value; S4.6 Determine the set of active edges Is it If yes, proceed to S5; otherwise, return to S4.1.

[0009] Optionally, in step S4.2, the obstacle placement operation includes the following steps: S4.2.1 Determine the geometric type of the obstacle, specifically: If the obstacle is a planar obstacle, proceed to S4.2.2; If the obstacle is a linear obstacle, proceed to S4.2.3; If the obstacle is a point obstacle, proceed to S4.2.4; S4.2.2. Based on the principle of aligning points directly opposite obstacles at the intersection of land transportation routes, two sets of alternative points are generated along the normal direction on both sides of the obstacle; specifically: ① Determine the reference points and layout direction, including: Projecting each corner point of the planar obstacle onto the line containing the current edge yields multiple projection points; Obtain the maximum and minimum x-coordinates of each projection point, and calculate the x-coordinate of the midpoint based on the maximum and minimum x-coordinates; Use the position of the midpoint's x-coordinate on the current edge as the reference point, and draw the normal line of the current edge through the reference point. Use this normal line as the direction for setting up points. ② Generate a set of candidate points on both the left and right sides of the current edge; where: the point placement operation on the right side is the same as on the left side. Taking the left side of the current edge as an example, the process of generating candidate points includes: Take the boundary of the planar obstacle along this normal direction as the starting point. The endpoint is located at a point where the starting position is extended a predetermined distance to the left along the normal direction. ; In the interval A set of candidate points is generated with the grid edge length as a fixed step size, wherein: all candidate points corresponding to the planar obstacle are located outside the planar obstacle buffer and the corresponding grid can be wired flag is true; ③ Add the candidate points on the left to the left candidate point set. Add the candidate points on the right to the candidate point set on the right. ; S4.2.3. Based on the alignment principle that land transportation routes are orthogonal to linear obstacles, generate intersection pairs along the normal direction before and after the obstacle crossing area; specifically: ① Determine the geometric intersection point between the current edge and the linear obstacle, and draw the normal to the linear obstacle through the geometric intersection point; ② Generate a set of candidate points on both the left and right sides of the current edge; taking the left side of the current edge as an example, the process of generating candidate points includes: Distance from the geometric intersection point along the normal direction of the linear obstacle This location serves as the starting point for the left-side layout. ,in: It is half the length of the minimum clamping line; Starting from the point of deployment Continue to generate candidate points to the left with a fixed step size of grid side length until the turning angle between the currently generated candidate point and the starting point S and the ending point T reaches the maximum turning angle allowed by the route design. Stop generating candidate points when the turning angle between the currently generated candidate point and the starting point S and the ending point T reaches the maximum turning angle allowed by the route design. Among them, all candidate points corresponding to linear obstacles are candidate points located outside the buffer zone of planar obstacles and whose corresponding grid wiring flag is true. ③ Arrange the left and right candidate points in pairs to form multiple sets of candidate intersection points. ; S4.2.4 For point obstacles, based on the principle of route avoidance, two sets of alternative points are generated on the left and right sides along the normal direction at the obstacle location, specifically: ① Project the point obstacle onto the line containing the current edge to obtain the projection point of the point obstacle, and draw the normal line of the current edge through the projection point of the point obstacle; ② Generate a set of candidate points on both the left and right sides of the current edge; where: the point placement operation on the right side is the same as on the left side. Taking the left side of the current edge as an example, the process of generating candidate points includes: The starting point will be 50 meters to the left along the normal direction of the current side. From the starting position Continue along the normal direction of the current side for 500 meters to the left as the endpoint. ; In the interval The candidate points to the left of the point obstacle are generated with a fixed step size of the grid side length. The candidate points are all located outside the buffer zone of the point obstacle, the corresponding grid can be wired flag is true, and the candidate points and the projection points of the point obstacle do not have spatial conflicts with other obstacles. ③ Add the candidate points on the left to the left candidate point set. Add the candidate points on the right to the candidate point set on the right. ; S4.2.5, Based on the left-side candidate point set Right-side alternative point set Pair set of alternative intersection points Constructing the initial candidate point set .

[0010] Optionally, S4.4 includes: S4.4.1. For each candidate point in the initial screening candidate point set, construct its complete detour path, specifically: For the left-side candidate point set and the right-side alternative point set The alternative points and the complete detour route are as follows: ; For the alternative intersection pair The alternative points and the complete detour route are as follows: ; S4.4.2 Calculate the engineering cost and cumulative risk value of the complete detour route corresponding to each candidate point; S4.4.3. Based on the project cost and cumulative risk value, the tournament ranking criteria are independently applied to each candidate point set to select the best candidate point set from the left side. Right-side alternative point set Pair set of alternative intersection points Find K high-quality candidate points and add them to the network point set. .

[0011] Optionally, in S4.4.2, the project cost The specific calculation formula is as follows: ; in: For land acquisition costs, For the cost of earthwork and stonework for the roadbed, For bridge construction costs, For tunnel construction costs, As a cost penalty; Cumulative risk value The specific calculation formula is as follows: ; in: For grid The risk value it carries, The risk value of each grid is determined based on its corresponding spatial constraint type.

[0012] Optionally, S4.4.3 specifically includes: After initial screening, each candidate point in the candidate point set is compared pairwise to obtain the dominance relationship between the two points. Specifically, for any two candidate points... and If both conditions are met and ,but Dominate ;in: As an alternative point The project cost, As an alternative point The project cost; As an alternative point The cumulative risk value, As an alternative point The cumulative risk value; After traversing all candidate points in the initial screening candidate point set, sort the candidate points according to their dominance relationship; On the left candidate point set respectively Right-side alternative point set Pair set of alternative intersection points The top K candidate points are selected as high-quality candidate points and added to the network point set. .

[0013] Optionally, S5 includes: S5.1 Perform a path search on the final candidate route map network to obtain all candidate paths from the starting point S to the ending point T; S5.2 Calculate the total engineering cost corresponding to each candidate path based on the engineering cost of the tentative connections involved in the candidate paths; S5.3 Sort the candidate paths from low to high according to the total project cost, and output the top N paths as the preferred solution group; where: N is the upper limit of the preset number of solutions.

[0014] In addition, the present invention provides a readable storage medium storing computer program instructions, which, when executed by a processor, implement the progressive optimization method for railway line schemes in densely constrained environments as described above.

[0015] The present invention also provides an electronic device, comprising: at least one processor, at least one memory, and computer program instructions stored in the memory, wherein the computer program instructions are executed by the processor to perform the cumulative optimization method for railway line schemes in a dense constraint environment as described above.

[0016] This invention addresses the core pain point of land traffic route selection under dense constraints. It replaces the existing "single route output" with "collaborative generation and optimization of a group of solutions." Through multi-constraint fusion modeling, progressive network construction, and quantitative evaluation mechanisms, it achieves a leapfrog upgrade in route selection technology from "single-point optimal solution" to "group optimal decision-making." Its specific beneficial effects are as follows: I. Overcoming the limitations of single-solution output to support flexible decision-making and multi-scenario adaptation Existing technologies aim to output a single route, adapting only to specific constraints and decision-making preferences. When faced with policy adjustments, differing demands from multiple departments, or fluctuations in engineering parameters, insufficient adaptability can lead to complete rework of the entire solution, impacting project progress efficiency. This invention, through "progressive network construction + parallel path search" technology, can generate up to 200 (with dynamic adjustment support) compliant and feasible route solutions. These solutions cover different detour routes, cost ranges, and risk levels, providing ample redundancy options for decision-making.

[0017] Quantitative evaluation dimensions enhance the scientific rigor and objectivity of the selection process; specifically: Existing technologies lack a systematic and quantitative evaluation system for route selection: traditional human-computer interaction route selection relies on experience-based judgment, resulting in highly subjective evaluation results; existing automated methods often only consider path length or single cost as optimization objectives, failing to consider multi-dimensional factors such as ecological risks, geological risks, and compliance risks. This leads to the selection of the "optimal solution" potentially having safety hazards or compliance defects, making it difficult to support scientific decision-making. This invention establishes a dual-objective quantitative evaluation system of "cost-risk" to accurately determine the merits of different routes: on the one hand, the engineering cost calculation covers factors such as land acquisition costs, roadbed earthwork costs, bridge and tunnel engineering costs, and special area intrusion cost penalties, ensuring the comprehensiveness and accuracy of the cost evaluation; on the other hand, differentiated risk values ​​are assigned based on grid constraint types, and the cumulative risk value of the route is obtained through accumulation, achieving a quantitative representation of risk.

[0018] Balancing computational efficiency with engineering practicality, we will promote the intelligent upgrading of route selection technology; specifically: Existing technologies suffer from dual bottlenecks in efficiency and practicality: traditional human-computer interactive route selection takes weeks or even months to generate only 1-2 feasible routes, resulting in extremely low efficiency and quality dependent on human experience; existing automated methods are either computationally inefficient or generate paths that do not conform to engineering alignment principles, requiring additional manual adjustments before implementation. This invention achieves a synergistic improvement in efficiency and practicality through technological optimization: it adopts a 30m / 90m optimal grid edge length to control the computational scale while ensuring constraint annotation accuracy, and combines spatial indexing technology to achieve rapid coordinate mapping, improving data processing efficiency; through strategies such as active edge cyclic convergence and path cost over-limit pruning, it reduces invalid calculations, ensuring the generation of a large number of high-quality solutions in a short period of time; it promotes the transformation of land transportation route selection technology from "semi-automated and experience-based" to "fully intelligent and standardized," providing efficient and reliable technical support for land transportation construction in densely constrained environments. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the progressive optimization method for railway line schemes in densely constrained environments, as described in this embodiment of the invention. Figure 2 This is a schematic diagram of the structure of the initial route search graph network in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of the initial route search graph network after point placement operations in an embodiment of the present invention; Figure 4 This is a schematic diagram of the final candidate circuit diagram network in an embodiment of the present invention.

[0021] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0023] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0024] Furthermore, in this invention, descriptions involving "first," "second," etc., are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0025] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0026] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0027] This invention proposes a progressive optimization method for railway line schemes in densely constrained environments, aiming to solve the problems of existing methods being unable to systematically evaluate conflicts, exhaustively explore feasible solutions, and easily cause repeated rework of schemes in constrained coupled scenarios.

[0028] See Figure 1 This embodiment proposes a progressive optimization method for railway line scheme groups in densely constrained environments, including the following steps: S1: Construct a multi-constraint fusion geographic grid model that integrates spatial constraints and auxiliary data of the research area; specifically: construct a multi-constraint fusion geographic grid model that supports graph network search, and integrate spatial constraints and auxiliary data into grid attributes, label wire availability, and provide a data foundation for conflict detection and alternative point evaluation.

[0029] S1 includes: S1.1 Divide the study area of ​​the line to be selected into square cell grids with side length d, and set row and column indexes for each grid; in this embodiment, d is preferably 30m or 90m to balance accuracy and efficiency. Each grid is assigned a unique index, and a row and column index is established to support fast coordinate mapping.

[0030] S1.2 Construct a structured attribute set for each grid, wherein: the structured attribute set includes spatial constraint elements, engineering auxiliary data, wired routing markers, and a list of associated constraints corresponding to the grid; spatial constraint elements include high-voltage corridors, underground pipelines, existing transportation corridors, ecological protection red lines, and noise and vibration sensitive areas; engineering auxiliary data includes bridge engineering costs, tunnel engineering costs, land unit prices, and roadbed earthwork engineering costs; if a grid falls into an absolutely prohibited crossing area or the local slope exceeds the maximum limit slope, the wired routing marker position is false, otherwise the wired routing marker position is true; the list of associated constraints includes the spatial constraint type corresponding to each grid and the control thresholds required by existing specifications; in this embodiment, the control thresholds include minimum clearance and minimum intersection angle thresholds; the absolutely prohibited crossing areas are basic farmland, cultural relic core areas, etc.

[0031] S1.3. Generate buffer regions for each spatial constraint type based on the control thresholds required by existing specifications and spatial constraint types; S1.4. Mark the corresponding spatial constraint type and control threshold of all grids covered by the buffer area to obtain a multi-constraint fusion geographic grid model.

[0032] S2: An initial route search graph network is generated based on a multi-constraint fusion geographic grid model, including a vertex set and an edge set, wherein: the vertex set includes the starting point S and the ending point T given by the route selection task, and the edge set is an adjacency matrix and is an empty set; in this embodiment, the initial route search graph network Vertex set edge set This is an adjacency matrix; see [link / reference]. Figure 2 ; S3: Construct a straight line between the starting point S and the ending point T as an initial trial connection, and perform spatial obstacle collision detection on the initial trial connection. If there is no collision, output the initial trial connection as the route optimization result between the starting point S and the ending point T; if there is a collision, mark the initial trial connection as an active edge and add it to the active edge set. Enter S4; S4: Based on the initial route search graph network and the set of active edges, perform point placement operations according to the geometry of obstacles to obtain the initial candidate point set. and the initial candidate point set A progressive network optimization process is used to obtain the final candidate route map network; See Figure 3 and Figure 4 , Figure 3 A schematic diagram of the structure after the initial route search graph network has undergone point placement operations; Figure 4 This is a schematic diagram of the final candidate route network. Figure 4 The blue lines represent tentative connections between potential planar obstacles, the green dashed lines represent tentative connections between potential linear obstacles, and the green dashed lines represent tentative connections between potential point obstacles.

[0033] S3 and S4 are based on the initial graph network and driven by spatial conflicts, cyclically executing a progressive operation of "placing points - connecting edges - constructing a network": according to the obstacle classification, points are placed on opposite / line / point obstacles to generate an initial set of candidate points. Then, for the initial candidate point set The effectiveness of the initial point selection is determined by conducting exploratory edge connections, and then the initial candidate point set is further refined based on both cost and risk indicators. An evaluation was conducted, and high-quality points were selected to be added to the network point set. Then, the adjacency matrix of the edges is updated, and a conflict-free candidate graph network is progressively constructed.

[0034] S4 includes: S4.1 Extract the set of active edges One of the active edges in the middle is used as the current edge. Extracting the obstacle set of the current edge based on a multi-constraint fusion geographic network model. ;in: This represents the number of obstacles corresponding to the current edge; S4.2. Traverse each obstacle on the current edge and perform point placement operations according to the geometry of the obstacle to obtain a set of candidate points including the left side. Right-side alternative point set Pair set of alternative intersection points initial candidate point set ; In step S4.2, the obstacle placement operation includes the following steps: S4.2.1 Determine the geometric type of the obstacle, specifically: If the obstacle is a planar obstacle, proceed to S4.2.2; in this embodiment, planar obstacles include development zones, ecological protection zones, basic farmland, etc. If the obstacle is a linear obstacle, proceed to S4.2.3; in this embodiment, linear obstacles include existing railways, integrated utility tunnels, high-voltage corridors, main rivers, etc. If the obstacle is a point obstacle, proceed to S4.2.4; in this embodiment, point obstacles include cultural relics, power towers, high-speed rail stations, etc.

[0035] S4.2.2. Based on the principle of aligning points directly opposite obstacles at the intersection of land transportation routes, two sets of alternative points are generated along the normal direction on both sides of the obstacle; specifically: ① Determine the reference points and layout direction, including: Projecting each corner point of the planar obstacle onto the line containing the current edge yields multiple projection points; Get the maximum x-coordinate of each projection point max and the minimum x-coordinate min The x-coordinate of the midpoint is calculated based on the maximum and minimum x-coordinate values. Use the position of the midpoint's x-coordinate on the current edge as the reference point, and draw the normal line of the current edge through the reference point. Use this normal line as the direction for setting up points. ② Generate a set of candidate points on both the left and right sides of the current edge; where: the point placement operation on the right side is the same as on the left side. Taking the left side of the current edge as an example, the process of generating candidate points includes: Take the boundary of the planar obstacle along this normal direction as the starting point. The endpoint is located at a point where the starting position is extended a predetermined distance to the left along the normal direction. In this embodiment, the distance is set to 500m. In the interval A set of candidate points is generated with the grid edge length as a fixed step size, wherein: all candidate points corresponding to the planar obstacle are located outside the planar obstacle buffer and the corresponding grid can be wired flag is true; ③ Add the candidate points on the left to the left candidate point set. Add the candidate points on the right to the candidate point set on the right. ; S4.2.3. Based on the alignment principle that land transportation routes are orthogonal to linear obstacles, generate intersection pairs along the normal direction before and after the obstacle crossing area; specifically: ① Determine the geometric intersection point between the current edge and the linear obstacle, and draw the normal to the linear obstacle through the geometric intersection point; ② Generate a set of candidate points on both the left and right sides of the current edge; taking the left side of the current edge as an example, the process of generating candidate points includes: Distance from the geometric intersection point along the normal direction of the linear obstacle This location serves as the starting point for the left-side layout. ,in: It is half the length of the minimum clamping line; Starting from the point of deployment Continue to generate candidate points to the left with a fixed step size of grid side length until the turning angle between the currently generated candidate point and the starting point S and the ending point T reaches the maximum turning angle allowed by the route design. Stop generating candidate points when the turning angle between the currently generated candidate point and the starting point S and the ending point T reaches the maximum turning angle allowed by the route design. Among them, all candidate points corresponding to linear obstacles are candidate points located outside the buffer zone of planar obstacles and whose corresponding grid wiring flag is true. ③ Arrange the left and right candidate points in pairs to form multiple sets of candidate intersection points. ; S4.2.4 For point obstacles, based on the principle of route avoidance, two sets of alternative points are generated on the left and right sides along the normal direction at the obstacle location, specifically: ① Project the point obstacle onto the line containing the current edge to obtain the projection point of the point obstacle, and draw the normal line of the current edge through the projection point of the point obstacle; ② Generate a set of candidate points on both the left and right sides of the current edge; where: the point placement operation on the right side is the same as on the left side. Taking the left side of the current edge as an example, the process of generating candidate points includes: The starting point will be 50 meters to the left along the normal direction of the current side. From the starting position Continue along the normal direction of the current side for 500 meters to the left as the endpoint. ; In the interval The candidate points to the left of the point obstacle are generated with a fixed step size of the grid side length. The candidate points are all located outside the buffer zone of the point obstacle, the corresponding grid can be wired flag is true, and the candidate points and the projection points of the point obstacle do not have spatial conflicts with other obstacles. ③ Add the candidate points on the left to the left candidate point set. Add the candidate points on the right to the candidate point set on the right. ; S4.2.5, Based on the left-side candidate point set Right-side alternative point set Pair set of alternative intersection points Constructing the initial candidate point set .

[0036] S4.3 Traversing the initial candidate point set For each candidate point in the initial candidate point set Construct tentative edges and evaluate their validity. Remove candidate points corresponding to tentative edges that fail the validity check, resulting in a preliminary candidate point set. Mark tentative edges that fail the validity check and have spatial conflicts as active edges and add them to the active edge set. In the middle; among which: tentative connections with a slope less than or equal to the maximum restricted slope and that do not cross the absolutely prohibited crossing zone are considered to pass the validity judgment; for the left candidate point set and the right-side alternative point set For each of the candidate points, construct two tentative edges: and For the alternative intersection pair set For each of the candidate points, construct three tentative edges: , and ;in: For the left-side candidate point set Or the right-side alternative point set alternative locations, Number the alternative sites; For alternative intersection pairs The Middle The left point of each intersection pair For alternative intersection pairs The Middle The rightmost point of each intersection pair; S4.4. Based on the dual objectives of cost and risk, the tournament ranking criterion is used to select and retain the left-hand candidate point set after the initial screening. Right-side alternative point set Pair set of alternative intersection points Select K high-quality candidate points and add the retained high-quality candidate points to the network point set. ; S4.4 includes: S4.4.1. For each candidate point in the initial screening candidate point set, construct its complete detour path, specifically... For the left-side candidate point set and the right-side alternative point set The alternative points and the complete detour route are as follows: ; For the alternative intersection pair The alternative points and the complete detour route are as follows: ; S4.4.2 Calculate the engineering cost and cumulative risk value of the complete detour route corresponding to each candidate point; In S4.4.2, the project cost The specific calculation formula is as follows: ; in: For land acquisition costs, For the cost of earthwork and stonework for the roadbed, For bridge construction costs, For tunnel construction costs, Cost penalties (route intrusion into special areas, such as high-voltage corridor control zones, integrated utility tunnel security zones, etc.); Cumulative risk value The specific calculation formula is as follows: ; in: For grid The risk value it carries, The risk value for each grid is determined based on its corresponding spatial constraint type. In this embodiment, the risk value for traversing environmentally sensitive points... Risk value of crossing the landslide hazard zone Risk of crossing a mudslide Risk value of crossing the flood control area of ​​the main river Risk value of crossing the safety zone of the adjacent underground utility tunnel Risk value of crossing the noise impact zone of adjacent densely populated areas Risk value of crossing the vibration impact zone of adjacent cultural relics and historical sites ; S4.4.3. Based on the project cost and cumulative risk value, the tournament ranking criteria are independently applied to each candidate point set to select the best candidate point set from the left side. Right-side alternative point set Pair set of alternative intersection points Find K high-quality candidate points and add them to the network point set. In this embodiment, K is 1.

[0037] Specifically, S4.4.3 includes: After initial screening, each candidate point in the candidate point set is compared pairwise to obtain the dominance relationship between the two points. Specifically, for any two candidate points... and If both conditions are met and ,but Dominate ;in: As an alternative point The project cost, As an alternative point The project cost; As an alternative point The cumulative risk value, As an alternative point The cumulative risk value; After traversing all candidate points in the initial screening candidate point set, sort the candidate points according to their dominance relationship; On the left candidate point set respectively Right-side alternative point set Pair set of alternative intersection points The top K candidate points are selected as high-quality candidate points and added to the network point set. .

[0038] S4.5, construct the mesh set Each high-quality candidate point is added to the vertex set, and the tentative edges corresponding to each high-quality candidate point are added to the adjacency matrix to obtain the final candidate route graph network; wherein: if there is no valid connection between the starting point S and the ending point T, the adjacency matrix is ​​assigned an invalid value; in this embodiment, the adjacency matrix is Among them, elements , Represents vertices and The connection weight between vertices is taken as the project cost in this embodiment. If there is no valid connection between two vertices, an invalid value, i.e., an infinite number, is assigned.

[0039] In this embodiment, Represents vertices and There are valid connections between them.

[0040] S4.6 Determine the set of active edges Is it If yes, proceed to S5; otherwise, return to S4.1.

[0041] S5: Based on the final candidate route map network, a breadth-first search method is used to search for candidate paths, and the candidate paths are sorted according to the cost index. The top N candidate paths are then output as the preferred solution group.

[0042] In this embodiment, a breadth-first search is used to traverse all simple paths from the starting point S to the ending point T. Each path is represented as a sequence of vertices. This constitutes the initial path set. Specifically: Based on cost indicators, for each feasible path Based on the current adjacency matrix, the weights of the edges involved in the path are accumulated to calculate the total project cost. ; For the set of feasible paths Based on total project cost Sort by height from lowest to highest and output the top few. The path is considered as a group of preferred solutions; among them The maximum number of preset schemes is set to 200 in this embodiment, and can be dynamically adjusted according to the needs of project comparison.

[0043] S5 includes: S5.1 Perform a path search on the final candidate route map network to obtain all candidate paths from the starting point S to the ending point T; S5.2 Calculate the total engineering cost corresponding to each candidate path based on the engineering cost of the tentative connections involved in the candidate paths; S5.3 Sort the candidate paths from low to high according to the total project cost, and output the top N paths as the preferred solution group; where: N is the upper limit of the preset number of solutions.

[0044] This embodiment also provides a readable storage medium storing computer program instructions, which, when executed by a processor, implement the progressive optimization method for railway line schemes in densely constrained environments as described above.

[0045] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0046] This embodiment also includes an electronic device, comprising: at least one processor, at least one memory, and computer program instructions stored in the memory, wherein the computer program instructions are executed by the processor to perform the cumulative optimization method for railway line schemes in densely constrained environments as described above.

[0047] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0048] The electronic device can be a mobile phone, desktop computer, laptop, handheld computer, cloud server, or other computing device. The electronic device may include, but is not limited to, processors and memory. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0049] 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. The processor is the control center of the electronic device, connecting all parts of the electronic device via various interfaces and lines.

[0050] The memory can be used to store the computer program and / or modules. The processor implements the computer program by running or executing the computer program and / or modules stored in the memory, and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital card (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0051] If the modules / units integrated in the electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0052] The above description is only a preferred embodiment of the present invention and does not limit the scope of the present invention. All equivalent structural transformations made under the inventive concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the protection scope of the present invention.

Claims

1. A progressive optimization method for railway line schemes in a densely constrained environment, characterized in that, Includes the following steps: S1: Construct a multi-constraint fusion geographic grid model that integrates spatial constraints and auxiliary data of the research area; S2: Generate an initial route search graph network based on a multi-constraint fusion geographic grid model, including a vertex set and an edge set, wherein: the vertex set includes the starting point S and the ending point T given by the route selection task, and the edge set is an adjacency matrix and is an empty set; S3: Construct a straight line between the starting point S and the ending point T as an initial trial connection, and perform spatial obstacle collision detection on the initial trial connection. If there is no collision, output the initial trial connection as the route optimization result between the starting point S and the ending point T. If a conflict occurs, the initial tentative connection is marked as an active edge and added to the active edge set. Enter S4; S4: Based on the initial route search graph network and the set of active edges, perform point placement operations according to the geometry of obstacles to obtain the initial candidate point set. and the initial candidate point set A progressive network optimization process is used to obtain the final candidate route map network; S5: Based on the final candidate route map network, a breadth-first search method is used to search for candidate paths, and the candidate paths are sorted according to the cost index. The top N candidate paths are then output as the preferred solution group.

2. The progressive optimization method for railway line schemes in densely constrained environments according to claim 1, characterized in that, S1 includes: S1.1 Divide the study area of ​​the line to be selected into a square cell grid with a side length of d, and set the row and column index for each cell; S1.2 Construct a structured attribute set for each grid, where: the structured attribute set includes the spatial constraint elements, engineering auxiliary data, wired routing flags, and a list of associated constraints corresponding to the grid; the spatial constraint elements include high-voltage corridors, underground pipelines, existing traffic corridors, ecological protection red lines, and noise and vibration sensitive areas; the engineering auxiliary data includes bridge engineering costs, tunnel engineering costs, land unit prices, and roadbed earthwork engineering costs; if a grid falls into an absolutely prohibited crossing area or the local slope exceeds the maximum limit slope, the wired routing flag is false, otherwise the wired routing flag is true; the list of associated constraints includes the spatial constraint types corresponding to each grid and the control thresholds required by existing specifications. S1.

3. Generate buffer regions for each spatial constraint type based on the control thresholds required by existing specifications and spatial constraint types; S1.

4. Mark the corresponding spatial constraint type and control threshold of all grids covered by the buffer area to obtain a multi-constraint fusion geographic grid model.

3. The progressive optimization method for railway line schemes in densely constrained environments according to claim 2, characterized in that, S4 includes: S4.1 Extract the set of active edges One of the active edges in the middle is used as the current edge. Extracting the obstacle set of the current edge based on a multi-constraint fusion geographic network model. ;in: This represents the number of obstacles corresponding to the current edge. S4.

2. Traverse each obstacle on the current edge and perform point placement operations according to the geometry of the obstacle to obtain a set of candidate points including the left side. Right-side alternative point set Pair set of alternative intersection points initial candidate point set ; S4.3 Traversing the initial candidate point set For each candidate point in the initial candidate point set Construct tentative edges and evaluate their validity. Remove candidate points corresponding to tentative edges that fail the validity check, resulting in a preliminary candidate point set. Mark tentative edges that fail the validity check and have spatial conflicts as active edges and add them to the active edge set. In the middle; among which: tentative connections with a slope less than or equal to the maximum restricted slope and that do not cross the absolutely prohibited crossing zone are considered to pass the validity judgment; for the left candidate point set and the right-side alternative point set For each of the candidate points, construct two tentative edges: and For the alternative intersection pair set For each of the candidate points, construct three tentative edges: , and ;in: For the left-side candidate point set Or the right-side alternative point set alternative locations, Numbering of alternative sites; For alternative intersection pairs The Middle The left point of each intersection pair For alternative intersection pairs The Middle The rightmost point of each intersection pair; S4.

4. Based on the dual objectives of cost and risk, the tournament ranking criterion is used to select and retain the left-hand candidate point set after the initial screening. Right-side alternative point set Pair set of alternative intersection points Select K high-quality candidate points and add the retained high-quality candidate points to the network point set. ; S4.5, construct the mesh set Each high-quality candidate point is added to the vertex set, and the tentative edges corresponding to each high-quality candidate point are added to the adjacency matrix to obtain the final candidate route graph network; where: if there is no effective connection between the starting point S and the ending point T, the adjacency matrix is ​​assigned an invalid value; S4.6 Determine the set of active edges Is it If yes, proceed to S5; otherwise, return to S4.

1.

4. The progressive optimization method for railway line schemes in densely constrained environments according to claim 3, characterized in that, In step S4.2, the obstacle placement operation includes the following steps: S4.2.1 Determine the geometric type of the obstacle, specifically: If the obstacle is a planar obstacle, proceed to S4.2.2; If the obstacle is a linear obstacle, proceed to S4.2.3; If the obstacle is a point obstacle, proceed to S4.2.4; S4.2.2 Based on the principle of aligning the intersection of land transportation routes with the opposite obstacle, two sets of alternative points are generated on both sides of the obstacle along the normal direction. Specifically: ① Determine the reference points and layout direction, including: Projecting each corner point of the planar obstacle onto the line containing the current edge yields multiple projection points; Obtain the maximum and minimum x-coordinates of each projection point, and calculate the x-coordinate of the midpoint based on the maximum and minimum x-coordinates; Use the position of the midpoint's x-coordinate on the current edge as the reference point, and draw the normal line of the current edge through the reference point. Use this normal line as the direction for setting up points. ② Generate a set of candidate points on both the left and right sides of the current edge; where: the point placement operation on the right side is the same as on the left side. Taking the left side of the current edge as an example, the process of generating candidate points includes: Take the boundary of the planar obstacle along this normal direction as the starting point. The endpoint is located at a point where the starting position is extended a predetermined distance to the left along the normal direction. ; In the interval A set of candidate points is generated with the grid edge length as a fixed step size, wherein: all candidate points corresponding to the planar obstacle are located outside the planar obstacle buffer and the corresponding grid can be wired flag is true; ③ Add the candidate points on the left to the left candidate point set. Add the candidate points on the right to the candidate point set on the right. ; S4.2.

3. Based on the alignment principle that land transportation routes are orthogonal to linear obstacles, generate intersection pairs along the normal direction before and after the obstacle crossing area; specifically: ① Determine the geometric intersection point between the current edge and the linear obstacle, and draw the normal to the linear obstacle through the geometric intersection point; ② Generate a set of candidate points on both the left and right sides of the current edge; taking the left side of the current edge as an example, the process of generating candidate points includes: Distance from the geometric intersection point along the normal direction of the linear obstacle This location serves as the starting point for the left-side layout. ,in: It is half the length of the minimum clamping line; Starting from the point of deployment Continue to generate candidate points to the left with a fixed step size of grid side length until the turning angle between the currently generated candidate point and the starting point S and the ending point T reaches the maximum turning angle allowed by the route design. Stop generating candidate points when the turning angle between the currently generated candidate point and the starting point S and the ending point T reaches the maximum turning angle allowed by the route design. Among them, all candidate points corresponding to linear obstacles are candidate points located outside the buffer zone of planar obstacles and whose corresponding grid wiring flag is true. ③ Arrange the left and right candidate points in pairs to form multiple sets of candidate intersection points. ; S4.2.4 For point obstacles, based on the principle of route avoidance, two sets of alternative points are generated on the left and right sides along the normal direction at the obstacle location, specifically: ① Project the point obstacle onto the line containing the current edge to obtain the projection point of the point obstacle, and draw the normal line of the current edge through the projection point of the point obstacle; ② Generate a set of candidate points on both the left and right sides of the current edge; where: the point placement operation on the right side is the same as on the left side. Taking the left side of the current edge as an example, the process of generating candidate points includes: The starting point will be 50 meters to the left along the normal direction of the current side. From the starting position Continue along the normal direction of the current side for 500 meters to the left as the endpoint. ; In the interval The candidate points to the left of the point obstacle are generated with a fixed step size of the grid side length. The candidate points are all located outside the buffer zone of the point obstacle, the corresponding grid can be wired flag is true, and the candidate points and the projection points of the point obstacle do not have spatial conflicts with other obstacles. ③ Add the candidate points on the left to the left candidate point set. Add the candidate points on the right to the candidate point set on the right. ; S4.2.5, Based on the left-side candidate point set Right-side alternative point set Pair set of alternative intersection points Constructing the initial candidate point set .

5. The progressive optimization method for railway line schemes in densely constrained environments according to claim 4, characterized in that, S4.4 includes: S4.4.

1. For each candidate point in the initial screening candidate point set, construct its complete detour path, specifically... For the left-side candidate point set and the right-side alternative point set The alternative points and the complete detour route are as follows: ; For the alternative intersection pair The alternative points and the complete detour route are as follows: ; S4.4.2 Calculate the engineering cost and cumulative risk value of the complete detour route corresponding to each candidate point; S4.4.

3. Based on the project cost and cumulative risk value, the tournament ranking criteria are independently applied to each candidate point set to select the best candidate point set from the left side. Right-side alternative point set Pair set of alternative intersection points Find K high-quality candidate points and add them to the network point set. .

6. The progressive optimization method for railway line schemes in densely constrained environments according to claim 5, characterized in that, In S4.4.2, the project cost The specific calculation formula is as follows: ； in: For land acquisition costs, For the cost of earthwork and stonework for the roadbed, For bridge construction costs, For tunnel construction costs, As a cost penalty; Cumulative risk value The specific calculation formula is as follows: ； in: For grid The risk value it carries, The risk value of each grid is determined based on its corresponding spatial constraint type.

7. The progressive optimization method for railway line schemes in densely constrained environments according to claim 5, characterized in that, Specifically, S4.4.3 includes: After initial screening, each candidate point in the candidate point set is compared pairwise to obtain the dominance relationship between the two points. Specifically, for any two candidate points... and If both conditions are met and ,but Dominate ;in: As an alternative point The project cost, As an alternative point The project cost; As an alternative point The cumulative risk value, As an alternative point The cumulative risk value; After traversing all candidate points in the initial screening candidate point set, sort the candidate points according to their dominance relationship; On the left candidate point set respectively Right-side alternative point set Pair set of alternative intersection points The top K candidate points are selected as high-quality candidate points and added to the network point set. .

8. The progressive optimization method for railway line schemes in densely constrained environments according to any one of claims 1-7, characterized in that, S5 includes: S5.1 Perform a path search on the final candidate route map network to obtain all candidate paths from the starting point S to the ending point T; S5.2 Calculate the total engineering cost corresponding to each candidate path based on the engineering cost of the tentative connections involved in the candidate paths; S5.3 Sort the candidate paths from low to high according to the total project cost, and output the top N paths as the preferred solution group; where: N is the upper limit of the preset number of solutions.

9. A readable storage medium, characterized in that, It stores computer program instructions, which, when executed by a processor, implement the progressive optimization method for railway line schemes in densely constrained environments as described in any one of claims 1 to 8.

10. An electronic device, characterized in that, include: At least one processor, at least one memory, and computer program instructions stored in the memory, wherein the computer program instructions are executed by the processor as described in any one of claims 1 to 8, a method for progressively optimizing a group of railway line schemes in a densely constrained environment.

Images