A method for rapid terrain exploration and cost map construction for intelligent railway route selection

Abstract

The present invention discloses a method for rapid terrain exploration and cost map construction for intelligent railway route selection, comprising the following steps: S1, setting project design parameters; S2, constructing a digital elevation model and a route selection boundary control surface region; S3, constructing a set of terrain exploration line plane models; S4, constructing a set of terrain exploration line vertical section models; S5, constructing a set of terrain exploration bridge and tunnel high-cost surface regions; S6, constructing a triangular network based on the surface region boundary; S7, constructing an undirected graph of the triangular network based on the triangular network; S8, setting surface region cost parameters and constructing a surface region query model; S9, constructing a triangular network cost map based on the undirected graph of the triangular network; S10, drawing the triangular network cost map and saving it. The method of the present invention can not only effectively express the connectivity relationship, but also reduce the data redundancy and improve the graph-based channel search efficiency.

Description

Technical Field

[0001] The present invention relates to a method for railway route selection design, and particularly to a method for rapid terrain exploration and cost map construction for intelligent railway route selection. Background Art

[0002] Intelligent railway route selection is a crucial intermediate link for improving the intelligent level of the railway design industry, and its main steps include line corridor search and corridor scheme fitting optimization. When conducting line corridor search, the traditional approach is to first construct a regular grid, then expand the spatial distance between any two cells into a generalized distance including costs such as engineering, operation, and environmental impacts of line schemes, and use the concept of distance transformation in image theory to construct a grayscale map, and conduct corridor search on this basis. Due to the large scale of general railway route selection scenarios and the large number of grids, intelligent corridor search generally takes a long time. Summary of the Invention

[0003] To solve the problems in the background art, the present invention provides a method for rapid terrain exploration for intelligent railway route selection based on railway route selection technical parameters, and constructing a cost map by triangulation based on the plane domain boundary, which is fast and practical.

[0004] For this purpose, the present invention adopts the following technical solutions:

[0005] A method for rapid terrain exploration and cost map construction for intelligent railway route selection, comprising the following steps:

[0006] S1, setting project design parameters:

[0007] According to the project design data, input line parameters, the storage path of the ground point cloud data file, and the route selection boundary control data layer in the configuration file. The line parameters include: vertical section design parameters and bridge-tunnel gap design parameters;

[0008] S2, constructing a digital elevation model and a route selection boundary control domain:

[0009] Read the ground point cloud data file according to the storage path, and generate a digital elevation model using Delaunay triangulation. Read the route selection boundary control data layer in S1 to obtain domain data, and generate an auxiliary boundary through the domain data to construct a route selection boundary control domain;

[0010] S3, constructing a terrain exploration line plane model set:

[0011] Set the exploration mode and exploration parameters, and construct an exploration path array; construct an intersection point array according to the exploration path, and set the radius and buffer length of each intersection point in the intersection point array to 0. Use the intersection point method to construct a line plane model, and construct a line plane model for each exploration path, thereby forming a set of terrain exploration line plane models; where:

[0012] The exploration parameters include an exploration starting point, an exploration ending point, an exploration route point array, a maximum exploration width, an exploration spacing, a maximum exploration angle, and an exploration angle step size;

[0013] The exploration mode includes rectangular parallel line exploration, fan-shaped ray exploration, and circular arc exploration;

[0014] S4. Construct a set of terrain exploration line vertical section models:

[0015] Perform vertical section design on each of the line plane models in the set of terrain exploration line plane models obtained in S3 to obtain a corresponding line vertical section model. Multiple line vertical section models constitute a set of terrain exploration line vertical section models; the vertical section model and the line plane model are in one-to-one correspondence; the vertical section design includes generating a ground line based on the plane model and the digital elevation model in S2, performing vertical section slope fitting and constraint processing;

[0016] S5. Construct a set of terrain exploration bridge and tunnel high-cost regions:

[0017] First, use the line vertical section model in S4, the ground line, and the bridge and tunnel gap design parameters in S1 to generate a bridge and tunnel gap array; then use the line plane model corresponding to the line vertical section model, and calculate the offset and offset coordinates on both sides of each bridge and tunnel gap at a fixed mileage step. The offset coordinates on the left and right sides of the bridge and tunnel gap each form a point array. The points in the two point arrays are sequentially connected, and then the starting points and ending points of the two connecting lines are connected respectively to form a closed polygon to obtain the bridge and tunnel gap region; finally, perform a union Boolean operation on all bridge and tunnel gap regions to merge similar regions and form a set of terrain exploration bridge and tunnel high-cost regions;

[0018] S6. Construct a triangulation network based on the region boundary:

[0019] First, extract the boundary polygons of the route selection boundary control region in S2 and the terrain exploration bridge and tunnel high-cost region in S5 as feature lines, perform Delaunay triangulation, and construct a triangulation network; then set the maximum side length parameter of the triangle, perform vertex interpolation in the triangulation network to construct an encrypted vertex array; and then use the boundary polygon feature line and the encrypted vertex array to perform Delaunay triangulation again to generate the final triangulation network;

[0020] S7. Construct an undirected graph of the triangulation network:

[0021] First, extract the vertex array and edge array of the final triangular mesh obtained in S6, and process the edge array to delete the overlapping edges with opposite directions; then create an empty undirected graph, add nodes to the undirected graph according to the vertex array, and use the vertex coordinates as node attributes. Next, add edges to the undirected graph according to the edge array, and use the side length as the edge attribute, thus obtaining an undirected graph of the triangular mesh.

[0022] S8, set the cost parameter of the region and construct a region query model:

[0023] Group the route selection boundary control region constructed in S2 and the terrain exploration bridge and tunnel high-cost region obtained in S5, and set the cost per meter for each region type; then use the boundary polygons of the route selection boundary control region obtained in S2 and the terrain exploration bridge and tunnel high-cost region obtained in S5 to construct a region query model, which can quickly query the set of region types to which a point coordinate belongs.

[0024] S9, construct a triangular mesh cost graph based on the undirected graph of the triangular mesh:

[0025] First, calculate the midpoint coordinates of each edge in the undirected graph of the triangular mesh in S7, then use the edge midpoint coordinates to query the region query model generated in S8 to obtain the set of region types, and save it to the edge attribute; finally, for each type in the set of region types, obtain the cost per meter and calculate the cost of each edge to form a triangular mesh cost graph; the edge attribute includes edge cost, side length, and set of region types.

[0026] S10, draw the triangular mesh cost graph and save it:

[0027] For each edge in the triangular mesh cost graph, set different colors according to the size of the edge cost; save the triangular mesh cost graph as a cost graph file; when performing channel search for intelligent railway route selection later, directly read the cost graph file and regenerate the cost graph.

[0028] In S1, the vertical profile design parameters include the minimum slope section length, maximum gradient, maximum algebraic difference in gradients, minimum algebraic difference in gradients of vertical curves, vertical curve radius, minimum slope length constraint, maximum gradient constraint, maximum algebraic difference in gradients constraint, relaxation of overlap constraint, gradient reduction constraint, gradient merging constraint, gradient smoothness constraint, and subgrade section treatment constraint; the bridge and tunnel gap design parameters include the critical height of bridges and tunnels, minimum gap for bridge and tunnel merging, and maximum fill and cut height for bridge and tunnel retention.

[0029] In S2, the area data includes rivers, lakes, existing railways, existing roads, poor geological areas, restricted areas, economic strongholds, planning areas, environmental protection core areas, environmental protection buffer areas, and environmental protection experimental areas. If the existing road or existing railway is a multi-segment line, it is converted into a closed area by setting the road width. The auxiliary boundaries include railway traffic corridor belts, road traffic corridor belts, and economic radiation areas, which are respectively formed by offsetting the boundaries of the existing railway, existing road, and economic stronghold outward by a set offset amount.

[0030] In S3, the specific rectangle parallel line exploration mode is as follows: First, construct a basic exploration path based on the exploration starting point, exploration passing point array, and exploration ending point. Then, offset the basic exploration path multiple times to both sides by an integer multiple of the exploration spacing to generate multiple new exploration paths, obtaining an exploration path array; the maximum offset amount on each side is limited to half of the maximum exploration width. The specific fan-shaped ray exploration mode is as follows: First, construct a basic exploration path based on the exploration starting point and exploration ending point; then, fix the exploration starting point, and rotate it multiple times to both sides from the basic exploration path by an integer multiple of the exploration angle step to generate multiple new exploration paths, obtaining an exploration path array; the maximum rotation angle on each side is limited to half of the maximum exploration angle. The specific circular arc exploration mode is as follows: First, construct a basic exploration path based on the exploration starting point and exploration ending point; then, fix the exploration starting point and ending point, calculate the midpoint of the basic exploration path, and use this midpoint as a reference to offset it to both sides by an integer multiple of the exploration spacing, calculate the radius and center coordinates of the circular arc using trigonometric functions, and construct a circular arc object; starting from the circular arc starting point, sample according to the exploration step to generate a new exploration path; according to the above method, after multiple offsets, generate multiple exploration paths in the same way to form an exploration path array; the maximum offset amount on each side is limited to half of the maximum exploration width. When considering passing points, only use the rectangle parallel line exploration mode; otherwise, use any one of the three exploration modes for exploration.

[0031] Preferably, the mileage step in S5 is 1m.

[0032] Preferably, in S6, set the maximum side length parameter of the triangle to 100 meters.

[0033] In S6, the method for vertex interpolation in the triangular mesh is as follows: Check each side of each triangle. If the side length of a certain side is greater than the set maximum side length, perform interpolation on this side with the maximum side length as the step, and add interpolation vertices; connect the interpolation vertices to the corner points of the triangle to obtain line segments, and perform secondary interpolation on these line segments according to the minimum side length to obtain new vertices; add all the generated interpolation vertices to the encrypted vertex array.

[0034] The areas in S8 are divided into cost-type areas, penalty-type areas, and reward-type areas, where:

[0035] The cost type area includes subgrade, bridge and tunnel, and is used to represent the structural types of railway projects during intelligent railway route selection;

[0036] The penalty type area includes rivers, lakes, existing railways, existing highways, poor geological areas, restricted areas, economic strongholds, planning areas, environmental protection core areas, environmental protection buffer areas, and environmental protection experimental areas, and is used to represent the areas to be avoided during intelligent railway route selection;

[0037] The reward type area includes railway traffic corridor belts, highway traffic corridor belts, and economic radiation areas, and is used to represent the areas to be as close as possible to during intelligent railway route selection to reduce land occupation and station setting requirements.

[0038] Preferably, in S8, the minimum value of the cost per meter of the cost type area and the penalty type area is 1; the maximum value of the cost per meter of the reward type area is 1.

[0039] In step S9, when calculating the edge cost, first accumulate the cost per meter of the cost type area and the penalty type area, then multiply the accumulated result by the cost per meter of the reward type area to generate the total cost per meter; finally, multiply the total cost per meter by the edge length to generate the edge cost.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. The method of the present invention considers important parameters such as the maximum gradient, minimum slope length, maximum algebraic difference of gradients, and bridge and tunnel settings during terrain exploration, and the constructed terrain exploration bridge and tunnel high-cost area has high reference value.

[0042] 2. The method of the present invention constructs a triangular mesh based on the area boundary and constructs an undirected graph based on the triangular mesh. Compared with the existing methods, it can not only effectively express the connectivity relationship, but also reduce the data redundancy, thereby improving the efficiency of graph-based channel search.

[0043] 3. The method of the present invention can quickly obtain the cost parameters by setting the area cost parameters and constructing an area query model, improving the efficiency of intelligent railway route selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a flowchart of the method of the present invention.

[0045] Figure 2 is a cost map obtained by using the method of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0046] The technical solutions of the present invention will be further described in detail below with reference to the drawings and embodiments.

[0047] AsFigure 1 As shown in Figure 1 , the method for rapid terrain exploration and cost map construction for intelligent railway route selection of the present invention includes the following steps:

[0048] S1. Set project design parameters:

[0049] According to the project design data, input the line parameters, the storage path of the ground point cloud data file, and the route selection boundary control data layer in the configuration file;

[0050] The line parameters include: vertical profile design parameters and bridge-tunnel gap design parameters; among them:

[0051] The vertical profile design parameters include: minimum slope section length, maximum gradient, maximum algebraic difference of gradients, minimum algebraic difference of gradients of vertical curves, vertical curve radius, minimum slope length constraint, maximum gradient constraint, maximum algebraic difference of gradients constraint, relaxation overlap constraint, gradient reduction constraint, gradient merging constraint, gradient smoothness constraint, and subgrade section treatment constraint;

[0052] The bridge-tunnel gap design parameters include bridge-tunnel critical height, minimum gap for bridge-tunnel merging, and maximum filling and excavation height for bridge-tunnel retention.

[0053] S2. Construct a digital elevation model and a route selection boundary control region:

[0054] Read the ground point cloud data file according to the storage path, and generate a digital elevation model using Delaunay triangulation; read the route selection boundary control data layer in S1 to obtain region data, generate an auxiliary boundary through the region data, and construct a route selection boundary control region;

[0055] The region data includes rivers, lakes, existing railways, existing highways, poor geological areas, restricted areas, economic strongholds, planning areas, environmental protection core areas, environmental protection buffer areas, and environmental protection experimental areas; if the existing highway or existing railway is a multi-segment line, it is converted into a closed region by setting the road width;

[0056] The auxiliary boundaries include railway traffic corridor belts, highway traffic corridor belts, and economic radiation areas, which are respectively formed by offsetting the boundaries of the existing railways, existing highways, and economic strongholds outward by a set offset amount.

[0057] S3. Construct a set of terrain exploration line plane models:

[0058] Set the exploration mode and exploration parameters, and construct an exploration path array. In the exploration path array, each exploration path is a set of point coordinates. Generate an intersection point array according to the exploration path. Each intersection point in the intersection point array includes coordinates, radius, and easement length attributes. Set the radius and easement length to 0, and use the intersection point method to construct a line plane model. Each exploration path constructs a line plane model, thereby forming a set of terrain exploration line plane models.

[0059] The exploration parameters include an exploration starting point, an exploration ending point, an array of exploration passing points, a maximum exploration width, an exploration spacing, a maximum exploration angle, and an exploration angle step size.

[0060] The exploration modes include rectangular parallel line exploration, fan-shaped ray exploration, and circular arc exploration. Among them:

[0061] The specific process of the rectangular parallel line exploration mode is as follows: First, construct a basic exploration path according to the exploration starting point, the array of exploration passing points, and the exploration ending point. Then, offset the basic exploration path multiple times to both sides by an integer multiple of the exploration spacing to generate multiple new exploration paths, obtaining an exploration path array. The maximum amount of offset on each side is limited to half of the maximum exploration width.

[0062] The specific process of the fan-shaped ray exploration mode is as follows: First, construct a basic exploration path according to the exploration starting point and the exploration ending point. Then, fix the exploration starting point, and rotate it multiple times to both sides from the basic exploration path by an integer multiple of the exploration angle step size to generate multiple new exploration paths, obtaining an exploration path array. The maximum rotation angle on each side is limited to half of the maximum exploration angle.

[0063] The specific process of the circular arc exploration mode is as follows: First, construct a basic exploration path according to the exploration starting point and the exploration ending point. Then, fix the exploration starting point and the ending point, calculate the midpoint of the basic exploration path, and use this midpoint as a reference to offset it to both sides by an integer multiple of the exploration spacing. Use trigonometric functions to calculate the radius and center coordinates of the circular arc, and construct a circular arc object. Starting from the starting point of the circular arc, sample according to the exploration step size to generate new exploration paths. According to the above method, after multiple offsets, generate multiple exploration paths in the same way to form an exploration path array. The maximum amount of offset on each side is limited to half of the maximum exploration width.

[0064] When considering passing points, only the rectangular parallel line exploration mode is used; otherwise, any one of the three exploration modes can be used for exploration.

[0065] S4. Construct a set of longitudinal section models of the terrain exploration line:

[0066] Perform longitudinal section design on each of the line plane models in the set of line plane models of the terrain exploration line obtained in S3 to obtain a corresponding line longitudinal section model. Multiple line longitudinal section models constitute a set of longitudinal section models of the terrain exploration line; the longitudinal section models and the line plane models are in one-to-one correspondence. The longitudinal section design includes generating a ground line according to the plane model and the digital elevation model in S2, performing longitudinal section slope fitting and constraint processing.

[0067] S5. Construct a set of high-cost regions of bridges and tunnels for terrain exploration:

[0068] First, generate a bridge-tunnel gap array using the line longitudinal section model in S4, the ground line, and the bridge-tunnel gap design parameters in S1. Then, use the line plane model corresponding to the line longitudinal section model to calculate the offsets on both the left and right sides of each bridge-tunnel gap at a mileage step of 1m, and calculate the offset coordinates on both sides. In this way, the offset coordinates on the left side of the bridge-tunnel gap form a point array, and the points in the point array are connected in sequence; the offset coordinates on the right side of the bridge-tunnel gap form a point array, and the points in the point array are connected in sequence; then connect the starting points of the two connected lines and connect the ending points to form a closed polygon, obtaining the bridge-tunnel gap region; finally, perform a union Boolean operation on all bridge-tunnel gap regions to merge similar regions and form a terrain exploration bridge-tunnel high-cost region set.

[0069] S6. Construct a triangular mesh based on the region boundary:

[0070] First, extract the boundary polygons of the route selection boundary control region in S2 and the terrain exploration bridge-tunnel high-cost region in S5 as feature lines, perform Delaunay triangulation, and construct a triangular mesh; then set the maximum side length parameter of the triangle (for example, set it to 100 meters), perform vertex interpolation in the triangular mesh to construct an encrypted vertex array; finally, use the boundary polygon feature lines and the encrypted vertex array to perform Delaunay triangulation again to generate the final triangular mesh;

[0071] The method of performing vertex interpolation in the triangular mesh is as follows: Check each edge of each triangle. If the length of a certain edge is greater than the set maximum side length, then perform interpolation on this edge with the maximum side length as the step size and add interpolation vertices; connect lines from the interpolation vertices to the corner points of the triangle to obtain line segments, and perform interpolation again on these line segments (the lines connecting the interpolation vertices and the corner points) according to the minimum side length to obtain new vertices; add all the generated interpolation vertices to the encrypted vertex array.

[0072] S7. Construct an undirected graph of the triangular mesh:

[0073] First, extract the vertex array and edge array of the final triangular mesh obtained in S6, and process the edge array to delete the overlapping edges with opposite directions; then create an empty undirected graph, add nodes to the undirected graph according to the vertex array, and use the vertex coordinates as node attributes. Then, add edges to the undirected graph according to the edge array, and use the side lengths as edge attributes, thereby obtaining the undirected graph of the triangular mesh.

[0074] S8. Set the region cost parameter and construct a region query model:

[0075] Group the route selection boundary control region constructed by S2 and the high-cost terrain exploration bridge and tunnel region obtained by S5, and set the cost per meter for each type of region; then use the boundary polygons of the route selection boundary control region obtained by S2 and the high-cost terrain exploration bridge and tunnel region obtained by S5 to construct a region query model, which can quickly query the set of region types to which a point coordinate belongs according to the point coordinates.

[0076] The regions are divided into cost regions, penalty regions, and reward regions; the cost regions include subgrade, bridges, and tunnels, representing the structural types of railway projects during intelligent railway route selection; the penalty regions include rivers, lakes, existing railways, existing highways, poor geological areas, restricted areas, economic strongholds, planning areas, environmental protection core areas, environmental protection buffer areas, and environmental protection experimental areas, representing the regions to be avoided as much as possible during intelligent railway route selection; the reward regions include railway traffic corridor belts, highway traffic corridor belts, and economic radiation regions, representing the regions to be as close to as possible during intelligent railway route selection to reduce land occupation and station setting requirements. Preferably, the minimum cost per meter of the cost region and the penalty region is 1; the maximum cost per meter of the reward region is 1.

[0077] The region query model is a data structure representing region types and region row and column intervals. This data structure is constructed by building a vertical line array within the range of the region boundary polygon according to a step size, performing intersection calculations between the vertical line array and all boundary polygons, adding the set of y-value intervals of the intersection points to the interval set with the vertical line array index as the key, and adding the interval set to the region set with the region type as the key.

[0078] S9. Construct a triangular mesh cost graph based on the triangular mesh undirected graph:

[0079] First, calculate the midpoint coordinates of each edge in the triangular mesh undirected graph in S7, then use the edge midpoint coordinates to query the region query model generated in S8 to obtain the set of region types and save it to the edge attributes; finally, for each type in the set of region types, obtain the cost per meter and calculate the cost of each edge to form a triangular mesh cost graph; the edge attributes include edge cost, edge length, and set of region types.

[0080] When calculating the edge cost, first accumulate the cost per meter of the cost region and the penalty region, then multiply the accumulated result by the cost per meter of the reward region to generate the total cost per meter; finally, multiply the total cost per meter by the edge length to generate the edge cost.

[0081] S10. Draw and save the triangular mesh cost graph:

[0082] For each edge in the triangular mesh cost graph, set different colors according to the size of the edge cost and draw it to visually reflect the high and low characteristics of the costs in different regions in the route selection scenario.Figure 2 An example of a cost map obtained by using the method of the present invention is shown. Different colors in the figure represent different costs. The triangular mesh cost map is saved as a cost map file.

[0083] When performing channel search for intelligent railway route selection subsequently, data can be directly read from the cost map file to form a cost map.

Claims

1. A method for rapid terrain exploration and cost map construction for intelligent railway line selection, characterized in that The following steps are involved: S1, set project design parameters: According to the project design data, input the line parameters, the storage path of the ground point cloud data file and the line selection boundary control data layer in the configuration file, wherein the line parameters include: longitudinal section design parameters and bridge and tunnel gap design parameters; S2, build digital elevation model and select line boundary control area: Read the ground point cloud data file according to the storage path, generate a digital elevation model using Delaunay triangulation, read the line selection boundary control data layer in S1 to obtain the surface area data, generate an auxiliary boundary through the surface area data, and construct a line selection boundary control surface area; S3, construct a terrain exploration route plane model set: Set the exploration mode and exploration parameters, build an exploration path array; build an intersection array based on the exploration path, and set the radius and slow length of each intersection in the intersection array to 0, build a line plane model using the intersection method, and build a line plane model for each exploration path, thereby forming a terrain exploration line plane model set; where: The detection parameters include detection starting point, detection end point, detection path point array, maximum detection width, detection spacing, maximum detection angle and detection angle step; The detection modes include rectangular parallel line detection, fan-shaped ray detection and circular arc detection; S4, constructing a terrain exploration route longitudinal section model set: Performing longitudinal section design on each of the line plane models in the terrain exploration line plane model set obtained in S3 to obtain a corresponding line longitudinal section model, and multiple line longitudinal section models constitute the terrain exploration line longitudinal section model set; the longitudinal section model and the line plane model correspond one to one; the longitudinal section design includes generating a ground line according to the plane model and the digital elevation model in S2, performing longitudinal section slope fitting and constraint processing; S5, construct a high-cost surface set for terrain exploration bridges and tunnels: First, the line longitudinal section model in S4, the ground line and the bridge and tunnel gap design parameters of S1 are used to generate a bridge and tunnel gap array; then, the line plane model corresponding to the line longitudinal section model is used to calculate the offset and offset coordinates on the left and right sides of each bridge and tunnel gap according to a fixed mileage step; the offset coordinates on the left and right sides of the bridge and tunnel gap each form a point array, and the points in the two point arrays are sequentially connected, and then the starting points and end points of the two connecting lines are connected respectively to form a closed polygon, and the bridge and tunnel gap area is obtained; finally, a union Boolean operation is performed on all bridge and tunnel gap area domains, and similar area domains are merged to form a high-cost area set of terrain exploration bridges and tunnels; S6, construct triangulated network based on surface boundary: First, extract the boundary polygons of the line selection boundary control area in S2 and the high-cost area of ​​the terrain exploration bridge and tunnel in S5 as feature lines, perform Delaunay triangulation, and construct a triangulated network; then set the maximum side length parameter of the triangle, perform vertex interpolation in the triangulated network, and construct an encrypted vertex array; then use the boundary polygon feature lines and the encrypted vertex array to re-perform Delaunay triangulation to generate the final triangulated network; S7, construct a triangulated undirected graph based on the triangulated network: First, extract the vertex array and edge array of the final triangulated network obtained by S6, and process the edge array to delete the overlapping edges with opposite directions; then create an empty undirected graph, add nodes of the undirected graph according to the vertex array, and use the vertex coordinates as node attributes, and then add edges of the undirected graph according to the edge array, and use the edge length as the edge attribute, thereby obtaining the triangulated network undirected graph; S8, set the face area cost parameters and build the face area query model: The line selection boundary control surface domain constructed by S2 and the high-cost surface domain of terrain exploration bridge and tunnel obtained by S5 are grouped, and the extended-meter cost is set for each surface domain type; then the boundary polygons of the line selection boundary control surface domain obtained by S2 and the high-cost surface domain of terrain exploration bridge and tunnel obtained by S5 are used to construct a surface domain query model, which can quickly query the surface domain type set according to the point coordinates; S9, construct the triangulated network cost graph based on the triangulated undirected graph: First, the midpoint coordinates of each edge in the triangulated undirected graph in S7 are calculated, and then the midpoint coordinates of the edge are used to query the face query model generated by S8, and the face type set is obtained and saved in the edge attributes; finally, for each type in the face type set, the linear meter cost is obtained, and the cost of each edge is calculated to form a triangulated network cost graph; the edge attributes include edge cost, edge length and face type set; S10, draw the triangulated network cost map and save it: For each edge in the triangulated network cost map, different colors are set according to the size of the edge cost; the triangulated network cost map is saved as a cost map file; when performing channel search for railway intelligent line selection later, the cost map file is directly read to regenerate the cost map.

2. The method for rapid terrain exploration and cost map construction for intelligent railway line selection according to claim 1 is characterized in that: The longitudinal section design parameters described in S1 include the minimum slope section length, maximum slope, maximum slope algebraic difference, minimum slope algebraic difference of vertical curves, vertical curve radius, minimum slope length constraint, maximum slope constraint, maximum slope algebraic difference constraint, relief overlap constraint, slope reduction constraint, slope merging constraint, slope smoothness constraint and roadbed section processing constraint; the bridge and tunnel gap design parameters include the critical height of bridge and tunnel, the minimum gap of bridge and tunnel merging and the maximum fill and cut height retained by bridge and tunnel.

3. The method for rapid terrain exploration and cost map construction for intelligent railway line selection according to claim 1 is characterized in that: The area data in S2 include rivers, lakes, existing railways, existing roads, unfavorable geological areas, restricted areas, economic strongholds, planning areas, environmental protection core areas, environmental protection buffer areas, and environmental protection experimental areas; If the existing highway or railway is a polyline, convert it into a closed surface by setting the road width; The auxiliary boundaries include a railway traffic corridor, a highway traffic corridor, and an economic radiation zone, which are formed by respectively shifting the boundaries of the existing railways, existing highways, and economic bases outward according to a set offset amount.

4. The method for rapid terrain exploration and cost map construction for intelligent railway line selection according to claim 1 is characterized in that: In S3: The rectangular parallel line exploration mode is specifically as follows: firstly, a basic exploration path is constructed according to the exploration starting point, the exploration path array and the exploration end point, and then the basic exploration path is shifted to both sides multiple times by the integer of the exploration interval to generate multiple new exploration paths, and obtain an array of exploration paths; the maximum amount of the shift on each side is limited to half of the maximum exploration width; The fan-shaped ray exploration mode is specifically as follows: first, a basic exploration path is constructed according to the exploration starting point and the exploration end point; then, the exploration starting point is fixed, and multiple rotations are performed from the basic exploration path to both sides at integer multiples of the exploration angle step length to generate multiple new exploration paths, and an array of exploration paths is obtained; the maximum angle of rotation on each side is limited to half of the maximum exploration angle; The circular arc exploration mode is specifically as follows: first, a basic exploration path is constructed according to the exploration start point and the exploration end point; then, the exploration start point and the exploration end point are fixed, the midpoint of the basic exploration path is calculated, and the midpoint is used as a reference to offset to both sides by an integer multiple of the exploration interval, and the radius and center coordinates of the arc are calculated by trigonometric functions to construct an arc object; starting from the arc start point, sampling is performed according to the exploration step length to generate a new exploration path; according to the above method, after multiple offsets, multiple exploration paths are generated by the same method to form an exploration path array; the maximum amount of offset on each side is limited to half of the maximum exploration width; When waypoints are considered, only the rectangular parallel lines probing mode is used; otherwise, any of the three probing modes are used for probing.

5. The method for rapid terrain exploration and cost map construction for intelligent railway line selection according to claim 1, characterized in that: The mileage step size in S5 is 1m.

6. The method for rapid terrain exploration and cost map construction for intelligent railway line selection according to claim 1, characterized in that: In S6, the maximum side length parameter of the triangle is set to 100 meters.

7. The method for rapid terrain exploration and cost map construction for intelligent railway line selection according to claim 1, characterized in that: In S6, the method of interpolating vertices in the triangulated network is as follows: check each edge of each triangle, if the length of an edge is greater than the set maximum edge length, interpolate on the edge with the maximum edge length as the step length, and add the interpolated vertex; Connect the interpolated vertex to the corner point of the triangle to get a line segment, and interpolate again on the line segment according to the minimum side length to get a new vertex; Add all interpolated vertices generated to the encrypted vertex array.

8. The method for rapid terrain exploration and cost map construction for intelligent railway line selection according to claim 1, characterized in that: The domains described in S8 are divided into cost-type domains, penalty-type domains and reward-type domains, where: The cost profile domain includes roadbed, bridge, and tunnel, which are used to represent the structural type of railway engineering during intelligent railway line selection; The penalty-type areas include rivers, lakes, existing railways, existing roads, bad geological areas, restricted areas, economic strongholds, planning areas, environmental protection core areas, environmental protection buffer areas, and environmental protection experimental areas, which are used to represent areas to avoid crossing during intelligent railway line selection; The reward-type areas include railway traffic corridors, highway traffic corridors, and economic radiation zones, which are used to represent areas that are as close as possible to reduce land occupation and station setting needs during intelligent railway line selection.

9. The method for rapid terrain exploration and cost map construction for intelligent railway line selection according to claim 8, characterized in that: In S8, the minimum value of the extended-meter cost of the fee-type surface area and the penalty-type surface area is 1; the maximum value of the extended-meter cost of the reward-type surface area is 1.

10. The method for rapid terrain exploration and cost map construction for intelligent railway line selection according to claim 9, characterized in that: When calculating the edge cost in S9, the extended-meter costs of the fee-type surface area and the penalty-type surface area are first accumulated, and then the accumulated result is multiplied by the extended-meter cost of the reward-type surface area to generate the total extended-meter cost; finally, the total extended-meter cost is multiplied by the edge length to generate the edge cost.

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