CN114154382B - High-resolution remote sensing three-dimensional visual railway route selection auxiliary decision making system and method - Google Patents
High-resolution remote sensing three-dimensional visual railway route selection auxiliary decision making system and method Download PDFInfo
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Abstract
The invention discloses a high-resolution remote sensing three-dimensional visual railway route selection aid decision making system and a method, comprising the following steps of firstly, building a plane design route; step two, generating an initial guide line; step three, intelligently optimizing a guide line; step four, editing the nodes in detail; designing transverse and longitudinal end faces; sixthly, evaluating a design scheme; step seven, comprehensive evaluation of cost; according to the method, the high-resolution remote sensing three-dimensional data source of the circuit planning place is extracted by the high-resolution image extraction module, the immersive three-dimensional scene based on the high-resolution remote sensing image is constructed by the three-dimensional modeling module and is displayed by the three-dimensional visualization module, the intuition of the circuit is improved, the display effect is improved, the initial guide line of the circuit is established by the basic HAO model, the planar longitudinal plane of the circuit is optimized by the RPSO particle swarm optimization algorithm, the method is simple and direct, the calculation efficiency is greatly improved, the error is reduced, and the reliability of the calculation result is improved.
Description
Technical Field
The invention relates to the technical field of railway topographic mapping, in particular to a high-resolution remote sensing three-dimensional visual railway route selection aid decision making system and method.
Background
In 2011, an improved Dijkstra algorithm is researched based on optimal path analysis, such as Korea and Chunhua, thought-easy and the like, an optimal path is automatically generated between control points based on knowledge reasoning, but the optimization algorithm has high dependency on related parameters, and a set of complete method system does not exist for selecting the current parameters;
the southwest traffic university thought professor carries out a great deal of research on a railway route selection design method and a plane automatic optimization method of a virtual environment, introduces a virtual environment concept into railway survey design, provides concepts such as intelligent environment modeling and natural environment modeling, researches an expression mode of knowledge in the virtual environment and an object-oriented reasoning mechanism, develops an intelligent CAD prototype system for designing a new railway route based on the virtual environment, is applied to the intelligent CAD prototype system for designing the new railway route, carries out experiments in an IRLCAD system, but requires iterative computation from a known initial point, and the selection of the initial point has great influence on optimization efficiency;
the method is characterized in that the Yangbulin of the university of China completes the positioning and planning of the spatial position of a railway line according to main technical standards in the aspect of railway intelligent route selection, provides a three-dimensional space intelligent route selection method based on an improved HAO model and a Rosenbrock-based PSO algorithm (RPSO), and develops a three-dimensional space intelligent route selection practical system by combining an ArcGIS with the method, but the system only considers part of constraint conditions, and has less factors considered in the aspects of engineering investment, engineering cost, expropriation and removal and environmental influence in the cost calculation;
cheng and Lee propose a neighborhood heuristic linear optimization model to find out a planar linear shape and a mixed integer programming method to find out a longitudinal section linear shape. The model considers various expenses such as earthwork, bridges and culverts, tunnels and the like in the objective function, and directly adds a relaxation curve while meeting curve constraint in the optimization of the planar linearity, so that the model is more in line with actual linearity, but the model is a three-dimensional linearity obtained in a two-stage mode, namely, the planar linearity is optimized firstly, and then the longitudinal section linearity is optimized on the basis, so that the model is easy to fall into local optimization;
at present, most railway route selection optimization systems on the market are not visual enough, most route optimization systems are two-dimensional imaging, the route design difficulty is high, certain difference exists between route calculation and cost calculation, the reliability of equipment is reduced, the existing calculation method is complex, the calculation efficiency is low, and the working efficiency is reduced.
Disclosure of Invention
The invention aims to provide a high-resolution remote sensing three-dimensional visual railway route selection auxiliary decision making system and method to solve the problems of low calculation efficiency, large error and non-intuitive result in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the high-resolution remote sensing three-dimensional visual railway route selection decision-making assisting system comprises a display screen, wherein a project management module, a high-resolution image extraction module, a plane design module, a transverse and longitudinal section design module and a design evaluation module are sequentially arranged on the display screen.
Preferably, the project management module comprises a three-dimensional visualization module, a three-dimensional roaming module, a three-dimensional modeling module, a design data management and output module, a newly-built project module, a project opening module, a project saving module and a project loading module, wherein the three-dimensional visualization module is positioned above the three-dimensional roaming module, the three-dimensional roaming module is positioned above the three-dimensional modeling module, the three-dimensional modeling module is positioned above the design data management and output module, the design data management and output module is positioned above the newly-built project module, the newly-built project module is positioned on duty of the project opening module, the project opening module is positioned above the project saving module, and the project saving module is positioned above the project loading module.
Preferably, the high-resolution image extraction module comprises a new image creation module, an image deletion module, an image loading module and a storage identification module, the new image creation module is located at one side of the image deletion module, the image deletion module is located at one side of the image loading module, and the image loading module is located at one side of the storage identification module.
Preferably, the plane design module comprises a manual line selection module, an automatic line selection module, a node editing module, a line new building module, a line editing module, a line deleting module, a line storage module and an intelligent optimization module, wherein the manual line selection module is positioned above the automatic line selection module, the automatic line selection module is positioned above the node editing module, the node editing module is positioned above the line new building module, the line new building module is positioned above the line editing module, the line editing module is positioned above the line deletion module, the line deletion module is positioned above the line storage module, and the line storage module is positioned above the intelligent optimization module.
Preferably, the horizontal and vertical section design module comprises a section newly-built module, a section editing module, a section deleting module, a section storing module, a section adjusting module and a section generating module, wherein the section newly-built module is located above the section editing module, the section editing module is located above the section deleting module, the section deleting module is located above the section storing module, the section storing module is located above the section adjusting module, and the section adjusting module is located above the section generating module.
Preferably, the design evaluation module comprises an earth and rock volume calculation module, a line slope point determination module and a comprehensive evaluation module, wherein the earth and rock volume calculation module is positioned above the line slope point determination module, and the line slope point determination module is positioned above the comprehensive evaluation module.
The auxiliary decision-making method for selecting the high-resolution remote sensing three-dimensional visual railway line comprises the following steps of firstly, building a plane design line; step two, generating an initial guide line; step three, intelligently optimizing a guide line; step four, editing the nodes in detail; designing transverse and longitudinal end faces; step six, evaluating a design scheme; step seven, comprehensive evaluation of cost;
in the first step, a new project is built by using a newly built project module in a project management module, then a high-resolution remote sensing three-dimensional image of a line selection position is obtained by using a high-resolution image extraction module, then a remote sensing three-dimensional image of the position needing line selection is called by using a three-dimensional visualization module, and then a line newly built module in a plane design module is used for setting related parameters such as a design line name, a design line number, a starting point stake number, a design speed, a line width and the like;
in the second step, after the line parameter setting in the first step is finished, a manual line selection module is used for manually selecting a line, a mouse is used for clicking a function button, coordinates are picked up in a three-dimensional image, unit prices of earthwork, bridge and tunnel are set, then the particle number and the total cycle number are set, a determination button is clicked immediately, and an initial guide line is automatically generated by an immediately-clicking line editing module according to a line generation method;
in the third step, after the initial guide line in the second step is generated, the intelligent optimization module is used for optimizing by adopting a particle swarm optimization circuit, namely, the three-dimensional linear optimization problem can be solved as a process of finding the optimal circuit plane and vertical plane parameter set in a research area, and the mathematical model description is as follows: min f (X, Y, R, L) 0 ,L C H, R), first modified by parameters: inertial weight, shrinkage factor, tracking dynamics: secondly, a mixing algorithm: improving the search behavior pattern from particle to particle: and finally, improving the particle swarm optimization in a mode of introducing an individual current optimal point in searching by using a network topology concept to obtain the particle swarm optimization, and then performing optimization calculation on the line by using the particle swarm optimization, wherein the steps of basic searching, static searching, axis searching and the like of the particles are performed, and the implementation process is as follows:
1) Initializing parameters such as particle dimension, particle scale, search range, speed, maximum iteration number and the like;
2) Calculating the fitness of each particle;
3) Comparing the adaptive value of each particle with the adaptive value of the best position pbest experienced by the particle, if the adaptive value is better, taking the adaptive value as the best position, and updating pbest;
4) Comparing the adaptive value of each particle with the adaptive value of the best global position gbest, if the adaptive value is better, taking the adaptive value as the current best global position, and updating the gbest;
5) Updating the speed and position of each particle;
6) If the end condition is met, outputting the gbest, otherwise, returning to 2);
in the aspect of automatic avoidance of the road ground objects, a linear intersection judgment method is adopted for realizing, and the basic idea is as follows: is known as (x) 1 ,y 1 ),(x 2 ,y 2 ) Determining a straight line Ax + By + C =0, wherein the coordinates (x, y) of the intersection point of the straight line can be obtained through calculating the coefficients A, B and C, and whether the intersection point is on the line segment only needs to be judged (y-y) 1 )/(y-y 2 ) The sign is positive, if the value is negative, the point is on the line segment, and on the line segment, the point needs to be avoided, and the specific implementation method is as follows: if the node on the ith tangent line is judged to be intersected with the line segment of the found point of the (i-1) th tangent line and any one edge of the ground object vector polygon, continuously searching a line node P which meets the gradient requirement and avoids the ground object on the ith tangent line i Forming an optimized line after automatically avoiding the obstacle;
in the fourth step, after the line in the third step is optimized, the detailed information of each node of the generated line is checked through the three-dimensional roaming function in the unique three-dimensional roaming module of Skyline, and the information such as coordinates, parameters, corners and the like is checked and the types of connecting lines at the nodes are modified by utilizing the node editing module;
in the fifth step, after the detailed node modification in the fourth step is finished, the transverse and longitudinal section design module generates transverse and longitudinal section information of the line, and prefabricating standard transverse sections of railway roads, bridges, tunnels and the like, and automatically finishing extraction and calculation of transverse and longitudinal section ground lines;
in the sixth step, after the transverse and longitudinal end faces in the fifth step are set, the earth and stone volume calculation module in the design evaluation module calculates, displays and outputs the earth and stone volume of the selected route scheme, and according to the cost model, the route scheme is designed and evaluated by comprehensively considering multiple targets of economy and environment, and the calculation model is as follows:
wherein, K j For the construction unit price of class j plots, j =1,2,3 j Area of class j plots covered for road, cost C associated with location N The calculation idea of the cost related to the length is as follows: in the line selection stage, the line is supposed to be only composed of a straight line unit and a circular curve unit, and R is set i Is the radius of the ith intersection circular curve, C i (xc i ,yc i ) And T i (xt i ,yt i ) Respectively ZY point and YZ point, delta at the ith intersection i Is the curve corner at the ith intersection point, the total length L of the line N Comprises the following steps:
in the formula: n is the total number of the circular curves, and the cost related to the road also comprises some engineering cost and environment related cost, wherein the cost of the roadbed earth and stone is the most important, and the corresponding cost of the roadbed earth and stone is calculated by adopting the following formula:
the roadbed cross section area algorithm formula is as follows:
A＝B·ΔH+m·ΔH 2
in the formula: b is the road pavement width; delta H is the filling and digging height of the roadbed, and the value of the filling and digging height is the absolute value of the difference between the ground elevation and the grid elevation of the point; 1 m-slope ratio; n is the number of calculated sections of the roadbed earth and stone; d i -the subgrade of section i is calculated for length; c. C i -the cost of the roadbed excavation at section i; a. The il -the cross sectional area of the roadbed at the left side of the i-th section; a. The ir The cross section area of the roadbed on the right side of the i-th section is determined;
in summary, the comprehensive cost calculation is to unify the multi-factor problem in the line optimization process, and convert the problem into the total line cost, and then the cost model is expressed as:
C＝C N +C Q +C L +C qs
thereby obtaining the cost required by the line construction;
in the seventh step, after the cost is calculated according to the cost model in the sixth step, the comprehensive evaluation module evaluates the cost in several aspects such as total cost, construction cost, engineering cost, floor space cost and the like, and outputs an evaluation result after the output position is selected.
Preferably, in the second step, the line generation method includes: generating an initial guide line by referring to the HAO model, and inputting coordinates S (x) of start and end points of the line s ,y s )、E(x E ,y E ) Considering relevant constraints, slope constraints, continuous turning limitation, elevation constraints of control points and the like in the design process, assuming that the starting point and the ending point are S and E respectively, connecting the starting point and the ending point SE, equally dividing the SE by m tangent lines, and intersecting the tangent lines and the lines at m different points P i And the m points are line intersection points, and line node optimization is performed on the m tangent lines, and the method defines two sets of coordinate systems: the global coordinate system takes north as an x axis and east as a y axis; secondly, the image local coordinate system takes the upper left corner of the image as the origin of coordinates, and the image boundaries are x and y axes respectively, and the method comprises the following concrete implementation steps:
on each tangent line, mark O i Is the origin of coordinates of the ith tangent line with coordinates of (x) oi ,y oi ) Comprises the following steps:
each point of intersection P i Everywhere d i In different one-dimensional local coordinate systems, in order to obtain the intersection point sequence of the line model, converting the intersection point sequence into a global coordinate system, adding a black tangent line and an x axis to form an included angle theta, and then obtaining the P value i The global coordinates of (a) are:
finally, a chain type broken line is formed by connecting all the intersection points, and an initial guide line designed by line selection is obtained.
Preferably, in the third step, the particle swarm algorithm PSO basic principle is as follows:
V id ＝ωV id +C 1 random(0,1)(P id -X id )+C 2 random(0,1)(P gd -X id )
X id ＝X id +V id
wherein, omega is an inertia factor, the value of which is not negative, and the global optimization performance and the local optimization performance can be adjusted by adjusting the value, C 1 And C 2 For the acceleration constant, the former is an individual learning factor for each particle, and the latter is a social learning factor for each particle, usually set to C 1 ＝C 2 =2,random (0, 1) means the interval [0,1]Random number of (2), P id D-dimension, P, representing the individual extremum of the i-th variable gd The d-th dimension representing the global optimal solution.
Compared with the prior art, the invention has the following beneficial effects: according to the method, the high-resolution remote sensing three-dimensional data source of the route planning place is extracted by using the high-resolution image extraction module, the immersive three-dimensional scene based on the high-resolution remote sensing image is constructed by the three-dimensional modeling module and displayed by the three-dimensional visualization module, the intuitiveness of the route is improved, the display effect is improved, the initial guide line of the route is established by using the basic HAO model, and the plane and the longitudinal plane of the route are optimized by using the RPSO particle swarm optimization algorithm, so that the method is simple and direct, the calculation efficiency is greatly improved, the error is reduced, and the reliability of the calculation result is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
FIG. 1 is a block diagram of the overall structure of the present invention;
FIG. 2 is a technical route flow diagram of the present invention;
FIG. 3 is a system flow diagram of the present invention;
FIG. 4 is a schematic diagram of the present invention prior to obstacle avoidance;
FIG. 5 is a schematic diagram of the present invention after obstacle avoidance;
FIG. 6 is a flow chart of the particle swarm optimization algorithm of the present invention;
FIG. 7 is a flow chart of a method of the present invention;
in the figure: 1. a project management module; 2. a high-resolution image extraction module; 3. a planar design module; 4. designing a module for the transverse and longitudinal sections; 5. designing an evaluation module; 6. a display screen; 101. a three-dimensional visualization module; 102. a three-dimensional roaming module; 103. a three-dimensional modeling module; 104. designing a data management and output module; 105. a project module is newly built; 106. opening the project module; 107. saving the project module; 108. loading a project module; 201. an image new building module; 202. an image deletion module; 203. an image loading module; 204. storing the identification module; 301. a manual line selection module; 302. an automatic line selection module; 303. a node editing module; 304. a circuit newly building module; 305. a line editing module; 306. a line deletion module; 307. a line saving module; 308. an intelligent optimization module; 401. building a module on the section; 402. a section editing module; 403. a section deletion module; 404. a section storage module; 405. a section adjusting module; 406. a section generation module; 501. an earth and stone volume calculating module; 502. a line slope point determining module; 503. and a comprehensive evaluation module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1-3, the present invention provides a technical solution: a high-resolution remote sensing three-dimensional visual railway route selection auxiliary decision-making system comprises a display screen 6, wherein a project management module 1, a high-resolution image extraction module 2, a plane design module 3, a transverse and longitudinal section design module 4 and a design evaluation module 5 are sequentially arranged on the display screen 6, the project management module 1 comprises a three-dimensional visual module 101, a three-dimensional roaming module 102, a three-dimensional modeling module 103, a design data management and output module 104, a new project module 105, an opening project module 106, a project storage module 107 and a loading project module 108, the three-dimensional visual module 101 is positioned above the three-dimensional roaming module 102, the three-dimensional roaming module 102 is positioned above the three-dimensional modeling module 103, the three-dimensional modeling module 103 is positioned above the design data management and output module 104, the design data management and output module 104 is positioned above the new project module 105, the new project module 105 is positioned on duty at the opening project module 106, the opened project module 106 is located above the saved project module 107, the saved project module 107 is located above the loaded project module 108, the high-resolution image extraction module 2 comprises an image creating module 201, an image deleting module 202, an image loading module 203 and a saving identification module 204, the image creating module 201 is located at one side of the image deleting module 202, the image deleting module 202 is located at one side of the image loading module 203, the image loading module 203 is located at one side of the saving identification module 204, the flat panel design module 3 comprises a manual route selection module 301, an automatic route selection module 302, a node editing module 303, a route creating module 304, a route editing module 305, a route deleting module 306, a route saving module 307 and an intelligent optimization module 308, the manual route selection module 301 is located above the automatic route selection module 302, and the automatic route selection module 302 is located above the node editing module 303, the node editing module 303 is located above the line new building module 304, the line new building module 304 is located above the line editing module 305, the line editing module 305 is located above the line deleting module 306, the line deleting module 306 is located above the line storing module 307, the line storing module 307 is located above the intelligent optimizing module 308, the cross section design module 4 comprises a section new building module 401, a section editing module 402, a section deleting module 403, a section storing module 404, a section setting module 405 and a section generating module 406, the section new building module 401 is located above the section editing module 402, the section editing module 402 is located above the section deleting module 403, the section deleting module 404 is located above the section storing module 404, the section storing module 404 is located above the section setting module 405, the section setting module 405 is located above the section generating module 406, the design and evaluation module 5 comprises an earth and stone volume calculating module 501, a line slope point determining module 502 and a comprehensive evaluation module 503, the earth and stone volume calculating module 501 is located above the line point determining module 502, and the line slope point determining module 503 is located above the comprehensive evaluation module 503.
Referring to fig. 4-7, the present invention provides a technical solution: the auxiliary decision-making method for selecting the high-resolution remote sensing three-dimensional visual railway line comprises the following steps of firstly, building a plane design line; step two, generating an initial guide line; step three, intelligently optimizing a guide line; step four, editing the nodes in detail; designing transverse and longitudinal end faces; sixthly, evaluating a design scheme; step seven, comprehensive evaluation of cost;
in the first step, firstly, a new project is built by using a newly-built project module 105 in a project management module 1, then, a high-resolution remote sensing three-dimensional image of a line selection position is obtained by using a high-resolution image extraction module 2, then, a remote sensing three-dimensional image of the position needing line selection is called by using a three-dimensional visualization module 101, and then, related parameters such as a design line name, a design line number, a starting point stake number, a design speed, a line width and the like are set by using a line newly-built module 304 in a plane design module 3;
in the second step, after the setting of the line parameters in the first step is completed, the manual line selection module 301 is used for performing manual line selection, a mouse is used for clicking a function button, coordinates are picked up in a three-dimensional image, unit prices of earthwork, bridge and tunnel are set, then the number of particles and the total number of cycles are set, a determination button is clicked immediately, the line editing module 305 automatically generates an initial guide line according to a line generation method, and the line generation method is as follows: generating an initial guide line by referring to the HAO model, and inputting coordinates S (x) of the start point and the end point of the line s ,y s )、E(x E ,y E ) And is arranged atConsidering relevant constraints, slope constraints, limitation of continuous turning, control point elevation constraints and the like in the counting process, assuming that a starting point and an end point are S and E respectively, connecting a starting point and an end point SE, equally dividing SE by m tangent lines, and intersecting the tangent lines and lines at m different points P i And the m points are line intersection points, line node optimization is performed on the m tangent lines, and the method also defines two sets of coordinate systems: the global coordinate system takes north as an x axis and east as a y axis; secondly, the image local coordinate system takes the upper left corner of the image as the origin of coordinates, and the image boundaries are x and y axes respectively, and the method comprises the following concrete implementation steps:
on each tangent line, note O i Is the origin of coordinates of the ith tangent line with coordinates of (x) oi ,y oi ) Comprises the following steps:
each point of intersection P i Everywhere d i In different one-dimensional local coordinate systems, in order to obtain the intersection point sequence of the line model, converting the intersection point sequence into a global coordinate system, adding a black tangent line and an x axis to form an included angle theta, and then obtaining the P value i The global coordinates of (a) are:
finally, a chain type folding line is formed by connecting all the intersection points to obtain an initial guide line designed by line selection;
in the third step, after the initial guide line in the second step is generated, the intelligent optimization module 308 is used to perform optimization by using a particle swarm algorithm, that is, the three-dimensional linear optimization problem can be summarized as a process of finding an optimal line plane and profile parameter set in a research area, and the mathematical model is described as follows: min f (X, Y, R, L) 0 ,L C H, R), the particle swarm algorithm PSO basic principle is as follows:
V id ＝ωV id +C 1 random(0,1)(P id -X id )+C 2 random(0,1)(P gd -X id )
X id ＝X id +V id
where ω is an inertia factor whose value is not negative, global optimization performance and local optimization performance can be adjusted by adjusting the value, and C 1 And C 2 For the acceleration constant, the former is an individual learning factor for each particle, and the latter is a social learning factor for each particle, and C is usually set 1 ＝C 2 =2,random (0, 1) means the interval [0,1]Random number of (2), P id D-dimension, P, representing the individual extremum of the i-th variable gd The d-th dimension, representing the global optimal solution, is first refined by parameters: inertial weight, shrinkage factor, tracking dynamics: and secondly, a mixing algorithm: improving the search behavior pattern from particle to particle: and finally, improving the particle swarm optimization algorithm in a mode of introducing an individual current optimal point in searching by using a network topology concept to obtain the particle swarm optimization algorithm, and then performing optimization calculation on the line by using the particle swarm optimization algorithm, wherein the steps of basic searching, static searching, axis searching and the like of the particles are performed, and the implementation process is as follows:
1) Initializing parameters such as particle dimension, particle scale, search range, speed, maximum iteration number and the like;
2) Calculating the fitness of each particle;
3) Comparing the adaptive value of each particle with the adaptive value of the best position pbest experienced by the particle, if the adaptive value is better, taking the adaptive value as the best position, and updating pbest;
4) Comparing the adaptive value of each particle with the adaptive value of the best global position gbest, if the adaptive value is better, taking the adaptive value as the current best global position, and updating the gbest;
5) Updating the speed and position of each particle;
6) If the end condition is met, outputting the gbest, otherwise, returning to 2);
in the aspect of automatic avoidance of the road ground objects, a linear intersection judgment method is adopted for realizing, and the basic idea is as follows: is known as (x) 1 ,y 1 ),(x 2 ,y 2 ) Determining the straight line Ax+ By + C =0. Wherein, the coordinates (x, y) of the intersection point of the straight line can be obtained by calculating the coefficients A, B and C, and whether the intersection point is on the line segment is detected only by judging (y-y) 1 )/(y-y 2 ) The sign is positive, if the value is negative, the point is on the line segment, and on the line segment, the point needs to be avoided, and the specific implementation method is as follows: if the line segment of the node on the ith tangent line and the found point of the (i-1) th tangent line is intersected with any one side of the ground feature vector polygon, continuously searching a line node P which meets the gradient requirement and avoids the ground feature on the ith tangent line i Forming an optimized line after automatically avoiding the obstacle;
in the fourth step, after the line in the third step is optimized, the detailed information of each node of the generated line is checked through the three-dimensional roaming function in the Skyline unique three-dimensional roaming module 102, and the information such as coordinates, parameters, corners and the like is checked and the connection line type at the node is modified by using the node editing module 303;
in the fifth step, after the detailed node modification in the fourth step is finished, the transverse and longitudinal section design module 4 generates transverse and longitudinal section information of the line, and prefabricating standard transverse sections of railway roads, bridges, tunnels and the like, and automatically finishing extraction and calculation of transverse and longitudinal section ground lines;
in the sixth step, after the transverse and longitudinal end faces in the fifth step are set, the earth and stone volume calculation module 501 in the design evaluation module 5 calculates, displays and outputs the earth and stone volume of the selected route scheme, and according to the cost model, comprehensively considers multiple targets of economy and environment to design and evaluate the route scheme, wherein the calculation model is as follows:
wherein, K j For the construction unit price of class j plots, j =1,2,3 j Area of class j plots covered for road, cost C associated with location N The calculation idea of the cost related to the length is as follows: in the route selection stage, the assumption is made that the route only consists of a straight line unit and a circular curve unitElement structure, provided R i Is the radius of the circular curve at the i-th intersection point, C i (xc i ,yc i ) And T i (xt i ,yt i ) Respectively ZY point and YZ point, delta at the ith intersection i Is the curve corner at the ith intersection point, the total length L of the line N Comprises the following steps:
in the formula: n is the total number of the circular curves, and the cost related to the road also comprises some engineering cost and environment related cost, wherein the cost of the roadbed earth and stone is the most important, and the corresponding cost of the roadbed earth and stone is calculated by adopting the following formula:
the roadbed cross section area algorithm formula is as follows:
A＝B·ΔH+m·ΔH 2
in the formula: b is the road pavement width; delta H is the filling and digging height of the roadbed, and the value of the filling and digging height is the absolute value of the difference between the ground elevation and the grid elevation of the point; 1 m-slope ratio; n is the number of calculation sections of the roadbed earth and stone squares; d i -the subgrade of section i is calculated for length; c. C i -the cost of the roadbed excavation at section i; a. The il -the cross sectional area of the roadbed at the left side of the i-th section; a. The ir -the cross sectional area of the roadbed at the right side of the roadbed at the i-th section;
in summary, the comprehensive cost calculation is to unify the multi-factor problem in the process of optimizing the line and convert the problem into the total cost of the line, and the cost model is expressed as follows:
C＝C N +C Q +C L +C qs
thereby obtaining the cost required by the line construction;
in the seventh step, after the cost is calculated based on the cost model in the sixth step, the comprehensive evaluation module 503 evaluates the cost in terms of the total cost, the structure cost, the construction cost, the floor space cost, and the like, and outputs the evaluation result after the output position is selected.
Based on the above, the method has the advantages that when the method is used, the three-dimensional visualization module 101 and the three-dimensional modeling module 103 are used for calling the high-resolution remote sensing three-dimensional data source, the immersive three-dimensional scene based on the high-resolution remote sensing image is constructed, the railway line can be selected more intuitively, the initial guide line of the line is established by adopting the basic HAO model, the RPSO particle swarm optimization algorithm is used for optimizing the plane and longitudinal plane of the line, and the calculation efficiency and the reliability of the final result can be remarkably improved.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (2)
1. A high-resolution remote sensing three-dimensional visual railway route selection aided decision method comprises the steps of firstly, building a plane design route; step two, generating an initial guide line; step three, intelligently optimizing a guide line; step four, editing nodes in detail; designing transverse and longitudinal end faces; step six, evaluating a design scheme; step seven, comprehensive evaluation of cost; the method is characterized in that:
in the first step, a new project is built by using a newly-built project module (105) in a project management module (1), then a high-resolution remote sensing three-dimensional image of a line selection position is obtained by using a high-resolution image extraction module (2), then a remote sensing three-dimensional image of the position needing line selection is called by using a three-dimensional visualization module (101), and then a line newly-built module (304) in a plane design module (3) is used for setting related parameters of a design line name, a design line number, a starting point stake number, a design speed per hour and a line width;
in the second step, after the line parameter setting in the first step is finished, a manual line selection module (301) is used for manually selecting a line, a function button is clicked by a mouse, coordinates are picked up in a three-dimensional image, unit prices of earthwork, bridge and tunnel are set, then the particle number and the total cycle number are set, a determination button is clicked immediately, and an initial guide line is automatically generated by an immediately line editing module (305) according to a line generation method;
in the third step, after the initial guide line in the second step is generated, the line is optimized by using an intelligent optimization module (308) and adopting a particle swarm optimization, namely, the three-dimensional linear optimization problem is solved into a process of finding the optimal line plane and vertical plane parameter set in a research area, and the PSO is as follows:
V id ＝ωV id +C 1 random(0,1)(P id -X id )+C 2 random(0,1)(P gd -X id )
where ω is an inertia factor whose value is not negative, global optimization performance and local optimization performance are adjusted by adjusting the value, C 1 And C 2 For the acceleration constant, the former is an individual learning factor of each particle, and the latter is a social learning factor of each particle, and C is set 1 ＝C 2 =2,random (0, 1) means the interval [0,1]Random number of (2), P id D-dimension, P, of individual extrema representing the ith variable gd Dimension d representing a global optimal solution, first passImproving the over-parameters: inertial weight, shrinkage factor, tracking dynamics: secondly, a mixing algorithm: improving the search behavior pattern from particle to particle: and finally, improving the particle swarm optimization in a mode of introducing an individual current optimal point in searching by using a network topology concept to obtain the particle swarm optimization, and then performing optimization calculation on the line by using the particle swarm optimization, wherein the method comprises the steps of basic searching, static searching and axis searching of particles, and the implementation process comprises the following steps:
1) Initializing parameters of particle dimension, particle scale, search range, speed and maximum iteration number;
2) Calculating an adaptive value of each particle;
3) Comparing the adaptive value of each particle with the adaptive value of the best position pbest experienced by the particle, if the adaptive value is better, taking the adaptive value as the best position, and updating pbest;
4) Comparing the adaptive value of each particle with the adaptive value of the best global position gbest, if the adaptive value is better, taking the adaptive value as the current best global position, and updating the gbest;
5) Updating the speed and position of each particle;
6) If the end condition is met, outputting the gbest, otherwise, returning to 2);
the method for realizing automatic avoidance of the line ground object by adopting a linear intersection discrimination method comprises the following steps: is known as (x) 1 ,y 1 ),(x 2 ,y 2 ) Determining a straight line Ax + By + C =0, wherein the intersection point coordinates (x, y) of the straight line are obtained By calculating three coefficients A, B and C, and the coordinates (y-y) are determined By judging 1 )/(y-y 2 ) The sign determines whether the detection intersection point is on the line segment, if the value is negative, the point is on the line segment, and on the line segment, the avoidance is needed, and the specific implementation method is as follows: if the node on the ith tangent line is judged to be intersected with the line segment of the found point of the (i-1) th tangent line and any one edge of the ground object vector polygon, continuously searching a line node P which meets the gradient requirement and avoids the ground object on the ith tangent line i Forming an optimized line after automatically avoiding the obstacle;
in the fourth step, after the line in the third step is optimized, the detailed information of each node of the generated line is checked through the three-dimensional roaming function in the three-dimensional roaming module (102) of Skyline, and the coordinates, the parameters, the corner information and the modification of the connection line type at the node are checked by using the node editing module (303);
in the fifth step, after the detailed node modification in the fourth step is finished, the transverse and longitudinal section design module (4) generates transverse and longitudinal section information of the line, prefabricating standard transverse sections of the railway road, the bridge and the tunnel, and automatically finishing the extraction and calculation of the transverse and longitudinal section ground lines;
in the sixth step, after the transverse end face and the longitudinal end face in the fifth step are set, an earth and stone volume calculating module (501) in a design and evaluation module (5) calculates, displays and outputs earth and stone volume of the selected route scheme, the route scheme is designed and evaluated based on multiple economic and environmental targets, and a calculation model is as follows:
wherein, K j For the construction unit price of the jth class of plots, (j =1,2,3,. Eta., m), a j Area of class j plots covered for road, cost C associated with location N The calculation idea of the cost related to the length is as follows: in the line selection stage, the line is supposed to be only composed of a straight line unit and a circular curve unit, and R is set i Is the radius of the circular curve at the i-th intersection point, C i (xc i ,yc i ) And T i (xt i ,yt i ) Respectively ZY point and YZ point, delta at the ith intersection i Is the curve corner at the ith intersection point, the total line length L N Comprises the following steps:
in the formula: n is the total number of the circular curves, and the cost related to the road comprises engineering cost, environment-related cost and roadbed earth and stone square cost, wherein the roadbed earth and stone square cost is calculated by adopting the following formula:
the roadbed cross section area algorithm formula is as follows:
A＝B·ΔH+m·ΔH 2
in the formula: b is the road pavement width; delta H is the filling and digging height of the roadbed, and the value of the filling and digging height is the absolute value of the height difference between the ground elevation and the grid elevation; 1 m-slope ratio; n is the number of calculated sections of the roadbed earth and stone; d i -the subgrade of section i is calculated for length; c. C i -the cost of the roadbed excavation at section i; a. The il -the cross sectional area of the roadbed at the left side of the i-th section; a. The ir -the cross sectional area of the roadbed at the right side of the roadbed at the i-th section;
the cost calculation was performed using the following cost model:
C＝C N +C Q +C L +C qs
thereby obtaining the cost required by the line construction;
in the seventh step, after the cost is calculated according to the cost model in the sixth step, the comprehensive evaluation module (503) evaluates the cost in terms of the total cost, the structure cost, the project cost and the floor space cost, and outputs the evaluation result after the output position is selected.
2. The high-resolution remote sensing three-dimensional visual railway route selection aided decision method according to claim 1, characterized in that: in the second step, the line generation method comprises: generating an initial guide line by referring to the HAO model, and inputting coordinates S (x) of start and end points of the line s ,y s )、E(x E ,y E ) Considering relevant constraints, slope constraints, continuous turning limitation and elevation constraints of control points in the design process, assuming that the starting point and the end point are S and E respectively, connecting the starting point and the end point SE, equally dividing the SE by m tangent lines, and intersecting the tangent lines and the lines at m different points P i The m points are line intersections, and line nodes are optimized on the m tangent linesThe way generation method defines two sets of coordinate systems: the global coordinate system takes north as an x axis and east as a y axis; secondly, the image local coordinate system takes the upper left corner of the image as the origin of coordinates, and the image boundaries are x and y axes respectively, and the method comprises the following concrete implementation steps:
on each tangent line, note O i Is the origin of the ith tangent line with the coordinate (x) oi ,y oi ) Comprises the following steps:
each point of intersection P i D of i In different one-dimensional local coordinate systems, in order to obtain an intersection point sequence of the line model, converting the intersection point sequence into a global coordinate system, adding a black tangent line and an x axis to form an included angle theta, and then P i The global coordinates of (a) are:
finally, a chain type broken line is formed by connecting all the intersection points, and an initial guide line designed by line selection is obtained.
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