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CN107368921A - Track traffic scheme comparison method based on 3DGIS+BIM technologies - Google Patents

Track traffic scheme comparison method based on 3DGIS+BIM technologies Download PDF

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Publication number
CN107368921A
CN107368921A CN201710574123.XA CN201710574123A CN107368921A CN 107368921 A CN107368921 A CN 107368921A CN 201710574123 A CN201710574123 A CN 201710574123A CN 107368921 A CN107368921 A CN 107368921A
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罗紫萍
李秉展
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Chengdu Zong Sheng Intelligent Technology Co Ltd
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    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract

The invention discloses a kind of track traffic scheme comparison method based on 3DGIS+BIM technologies, groundwork includes carrying out the visual design and structure Multiple Attribute Decision Model using 3DGIS+BIM technologies, finally chooses optimal case.By BIM technology and 3DGIS technological incorporation, BIM technology has the characteristics of fine display, abundant information, compensate for GIS details deficiency defects, beneficial complement is provided for the more deep application of GIS technology;Necessary information data is extracted from 3DGIS+BIM models, as Multiple Attribute Decision Model important parameter;Multiple Attribute Decision Model is built, the decision model is based on objective weight Design Rule, weight is determined by certain mathematical method, smaller compared to the flexible strategy deviation that subjective weights method obtains, and can more reflect the actual significance level of numerous evaluation indexes.

Description

Rail transit scheme comparison and selection method based on 3DGIS + BIM technology
Technical Field
The invention belongs to the field of rail transit design, and particularly relates to a rail transit scheme comparing and selecting method based on a 3DGIS + BIM technology.
Background
The scheme selection and scheme design of urban rail transit engineering are comprehensive work, have the characteristics of wide involvement, strong complexity, great responsibility and the like, and are generally influenced by multiple factors such as urban planning, terrain and landform, engineering geology and hydrogeology conditions, ground and underground buildings, ground traffic conditions and the like. The traditional two-dimensional plane-based scheme selection and design method is generally difficult to integrate important information of urban three-dimensional buildings, geology, roads, pipe networks and the like, so that the cases of scheme selection errors and design deviation frequently occur. For example, a newly built project conflicts with an existing underground pipe network of a city, building traffic facilities and the like, and further design change occurs, so that a large amount of removal, transformation and transfer work can be caused, and great influence is generated on the engineering construction and the environment of the area along the line.
In recent years, with the rapid development of urban rail transit, scheme selection and design are gradually changed from a two-dimensional plane to a three-dimensional entity. Particularly, the Geographic Information System (GIS) technology provides good technical support for rail transit design and scheme selection. The GIS system is based on a spatial database, has good advantages in the aspect of displaying large scenes, but has great defects in detail display, and is difficult to provide powerful guidance for line selection.
In the current commonly used scheme comparison and selection work, a design scheme decision maker needs to comprehensively consider the influence of a plurality of factors, define the weights of different influence factors to establish a decision model, evaluate each alternative scheme, and find out the optimal scheme through the quality sequence of each alternative scheme. Currently, commonly used decision selection methods, such as Analytic Hierarchy Process (AHP), fuzzy AHP (fuzzy AHP), Delphi, network Analysis (ANP), etc., are all weighted according to the degree of importance of experts on each attribute, and all belong to subjective weighting methods. The subjectively weighted weights inevitably vary from person to person, and the overall evaluation results obtained for different weights may be different.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems, the invention provides a rail transit scheme comparing and selecting method based on a 3DGIS + BIM technology.
The technical scheme is as follows: in order to realize the purpose of the invention, the technical scheme adopted by the invention is as follows: a rail transit scheme comparing and selecting method based on a 3DGIS + BIM technology specifically comprises the following steps:
(1) establishing a three-dimensional ground environment model based on a geographic information system technology;
(2) establishing a three-dimensional underground environment model based on a geographic information system technology;
(3) building a rail transit model based on a building information model technology;
(4) integrating a three-dimensional overground environment model, a three-dimensional underground environment model and a rail transit model;
(5) providing a plurality of comparison schemes;
(6) constructing a multi-attribute decision model and evaluating;
(7) and determining an optimal recommendation scheme.
The step 1 specifically comprises the following steps:
(1.1) acquiring terrain data based on a geographic information system technology, and drawing a three-dimensional terrain model;
(1.2) acquiring urban landscape data based on a geographic information system technology, and drawing a three-dimensional urban model;
(1.3) adopting UAV oblique photography technology to assist modeling;
and (1.4) integrating and establishing a three-dimensional ground environment model.
The step 2 specifically comprises the following steps:
(2.1) acquiring data information such as geological drilling and the like based on a geographic information system technology, and drawing a three-dimensional groundwater model;
(2.2) acquiring data information such as geological drilling and the like based on a geographic information system technology, and drawing a three-dimensional geological model;
(2.3) acquiring pipeline data based on a geographic information system technology, and drawing a three-dimensional underground pipeline model;
and (2.4) integrating and establishing a three-dimensional underground environment model.
The step 6 specifically comprises the following steps:
(6.1) establishing a decision matrix;
(6.2) defining uncertain information;
(6.3) preprocessing data;
(6.4) weight setting;
(6.5) correlation analysis;
(6.6) prioritization.
Has the advantages that: the invention integrates the BIM technology and the 3DGIS technology, the BIM technology has the characteristics of fine display and rich information, the defect of insufficient GIS details is overcome, and beneficial supplement is provided for deeper application of the GIS technology; a multi-attribute decision model is constructed, the weight of the decision model is determined by a certain mathematical method based on an objective weight design rule, and the weight deviation is smaller compared with the weight deviation obtained by a subjective weighting method, so that the actual importance degree of a plurality of evaluation indexes can be reflected better.
Drawings
FIG. 1 is a flow chart of a rail transit scheme comparison method based on 3DGIS + BIM technology according to the present invention;
FIG. 2 is a flow chart of an urban rail transit visualization design;
FIG. 3 is a detailed flow diagram of the construction of a multi-attribute decision model;
FIG. 4 is a schematic diagram of a generalized gray correlation preprocessing technique model.
Detailed Description
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
As shown in fig. 1, the rail transit scheme selection method based on 3DGIS + BIM technology of the present invention mainly includes performing visual design and constructing a multi-attribute decision model by using 3DGIS + BIM technology, and finally selecting an optimal scheme. The method specifically comprises the following steps:
(1) establishing a three-dimensional ground environment model based on a 3D Geographic Information System (GIS) technology;
(2) establishing a three-dimensional underground environment model based on a 3D Geographic Information System (GIS) technology;
(3) building a rail transit model based on Building Information Model (BIM) technology;
(4) the 3D GIS and the BIM model are integrated, the BIM technology has the characteristics of fine display and rich information, the defect of insufficient GIS details is overcome, and beneficial supplement is provided for more deep application of the GIS technology;
(5) on the basis of integrating the 3DGIS and the BIM model, a plurality of selection schemes are provided;
(6) the method comprises the steps of constructing a multi-attribute decision model and evaluating, wherein the decision model is based on an objective weight design rule, the weight is determined by a certain mathematical method, and compared with a subjective weighting method, the weight deviation is smaller, and the actual importance degree of numerous evaluation indexes can be reflected better;
(6) and determining an optimal recommendation scheme.
The specific flow of steps 1-4 is shown in fig. 2, and the specific implementation method of step 1 is as follows:
(1.1) integrating terrain data based on a GIS technology to draw a three-dimensional terrain model;
(1.2) drawing a three-dimensional city model through city landscape data based on a GIS technology;
(1.3) adopting an UAV oblique photography technology to assist in modeling, and improving the model reality degree;
and (1.4) integrating and establishing a three-dimensional ground environment model.
The specific implementation method of the step 2 is as follows:
(2.1) integrating data such as geology, drilling and the like based on a GIS technology to draw a three-dimensional groundwater model;
(2.2) integrating data such as geology, drilling and the like based on a GIS technology to draw a three-dimensional geological model;
(2.3) integrating pipeline data based on a GIS technology to draw a three-dimensional underground pipeline model;
and (2.4) integrating and establishing a three-dimensional underground environment model.
The specific flow of step 6 is shown in fig. 3, and the specific implementation method is as follows:
(6.1) establishing a decision matrix;
the multi-attribute decision matrix is defined by "attribute" and "scheme", and the decision model of the present invention uses uncertain information, so that the evaluation values in the decision matrix are presented in gray scale, i.e. the evaluation values in the decision matrix are presented in gray scaleThe whole decision matrix is presented as formula (1):
as shown in equation 1, the decision matrix is a matrix composed of n schemes and m attributes, wherein,indicating the gray scale evaluation value of the ith scheme on the jth attribute.
(6.2) defining uncertain information;
the example uses six attribute indexes: the operation effect and economic benefit, the construction cost, the line technical route, the feasibility, the passenger flow attraction effect and the conformity of the upper planning.
The influence evaluation values of the six attribute indexes are often difficult to specify, but an interval, namely, a gray number, is given to the evaluation values according to the obtained information and cognition. The invention adopts the grey number concept to define the uncertain information, adopts the form of non-fixed value, but numerical value interval to carry out grading, and is more in line with the objectivity of human perception.
(6.3) preprocessing data;
in the aspect of data preprocessing, a generalized gray correlation preprocessing technology model of gray number is adopted, as shown in fig. 4. The data preprocessing was examined with reference to FIG. 4, so that the gray scale evaluation value was generated
(1) When in useWhen the temperature of the water is higher than the set temperature,
due to the fact thatTo the left of the generating function, there is no sequential aliasing problem, and the formula in this case is:
wherein,is an evaluated value of the gray number after generation.
(2) When in useWhen the temperature of the water is higher than the set temperature,
due to the fact thatIs covered toOn the left, the assumption that the expected value is 1 must therefore be considered, the formula in this case being:
(3) when in useWhen the temperature of the water is higher than the set temperature,
at this time, the process of the present invention,covering the wholeConsidering the assumption that the expected value generation is 1, the generation formula in this case is:
(4) when in useWhen the temperature of the water is higher than the set temperature,
at this time, the process of the present invention,is covered toIn addition to the assumption that the desired value is generated as 1, the problem of sequence confusion is also considered, and the generation formula in this case is:
(5) When in useWhen the temperature of the water is higher than the set temperature,
at this time, the process of the present invention,the problem of order confusion exists at the right side of the generating function, so the generating formula in this case can be summarized as follows:
(6.4) weight setting;
the objective weight setting determines the weight according to the information provided by the decision matrix, mainly measures the dispersion degree between data in the attribute, and when the dispersion in the attribute is larger, the attribute has higher discrimination, and higher weight can be given. According to the concept, the accurate number weight setting model based on the maximum dispersion is firstly deduced.
Some decision matrix is X ═ Xi(j)]n×mAfter normalization, a normalized matrix R is obtained, assuming that the weight vector is:
w=[w(1),w(2),...,w(m)],w(j)≥0,
in terms of attribute u (j), intra-attribute scheme riThe dispersion from other schemes can be defined as:
wherein r isiIs xiThe generated sequence of (1). Then, let:
Δ (j) represents the weighted total dispersion of all solutions within the attribute u (j). According to the concept of dispersion maximization, the weighting vector w is assigned such that the weighted total dispersion of all attributes is maximized. For this purpose, its objective function can be set as:
then, solving w of the following optimization model, the weight vector with maximum dispersion can be obtained:
if the optimization problem is solved by Lagrange's function, then:
the gradient is calculated, and the following steps are carried out:
the best solution can be obtained as follows:
in addition, since the decision model generally adopts a unitization weight, w (j) is further unitized, that is:
this gives:
the weight setting method of formula 16 for processing precise numbers must be further defined when expanding to gray spacei(k) The calculation method of (1). According to the gray-number Minkowski distance function, the gray-number Minkowski distance function can be obtainedi(k) Is defined as:
at this time, the gray number distance is substituted back to the formula 16, and an objective weight setting value can be obtained.
(6.5) correlation analysis;
and after the attribute weight is obtained, calculating the correlation analysis among the gray number sequences. And (3) correlation analysis, namely analyzing the correlation between the reference sequence and the grey decision matrix, wherein the judgment of the similarity degree is based on a distance function.
Let the reference sequence be defined as:
the grey-weighted Mincosky distance between the reference sequence and the decision matrix is used as the basis of the correlation analysis, namely:
wherein,means thatTo be provided withW (j) is a weight of the j-th attribute obtained by the gray weight setting technique, and p is a Minkowski distance parameter, and is the most common Euclidean distance when p is 2.
On the basis, the association analysis can prioritize the schemes according to the size through a calculation formula of gray association degree.
Wherein dmin and dmax are doiMinimum and maximum values of (d).
Through a decision matrix, a preprocessing technology, a weight and an association analysis technology, the alternative schemes of the urban rail transit line station can be prioritized. The attribute indices, definitions, and data sources are shown in table 1.
TABLE 1
(6.6) prioritization.
In the step 6, through scoring the six indexes, the discrimination of each index can be directly calculated and weighted according to the scores in the decision matrix, on one hand, the process of alternative scheme selection is simplified, and meanwhile, the influence of subjective weight on the result is reduced. The score can be an interval rather than a constant value, and is more in line with the objectivity of human perception.

Claims (8)

1. A rail transit scheme comparing and selecting method based on 3DGIS + BIM technology is characterized in that: the method specifically comprises the following steps:
(1) establishing a three-dimensional ground environment model based on a geographic information system technology;
(2) establishing a three-dimensional underground environment model based on a geographic information system technology;
(3) building a rail transit model based on a building information model technology;
(4) integrating a three-dimensional overground environment model, a three-dimensional underground environment model and a rail transit model;
(5) providing a plurality of comparison schemes;
(6) constructing a multi-attribute decision model and evaluating;
(7) a recommendation is determined.
2. The rail transit scheme comparing and selecting method based on 3DGIS + BIM technology as claimed in claim 1, wherein: the step 1 specifically comprises:
(1.1) integrating terrain data based on a geographic information system technology, and drawing a three-dimensional terrain model;
(1.2) integrating urban landscape data based on a geographic information system technology, and drawing a three-dimensional urban model;
(1.3) adopting UAV oblique photography technology to assist modeling;
and (1.4) integrating and establishing a three-dimensional ground environment model.
3. The rail transit scheme comparing and selecting method based on 3DGIS + BIM technology as claimed in claim 1, wherein: the step 2 specifically comprises:
(2.1) integrating data information such as geological drilling and the like based on a geographic information system technology, and drawing a three-dimensional groundwater model;
(2.2) integrating data information such as geological drilling and the like based on a geographic information system technology, and drawing a three-dimensional geological model;
(2.3) integrating pipeline data based on the geographic information system technology, and drawing a three-dimensional underground pipeline model;
and (2.4) integrating and establishing a three-dimensional underground environment model.
4. The rail transit scheme comparing and selecting method based on 3DGIS + BIM technology as claimed in claim 1, wherein: the step 6 specifically includes:
(6.1) establishing a decision matrix;
(6.2) defining uncertain information;
(6.3) preprocessing data;
(6.4) weight setting;
(6.5) correlation analysis;
(6.6) prioritization.
5. The rail transit scheme comparing method based on 3DGIS + BIM technology as claimed in claim 4, wherein: the attribute indexes can cover the operation effect, economic benefit, engineering cost, line technical route, feasibility, passenger flow attraction effect, conformity with upper planning and the like; part of attribute index data is derived from a 3D GIS + BIM model.
6. The rail transit scheme comparing method based on 3DGIS + BIM technology as claimed in claim 4, wherein: and giving an evaluation interval of the attribute indexes aiming at the uncertain information.
7. The rail transit scheme comparing method based on 3DGIS + BIM technology as claimed in claim 4, wherein: the data preprocessing adopts a generalized grey correlation preprocessing technology model.
8. The rail transit scheme comparing and selecting method based on 3DGIS + BIM technology as claimed in claim 1, wherein: the weight is determined by a certain mathematical method based on an objective weight design rule by constructing a multi-attribute decision model.
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CN109711600A (en) * 2018-11-27 2019-05-03 中国公路工程咨询集团有限公司 Route selection evaluation system and method based on oblique photograph threedimensional model
CN110110376A (en) * 2019-04-09 2019-08-09 天津大学 A kind of hinge dam type scheme analysis method for quantitatively evaluating and device based on BIM
CN111047157A (en) * 2019-11-26 2020-04-21 深圳大学 Construction scheme comparing and selecting method in building engineering
CN113887010A (en) * 2021-08-30 2022-01-04 长江勘测规划设计研究有限责任公司 Water conservancy and hydropower station traffic planning and organization method based on live-action modeling and BIM
CN114492093A (en) * 2022-04-18 2022-05-13 济南轨道交通集团有限公司 City visualization method and system
CN118095595A (en) * 2024-02-29 2024-05-28 同济大学 Underground road reinforcement learning intelligent route selection method based on multi-source data

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CN109711600A (en) * 2018-11-27 2019-05-03 中国公路工程咨询集团有限公司 Route selection evaluation system and method based on oblique photograph threedimensional model
CN110110376A (en) * 2019-04-09 2019-08-09 天津大学 A kind of hinge dam type scheme analysis method for quantitatively evaluating and device based on BIM
CN111047157A (en) * 2019-11-26 2020-04-21 深圳大学 Construction scheme comparing and selecting method in building engineering
CN113887010A (en) * 2021-08-30 2022-01-04 长江勘测规划设计研究有限责任公司 Water conservancy and hydropower station traffic planning and organization method based on live-action modeling and BIM
CN113887010B (en) * 2021-08-30 2024-07-23 长江勘测规划设计研究有限责任公司 Traffic planning organization method in water conservancy water electric field based on live-action modeling and BIM
CN114492093A (en) * 2022-04-18 2022-05-13 济南轨道交通集团有限公司 City visualization method and system
CN118095595A (en) * 2024-02-29 2024-05-28 同济大学 Underground road reinforcement learning intelligent route selection method based on multi-source data

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