CN106373069A - Intelligent traffic system project construction sequence determination method - Google Patents

Abstract

The invention provides an intelligent traffic system project construction sequence determination method, which comprises the following steps: constructing an evaluation index system, wherein the evaluation index system comprises a target layer, an index layer and a scheme layer; determining relative weight of the evaluation index system by utilizing an analytic hierarchy process; and according to the relative weight, determining ITS project construction sequence through a technique for order preference similarity to ideal solution(TOPSIS) method. The intelligent traffic system project construction sequence determination method determines the relative weight for each ITS construction project evaluation index and sub-index thereof through the analytic hierarchy process and determines the ITS project construction sequence through the TOPSIS method, so that the method can effectively solve the problem of large influence of subjective factors when the construction sequence is determined through a conventional experiential decision making method, can improve utilization rate of human resources, material resources and financial resources and can improve benefit in the ITS construction and operation process, and has a great guiding function and meaning for ITS construction and implementation.

Description

Intelligent transportation system project construction sequential determines method

Technical field

The present invention relates to intelligent transportation field, more particularly, to a kind of intelligent transportation system project construction sequential determines method.

Background technology

With the development of social economy, the traffic problems such as the urban highway traffic of China is crowded, vehicle accident, environmental pollution Increasingly severe.Intelligent transportation system (intelligent traffic system, abbreviation its) is by advanced science and technology (information technology, computer technology, data communication technology, sensor technology, electron controls technology, Theory of Automatic Control, plan strategies for , artificial intelligence etc.) effectively integrated use in transportation, Service controll and vehicle manufacture, strengthen vehicle, road, use Contact between person three, thus form a kind of multi-transportation system ensure safety, improve efficiency, improving environment, energy saving System, as alleviating traffic congestion, reducing vehicle accident, reduce one of effective measures of environmental pollution, cities in China puts into A large amount of manpower and materials planning construction its.

At present, domestic its project construction sequential determines that method mainly has the expense effect using the quantitative analyses its project implementation The item than method with using the aspect such as analytic hierarchy process (AHP) comprehensive method of investment construction cost, benefit, technology maturity, policy goodness of fit for the benefit Mesh builds time sequence determination method.But, above-mentioned cost effectiveness ratio method does not meet the not enough national conditions of domestic basic data, and domestic Scholar determines its project construction sequential using analytic hierarchy process (AHP) in terms of cost, benefit, technology maturity, policy goodness of fit etc. Then exist subjective factorss impact larger the problems such as, therefore, need a kind of new technological means badly, to overcome above-mentioned technical problem.

Content of the invention

In view of this, the present invention provides a kind of intelligent transportation system project construction sequential to determine method, to solve above-mentioned skill Art problem.

The intelligent transportation system project construction sequential that the present invention provides determines method, comprising:

A. build assessment indicator system, described assessment indicator system includes

Destination layer, for determining the construction of its (intelligent traffic system, intelligent transportation system) project Sequential；

Indicator layer, comprises performance indications, safety benefit index, economic results in society index, environmental benefit index, risk refer to Mark and the indicator of costs；

Solution layer, including several its construction projects；

B. the relative weighting of assessment indicator system is determined using analytic hierarchy process (AHP),

C. the construction sequential of its project according to described relative weighting, is determined using the sort method approaching optimal solution.

Further, each index in described indicator layer is respectively provided with corresponding sub- index, and all sub- indexs form son and refer to Mark layer, wherein:

Performance indications include security reliability, practical advanced, open autgmentability and accurate and effective temper index；

Safety benefit index includes direct safety benefit and the sub- index of indirect safety benefit；

Economic results in society index includes reducing Transportation costs benefit, reduces travel time benefit, slows down soil money Source utilization benefit, promote industry development index, quality of making the life better and the sub- index of other indirect economic results in society；

Environmental benefit index includes reducing pollution emission benefit and reduces the traffic noise pollution sub- index of benefit；

Risk indicator includes the sub- index of integrated risk evaluation grade；

The indicator of costs includes investment construction fund cost and the sub- index of investment construction time cost.

Further, described step b specifically includes:

B1. set up hierarchy Model, destination layer, indicator layer and sub- indicator layer are represented by described hierarchy Model Interconnect relation,

B2. development of judgment matrix, and the relative importance between each similar evaluation index is determined according to described judgment matrix.

Further, step b2 also includes carrying out standardization processing to judgment matrix, and the judgment matrix after process is:

$\stackrel{\&overbar;}{b_{ij}}=\frac{a_{ij}}{\underset{k=1}{\overset{n}{\σ}}{a}_{kj}}$

Wherein, a_ijRepresent similar index ai and the relative importance of aj, 0 < a_ij≤ 9, a_ij=1/a_ji, a_ii=1.

Further, when judgment matrix crash consistency is in tolerance interval, obtain same level each element for upper one The relative weighting vector of certain element in level, that is, include that indicator layer is vectorial to the relative weighting of destination layer, sub- indicator layer pair The relative weighting of each corresponding index of indicator layer is vectorial and sub- indicator layer in every sub- index relative target layer relative weighting.

Further, step c also includes building decision matrix, determines ideal solution and minus ideal result according to described decision matrix, Obtain the relative similarity degree of each project alternative and ideal solution, and the relative similarity degree of project alternative and ideal solution is carried out descending Sequence, the construction sequential of scheme of identifying project.

Further, step c also includes decision matrix is carried out standardization processing, and to the decision matrix weighting after processing, Obtain weighted normal decision matrix, ideal solution and minus ideal result are determined according to described weighted normal decision matrix.

Beneficial effects of the present invention: the intelligent transportation system project construction sequential in the present invention determines method, by level Analytic process demarcates relative weighting to each its appraisal of construction projects index and its sub- index, using the sort method approaching optimal solution Determine the construction sequential of its construction project, the subjective factorss building sequential presence can be determined by the traditional empirical decision making of effectively solving Affect larger problem, the utilization rate of human and material resources, fund resources can be improved, and during its construction operation can be improved Benefit, constructs and implements for its and has great directive function and meaning.

Brief description

The invention will be further described with reference to the accompanying drawings and examples:

Fig. 1 is the principle schematic of the present invention.

Specific embodiment

The invention will be further described with reference to the accompanying drawings and examples: Fig. 1 is the principle schematic of the present invention.

As shown in figure 1, the intelligent transportation system project construction sequential in the present embodiment determines method, including

A. build assessment indicator system, described assessment indicator system includes

Destination layer, for determining the construction sequential of its project；

Indicator layer, comprises performance indications, safety benefit index, economic results in society index, environmental benefit index, risk refer to Mark and the indicator of costs；

Solution layer, including several its construction projects；

B. the relative weighting of assessment indicator system is determined using analytic hierarchy process (AHP),

C. the construction sequential of its project according to described relative weighting, is determined using the sort method approaching optimal solution.

In the present embodiment, its appraisal of construction projects index system is by destination layer, indicator layer, sub- indicator layer and solution layer Constitute.Wherein destination layer determines the construction sequential of its project；Indicator layer mainly comprises performance indications, safety benefit index, society Meeting economic benefits indicator, environmental benefit index, risk indicator and the indicator of costs；Sub- indicator layer is the performance indications in indicator layer Security reliability, practical advanced, open autgmentability, 4 sub- indexs of accurate and effective, the directly safety of safety benefit index is imitated Beneficial and indirect 2 sub- indexs of safety benefit, the reduction Transportation costs benefit of economic results in society index, minimizing travel time Benefit, the land resources utilization benefit that slows down, promotion industry development index, quality of making the life better and other indirect economic results in society 6 sub- indexs, the minimizing pollution emission benefit of environmental benefit index and the reduction traffic noise pollution each sub- index of benefit 2, The sub- index of integrated risk evaluation grade of risk indicator, and the investment construction fund cost of the indicator of costs and investment construction time 2 sub- indexs of cost；Solution layer is that several its construction projects are constituted.

In the present embodiment, step b specifically includes

B1. set up hierarchy Model, destination layer, indicator layer and sub- indicator layer are represented by described hierarchy Model Interconnect relation,

B2. development of judgment matrix, and the relative importance between each similar evaluation index is determined according to described judgment matrix.

Hierarchy Model in the present embodiment can represent the relation that interconnects between packet factor, generally according to classification because Element is divided into destination layer, indicator layer and sub- indicator layer, as shown in Figure 1.Judgment matrix as shown in table 1, reacts same by matrix Relative importance between class evaluation index, and it can be deployed in scaling law is determining the importance between similar index

Table 1

Wherein, a_ijRepresent similar index ai and the relative importance of aj；0<a_ij≤ 9, a_ij=1/a_ji, a_ii=1；Importance Scale value can by table 2 value,

Scale value aij	Implication
		1	I factor is of equal importance with j factor
3	I factor is slightly more important than j factor
		5	I factor is substantially more important than j factor
7	I factor is more extremely important than j factor
		9	I factor is more absolutely essential than j factor
2,4,6,8	The corresponding scale value of intermediateness between judging for above two

Table 2

Judgment matrix has the eigenvalue of maximum λ max of unique non-zero, and λ max=n, then this matrix have completely the same Property.But during due to there is larger error when factor each to complexity is compared two-by-two, necessarily lead to eigenvalue and feature Deviation in vector, and judgment matrix does not then enable crash consistency.

First, will determine that matrix standardizes by row

$\stackrel{\&overbar;}{b_{ij}}=\frac{a_{ij}}{\underset{k=1}{\overset{n}{\&sigma;}}{a}_{kj}}---\left(1\right)$

Then calculate transition value parameter

$\stackrel{\&overbar;}{w_i}=\underset{j=1}{\overset{n}{\&sigma;}}\stackrel{\&overbar;}{b_{ij}},(i=1,2,...,n)---\left(2\right)$

WillStandardization, obtains i-th component wi of characteristic vector w:

$w_i=\frac{\stackrel{\&overbar;}{w_i}}{\underset{i=1}{\overset{n}{\&sigma;}}\stackrel{\&overbar;}{w_i}},(i=1,2,...,n)---\left(3\right)$

Calculating eigenvalue of maximum λ max:

${\mathrm{\&lambda;}}_{\max }=\underset{i=1}{\overset{n}{\&sigma;}}\frac{\underset{j=1}{\overset{n}{\&sigma;}}{a}_{ij}{w}_j}{{\mathrm{nw}}_i}---\left(4\right)$

When judgment matrix is completely inconsistent, usual eigenvalue of maximum λ max can be more than n, calculates test and judge matrix first Coincident indicator ci:

$ci=\frac{{\mathrm{\&lambda;}}_{\max }-n}{n-1}---\left(5\right)$

As λ max=n, during ci=0, judgment matrix is completely the same；When ci value is bigger, then illustrate complete the one of judgment matrix Cause property is poorer；It has been generally acknowledged that during ci≤0.1, judgment matrix crash consistency is in tolerance interval；Otherwise again compared Judge.

When judgment matrix dimension n is bigger, the crash consistency of judgment matrix will be poorer, therefore introduce correction value ri, and take cr As the index weighing judgment matrix more reasonably crash consistency.

$cr=\frac{ci}{ri}---\left(6\right)$

In formula: ri can be by table 3 value.

Dimension	1	2	3	4	5	6	7	8	9
										ri	0.00	0.00	0.58	0.90	1.12	1.24	1.32	1.41	1.45

Table 3

When judgment matrix crash consistency is in tolerance interval, can get same level each element in last layer time Certain element relative weighting vector.

Indicator layer is w to the relative weighting vector of destination layer⁰:

$w^0={(w_1^0,w_2^0,...,w_n^0)}^t---\left(7\right)$

Sub- indicator layer is respectively to the relative weighting vector of the index 1 of indicator layer to index n

$w_1^1={(w_{11}^1,w_{12}^1,...,w_{1i}^1)}^t---\left(8\right)$

$w_2^1={(w_{21}^1,w_{22}^1,...,w_{2j}^1)}^t---\left(9\right)$

……

$w_n^1={(w_{n1}^1,w_{n2}^1,...,w_{nk}^1)}^t---\left(10\right)$

In the present embodiment in addition it is also necessary to determine combination level relative weighting, combination level relative weighting is in sub- indicator layer The relative weighting of every sub- index relative target layer, needs the relative weighting to destination layer by combined index layer, sub- indicator layer The relative weighting of indicator layer is obtained.

The relative weighting w to destination layer for the sub- indicator layer².

$\begin{array}{c}{w}^2=(w_1^0{w}_{11}^1,w_1^0{w}_{12}^1,...,w_1^0{w}_{1i}^1,w_2^0{w}_{21}^1,w_2^0{w}_{22}^1,\\ ...,w_2^0{w}_{2j}^1,...,w_n^0{w}_{n1}^1,w_n^0{w}_{n2}^1,...,w_n^0{w}_{nk}^1{)}^t\end{array}---\left(11\right)$

In the present embodiment, step c also includes building decision matrix, determines ideal solution and negative reason according to described decision matrix Want to solve, obtain the relative similarity degree of each project alternative and ideal solution, and the relative similarity degree of project alternative and ideal solution is entered Row descending sort, the construction sequential of scheme of identifying project, decision matrix is carried out with standardization processing, and to the decision-making square after processing Battle array weighting, obtains weighted normal decision matrix, determines ideal solution and minus ideal result according to described weighted normal decision matrix.This reality Apply example by decision matrix vector standardization, to obtain programming decision-making matrix, decision matrix x is expressed as:

Wherein, x_ijFor the property value of j-th evaluation index of i-th project in decision matrix x, can in conjunction with statistical yearbook, Government notice, the development related data such as annual report and the Internet, are obtained using Experts consultation method or calculating.Then made by formula (12) Decision matrix standardizes:

$y_{ij}=\frac{x_{ij}}{\sqrt{\underset{i=1}{\overset{m}{\&sigma;}}{\left(x_{ij}\right)}^2}}---\left(12\right)$

Obtain specified decision matrix y:

Again to specified decision matrix weights, obtain weighted normal decision matrix, by formula (14) to Standard Process plus Power:

z_ij=ω_j×y_ij(14)

Wherein, ω_jFor the weighted value of j-th attribute, property set weight vectors ω=(ω₁,ω₂,…,ω_n)^tCan be according to layer The weight assignment result of fractional analysis obtains.

Obtain weighted normal decision matrix z:

In the present embodiment, it is first determined ideal solution and minus ideal result, its property value is weighted normal decision matrix respectively In the best property value of j-th attribute and worst property value, use respectivelyRepresent:

Ideal solution is:

Minus ideal result is:

Then define virtual ideal scheme a* and ill ideal solution a-:

$a^{*}=(z_1^{*},z_2^{*},...,z_n^{*},)---\left(18\right)$

$a^{-}=(z_1^{-},z_2^{-},...,z_n^{-})---\left(19\right)$

Calculate each project alternative to euclid distance (Euclidean distance) of ideal solution and minus ideal result, use respectivelyRepresent:

${d_i}^{*}=\left|\right|z_i-a^{*}\left|\right|=\sqrt{\underset{j=1}{\overset{n}{\mathrm{\&sigma;}}}{(z_{ij}-{z_j}^{*})}^2},(i=1,2,...,m)---\left(20\right)$

${d_i}^{-}=\left|\right|z_i-a^{-}\left|\right|=\sqrt{\underset{j=1}{\overset{n}{\mathrm{\&sigma;}}}{(z_{ij}-{z_j}^{-})}^2},(i=1,2,...,m)---\left(21\right)$

Wherein:

z_i=(z_i1,z_i2,…,z_in) (22)

Calculate the relative similarity degree of each project alternative and ideal solution

${d_i}^{*}=\frac{d_i}{d_i+{d_i}^{*}},(i=1,2,...,m)---\left(23\right)$

According to the relative similarity degree descending of project alternative and ideal solution, the construction sequential of scheme of identifying project.

Finally illustrate, above example only in order to technical scheme to be described and unrestricted, although with reference to relatively Good embodiment has been described in detail to the present invention, it will be understood by those within the art that, can be to the skill of the present invention Art scheme is modified or equivalent, the objective without deviating from technical solution of the present invention and scope, and it all should be covered at this In the middle of the right of invention.

Claims (7)

1. a kind of intelligent transportation system project construction sequential determine method it is characterised in that: include

A. build assessment indicator system, described assessment indicator system includes

Destination layer, for determining the construction sequential of i ts project；

Indicator layer, comprise performance indications, safety benefit index, economic results in society index, environmental benefit index, risk indicator and The indicator of costs；

Solution layer, including several i ts construction projects；

B. the relative weighting of assessment indicator system is determined using analytic hierarchy process (AHP),

C. the construction sequential of i ts project according to described relative weighting, is determined using the sort method approaching optimal solution.

2. intelligent transportation system project construction sequential according to claim 1 determine method it is characterised in that: described index Each index in layer is respectively provided with corresponding sub- index, and all sub- indexs form sub- indicator layer, wherein:

Performance indications include security reliability, practical advanced, open autgmentability and accurate and effective temper index；

Safety benefit index includes direct safety benefit and the sub- index of indirect safety benefit；

Economic results in society index includes reducing Transportation costs benefit, reduces travel time benefit, slows down land resource profit With benefit, promote industry development index, quality of making the life better and the sub- index of other indirect economic results in society；

Environmental benefit index includes reducing pollution emission benefit and reduces the traffic noise pollution sub- index of benefit；

Risk indicator includes the sub- index of integrated risk evaluation grade；

The indicator of costs includes investment construction fund cost and the sub- index of investment construction time cost.

3. intelligent transportation system project construction sequential according to claim 2 determine method it is characterised in that: described step B specifically includes:

B1. set up hierarchy Model, the mutual of destination layer, indicator layer and sub- indicator layer is represented by described hierarchy Model Connection relation,

B2. development of judgment matrix, and the relative importance between each similar evaluation index is determined according to described judgment matrix.

4. intelligent transportation system project construction sequential according to claim 3 determine method it is characterised in that: step b2 is also Carry out standardization processing including to judgment matrix, the judgment matrix after process is:

$\stackrel{\&overbar;}{b_{ij}}=\frac{a_{ij}}{\underset{k=1}{\overset{n}{\&sigma;}}{a}_{kj}}$

Wherein, a_ijRepresent similar index a_iAnd a_jRelative importance, 0 < a_ij≤ 9, a_ij=1/a_ji, a_ii=1.

5. intelligent transportation system project construction sequential according to claim 4 determine method it is characterised in that: when judging square When battle array crash consistency is in tolerance interval, obtain the relative power for certain element in last layer time for the same level each element Weight vector, that is, include that indicator layer is vectorial to the relative weighting of destination layer, sub- indicator layer relative to each corresponding index of indicator layer The relative weighting of every sub- index relative target layer in weight vectors and sub- indicator layer.

6. intelligent transportation system project construction sequential according to claim 5 determine method it is characterised in that: step c is also Including building decision matrix, ideal solution and minus ideal result are determined according to described decision matrix, obtain each project alternative and ideal The relative similarity degree of solution, and the relative similarity degree of project alternative and ideal solution is carried out descending sort, the building of scheme of identifying project If sequential.

7. intelligent transportation system project construction sequential according to claim 6 determine method it is characterised in that: step c is also Including decision matrix is carried out with standardization processing, and to the decision matrix weighting after processing, obtain weighted normal decision matrix, root Determine ideal solution and minus ideal result according to described weighted normal decision matrix.