Research Article Research on Assessment Methods for Urban ...

Research ArticleResearch on Assessment Methods forUrban Public Transport Development in China

Linghong Zou1 Hongna Dai2 Enjian Yao2 Tian Jiang3 and Hongwei Guo4

1 Graduate School of Architecture Planning and Preservation Columbia University 1172 Amsterdam AvenueNew York NY 10027 USA

2 School of Traffic and Transportation Beijing Jiaotong University No 3 Shang Yuan Cun Hai Dian District Beijing 100044 China3 China Urban Sustainable Transport Research Center (CUSTReC) China Academy of Transport SciencesMinistry of Transport No 240 Huixinli Chaoyang District Beijing 100029 China

4Department of Transportation Engineering Beijing Institute of Technology No 5 South Zhongguancun StreetHaidian District Beijing 100081 China

Correspondence should be addressed to Tian Jiang peter zealothotmailcom

Received 26 July 2014 Accepted 5 October 2014 Published 4 November 2014

Academic Editor Xiaobei Jiang

Copyright copy 2014 Linghong Zou et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

In recent years with the rapid increase in urban population the urban travel demands in Chinese cities have been increasingdramatically As a result developing comprehensive urban transport systems becomes an inevitable choice to meet the growingurban travel demands In urban transport systems public transport plays the leading role to promote sustainable urbandevelopmentThis paper aims to establish an assessment index system for the development level of urban public transport consistingof a target layer a criterion layer and an index layer Review on existing literature shows that methods used in evaluating urbanpublic transport structure are dominantly qualitative To overcome this shortcoming fuzzy mathematics method is used fordescribing qualitative issues quantitatively and AHP (analytic hierarchy process) is used to quantify expertrsquos subjective judgmentThe assessment model is established based on the fuzzy AHP The weight of each index is determined through the AHP and thedegree of membership of each index through the fuzzy assessment method to obtain the fuzzy synthetic assessment matrix Finallya case study is conducted to verify the rationality and practicability of the assessment system and the proposed assessment method

1 Introduction

With the acceleration of the urbanization and the rapidexpansion of cities China has been experiencing a con-tinuous increase in urban population Consequently sharpgrowth in the total travel volume as well as the travel distanceof urban residents is witnessed in Chinese cities As a resultthe urban transport structure has undergone significantnegative changes the proportion of motorized travel hasrisen rapidly while the proportion of nonmotorized travelhas gone through a constant decline These changes raiseenormous challenges to Chinese cities with the worseningtraffic urban congestion and the rising pressure on environ-mental pollution and energy consumption Therefore theurban transport has become the bottle neck for sustainable

urban development Given the shortage of transport andenvironmental resources many issues have to be addressedbefore an inclusive urban transport system is established inwhich public transport plays the leading role and the basictravel demands of the wider public are met These issuesinclude the rapid increase in the number of private automo-biles the deterioration of urban congestion conditions andthe situationwhere urban public transport plays a passive rolein urban developmentThesemake public transport speed upthe pace of development to face severe problems

In an effort of facilitating urban public transport devel-opment and improving public transport service capacitiesChinese government has launched the public transport pri-ority development strategy in 2005 The initiative includesthe implementation of scientific planning and control

Hindawi Publishing CorporationComputational Intelligence and NeuroscienceVolume 2014 Article ID 941347 8 pageshttpdxdoiorg1011552014941347

2 Computational Intelligence and Neuroscience

line network optimization infrastructure construction andinformation services improvement as well as other supple-mentary measures The goals are to enhance the appeal ofpublic transport systems reduce the reliance of the public onprivate automobiles and improve the operation efficiency ofurban transport systems

In this context it is of great importance to scientificallyassess the development level of urban public transportidentify the gap between urban public transport develop-ment and residentsrsquo actual travel demands and reduce theldquomalpositionrdquo effect in urban public transport infrastructureconstruction and urban development so as to provide adecision-making basis for urban public transport planningconstruction and management in the next step

During the last two decades there have been a sig-nificant volume of studies assessing public transportationdevelopment Been [1] assessed the quality and quantity ofpublic transport system service Parkes et al [2] focusedon accessibility Sheth et al [3] evaluated bus service levelby DEA (data envelopment analysis) Olivkova [4] estab-lished passenger satisfaction from travel time regularity andaccuracy time and spatial offer comfort costs of freightand impact on the environment and calculates the averagerelative importance by passengers who participated in thesurvey Vstedal et al [5] identified 10 key indicators toassess urban public transport accessibility from policy andinvestment service operations and standards informationticketing vehicles and built environment and seamlesstravel Dodson et al [6] took multiple indictors into consid-eration such as reduction of air pollution parking conges-tion mitigation and reduction of traffic congestion Mavoaaet al [7] expanded current public transport accessibilitymeasures by including all components of public transportjourney

In china a lot of studies have been carried out to assessperformance in public transport Due to the specialty ofpriority development of urban public transport syntheticassessment system to evaluate public transport developmenthas yet to be established Thus strategic modeling andanalysis approaches are needed for evaluating public trans-port development In [8 9] the hierarchical structure forthe assessment of urban public transport development levelconsisting of 23 indexes was constructed in three aspectsnamely infrastructure level service level and benefit levelTian and Wu [10] discussed that the urban public transportdevelopment level was assessed from the network structureinfrastructure level and service level Wei-Hua et al [11] con-sidered that the urban public transport development level wasassessed synthetically from analysis of convenience quick-ness safety efficiency economy comfort and environmentalinfluence In [12] the urban public transport assessmentsystem was established at the network technology level andoperation service level in [13] the implementation effects ofpublic transport priority development measures and planswere assessed from the four aspects of the social economytransport functions environment influence and resourceutilization in [14] the serviceability of urban public transportdevelopment was analyzed by introducing the social andeconomic indexes The synthetic urban public transport

development assessment methods mainly focused on greycluster method [8 9 14] entropy weight matter-elementanalysis model [4] fuzzy synthetic assessment method [1213] multifactor fuzzy assessment [15] and so forth

In this paper a multitiered urban public transport devel-opment level assessment index system for the conventionalbus transport system is established according to the actualconditions of urban public transport development after theimplementation of the public transport priority develop-ment strategy A number of complimentary indexes havebeen proposed additional to the established index systemincluding public transport prioritized lane ratio prioritizedintersection ratio harbor-type stop setting rate and real-time incoming vehicle information forecast coverage as wellas urban and rural passenger transport line transit-orientedoperation rate Finally the fuzzy AHP combining the AHPand the fuzzy assessment is used to analyze the scientificlegitimacy rationality and serviceability of the assessmentindex system and the assessment method based on a casestudy

2 Establishment of Urban Public TransportDevelopment Assessment Index System

The full-scale implementation of the government initiatedstrategy of giving priority to urban public transport hasgiven rise to a multitude of prominent characteristics ofpublic transport in large and medium-sized Chinese citiesthe acceleration of infrastructure construction the contin-uous improvement of public transport service level theacceleration of IT application the increasing emphasis onsustainable development the expanding policy support andthe significant social benefits

The establishment of a multitiered urban public trans-port development level assessment index system in thispaper is informed by the experiences in implementing thestrategy of prioritizing urban public transport Based onthe principle of integrity scientific legitimacy comparabilityconciseness and practicality the assessment index systemconsisted of a target layer a criterion layer and an indexlayer and evaluates the level of public transit developmentfrom six aspects namely infrastructure construction levelservice level IT development level sustainable developmentlevel government support level and social benefit level(see Table 1) The assessment index system is described asfollows

(1) Infrastructure Construction Level (1198801) Infrastructure

construction level reflects macroscopically the rationality ofurban public transport planning and construction mainlyexploiting the indexes such as tram and bus line networkpercentage (119880

11) bus stop coverage with a radius of 500m

(11988012) dedicated bus lane setting rate (119880

13) public transport

priority intersection percentage (11988014) bus bay stop setting

rate (11988015) and public transport vehicle population per 10000

persons (11988016) The implementation of prioritizing public

transport strategy has accelerated the proliferation of infras-tructures which formerly sparsely existed such as bus lanes

Computational Intelligence and Neuroscience 3

Table1Urban

publictransportd

evelop

mentlevelassessmentsystem

andgradingcriteria

Targetlayer

Criterio

nlayer

Indexlayer

Unit

Grading

criteria

Level1

Level2

Level3

Level4

Level5

Urban

public

transport

developm

ent

level

assessment

syste

m119880

Infrastructure

constructio

nlevel1198801

Tram

andbu

slinen

etworkpercentage

11988011

ge65

[5565)

[4555)

[3545)

lt35

Busstopcoverage

with

ther

adiuso

f500

m11988012

ge95

[9095)

[8590)

[8085)

lt80

Rateof

dedicatedbu

slane11988013

ge20

[1530)

[1015)

[510)

lt5

Thep

ercentageo

fintersections

with

publictransportp

riority

11988014

ge50

[3050)

[1030)

[510)

lt5

Rateof

setting

busa

ndtram

baysto

p11988015

ge50

[3050)

[1030)

[510)

lt5

Publictransportvehiclesp

er10000

person

s11988016

Units

1000

0person

sge18

[1518)

[1215)

[1012)

lt10

Operatio

nservice

level1198802

Fullload

rateof

publictransportd

uringpeak

hours11988021

[6090)

[90100)

[100110)

[110120)

ge120

Tram

andbu

spun

ctualityrate

11988022

ge75

[7075)

[6570)

[6065)

lt60

Averageo

peratin

gspeeddu

ringpeak

hours11988023

kmh

ge19

[1719)

[1517)

[1315)

lt13

Tram

andbu

saccidentm

ortality

11988024

Passm

illionkm

lt003

[0030035)

[0035004)

[0040045)

[0045005)

Publictransportp

assenger

satisfaction

11988025

ge80

[7580)

[7075)

[6570)

lt65

Publictransportcom

plaint

hand

lingrate

11988026

ge80

[7080)

[6070)

[5060)

lt50

ITapplicationlevel1198803

Installationrateof

electro

nico

n-bo

ardpo

sitioning

term

inal

11988031

ge95

[8595)

[7585)

[6575)

lt65

Electro

nicp

aymentcarduser

ate11988032

ge70

[6070)

[5060)

[4050)

lt40

Coverageo

fincom

ingvehicle

119894real-timeforecast11988033

ge75

[5075)

[3050)

[2030)

lt20

Susta

inable

developm

entlevel

1198804

Percentage

ofgreenpu

blictransportvehicles11988041

ge60

[5060)

[4050)

[3040

)lt30

Docking

rateof

busa

ndtram

durin

gnight11988042

ge90

[8090)

[7080)

[6070)

lt60

Governm

entsup

port

level1198805

Availabilityof

subsidyforp

ublic

transporto

peratio

n11988051

ge75

[5075)

[4050)

[2040

)lt20

Com

pleted

egreeo

frelated

policieslawsandregu

lations

11988052

Level1

Level2

Level3

Level4

Level5

Socialbenefit

level1198806

Num

bero

ftrip

sbypu

blictransportp

ercapitaperd

ay11988061

Times

ge10

4[09

104)

[07709)

[063077)

lt063

Mod

elshareo

fpub

lictransport11988062

ge60

[5060)

[4050)

[3040

)lt30

Transit-orie

nted

operationrateof

urban-ruralp

assenger

transportlines

11988063

ge85

[7585)

[6575)

[5565)

lt55


bus priority intersections and harbor-type stops Thereforethe calculation methods for 119880

13 11988014 and 119880

15are as follows

11988013

=119897119887119897

119871

11988014

=

119899119901119895

119873119895

11988015

=119899119887119887119904

119873119887119904

(1)

where 119897119887119897is length of dedicated bus lanes 119871 is length of bus

line networks 119899119901119895is number of bus priority intersections 119873

119895

is total number of urban trunk intersections 119899119887119887119904

is numberof bay stops and 119873

119887119904is total number of stops

(2) Operation Service Level (1198802) As an important mani-

festation of public transport operation results the opera-tional level of service reflects the contents such as comfortpunctuality safety and public satisfaction of urban publictransport system through the indexes such as full load rateof public transport during peak hours (119880

21) tram and bus

punctuality rate (11988022) average operating speed during peak

hours (11988023) tram and bus accident mortality (119880

24) public

transport passenger satisfaction (11988025) and public transport

complaint handling rate (11988026) With the rapid motorization

transport congestion during peak hours worsens at an alert-ing pace Meanwhile the comfort degree of public transportrelates directly to the choice of travel mode by the publicConsidering these two factors the calculationmethod for119880

21

is as follows

11988021

=

sum 119899119901

sum 119899119903119901

(2)

where 119899119901is the sum of passengers of all running buses at

maximum passenger flow section during peak hours 119899119903119901

issum of the rated capacity of all running buses at maximumpassenger flow section during morning and evening rushhours

(3) IT Application Level (1198803) IT application as an important

sign of the development level of the modern transportindustry reflects the degree of IT application in urban publictransport through the indexes such as installation rate ofon-board equipment (119880

31) electronic payment card use

rate (11988032) and electronic stop board setting rate (119880

33) Its

calculation method is shown as follows

11988031

=119899V119905V

119873Vtimes 100

11988032

=119901119890119888

119901times 100

11988033

=

119899119887119891

119873119887119904

times 100

(3)

where 119899V119905V is the number of vehicles with on-board position-ing terminals 119873V is the total number of buses 119901

119890119888is the total

number of passengers using electronic payment card 119901 is

total number of passengers of public transport 119899119887119891

is totalnumber of stops providing real-time prediction of incomingvehicle information and 119873


(4) Sustainable Development Level (1198804) Sustainable devel-

opment level sets new requirements for the development ofthe transport industry In this paper sustainable developmentlevel reflects the rational use of resources and land of urbanpublic transport systems and their sustainable developmentlevel through the indexes such as percentage of green publictransport vehicles (119880

41) and bus and tram overnight docking

rate (11988042) Strengthening the promotion of green public

transport vehicles should be an important measure for citiesto take the path of sustainable development with low energyconsumption low pollution and high energy efficiency Thecalculation method for 119880

41is as follows

11988041

=119899V119905V

119873Vtimes 100 (4)

where 119899V119905V is number of green public transport vehicles and119873V is total number of public transport vehicles

(5) Government Support Level (1198805)After the implementation

of the strategy of giving priority to public transport develop-ment the government has demonstrated expanding supporton urban public transport This paper analyzes the level ofgovernment support to urban public transport developmentfrom the aspects of subsidy guarantee (119880

51) and formulation

of relevant policies laws and regulations (11988052) The financial

aid of the government plays a crucial role in normal operationof public transport and the calculationmethod for119880

51in this

paper is shown as follows

11988051

=119872119905119904

119872119901119904

times 100 (5)

where 119872119905119904is actual amount of subsidies for urban public

transport 119872119901119904is total policy subsidies reasonably calculated

including various subsidies calculated by third-sector organi-zations and undertaken by government such as new and rareline subsidies fare subsidies and mandatory compensation

(6) Social Benefits Level (1198806) The level of social benefits

mainly reflects the positive externalities generated by urbanpublic transport as a public welfare To reflect such influenceindexes such as number of trips by public transport percapita per day (119880

61) mode share of public transport (119880

62)

and transit-oriented operation rate of urban-rural passengertransport lines (119880

63) have been taken into consideration

With the acceleration of urbanization urban-rural passengertransport lines have gradually adopted the transit-orientedoperation mode with low fares multifrequency and multi-stopping sites The calculation method for 119880

63is as follows

11988063

=

119899119901119906119903

119873119906119903

times 100 (6)

where 119899119901119906119903

is number of urban-rural passenger transportlines adopting the transit-oriented operation mode and 119873

119906119903

is total number of urban-rural passenger transport lines


In this paper the 22 indexes are divided into the 5 gradesof ldquoLevel 1rdquo ldquoLevel 2rdquo ldquoLevel 3rdquo ldquoLevel 4rdquo and ldquoLevel 5rdquo onthe base of ldquocode for transport planning on urban roadrdquoThe national standards for actual values of the indexes orthe average levels the cities can reach are the upper limit ofreference (Table 1)

3 Assessment of Urban Public TransportDevelopment Level Based on Fuzzy AHP

Fuzzy mathematics method is applicable for describing qual-itative issues by quantitative way and AHP is able to quantifyexpertrsquos subjective judgment Fuzzy AHP is an algorithmproposed to address the problems of the traditionalAHP suchas difference in judgment consistency andmatrix consistencyconsistency validation difficulty and lack of scientificnessgiven the fuzziness in judgment of complicated things [16ndash19] It can ensure that the results of assessment of urbanpublic transport development level are objective impartialscientific and reasonable The fuzzy AHP is to determine theweight of each index through the AHP and establishing themembership function of each index to get the fuzzy syntheticassessment matrix and thus obtain the synthetic assessmentvalues

31 Determination of Weight of Each Index through AHP

(1) Establishment of Judgment Matrix To get the local weightin the hierarchical structure of the assessment index systemfor urban public transport development level we mustgradually establish the judgment matrix If the upper index119880119905contains 119899 lower indexes then 119880

119905can be divided into the

following 119899 factor sets

119880119905

= 1198801199051

1198801199052

119880119905119899

(7)

In this paper we have adopted 1sim9 scales (Table 2)asked the experts to carry out pairwise comparison of theimportance of 119880

119905119894with respect to 119880

119905 and established the

judgment matrix 119860119905

(2) Consistency Validation of Judgment Matrix and Determi-nation of Weight Set The root method is used to calculatethe maximal eigenvector of the judgment matrix If thejudgment matrix 119860

119905satisfies the consistency requirements

its eigenvector [1199081199051

1199081199052

119908119905119899

] corresponding to the maxi-mum eigenvalue should be served as the weight coefficientif the judgment matrix 119860

119905dissatisfies with the consistency

requirements it should be properly adjustedThe adjustmentmethod can be referred to in [20]

For this paper experts have been invited to carry outpairwise comparison according to the standards in Table 2and the AHP judgment matrix has been obtained Theweights of each index and the weighted average have beenobtained and the weight vectors obtained are as shown inTable 3

Table 2 Explanations of 1sim9 scales

Value Explanation1 Two indexes are equally important3 By comparison 119909

119894is slightly more important than 119909

119895

5 In comparison 119909119894is clearly more important than 119909

119895

7 In comparison 119909119894is much more important than 119909

119895

9 In comparison 119909119894is extremely more important than 119909

119895

2 4 6 8 Intermediate state corresponding to the above adjacentjudgment

Table 3 Weight vectors of assessment indexes

Weight vector Results119908 [0294 0245 00951 00814 01591 01254]

1199081

[02411 03547 01078 00961 0067 01333]

1199082

[01011 01719 02105 01887 0225 01028]

1199083

[04773 02958 02269]

1199084

[06389 03611]1199085

[06574 03426]

1199086

[04352 03686 01962]

32 Establishment of Fuzzy Assessment Matrix

(1) Establishment of Judgment Set The grading is carried outaccording to the indexes in the assessment system that canbe divided into the 5 grading criteria of ldquoLevel 1rdquo ldquoLevel 2rdquoldquoLevel 3rdquo ldquoLevel 4rdquo and ldquoLevel 5rdquo Let the judgment set be119881 =

1198811 1198812 1198813 1198814 1198815 in which 119881

119894(119894 = 1 2 3 4 5) means the 119894th

grade

(2) Determination of Membership Degree To better reflectthe characteristics of each assessment index of ldquoTransitMetropolisrdquo we eliminate the dimensional effect of eachassessment index and it is necessary to carry out the abstractand fuzzy processing of each index data

For the quantitative indexes in this system the followingmembership function is adopted in this paper for smallerbetter indexes such as full load rate of public transport duringpeak hours and tram and bus accident mortality

119903 (119894) =

1 119909 (119894) lt 119886

119887 minus 119909 (119894)

119887 minus 119886 119886 le 119909 (119894) lt 119887

0 119909 (119894) ge 119887

(8)

where 119903(119894) ismembership function of index 119894119909(119894) is the actualvalues of index 119894 119886 119887 are the upper and lower boundaries ofmembership function

For bigger better indexes such as bus stop coverage witha radius of 500m and dedicated bus lane setting rate thefollowing membership function can be adopted

119903 (119894) =

0 119909 (119894) lt 119886

119909 (119894) minus 119886

119887 minus 119886 119886 le 119909 (119894) lt 119887

1 119909 (119894) ge 119887

(9)


For the qualitative indexes such as complete degree ofrelevant policies laws and regulations their membershipdegree can be determined according to the fuzzy statisticalmethod [16]

(3) Establishment of Fuzzy Assessment Matrix of IndexesThe single factor assessment matrix of the 119894th subset of theurban public transport development level assessment indexsystem is established as follows 119903

119905119894= 1199031199051198941

1199031199051198942

1199031199051198945

119894 =

1 2 119899 in which 119903119905119894119895

(119894 = 1 2 119899 119895 = 1 2 5) meansthe membership degree of the 119894119895 lower index of the index 119880

119905

with respect to the grade 119881 and the matrix 119903119905119894119895is normalized

to obtain the fuzzy assessment matrix 119877119905of the index 119880

119905

119877119905119899times5

=[[

[

1199031015840

1199051198941sdot sdot sdot 1199031015840

1199051198945

d

1199031015840

1199051198991sdot sdot sdot 1199031015840

1199051198995

]]

]

(10)

33 Analysis of Synthetic Assessment Results The resultsof synthetic assessment are obtained through compoundcalculation of the single factor weightmatrix119908

119905and the fuzzy

matrix 119877119905 that is the synthetic assessment set 119880

119905 which is

denoted as follows

119880119905

= 119908119905

times 119877119905

= (1198801199051

1198801199052

1198801199055

) (11)

The synthetic assessment matrix 119880 of urban public trans-port development level can eventually be obtained throughcalculating gradually upwards layer by layer from the indexlayer According to the principle of maximum degree ofmembership the assessment grade corresponding to themaximumelement in thematrix119880 is the synthetic assessmentgrade of urban public transport development level

The score of the determined assessment grade is writtenin the following vector calculation form

119876 = [100 80 70 60 40] (12)

The total score 119878 of the assessment index system can beobtained by multiplying 119880 and 119876

119878 = 119880 lowast 119876119879

(13)

4 Case Study

Kunming is a major city in southwest China Along with therapid advancement of socioeconomic development as wellas fast urbanization the city is featured by the adjustmentof urban spatial structure the continuous improvement oftransport infrastructure the sustainably growth in vehiclenumbers and the drastic increase in residentsrsquo trip demandsThose factors have led to the increasingly serious congestionin the city center As Kunming is one of the first batchcities in the ldquoTransit Metropolisrdquo Program announced by theMinistry of Transport of China its urban public transportdevelopment has attracted increasing professional as well asacademic attention The present public transport develop-ment of Kunming is analyzed by using the fuzzy AHP as thefollowing

Table 4 Basic data on urban public transport of Kunming

Index ValuePercentage of tram and bus line network () 3687Bus stop coverage with a radius of 500m () 8220Rate of setting dedicated bus lane setting () 1330The percentage of intersections with public transportpriority () 10

Rate of setting bus and tram bay stop () 13Public transport vehicle per 10000 persons(units10000 persons) 137

Full load rate of public transport during peak hours () 92Tram and bus punctuality rate () 4546Average operating speed during peak hours (kmh) 157Tram and bus accident mortality (passmillion km) 0037Public transport passenger satisfaction () 80Public transport complaint handling rate () 82Installation rate of electronic on-board positioningterminal equipment () 5860

Electronic payment card use rate () 50Incoming vehicle information real-time forecastcoverage () 0

Percentage of green public transport vehicles () 730Bus and tram overnight docking rate () 9630Availability of public transport operation subsidy () 60Number of trips by public transport per capita per day(times) 051

Model sharing of public transport () 4850Transit-oriented operation rate of urban-ruralpassenger transport lines () 8450

(1) Establishment of Membership Matrix The related assess-ment data is acquired according to the data on Kunmingrsquosurban public transport development in 2011 (Table 4)

Themembership degree matrix is calculated and normal-ized according to the index grading criteria in Table 1 andthe fuzzy assessment subsets of the 22 indexes are acquiredwhich form 6 fuzzy assessment matrixes 119877

1 1198772 1198773 1198774 1198775

and 1198776corresponding to the indexes at the criteria layer

1198771

=

[[[[[[[

[

0 0 0094 05 0406

0 0 022 05 028

0 033 05 017 0

0 0 0167 05 0333

0 0075 05 0425 0

0 0284 05 0216 0

]]]]]]]

]

1198772

=

[[[[[[[

[

0 0 005 05 045

0 0 0 0313 0687

0 0425 05 0075 0

0 03 05 02 0

05 05 0 0 0

0526 0474 0 0 0

]]]]]]]

]


Table 5 Assessment result of urban public transport development level of Kunming

Assessment target Fuzzy assessment matrix Assessment results ValueInfrastructure construction level [0 00785 02708 04215 02292] Level 4 5969Operation service level [01666 03073 02047 01579 01636] Level 2 7159IT application level [0 0 01479 03990 04531] Level 5 5297Sustainable development level [03048 00563 0 01246 05143] Level 5 6303Government support level [01657 03972 04028 00343 0] Level 3 7860Social benefit level [00932 02548 01892 02226 02402] Level 2 6591Overall assessment index [01037 02076 02407 02346 02134] Level 3 6653

1198773

= [

[

0 0 0 0526 0474

0 0 05 05 0

0 0 0 0 1

]

]

1198774

= [0 0 0 0195 0805

0844 0156 0 0 0]

1198775

= [02 05 03 0 0

01 02 06 01 0]

1198776

= [

[

0 0 0 0448 0552

0 0425 05 0075 0

0475 05 0025 0 0

]

]

(14)

(2) Calculation and Analysis of Assessment ResultsAccordingthe principle of maximum membership degree the maxi-mum value in fuzzy set is the evaluation resultThe fuzzy syn-thetic assessment results show that the synthetic assessmentresult of Kunmingrsquos urban public transport development isldquoLevel 3rdquo and the overall score is 6653 so its public transportsystemcanbe considered to be reasonable andmeet the actualconditions (Table 5)

The fuzzy assessmentmatrix and the synthetic assessmentresult show that there are still some problems existing in thedevelopment of urban public transport in Kunming

(1) The infrastructures need to be improved markedlyThe pace of urban public transport infrastructureconstruction is not in line with that of urban con-struction and the percentage of bus line network isstill at a very low level of only 3687 the dedicatedbus lane setting rate is 133 the bus priority inter-section rate is 10 the bus bay stop setting rate is 13and the public transport vehicle population per 10000persons is 137 standard units mostly in the moderateor poor grades In the future it is necessary to increasethe input in public transport-dedicated road facilityconstruction and transport capacity improvement toenhance the appeal of public transport

(2) The level of IT application remains to be improvedThe level of digitization and intellectualization ofurban public transport in Kunming needs to beimproved which is the direction of urban publictransport development in the next step In additionit is necessary to strengthen the input in intelligenton-board electronic devices to constantly improve

the use rate of card for bus riding and to make abreakthrough in the ldquozero stagerdquo situation in elec-tronic bus stop board services to make it convenientfor the public to travel and attract more passengers totravel by public transport systems

(3) The level of sustainable development needs to beincreased Based on the requirements of resourceconservation and environmental protection it is nec-essary to promote the development of new energyvehicles for public transport with emphasis on energyconservation and emission reduction Additionallythe phase-out of old vehicles should speed up toimprove the overall transport capacity The prioritiesof land use for bus stops should be ensured to addressthe problem of public transport vehicle parking

(4) Theguarantee and support from the government needto be materialized Public transport will be difficultto operate normally without the policy support andinvestment of the government In the future publictransport vehicles road infrastructures and IT appli-cation still need considerable finance-policy supportit has become a key task of how to ensure various buspriority policies implementation of the government inthe next step

5 Conclusions

This paper establishes a multitiered urban public transportdevelopment assessment system in which the priorities aregiven to public transport according to the characteristics ofpublic transport development in medium and large cities inChina Some of important assessment indexes were takeninto consideration including the infrastructure constructionthe service level of public transport the acceleration ofIT application and the increasing emphasis on sustainabledevelopment as well as the expanding policy support andsignificant social benefits The assessment model is henceestablished based on the fuzzy AHP The weight of eachindex is determined through the AHP and the degree ofmembership of each index is calculated through the fuzzyassessment method to obtain the fuzzy synthetic assessmentmatrix With such methodology the overall assessment scoreof urban public transport development level can be analyzedquantitatively In addition Kunming China is studied asan example to prove the rationality and practicability of theassessment system and the assessment method


The results from the case study show that a quantitativeassessment can be obtained to directly reveal the actual devel-opment of public transport in Kunming city However due tothe limit of resources and scopes the case study uses the datafrom only one city which makes it hardly a comprehensivecontrastive analysis In future work the contrastive analysiswill be performed by using the data derived from multiplecities of comparable scale and economic level which wouldbe an essential work to test and verify the proposed model

Conflict of Interests

The authors declare that there is no conflict of interestsregarding to the publication of this paper

Acknowledgments

This research was funded by Volvo Research and EducationFoundations The perspectives of the paper are from theauthorsrsquo viewpoints and might not represent the perspectivesof Ministry of Transport of China

References

[1] H P Been Bus Route Evalution Standards National AcademyPress Washington DC USA 1995

[2] T Parkes B Corcoran and J GouldEvaluation of theAct ActionPlan for Accessible Public Transport 2003

[3] C Sheth K Triantis and D Teodorovic ldquoPerformance eval-uation of bus routes a provider and passenger perspectiverdquoTransportation Research Part E Logistics and TransportationReview vol 43 no 4 pp 453ndash478 2007

[4] I Olivkova Evaluation of Quality Indicators Public TransportNumber IV vol 5 2010

[5] L Vstedal G Azalde and T Derud ldquoAccessibility indicators forurban public transportrdquo Mediate Methodology for Describingthe Accessibility of Transport in Europe EU 2011

[6] J Dodson P Mees J Stone and M Burke The Principles ofPublic Transport Network Planning A Review of the EmergingLiterature with Select Examples Urban Research Program Grif-fith University 2011

[7] SMavoaa KWittena TMcCreanorb andDOrsquoSullivanc ldquoGISbased destination accessibility via public transit and walkingin Auckland New Zealandrdquo New Zealand Journal of transportgeography vol 20 no 1 pp 15ndash22 2012

[8] L Yuhua and S Kai ldquoOn the comprehensive evaluation of urbanpublic transport based on gray clustering methodrdquo Journal ofHarbin University vol 9 no 6 pp 76ndash82 2004

[9] L Yuhua and H Yunquan ldquoGray clustering method appliedto evaluation of Urban public transport development levelrdquoMathematics in Practice and Theory vol 32 no 2 pp 125ndash1322006

[10] M Tian andZWu ldquoFuzzy comprehensive evaluation forUrbanpublic transport developmentrdquo Urban Public Transportationvol 7 pp 35ndash37 2010

[11] Z Wei-Hua L Hua-Pu and L Qiang ldquoStudy on evaluationindex system of bus priority measuresrdquo Communications Stan-dardization Issue no 135 pp 85ndash89 2004

[12] Z Liu Y Yu and S Cheng ldquoA comprehensive evaluationindex system for public transportation based on entropy weight

matter-element modelrdquo Urban Transport of China vol 8 no 6pp 79ndash84 2010

[13] W-X Cai and X-T Guo ldquoThe research amp evaluation of urbanand rural public transport networks based on AHP and thefuzzy comprehensive evaluationrdquo in Proceedings of the 8thInternational Conference of Chinese Logistics and TransportationProfessionals pp 699ndash705 August 2008

[14] H Chen Y Wu and Y Guo ldquoAdaptability evaluation of urbanpublic transport based on weighted grey incidence degreerdquo inProceedings of the 12th International Conference of Transporta-tion Professionals (CICTP rsquo12) pp 1568ndash1576 Beijing ChinaAugust 2012

[15] Y Xu J Qiao and L Wang ldquoApplication of multi-factorhierarchical fuzzy evaluation in public transportrdquo inProceedingsof the International Conference on Measuring Technology andMechatronics Automation (ICMTMA rsquo10) vol 1 pp 642ndash646March 2010

[16] Q Wang F Wen M Liu and S Yi ldquoCombined use of fuzzyset theory and analytic hierarchy process for comprehensiveassessment of electricity marketsrdquo Automation of Electric PowerSystems vol 33 no 7 pp 32ndash37 2009

[17] Z Chan L Xin and L Tongtao ldquoResearch on comprehensiveevaluation of network performance based on FAHPrdquo Applica-tion Research of Computer vol 26 no 10 pp 3852ndash3855 2009

[18] L Chen ldquoApplication of fuzzy analytical hierarchy process inairline safety evaluationrdquo Aeronautical Computing Techniquevol 41 no 5 pp 71ndash73 2011

[19] T L Saaty and L T Tran ldquoOn the invalidity of fuzzifyingnumerical judgments in the analytic hierarchy processrdquo Math-ematical and Computer Modelling vol 46 no 7-8 pp 962ndash9752007

[20] T L Satty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Distributed Sensor Networks


Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014


ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014


Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications


Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia


Biomedical Imaging


ArtificialNeural Systems

Advances in


RoboticsJournal of



Computational Intelligence and Neuroscience

Industrial EngineeringJournal of


Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014


Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in



line network optimization infrastructure construction andinformation services improvement as well as other supple-mentary measures The goals are to enhance the appeal ofpublic transport systems reduce the reliance of the public onprivate automobiles and improve the operation efficiency ofurban transport systems

In this context it is of great importance to scientificallyassess the development level of urban public transportidentify the gap between urban public transport develop-ment and residentsrsquo actual travel demands and reduce theldquomalpositionrdquo effect in urban public transport infrastructureconstruction and urban development so as to provide adecision-making basis for urban public transport planningconstruction and management in the next step

During the last two decades there have been a sig-nificant volume of studies assessing public transportationdevelopment Been [1] assessed the quality and quantity ofpublic transport system service Parkes et al [2] focusedon accessibility Sheth et al [3] evaluated bus service levelby DEA (data envelopment analysis) Olivkova [4] estab-lished passenger satisfaction from travel time regularity andaccuracy time and spatial offer comfort costs of freightand impact on the environment and calculates the averagerelative importance by passengers who participated in thesurvey Vstedal et al [5] identified 10 key indicators toassess urban public transport accessibility from policy andinvestment service operations and standards informationticketing vehicles and built environment and seamlesstravel Dodson et al [6] took multiple indictors into consid-eration such as reduction of air pollution parking conges-tion mitigation and reduction of traffic congestion Mavoaaet al [7] expanded current public transport accessibilitymeasures by including all components of public transportjourney

In china a lot of studies have been carried out to assessperformance in public transport Due to the specialty ofpriority development of urban public transport syntheticassessment system to evaluate public transport developmenthas yet to be established Thus strategic modeling andanalysis approaches are needed for evaluating public trans-port development In [8 9] the hierarchical structure forthe assessment of urban public transport development levelconsisting of 23 indexes was constructed in three aspectsnamely infrastructure level service level and benefit levelTian and Wu [10] discussed that the urban public transportdevelopment level was assessed from the network structureinfrastructure level and service level Wei-Hua et al [11] con-sidered that the urban public transport development level wasassessed synthetically from analysis of convenience quick-ness safety efficiency economy comfort and environmentalinfluence In [12] the urban public transport assessmentsystem was established at the network technology level andoperation service level in [13] the implementation effects ofpublic transport priority development measures and planswere assessed from the four aspects of the social economytransport functions environment influence and resourceutilization in [14] the serviceability of urban public transportdevelopment was analyzed by introducing the social andeconomic indexes The synthetic urban public transport

development assessment methods mainly focused on greycluster method [8 9 14] entropy weight matter-elementanalysis model [4] fuzzy synthetic assessment method [1213] multifactor fuzzy assessment [15] and so forth

In this paper a multitiered urban public transport devel-opment level assessment index system for the conventionalbus transport system is established according to the actualconditions of urban public transport development after theimplementation of the public transport priority develop-ment strategy A number of complimentary indexes havebeen proposed additional to the established index systemincluding public transport prioritized lane ratio prioritizedintersection ratio harbor-type stop setting rate and real-time incoming vehicle information forecast coverage as wellas urban and rural passenger transport line transit-orientedoperation rate Finally the fuzzy AHP combining the AHPand the fuzzy assessment is used to analyze the scientificlegitimacy rationality and serviceability of the assessmentindex system and the assessment method based on a casestudy

2 Establishment of Urban Public TransportDevelopment Assessment Index System

The full-scale implementation of the government initiatedstrategy of giving priority to urban public transport hasgiven rise to a multitude of prominent characteristics ofpublic transport in large and medium-sized Chinese citiesthe acceleration of infrastructure construction the contin-uous improvement of public transport service level theacceleration of IT application the increasing emphasis onsustainable development the expanding policy support andthe significant social benefits

The establishment of a multitiered urban public trans-port development level assessment index system in thispaper is informed by the experiences in implementing thestrategy of prioritizing urban public transport Based onthe principle of integrity scientific legitimacy comparabilityconciseness and practicality the assessment index systemconsisted of a target layer a criterion layer and an indexlayer and evaluates the level of public transit developmentfrom six aspects namely infrastructure construction levelservice level IT development level sustainable developmentlevel government support level and social benefit level(see Table 1) The assessment index system is described asfollows

(1) Infrastructure Construction Level (1198801) Infrastructure

construction level reflects macroscopically the rationality ofurban public transport planning and construction mainlyexploiting the indexes such as tram and bus line networkpercentage (119880

11) bus stop coverage with a radius of 500m

(11988012) dedicated bus lane setting rate (119880

13) public transport

priority intersection percentage (11988014) bus bay stop setting

rate (11988015) and public transport vehicle population per 10000

persons (11988016) The implementation of prioritizing public

transport strategy has accelerated the proliferation of infras-tructures which formerly sparsely existed such as bus lanes


Table1Urban

publictransportd

evelop


andgradingcriteria

Targetlayer

Criterio

nlayer

Indexlayer

Unit

Grading

criteria

Level1

Level2

Level3

Level4

Level5

Urban

public

transport

developm

ent

level

assessment

syste

m119880

Infrastructure

constructio

nlevel1198801

Tram

andbu

slinen

etworkpercentage

11988011

ge65

[5565)

[4555)

[3545)

lt35

Busstopcoverage

with

ther

adiuso

f500

m11988012

ge95

[9095)

[8590)

[8085)

lt80

Rateof

dedicatedbu

slane11988013

ge20

[1530)

[1015)

[510)

lt5

Thep

ercentageo

fintersections

with

publictransportp

riority

11988014

ge50

[3050)

[1030)

[510)

lt5

Rateof

setting

busa

ndtram

baysto

p11988015

ge50

[3050)

[1030)

[510)

lt5


er10000

person

s11988016

Units

1000

0person

sge18

[1518)

[1215)

[1012)

lt10

Operatio

nservice

level1198802

Fullload

rateof

publictransportd

uringpeak

hours11988021

[6090)

[90100)

[100110)

[110120)

ge120

Tram

andbu

spun

ctualityrate

11988022

ge75

[7075)

[6570)

[6065)

lt60

Averageo

peratin

gspeeddu

ringpeak

hours11988023

kmh

ge19

[1719)

[1517)

[1315)

lt13

Tram

andbu

saccidentm

ortality

11988024

Passm

illionkm

lt003

[0030035)

[0035004)

[0040045)

[0045005)

Publictransportp

assenger

satisfaction

11988025

ge80

[7580)

[7075)

[6570)

lt65

Publictransportcom

plaint

hand

lingrate

11988026

ge80

[7080)

[6070)

[5060)

lt50


Installationrateof

electro

nico

n-bo

ardpo

sitioning

term

inal

11988031

ge95

[8595)

[7585)

[6575)

lt65

Electro

nicp

aymentcarduser

ate11988032

ge70

[6070)

[5060)

[4050)

lt40

Coverageo

fincom

ingvehicle


ge75

[5075)

[3050)

[2030)

lt20

Susta

inable

developm

entlevel

1198804

Percentage

ofgreenpu


ge60

[5060)

[4050)

[3040

)lt30

Docking

rateof

busa

ndtram

durin

gnight11988042

ge90

[8090)

[7080)

[6070)

lt60

Governm

entsup

port

level1198805

Availabilityof

subsidyforp

ublic

transporto

peratio

n11988051

ge75

[5075)

[4050)

[2040

)lt20

Com

pleted

egreeo

frelated

policieslawsandregu

lations

11988052

Level1

Level2

Level3

Level4

Level5

Socialbenefit

level1198806

Num

bero

ftrip

sbypu

blictransportp

ercapitaperd

ay11988061

Times

ge10

4[09

104)

[07709)

[063077)

lt063

Mod

elshareo

fpub


ge60

[5060)

[4050)

[3040

)lt30

Transit-orie

nted

operationrateof

urban-ruralp

assenger

transportlines

11988063

ge85

[7585)

[6575)

[5565)

lt55



13 11988014 and 119880

15are as follows

11988013

=119897119887119897

119871

11988014

=

119899119901119895

119873119895

11988015

=119899119887119887119904

119873119887119904

(1)



119895






21) tram and bus



24) public




21

is as follows

11988021

=

sum 119899119901

sum 119899119903119901

(2)








33) Its


11988031

=119899V119905V

119873Vtimes 100

11988032

=119901119890119888

119901times 100

11988033

=

119899119887119891

119873119887119904

times 100

(3)












41is as follows

11988041

=119899V119905V

119873Vtimes 100 (4)




51) and formulation



51in this


11988051

=119872119905119904

119872119901119904

times 100 (5)







62)




63is as follows

11988063

=

119899119901119906119903

119873119906119903

times 100 (6)

where 119899119901119906119903


119906119903










119880119905

= 1198801199051

1198801199052

119880119905119899

(7)


119905119894with respect to 119880






1199081199052

119908119905119899








119895


119895


119895


119895




1199081

[02411 03547 01078 00961 0067 01333]

1199082

[01011 01719 02105 01887 0225 01028]

1199083

[04773 02958 02269]

1199084

[06389 03611]1199085

[06574 03426]

1199086

[04352 03686 01962]



1198811 1198812 1198813 1198814 1198815 in which 119881

119894(119894 = 1 2 3 4 5) means the 119894th

grade



119903 (119894) =

1 119909 (119894) lt 119886

119887 minus 119909 (119894)

119887 minus 119886 119886 le 119909 (119894) lt 119887

0 119909 (119894) ge 119887

(8)



119903 (119894) =

0 119909 (119894) lt 119886

119909 (119894) minus 119886

119887 minus 119886 119886 le 119909 (119894) lt 119887

1 119909 (119894) ge 119887

(9)




119905119894= 1199031199051198941

1199031199051198942

1199031199051198945

119894 =

1 2 119899 in which 119903119905119894119895


119905



119905

119877119905119899times5

=[[

[

1199031015840

1199051198941sdot sdot sdot 1199031015840

1199051198945

d

1199031015840

1199051198991sdot sdot sdot 1199031015840

1199051198995

]]

]

(10)


119905and the fuzzy


119905 which is

denoted as follows

119880119905

= 119908119905

times 119877119905

= (1198801199051

1198801199052

1198801199055

) (11)



119876 = [100 80 70 60 40] (12)


119878 = 119880 lowast 119876119879

(13)

4 Case Study











1 1198772 1198773 1198774 1198775


1198771

=

[[[[[[[

[

0 0 0094 05 0406

0 0 022 05 028

0 033 05 017 0

0 0 0167 05 0333

0 0075 05 0425 0

0 0284 05 0216 0

]]]]]]]

]

1198772

=

[[[[[[[

[

0 0 005 05 045

0 0 0 0313 0687

0 0425 05 0075 0

0 03 05 02 0

05 05 0 0 0

0526 0474 0 0 0

]]]]]]]

]




1198773

= [

[

0 0 0 0526 0474

0 0 05 05 0

0 0 0 0 1

]

]

1198774

= [0 0 0 0195 0805

0844 0156 0 0 0]

1198775

= [02 05 03 0 0

01 02 06 01 0]

1198776

= [

[

0 0 0 0448 0552

0 0425 05 0075 0

0475 05 0025 0 0

]

]

(14)








5 Conclusions






Acknowledgments


References





























Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




Table1Urban

publictransportd

evelop


andgradingcriteria

Targetlayer

Criterio

nlayer

Indexlayer

Unit

Grading

criteria

Level1

Level2

Level3

Level4

Level5

Urban

public

transport

developm

ent

level

assessment

syste

m119880

Infrastructure

constructio

nlevel1198801

Tram

andbu

slinen

etworkpercentage

11988011

ge65

[5565)

[4555)

[3545)

lt35

Busstopcoverage

with

ther

adiuso

f500

m11988012

ge95

[9095)

[8590)

[8085)

lt80

Rateof

dedicatedbu

slane11988013

ge20

[1530)

[1015)

[510)

lt5

Thep

ercentageo

fintersections

with

publictransportp

riority

11988014

ge50

[3050)

[1030)

[510)

lt5

Rateof

setting

busa

ndtram

baysto

p11988015

ge50

[3050)

[1030)

[510)

lt5


er10000

person

s11988016

Units

1000

0person

sge18

[1518)

[1215)

[1012)

lt10

Operatio

nservice

level1198802

Fullload

rateof

publictransportd

uringpeak

hours11988021

[6090)

[90100)

[100110)

[110120)

ge120

Tram

andbu

spun

ctualityrate

11988022

ge75

[7075)

[6570)

[6065)

lt60

Averageo

peratin

gspeeddu

ringpeak

hours11988023

kmh

ge19

[1719)

[1517)

[1315)

lt13

Tram

andbu

saccidentm

ortality

11988024

Passm

illionkm

lt003

[0030035)

[0035004)

[0040045)

[0045005)

Publictransportp

assenger

satisfaction

11988025

ge80

[7580)

[7075)

[6570)

lt65

Publictransportcom

plaint

hand

lingrate

11988026

ge80

[7080)

[6070)

[5060)

lt50


Installationrateof

electro

nico

n-bo

ardpo

sitioning

term

inal

11988031

ge95

[8595)

[7585)

[6575)

lt65

Electro

nicp

aymentcarduser

ate11988032

ge70

[6070)

[5060)

[4050)

lt40

Coverageo

fincom

ingvehicle


ge75

[5075)

[3050)

[2030)

lt20

Susta

inable

developm

entlevel

1198804

Percentage

ofgreenpu


ge60

[5060)

[4050)

[3040

)lt30

Docking

rateof

busa

ndtram

durin

gnight11988042

ge90

[8090)

[7080)

[6070)

lt60

Governm

entsup

port

level1198805

Availabilityof

subsidyforp

ublic

transporto

peratio

n11988051

ge75

[5075)

[4050)

[2040

)lt20

Com

pleted

egreeo

frelated

policieslawsandregu

lations

11988052

Level1

Level2

Level3

Level4

Level5

Socialbenefit

level1198806

Num

bero

ftrip

sbypu

blictransportp

ercapitaperd

ay11988061

Times

ge10

4[09

104)

[07709)

[063077)

lt063

Mod

elshareo

fpub


ge60

[5060)

[4050)

[3040

)lt30

Transit-orie

nted

operationrateof

urban-ruralp

assenger

transportlines

11988063

ge85

[7585)

[6575)

[5565)

lt55



13 11988014 and 119880

15are as follows

11988013

=119897119887119897

119871

11988014

=

119899119901119895

119873119895

11988015

=119899119887119887119904

119873119887119904

(1)



119895






21) tram and bus



24) public




21

is as follows

11988021

=

sum 119899119901

sum 119899119903119901

(2)








33) Its


11988031

=119899V119905V

119873Vtimes 100

11988032

=119901119890119888

119901times 100

11988033

=

119899119887119891

119873119887119904

times 100

(3)












41is as follows

11988041

=119899V119905V

119873Vtimes 100 (4)




51) and formulation



51in this


11988051

=119872119905119904

119872119901119904

times 100 (5)







62)




63is as follows

11988063

=

119899119901119906119903

119873119906119903

times 100 (6)

where 119899119901119906119903


119906119903










119880119905

= 1198801199051

1198801199052

119880119905119899

(7)


119905119894with respect to 119880






1199081199052

119908119905119899








119895


119895


119895


119895




1199081

[02411 03547 01078 00961 0067 01333]

1199082

[01011 01719 02105 01887 0225 01028]

1199083

[04773 02958 02269]

1199084

[06389 03611]1199085

[06574 03426]

1199086

[04352 03686 01962]



1198811 1198812 1198813 1198814 1198815 in which 119881

119894(119894 = 1 2 3 4 5) means the 119894th

grade



119903 (119894) =

1 119909 (119894) lt 119886

119887 minus 119909 (119894)

119887 minus 119886 119886 le 119909 (119894) lt 119887

0 119909 (119894) ge 119887

(8)



119903 (119894) =

0 119909 (119894) lt 119886

119909 (119894) minus 119886

119887 minus 119886 119886 le 119909 (119894) lt 119887

1 119909 (119894) ge 119887

(9)




119905119894= 1199031199051198941

1199031199051198942

1199031199051198945

119894 =

1 2 119899 in which 119903119905119894119895


119905



119905

119877119905119899times5

=[[

[

1199031015840

1199051198941sdot sdot sdot 1199031015840

1199051198945

d

1199031015840

1199051198991sdot sdot sdot 1199031015840

1199051198995

]]

]

(10)


119905and the fuzzy


119905 which is

denoted as follows

119880119905

= 119908119905

times 119877119905

= (1198801199051

1198801199052

1198801199055

) (11)



119876 = [100 80 70 60 40] (12)


119878 = 119880 lowast 119876119879

(13)

4 Case Study











1 1198772 1198773 1198774 1198775


1198771

=

[[[[[[[

[

0 0 0094 05 0406

0 0 022 05 028

0 033 05 017 0

0 0 0167 05 0333

0 0075 05 0425 0

0 0284 05 0216 0

]]]]]]]

]

1198772

=

[[[[[[[

[

0 0 005 05 045

0 0 0 0313 0687

0 0425 05 0075 0

0 03 05 02 0

05 05 0 0 0

0526 0474 0 0 0

]]]]]]]

]




1198773

= [

[

0 0 0 0526 0474

0 0 05 05 0

0 0 0 0 1

]

]

1198774

= [0 0 0 0195 0805

0844 0156 0 0 0]

1198775

= [02 05 03 0 0

01 02 06 01 0]

1198776

= [

[

0 0 0 0448 0552

0 0425 05 0075 0

0475 05 0025 0 0

]

]

(14)








5 Conclusions






Acknowledgments


References





























Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in





13 11988014 and 119880

15are as follows

11988013

=119897119887119897

119871

11988014

=

119899119901119895

119873119895

11988015

=119899119887119887119904

119873119887119904

(1)



119895






21) tram and bus



24) public




21

is as follows

11988021

=

sum 119899119901

sum 119899119903119901

(2)








33) Its


11988031

=119899V119905V

119873Vtimes 100

11988032

=119901119890119888

119901times 100

11988033

=

119899119887119891

119873119887119904

times 100

(3)












41is as follows

11988041

=119899V119905V

119873Vtimes 100 (4)




51) and formulation



51in this


11988051

=119872119905119904

119872119901119904

times 100 (5)







62)




63is as follows

11988063

=

119899119901119906119903

119873119906119903

times 100 (6)

where 119899119901119906119903


119906119903










119880119905

= 1198801199051

1198801199052

119880119905119899

(7)


119905119894with respect to 119880






1199081199052

119908119905119899








119895


119895


119895


119895




1199081

[02411 03547 01078 00961 0067 01333]

1199082

[01011 01719 02105 01887 0225 01028]

1199083

[04773 02958 02269]

1199084

[06389 03611]1199085

[06574 03426]

1199086

[04352 03686 01962]



1198811 1198812 1198813 1198814 1198815 in which 119881

119894(119894 = 1 2 3 4 5) means the 119894th

grade



119903 (119894) =

1 119909 (119894) lt 119886

119887 minus 119909 (119894)

119887 minus 119886 119886 le 119909 (119894) lt 119887

0 119909 (119894) ge 119887

(8)



119903 (119894) =

0 119909 (119894) lt 119886

119909 (119894) minus 119886

119887 minus 119886 119886 le 119909 (119894) lt 119887

1 119909 (119894) ge 119887

(9)




119905119894= 1199031199051198941

1199031199051198942

1199031199051198945

119894 =

1 2 119899 in which 119903119905119894119895


119905



119905

119877119905119899times5

=[[

[

1199031015840

1199051198941sdot sdot sdot 1199031015840

1199051198945

d

1199031015840

1199051198991sdot sdot sdot 1199031015840

1199051198995

]]

]

(10)


119905and the fuzzy


119905 which is

denoted as follows

119880119905

= 119908119905

times 119877119905

= (1198801199051

1198801199052

1198801199055

) (11)



119876 = [100 80 70 60 40] (12)


119878 = 119880 lowast 119876119879

(13)

4 Case Study











1 1198772 1198773 1198774 1198775


1198771

=

[[[[[[[

[

0 0 0094 05 0406

0 0 022 05 028

0 033 05 017 0

0 0 0167 05 0333

0 0075 05 0425 0

0 0284 05 0216 0

]]]]]]]

]

1198772

=

[[[[[[[

[

0 0 005 05 045

0 0 0 0313 0687

0 0425 05 0075 0

0 03 05 02 0

05 05 0 0 0

0526 0474 0 0 0

]]]]]]]

]




1198773

= [

[

0 0 0 0526 0474

0 0 05 05 0

0 0 0 0 1

]

]

1198774

= [0 0 0 0195 0805

0844 0156 0 0 0]

1198775

= [02 05 03 0 0

01 02 06 01 0]

1198776

= [

[

0 0 0 0448 0552

0 0425 05 0075 0

0475 05 0025 0 0

]

]

(14)








5 Conclusions






Acknowledgments


References





























Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in











119880119905

= 1198801199051

1198801199052

119880119905119899

(7)


119905119894with respect to 119880






1199081199052

119908119905119899








119895


119895


119895


119895




1199081

[02411 03547 01078 00961 0067 01333]

1199082

[01011 01719 02105 01887 0225 01028]

1199083

[04773 02958 02269]

1199084

[06389 03611]1199085

[06574 03426]

1199086

[04352 03686 01962]



1198811 1198812 1198813 1198814 1198815 in which 119881

119894(119894 = 1 2 3 4 5) means the 119894th

grade



119903 (119894) =

1 119909 (119894) lt 119886

119887 minus 119909 (119894)

119887 minus 119886 119886 le 119909 (119894) lt 119887

0 119909 (119894) ge 119887

(8)



119903 (119894) =

0 119909 (119894) lt 119886

119909 (119894) minus 119886

119887 minus 119886 119886 le 119909 (119894) lt 119887

1 119909 (119894) ge 119887

(9)




119905119894= 1199031199051198941

1199031199051198942

1199031199051198945

119894 =

1 2 119899 in which 119903119905119894119895


119905



119905

119877119905119899times5

=[[

[

1199031015840

1199051198941sdot sdot sdot 1199031015840

1199051198945

d

1199031015840

1199051198991sdot sdot sdot 1199031015840

1199051198995

]]

]

(10)


119905and the fuzzy


119905 which is

denoted as follows

119880119905

= 119908119905

times 119877119905

= (1198801199051

1198801199052

1198801199055

) (11)



119876 = [100 80 70 60 40] (12)


119878 = 119880 lowast 119876119879

(13)

4 Case Study











1 1198772 1198773 1198774 1198775


1198771

=

[[[[[[[

[

0 0 0094 05 0406

0 0 022 05 028

0 033 05 017 0

0 0 0167 05 0333

0 0075 05 0425 0

0 0284 05 0216 0

]]]]]]]

]

1198772

=

[[[[[[[

[

0 0 005 05 045

0 0 0 0313 0687

0 0425 05 0075 0

0 03 05 02 0

05 05 0 0 0

0526 0474 0 0 0

]]]]]]]

]




1198773

= [

[

0 0 0 0526 0474

0 0 05 05 0

0 0 0 0 1

]

]

1198774

= [0 0 0 0195 0805

0844 0156 0 0 0]

1198775

= [02 05 03 0 0

01 02 06 01 0]

1198776

= [

[

0 0 0 0448 0552

0 0425 05 0075 0

0475 05 0025 0 0

]

]

(14)








5 Conclusions






Acknowledgments


References





























Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in






119905119894= 1199031199051198941

1199031199051198942

1199031199051198945

119894 =

1 2 119899 in which 119903119905119894119895


119905



119905

119877119905119899times5

=[[

[

1199031015840

1199051198941sdot sdot sdot 1199031015840

1199051198945

d

1199031015840

1199051198991sdot sdot sdot 1199031015840

1199051198995

]]

]

(10)


119905and the fuzzy


119905 which is

denoted as follows

119880119905

= 119908119905

times 119877119905

= (1198801199051

1198801199052

1198801199055

) (11)



119876 = [100 80 70 60 40] (12)


119878 = 119880 lowast 119876119879

(13)

4 Case Study











1 1198772 1198773 1198774 1198775


1198771

=

[[[[[[[

[

0 0 0094 05 0406

0 0 022 05 028

0 033 05 017 0

0 0 0167 05 0333

0 0075 05 0425 0

0 0284 05 0216 0

]]]]]]]

]

1198772

=

[[[[[[[

[

0 0 005 05 045

0 0 0 0313 0687

0 0425 05 0075 0

0 03 05 02 0

05 05 0 0 0

0526 0474 0 0 0

]]]]]]]

]




1198773

= [

[

0 0 0 0526 0474

0 0 05 05 0

0 0 0 0 1

]

]

1198774

= [0 0 0 0195 0805

0844 0156 0 0 0]

1198775

= [02 05 03 0 0

01 02 06 01 0]

1198776

= [

[

0 0 0 0448 0552

0 0425 05 0075 0

0475 05 0025 0 0

]

]

(14)








5 Conclusions






Acknowledgments


References





























Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in






1198773

= [

[

0 0 0 0526 0474

0 0 05 05 0

0 0 0 0 1

]

]

1198774

= [0 0 0 0195 0805

0844 0156 0 0 0]

1198775

= [02 05 03 0 0

01 02 06 01 0]

1198776

= [

[

0 0 0 0448 0552

0 0425 05 0075 0

0475 05 0025 0 0

]

]

(14)








5 Conclusions






Acknowledgments


References





























Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in







Acknowledgments


References





























Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in










Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in



Research Article Research on Assessment Methods for Urban ...

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