public transport in rural roads: measures to increase its

Research ArticlePublic Transport in Rural Roads Measures to Increase Its ModalShare in Iran

Alireza Afkham 1 Shahriar Afandizadeh 2 and Ali Naderan 1

1Department of Civil Engineering Sciences and Research Branch Islamic Azad University Tehran Iran2Department of Transportation School of Civil Engineering Iran University of Science and Technology Tehran Iran

Correspondence should be addressed to Shahriar Afandizadeh zargariiustacir

Received 7 November 2021 Accepted 8 December 2021 Published 24 December 2021

Academic Editor Qingyuan Zhu

Copyright copy 2021 Alireza Afkham et al is is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

e supply and demand management of rural public transport has gained an important place in Iran given its decreasing trendover the last decade Accordingly an effective approach is to analyze stakeholdersrsquo opinions in this field to identify the effectivelocal solutions for increasing the share of this transport method e used methodology was to design a mixed questionnaire apart of which included fuzzy pairwise comparison while in its first layer the variables were classified using rotary analysis In theother two sections of the questionnaire the respondents were asked to express their opinions regarding the questions in the formof qualitative and words cloud According to the inquiries made from the users in 20 selected terminals of Iran providing servicesto more than 85 of rural passengers the indicators were weighted and divided into two groups based on the rotary analysis eweighted results obtained from the usersrsquo opinions revealed that the safety dynamics of incentive policies and traffic systemperformance in the rural transport had the highest effects on the micro- and macro-level indicators In the second section basedon the qualitative questions a multivariate linear estimation model of the number of rural passengers was constructed Moreoverin the third section the usersrsquo suggested keywords focused on policy-making travel time optimization quality of services andsafety Both the second and third sections had an acceptable agreement with the pairwise comparisons Given the vast area of Iranand the distance between the population centers in the country the obtained solutions to increase the share of public rural roadtransport included reducing the desirability of travel with private cars in short rural distances through interaction with industrialtowns around metropolises along with providing such areas with special services to attract passengers to rural transport withoccupational goals

1 Introduction

is study aims to seek solutions for mitigating the decliningshare of rural public transport in IR Iran since 2008 and tosuggest measures to attract passengers to this mode of trans-port According to the latest data published by the IranianRoads and Transportation Organization for 2019 the averagenumber of passengers was 18 per bus 14 perminibus and 4 perpassenger car Table 1 presents the number of intrastate andinterstate passengers in terms of vehicle type from2008 to 2019

According to Table 1 the following remarks can bepresented

Road passengers are more likely to choose a minibus forintrastate trips while interstate passengers are more likely to

choose a bus In recent years the popularity of buses andminibuses has declined while passenger cars have main-tained their popularity

From 2008 to 2019 using buses and minibuses for in-terstate and intrastate trips has decreased on a yearly basis Itseems that appropriate policies had been adopted for roadtrips by 2008 however the market share of this mode hasbeen later absorbed by other modes

e number of road passengers is decreasing and it canbe seen that in recent years the attractiveness of roadtransport has decreased

Finally the question arises as how to increase the utilityof road public transport systems It is noteworthy that thedecrease in the total number of public transport passengers

HindawiComplexityVolume 2021 Article ID 3191609 12 pageshttpsdoiorg10115520213191609

may occur for two reasons first a reduction in the numberof intercity passengers due to reduced financial capacity andconsequently a reduction in the general willingness to travelsecondly a shift in the tendency of passengers from usingpublic toward private modes of transport e devel-opment of remedial strategies to increase the modalshare of public transport requires identifying the mainvariables affecting the utility of the public transportsystem is is to be carried out through extensive in-terviews stakeholder surveys information analysis andthe classification of variables using a rotary analysis and afuzzy AHP approach Passengers in all major rural busterminals in the country (ie 20 terminals) accountingfor 85 of total passengers were randomly selected forthe interviews

e fuzzy pairwise comparison was applied due to itsgood adaptability with the data of the study and the way theywere collected e rotary analysis was also performed tocomplete the study using a method based on a programminglanguage that readily makes complex calculations and can besuggested as an experience for future studies on rural roadtransport It is worth noting that the usersrsquo opinions werecollected compared and verified in three different sectionsincluding rotary pairwise comparison qualitative assess-ment and word cloud

e study was completed by fuzzy rotary classifying theopinions words cloud analyzing the usersrsquo behavior con-structing a multivariate linear estimation model of thenumber of rural passengers and identifying an effectivesolution that can remarkably impact the share of rural publictransport

2 Literature Review

Analyzing the factors influencing the choice of transport anddetermining its utility leads to identifying the people who areattracted to each mode of transport and meeting the needs ofeach individual based on the utility of those transportmodes e choice of transport in intercity travels dependson many factors and this diversity is due to the commercialdifferences between different modes of transportation the

heterogeneity of their passengers and using them formodeling and evaluation

When expressing their opinions public transport usersgenerally consider their immediate needs rather than thetotal utility of the transport system Using the previousempirical criteria Hoque et al (2021) [2] indicated thattraffic forecasters used their set of values in expressing theiropinions A goal of inquiries from users is to identify theissues of different parts of a transportation system In thisregard Jafino (2021) [3] sought to identify parts of a networkbased on utilitarianism In this framework two main ideaswere investigated calculation of the transport demand withbalanced weights and balance of users in the network Jafinoet al (2020) [4] stated that the importance of using theopinions of transportation users to support decision-makingis increasing while the principle of balanced distributionresulting from ethical analyses is still applied minimally

e way passengers value the waiting time and the accessquality are among the crucial factors determining the de-sirability of a public transport system Instead of conductinga face-to-face survey of passengers Yap and Cats (2021) [5]investigated the behavior of passengers who denied boardingand their alternative decisionse competitive evaluation ofpublic transport operators from the usersrsquo perspective is ofgreat importance to identify the supply improvementmethods Mo (2021) [6] assessed the competitive approachand a systemrsquos performance from four stakeholdersrsquo per-spectives including automatic vehicle operators publictransportation operators passengers and the transportauthority Introducing the required data and the processingstages Horl and Balac (2021) [7] studied a sample of re-peatable travel demand for Paris and the suburbs to developa general designere are several contradictory approachessuch as the usersrsquo needs against the systemrsquos performanceand goals (eg increasing the spatial coverage and increasingthe frequency) for the redesign of public transport networksWeckstrom (2021) [8] provided a multidimensional navi-gability approach from the usersrsquo perspective

With the development of social media we should in-vestigate whether we can access reliable data through them tomeet the information needs of public transport According to

Table 1 Number of public Rural Road Passengers in Terms of Vehicle Type from 2008 to 2019 (Statistical yearbooks of road transport from2008 to 2019) [1]

YearInter-state passenger (thousand) Intra-state passenger (thousand) Total (thousand)

Bus Minibus Passenger car Bus Minibus Passenger car Bus Minibus Passenger car2008 74075 12004 7107 43901 67923 18945 117976 79927 260522009 80981 12757 7489 52324 73755 20305 133305 86512 277942010 84252 13670 8593 56290 76455 24382 140542 90125 329752011 84268 13366 9568 57675 75020 27057 141943 88386 366252012 79006 11211 8962 51593 68171 26026 130599 79382 349882013 76725 10640 8488 49026 65139 25770 125751 75779 342582014 77239 10136 9226 43600 59173 26176 120839 69309 354022015 75772 8588 9120 39209 52259 26330 114981 60847 354502016 67547 6790 8769 32599 47227 27207 100146 54017 359762017 64240 6334 8507 30137 45407 24323 94377 51741 328302018 62923 5816 7724 29100 39684 21742 92023 45500 294662019 57514 6642 7776 25137 35354 21552 82651 41996 29328

2 Complexity

studies this approach has had good results in some routes buton a large scale like within a country comprehensive datacannot be accessed given the governmental restrictions Salaet al (2021) [9] questioned whether it was possible to extractreliable data on passenger travels from the content of socialmedia (Twitter) to design bus routes in areas around citiese information was tested for a great musical event inBarcelona and an acceptable image of supply distribution wassuggested In a similar way Yao (2021) [10] analyzed theinformation of twits regarding the sleepwake status localevents and planned traffic incidents of each day to describethe traffic of the morning in next day in 53 road segments ofPittsburgh

Despite the unprecedented volume and variety of dis-placement data origin-destination (OD) matrices are stillthe widest tools for organizing and expressing travel de-mand Ballis and Dimitriou (2020) [11] stated that standardODs could not fully demonstrate the factors affecting travelbehavior such as trip interdependency and trip chainingey suggested considering home-based trip chains andconsequently activity schedules in studying personal mo-bility Khan et al (2021) [12] reported increasing the at-tractiveness of public transport as a necessity for sustainablesystems and mentioned a lack of empirical research toanalyze how to do so Santos and Lima (2021) [13] evaluatedthe public transport quality indicators and their perfor-mance concerning the usersrsquo opinions based on a multi-criteria approach

Fournier et al (2021) [14] performed a survey of pas-sengers regarding heterogeneous values which resulted in acomputational model for policy-making in determining thetransportation price Transportation based on manageddemand can potentially raise the desirability of public travelKucharski and Cats (2020) [15] identified a combination ofcompatible trips which remain attractive by replacing travelwith private cars ey achieved a formulation that obtainsoptimum time value among prices delays and dissatisfac-tions Developing and verifying a questionnaire Deb et al(2017) [16] analyzed the acceptance level of fully self-drivingvehicles e outcomes revealed that men and the youthresiding in cities were more open to changes Jokubauskaiteet al (2019) [17] investigated different trips and the weightsallocated to them and found a framework to develop nu-merous trips

Popovic et al (2018) [18] presented a satisfactory roadtransport system in the European Transport Committeebased on the domestic market fair competition the reali-zation of workersrsquo rights the implementation of decar-bonization policies using digital technologies in passengertransport in accordance with the principles of transportsustainable transfers in cities and fare and payment modesAugustin et al (2017) [19] investigated intercity buses inGermany and Italy based on a number of performanceindicators such as the travel companyrsquos development pol-icies the ticket prices the frequency of service per day thetype of vehicles and competitive indicators Solak (2016)[20] evaluated the effects of the rules and policies of sub-urban road transport in Turkey as a platform for attractingmore passengers and they provided a structure to expand

the contribution of public road transport Afandizadeh andSafari (2020) [21] presented a set of models developed usingclustering methods based on departure time

e requirements for the intercity bus system are pre-sented in the TCRP-79 (2019) [22] Report and used as areference the original version of which was published in2002 is report addresses the issue of intercity buses inthree sections e first section deals with the requirementsfor developing intercity bus systems related industries andinvestment issues in this area e second section presents anumber of system improvement strategies in the form ofplanning the establishment of affiliated branches marketingand the development of service facilities smart equipmentand related items e final section involves field studiescarried out in different states to improve the system eInterregional Travel Guide (2016) [23] discusses the topicsrelated to passengers in suburban trips however these topicsare not limited to the road systemis guide is important forproviding a unified structure for developing benchmarksgathering information and providing an analytical tool

Brzezinski et al (2018) [24] analyzed the possibility ofutilizing high-efficiency means of transportation in trans-portation companies as one of the most important ways toachieve a competitive advantage is point is especiallyimportant in the passenger transport services market in largeareas because in addition to the economic dimension thisalso involves a social aspect It should be noted that theirstudy focused on groups of passenger transport vehiclesWang et al (2020) [25] argued that the rapid constructionand development of existing high-speed rail (HSR) lines inChina had increased the convenience of this mode oftransportation and attracted passengers from other modes oftransportation Yan et al (2021) [26] stated that the rapidgrowth in demand for intercity travel had put significantpressure on passenger transport networks in variouscountries Wang et al (2020) [27] evaluated the inevitabletransfer in a multimode public transport network and whileconfirming it they explored the planning and managementfor an efficient transmission network and identified theneeds that would lead to understanding the factors of thesetransfers Paudel (2021) [28] considered the relationshipbetween congestion and the quality of services in trans-portation systems as one of the concerns of citizens plan-ners transportation managers and passengers

3 Methodology

In order for an inquiry the first step is to determine the sizeof the needed sample for meaningful analyses According tothe annual statistics recorded by the Road Maintenance andTransportation Organization of Iran (2019) [29] more than85 of intercity passengers travel through 20 main termi-nals Equation (1) was used to determine the number ofsamples required in the mentioned terminals (Transit Ca-pacity and Quality of Service Manual 2013) [30]

N z21minus α2p(p minus 1)

d2

111386811138681113868111386811138681113868111386811138681113868

111386811138681113868111386811138681113868111386811138681113868 (1)

Complexity 3

where Nis the adequate number of passengers z21minus (α2) is

the normal distribution at the confidence level of α(z21minus (α2) 196 based on the confidence level of 95) P isthe distribution percentage (p 05) and d is the ac-ceptable error (d 05)

In order to analyze the opinions of stakeholders of roadtransport a questionnaire was designed a part of whichrepresented pairwise comparisons while the variables re-quired for rotary analysis were included in its hidden layere questionnaire was given to technical experts officemanagers representatives of the union drivers and pas-sengers of carriers throughout the country and they wereasked to fill it in a given time

In the first section of the questionnaire aimed at thepairwise comparison the respondents were asked to givescores to each of the determined indicators based on thedeveloped questions In the second section of thequestionnaire entitled quality assessment the respon-dents were requested to express their qualitative opin-ions on road transport infrastructures and services toindicate their satisfaction with the system in the intendedsample according to the variables expressed and theseparated provincial socioeconomic data of the NationalStatistics Center of Iran [31] and the Ministry of Roadsand Urban Development of Iran [1 29] a suitablemultivariate linear estimation model of the number ofsuburban passengers can be constructed In the thirdsection the participants were asked to give their solu-tions to increase the share of public road transport inpassenger transportation in the form of general and briefopinions A statistical analysis program adaptable withthe analytic features of Excel (XLSTAT) was employed toanalyze the keywords and the results were displayedusing the word cloud method is method was effectivein identifying the frequency and similarity of opinionsfrom the participantsrsquo responses

Regarding the first section of the questionnaire since thestudied indicators were returned frommicro-level to macro-level and vice versa their direct pairwise comparison in-dicates a linear curve with frequent breaks while paving thepath for a back-analysis erefore in order to classifythe indicators the questions were asked from the par-ticipants in the form of pairwise comparison to identifythe bilinear and hidden effective level and accordinglyperform the ultimate classification through rotaryanalysis (using the R statistical programming language)and introduce the output of the classification as the inputto the pairwise comparison weighting through fuzzyAHP It is worth noting that rotary analysis is a statisticalmethod that uses the studied data in the analysis of thesame data and paves the path for the evaluation of otherdata from the same class concerning their nature at iswhy it is called rotary analysis In the first phase ofclassification the concentration density of respondentson the performance levels of indicators is investigatedAs can be seen in (2) by using the power cosine dis-tribution function the classification of the concentrationof respondents on the performance levels of indicatorscan be shown in Figure 1

f(θ) 2minus 1+1ζΓ2(1 + 1ζ)

π Γ(1 + 2ζ)(1 + cos(θ minus μ))

1ζ (2)

After determining the density of concentration on levelsthe indicators are classified to be weighted regardless of theirperformance levels According to equation (3) using the vonMises density distribution function and based on the con-centration density the classification levels of indicators canalso be determined and displayed Circular statistics in R(2014) [32]

f(θ) 1

2πI0(κ)eκcos(θminus μ)

Ip(κ) 12π

11139462π

0cos pθe

κcos(θ)dθ

(3)

In the next step by performing the fuzzy hierarchicalanalysis the weights of indicators in each class can be de-termined Given the advantages of the fuzzy (AHP) hier-archical analysis in reflecting the expertsrsquo opinions thismethod was employed to weight and analyze the partici-pantsrsquo answers in the form of linguistic preferences fromequal importance to completely more important and withinthree fuzzy spectra of the lower middle and upper limitse participants had to score their opinions from 1 to 9 andfrom 12 to 19 (reverse structure) in the form of pairwisecomparison

Regarding the numerical representation of fuzzy ex-pressions it is suggested that a fuzzy number may beexpressed as a triangle or a trapezoid In the triangular casethe corresponding number is displayed as M (a b c)where a b and c represent the lowest possible value themost probable value and the maximum possible value forthe desired number respectively and the desired numbercan be between a and c e fuzzy hierarchical analysis wasconducted in the study according to the method suggestedby Wang (2008) [33] as follows

Interactive level

Micro levelMacro level

π

2

+ 0

3π

2

π

Figure 1 e classification of indicator levels using cosine powerdistribution

4 Complexity

e first step plotting the hierarchy curveIn anymulticriteria analysis plotting the hierarchy curve

(decision tree) is one of the first and of course importantsteps Because it is the goal after plotting this curve thestructure of the hierarchy of indicators and subindicatorsand the options are clearly defined In principle even beforedesigning a fuzzy AHP questionnaire the decision hierarchyplan must first be determined

e second step defining the fuzzy numbers to makepairwise comparisons

In this stage it is necessary to define the fuzzy numbersthat are needed to make pairwise comparisons so thatexperts can provide their answers accordingly esenumbers are already listed in Table 2

e third step creating the pairwise comparison matrixusing fuzzy numbers

At this step the questionnaires have been provided to theexperts and they have answered them erefore in thisstep the matrix of pairwise comparisons containing fuzzynumbers is prepared

e fourth step calculating matrix S for each row of thepairwise comparison matrix

e S are triangular fuzzy numbers calculated from thefollowing equation

1113957Si 1113944m

j11113957M

jgi

times 1113944n

i11113944

m

j1

1113957Mjgi

⎛⎝ ⎞⎠

minus 1

(4)

in whichM denotes the triangular fuzzy numbers inside thepairwise comparison matrix In fact when calculating thematrix S components of fuzzy numbers are added peer topeer and multiplied by the total inverse fuzzy sum is stepis similar to calculating the normalized weights in the or-dinary AHP but with fuzzy numbers

e fifth step calculating the relative magnitude of SisIn this step Sis are compared with respect to their

magnitude based on the equation (5) and Figure 2

V M2 geM1( 1113857 hgt M1 capM2( 1113857 μM2(d)

1 if m2 gem1

0 if l1 ge u2

l1 minus u2

m2 minus u2( 1113857 minus m1 minus l1( 1113857 otherwise

⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(5)

From the equation above

M2 l2 m2 u2( 1113857 M1 l1 m1 u1( 1113857 (6)

e sixth step calculating the weights of criteria andoptions in pairwise comparison matrices

In this step the unnormalized weight vector is obtainedby finding the lowest value of the calculated Vs in theprevious step

e seventh step calculating the ultimate weight vectorIn the last step the weight vector obtained in the pre-

vious step is normalized to achieve the ultimate weightvector as the goal of fuzzy computations

4 Data Description

e studied data were defined in three sections In the firstsection with the goal of pairwise comparison of indicatorsthe respondents were asked to give scores to each of thedetermined indicators based on the designed questions

(i) Dynamics of incentive policies is variable in-dicates whether the policies considered at themacro-level to develop a public road transportsystem are up-to-date or not

(ii) Traffic performance of the system is variabledenotes the performance of the road transportsystem including its infrastructures and executivetools erefore it involves the performance and

function of some cases such as the qualitative levelof roads terminals buses minibuses and roadtaxis

(iii) System coverage is variable represents thecoverage level of the public road transport fleet bythe whole origin-destination pairs of the country

(iv) System integrity It denotes the function and in-teraction of different modes of public roadtransport and the performance of the related ex-ecutive organizations with each other

(v) Safety It indicates the safety level of the publicroad transport system

(vi) Environment is variable represents the indi-cators associated with the environment especiallyair pollution regarding the road transport system

(vii) Trip time It indicates the condition and quality ofchoosing the public road transport mode con-cerning trip time

(viii) Resting services It indicates the quality of restingservices regarding the public road transport in-frastructures such as terminals and roadhouses

(ix) Smart systems is variable indicates the effect ofusing smart systems in attracting passengers andthe way they are employed in the current conditionof the public road transport system

Complexity 5

In the second section of the questionnaire the qualitativeopinions of the participants on the road transport infra-structures and services were received to identify the level ofsatisfaction with the system

In the third section of the questionnaire the respon-dentsrsquo opinions were obtained in the form of solutions toincrease the share of public road transport in transferring thepassengers

Given the existing limitations the inquiries were madefrom the passengers in four successive days from 2019 to 02-12 to 2019-02-15 e surveys in the West East South andBeyhaghi Terminals of Tehran (the commercial and ad-ministrative center of Iran) were made face-to-faceMeanwhile the coordinated representatives performed thesurveys in the other 20 terminals selected (Tabriz CentralBus Terminal Kaveh Bus Terminal in Isfahan ShahidKalantari Bus Terminal in Karaj Bushehr Bus TerminalImam Reza Bus Terminal in Mashhad Siahat Bus Terminalin Ahvaz Enqelab Bus Terminal in Zahedan Shahid Kar-andish Bus Terminal in Shiraz Azadegan Bus Terminal inQazvin Qom Bus Terminal Shahid Kaviani Bus Terminal inKermanshah Eastern Borujerd Bus Terminal Sari State BusTerminal Persian Gulf Bus Terminal in BandarabbasHamedan Bus Terminal and Yazd Bus Terminal) during thesame period A total of 330 samples including 114 pas-sengers 63 drivers 32 members of passenger unions and 21traffic experts were selected and surveyed Of the partici-pants 45 had BSc Degrees and 29 had MSc or higherdegrees e experts separated by expertise and manage-ment levels were selected such that all levels (from associateto PhD degrees) were covered e passengers were chosenrandomly and the drivers were selected according to theirvehicles and working hours

5 Results and Discussion

is study aims to replace the traditional methods ofattracting passengers to the public road transport systemwith scientific techniques and identify effective solutions toincrease the share of this transportation mode with the aid ofthe usersrsquo opinions It should be noted that the efficiency ofsocial networking services especially on regional and localscales has been recognized based on the studies by Sala et al(2021) [9] and Yao (2021) [10] However given the filteringof such tools as Twitter and Telegram in Iran and the na-tional scale of this study using questionnaires seems to bestill more efficient unless the conditions change e studyby Ballis and Dimitriou (2020) [11] had a similar suggestion

51 Evaluationof the Information regarding theFirst Sectionofthe Questionnaire Pairwise Comparison of the IndicatorsTable 3 lists the classification results of the indicators used inthis study for policy-making in road transport to increase itsshare in micro- and macro-levels using the indicators ef-fective in the desirability of public road transport system andthe power cosine distribution function

e classification of the concentration of respondents onthe performance levels of indicators revealed that they hadequal comparisons in the micro- and macro-levels How-ever regarding the indicators with conflicting levels theyexpressed different opinions proving the performancepower of these indicators (eg safety environment andsystem coverage) It also revealed that the respondents hadproperly separated the micro- and macro-levels and had notpositioned them in one analytical field

After determining the concentration density on levelsthe indicators should be classified to be weighted regardlessof their performance levels According to equation (3) byusing the von Mises density distribution function and basedon the concentration density the levels of indicators weredivided into two groups one with five indicators and theother with four indicators as shown in Table 4 As can beseen in Figure 3 four indicators are grouped and shown bydashes and four other indicators are in another groupshown by dots Another indicator (shown by a solid line)positioned between the two groups is classified in the groupshown by dots given its shorter polar distance with them

Table 2 Fuzzy spectrum corresponding to linguistic preferences

Linguistic preferences Importance Low limit (L) Midline (M) High limit (U)Equal preference 1 1 1 1Preference lower than medium 2 1 2 3Medium preference 3 2 3 4Medium preference to high 4 3 4 5High preference 5 4 5 6High preference to very high 6 5 6 7Very high preference 7 6 7 8Very high preference to completely high 8 7 8 9Completely high preference 9 8 9 10

1

V (M2 ge M1) D

M2

l2 l1 u2 u1m1m2

M1

Figure 2 Pairwise comparison of triangular fuzzy numbers

6 Complexity

In the next step regarding the defined classificationthe weights of indicators in each class were determinedby performing the fuzzy hierarchical analysis Table 5provides the ultimate results of the stakeholdersrsquoopinions

According to the statistics published in the WorldBank Report on Iran (2016) [34] and National StatisticsCenter (2019) [31] the main competitor of public roadtrips is trips by private cars and rail and air transportmethods have no great potential due to their improperinfrastructures in Iran is issue along with the highimportance of safety in trips reported by the users giventhe high rate of road accidents in Iran indicates the

necessity to improve the safety of public trips Moreoveraccording to the Office of Transportation Planning andEconomics (2017) [35] public trips are safer than privateones e delays dissatisfactions and optimum time valueformulation introduced by Kucharski and Cats (2020) [15]are different from the obtained results e reason is thatthe users in Iran pay attention to the high rate of roadaccidents and underestimate the importance of the en-vironment smart systems and trip time which can beexpected from the users in a developing country like IranIt seems that the concern of Iranian users over safetyinfluences important indicators like trip time mentionedin other studies

Table 3 Indicators affecting the utility of the public rural road transport system

Effective indicators Micro-level Macro-levele dynamics of incentive policies System traffic performance System coverage System integrity Safety e environment Time of trip Resting services Smart systems

Table 4 Classification of indicators based on rotational analysis

First category Second categorye dynamics of incentive policies System traffic performanceSystem coverage SafetySystem integrity Time of tripe environment Smart systemsResting services mdash

π

2

+ 0

3π

2

π

Figure 3 Functional classification of indicators for weighting

Complexity 7

52 Evaluation of the Information regarding the Second Sec-tion of the Questionnaire In the second section six ques-tions were asked to evaluate the quality of the current roadtransport infrastructures and services e following pro-vides each question along with the answers given to it

(i) e first question What is your evaluation ofthe status of the countryrsquos roads regardinginfrastructures

Of the participants 51 described the status of thecountryrsquos roads as weak in terms of infrastructures More-over 43 gave a good score and 6 gave an excellent scoreto the road infrastructures of the country Given the un-developed infrastructures of Iran according to the Plan andBudget Organization (2015) [36] the similarity of the usersrsquoopinions with the multidimensional attitude of Weckstrom(2021) [8] and Jafino et al (2020) [4] indicates the lowexpectations of the Iranian users

(ii) e second question What is your evaluation of thestatus of the countryrsquos roads regarding safety

Of the respondents 69 stated that the countryrsquos roadshad weak safety Moreover 26 gave a good score and 5gave an excellent score to the safety of the countryrsquos roadsHorl and Balac (2021) [7] mentioned the role of safety inrepeatable trips which can help identify a solution in thecurrent study

(iii) e third question What is your evaluation of theservices provided by the carriers

Fifty-one percent of the participants described the ser-vices provided by carriers as good In addition 40 gave aweak score and 9 gave an excellent score to the state oftheir services e responses to this question have a goodagreement with the condition of the carriers that provideservices to the users

(iv) e fourth question What is your evaluation of thestatus of passenger terminals regarding their pro-vided services and construction quality

Of the whole participants 61 stated that the passengerterminals had good performance regarding their providedservices and construction quality Furthermore 37 gave aweak score and 2 gave an excellent score to the state of theservices provided by them e relative satisfaction of theusers can indicate the potential to attract more passengers tothe public transport system Mo (2021) [6] mentioned thiscompetitive attitude

(v) e fifth question What is your evaluation of theaccess to passenger terminals

Sixty-nine percent of the respondents described thecondition of access to passenger terminals as good Mean-while 28 gave a weak score and 3 gave an excellent scoreto this variable According to Fournier et al (2021) [14] itcan be realized that the users are relatively satisfied with theaccess costs

(vi) e sixth question In your idea to what extent docarriers have delays

Of the respondents 52 stated that the carriers have agood performance regarding the probable delays However47 gave a weak score and only 1 gave an excellent scoreto this variable of the carriers Although the valuation of thepassengers to the delay time has no conflict with the resultsof Yap and Cats (2021) [5] the Iranian users do not give thedelay in trips the importance that they should due to the lackof fast access systems like subways to most terminals of thecountryis issue is more analyzed in the fourth part of thissection

Based on the questions asked and statistics informationa multivariate linear estimation model of the number ofrural passengers can be constructed is model helpsmeasure the impact of changes in different sectors onpassenger volume in order to apply appropriate strategiesaccordingly

Regarding the bus passenger estimation modelaccording to the variables expressed and the separatedprovincial socio-economic data of the National Statistics

Table 5 Results of weighting the indicators

e first category Weight e second category Weight043 057

Indicator Weight Indicator Weighte dynamics of incentive policies 027 Safety 039Resting services 021 System traffic performance 026System coverage 019 Time of travel 019System integrity 018 Smart systems 016e environment 015 mdash mdash

8 Complexity

Center of Iran [31] and the Ministry of Roads and UrbanDevelopment of Iran [1] [29] the estimated volume of ruralbus passengers is as follows

UBus β1 times v1 minus β2 times v2 + β3 times v3 minus β4 times v4 minus β5 times v5 minus β6 times v6 minus β7 times v7 minus β8 times v8

+ β9 times v9 minus β10 times v10 + β11 times v11 minus β12 times v12 + β13 times v13 + β14 times v14 + β15 times v15

+ β16 times v16 minus β17 times v17 + β18 times v18 + β19 times v19 + Ci + εi

(7)

is model is made using data from 2008 to 2019 eresults of themodel construction and names are presented inTable 6

53 Evaluation of the Stakeholdersrsquo Responses in the WordsCloud Section In the third section of the questionnaire theusers were requested to express their opinions about theshort-term and long-term solutions and programs to in-crease the share of public road transport in the trans-portation of passengers in the form of separate itemsFigure 4 demonstrates the obtained word cloud whichindicates the concentration of the suggestions

e suggested solutions focus on policy-making triptime optimization safety level improvement and quality ofservices e other keywords extracted from the suggestions

can also be seen in the figure e opinions are depictedeither horizontally or vertically given the small space of thefigure e larger thickness of the text for an indicatorrepresents its more repetitions

As can be seen the results of this section agree with thoseof the two previous sections e users preferred theirpersonal benefits to the system as stated by Hoque et al(2021) [2] and the utilitarianism principle of Jafino (2021)[3] is also observed In this section the users paid slightlylower attention to safety and gave more importance tomanagement issues such as trip time and quality of servicese difference between the results of this section indicatesthe importance of the surveying method and the fact that thetype of questions can lead to the answers is can be one ofthe reasons to consider the data of social networks as asupporting factor

Table 6 Results of constructing the bus passenger estimator model in rural trips

Variables name Coefficient t-test Variables Coefficient t-test1Age 313eminus 2 264 11Number of transportation companies 234eminus 5 2762Employment rate 0231 minus 232 12Number of buses 173eminus 2 3453Family size 0103 223 13Bus age 433eminus 3 minus 3234Gender composition 2234 minus 263 14Number of resting complexes 597eminus 5 2435Per capita car ownership 425eminus 2 minus 365 15Freeway and highway length 461eminus 2 3446Level of education 267eminus 5 minus 228 16e length of the arterial pathways 227eminus 4 2237Economic strength of the household 243eminus 2 minus 329 17Waiting time (delay) 483eminus 2 minus 3888Travel expenses 211eminus 3 minus 412 18Access 569eminus 3 4459e purpose of the trip 625eminus 2 375 19Fixed model 037 22310Number of accidents (killed) 178eminus 4 minus 289

Accidents

Demand Management

Tax

Advertisement

Tourism

Subsidized fuel

Welfare Services

Infrastructure

Movement speed

Smart transportation

Safety

Research studies

Fleet renovation

Rules

Penalty

Fleet wear

Culture-making

Quality of services

Statement

Accessibility

Long-term loan

Policy -Making

Investment

Delay

Service disable

Travel Time

Figure 4 Word cloud map for the answers of the respondents to the questionnaire

Complexity 9

54 IntegratedAnalysis of the StakeholdersrsquoAnswers In orderto draw a conclusion from the usersrsquo responses the travelstatus of the passengers in the rural public transport systemduring different months of a year is investigated Figure 5demonstrates the travels of passengers in 2019 May AugustSeptember and November have the highest number ofpublic travels

e least travels have occurred in June due to the be-ginning of Ramadan and October due to the reopening ofthe schools and universities e relative agreement betweenFigures 5 and 6 indicates that the most travels occur insummer and the months with more holidays but the goals oftrips in these months should also be studied

According to Figure 5 in each month on average 12831thousand passengers are transferred by the public transportsystem of the country Meanwhile according to the annualreport of the Road Maintenance and Transportation Or-ganization (2019) a large portion of travels especially onholidays take place with private cars (4 with buses andminibuses and 2 with automobiles) Based on the origin-destination report of the country (2016) most of the travelsby bus have occupational (42) and educational (19)objectives Accordingly of the total monthly travels 5389thousand have occupational objectives A glance at theanswers given to the question concerning the delay in travelsand performance of terminals reveals that while a largeportion of travels happen with occupational objectives theusers have no considerable sensitivity to delays and per-formance of passenger terminals

Moreover according to the data of the geographic in-formation system of industrial towns and areas of Iran(2018) [31] the average distance between industrial townsand cities is 30 km as shown in Figure 7 On the other handalmost 41700 industrial and manufacturing units are activein the industrial towns of the country in which 729thousand people work With an average of 25 workingdays per month there is a potential for 36450 thousandtravels 15 of which have been attracted to public

transport e low share of public business travels fromthe total potential working travels in the country can beattributed to the indifference of existing users to the

12340

14109

11159

1305814107

14789

11319

14441

1280312062 11772 12222

April

May

June

July

August

September

October

Novem

ber

Decem

ber

January

February

March

Number of public Passengers

End

of R

amez

an

Begi

nnin

g of

Ram

ezan

0

2000

4000

6000

8000

10000

12000

14000

16000

Figure 5 e bar graph of the number of public passengers (thousand) in different months of 2019

10

6 6

8

4

6 6 6 65 5

6

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

0

2

4

6

8

10Number of Public holidays

Figure 6 Number of public holidays in each month of 2019

Road Maintenance and Transportation Organization

Iran

Figure 7 Location of industrial towns

10 Complexity

coverage and integrity of the system and the quality of therural road infrastructures

6 Conclusions

e dynamics of incentive policies in the first class and safetyin the second class have greater weights as an indicator ofthe macro-level and an indicator of the interactive levelrespectively which are along each other according to therotary analysis us the weighting results indicate that thedynamics of incentive policies and policy-making with afocus on safety can highly influence the micro- and macro-level indicators to increase the share of public roadtransport

In the first class following the dynamics of incentivepolicies the coverage and integrity of the system have re-spectively greater weights Regarding the comparison withthe opinions of the users in the second section and the 50satisfaction with the infrastructures in this class the usersprioritize development and incentive policies to completethe existing network rather than constructing new roadsAlmost 70 of the respondents have described safety asweak indicating the correct weight of this indicator in thesecond class of the first section of the questionnaire esatisfaction with passenger terminals (61) and with accessto them (69) along with the relative satisfaction with theinfrastructures can indicate the potential to attract morepassengers in the existing conditions e only risk leadingto the undesirability of this method is the strong belief of theusers in the lack of safety in the system is shows theimportance of focusing on making society aware of thehigher safety of public travels compared to private ones aswell as trips with short distances to attract passengers in theshort term

In the word cloud section safety was mentioned aftertrip time and services but there is an acceptable agreementwith the weights obtained in the first section overall eaccess and incentive policies were again emphasized whilethe users still did not pay attention to smart transportationRegarding the delay in trips and satisfaction with carrierssome differences can be observed between the classificationsand opinions of users which is due to the large portion ofbusiness travels and can be more analyzed in future studiese passengers with occupational objectives who travel forwork have a small share among the total intercity pas-sengers including public and private transport Meanwhilethis small share makes up 40 of the public travels of thecountry is is the reason for the lower attention of Iranianusers to delays and the role of passenger terminals in in-creasing the desirability of rural public road travels

By increasing the costs of business travels with privatecars in short rural distances through interactions with in-dustrial towns and providing these areas with special ser-vices the finances of public transport can be improved andthe potential to make the number of rural public travels sixtimes larger can be realized Establishing carriers in in-dustrial towns and encouraging their workers to use publictransport creating smart mechanisms to provide specialfacilities in this field (eg timing and ticket applications)

offering special discounts providing VIP services formanagers of workshops and factories to promote using thissystem coordination with managers of towns in macro-levels to impose restrictions on the passage of private carsie increasing the performance costs of this system are allappropriate solutions that further activate the public ruraltransport system in this field and effectively increase publictravels

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

References

[1] R Maintenance and Transportation Organization ldquoRoadmaintenance and transportation organizationrdquo StatisticalYearbooks of Road Transport from 2008 to 2019 Ministry ofRoad and Urban Development I R Of Iran 2019 httpwwwrmtoir

[2] J M Hoque G D Erhardt D Schmitt M Chen andM Wachs ldquoEstimating the uncertainty of traffic forecastsfrom their historical accuracyrdquo Transportation Research PartA Policy and Practice vol 147 pp 339ndash349 2021

[3] B A Jafino ldquoAn equity-based transport network criticalityanalysisrdquo Transportation Research Part A Policy and Practicevol 144 pp 204ndash221 2021

[4] B A Jafino J Kwakkel and A Verbraeck ldquoTransport net-work criticality metrics a comparative analysis and aguideline for selectionrdquo Transport Reviews vol 40 no 2pp 241ndash264 2020

[5] M Yap and O Cats ldquoTaking the path less travelled valuationof denied boarding in crowded public transport systemsrdquoTransportation Research Part A Policy and Practice vol 147pp 1ndash13 2021

[6] B Mo Z Cao H Zhang Y Shen and J Zhao ldquoCompetitionbetween shared autonomous vehicles and public transit a casestudy in Singaporerdquo Transportation Research Part CEmerging Technologies vol 127 Article ID 103058 2021

[7] S Horl and M Balac ldquoSynthetic population and travel de-mand for Paris and Ile-de-France based on open and publiclyavailable datardquo Transportation Research Part C vol 130Article ID 103291 2021

[8] C Weckstrom M N Mladenovic R Kujala and J SaramakildquoNavigability assessment of large-scale redesigns in ninepublic transport networks open timetable data approachrdquoTransportation Research Part A Policy and Practice vol 147pp 212ndash229 2021

[9] L Sala S Wright C Cottrill and E Flores-Sola ldquoGeneratingdemand responsive bus routes from social network dataanalysisrdquo Transportation Research Part C Emerging Tech-nologies vol 128 Article ID 103194 2021

[10] W Yao and S Qian ldquoFrom Twitter to traffic predictor next-day morning traffic prediction using social media datardquoTransportation Research Part C Emerging Technologiesvol 124 Article ID 102938 2021

Complexity 11

[11] H Ballis and L Dimitriou ldquoRevealing personal activitiesschedules from synthesizing multi-period origin-destinationmatricesrdquo Transportation Research Part B Methodologicalvol 139 pp 224ndash258 2020

[12] J Khan R Hrelja and F Pettersson-Lofstedt ldquoIncreasingpublic transport patronage - an analysis of planning principlesand public transport governance in Swedish regions with thehighest growth in ridershiprdquo Case Studies on Transport Policyvol 9 no 1 pp 260ndash270 2021

[13] J B d Santos and J P Lima ldquoQuality of public transportationbased on the multi-criteria approach and from the perspectiveof userrsquos satisfaction level a case study in a Brazilian cityrdquoCase Studies on Transport Policy vol 9 no 3 pp 1233ndash12442021

[14] N Fournier E Christofa and E J Gonzales ldquoA continuousmodel for coordinated pricing of mixed access modes totransitrdquo Transportation Research Part C Emerging Technol-ogies vol 128 Article ID 103208 2021

[15] R Kucharski and O Cats ldquoExact matching of attractiveshared rides (ExMAS) for system-wide strategic evaluationsrdquoTransportation Research Part B Methodological vol 139pp 285ndash310 2020

[16] S Deb L Strawderman D W Carruth J DuBien B Smithand T M Garrison ldquoDevelopment and validation of aquestionnaire to assess pedestrian receptivity toward fullyautonomous vehiclesrdquo Transportation Research Part CEmerging Technologies vol 84 pp 178ndash195 2017

[17] S Jokubauskaite R Hossinger F Aschauer et al ldquoAdvancedcontinuous-discrete model for joint time-use expenditure andmode choice estimationrdquo Transportation Research Part BMethodological vol 129 pp 397ndash421 2019

[18] V D Popovic P Gladovic M Milicic and M StankovicldquoMethodology of selecting optimal fare system for publictransport of passengersrdquo Promet - Traffic amp Transportationvol 30 no 5 pp 539ndash547 2018

[19] R Grimaldi K Augustin and P Beria ldquoIntercity coachliberalisation e cases of Germany and Italyrdquo Trans-portation Research Procedia vol 25 no 3 pp 474ndash490 2017

[20] A O Solak ldquoRegulations in scheduled intercity coachtransport sector in Turkeyrdquo International Journal of Eco-nomics and Finance vol 8 no 8 p 33 2016

[21] S Afandizadeh Zargari and F Safari ldquoUsing clusteringmethods in multinomial logit model for departure timechoicerdquo Journal of Advanced Transportation vol 2020pp 1ndash12 2020

[22] Transportation research board and National research councilEffective Approaches to Meeting Rural Intercity Bus Trans-portation Needs TCRP REPORT 79 Transportation ResearchBoard National Research Council Italy 2019

[23] Transportation research board Interregional Travel TRBPublications Washington DC 2016

[24] M Brzezinski M Kijek P Owczarek K GłodowskaJ Zelkowski and P Bartosiak ldquoAspects of improvement inexploitation process of passenger means of transportrdquo Journalof Advanced Transportation vol 2018 pp 1ndash13 2018

[25] B Wang S Ni F Jin and Z Huang ldquoAn optimizationmethod of multiclass price railway passenger transportticket allocation under high passenger demandrdquo Journal ofAdvanced Transportation vol 2020 Article ID 886011515 pages 2020

[26] H Yan X Zhang and X Wang ldquoHierarchical passenger hublocation problem in a megaregion area considering serviceavailabilityrdquo Promet - Traffic amp Transportation vol 33 no 2pp 247ndash258 2021

[27] W Wang Y Wang G H d A Correia and Y Chen ldquoAnetwork-based model of passenger transfer flow between busand metro an application to the public transport system ofbeijingrdquo Journal of Advanced Transportation vol 2020pp 1ndash12 2020

[28] J Paudel ldquoBus ridership and service reliability the case ofpublic transportation in Western Massachusettsrdquo TransportPolicy vol 100 pp 98ndash107 2021

[29] R Maintenance and Transportation Organization RoadTransport Traffic Census Yearbook 2019 Management ReportsSection Road Maintenance and Transportation OrganizationMinistry of Road and Urban Development IR Of Iran 2019httpwwwrmtoir

[30] National Academies of Sciences Engineering MedicineldquoTransit capacity and quality of service manual third editionrdquoTransit Capacity and Quality of Service Manual e NationalAcademies Press Washington DC ird Edition 2013

[31] National Statistics Center Results of the General Populationand Housing Census National Statistics Center of Iran Planand Budget Organization Presidency Islamic Republic ofIran Iran 2018 httpwwwamarorgir

[32] A Pewsey M Neuhauser and G D Ruxton Circular Statisticsin R Oxford University Press Oxford United Kingdom 2014

[33] Y-M Wang Y Luo and Z Hua ldquoOn the extent analysismethod for fuzzy AHP and its applicationsrdquo European Journalof Operational Research vol 186 no 2 pp 735ndash747 2008

[34] R Maintenance and Transportation Organization WorldBank Report on Iran Road Maintenance and TransportationOrganization Ministry of Road and Urban Development IROf Iran 2016 httpwwwrmtoir

[35] Office of Transportation Planning and Economics Compre-hensive Plan of the Countryrsquos Transportation ManagementReport Deputy Minister of Transportation Ministry of Roadand Urban Development IR Of Iran 2016 httpswwwmrudir

[36] Detailed Document of the Sixth Economic Social and CulturalDevelopment Plan of the Islamic Republic of Iran Plan andBudget Organization Presidency Islamic Republic of IranPublications of the Management and Planning OrganizationVienna Austria 2015 httpswwwmporgir

12 Complexity

may occur for two reasons first a reduction in the numberof intercity passengers due to reduced financial capacity andconsequently a reduction in the general willingness to travelsecondly a shift in the tendency of passengers from usingpublic toward private modes of transport e devel-opment of remedial strategies to increase the modalshare of public transport requires identifying the mainvariables affecting the utility of the public transportsystem is is to be carried out through extensive in-terviews stakeholder surveys information analysis andthe classification of variables using a rotary analysis and afuzzy AHP approach Passengers in all major rural busterminals in the country (ie 20 terminals) accountingfor 85 of total passengers were randomly selected forthe interviews

e fuzzy pairwise comparison was applied due to itsgood adaptability with the data of the study and the way theywere collected e rotary analysis was also performed tocomplete the study using a method based on a programminglanguage that readily makes complex calculations and can besuggested as an experience for future studies on rural roadtransport It is worth noting that the usersrsquo opinions werecollected compared and verified in three different sectionsincluding rotary pairwise comparison qualitative assess-ment and word cloud

e study was completed by fuzzy rotary classifying theopinions words cloud analyzing the usersrsquo behavior con-structing a multivariate linear estimation model of thenumber of rural passengers and identifying an effectivesolution that can remarkably impact the share of rural publictransport

2 Literature Review

Analyzing the factors influencing the choice of transport anddetermining its utility leads to identifying the people who areattracted to each mode of transport and meeting the needs ofeach individual based on the utility of those transportmodes e choice of transport in intercity travels dependson many factors and this diversity is due to the commercialdifferences between different modes of transportation the

heterogeneity of their passengers and using them formodeling and evaluation

When expressing their opinions public transport usersgenerally consider their immediate needs rather than thetotal utility of the transport system Using the previousempirical criteria Hoque et al (2021) [2] indicated thattraffic forecasters used their set of values in expressing theiropinions A goal of inquiries from users is to identify theissues of different parts of a transportation system In thisregard Jafino (2021) [3] sought to identify parts of a networkbased on utilitarianism In this framework two main ideaswere investigated calculation of the transport demand withbalanced weights and balance of users in the network Jafinoet al (2020) [4] stated that the importance of using theopinions of transportation users to support decision-makingis increasing while the principle of balanced distributionresulting from ethical analyses is still applied minimally

e way passengers value the waiting time and the accessquality are among the crucial factors determining the de-sirability of a public transport system Instead of conductinga face-to-face survey of passengers Yap and Cats (2021) [5]investigated the behavior of passengers who denied boardingand their alternative decisionse competitive evaluation ofpublic transport operators from the usersrsquo perspective is ofgreat importance to identify the supply improvementmethods Mo (2021) [6] assessed the competitive approachand a systemrsquos performance from four stakeholdersrsquo per-spectives including automatic vehicle operators publictransportation operators passengers and the transportauthority Introducing the required data and the processingstages Horl and Balac (2021) [7] studied a sample of re-peatable travel demand for Paris and the suburbs to developa general designere are several contradictory approachessuch as the usersrsquo needs against the systemrsquos performanceand goals (eg increasing the spatial coverage and increasingthe frequency) for the redesign of public transport networksWeckstrom (2021) [8] provided a multidimensional navi-gability approach from the usersrsquo perspective

With the development of social media we should in-vestigate whether we can access reliable data through them tomeet the information needs of public transport According to

Table 1 Number of public Rural Road Passengers in Terms of Vehicle Type from 2008 to 2019 (Statistical yearbooks of road transport from2008 to 2019) [1]

YearInter-state passenger (thousand) Intra-state passenger (thousand) Total (thousand)

Bus Minibus Passenger car Bus Minibus Passenger car Bus Minibus Passenger car2008 74075 12004 7107 43901 67923 18945 117976 79927 260522009 80981 12757 7489 52324 73755 20305 133305 86512 277942010 84252 13670 8593 56290 76455 24382 140542 90125 329752011 84268 13366 9568 57675 75020 27057 141943 88386 366252012 79006 11211 8962 51593 68171 26026 130599 79382 349882013 76725 10640 8488 49026 65139 25770 125751 75779 342582014 77239 10136 9226 43600 59173 26176 120839 69309 354022015 75772 8588 9120 39209 52259 26330 114981 60847 354502016 67547 6790 8769 32599 47227 27207 100146 54017 359762017 64240 6334 8507 30137 45407 24323 94377 51741 328302018 62923 5816 7724 29100 39684 21742 92023 45500 294662019 57514 6642 7776 25137 35354 21552 82651 41996 29328

2 Complexity








3 Methodology



d2

111386811138681113868111386811138681113868111386811138681113868

111386811138681113868111386811138681113868111386811138681113868 (1)

Complexity 3






f(θ) 2minus 1+1ζΓ2(1 + 1ζ)


1ζ (2)


f(θ) 1


Ip(κ) 12π

11139462π

0cos pθe

κcos(θ)dθ

(3)



Interactive level


π

2

+ 0

3π

2

π


4 Complexity









1113957Si 1113944m

j11113957M

jgi

times 1113944n

i11113944

m

j1

1113957Mjgi

⎛⎝ ⎞⎠

minus 1

(4)





1 if m2 gem1

0 if l1 ge u2

l1 minus u2


⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(5)


M2 l2 m2 u2( 1113857 M1 l1 m1 u1( 1113857 (6)





4 Data Description












Complexity 5











1

V (M2 ge M1) D

M2

l2 l1 u2 u1m1m2

M1


6 Complexity








π

2

+ 0

3π

2

π


Complexity 7



















8 Complexity





(7)








Accidents

Demand Management

Tax

Advertisement

Tourism

Subsidized fuel

Welfare Services

Infrastructure

Movement speed


Safety

Research studies

Fleet renovation

Rules

Penalty

Fleet wear

Culture-making

Quality of services

Statement

Accessibility

Long-term loan

Policy -Making

Investment

Delay

Service disable

Travel Time


Complexity 9






12340

14109

11159

1305814107

14789

11319

14441

1280312062 11772 12222

April

May

June

July

August

September

October

Novem

ber

Decem

ber

January

February

March


End

of R

amez

an

Begi

nnin

g of

Ram

ezan

0

2000

4000

6000

8000

10000

12000

14000

16000


10

6 6

8

4

6 6 6 65 5

6

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

0

2

4

6

8




Iran


10 Complexity


6 Conclusions






Data Availability




References











Complexity 11



























12 Complexity








3 Methodology



d2

111386811138681113868111386811138681113868111386811138681113868

111386811138681113868111386811138681113868111386811138681113868 (1)

Complexity 3






f(θ) 2minus 1+1ζΓ2(1 + 1ζ)


1ζ (2)


f(θ) 1


Ip(κ) 12π

11139462π

0cos pθe

κcos(θ)dθ

(3)



Interactive level


π

2

+ 0

3π

2

π


4 Complexity









1113957Si 1113944m

j11113957M

jgi

times 1113944n

i11113944

m

j1

1113957Mjgi

⎛⎝ ⎞⎠

minus 1

(4)





1 if m2 gem1

0 if l1 ge u2

l1 minus u2


⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(5)


M2 l2 m2 u2( 1113857 M1 l1 m1 u1( 1113857 (6)





4 Data Description












Complexity 5











1

V (M2 ge M1) D

M2

l2 l1 u2 u1m1m2

M1


6 Complexity








π

2

+ 0

3π

2

π


Complexity 7



















8 Complexity





(7)








Accidents

Demand Management

Tax

Advertisement

Tourism

Subsidized fuel

Welfare Services

Infrastructure

Movement speed


Safety

Research studies

Fleet renovation

Rules

Penalty

Fleet wear

Culture-making

Quality of services

Statement

Accessibility

Long-term loan

Policy -Making

Investment

Delay

Service disable

Travel Time


Complexity 9






12340

14109

11159

1305814107

14789

11319

14441

1280312062 11772 12222

April

May

June

July

August

September

October

Novem

ber

Decem

ber

January

February

March


End

of R

amez

an

Begi

nnin

g of

Ram

ezan

0

2000

4000

6000

8000

10000

12000

14000

16000


10

6 6

8

4

6 6 6 65 5

6

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

0

2

4

6

8




Iran


10 Complexity


6 Conclusions






Data Availability




References











Complexity 11



























12 Complexity






f(θ) 2minus 1+1ζΓ2(1 + 1ζ)


1ζ (2)


f(θ) 1


Ip(κ) 12π

11139462π

0cos pθe

κcos(θ)dθ

(3)



Interactive level


π

2

+ 0

3π

2

π


4 Complexity









1113957Si 1113944m

j11113957M

jgi

times 1113944n

i11113944

m

j1

1113957Mjgi

⎛⎝ ⎞⎠

minus 1

(4)





1 if m2 gem1

0 if l1 ge u2

l1 minus u2


⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(5)


M2 l2 m2 u2( 1113857 M1 l1 m1 u1( 1113857 (6)





4 Data Description












Complexity 5











1

V (M2 ge M1) D

M2

l2 l1 u2 u1m1m2

M1


6 Complexity








π

2

+ 0

3π

2

π


Complexity 7



















8 Complexity





(7)








Accidents

Demand Management

Tax

Advertisement

Tourism

Subsidized fuel

Welfare Services

Infrastructure

Movement speed


Safety

Research studies

Fleet renovation

Rules

Penalty

Fleet wear

Culture-making

Quality of services

Statement

Accessibility

Long-term loan

Policy -Making

Investment

Delay

Service disable

Travel Time


Complexity 9






12340

14109

11159

1305814107

14789

11319

14441

1280312062 11772 12222

April

May

June

July

August

September

October

Novem

ber

Decem

ber

January

February

March


End

of R

amez

an

Begi

nnin

g of

Ram

ezan

0

2000

4000

6000

8000

10000

12000

14000

16000


10

6 6

8

4

6 6 6 65 5

6

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

0

2

4

6

8




Iran


10 Complexity


6 Conclusions






Data Availability




References











Complexity 11



























12 Complexity









1113957Si 1113944m

j11113957M

jgi

times 1113944n

i11113944

m

j1

1113957Mjgi

⎛⎝ ⎞⎠

minus 1

(4)





1 if m2 gem1

0 if l1 ge u2

l1 minus u2


⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(5)


M2 l2 m2 u2( 1113857 M1 l1 m1 u1( 1113857 (6)





4 Data Description












Complexity 5











1

V (M2 ge M1) D

M2

l2 l1 u2 u1m1m2

M1


6 Complexity








π

2

+ 0

3π

2

π


Complexity 7



















8 Complexity





(7)








Accidents

Demand Management

Tax

Advertisement

Tourism

Subsidized fuel

Welfare Services

Infrastructure

Movement speed


Safety

Research studies

Fleet renovation

Rules

Penalty

Fleet wear

Culture-making

Quality of services

Statement

Accessibility

Long-term loan

Policy -Making

Investment

Delay

Service disable

Travel Time


Complexity 9






12340

14109

11159

1305814107

14789

11319

14441

1280312062 11772 12222

April

May

June

July

August

September

October

Novem

ber

Decem

ber

January

February

March


End

of R

amez

an

Begi

nnin

g of

Ram

ezan

0

2000

4000

6000

8000

10000

12000

14000

16000


10

6 6

8

4

6 6 6 65 5

6

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

0

2

4

6

8




Iran


10 Complexity


6 Conclusions






Data Availability




References











Complexity 11



























12 Complexity











1

V (M2 ge M1) D

M2

l2 l1 u2 u1m1m2

M1


6 Complexity








π

2

+ 0

3π

2

π


Complexity 7



















8 Complexity





(7)








Accidents

Demand Management

Tax

Advertisement

Tourism

Subsidized fuel

Welfare Services

Infrastructure

Movement speed


Safety

Research studies

Fleet renovation

Rules

Penalty

Fleet wear

Culture-making

Quality of services

Statement

Accessibility

Long-term loan

Policy -Making

Investment

Delay

Service disable

Travel Time


Complexity 9






12340

14109

11159

1305814107

14789

11319

14441

1280312062 11772 12222

April

May

June

July

August

September

October

Novem

ber

Decem

ber

January

February

March


End

of R

amez

an

Begi

nnin

g of

Ram

ezan

0

2000

4000

6000

8000

10000

12000

14000

16000


10

6 6

8

4

6 6 6 65 5

6

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

0

2

4

6

8




Iran


10 Complexity


6 Conclusions






Data Availability




References











Complexity 11



























12 Complexity








π

2

+ 0

3π

2

π


Complexity 7



















8 Complexity





(7)








Accidents

Demand Management

Tax

Advertisement

Tourism

Subsidized fuel

Welfare Services

Infrastructure

Movement speed


Safety

Research studies

Fleet renovation

Rules

Penalty

Fleet wear

Culture-making

Quality of services

Statement

Accessibility

Long-term loan

Policy -Making

Investment

Delay

Service disable

Travel Time


Complexity 9






12340

14109

11159

1305814107

14789

11319

14441

1280312062 11772 12222

April

May

June

July

August

September

October

Novem

ber

Decem

ber

January

February

March


End

of R

amez

an

Begi

nnin

g of

Ram

ezan

0

2000

4000

6000

8000

10000

12000

14000

16000


10

6 6

8

4

6 6 6 65 5

6

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

0

2

4

6

8




Iran


10 Complexity


6 Conclusions






Data Availability




References











Complexity 11



























12 Complexity



















8 Complexity





(7)








Accidents

Demand Management

Tax

Advertisement

Tourism

Subsidized fuel

Welfare Services

Infrastructure

Movement speed


Safety

Research studies

Fleet renovation

Rules

Penalty

Fleet wear

Culture-making

Quality of services

Statement

Accessibility

Long-term loan

Policy -Making

Investment

Delay

Service disable

Travel Time


Complexity 9






12340

14109

11159

1305814107

14789

11319

14441

1280312062 11772 12222

April

May

June

July

August

September

October

Novem

ber

Decem

ber

January

February

March


End

of R

amez

an

Begi

nnin

g of

Ram

ezan

0

2000

4000

6000

8000

10000

12000

14000

16000


10

6 6

8

4

6 6 6 65 5

6

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

0

2

4

6

8




Iran


10 Complexity


6 Conclusions






Data Availability




References











Complexity 11



























12 Complexity





(7)








Accidents

Demand Management

Tax

Advertisement

Tourism

Subsidized fuel

Welfare Services

Infrastructure

Movement speed


Safety

Research studies

Fleet renovation

Rules

Penalty

Fleet wear

Culture-making

Quality of services

Statement

Accessibility

Long-term loan

Policy -Making

Investment

Delay

Service disable

Travel Time


Complexity 9






12340

14109

11159

1305814107

14789

11319

14441

1280312062 11772 12222

April

May

June

July

August

September

October

Novem

ber

Decem

ber

January

February

March


End

of R

amez

an

Begi

nnin

g of

Ram

ezan

0

2000

4000

6000

8000

10000

12000

14000

16000


10

6 6

8

4

6 6 6 65 5

6

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

0

2

4

6

8




Iran


10 Complexity


6 Conclusions






Data Availability




References











Complexity 11



























12 Complexity






12340

14109

11159

1305814107

14789

11319

14441

1280312062 11772 12222

April

May

June

July

August

September

October

Novem

ber

Decem

ber

January

February

March


End

of R

amez

an

Begi

nnin

g of

Ram

ezan

0

2000

4000

6000

8000

10000

12000

14000

16000


10

6 6

8

4

6 6 6 65 5

6

April

May

June July

Augu

st

Sept

embe

r

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

0

2

4

6

8




Iran


10 Complexity


6 Conclusions






Data Availability




References











Complexity 11



























12 Complexity


6 Conclusions






Data Availability




References











Complexity 11



























12 Complexity



























12 Complexity

public transport in rural roads: measures to increase its

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