Impacts Analysis towards a Sustainable Urban Public Transport

System

Darwin Aldas

, John Reyes

, Luis Morales

, Pilar Pazmiño

, José Núñez

and Bladimir Toaza

Faculty of Accounting and Auditing, Universidad Técnica de Ambato, Ambato, Tungurahua, Ecuador

Faculty of Engineering Systems, Electronics and Industrial, Universidad Técnica de Ambato,

Ambato, Tungurahua, Ecuador

Faculty of Agricultural Sciences, Universidad Técnica de Ambato, Ambato, Tungurahua, Ecuador

Faculty of Agricultural Sciences and Natural Resources, Universidad Técnica de Cotopaxi, La Maná, Cotopaxi, Ecuador

Keywords: Analytic Hierarchy Process, Sustainable Transport, Transport Model, Sustainability, Super Decisions.

Abstract: Nowadays, both big and small cities look to optimize their urban public transport systems through models

that allow reduction of transfer time and environmental impacts, to create sustainable cities. Thus, cities of

Latin American countries are adapting their public transport systems to energetic sustainability conditions.

This study analyzes the impacts of transport models and chooses the best alternative, considering four cities

with a high urban mobility index and optimal conditions of sustainable development. A review of scientific

literature is conducted and priority criteria, such as traffic, environmental impact, social impact, and

economic impact are established and evaluated via the Analytical Hierarchy Process (AHP) decision making

method. As a result, the AHP model defines the city of Curitiba as the best sustainable transport alternative,

with 31, 8% against 27, 6% of Singapore, 17, 8% of Santiago de Chile and Montreal with 22, 9%. The

proposal uses a four-step transport model: trip generation, trip distribution, mode choice and route

assignment.

1 INTRODUCTION

Transport constitutes an important factor in the

development of society but accelerated urbanization

and demographic growth cause vehicle congestion,

increase in travel time, irregular operation of the

public transport system, among others. Besides,

current transport patterns, based on fossil energy

sources generate negative social, economic, and

environmental impacts (Dalkmann and Sakamoto,

2011).

The traditional focus on the layout of public

transport is centered on static models that assume

users’ instant change of behavior toward changes in

public transport. However, this focus does not offer

a real description of users’ behavior. (Jarboui, et al.,

2013). The dynamic focus, on the other hand,

considers realistic users’ behaviors looking for a

change of paradigm oriented at sustainable transport,

with efficient transport modes and vehicles, and

clean, low-carbon energy sources. This change of

paradigm focuses on three strategies: avoiding long

and unnecessary motorized trips, changing transport

of goods and people to more efficient modes of

transport, and improving the technology and

operational administration of the transport system

(Hidalgo and Huizenga, 2013).

Most developed cities work with the first

strategy, while Latin American cities – that are

mostly at an intermediate level of development –

progress through the third strategy since they still

depend on motorized transport. There exist nine

options to promote urban public sustainable

transport in cities located in developing countries:

road infrastructure, track-based public transport,

road public transport, support of non-motorized

travel modes, technological solutions, sensitivity

awareness campaigns, price establishment

mechanisms, vehicle access restrictions, and land

use control (Pojani and Stead, 2015).

Thus, for example, in a few cities such as Buenos

Aires and Sao Paulo there exists the light rail transit

(LRT), which construction and operation cost is

higher than other alternatives, like conventional

buses. (Pojani and Stead, 2015). Cable cars or

gondolas – with similar characteristics to small or

Aldas, D., Reyes, J., Morales, L., Pazmiño, P., Núñez, J. and Toaza, B.

Impacts Analysis towards a Sustainable Urban Public Transport System.

DOI: 10.5220/0006537700380046

In Proceedings of the 7th International Conference on Operations Research and Enterprise Systems (ICORES 2018), pages 38-46

ISBN: 978-989-758-285-1

medium-sized trams – have become an attractive

proposal of urban public transport in cities like

Medellin in Colombia, and Caracas, in Venezuela,

due to the fact that they provide adequate transport

over mountainous land, rivers, historic and densely

residential areas (Bergerhoff and Perschon, 2013).

When it comes to road public transport, bus rapid

transit (BRT) has been implemented as a new

transport system in cities where the other options are

not available. BRT, which was born in Curitiba, has

set an example for cities like Quito, Bogotá, Pereira,

Sao Paulo, Santiago de Chile, and Guayaquil,

showing to be an efficient and sustainable solution

in congested cities (Jirón, 2013).

The solution to transport problems, and selection

of one or more options – of the nine afore mentioned

– can be analyzed through trips or transport models.

These models are tools that provide a systematic

referential framework to represent how trip demand

changes in response to different presumptions, and

allow evaluation of advantages and disadvantages of

different transport alternatives (Castiglione, et al.,

2015).

Transport modeling includes instruments,

strategies, and solutions that have an influence on

the results of vehicle congestion, times and trip

speeds, which makes it difficult to determine which

the best option is; just focusing on one criterion

limits taking advantage of all these instruments.

Conversely, evaluation of transport model variables,

using multi-criteria decision analysis (MCDA) helps

to find the best option that suit the goal (Nosal and

Solecka, 2014). One of the most known MCDA is

analytic hierarchy process (AHP).

The number of researches using AHP has

increased over the last decade, especially in

mathematical methods, computer science and

management studies. Furthermore, AHP has been

successfully applied in the management of limited

resources, the transportation sector, strategic

planning and in the area of logistics (Emrouznejad

and Marra, 2017). In optimization of the public

transport net, multifactor analysis through AHP

adjusts better since more reasonable and practical

results are attained (Xiaowei, et al., 2010).

The future view is the search of sustainable

transport, which is essential to achieve most – if not

all – of the goals set by the United Nations

Organization for Sustainable Development.

However, climate change debate concentrates on

energy and industrial activity, setting aside transport,

without considering that the latter is responsible of a

fourth of greenhouse gas emissions per year,

globally (United Nations, 2015). In Latin America,

the amount of CO

emissions is around 357

thousand tons per day, being individual transport

vehicles, the ones producing higher amounts than

public transport vehicles (CAF, 2016).

This study proposes selecting a sustainable

transport methodology for an Ecuadorian city,

considering the variables travel time, waiting time,

pollutants emission and noise, technology, system

costs, among others; part of the search for

sustainable transport as an applied case in the city of

Ambato.

2 METHODOLOGY

Conventional multi-criteria decision making

considers both quantitative and qualitative criteria;

there exist methods for the quantitative approaches

and other for the qualitative ones. However, the

problem of this study, about selecting a sustainable

transport methodology, combines quantitative and

qualitative criteria for valuation of the best option.

For this reason, AHP method is used, which allows

handling both approaches. This method, developed

by Thomas L. Saaty in 1980, makes paired

comparisons at a scale implemented by himself. In

the AHP solution, the problem is modeled with a

hierarchy; first, the object is defined, becoming the

highest. Then, the criteria and sub criteria are

established, locating these in the intermediate level.

Afterwards, the alternatives are identified in the

lower level, to finally establish the priorities of each

alternative and choose the best option. (Saaty, 1980).

After the alternatives are compared with each

other in terms of each one of the decision criteria,

the method evaluates each alternative with respect to

each criterion and then multiples that evaluation by

the importance of the criterion. This product is

summed over all the criteria for the particular

alternative to generate the rank of the alternative.

Mathematically:





 











(1)

Where R

is the rank of the i

alternative, a

the actual value of the i

alternative in terms of the

criterion, and w

is the weight or importance of the

criterion (Nguyen, 2014).

The proposed objective in the AHP model of this

research is the selection of the best model of

sustainable urban public transport, based on results

and experiences of other cities.

Impacts Analysis towards a Sustainable Urban Public Transport System

2.1 Criteria

The used criteria for evaluation are gathered through

a review of studies and researches that have

similarities with the use of AHP in urban public

transport. The criteria are grouped into four

categories that are directly related with the objective:

traffic, environmental impact, social impact and

economic impact.

2.1.1 Traffic

This criterion refers to the project variables, based

on passenger demand and operation parameters of

the vehicles. These parameters must look for

optimization of transport service operation. Five sub

criteria are included in this criterion: travel time,

operational speed, waiting time, passenger per

kilometre rate and vehicle occupation rate.

Travel time is the average travel time of a

passenger on public transport (Solecka, 2013).

Operational speed is the average speed between an

origin stop and another destination, including all the

intermediate stops (Soltani, et al., 2013). Waiting

time is the interval between the arrival of a

passenger at the stop, and the moment at which they

get on a bus (Cepeda, 2006). The passenger per

kilometer rate is the relation between transported

passengers and the total number of traveled

kilometers (Soltani, et al., 2013). Vehicle occupation

is the average amount of passengers per vehicle at a

specific period and section (CTS EMBARQ, 2015) .

2.1.2 Environmental Impact

It refers to the impact that the transport project has

on the environment, considering the requirements to

minimize the damaging effects on it, in respect to

nitrogen oxides, sulfur dioxides, hydrocarbons,

carbon oxides. It has four sub criteria: type of fuel,

air contaminant emission, noise emission and fuel

economy.

Type of fuel refers to the source of energy that

public transport uses for functioning, currently

existing five types: gasoline, diesel, natural gas,

hybrid and entirely electric (CTS EMBARQ, 2015).

Air contaminant emissions are produced by public

transport, mostly regulated by the Euro Standards

environmental norm, in respect to the level of carbon

monoxide, hydrocarbons, nitrogen oxide, and

particulate matter (CTS EMBARQ, 2015). Noise

emission produced by transport happens because of

engines and propulsion systems, road coating, tires

and aerodynamic noise of speed that, together,

produce sonorous pollution (Ceballos and Palacio,

2015). Fuel economy is the relation that exists

between the number of traveled kilometers by the

vehicle and the amount of fuel or energy (CTS

EMBARQ, 2015).

2.1.3 Social Impact

It takes into consideration the impact that a project

causes, from a social benefit point of view. In social

impact are included safety and comfort offered by

the transport system, accessibility to people with

Figure 1: Arthur D. Little’ Urban Mobility Index 2.0 (Van Audenhove, et al., 2014).

ICORES 2018 - 7th International Conference on Operations Research and Enterprise Systems

reduced mobility, fare payment, type of bus stop and

the technology inside the fleet.

Safety and comfort refer to the assessment that

users make in relation to the public transport system

(Soltani, et al., 2013). Passenger accessibility is the

combination of elements of the built space that allow

access, movement, and use by disabled people,

existing four cases: stair access, low floor access,

wheelchair ramp access and automatic elevator. Fare

payment refers to charging mechanisms, validation

and distribution of public transport fees, being the

most common access through a token or ticket, fee-

free access, smart card, and direct collection by

operator. The stations or stops are the physically

delimited spaces, where users go on and off, which

can be the center of the road or the sidewalk.

Technology refers to the technological service on

board the vehicle, such as video surveillance

cameras, GPS location, type of information for the

user, Wi-Fi service and others. (CTS EMBARQ,

2015).

2.1.4 Economic Impact

It implies knowing the financial model before the

investment is made, that is, to consider the costs that

the transport system generates and if the expected

annual profitability could be achieved, inside the

expectations. This criterion contains two sub criteria:

operational cost and travel cost.

The operational cost refers to the implementation

and operation cost of public transport, including new

road sections, new stations, purchase and

maintenance of vehicles. Travel cost, on the other

hand, is the fee that the user pays for using public

transport. (Nosal and Solecka, 2014).

2.2 Alternatives

The considered alternatives are from the study

“Future of Urban Mobility” (Van Audenhove, et al.,

2014), that evaluates 84 cities around the world,

classified intro three representative groups; first,

Figure 2: Hierarchy tree.

Sustainable urban public transport model selection.

C1. Traffic

C2. Environmental

impact

C3. Social impact

C4. Economic

impact

C11. Travel time

C12. Operational speed

C13. Waiting time

C14. Passenger per kilometer

C15. Vehicle occupation rate

C21. Type of fuel

C22. Air contaminant emission

C23. Noise emission

C24. Fuel economy

C31. Safety and comfort

C32. Accessibility

C33. Fare payment type

C34. Bus stop

C35. Technology

C41. Operational cost

C42. Travel cost

Singapore

Santiago de Chile

Montreal

Curitiba

Impacts Analysis towards a Sustainable Urban Public Transport System

megacities (40), secondly, big metropolises with a

high gross domestic product (GDP) (24), and the

group of small cities with good environmental

practices (20) via the urban mobility index that

scores, in a 0 to 100 scale, 19 aspects related to the

city’s maturity in terms of its infrastructure, public

transport, performance, pollutant gas emissions,

among others. Hong Kong has the highest score,

58,2 and the lowest belongs to Bagdad with 28,6,

resulting in a global average of 43,9. Nine of the 84

cities are Latin American, as shown Figure 1.

The criteria to be considered for a preliminary

selection of possible alternatives are: the urban

mobility index must be inside the average or above

and the cities must be in the third group. Hence, 19

cities meet the prerequisites, among them Stockholm

at 57,4 and Portland with 37,8 as shown in Table 1.

Table 1: Filtered cities for selection.

Group

Ranking

City

Mobility Index

Above

average

Stockholm

57,4

Amsterdam

57,2

Copenhagen

56,4

Vienna

56,0

Singapore

55,6

Zurich

54,7

Helsinki

53,2

Munich

53,0

Average

Stuttgart

51,9

Hanover

50,1

Brussels

49,7

Frankfurt

48,8

Prague

47,8

Nantes

47,7

Santiago de Chile

47,1

Montreal

45,4

Curitiba

44,0

Dubai

40,6

Portland

37,8

Table 2: Selected cities.

Group

Ranking

City

Mobility Index

Above

average

Singapore

55,6

Average

Santiago de Chile

47,1

Montreal

45,4

Curitiba

44,0

Out of the 19 cities, four with are selected. The

selected cities are: Singapore, Santiago de Chile,

Montreal and Curitiba, as shown in Table 2.

Out of the four cities, three are American and

one is Asian, two are in South America and one in

North America. Singapore is a state city, Santiago is

the capital of Chile, Montreal is a Canadian city and

Curitiba belongs to Brazil.

2.3 The Evaluation Model

The hierarchy built for this study has four levels: in

the first level is the decision objective, in the second

one, the four evaluation criteria, in the third one, the

sub criteria of each criterion – that add up to 16 in

total – and in the last level, the four alternatives.

Figure 2 shows the structure of the hierarchy tree of

this study.

2.4 Prioritization

Prioritization of criteria, in relation to the objective,

is done via paired comparisons based on Saaty’s

table, considering as value judgments the goals

established on the mobility master plan of the city of

Ambato. Likewise, prioritizations of sub criteria, in

relation to each criterion, are done via paired

comparisons based on Saaty’s table, considering as

value judgements the policies set out by the mobility

master plan. The weights of the alternatives, in

relation to each sub criterion, are done via paired

comparisons for qualitative ones, and addition

normalization, for quantitative ones; they have value

judgements according to the reports presented by

transport authorities in each city, such as the Land

Transport Authority (LTA, 2014; 2015a; 2015b;

2016) in Singapore, the Metropolitan Public

Transport Directory (DTPM, 2014; 2015a; 2015b;

2016) in Santiago, the Société de Transport (STM,

2014; 2015) of Montreal and the Urbanização de

Curitiba (URBS, 2015a; 2015b; 2015c; URBS,

2015d) as shown in Table 3.

3 RESULTS

Synthesis of the hierarchical model, done over

SuperDecisions software determines prioritizations

of each criterion, in respect of each alternative, as

shown in Table 4.

The results show that Singapore has 27,6%

priority of being selected, Santiago keeps 17,8%,

Montreal 22,9% and Curitiba 31,8%, becoming the

ICORES 2018 - 7th International Conference on Operations Research and Enterprise Systems

last one the highest percentage, as shown in Figure

The methodological characteristics of the

transportation of the city of Curitiba applied in the

city of Ambato-Ecuador, allow to estimate the traffic

of public transport and also to evaluate the level of

the service of the complete transport network.

Table 3: Weight of the sub criteria for each city.

Sub criteria

Singapore

Santiago de Chile

Montreal

Curitiba

C11. Travel time (min)

19,93

59,2

C12. Operational speed

(km/h)

28,9

20,84

17,9

19,75

C13. Waiting time (min)

9 min

7,5

C14. Passenger per

kilometer (pas/km)

3,601

2,1

3,4

2,19

C15. Vehicle occupation

(%)

63,21

95,5

97,6

71,023

C21. Type of fuel

Diesel

Natural gas, Hybrid

Biodiesel

Biodiesel B100,

Hybrids

C22. Air contaminants

emission

EURO V

EURO III

EURO V

C23. Noise emission

dB(A)

C24. Fuel economy

(km/lit)

2,35

2,4

2,22

2,43

C31. Safety and comfort

9,0

4,3

8,0

5,4

C32. Accessibility

Low floor

Access ramps

Low floor

Braille signs

Access ramps

Fee exemption

Door-to-door buses

for people with

limited mobility

Access ramps

Low floor

Braille signs

Fee exemption

Electric lifting

platforms

Door-to-door buses for

people with limited

mobility

C33. Fare payment type

Onboard,

Smartcard

Onboard, Smartcard

Onboard,

Smartcard

Smartcard, payment at

stop

C34. Bus stop

At the center

of the road

and sidewalk

At sidewalk, with

shelter

At sidewalk, with

shelter

At sidewalk, with

shelter, at the center of

the road

C35. Technology

GPS location

Wi-Fi

Not allowed to travel

with open doors

Surveillance cameras

GPS location

Surveillance

cameras

GPS location

Surveillance cameras

Internet access

USB chargers

GPS location

C41. Operational cost

(USD millions)

1,4

25,9

C42. Travel cost (USD)

0,95

0,98

2,42

1,06

Impacts Analysis towards a Sustainable Urban Public Transport System

Table 4: Final scores.

Sub

criteria

Singapore

Santiago

Montreal

Curitiba

C11

0,092

0,031

0,02

0,047

C12

0,022

0,016

0,014

0,015

C13

0,014

0,016

0,031

0,020

C14

0,007

0,004

0,006

0,004

C15

0,008

0,012

0,013

0,009

C21

0,002

0,006

0,013

C22

0,029

0,006

0,029

C23

0,02

0,019

0,021

0,02

C24

0,003

C31

0,03

0,014

0,027

0,018

C32

0,009

0,029

0,023

0,088

C33

0,005

0,014

C34

0,004

0,002

0,001

0,005

C35

0,004

0,014

0,006

0,029

C41

0,024

0,001

0,024

0,001

C42

0,003

0,001

0,003



0,276

0,178

0,229

0,318

Figure 3: Synthesis of the hierarchical model.

3.1 The Curitiba Model

Curitiba is the capital of Paraná, state of the south

region in Brazil, located at 945 MASL; it has an

extension of 434,967 km

and a population of

3.261.168 inhabitants. During the last 30 years, it

has concentrated on urban planning through its

Directive Plan, made up by six sectorial plans in

areas of social development, transport and mobility,

housing, security and social defense, economic

development and environment.

As part of the transport and mobility sectorial

plan, the Urban Mobility and Integrated Transport

Plan, Planmob, was prepared to establish policies

and guidelines related to urban mobility, with a

projected scenario in 2020; first a diagnosis and

analysis are done, then, structuring of scenarios and

alternatives to, afterwards, set up a preliminary

proposal and lastly, introduce a final proposal. The

estimated demand calculation bases for future

scenarios during plan elaboration were done using

the transport model based on trips, or four-step

model: generation, distribution, assignment and

application.

Generation and travel attraction is the starting

point, for which it is necessary to compile and

possess enough information through investigation

and surveys, for example, the Origin-Destination

survey. Travel distribution is defined through

assembly of Origin-Destination arrays, based on

surveys, which allows adjusting the model to the

observed volumes. In travel assignment, the arrays

are located on a simulation net, to evaluate the

effects of vehicle occupancy, travel delays, road

sections, among others; the arrays must be calibrated

in case they do not adjust to reality. Finally, the

proposed future scenarios model is applied.

4 DISCUSSION

Figure 4 shows that in the criterion traffic, the

alternative with higher prioritization is Singapore, at

36% and below is Curitiba, with 24%, due to the fact

that its public transport system maintains better

circulation frequencies and lower travel time, which

allows satisfying its passenger demand. In the

environmental criterion, the city with higher priority

is Curitiba, at 31%, since its master mobility plan

focuses on sustainability. The social criterion also

predominates for Curitiba, at 46% due to the fact it

looks for integration of disabled people, for which

technology is also required, but it is evident that the

more technology is sought after, a greater

investment is needed. Therefore, in the economic

criterion, Curitiba is in the last place, at 7%, and

Singapore in the first at 45%, since the Singapore

fleet does not have much technology; even the

majority is not disabled people friendly.

Curitiba is the selected alternative; even though

its public transport system is expensive, its transport

model has had good results. Considering the social

criterion, it would dominate over other alternatives,

hence, the idea would be to apply this transport

model in the city of Ambato. As a second option, the

Singapore transport model could be adapted since it

is the one that offers a greater priority to the

ICORES 2018 - 7th International Conference on Operations Research and Enterprise Systems

criterion traffic and, also, is in second place in

respect to the objective.

Figure 4: Sensitivity analysis.

5 CONCLUSIONS AND FURTHER

DEVELOPMENT

The methodologies analyzed in this study

demonstrate that most cities look for progress of

mobility in the environmental field, promoting in

their strategic plans the use of electric massive

transport systems, or with reduced emission of

contaminants. Developed cities such as Copenhagen,

Vienna or Amsterdam even look to apply non-

motorized mobility and, in the worst scenario, they

encourage the use of massive public transport and

reduction of individual motorized transport. On the

other hand, developing cities such as Santiago de

Chile, Curitiba, where this paradigm shift is

difficult, improvement of public transport is sought

after through modeling.

Evaluation of the methodologies of the four

chosen cities through AHP method, considers traffic,

environmental, social and economic criteria,

determining that the best city is Curitiba, getting

31,8%, before Singapore with 27,6%, Santiago with

17,8% and Montreal with 22,9%, even though the

cost of its system is the highest when compared to

the other cities. However, this cost is reflected in its

high social development, in relation to accessibility

of people with reduced mobility to the transport

system. The Curitiba model is four-step, multimodal,

structured by travel generation, travel distribution,

selection of mode of travel, and assignment of routes

in the transport network.

The decision to select the sustainable transport of

this research is the basis for future work in which it

is intended to experiment these results using the

software VISUM 16.0 and VISSIM 10.0. These

systems will allow a complete simulation of the

urban transport network under study to model and

analyze the operation of urban traffic in various

conditions. This includes environmental aspects that

reduce the emission of pollutants that are emitted

into the atmosphere, such as carbon dioxide.

This study considers the different variables involved

in a public transport sustainable system. Especially

in a complex urban topographies such as the city of

Ambato, which is located in the Andes mountains

range when will be of proposing a possible

infrastructure in the development of the system.

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