Application of an Urban Cargo Transport Mobility Index to ...ijens.org › Vol_16_I_04 › 162704-5858-IJCEE-IJENS.pdf · (SUMI), as well as public policies applied index. It is composed

International Journal of Civil & Environmental Engineering IJCEE-IJENS Vol: 16 No: 04 16

162704-5858-IJCEE-IJENS © August 2016 IJENS I J E N S

Abstract— This article presents the results of an index

application, in which is possible to inform the situation of a

particular region regarding to suitability of cargo vehicles

movability - Urban Cargo Transport Mobility Index (UCTMI).

This index is based on Measures Aggregation Method,

restrictions (Government's responsibility) and their respective

weights (obtained from SPC Methodology), where UCTMI final

values can vary between 0 and 1 (values around zero are

considered unfavorable for cargo vehicle circulation and 1 more

favorable). UCTMI was applied in Niterói city, where part of the

downtown district was selected from this point, blocks and streets

were traveled, applying it. The value obtained by the index was

closer to 0, indicating that the selected area does not have a good

mobility for urban cargo transportation, and measures to reverse

this situation are required.

Index Term— cargo, index, mobility urban.

I. INTRODUCTION

THE rapid population growth in urban areas corroborates the

increase of goods produced and consumed. This fact benefits

economic expansion, which increases the flow of different

transportation modes in all areas of the city, especially in large

urban centers. [1] It demonstrates that the current development

model is based on not shared and planned transportation,

especially when it refers to urban cargo transport, not

efficiently satisfying people's needs, generating large

environmental, social and economic costs [1], [2]. However,

gradually the situation has been changed around the world.

The forerunners countries in this area of study, have been

paying greater attention to issues related to cargo transport

system in urban areas in Europe, and they have served as an

example for developing countries like Brazil [3], [4], [5].

Brazil has raised concerns regarding to its transportation

sector, urban mobility issues and cargo transport logistics.

Cities grew rapidly, but their transportation systems could not

keep up with all this development, resulting in difficulties,

discomforts and impacts to society in general [6]. Despite the

urban mobility issue is already widespread in academia and

C. V. C Rocha is a master degree student at Military Institute of

Engineering, Rio de Janeiro, RJ, Brazil (e-mail:cvrengenharia.com.br)

S. L. Issomura is a master degree student at Military Institute of Engineering, Rio de Janeiro, RJ, Brazil (e-mail: [email protected])

S. M. Pessanha is a master degree student at Military Institute of

Engineering, Rio de Janeiro, RJ, Brazil (e-mail:[email protected])

V. B. G. Campos, is a professor at Military Institute of Engineering, Rio de

Janeiro, RJ, Brazil (e-mail:[email protected]) R. A. M. Bandeira, is a professor at Military Institute of Engineering, Rio

de Janeiro, RJ, Brazil (e-mail:[email protected]).

some policy proposals are in progress, the inclusion of urban

cargo in this theme is still new, requiring development of more

studies involving various aspects of the subject.

The objective of this article was based on the assumptions

above and in the fact that it is important to explore various

points of urban cargo related to urban mobility: to develop a

mobility index for cargo transport in urban areas, aiming to

characterize regions according to suitability of cargo vehicles

mobility, and to apply it to verify its results.

This article is divided in four sections, as follows: section 2

presents general aspects of analysis and synthesis of robust

control systems, as well as defining the SSV and present its

upper limit. Section III presents a review on measures and

restrictions applied to urban freight transport that have been

implemented in some countries. Section IV presents an

application of this technique to a missile control problem, and

comparing the results obtained by Synthesis DJG related to a

controller given in IV. The last section presents the

conclusions.

II. INDEXES AND INDICATOR FOR TRANSPORTATION

Sustainable mobility planning and management is a way to

retrieve urban life quality, to reshape public and green spaces,

instigate equity in displacement and may contribute to

environmental pollution reduction. However, to obtain good

results in planning, it is essential to monitor and evaluate

periodically. Indexes based in indicator can be used as a tool

to monitor regularly the actions implemented [7].

The words “index” and “indicator” are often misunderstood.

Usually they are used wrongly as synonyms, due to superficial

analysis of the question. Indexes serve as "a warning signal to

show the situation of the evaluated system because values are

static, in other words, they give a picture of the present

moment". [8]

Index actually "is the final value from a complete

calculation procedure, including indicators as it variables and

components". Since indicators are employed in pretreatment

of original data, to finally compose index, that can be

considered a higher level of aggregation [8].

Regarding to transportation, indexes and indicators can qualify

and quantify urban mobility and evaluate degree of

sustainability. Urban sustainability indicators are different

from traditional urban indicators. It’s due to the fact that

indicators deal with social, economic and environmental

aspects in an integrated manner, and also have a long-term

vision and balance interests of various participants [9].

Although both are great tools in actions planning and

management, it also represents a challenge because of lack of

Application of an Urban Cargo Transport

Mobility Index to Niterói City Government C. V. C. Rocha, S. L. Issomura, S. M. Pessanha, V.B.G.Campos, R.A.M.Bandeira



data. Most Brazilian cities doesn´t have database [7]. In most

capitals and major cities, the government has no data

collection routines, and their departments do not have

infrastructure or qualified personnel for this task.

In most studies (nationally and internationally) the proposed

indicators are linked to sustainability issues, land use,

movement of people individually and collectively, leaving the

cargo handling aside. Several studies and projects followed

this path, some examples are: Costa (2003), et.al. Banister

(2000), Campos and Ramos (2005), the PROPOLIS project

(Lautso et al., 2004), project SCATTER (Gayda et al. 2005),

project PROSPECTS (Minken et al. 2001), TRANSPLUS

project (CAMPOS, 2006), Mobility 2030 project (WBCSD,

2004).

Since indicators serve a greater purpose (index

development), it is necessary that they undergo analysis by

arithmetical methods or heuristic algorithms, and then get to a

quality or sustainability index. These analyses allow an

examination of particular area conditions, and can even

simulate scenarios related to actions to be taken [10].

Several studies have addressed urban mobility index issue

involving individual vehicles, people and groups, but there are

few that address the theme of Urban Cargo Transport

mobility, making necessary to create an index for it. To be

aware of how to draw up an index, some methods that have

been developed in order to determine an index for urban

mobility and related policies are presented as follow:

A. Campos e Ramos (2005)

The authors proposed a procedure to define a sustainable

mobility index based on Multicriteria Evaluation technique,

called Analytical Hierarchy Process (AHP). The indicators

used were related to land use and occupation and to

transportation system. Its presented in the items below the step

by step method to prepare this index.

Hierarchical structure: indicators were divided into groups

according to the themes: (1) Encouraging the use of public

transport, (2) promoting the use of non-motorized

transportation, (3) Environmental and Safety Comfort, (4)

Transportation and Economic Activity Conjunction, (5)

Automobile use intensity. Regarding to the indicators, each

received the influence signal to the conditions of mobility.

Those with (-) represent a negative influence and the (+)

positive influences.

Model Development: the weights related to the indicators

and to the indicators group was obtained through the

comparison methodology Peer to Peer (Saaty analysis model),

which was applied to a panel of experts. Based on the results

obtained by applying this methodology, we calculate the

consistency index (CI) in order to verify if the results are

consistent.

Consistency grade: based on the result of consistency index

(CI) and randomness index RI (Random Index) which is

tabulated, consistency level (CL) is calculated. If the CL is

greater than 0.1, it is important to re-evaluate the comparison

matrix, or review matrix values, creating a new peer to peer

comparison matrix.

Indicator weight: since the indicators weights were assigned

by evaluators, it may vary. Thus, in order to have a single

value of weight, you should take the average for each

indicator.

Matrix: in order to generate the index, a matrix in which the

rows correspond to an indicator and the columns to the

regions, obtaining a matrix n x r. After this normalization

process is initiated by the method of maximum and minimum

values given by equation 1, in which the variables are:

Ri= criterion value to be normalized;

Rmin e Rmax= criterion maximum and minimum values;

Normalized interval = usually equal to 0,1.

(1)

Index equation: Finally, the equation that defines the value

of sustainable mobility index for each analysis region is given

below. It is important to give the indicators a subject

classification and a signal indicating its influence on mobility

(positively or negatively), in Eq 2.

∑ (∑ )

(2)

Where:

ai: parameter which is equal to 1 or -1, depending on the

indicator. If it contributes positively or negatively for

sustainable mobility

Wi: indicator i weight;

Vi: indicator i normalized value, for region r;

Wt: resulting weight for theme t;

nt: quantity of indicators considered per theme;

m: quantity of theme.

B. Costa (2008)

This methodology aims a sustainable urban mobility index

(SUMI), as well as public policies applied index. It is

composed by 87 indicators, divided into 37 themes, and these

themes are divided into nine domains. This methodology is

considered by many scholars to be adaptable to any urban

reality, since it presents traditional issues and related to urban

mobility, and by other scholars as too long, making it difficult

to capture data and affecting its results.

The indicator evaluation is through a system of weights,

which may qualify them individually or in groups, allowing a

holistic view of each element in the system. In addition to

criteria hierarchy, this method uses a system of weights that

are defined in addition to individual qualification, also at the

sectoral level, for the themes for each dimension of

sustainability.

The author developed an SUMI Indicator Guide, which

features tables and all the details about the index calculation

and the indicators normalization procedure. In a simplified

way the steps of this method are:

1) Definition: description of each SUMI indicator;

2) Data source: necessary data for each specific indicator

calculation;

3) Calculation method: Resume indicator development,

according to the steps of the Guide;



4) Score: non normalized results;

5) Normalization: normalized result in 0 to 1 scale,

according to Guide table.

6) Weights: criterion weights according to specialists’

evaluation.

C. Quezada, Navarrete e Biosca (2013)

The aim of this index is to check how the implemented

policies and public interventions are contributing to reduce

problems caused by urban freight transport. This index was

developed over four years to be applied in Querétaro city

(Mexico) and is the improvement of Urban Transport Index

(UFTI) developed in 2010 by Quezada and Navarrete. To

develop this index, the Referential Análisis del Transporte

Cargo Urban (RATUC) was previously developed, and is

composed by 3 stages: A, B and C.

STAGE A: basic elements determination

1) Structure definition: the chosen structure is presented at

Fig 1, where the input data are actions implemented by the

government.

Fig. 1. Structure definition

2) Problem scale definition: authors classify the problems

from the lowest to the biggest level, ranging from the marginal

effect to seriously affect the urban environment. The grades

are: low (L1), medium low (L2), medium (L3), medium high

(L4), high (L5).

3) Setting the measuring range: refers to the level of

commitment of the government and private institutions to

perform interventions such as: actions and policies to change

the current situation.

STAGE B: Evaluation tool development

1) Group definition: at this stage, taking as reference TUC

practices adopted by the OECD (2003), the authors separate

actions into groups: (1) planned or implemented actions at

national level, (2) planned or implemented actions in local or

regional level, (3) analytical tool for decision making and (4)

implemented actions by the private sector.

2) Indicator identification: as the groups to be evaluated are

already defined, the indicators should be selected. For

RATUC, 34 indicators were employed, being respectively

distributed to the group order displayed in the first stage of

Step B: 13, 12, 4 and 5.

3) Reagents definition: the reagent is a question or

statement that expresses a sign, demonstration or proves a

qualitative value. The reagent kit for the 34 indicators in four

evaluation groups result in 234, respectively distributed on the

measuring scales S1 (16), S2 (37), S3 (55), S4 (78), S5 (48).

Each S (n) symbolizes the complexity of intervention

pattern, S1 is the minimum attention given to TUC and the S5

is more comprehensive interventions that are supported by one

or more coordinated actions already taken.

Assigning reagents nominal weight: the weight of each

reagent is corresponding to its category of intervention, e.g.:

for a reagent classified as S5 intervention state, it is assign a

weight of 5, for S3 the weight is 3. After this, a a diagram

related to STAGES A and B, as shown in Fig 2.

Fig. 2. Diagram qualification from RATUC

STAGE C: Preparation and systematization

RATUC is given by the following equations, but it was

calculated by the authors in computer software that produces

automated graphics. Next, before the equations, the variables

used are presented:

(N j): Group of planned or implemented actions from

national level j to level s i (i = 1.2 .. 5.);

(R j): Group of planned or implemented actions at local or

regional level j to level s i (i = 1.2 .. 5.);

(D j): Group analysis elements for making decision level j s

i (i = 1,2, ..., 5);

(P j): Group of implemented actions by private sector j level

s i (i = 1,2, ..., 5).

Equations 3 through 6 contain reagents applicable to the

four groups tested, belonging to the five stages of the

established method by characterizing measures.

For planned or implemented actions at national level (N):

(4)

Analysis elements for decision making (D):

(5)

Implemented actions by private sector (P):

(6)

Equations 7 and 8 show that RATUC is calculated as

cumulated by level.

(7)

(8)

Index

Sub - indicators

Indicators

Reactive (Data)



Where the level is: L z: Level z (Z = N, R, D, P ).

For this index, the authors choose a scale between 1 and

807 points (sum of weights). The near the index is to 807, the

best are the policies.

D. Other Methods To Index Development

Decision-making for solving a problem involves a six-step

process: (i) problem definition, (ii) criteria identification, (iii)

weighting the criteria as preferably (iv) alternatives exposure,

(v) alternatives evaluation based on criteria, (vi) the

calculation of the alternatives and choose the best result. [10]

The decision-making process, presents difficulties since it

involves various criteria. This is because each criterion

presents a particular importance when compared to each other,

but this amount may vary depending on the decision maker

agent [12]. In this way, it is assigned weight to reflect the

relative importance, and these weights should be assigned

correctly to keep the decision makers preferences.

The assignment of weights allows to identify which factors

should suffer a priority intervention. There are several models

to support decisions that help to define criteria weighting,

models such as AMD, ELECTRE, PROMETHEE, AHP, SPC

etc., but the most discussed in academic and business

environment is the Analytic Hierarchy Process Model (AHP)

[13].

As shown in previous models, each researcher chooses a

way to assign weights to compose his/ her index. Two models

can be applied, as follows:

1)Analytic Hierarchy Process- AHP

AHP method was developed in the 70s by Tomas L. Saaty

and, until today, it has been the multi-criteria analysis method

most widely used due to its flexibility when applied to

decision-making problems. It is based on the problem

decomposition into pieces, which can be further decomposed

again and related [14]. This method is divided into three

stages:

1) Hierarchies Construction: the problem is structured in

hierarchical levels, where the first level is the general purpose,

the second level refers to the criteria and the third, the

alternatives.

2) Setting priorities: this stage is based on the identification

of relationship between objects and situations. To set

priorities, four sub-steps should be followed: trial pairwise,

normalization of trial arrays, average local priorities and

global priorities calculation.

3) Logical consistency degree: provides a measure of made

judgments accuracy or consistency. This value should be less

than or equal to 0.10, if higher, it is required re-evaluate,

because they are considered inconsistent.

2) Analytic Hierarchy Process- AHP

The Structured Pair - wise Comparison method is based on

AHP, and is also known as simplified AHP [15]. This

methodology avoids that the most important factor is

compared to the least important, as shown in following steps:

1) The factors must be submitted to the evaluator. These

factors will be put in priority order;

2) Factor are compared according to the ordered list,

identifying the importance of a factor in relation to each other,

assigning numerical value 1 for "weak" condition and value 2

to "Strong" condition.

3) matrix calculation, similar to AHP, an average and an

average proportion is removed for each factor. The indicator

value is the average proportion.

Based on this section, a methodology proposal for mobility

index for urban cargo transport was developed. Among the

models presented, which served as a pillar to develop the

mobility index for freight urban transport is the Campos and

Ramos (2005). Their model does not address the urban freight,

but the research proposed by these authors is characterized as

simplistic, which is essential for an index. Therefore, in the

next section a review on measures and restrictions are

presented and applied in various locations around the world in

order to mitigate the problems caused by the TUC. Based on

these measures, indicators and sub-indicators for the index are

defined.

III. ACTIONS AND RESTRICTIONS TO URBAN CARGO

TRANSPORT

Actions and restrictions policies are required in a given area

in order to remedy the daily problems, and these policies have

been applied to various problems from ancient Rome

Restriction is any action taken by an authority whose

purpose is divert production course that would directly have

followed if it were not obstructed, and this production also

covers trade and transportation. Since the measures can be

classified as preventive, mitigating and compensatory.

Preventive actions are intended to prevent an impact,

mitigating measures aim to reduce an existing impact as

compensatory or preventive action to an impact that is

inevitable [16] [17] [18].

Solutions for cargo transportation can be classified into five

groups, according to the field of application: (i) access

conditions: it involves space and time constraints; (ii) traffic

management: it is the reorganization of cargo vehicles flow in

locations where the traffic is dense; (iii) land use management:

covers the areas to be used for the TUC, as well as regulations

determination that, directly or indirectly, may affect new

buildings implementation in certain areas or even existing;

(Iv) public infrastructure: this classification refers to

construction of new infrastructure or existing adaptation in

order to facilitate urban logistics; (v) sanctions and

promotions: this classification relates to all other

classifications that may be applied together. The sanctions

require the implementation of certain solutions, since

promotions refer to solutions used by administrators to support

particular practice without imposing it. [19]

In this section, a summary of some authors reporting their

experiences with some cities that have implemented measures

and restrictions for TUC to improve mobility for passenger

cars, people and freight vehicles. As a way to identify some of

these measures and restrictions, a literature survey was

conducted in 17 national and international works (see Table I).



TABLE I

RESEARCHED WORKS

Author Year Thesis

Paper Technical

report

Book Workshop

Action Project

Ogden 1992 x Visser,

Binsbergen e

Nemoto

1999 x

Pivo et.al

2002 x

City Freigth – 2004

2004 x

Dutra 2004 x Emberg

er 2004 x

Munuzuri

2005 x

Sinarimbo

2005 x

Silva 2006 x BESTUF

S 2008 x

C-LIEGE 2010 x Pacote

de Mobilidade de

Portugal

2011 x

Silva 2012 x Leonard

i et.al 2014 x

Holguin- Veras et.al

2014 x

Oliveira 2015 x Megacit

y Logistics

2015 x

A. Public Infrastructure

Ogden (1992), et.al Pivo (2002), Sinarimbo (2005), Silva

(2006), Silva (2012) and Oliveira (2015) address the issues

about road dimensions plus direction imposed on the flow and

correct pathway signaling, as this influences the maneuvers

and vehicle operating time. For deliveries made by non-

motorized modes, they address the issues related to pavement

conditions and urban equipment disposal on the sidewalks that

can be considered obstructions in some cases. Integration with

other transportation modes (even with the public passenger

transport) encapsulated cargo transport are presented by

Visser, Binsbergen (1999), City Freight (2004), Dutra (2004),

Emberger (2004), Muñuzuri (2005) Sinarimbo (2005), et.al

Leonardi (2014) and Oliveira (2015). Regarding to actions that

can be certainly determined by the master plan, such as

location of areas for transshipment, imposition of service

roads for loading and unloading, and number of roads

determination as the region of use are the solutions presented

by the authors Ogden (1992) Visser, Binsberger (1999), PIVO

et.al (2002), Dutra (2004), Muñuzuri (2005), Smith (2006) and

Oliveira (2015).

B. Land Use Management

The authors address issues related to travel generators

poles, as in the case of Pivoet.al (2002) and Muñuzuri (2005),

who report that it is extremely important that these PGVs have

own parking area, Pivoet.al (2002) also considers that

equipment and load ramps for this specific use make easier

loading and unloading. Silva (2006) and Oliveira (2015)

complement the exclusive access conditions for cargo.

Regarding to measures to bays consider that: they should be

spread along the road (preferably in service roads) but must

not exceed 500m from PGV center, another important point

made by some authors is that it is important to know the

dimensions of large vehicles circulating in the region to then

determine the standard measure for the stalls, thus facilitating

these vehicles find points so that they conduct their logistics

operations (OGDEN 1992; VISSER, Binsbergen and Nemoto,

1999; PIVO et.al 2002 ; MUÑUZURI, 2005; SINARIMBO,

2005; SILVA, 2006; SILVA, 2012). Other measures that are

presented by some authors are the property of reversible lanes

for parking (off peak hours), the location of distribution

centers close to the trade and the stipulation of collective

points of delivery and collection of goods (in order to induce

fewer shifts). Some authors emphasize that historic areas are

not conducive to be areas of trade due to the foundation of the

building and paving of roads not withstand the vibrations

generated by large vehicles (OGDEN, 1992; VISSER,

Binsbergen and Nemoto, 1999; PIVO et.al 2002; CITY

FREIGHT, 2004; Dutra, 2004; Emberger, 2004; MUÑUZURI,

2005; SINARIMBO, 2005; PACKET PORTUGAL

MOBILITY, 2011; SILVA, 2012 and OLIVEIRA, 2015).

C. Traffic Management

According to Visser, Binsbergen and Nemoto (1999), et.al

Pivo (2002), City Freight (2004), Dutra (2004), Sinarimbo

(2005) and Leonardi et.al (2014), some actions encourage

traffic management, such as: at the distribution center,

separate goods whose destination are in the same region, then

the delivery is programmed in one-time process, called

collective delivery, and deliveries outside peak hours or night

shifts. Other actions for deliveries are to schedule a time to

receive the goods with the client, and also the monopolization

of deliveries by a single carrier. Another important action

raised by Muñuzuri (2005), Sinarimbo (2005), Packet

Mobility Portugal (2011), et.al Leonardi (2014), Oliveira

(2015), is the electronic load and unload booking, preventing

trucks to circulate in urban centers looking for a place to park.

Visser and Binsbergen Nemoto (1999), Dutra (2004) and

Muñuzuri (2005) on address on the classification of load

zones, including stipulation weight, volume and height to

allow passage in determined route.

D. Sanctions And Promotions

Each author suggests a different measure. It is proposed to

encourage more efficient vehicles (fuel and noise) studies,

urban logistics forums and creation of urban mobility and

master plans integrated to load subject. Other proposed actions

are: road monitoring via camera and that traffic situation is

reported in real time to drivers, which stimulate the

competitiveness of service delivery through certification of

carriers, instigating the carriers to adhere to alternative



vehicles to perform the services, and train their drivers

according to the. Measures such as differentiated collection of

tolls or taxes for companies that carry out logistics services

during off-peak hours, goods tracking are also cited by the

study authors.

D. Conditions of Access

Access conditions addressed by the authors, can be divided

into access to the city center and the stalls. Regarding access

to the city center, Ogden (1992) Visser, Binsbergen and

Nemoto (1999), Pivo et.al (2002), Dutra (2004), Emberger

(2004), Muñuzuri (2005), Sinarimbo (2005) Silva (2006),

Packet Mobility Portugal (2011), Silva (2012), Holguin- Veras

et.al (2014) and Oliveira (2015), point out that tolls and

parking charges stimulate the use of new systems preventing

motor delivery mode and the number of trips. Other measures

mentioned by them are determine specific routes or routes for

freight vehicles, determination of minimum occupancy vehicle

percentage, and also the standardization of vehicle color for a

particular type of goods, so it would be possible to give

preference to the ones that have short shelf life such as meat

and fish. In reference to the stalls access conditions, the

permission for commercial vehicles to park in bays properly

identified, and an intensive monitoring on the parking time,

thus avoiding loading and unloading of not allowed vehicles

or time abuse, avoiding traffic jam or lower flow velocity

(PIVO et .al, 2002; SINARIMBO, 2005; SILVA, 2000; and

SILVA, 2012).

Based on the actions and restrictions found in this

literature review and on the assumption that the government is

the most responsible for mitigating the problems caused by the

TUC, this article proposes the indicators and sub-indicators to

be used as a measure of urban cargo transport mobility. The

proposal of these indicators is presented and discussed in the

following section.

IV ACTIONS AND CONSTRAINTS FOR URBAN

CARGO TRANSPORT

The problems related to urban freight distribution process

are related to various stakeholders: the community, retailers,

logistics providers, manufacturers, carriers and local

authorities. In order to mitigate or solve TUC problems, it is

necessary that all stakeholders contribute positively and

continuously, always focusing on improving urban mobility.

Although their importance to improve mobility in urban

areas, the government owns the greater role: to seek ways to

implement measures and restrictions, and incentives to make it

happen. It is local authorities’ duty to seek measures which

regulate traffic and limit the number of vehicles circulating,

and this should include both the common and cargo traffic.

Examples below show government actions that should be

considered:

1) Adoption of strategies to reduce the use of private

vehicles by improving the public transport system;

2) Electronic panels with information on traffic conditions,

to guide the driver on the route to be used;

3) proper regulation and effective inspection of new

businesses location, avoiding betray a volume of vehicles

which are not appropriate to the roads surrounding the project;

4) regulation with active surveillance of the parking areas;

5) Improvements of roads physical conditions;

6) Regulation and control of constant public works

blocking the tracks;

7) Roads sharing regulations between different types of

users, automobile, cargo vehicles and public transport;

8) Regulatory load and unload operation in night hours in

areas with high traffic density. [20].

Based on the principle that the government should enforce

and stimulate actions in order to mitigate the problems of

urban cargo transport, and based on the literature review in

section 3, indicators are proposed. The actions and restrictions

were considered to be government responsibility, such as

implement and enforce; those will define the proposed

mobility index. Actions and restrictions were selected those

cited in greater quantities by the authors and were related to

the government's actions, resulting in a set of 29 sub-

indicators, which were classified in the indicators were based

on the description given at the beginning of Section 3 (i )

access conditions, (ii) management of traffic, (iii) land use,

(iv) motorized transport and (v) non-motorized transport. The

following is a description of each solution area and its sub-

indicators.

E. Conditions of Access

The result of this indicator will present access restrictions

dimensions, will indicate the ease accesses in some regions of

urban areas. The sub-indicators measure the reduction in

number of vehicles in circulation as well as the use of other

forms of delivery. This indicator is composed from sub-

indicators:

1) loading zone classification;

2) Establishment of minimum density of vehicle

occupancy;

3) monopolization of deliveries;

4) urban toll;

5) Electronic loading and unloading Booking;

F. Traffic Management

This indicator measures aspects related to traffic

management, operational characteristics or information that

minimize and monitor the traffic, thus providing a road

optimization. Thus, the composition proposed for this

indicator:

1) access and bays electronic surveillance;

2) reversible roads for parking and circulation;

3) Transit permission in bus lane;

4) Traffic system information;

5) parking fees for stalls.

6) public and cargo shared transport;

G. Land Use

This indicator measures aspects related to land use

diversity, which is intrinsically related to transportation, as the

occupation of the city influence the traffic generation. Thus, as

a composition of land use management indicator, are

proposed:



1) commercial density;

2) residential density;

3) The distance between the trading area and distribution

center;

4) Enterprises with exclusive parking charge;

5) PGV with exclusive load access;

6) Transshipment in the periphery.

Commercial and residential property density in an area is

proposed to be an indicator easily obtainable, since

commercial records are public, and can perform a visual

count, the same goes for the residential areas. These two

indicators compositions demonstrate the variety of land use

which marks the searched area.

H. Motorized Transport

This indicator allows to identify the points where there is

greater motorization. This enables to study ways to stimulate

flow reduction of vehicles in a region, encouraging other ways

of delivery or setting few points for loading and unloading and

more flexible hours, in order to avoid the increase of traffic

jam. Thus, we propose the following sub-indicators for this

indicator:

1) Stalls along the route;

2) Stalls in service streets;

3) Pavement conditions;

4) corners with suitable angles;

5) Road slope;

6) Road Width;

7) Number of lanes per direction.

I. Non-Motorized Transport

The non-motorized transport infrastructure indicator

measures the conditions offered to freight by walking or

human-powered. The higher is this indicator value, the better

are the conditions of urban mobility because fewer motorized

vehicles will be circulating in various ways, thus avoiding

further congestion, in addition to problems related to the

environment (noise, air pollution, etc.). For this indicator, the

following sub-indicators are proposed:

1) The effective sidewalk width;

2) Number of bays in a 500m radius from PGV;

3) Obstruction on sidewalks;

4) Ramps between sidewalk and road;

5) Regularity of sidewalk paving;

IV. SUB-INDICATORS MEASUREMENT

Indicators can be measured in two ways: numerically

(percentages, ordinals, etc.) or orally, which is considered in

this case as qualitative indicator. Since to the focus of this

article is the definition of a mobility index for TUC, it

proposes actions which may be expressed numerically. The

following sub-indicators are presented:

A. Access Conditions

Loading zone classification: in loco verification of access

restriction sign plates; they can be regarding to time, weight,

volume, height, etc.

Measurement Unit: indicative plates attendance.

Parameter: 1 is considered for signs indicating the access

or parking time for cargo vehicles, 0.5 for sign plate’s

attendance, which indicate weight limit, height or load vehicle

volume, value and 0 for the total absence of sign plates.

Establishment of minimum density of vehicle occupancy:

verify the existence of normative instruction, regulations in the

master plan, mobility plans, or other provision of the

municipality.

Unit of measure: Existence of rules

Parameter: It is considered maximum value of 1 for the

favorable situation and 0 to total absence of any consideration

of the establishment of minimum density of cargo vehicle

occupation to access the city center.

Monopolization of deliveries: check in place with

commercial ventures if the systems deliveries of the

enterprises of the region are carried out by the same company.

Unit of measure: Deliveries made by one company.

Parameter: Consider 1 in case of delivery monopolization

in the same day, 0.5 if it is same suppliers, but delivery is not

in the same day, 0.25 to sites where there is no similar trade

concentration thus having potential for deliveries monopolized

and 0 if there is none of the situations presented.

Urban toll: check in loco if there is toll

Unit: Toll payment

Parameter: It must be admitted a maximum value of 1 for

the region with urban toll, and value of 0 for regions without

toll.

Electronic load and unload booking: check if there are

electronic booking in public areas.

Unit of measure: electronic booking Existence.

Parameter: 1 for electronic booking and 0 if there is none.

B. Traffic Management

Electronic surveillance for bays access: analyze in situ the

camera existence along the segment that control access to

bays.

Unit of measure: Camera existence.

Parameter: 1 if there is at least a camera, and 0 if not.

Tracks reversible to park and circulation: in loco verification

of lanes that can be used for loading and unloading.

Unit of measure: Existence of tracks with reversion to load

vehicles and parking.

Parameter: It is considered a maximum of 1 to segment

where there are reversible tracks and 0 for segment where

there is no reversible range.

Traffic allowed on buses lanes: in loco verification of the

dedicated lanes dedicated for public transport that can be used

at specific times for cargo vehicles.

Unit of measure: reversible lane reversible to cargo

vehicles.

Parameter: 1 if there are reversible lanes and 0 for none.

Traffic information System: verify in loco the existence of

traffic information system in real time.

Unit of measure: information system existence.

Parameter: 1 if there is an information system and 0 for

none.

Public transportation shared with load transport: check in

loco if there is public transportation shared with load

transport.

Unit of measure: Shared transportation existence

Parameter: 1 if there is shared transportation (cargo +

passengers)



Bay parking fees: check in loco if there is any bay parking

fee.

Unit of measure: fee payment requirement.

Parameter: It must be admitted a maximum value of 1 for

the region with the presence of parking fees in bays regardless

of the bay or parking for loading and unloading, and 0 for

nonexistence.

C. Land Use

Commercial density: check in loco, total commercial

ventures range in the segment.

Unit of measure: Percentage of business enterprise range.

Parameter: To determine the commercial range, it must be

admitted the range of commercial enterprises located in the

road segment in question, in meters. Next step: divide it per

road length. Equation 9 will standardize the value within the

working range 0-1.

(9)

Residential Density: check in loco residential range in the

segment length.

Unit of measure: Proportion of residential development

range.

Parameter: To determine residential range, it must be

admitted the residence range in meters, and divide it by the

length of the analyzed route. Equation 10 will standardize the

value within the working range 0-1.

(10)

Distance between trade areas and distribution centers:

Check on the map the distance between commercial and

distribution centers.

Unit of measure: km.

Parameter: It must be admitted to this indicator Eq 11 to

calculate the distance between the trade area:

(11)

Where:

A – Distance between commercial area to city boundary

(Km);

B – Distance between commercial area to distribution

center (Km).

Through this formula the values of the distances are

already standardized in the range from 0 to 1, the scale

adopted,

Parameter: check the demand for exclusive parking charge.

Unit of measure: Ratio of enterprises with exclusive

parking charge.

Parameter: To standardize the amount of the sub-window

on the scale from 0 to 1, should be used to EQ.4.15. It is

considered a minimum value 0 to the lack of projects with

exclusive parking for cargo vehicles and a maximum of 1 to a

location where all enterprises have parking charge.

(12)

PGV with exclusive access for load vehicles: check in

Loco the developments that have exclusive access for load and

plans for land use and occupation.

Unit of measure: PGV ratio that have exclusive access to

load.

Parameter: it is considered a minimum value of 0 for the

absence of PGV with exclusive access to cargo vehicles and a

maximum of 1 to a location where all TGHs have access to

load.

(13)

Transshipment in periphery areas: check in the master plan

the existence of requirement for cargo exclusive access.

Unit of measure: transshipment of existence in periphery

area.

Parameter: it should be considered maximum value 1 for

the existence of transshipment in periphery area and / or

regulation and 0 for failure.

D. Motorized Transport

Stalls along the track (analyzed segment): check in loco

bays for loading and unloading existence along the segment.

Unit of measure: bays existence.

Parameter: it must be admitted the values described below:

1 for loading and unloading specific bays;

0.5 for stalls that are in passenger car parking lanes (there

must be signs indicating);

0.25 for loading and unloading operations carried in

passenger vehicles lanes, no indication of any board;

0 for opposite situations than those presented above.

Stalls in service of streets: check in loco stalls in service

streets.

Unit of measure: bays in service streets.

Parameter: service streets are those which are not trade

accesses or which the flow of people and passenger vehicles

are constant. Usually these streets are perpendicular to

commercial streets, or are located on the back of large

enterprises. It must be admitted maximum value 1 for the

stalls exclusively in service streets, value of 0.5 for bays on

adjacent streets and also in the main and 0 for stalls only on

main streets or no stall nearby.

Conditions floors: analyze in loco the segment pavement

situation.

Unit of measure: regular pavement ratio.


on the scale from 0 to 1, Eq 14 should be used. The maximum

value of 1 is considered for a completely equalized extension

and / or new floor, since the minimum value is 0.

(14)

Corners with appropriate angles: check in loco if corner

angles are suitable (not obtuse or too closed).

Unit of measure: Angles in degrees.

Parameter: It must be admitted value 0 for lower angles 90

degrees and corners having 1 to angle of 90 degrees or greater.

Road slope: check in loco the segment slope.

Measure unit: road slope (analyzed segment) - (%)



Parameter: According to municipal guidelines, there are

the following slope: structural or expressways, main road,

Minor road: 2 to 3% and secondary road, and local bus

corridor: 2%. Thus, it must be admitted as an ideal value

(value 1) to a lower slope or equal to 3%. To determine the

value within the range (0-1) for other inclinations should

calculate Eq 15.

(15)

Road width: check in loco road width.

Measure unit: Meter.

Parameter: To determine the normalized value of the sub-

indicator within the scale from 0 to 1, has the following:

Step 1- determine the ideal road width and minimum width for

the road in question: it should be noted the number of lanes

that exists and width recommended for the rolling lane (width

range is tabulated as standard). According to these values the

following equations should be calculated:

(16)

(17)

Step 2- Values comparison: ,

e o should be compared.

– (18) - 1 is

recommended

– (19) – verify the

conditions:

– (20) - 0;

– (21) – interpolate values

Number of lanes per direction: check in loco the number of

lanes per direction.

Measurement unit: Number of rolling lanes

Parameter: to standardize the number of tracks within the

range from 0 to 1, the following parameters must be adopted:

One-way with 1 band, consider value 0;

one-with 2 or more lanes, consider 1;

Two-way with 1 band, consider value 0;

double hand with two or more lanes, consider 1;

E. Non-Motorized Transport

Free sidewalk width: check in loco sidewalk width, free of

obstacles.

Measurement Unit: Meter.

Parameter: According to Rio de Janeiro urban road design

guidelines, the ideal sidewalk should be divided into 3 bands:

service range (1m), for trees and street furniture; free range

where pedestrians should circulate and the last track is the

access to allotment, this band may or may not exist depending

on the sidewalk total width. Based on these conditions,

depending on the flow of people, the minimum effective width

free of obstacles would 2,15m (minimum commercial areas).

So it must be admitted the value in meters according to the

flow of people on that sidewalk, and the minimum value of

1.50 m free of obstacles, and a maximum of 3,75m value.

Transforming these values to the 0 to 1 range The following

parameters are presented:

For sidewalk width (clearway) greater than or equal to

2,15m is adopted 1;

To sidewalk width (clearway) less than 1.50m, is adopted

value 0;

To sidewalk width (clearway) between 1,50m and 2,15m,

should perform interpolation

Number of bays within 500m from PGV: check in loco the

number of bays in 500m radius from PGV.

Measurement Unit: Stalls within 500m.


on the scale from 0 to 1, should be used Eq 22 When 500m of

two or more TGHs are, should take the average of them.

(22)

Obstruction on sidewalks: check in loco urban equipment

(benches, bus stops, bins), newsstands and shops displaying

goods on the sidewalks.

Measurement Unit: Proportion of obstructions on

sidewalks.


in the range of 0 to 1, should be used to Eq 23. It is considered

a maximum value of 1 for a completely obstructed extent,

since the minimum value is 0.

(23)

Ramps between sidewalk and road: check in loco the

existence of ramps.

Measurement Unit: ramp existence.

Parameter: It is considered that the presence of ramps

between road and sidewalk, is a key factor for deliveries made

on foot or for human propulsion pushchairs. Thus, it must be

admitted a maximum value of 1 for the region with the

presence of ramps from sidewalks and road, and 0 for regions

without ramps.

Sidewalk paving: check in loco the quality of sidewalks

paving.

Measurement unit: Proportion of regularized extension.


in the range of 0 to 1, should be used to Eq 24. It is considered

a maximum value of 1 for a completely equalized extension

and / or new floor, since the minimum value is 0.

(24)

V. DEVELOPMENT AND APPLICATION OF MOBILITY INDEX

A. Analyzed Area

To start the proposed procedure a Niteroi city map was

obtained, through Google maps.

Niteroi city has 133, 916 km² area, being bounded by Sao

Goncalo and Marica cities, and bathed by the waters of

Guanabara bay and Atlantic Ocean. The city is divided into



five regions: east, north, Oceanic, Pendotiba and bay beaches,

comprising 51 districts.

Nowadays, Niteroi city economy is mainly presented in the

tertiary sector, although there are other types of activities in

the city, and is considered one of the best to live in, according

to IBGE estimative, in 2015 the city's population is

approximately 496,696 inhabitants, having a quality of life

index HDI (2010) 0.837.

In every neighborhood there are major streets that support

trades and services, but it is in Center and Icaraí

neighborhoods that concentration is more evident (see figure

3).

Although both districts have many shopping venues as

shown in Figure 3, there is a difference between Icarai and

Central neighborhood, starting with the population density

(inhabitants / km2) (see Figure 4). Icaraí neighborhood has

one of the highest population densities in Niterói city (40001-

1827580 inhabitants / km2) due to large number of residential

buildings, but at the same time has a strong trade, as some

residential buildings have single-story areas intended for trade.

When the streets run through, it is possible to note the

grouping of clothing stores, footwear, optics, restaurants,

aesthetic clinics (there are other services, but what is displayed

on the streets is quoted).

Fig. 3. Niterói economic activities 2003).

Fig. 4. Niterói city population density – hab/km2

Based on this information, Center downtowns was

determined as study area. Figure 5, shows the area enclosed to

study. In this area were selected 16 cross streets (A – P streets)

and 5 longitudinal, (Q, R, S, T, U streets) creating a grid of 41

blocks for analysis (blocks 1-42). The numbering 42-47

correspond to blocks that were considered for the analysis of

street R, since the blocks 48 to 50 were considered for analysis

of street A. The blocks that have crosshatch indicate where are

the PGV's.

Fig. 5. Analyzed area boundaries

Streets name A- Av. Feliciano Sodré

B- R:Dr. Froés da Cruz

C- R: Saldanha Marinho D- Marquês de caxias

E- R: Mal. Deodoro

F- R: São João G- R: São Pedro

H- R: Cel. Gomes Machado

I- Av. Ernani do Amaral Peixoto J- R: da Conceição

K- R: José Clemente

L- R: Aurelino Leal M- R: 15 de Novembro

N- R: Pedro Augusto Nolasco

O- R:Gen. Penha Brasil P- Av. Bagder da Silveira

Q- R: Gen. Andrade Neves

R- Av. Visconde do Rio Branco S- R: Visconde do Uruguai

T- R: Visconde de Itaboraí

U- R: Maestro Feliciano Tolêdo

Centro

Icaraí



B. Indicators and Sub-Indicators Weight Definition

Interviews with 11 cargo transport researchers were

applied in order to determine the degree of importance of each

indicator and their interrelationship. According to the response

of each researcher, it was possible to arrange SPC matrix, and

with the results of each matrix generated by each interview,

get to the final weight for each indicator and sub-indicator,

according to Table II. Observing this table note that the group

that has most relevance to respondents is the land use

indicator, followed by motorized transport indicator.

TABLE II

INDICATORS AND SUB-INDICATORS WEIGHT

Index Weight Sub Weight

Lan

d u

se

0.3

39

Commercial density 0.321

Residential density 0.068

Distance between trade area and

distribution center

0.235

Developments with exclusive parking charge

0.140

PGV with exclusive access to load 0.174

Transshipment in periphery 0.062

Moto

rize

d t

ran

spo

rt

0.2

49

Stalls along the track 0.148

Stalls in service areas 0.176

Conditions floors 0.116

Corners with appropriate angles 0.083

track gradient 0.055

Track width 0.270

Number of lanes per direction 0.152

Tra

ffic

man

agem

ent

0.2

49

Electronic surveillance and access

stalls

0.219

Tracks reversible rolling and parking and circulation

0.192

Transit permission in bus lane 0.107

Traffic information system 0.263

Shared public transportation for

cargo

0.094

Parking fees of stalls 0.125

Acc

ess

cond

itio

ns

0.1

36

Deliveries monopolization 0.081

Electronic booking of cargo spaces

and unloading

0.272

Loading zone rating 0.292

Establishment of minimum density of vehicle occupancy

0.217

Urban Tolling 0.138

No

n-m

oto

rize

d

tran

spo

rt

0.0

96

Free sidewalk width 0.239

Number of stalls in a 500m radius

PGV

0.217

Obstruction of sidewalks 0.250

Ramps between sidewalks and via 0.149

Flatness of sidewalk paving 0.144

An influence signal should be assigned to each indicators

and sub-indicators weight; positive signal to sub-indicators

contributing to increase the index and negative signal to sub-

indicators contributing negatively to mobility in urban areas.

The negative sign should be justified as poor contribution to

mobility:

1) Commercial Density: The higher commercial density, the

best should be the actions to receive the goods in the area

2) The distance between trade area and distribution center:

The greater the distance between trade and the area for goods

distribution centers, the greater the distance to be traveled

within the city, contributing to the reduction of mobility in

different urban areas

3) Obstruction on sidewalks: the greater the obstruction of

sidewalks the least would be the stimulus to foot deliveries or

other non-motorized modes.

C. In Loco Measurement And Values Standardization

In order to quantify the sub-indicators in loco, a spreadsheet

was elaborated to collect the information. This worksheet was

filled with the dimensions and requested information (what to

measure according to the unit). Later that collected data were

standardized according to the standardization process already

presented in section 5 in Table III, is presented as an example,

a part of this worksheet to collect information in loco, as in

Table IV, a part of the standardization of data sheet is

presented (with some data already standardized).

TABLE III

WORKSHEET EXAMPLE

Index: Motorized Transport

Su

b

Wh

ere

chec

k

Wh

at t

o

chec

k

Un

it

Block

Street

__and__

__and__

__and__

Sta

lls

alo

ng

the

trac

k (

anal

yze

d

seg

men

t)

In l

oco

Chec

k t

he

stal

ls

pre

sen

ce f

or

load

ing

and

unlo

adin

g a

long

the

trac

k

Sta

lls

pre

sence

Sta

lls

in

serv

ice

stre

ets

In l

oco

Chec

k t

he

stal

ls

pre

sen

ce

in s

ervic

e

stre

ets

Sta

lls

pre

sen

ce

in s

ervic

e

stre

ets

Sta

lls

in s

erv

ice

stre

ets

In l

oco

An

aly

ze t

he

pav

emen

t

con

dit

ion

s in

the

seg

men

t

Reg

ula

r p

avem

ent

exte

nsi

on /

exte

nsi

on t

ota

l o

f

anal

yze

d s

tret

ch

Pav

emen

t

con

dit

ion

s

In l

oco

Con

sid

er w

het

her

the

corn

ers

ang

les

are

adeq

uat

e (n

ot

obtu

se o

r to

o

clo

sed

)

Su

itab

le a

ng

les

Co

rner

s an

gle

s

app

rop

riat

e

In l

oco

An

aly

ze t

he

seg

men

t sl

op

e

Tra

ck

incl

inat

ion

(an

alyze

d

seg

men

t) %



Tra

ck

wid

th

In l

oco

An

aly

ze

the

effe

ctiv

e

trac

k w

idth

Wid

th i

n

met

ers

N

um

ber

of

lan

es p

er

dir

ecti

on

In l

oco

An

aly

ze t

he

nu

mber

of

trac

ks

in

roll

ing

dir

ecti

on

Nu

mber

of

roll

ing b

y

trac

ks

TABLE IV APLICATION WORKSHEET EXAMPLE

Non-motorized transport

Index

Wei

ght

Su

b

Wei

ght

Used parameter Block

Street

48

an

d 1

49

an

d 2

50

e 3

non

-mo

tori

zed t

ran

spo

rt

0,0

96

Sid

ewal

k e

ffec

tiv

e w

idth

0,2

39

To

eac

h s

idew

alk m

eter

(ob

stac

les

free

) g

reat

er t

han

or

equ

al t

o

2,1

5m

is

adopte

d v

alue

1

To

eac

h s

idew

alk m

eter

(ob

stac

les

free

) o

f le

ss t

han

1.5

0 m

is

ado

pte

d v

alue

0

To

eac

h s

idew

alk m

eter

(ob

stac

les

free

) bet

wee

n 1

,50

m a

nd 2

,15

m

should

rea

lize

inte

rpola

tion

1

1

0.7

Sta

lls

wit

hin

500

m f

rom

PG

V

0,2

17

Sta

lls

wit

hin

500

m f

rom

PG

V /

Nu

mber

of

road

s

seg

men

ts

wit

hin

500

m

0

0

0

Sid

ewal

ks

ob

stru

ctio

n

-0,2

50

Ex

tensi

on o

f

ob

stru

ctio

ns

/

tota

l an

alyze

d

stre

tch

exte

nsi

on

0,0

1

0,0

3

0

Ram

ps

bet

wee

n

sidew

alk

s an

d v

ia

0,1

49

It m

ust

be

adm

itte

d a

max

imum

val

ue

of

1

for

regio

n w

ith

pre

sen

ce r

amp

s fr

om

sidew

alk

s ra

mp

s fr

om

sidew

alk

s an

d r

oad

,

and

0 f

or

Reg

ion

s fr

ee

of

ram

ps

1

1

1

Fla

tnes

s o

f

sidew

alk

pav

ing

0144

Reg

ula

r

pav

emen

t

exte

nsi

on /

tota

l

exte

nsi

on o

f

anal

yze

d

stre

tch

1

0,9

7

1

Total index group by block

0,0

50

0,0

49

0,0

44

D. Data Analysis

At this stage, the results of the application of the index

proposed in this paper is presented. For the calculations,

spreadsheets have been prepared in Excel. Based in all sheets

applied in the field and already standardized, the results were

compiled in:

1) Segment Index (assessed court) – IMTUCsegment;

2) via Index – IMTUCstreet;

3) General Index - IMTUCgeneral.

1)Segment Index – IMTUCsegment

The segment index (IMTUCsegment) is based on the

fulfillment of the values observed in the field of each sub-

indicator for each segment analyzed (each block). The

observed values pass through standardization (adjustment in

the range of 0 to 1) and then the application of their respective

weights and their indicators, thus yielding the final value of

the segment index.

Table V presents as an example one of the tables used for

the IMTUCsegment, it is also presented the indicators values

(motorized transport, non-motorized transport, land use, traffic

management and access restrictions).

TABLE V

SEGMENT INDEX CALCULATION EXAMPLE

Segment rated Saldanha Marinho street

Between blocks

4 e 7 5 e 8 6 e 9

Motorized transport 0,1230 0,1230 0,1230

Non-motorized transport 0,0472 0,0518 0,0515

Land Use 0,0406 0,0293 0,0293

Traffic management 0,0000 0,0000 0,0000

Access conditions 0,0000 0,0000 0,0000

IMTUC segment 0,2108 0,2041 0,2038

Analyzing the IMTUCsegment values, it is observed that

the values are much closer to zero than to one. Some

considerations about this index are made:

1) Motorized transport indicator is the one with highest

value among the other indicators in almost all the segments

analyzed. This demonstrates that the local analysis is more

likely to cargo freight by motorized transportation, since the

conditions found are more conducive (supply bays for loading

and unloading operation, good road slopes, pavement

favorable conditions for traffic vehicles).

2) For non-motorized transport indicator, it was observed

that in general, all sub-indicators have Real value (non zero).

The most prominent are the road effective width that is shown

as good in most cases (visible in the segments of the main

routes Visconde do Rio Branco and Amaral Peixoto Avenue).

3) The land use mostly showed negative values, this is due

to the fact that the commercial density is higher than

residential density (sometimes is more than 80%).

4) traffic management indicator the one that showed the

worst values (zero in more than half of the segments

analyzed). Their values are justified by not existing in all

cases: electronic monitoring of bays or accesses, traffic

information systems in real time, public transport share with

cargo transport and cargo vehicles permission in bus lanes

(even in off-peak hours). The sub-indicator that contributed

for this indicator not be zero in some cases is the collection of

parking fees - which is considered a positive step, since it

stimulates the deliveries to occur on a scheduled basis and

avoid wasting time in parking lot and unnecessary movement

in pathways causing slowdowns or obstruction in the way.



5) The access restriction indicator was another that did not

showed good values in the analyzed segments. The indicator

final value for each segment analyzed, justified by the absence

of the following sub-indicators: tolls, minimum occupation

density establishment and electronic loading and unloading

booking. If these sub-indicators possess a field observation

value would increase the value of the indicator and

demonstrate that there is a greater incentive for urban load

traffic to be best planned, preventing cargo vehicles to

circulate in that region without real need. The sub-indicators

had real value in the field of analysis and did not allow this

indicator to be zero (in some cases) was the cargo area

classification (establishment of circulation times, height and

weight of vehicles) and the monopolization of deliveries

(deliveries made by same suppliers).

2)Road Index – IMTUCstreet

Road index (IMTUCstreet) is obtained by the average of

analyzed segments index values, when belonged to that route.

In Table VI are presented every street index values.

TABLE VI ROAD INDEX

INDEX PER STREET

Street Street name IMTUCstreet

A Street: Feliciano Sodré Avenue 0.2248

B Street: Dr. Fróes da Cruz 0.1958

C Street: Saldanha Marinho 0.2062

D Street: Marquês de Caxias 0.2333

E Street: Mal. Deodoro 0.2238

F Street: São João 0.1749

G Street: Cel. Gomes Machado 0.1255

H Street: São Pedro 0.1793

I Street: Ernani do Amaral Peixoto 0.2352

J Street: da Conceição Avenue 0.1599

K Street: José Clemente 0.1332

L Street Aurelino Leal 0.2243

M Street 15 de Novembro 0.1991

N Street Pedro Augusto Nolasco 0.2770

O Street Tv. Gen. Penha Brasil 0.2213

P Street Bagder da Silveira Avenue 0.2127

Q Street Gen. Andrade Neves 0.2727

R Street Visconde do Rio Branco Avenue 0.1451

S Street Visconde do Uruguai 0.1351

T Street Visconde de Itaborai 0.1881

U Street Maestro Feliciano Toledo 0.1101

Note that the street with higher IMTUCstreet (0277) is

Pedro Augusto Nolasco Street (see Street N in Figure 5) which

is not a very street trade despite being close to a PGV. The

lowest rate calculated belongs to Maestro Feliciano Toledo

Street (U Street), which resulted in 0, 1101 IMTUCstreet, and

this way along its entire length has trade.

3)General Index – IMTUCgeneral

The region would be considered good and attractive to

receive new trades that would generate greater flow of goods

and would have an approximate UCTMI value near 1, since

the region whose UCTMI value is close to 0, is not able to

receive new trades, according to an evaluation as the sub-

indicator.

The general index of the analyzed region is the average of

the indexes of each street (as shown in Table 6). The value

obtained in the analysis of this region was a general IMTUC

value equal to 0.1942. Thus, according to the result Niterói

downtown district is not able to receive new commercial

ventures, unless actions are implemented to improve the

indicator values obtained in the field. At first, actions have to

have mitigating character in order to reduce existing impacts

and problems. Thus, the sub-indicators that showed low values

should be reviewed. Subsequently, for further improve in

mobility in this region, a study should be done to analyze the

application of preventative actions to prevent other problems.

VI. CONCLUSION

The purpose of this article is to develop a mobility index for

urban cargo transport and apply it. This index is able to

indicate a particular area mobility condition and say whether it

is fit to receive new commercial enterprises that generate

cargo handling in its surroundings. The importance of the

development of this research is due to cities constant

expansion and the consequent increase in people, vehicles and

cargo displacement. When these are not properly planned,

affect urban mobility as a whole, creating a number of

problems related to social, economic and environmental

aspects of city life.

In Brazil, urban mobility issue is already widespread, but

does not include urban cargo transport. This fact is mainly due

to the lack of studies on the subject and government restrictive

view. Gradually this picture has taken other directions, as Law

12.587 / 12, where municipalities should pay more attention to

cargo handling in urban areas, being provided in mobility

plans, actions including TUC to improve the transport system

as a whole. With the implementation of this law, new studies

are necessary to include cargo mobility in urban areas.

To develop this article, an approach to urban mobility index

was necessary, to monitor many areas of the city and carry out

a follow-up about implemented actions in order to optimize

mobility as a whole. During search on mobility index models,

it was found that most authors did not consider freight

transport (excluding Quezada, Navarrete and Biosca (2013),

which proposed an index - RATUC - which is still under

review). Thus, report analysis about actions implementation in

order to mitigate, prevent and remedy the problems arising

from cargo handling, and then be able to define a mobility

index for cargo transport in urban areas. 17 studies of

Brazilian and foreign researchers were analyzed, from them 54

actions and restrictions were detached in order to mitigate /

minimize the problems caused by TUC. These measures and

restrictions were initially grouped in a categorization proposed

by Munuzuri (2005), being divided respectively: 11 actions to

public infrastructure area, 12 actions for land use

management, 7 actions for traffic management, 13 actions for

sanctions and promotions and 11 restrictions on access

conditions.

According to these 54 actions and restrictions found, it was

identified 29 actions and restrictions which are government

responsibility (to deploy, to supervise and to store data in

order to create historic evaluation) which were the basis for



sub-indicators proposal. These 29 sub-indicators were grouped

into 5 major themes considered indicators. These themes were

defined based on the classification proposed by Munuzuri

(2005), but with adaptation, so that the 5 themes, hereinafter

indicators, and these are: land use, motorized transport, non-

motorized transport, access conditions and management

traffic. After this was established as each sub-indicator would

be measured in the field and as such measurements would be

transformed to be within the established range (0-1).

When determining the degree of sub-indicators and

indicators importance within the index, SPC method

(Structured Pair-wise Comparison) was applied, and a

questionnaire was administered to 11 experts in the area,

which made a peer to peer comparison, so that subsequently

the final value of the weights of each indicator and sub-

indicator was obtained. SPC methodology is AHP simplified

method, facilitating the data filling by the respondents.

According to each indicator and sub-indicator weight and

based on mobility index models, it was proposed a procedure

to calculate a mobility index for urban cargo transport. This

index is characterized by joining indicators, sub-indicators and

standard values measured in the field. This procedure was

applied in Niteroi Center district. The choice of this area of

study is justified due to high concentration of trade in various

branches.

Three urban cargo transport mobility indexes were

obtained: IMTUCsegment, IMTUCstreet, UCTMIgeneral. For

all calculated indexes, noted that the values are much closer to

0 than 1. It means that the analyzed area doesn´t have good

conditions for cargo freight, i.e., it is not recommended to

have more trades in the region.

If new forms of commerce are required to be implemented,

it is important that interventions should be made in order to

improve mobility in the region, thus increasing the indicators

value of each IMTUC. It is important for the action

implementation to raise the index. At first instance analyze

indicator groups that show the lowest values; if this

application should be prioritized and directed to land use and

traffic management areas.

Analyzing real traffic in the region, it is remarkable that the

values obtained for IMTUC correspond to existing mobility.

In other words, low rates can be verified when checked

visually, observing that several cargo vehicles parked and in

circulation roads where it is not allowed. All this influences

general mobility of the region (individual, collective and

pedestrian vehicles mobility).

The parameters adopted to standardize the values measured

in the field were restrictions to this article. If it is applied in

another city, parameter values for sub-indicators should be

searched in local established regulations or in a reference town

nearby, maintaining the same form to normalize the values in

the range 0 to 1. Calculated weights may be used in other

cities, where it is not possible to carry out a survey with

experts.

As stated, the index can be applied in several cities, and its

parameters can be modified according to the city rules. Once

applied in two or more cities, it can be used to compare the

index values and define regions mobility ranking.

Also, other parameters can be incorporated to and removed

from this index, keeping in mind the needs of city managers

that will apply the index.

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Rio de Transportes. Rio de Janeiro, Brazil. 2004.



Cynthia Vargas Cuchava Rocha, was born

in Itajaí city, Brazil in 1991. Graduated in Civil Engineering from the University of Vale

do Itajaí - Santa Catarina state, Brazil (2013)

and Master in Transportation Engineering from IME (2016). She has experience in civil

construction through development and

execution of projects (architectural, sanitary, electrical, structural) works monitoring of

Compliance Projects Monitoring the

disciplines: sociology and urban planning, architecture, design I and II, and transport

engineering area has experience in urban mobility for freight transport.

Simone Lie Issomura was born in São Paulo city, Brazil, in 1981. She received the B.S.

degree in civil engineering from State

University of Campinas (UNICAMP), Campinas, São Paulo, Brazil, in 2004; quality

and value engineering specialization degree

from São Paulo University (USP), São Paulo,

São Paulo, Brazil, in 2007; railway engineering

specialization degree from Minas Gerais

Pontifical Catholic University (PUC Minas), Belo Horizonte, Minas Gerais, Brazil, in 2008

and MBA degree from Getúlio Vargas

Foundation (FGV), São Paulo, São Paulo, Brazil, in 2009. She is currently working pursuing the M.S. degree in transportation

engineering at Military Institute of Engineering (IME), Rio de Janeiro,

Rio de Janeiro, Brazil. From 2005 to 2007 she has worked as Civil Engineer at São Paulo

Subway Company and since 2008 she is working as Permanent Way

Engineer at a Brazilian mining company in Vitoria, Espírito Santo, Brazil.

Swellen Mendonça Pessanha was born in Campos dos Goytacazes city, RJ, Brazil, in

1989. Graduated in Architecture and Urbanism

from Federal Fluminense Institute (IFF) in

2012. Currently, she is pursuing the M.S.

degree in Transportation Engineering at

Military Institute of Engineering (IME), Rio de Janeiro, Rio de Janeiro, Brazil.

She has experience in Architecture, Urban

Planning, Construction Technologies and Transportation Engineering, mainly in

demand´s behavior, Transferred Demand,

Passenger Trains systems and Stated and Revealed Preference Survey.

Vania Barcellos Gouvea Campos graduated in architecture at Rio de Janeiro Federal University (UFRJ), Rio de Janeiro,

Brazil, in 1978. She received the master

degree in transportation engineering from Military Institute of Engineering (IME), Rio

de Janeiro, Rio de Janeiro, Brazil, in 1980;

the Ph.D. degree in production engineering

from UFRJ, Rio de Janeiro, Brazil, in 1997

and the PostDoc from Minho University,

Minho, Portugal, in 2005. From 1981 to 1982 she worked as Architect

at Petropolis city hall, from 1982 to 1984 she worked as Planning

Assessor at Sermapi S.A and from 1986 she has been working as a Professor at IME, Rio de Janeiro, Rio de Janeiro, Brazil. Her research

interest includes: cargo and passenger urban transportation, traffic

control, mobility, land use and transportation logistics.

Renata Albergaria de Mello Bandeira graduated in fortification and construction

engineering at Military Institute of

Engineering (IME), Rio de Janeiro, Brazil, in 2002. She received the master degree in

production engineering from Rio Grande do

Sul Federal University (UFRGS), Rio Grande do Sul, Brazil, in 2006 and the

Ph.D. degree in administration from

UFRGS, Rio Grande do Sul, Brazil, in 2009.

From 2009 to 2010 she worked as a Professor at UFRGS, from 2010 to

2011 she worked as Professor at TecBrasil and since 2011 she has been working as a Professor at IME, Rio de Janeiro, Rio de Janeiro, Brazil.

Her research interest includes: logistics, supply chain management,

logistics outsourcing, project management and statistics.

Documents

Application of an Urban Cargo Transport Mobility Index to ...ijens.org › Vol_16_I_04 › 162704-5858-IJCEE-IJENS.pdf · (SUMI), as well as public policies applied index. It is composed