sustainable road layout design for a suburban …...5.4 central data center 42 5.5 procedure for...
TRANSCRIPT
SUSTAINABLE ROAD LAYOUT DESIGN FOR A
SUBURBAN AREA (TAMBARAM) USING FUZZY
AIDED SYSTEM
A THESIS
Submitted by
K.YOGESWARI
Under the guidance of
Dr. E.RASUL MOHIDEEN
in partial fulfillment for the award of the degree of
DOCTOR OF PHILOSOPHY in
CIVIL ENGINEERING
B.S.ABDUR RAHMAN UNIVERSITY (B.S. ABDUR RAHMAN INSTITUTE OF SCIENCE & TECHNOLOGY)
(Estd. u/s 3 of the UGC Act. 1956) www.bsauniv.ac.in
JUNE 2015
ii
B.S.ABDUR RAHMAN UNIVERSITY (B.S. ABDUR RAHMAN INSTITUTE OF SCIENCE & TECHNOLOGY)
(Estd. u/s 3 of the UGC Act. 1956) www.bsauniv.ac.in
BONAFIDE CERTIFICATE
Certified that this thesis report SUSTAINABLE ROAD LAYOUT
DESIGN FOR A SUBURBAN AREA (TAMBARAM) USING FUZZY
AIDED SYSTEM is the bonafide work of K. YOGESWARI (RRN:
0980201) who carried out the thesis work under my supervision. Certified
further, that to the best of my knowledge the work reported herein does not
form part of any other thesis report or dissertation on the basis of which a
degree or award was conferred on an earlier occasion on this or any other
candidate.
SIGNATURE SIGNATURE
Dr. E.RASUL MOHIDEEN Dr. P. Vasanthi
RESEARCH SUPERVISOR HEAD OF THE DEPARTMENT
Professor Professor & Head
Department of CIVIL Department of CIVIL
B.S. AbdurRahman University B.S.Abdur Rahman University
Vandalur, Chennai – 600 048 Vandalur, Chennai – 600 048
iii
ACKNOWLEDGEMENT
I would like to express my sincere thanks to Dr.V.M.Periasamy,
Vice Chancellor in-charge, B.S.AbdurRahman University,
Dr.M.V.Molykutty, Dean, School of Infrastructure, and Dr. P. Vasanthi
Head of Department of Civil Engineering, for providing me with all the
necessary facilities to carry out research.
I thank my supervisor Dr. E.RASUL MOHIDEEN, Professor,
Department of Civil Engineering, for the constant support throughout this
research work. Without his initiation, encouragement and directions, this
dissertation would not have taken shape. His critical remarks helped me a lot
to fine tune and complete the research successfully.
I would like to express my gratitude to my doctoral committee
members, Dr.S.Lakshmi, Professor, Department of Transportation
Engineering, Anna University, for her constant advice and suggestions.
I express my sincere thanks to the faculty members of Civil
Engineering Department, B.S.AbdurRahman University, for their whole
hearted co-operation in completing this work.
Above all, I thank my family members for their patience, love and
prayers. I thank all my friends who have helped me in one way or other for
the successful completion of this work. Last but not the least, I thank the
Almighty for blessing me to successfully complete this work.
K.YOGESWARI
iv
ABSTRACT
Sustainable transportation system aim at designing of congestion-
free urban planning with bicycle and pedestrian friendly design of their areas.
It focuses on moving people and not only the vehicles, which in turn would
reduce air pollution as well as the increasing congestion. Sustainability can be
achieved with the change in behavioral aspects of people. When people
understand the impact of transportation they can in turn make choices that
reduces the need for resources and thus minimize the adverse impacts.
The aim of this study is to provide a systematic description and
analysis of Sustainable road layout design using Fuzzy logic system. The
selection of methodological framework is justified on the ground that it
enables one to group the interlink ages between the various indicators of the
sustainability, while at the same time, highlighting the factors that influence
such interlink ages. A suburban area (Tambaram) in south Chennai,
Tamilnadu state, India, is chosen for conducting the analysis of sustainable
road layout. The present work is exploratory in its methodology and
theoretical framework.
The study utilizes the sustainable transportation planning concept
for Road layout design for suburban area. The use of multi objective
optimization method by fuzzy logic is present further in this thesis, will allow
engineers, planners and decision makers to optimize the component of an
urban street and obtain the perceived level of services across all modes on
urban street within a given right of way.
v
TABLE OF CONTENTS
CHAPTER NO. TITLE PAGE NO.
ACKNOWLEDGEMENT iii
ABSTRACT iv
LIST OF TABLES ix
LIST OF FIGURES xii
LIST OF SYMBOLS AND ABBREVIATIONS xiv
1. INTRODUCTION 1
1.1 INTRODUCTION TO SUSTAINABLE
DEVELOPMENTS 1
1.2 DEFINITION OF SUSTAINABLE
TRANSPORTATION 2
1.3 SUSTAINABLE TRANSPORTATION SYSTEM 3
1.4 NEED FOR SUSTAINABLE
TRANSPORTATION SYSTEM 4
1.5 CONCLUSION 5
2. LITRETURE REVIEW 6
2.1 SUSTAINABLITY– A SHORT STORY 6
2.2 SUSTAINABLE – GLOBAL OUTLOOK 6
2.3 REVIEW OF STATUS OF RESEARCH –
INTERNATIONAL SCENARIO 9
2.4 CURRENT SCENARIO PREVAILING
IN INDIA AS PER THE LITERATURE 11
2.5 RESEARCH ISSUES TO BE ADDRESS
SUSTAINABILITY IN URBAN TRANSPORT 11
2.6 CONCLUSION 12
vi
CHAPTER NO. TITLE PAGE NO.
3. RESEARCH METHODOLOGY AND DESIGN 13 3.1 INTRODUCTION 13
3.2 MOTIVATION FOR THE STUDY 13
3.3 AIM OF THE STUDY 14
3.4 OBJECTIVE OF THE STUDY 14
3.5 COMPONENTS OF SUSTAINABLE
TRANSPORT 15
3.6 METHODOLOGY 15
3.7 CONTRIBUTION TO STATE
OF THE KNOWLEDGE 17
4. STUDY AREA AND ITS CHARACTERISTICS 18
4.1 INTRODUCTION 18
4.2 TAMBARAM AS A SUB URBAN –
BOUNDARY CONDITION 20
4.3 BUILT ENVIRONMENT 20
4.4 THE TRANSPORTATION NETWORK 21
4.5 THE ECONOMY 23
4.6 URBANISATION 24
4.7 LAND USE 25
4.7.1 The Future Land Use 26
4.7.2 Land use Changes 27
4.8 MOTORIZATION 28
4.9 EFFECTS OF MOBILITY 30
4.10 CONGESTION INDEX 31
4.11 SAFETY 32
4.12 PARKING 33
4.13 IDENTIFICATION ISSUES 34
4.14 CONCLUSION 34
vii
CHAPTER NO. TITLE PAGE NO.
5 STUDY OF HETEROGENEOUS TRAFFIC
USING VIDEO IMAGE PROCESSING
TECHNIQUES 36
5.1 INTRODUCTION 36
5.2 VIDEO SHOOTING METHODOLOGY 36
5.2.1 Angle 37
5.2.2 Focus 38
5.2.3 Zoom 38
5.2.4 Lighting Conditions 38
5.2.5 Shutter Speed 38
5.2.6 Height 38
5.3 TRAZER SOFTWARE 39
5.4 DATA ACQUISITION BY VIDEO
SURVEILLANCE METHOD 40
5.5 DATA ANALYSIS FROM TRAZER
AND RESULTS 41
5.6 AVERAGE VEHICLES VOLUMES 43
5.6.1 G.S.T Road – Arterial Road 43
5.6.2 Velachery Main Road – Sub Arterial Road 45
5.6.3 MudichurRoad – Sub Arterial Road 46
5.6.4 Collector Street 47
5.7 VEHICLE TRAJECTORY 48
5.8 CONCLUSION 50
viii
CHAPTER NO. TITLE PAGE NO.
6. SUSTAINABLE ROAD LAYOUT
DESIGN FOR LIVE ABLE AREA (TAMBARAM)
WITH THE AID OF FUZZY LOGIC SYSTEM 51
6.1 INTRODUCTION 51
6.2 NEED FOR SUSTAINABLE INDICATORS
AND ITS LIMITATIONS 52
6.3 INDICATORS OF SUSTAINABILITY 53
6.4 INDICATOR USED IN THE SUSTAINABLE
ROAD LAYOUT DESIGN – INPUT
PARAMETERS: FOR MODEL USING
FUZZY LOGIC SYSTEM 54
6.5 FUZZY LOGIC SYSTEM 60
6.6 FLOW CHART OF THE PROPOSED
FUZZY LOGIC SYSTEM 60
6.6.1 Fuzzification 61
6.6.2 Inference 62
6.6.3 Defuzzification 64
6.6.4 Crisp Output Value 64
6.7 SUSTAINABLE ROAD LAYOUT 66
6.7.1 Road Layout Design P 66
6.7.2 Road Layout Design Q 67
6.7.3 Road Layout Design R 68
6.7.4 Road Layout Design S 69
7. RESULTS AND DISCUSSIONS 73
7.1 OUTPUT FOR THE ROAD LAYOUT P 73
7.2 OUTPUT FOR THE ROAD LAYOUT Q 74
7.3 OUTPUT FOR THE ROAD LAYOUT R 75
ix
CHAPTER NO. TITLE PAGE NO.
7.4 OUTPUT FOR THE ROAD LAYOUT S 76
7.5 ACCIDENT CASE 78
7.6 MOTORIZATION 79
7.7 CONCLUSION 80
8. CONCLUSIONS 82
9. SUMMARY OF THE STUDY 84
10. SCOPE FOR FUTURE WORK 85
REFERENCES 86
LIST OF PUBLICATIONS 114
TECHNICAL BIOGRAPHY 115
x
LIST OF TABLES
TABLE NO. TITLE PAGE NO.
4.1 Inventory of road network 23
4.2 Historical growth of population in Tambaram 24
4.3 Urban conglomeration in India according 2001 census 25
4.4 Land use changes 28
4.5 Desirable modal split for Indian cities
(as percentages of total trips) 29
4.6 Existing modal split in Indian cities
(as percentage of total trips) 30
4.7 Anticipated average journey speed (kmph) on major roads 30
4.8 The journey speed on the roads in study area 31
4.9 Total number of accidents in the study area 32
4.10 Parking characteristics 33
5.1 Inventory of road network of the video shooting roads 41
5.2 Average vehicles volumes in G.S.T road towards Chrompet 44
5.3 Average vehicles volumes in GST road towards Vandalur 44
5.4 Average vehicles volumes in Velachery road towards
Tambaram 45
5.5 Average vehicles volumes in Velachery road towards
Madippakam 46
5.6 Average vehicles volumes in Mudichur road
towards Tambaram 47
5.7 Average vehicles volumes in data for collector roads 47
5.8 Vehicle trajectories 48
5.9 Accuracy of object detection, classification,
and vehicle trajectory 49
xi
TABLE NO. TITLE PAGE NO.
6.1 Details about the indicator selected to evaluate
the road layout sustainability 55
6.2 Crisp input data 61
6.3 Fuzzy rules 63
6.4 Crisp output data 64
6.5 Sequence of road layout 70
6.6 Roads with its layout and contribution 71
7.1 Contribution level for different parameters 77
xii
LIST OF FIGURES
FIGURE NO. TITLE PAGE NO.
1.1 Sustainability curve 3
3.1 Methodology of the study 16
4.1 Tambarammunicipality base map 19
4.2 Google images of Tambaram map 22
4.3 Hierarchy of road network map 22
4.4 Population growth in Tambaram 24
4.5 Existing Landuse 2010 25
4.6 Percentage of land use 2010 26
4.7 FurtureLanduse 2026 26
4.8 Percentage of land use 2026 27
4.9 Land use changes 27
4.10 Growth of motor vehicle fleet by type of vehicle 29
4.11 Congestion index 31
5.1 Video shooting methodology 37
5.2 Microscopic data analysis using TRAZER 39
5.3 Tambaramroad network 40
5.4 Central data center 42
5.5 Procedure for image process 42
5.6 Vehicle extraction 43
5.7 Vehicle trajectories 48
6.1 (a) Road map from Tambaram to Velachery
(b) Road map of GST road (c) Road map from
Tambaram to Mudichur(d) Road map of Camp road 57
6.2 Land usage allocation for different parameters in 2013 59
6.3 Flow chart of the proposed Fuzzy logic system 60
xiii
FIGURE NO. TITLE PAGE NO.
6.4 Factors influencing fuzzification 62
6.5 Defuzzification process 64
6.6 (a) shows the traffic flow in one of the area in Tambaram
with existing lanes, (b) shows allocation vehicles in no
parking area, (c) subway which is allocated with
platform shops, fig(d) shows roads which are left
unconstructed 65
6.7 21m road layout as P layout 66
6.8 18 m road layout as Q layout 67
6.9 9 m road layout as R layout 68
6.10 7.5m road layout as S layout 69
7.1 MATLAB output for the road layout P 73
7.2 MATLAB output for the road layout Q 74
7.3 MATLAB output for the road layout R 75
7.4 MATLAB output for the road layout S 76
7.5 Accident management graph for 4 different
Layouts of 2013 in Tambaram 79
7.6 Motorization for 4 different road layouts 80
xiv
LIST OF SYMBOLS AND ABBREVIATIONS
AM chart - Accidental management Chart
B/C - Benefit – cost ratio
C - capacity
EgM - Energy management
EM - Environmental management
GST - Grand southern trunk
GUI - Graphical user interface in MATHLAB
HMV - Heavy motor vehicle
ID - Identification Number
ITS - Intelligent transport system
LMV - Light Motor vehicle
MEPZ - Madras export processing chart
MOUD - Ministry of Urban development
NH - National Highway
PCU - Passenger Car Unit
PP - Pedestrian path
ROW - Right of way
SM - Safety management
Q - Sustainable road layout for 18m
P - Sustainable road layout for 21m
S - Sustainable road layout for 7.5m
R - Sustainable road layout for 9m
TM - Traffic management
TM chart - Transportation Modal chart
TW - Two wheeler
VIPS - Video image processing System
V - Volume
1
1. INTRODUCTION
1.1 INTRODUCTION TO SUSTAINABLE DEVELOPMENTS
“Meets the needs of the present without compromising the ability
of future generations to meet their own needs” – (WCED 1987)
(Brundtland Commission’s Report)
There is growing interest in the concept of sustainability,
liveability, sustainable development and sustainable transportation.
Sustainability generally refers to a balance of economic, social and
environmental goals, including those that involve long term, indirect and non-
market impacts, liveability refer to the subset of sustainability goals that
directly affects community members. As transportation have immense
economic, social, and environmental effects its plays a significant role in
maintaining sustainable development.
“Sustainability is not about threat analysis, Sustainability is about
system analysis, specifically, it is about how environmental, economic and
social system interact to their mutual advantage or disadvantage at various
space- based scale of operations”
(Transport Research Board 1997)
Thus a sustainable transport system is one that is accessible, safe,
environmentally-friendly and affordable.
2
1.2 DEFINITION OF SUSTAINABLE TRANSPORTATION
A sustainable transportation system is one that (centre for
sustainable transportation, CST, 2005)
Allows the basic access needs of individuals and societies to
be met safely and in a manner consistent with human and
ecosystem health and with equity within and between
generations.
Is affordable, operates efficiently, offers choice of
transportation mode and support a vibrant economy.
Limits emission and waste within the planet’s ability to absorb
them, minimize consumption of non-renewable resources,
limits consumption of renewable resources to the sustainable
yield level, reuses and recycle its components and minimizes
the use of land and the production of noise.
Good land use planning requiring minimum need to travel,
transportation network friendly for all classes of people, transportation modes
causing minimum amount of air pollution and transportation options
demanding least cost and effort of people can be considered as various aspects
of a sustainable transportation system. It includes the application of system,
policies and technologies which would help achieve the continuous economic
development without having a detrimental effect on environmental and
human resources. Sustainable transportation aims at the efficiency of the
transit of goods, services and delivery systems with minimum accessibility
problems.
3
1.3 SUSTAINABLE TRANSPORTATION SYSTEM
Sustainable transportation system aim at designing of congestion-
free urban planning with bicycle and pedestrian friendly design of their areas.
It focuses not only on the vehicles but also on moving people , which in turn
would reduce air pollution as well as the increasing congestion. Sustainability
can be achieved with the change in behavioural aspects of people. When
people understand the impact of transportation they can in turn make choices
that reduces the need for resources and thus minimize the adverse impacts.
0
5
10
15
20
25
TIME
SOU
RCES
APP
ORO
PRIA
TE M
EASU
RE
SUSTAINABILITY
RESOURCES &ENVIRONMENT
NEEDS & TECHNOLOGY
Sources:- Sustainability Transportation conceptualization and performance measure, Texas transportation Institute.
Figure 1.1: Sustainability Curve
Socio-economic needs of the people increase with growth in
technology. Figure 1.1 shows the increasing needs of and depleting resources.
After a certain point of time, the resources are unable to satisfy the needs and
the unsustainable conditions arise. Thus the imbalance is created as the supply
gets diminished as compared to demands
4
1.4 NEED FOR SUSTAINABLE TRANSPORTATION
Urban transportation facilities or the processes of achieving
mobility in a urban setting are a part of the urban habitat. The question is what
does this habitat includes other than the roads, intersections, bus-stops, rail
lines and so on? The urban habitat includes the people belongs to the different
classes such as rich, middle and poor. The work places, the services (like the
hospital, the fire services etc).the residential areas the recreational facilities,
educational institutions, commercial establishments have been organised in
the urban habitat. The way this habitat is organised creates the transportation
demand and supply pattern.
A definite mandate of any transportation system should be to allow
the uses of the system to efficiently harvest the opportunities. What types of
demand pattern are created and how they are met (supply pattern) through the
use of the resources have a large bearing on whether the transportation system
is sustainable. (i.e) whether the transport system will remain efficient for over
a period of time and space (i.e) the system must be efficient not only to a
restricted area but also regionally.
Efficiency has been a driving force in engineering design. If a
system is seen to be inefficient, then effort is expanded to improve the
efficiency. If the problem arises in the way then efficiency is often measured.
A couple of example on how a tradition view of efficiency can lead to non-
sustainable developments whereas a more inclusive definition of efficiency
could have led to sustainable development will highlights this issue better.
Few decades ago, it was felt that good roads should be provided to
achieve fast and safe transportation of people and goods, the efficiency of the
road system would be measured according to how well it met the stated goals.
Hence, when roads become congested one built even more roads, roads
5
without- at grade intersections, limited access roads and so on. Two lane
roads become four lane highways, four lane highways become six – lane
expressways and this would have continued but for the realization that there is
no end to it. If on the other hand, the definition of efficiency was more
inclusive and had features like.
(i) The amount of exhaust that would create if more people
drove.
(ii) The amount of fossil fuel that will be consumed etc, then
obviously which encouraged more automobile traffic would
no longer be thought of as efficient.
Planners and Engineers would have had to look for other solutions.
Thus three aspects are important to the creations of a sustainable
urban transportation system.
(i) The habitat of which the transportation system is a part
(ii) The resources that such a system will need to harvest.
(iii) The measure of efficiency that should be employed to evaluate
such a system.
1.5 CONCLUSION
A sustainable condition for this planet is one in which there is
stability for both social and physical systems, achieved through meeting the
needs of the present without compromising the ability of future generations to
meet their own needs. Thus a sustainable transport system is one that is
accessible, safe, environmentally-friendly and affordable is required to make
the roads more efficient.
6
2. LITERATURE REVIEW
2.1 SUSTAINABILITY – A SHORT STORY
The first step for the emergence of sustainability was seen in the
UN conference on the Human environment held at Stockholm in1972. The
term came into general use in 1987 when a report was published on common
future by GroBrundtland Committee. Sustainability has turned to be a rising
political work with the united national conference on environment and
development in Rio,1992 and its global action plan for sustainable
development (Agenda 21) that brought the terms into the political agenda.
There are many definitions of sustainability, liveability, sustainable
development and sustainable transport.
2.2 SUSTAINABLE – GLOBAL OUTLOOK
1. UN World Commission on Environment and Development –
GroBrundtland Committee – 1987
“To meet the needs of the present without compromising the ability
of future generations to meet their needs.”
2. Mega – Pedersen - 1998
“Sustainability is equity and harmony extended into the future, a
careful journey without an end point, a continuous striving for
harmonious co –evolution of environmental, economic and socio
culture goals”
7
3. Wilson – 1998
“The common aim [ of sustainable development} must be to
expand resources and improve the quality of life for as many
people as heedless population growth forces upon the earth and do
it with minimal prosthetic dependence.”
4. Enviromentally Sustainable Transport [EST- 1998}
“Transportation that does not endanger public health or ecosystem
and meets needs for access consistent with (a) use of renewable
resources at below their rates of regenerations (b) use of non-
renewable resources at below the rates of development of
renewable substitute.” In 2000 EST produced the guidelines for
Environmentally sustainable transport. In 2001 the environmental
Indicators towards the sustainable development were developed.
5. National Round Table on the Environment and the Economy
(NRTEE - 2003) – Ottawa, Canada.
It has developed a draft set of Sustainable Transportation principles
that “concern access, equity, individual and community responsibility,
health and safety educations and public participation, integrated
planning, land and resources use, pollution prevention and
economic well being”.
6. Victoria Transport Institute –( VTPI – 2003)
Todd Litmen, Victoria, Cannada presents a Literature review on its
approach and selection criteria for sustainable Indicators. They
offer an alternative perspective on the selection of transport
indicators by focussing on access rather than on the transportation
system’s ability to “move vehicles”. Sustainable developments can
8
be defined as “Providing for a secure and satisfying material future
for everyone, in a society that is equitable, caring and alternative to
basic human needs”.
7. Centre for Sustainable transportation – CST (2003) – Toronto,
Canada.
The centre for Sustainable Transportation, Canada developed initial
set of 14 Sustainable Transportation performance indicators. CST
defines a sustainable transportation system as
(1) Allows the basic access needs of individual and societies to be
met safely and in a manner consistent with human and
ecosystem health and with equity within and between
generations.
(2) Is affordable, operates efficiently, offer choice of transport
mode and supports a vibrant economy.
(3) Limits emission and waste within the planet ability to absorb
them, minimize consumption of non-renewable resources,
reuse and recycles its components and minimizes the use of
land and production of noises.
Sustainability is “the capacity for continuance into the long term
future. Anything that can go on being done on an indefinite basis is
sustainable. Anything that cannot go on being done indefinitely is
unsustainable. ”
8. Procedure for recommending optimal Sustainable planning of
European city Transport System (2003) discuss about A sustainable
urban transport and land use system
9
(1) Provide access to goods and service in an efficient way for all
inhabitants of urban area.
(2) Protects the environment, culture heritage and ecosystem for
the present generation.
(3) Does not endanger the opportunities of future generations to
reach at least the same welfare level as those living now
including the welfare they derive from their natural
environment and culture heritage.
9. Michel Neuman, Associate Professor, Department of Landscape
Architecture and Urban planning, Texas university have
contributed for sustainable transportation planning in Texas, 2003-
2012.
10. Todd Litmen, Director, Victoria transport policy institute (2003 -
2013) have contributed for comprehensive and sustainable
Transport planning.
2.3 REVIEW OF STATUS OF RESEARCH – INTERNATIONAL
SCENARIO
Research has been carried out by Celko, J. Gavulova, A.(2009)
Department of Highway Engineering, University of Zilina, Slovakia. The
quality traffic-planning process is an important tool for achieving sustainable
traffic. The modern platform for modeling and simulating traffic relations has
also begun to be utilized in Slovakia the new transport relations and traffic
problems were analyzed. This chosen part of the transport network was
imported into a micro simulation model in the VISSIM. New alternative
transport solutions and the impact on the infrastructure loading were explored
in microscopic models. Real – time Information production and presentation
10
using GIS-Based Maps for Urban transportation planning was carried out by
Balamohan N (2000). GIS Approach of Delineation and Traffic Assessment
for the Traffic Analysis zone were calculated using Land use, cadastral and
census data.
In 2013, Raja Noriza Raja Ariffina et al. have resourcefully
introduced a paper to analyze the features that had an immense influence on
the status of the city transport system in the Klang Valley. It scrutinizes the
manner in which the policy schedule is adversely affected by the customs,
behaviors and viewpoints of those employed in the transport-linked areas. The
preliminary records are collected through semi-structured interviews.
Government credentials and archival data furnish the vital source for resultant
data. The philosophy and attitude of the transport communities appear to have
a significant effect on sustainable transport agenda in the Klang Valley.
In 2013, Kibrom Abay industrially investigated the injury
harshness of pedestrians taking into account comprehensive road user features
and substitute model design by means of superior-quality Danish road mishap
information. This kind of approach went a long way in estimating the
sensitivity of experimental deductions to the selection of these brands. The
experimental scrutiny exposed the fact that overall road user features like
criminal record of drivers and temporary behavior of road users at the time of
the mishap indicated an interesting insight in the injury intensity
investigation. Similarly, the substitute investigative design of the models
brought to light that certain traditionally used set-constraints injury harshness
models were in a position to underrate the influence of several crucial
attitudinal attributes of the accidents.
11
2.4 CURRENT SCENARIO PREVAILING IN INDIA AS PER
THE LITERATURE
Bottom -up approach
In this approach, identification and analysis of comprehensive
set of transport problems are made.
Potential solutions to the problem are assessed in isolation and
in combination using a detailed transport model.
Combination which best solves the problems is taken as
preferred strategy.
2.5 RESEARCH ISSUES TO ADDRESS SUSTAINABILITY IN
URBAN TRANSPORT
Develop goal – oriented approach for developing urban
transport strategies in India
Developing model that reflects the impact of changing Land-
use and /or control policies , slum development, etc., on
transportation and vice versa
Activity – based modelling – still to be developed and
attempted in India for possibly better travel demand modelling
More realistic road layout modelling of modal spit ( Bi- cycle,
Two wheeler ,Auto, LMV, HMV walk, public transport
modes ) has to be developed.
12
2.7 CONCLUSION
A review of the existing literature did not reveal a sustainable
approach to urban street with multi – modal design. Previous research studies
focused on analysing each transportation mode independently and providing
insight on how model was perceive the arterial roadway environment.
Complete Street design can be accomplished by providing optimal facilities
for all the modes expected to be present on urban arterials. The concept of
complete street has gained interest in recent years. Policy makers, planners
and engineers are investing energy in promoting the idea of urban street that
accommodates all modes. This study provides a method for practioners to
design a urban street for better sustainable transport.
13
3. RESEARCH METHODOLOGY AND DESIGN
3.1 INTRODUCTION
The aim of this study is to provide a systematic description and
analysis of Sustainable road layout design using Fuzzy logic system. The
selection of methodological framework is justified on the ground that it
enables one to group the interlinkages between the various indicators of the
sustainability, while at the same time, highlighting the factors that influence
such interlinkages. A suburban area (Tambaram) in south Chennai,
Tamilnadu state, India, is chosen for conducting the analysis of sustainable
road layout. The present work is exploratory in its methodology and
theoretical framework.
3.2 MOTIVATION FOR THE STUDY
The motivation is to consider all model users when designing urban
street, the methods by which engineers and planners analyse their design have
yet to be fully developed. Typically when preparing new designs, planners
and engineers utilize many methods to access the impact of their design
ranging from estimating safety performance, operational performance,
determining air quality issues, addressing human factors consideration and
finally estimating the cost of the proposed design. The current state of art
methodology for urban street operational analysis is provided by the Highway
Capacity Manual (HCM) 2010 has the tool for engineers and planners that can
use to analyse the operational performance of Urban street, however it does
14
not provide a method to optimize their proposed design to meet perceived
level of services on urban street.
3.3 AIM OF THE STUDY
The aim of this thesis is to ensure safe, affordable, quick,
comfortable, reliable and Sustainable access to livable communities. The
study involves planning, design and orientation of road network configuration
to attain sustainability.
3.4 OBJECTIVE OF THE STUDY
The above aim is attained by achieving the following objectives
To identify the sustainable transport parameters for urban
street for heterogeneous traffic in the decision making process.
An approach for study of heterogeneous traffic using video
image processing.
To develop a sustainable road layout design model that
demonstrates the potential of possible best practice in
Sustainable urban Transportation system.
The objectives of this thesis would be achieved through a multi –
pronged approach.
15
3.5 COMPONENTS OF SUSTAINABLE TRANSPORT
Sustainable transport can be achieved through measures pertaining to
Transportation System Management - Access, not mobility
Energy Management - Moving People , not
cars
Safety Management - Reducing the accidents
frequency & severity
Environmental Management - Minimizing
Environmental
impacts
3.6 METHODOLOGY
The Methodology to attain a sustainable layout is explained in the
Figure 3.1. The flowchart explain the various indicators used for transport
system management, Energy management, safety management and
environmental management to attain a sustainable road layout design. The
modelling is done using fuzzy logic system.
16
Figure 3.1: Methodology of the Study
Modelling
Detailed assessment of each measure with Current Scenario was assessed using Fuzzy logic System for a road
layout design
Formulation of road layout design for
Arterial road Sub arterial road Collector street Local street
To attain the Sustainable Urban Transport system for live able communities.
17
3.7 CONTRIBUTION TO STATE OF THE KNOWLEDGE
The study utilizes the sustainable transportation planning concept
for Road layout design for suburban area. The use of multi objective
optimization method by fuzzy logic is present further in this thesis, will allow
engineers, planners and decision makers to optimize the component of an
urban street and obtain the perceived level of services across all modes on
urban street within a given right of way.
Specifically this study
1. Identifies the sustainable transportation parameters on urban
street for heterogeneous traffic in the decision making process.
2. An approach for study of heterogeneous traffic using image
processing techniques.
3. Develop a sustainable road layout model using fuzzy logic
system to design a sustainable road layout for suburban area.
The contribution of the new model provides practitioners with a
tool that will allow them to design street that will accommodate all modes
ideally a transportation engineer or planner will utilize the modelling
approach presented here in the preliminary design stage of a new facility or in
the redevelop process of an existing cross section of urban arterial. The
modelling approach presented takes into account the level of perceived
service of pedestrians, bicyclists, two wheeler, auto, LMV, and HMV with the
available right of way and required design standards.
18
4. STUDY AREA AND ITS CHARACTERISTICS
4.1 INDRODUCTION
Chennai metropolis is the fourth largest in the country,
encompassing an area of 1189 Sq.km and having an estimated population of
over 90 lakhs as of the year 2011.Consequent to global liberalizations, the
scale of developments and vehicular growth had increased tremendously in
the country and reflected in this metropolis as well. High population
disposition in the master plan have increased urban sprawl. Tambaram is one
such urban sprawl which has experiencing the tremendous growth of Chennai
Metropolis. Tambaram which was a small panchayat till 1964 is today a
selection grade Municipal town in Chennai metropolitan area.
Tambaram a suburban area in the south of Chennai has become a
transit zone offering to a number of other facilities of a city, schools,
hospitals, colleges, residential along the GST road and Tambaram velechery
road stretch reflects perfectly the character of city. Tambaram itself act like a
poly centred city growing eccentrically amidst the contrast. It is taluk head
quarters as well as the parliamentary constituency and there are a large
number of central government and state government regional and local
offices. It is gateway to Chennai from the south. It is a suburban icon. The area
of Tambaram municipality as Figure. 4.1 is 20.72 Sq.km. there are 39 wards in
the area. Total length of the road is 100.403 Kms. Populations as per 2011 census
is 1,64,830. Total no of roads in Tambaram municipality is 949. Grand southern
trunk road (GST road) is the arterial road in Tambaram municipality. Tambaram
– velechery road is sub arterial road. Gandhi road, shumuga road, mudichur road,
19
are the collector street and rajaji road, Bharatamatha road and agaram road are
the collector street and other roads are Local Street. All the roads are bitumen top
road and have been frequently maintained.
Tambaram become important with the opening of the Beach –
Tambaram electrified suburban line 1930 and its development has not since
been locked back. The establishment of Madras Christian College was
another landmark in its development. Today it is a centre for a number of
higher educational institutions in a transport hub linked as it is with NH45 and
the rail link to the south. The international and domestic airport of Chennai
adjoins Tambaram area by 12kms from the centre of Tambaram.
Figure 4.1: Tambaram Municipality base map
20
4.2 TAMBARAM AS A SUB URBAN – BOUNDARY CONDITION
The boundaries would extend from chrompet in the north up to
Irumbuillur on south along GST Road and from Medavakkam in the east to
Mudichur on the west along the lateral axis forming roughly a square, with
the current business district of West Tambaram and Tambaram Railway
Station as the centre of this city.
4.3 THE BUILT ENVIRONMENT
The Built Environment is the first identity for a city. It creates an
image for the city and has the power to imbibe a sense of pride in its citizens.
Tons of examples from around the world can be used to substantiate this
statement and the significance of the built environment to creating a positive
image for a city. Most of the built environment within the geographical
boundary of Tambaram city is devoid of architectural/ historic character.
Civic services in the form of water supply and drainage are grossly
inadequate, below par if not diabolical and needs immediate attention.
Pedestrian infrastructure is absent which is ironical because the region still
sees a large volume of pedestrian traffic. This also has meant that much of the
built-environment presents a picture of being over-crowded. Much of the
growth in this region has been in the form of plotted development which has
led to a clustered pattern with very little connection between neighbouring
developments except for an arterial road or the railway station. This pattern of
suburban development is synonymous with suburban communities in other
parts of the world, but poses some serious challenges when it comes to
urbanization. Going by the above assessment of Tambaram, by and large, the
built environment in this region needs a serious makeover. It will not only
help to solve a few of the current issues, it will go a long way in creating an
21
identity for the city which is currently labelled as Chennai’s bedroom and
Chennai’s rail and bus yard.
4.4 THE TRANSPORTATION NETWORK
Transportation is the life-line of a city. Goods and people move in
and out of the city and the health of a city depends on how easily this
movement is enabled. Tambaram’s location as shown in Figure 4.2 is a
premier suburb of Chennai means it is very well connected to the rest of
Chennai and by being Chennai’s gateway to the South-West, to the rest of
Tamil Nadu. The proximity of the international airport to this region also is to
Tambaram’s advantage enabling its global connectivity. The region is
geographically split into two halves East and West by the railway line and
GST Road. In the transverse direction, Velachery Road and Mudichur Road
split the region roughly into two halves North and South. While Tambaram’s
centre is very well connected to the rest of Chennai, Tamil Nadu, India and
the world, the connectivity in the inner parts of these four different quadrants
is a challenge. Reliance on private transportation, mostly in the form of two-
wheelers is very high. As far as goods traffic is concerned, there is an
extremely heavy reliance on the central markets of Tambaram. Truck
transportation of various sizes from small tempos to mini vans and Lorries are
the primary mode of goods transportation in the region. The continued
pressure of personal automobiles means the excellent infrastructure in terms
of the road network is choc a bloc and reduces the efficiency of moving
people and goods in the region. While the bypass roads and ring roads would
ease the pressure of traffic flowing through Tambaram, the pressure of traffic
flowing to Tambaram and for Tambaram poses to cause a lot of strain.
22
Figure 4.2: Images of Tambaram map
Figure 4.3: Hierarchy of road network map
Tambaram has a good geographical transport network ref
Figure 4.3. It has both the train and road modes of transport which daily
carries a large volume of traffic and caters to the needs of people. Tambaram
Road network inventory is discussed in Table 4.1.
23
Table 4.1: Inventory of Road Network
Road Name Hierarchy of roads
Width in M
No of Lanes
Footpath in M Land Use Encroachment
L R
GST Road Arterial Road 21 6 1 2 Com Moderate
Velachery Road
Sub arterial
road 18 6 1.5 1.5 Mixed Low
Mudichur Road
Subarterial road 7.5 3 - - Mixed Moderate
Gandhi road Collector street 9 4 1.5 1.5 Residential Moderate
Rajaji road Collector street 7.5 2 1.5 1.5 Mixed High
Agaram steet
Local street 7.5 2 - - Com High
4.5 THE ECONOMY
A city’s economy determines the importance of it not only at the
state or national level but at the international level. In terms of food and raw
materials, cities are seen to be consumers. In terms of processed goods and
services, cities are seen to be producers. What a city produces is key to its
prominence at the global level while what a city consumes is key to its
prominence at the local/ regional level. Till the emergence of IT in the MEPZ
complex, Tambaram region had some of the better leather tanneries of the
world, a few garment factories that had its own international market and the
erstwhile Standard Motors and a few other industries. Most of the other jobs
in the region were informal and unorganized. Tambaram has also been home
to some prestigious institutions which were the only sources of white collared
jobs in the region till not so long ago. Most of the people living in the region
worked in Chennai or other suburban areas of Chennai.
24
4.6 URBANIZATION
Tambaram which was a small panchayat till 1964 is today a
selection grade Municipal town in Chennai metropolitan area. It is gateway to
Chennai from the south. It is a suburban icon. The area of Tambaram
municipality is 20.72 Sq.km. there are 39 wards in the area. Total length of
the road is 100.403 Kms. Populations as per 2011 census is 1, 64,830. The
population growth in the Tamabaram is shown in the Figure 4.4 and Table 4.2
Table 4.2: Historical growth of population in Tambaram
Year Population (in lakhs)
Density of population per
sq.km
Average annual exponential growth rate
1950 0.25 144 - 1960 0.30 150 0.16 1970 0.45 211 0.33 1980 0.70 333 0.36 1990 1.00 482 0.30 2000 1.33 642 0.25 2010 1.64 791 0.19
0
20
40
60
80
100
120
140
160
180
1950 1960 1970 1980 1990 2000 2010
Popu
latio
n in
Tho
usan
ds
Year
Source: Tambaram Municipality
Figure 4.4: Population growth in Tambaram
25
Table 4.3: Urban conglomeration in India according 2001 census
Class Population size Population density /Sq.Km
Class I 100,000 and above 393 Source : Census 2010
The Urban conglomeration in India according to 2001 census for class I city is given in Table 4.3. Since different spaces have been allotted and space has been allotted for mixed residential, continuous building area and other things .The population is expected to increase 230167 and as the population increases the vehicular population will also increase.
4.7 LAND USE
The intensity and pattern of traffic depends upon land use arrangements. For planning purposes, a correct definition and inventory of the existing use of all lands are essential since every change in the use of the land causes a change in the intensity of traffic. In the existing land use Figure 4.5 more space has been allotted for residential area
Figure 4.5: Existing land use 2010
26
Figure 4.6: Percentage of land use 2010
4.7.1 The Future Land Use
In the future land use Figure 4.7 & Figure 4.8 space has been
allotted for mixed residential, continuous building area and was resulting in
lesser space allotted purely for residential purposes.
Figure 4.7: Future land use 2026
27
Figure 4.8: Percentage of land use 2026
4.7.2 Land Use Changes
As we can see in the future the land use has been classified so that
the entire land is being used correctly and to the fullest extent. As in Table 4.4
and Figure. 4.9 Provisions have been made and rules put accordingly for
mixed residential, and continuous building areas which where are not present
in the current land use. The entire low lying area in the present has been
converted into residential zone.
Figure 4.9 : Land use changes
28
Table 4.4: Land use changes
LAND USE 2010 2026
Residential 50 39
Mixed Residential - 13
Institutional 11 19
Commercial 1 1
Industrial 6 5
area around IAF - 2
Nonurban - 0
Agricultural 6 6
Waterbody 7 7
Ews - 2
continuous building - 6
Since different spaces have been allotted and space has been
allotted for mixed residential, continuous building area and other things .
4.8 MOTORIZATION
Indian cities have registered an astronomical growth in registered
motor vehicle in the last decade. Figure 4.10 shows the existing modal split
for Chennai. Table 4.5 gives deseriable modal split on Indian cities. Booming
economy, aspiraration to own a car, unmatched public transport (with respect
to demand, comfort or both), the government’s encouraging policies (open car
market, easy loan schemes), etc. are a few reasons for increasing motorization
at rapid rate.
29
0
1
2
3
4
5
6
7
8
2007 2008 2009 2010 2011 2012
no.o
f vec
hile
regi
stre
d in
che
nnai
(in L
akhs
)
Year
Vehicular growth
Two wheeler
cars,jeeps& taxis
buses
goods vechile
others
Source: - office of state Transport commissioner/UT administration
Figure 4.10: Growth of motor vehicle fleet by type of vehicle
Table 4.5: Desirable modal split for Indian cities (as percentages of total trips)
City population (in millions Mass transport Bicycle Other modes
0.10-0.25 30-40 30-40 25-35
Source : MOUD, Traffic and transportation policies and strategies in urban areas in India,
The estimates of vehicular growth are unimaginable and
threathining. Unfortunately, a similar growth has not been observed for bus
fleets of major transport undertakings in Chennai. Table 4.6 shows the
existing modal split for different Indian cities based on population size.
30
Table 4.6: Existing modal split in Indian cities (as percentage of total trips)
Existing modal split
City population
(in millions)
walk Mass transport
Intermediate public
transport car TW bicycle Total
fast slow Indian cities 0.10-0.25 37.1 16.4 10.4 20.1 3.3 24.1 25.7 100
Tambaram 0.10-0.25 19.1 9.3 14.4 13.9 11.2 29.6 21.6 100 Source for Indian cities: MOUD, Traffic and transportation policies and strategies in urban areas in India, Final report. Ministry of Urban development, Government of India, New Delhi
Source for Tambaram; Video Survey
4.9 EFFECTS ON MOBILITY
The average journey speed in 2007 on important city corridors in
the range of 17-26kmph.Table 4.7 shows the anticipated average journey
speed (kmph) on major roads in Indian cities for category -1. The journey
speed on the roads in study area is give in the Table 4.8.
Table 4.7 Anticipated average journey speed (kmph) on major roads
Population 2007 2011 2021 2031
Category 1 < 5 26 22 15 8 Sources:- MOUD, Traffic and transportation policies and strategies in urban areas in India, Final report. Ministry of Urban development, Government of
India, New Delhi.2008
31
Table 4.8: The journey speed on the roads in study area
Sl.No. Road Name
Hierarchy of Roads
Journey Speed in (Km/h) LMV AUTO HMV TW
1. G.S.T Road
Arterial Road 25-50 15-30 35-50 25-45
2. Velachery main road
Sub arterial road 20-30 20-25 30-40 20-40
3. Mudichur road
Subarterial road 15-25 15-20 10-20 15-20
4. Gandhi road
Collector street 20-25 15-20 20-25 25-35
5. Rajaji road Collector street 20-25 12-18 15-20 20-25
6. Agaram steet Local street 15-20 15-20 - 20-25
4.10 CONGESTION INDEX
The average congestions index is 0.3 the Figure 4.11 shows the
congestion index of the study area.
Figure 4.11: Congestion index
......Average congestion index
32
4.11 Safety
The traffic accident has come to be considered as the third deadliest
killer. The Table 4.9 gives the total no of accidents in the study area. The
growth in the number as well as the speed of motor vehicles has far outpaced
improvements to the road and other traffic facilities. The heavy toll of deaths,
injuries and property damage in motor vehicles accidents on streets and roads
is an international problem.
Table 4.9: Total Number of accidents in the study area
Sl. No. Road Year No of Accident
1. GST Road 2010 390
2011 439
2. Velachery Road 2010 117
2011 120
3. Mudichur Road 2010 52
2011 30
4. Gandhi road 2010 43
2011 52
5. Rajaji road 2010 22
2011 45
6. Agaram steet 2010 19
2011 22
As the road users are increasing it must follow by the increase in
accidents. When vehicle population increases every day, the extent of
transportation space in Tambaram area is static. When “V” is increasing and
33
“C” is static, the ratio of V and C also increases so also the accidents. The
Table shows the static
4.12 PARKING
Tambaram is a mixed residential area in Chennai. A summary of
parking characteristics in various roads is given in Table 4.12.
Table 4.10: Parking characteristics
Sl. No.
Roads Hierarchy
Width of the Roads
M
Parking Type
Length in m
Peak Accumulation
(PCU)
1. G.S.T Road – infront of Ponnusamy hotel
Arterial Road 10 On – car
parking 0.25 10
2.
G.S.T road – Tambaram bustand , before vasanthabhavan hotel
arterial road 10
Off – car & two
wheeler parking
20
3.
Velachery main road – bharadha madha street to IAF road Jn
Sub arterial
road 9 On – Car
parking 0.45 25
4.
Velachery main road – opp Selaiyur Govt.Municipality school
Sub arterial
road 9 On – Car
parking 0.30 20
3. Mudichur road Sub
arterial road
8 On- car parking 0.20 11
4. GST road -Gandhi road incoming
Collector street 7
On street – TW
parking
0.53 30
5. Rajaji road Collector street 7
On street – TW
parking 0.23 12
34
The commercial hub, mofassel bus stand and railway junction at
Tambaram intersection have created a major demand for parking. Most of the
adjoining properties do not have off- street parking space. Provision of
dedicated off-street parking space in Tambaram area may serve to relive
some problems, but land availability is the constraint.
4.13 IDENTIFICATION OF ISSUES
1. No Development without violation
2. No open spaces
3. Traffic congestion
4. No consideration for Pedestrians
With the some part of residential land being allotted to mixed
residential and other land use like continuous building as the population is
increasing, the traffic also bound to increase in these places.
4.14 CONCLUSION
To summarize this section Tambaram is characterised by high
density urban area, absence of proper control on land-use, lack of proper
roads and parking facilities poor public transport, lack of road-user discipline,
etc.
This level and type of urbanization in India has caused many
problems, especially with regards to its impact on the demand for
infrastructure facilities. Urban transport system has come under heavy strain
and this has adversely affected the quality of life of the urban dwellers. Mass
transport facilities in the Tambaram are grossly inadequate for providing fast,
comfortable and convenient travel. This has resulted in heavy shift of
35
commuter’s patronage from mass transportation to private and intermediate
transport and consequently a huge increase in intermediate and private vehicle
ownership.
The resultant effects are increased traffic congestion and transport
brone pollution, heavy fuel consumption and transport – brone pollution
heavy fuel consumption, poor level of services to the commuters, etc.
So, it can be clearly said that the current system and trends in
Tambaram suburban are not sustainable.
36
5. STUDY OF HETEROGENEOUS TRAFFIC USING
VIDEO IMAGE PROCESSING TECHNIQUES
5.1 INTRODUCTION
One of the fundamental measures of traffic on a road system is the
volume of traffic using the road in a given internal of time (1). It is termed as
flow and it is expressed in vehicles per hour or vehicles per day. Knowledge
of the vehicular volume using a road network is important for understanding
the efficiency at which the system works at present and the general quality of
service offered to the road uses(2). Empirical traffic data are the basic input in
any traffic management scheme and in analyzing traffic flow models(3).
Very limited empirical data are available for this purpose. For collecting data
under heterogeneous traffic conditions several types of equipments are used.
Recently, video images processing systems (VIPS) – techniques are being
used. The advantages of video film based method are to device continuous
and regular record of traffic flow. In this chapter , an attempt is made to study
a microscopic analysis of traffic data using video image processing software
TRAZER.
5.2 VIDEO SHOOTING METHODOLOGY
The camera with the tripod step should be placed in an appropriate
location to shoot the video. The location can be selected based on the
following parameters ref Figure 5.1
(i) Angle
37
(ii) Focus
(iii) Zoom
(iv) Lighting Condition
(v) Shutter Speed
(vi) Height
Figure 5.1: Video shooting methodology
5.2.1 Angle
Camera should be placed above the central lane and should look
straight middle of the road. The tripod can be placed maximum one lane left
/right to the central lane which comes down to around + 15 degrees. The
Horizontal view angle must be adjusted in such way that the camera covers
the width of the road. The vertical view angle should be set such that it cover
20-25 meters from camera. The camera should be placed at a height of
10-12m (Height of fly over).
38
5.2.2 Focus
Focus determines the sharpness of the vehicles in the video. To get
the Sharpe image of the vehicles the camera should be focused. This is
normally done by using the focus ring in the profession cameras near the front
of the lens housing.
5.2.3 Zoom
Zoom determines the magnification of the vehicle. More the zoom,
bigger the vehicles look the zoom factor should be determined visually such
that the vehicles are not too big or too small.
5.2.4 Lighting Condition
The video should be shot with sufficient lighting. In the case of
bright lighting care should be taken such that light doesn’t fall on the camera
directly. The lighting conditions changes with the time of the day and iris is
adjusted.
5.2.5 Shutter Speed
Shutter speed determines the sharpness of moving objects. High
shutter speed means more sharp objects and less motion blur. So when shooting a
video of vehicle moving with high speed the shutter speed should be high. A
camera has its shutter set to 1/60, each frame will be exposed for 1/60 second.
5.2.6 Height
A video camera with the above discussed shooting methodology is
placed on the fly – over bridge which is in right angles to the subject approach
exactly on the centre line of the road.
39
5.3 TRAZER : SOFTWARE
TRAZER is a revolutionary new technology to classify traffic for
planning purpose. Unlike competing technologies, it uses the same techniques
as used by humans to identify objects like vehicles, that is the power of sight
with cutting edge electronic cameras as its eyes and server class PC as its
brain it provides an extremely robust platform to do traffic counting
(Figure 5.2).
Figure 5.2: Microscopic data analysis using TRAZER
Trazer is speedily designed for Indian conditions and can handle
multiple Lane dense traffic and does not assume lane discipline and works
perfectly with slow moving or even stationary traffic and gives 95-100%
result even in the large number of classes of vehicles.
40
5.4 DATA ACQUISITION BY VIDEO SURVEILLANCE
METHOD
The Practice is recommended by the Indian Road congress for the
traffic census on urban road in IRC SP19-2001. The traffic volume content is
taken in an urban Arterial Road (G.S.T Road) Tambaram railway station and
Sub arterial road (Velachery Road and Mudichur Road) and for collector
street (camp road, Gandhi road, rajaji road)for the period of 8.00A.M to
12.00 A.M and to 4.00 P.M. to 8.00 P.M for three consecutive day in the
middle of the week (namely Tuesday, Wednesday, Thursday) The days are
selected that there is no abnormal traffic conditions like a seasonal fair. Data
extracted from the film using TRAZER software are discussed in detail in the
following sections.
Tambaram has a good geographical transport network ref
(Figure 5.3). It has both the train and road modes of transport which daily
carries a large volume of traffic and caters to the needs of people. Tambaram
Road network inventory is discussed in Table 5.1.
Figure 5.3: Tambaram road network
41
Table 5.1: Inventory of road network of the video shooting roads
Road Name Width Lanes Footpath
Land Use Encroachment L R
GST Road 21 6 1 2 Com Moderate
Velachery Road 18 6 1.5 1.5 Mixed Low
Mudichur Road 7.5 3 - - Mixed Moderate
Gandhi road 9 4 1.5 1.5 Residential Moderate
Rajaji road 7.5 2 1.5 1.5 Mixed High
Agaram road 7.5 2 - - Com High
5.5 DATA ANALYSIS FROM TRAZER AND RESULTS
A detailed discussion on the data collected using TRAZER is
necessary to know its accuracy and usefulness. The data collected from the
video surveillance is stored and analyzed at central Data centre unit. The data
storage will be done in a database setup on a server class machine with 5TB
RAID hard disk ref (Figure 5.4).
A specific advantage of the TRAZER for mixed traffic is its ability
to track vehicles, even when there is a lateral movement. It could also track
vehicles, even under dense traffic condition. Trajectories obtained from
TRAZER are smoothened using as local regression techniques. Velocities and
acceleration values are obtained by performing first and second order
differentiation on the trajectory equation. Since the trajectories of all vehicles
are available, it is possible to measure the lateral and longitudinal spacing
maintained by different vehicles w.r.t to nearest neighbor vehicle. Whenever
the vehicles are coring an imaginary line drawn on the road, classified flow,
speed and occupancy data are obtained. Occupancy measured in this study is
the time taken by any vehicle cross the imaginary line.
42
Figure 5.4: Central data center
Each vehicle is associated with a feature vector of five dimensions.
In an offline analysis phase the features are computed for vehicles falling into
various categories. According to Figure 5.5 The features used in the system
are shape features and for extracting these features it uses system known as
hierarchical image process. The features for some vehicles are shown in
Figure 5.6.
Figure 5.5: Procedure for image process
43
Figure 5.6: Vehicle extraction
5.6 AVERAGE VEHICLES VOLUMES
This format stores vehicles counts per each interval. The interval
size and vehicle categories are configurable. Table 5.2 and 5.3 shows the
volume of traffic on arterial road(G.S.T road). Tables 5.4 to 5.7, shows the
volume of traffic on sub arterial road (Velachery road , Mudichur Road), and
Table 5.8 gives the volume count in collector street such as camp road,
Gandhi road, Rajaji road.
5.6.1 GST Road - Arterial Road
The Table 5.2 and 5.3 gives the total no of vehicle passing in the
G.S.T road during peak hour and non- peak hour. since it is a arterial road the
capacity of the road is 7500 pcu /hour. The average vechile crossing the G.S.T
road during the peak hour is 4500pcu/hour. The v/c ratio is lesser than
1and ranges between 0.5- 1.1 in the peak hour at present. This Ratio is
expected to double by 2026 as this road is a major highway which connects
Chennai City to southern Tamil Nadu.
44
Table 5.2: Average vehicles volumes in G.S.T road towards Chrompet
S.No. Timing LMV Auto HMV TW Total
Peak hours
1. 8-9 am 1172 291 338 1989 3790
2. 9-10 am 1253 328 266 2412 4259
3. 4-5 pm 1445 224 435 2115 4219
4. 5-6 pm 1509 254 309 1943 4015
5. 6-7pm 1683 246 298 2360 4587
6. 7-8 pm 1691 231 384 2265 4571
Non peak hours
7. 10-11 am 1157 287 289 1844 3577
8. 11-12 am 1065 242 257 1689 3253
Table 5.3: Average vehicles volumes in GST road towards Vandalur
Sl.No. Timing LMV Auto HMV TW Total
Peak hour
1. 8-9 am 558 209 419 1721 2907
2. 9-10 am 782 258 224 2444 3708
3. 4-5 pm 510 247 222 802 1781
4. 5-6 pm 785 221 253 1058 2317
5. 6-7 pm 1108 263 288 1620 3279
6. 7-8 pm 1602 237 345 2488 4672
Non peak hour
7. 10-11 am 875 216 223 1851 3165
8. 11-12 am 823 199 277 1512 2811
45
5.6.2 Velachery Main Road
Table 5.4 and Table 5.5 shows the number of vehicle count in both
peak hours and non peak hours. The v/c ratio ranges between 0.5- 0.8 in the
non peak hour to peak hour.
Table 5.4: Average vehicles volumes in Velachery road towards Tambaram
S.No. Timing LMV Auto HMV TW Total
Peak hours
1. 8-9 am 490 236 230 1280 2236
2. 9-10 am 574 249 217 1061 2155
3. 4-5 pm 398 214 184 910 1706
4. 5-6 pm 421 224 211 874 1730
5. 6-7 pm 558 231 247 1088 2124
6. 7-8 pm 569 224 260 1167 2220
Non peak hours
7. 10-11 am 440 195 196 760 1591
8. 11-12 am 405 201 200 866 1672
This Road will see Heavy Traffic within the Next 5 years due to the
development seen in Selaiyur, Madipakkam, Pallikaranai, Kelambakkam,
ECR and OMR. This road is one of the major roads which connect the
Eastern coastal areas to Tambaram.
46
Table 5.5: Average vehicles volumes in Velachery road towards Madippakam
Sl.No. Timing LMV Auto HMV TW Total
Peak hours
1. 8-9 am 564 229 235 1084 2112
2. 9-10 am 595 246 279 1195 2315
3. 4-5 pm 386 217 190 794 1587
4. 5-6 pm 400 232 223 811 1666
5. 6-7 pm 578 240 271 1109 2198
6. 7-8 pm 502 226 294 1214 2236
Non peak hours
7. 10-11 am 433 219 201 976 1837
8. 11-12 am 429 223 214 735 1601
5.6.3 Mudichur Road
The Table 5.6 give the volume of traffic in both peak hour and non
peak hour. The capacity of the road is 2000pcu/hour. The average number of
vehicle during peak hour is 2500pcu. The v/c ratio ranges between 1.23 – 1.1
in the peak hour .This road has a lot of HMV especially Lorries. This State
highway will be a Major route connecting the Outer Ring Road area to
Tambaram. As a Result Traffic is expected to increase manifold on this Road
in the next 5-6 years and will become a Arterial Road in the long term.
47
Table 5.6: Average vehicles volumes in Mudichur road towards Tambaram
Sl.No. Timing LMV Auto HMV TW Total Peak hours
1. 8-9 am 543 258 295 1211 2307 2. 9-10 m 608 266 305 1357 2536 3. 4-5 pm 340 269 280 865 1754 4. 5-6 pm 376 230 297 810 1713 5. 6-7 pm 487 253 315 1085 2140 6. 7-8 pm 453 244 329 1133 2159
Non peak hours 7. 10-11 am 500 233 256 954 1943 8. 11-12 am 408 241 267 765 1681
5.6.4 Collector Roads
The Table 5.7 gives the volume of traffic in the collector street such
as camp road, Gandhi road and Rajaji road . the average volume of traffic is
1200 pcu/ hour. The capacity of the road is 1500pcu/hour. The v/c ratio
comes to be around 0.5-0.8 during the peak hour. These road are developing
as mixed residential and hence in future more vehicle is expected.
Table 5.7: Average vehicles volumes in Data for Collector roads
Sl.No. Timing LMV Auto HMV TW Total Camp road
1. 10-11 am 117 131 20 972 1240 Gandhi road
1. 11-12 am 145 79 21 969 1214 Rajaji road
1. 1-2 pm 219 136 43 844 1242
48
5.7 VEHICLE TRAJECTORY
The trajectory includes Vehicles images location and as well as its
mapped on road location. The trajectory is very fine grained and is updated
every 40 milli seconds ref Figure 5. The Table 8 gives the vehicle trajectory
such as average speed, occupancy of four category of vehicle HMV, LMV,
Auto, TW for every 40 milli Seconds.
Figure 5.7: Vehicle trajectories
Table 5.8: Vehicle trajectories
S. No.
Date/
StartTime
Date/
EndTime
Average Velocity
LMV AUTO HMV TW
1 2012-04-04 00:00:00 2012-04-04 00:01:00 68.75 60.82 74.86 57.84
2 2012-04-04 00:01:00.0400 2012-04-04 00:02:00.0400 97.62 0 62.5 49.33
3 2012-04-04 00:02:00.0800 2012-04-04 00:03:00.0800 76.79 0 50.07 54
4 2012-04-04 00:03:00.1199 2012-04-04 00:04:00.1199 68.83 48.64 51.01 41.99
5 2012-04-04 00:04:00.1600 2012-04-04 00:05:00.1600 92.4 47.38 90.65 78.25
49
Some of the vehicle trajectories obtained over a certain road length
are
Real time vehicle classification HMV, LMV, Three Wheelers,
Two Wheelers in both day and night.
Flow statistic: Vehicle flow at particular time velocity of
traffic, quell a length etc.
Lane wise automatic red light (traffic stoppage) detection.
Extensive vehicle trajectory log (time + vehicle ID, Vehicle
Location in image world co-ordination
The proposed approach is applied on test sequence representing 30
minutes of real video, in which the ground truth was obtained manually.
Vehicle’s counting is performed for each lane and classification is done using
the objects size histogram. Results of counting and classification are shown
respectively in Table 5.9.
Table 5.9: Accuracy of object detection, classification, and vehicle trajectory
Ground Truth
Detected objects
Accuracy detection
Accuracy Classification
Accuarcy vehicle
trajector 115 110 96% 92% 93%
50
5.8 CONCLUSION
Microscopic data collection under mixed traffic condition is one of
the difficult tasks faced by the research community. Several data collection
system that was tried in the past proved to be inefficient for mixed traffic.
Image processing based data collection systems such as TRAZER is useful in
collecting vehicle trajectory data over a certain road length. The TRAZER
help in Real time Data that can be analysis. TRAZER is the image processing
based system which caters specifically to the heterogeneous traffic of the
developing countries. We have presented a comprehensive review of
TRAZER software techniques for vehicle detection and vehicle trajectory in
the Tambaram area, Sudurban at Chennai. The research always seems tailored
to local environment which makes the proposed method only useful in
specified environment. This fact reflects from the side the diversity,
complexity of real traffic scenes. To deal with higher demand in ITS and
more complex traffic scenes, the methods are required to percept and self –
adapting to the surroundings, and the robustness of algorithm needs to be
improves.
51
6. SUSTAINABLE ROAD LAYOUT DESIGN FOR
LIVE ABLE AREA (TAMBARAM) WITH THE
AID OF FUZZY LOGIC SYSTEM
6.1 INTRODUCTION
Road transport is vital to the economic development and social
integration of the country. To make road transport a sustainable one we focus
mainly on four critical factors such as transport management, safety
management, energy management and environment management. All these
must contribute jointly to get a sustainability of 100% in road transport
system management. To provide a sustainable transport, the criterion that is to
be concentrated is the layout of the road, which when selected, must provide
an optimal design. So in the proposed work, we are designing a road by
concentrating on the major parameters factors like road layout, road width,
population of the area concerned and the Average number of vehicle
movements with each LMV, HMV, Auto and two wheelers passes is taken in
to consideration with the land use and accident case of 2013 by using them we
are designing four road layouts. In this proposed work I intend to employ
fuzzy logic system for the process which chooses optimal road layout design
and also the individual contribution of each and every factor involved in the
sustainable transport for a specific area.
The Current Road network is grossly insufficient to handle the
present Traffic volume and hence a new, widespread Road system is required.
In the proposed work a design of roads with proper lanes for LMV, HMV,
52
TW, pedestrian path, Auto along with adequate footpath width is being
envisaged for the major part of Tambaram area. The main congestion in
widening of the roads is the lack of space and the allocation for commercial
area for the humans to survive. This flow chart explains the course of our
proposed methodology by means of fuzzy logic process for the present road
system with appropriate lane allocation.
6.2 NEED FOR SUSTAINABLE INDICATORS AND ITS
LIMITATIONS
To quantify the progress towards the objective of sustainable
transportation it is crucial to define as selected targeted and compressed
variable that reflect public concerns and are of use to decision makers. The set
of indicators constructed according to the available data and of smaller sizes
are more convenient to use but may fail to include important impact. In
contrast larger set can be more comprehensive but the costs associated with
the data collection process can be prohibitive.
In the transportation literature existing indicators mainly reflects
the economic, social and environmental effects of a system, thus sustainability
indicators are generally categorized in these three dimensions. There are also
additional dimensions mentioned in some studies such as technical,
operational or institutional. When the number of indicators is large being able
to identify an indicator as a member of a single category simplifies any
decision making analysis.
Sustainability is characterized by very different indicators and a
system would be evaluated as sustainable if it performs reasonably well with
respect to all of the specified Indicators. A system having average indicators
values may be evaluated as more sustainable than a system with the highest
value for most of the Indicators and lowest value for some of Indicators.
53
6.3 INDICATORS OF SUSTAINABILITY
Various researchers are conducting research to define measures of
sustainability developments, but no definitive set of measure has been arrived
at as acceptable by everyone. Indicators of sustainability can be the units of
measuring progress towards sustainable developments.
There are three basic functions of Indicators- simplification,
quantification and communications. Indicators generally simplify in order to
make complex phenomena quantifiable so that information can be
communicated. The general public is concerned about sustainable
developments and the environment. They like to be informed about the state
of the environment and the economy and how and why they are changing.
Performance should be measured in ways that meet both
governmental standards and public needs and wishes. A primary performance
measure can be devised which indicates how regional travel time delay is
affected by the recommended strategy. Other secondary benefits could be
identified and measured that are of intent to stakeholder group. A clear
additional benefits is how equitably people across a region share in the
primary benefit of congestion relief. For some traveller, having more travel
choices, especially safe non-motorized mode is a benefit.
Other measurable benefits indicators include reduction in health
impacts, environmental damages and accident costs as travellers shift to
transit, ride share and non-motorized modes.
54
The University of reading gives the indicators for sustainable
transportation in terms of car use and total passenger travel, short journey,
real changes in the cost of transport and freight traffic while there is no simple
or single means of achieving efficient transportation measures for the study
could include the following
Congestion Index
Reduction in pollution levels
Per capita energy consumption
Reduction in travel time or the travelling costs
Percentage of excess of capacity over the demand
Benefit-cost ratio (B/C) of travel. B/C >1 is a sustainable
conditions
6.4 INDICATOR USED IN THE SUSTAINABLE ROAD
LAYOUT DESIGN - INPUT PARAMETERS: FOR MODEL
USING FUZZY LOGIC SYSTEM
The indicators used in the sustainable road layout design as input
parameters for model using fuzzy logic system is discussed in Table 6.1.
55
Table 6.1: Details about the indicator selected to evaluate the road layout sustainability
Dimension Indicator Description Measurement unit Source Preferred
Direction
Transportation System
Management
Urbanization
a. To reduce the change in Landuse pattern
% Share Census
b. To ensure the population growth
Density – no of person /sq.km Census
Motorization
a. To increase productivity and efficiency of transport supply
Passenger * kilometre per lane kilometre
*hour
Traffic Data
b. To increase the capacity of transport supply
Road length or Road area
Geomentric of roads
Modal share
a. To increase the number of modal choices
Number of modal choices per each trip for different purposes at
different times in a day
Traffic data PCU
b. To ensure equality in using the transport services
Square metre * hours for
certain mode during critical period (peak
hours)
Traffic data
Effects on mobility
a. To reduce congestion index
value
b. To reduce Volume / capacity ratio
Value
56
Table 6.1: (Continued)
Dimension Indicator Description Measurement unit Source Preferred
Direction
Safety management
Accident To reduce
accident frequency
Accident numbers, accident
density per kiolmeter of road length
Accident data
parking
To increase the off street parking facilities
No of off street parking area
available
Municipality data
Energy Management
Pedestrian facilities
To increase the walking mode for short distance
Width of footpath and
crossing facilities
Geomentric of roads
NMT services To increase the
non-motorised transport
Seperate lane for non-
motorised transport
Geomentric of roads
Environmental management
Air pollution To reduce the
carbon emission
Tones/1000 sq.km
Pollution control board
Noise pollution
To reduce noise level in the study area
Dbl level Pollution control board
a) Motorization
The average number of vehicle in that specified area is also a factor
affecting in sustainable transport. The vehicles are broadly divided into 4
major categories they are, LMV (Low Motor Vehicles), HMV (Heavy Motor
Vehicles), Auto and Two wheelers. The number of all these values is given
and based on this values the corresponding output layout are be mentioned
b) Road width
To design an optimal road, the first factor to be considered is the
width of the existing roads. The Main Arterial Road in Tambaram is the GST
57
Road. The Current Width of the road is 21m with no lane Demarcation.
Hence to Improve Traffic Flow, a proposed method is designed with fuzzy
logic to provide an optimal layout of the existing road to ensure a sustainable
transport. Google road map are shown in Figure 6.1.
Figure 6.1: (a) Road map from Tambaram to Velachery (b) Road map of GST road (c) Road map from Tambaram to Mudichur (d) Road map of Camp road
c) Average population in the specified area
In the particular area, the subsequent factor to be taken into report
is the amount of average population. The intensity and sample of traffic
depend mainly upon land use arrangements. For development purposes, an
accurate definition and inventory of the presented use of all lands are
necessary as every alter in the use of the land causes a modify in the intensity
of traffic. There is no population in the national highway roads in many cases.
Therefore we have to spotlight on the region where the population rate is
58
high. Hence we are categorizing the population in the shape of percentage
from zero to hundred in our suggested method.
d) Accident case management
Road accident costs are an imperative component of outside costs
of traffic, a considerable part is connected to fatal accidents. The assessment
of fatal accident costs critically depends on the accessibility of an estimate for
the economic value of an arithmetical life. 35% of people are harmed by
accident in the total population of Chennai.
e) Land usage
The intensity and sample of traffic depends upon land use
arrangements. A proper definition and inventory of the presented use of all
lands are necessary for development purposes as every alter in the use of the
land causes a modify in the intensity of traffic.
The road is planned by erecting the approximate lanes across the
road by considering all these reasons as the input parameters. All these input
parameters are united and delivered as single input to the fuzzy logic system
for more process. Pitiable traffic management particularly in respect of the
uncontrolled driving of buses, Share auto and auto rickshaws, incompetent
traffic control at intersections, deprived road geometrics, lack of public
understanding, road users’ disorderliness and incompetent movement,
indeterminate bus stops, etc. are the most important causes of road accidents.
For our suggested method, the total road accident happened in Tambaram area
is of 1472 and it is specified as input in 2013. The accident management case
can be afforded based on the dissimilar layout.
59
The pie chart describe in Figure 6.2 the land allocation of tambaram
with different parameters such as agriculture, water body, residential,
industrial, low lying area commercial, institutional, excluded area. In the
future space has been allotted for mixed residential, continuous building area
and resulting in lesser space allotted purely for residential purposes. With the
some part of residential land being allotted to mixed residential and other land
use like continuous building the population is going to increase and the traffic
is bound to increase in these places due to Commercialization of Existing
Residential Plots.
Land use in 2013:
Figure 6.2 : Land usage allocation for different parameters in 2013
In our method the input for the land usage is given by the numerical
value 0.1, 0.2, 0.3, 0.4, where each value represents for different P, Q, R, S
road layouts respectively. Each numerical value has its own standards and if
the value is given in different format the chart for the corresponding layout
will not be displayed and will display out of limit in command window during
processing.
60
6.5 FUZZY LOGIC SYSTEM
It is the procedure of nonlinear mapping of input data cluster to an
output scalar data cluster. In essence, a fuzzy logic system comprises four
vital segments such as crisp input values, fuzzification, inference,
de-fuzzification and crisp output values
6.6 FLOW CHART OF THE PROPOSED FUZZY LOGIC
SYSTEM
Crisp input values
Figure 6.3: Flow chart of the proposed Fuzzy logic system
Sustainable road layout
Start
Fuzzy logic process
Crisp input values
Fuzzificationnn
Defuzzification
Inference
Crisp output values
Stop
Input parameters
LMV
Human population
Two wheelers
Road Width
HMV
Autos
Land usage
Accident case
61
At the outset, the input constraints are pooled together and
furnished to the fuzzy logic mechanism. As they are not capable of being
treated straight in the FLS, fuzzification of the input constraints is performed.
Crisp data for input parameters
Table 6.2: Crisp input data
Vehicle type Road width Average
population Crisp data
Low Low lying Minimum 1
Medium Average Normal 2
High Large Maximum 3
6.6.1 Fuzzification
Fuzzification is the procedure of change of the crisp set of input to
fuzzy set by means of fuzzy linguistic variables Figure 6.4, fuzzy linguistic
terms and membership functions. A linguistic variable can be in the shape of
words or sentences which signify a normal or simulated language. A linguistic
variable is usually decayed into a group of linguistic terms. In our procedure
width (low lying, average, larger), number of vehicles (low, medium, high),
number of population (zero, minimum, maximum) are the linguistic variables
and their parallel linguistic term. Membership functions are employed in the
fuzzification, to map the non-fuzzy input values to fuzzy linguistic terms. A
membership function is made use of to measure a linguistic term.
62
Figure 6.4: Factors influencing fuzzification
6.6.2 Inference
It is the procedure of devising the mapping from a pre-defined
input to an output by means of fuzzy logic. Usually the fuzzy inference is
based on the fuzzy rules which are saved as the data base. The estimates of
the fuzzy rules and the blend of the outcomes of the distinct rules are executed
by means of fuzzy set functions. The functions on fuzzy sets are not the same
as those on the non-fuzzy sets. In accordance with the fuzzy values for every
characteristic that are produced in the Fuzzification procedure, the Fuzzy
Rules are also created.
General form of Fuzzy Rule
“IF A THEN B”
The “IF” part of the Fuzzy Rule is known as the “antecedent” and
also the “THEN” part is called as the “conclusion” in fuzzy rules.
Fuzzification
Membership
Linguistic Linguistic
63
Table 6.2: Fuzzy rules
Vehicle Width Population Layout Low Low lying Minimum S Low Low lying Normal S Low Low lying Maximum S Low Average Minimum S Low Average Normal Q Low Average Maximum Q Low Large Minimum S Low Large Normal Q Low Large Maximum Q
Medium Low lying Minimum S Medium Low lying Normal S Medium Low lying Maximum Q Medium Average Minimum S Medium Average Normal Q Medium Average Maximum Q Medium Large Minimum S Medium Large Normal Q Medium Large Maximum R
High Low lying Minimum P High Low lying Normal R High Low lying Maximum Q High Average Minimum P High Average Normal R High Average Maximum R High Large Minimum P High Large Normal R High Large Maximum R
64
6.6.3 Defuzzification
After the inference step is complete, the general outcome obtained
is treated as a fuzzy value. The outcome thus obtained is de-fuzzified to arrive
at the ultimate crisp output. The input furnished for the De-fuzzification
process is the fuzzy set and the output achieved is a solitary number
Figure 6.5. De-fuzzification is executed in accordance with the membership
function of the output variable.
Figure 6.5: Defuzzification process
6.6.4 Crisp Output Value
At last the fuzzy outputs are transformed to crisp data by means of
appropriate member ship function.
Crisp data for sustainable road layout
Table 6.3: Crisp output data
Sustainable road layout Crisp data P 1 Q 2 R 3 S 4
Defuzzification Crisp data
Membership Function
Fuzzy output set
65
(a) (b)
(c) (d)
Figure 6.6: (a) shows the traffic flow in one of the area in Tambaram with existing lanes, (b) shows allocation vehicles in no parking area, (c) subway which is allocated with platform shops, fig(d) shows roads which are left unconstructed
The images given in Figure 6.6(a) to 6.6(d) are obtained from the
concurrent research in the Tambaram area for the project work and
highlighted to develop the area by effectively applying our project outcomes.
Tables 6.4-6.10 contain the data gathered from the concurrent investigations.
66
6.7 SUSTAINABLE ROAD LAYOUT
6.7.1 Road layout Design 1: P
Figure 6.7: 21m road layout as P layout
This road layout Figure 6.7 represents the 21m road which is
mentioned as P. This is the sustainable layout for the GST road which is
considered as the heart of Tambaram area. In this road layout, there are two
separate sections which are considered as over bridge and main road. All
together there are 12 lanes considering both over bridge and main road with
each lane capacity of 720 vehicles per lane and two lanes are allocated for the
67
convenience of the people who walks out through the small path. D represents
allocation for two wheelers with 1.5m and 4m wide respectively on both sides
of the road, G represents allocation for LMV+Auto+Two wheelers. Now
considering on the main road, there are 8 lanes including two pedestrian paths
where E is allocated for the pedestrian path on both side of the road with 2m
each. B represents allocation for HMV with 2m wide on both side and F
represents allocation for LMV+Auto with space allocation of 2m wide. The
spacing between each road is 0.33m wide and H represents area for bridge
construction. In over bridge the gap between the two roads is 0.25m and in
main road the gap is of 0.366m between each road.
6.7.2 Road Layout Design 2: Q
Figure 6.8: 18 m road layout as Q layout
The layout of the road in Figure 6.8 represents 18m wide road
which is mentioned as Q. In this layout the allocation for the pedestrian path
is at the left most side and at the right most side of which is represented by E
with a width of 0.5m, followed by allocation of road for two wheelers with a
width of 4m and it is represented by D on either side of the road. F represents
the road allocation for LMV + Auto with a width of 2m each sides. Finally B,
68
which is allocated for HMV with a width of 2m.and LMV+ Auto is allocated
in two lanes due to the increase in the number of vehicles. Due to the increase
in the width of the road the allocation for each lane is highly spaced. The
capacity of each lane is around 520vehicles/lane. The spacing between each
road is 0.25m for easy mode of traffic.
6.7.3 Road Layout Design 3: R
Figure 6.9: 9 m road layout as R layout
The road layout in Figure 6.9 represents 9m road which is
described as R. In this layout, E represents the path for pedestrian with a
width of 0.5m and located in both the end of road layout. Mostly the
pedestrian path is allocated only where the population is present or in the area
where the distance between the starting point and designations is very small.
Followed by the pedestrian path there are two lanes for two wheelers with a
width of 2m and 1.5m respectively. G represents road allocation for
LMV+Auto+Two wheelers with a width of 3m and finally B with width of
total 2m which represents HMV. The capacity of each lane is about
421vehicles/hour.
69
6.7.4 Road Layout Design 4: S
Figure 6.10 illustrates the road layout with a road width of 7.5m
which is represented as S and to modify this road we have suggested the road
plan with twin ways comprising the main road and the subway. In the sub
way there are 6 lanes which are allocated only for two-wheelers and heavy
moving vehicles.
Figure 6.10: 7.5m road layout as S layout
H represents the area for the construction of the bridge and D, A, B
and F represent the road allocations for Two wheelers, LMV, HMV,
LMV+Auto respectively. The capacity of each lane is 721vehicles/lane. As
70
the subway is allocated, the traffic flow will be easy and larger number of
traffic can be made to allow without any distortion or congestion.
Description: LMV – light motor vehicles, HMV – heavy motor vehicles,
TW – tow wheelers, PP – pedestrian path
Let, LMV – A, HMV – B, Auto – C, TW – D, PP – E,
LMV+Auto – F, LMV+Auto+TW – G, Bridge work – H. Then
the sequencing order for each road layout is Table 6.5:
Sequence of road layout
Table 6.5: Sequence of road layout
Road layout Width of road(m) Sequence
P 21 HDDGGDDH+HEFBGGBFEH
Q 18 EDBFFBDE
R 9 EDBGGBDE
S 7.5 HEFAAFEH+HBDDDDBH
To obtain the sustainable layout, all the four criteria such as
transport management, safety management, energy management and
environment management which affect the sustainability must be satisfied.
Urbanization and motorization are the twin objectives of effective transport
system management system and our focus is mainly centered on reducing
traffic congestion during peak hours. We intend to design an optimal road
based on input specification (road width, population of the area and Average
number of vehicle passes on the road) in order to ensure unhindered traffic. If
these inputs tend to fail during peak hours, then a part of the traffic may be
diverted to another route which is in a nearby location. To ensure
71
environmental management, alternate fuels such as natural gas, propane,
methane, and biogas may be provided. In the future one of the sources of fuel
is hydrogen, which is converted to liquid fuel. Hence, in this investigation, we
put forward an innovative layout with maximum optimal solution leading to
sustainability by means of the fuzzy logic system. Thus, with the help of this
technique we arrive at an optimal road layout where each individual factor
contributes to a specified level.
The Table 6.6 represents the roads which are used in the
experiment to calculate the sustainability and also the input parameters such
as average number of vehicles, road width and average number of population
of the specified road.
Table 6.6 Roads with its layout and contribution
Road Names
Input parameter Output Average
no of vehicles
Road width
Average no of
population
Sustainable road Contribution
G.S.T Road 2870 21 10 P
TM-50% SM-30% EM-10% Egm-10%
Camp Road 2877 9 40 R
TM-20% SM-10% EM-10% Egm-40%
Velachery Main Road 2000 18 80 Q
TM-20% SM-10% EM-40% Egm-30%
72
Table 6.6 (Continued)
Road Names
Input parameter Output Average
no of vehicles
Road width
Average no of
population
Sustainable road Contribution
Mudichur Road(SH 110) 1434 7.5 10 S
TM-10% SM-50% EM-20% Egm-20%
Velachery Side Road 1478 10 60 Q
TM-20% SM-10% EM-40% Egm-30%
MEPZ to Camp Road 2700 7.5 10 S
TM-10% SM-50% EM-20% Egm-20%
Rajaji Road 2100 7.5 5 S
TM-10% SM-50% EM-20% Egm-20%
Agaram Road 1975 7.5 39 S
TM-10% SM-50% EM-20% Egm-20%
Depending on these parameters the optimal road is designed and
the contribution of Transport Management (TM), Safety Management (SM),
Energy Management (EM) and Environment Management (Egm) are found
out.
73
7. RESULT AND DISCUSSION
7.1 OUTPUT FOR THE ROAD LAYOUT P
Figure 7.1: MATLAB output for the road layout P
Figure 7.1 shows the GUI output for the layout of P. Here the input
parameters are assigned and the corresponding road layout is obtained. The
contribution of TM and SM are of 50% and 30% each. EM and Env
contributions are 10% each. The model diagram shows the model output for
our proposed method. Here we have to furnish the input parameters such as
vehicles, width, population, accident case, land usage and by means of the
process we achieve appropriate layout with layout design and the individual
contribution of each and every distinct criterion.
74
In Figure 7.1 the average number of vehicle is given by splitting in
4 different types as LMV, HMV, two wheelers and auto and the input is given
as 1000, 200, 1400, 300 and width as 20 and population as 30 which lies
under the sequence HDDGGDDH+HEFBGGBFEH and the corresponding
output will be layout P. In this layout the contribution for TM and SM are
50% and 30% each. In this layout the capacity of each lane is
720vehicles/lane. Hence this layout has two sections so the traffic can flow
through the perceptive lanes without any disturbance. So the safety
management will be high so its contribution will be low. Highlighting on
energy and environment management, both seeks the same level of
distribution. Accidental management (AM chart), Transportation Modal (TM
chart) and its corresponding land usage is shown in the GUI output. In TM
chart 1,2,3,4 represents LMV, HMV, Auto, and two wheelers.
7.2 OUTPUT FOR THE ROAD LAYOUT Q
Figure 7.2: MATLAB output for the Road layout Q
This GUI output Figure 7.2 shows the output of Q layout. Here the
input for vehicle is LMV, HMV, tow wheelers and auto are 175, 279, 500,
75
246 respectively and width is 15 and population as 75 which lies under the
sequence EDBFFBDE and the corresponding layout is Q and the capacity of
each lane is 520vehicles/hour. So the input for vehicle is given less than the
capacity of total vehicles of all lanes. The contribution for each criterion is
also described. As the amount of total vehicle is less hence the contribution
will be more in the transport management and it is given as 20%. The
accident case will be high and its contribution will be low and it is gives as
10%. Here the path for the pedestrian is allocated separately so the two
wheelers can be reduced and hence energy consumption will be reduced and
the environment pollution will be reduced. Hence both contribute to an
average amount of 30% and 40% each. Among our road layout velachery
main road and velachery side road satisfies this case. The lanes allocated for
two wheelers are two and the vehicles per lane will be reduced by using the
pedestrian path. Accidental management (AM chart), Transportation Modal
(TM chart) and its corresponding land usage is shown in the GUI output. In
TM chart 1,2,3,4 represents LMV, HMV, Auto, and two wheelers.
7.3 OUTPUT FOR THE ROAD LAYOUT R
Figure 7.3: MATLAB output for the road layout R
76
This output Figure 7.3 provides for the layout of R. here the input
of vehicle given as LMV, HMV, tow wheelers and auto are 608, 305, 1875,
266 respectively and width as 10 and population as 40 which lie under the
sequence EDBGGBDE. The sustainable layout design is also given in the
output. The capacity of each lane is 421vehicles/hour. The contributions for
each factor are also given with transport management as 20%. Since the
vehicles are to be diverted in another area, the corresponding area allocation
has to be managed in advance. The safety management will be 10% because
the traffic conjunction will be low. On focusing energy and environment
management there will be 30% and 40% respectively. Since there is separate
allocation for pedestrian path the environment will be not so polluted and the
energy will be reduced in very small amount. Accidental management (AM
chart), Transportation Modal (TM chart) and its corresponding land usage is
shown in the GUI output. In TM chart 1,2,3,4 represents LMV, HMV, Auto, and two wheelers.
7.4 OUTPUT FOR THE ROAD LAYOUT S
Figure 7.4: MATLAB output for the Road layout S
77
This GUI output Figure 7.4 is given for layout S. here the input
given for vehicle as LMV, HMV, tow wheelers and auto are 117, 20, 972, 131
respectively and width as 7.5 and population as 25 which lies under the
sequence HEFAAFEH+HBDDDDBH then the output with corresponding
layout is provided. Even the contribution of each factor is also given with a
pie graph. In this layout there are two roads as divided into main road and
subway. The contribution for transport management is 10% because large
amount of traffic can be diverted to subway and hence the main road will
provide more area for the movement of vehicles freely. In subway there are 4
lanes for two wheelers during peak hour: during non-peak hour among 6
lanes, 2 are for two wheelers and HMV. Hence the safety management will be
at a percentage of 50. Hiring on energy management will be at 20% as no
other sources are allowed for the traffic and environment management will be
only 20%. Mudichur Road, MEPZ to Camp Road, Rajaji Road and Agaram
Road satisfies this condition. Accidental management (AM chart),
Transportation Modal (TM chart) and its corresponding land usage is shown
in the GUI output. In TM chart 1,2,3,4 represents LMV, HMV, Auto, and two
wheelers. Figures 7.9 to 7.11 also explains each road layout and produces
each with different contribution. The table below shows each layout with
different contribution.
Table 7.1: Contribution level for different parameters
Road layout
Transport Management
Safety Management
Energy Management
Environment Management
P 50 30 10 10
Q 20 10 40 30
R 20 10 30 40
S 10 50 20 20
78
7.5 ACCIDENT CASE
Cost of accident is an important parameter in the economic
appraisal of transportation projects. Even though there are several methods of
calculating the accident costs the choice of a particular method primarily
depends on the objectives of the intended project and largely with national
objectives. In India, very few studies have been carried out on the subject and
the studies already undertaken lacked in area coverage and precise cost
estimation. International analysis showed a high degree of variation in cost of
accidents. It is felt necessary to carry out detailed accident cost studies for
Chennai city. Accident cost need to be estimated for urban and rural areas
separately.
In average the total number of accident in 2013 is 1472 for the
estimated area in Tambaram. The graph Figure 7.5 below describes the
accident detail which contributes due to the traffic conjunction and it is
represented separately for four different layouts of the developed roads. The
values of contribution for layout P, Q, R, S is given as 1030, 1324, 1178, 736
respectively. The value is determined by the following equation as,
Accident case = Total number of accident -(total number of accident ×SM contribution)
100
In our method the input for the accident case is given by the
numerical value 1,2,3,4, where each value represents for different P, Q, R, S
road layouts respectively. Each numerical value has its own standards and if
the value is given in different format the chart for the corresponding layout
will not be displayed and will display out of limit in command window during
processing. Here SM stands for Safety Management contribution of each
separate layout and hence 4 different graph is obtained
79
(P) (Q)
(R) (S)
Figure 7.5: Accident management graph for 4 different layouts of 2013 in Tambaram
7.6 MOTORIZATION
Motorization refers to the type of traffic which flows in the lanes of
4 different type of road layout. Here the Low Motor Vehicles (LMV), Auto,
Heavy Motor Vehicles (HMV), Two-wheelers are described and it is
represented in the graph format. These are the data retrieved from the real
time experiment and utilized to produce a bar graph Figure 7.6.
80
(P) (Q)
(R) (S)
Figure 7.6: Motorization for 4 different road layouts
7.7 CONCLUSION
Attention must be given on the population in the precise area, width
of each and every accessible road and their facility etc for the assessment of
the sustainable transport in a particular urban area. However it is a hard
assignment. The numbers of vehicles that pass through the road normally
determine the capacity the road. We have focused on eight roads of
Tambaram area, located in Chennai in our proposed paper. Width of each
81
road, population around the particular area, average number of vehicles in the
road during peak hours, accident case and land usage in 2013 has been found
out regarding these eight roads. We have acquired through the utilization of
our proposed method sustainable road layout and its corresponding
contribution for each and every factor such as transport management, safety
management, energy management and environment management etc. The
fuzzy logic concept is made use of in our procedure to provide optimal road
layout. There are a total of 19 lanes in existing roads but in our proposed
method there are total of 42 lanes including the pedestrian path.
Consequently by our proposed method there is an increase of 23% in total
lanes. A change in the mode of travel must be taken into account which
focuses on increasing the pedestrian path and reducing two wheelers to travel
in a short distance, and the spatial pattern of travel which is anticipated to
increase the area for travelling. If we put it in another way, the spatial
separation of activities and the distribution of land-uses increase the need to
travel. As a result, it is essential to consider a spatial layout that can facilitate
to support a better eco-friendly transport choice. The future work can be
focused on developing a road which provides better contribution for all the
four factors such as transport management, safety management, energy
management and environment management are to be considered in our future
road projects. So special attention must be paid for this purpose. The existing
largest road width is 21m in Tambaram area. This road width can be increased
by widening the road by removing unnecessary buildings, unwanted parking
areas, roads which are left unconstructed, road side shops etc from the road.
Accordingly the sustainability can be enlarged further in the future for making
higher contribution in all the four parameters such as transport management,
safety management, energy management and environment management.
Only the government can help doing this so that the involvement for each
factor can be greater than before.
82
8. CONCLUSION
This thesis analysed an existing data set to determine the street
characteristics for sustainable layout and combined the result into multi-
objective optimization model for road layout. Fuzzy logic model to estimate
traveller’s perception of sustainable layout where developed in the pursuit of
complete road layout tool
The fuzzy logic model developed for the transport management,
safety management, energy management, environmental management showed
that the number of through lanes, the posted speed limit and the width of the
sidewalk and bike lane respectively. These characteristic are among the most
highly correlated street characteristic for sustainable road layout.
When compared to the existing regression analysis model, the
fuzzy logic modelling techniques was determined to be more powerful and
accessible model to determine the sustainable road layout design. This
techniques provides partitions with the distribution of sustainable rating and
there model require fewer number of variables that are easily accessible.
The various indicators of sustainable road layout where
incorporated into the proposed fuzzy logic multi-object optimization model.
The objective function of the model was to balance the probabilities of
sustainable ratings, constrained by a series of factors, and to prevent them
from falling below the minimum probability calculated. The objective
function was subjected to decision variables and constants selected from the
data used and from the standards. The constraint that brought the street
83
characteristics for the three modes together was the ROW width. This
constant compared a given ROW width value with an equation for ROW
width containing the values the street charactersties. The scenarios showed
that fuzzy logic model provides information about sustainable design
satisfaction with different street design.
The fuzzy logic multi-objective optimization model surpassed the
previously created model by including four travel modes simultaniouedy into
one optimization model.
It has been designed using readily available software (math lab)
thus creating a scholastic interface that allows easy manipulation of the
components. However, the model can be further designed into a user-friendly
interface that, when given to a designer, would allow to simple operation of
inserting the given ROW width in a cell and a function button would be
clicked for the model to start the iteration process. The final results would be
the values for the street charatersists included in the design for street segment.
The complete street design will accommodated LMV, HMV, pedestrian,
bicycle, two wheelers with the same ROW while achieving an sustainable
layout level determine by the designer.
The objectives this thesis was to design fuzzy logic model for
sustainable road layout design which has been accomplished and
demonstrated in this document.
84
9. SUMMARY OF THE STUDY
The aim of this study is to provide a systematic description and
analysis of sustainable road layout design using fuzzy logic system. The
selection of methodological framework is justified on the ground that it
enables one to grasp the interlinkages between the various indicators of the
sustainability, while at the same time, highlighting the factors that influences
such interlinkages.
A suburban area is chosen for conducting the analysis of
sustainable road layout.
The study involves planning, design and orientation of road
network configuration to attain sustainability.
The study is framed with design comprising of
1. Attainment of self similarity
2. Path prioritization for improvement to serve as a tool for road
administrative.
Specific conclusions drawn from the study are
1. An approach for study of heterogeneous traffic using video
image processing is attempted.
2. A model for sustainability road layout has been developed
The present work is exploratory both in its methodology and
theoretical framework.
85
10. SCOPE FOR FURTHER STUDIES
The fuzzy logic multi-objective optimization model proposed with
this thesis was an approach selected due to the structure of the data and the
goal of the model. It is certain that different approaches can be explored in
future studies such as evolutionary computation. In addition, future model
could incorporate cost calculation and construction budget that the
optimization model is indirectly include when restricting the ROW width.
Further, the fuzzy logic multi-displine optimization model does not include
the transit mode due to the limits of the data collected through video
surveillance study. Additional data collection could be conducted to allow for
the inclusion of the transit mode in future studies.
Several different option of the model can also be created where the
user would have the ability to enter certain preferences, including the weight
of a certain mode in comparison with the other modes. Also, a single model
can be created to combine several different sceneries when the user could
select the constraints and the weights for each mode.
Overall the entire model performed well and provides a unique
approached to the design of urban streets which can be termed complete street.
The method provided within this document provide insight into the
precipitation of level of services by bicycle and pedestrian model user on
urban streets, as well as providing a method for engineers and planners to
design urban complete street to refute travellerar’s perception of screeches
and relevant design standard.
86
REFERENCES
[1] Anjali Awasthi, Satyaveer S. Chauhan, Hichem Omrani (2011) Application of fuzzy TOPSIS in evaluating sustainable transportation systems Expert Systems with Applications 38, 12270–12280.
[2] Awasthi, A., & Omrani, H. (2009). A hybrid approach based on AHP and belief theory for evaluating sustainable transportation solutions. International Journal of Global Environmental Issues, 9(3), 212–226.
[3] Basler, E. (1998). Measuring the sustainability of transport. Materials of NRP 41 (Vol.M3, pp. 1–13). National Research Programme 41.
[4] Beinat, E. (2001). Multi-criteria analysis for environmental management. Journal of Multi-Criteria Decision Analysis, 10–51.
[5] Beynon, M. (2002). DS/AHP method: A mathematical analysis, including an understanding of uncertainty. European Journal of Operational Research, 140(1), 148–164.
[6] Black, W. R. (1996). Sustainable transportation: A US perspective. Journal of Transport Geography, 4, 151–159.
[7] Black, J., Paez, A., & Suthanya, P. (2002). Sustainable urban transportation: Performance indicators and some analytical approaches. ASCE Journal of Urban Planning and Development, 128(4), 184–209.
[8] Bond, R., Curran, J., Kirkpatrick, C., & Lee, N. (2001). Integrated impact assessment for sustainable development: A case study approach. World Development, 29(6), 1011–1024.
[9] Browne, D., O’Regan, B., & Moles, R. (2008). Use of ecological footprinting to explore alternative policy scenarios in an Irish city-region. Transportation Research Part D, 13(5), 315–322.
[10] Buckley, J. J. (1985). Ranking alternatives using fuzzy numbers. Fuzzy Sets Systems, 15(1), 21–31.
87
[11] Chang, P., & Chen, Y., 1991. Fuzzy number in business conditions monitoring indicators: Fuzzy set methodologies in economic condition. In Fuzzy engineering toward human friendly systems, Proceedings of the international fuzzy engineering symposium 91, Yokohama, Japan (pp. 1091–1100).
[12] Chen, M., Tzeng, G., & Liu, D. (2003). Multi-criteria task assignment in workflow management systems. In IEEE Proceedings of the 36th Hawaii international conference on system sciences.
[13] Delgado, M., Verdegay, J. L., & Vila, M. A. (1992). Linguistic decision making models. Intelligent Journal of Intelligent System, 7, 479–492.
[14] Dempster, A. P. (1968). A generalisation of Bayesian inference. Journal of the Royal Statistical Society, 205–247.
[15] Denoeux, T., & Smets, P. (2006). Classification using belief functions: The relationship between the case-based and model-based approaches. IEEE Transactions on Systems, Man and Cybernetics B, 36(6), 1395–1406.
[16] Dubois, D., & Prade, H. (1982). A class of fuzzy measures based on triangular norms. International Journal of General Systems, 8, 43–61.
[17] ECOSYMPA. <http://www.aire198.org>. El-Diraby, T. E., Abdulhai, B., & Pramod, K. C. (2005). The application of knowledge management to support the sustainable analysis of urban transportation infrastructure. Canadian Journal of Civil Engineering, 32, 58–71.
[18] Fischer, T., Wood, C. M., & Jones, C. E. (2002). Policy, plan and programme environmental assessment in England, the Netherlands and Germany: Practice and prospects. Environment and Planning B (29), 159–172.
[19] Goedkoop, M. J., & Spriemsma, R. (2000). The eco-indicator – A damage oriented method for Life Cycle Impact Assessment. Methodology report and methodology (2nd ed., pp. 82–132), report (INRETS).
88
[20] Guine, J. B. (2002). Handbook on Life Cycle Assessment. An operational guide to the ISO standard (p. 704). London: Kluwer Academic.
[21] Herrera, F., & Verdegay, J. L. (1993). Linguistic Assessments in Group Decision. In Proceedings of the first European congress on fuzzy and intelligent technologies,Aachen (pp. 941–948).
[22] Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making methods and application. New York: Springer-Verlag.
[23] Jay, S., & Handley, J. (2001). The application of environmental impact assessment to land reclamation practice. Journal of Environmental Planning and Management, 44(6), 765–782.
[24] Jeon, C., Amekudzi, A., & Guensler, R. (2008). Sustainability assessment at the transportation planning level: Performance measures and indexes. In Proceedings of the 87th annual meeting of the transportation research board (TRB), Washington, DC (pp. 1–26).
[25] U. Chattaraj and M. Panda,(2010) some applications of fuzzy logic in transportation engineering Challenges and Applications of Mathematics in in Science and Technology AMIST held in Mathematics department, NIT Rourkela.
[26] Zimmermann, H.J. (2001), “Fuzzy set theory and its applications”, Fourth edition, Kluwer Academic Publishers, Boston/Dordrecht/ London.
[27] Zadeh, L.A. (1965), “Fuzzy sets”, Information and Control , vol. 8, pp 338–353.
[28] Bellman, R.F. and Zadeh, L.A. (1970), “Decision making in a fuzzy environment” Management Science, vol. 17, pp 14–164.
[29] Kaufmann, A. and Gupta, M.M. (1985), “Introduction to fuzzy arithmetic theory and its applications”, Van Nostrand Reinhold Company, New York.
[30] Klir, G.J. and Folger, T.A. (1988), “Fuzzy sets, uncertainty, and information”, Prentice Hall, Englewood Cliffs, New Jersey.
89
[31] Zadeh, L.A. (1979), “A theory of approximate reasoning” Machine Intelligence, vol. 9, pp 149–194.
[32] Gazis, D.C., Herman, R. and Rothery, R.W. (1961), “Nonlinear follow–the–leader models of traffic flow” Operations Research, vol. 9, pp 545–567.
[33] Chakroborty, P. and Kikuchi, S. (1999). “Evaluation of the General Motors based carfollowing models and a proposed fuzzy inference model”, Transportation Research Part C, vol. 7, pp. 209–235.
[34] Chakroborty, P. and Kikuchi, S. (2003), “Calibrating the membership functions of fuzzy inference system: Instantiated by Car–following Data” Transportation Research Part C, vol. 11, pp. 91–119.
[35] Henn, V. (2000), “Fuzzy route choice model for traffic assignment”, Fuzzy Sets and Systems, vol. 116, pp 77–101.
[36] Hoogendoorn–Lanser, S. (1998), “Structured modelling of multi – modal urban travel choice behaviour”, 4th TRAIL PhD Congress.
[37] Wei, W., Zhang, Y., Mbede, J.B., Zhang, Z. and Song, J. (2001), “Traffic signal control using fuzzy logic and moga”, IEEE, vol. 2, pp 1335–1340.
[38] Niittymaeki, J. and Maeenpaeae, M. (2001), “The role of fuzzy logic public transport priority in traffic signal control” Traffic engineering & control, vol. 42, pp 22–26.
[39] Hoogendoorn, S., Hoogendoorn–Lanser, S. and Schuurman, H. (1998), “Fuzzy perspectives in traffic engineering”, Research Report, TRAIL Research School, Delft, report on behalf of Dutch Ministry of Transport.
[40] Chen, L.C., May, A.D. and Auslander, D.M. (1990), “Freeway ramp control using fuzzy set theory for inexact reasoning”, Transportation Research, vol. 24A, pp 15–25.
[41] Hellendoorn, H., and Baudrexl, R. (1995), “Fuzzy neural traffic control and forecasting”. International Joint Conference of the 4th IEEE International Conference On Fuzzy Systems and The 2nd International Fuzzy Engineering Symposium IEEE International Conference on Fuzzy Systems, vol. 4, IEEE, Piscataway, pp 2187–2194.
90
[42] Kirschfink, H., Lange, R. and Jansen, B. (1997), “Monitoring, control and management on the motorway network in Hessen using intelligent traffic modeling”, Proceedings of the ’97 ITS Word Conference, Berlin.
[43] Busch, F., Cremer, M., Ghio, A. and Henninger, T. (1994), “A multi-model approach for traffic state estimation and incident detection on motorways”, Proceedings Of The First World Congress On Applications Of Transport Telematics And Intelligent Vehicle- Highway Systems, Paris, vol. 3, pp 1245–1252.
[44] S.K. Das, A. Goswami, S.S. Alam, Multi-objective transportation problem with interval cost, source and destination parameters, European Journal of Operational Research 117 (1999) 100–112.
[45] A.K. Bit, Fuzzy programming with hyperbolic membership functions for multi-objective capacitated solid transportation problem, The Journal of Fuzzy Mathematics 13 (2) (2005) 373–385.
[46] A.K. Bit, M.P. Biswal, S.S. Alam, Fuzzy programming approach to multi-objective solid transportation problem, Fuzzy Sets and Systems 57 (1993) 183–194.
[47] F. Jimenez, J.L. Verdegay, Uncertain solid transportation problem, Fuzzy Sets and Systems 100 (1998) 45–57.
[48] L. Li, K.K. Lai, A fuzzy approach to the multi-objective transportation problem, Computers and operation research 27 (2000) 43–57.
[49] F. Waiel, Abd El-Wahed, A multi-objective transportation problem under fuzziness, Fuzzy Sets and Systems 117 (2001) 27–33.
[50] Omar M. Saad, Samir A. Abass, A Parametric study on transportation problem under fuzzy environment, The Journal of Fuzzy Mathematics 11 (1) (2003) 115–124.
[51] G.A. Vignaux, Z. Michalewicz, A genetic algorithm for the liner transportation problem., IEEE Transactions on Systems, Man and Cybernetics 21 (2) (1999) 445–452.
91
[52] E.H. Mamdani, S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man-Machine Studies 7 (1975) 1–13. Fuzzy logic toolbox user’s guide, 2005.
[53] L. Shi, J. Sun, S. Lu, M. Yin, Flexible planning using fuzzy description logics: theory and application, Applied Soft Computing 9 (1) (2009) 142–148.
[54] L. Bhounek, On the difference between traditional and deductive fuzzy logic, Fuzzy Sets and Systems 159 (10) (2008) 1153–1164.
[55] Zbigniew Michalewicz, Genetic Algorithm+Data Structures=Evolution Programs, third revised and extended edition, Springer International Edition First Indian Reprint. p-2, 2009.
[56] D.E. Goldberg, J. Richardson, Genetic algorithms with sharing for multimodal optimization, in: Genetic Algorithms and Their Application: Proceedings of Second International Conference on Genetic Algorithms, 28–31 July, Lawrence Erlbaum Associates, Cambridge MA, USA, 1987.
[57] N. Srinivas, K. Deb, Multiobjective function optimization using nondominated sorting in genetic algorithms, Evolutionary Computation Journal 2 (3) (1995) 221–248.
[58] T.J. Ross, Fuzzy Logic with Engineering Applications, John Wiley and Sons (Asia), PTE. Ltd., Singapore, 2005.
[59] Andriantiatsaholiniaina LA, Kouikoglou V, Phillis Y (2004) Evaluating strategies for sustainable development: fuzzy logic reasoning and sensitivity analysis. Ecol Econ 48:149–172.
[60] Awasthi A, Omrani H (2009) A hybrid approach based on AHP and belief theory for evaluating sustainable transportation solutions. Int J Glob Environ Issues 9(3):212–226.
[61] Awasthi A, Chauhan SS, Omrani H (2011) Application of fuzzy TOPSIS in evaluating sustainable transportation systems. Expert Syst Appl 38:12270–12280.
[62] Beynon M (2002) DS/AHP method: a mathematical analysis, including an understanding of uncertainty. Eur J Oper Res 140(1).
92
[63] Browne D, O’Regan B, Moles R (2008) Use of ecological footprinting to explore alternative policy scenarios in an Irish cityregion. Transp Res Part D 13:315–322.
[64] Burgess MA (1977) Urban traffic noise prediction from measurements in the metropolitan area of Sydney. Appl Acoust 10:1–7.
[65] Buckley JJ (1985) Fuzzy hierarchy analysis. Fuzzy Set Syst 17: 233–247.
[66] Cornelissen AMG, van den Berg J, Koops WJ, Grossman M, Udo HMJ (2001) Assessment of the contribution of sustainability indicators to sustainable development: a novel approach using fuzzy set theory. Agric Ecosyst Environ 86:173–185.
[67] Dalal-Clayton B, Bass S (2002) Sustainable development strategies, 1st edn. Earthscan Publications Ltd, London, p 358.
[68] Dubois D, Prade H (1987) Possibility theory. An approach to computerized processing of uncertainty. Plenum Ed, New York.
[69] Dunn EG, Keller JM, Marks LA, Ikerd JE, Gader PD, Gosey LD (1995) Extending the application of fuzzy sets to the problem of agricultural sustainability. In: Proceedings of 3rd International Symposium on Uncertainty Modelling and Analysis (ISUMA ’95). IEEE Computer Society, Washington DC, pp 497–502.
[70] ECMT (2004) Assessment and decision making for sustainable transport. European Conference of Ministers of Transportation, Organization of Economic Coordination and Development, http:// www.oecd.org.
[71] EMEP/EEA (2009) Air pollutant emission inventory guidebook 2009, Technical report no. 9/2009, www.eea.europa.eu
[72] Ferreira L, Charles P, Tether C (2007) Evaluating flexible transport solutions. Transp Plan Technol 30(2–3):249–269.
[73] Guine JB (2002) Handbook on life cycle assessment. An operational guide to the ISO standard. Kluwer, London, p 704.
93
[74] Haghshenas H, Vaziri M (2012) Urban sustainable transportation indicators for global comparison. Ecol Indic 15:115–121.
[75] Henn V (2000) Fuzzy route choice model for traffic assignment. Fuzzy Set Syst 116:77–101.
[76] Ibeas A, dell’Olio L, Barreda Montequín R (2011) Citizen involvement in promoting sustainable mobility. J Transp Geogr 19:475– 487.
[77] INFRAS, CE Delft, ISI, and University of Gdansk (2007) Handbook on estimation of external costs in the transport sector. Report for the European Commission, produced within the study Internalisation Measures and Policies for All External Costs of Transport (IMPACT).
[78] Keeney RL, Raiffa H (1993) Decisions with multiple objectives. Cambridge University Press, Cambridge.
[79] Klir GJ, Yuan B (1995) Fuzzy sets and fuzzy logic. Theory and applications. Prentice-Hall PTR, Upper Saddle River.
[80] Kouikoglou VS, Phillis YA (2009) On the monotonicity of hierarchical sum-product fuzzy systems. Fuzzy Set Syst 160(24):3530– 3538.
[81] Krueger RA, Casey MA (2008) Focus groups: a practical guide for applied research, 3rd edn. Sage Publications Inc., Thousand Oaks.
[82] Kunreuther H, Grossi P, Seeber N, Smith A (2003) A framework for evaluating the cost-effectiveness of mitigation measures. Columbia University, USA.
[83] Litman T (2008) Well measured. Developing indicators for comprehensive and sustainable transport planning. Victoria Transport Policy Institute.
[84] Lozano R (2008) Envisioning sustainability three-dimensionally. J Clean Prod 16:1838–1846.
[85] Mageean J, Nelson J (2008) The evaluation of demand transport services in Europe. J Transp Geogr 11:255–270.
94
[86] Mamdani EH (1977) Application of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Trans Comput 26 1182–1191.
[87] Mori K, Christodoulou A (2012) Review of sustainability indices and indicators: towards a new City Sustainability Index (CSI). Environ Impact Assess Rev 32:94–106.
[88] Munda G (1995) Multicriteria evaluation in a fuzzy environment. Theory and applications in Ecological Economics.
[89] Physica-Verlag, Heidelberg Organization of Economic Cooperation and Development (OECD) (1996) Towards sustainable transportation. OECD Proceedings of the Vancouver Conference, OECD.
[90] Phillis Y, Andriantiatsaholiniaina LA (2001) Sustainability: an illdefined concept and its assessment using fuzzy logic. Ecol Econ 37:435–456.
[91] Rassafi AA, Vaziri M (2005) Sustainable transport indicators: definition and integration. Int J Environ Sci Technol 21:83–96.
[92] Rossi R, Vescovi R, Gastaldi M (2006) Analysis of results from an SP survey on goods transportation choices of manufacturing companies based on the theory of fuzzy sets. In Dry ports, freight depots, logistic centres and competitive development. (In Italian).
[93] Venezia, 17 Nov 2005. Aracne Edizioni, Italy, pp 29–44.
[94] Rossi R, Vescovi R, Gastaldi M (2007) An application of fuzzy sets and possibility theory to the goods transportation choices of manufacturing companies. Proceedings of 22nd European Conference on Operational Research - Stream: Transportation and Logistics - Invited session, Prague, July 8–11, 2007.
[95] Rossi R, Gastaldi M, Vescovi R (2009) A methodological approach to evaluating the sustainability level of a transportation service. Sustain Dev Plan 4(2):411–424, WITPress, ISBN: 978- 1-84564-181-8.
95
[96] Rossi R, Gastaldi M, Gecchele G, Vescovi R (2010) Using a fuzzy approach for evaluating sustainability of transportation system pollution-reducing policies: a case study. Proceedings of TRB 89th Annual Meeting, Washington D.C., 10–14 January 2010.
[97] Rossi R, Gastaldi M, Gecchele G (2011) Fuzzy systems approach versus possibility theory approach for representing customers' stated preferences on freight transport services.
[98] In: Mussone L, Crisalli U (eds) Transport Management and Land-Use Effects in Presence of Unusual Demand. Selected Papers, vol 1797.38.
[99] Franco Angeli, Milan, pp 275–296, ISBN: 978-88-568-4174-9.
[100] Roy B, Hugonnard D (1982) Ranking of suburban line extension projects on the Paris Metro System by a multi-criteria method. Transp Res Rec 16A(4):301–312.
[101] Russo F, Comi A (2011) Measures for sustainable freight transportation at urban scale: expected goals and tested results in Europe. J Urban Plan Dev 137(2):142–152.
[102] Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New York.
[103] Saaty TL (1994) How to make a decision: the analytic hierarchy process. Interfaces 24(6):19–43.
[104] Silvert W (1997) Ecological impact classification with fuzzy sets. Ecol Model 96:1–10.
[105] Tao C-C, Hung C-C (2003) A comparative approach of the quantitative models for sustainable transportation. J East Asia Soc.
[106] Transp Stud 5:3329–3344, http://www.easts.info/2003journal/ papers/3329.pdf.
[107] TRB (1997) Toward a sustainable future; addressing the long-term effects of motor vehicle transportation on climate and ecology.
[108] TRB Special Report 251, National Academy Press, Washington, DC.
96
[109] United Nations World Commission on Environment and Development (1987) Our common future. Oxford University Press, Oxford.
[110] Vaní ek J, Vrana I, Aly S (2009) Fuzzy aggregation and averaging for group decision making: a generalization and survey. Knowl- Based Syst 22:79–84.
[111] Wood C (2002) Environmental impact assessment: a comparative review, vol 405, 2nd edn. Prentice-Hall, UK.
[112] Yager RR (1978) Fuzzy decision making including unequal objectives. Fuzzy Set Syst 1:87–95.
[113] Yu W (1992) ELECTRE Tri: Aspects méthodologiques et manuels d’utilisation. Document de LAMSADE, 74, Université Paris- Dauphine.
[114] Zito P, Salvo G (2011) Toward an urban transport sustainability index: a European comparison. Eur Transp Res Rev 3:179–195.
[115] Zuidgeest MHP (2005) Sustainable urban transport development: a dynamic optimization approach, PhD Thesis, University of Twente, Enschede. http://doc.utwente.nl/57439.
[116] Ashley, R., and Hopkinson, P. ~2002!. “Sewer systems and performance indicators—Into the 21st century.” Urban Water, 4~2!, 123–135.
[117] Balkema, A. J., Preisig, H. A., Otterpohl, R., and Lambert, F. J. D. ~2002!. “Indicators for the sustainability assessment of wastewater treatment systems.” Urban Water, 4, 153–161.
[118] Baltic 21. ~2000!. “Indicators on sustainable development in the Baltic Sea region ~An initial Set!.” Baltic 21 Transport Sector Rep. Indicators for Sustainable Transportation, Stockholm, Sweden.
[119] Bannister, D., and Pucher, J. ~2003!. “Can sustainability be made acceptable?” Paper for Presentation at the Proc., 2nd STELLA focus group meeting on Institution, Regulation, and Markets in Transportation. Sustainable Transport in Europe and Links and Liaisons with America ~STELLA!, Santa Barbara, Calif.
97
[120] Black, J. A., Paez, A., and Suthanaya, P. A. ~2002!. “Sustainable urban transportation: Performance indicators and some analytical approaches.” J. Urban Plann. Dev., 128~4!, 184–209.
[121] Centre for Sustainable Transportation ~CST!. ~2003 “Transportation performance indicators.” CSR, Toronto, ^www.cstctd.org&, accessed September 2003.
[122] Cortese, A. D. ~2003. “The critical role of higher education in creating a sustainable future.” Planning Higher Education, 31~3!, 15–22.
[123] Dawes, R. M. ~1988!. Rational choice in an uncertain world, Harcourt Brace College Publishers, San Diego.
[124] Deakin, E. ~2001–2003!. “Sustainable development and sustainable transportation: Strategies for economic prosperity, environmental quality and equity.” Working Paper 2001-03, Institute of Urban and Regional Development, Univ. of California at Berkeley, Berkeley, Calif.
[125] Department of Sustainable Development ~DSD!. ~2003!. “Achieving a better quality of life, Review of progress towards sustainable development.” United Kingdom http://www.sustainabledevelopment.gov.uk/ar2002/pdf/ar2002.pdf&
[126] Environment Canada. ~1991!. “A Report on Canada’s Progress Towards a National Set of Environmental Indicators.” State of the Environment Rep. No. 91-1, Minister of Supply and Services, Ottawa.
[127] Environment Canada. ~2003!. “Environment signals: Canada’s National Environmental Indicator Series.” Canada.
[128] Environmental Defense. ~1999!. “Environmental sustainability kit.” Pollution Prevention Alliance, United States.
[129] European Commission ~Energy, Environment and Sustainable Development Programme, Procedures for Recommending Optimal Sustainable
98
[130] Planning of European City Transport Systems ~PROSPECTS ~2003 “Developing Sustainable Urban Land Use and Transport Strategies:” Methodological guidebook.
[131] European Environment Agency ~EEA. ~2002 “Transport and environment reporting mechanism ~TERM! 2002—Paving the way for EU enlargement: Indicators of transport and environment integration Environmental Issues.” Copenhagen, Denmark.
[132] Federico, C., Cloud, J. P., and Wheeler, K. ~2003! “Kindergarten through twelfth grade education for sustainability.” Environmental law reporter, Vol. 2, Environmental Law Institute, Washington, D.C.
[133] Gilbert, R., and Tanguay, H. ~2000. “Brief review of some relevant worldwide activity and development of an initial long list of indicators.”
[134] Sustainable Transportation Performance Indicators ~STPI Project, Center for Sustainable Transportation ~CST, Toronto.
[135] Gudmundsson, H. ~2000!. “Indicators for performance measures for transportation, environment and sustainability in North America: Report from a German Marshall Fund Fellowship 2000 individual study tour October 2000.” Research Notes Rep. No. 148, Ministry of Environment and Energy, National Environmental Research Institute, Denmark.
[136] Litman, T. ~2003!. “Sustainable transportation indicators.” Victoria Transport Policy Institute ~VTPI!, Victoria, Canada. ^http://www.vtpi.org/ sus-indx.pdf&
[137] Meyer, M. D., and Jacobs, L. J. ~2000!. “A Civil engineering curriculum for the future: The Georgia Tech Case.” J. Prof. Issues Eng. Educ.Pract., 126~2!, 74–78.
[138] Journal of infrastructure systems © asce / march 2005 / 49 Downloaded 21 Sep 2011 to 203.199.213.66. Redistribution subject to ASCE license or copyright. Visithttp://www.ascelibrary.org
[139] National Round Table on the Environment and the Economy ~NRTEE~2003. “Environment and Sustainable Development Indicators for Canada, Ottawa, Ontario.” ^http://www.nrtee-trnee.ca/eng/programs/
99
[140] CurrentIPrograms/SDIndicators/ESDI-Report/ESDI-Report-E.pdf&accessed October 2003.
[141] New Zealand Ministry of the Environment ~NZME!. ~1999 “Proposals for indicators of the environmental effects of transport.” ^http://www.mfe.govt.nz/publications/ser/transport-proposals-full-jun99.pdf& Ontario Round Table on Environment and Economy
[142] ORTEE!. ~1995“Sustainability indicators: The transportation sector.” Report, ORTEE,Toronto.
[143] Organization for Economic Cooperation and Development ~OECD~1999a “Indicators for the integration of environmental concerns into transport policies.” Environment Directorate, Paris.
[144] Organization for Economic Cooperation and Development ~OECD ~1999b “Using the pressure-state-response model to develop indicators of sustainability.” OECD Environmental Indicators.
[145] Pearce, A. R. ~2000 “Sustainability and the built environment: A metric and process for prioritizing improvement opportunities.” PhD thesis, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta.
[146] Pearce, A. R., and Vanegas, J. A. ~2002. “Defining sustainability for built environment systems.” Int. J. Environ. Technol. Manage., 2~1!, 94– 113.
[147] Rijsberman, M. A., and van de Ven, F. H. M. ~2000!. “Different approaches to assessment of design and management of sustainable urban water systems.” Environ. Impact Assess. Rev., 20~3!, 333–345.
[148] Schwartz, P. ~1996!. The art of the long view, Doubleday, New York.Segnestam, L. ~1999!. “Environmental performance indicators ~second edition!, Environmental Economics Series.” Paper No. 71,
[149] Transportation Association of Canada ~TAC!. ~1999!. “Urban transportation indicators.” Ottawa. ^http://www.tac-atc.ca/english/productsand services/ui/exec.asp& Transport Canada ~TC! ~2001!. “Sustainable development strategy 2001– 2003, Ottawa: Transport Canada.” ^http://www.tc.gc.ca/programs/
100
[150] environment/sd/strategy0103/actionplan.htm& United States Department of Energy ~USDOE!. “Ten steps to sustainability.”
[151] Energy Efficiency and Renewable Energy Network ^http:// www.sustainable.doe.gov/management/tensteps.shtml&, accessed September 2003.
[152] United States Department of Transportation ~USDOT!. ~2003. PerformanceRep. No. 2004 Performance Plan, Washington, D.C.
[153] ^http:// www.dot.gov/PerfPlan2004/index.html& United States Environmental Protection Agency ~USEPA!. ~1999!. Indicators of the environmental impacts of transportation, 2nd. Ed.,
[154] Washington, D.C. ^http://www.epa.gov/otaq/transp/99indict.pdf
[155] Wheeler, K. A., and Byrne, J. M. ~2003!. “K-12 sustainability education: Its status and where higher education intervenes.” Planning Higher Education, 31~3!, 23–29.
[156] World Commission on Environment and Development ~WCED ~1987 Our common journey, Oxford Univ. Press, Oxford, England.
[157] Zegras, C., Sussman, J., and Christopher, C. ~2004!. “Scenario planning for strategic regional transportation planning.” J. Urban Plann. Dev., 130~1!, 2–13.
[158] Journal of infrastructure systems © asce / march 2005 downloaded 21 sep 2011 to 203.199.213.66. redistribution subject to asce license or copyright. Visithttp
[159] N. Buch, S.A. Velastin and J. Orwell, “ A review of computer vision techniques for the analysis of Urban Traffic,” IEEE Transactions on Intelligent Transportation Systems, Vol.12, no.3, pp.920-930,2011.
[160] J.Zhag, F-Y Wang, K. Wang, W.-H.Lin, X, Xu and C. Chen, “Data-Driven intelligent transportation system: a survey,” IEEE Transactions on Intelligent Transportation Systems, Vol.12, No : 4, pp. 1624-1639, 2011.
101
[161] G. Cheng and X. Chen, “A Vehicle detection approach based on multi-features fusion in the fisheye images,” in Proceedings of the 3rd International Conference on Computer Research and Development (ICCRD), 2011, pp. 1-5.
[162] X. Ma and W. E.L. Grimson, “ Learnin, coupled conditional random field for image decomposition with application on object categorization,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008, pp. 1-8.
[163] L-W. Tsai, J-W Hsieh and K-C. Fan, “Vehicle detection using normalized color and edge map,” IEEE Transaction on Image Processing, Vol.16. 3 pp. 850-864, 2007.
[164] N. Srinivasa, “ Vision-based vehicle detection and tracking method for forward collision warning in automobiles,” in Proceedings of IEEE Intelligent Vehicle Symposium, 2002, pp.626-631.
[165] J. Yang, Y. Wang, A. Sowmya and Z. Li, “ Vehicle detection and tracking with low-angle cameras,” in Proceedings of the 17th IEEE International Conference on Image Processing(ICIP). 2010, pp.685-688.
[166] T. Horprasert, D. Harwood and L. S. Davis, “ A statistical approach for real-time robust background subtraction and shadow detection, “ in Proceedings of IEEE International Conference on Computer Vision, 1999, pp. 1-19.
[167] Yuqiang Liu,Bin Tian, A Survey of vision based vehicle detection and tracking Techniques in ITS in proceeding of IEEE international conference on computer vision,2013,pp 72-76
[168] Yuqiang Liu,Bin Tian, A Survey of vision based vehicle detection and tracking Techniques in ITS in proceeding of IEEE international conference on computer vision,2013,pp 72-76
[169] Ashish Verma1, S. Sreenivasulu and N. Dash, “Achieving sustainable transportation system for Indian cities – problems and issues ” - Current Science, vol. 100, no. 9, 10, pp. 1328 – 1339 may 2011.
102
[170] Rajat Rastogi, “Promotion of non-motorized modes as sustainable transportation option: policy and planning issues” Current Science, vol. 100, no. 9, 10 may 2011 pp. 1340 – 1348 may 2011
[171] Christy Mihyeon Jeon, and Adjo Amekudzi, “Addressing Sustainability in Transportation Systems: Definitions, Indicators, and Metrics” Journal of infrastructure systems © asce / pp 31 – 48/ march 2005
[172] Robert A. Johnston , “Indicators for Sustainable Transportation Planning” Transportation Research Record: Journal of the Transportation Research Board,No. 2067, , 2008, pp. 146–154.
[173] M. Hatzopoulou_, E.J. Miller, “ Institutional integration for sustainable transportation policy in Canada” Transport Policy 15 (2008) 149–162.
[174] Stef Proostan and Kurt Van Dender, “What sustainable road transport future? Trends and policy options”, Journal of international transport forum, 2010.
[175] Sun Ye and Li Guiyan, “Evaluation on Sustainable Development Ability of Urban Road Transportation in Shandong Province”, in proceedings of International Conference on Computing, Control and Industrial Engineering , Wuhan, Vol 2, pp. 162-165,2010.
[176] YING Xiwen and SHI Jing, “Road Resources Distribution and Evolution Analysis Using a Species Competition Model for Improving Road Equity”, Journal of Tsinghua Science and Technology, Vol. 13, No.5, pp.651-659, 2008.
[177] Andre de Palma and Robin Lindsey, “Traffic congestion pricing methodologies and technologies”, Elsevier Journal of Transportation Research, Vol.19, pp.1377-1399, 2011.
[178] Wanli Min and Laura Wynter, “Real-time road traffic prediction with spatio-temporal correlations”, Elsevier Journal of Transportation Research, Vol.19, pp.606-616, 2011.
[179] Nick Hounsell and Birendra Shrestha, “A New Approach for Co-Operative Bus Priority at Traffic Signals”, IEEE transactions on intelligent transportation systems, vol. 13, no. 1, march 2012.
103
[180] S. K. Zegeye and B. De Schutter, “A Predictive Traffic Controller for Sustainable Mobility Using Parameterized Control Policies”, IEEE transactions on intelligent transportation systems, Vol. 13, No. 3, pp.1420-1429, 2012.
[181] Antonio J. Torija and Diego P. Ruiz, “Using recorded sound spectra profile as input data for real-time short-term urban road-traffic-flow estimation”, Elsevier journal of Science of the Total Environment, Vol.,pp. 270–279, 2012.
[182] Milena Radenkovic and Andrew Grundy, “Efficient and adaptive congestion control for heterogeneous delay-tolerant networks”, Elsevier journal of Ad Hoc Networks,Vol.10, pp. 1322–1345, 2012.
[183] Hesham A. Rakha, Kyoungho Ahn, Waleed Faris, and Kevin S. Moran, “Simple Vehicle Powertrain Model for Modeling Intelligent Vehicle Applications”, IEEE transactions on intelligent transportation systems, Vol. 13, No. 2, pp.770-780,2012.
[184] Ian Savage, “Comparing the fatality risks in United States transportation across modes and over time”, Elsevier journal of Research in Transportation Economics,Vol.43, pp.9-22,2013.
[185] Alexander Y. Bigazzi and Miguel A. Figliozzi, “Marginal costs of freeway traffic congestion with on-road pollution exposure externality”, Elsevier journal of Transportation Research Part A, Vol.57, pp.12-24,2013.
[186] Jian Wang and Ling Wang, “Congestion analysis of traffic networks with direction-dependant heterogeneity”, Elsevier journal of Physica part A, Vol. 392, pp. 392–399,2013.
[187] Guillermo Rey Gozalo, Juan Miguel Barrigón Morillas and Valentín Gomez Escobar, “Urban streets functionality as a tool for urban pollution management”, Elsevier journal of Science of the Total Environment, pp.453–461,2013.
[188] Raja Noriza Raja Ariffina and Rustam Khairi Zahari, ”Towards a Sustainable Urban Transport System in the Klang Valley, Malaysia: The key challenges”, Elsevier journal of Procedia - Social and Behavioral Sciences,Vol.85, pp. 638 – 645, 2013.
104
[189] Gang Xiong, Xisong Dong, Dong Fan,Fenghua Zhu, , Kunfeng Wang, and Yisheng Lv, “Parallel Traffic Management System and Its Application to the 2010 Asian Games”, IEEE transactions on intelligent transportation systems, Vol. 14, No. 1, pp. 225-235, 2013.
[190] Kibrom A. Abay, “Examining pedestrian-injury severity using alternative disaggregate models”, Elsevier journal of Research in Transportation Economics, Vol.43, pp. 123-136, 2013.
[191] Gail Blattenberger , Richard Fowles and Peter D. Loeb, “Determinants of motor vehicle crash fatalities using Bayesian model selection methods”, Elsevier journal of Research in Transportation Economics, Vol.43, pp.112-122,2013.
[192] Youngguk Seo and Seong-MinKim, “Estimation of materials-induced CO2 emission from road construction in Korea”, Renewable and Sustainable Energy Reviews , Vol.26,pp.625–631, 2013.
[193] Lohia, S. K., Urban transport in India, Proc. Indo-US conference on Mass Transit Travel Behaviour Research’ 08 (MTTBR-08), IIT Guwahati, India, 2008.
[194] MOUD, Study on traffic and transportation policies and strategies in urban areas in India, Govt of India, 2008.
[195] Schipper, L., Fabian, H. and Leather, J., Transport and carbon dioxide emissions: forecasts, options analysis, and evaluation, Asian Development Bank Sustainable: Working Paper Series, No. 9, 2009.
[196] Bertraud, A., The economic impact of land and urban planning regulations in India, 2002, unpublished manuscript available at http://www.Alainbertaud.com/images/AB_%20India_%20Urban_Land_Reform.doc
[197] Padam, S. and Singh, S. K., Urbanization and urban transport India: The sketch for a policy, Transport Asia Project Workshop,Pune, India, 2001, http://www.deas.harvard.edu/TransportAsia/workshop_papers/Padam-Singh.pdf
[198] Census of India, 2001; http://www.censusindia.gov.in/
105
[199] MOUD, Traffic and transportation policies and strategies in urban areas in India, Final Report. Ministry of Urban Development,Government of India, New Delhi, 1998.
[200] European Union Road Federation: European Road Statistics, 2007.
[201] Ministry of Road Transport and Highways, Handbook on transport statistics in India, Transport Research Office, Ministry of Road Transport and Highways, Delhi, India, 1999.
[202] Ministry of Road Transport and Highways, Handbook on transport statistics in India, Transport Research Office, Ministry of Road Transport and Highways, Delhi, India, 2000.
[203] Ministry of Road Transport and Highways, Handbook on transport statistics in India, Transport Research Office, Ministry of Road Transport and Highways, Delhi, India, 2003.
[204] Bhat, C. R. and Koppelman, F. S., Activity-based modelling of travel demand. In Handbook of Transportation Science (ed. Hall,R.), Kluwer Academic Publishers, Norwell. A, 1999.
[205] International Energy Agency (IEA), 2007; World Energy Outlook; www.iea.org/textbase/nppdf/free/2007/weo_2007.pdf
[206] Rastogi, Issues in data collection and non-motorized planning,Proc. Indo-US conference on Mass Transit Travel Behavior Research’08 (MTTBR-08). IIT Guwahati, India, 2008.
[207] ECMT, Assessment and decision making for sustainable transport,
[208] European Conference of Ministers of Transportation, Organization of Economic Coordination and Development, 2004; www.oecd.org) www.internationaltransportforum.org/europe/ecmt/pubpdf/04Assessment.pdf
[209] SUSTRAN, Key issues in sustainable transportation, 1996; http://www.gdrc.org/uem/sustran/key-issues.html
[210] OECD, Sustainable Transportation Principles, In International Conference ‘Towards Sustainable Transportation’ organized by OECD and hosted by Government of Canada, Vancouver, Canada,24–27 March 1996.
106
[211] Bawa, P. S. and Bansal, A. N., Cycle in urban transport. J. IndianRoads Congr., 1981, 42(2), 291–306.
[212] Khisty, C. J., Transportation in developing countries: Obvious problems, possible solutions. Transport. Res. Rec., 1993, 1396,44–49.
[213] Litman, T., Bicycling and transportation demand management.Transport. Res. Rec., 1994, 1441, 134–140.
[214] Zegras, P. C. and Birk, M. L., Moving toward integrated transport planning: energy, environment and mobility in ten Asian Cities.Transport. Res. Rec., 1994, 1441, 84–92.
[215] Litman, T., Whose roads? Defining bicyclists’ and other nondrivers’ right to use roadways, Report of Victoria Transport Policy Institute, Canada, 1996.
[216] Pettinga, A., Quicker by bicycle: Policy manual for bicycle friendly infrastructure. In Non Motorized Transport, The World Bank and The Inter-American Development Bank, 1996, pp. 85– 105.
[217] Pendakur, V. S., Badami, M. G. and Lin, Y. R., Nonmotorised transportation equivalents in urban transport planning. Transport. Res. Rec., 1995, 1487, 49–55.
[218] Lin, X., Shen, L. D. and Ren, F., Overview of bicycle transportation in China. Transport. Res. Rec., 1993, 1–4.
[219] Goodland, R. J. A., Urgent need for environmental sustainability in land transport in developing countries: an informal personal view. Transport. Res. Rec., 1994, 1441, 44–52.
[220] Replogle, M. A., Role of bicycle in public transportation access. Transport. Res. Rec., 1984, 959, 55–62.
[221] Replogle, M. A., Bicycle access to public transportation: learning from abroad. Transport. Res. Rec., 1993, 1396, 75–80.
[222] Nelson, A. C., Private provision of public pedestrian and bicycle access ways: public policy rational and the nature of public and private benefits. Transport. Res. Rec., 1995, 1502, 96–104.
107
[223] Komanoff, C., Roelofs, C., Orcutt, J. and Ketcham, B., Environmental benefits of bicycling and walking in the United States. Transport. Res. Rec., 1993, 1405, 7–12.
[224] Pinsof, S. A., Transportation control measure analysis: bicycle facilities. Transport. Res. Rec., 1982, 847, 86–93.
[225] Chiquetto, S., The environmental impacts from the implementation of a pedestrianisation scheme. Transport. Res., 1997, 2(2)D,133–146.
[226] Litman, T., The costs of automobile dependency, Report of Victoria Transport Policy Institute, Canada, 1996.
[227] Gupta, R. G., Delhi 2010 AD: cycle – an important mode even after the 20th century. In Proceedings of the International Conference on Transportation System Studies, IIT Delhi, 1986, pp. 625–632.
[228] Jacobs, G. D., Maunder, D. A. C. and Fouracre, P. R., Transport problems of the urban poor in developing countries. In Proceedings of the World Conference on Transport Research, London, 1980, pp. 1644–1656.
[229] Pendakur, V. S., Urban transport planning and the urban poor.J. Indian Roads Congr., 1984, 45(2), 421–445.
[230] Replogle, M. A., Sustainable transportation strategies for thirdworld development. Transport. Res. Rec., 1991, 1294, 1–8.
[231] Gibbons, S., Urban land use and non-motorised transport in Kanpur, India. Transport. Res. Rec., 1991, 1294, 34–39.
[232] Koike, H., Current issues and problems of bicycle transport in Japan. Transport. Res. Rec., 1991, 1294, 40–46.
[233] Hanson, M. E., Economic incentives and mode choice. Transport.Res. Rec., 1993, 1396, 61–68.
[234] Sharma, S. K., Bicycle renaissance. In Proceedings of the International Conference on Transportation System Studies, IIT Delhi, 1986, 470–474.
[235] Illich, I., Energy and Equity, Harper and Row, New York, USA,1974.
108
[236] Whitelegg, J., Transport for a Sustainable Future: The Case for Europe, Belhaven Press, London, UK, 1993.
[237] TTI, Urban mobility study and mobility measures, Texas Transportation Institute, 2007.
[238] Karekezi, S., Majoro, L. and Johnson, T., Climate Change Mitigation in the Urban Transport Sector: Priorities for the World Bank,The World Bank, 2003.
[239] Hook, W., Preserving and expanding the role of non-motorised transport. A Sourcebook for Policy-makers in Developing Cities,
[240] Litman, T., Evaluating Non-motorized Transportation Benefits and Costs. Victoria Transport Policy Institute; www.vtpi.org
[241] NHTS, 2009, National Household Travel Survey, USDOT,2009.
[242] Kenworthy, J. R. and Laube, F. B., An International Sourcebookof Automobile Dependence in Cities, University Press of Colorado,Boulder, 2000, 1960–1990.
[243] Dill, J. and Gliebe, J., Understanding and measuring bicycling behaviour: A focus on travel time and route choice, Oregon Transportation Research and Education Consortium (OTREC),2008.
[244] Efroymson, D. and Bari, M., Improving Dhaka’s traffic situation:Lessons from MirpurRoad,2005;
[245] Walkable Communities, Twelve steps for an effective programme.Pedestrian and bicycle programme, State Safety Office, Florida Department of Transportation, USA, 1995.
[246] Wilmink, A., The effects of an urban bicycle network: results of the Delft bicycle project. In Proceedings of the Velo City 1987
[247] Planning for the Cyclist, International Bicycle Congress, Groningen, The Netherlands, 1987, 233–238.
[248] TCRP Synthesis 62, Integration of bicycles and transit. Synthesis of transit practice, Transportation Research Board of the National Academics, Washington DC, 2005, p. 22.
109
[249] Replogle, M. A., Non-motorized vehicles in Asian cities, World Bank Technical Report 162, The Environmental Defense Fund, 1875 Connecticut Ave. NW, Washington, DC 20009 USA, 1991, p. 5.
[250] Tanaboriboon, Y. and Ying, G., Characteristics of bicycle users in Shanghai, China. Transport. Res. Rec., 1993, 1396, 22–29.
[251] Tanaboriboon, Y. and Jing, Q., Chinese pedestrians and their walking characteristics: Case study in Beijing. Transport. Res. Rec., 1994, 1441, 16–26.
[252] Rastogi, R., A policy sensitive model of transit access. Unpublished Ph D thesis, submitted to Indian Institute of Technology Bombay, Mumbai, India, 2001.
[253] Arasan, V. T., Rengaraju, V. R. and Rao, K. V. K., Characteristics of trips by foot and bicycle modes in Indian city. American Society of Civil Engineers. J. Transport. Eng., 1994, 120(2), 283–294.
[254] Rastogi, R. and Krishna Rao, K. V., Travel characteristics of commuters accessing transit: a case study. J. Transport. Eng., 2003, 129(6), 684–694.
[255] Soegijoko, S. T. B. and Horthy, S. I., Role of nonmotorised transport modes in Indonesian cities. Transport. Res. Rec., 1991, 1294, 16–25.
[256] Ren, N. and Koike, H., Bicycle: a vital transportation means in Tianjin, China. Transport. Res. Rec., 1993, 1396, 5–10.
[257] Bhargav, R., Bicycle movements in a class-I city. Unpublished M Tech project, submitted to Department of Civil Engineering, Indian Institute of Technology Roorkee, 2009.
[258] Kotkar, K. L., Rastogi, R. and Chandra, S., Pedestrian flow characteristics in mixed traffic conditions. J. Urban Plan. Dev., 2010, 136(1), 23–33.
[259] Rastogi, R., Illango, T. and Chandra, S., Design implications of walking speed for pedestrian facilities. Paper accepted by J. Trans. Engg., 2011; doi: 10.1061/(ASCE)TE.1943–5436.0040251.
110
[260] Rastogi, R., Kotkar, K. L. and Chandra, S., Pedestrian flow characteristics on a walkway near bus terminus. In Proceedings of International Conference on Best Practices to Relieve Congestion on Mixed-traffic Urban Streets in Developing Countries, IIT Madras, 12–14 September 2008.
[261] Illango, T., Rastogi, R. and Chabdra, S., Influence of bottleneck on pedestrian walking speed and pedestrian behaviour at sidewalks.In Proceedings of International Conference on Recent Issues andSolution Methodologies in Transport Engineering and Planning:Sustainable Transport, NIT Srinagar, Kashmir, India, 2010.
[262] Vamsheedhar, J., Pedestrian crossing behaviour under uncontrolled traffic conditions, Unpublished M Tech thesis, submitted to Indian Institute of Technology Roorkee, 2009.
[263] CSR-364, Pedestrian behaviour under varied traffic and spatial conditions. Second progress report of research scheme sponsored by Council of Scientific and Industrial Research, New Delhi, India, 2010.
[264] Illango, T., Chandra, S. and Rastogi, R., Comparison of pedestrian characteristics of North and South India. Indian Highways, Indian Roads Congress, New Delhi, India, 2010, vol. 39(4), pp. 29–37.
[265] System architects and work methodology automatic traffic counting & clarification by KRITIAL SOLUTION PRIVATE LTD.
[266] http : //www. Kritikalsolutions. Com/ products) traffic – analyzer. html.
[267] Traffic Data collection and mixed traffic condition using video image processing C. Mallikarjuna, Dept of civil Engg IIT Delhi. A. Phanindra Senior Design Engineer. Imagin Group Kirtikal solution private limits, Noida – 201 301.K. Ramachandra Rao,Asst.Traffic Department of civil Engg IIT, Delhi. Journal of Transportation Engineering . Vol . 135, No.4, April 1, 2009.
[268] Analysis of Microscopic Data under Hetrogeneous Traffic condition. Mallikarjuna chunchu, Civil Engg dept IIT Guwahati, Assam, India b.Ramachandra Rao kalarger Asst.Traffic Department of civil Engg IIT, Delhi. Naga Venkata Satish kumar Seethapall, Civil Engg Dept, IIt Delhi, New Delhi, India. Transport Journal 2010 – 25(3) 262 – 268.
111
[269] K. Robert, “Video-based traffic monitoring at day and night vehicle features detection tracking,” in Proc. IEEE ITSC, pp. 1-6, Oct. 2009.
[270] T. Rodriguez and N. Garcia, “An adaptive real-time traffic monitoring system,” Machine Vision and Applications, January 2009.
[271] N. Buch, S. A. Velastin and J. Orwell, “A Review of Computer Vision Techniques for the Analysis of Urban Traffic,” IEEE Trans. Intell. Transp. Syst., no. 99, pp. 1-20, 2011.
[272] Autoscope. [Online]. Avalilable: http://www.autoscope.com.
[273] P. G. Michalopoulos, “Vehicle detection video through image processing: the Autoscope system,” IEEE Trans. Veh. Technol., vol. 40, no. 1, pp. 21-29, Feb. 1991.
[274] Traficon. [Online]. Available: http://www.traficon.com.
[275] Citilog. [Online]. Available: http://www.citilog.com
[276] Ipsotek. [Online]. Available: http://www.ipsotek.com/
[277] P. Kumar, S. Ranganath, Weimin Huang and K. Sengupta, “Framework for real-time behavior interpretation from traffic video,” IEEE Trans.Intell. Transp. Syst., vol.6, no.1, pp. 43-53, Mar. 2005.
[278] C. Stauffer and W.E.L. Grimson, “Adaptive Background Mixture Models for Real-Time Tracking,” in Proc. IEEE Conf. Comput. Vis.Pattern Recog., June 1999
[279] Y. Zou, G. Shi, H. Shi and H. Zhao, “Traffic incident classification at intersections based on image sequences by hmm/svm classifiers.”in Proc. IEEE HIS, Aug. 2009.
[280] H. Huang, Z. Cai, S. Shi, X. Ma and Y. Zhu, “Automatic Detection of Vehicle Activities Based on Particle Filter Tracking,” in Proc. ISCSCT, pp. 381-384, 2009.
[281] M. Pucher, D. Schabus, P. Schallauer, Y. Lypetskyy, F. Graf, H. Rainer, M. Stadtschnitzer, S. Sternig, J. Birchbauer, W. Schneider, B. Schalko, “Multimodal highway monitoring for robust incident detection,” in Proc. IEEE Int. Conf. Intell. Transp. Syst., pp. 837-842, Sept. 2010.
112
[282] O. Akoz, M.E. Karsligil, “Severity detection of traffic accidents at intersections based on vehicle motion analysis and multiphase linear regression,” in Proc. IEEE Int. Conf. Intell. Transp. Syst., pp. 474-479, Sept. 2010.
[283] O. Akoz, M.E. Karsligil, “Video-based traffic accident analysis at intersections using partial vehicle trajectories,” in Proc. IEEE SIU, pp. 499-502, Apr. 2010.
[284] W. Hu, X. Xiao, D. Xie and T. Tan, “Traffic accident prediction using vehicle tracking and trajectory analysis,” in Proc. IEEE Int. Conf.Intell. Transp. Syst., vol. 1, pp. 220-225, Oct. 2003.
[285] S. Atev, H. Arumugam, O. Masoud, R. Janardan and N.P. Papanikolopoulos, “A vision-based approach to collision prediction at traffic intersections,” IEEE Trans. Intell. Transp. Syst., vol. 6, no. 4,pp. 416-423, Dec. 2005.
[286] G. Medioni, I. Cohen, F. Bremond, S. Hongeng and R. Nevatia, “Event detection and analysis from video streams,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 23, no. 8, pp. 873-889, Aug. 2001.
[287] R. Cucchiara, M. Piccardi and P. Mello. “Image analysis and rulebased reasoning for a trac monitoring system,” IEEE Trans. Intell.Transp. Syst., vol. 1, no. 2, pp. 119-130, 2000.
[288] D. Cmaniciu, V. Ramesh and P. Meer, “Kernel-based object tracking,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 5, pp. 564-577, May 2003.
[289] S. Atev, O. Masoud, R. Janardan and N. Papanikolopoulos, “A Collision Prediction System for Traffic Intersections”, in Proc. IEEE IROS, pp. 2844-2849, Aug. 2005.
[290] D.Grest, J.-M.Frahm and R.Koch, “A color similarity measure for robust shadow removal in real time,” In Vision, Modeling and Visualization, pp. 253-260, 2003.
[291] S.-C. Chen, M.-L. Shyu, C. Zhang and R.-L. Kashyap, “Identifying overlapped objects for video indexing and modeling in multimedia database systems,” International Journal on Artificial Intelligence Tools, vol. 10, no. 4, pp. 715-734, Dec. 2001.
113
[292] D. Beymer, P. McLauchlan, B. Coifman and J. Malik, “A real-time computer vision system for measuring traffic parameters,” in Proc.IEEE CVPR, pp. 495-501, Jun. 1997.
[293] Q. Tu, Y. Xu and M. Zhou, “Robust vehicle tracking based on Scale Invariant Feature Transform,” in Proc. IEEE ICIA, pp. 86-90, June 2008.
114
LIST OF PUBLICATIONS
Paper Published (International Journal)
1. K. Yogeswari, Dr. E. RasulMohideen, Sustainable road layout design for liveable area ( Tambaram) with the aid of fuzzy logic system in Journal of Theoretical and applied information technology, Vol 63, issue 2, pp 381 – 396, May 2014.
2. K. Yogeswari, Dr. E. RasulMohideen, Study of traffic for sustainable transportation using Image processing in International journal of Advances in image processing techniques , Vol 1; issue 2 , pp 12 – 16, June 2014.
Paper Published (International Conferences)
1. K. Yogeswari , Dr. E. RasulMohideen, Study of traffic for sustainable transportation using Image processing in International conference – IRED – CSEB’14 Kulalumpur, Malaysia, 8-9 March 2014, Vol 1; Pp 12 – 16.
Paper Published (National Conferences)
1. K. Yogeswari , Dr. E. RasulMohideen, Challenges faced by the Developing countries to meet the technology development in Transportation – A Review in National Conference on “Current Trends In Telematics” Oct, 2009 .
2. K. Yogeswari , Dr. E. RasulMohideen, Traffic and Transportation Management in suburban area Tambaram in National Conference on “Tharamigu Tambaram 2020 People plan for Development”, Dec, 2010
3. K. Yogeswari , Dr. E. RasulMohideen, Analysis of heterogeneous traffic for Sustainable Transportation planning in National Conference on “Sustainable techniques in civil enginering” April, 2012.
4. K. Yogeswari , Dr. E. RasulMohideen, The role of ITS in Sustainable transportation in National Conference on “Sustainable transportation using ITS ” Feb, 2012.
115
TECHNICAL BIOGRAPHY
Mrs. K. Yogeswari (RRN. 0980201) was born on 12TH February
1977, in Chennai, Tamil Nadu . She did her schooling in St.Anthony’s higher
secondary school and secured 86% in the Higher Secondary Examination.
She received B.E. degree in Civil Engineering from V.L.B Jannakiammal
College of Engineering, Coimbatore, Bharathyar University in the year 1998 .
She did her Masters in M.Tp. Town planning from School of Architecture and
planning, Guindy, Anna University in the year 2000. She has got fifteen years
of academic experience. She is the employee with B.S. Abdur Rahman
University, Chennai. She is currently pursuing her Ph.D. Degree in
Sustainable transportation planning in the Department of Civil Engineering
of B.S. Abdur Rahman University. Her area of interests include
Transportation Engineering and urban planning. She has published two
papers in the International journals and presented one papers in the
International Conferences and four paper in the national conference. Her
e-mail ID is: [email protected] and the contact number is :
9444208072.