doctor of philosophy - hec
TRANSCRIPT
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ESTIMATION OF SATURATION FLOW AND LOST TIME AT SELECTED
SIGNALIZED INTERSECTIONS OF KARACHI (PAKISTAN)
A thesis submitted by
Muhammad Jawed Iqbal
In fulfillment of the requirement for the degree of
Doctor of Philosophy
In
Civil Engineering
Department of Civil Engineering
Faculty of Engineering
Mehran University of Engineering & Technology,
Jamshoro
2009
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MEHRAN UNIVERSITY OF ENGINEERING & TECHNOLOGY
JAMSHORO
This thesis written by Muhammad Jawed Iqbal under the direction of his supervisors, and
approved by all the members of the thesis committee, has been presented to and accepted
by the Dean, Faculty of Engineering, in fulfillment of the requirement of the degree of
Doctor of Philosophy in Civil Engineering.
_________________ __________________ ____________________ (Supervisor) (Internal Examiner) (External Examiner)
___________________ (Co-Supervisor)
__________________________ _________________________ (Director Post Graduate Studies) (Dean, Faculty of Engineering) Dated: __________________________
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This thesis is dedicated to my “MOTHER”, who’s foresight and
values paved the way for a privileged education, and who gently
offered guidance and unconditional support at each turn of my life,
and who always helped me and pray for me to be what I am today
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ACKNOWLEDGEMENTS ALHAMDOLILLAH, I am grateful to ALLAH Almighty who always showered his blessings on
me and gave me the strength to complete this thesis.
There are many people that assisted me in the completion of this research. First of all, my
expression in words is not enough to express my sincere appreciation to my Supervisors,
Prof. Dr. Abdul Sami Qureshi and Prof. Dr. Ghous Bux Khaskheli. Without their guidance,
support, mentorship and encouragement, this research would not have been possible.
I am also indebted to Dr. Arif Kazmi of Arizona Department of Transportation, Prof. Dr.
Rahim F. (Ray) Benekohal of University of Illinois at Urbana-Champaign, Prof. Dr. Ghulam
Qadir Memon of Hamdard University and Major General. Dr. Tariq Mehmood of National
Institute of Transportation (NIT), whose comments and valuable advice during the
evaluation made the final copy of this thesis possible.
I also want to acknowledge my gratitude to the Higher Education Commission of Pakistan
for their financial support through HEC’s ‘Merit Scholarship Scheme for PhD Studies in
Science and Technology (300 Scholarships)’. I am thankful to Mehran University of
Engineering and Technology (MUET), Jamshoro for providing me opportunity to study/work
in this university and facilitating me in my PhD research. I am also thankful to Civil
Engineering Department of Mehran University of Engineering and Technology for their
support.
I would like to thanks all the staff at Directorate of Postgraduate Studies, especially Mr.
Mehboob Ali Abbasi, for his endless support through out my research.
I would like to give my profound love and thanks to my parents who provide priceless
support, their unconditional and endless love, patience and absolute faith in me.
Last but not the least, I would like to give my thanks to my wife, who was always with me,
who has been so patient, who has been so supportive and sacrificed and who always
stands with me. I also would like to give my deepest love and thanks to my daughter
Aamna and my son Ibrahim and Zain, who are the source of my adrenaline.
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ABSTRACT
Due to rapid increase in car ownership and other related factors we often experience traffic
Jam at intersections with formation of long queues. This is a common phenomenon in major
cities of Pakistan. In order to solve this problem it is necessary to review the traffic signal
setting. For a particular junction cycle time is an important parameter to minimize delay
which ultimately causes formation of long queues and accidents. The most important
factors in determining the optimum cycle time is saturation flow and lost time. Direct
measurement of saturation flow is obviously desirable to achieve satisfactory results, but in
case of new intersection, results from measurements of saturation flow are being estimated
from the work of previous researchers. In case of Pakistan where no standard value of
saturation flow and lost time are available pertaining to local traffic condition, values used in
developed countries are being applied resulting in non achievement of optimum cycle time.
This thesis describes experimental research which is carried out for estimating the
saturation flow and lost time under local conditions of Karachi. Data was collected by video
recording of traffic flow at eighteen (18) signalized intersections along two major arterials,
namely Shahra-e-Faisal and M.A. Jinnah Road, of Karachi city. Recorded data was
analyzed in laboratory to retrieve the information on the headway of all the vehicles in
saturated cycles. The analysis of PCU values were carried out by comparing the average
car headway with the average headway other vehicle type.
Different studies show a great deal of variations in saturation flow rates and start-up lost
times. This indicates a lack of stability. This is acknowledged in the HCM. Due to these
instabilities, the HCM recommends that local data collection be performed to produce more
accurate estimates of local saturation flow rates and start-up lost times.
It is a known fact that there are close relationships between intersection characteristics and
saturation flow. Empirical relationships have been developed for estimation of saturation
flow and lost time for many countries such as Great Britain, Australia, U.S.A, Bangkok,
Malaysia, India and Bangladesh etc but such relationship not developed for Pakistan as yet.
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An effort has been made in this research to derive empirical relationship between
intersection characteristics (approach width) and saturation flow. Appropriate PCU values
as per local traffic conditions have been calculated for saturation flow estimation. This is for
the first time in Pakistan that such values, based on local traffic, has been calculated.
In this thesis, an effort has been made to establish relationship between saturation flow and
approach width and comparison of the results of has been carried out with previous work
done. The major focus of this thesis is on measurement of departure headways at selected
signalized intersections in Karachi (Pakistan) and to gather as much basic information as
possible which can be used in the analysis of the collected data as required in the thesis.
As outcome of the research, relationship has been established, through predictive models,
for the estimation of saturation flow in Pakistan. The results obtained have a very practical
application potential in Karachi and in urban areas of similar traffic characteristics.
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TABLE OF CONTENTS Description Page Table of Contents (i) List of Tables (v) List of Figures (vii) List of Appendices (ix) Chapter 1 INTRODUCTION 1
1.1 Preamble 1
1.2 Objectives of Study 3
1.3 Methodology 4
Chapter 2 SIGNALIZED INTERSECTIONS – CONCEPT 5
2.1 General 5
2.2 Terminology and Key Definitions 5
2.3 Traffic Flow Characteristics at Signalized Intersection 8
2.3.1 Performance Measures 9
2.3.2 Discharge Headway, Lost Time and 10 Saturation Flow
2.3.2.1 Discharge Headway 10
2.3.2.2 Lost Time 13
2.3.2.3 Effective green & Red Time 14
2.3.2.4 Saturation Flow 15
2.4 Capacity and Level of Service Concepts 16
2.4.1 Capacity 16
2.4.2 Level of Service 17
2.4.3 Factors Affecting Level of Service 19
2.4.3.1 Base Conditions 19
2.4.3.2 Roadway Conditions 20
2.4.3.3 Traffic Conditions 20
2.4.3.4 Control Conditions 21
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Chapter 3 LITERATURE SURVEY 22
3.1 General 22
3.2 Departure Headway 22
3.3 Capacity 24
3.4 Level of Service 25
3.5 Saturation Flow 26
3.5.1 Cycle Profile 27
3.6 Relationship of Saturation Flow to Optimum 28 Signal Time
3.7 Estimation of Saturation Flow 29
3.7.1 Effect of Approach Width 29
3.7.2 Effect of Gradient 31
3.7.3 Effect of Site Characteristics 32
3.7.4 Effect of Composition of Traffic 33
3.7.5 Effect of Right Turning Traffic 35
3.7.6 Effect of Left Turning Traffic 35
3.7.7 Effect of Parked Vehicles 36
3.8 Heterogeneous Traffic 36
3.8.1 Difference between Heterogeneous and 37 Homogeneous Traffic Flow
3.9 Passenger Car Unit (PCU) 38
3.9.1 Factors Affecting PCU Values 38
3.9.2 Determination of PCU 39
Chapter 4 METHODS FOR MEASURING SATURATION FLOW 44
4.1 General 44
4.2 Measurement Technique 44
4.3 Measurement Methods 45
4.3.1 Road Research Laboratory Method 45
4.3.2 Recorder Method 45
4.3.2.1 Typewriter Method 46
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4.3.2.2 The Rustrak Four Channel Event 46 Recorder Method
4.3.3 Battery Operated Cassette Recorder Method 46
4.3.4 Time Lapse Photography Method 47
4.3.5 Video Tape Recorder Method 47
4.3.6 Use of Mobile Traffic Laboratory 48
4.3.7 GIS Based Method 50
4.4 Method Used in this study 50
Chapter 5 EXPERIMENTAL INVESTIGATIONS 51
5.1 General 51
5.2 Selection of Sites 51
5.3 Study Timings 52
5.4 Materials and Equipment 56
5.5 Data Collection and Analysis for PCU 57
5.6 Data Collection at Shahra-e-Faisal 58
5.6.1 PCU Equivalents for Passenger Cars 58
5.6.2 PCU Equivalents for Motorcycle 59
5.6.3 PCU Equivalents for Minibuses 59
5.6.4 PCU Equivalents for Vans 59
5.6.5 PCU Equivalents for Rickshaw 60
5.6.6 PCU Equivalents for Buses/Trucks 60
5.7 Data Collection at M.A. Jinnah Road 61
5.7.1 PCU Equivalents for Passenger Cars 61
5.7.2 PCU Equivalents for Minibuses 61
5.7.3 PCU Equivalents for Buses/Trucks 61
5.7.4 PCU Equivalents for Vans 62
5.7.5 PCU Equivalents for Rickshaw 62
5.7.6 PCU Equivalents for Motorcycle 62
5.8 Comparison of PCU Values of Shahra-e-Faisal 64 and M.A. Jinnah Road
5.8 Comparison of PCU Values of Shahra-e-Faisal and 64 M.A. Jinnah Road With PCU Values in Other Countries
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5.10 Measurement of Approach Width 64
5.11 Saturation Flow Data Collection and Analysis 67 (For both Arterials)
5.12 Lost Time 71
Chapter 6 SATURATION FLOW & LOST TIME ANALYSIS 80 & DISCUSSION OF RESULTS
6.1 General 80
6.2 Saturation Flow and Approach Width 80
6.3 Effect of Composition of Traffic 81
6.4 Comparison of Observed & Estimated Saturation Flow84
6.5 Comparison of both Arterials of Present Study 87
6.6 Generalized Model and its Comparison 87
6.7 Comparison of Present Study with Earlier Studies 90
Chapter 7 CONCLUSIONS 92
7.1 General 92
7.2 Future Scope 94
7.3 Recommendations / Suggestions 95
References 96
Appendices 106
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LIST OF TABLES
DESCRIPTION PAGE Table 3.1 Summary of Saturation flow with approach widths as given 41 in RRTP-56 Table 3.2 Summary of Effect of Gradient on Saturation flow from 41 Various Studies Table 3.3 Effect of Site Characteristics on Saturation flow as per RRTP-56 42 Table 3.4 Average lane Saturation flow in tcu/h by lane type and 42 Environment given in ARRB Bulletin No.3 (Miller) Table 3.5 Summary of PCU values from various studies 43 Table 3.6 Level of Service Criteria for Signalized Intersections 43 Table 5.1a Summary of Approach Widths which have been studied on 63 Shahra-e-Faisal Table 5.1b Summary of Approach Widths which have been studied on 63 M.A. Jinnah Road Table 5.2 Summary of PCU values observed at Shahra-e-Faisal 64 Table 5.3 Summary of PCU values observed at M.A. Jinnah Road 64 Table 5.4 Comparison of PCU values of Shahra-e-Faisal and M.A.Jinnah 66 Road with Other Countries Table 5.5 Observed Saturation Flow on each Approach on Shahra-e-Faisal 69
(Vehs/hr) Table 5.6 Observed Saturation Flow on each Approach on M.A. Jinnah Road 69
(Vehs/hr) Table 5.7 Observed Saturation Flow on each Approach on Shahra-e-Faisal 70
(PCU/hr) Table 5.8 Observed Saturation Flow on each Approach on M.A. Jinnah Road 70
(PCU/hr) Table 5.9 Lost Time Calculation (McShane & Roess) 73 Table 5.10 Saturation Flow & Lost Time Measurement Form (Akcelik 1993) 76 Table 5.11 Summary of Lost Time Calculated on each Approach on 79 Shahra-e-Faisal
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Table 5.12 Summary of Lost Time Calculated on each Approach on 79 M.A. Jinnah Road Table 6.1 Summary of PCU Values along both Arterials of Karachi 83 Table 6.2 Comparison of Observed and Estimated Saturation Flow 85 on Shahra-e-Faisal Table 6.3 Comparison of Observed and Estimated Saturation Flow 85 on M.A. Jinnah Road Table 6.4 Comparison between Two Models 88 Table 6.5 Comparison of Generalized Model with Faisal & Jinnah Model 89 Table 6.6 Comparison of Saturation flows predicted by present study model 91 with Earlier Studies
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LIST OF FIGURES
DESCRIPTION PAGE Fig 2.1 Fundamental attributes of flow at Signalized Intersections 9 Fig 2.2 Conditions at Traffic Interruption in an Approach Lane 10 of a Signalized Intersections Fig 2.3 Concept of Saturation Flow Rate & Lost Time 12 Fig 3.1 Variation with Time of Discharge Rate of Queue in a fully 27 Saturated green Period Fig 3.2 a) Homogeneous Mix 38 Fig 3.2 b) Heterogeneous Mix 38 Fig 4.1 Typical layout of field data collection equipment set up 48 Fig 4.2 Field data collection set up 49 Fig 4.3 Field data collection screen view 49 Fig 5.1 Road Network of Karachi City 53 Fig 5.2 Data Collection Sites on Shahra-e-Faisal 54 Fig 5.3 Intersections on M.A.Jinnah Road 55 Fig 5.4 Cycle Profile (Lost Time Concept) 72 Fig 5.5 Saturated Headway & Lost Time Measurement 73 Fig 5.6 Observed Discharge across Stop Line 77 Fig 5.7 Average Cycle Profile (Awami Markaz 78 Fig 6.1 Relationship between observed Saturation Flow and 82 Approach Width on Shahra-e-Faisal Fig 6.2 Relationship between observed Saturation Flow and 82 Approach Width on M.A. Jinnah Road Fig 6.3 Graphical comparison of observed Vs theoretical saturation flow 86 on Shahra-e-Faisal Fig 6.4 Graphical comparison of observed Vs theoretical saturation flow 86 on M.A. Jinnah Road Fig 6.5 Generalized Relationship between Saturation Flow and Approach 88
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Width (incorporating both approaches) Fig 6.6 Graphical Comparison of Present Study Model with Previous 90
Models
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LIST OF APPENDICES
DESCRIPTION PAGE APPENDIX 1 Headways of Straight-Ahead Motorcycles 107 APPENDIX 2 Headways of Straight-Ahead Passenger Cars 109 APPENDIX 3 Headways of Straight-Ahead Rickshaws 112
APPENDIX 4 Headways of Straight-Ahead Vans 114
APPENDIX 5 Headways of Straight-Ahead Minibuses 116 APPENDIX 6 Headways of Straight-Ahead Buses/Trucks 118 APPENDIX 7 Sample sheet for traffic flow data collection 119 APPENDIX 8 Data sheet for traffic flow at Awami Markaz Junction 120 APPENDIX 9 Data sheet for traffic flow at Drig Road Junction 121 APPENDIX 10 Data sheet for traffic flow at Karsaz Junction 122 APPENDIX 11 Data sheet for traffic flow at Mehran Hotel Junction 123 APPENDIX 12 Data sheet for traffic flow at Regent Plaza Junction 124 APPENDIX 13 Data sheet for traffic flow at Shah Faisal Junction 125 APPENDIX 14 Data sheet for traffic flow at star Gate Junction 126 APPENDIX 15 Data sheet for traffic flow at Tariq Road Junction 127 APPENDIX 16 Data sheet for traffic flow at Kashif Centre Junction 128 APPENDIX 17 Data sheet for traffic flow at Faisal Base Junction 129 APPENDIX 18 Data sheet for traffic flow at Lal Dila Junction 130 APPENDIX 19 Data sheet for traffic flow at Kala Pull Junction 131 APPENDIX 20 Data sheet for traffic flow at Nursery Junction 132 APPENDIX 21 Sample sheet for Saturation Flow calculation 133 APPENDIX 22 Calculation of Saturation Flow (example) 134
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APPENDIX 23 Saturation flow calculation sheet - Awami Markaz Junction 135 APPENDIX 24 Saturation flow calculation sheet – Drig Road Junction 136 APPENDIX 25 Saturation flow calculation sheet - Karsaz Junction 137 APPENDIX 26 Saturation flow calculation sheet – Mehran Hotel Junction 138 APPENDIX 27 Saturation flow calculation sheet – Regent Plaza Junction 139 APPENDIX 28 Saturation flow calculation sheet – Shah Faisal Junction 140 APPENDIX 29 Saturation flow calculation sheet – Star Gate Junction 141 APPENDIX 30 Saturation flow calculation sheet – Tariq Road Junction 142 APPENDIX 31 Saturation flow calculation sheet – Kashif Centre Junction 143 APPENDIX 32 Saturation flow calculation sheet – Faisal Base Junction 144 APPENDIX 33 Saturation flow calculation sheet – Lal Qila Junction 145 APPENDIX 34 Saturation flow calculation sheet – Kala Pull Junction 146 APPENDIX 35 Saturation flow calculation sheet – Nursery Junction 147 Statistical Analyses for Vehicle’s Headway 148 APPENDIX 36 Statistical analyses for Headways of Cars 149 APPENDIX 37 Statistical analyses for Headways of Motorcycles 150 APPENDIX 38 Statistical analyses for Headways of Minibuses 151 APPENDIX 39 Statistical analyses for Headways of Vans 152 APPENDIX 40 Statistical analyses for Headways of Rickshaws 153 APPENDIX 41 Statistical analyses for Headways of Buses/Trucks 154 APPENDIX 42 Average cycle profile at Awami Markaz Junction 155 APPENDIX 43 Average cycle profile at Drig Road Junction 156 APPENDIX 44 Average cycle profile at Karsaz Junction 157 APPENDIX 45 Average cycle profile at Mehran Hotel Junction 158 APPENDIX 46 Average cycle profile at Regent Plaza Junction 159
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APPENDIX 47 Average cycle profile at Shah Faisal Junction 160 APPENDIX 48 Average cycle profile at Star Gate Junction 161 APPENDIX 49 Average cycle profile at Tariq Road Junction 162
1
CHAPTER 1
INTRODUCTION
1.1 Preamble Traffic signals are perhaps the most important traffic control devices for at grade
intersection in urban traffic system. Proper installation of traffic signals can reduce
the number of accidents and minimize delays to vehicles at intersections.
Furthermore, traffic signals can increase intersection capacity.
Since last three decades it is found that there is a significant increase in
urbanization and consequent rapid growth of car ownership. Roadways of several
major cities are unable to cater this increased traffic flow.
Therefore, we more often come across with a situation in central areas that the
traffic is congested with formation of long queues, causing delay, frustration and
environmental issues for both the pedestrians and vehicle-users. Such traffic
problems more often become the cause of accidents.
The rapid increase in vehicle ownership in Pakistan in general, and Karachi in
particular has increased the traffic intensity that has created various serious
problems such as congestion and formation of long queues ultimately causing
heavy delays and increase in the number of accidents at various locations on
roadways.
It is usually a challenge to ascertain a particular factor that causes the traffic
problem, because many parameters are involved. However, problems have also
been attributed to the following reasons:
i) Traffic signal installation (timing) in Pakistan is dependent either on
Webster and Cobbe’s formula (British Standard 1966) [1] or on ad-hoc
basis.
ii) Local intersections are not complying with the British Standard practice as
far as traffic behavior, vehicle characteristics and surface characteristics of
the intersection are concerned.
2
iii) Efforts have not been made on national level to develop a formula for
estimation of saturation flow, which simulate our traffic conditions.
In order to solve this problem, it will be necessary to review the traffic signal
timing. For a particular intersection, cycle time is an important parameter to
minimize delay that ultimately causes formation of long queues and accidents. An
important component required for the optimum cycle time is saturation flow. Direct
measurement of saturation flow is obviously desirable to achieve satisfactory
results, but in case of new intersection, results from measurements of saturation
flow are being estimated from the work of outdated researches. In case of
Pakistan, where no standard values of saturation flow are available pertaining to
local traffic conditions, values are being applied from earlier work either carried in
U.K or in USA that does not relate to the actual cycle time needed for local traffic.
A critical need for traffic analysis is a clear understanding of the ability of various
types of facilities to carry traffic. This knowledge, when integrated with
measurements of current traffic demand and forecast of future traffic demand,
allows the traffic engineer to plan and design facilities that can adequately serve
public needs.
Established work has been conducted to estimate the saturation flow and lost time
in developed countries. The procedure in HCM [2] (Highway Capacity Manual) and
other such studies assume that the traffic flow is homogenous and follows lane
discipline. Traffic composition in Pakistan and other developing countries is mixed
in nature with different types of vehicles and the vehicles do not follow lane
discipline. Hence, the procedure for assessing the facility in Pakistan which has
been adopted from developed countries will not be suitable in Pakistan.
Signalized intersections are vital nodal point in transportation network and their
efficiency of operation, in terms of signal timings, greatly influences the entire
network performance. Traffic signals are installed at these nodal points in order to
allocate the right-of-way to different competing streams of vehicles passing
through the intersections. As for the research area in Pakistan, pre-timed signal
controls are in use [3].
3
The HCM presents the results of selected studies that measured saturation flow
rates at various locations throughout the U.S. from 1967 to 1992. The reported
saturation flow rate of each study varies from one another. The average obtained
from measurements of start-up lost times also varies. The large variations in
saturation flow rates and start-up lost times indicate a lack of traffic stability. This
is acknowledged in the HCM. Due to these instabilities, the HCM recommends
that local data collection be performed to produce more accurate estimates of
local saturation flow rates and start-up lost times [19].
It is a known fact that there are close relationships between intersection
characteristics and saturation flow. Empirical relationships have been developed
for estimation of saturation flow and lost time in many countries such as Great
Britain, Australia, U.S.A, Bangkok, Malaysia, India and Bangladesh, etc, but such
relationship has not been developed for Pakistan yet. Therefore, a need was felt
to carry out the research on signalized intersections of Pakistan to derive
empirical relationships between intersection characteristics and saturation flow.
The study reported herein analyzes the capacity of pre-timed signalized
intersections and suggests modifications required in the formula while predicting
the traffic behavior for mixed traffic conditions. The study area of analysis is
concentrated to largest city of Pakistan, known as Karachi.
1.2 Objectives of Study The aim and objectives of the subject study in the city of Karachi are:
1. To collect traffic data and study the traffic flow characteristics at selected
signalized intersections of Karachi in general and at Shahra-e-Faisal
(Faisal Road) and M.A. Jinnah Road in particular.
2. To measure headway and saturation flow of traffic at several
signalized intersections.
3. To determine passenger car unit (PCU) for different vehicle types for
saturated conditions.
4
4. To derive general relationship between intersection characteristic
(approach width) and saturation flow.
5. To measure the lost time at signalized intersections.
6. To compare the subject results with the results of earlier researchers, and
to develop empirical relationship to estimate traffic intensity, i.e., saturation
flow and lost time.
1.3 Methodology Literature review reveals that little work has been done towards the effect of
heterogeneity of traffic on capacity analysis of signalized intersections. There is no
systematic procedure available to deal with mixed traffic in the analysis of
signalized intersections. HCM provides basis for the capacity analysis and is
being widely used in most of the developed countries. The present study attempts
to incorporate changes in the existing formula based on experimental results for
making it applicable to the traffic conditions in Karachi, Pakistan.
As far as data collection is concerned, Video Recording Technique is used to
collect data in the field. Video based technique overcomes many difficulties in
collecting traffic information. The video camera continuously records the traffic
flow. A total of thirteen intersections on Shahra-e-Faisal and five intersections on
M.A. Jinnah Road were selected in Karachi city for the analyses. All intersections
were pre-timed signals.
The data recorded films were played back in the laboratory on a large screen with
a slow motion built in facility to retrieve the required information. PCU values are
calculated using regression technique. In addition to the saturation flow, geometric
characteristics (width, gradient, filtration of left turning movements) of the
intersections including parking of vehicles within 40m are also taken into account.
Based on the experimental data, saturation flow model is developed to suit mixed
traffic conditions by regression analysis which simulates local traffic conditions.
5
CHAPTER 2
SIGNALIZED INTERSECTIONS CONCEPT
2.1 General Intersection may be signalized for a number of reasons, most of which relate to
the safety and effective movement of conflicting vehicular and pedestrian flows
through intersection. Three concepts are important in understanding signalized
intersection design and operation:
1) The time allocation of the 3600 seconds in an hour to conflicting
movements and to "lost time" in the cycle.
2) The effect of left turning and right-turning vehicles on the operation of the
intersection.
3) Geometric parameters such as lane width, gradient and site characteristics,
etc.
This chapter discusses the basic principles of traffic behavior at signalized
intersections.
2.2 Terminology and Key Definitions [2] The following terms are commonly used to describe traffic signal operation:
Cycle: One complete sequence of signal indications, start green time on one
phase to start of green again on the same phase is called a cycle.
Cycle Length (C): Total length of time for the signal to complete one cycle.
Phase: The sequence of conditions applied to one or more streams of traffic
during which the cycle receive identical signal light conditions.
Change Interval (Y): The "yellow" and /or "all-red" intervals, which occur at the
end of a phase to provide for clearance of the intersection before conflicting
movement are released.
6
Green Time (G): Time within a given phase during which the "green" indication is
shown.
Lost Time: Time during which the intersection is not effectively used by any
movement or the amount of a time in a cycle, which is effectively lost to the traffic
movement in the phase because of starting delay, and at the end of green phase
with start of amber period. Pedestrian movement at start of phase and the falling
of the discharging rate, which occurs during the amber period.
Effective Green Time: Time during which a given phase is effectively available
for stable moving platoons of vehicles in the permitted movements.
Green Ratio: Ratio of effective green time to the cycle length.
Effective Red: Time during which a given movement or set of movements is
effectively not permitted.
Optimum Cycle Time: The cycle time, which gives the least average delay to all
vehicles using the intersection.
Passenger Car Unit (PCU): Vehicle of different types require variable area in the
road space because of variation in size and performance. In order to allow for
capacity measurements for roads and intersections, traffic volumes are expressed
in PCU. (It is equivalent ratio between another type of vehicle and a normal
passenger car.)
Early Cut Off: To facilitate a right turning movement from one approach, the
green of the opposing arm can be cut off a few seconds before the arm having the
right turn’s movement.
Degree of Saturation: It is the ratio of the design flow to the actual capacity of a
particular approach, weighted by the amount of green the approach receives in a
cycle.
Early Cutoff Overlap: Condition in which one or more traffic streams are
permitted to move after the stoppage of one or more other traffic streams, which
during the preceding stage had been permitted to move with them.
7
Effective Green Period: The time during which a given traffic movement or set of
movements may proceeds; it is equal to the cycle length minus the effective red
time [5].
Flow Factor: The flow factor or `y' value of an approach is the ratio of the design
flow to the saturation flow of the particular approach.
Green Split: The ratio of green time allocated to each of the conflicting phases in
a signal sequence [6].
Intergreen Period: The period between the end of the green display on one stage
and the start of the green display on the next stage is known as the intergreen
period.
Minimum Cycle Time: The minimum cycle time that is just sufficient to pass the
traffic.
Offset: The time difference or interval in seconds between the start of the green
indication at one intersection as related to the start of the green interval at another
intersection from a synchronized system time base[6].
PCU Factor: An average PCU value derived for the convenience of signal
calculation to convert unclassified (by type) vehicle counts from vehicles per hour
units to PCU per hour units.
Saturation Flow: The maximum flow which could be obtained if 100 percent
green time was awarded to a particular approach.
Traffic signals may operate in following basic modes, depending upon the type of
control equipment used:
a. Pre-timed operation: In pre-timed operation, the cycle length, phases,
green times, and change intervals are all preset. The signal rotates through
8
this defined cycle in constant fashion. Each cycle is same, with the cycle
length and phase lengths constant.
b. Semi-actuated operation: In semi-actuated operation, the designated
main street has a "green" indication at all times until detectors on the side
street determine that some vehicles have arrived on one or both of the
minor approaches. The signal then provides a "green" phase for the minor
approach, after an appropriate change interval, which is retained until all
vehicles are crossed, or until a preset maximum side-street allocated green
time is reached. In this type of operation, the cycle length and green times
vary from cycle to cycle in response to demand.
c. Fully- actuated operation: In fully-actuated operation, all signal phases
are controlled by detector actuations. In general, minimum and maximum
green times are specified for each phase. In this type of control, cycle
length and green times may vary considerably in response to demand.
d. Real-time operation: It is an integral part of the urban traffic control
system which takes an input detector data for real-time measurement of
traffic flow, and “optimally” controls the flow through the network.
2.3 Traffic Flow Characteristics at Signalized Intersection At any typical signalized intersection, we can observe a minimum of three signal
lights are seen which are red, yellow and green. Some basic parameters of traffic
flow at typical signalized intersection are presented in Figure 2.1. The figures
implies at typical scenario of one-way approach with cycle of two phases to a
signalized intersection (HSC 2000). [7]
The figure comprises of three portions. A time versus space graph of vehicles has
been shown in first part. The diagram also indicates intervals for the signal cycle
of the particular approach. From the diagram, the timing interval of interest, along
with the labels with the symbols can be seen in second part. An ideal graphical
representation of flow rate along the reference line is provided in the third part
which is indicating the saturation flow.[7]
9
Figure 2.1 Fundamental Attributes of Flow at Signalized Intersections
(Source: HCM 2000)
2.3.1 Performance Measures
The performance measures of a signalized intersection can be evaluated by
stops, delay, and queue length. Each of these factors may be represented as
values, which express totals or averages for the whole intersection or for
individual approaches. These averages are generally expressed on a per vehicle
basis. Other performance measures include throughput and total travel time [8, 9].
Delay, specifically the control delay is the parameter used in the signalized
intersection methodology of the HCM 2000 and the primary measure used in the
number of signalization optimization procedures. Performance measures are
critical part of all intersection design methodologies.
10
2.3.2 Discharge Headway, Lost Time and Saturation Flow
2.3.2.1 Discharge Headway
Before calculating intersection signal timings it is necessary to understand the
vehicle discharge phenomenon, from the intersection when the signal turned on
green. A group of N vehicles at a signalized intersection is illustrated in Figure 2.2.
The vehicles are in queue and waiting for the green signal to be turned on. When
the green light is turned on, the headways of the departing vehicles will be
observed as these vehicles cross the stop line, as shown in the Figure 2.2 [10].
The time interval between the indication of the green light and the crossing of the
first vehicle through the stop line will be the first headway. On the same lines the
second headway is the time interval between the first and second vehicles
crossing the stop line, etc. Generally the headways are measured as the front
wheels of the vehicle cross the stop line. The first headway is relatively long, as it
includes the reaction time and the time required by the first vehicle’s driver to
accelerate. Whereas, the second headway is shorter, because of the overlapping
of second driver’s reaction and acceleration time with the first driver. Each
successive headway becomes smaller. Finally, the headways becomes stable.
This happens when vehicles have fully accelerated while crossing the stop line [10].
Fig 2.2: Conditions at Traffic Interruption in an Approach Lane of a Signalized Intersection (Source: HCM 2000)
11
Veh in Queue Headway
1 h + t1
2 h + t2
3 h + t3
. .
N h + t N
N + 1 h
N + 2 h
. .
. .
n h
the saturation headway is defined as the level headway attained by the vehicles
passing during the green phase [10].
Figure 2.3 shows conceptual plot of headways of vehicles entering the
intersection versus the position of the vehicle in the queue.
12
Figure 2.3 Concept of Saturation Flow Rate and Lost Time (Source: HCM 2000)
The behavior at a signalized intersection can be modeled by considering that each
vehicle requires an average of “h” seconds of green time to cross the intersection.
A related term of saturation flow rate has been arise from this assumption. If each
vehicle requires h seconds of green time, and if the signal remains green, then s
vehicles/hour could cross the intersection, where s is the saturation flow rate [10].
Thus:
s = 3600 h
where: s = saturation flow rate, vehicles per hour of green time per lane
(vphgpl)
h = saturation headway, seconds
The units of saturation flow rate are “vehicles per hour of green time per lane.” It
can be multiplied by the number of lanes to yield units of vehicles per hour of
green time” [10]. If the signal were always green, the saturation flow rate would be
the capacity of all the lanes.
13
From the conceptual plot of headways it is clear that the fifth vehicle following the
beginning of a green should be used as the starting point for saturation flow
measurements. The value h represents the saturation headway, estimated as the
constant average headway between vehicles after the fourth vehicle in the queue
and continuing until the last vehicle that was in the queue at the beginning of the
green has cleared the intersection [5]. The saturation headway is the time interval
that a vehicle in the stopped queue takes to pass through a signalized intersection
on the green signal, assuming that there is a continuous queue of vehicles moving
through the intersection.[2]
2.3.2.2 Lost Time
Delay in start and stoppages at end of a phase indicate that a portion of the cycle
length is not being completely utilized. This is called lost time (time which is not
effectively serving any movement of traffic). Total lost time is a combination of
start-up and clearance lost times.
Start-up lost times occur when a signal indication first turns from red to green,
drivers in the queue do not instantly start moving at the saturation flow rate. This
start-up delay results in a portion of the green time for that movement not being
completely utilized. This start-up lost time (has a value that is typically around 2
seconds).
When green phase finishes, drivers hesitate while crossing the intersection, thus,
green time is not effectively utilized. This causes delay and drop in saturation flow.
This time lost at the end of green phase is termed as clearance lost time. Start-up
and clearance lost times are summed to arrive at a total lost time for the phase,
given as:
tL = l1 + l2
Where:
tL = total lost time for a movement during a cycle in seconds,
l1 = start-up lost time in seconds, and
l2 = clearance lost time in seconds.
Lost time remains fixed, regardless of cycle length. For shorter cycle lengths, the
cycle length will comprise a larger percentage of the lost time, and will result in a
larger total of lost time over the course of a day than for longer cycle lengths.
14
Longer cycle lengths usually have more phases than shorter cycle lengths, which
may result in similar proportions of lost time.
2.3.2.3 Effective Green and Red Times
For analysis purposes, the time during a cycle that is effectively (or not effectively)
utilized by traffic must be used (the green, yellow, and red signal indications are
not directly useful for analysis). Effective green time is the time during which a
traffic movement is effectively utilizing the intersection [5].
The effective green time is calculated as [2]
g = G + Y + AR − tL
Where:
g = effective green time for a traffic movement in seconds,
G = displayed green time for a traffic movement in seconds,
Y = displayed yellow time for a traffic movement in seconds,
AR = displayed all-red time in seconds, and
tL = total lost time for a movement during a cycle in seconds.
Effective red time is the time during which a traffic movement is not effectively
utilizing the intersection. The effective red time is calculated as:
r = R + tL
Where:
r = effective red time for a traffic movement in seconds,
R = displayed red time for a traffic movement in seconds, and
tL = total lost time for a movement during a cycle in seconds.
Alternatively, the effective red time can be calculated as follows, assuming the
cycle length and effective green time have already been determined:
r = C − g
Where:
r = effective red time for a traffic movement in seconds,
C = cycle length in seconds, and
g = effective green time for a traffic movement in seconds,
15
Likewise, the effective green time can be calculated by subtracting the effective
red time from the cycle length. The capacity at signalized intersection is based on
saturation flow rate, the lost time and the signal timing.
2.3.2.4 Saturation Flow
Saturation flow is important in transportation engineering because it is used in the
evaluation of the intersection performance, to estimate the intersection capacities
and for setting the timings of the traffic signal. The saturation flow rate is “the
equivalent hourly rate at which previously queued vehicles can traverse an
intersection approach under prevailing conditions, assuming that the green signal
is available at all times and no lost times are experienced [2].” According to a
special report of the Australian Road Research Board [98] on traffic signal capacity
and timing analysis, the saturation flow rate “represents the most important single
parameter in the capacity and timing analysis of signalized intersections”.
The definition of the saturation flow rate can be confusing because the rate at
which the first few stopped vehicles enter an intersection after a signal changes to
green is well known to be less than the flow rate of subsequent vehicles.
Consequently, the extra time consumed by the first few vehicles is considered as
“lost time” and is treated as a separate factor in capacity and signal timing
determinations.
The base saturation flow rate is usually calculated empirically by simply starting
measurements of queue dispersion after the first three to five vehicles, and their
accompanying lost times, are skipped. This treatment has led to the base
saturation flow rate being perceived as a constant value subject to adjustment
factors which cause the rate to be increased or decreased due to any special
conditions specific to an intersection approach site under study. Similarly, the
estimated lost time incurred in the start-up of the first three to five vehicles can be
increased or decreased due to any special characteristics existing at a given
intersection approach.
Saturation flow rates are not usually measured directly. Instead, headways
between successive vehicles are measured and averaged, and the saturation flow
16
rate is calculated from the average saturation headway by dividing it into 3,600 s
per hour. The saturation headway is defined by the HCM as “the average
headway between vehicles occurring after the fourth vehicle in the queue and
continuing until the last vehicle in the initial queue clears the intersection”. The
time at which the last vehicle in the initial queue clears the intersection [5] can be a
cause of confusion because the HCM defines the headway screen line as the stop
line and the measurement benchmark as the front wheels of a vehicle, which is
not a position where the last vehicle “clears the intersection”[19].
2.4 Capacity and Level of Service Concepts The capacity analysis is carried out to ascertain the maximum traffic that can be
accommodated by given facility. It is also intended to estimate the maximum
amount of traffic that can be accommodated by a facility without compromising the
operational qualities. The definition of operational criteria is accomplished by
introducing the concept of level of service. Range of operating conditions is
defined for each type of facility and is related to the amount of traffic that can be
accommodated at each service level.
2.4.1 Capacity The capacity of a lane in an intersection is the number of vehicles per hour of
green time that can pass through the intersection. In a fully-utilized intersection,
time is lost because of start-up time (the headway for the first 4 or 5 cars is larger
than h) and slowdown. Thus, the effective green time is nh, where n is the number
of vehicles that pass through the intersection on the green phase and h is the
saturation headway time. The proportion of actual time available for movement in
lane i during a complete cycle is nh/C where C is the cycle length. The capacity is
computed by multiplying the saturation rate by this quotient [10]. That is,
C i = S i nh
C where: Ci = capacity of lanes serving movement i, vph or vphpl
17
Si = saturation flow rate for movement i, vphg or vphgpl
n = average number of vehicles that pass through the intersection
on the green phase
h = saturation headway, seconds
C = signal cycle (green, yellow, red) length, seconds
The Highway Capacity Manual 2000 defines the capacity of facility as " the
maximum hourly rate at which persons or vehicles can reasonably be expected to
traverse point or uniform section of a lane or roadway during a given time period
under prevailing roadway, traffic, and control conditions”.
Prevailing roadway, traffic, and control conditions, which should be reasonably
uniform for any section of a facility, define capacity as “Any change in the
prevailing conditions will result in the change in capacity of the facility”.
Capacity is defined on the basis of "reasonable expectancy." That is stated
capacity for a given facility is a rate of flow that can be repeatedly achieved during
every peak period for which sufficient demand exists and that can be achieved on
any facility with similar characteristics [11].
The capacity of highway facility is an important characteristic. Operating
conditions at capacity are, however, generally poor. Few facilities are designed to
operate at or near capacity because of poor operating characteristics and the
difficulty in maintaining capacity operations without breakdown. Thus, the ability to
analyze the traffic carrying ability of facilities under better operating is major
aspect of capacity analysis. Capacity may be defined in terms of persons per
hour, passenger cars per hour, or vehicles per hour depending upon the type of
facility and type of analysis.
2.4.2 Level-of-Service The Highway Capacity Manual 2000 defines level of service (LOS) as term, which
denotes a range of operating conditions that occur on transportation facility when
it is accommodating range of traffic volumes.
18
Highway Capacity Manual describes service quality in following terms:
(i) Speed and travel time. One of the most easily perceived measures of service
quality is speed, or travel time. On freeway, speed is very evident measure of
quality, while on surface street systems, the driver is very sensitive to total
travel time.
(ii) Density. Density is not often used in traffic analysis. A density describes the
proximity of vehicles to each other in the traffic stream and reflects ease of
maneuverability in the traffic stream, as well as psychological comfort of
drivers.
(iii) Delay. Delay can be described in many ways. It represents excess or
additional travel time due to travel time of controls.
(iv) Other measures. A variety of other measures are used to describe service
quality. In some cases, measures used are not directly related to drivers or
passengers. Such measures generally rely upon volumes or flow rates.
Six level of service (LOS) are defined for capacity analysis and are designated A
through F, with LOS A representing the best range of operating conditions and F
the worst [8]. Safety is also a parameter, used to establish level of service.
The specific terms in which each level of service is defined vary with the type of
facility involved. In general LOS A describes a free flowing condition in which
individual vehicle of the traffic stream are not influenced by the presence of other
vehicles. LOS F generally describes breakdown operations (except for signalized
intersections), which occur when flow arriving at a point is greater than facility's
capacity to discharge flow [12]. Level of service B, C, D, and E represent
intermediate conditions, with lower bound of LOS E often corresponds to capacity
operations.
Each facility has five service flow rates, one for each level of service (A through
E). For LOS F, it is difficult to predict flow since stop-start conditions often occur.
Service flow rate is the maximum hourly rate at which person or vehicles can
reasonably be expected to traverse a point or uniform segment of lane or roadway
during given period under prevailing roadway, traffic, and control conditions while
maintaining a designated level of service. The service flow rates are generally
based on a 15-min period [13].
19
2.4.3 Factors Affecting Level of Service
2.4.3.1 Base Conditions
Many of the procedures in HCM 2000 provide formula or simple tabular or graphic
presentations for set of specified standard conditions, which must be adjusted to
account for any prevailing conditions not matching those specified. Base
conditions assume good weather, good pavement conditions, user familiar with
facility, and no incident impending traffic flow [14].
Base conditions for uninterrupted flow facilities are:
a. Lane width of 3.6 m,
b. Clearance of 1.8 m between the edge of the travel lane and the nearest
obstruction or the objects at the road side and in the median,
c. Free-flow speed of 100km/h for multilane highway,
d. Only passenger cars in the traffic streams (no heavy vehicles),
e. Level terrain,
f. Absence of no-passing zone on two-lane highway, and
g. No impediment to through traffic due to traffic control or turning vehicles.
Base conditions for intersection approaches include [14]:
a. Lane width of 3.6 m,
b. Level grade,
c. No curb parking on the approaches,
d. Only passenger cars in the traffic streams and no local transit buses
stopping at the travel lanes,
e. Intersection located in a non-central business district area, and
f. No pedestrians.
20
In most capacity analysis, prevailing conditions differ from the base conditions,
and computation of capacity, service flow rate, and level of service must include
adjustment to reflect this. Prevailing conditions are generally categorized as
roadway, traffic, or control.
2.4.3.2 Roadway Conditions
Roadway conditions include geometric and other elements. These include:
a. Number of lanes
b. The type of facility and its development environment,
c. Lane widths,
d. Shoulder widths and lateral clearance,
e. Design speed,
f. Horizontal and vertical alignments, and
g. Availability of exclusive turn lanes at intersection.
2.4.3.3 Traffic Conditions
Traffic conditions that influence capacities and service levels include vehicle type
and lane or directional distribution.
a. Vehicle Type: whenever a vehicle other than passenger cars exists in the
traffic stream, the number of vehicles that can be served is affected. Heavy
vehicles adversely affect traffic in two ways:
(i) They are larger than passenger cars and therefore occupy more roadway
space, and
(ii) They have poorer operating capability than passenger car, particularly with
respect to acceleration, deceleration, and the ability to maintain speed on
upgrades.
21
b. Directional Distribution
Directional distribution and lane distribution also affect capacity, service flow rates,
and level of service.
2.4.3.4 Control Conditions
For interrupted flow facilities, the control of the time available for movement of
specific traffic flow is critical element affecting capacity, service flow rates, and
level of service. The most critical type of control on such facilities is the traffic
signal. Operations are affected by the type of control in use, signal phasing, and
allocation of green time, cycle length, and relationship with adjacent control
measures.
22
CHAPTER 3
LITERATURE SURVEY ABOUT DEPARTURE HEADWAY,
SATURATION FLOW AND LOST TIME
3.1 General This chapter reviews the literature regarding the work, which has been carried-out
on the saturation flow and lost time all over the world, the behavior of varying
cycle profile and junction capacity (traffic flow).
The concept of capacity and level of service are central to the analyses of
intersections, as they are for all types of facilities. It is necessary to consider both
capacity and level of service to evaluate the overall operation of signalized
intersections. As per HCM 2000 level of service is based upon the average control
delay per vehicle for various movements within the intersections. Literature
review of departure headway, saturation flow, delay, level of service, etc., is
presented in this chapter under respective headings.
3.2 Departure Headway
A lot of research work has been carried out regarding departure headway to
analyze traffic characteristics like passenger car unit, delay, saturation flow rate,
and lost time. This is because the knowledge of departure headways at signalized
intersections plays a pivotal role in assessing the intersection capacity analysis
and signal timings [15].
Though there are many definitions which have been proposed by various
researchers from time to time, the term of departure headways at signalized
intersections can defined as “the time intervals between two successive vehicles
passing stop line or any predetermined reference line at the intersection” [15]. The
values of various basic parameters in connection with signalized intersection
operation, such as delay, saturation flow and lost time, are generally the basic tool
of measurements of departure headways. Improper headways can results in
23
errors in estimation of saturation flow and lost time which will consequently result
in traffic accidents, delays, congestion, and economic losses [15].
Hung [15] has acknowledged the earlier work of Greenshield [16] as a pioneer work
regarding departure headway study in the filed of traffic engineering. A camera
with 16-mm lens was utilized to take a series of time-motion pictures at short
successive time intervals in New Haven, Connecticut and New York City while
studying traffic performance at intersections. Greenshield [16] made 2,359
observations and his recommendations for departure headways from first to fifth
vehicles in a queue are 3.8, 3.1, 2.7, 2.4, and 2.2 seconds. He did not consider
the effect of left-turning movements and heavy vehicles. After fifth vehicles the
departure headway touched to 2.1 seconds [15].
Hung [15] has referred the earlier work of Gerlough and Wanger[17] who studied the
departure headways at signalized intersections in Los Angeles. They developed a
simulation model to analyze the traffic signals at individual intersections. The
summary of the headways for the first to twentieth vehicle ranges from 3.85 to
2.28 seconds [15].
Carstens [18] carried out his research at four signalized intersections in Ames and
Iowa with manual counts. He studied starting delay and headway of vehicles.
Altogether 2,093 signal cycles were analyzed which revealed average headway of
straight through passenger cars 2.29 seconds per vehicle [15].
Yean-Jye Lu [19] has used a time recorder and stop watches at one signalized
junction in Austin, Texas, to collect departure headways. The departure headways
of protected left turns were in range of 2.43 to 2.09 sec for the vehicles in the first
through fourth queue positions respectively. A headway of 1.8 sec was recorded
when the vehicles were in a queuing position up to fifth vehicle and onward. He
studied three classes of vehicles i.e., large cars, small cars, trucks / buses [15].
Lee and Chen [20] conducted their survey with the help of video camera. In their
study the average headways ranges from 3.80 to 1.76 sec. They suggested six
24
important factors which influence the departure headways. The detail is given in
their research paper [15].
Massoum Moussavi and Mohammed Tarawneh [21] have studied departure
headways for 10,000 vehicles in six cities of Nebraska. The departure headways
ranges were 2.90 to 1.75 for straight through vehicle [15].
Niittymaki et al [22] studied departure headways at Finland while studying
saturation flow at signalized intersection. His research revealed a mix type of time
headway for 1st, 2nd and 3rd vehicles in the queue, after 3rd vehicle headway
reached at 2.0 seconds [15].
Overall conclusion of all the above studies pertaining to departure headways are
indicating that departure headways are varying from site to site and from country
to country. However, it can be concluded that for each saturation flow, lost time
and passenger car unit study, the departure headway study is quite essential.
3.3 Capacity Miller [23] stated that “the capacity of an approach to any intersection is the
maximum sustainable rate at which vehicles can cross the intersection from that
approach (under consideration) under the prevailing roadway and traffic
conditions”. The actual rate on which the vehicles cross any reference line is also
same as the capacity, if the traffic flow is continuous throughout the full green
period. Therefore, it is important when discussing the capacity of signalized
intersection, to state the prevailing conditions of roadway and traffic, and actual
rate at which vehicles cross the stop line.
Individual lane group’s capacity is defined as capacity at intersection which is
defined as “The lane group capacity is the maximum hourly rate at which vehicles
can reasonably be expected to pass through the intersections under prevailing
roadway, traffic and signalization conditions” [7]. While referring to traffic
conditions, it generally include vehicle type distribution, volumes on each
approach, use of bus stops and their locations within intersection area, distribution
25
of vehicles by movement, parking movements on approaches, and and pedestrian
crossing flows. Roadway conditions include the width and number of lanes,
grades, basic geometric parameters of the intersections, and lane use [7].
Signalization condition refers to signal phasing, timing, and type of control.
3.4 Level of Service
In the 1965 Highway Capacity Manual, levels of service at signalized intersection
were related to load factor. Load factor presented some problem such problem as
its insensitivity to low service volume, absence of any rational; basis for defining
break points, and difficulty in identifying loaded cycle. Sutaria and Haynes [24] used
road user opinion survey that involves depicting and rating different traffic situation
at carefully selected single signalized intersection. Over 300 drivers rated
randomly arranged film sequences of two types - a driver view (micro view) and
an overall view (macro view) of an intersection. Later on these films were
reviewed, segment by segment, in terms of appropriate level of service. Statistical
analyses indicated that average individual delay correlated better with level of
service. The hypothesis for load factor as a better predictor of Level of Service
was tested and was rejected through the latest results.
Chandra et al. (1996)[25] studied the parameter to define level of service for mixed
traffic at signalized intersections. Due to many problems associated with the
measurement and interpretation of delay at signalized intersection LOS
parameters were redefined. Degree of saturation and percent of vehicle stopping
in the approach were considered the appropriate parameters. Data collected at
eight signalized intersections in Delhi were analyzed. They developed the
graphical relationship incorporating the average stopped delay, saturation green
ratio and the degree of saturation (DOS). Break points in the range of DOS for
different LOS have been determined based on these parameters. DOS was also
related to the percent stopping to define six LOS for mixed traffic flow at signalized
intersections.
The control delay per vehicle is calculated for each lane group, then on the basis
of this average control delay it is estimated for each approach and on the similar
26
lines aggregated for the whole intersection. This control delay is directly
concerned with the Level of Service. The criteria for which is given in Table 3.6 [13].
Level of service A: describes operation with very low control delay. This level of
service occurs when progression is extremely favorable and most vehicles arrive
during green phase. Many vehicles do not stop at all.
Level of service B: this level generally occurs with good progression, short cycle
length, or both. More vehicles stop than LOS A causing higher level of delay.
Level of service C: the higher delays may result from only fair progression,
longer cycle length, or both. Individual cycle failures may begin to appear at this
level. The number of vehicles stopping is significant.
Level of service D: at this level the influence of congestion becomes more
noticeable and longer delays may result from some combination of unfavorable
progression, long cycle lengths, or high v/c ratios. Many vehicles stop and
individual cycle failures are noticeable.
Level of service E: at LOS E delays will be high indicating poor progression, long
cycle length, and high v/c ratios. Individual cycle failures are frequent.
Level of service F: this level is considered to be unacceptable to most drivers
and often occurs with over saturation, i.e., when arrival flow rate exceeds the
capacity of lane groups. It may also occur at high v/c ratios with many individual
cycle failures. Poor progression and long cycle lengths may also be major
contributing causes to such delay levels.
3.5 Saturation Flow Saturation flow is a vital traffic performance measure of the maximum rate of flow;
it is most oftenly used in intersection design and the control applications.
Saturation flow is an important performance measure of junction operation at
macro level. The potential capacity of an intersection when operating under 'ideal'
conditions is also indicated by saturation flow [26].
27
The saturation flow is the uniform flow of vehicles through an approach while the
full green time is lapsed still few vehicles are in queue waiting to cross the
junction. Researchers have expressed Saturation flow in Passenger Car Units
(PCU) per hour of green time. Its value depends on the prevailing roadway and
traffic conditions. The roadway includes the layout of the intersection, the width of
approach, the number and width of lanes, site conditions and also the gradient.
The traffic condition includes the traffic composition, the number of right and left
turning vehicles, the presence of parked vehicles and many other related factors
which vary from area to area and site to site.
3.5.1 Cycle Profile
Figure 3.1 represent an ideal plot of saturation flow at a typical signalized
intersection. When green light turns on at traffic signal, initially there is a very little
gap as the first driver reacts to the signal. In the beginning the rate of vehicles
crossing the stop line increases as per the speed of the cars they are following.
Soon the vehicles attain a steady state where they cross the stop line at a
constant gap or headway [26].
Fig. 2.1 Variation with Time of Discharge Rate of Queue in a fully Saturated Green Period.
RedAmber
Amber Red
Time
Effective Green Time
Saturation Flow
Final Lost TimeInitial Lost Time
Rat
e O
f D
isch
arge
of
Que
ue in
Sa
tura
ted
Gre
en P
erio
d
Fig. 3.1
28
This steady state is illustrated as the plateau in this profile. In a saturated
intersection, too long queue will be formed, during red indication of signal which
will not be clear in the green period and hence the cars will be following one each
other at constant spacing during the green period. This flow will start decreasing
when the signal turned on amber light. Now the flow rate will decrease at an
increasing rate as in the beginning vehicles carry on through the stop line on
amber light and then stop as the signals turned on red light. The saturation flow is
then calculated by converting the curved profile into a rectangle from which the
dimensions can be measured. This is done through the concept of lost time and
effective green time. Here the lost time will be the time from the start of green light
to a point where vehicles are crossing at half the maximum flow and the sum of
time from where vehicles are flowing at half the maximum flow at the end of
saturation to the start of the red period [26].
3.6 Relationship of Saturation Flow to Optimum Signal Time The relationship of saturation flow to optimum signal cycle time can be found from
the theoretical analysis that the saturation flow is one of the parameter of the
formula for optimizing signal cycle time. For setting fixed time signals to minimize
the delay two formulas have been proposed one by Webster & Cobbe[1] and other
by Australian Road Research Board[98] Both formulas yield more or less similar
results. The main equations are:
C = 1.5 L + 5……………………………………………3.1
1 –
n
1 I
Yi
C = L + 2.2 L/S ………………………………………3.2
1 –
n
1 I
Yi
Where,
C = Optimum Signal Cycle Time (sec)
L = Total Lost Time Per Cycle (sec)
Yi = Representative movement for ith phase ( qi/Si)
n = Number of phases
29
S = Saturation Flow in PCU per sec.
3.7 Estimation of Saturation Flow There are many factors affecting the saturation flow, i.e., approach width,
gradient, traffic composition, right turning traffic, left turning traffic, pedestrian,
parked vehicles and site characteristics.
3.7.1 Effect of Approach Width As per RRTP-56 [1], the saturation flow is expressed in terms of PCU per hour,
with no turning traffic and no parked vehicles present on the approach. The
summary of saturation flow with respect to approach width is given in Table 2. 1.
For approach width greater than 17 feet the saturation flow varies linearly and is
given by:
S= 160 W, pcu/h (W= Width in ft)……………… (3.3)
S = 525 W, pcu/h (W= Width in meters)………. (3.4)
In this context the Australian Road Research Board has also done considerable
research as Leong [27] studied 23 approaches in Sydney metropolitan area the
width of approach was from 3.6 to 9.3 m. Leong[27] stated through his research
that if the approach width ranges from 2.75 m to 3.5 m, then there had been no
effect on saturation flow, this is because there is only a single queue of vehicles,
which could be accommodated within this width.
Leong’s equation is as given below:
S = 1700 veh/h, per lane ……………(3.5)
Sarna and Malhotra [28] presented the results and analysis of the studies on
saturation flow conducted at a number of different intersections with varying
approach road widths. They developed the relationship between the saturation
flow and the approach road width at signalized intersections. Effect of approach
30
volume and increasing percentage of bicycles on the saturation flow was also
studied. It was suggested that flaring of the approach should be done to increase
discharging capacity. The study has shown that the saturation flow increases with
the increase in approach volume.
Miller [23] measured saturation flow at seven main cities of Australia at signalized-
intersections. He observed that the saturation flow increased up to 3.05 m
approach width and than remained constant up to 3.95 m as explained in
Australian Road Research Board bulletin No.3.
Branston [29] studied seven single lane sites, two two-lane sites and one three lane
sites. Like RRTP-56, which gives three different site characteristics, he has also
given three different formulae for the different times of the day and visibility, i.e.,
off peak periods, dark peak periods, and dry light peak periods.
S = 885 + 222W For off peak periods …………… (3.6)
S = 960 + 222W For dark peak periods …………. (3.7)
S = 1045 + 222W For light peak periods ………..... (3.8)
All the above formulas as described by Branston underestimate saturation flow
when compared with the Road Research Laboratory’s recommended formula
given in RRTP-56.
Abu-Rehmeh [30] carried out a study of over 23 signalized approaches in city of
Sheffield. The width of those approaches varied from 2.5 to 6.7 m. Analysis of this
study showed that the width had an effect on saturation flow; however his results
were just nearer to the lowest limit of RRTP-56 given formula.
Through the Regression Analysis he developed the following equation:
S = 475 W pcu/h …………………….. (3.9)
Where, W is the width of approach in meters.
Chang Chien [31] carried out a study over 17 approaches in Bangkok. The width of
approaches varied from 2.80 to 3.50 m. Linear relationship was developed
between Saturation Flow and lane width as:
S = 643 W pcu/green hour ………….. (3.10)
31
Research by Cuiddan and Cuiddan & Ogden [32] developed a new method for
collecting saturation flow data for the design and analysis of signalized
intersection. They have used a portable computer and dedicated software named
SATFLOW for saturation flow measurement and analysis. Data were collected for
a total of 40,000 saturation headway in 160 lanes at 71 sites through out the
Melbourne Metropolitan area.
Ibrahim et. al. [33] had carried out a study to determine the ideal saturation flow at
signalized intersections under Malaysian road conditions. They adopted the
similar method of measuring saturation flow as given by Road Research
Laboratory. The averaged flow values were then regressed with lane widths to
obtain a linear regression model as shown below [34]:
S = 1020 + 265w; R2 = 0.876………….. (3.11)
Where, S = measured saturation flow rate in pcu/hr
w = lane width (m)
R = Constant (Y intercept)
3.7.2 Effect of Gradient Gradient is the average slope between stop line and a point 200 ft. before the stop
line. As per RRTP-56 “ for each 1% of uphill gradient the saturation flow has been
decreased by 3%, and for each 1% downhill gradient the saturation flow increases
by 3%”.
Dick [35] investigated the effect of gradient on saturation flow having measured
approach gradient by using engineer’s level and staff. The result of Dick’s
experiment showed, increase of 1% gradient produces a decrease of 3% in
saturation flow where the gradient continued through the junction.
Heyes and Ashworth [36] carried out an experiment on the effect of gradient on
capacity in Queensway Mersery road Tunnel at Liverpool and they found that 6%
uphill gradi/ent had an effect of 13% reduction in capacity. Leong [27] studied
32
limited gradient effect in Australia and he concluded that 4% up hill gradient
reduced the saturation flow by 9%.
Al-Samarrai [37] studied three sites in city of Sheffield and his results at two sites
showed that 1% uphill gradient decreases the saturation flow by 2% and 1%
downhill gradient increased the saturation flow by 0.33%.
Khaskheli [38] in his study at a flared approach without an additional traffic lane
showed an increase of 5.1% in saturation flow for each 1% downhill gradient.
However, another flared approach with one additional traffic lane showed an
increase of 4.4% in saturation flow for each 1% downhill gradient.
The summary of all the research work that has been carried out in context of
gradient effect on saturation flow is given in Table 3.2.
3.7.3 Effect of Site Characteristics Sites are classified as good, average or poor according to the descriptions given
in Table 3.3.Standard saturation flow is based on observation of ‘average’ sites.
Miller [23] also collected data from many approaches at various locations having
different environmental conditions and measured headway by lane. Four
environments; central business district, industrial, suburban shopping and
residential and three lane types; including left, through and right turning were used
in his experiments. These are defined below.
a. Central business district (CBD)
Central business district of a city with large numbers of pedestrians, high parking
turnover, cars and taxis, pick up and setting down, bus stop, some loading and
unloading of commercial vehicles.
33
b. Industrial
Usually at the edge of the city center. Development includes high industry,
warehouse and other commercial activities. Smaller number of pedestrians than
for CBD but with interference caused by loading unloading of goods vehicles,
vehicle interring and leaving industrial premises with a low parking turnover.
c. Suburban Shopping
Suburban shopping street with moderate numbers of pedestrian and parking
turnover.
d. Residential
Residential or parkland development. Perhaps a hotel or shop or a corner service
station but very few pedestrian. Ideal or nearly ideal conditions for free movement
of vehicles.
Table 3.4 is the basic table of saturation flow for the 12 combinations of lane type
and environment, containing average value.
3.7.4 Effect of Composition of Traffic For measuring the saturation flow in pcu per hour of green time, the information of
pcu equivalents for different type of vehicles is an essential element. In this
regard, Webster & Cobe [1] has carried out an extensive work at the Road
Research Laboratory, and measured the pcu values, which are expressed in
RRTP-56. The summary of all the findings in this context are given in Table 3.5.
Lee and Chen[20] studied the entering headways in small city Lawrence, Kansas
and six factors were examined. Entering headway values from total of 1,899 traffic
queues were recorded by using video camera equipment. From the data, mean
entry headway of vehicle 1 through 12 were found to be 3.80, 2.56, 3.25, 2.22,
34
2.16, 2.03, 1.97, 1.94, 1.94, 1.78, 1.64, and 1.76 sec., respectively. He found the
following observations:
(i) Signal type has little influence on entering headway at signalized intersections.
(ii) Time of the day (a.m. or p.m.) has little influence on entering headways.
(iii) The inside lane of an approach has slightly lower entering headways than
does outside lane.
(iv) The entering headways at approaches with speed limits of 20 mph are
significantly higher than those at approaches with higher speed limits. (>=30
mph). For approaches with speed limits higher than 30 mph, the influence of
speed limit on the headway is noticeable.
(v) In general, streets that have higher speed limits and less roadside friction
have lower entering headway values.
(vi) When queue lengths increase, the general observation is that the entering
headway values decrease.
Taylor et al. (1989) [39] used video-based equipment to estimate the character
speeds and headway. This technique provided cheap, quick, easy, and accurate
method of investigating traffic systems. Investigation of headways on freeway
traffic allows the potential of this technology in a high-speed environment to be
determined. Its application to the study of speeds in parking lots enabled its
usefulness in low-speed environments to be studied. The data obtained from the
video was compared to traditional methods of collecting headways and speed
data.
The departure headways of approximately 10,000 vehicles from straight-through,
exclusive left and exclusive right-turning lanes at 22 intersections in six cities in
Nebraska were collected in the study of Massoum Moussavi and Mohammed
Tarawneh [21]. A microcomputer was used to collect, extract and analyze the data.
The average departure headways obtained in this study were 2.90, 2.04, 2.10,
2.04, 1.87, 1.91 and 1.75 sec respectively, for the first through seventh vehicle in
a stopped queue at signalized intersections. The researchers made comparisons
of the departure headways in different cites and emphasized the variability of
departure headways at signalized intersections [40].
35
Niittymaki et al. [22] found that the departure headway of first vehicle was less than
1.5 sec in the study of saturation flow in Finland. The headway of the second
vehicle in queue was more than 2.5 sec. The third one is around 2.2 sec. After the
fourth and fifth vehicle, the departure headway became constant, less than 2.0
sec. Their study aimed at updating the saturation flow values. The effects of
geometric and traffic composition factors, such as percentage of turning vehicles,
traffic composition, lane width and approach grade were examined [40].
Hossain [41] used micro simulation technique to model traffic operation at
signalized intersections of developing cities. The model was calibrated and
validated on the basis of data collected from Dhaka, the capital of Bangladesh.
Leong et. al. [42] have developed a new statistical approach for finding the PCU
values of different vehicles at signalized intersections with respect to Malaysian
traffic conditions.
3.7.5 Effect of Right Turning Traffic Without opposing flow and with exclusive right turning lanes, it is observed that
the saturation flow of a stream turning through a right angle depends on the radius
of curvature, and is given by: [1]
S = 5/r 1
1800
pcu/h for single file stream………………. (3. 12)
S = 5/r 1
3000
pcu/h for double file stream………………. (3.13)
Where r = radius of curvature (m)
3.7.6 Effect of Left Turning Traffic If the proportion of left turning vehicles is more than 10% of the traffic, a correction
could be made for the excess over 10% by assuming each left turning vehicle
equivalent to 1 .25 straight ahead vehicles [1]
36
3.7.7 Effect of Parked Vehicle
If a vehicle is parked within 10 m. from the stop line there has to be a reduction in
saturation flow. The reduction in saturation flow is equivalent to a loss of carriage
way width at the stop line and can be expressed approximately as follows: [1]
Effective loss of carriageway width = 5.5 — K
25) -(Z 0.9 ft ………… (3.14)
Where Z (>25 ft.) is the clear distance to the nearest parked car from the stop line
and K is green time in sec.
Priyanto [43] in his study investigated the effect of parked vehicles on saturation
flow, extra delay and driver behavior in terms of gap / lag characteristics in
merging behind the parked vehicle. This study covered three approaches.
Saturation was not affected on the right hand lane but it was affected on left
(blocked) and middle (adjacent) lanes. It was found that the use of flashing hazard
indicators caused drivers in the blocked lane to accept shorter gaps and also to
merge further up stream. The later increased the effective length of bottleneck,
which resulted in overall increase in extra delay.
3.8 Heterogeneous Traffic The composition of traffic in developing countries is mixed, with a variety of
vehicles, motorized and non-motorized, using the same right of way. The
motorized or fast moving vehicles include passenger cars, buses, trucks, auto-
rickshaws, scooters and motorcycles; non-motorized or slow moving vehicles
including bicycles, cycle-rickshaw, and animal drawn carts.
Since 1950s, considerable research has been made to develop traffic flow models
for roadways with mainly homogeneous traffic, representing the composition of
traffic primary in developed countries (Khan and Maini) [44]. Very limited studies
have been done to develop an understanding of traffic flow for non-lane-based
heterogeneous or mixed traffic condition in developing countries. Some efforts
have applied a variation of practices developed for homogeneous traffic by
converting heterogeneous traffic by to equivalent passenger car-units and then
applying procedures for homogeneous traffic. However, these efforts have
37
produced mixed results. Recent efforts include the development of microscopic
simulation models.
3.8.1 Comparison of Heterogeneous and Homogeneous Traffic Flow The differences that characterize mixed traffic system are owing to the wide
variation in the operating and performance characteristic of vehicles. The traffic in
mixed traffic flow can be classified as fast-moving and slow moving vehicles or
motorized and non-motorized vehicles. In urban areas, mixed traffic flow often is
also accompanied by substantial pedestrian movement, encroachment at
intersections, street parking, business demand of abutting properties, and narrow
roads.
Lane markings, if present, are typically not followed by mixed traffic flow. Figure
3.2 shows the homogeneous and heterogeneous traffic flow. Traffic does not
move in single lane. Moreover, there is a significant amount of lateral movement,
primarily by smaller-sized motor vehicles. Vehicles do not follow each other within
lanes; hence the concept of relating headways and linear densities is not
meaningful. Vehicles traverse in both the lateral and transverse directions.
At intersection specifically, smaller vehicles such as bicycles, motorcycles, and
scooters use the lateral gaps between larger vehicles in order to reach at the head
of the queue and to discharge quickly (Khan and Maini). [44]
38
Figure 3.2 a) Homogeneous Mix b) Heterogeneous Mix
3.9 Passenger Car Unit (PCU) The unrestricted mixing of various classes of vehicles along a road creates many
problems to the traffic engineers and planners. One type of vehicles in the traffic
stream cannot be considered equivalent to any other type, as there is large
difference in their vehicular and flow characteristics The space of the carriage way
is shared by vehicles depending upon their size, speed, headway and lateral gap
maintained by them. The non-uniformity in the static and dynamic characteristics
of the vehicles is normally taken into account by converting all vehicles in terms of
common unit. The most accepted one such unit is passenger car unit (PCU).
3.9.1 Factors Affecting PCU Values PCU value of a class of vehicle may be considered as the ratio of the capacity of a
road with only that class of vehicles on the road to the capacity with a straight
ahead passenger cars only, under identical conditions.
39
PCU value depends on the following factors:
(i) Vehicle characteristics:
Physical and mechanical, such as length, width, power, acceleration,
deceleration and breaking characteristic of vehicles.
(ii) Stream characteristics:
(a) Mean stream speed
(b) Longitudinal and lateral clearance distribution
(c) Speed characteristic of the stream
(d) Percentage composition of different classes of vehicle
(iii) Roadway characteristics:
(a) Horizontal alignment, grade, location etc.
(b) Stretch: mid-block, signalized intersection etc.
(c) Pavement surface condition, pavement type, pavement width
(iv) Environmental conditions
(v) Climatic conditions
(vi) Control conditions
Since the PCU values depend on the traffic flow parameters, these values are
subject to variations due to the factors influencing the traffic flow parameters.
Therefore, it may not be precisely correct to adopt a constant set of PCU values
under different roadway and traffic conditions.
3.9.2 Determination of PCU Methods previously used for deriving PCU values fall broadly into three groups:
Webster Method, headway method and regression methods (Kimber and
Hounsell)[45]. In headway method, observers with event-recording equipment
makes a detailed record of vehicle departures, and inter vehicle time headways
are calculated by differencing. In essence the method consists of calculating the
effective sample mean time headway hi for vehicle class i, and from it the PCU
value ai is estimated belonging to that class.
40
a i = hi / h1 ....................................... 3.15
where, h1 = headway of cars.
In multiple regression analysis method, the vehicle departures are recorded over
saturated periods T, which begin and end at arbitrary instants. The saturated
green time T is regressed against the number of each category of vehicles
crossing the stop during green time assuming a linear relationship between the
variables. The regression equation will be:
T = a0 + a1x1 + a2x2 + …. anxn …………….3.16
where, T = the clearance time (sec)
xi = the number of vehicles of type i
a0 = error term.
If the vehicle type 1 is passenger car, then the PCU of vehicle type i is given by
ai / a1 …………………………………………………3.17
41
Table 3.1: Summary of saturation flow with approach width as given in
RRTP-56
Approach
width ( ft ) 10 11 12 13 14 15 16 17
Approach
width ( m ) 3.08 3.38 3.69 4.00 4.31 4.62 4.92 5.23
Saturation
Flow
pcu/h
1850 1875 1900 1950 2075 2250 2475 2700
Table 3.2: Summary of effect of gradient on saturation flow from various
Studies
Study Effect of gradient on Saturation Flow
Percent of uphill Percent of downhill
RRTP- 56
LEONG
MILLER
AL-SAMMARI
ABU-REHMEH
KHASKHELI G.B
- 3
- 2.25
- 0.5
- 2
- 1.1
-
+ 3
-
+ 0.5
+ 0.33
+ 1.1
+ 5.5
42
Table 3.3: Effects of site characteristics on saturation flow as per
RRTP-56
Site
Designation Description
% of standard
saturation flow
Good
Average
Poor
Dual carriage way. No noticeable
interference from pedestrian, parked
vehicles and right turning traffic. Good
visibility and adequate turning radii. Exit of
adequate width and alignment
Average Site. Some characteristics of good
and poor
Average speed low, some interference from
standing vehicles, pedestrians and right
turning traffic. Poor visibility and poor
alignment of intersection. Busy shopping
street.
120
100
85
Table 3.4: Average lane saturation Flow in tcu/h* by lane type and
Environment given in ARRB Bulletin No.3 (Miller)
Environment Lane Type
L T R
C.B.D
Industrial
Sub Urban Shopping
Residential
1270
1570
1670
1700
1580
1700
1810
1850
1550
1670
1770
1810
* tcu/h = Through Car Units / Hour
43
Table 3.5: Summary of PCU values from various studies
Study Comm.
Vehicle Bus
R. Turning
Vehicle
L.
Turning
Vehicle
Motor
Cycle
Pedal
Cycle
RRTP – 56
LEONG
MILLER
AL-
SAMMARI
ABU-
REHMEH
CHANG
CHIEN
KHASKHELI
1.75
1.70
2.00
1.69-
2.34
1.60
1.65
1.70
2.25
---
---
2.00
1.80
---
1.95
1.75
1.69
2.09
1.75
1.60
1.12
---
1.25
1.12
1.25
1.34
1.10
1.12
---
0.33
---
---
---
---
0.24
---
0.20
---
---
---
----
----
---
Table 3.6: Level of Service Criteria for Signalized intersections [46]
Level of Service Control Delay per Vehicle (s/veh)
A
B
C
D
E
F
< = 10
> 10 – 20
> 20 – 35
> 35 – 55
> 55 – 80
> 80
44
CHAPTER 4
METHODS FOR MEASURING SATURATION FLOW
4.1 General There are various methods of data collection to measure saturation flow, ranging
from manual to complex automatic techniques. This chapter presents the review
of various methods, which have been used by researchers to record saturation
flow at signalized intersections. All these methods have some merits and
demerits. Any method, which should be selected for any study depends on many
factors like the type of study, availability of manpower, ease of analysis, cost and
should provide a permanent record of data for further analysis at any time.
4.2 Measurement Techniques All the existing methods of measuring saturation flows assume that saturation flow
rate is fixed during a saturated green signal. Three distinguished measurement
methods have been proposed [47]:
a) Headway method (Greenshields et al. [16] ; TRB 1997) estimates the
average time headway between the vehicles discharging from queue as
they pass the stop-line. The first several vehicles are skipped to avoid the
effect of vehicles' inertia in the initial seconds of green time. The saturation
flow rate is calculated as reciprocal of the mean headway.
b) Regression technique (Branston and Gipps [48]; Kimber et al.[45] ; Stoke et
al. [49] ) is used to develop an equation involving saturated green time,
number of vehicles in various categories, and lost time. A regression
analysis yields the saturation flow, the lost times, and the passenger car
equivalents for vehicles other than passenger cars.
45
c) TRL method (TRRL 1963)[47,50], vehicles are counted in three saturated
green intervals. The saturation flow is calculated as the number of vehicles
in the middle interval divided by the length of this interval.
4.3 Measurement Methods 4.3.1 Road Research Laboratory Method This is a manual method for data collection for saturation flow estimation. The
details are described in Road Note No.34 [50].
According to this method, green plus amber time is to be divided in to short
interval such as of 0.1 minute (6 seconds). All those vehicles whose rear wheels
cross the stop line during each 0. 1 min intervals are to be counted.
The flows in saturated intervals, which are free from lost time, are averaged to get
saturation flow It is seen that saturation flows in the first and last intervals are
affected by driver’s starting delay at the start of amber and stopping at the lapse of
green time, respectively. The saturation flow observed in those intervals which are
free from lost time, is to be compared with the saturation flow in the first and last
intervals to get the initial and final lost time, respectively. Special forms are to be
used at site during experiment.
Two “split second”, stopwatches are required to record the data on the forms.
These watches should be graduated in tenth and hundredths of a minute. All the
timings should be recorded to nearest 0.01 min. Watches are to be synchronized
before the start of data collection.
This method is simplest but it has a drawback, causing difficulty in classifying the
different types of vehicles and recording the various turning movements.
Therefore, it requires more manpower, which is uneconomical.
4.3.2 Recorder Method In this method, the data should be recorded either on paper tape or on a paper
chart driven at a constant speed. All the information relevant to saturation flow
should be recorded on to paper tape or chart. The analysis involves the manual
work of measuring the distance on the tape or on the chart to know the time
interval. Therefore some errors are inevitable due to variation in the observer’s
46
reaction time. The following are the various types of the recorder method, which
have been used by various researchers in earlier studies.
4.3.2.1 Typewriter Method This method was developed by Helim [53] in 1957-58, during the study of
saturation flow at light controlled intersection in Newcastle Upon Tyon and
GateShied. During the observation vehicles were classified into four groups, light
vehicles, heavy vehicles, heavy commercial vehicles and public service vehicles.
For the data collection a modified typewriter was used. With the use of a modified
typewriter, measurements were within a limit of 1/10 seconds; this enabled the
data collection suitable for individual vehicle analysis as well as for whole traffic
stream.
4.3.2.2 The Rustrak Four Channel Event Recorder Method This method was developed while collecting data for saturation flow and lost time
in Aberdeen by using the same procedure of Road Research Laboratory method,
as highlighted above, but permitting simultaneous classified counts of four traffic
streams and timing of signal cycles. [54]
4.3.3 Battery Operated Cassette Tape Recorder Method This method was used by Miller,[23] for data collection in seven main cities of
Australia. It was similar to Road Research Laboratory method. The only difference
being that in the case of Road Research Laboratory method the traffic data were
recorded on forms at the sites whereas in this method, the data were recorded on
the tape and then abstracted by playing back the recorded cassette in the
laboratory. All the information concerned with the data, i.e., vehicle types, turning
movements, change in signal phase and all the vehicles that cross the stop line
during these short intervals, were recorded.
47
4.3.4 Time Lapse Photography Method Time laps cinematography is an old technique and was developed extensively for
many forms of engineering data collection. Each picture or frame might be
considered as a pictorial description of position of those vehicles, which are within
the field of camera view at the instant of exposure. By comparing the positions of
the individual vehicles on consecutive frames of the film distance which these
vehicles had been moved could be estimated and hence these various
parameters of traffic flow could be evaluated.
For precise measurement, a series of the equidistant markings along the side of
carriage way could be marked before the filming commenced. This marking would
come up on the film through which the positions of the vehicles could be
determined.
Time laps photography has proved a useful tool for data collection in the traffic
engineering for studying the traffic behavior. The drawback in this method is the
inability of the equipment to operate in excess of four frames per second with an
accurate time base as discovered by Ashworth [55]
4.3.5 Video Tape Recorder Method During the last three decades video tape recorder has proved to be the most
popular alternative method of recording traffic behavior. This equipment has
provided more satisfactory results than the time laps photography in its early
stage.
During the data collection at the site the portable video recording camera and
number generator is used to super impose the time based on the recorded traffic
events. Nowadays cameras with a built-in time base recording are available, that
can measure the time in fraction of a second.
While recording, the camera should be so placed that the reference line should be
visible and every traffic event should be abstracted easily. This instrument has
proved satisfactory, but there exists one disadvantage of blurring image, which is
less evident in time laps photography. Due to the availability of slow motion facility
48
in the video cassette player, it appears to be better than the other methods
because of accuracy and required manpower. The advocacy of this method is
proved by many researchers [30,31,37,43]
4.3.6 Use of Mobile Traffic Laboratory
This is an advance version of use of video recording method. This method was
used by Cartagena and Tarko and is explained in their research paper [94].In this
method a digital video recoder and cameras on a 45-ft mast were used for
recoding traffic queues and signal displays. The mobile traffic laboratory was
parked near the intersection where traffic operations were not affected by its
presence. [56]
Fig. 4.1 Typical layout of field data collection equipment setup [56]
49
Fig. 4.2 Field data collection setup[56]
Fig. 4.3 Field data collection screen view[39]
50
4.3.7 GIS Based Method
With the recent developments in the field of remote sensing and GIS, this
technology is also being used for traffic data collection. Data collected using GIS
has several advantages and some limitations. The satellite imagery of the project
area or area of interest is obtained and the required data is retrieved [97].
4.4 Method Used In This Study To achieve the objectives of this thesis, field observations were required to
measure the vehicular headways for saturation flow at different approach
configurations containing traffic flows of varied compositions.
Since it will need two or more observers to collect the necessary data manually, it
was decided to use a Video Recording technique for data collection. This
technique had several advantages. Information on headway, vehicle types, turning
movements, end of saturated flow conditions, interruptions to traffic streams and
traffic volumes could all be gathered simultaneously by one observer and
analyzed by a single observer on a television screen. The other advantages of
data collection and analysis by single observer are consistency of observation,
reaction and judgment. Errors could also be minimized by replaying the field data
tape on the screen. A disadvantage with this method is that, one cannot record
film for a complete intersection, but only one approach under this observation.
Considering the obvious advantages, use of technology and ease of operation,
Video recording method is preferred. A camcorder mounted over stand was
placed at vantage point to cover the traffic flow over the entire approach. The data
for traffic flow was recorded and later analyzed in the laboratory.
51
CHAPTER 5
EXPERIMENTAL INVESTIGATIONS
5.1 General This chapter presents the collection of data and presentation of results from the
collected data. The objectives of this research work reported in this thesis are
given in chapter one. In order to meet the designed parameters, a strategy was
planned to meet the target.
The study area selected were two major arterials of Karachi, namely, Shahra-e-
Faisal (Figure 5.2) and M.A. Jinnah Road (Figure 5.3). To start the study, a
planning session was arranged to select sites where the required data could be
collected.
5.2 Selection of Sites The choice of study locations was based on the following requirements:
(i) The site should have a zero uphill and downhill gradient with no
interference of turning movements.
(ii) Approaches would be ideal if little or no interference to the flow of vehicular
traffic is caused by a pedestrian crossing.
(iii) Compliance in lane discipline to enable each lane to be observed
separately.
(iv) Site should be such that a high vantage point could be easily selected
close to the intersection, which could enable researcher to use video-
camera to record traffic flow properly.
(v) Good geometric design, uniform road width and pavement surface are
required.
(vi) Approaches should not have “active” driveways within 300 ft of the stop
line.
52
(vii) Approaches should not have local bus stops on the near or far side of the
subject approach.
(viii) Approaches should not have sharp curves or other unusual
horizontal/vertical geometric condition.
(ix) Approaches should not experience queue spillback during the study period.
For the selection of sites, a preliminary survey was carried out to find the suitable
sites that fulfill the requirements of this study. For this purpose a 30 day site
selection program was used to utilize all the above factors and select most
suitable sites.
5.3 Study Timings During preliminary survey, it was observed that the queues were denser and had
longer length at morning peak from 8:00 am to 10:30 am and at the evening from
5:30 p.m. to 8:00 p.m. It was observed that over saturated periods were longer
during evening peaks.
It has been observed that some of the intersections on Shahra-e-Faisal (Major
arterial of Karachi) have longer green periods at peak times. Programmable
controllers are installed that have ability to vary the relative duration of the green
and red phases according to preset traffic pattern. Thus making it possible to
operate signals with different sequences for the morning and evening peak
periods.
All traffic events were recorded during the observed peak traffic hours (e.g.,
morning, noon, and/or afternoon peak). The equipment was set up at least15
minutes before the start of each study period. Prior to the start of each study, the
clock in each camcorder was synchronized with a common stopwatch.
Data were collected during time periods that are reflective of typical peak traffic
periods at each study site. These periods typically occurred during working days
in the morning (7:30 to 10:00 a.m.) and evening (5:00 to 8:00 p.m.) peak periods.
Data were not collected during holidays, periods of inclement weather, incidents,
construction activity or any other reason due to which abnormally low or high
volume of traffic occurs.
53
Fig
5.1
R
oad
Net
wo
rk o
f K
arac
hi
Cit
y
54
INT
ER
SE
CT
ION
S W
HE
RE
DA
TA
HA
S B
EE
N
RE
CO
RD
ED
A 2
A 1
A 9
A 8
A 7
A 4
A 3
A 1
0
A 6
A 5
A 1
2A
13
A 1
1
INT
ER
SE
CT
ION
S W
HE
RE
DA
TA
HA
S B
EE
N
RE
CO
RD
ED
A 2
A 1
A 9
A 8
A 7
A 4
A 3
A 1
0
A 6
A 5
A 1
2A
13
A 1
1
Fig
5.2
A
lign
me
nt
of
Sh
ahra
-e-F
aisa
l (K
arac
hi)
55
SH
AH
RA
-E
-F
AIS
AL
M.A
.JIN
NA
H R
OA
D B1
B2
B3
B4 B5
SH
AH
RA
-E
-F
AIS
AL
M.A
.JIN
NA
H R
OA
D B1
B2
B3
B4 B5 Fig
5.3
In
ters
ecti
on
s o
n M
.A.
Jin
nah
Ro
ad
56
For the purpose of experimental investigation thirteen different signalized
intersections were selected on Shahra-e-Faisal and five intersections were
selected on M.A. Jinnah Road. Data was collected and analyzed for all eighteen
intersections. In this study the width of the lane varied from 2.5 to 3.5 meters.
An important observation was that on most of the approaches, the traffic did not
follow the lane discipline due to which it was a challenge to study each individual
lane. Therefore, it was decided to study the full approach width used by the traffic
as a whole.
It is pertinent to mention that Shahra-e-Faisal is the only arterial in Karachi city
which meets the criterion for selection of intersections and approaches for data
collection. However, for the purpose of comparison, another arterial M.A. Jinnah
Road was selected where flow, conditions, intersection geometry, traffic and
vehicle type is totally different from Shahra-e-Faisal. Summary of approaches
studied in this research is listed in Table 5.1a and 5.1b.
5.4 Materials and Equipment A camcorder mounted on stand was used to record the traffic flow. Recording was
carried out from a higher floor of a building to provide the best coverage for
studying the required approach as well as not to create any suspicion in the minds
of the intersection users.
To give camcorder the time to attain normal operating speed, recording at an
approach started from the start of the amber period of the cross phase at the
latest. Commencement of green phase on some approaches was verbally
recorded on the videotape, as at some intersections the signal lights were not
visible from the position of the camcorder. This technique is used in several
countries of the world in case of hindrance to traffic signals.
The data tapes were analyzed in the laboratory using a video cassette player at
real life speed and a television set. All data were analyzed while playing back the
recorded video cassette in the laboratory.
57
5.5 Data Collection and Analysis for Passenger Car Unit Every traffic platoon may be composed of different classes of vehicles that would
require different road space according to their sizes. The traffic comprises of
larger and lower-performance vehicles, such as buses, loading trucks and
recreational vehicles, reduces the capacity of highways. HCM 2000 mentions the
philosophy of vehicle’s equivalents on the bases on observations of free flow
conditions in which the larger vehicles creates less than base conditions. It further
mentions that physical road space occupied up by a heavy vehicle is generally
greater as compare to the passenger car in terms of length [7].
For capacity analysis on the basis of a consistent measure of flow, the larger type
vehicle is converted into an equivalent number of passenger cars [7]. Therefore it
is usual to assign weighting factors, called passenger car equivalents (PCE) or
passenger car units (PCU), to the various types of vehicles, so that flows can be
expressed in the common base of PCU/hr. The PCU value of a given type of a
vehicle is related to its effect relative to a standard passenger car, where the PCU
value of a passenger car is by definition equal to 1.0.
There is a great deal of literature on PCU values and ways of estimating them, for
example Miller [23], Branston and Van Zuylen [57], Akcelik [58], Kimber et al [45] and
McLean [59].
McLean devotes a section of his book to the derivation of PCU values for 2 lane -
2 way roads. He divides methods of PCU derivation into ‘direct’ methods, in which
equivalency is directly related to flow performance, and ‘indirect’ methods, in
which it is not. The direct method includes the derivation of PCU values from
observing flows at capacity (which he points out is not often reached on 2 way
rural roads and which is in any case difficult to define because of directional
distribution) and from empirical speed-flow observations. He explains that this can
be difficult because the opposing stream interaction complicates the impedance
effects of slow vehicles when the combined performance of both streams is taken
into account. This is because a slow vehicle in one direction will delay other
vehicles in the same direction but will also cause platooning which is beneficial
(for overtaking opportunities) to the opposing stream.
58
The indirect method includes the equivalent overtaking rate method that was used
in the former version of HCM 2000 (HCM 1965). He also includes the ‘headway
method’, in which the PCU value of a truck is taken to be the ratio of the average
headway of trucks to cars. Therefore, it is necessary in the subject study to
introduce the passenger car units (PCU) for each class of vehicle to express the
traffic flow in passenger car units equivalents for calculation of signal phases and
the cycle timing.
To collect the data and to find the PCU values for different types of vehicles, a
camcorder, equipped with built-in timer to measure time up to 0.1 second, is used
to collect the data. The recorded films were played back in the laboratory on a
large screen TV monitor to extract the desired information. Recorded tapes were
played back to extract the “headway” between rear wheels of the each two
consecutive vehicles. The headway was measured by individual lanes at the stop
line.
The time was counted from the moment that the signal changed to green and
continued until the flow had fallen below the saturation level. Timing was always
based on the moment when the rear wheels of a vehicle crossed the stop line,
because vehicles frequently stopped ahead of the stop line.
The extracted results are used to obtain the passenger car units equivalents of the
different types of vehicles by comparing their average headway with the average
headway of normal passenger cars.
5.6 Data Collection at Shahra-e-Faisal
5.6.1 Passenger Cars
A sample of 300 headway of cars was taken through the saturated cycles
(Approaches not containing heavy vehicles) and then analyzed. The headway of
cars ranged between 0.14 to 2.4 seconds with a mean value of 1.24 seconds. The
standard deviation of the sample was ±0.296 and at 95 % confidence interval
upper and lower limit of the sample were 1.23 and 1.30
Therefore, for the purpose of obtaining PCU values for various vehicle types, a
mean headway of passenger cars of 1.24 seconds has been taken to compare the
59
headway of the other types of vehicles to get the required pcu values for such
vehicles. [Appendix 36, page 149]
5.6.2 PCU Equivalents for Motorcycles
It was observed that motorcycles did not occupy any fixed position in the lane and
are not causing an effect to the saturation flow. However, a sample of 200
motorcycles headways was analyzed to obtain the pcu value for motorcycle.
The headway ranged from 0.08 to 1.24 with a mean value of 0.46 seconds. The
standard deviation of the sample was 0.25 and at 95% confidence interval upper
and lower limit of the sample were in between 0.44 and 0.56.
The pcu equivalent so obtained for motorcycle was 0.37. [Appendix 37, page 150]
5.6.3 PCU Equivalents for Minibuses
A sample of headway for 70 minibuses was analyzed to find the pcu value for the
minibuses. The headway ranged between 1.84 to 3.28 seconds with a mean
headway of 2.61. The standard deviation of the sample was ±0.43 and at 95%
confidence interval upper and lower limit of the sample were 2.44 and 2.80.
The pcu equivalent of minibuses was obtained by dividing the headway of minibus
to that of car and comes out 2.10. [Appendix 38, page 151]
5.6.4 PCU Equivalents for Vans
A sample of headway for 70 vans was analyzed to find the pcu value for the vans.
The headway ranged between 1.50 to 3.28 seconds with a mean headway of
1.87. The standard deviation of the sample was ±0.40 and at 95% confidence
interval, upper and lower limit of the sample were 1.4 to 2.24.
The pcu equivalent of van was obtained by dividing the headway of van to that of
car and comes out 1.51. [Appendix 39, page 152]
60
5.6.5 PCU Equivalents for Rickshaws
A sample of headway for 80 rickshaws was analyzed to obtain the pcu value for
the same. The headway ranged between 0.12 to 1.12 seconds giving a mean
value of 0.54 seconds. The standard deviation of the sample was 0.24 and at 95%
confidence interval upper and lower limit of the sample were in between 0.43 and
0.65 seconds.
The pcu equivalent for rickshaw so calculated comes to 0.43. [Appendix 40, page
153]
5.6.6 PCU Equivalents for Buses/Trucks
A sample of headway for 40 buses was analyzed to find the pcu value for buses.
The headway ranged between 2.80 to 4.56 seconds with a mean headway value
of 3.76 seconds. The standard deviation of the sample was ±0.39 and at 95%
confidence interval limit the mean of the sample was in between 3.52 to 3.80
seconds.
The mean headway of bus was divided to that of car to obtain pcu equivalent,
which comes out 3.0. [Appendix 41, page 154]
The pcu values which have been found through the comparison of average
passenger car headway with the other types of vehicles headway on Shahra-e-
Faisal are given in Table 5.2. These values are used in this study to convert the
saturation flow from vehicles per hour to pcu per hour.
61
5.7 Data Collection at M.A. Jinnah Road
5.7.1 Passenger Cars
The sample of headway for 200 cars was taken through the saturated cycles and
then analyzed. The headway of cars ranged between 0.16 to 2.8 seconds with a
mean value of 1.34. The standard deviation of the sample was 0.30 and at 95%
confidence interval lower and upper limits of the mean value of the sample was
1.24 and 1.36
Therefore, for the purpose of obtaining pcu values for various vehicle types a
mean headway of passenger cars of 1.34 seconds has been taken to compare the
headway of the other types to get the required pcu values for other types of
vehicle.
5.7.2 PCU Equivalents for Minibuses
A sample of headway for 50 minibuses was analyzed to find the pcu value for the
minibus. The headway ranged between 2.76 to 3.40 seconds with a mean
headway of 3.43. The standard deviation of the sample was 0.403 and at 95%
confidence interval lower and upper limits of the mean value of the sample was in
between 2.64 to 4.12.
The pcu equivalent of minibus was obtained by dividing the headway of minibus to
that of car and comes out 2.55.
5.7.3 PCU Equivalents for Buses/Trucks
A sample of headway for 40 buses was analyzed to find the pcu value for buses.
The headway ranged between 3.20 to 4.86 seconds with a mean headway value
of 4.96 seconds. The standard deviation of the sample was 0.32 and at 95%
confidence interval lower and upper limits of the mean value of the sample was in
between 3.80 to 5.42 seconds.
The mean headway of bus was divided to that of car to obtain pcu equivalent,
which comes out 3.69.
62
5.7.4 PCU Equivalents for Vans A sample of headway for 50 vans was analyzed to find the pcu value for the vans.
The headway ranged between 1.60 to 3.28 seconds with a mean headway of
2.47. The standard deviation of the sample was 0.36 and at 95% confidence
interval lower and upper limits of the mean value of the sample was in between
1.88 to 2.64.
The pcu equivalent of van was obtained by dividing the headway of van to that of
car and comes out 1.84.
5.7.5 PCU Equivalents for Rickshaws
A sample of headway for 50 rickshaws was analyzed to obtain the pcu value for
the same. The headway ranged between 0.24 to 1.32 seconds giving a mean
value of 0.708 seconds. The standard deviation of the sample was 0.28 and at
95% confidence interval lower and upper limits of the mean value of the sample
was in between 0.56 and 0.88 seconds.
The pcu equivalent for rickshaw so calculated comes to 0.52.
5.7.6 PCU Equivalents for Motorcycles
It was observed that motorcycles did not occupy any fixed position in the lane and
are not causing an effect to the saturation flow. However, a sample of headway for
100 motorcycles was analyzed to obtain the pcu value for motorcycle.
The headway ranged between 0.15 to 1.44 with a mean value of 0.61 seconds.
The standard deviation of the sample was 0.21 and at 95% confidence interval
lower and upper limits of the mean value of the sample was in between 0.51 and
0.68.
The pcu equivalent so obtained for motorcycle was 0.45.
The pcu values which have been found through the comparison of average
passenger car headway with the other types of vehicles headway are given in
Table 5.2 and 5.3. These values are used in this study to convert the saturation
flow from vehicles per hour to pcu per hour.
63
Table 5.1a Summary of Approach Widths Studied on Shahra-e-Faisal
S.No Name of Approach Width (m) No. of Lanes in each direction
1
2
3
4
5
6
7
8
9
10
11
12
13
Star Gate (A1)
Shah Faisal Colony (A2)
Drig Road (A3)
Karsaz (A4)
Awami Markaz (A5)
Tariq Road (A6)
Regent Plaza (A7)
Mehran Intersection (A8)
Kashif Centre (A 9)
Faisal Base (A 10)
Lal Qila (A 11)
Kala Pull (A 12)
Nursery (A 13)
11.6
16.0
13.1
12.7
12.0
12.0
12.0
9.0
6.4
12.0
6.4
10.06
12.0
3
4
3
3
3
3
3
3
2
3
2
3
3
Table 5.1b Summary of Approach Widths Studied on M.A. Jinnah Road
S.No Name of Approach Width (m) No of Lanes in each direction
1
2
3
4
5
Mazar-e-Quaid (B1)
Capri Cinema (B2)
Prince Cinema (B3)
Garden Road (B4)
Tibet Centre (B5)
15.6
12.6
12.0
13.1
9.0
4
3
3
3
3
64
Table 5.2 Summary of PCU Values Observed at Shahra-e-Faisal
Vehicle Type Total
Sample Size
Range of Headways
(sec)
Lower & Upper Limit of Mean @
95%
Mean Headway
s (sec)
Standard
Deviation
PCU Values
Car 300 0.14 – 2.4 1.23 – 1.30 1.2398 0.29 1.0
Motorcycle 200 0.08- 1.24 0.44 – 0.56 0.4607 0.25 0.37
Rickshaw 80 0.12 – 1.12 0.43 – 0.65 0.5420 0.24 0.43
Van 70 1.50 – 3.28 1.40 – 2.24 1.8750 0.40 1.51
Minibus 70 1.84 – 3.28 2.44 – 2.80 2.6144 0.43 2.10
Bus / Truck 40 2.80 – 4.56 3.52 -3.80 3.7680 0.38 3.0
Table 5.3 Summary of PCU Values Observed on M.A. Jinnah Road
Vehicle Type
Total
Sample Size Range of
Headways (sec)
Lower & Upper Limit of Mean
@ 95%
Mean Headways
(sec)
Standard Deviation
PCU Values
Car 200 0.16 – 2.8 1.24 – 1.36 1.345 0.3004 1.0
Motorcycle 100 0.15 -1.44 0.51 – 0.68 0.612 0.2184 0.39
Rickshaw 50 0.24 –1.32 0.56 – 0.88 0.708 0.2864 0.47
Van 50 1.60 – 3.28 1.88 – 2.64 2.478 0.3618 1.64
Minibus 50 2.24 – 4.40 2.64 – 4.12 3.434 0.4035 2.32
Bus / Truck 40 3.20 – 4.86 3.80 -5.42 4.9640 0.3218 3.52
65
5.8 Comparison of PCU Values of Shahra-e- Faisal and M.A. Jinnah Road
Comparison of pcu values of Shahra-e-Faisal and M.A. Jinnah Road reveals that
pcu values of vehicles on M.A. Jinnah Road are higher than that of pcu values on
Shahra-e-Faisal. It is owing to the fact that Shahra-e-Faisal is a major arterial and
flow of traffic is comparatively smooth with fewer hindrances. Drivers obey traffic
rules because of strict enforcement. On Shahra-e-Faisal number of buses and
goods vehicles is less and animal drawn vehicles are not allowed. On the other
hand on M.A. Jinnah Road traffic congestion is quite often. Number of buses is
more. Animal drawn vehicles are also there and due to less enforcement drivers
usually do not obey rules. Hence, formation of long queues and traffic jam is
normal phenomenon.
5.9 Comparison of PCU Values of Shahra-e- Faisal and M.A. Jinnah Road With PCU Values in Other Countries
In Overseas Road Note No 13 [61], published by Overseas Centre, Transport
Research Laboratory, U.K. in 1966, a detail discussion has been carried out on
the use of traffic signals in developing cities. In this Road Note PCU values used
in different countries has been discussed. Table 5.4 presents the comparison of
PCU values of Shahra-e-Faisal and M.A. Jinnah Road with PCU values in other
countries.
5.10 Measurement of Approach Width
The measurement of all approach widths were made at site by measuring tape
and number of lanes in each direction were also noted. Measurements were made
at the stop line. The widths of all approaches and number of lanes in each
direction that were studied in this research are given in Table 5.1a and 5.2b.
66
Table 5.4 Comparison of PCU Values of Shahra-e-Faisal and M.A. Jinnah Road With Other Countries
(Source: The Use of Traffic Signals in Developing Cities, Overseas Road Note 13. Overseas Centre, Transport Research Laboratory. 1996.)
Vehicle
Type England
1966 France 1974
Japan 1974
Indonesia 1984
India Cairo 1985
Chile 1984
Road Note 13
1996
Shahra-e-Faisal
2008
M.A. Jinnah Road 2008
Car 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
Minibus 1.0 - - 1.25 - 1.0 1.26 1.25 2.10 2.55
Motorcycle 0.33 0.3 0.33 0.2 0.25 0.5 0.64 0.3 0.37 0.45
Heavy Goods 1.75 2.0 1.75 2.25 2.8 1.6 2.23 2.5 - -
Bus 2.25 2.0 1.75 2.62 3.6 2.5 1.52 2.5 3.0 3.69
Auto Rickshaw - - - 0.52 0.6 - - 0.5 0.43 0.52
Van - - - - - - - - 1.51 1.84
Pedal Rickshaw - - - 0.93 1.4 - - 1.0 - -
Pedal Cycle - 0.3 0.2 - 0.4 - - 0.3 - -
Horse & Cart - - - - 2.6 4.0 - 3.0 - -
Bullock Cart - - - - 11.2 4.0 - - - -
67
5.11 Saturation Flow Data Collection and Analysis (For both
Arterials, i.e., Shahra-e-Faisal & M.A. Jinnah Road)
For measuring the saturation flow, the method of video tape recording was used,
as it was used for passenger car units’ equivalents. According to Road Note No.
34 [50], the forms were prepared and all the vehicles crossing the stop line during
green period were recorded.
Before starting data retrieval, it is necessary to group the lanes having similar
characteristics. Following guidelines were used [51]:
(i) Each exclusive right turn or left turn lane/lanes was designated as separate
lane groups.
(ii) On approaches with exclusive left-turn and or right-turn lanes, all other
lanes would generally be included in single lane group [51].
(iii) When two or more lanes are included in lane group for analysis purposes,
all subsequent computation treat these lanes as single entity [51].
Saturation flow rate is the maximum discharge rate during green time. It is
calculated either in PCU/hr or Vehicles/hr. Saturation period and movement wise
traffic volume is necessary to calculate saturation flow for particular lane group.
The procedure for measuring prevailing saturation flow is summarized below [51].
A sample worksheet used for recording retrieved information is included in
Appendix 7. One person can retrieve required data but more than one would be
able to reduce total retrieval time. Observation point was selected by playing video
cassette. The observation point is normally stop line. Start of the green is noted
down from camcorder timer. Camcorder gives time with accuracy of one minute.
Video Cassette Player (VCP) timer was used to measure time in seconds.
Conventional stop watch may also be used for this purpose. VCP timer is set to
zero, by pausing the cassette at the moment signal indication turns to green.
Cassette is played until the last vehicle in the queue crosses the observation
point. Saturation period is noted down from the VCP timer.
The period of saturation flow begins when the green has been displayed for 10
seconds. Saturation flow ends when the rear axle of the last queued vehicle that
68
was present at the beginning of the green time crosses the stop line(HCM 2000)
[2]. Then cassette is reversed to original position and replayed. This time classified
vehicles count is done for each movement. Initial 10 seconds from the start of
green are left to take into account start up loss time. It is not possible to count all
classified vehicle count at a time for all movements. Therefore, cassette was
replayed number of times and every time vehicle count of one or two category
was done. The above procedure was repeated for each cycle of recorded period.
This methodology was applied to all approaches that have been studied in this
study. A sample of such form comprising of calculation for saturation flow is given
in Appendix 21.
The summary of saturation flow at all the approaches in veh / hour for both
arterials is given in Tables 5.5 and 5.6, respectively. The values of pcu
equivalents which are given in Tables 5.2 and 5.3 were used to convert the
observed saturation flow in to pcu / hour from veh / hour. The summary of such
data is given Table 5.7 and 5.8.
69
Table 5.5 Observed Saturation Flow on each Approach on Shahra-e-Faisal (Vehs / hr)
Name of Approach Width (m) Saturation Flow
A 1
A 2
A 3
A 4
A 5
A 6
A 7
A 8
A 9
A 10
A 11
A 12
A 13
11.6
16.0
13.1
12.7
12.0
12.0
12.0
9.0
6.4
12.0
6.4
10.06
12.0
8570
10994
9100
9280
9777
9765
9555
7824
6697
10107
6622
8405
9300
Table 5.6: Observed Saturation Flow on each Approach on M.A. Jinnah Road (Vehs/ hr)
Name of Approach
Width (m) Saturation Flow
B 1
B 2
B 3
B 4
B 5
15.6
12.6
12.0
13.1
9.0
11298
9540
8610
9080
8277
70
Table 5.7 Observed Saturation Flow on each Approach on Shahra-e-Faisal
(PCU / hr)
Name of Approach Width (m) Saturation Flow
( PCU / hr)
A 1
A 2
A 3
A 4
A 5
A 6
A 7
A 8
A 9
A 10
A 11
A 12
A 13
11.6
16.0
13.1
12.7
12.0
12.0
12.0
9.0
6.4
12.0
6.4
10.06
12.0
8210
10463
8539
7481
8556
8021
7340
6170
5606
9366
4744
6929
8064
Table 5.8: Summary of Saturation Flow on each Approach on M.A. Jinnah Road (PCU/hr)
Name of Approach
Width (m) Saturation Flow ( Vehs / hr)
Saturation Flow ( PCU / hr)
B 1
B 2
B 3
B 4
B5
15.6
12.6
12.0
13.1
9.0
11298
9540
8610
9080
8277
10210
8836
8085
8574
7856
71
5.12 Lost Time
Lost time can be defined as “the time, in seconds, during which an intersection is
not used effectively by any movement. It is the sum of clearance lost time plus
start-up lost time”. or “The time per signal cycle during which the intersection is
effectively not used by any movement. This occurs during the change and
clearance intervals and at the beginning of most phases” [2].
The terminology of lost time is being used for the time during which no vehicles
can pass through an intersection though the green signal is displaying for
particular approach. The total lost time is the outcome of two different
components: start-up lost time and clearance lost time. Start-up lost time is being
defined as time lost when a traffic signal turns from red (stop) to green. Due to this
phenomenon some amount of time elapses between the changing of signal from
red to green and the first vehicle in the queue to move through the intersection. An
additional amount of time for the next vehicle to start to move and pass the
intersection. The total time taken for all the vehicles in queue to react and
accelerate to pass the intersection is termed as the start-up lost time [52].
The term clearance lost time is defined as the time lost at stopline by the vehicles
at the end of a green phase. Unit for measurment of lost time is seconds. Start-up
lost time can be calculated while evaluating the sum of the differences between
the headways for the first cars in queue and the average headway through the
intersection at a ideal maximum flow,i.e., the saturation flow rate. In the absence
of any observations, the start-up lost time is being considered as 2.0 seconds as a
default value [79] [52].
A lot of research has been carried out by many researchers to calculate/estimate
lost time at signalized intersections. Different methods have been evolved and
been recommended by the researchers.
As per Overseas Road Note No 13, [61] lost time in the green and amber periods is
the un used time during which no flow takes place. Total lost time per cycle is the
sum of these lost times for the critical phases plus other lost times due to red-
amber periods, all red periods and pedestrian green and flashing green times.
Figure 5.4 presents the concept of cycle profile which includes green, amber and
red and graphical representation of lost time. The lost time for a single phase
72
during the green and amber period is normally about 4 seconds. In other words,
the effective green time is thus the green time + 1, then, per cycle:
Total lost time = 4*number of stages + all red
Figure 5.4: Cycle Profile (Lost Time Concept) [88]
Minh and Sano [62] concluded that start-up lost time is the time lost due to driver
reactions and vehicle acceleration. The start-up lost time is estimated by the
summation of the difference between the observed headway of each vehicle and
saturated headway. Figure 5.5 presents model proposed by Minh and sano[62] .
Start-up lost time = Σ(Observed headway – Saturated headway)
and then
Total Lost Time = Start-up lost time + Clearance Lost Time
RedAm ber
A m ber Red
T im e
Effective Green T im e
Saturation Flow
Final Lost Tim eInitial Lost Tim e
Rat
e O
f D
isch
arge
of
Que
ue in
S
atur
ated
Gre
en P
erio
d
73
Figure 5.5: Saturated Headway & Lost Time Measurement (Adopted from [62])
According to McShane and Roess [63], lost time (Lt) is the time during which the
intersection is not effectively used by any approach. This occurs during the
change interval or the clearance time, (change interval lost time) and at the
beginning of each green indication as the first few cars in a standing queue
experience start-up delays, i.e., start up lost time.
The start-up lost time is estimated by the sum of the differences between the
observed headway for each of the vehicles before the headway stabilizes (Table
5.9)
Table 5.9: Lost Time Calculation (McShane and Roess)
Queue Position
Observed Average Headway (sec)
Estimated Headway (sec)
Difference, Observed Minus Actual (sec)
1 2.61 2.14 0.47
2 3.00 2.14 0.86
3 2.52 2.14 0.38
4 2.37 2.14 0.23
5 2.21 2.14 0.07
> 5 2.14 2.14 0.00
Start-up lost time = 2.10 sec
74
Akcelik [58], has proposed a simple method for measurement of the saturation flow
and lost time in vehicle units (without considering the composition of traffic). It can
be achieved using a form as reproduced in the table 5.10. This method consists of
vehicle count departing from the queue in each lane during three different
intervals for simplicity, columns 1 to 3 of Table 5.10 can be seen for suitability of
method for traffic count [58, 64]:
First Interval: It comprises of the first 10 seconds of the green period;
Middle Interval: It is the rest of the green period while saturated;
Last Interval: This interval is the period after the end of green, i.e., amber and the
following red period.
All those vehicles that cross the stop line are then counted, but a decision has to
be made about when the saturated period ends by observing the back of the
queue of vehicles. Thus, the saturation time (column 4 of the table 5.10) was
recorded as the time to clear the vehicles awaiting to cross the intersection which
are stopped during the red period as well as the vehicles which arrive at the end
of the queue and are stopped during the green period. However, the vehicles
which did not stop are being excluded from this count. The saturation period only
includes the first interval. Its maximum value is the green time (given in column 5),
which corresponds to a fully saturated cycle. If the saturation time is less than 10
seconds, the counts of this cycle must be excluded. The departures of vehicles in
the last interval were counted only for fully saturated conditions, i.e., when the
queue of vehicles existed at the end of the green period. If no vehicles departed in
the last interval of the green period despite saturated conditions, zero value has
been recorded in column 3 [64].
The vehicle counts must be repeated for a number of cycles. The total and the
number of samples must be calculated for Columns 1-5 in the given table. If there
is a non-deleted number recorded in a column, it is counted as a sample. The lost
time can then be calculated from the given formulae [58] [64]:
L = I + 10 - 1/S (X1/n1 + X3/n3) …………..(5.1)
where I is the inter-green time as measured in the field.
75
Another method for calculating lost time is being advocated by TRRL [50], Huapu
Lu et.al [65] and other researchers as well. This method is described below.
Recording of traffic flow data is carried out at intersection. Now the saturation flow
at the signalized intersections and lost time can be calculated after recording the
vehicles crossing the intersection per unit time during the green time. To further
simplify the procedure, an interval of 6 seconds is taken as investigation interval [66].
Following method is used to calculate the saturation flow at signalized
intersection. The distribution pattern of vehicles passing by the intersection during
the green time is illustrated in Figure 5.6. Each column represents the average
number of vehicles in the interval (veh / 6 sec). Due to the starting delay, initially
the average of vehicles is less than that in the following ones, i.e., starting lost,
then vehicles continue to cross the intersection at a certain flow density [66].
When the green time ends, the average of vehicles is also lower, i.e., clearance
lost time. The saturation flow is defined as the average number of vehicles
crossing in the effective green time, that is, the green time excluding the starting
and clearance lost time [66].
76
Table 5.10: Saturation Flow and Lost Time Measurement Form (Akcelik
1993)[53]
Inter-green time measured in the survey is 5 sec
77
Figure 5.6: Observed Discharge Across Stop Line
Initial and final lost time can be calculated by comparing rectangles. From the fig
5.6
ed x ef = cd x ac
ed x Saturation flow rate = Time interval x Observed discharge
ed = (Time interval x Observed discharge)/
Saturation flow rate
ce (Initial Lost Time) = cd – ed …………(5.2)
ce (Initial Lost Time) = Time interval – ed
Similarly final lost time can be calculated by using following equation (refer to fig)
jl (Final Lost Time) = kl – kj
………….(5.3)
jl (Final Lost Time) = Time interval – kj
In this study, the above method is being followed to calculate lost time at
signalized intersections. For ease of observation during the vehicle discharge, the
time interval is kept as 10 sec. to elaborate further, lost time calculation at Awami
Markaz Intersection is given below;
78
AVERAGE CYCLE PROFILE AT AWAMI MARKAZ
21.5325.67
28.53 28.47 30.2 29.1327.27 26.13
0
5
10
15
20
25
30
35
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec 80 sec
GREEN TIME INTERVAL
NO
OF V
EH
Saturation flow rate Final lost timeInitial lost time
AVERAGE CYCLE PROFILE AT AWAMI MARKAZ
21.5325.67
28.53 28.47 30.2 29.1327.27 26.13
0
5
10
15
20
25
30
35
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec 80 sec
GREEN TIME INTERVAL
NO
OF V
EH
Saturation flow rate Final lost timeInitial lost time
Figure 5.7: Average Cycle Profile at Awami Markaz
ed x 27.16 (Sat. Flow/ 10 sec) = 21.53 (veh discharge = ac) x ( time = cd) 10
ed = 21.53 x 10 / 27.16
ed = 7.92 sec
or ce = 2.08 sec
Similarly:
kj x 27.16 = 26.13 x 10
kj = 26.13 x 10 / 27.16
kj = 9.62 sec
or jl = 0.38 sec
Lost time = ce + jl
= 2.08 + 0.38
= 2.46 sec
Similarly, lost time has been calculated on all selected intersections. Detail is
tabulated in table 5.12 and 5.13 for Shahra-e-Faisal and M.A. Jinnah Road,
respectively.
79
Table: 5.11 Summary of Lost Time Calculated on Each Approach at
Shahra-e-Faisal
Name of Approach Width (m) Saturation Flow
( PCU / hr)
Lost Time
Sec
A 1
A 2
A 3
A 4
A 5
A 6
A 7
A 8
A 9
A 10
A 11
A 12
A 13
11.6
16.0
13.1
12.7
12.0
12.0
12.0
9.0
6.4
12.0
6.4
10.06
12.0
8210
10463
8539
7481
8556
8021
7340
6170
5606
9366
4744
6929
8064
2.46
1.31
2.16
1.69
1.09
2.36
0.62
1.43
1.83
2.61
1.11
2.74
1.31
Table 5.12: Summary of Lost Time Calculated on Each Approach at M.A. Jinnah Road
Name of Approach
Width (m) Saturation Flow( PCU / hr)
Lost Time (Sec)
B 1
B 2
B 3
B 4
B 5
15.6
12.6
12.0
13.1
9.0
10210
8836
8085
8574
7856
3.59
4.88
3.37
3.65
6.56
80
CHAPTER 6 SATURATION FLOW AND LOST TIME ANALYSIS & DISCUSSION
OF RESULTS
6.1 General Saturation flow rate is the maximum rate of vehicular flow that can pass through a
given intersection approach, during green period. This is one of the important
parameters in capacity analysis of signalized intersections. Knowledge of
saturation flow is essential in signal design. Saturation flow depends upon number
of different parameters. This chapter primarily deals with field measurement of
saturation flow, estimation of PCU values and development of regression model
for saturation flow. This chapter also compares the test results with the earlier
studies and provides a sound reason if there is any variation of standard formulae
with the results reported in this report.
6.2 Saturation Flow and Approach Width Webster and Cobbe [1] gave a linear relationship between saturation flow and
approach width, provided that approach width is greater than 17 ft. (5.23m). In the
present study, it was observed during data collection that most of the vehicle
users are not driving as per lane distribution, so it was not possible to study
individual lane as is being studied in developing countries, such as the study of
Webster and Cobbe [1] in Great Britain and Miller[23] in Australia.
The approach widths studied in this research are ranging between 6.4m to
10.06m; so Regression Analysis was carried out for all approaches by using
MINITAB Program [67]. The object was to develop a relationship between
saturation flow and approach width. The result of regressing saturation flow on Y
axis and approach width on X-axis, the following equation was achieved for
Shahra-e-Faisal with a correlation coefficient of 0.85:
S = 1637 + 538 W …….. (6.1)
Where, W is approach width in meters.
81
Similarly, the regression analysis resulted following equation for M.A. Jinnah Road
with a correlation coefficient of 0.81:
S = 4314 + 350 W …….. (6.2)
The estimated saturation flows are compared with measured saturation flows and
are presented in graphical form, as shown in Figure 6.1 for Shahra-e-Faisal and in
Figure 6.2 for M.A. Jinnah Road.
6.3 Effect of Composition of Traffic The value of the saturation flow depends on the proportion of different types of
vehicles in a traffic stream, which is crossing a signalized intersection. To obtain a
value, which is independent of the composition of the traffic, the saturation flow
may be expressed in passenger car units (pcu) per green hour, rather than in
vehicles per green hour in order to avoid any error in estimation of saturation flow.
The following pcu equivalents as given by Webster and Cobbe [1] are quoted here
in this thesis
1 heavy commercial vehicle 1.75 pcu
1 bus 2.25 pcu
1 light commercial vehicle 1 .00 pcu
1 motorcycle 0.33 pcu
1 pedal cycle 0.20 pcu
82
Fig 6.1 Relationship between Observed Saturation Flow & Approach Width on Shahra-e-Faisal
S = 4314 + 350.79 W
R2 = 0.8123
5000
6000
7000
8000
9000
10000
11000
5 7 9 11 13 15 17
Width (m)
Sa
tura
tio
n F
low
(p
cu
/hr)
Fig 6.2 Relationship between Observed Saturation Flow and Approach Width on M.A. Jinnah Road
y = 5 3 8 .3 9 x + 16 3 7 .1
R 2 = 0 .8 5 7 7
0
2000
4000
6000
8000
10000
12000
6 8 10 12 14 16 18
Width ( m )
Sat
ura
tio
n F
low
P
CU
/ h
ou
r
83
It is reported in literature that there is a great variation in vehicle performance,
geometric condition, driver behavior, length and width of vehicles, composition of
traffic and surface characteristics of the road as the time changes, so pcu values
are different for each study. It is also seen that the pcu values do vary from area
to area, and from site to site. Hence, it is obvious from research point of view to
establish pcu before saturation flow is being measured for each study.
PCU values for our local area are based on observations which carried out in this
study. The traffic was classified as follows.
Car (C) Minibus (M)
Van (V) Bus/Truck (B)
Rickshaw (R) Motorcycle (m)
It should be noted that Minibus and Rickshaw are the only vehicles available in
the India-Pakistan subcontinent that is why no pcu value for such vehicles has
been determined by the researchers in other countries like U.K, Australia and
Hong Kong, etc.
Table 6.1 presents the summary of pcu values of present study along the both
arterial routes of Karachi.
Table 6.1: Summary of PCU Values along Both Arterials of Karachi
Veh Type PCU Value at
Shahra-e-Faisal
PCU Value at
M.A. Jinnah Road
Car
Minibus
Bus / Truck
Van
Rickshaw
Motorcycle
1.00
2.10
3.00
1.51
0.43
0.37
1.00
2.55
3.69
1.84
0.52
0.45
The detailed data analysis is provided in Appendices.
84
6.4 Comparison of Observed and Estimated Saturation Flow. The difference between the saturation flows estimated from Equations 6.1 and 6.2
and the observed saturation flows using pcu values as obtained in this study are
given in Tables 6.2 and 6.3 for Shahra-e-Faisal and M.A. Jinnah Road,
respectively and their graphical presentation is given in Figures 6.3 and 6.4.
85
Table 6.2 Comparison of Observed and Estimated Saturation Flow on Shahra-e-Faisal
Approach Approach width
( m ) Theoretical *
Saturation flow ( pcu / hr )
Observed Saturation Flow
( pcu / hr )
Difference %
A 1
A 2
A 3
A 4
A 5
A 6
A 7
A 8
A 9
A 10
A 11
A 12
A 13
11.6
16.0
13.1
12.7
12.0
12.0
12.0
9.0
6.4
12.0
6.4
10.06
12.0
7882
10251
8690
8474
8098
8098
8098
6482
5082
8098
5082
7053
8098
8210
10463
8539
7481
8556
8021
7340
6170
5606
8366
4744
6921
8064
+ 4.16 %
+ 2.06 %
- 1.73 %
- 11.71 %
+ 5.65 %
- 0.95 %
- 9.36 %
- 4.81 %
+ 10.31 %
+ 3.31 %
- 6.65 %
- 1.87 %
- 0.42 %
Theoretical values obtained from S = 1637 + 538 W
Table 6.3 Comparison of Observed and Estimated Saturation Flow on M.A. Jinnah Road
Approach Approach width
( m ) Theoretical *
Saturation flow ( pcu / hr )
Observed Saturation Flow
( pcu / hr )
Difference %
B 1
B 2
B 3
B 4
B 5
15.6
12.6
12.0
13.1
9.0
9774
8724
8514
8899
7464
10210
8836
8085
8574
7856
+ 4.46 %
+ 1.28 %
- 5.03 %
- 3.65 %
+ 5.25 %
Theoretical values obtained from S = 4314 + 350 W
86
Comparision of Observed Vs Theoretical Saturation Flow
0
2000
4000
6000
8000
10000
12000
0 2000 4000 6000 8000 10000 12000
Theoretical Saturation Flow
Ob
serv
ed s
atu
rati
on
Flo
w
Fig 6.3 Graphical Comparison of Observed Vs Theoretical Saturation Flow (Shahra-e-Faisal)
Comparision of Observed Vs Theoretical Saturation Flow
0
2000
4000
6000
8000
10000
12000
0 2000 4000 6000 8000 10000 12000
Theoretical Saturation Flow
Obs
erve
d sa
tura
tion
Flo
w
σest = 470
Fig 6.4 Graphical Comparison of Observed Vs Theoretical Saturation Flow on M.A. Jinnah Road
σest = 441
87
6.5 Comparison of Both Arterials of Present Study The models developed for both the arterials have been compared. This
comparison shows that results of two models differ up to 20% for approaches
having lesser width, but this difference reduces as the approach width increases
and it reduces to around 1% for approaches having width around 13m. The
results of this comparison have been presented in Table 6.4.
6.6 Generalize Model and Its Comparison In this research, two arterials have been studied. These arterials are entirely
different from each other. One arterial provides smooth traffic flow conditions with
lesser interference, less vehicle mix, less goods carrying vehicles and no animal
drawn vehicles. On the other hand, the other arterial had the congested traffic
conditions with mix vehicles, lot of interferences and disrupting traffic flow. Traffic
comprises of lot of passenger buses and goods vehicles (Trucks).
Traffic data have been collected along both the arterials. This data along both the
arterials has been incorporated to get the generalize model. Figure 6.5 presents
the relationship for generalized model.
This generalize model has been compared with the two models already
developed, i.e, The model developed for Shahra-e-Faisal (Faisal Model) and the
model developed for M.A. Jinnah Road (Jinnah Model). The comparison has
been presented in Table 6.5.
88
Table 6.4: Comparison between Two Models
Width (m) Shahra-e-Faisal M.A.Jinnah Road Difference %
6.4 5226.38 6559.12 20.32
6.4 5226.38 6559.12 20.329 6653.00 7471.20 10.95
10.06 7234.62 7843.05 7.76
11.6 8079.62 8383.28 3.6212 8299.10 8523.60 2.6312 8299.10 8523.60 2.6312 8299.10 8523.60 2.6312 8299.10 8523.60 2.6312 8299.10 8523.60 2.63
12.7 8683.19 8769.16 0.9813.1 8902.67 8909.48 0.0816 10493.90 9926.80 -5.71
S = 1995.5 + 516.14 W
R2 = 0.8355
0
2000
4000
6000
8000
10000
12000
0 2 4 6 8 10 12 14 16 18
Width (m)
Sat
ura
tio
n F
low
(p
cu h
r)
Fig 6.5 Generalized Relationship between Saturation Flow and Approach Width (Incorporating Both Approaches)
89
Table 6.5 Comparison of Generalized Model With Faisal and Jinnah Model
Width (m) Field Data Faisal Model Difference Jinnah Model Difference Generalized Model Difference6.4 5606 5082.76 -10.29 6559.12 14.53 5297.90 -5.826.4 4744 5082.76 6.66 6559.12 27.67 5297.90 10.469 6170 6482.60 4.82 7471.20 17.42 6639.50 7.079 7856 6482.60 -21.19 7471.20 -5.15 6639.50 -18.32
10.06 6929 7053.30 1.76 7843.05 11.65 7186.46 3.5811.6 8210 7882.44 -4.16 8383.28 2.07 7981.10 -2.8712 8556 8097.80 -5.66 8523.60 -0.38 8187.50 -4.5012 8021 8097.80 0.95 8523.60 5.90 8187.50 2.0312 7340 8097.80 9.36 8523.60 13.89 8187.50 10.3512 9366 8097.80 -15.66 8523.60 -9.88 8187.50 -14.3912 8064 8097.80 0.42 8523.60 5.39 8187.50 1.5112 8085 8097.80 0.16 8523.60 5.15 8187.50 1.25
12.6 8836 8420.84 -4.93 8734.08 -1.17 8497.10 -3.9912.7 7481 8474.68 11.73 8769.16 14.69 8548.70 12.4913.1 8539 8690.04 1.74 8909.48 4.16 8755.10 2.4713.1 8574 8690.04 1.34 8909.48 3.77 8755.10 2.0715.6 10210 10036.04 -1.73 9786.48 -4.33 10045.10 -1.6416 10463 10251.40 -2.06 9926.80 -5.40 10251.50 -2.06
Avg Differenc -1.49% Avg Difference 5.55% Avg Difference -0.02%
90
6.7 Comparison of Present Study with Earlier Studies
It is observed through literature that variation in intersection geometry, vehicle
size, traffic conditions, driver behavior and traffic regulations may give different
results in the determination of the intersection saturation flow in different countries
or cities, even if the same methodology is being used.
The comparison of the saturation flow, as predicted by generalized model
developed through the regression analysis which is based on the saturation flow
of both arterials in present study, with earlier studies is presented graphically in
Figure 6.6. This comparison is tabulated in Table 6.6.
Comparision of Models
0
2000
4000
6000
8000
10000
12000
5 7 9 11 13 15 17
Width (m)
Sa
tura
tio
n F
low
( p
cu
/hr)
Current Study (2007)
Webster andCobbe(1956)
Abu Rahmeh(1982)
M. Hussain(2001)
Ibrahim(2002)
Leong (2005)
Study (2008)
Comparision of Models
0
2000
4000
6000
8000
10000
12000
5 7 9 11 13 15 17
Width (m)
Sa
tura
tio
n F
low
( p
cu
/hr)
Current Study (2007)
Webster andCobbe(1956)
Abu Rahmeh(1982)
M. Hussain(2001)
Ibrahim(2002)
Leong (2005)
Study (2008)
Fig 6.6 Graphical Comparison of Present Study Model with Previous Models
91
Table 6.6 Comparison of Saturation Flows Predicted by Present Study Model with Earlier Studies
Width (m) Obs Current Difference Webster and Difference Abu Rahmeh Difference M. Hussain Difference Ibrahim Difference Leong Difference
Study (2008) % Cobbe(1966) % (1982) % (2001) % (2002) % (2005) %
6.4 5606 5083 10.29 3360 66.85 3040 84.41 4252 31.84 3356 67.04 3373.82 66.16
6.4 4744 5083 -6.66 3360 41.19 3040 56.05 4252 11.57 3356 41.36 3373.82 40.61
9 6170 6483 -4.82 4725 30.58 4275 44.33 5370 14.90 4305 43.32 4744.44 30.05
10.06 6929 7053 -1.76 5282 31.19 4779 45.00 5826 18.94 4692 47.68 5303.23 30.66
11.6 8210 7882 4.16 6090 34.81 5510 49.00 6488 26.54 5254 56.26 6115.06 34.2612 8556 8098 5.66 6300 35.81 5700 50.11 6660 28.47 5400 58.44 6325.92 35.2512 8021 8098 -0.95 6300 27.32 5700 40.72 6660 20.44 5400 48.54 6325.92 26.8012 7340 8098 -9.36 6300 16.51 5700 28.77 6660 10.21 5400 35.93 6325.92 16.0312 9366 8098 15.66 6300 48.67 5700 64.32 6660 40.63 5400 73.44 6325.92 48.0612 8064 8098 -0.42 6300 28.00 5700 41.47 6660 21.08 5400 49.33 6325.92 27.48
12.7 7481 8475 -11.73 6668 12.20 6033 24.01 6961 7.47 5656 32.28 6694.93 11.7413.1 8539 8690 -1.74 6878 24.16 6223 37.23 7133 19.71 5802 47.19 6905.80 23.65
16 10463 10251 2.06 8400 24.56 7600 37.67 8380 24.86 6860 52.52 8434.56 24.05Avg. Diff. -0.03 % Avg. Diff. 31.22 % Avg. Diff. 45.03 % Avg. Diff. 20.12 % Avg. Diff. 50.26 % Avg. Diff. 31.9 %
92
CHAPTER 7
CONCLUSIONS
7.1 General Altogether eighteen (18) signalized intersections have been studied. Thirteen (13) were on
Shahra-e-Faisal and five (5) were on M.A. Jinnah Road. Data has been analyzed through
the playing back of video tapes to achieve the objectives of the study as set in the start of
study. From the collected data, information regarding the vehicle headways (time headway)
has been ascertained and calculated individually for all types of vehicles. Using the
information from the collected data, PCU values for different types of vehicles have been
calculated.
Following conclusions can be drawn based on the experimental data and statistical analysis
of the collected data and developed empirical equation:
1. The PCU equivalents by Webster and Cobbe [1] for vans (commercial vehicles), bus,
light vehicles and motorcycles were 1.75, 2.25, 1.00 and 0.33, respectively. Whereas
present study reveals that equivalents on Shahra-e-Faisal are 1.51, 3.0, 1.00 and
0.37 respectively. This means for buses and motor cycles, the present study PCU on
Shahra-e-Faisal are slightly larger; where as for vans, the present study headway is
slightly smaller than the earlier work. In addition to this, the PCU equivalents are also
obtained for Rickshaw and Minibuses which are 0.43 and 2.1 respectively. The
comparison of ARRB’s PCU values at 95% confidence limits with this study showed
a significant difference. This may be due to the difference of traffic composition,
driver behavior and other environmental conditions.
2. Present study concludes that PCU equivalents for vans (commercial vehicles), bus,
light vehicles and motorcycles on M.A. Jinnah Road are 1.84, 3.69, 1.00 and 0.45,
respectively. Comparison of these values with values given by Webster and Cobbe[1]
shows that values obtained through this study are higher for all types of vehicles.
93
This is owing to the difference in type of vehicles, intersection geometry and
enforcement of law, etc.
3. As far as method for data collection is concerned, Camcorder was used for data
collection and it showed that this is the easiest method of recording the traffic data.
The video recorder permitted the abstraction of data for PCU equivalents as well as
for saturation flow. A built-in timer giving fraction of seconds was used to measure
time headways. The video recording is then transferred on a CD-ROM for further
analysis and presentation purposes. Video recorded data collection is much more
superior to manual data collection. It requires less manpower. It produces
permanent, complete record of the traffic scene; however data extraction is bit
tedious.
4. Relationship between saturation flow & approach width has been determined for
arterials having similar traffic conditions as on Shahra-e- Faisal:
S = 1637 + 538 W
Where, S = saturation flow in pcu/hour
W = width of approach in meters.
5. Relationship between saturation flow & approach width for arterials having mix traffic
as on M.A. Jinnah Road has been established as:
S = 4314 + 350.8 W
6. By comparing the data from both arterial routes, the following generalized equation
has been developed:
S = 1995.5 + 516 W
7. Comparison of the results of this study with earlier studies shows that the average
difference falls in the range of 20% to 50%. Reasons of such a big difference are
very obvious like type of vehicles, mix traffic, no lane discipline, non-compliance of
law by road users and lack of enforcement by concerned authorities, etc.
8. Many of the approaches found with increased saturation flow in first interval of 10
seconds as compared to other intervals showed significant difference of cycle profile
as obtained by various researchers in developed countries. This is because vehicle
users tend to form many lanes as much as they can without following the lane
94
discipline or lane marking. The cycle profile so obtained through the data collected in
this research, slightly different from the cycle profile given by other researchers.
9. HCM 2000 suggests measurement of saturation period after 10 second of green
period. 10 seconds are left considering starting delay which is called start up lost
time. In mixed traffic condition this start up lost time is not significant. In this study, it
is observed that auto rickshaws and two-wheeler find way in between heavy vehicles
and try to come near to stop line. Most of the times these vehicles cross stop line
before green starts. During red period large numbers of vehicles accumulate near
stop line. This scenario allows large amount of traffic to discharge during initial 10
seconds. Hence, it is proposed that count for measurement of saturation flow must
start after 10 seconds of green start.
10. Lost time at Shahra-e-Faisal is less as compare to the one calculated by researchers
in developed countries whereas it is more at M.A. Jinnah Road
11. Results of this study can be used as base for calculation of saturation flow values in
most areas of Pakistan (For the Intersections having similar traffic conditions).
12. Regression model was developed to estimate saturation flow and it showed good
correlation with observed values. This study presents estimation of saturation flow
for Shahra-e-Faisal and M.A. Jinnah Road, Karachi; further tuning based on
observed data is needed to establish reliable parameter estimates for general
application, especially for varying geometric, traffic and environmental conditions.
However, this model can be used to estimate saturation flow at any other
intersections having similar traffic and geometric characteristics.
7.2 Future Scope 1. The regression model developed for saturation flow is based on traffic conditions of
Karachi city. This model can be applied to other cities of Pakistan. This developed
model may be applied in those cities of Pakistan that have similar traffic
characteristics like Karachi.
2. Saturation flow depends on various factors. In the present study, being first effort in
95
the country to develop an equation for estimation of saturation flow based on the
local conditions, all intersections were selected having almost flat surface.
Saturation flow also gets affected by gradient, site conditions and vehicle parking
near intersections. Future researchers may take all these factors in to account to
develop a unique model considering maximum possible variables.
3. Effects of other factors affecting saturation flow can be incorporated after collection
of other related data. These factors may include turning vehicles (right turning/left
turning), area population, etc.
7.3 Recommendations /Suggestions
1. It is expected that the results of this study can be used as a baseline for further
research work of traffic system in Karachi as well as in other major cities of Pakistan
to update the derived relationship between saturation flow and approach width.
2. Saturation flow and whole approach width may provide a better relationship,
particularly in case in which lane discipline is not good.
3. More intersections that are located in thickly populated area and where there is more
interference of traffic and pedestrian is involved, be studied and present equation /
model be updated.
96
REFRENCES
1. Webster, F.V and Cobbe (1966),” Traffic Signals”, Road Research Technical Paper
No.56, HMSO, London.
2. HCM (Highway Capacity Manual) 4th Edition (2000). Transportation Research Board,
Washington D.C.
3. http://scholar.lib.vt.edu/theses/available/etd-04202000-12070029/unrestricted/
Chapter07.pdf
4. Leong,G.“A Unified Theory of Saturation Flow”, Paper presented at 85th Annual
Meeting in Jan 2006.
5. http://www.akcelik.com.au/HCMGlossary.htm
6. http://www.iowasudas.org/designs/ch13sec1.pdf
7.http://www.kfupm.edu.sa/ce/Lab_manual/Highway%20Capacity%20Analysis%20Lab%20
Manual.pdf
8. http://fultonecd.org/focusfulton/plan-01-06/8transp.pdf
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APPENDICES
107
Headways of Straight-Ahead Motorcycles
S.No Headways S.No Headways S.No Headways S.No Headways
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
0.24
0.56
0.76
0.20
0.15
0.32
0.36
0.48
0.44
0.28
0.15
0.88
0.52
0.44
0.24
0.15
0.36
0.42
0.52
0.56
0.64
0.15
0.24
0.24
0.42
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
0.48
0.36
0.92
1.04
0.24
0.28
0.36
0.32
0.52
0.56
0.72
0.76
0.88
1.20
0.76
0.44
0.36
0.32
0.72
0.64
0.24
0.44
0.44
0.76
0.82
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
1.24
0.32
0.24
0.15
0.22
0.42
0.52
0.56
0.56
0.72
0.24
0.24
0.32
0.46
0.44
0.52
0.64
0.28
0.24
0.32
0.44
0.52
0.56
0.56
0.64
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
0.72
0.76
0.84
0.20
0.24
0.20
0.44
0.52
0.56
0.64
0.24
0.20
0.48
0.56
0.24
0.20
0.76
0.64
0.20
0.24
0.56
0.64
0.24
0.64
0.44
APPENDIX 1
108
S.No Headways S.No Headways S.No Headways S.No Headways
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
0.44
0.22
0.15
0.56
0.72
0.24
0.88
0.52
0.40
0.24
0.15
0.36
0.42
0.52
0.56
0.64
0.15
1.24
0.32
0.24
0.15
0.22
0.24
0.44
0.64
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
0.84
1.20
0.76
0.84
0.20
0.24
0.20
0.48
0.36
0.32
0.72
0.64
0.24
0.44
0.64
0.28
0.24
0.32
0.42
0.24
0.20
0.76
0.88
0.24
0.32
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
0.24
0.32
0.48
0.52
0.56
0.24
0.20
0.48
0.56
0.44
0.28
0.15
0.88
0.56
0.64
0.72
0.76
0.88
0.28
0.36
0.32
0.52
1.20
0.24
0.56
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
0.72
0.76
0.88
1.20
0.20
0.76
0.64
0.20
0.24
0.56
0.64
0.24
0.64
0.44
1.24
0.32
0.24
0.64
0.24
0.44
0.15
0.56
0.72
0.24
0.32
109
Headways of Straight-Ahead Passenger Cars
S.No Headways S.No Headways S.No Headways S.No Headways
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
2.40
1.20
1.44
1.48
1.50
2.30
1.90
1.95
1.45
1.35
0.20
0.14
1.40
0.90
0.80
1.10
0.16
0.38
1.30
1.44
1.22
1.36
0.90
1.20
1.10
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
1.60
1.35.
1.20
1.25
1.33
1.25
1.63
1.10
1.00
0.95
1.05
1.13
1.45
1.40
1.40
1.20
1.45
1.25
1.55
1.61
1.25
1.20
1.46
1.20
1.45
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
0.95
1.55
1.65
1.15
1.10
1.45
1.40
1.05
1.35
1.15
1.65
1.45
1.55
1.50
1.35
1.25
1.45
1.35
1.15
1.50
1.35
1.45
0.80
1.45
1.35
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
1.10
0.95
1.25
1.00
1.35
0.75
1.20
1.35
1.25
1.33
1.20
1.45
0.85
0.95
1.25
0.65
1.25
1.05
1.25
0.93
1.00
1.55
1.15
0.92
1.15
APPENDIX 2
110
S.No Headways S.No Headways S.No Headways S.No Headways
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
1.15
0.93
1.15
1.25
1.60
1.20
1.58
1.30
1.05
1.85
1.15
1.58
1.13
1.00
1.10
0.95
1.05
1.25
1.40
1.35
1.05
1.20
0,85
1.10
0.95
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
0.45
0.95
1.20
1.58
1.25
1.10
0.95
1.15
1.40
0.75
1.45
1.25
1.33
1.45
1.25
1.18
1.43
1.25
1.20
0.90
1.05
0.95
1.00
1.25
1.30
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
1.25
0.95
1.25
0.60
1.35
1.15
1.25
1.20
1.35
1.15
1.35
1.33
1.35
1.30
1.35
1.55
1.35
1.45
1.54
0.90
1.33
1.55
1.63
1.55
1.30
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
1.35
1.40
1.50
1.55
1.40
1.60
1.68
1.45
1.35
1.43
1.10
1.25
1.35
1.05
0.95
0.80
1.10
1.05
1.50
1.13
1.20
1.50
1.10
1.00
0.85
111
S.No Headways S.No Headways S.No Headways S.No Headways
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
2.40
1.20
1.44
1.48
1.50
0.90
0.80
1.10
0.16
0.38
1.30
1.44
1.22
1.36
0.90
1.20
1.10
1.15
1.25
1.20
1.10
0.95
1.15
1.40
0.75
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
1.60
1.35
1.00
0.95
1.05
1.13
1.45
1.40
1.40
1.20
1.45
1.25
1.55
1.61
1.25
1.20
1.46
1.20
1.45
1.25
1.33
1.45
1.25
1.10
1.00
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
1.43
1.25
1.20
0.90
1.65
1.45
1.55
1.50
1.35
1.25
1.45
1.35
1.15
1.50
1.35
1.43
1.10
1.35
1.45
0.80
1.45
1.54
0.90
1.33
1.35
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
1.10
1.25
0.93
1.00
1.15
1.10
1.45
1.40
1.05
1.55
1.15
0.92
1.15
1.45
1.25
1.33
1.25
1.60
1.20
1.50
1.13
1.20
1.15
1.35
1.33
112
Headways of Straight-Ahead Rickshaws
S.No Headways S.No Headways
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
0.24
0.32
0.52
0.6
0.36
0.32
0.24
0.48
0.40
0.32
0.84
1.12
0.72
0.24
0.36
0.40
0.6
0.64
0.24
0.84
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
0.72
0.88
0.40
0.36
0.32
0.24
0.64
0.72
0.88
0.92
0.40
0.36
0.32
0.52
0.72
0.84
0.92
0.64
0.32
0.24
APPENDIX 3
113
S.No Headways S.No Headways
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
0.24
0.48
0.40
0.32
0.84
1.12
0.72
0.88
0.40
0.24
0.32
0.24
0.36
0.32
0.32
0.52
0.60
0.36
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
0.36
0.40
0.60
0.64
0.24
0.84
0.92
0.64
0.72
0.36
0.72
0.84
0.32
0.24
0.64
0.72
0.88
0.24
114
59
60
0.32
0.92
79
80
0.40
0.52
Headways of Straight-Ahead Vans
APPENDIX 4
115
S.No Headways S.No Headways
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
3.0
1.86
2.00
2.20
2.90
2.20
2.44
1.90
2.20
2.20
2.10
2.16
2.30
2.34
3.28
2.96
2.48
1.96
2.65
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
3.12
3.08
2.12
2.96
2.36
2.24
2.00
1.60
2.24
2.32
2.40
2.40
2.56
2.20
1.80
2.96
2.60
2.72
2.56
S.No Headways S.No Headways
116
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
2.44
2.92
2.88
1.86
2.00
2.20
2.90
2.56
3.00
3.10
2.10
1.96
3.08
2.12
2.96
1.96
2.10
2.00
2.82
2.20
2.34
60
61
62
63
64
65
66
67
68
69
70
2.20
2.10
2.16
2.30
2.30
2.34
3.28
2.56
2.20
1.80
2.60
Headways of Straight-Ahead Mini-Buses
APPENDIX 5
117
S.No Headways S.No Headways
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
3.24
1.96
2.32
2.36
2.16
3.24
2.44
2.80
1.84
2.24
2.44
2.92
2.16
2.16
2.80
2.24
2.44
2.36
2.44
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
3.00
3.24
3.24
2.92
2.48
1.96
3.24
3.20
3.08
2.40
3.28
2.44
2.00
1.84
2.28
2.48
2.40
2.92
2.56
118
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
2.32
1.92
3.04
2.60
2.76
2.60
2.88
3.12
3.08
2.56
3.12
3.20
2.92
2.48
3.00
3.24
3.20
2.80
1.84
2.24
2.44
2.92
61
62
63
64
65
66
67
68
69
70
3.28
2.44
2.00
1.84
2.32
2.36
2.16
2.48
2.40
2.92
APPENDIX 6
119
Headways of Straight-Ahead Buses / Trucks
S.No Headways S.No Headways
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
3.28
4.56
3.36
3.20
4.04
3.64
3.96
3.64
4.04
3.96
3.24
4.40
3.36
3.20
4.00
3.24
3.20
3.60
4.04
3.40
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
3.20
3.80
3.64
3.96
3.60
4.04
4.00
3.24
3.20
4.00
3.60
3.40
3.36
3.24
3.28
3.96
3.32
4.00
4.20
3.40
120
SAMPLE SHEET FOR TRAFFIC FLOW DATA COLLECTION
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B123456789
1011121314151617181920
To
tal
Su
m60 sec 70 sec 80 sec 10 sec 20 sec 50 sec C
ycle No. of Vehicles per (10 sec) Interval
30 sec 40 sec
LEGEND
m = Motor Cycle V = Van C = Car M = Minibus R = Rickshaw B = Bus / Truck
APPENDIX 7
121
Site Awami Markaz
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 8
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B1 4 10 0 1 1 1 10 11 0 1 1 1 13 11 0 1 2 0 11 15 2 2 0 0 17 13 1 1 0 0 14 12 0 2 2 0 10 11 1 2 2 0 9 10 0 0 2 02 5 10 1 1 1 0 9 12 1 2 2 1 20 12 0 1 1 0 12 11 1 1 2 0 12 14 1 1 2 0 10 13 1 1 1 0 10 12 0 2 1 0 11 12 0 2 1 03 10 8 1 2 1 0 8 14 1 2 2 1 19 11 1 2 2 1 13 10 0 2 1 0 11 15 1 3 1 0 7 13 1 2 2 0 9 11 1 2 2 1 10 11 0 2 2 04 6 12 0 2 2 0 11 9 0 2 1 1 13 12 1 2 2 0 9 12 1 2 2 0 14 13 0 2 2 0 10 12 1 1 3 0 10 14 1 2 2 0 9 13 1 1 2 05 5 11 0 1 1 0 10 8 1 1 2 1 11 13 0 1 2 1 12 13 0 3 2 1 12 15 1 3 2 0 12 14 0 2 2 1 9 12 0 2 3 0 10 11 0 2 1 16 7 11 1 2 2 0 11 12 0 3 1 0 14 10 1 2 2 1 12 11 1 2 1 0 13 12 0 2 2 1 11 15 1 2 1 1 10 14 1 1 2 1 10 11 1 2 2 07 6 10 1 2 1 0 10 13 1 1 0 1 12 10 0 1 2 0 10 11 1 2 3 0 11 12 1 2 2 0 10 14 0 1 2 1 9 15 1 2 2 1 10 12 0 1 1 18 11 9 0 2 3 1 12 11 0 2 1 0 10 13 2 2 1 0 9 10 2 2 2 2 13 12 1 3 1 1 11 16 0 2 2 1 9 12 0 2 2 0 12 11 1 1 2 19 9 8 0 1 1 1 9 10 1 2 2 0 9 12 1 2 3 0 12 11 0 3 2 1 15 12 1 2 1 1 10 15 1 2 2 0 11 13 0 1 2 1 11 13 1 2 2 1
10 8 10 1 1 2 0 11 12 0 1 1 1 11 11 0 0 2 1 11 12 1 2 2 0 13 11 0 3 2 0 9 16 1 2 1 0 12 12 1 2 1 0 12 10 1 2 2 111 8 11 1 1 2 0 10 13 1 2 2 0 15 12 0 1 1 0 10 14 1 3 1 0 13 12 1 2 2 0 11 17 1 2 2 1 9 13 1 2 2 0 10 13 0 2 2 012 7 12 1 1 1 1 9 12 0 0 1 2 12 11 1 2 2 0 12 16 0 3 3 0 12 11 1 3 1 0 8 13 1 2 2 1 10 15 1 3 2 0 11 10 1 3 2 013 10 10 0 2 2 1 10 11 1 0 1 1 14 10 0 2 3 1 11 13 1 1 2 2 14 13 0 1 2 1 11 15 0 1 3 0 9 16 1 3 2 0 12 11 1 1 2 214 4 9 0 2 2 1 13 12 1 2 2 0 11 9 1 1 0 1 12 11 1 2 1 1 15 12 1 1 3 0 12 11 1 1 2 1 8 11 0 2 3 0 9 12 0 1 2 015 10 9 1 2 4 0 12 9 0 1 2 0 13 12 0 2 1 0 11 12 0 2 2 1 11 14 1 2 2 0 10 13 1 2 3 0 7 12 1 1 2 1 10 11 1 2 1 0
To
tal
110 150 8 23 26 6 155 169 8 22 21 10 197 169 8 22 26 6 167 182 12 32 26 8 196 191 11 31 25 4 156 209 10 25 30 7 142 193 10 29 30 5 156 171 8 24 26 7
Su
m
60 sec 70 sec 80 sec 10 sec 20 sec 50 sec Cyc
le No. of Vehicles per (10 sec) Interval30 sec 40 sec
409323 385 428 392427 458 437
122
Site DRIG ROAD INTERSECTION
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 9
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B1 14 10 0 0 0 0 12 13 2 1 3 0 13 14 2 1 2 1 10 12 2 0 1 1 11 8 1 0 1 1 12 9 2 1 0 0 6 8 1 1 1 02 12 8 0 2 3 0 9 9 0 2 3 1 11 11 2 1 1 0 11 10 1 1 2 1 12 10 1 2 1 2 12 10 1 2 0 0 10 9 2 0 0 03 15 9 0 1 2 1 10 12 2 0 3 1 12 15 0 0 4 1 14 9 1 0 1 1 16 9 3 0 1 0 14 8 3 0 1 0 14 6 2 1 1 14 13 10 0 3 2 0 8 13 1 0 2 0 16 8 1 1 4 0 19 10 2 0 0 2 15 10 2 1 1 1 13 11 1 1 0 0 15 8 0 0 0 05 16 7 0 0 2 0 14 10 0 1 4 0 10 12 1 3 0 1 10 11 2 1 2 1 12 11 2 0 3 0 8 8 0 0 3 0 9 7 1 0 3 16 15 8 1 1 2 0 8 11 1 1 2 1 12 11 0 2 3 0 15 9 1 1 1 1 13 12 1 1 3 1 12 9 1 1 3 0 11 12 1 1 3 07 10 8 0 1 2 1 10 12 1 2 0 0 10 13 2 2 2 1 10 12 1 1 2 2 11 7 1 0 2 1 11 10 1 0 2 1 9 7 1 0 2 18 16 7 1 0 2 0 10 12 2 1 3 0 12 9 0 1 1 0 13 13 0 0 0 1 14 10 0 1 3 0 10 8 0 1 3 0 9 9 1 0 3 09 12 10 0 1 1 0 10 13 1 1 0 1 14 8 1 2 4 1 11 14 1 0 2 0 12 11 2 0 0 0 12 9 2 0 0 0 8 9 2 1 0 0
10 14 9 1 0 2 1 8 11 3 2 1 1 13 10 0 2 1 0 12 11 2 2 0 0 11 8 1 1 0 2 11 7 0 1 0 0 10 5 0 0 0 011 12 6 0 0 1 0 11 13 0 2 0 0 12 9 1 1 2 1 14 10 1 0 2 0 15 9 1 0 1 0 15 7 1 0 1 0 8 12 0 0 1 112 10 10 1 1 1 0 9 10 1 1 1 1 11 8 1 1 1 1 10 11 2 1 1 1 17 10 2 2 2 0 18 10 2 2 2 0 20 8 1 2 2 013 14 9 1 0 1 1 12 8 0 2 1 0 9 11 0 1 3 0 14 12 2 1 2 0 12 5 1 0 2 1 12 5 1 0 2 0 5 5 1 0 2 114 10 9 0 1 3 0 14 10 1 1 2 1 16 12 2 0 1 0 10 12 0 0 3 0 10 11 2 2 1 0 10 11 2 2 1 0 9 11 0 1 1 015 11 9 0 0 2 0 6 12 0 0 1 0 12 10 0 1 0 1 12 11 0 0 1 2 11 10 1 0 1 1 11 10 0 0 0 0 9 7 1 0 0 0
To
tal
194 129 5 11 26 4 151 169 15 17 26 7 183 161 13 19 29 8 185 167 18 8 20 13 192 141 21 10 22 10 181 132 17 11 18 1 152 123 14 7 19 5
Su
m
411 396 360 320369 385 413
Cyc
le
10 sec 20 sec
No. of Vehicles per (10 sec) Interval30 sec 40 sec 60 sec 70 sec 50 sec
123
Site Karsaz Intersection
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 10
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B1 9 15 1 1 0 0 14 15 1 1 0 1 10 11 1 0 1 0 6 11 1 0 1 1 9 18 0 0 1 0 6 16 2 0 2 0 10 11 2 0 1 02 19 14 0 1 1 0 16 14 1 0 2 0 9 18 0 1 1 0 6 19 0 1 2 0 11 13 3 0 1 1 6 9 0 1 1 0 9 12 0 1 0 03 14 16 1 0 2 0 10 15 0 1 2 1 11 17 3 0 1 1 9 16 0 1 0 1 8 17 1 0 2 1 8 14 3 1 3 1 8 5 2 0 2 14 20 17 0 2 3 1 18 13 3 1 2 0 18 16 0 3 1 0 7 15 0 1 1 2 6 13 0 1 1 0 10 12 0 1 2 1 9 12 1 1 1 15 14 15 1 1 1 0 12 13 2 0 1 0 20 15 1 0 1 1 14 12 2 1 2 0 4 12 1 1 0 1 5 12 1 2 0 1 7 9 1 0 1 06 16 18 0 1 2 0 13 14 3 0 2 1 12 14 2 0 1 0 10 12 2 1 1 0 9 11 1 0 1 0 4 8 0 1 1 2 8 7 0 2 1 07 16 11 1 0 1 0 8 10 0 1 1 1 6 14 0 1 1 0 5 11 0 1 1 0 3 9 2 0 1 0 6 8 0 1 1 0 6 8 0 1 0 18 18 11 2 0 1 0 10 15 1 0 2 0 13 15 0 1 2 0 7 16 0 0 1 1 7 14 0 2 1 0 8 11 1 0 1 1 9 9 1 1 0 09 21 15 0 1 1 1 13 14 2 1 1 0 7 10 0 1 1 0 5 9 0 1 1 0 5 8 0 0 0 1 6 3 0 1 1 0 5 6 0 0 1 0
10 18 16 0 1 0 1 13 17 0 1 1 0 9 12 1 1 0 0 9 14 1 1 0 0 3 10 1 0 1 0 7 4 0 1 0 1 4 7 1 0 1 011 15 11 1 0 1 0 20 13 0 0 1 0 11 14 1 1 0 0 12 16 0 1 1 0 9 12 1 0 3 0 5 7 0 1 1 1 7 10 0 1 0 012 20 14 1 0 1 0 19 10 0 0 1 0 18 16 2 0 1 0 3 12 1 0 2 1 4 5 0 0 1 0 6 4 0 0 1 0 8 5 1 2 0 113 22 12 0 0 2 0 18 16 3 1 1 0 13 14 1 1 0 0 8 17 1 0 1 0 6 11 3 0 2 0 5 9 0 1 1 0 9 10 2 1 1 014 19 11 2 0 1 1 14 9 2 0 3 0 21 11 2 1 1 0 10 15 1 0 2 0 9 12 0 1 4 0 7 17 0 1 0 1 5 9 0 1 2 015 20 12 1 0 1 0 17 11 1 0 1 0 12 14 1 1 2 0 10 16 0 1 1 0 10 18 0 1 1 0 6 10 1 0 1 0 6 8 1 0 1 016 23 13 0 1 1 0 16 17 2 0 1 0 13 17 0 1 2 0 11 17 2 0 1 0 8 16 1 0 1 0 10 12 2 0 1 0 5 9 0 0 1 0
To
tal
284 221 11 9 19 4 231 216 21 7 22 4 203 228 15 13 16 2 132 228 11 10 18 6 111 199 14 6 21 4 105 156 10 12 17 9 115 137 12 11 13 4
Su
mC
ycle
10 sec 20 sec
No. of Vehicles per (10 sec) Interval30 sec 40 sec 60 sec 70 sec 50 sec
292548 501 477 309405 355
124
Site Mehran Hotel Intersection
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 11
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B1 8 17 2 0 1 0 12 14 1 1 0 0 11 12 1 0 0 0 6 12 1 0 0 1 7 18 0 0 1 0 4 17 2 0 0 0 15 17 2 0 0 02 21 12 1 0 1 0 15 16 1 0 0 0 9 20 0 0 0 0 4 19 0 0 0 0 11 13 5 0 0 0 2 5 0 0 0 0 6 9 0 0 0 03 10 16 1 0 0 0 6 15 0 0 1 0 9 17 3 0 0 0 4 16 0 0 0 1 2 14 1 0 0 0 4 14 5 0 1 0 1 5 2 0 0 04 25 15 0 0 0 0 18 13 3 0 1 0 20 16 0 0 1 0 4 15 0 0 0 1 1 15 0 0 0 0 5 14 2 0 0 0 13 10 1 0 0 05 9 12 1 0 0 0 8 11 2 0 1 0 20 13 1 0 1 0 13 12 2 0 0 0 0 11 1 0 0 0 3 9 0 0 0 0 4 6 1 0 1 06 16 18 0 0 0 0 10 15 4 0 0 0 10 9 2 0 1 0 10 12 2 0 0 0 0 11 1 0 1 0 0 6 0 0 0 0 1 2 0 0 0 07 6 12 1 0 0 0 5 8 0 0 0 0 1 14 0 0 0 0 1 11 0 1 0 0 1 5 2 0 1 0 3 2 0 0 0 0 14 4 0 1 0 08 18 11 2 0 1 0 11 15 3 0 1 0 13 15 2 0 2 0 6 16 2 0 0 0 1 14 0 2 1 0 3 12 1 0 0 0 0 1 0 0 0 09 15 12 0 0 1 0 10 14 3 0 1 0 3 10 0 0 0 0 1 1 0 0 0 0 1 2 0 0 0 0 6 1 0 0 0 0 8 7 0 0 2 0
10 13 14 0 0 0 0 13 18 0 0 0 0 0 12 1 1 0 0 8 16 1 1 0 0 1 11 1 0 1 0 7 7 0 0 0 0 6 5 1 0 0 011 16 10 1 0 1 0 23 13 0 0 1 0 8 14 1 1 0 0 7 16 0 0 0 0 6 15 1 0 3 0 3 5 0 0 0 0 4 4 0 0 0 012 20 12 3 0 1 0 19 10 0 0 1 0 21 16 2 0 1 0 2 13 3 0 3 0 1 7 0 0 1 0 4 4 0 0 1 0 8 5 0 0 0 013 18 11 0 0 2 0 18 16 3 0 0 0 13 14 1 1 0 0 2 19 1 0 0 0 2 8 3 0 2 0 2 5 2 0 0 0 0 10 2 0 0 014 18 8 2 0 0 0 14 7 2 0 3 0 21 11 4 0 0 0 10 15 1 0 0 0 2 10 0 1 4 0 1 17 0 0 0 0 3 10 0 0 0 015 18 11 1 0 1 0 14 10 1 0 1 0 7 14 1 1 2 0 5 16 0 0 1 0 3 20 0 0 0 0 6 10 1 0 1 0 5 7 0 0 1 016 23 13 0 0 0 0 16 17 2 0 0 0 13 17 0 0 2 0 10 16 2 0 1 0 6 16 1 0 1 0 10 12 2 0 1 0 5 11 0 0 1 0
To
tal
254 204 15 0 9 0 212 212 25 1 11 0 179 224 19 4 10 0 93 225 15 2 5 3 45 190 16 3 16 0 63 140 15 0 4 0 93 113 9 1 5 0
Su
m
343 270 221482 461 436 222
Cyc
le
10 sec 20 sec
No. of Vehicles per (10 sec) Interval30 sec 40 sec 60 sec 70 sec 50 sec
125
Site: Regent Plaza Intersection
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 12
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B1 7 15 2 0 1 0 12 15 1 1 0 1 13 14 1 0 0 1 9 14 1 0 1 1 14 15 0 1 2 0 12 17 2 0 1 0 12 15 2 0 1 02 15 12 1 1 1 0 15 16 1 0 0 0 11 17 0 0 1 0 12 17 0 1 1 0 15 16 5 0 1 0 11 12 0 1 0 1 13 11 0 1 0 03 10 12 1 0 0 1 11 14 0 0 1 0 10 14 3 0 1 0 11 15 0 1 0 1 12 14 1 0 1 0 13 14 5 0 1 0 8 10 2 0 1 14 18 14 0 0 1 0 18 19 3 0 1 0 16 15 0 0 1 0 12 14 0 1 1 1 11 16 0 1 1 0 10 14 2 1 1 0 12 10 1 1 0 05 9 11 1 0 0 0 12 11 2 0 1 0 18 13 1 0 1 0 13 12 2 2 1 0 13 14 1 0 1 0 16 10 0 1 0 1 9 8 1 0 1 06 12 15 0 0 1 1 10 15 4 1 0 0 10 10 2 0 1 0 10 12 2 0 1 0 6 11 1 0 1 0 7 9 0 2 2 0 11 5 0 1 0 07 6 12 1 0 0 0 9 12 0 2 1 0 9 14 0 1 1 0 11 12 0 1 1 1 13 8 2 0 1 0 11 12 0 1 2 0 8 11 0 1 0 08 12 11 2 0 1 0 11 15 3 1 1 0 13 15 2 0 2 0 9 16 2 0 1 0 10 14 0 2 1 0 9 12 1 0 1 0 6 12 1 1 0 19 11 12 0 0 1 0 12 14 3 0 1 0 7 10 0 1 0 1 11 12 0 2 0 1 11 12 0 2 0 1 13 9 0 2 2 0 12 7 0 0 2 0
10 13 12 0 1 1 0 13 18 0 1 0 0 6 12 1 1 0 0 9 16 1 1 0 0 8 11 1 0 1 0 12 7 0 2 1 0 9 5 1 0 0 111 16 10 1 0 1 0 20 13 0 0 1 0 11 14 1 1 0 0 11 16 0 1 0 1 11 12 1 0 3 0 7 5 0 1 2 0 12 10 0 1 0 112 17 12 3 0 1 0 16 10 0 0 1 0 20 15 2 0 1 0 9 13 3 0 3 0 6 9 0 0 1 0 6 12 0 0 1 0 8 14 0 1 1 013 18 11 0 0 2 0 18 16 3 1 0 0 13 15 1 1 0 1 7 19 1 0 1 0 11 11 3 0 2 0 7 9 2 0 1 0 3 10 2 0 1 014 17 8 2 0 0 1 12 9 2 0 3 0 17 13 4 0 1 0 10 15 1 2 0 0 9 12 0 1 4 0 10 16 0 0 0 1 13 8 0 1 0 015 18 11 1 0 1 0 14 10 1 0 1 0 7 14 1 1 2 0 9 16 0 0 1 0 10 19 0 0 1 0 8 10 1 0 1 0 14 7 0 0 1 0
To
tal
199 178 15 2 12 3 203 207 23 7 12 1 181 205 19 6 12 3 153 219 13 12 12 6 160 194 15 7 21 1 152 168 13 11 16 3 150 143 10 8 8 4
Su
mC
ycle
10 sec 20 sec
No. of Vehicles per (10 sec) Interval30 sec 40 sec 60 sec 70 sec 50 sec
323409 453 426 363415 398
126
Site: Shah Faisal Colony
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B1 14 10 1 2 1 1 16 12 2 1 2 0 16 14 1 2 4 1 12 11 2 2 1 2 16 10 1 1 1 12 10 11 2 2 2 1 11 14 1 3 3 1 14 12 1 3 3 1 14 13 1 1 2 0 12 12 0 2 1 03 11 9 9 1 2 0 12 12 3 1 4 0 13 14 2 1 3 0 16 14 0 2 3 0 14 11 0 1 3 04 16 10 2 1 3 0 16 11 2 2 3 0 12 12 1 1 2 1 18 10 1 2 1 2 12 13 1 1 1 15 11 14 1 2 1 1 18 15 1 1 4 4 15 14 2 2 5 0 14 11 2 1 4 0 12 12 0 1 4 06 12 8 1 2 1 2 10 11 2 2 2 1 12 14 1 1 3 1 13 14 1 2 1 1 14 12 1 2 1 17 10 9 2 1 2 2 15 12 1 2 1 1 16 12 3 2 2 1 12 10 0 1 2 1 14 10 0 1 2 18 14 13 1 2 1 0 14 10 2 2 2 0 16 13 1 3 2 0 14 12 1 1 1 1 12 9 1 1 1 19 12 8 2 2 2 0 12 12 0 2 1 1 13 12 0 1 1 1 12 11 2 2 2 0 12 8 0 2 2 0
10 11 12 1 1 2 1 18 14 2 1 2 1 12 15 1 2 2 1 13 10 1 1 2 0 13 11 1 1 2 011 10 11 2 1 1 0 13 11 1 1 2 1 15 13 2 1 2 1 10 13 1 1 2 0 10 19 1 1 2 012 11 14 1 2 2 0 15 13 0 2 1 0 14 12 1 2 2 0 11 11 0 2 1 1 12 10 0 2 1 1
To
tal
142 129 25 19 20 8 170 147 17 20 27 10 168 157 16 21 31 8 159 140 12 18 22 8 153 137 6 16 21 6
Su
m
339
20 sec 50 sec
359343 391 401
10 sec Cyc
le No. of Vehicles per (10 sec) Interval30 sec 40 sec
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 13
127
Site: Star Gate
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 14
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B1 11 10 1 1 4 0 12 11 2 1 2 0 13 11 1 1 2 0 16 6 2 0 1 0 12 8 2 2 1 0 10 8 2 2 2 0 9 10 0 0 3 0 10 11 2 1 3 02 11 8 2 2 3 0 10 12 1 0 3 0 17 11 0 0 3 0 15 9 0 0 1 1 10 8 0 0 3 0 9 7 0 1 2 0 9 11 2 1 2 1 11 10 1 0 2 03 9 9 1 0 4 0 9 11 0 1 3 0 11 9 1 1 2 1 12 9 1 1 3 0 9 10 2 3 0 0 14 9 1 0 0 0 10 9 0 1 0 0 9 8 0 1 1 04 9 8 0 1 4 1 10 9 0 0 3 0 10 10 1 1 3 0 11 10 2 0 0 2 12 8 0 1 4 1 12 7 2 1 2 0 8 7 1 1 2 0 12 6 1 0 3 15 11 10 1 0 3 0 8 11 0 0 3 1 9 11 0 1 2 0 15 6 1 1 0 1 8 9 1 1 1 1 10 9 0 0 3 0 10 7 1 0 0 1 9 8 2 0 3 16 8 5 0 0 1 1 10 9 0 1 3 0 12 7 1 4 1 2 13 10 0 0 3 0 10 11 1 1 2 1 8 8 1 1 2 0 12 7 1 1 2 0 10 6 0 2 2 07 9 10 1 2 3 1 11 9 1 2 1 1 8 10 2 2 2 1 15 9 1 1 1 1 9 10 1 2 3 0 11 10 1 2 2 0 9 7 2 1 1 0 8 9 1 1 2 08 10 9 1 1 2 0 9 10 1 1 4 2 10 12 0 1 4 0 19 5 0 1 4 2 11 8 0 4 1 1 9 8 0 1 3 0 11 9 1 1 0 1 9 6 0 1 3 09 12 7 1 1 1 1 8 9 1 1 2 1 9 12 1 2 2 0 18 10 1 1 1 1 10 9 2 1 1 0 8 11 1 1 3 1 9 7 1 2 2 0 7 10 1 2 2 1
10 10 9 0 1 2 0 11 8 1 1 3 0 10 6 1 1 2 0 18 9 0 1 1 0 11 8 1 3 1 1 12 8 1 1 1 2 9 10 0 3 2 0 6 6 0 1 3 011 9 10 2 2 3 0 8 11 0 1 6 1 10 8 1 2 2 2 12 8 2 1 4 0 7 9 0 2 1 0 9 10 0 1 1 0 10 9 1 2 2 1 8 9 0 0 2 112 8 6 1 2 2 1 10 14 0 0 0 1 9 10 1 1 2 0 18 8 0 0 2 0 9 10 1 1 1 1 10 9 1 2 0 2 8 10 1 2 3 1 8 6 0 1 2 1
To
tal
117 101 11 13 32 5 116 124 7 9 33 7 128 117 10 17 27 6 182 99 10 7 21 8 118 108 11 21 19 6 122 104 10 13 21 5 114 103 11 15 19 5 107 95 8 10 28 5
Su
m
50 sec Cyc
le
10 sec 20 sec
No. of Vehicles per (10 sec) Interval30 sec 40 sec
267279 296 305
60 sec 70 sec 80 sec
253327 283 275
128
Site: TARIQ ROAD
m C R V M B m C R V M B m C R V M B m C R V M B1 12 6 0 0 1 0 20 15 1 1 1 0 14 17 0 0 2 1 10 19 2 1 1 02 16 7 1 1 1 0 12 17 0 2 2 0 13 15 1 1 0 1 8 16 1 2 2 13 15 8 1 2 0 1 14 13 1 1 2 1 10 12 1 1 2 0 12 14 0 0 1 14 14 6 1 1 2 0 15 12 1 1 2 0 16 11 0 2 2 0 9 10 0 1 1 15 11 9 0 2 1 0 12 13 0 2 1 1 15 10 0 1 1 1 8 11 1 2 0 06 20 16 0 0 2 0 4 19 1 0 1 0 8 12 1 2 3 1 4 5 3 0 1 17 14 12 0 1 1 0 14 15 1 1 2 0 12 10 0 2 2 1 6 8 1 1 2 08 10 9 0 1 2 1 13 12 0 1 2 1 11 10 1 2 2 0 8 10 0 2 1 09 11 11 1 1 1 0 14 12 1 2 1 0 14 12 0 1 2 0 9 11 1 1 1 0
10 14 11 0 2 2 0 18 15 0 1 2 0 13 14 1 0 2 1 10 9 0 2 1 011 12 8 1 1 2 0 14 15 1 0 2 1 11 11 0 2 2 0 9 13 0 1 1 112 12 5 0 2 1 0 12 15 1 1 2 0 9 13 0 1 1 1 7 7 0 2 1 0
To
tal
161 108 5 14 16 2 162 173 8 13 20 4 146 147 5 15 21 7 100 133 9 15 13 5
Su
mC
ycle No. of Vehicles per (10 sec) Interval30 sec 40 sec
306 380 341
10 sec 20 sec
275
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 15
129
Site: KASHIF CENTRE
Cyc
le No. of Vehicles per (10 sec) Interval
10 sec 20 sec 30 sec 40 sec
m C R V M B m C R V M B m C R V M B m C R V M B1 10 8 1 0 1 0 13 12 1 2 1 0 9 10 0 1 1 1 7 10 2 1 1 02 9 6 1 1 1 0 9 10 0 1 0 0 8 11 1 1 0 0 8 8 1 2 2 13 8 7 0 1 1 1 10 8 1 1 2 1 10 10 1 2 1 0 9 8 0 1 2 04 8 3 1 2 1 0 10 9 1 2 1 0 8 6 0 1 2 0 7 7 0 2 1 15 9 4 0 3 1 0 7 11 0 2 1 0 9 10 0 1 0 1 8 9 1 1 1 06 11 8 0 2 0 0 6 9 1 0 3 0 9 7 1 1 1 0 5 6 3 0 1 17 8 8 0 1 1 0 6 10 1 1 0 0 7 8 0 2 2 1 7 8 1 1 2 08 5 6 0 0 1 1 7 7 0 1 1 1 8 9 1 1 2 0 5 8 0 2 0 09 7 7 1 1 1 0 8 8 1 0 0 0 5 6 0 1 1 0 8 9 1 1 1 0
10 9 6 0 0 2 0 9 8 0 1 1 0 7 8 1 0 0 1 5 7 0 0 1 011 8 8 1 1 0 0 8 7 1 1 2 1 8 9 0 1 1 0 8 9 0 1 2 112 5 4 0 2 1 0 10 6 1 1 1 0 6 5 0 1 0 0 6 5 0 1 1 0
To
tal
97 75 5 14 11 2 103 105 8 13 13 3 94 99 5 13 # 4 83 94 9 13 15 4
Su
m
204 245 226 218
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 16
130
Site: FAISAL BASE
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B1 4 10 0 1 1 1 10 11 0 1 3 1 14 11 0 1 2 1 11 15 2 2 0 2 17 13 1 1 1 1 14 12 0 2 2 2 10 11 1 2 2 1 9 10 0 0 2 12 5 10 1 1 1 2 9 12 1 2 2 2 20 12 0 1 1 0 12 11 1 1 2 0 12 14 1 1 2 2 10 13 1 1 1 2 10 12 0 2 1 2 11 12 0 2 1 03 10 8 1 2 1 2 8 14 1 2 2 1 19 11 1 2 2 1 13 10 0 2 1 1 11 15 1 3 1 1 7 13 1 2 2 1 9 11 1 2 2 1 10 11 0 2 2 24 6 12 0 2 2 0 11 9 0 2 1 1 13 12 1 2 2 0 9 12 1 2 2 0 14 13 0 2 2 1 10 12 1 1 3 2 10 14 1 2 2 0 9 13 1 1 2 05 5 11 0 1 1 1 10 11 1 1 2 1 11 13 0 1 2 1 12 13 0 3 2 1 12 15 1 3 2 2 12 14 0 2 2 1 9 12 0 2 3 1 10 11 0 2 1 26 7 11 1 2 2 0 11 12 0 3 1 2 14 10 1 2 2 1 12 11 1 2 2 0 13 12 0 2 2 1 11 15 1 2 1 3 10 14 1 1 2 1 10 11 1 2 2 17 6 10 1 2 1 1 10 13 1 1 2 1 12 10 0 1 2 0 10 11 1 2 3 1 11 12 1 2 2 1 10 14 0 1 2 2 11 15 1 2 2 1 10 12 0 1 1 18 11 9 0 2 3 1 12 11 0 2 1 0 10 13 2 2 3 1 9 10 2 2 2 2 13 12 1 3 2 2 11 16 0 2 2 1 12 12 0 2 2 0 12 11 1 1 2 39 9 18 0 1 2 1 9 10 1 2 2 0 9 12 1 2 3 0 12 11 0 3 2 1 15 12 1 2 1 1 10 15 1 2 2 3 11 13 0 1 2 1 11 13 1 2 2 1
10 8 10 1 1 2 0 11 12 0 1 1 1 11 11 0 3 2 1 11 12 1 2 2 0 13 11 0 3 2 2 9 16 1 2 1 1 12 12 1 2 1 0 12 10 1 2 2 111 8 11 1 1 2 0 10 13 1 2 2 0 15 12 0 1 2 0 10 14 1 3 2 1 13 12 1 2 2 1 11 17 1 2 2 2 9 13 1 2 2 1 10 13 0 2 2 112 7 12 1 1 1 1 9 12 0 0 1 2 12 11 1 2 2 2 12 16 0 3 3 0 12 11 1 3 3 1 8 13 1 2 2 1 10 15 1 3 2 0 11 10 1 3 2 213 10 10 0 2 2 1 10 11 1 0 1 1 14 10 0 2 3 1 11 13 1 1 2 2 14 13 0 1 2 1 11 15 0 1 3 2 9 16 1 3 2 2 12 11 1 1 2 214 4 9 0 2 2 1 13 12 1 2 2 1 11 9 1 1 0 1 12 11 1 2 1 1 15 12 1 1 3 2 12 11 1 1 2 1 8 11 0 2 3 1 9 12 0 1 2 015 10 9 1 2 4 0 12 9 0 1 2 0 13 12 0 2 2 0 11 12 0 2 2 1 11 14 1 2 2 1 10 13 1 2 3 2 7 12 1 1 2 1 10 11 1 2 1 1
To
tal
110 160 8 23 27 12 155 172 8 22 25 14 198 169 8 25 30 10 167 182 12 32 28 13 196 191 11 31 29 20 156 209 10 25 30 26 147 193 10 29 30 13 156 171 8 24 26 18
Su
m
403434 478 456 422340 396 440
Cyc
le No. of Vehicles per (10 sec) Interval30 sec 60 sec 70 sec 80 sec 10 sec 20 sec 50 sec 40 sec
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 17
131
Site: LAL QILA
C
ycle
No. of Vehicles per (10 sec) Interval 10 sec 20 sec 30 sec 40 sec
m C R V M B m C R V M B m C R V M B m C R V M B1 10 6 0 0 1 0 11 9 1 1 1 0 11 9 0 0 1 1 10 8 2 1 1 02 11 7 1 1 0 0 10 8 0 0 0 0 9 8 1 1 0 0 8 8 1 0 0 03 9 8 1 0 0 1 11 6 1 1 1 1 10 5 1 0 0 0 12 9 0 0 1 04 11 6 1 1 1 0 12 7 1 0 0 0 12 7 0 0 0 0 9 5 0 1 1 05 9 9 0 1 0 0 10 6 0 1 1 1 10 8 0 1 1 1 8 6 1 0 0 06 8 6 0 0 0 0 4 8 1 0 0 0 8 9 1 0 0 0 4 5 3 0 1 17 11 7 0 1 1 0 7 8 1 1 0 0 12 6 0 1 1 0 6 8 1 1 0 08 10 9 0 0 0 1 9 7 0 0 0 1 11 8 1 0 1 0 8 6 0 0 1 09 11 6 1 0 1 0 11 7 1 0 1 0 10 7 0 1 0 0 9 7 1 1 0 0
10 10 8 0 1 0 0 12 8 0 1 0 0 10 7 1 0 0 1 10 6 0 0 1 011 10 8 1 1 0 0 12 5 1 0 1 0 11 8 0 0 1 0 9 6 0 1 0 112 10 5 0 0 1 0 9 5 1 1 0 0 9 8 0 1 0 0 7 7 0 1 1 0
To
tal
120 85 5 6 5 2 118 84 8 6 5 3 123 90 5 5 5 3 100 81 9 6 7 2
Su
m
223 224 231 205
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 18
132
Site: KALA PULL
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B1 10 9 1 1 1 1 11 10 2 1 1 1 11 12 2 0 1 1 10 15 2 1 0 1 6 12 1 1 0 1 15 17 2 2 0 0 7 18 2 2 1 02 11 12 2 0 2 0 9 13 1 0 1 1 9 14 0 1 0 0 12 5 0 1 2 0 4 19 0 1 0 0 6 9 0 0 2 0 11 13 5 0 0 03 6 11 0 1 1 1 10 12 1 1 1 0 11 12 3 0 2 1 13 14 5 1 1 0 4 16 0 0 0 1 3 7 2 1 2 0 2 14 1 1 2 14 8 13 3 1 1 0 11 10 1 2 1 1 12 12 0 2 1 0 14 14 2 2 0 1 4 15 0 2 0 0 13 10 1 0 0 1 1 15 0 0 0 05 8 11 2 0 1 1 9 12 1 2 0 0 11 9 1 0 1 1 10 12 0 0 1 0 13 12 2 0 0 0 8 6 1 1 1 0 4 11 1 2 0 06 10 14 4 2 0 0 10 9 0 2 1 1 10 10 2 0 1 0 17 6 0 2 1 0 10 12 2 1 0 0 9 6 2 1 0 1 5 11 1 0 1 17 5 8 0 2 0 1 12 12 1 1 0 0 15 12 0 1 1 0 12 10 1 2 0 1 1 11 0 1 0 1 14 7 0 1 0 0 1 5 2 2 1 08 11 10 3 0 1 0 10 11 2 0 1 0 11 12 2 2 2 1 11 12 1 1 1 0 6 16 2 0 0 0 10 9 3 2 0 1 7 14 0 2 1 09 10 11 3 1 1 1 9 12 0 3 1 1 9 10 0 0 0 0 10 8 0 0 1 1 2 7 2 1 2 0 8 7 0 0 2 0 1 2 0 0 0 0
10 10 12 1 1 1 0 11 9 0 0 0 0 10 12 1 1 1 0 7 14 0 2 0 0 8 16 1 1 0 1 8 5 1 0 0 0 6 11 1 1 1 011 9 7 0 2 1 1 10 9 1 1 1 0 12 10 1 1 0 0 12 9 0 1 0 1 7 16 0 0 0 0 9 6 1 1 0 1 6 15 1 1 3 012 12 9 0 1 1 0 11 12 3 0 1 1 13 8 2 2 1 1 12 8 0 2 1 0 2 13 3 1 3 0 8 5 0 1 0 1 4 7 0 1 1 113 11 8 3 1 0 1 14 11 0 1 2 0 13 12 1 1 0 0 11 11 2 1 1 0 2 19 1 0 1 1 12 10 2 2 0 0 2 8 3 2 2 014 8 7 2 0 3 0 9 14 2 2 0 1 11 11 4 2 0 0 7 17 1 1 1 1 10 15 1 2 2 0 11 10 0 2 0 0 2 10 0 1 4 015 9 10 1 1 1 0 12 11 1 0 1 0 13 9 1 1 2 0 9 10 1 1 1 0 5 16 0 1 1 0 9 7 0 1 1 0 3 20 0 0 0 016 11 12 2 2 1 1 10 9 2 1 1 1 12 12 0 0 2 1 10 12 2 0 1 0 10 16 2 1 1 0 9 11 0 1 1 0 6 16 1 1 1 1
To
tal
149 164 27 16 16 8 168 176 18 17 13 8 183 177 20 14 15 6 177 177 17 18 12 6 94 231 17 13 10 5 152 132 15 16 9 5 68 190 18 16 18 4
Su
m
50 sec Cyc
le
10 sec 20 sec
No. of Vehicles per (10 sec) Interval30 sec 40 sec
314380 400 415
60 sec 70 sec
407 370 329
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 19
133
Site: NURSERY
m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B m C R V M B1 6 11 1 1 1 0 8 9 0 1 1 0 12 10 0 1 1 0 10 12 2 1 0 0 15 11 1 1 0 0 12 12 0 2 1 0 11 11 1 2 2 0 10 9 0 0 1 12 7 10 0 1 1 0 9 10 1 2 1 1 13 12 0 1 1 0 11 11 1 1 2 1 12 14 1 1 2 0 10 13 1 1 1 0 10 12 0 2 1 0 11 12 0 2 1 03 10 8 1 2 1 1 8 12 1 2 1 0 15 11 1 2 2 1 11 9 2 1 1 0 11 13 1 2 1 1 7 13 1 2 2 0 9 11 1 2 2 1 10 11 0 2 2 14 6 10 1 2 2 0 11 9 0 2 1 0 11 12 1 1 1 0 10 11 1 2 2 0 12 13 0 2 2 0 10 12 1 1 3 0 10 14 1 2 2 0 9 12 1 1 1 05 5 11 0 1 1 1 9 8 1 1 2 1 11 10 0 1 2 1 10 9 0 3 2 1 12 9 1 1 2 0 12 10 0 2 2 1 9 12 0 2 1 1 10 11 0 2 1 16 7 11 1 2 2 0 11 12 0 3 1 0 12 10 1 2 2 1 12 11 1 1 1 0 11 12 0 2 1 1 11 15 1 2 1 1 10 14 1 1 2 1 8 11 1 2 2 07 6 10 1 2 1 0 9 11 1 1 0 1 10 10 0 1 2 0 10 11 1 2 1 1 11 12 1 1 2 1 10 14 0 1 2 0 9 15 1 2 2 1 10 12 0 1 1 18 10 8 0 2 3 1 12 11 0 2 1 1 10 11 2 2 1 1 11 10 2 2 2 0 13 12 1 0 1 0 11 16 0 2 2 1 9 12 0 2 2 0 11 11 1 1 2 19 9 8 0 1 1 1 9 10 1 2 1 0 9 12 1 2 2 0 12 11 0 1 1 1 14 12 1 2 1 1 10 15 1 2 2 0 11 13 0 1 2 1 11 10 1 2 1 1
10 8 10 1 1 2 0 11 11 0 1 1 1 10 11 0 0 2 1 11 10 1 2 2 0 13 11 0 3 2 0 9 16 1 2 1 0 12 12 1 2 1 0 12 10 1 2 2 111 8 11 1 1 2 0 10 12 1 1 2 0 9 12 0 1 1 0 10 14 1 3 1 1 13 12 1 2 2 1 11 15 1 2 1 1 9 13 1 2 2 0 10 13 0 2 1 012 7 12 1 1 1 1 9 10 0 0 1 1 12 9 1 2 2 0 12 12 0 3 3 0 12 11 1 3 1 0 8 13 1 2 2 1 10 12 1 3 2 1 11 10 1 1 2 013 10 10 0 2 2 0 10 11 1 0 1 1 12 10 0 2 3 1 11 13 1 1 2 1 14 13 0 1 1 1 11 15 0 1 2 0 9 14 1 3 2 0 12 11 1 1 1 014 4 9 0 2 2 1 9 12 1 2 2 0 11 9 1 1 0 1 12 11 1 2 1 0 11 12 1 1 2 0 12 11 1 1 2 1 8 11 0 2 1 0 9 12 0 1 2 015 10 9 1 2 4 0 10 9 0 1 1 0 10 12 0 2 1 0 11 12 0 2 2 1 10 12 1 2 2 0 10 13 1 2 1 0 7 12 1 1 2 1 10 11 1 2 1 1
To
tal
113 148 9 23 26 6 145 157 8 21 17 7 167 161 8 21 23 7 164 167 14 27 23 7 184 179 11 24 22 6 154 203 10 25 25 6 143 188 10 29 26 7 154 166 8 22 21 8
Su
m
379402 426 423
Cyc
le No. of Vehicles per (10 sec) Interval30 sec 40 sec
403325 355 387
60 sec 70 sec 80 sec 10 sec 20 sec 50 sec
C= Passenger car/ Taxi/ Jeep M = Costar, Mini Buses
B = Buses
R = Rickshaw
V = Vans
m = Motor CycleLegend:
APPENDIX 20
134
SAMPLE SHEET FOR SATURATION FLOW CALCULATION
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec 80 sec 90 sec
1
23456789
1011121314151617181920
To
tal
Sam
ple
Cyc
le No. of Vehicles per 10 Seconds interval
APPENDIX 21
135
Calculation of Saturation Flow (EXAMPLE)
Saturation Flow = ( Total Flow in Saturated intervals) / ( Total of the Samples of
the Saturated intervals)
= (548 + 501 + 477 + 405 + 355 + 309 + 292 ) / ( 16 x 7 x 10 )
= ( 2887 ) / ( 16 x 7 x10 )
= 2.57 Vehs / sec
= 9280 Vehs / hr
APPENDIX 22
136
SATURATION FLOW - AWAMI MARKAZ
C
ycle
No. of Vehicles per 10 Seconds interval
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec 80 sec
1 17 24 27 30 32 30 26 21
2 18 27 34 27 30 26 25 26 3 22 28 36 26 31 25 26 25 4 22 24 30 26 31 27 29 26 5 18 23 28 31 33 31 26 25 6 23 27 30 27 30 31 29 26 7 20 26 25 27 28 28 30 25 8 26 26 28 27 32 32 25 28 9 20 24 27 29 32 30 28 30
10 22 26 25 28 29 29 28 28 11 23 28 29 29 30 34 27 27 12 23 24 28 34 28 27 31 27 13 25 24 30 30 31 30 31 29 14 18 30 23 28 32 28 24 2415 26 24 28 28 30 29 24 25
Ave
rag
e
21.53 25.67 28.53 28.47 30.6 29.13 27.27 26.13
To
tal
323 385 428 427 458 437 409 392
Sam
ple
15.00 15.00 15.00 15.00 15.00 15.00 15.00 15.00
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 3259 / (15 x 8 x 10) = 2.71 Vehs / sec
= 9777 Vehs / hr
APPENDIX 23
137
SATURATION FLOW AT DRIG ROAD
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec
1 24 31 33 26 22 24 17
2 25 24 26 26 28 25 213 28 28 32 26 29 26 254 28 24 30 33 30 26 235 25 29 27 27 28 19 216 27 24 28 28 31 26 287 22 25 30 28 22 25 208 26 28 23 27 28 22 229 24 26 30 28 25 23 20
10 27 26 26 27 23 19 1511 19 26 26 27 26 24 2212 23 23 23 26 33 34 3313 26 23 24 31 21 20 1414 23 29 31 25 26 26 2215 22 19 24 26 24 21 17
Ave
rag
e
24.60 25.67 27.53 27.40 26.40 24.00 21.33
To
tal
369 385 413 411 396 360 320
Sam
ple
15 15 15 15 15 15 15
Cyc
le No. of Vehicles per 10 Seconds interval
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 2654 / (15 x 7 x 10) = 2.5276 Vehs / sec = 9100 Vehs / hr
APPENDIX 24
138
SATURATION FLOW - KARSAZ
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec
26 32 23 20 28 26 24
35 33 29 28 29 17 2233 29 33 27 29 30 1843 37 38 26 21 26 2532 28 38 31 19 21 1837 33 29 26 22 16 1829 21 22 18 15 16 1632 28 31 25 24 22 2039 31 19 16 14 11 1236 32 23 25 15 13 1328 34 27 30 25 15 1836 30 37 19 10 11 1736 39 29 27 22 16 2334 28 36 28 26 26 1734 30 30 28 30 18 1638 36 33 31 26 25 15
34.25 31.31 29.81 25.31 22.19 19.31 18.25
548 501 477 405 355 309 292
16 16 16 16 16 16 16
No. of Vehicles per 10 Seconds interval
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 2887 / (16 x 7 x 10) = 2.57 Vehs / sec = 9280 Vehs / hr
APPENDIX 25
139
SATURATION FLOW MEHRAN INTERSECTION
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec
1 28 28 24 20 26 23 34
2 35 32 29 23 29 7 153 27 22 29 21 17 24 84 40 35 37 20 16 21 245 22 22 35 27 12 12 126 34 29 22 24 13 6 37 19 13 15 13 9 5 198 32 30 32 24 18 16 19 28 28 13 2 3 7 17
10 27 31 14 26 14 14 1211 28 37 24 23 25 8 812 36 30 40 21 9 9 1313 31 37 29 22 15 9 1214 28 26 36 26 17 18 1315 30 26 25 22 23 18 1316 36 35 32 29 24 25 17
Ave
rag
e
30.06 28.81 27.25 21.44 16.88 13.88 13.81
To
tal
481 461 436 343 270 222 221
Sa
mp
le
16 16 16 16 16 16 16
Cyc
le No. of Vehicles per 10 Seconds interval
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 2434 / (16 x 7 x 10) = 2.17 Vehs / sec = 7824 Vehs / hr
APPENDIX 26
140
SATURATION FLOW - REGENT PLAZA
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec
1 25 30 29 26 32 32 30
2 30 32 29 31 37 25 253 24 26 28 28 28 33 224 33 41 32 29 29 28 245 21 26 33 30 29 28 196 29 30 23 25 19 20 177 19 24 25 26 24 26 208 26 31 32 28 27 23 219 24 30 19 26 26 26 21
10 27 32 20 27 21 22 1611 28 34 27 29 27 15 2412 33 27 38 28 16 19 2413 31 38 31 28 27 19 1614 28 26 35 28 26 27 2215 31 26 25 26 30 20 22
Ave
rag
e
27.27 30.2 28.4 27.67 26.53 24.2 21.53
To
tal
409 453 426 415 398 363 323
Sam
ple
15 15 15 15 15 15 15
Cyc
le No. of Vehicles per 10 Seconds interval
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 2787 / (15 x 7 x 10) = 2.65 Vehs / sec = 9555 Vehs / hr
APPENDIX 27
141
SATURATION FLOW - SHAH FAISAL COLONY
10 sec 20 sec 30 sec 40 sec 50 sec
1 29 33 38 30 30
2 28 33 34 31 273 32 32 33 35 294 32 34 29 34 295 30 43 38 32 296 26 28 32 32 317 26 32 36 26 288 31 30 35 30 259 26 28 28 29 24
10 28 38 33 27 2811 25 29 34 27 3312 30 31 31 26 26
Ave
rag
e
28.58 32.58 33.42 29.92 28.25
To
tal
343 391 401 359 339
Sam
ple
12 12 12 12 12
Cyc
le No. of Vehicles per 10 Seconds interval
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 1833 / (12 x 4 x 10) = 3.054 Vehs / sec = 10994 Vehs / hr
APPENDIX 28
142
SATURATION FLOW - STAR GATE
Cy
cle
No. of Vehicles per 10 Seconds interval
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec 80 sec
1 27 28 28 25 25 24 22 27
2 26 26 31 26 21 19 26 24 3 23 24 25 26 24 24 20 19 4 23 22 25 25 26 24 19 235 25 23 23 24 21 22 19 236 15 23 27 26 26 20 23 20 7 26 25 25 28 25 26 20 21 8 23 27 27 31 25 21 23 19 9 23 22 26 32 23 25 21 23
10 22 24 20 29 25 25 24 16 11 26 27 25 27 19 21 25 20 12 20 25 23 28 23 24 25 18
Av
erag
e
23.25 24.67 25.42 27.25 23.58 22.92 22.25 21.08
To
tal
279 296 305 327 283 275 267 253
Sam
ple
12 12 12 12 12 12 12 12
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 2285 / (12 x 8 x 10) = 2.3805 Vehs / sec = 8570 Vehs / hr
APPENDIX 29
143
SATURATION FLOW TARIQ ROAD
10 sec 20 sec 30 sec 40 sec
1 19 38 34 33
2 26 33 31 303 27 32 26 284 24 31 31 225 23 29 28 226 38 25 27 147 28 33 27 188 23 29 26 219 25 30 29 23
10 29 36 31 2211 24 33 26 2512 20 31 25 17
Ave
rag
e
25.5 31.67 28.42 22.92
To
tal
306 380 341 275
Sam
ple
12 12 12 12
Cyc
le No. of Vehicles per 10 Seconds interval
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 1302 / (12 x 4 x 10) = 2.7125 Vehs / sec = 9765 Vehs / hr
APPENDIX 30
144
SATURATION FLOW KASHIF CENTRE
Cyc
le
No. of Vehicles per 10 Seconds interval
10 sec 20 sec 30 sec 40 sec
1 20 29 22 21
2 18 20 21 22 3 18 23 24 20 4 15 23 17 18 5 17 21 21 20 6 21 19 19 16 7 18 18 20 19 8 13 17 21 15 9 17 17 13 20
10 17 19 17 13 11 18 20 19 21 12 12 19 12 13
Av
erag
e
17 20.42 18.83 18.17
To
tal
204 245 226 218
Sam
ple
12 12 12 12
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 893 / (12 x 4 x 10) = 1.8604 Vehs / sec = 6697 Vehs / hr
APPENDIX 31
145
SATURATION FLOW FAISAL BASE
Cyc
le
No. of Vehicles per 10 Seconds interval
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec 80 sec
1 17 26 29 32 34 32 27 22
2 20 28 34 27 32 28 27 26 3 24 28 36 27 32 26 26 27 4 22 24 30 26 32 29 29 26 5 19 26 28 31 35 31 27 26 6 23 29 30 28 30 33 29 27 7 21 28 25 28 29 29 32 25 8 26 26 31 27 33 32 28 30 9 31 24 27 29 32 33 28 30
10 22 26 28 28 31 30 28 28 11 23 28 30 31 31 35 28 28 12 23 24 30 34 31 27 31 29 13 25 24 30 30 31 32 33 29 14 18 31 23 28 34 28 25 24 15 26 24 29 28 31 31 24 26
Ave
rag
e
22.67 26.40 29.33 28.93 31.86667 30.40 28.13 26.87
To
tal
340 396 440 434 478 456 422 403
Sam
ple
15.00 15.00 15.00 15.00 15.00 15.00 15.00 15.00
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 3369 / (15 x 8 x 10)
= 2.8075 Vehs / sec = 10107 Vehs / hr
APPENDIX 32
146
SATURATION FLOW - LAL QILA
Cy
cle
No. of Vehicles per 10 Seconds interval
10 sec 20 sec 30 sec 40 sec
1 17 23 22 22
2 20 18 19 17 3 19 21 16 22 4 20 20 19 16 5 19 19 21 15 6 14 13 18 14 7 20 17 20 16 8 20 17 21 15 9 19 20 18 18
10 19 21 19 17 11 20 19 20 17 12 16 16 18 16
Av
erag
e
18.5833333 18.58 19.25 17.08
To
tal
223 224 231 205
Sam
ple
12 12 12 12
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals) = 883 / (12 x 4 x 10) = 1.8395 Vehs / sec = 6622 Vehs / hr
APPENDIX 33
147
SATURATION FLOW - KALA PULL
Cyc
le
No. of Vehicles per 10 Seconds interval
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec
1 23 26 27 29 21 36 30
2 27 25 24 20 24 17 29 3 20 25 29 34 21 15 21 4 26 26 27 33 21 25 16 5 23 24 23 23 27 17 18 6 30 23 23 26 25 19 19 7 16 26 29 26 14 22 11 8 25 24 30 26 24 25 24 9 27 26 19 20 14 17 3
10 25 20 25 23 27 14 20 11 20 22 24 23 23 18 26 12 23 28 27 23 22 15 14 13 24 28 27 26 24 26 17 14 20 28 28 28 30 23 17 15 22 25 26 22 23 18 23 16 29 24 27 25 30 22 26
Av
erag
e
23.75 25.00 25.9375 25.44 23.13 20.56 19.63
To
tal
380 400 415 407 370 329 314
Sam
ple
16 16 16 16 16 16 16
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals)
= 2615 / (16 x 7 x 10) = 2.33 Vehs / sec = 8405 Vehs / hr
APPENDIX 34
148
SATURATION FLOW - NURSERY
C
ycle
No. of Vehicles per 10 Seconds interval
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec 80 sec
1 20 19 24 25 28 27 27 21
2 19 24 27 27 30 26 25 26 3 23 24 32 24 29 25 26 26 4 21 23 26 26 29 27 29 24 5 19 22 25 25 25 27 25 25 6 23 27 28 26 27 31 29 24 7 20 23 23 26 28 27 30 25 8 24 27 27 27 27 32 25 27 9 20 23 26 26 31 30 28 26
10 22 25 24 26 29 29 28 28 11 23 26 23 30 31 31 27 26 12 23 21 26 30 28 27 29 25 13 24 24 28 29 30 29 29 26 14 18 26 23 27 27 28 22 24 15 26 21 25 28 27 27 24 26
Ave
rag
e
21.67 23.67 25.80 26.80 28.4 28.20 26.87 25.27
To
tal
325 355 387 402 426 423 403 379
Sam
ple
15.00 15.00 15.00 15.00 15.00 15.00 15.00 15.00
Saturation Flow = (Total Flow in Saturated intervals) / (Total of the Samples of the Saturated Intervals)
= 3100 / (15 x 8 x 10) = 2.58 Vehs / sec = 9300 Vehs / hr
APPENDIX 35
149
STATISTICAL ANALYSIS FOR VEHICLE’S HEADWAY
150
2.21.81.41.00.60.2
95% Confidence Interval for Mu
1.301.261.22
95% Confidence Interval for Median
Variable: Car
1.23664
0.26925
1.21063
Maximum3rd QuartileMedian1st QuartileMinimum
NKurtosisSkewnessVarianceStDevMean
P-Value:A-Squared:
1.30000
0.31615
1.27671
2.400001.440001.250001.100000.14000
3003.61761-3.4E-018.46E-020.29081
1.2398
0.0003.738
95% Confidence Interval for Median
95% Confidence Interval for Sigma
95% Confidence Interval for Mu
Anderson-Darling Normality Test
Descriptive Statistics APPENDIX 36
151
0.1 0.3 0.5 0.7 0.9 1.1 1.3
95% Confidence Interval for Mu
0.45 0.50 0.55
95% Confidence Interval for Median
Variable: Motor Cycle
A-Squared:P-Value:
MeanStDevVarianceSkewnessKurtosisN
Minimum1st QuartileMedian3rd QuartileMaximum
0.48486
0.23178
0.44000
2.5960.000
0.4607
0.2545206.48E-020.8248920.618398
200
0.080000.320000.490000.640001.24000
0.55584
0.28224
0.56000
Anderson-Darling Normality Test
95% Confidence Interval for Mu
95% Confidence Interval for Sigma
95% Confidence Interval for Median
Descriptive Statistics APPENDIX 37
152
1.9 2.2 2.5 2.8 3.1
95% Confidence Interval for Mu
2.42 2.52 2.62 2.72 2.82
95% Confidence Interval for Median
Variable: Mini-Bus
A-Squared:P-Value:
MeanStDevVarianceSkewnessKurtosisN
Minimum1st QuartileMedian3rd QuartileMaximum
2.49586
0.37447
2.44000
1.2750.002
2.61440
0.436750.1907481.88E-02-1.12270
70
1.840002.310002.480003.000003.28000
2.70414
0.52406
2.80000
Anderson-Darling Normality Test
95% Confidence Interval for Mu
95% Confidence Interval for Sigma
95% Confidence Interval for Median
Descriptive StatisticsAPPENDIX 38
153
1.4 1.6 1.8 2.2 2.8
95% Confidence Interval for Mu
1.4 1.7 2.2 2.9
95% Confidence Interval for Median
Variable: Vans
A-Squared:P-Value:
MeanStDevVarianceSkewnessKurtosisN
Minimum1st QuartileMedian3rd QuartileMaximum
1.71284
0.34988
1.40000
1.4400.001
1.87500
0.408060.1665120.436967-7.5E-01
70
1.500001.715001.81000
2.745003.28000
2.90744
0.48963
2.24000
Anderson-Darling Normality Test
95% Confidence Interval for Mu
95% Confidence Interval for Sigma
95% Confidence Interval for Median
Descriptive Statistics APPENDIX 39
154
0.1 0.3 0.5 0.7 0.9 1.1
95% Confidence Interval for Mu
0.45 0.55 0.65
95% Confidence Interval for Median
Variable: Rickshaw
A-Squared:P-Value:
MeanStDevVarianceSkewnessKurtosisN
Minimum1st QuartileMedian3rd QuartileMaximum
0.52705
0.20785
0.43115
1.7010.000
0.54200
0.2401685.77E-020.225010-1.01025
80
0.120000.360000.600000.750001.12000
0.63395
0.28447
0.65771
Anderson-Darling Normality Test
95% Confidence Interval for Mu
95% Confidence Interval for Sigma
95% Confidence Interval for Median
Descriptive Statistics APPENDIX 40
155
2.8 3.2 3.6 4.0 4.4
95% Confidence Interval for Mu
3.52 3.62 3.72 3.82
95% Confidence Interval for Median
Variable: Bus/Truck
A-Squared:P-Value:
MeanStDevVarianceSkewnessKurtosisN
Minimum1st QuartileMedian3rd QuartileMaximum
3.52958
0.31868
3.52930
0.4010.346
3.76800
0.389030.1513483.41E-02-2.8E-01
40
2.800003.330003.640003.990004.56000
3.77842
0.49953
3.80000
Anderson-Darling Normality Test
95% Confidence Interval for Mu
95% Confidence Interval for Sigma
95% Confidence Interval for Median
Descriptive Statistics APPENDIX 41
156
AVERAGE CYCLE PROFILE AT AWAMI MARKAZ
21.5325.67
28.53 28.4730.6 29.13
27.27 26.13
0
5
10
15
20
25
30
35
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec 80 sec
GREEN TIME INTERVAL
NO
OF
VE
H
APPENDIX 42
157
AVERAGE CYCLE PROFILE AT DRIG ROAD JUNCTION
24.6 25.6727.53 27.4 26.4
2421.33
0
5
10
15
20
25
30
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec
GREEN TIME INTERVAL
NO
OF
VE
HS
APPENDIX 43
158
AVERAGE CYCLE PROFILE AT KARSAZ JUNCTION
34.2531.31 29.81
25.3122.19
19.31 18.25
0
5
10
15
20
25
30
35
40
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec
GREEN TIME INTERVAL
NO
OF
VE
HIC
LE
S
APPENDIX 44
159
AVERAGE CYCLE PROFILE AT MEHRAN HOTEL JUNCTION
30.06 28.8127.25
21.44
16.8813.88 13.81
0
5
10
15
20
25
30
35
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec
GREEN TIME INTERVAL
NO
OF
VE
H
APPENDIX 45
160
AVERAGE CYCLE PROFILE AT REGENT PLAZA JUNCTION
27.2730.2
28.4 27.67 26.5324.2
21.53
0
5
10
15
20
25
30
35
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec
GREEN TIME INTERVAL
NO
OF
VE
HIC
LE
S
APPENDIX 46
161
AVERAGE CYCLE PROFILE AT SHAH FAISAL COLONY
28.58
32.58
29.92
28.25
33.42
25
26
27
28
29
30
31
32
33
34
10 sec 20 sec 30 sec 40 sec 50 sec
GREEN TIME INTERVAL
NO
OF
VE
HIC
LE
S
APPENDIX 47
162
AVERAGE CYCLE PROFILE AT STAR GATE
23.2524.67 25.42
23.58 22.92 22.25 21.08
27.25
0
5
10
15
20
25
30
10 sec 20 sec 30 sec 40 sec 50 sec 60 sec 70 sec 80 sec
GREEN TIME INTERVAL
NO
OF
VE
HIC
LE
S
APPENDIX 48
163
AVERAGE CYCLE PROFILE AT TARIQ ROAD
25.5
31.67
28.42
22.92
0
5
10
15
20
25
30
35
10 sec 20 sec 30 sec 40 sec
GREEN TIME INTERVAL
NO
OF
VE
HIC
LE
S
APPENDIX 49