To help transportation engineering student in volume study

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Traffic Volume Study
Report Submitted By –
Pronob Kumar Ghosh
Std ID: 1204011
Group No: 01
Submitted to –
Professor Md. Shamsul Haque
Assistant Professor Sanjana Hossain
Department of Civil Engineering
Bangladesh University of Engineering and Technology

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ABSTRACT
The goal of traffic engineering is to assure safe, convenient and time efficient movement
of people and goods on roadways. This movement of the people and goods is dependent
on traffic parameters. The three main parameters of a traffic flow are volume, speed and
density. The current studies on traffic volume characteristics of roadway from Panthapath
Signal to Russel Square in Dhaka City .The amount of vehicle have increased
significantly in the last decade due to the increase of the economic condition of people.
The vehicles of highly heterogeneous traffic with widely varying physical and
operational characteristics without any lane discipline. In this study emphasis is given on
traffic volume data collection and the different analysis are carried out. The interaction
between moving vehicles under such heterogeneous traffic condition is highly complex.
For better understanding of the present status of traffic flow at the junction, traffic survey
is conducted. With the help of the data collection, it has made clear to understand the
traffic patterns during different time periods. Hence the analysis from the present study
are helpful in controlling the traffic flow at the intersection and also in suggesting some
traffic management measures to improve the traffic movement in this region.

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ACKNOWLEDGEMENT
First of all, we would like to express my deepest sense of gratitude to almighty God.
I write this acknowledgement with great honor, pride and pleasure to pay my respects to
all who enable us either directly in completing this report. I express my deep sense of
gratitude to Md. Shamsul Haque, Professor, Department of Civil Engineering and Sajana
Hossain, Assistant Professor, Department of Civil Engineering, Bangladesh University of
Engineering & Technology for being valuable guidance to us especially for writing this
report that I have encountered while working on this report.

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CONTENTS
Page No.
Abstract ii
Acknowledgement iii
Contents iv
List of Figures
List of Tables
Abbreviations
CHAPTER 1 INTRODUCTION 1
CHAPTER 2 LITERATURE REVIEW 2
2.1 Traffic Survey
2.2 Traffic Volume Study
2.3 DEFINATION
2.3 a. Volume
2.3 b. Rate of Flow
2.3 c. Average Daily Traffic
2.3 d. Average Annual Daily Traffic
2.4 Expansion Factor
2.4 a. Hourly Expansion Factor
2.4 b. Daily Expansion Factor
2.4 c. Monthly Expansion Factor

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2.5 Type of Traffic Volume Counts
2.5 a. Screen Line Count
2.5 b. Cordon Count
2.5 c. Intersection Count
2.5 d. Pedestrian Volume Count
2.5 e. Continuous Count
2.6 Previous Traffic Volume Study
CHAPTER 3 METHODOLOGY
3.1 Method of Traffic Volume Study
3.1 a. Manual Counting
3.1 b. Automatic Recorders
3.1 c. Moving Vehicle Method
CHAPTER 4 DATA COLLECTION
CHAPTER 5 DATA ANALYSIS
5.1 Detailed Calculation
5.2 Vehicle Composition
5.3 Service Flow Rate from Panthapath to Russel Square
5.4 Service Flow Rate from Russel Square to Panthpath
5.5 Directional Distribution
5.6 Flow Fluctuation

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CHAPTER 6 CONCLUSION AND RECOMMENDATION
6.1 Conclusion
6.2 Recommendation
6.3 Limitation
6.4 Future Work
References
Appendix – A Data Collection Table
A.1 Volume Data Table for Individual Vehicle

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List of Figures
Figure No. Figure Title Page
2.1 Typical Example of Cordon Count.
2.2 Electric Manual Counter.
3.1 Map and Length of our traffic study roadway.
3.2 Tally Counter.
3.3 Road Measuring Wheel Stock.
5.1 Vehicle Composition of Traffic Stream of Group-1.
5.2 Traffic Flow Rate from Panthapath
to Russel Square at different section.
5.3 Traffic Flow Rate from Russel Square
to Panthapath at different section.
5.4 Flow Fluctuation Curve.

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List of Tables
Table No. Table Title Page
4.1 Summary Data of First Four Group
from Panthapath to Russsel Square.
4.2 Summary Data of First Four Group
from Russel Square to Panthapath.
5.1 Total Vehicle in terms of PCU/10min.
5.2 Hourly & Daily Expansion Factor.
5.3 Vehicle Composition of Traffic Stream.
5.4 Traffic Flow Rate (PCU/hour) from
Panthapath to Russel Square.
5.5 Traffic Flow Rate (PCU/hour) from
Russel Square to Panthapath.
5.6 Calculation of Directional Distribution
of Traffic Stream.
5.7 Flow Fluctuation table of all group.
5.8 Percent of ADT.

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ABBREBIATION
PCU Passenger Car Unit
PCE Passenger Car Equivalent
ADT Average Daily Traffic
AADT Annual Average Daily Traffic
DEF Daily Expansion Factor
HEF Hourly Expansion Factor
MEF Monthly Expansion Factor

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Chapter 1
INRODEUCTION
Traffic volume is defined as the amount of vehicles crossing a particular cross section per
unit time. It is measured in vehicle per minute or vehicle per hour or vehicle per day. In
order to express the traffic flow on a road per unit time, it is
necessary to convert the flow of the different vehicle classes into a standard vehicle class
known as Passenger Car Unit (PCU). The traffic volume is dynamic and varies during 24
hours of the day. Daily traffic volume varies on different days of a week and different
months and seasons of the years. The information on traffic volume is an important input
required for planning, analysis, design and operation of roadway systems. Vehicle
composition of traffic stream, flow rate, directional distribution, peak hour flow and
annual average daily traffic (AADT) are used for planning, design and operation of
highways in most of the developed countries, pertain to fairly homogeneous traffic
conditions comprising vehicles of more or less uniform static and dynamic
characteristics. But the traffic scenario of Panthapath to Russel Square roadway in Dhaka
City differs significantly from the conditions of developed countries in many respects. In
this road traffic, the heterogeneity is of high degree with vehicles of widely varying static
and dynamic characteristics. Consequently, the vehicles tend to choose any advantageous
lateral position on the road based on space availability. Under the said traffic conditions
expressing traffic volume as number of vehicles passing a given section of road per unit
time will inappropriate. The problem of measuring volume of such heterogeneous traffic
has been addressed by converting the different types of vehicles into Passenger Cars Unit
and expressing the volume in terms of Passenger Car Unit (PCU) per hour. The PCU is
the universally adopted unit of measurement of traffic volume, derived by taking the
passenger car as the standard vehicle. The interaction between moving vehicles in a
traffic stream for Panthapath to Russel Square roadway is highly complex and is
influenced by a number of roadway and traffic factors. This Traffic Volume study can be
used for better operation and management of facilities in this roadway.

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CHAPTER 2
LITERATURE REVIEW
Transportation Service of Dhaka City is measured in terms of ability of highway to
accommodate vehicular traffic safely and efficiently. Determination of functional
effectiveness of prescribed highway from Panthapath to Russel Square needs the
vehicular analysis of traffic. In undertaking such analysis, various parameters of traffic
such as vehicular composition, flow rate, directional distribution, flow fluctuation and
AADT must be addressed. For those analysis traffic volume is counted. Generally
passenger car is adopted as standard vehicle and this factor is known as passenger car
unit (PCU). Many researchers have developed methods to estimate PCU for classified
vehicle. In this report PCU value is taken from Roads and Highway Department,
Bangladesh Government.
2.1 Traffic Survey
Traffic engineers and planners need information about traffic. They need information to
design and manage road and traffic system. They use the information for planning and
designing traffic facilities, selecting geometric standards. They use this to justify warrant
of traffic control devices such as signs, traffic signals, pavement markings, school and
pedestrian crossings. They also use this information to study the effectiveness of
introduced schemes, diagnosing given situations and finding appropriate solutions,
forecasting the effects of projected strategies, calibrating and validating traffic models.
Transportation system is a dynamic system. Information about traffic volume must be
regularly updated to keep pace with ever-changing transportation system. Traffic Volume
surveys are the means of obtaining information about traffic.
But in our traffic volume study, due to time shortage traffic survey is not done before the
data collection. As our prescribed roadway Panthapath to Russel Square is one of the
main roadway of Dhaka City, the traffic volume study is represented to analysis vehicle
composition, flow rate, directional distribution, flow rate etc. for present condition.

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2.2 Traffic Volume Study
Traffic volume studies are conducted to determine the number, movements, and
classifications of roadway vehicles at a given location. These data can help identify
critical flow time periods, flow fluctuation curve, determine the influence of large
vehicles or document traffic volume trends.
2.3 Definition
2.3 a. Volume: The total number of vehicles that pass over a given point or section of a
lane or roadway during a given time interval is called volume. It is the actual number of
vehicle observed or predicted to passing a point during a given interval.
2.3 b. Rate of flow: The equivalent hourly rate at which vehicles pass over a given point
or section of a lane or roadway during a time interval less than 1hr. usually 15 min.
2.3 c. Average Daily Traffic (ADT): The average 24-hr volume at a given location over
a defined time period less than one year. The common application is to measure an ADT
for each month of the year. Others are
Planning of highway activities.
Measurement of current demand.
Evaluation of existing traffic flow.
2.3 d. Average Annual Daily Traffic (AADT)
The average 24-hr volume at a given location over a full 365 days year, estimated as the
number of vehicles passing a site in a year divided by 365 days is known as Average
Annual Daily Traffic.
The application of AADT is following –
Estimation of highway users.
Traffic volume trends.
AADT can be converted into Vehicles Mile Travelled.
Economic feasibility study.
Development of hierarchical system of facilities.
Improvement and maintenance programs.

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2.4 Expansion Factors
Hourly, daily, and monthly expansion factors can be determined from data obtained.
2.4 a. Hourly Expansion Factor
Hourly Expansion Factor, HEF =
(Total volume for 24 hour period / Volume for particular hour)
2.4 b. Daily Expansion Factor
Daily Expansion Factor, DEF =
(Total volume for a week / Volume for a particular day)
2.4 c. Monthly Expansion Factor
Monthly Expansion Factor, MEF =
(Total volume for a year / Volume for particular month)
2.5 Type of Traffic Volume Count
2.5 a. Screen Line Count
A screen line is an imaginary line on a map, composed of one or more straight line
segments. Screen line analysis provides a means of comparing the results of a traffic
assignment with traffic count data. This is facilitated by comparing the directional (or bi-
directional) sum of traffic count volumes across a screen line with the directional (or bi-
directional) sum of the assigned traffic volumes across the same screen line and then
computing the ratio of the sums, generally the assigned flow sum to the count sum.
Collection of data at these screen-line stations at regular intervals facilitates the detection
of variations in the traffic volume and traffic flow direction due to changes in the land-
use pattern of the area.

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2.5 b. Cordon Count
The area for which the data are required is cordoned off by an imaginary closed
boundary; the area enclosed within this boundary is defined as the cordon area. Figure
2.1 shows such an area where a city is enclosed by the imaginary loop. The information
obtained from such a count is useful for planning parking facilities, updating and
evaluating traffic operational techniques and making long-range plans for freeway and
arterial street systems.
Figure 2.1 Typical Example of Cordon Count.
2.5 c. Intersection Count
Intersection counts are considered to determine vehicle classifications through
movements and turning movements at intersections. These data are used mainly in
determining cycle times for signalized intersections in the design of channelization at
intersections.
2.5 d. Pedestrian Volume Count
Pedestrian volume counts for each cross walk should be made during the same period
as the vehicle volume count. Tallies should be recorded for each quarter hour for the
duration of the count. Pedestrian counts are not required in sparsely settled rural areas
or at other locations where it is apparent that pedestrian movement is negligible.

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Figure 2.2 Electric Manual Counter.
2.5 e. Continuous Count
Continuous counts are taken using mechanical or electronic counters showed in Figure
2.3.Stations at which continuous counts are taken as permanent count stations. In
selecting permanent count stations, the highways within the study area must first be
properly classified. Each class should consist of highway links with similar traffic
patterns and characteristics. A highway link is defined for traffic count purposes as a
homogeneous section that has the same traffic characteristics, such as AADT and daily,
weekly, and seasonal variations in traffic volumes at each point.
2.6 Previous Traffic Volume Study
Present traffic volume study in Dhaka City is important for the measurement of traffic
parameters and analysis of traffic volume, speed-flow relationships, passenger car
equivalents, peak hour factor, flow variations and traffic capacity and level of
serviceability.
Chandra S, Kumar V and Sikdar (1995) made a comprehensive study on capacity of
urban roads. It was emphasized that PCU values for vehicle type is dynamic in nature and
depends on all factors affecting the behavior of vehicle in the traffic stream. Data
collected at various at various mid-block sections of Delhi were used to study the
dynamic nature of PCU for a vehicle type. They observed that the PCU for a vehicle type
decreases with increase in its own proportion in the traffic stream.

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Parker (1996) observed that knowledge of traffic composition plays an important role in
determining capacity. It was found that the percentage of heavy goods vehicles (HGVs)
within traffic stream has a major effect on capacity due to length, limited
maneuverability, lower desired speed and engine power to weight ratio. As the presence
of HGV’s in the traffic stream increases, the capacity reduces in term of throughout of
vehicle per hour.
Chandra and Sikdar (2000) observed that PCU for a vehicle type is mainly controlled
by homogeneity/ heterogeneity of the traffic stream, which in turn, depend upon the
relative proportion of different types of vehicle. The basic philosophy involved in the
development of concept of dynamic PCU was that capacity estimation in a common unit
must be same irrespective of stream composition under given physical and control
conditions. They developed a computer program to evaluate PCU for a vehicle type of
urban roads.
Central Road Research Institute (CRRI), (1988) New Delhi to determine the PCU
value for different types of vehicles comprises of linear regression of the speed of cars
with volume of different categories of vehicles. The method suggests collection of large
amount of data on speed of cars under traffic volume and composition and fitting
multiple linear regression equations.
Chandra.S and Prasad N.V (2004) found that the PCU factors calculated at different
sections of urban roads vary substantially across the sections. Capacity varies with
physical and traffic conditions and traffic composition. Capacity of a multilane divided
urban road increases linearly with increase in the proportion of two-wheelers in traffic
stream. It is estimated that capacity of an urban road section increases by approximately 9
percent for every 10 percent increase in the proportion of 2-wheeler. The capacity of a
section with side friction is approximately12 percent lower as compared to a section with
no side friction.
V.T Hamizh Arasan and Krishnamurthy (2008) provided an insight into the
complexity of the vehicular interaction in heterogeneous traffic. The PCU estimates,
made through microscopic of simulation, for the different types of vehicles of
heterogeneous traffic, for a wide range traffic volume and roadway conditions indicate
that the PCU value of a vehicle significantly changes with change in traffic volume and
width of roadway.

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Satyanarayana (2012) studied the effect of traffic volume, its composition and stream
speed on passenger car equivalents. Method proposed by Chandra is used for developing
the PCU factors and found that for two axle trucks PCU values are found to increase with
an increase in compositional share of respective vehicle types in the traffic stream. The
PCU of two wheelers practically remains unaffected by its compositional share in the
traffic stream.
Our prescribed road for traffic volume study Panthapath to Russel Square is one of the
main primary road in Dhaka City. To ensure safe, convenient and efficient traffic
movement into this roadway, we continue this traffic survey. To facilitate the existing
road condition, it is necessary to analysis traffic volume composition, directional
distribution, flow fluctuation, flow rate etc. for this roadway. After this traffic volume
study, we can ensure the better traffic condition.

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CHAPTER 3
METHODOLOGY
3.1 Method of Traffic Volume Count
Traffic volume studies are conducted to determine the number, movements, and
classifications of roadway vehicles at a given location. Our Traffic Volume Study is
continued in Panthapath to Russel Square in Dhaka City. The location is chosen because
of rapid growth of commercial and institutions in the area. These data helps to identify
peak hour flow, determine the composition of vehicles on vehicular traffic flow. The way
of traffic volume count can be collected by the following methods:-
3.1 a. Manual counting
In this method a team of enumerators is engaged to record traffic volume on the
prescribed roadway in a specified period. A sample of the field sheet which is used for
traffic counts.
The main advantage of this method is that the field team can record the type and
direction of vehicles. However, it is not practicable to do manual counting for all the 24
hours of the day and on all days round the year. But this method is commonly used due
to its specific advantage over the automatic recorders.
3.1 b. Automatic recorders
In this method, the total number of vehicles crossing at a road intersection in the
desired period is automatically recorded by a mechanical recorder. These recorders are
either fixed type or portable type and may record data though the following ways-
Photo electric cell method –
In this method, the automatic recorder is actuated by the interruption of a light beam
falling on a photo electric cell placed on the road side as a vehicle passes.
Electrical method –
In this method, the automatic recorder is actuated by closing of an electric circuit by
the passage of vehicle.
The main advantage of the methods of automatic recorders is that they can work
throughout the day and night for the desired period, recording total hourly volume of
traffic. But the disadvantage of this method is that the automatic recorders cannot record
the type and direction of vehicles. Moreover the data is not as accurate as in case of
manual counting since two or more vehicles going abreast will be recorded as a single
unit.

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3.1 c. Moving Vehicle Method
In this method, the number of vehicles met overtaken and the time taken to travel
are noted by the observer moving in a car once against the traffic and second time
along with the traffic. Then the volume of traffic is calculated by the following
relationship –
V= (X+Y) / (ta+tw)
Where, V= Vehicles per minute in one direction.
X= Number of vehicles met when moving against the desired direction in
ta minutes.
Y= Number of vehicles overtaken while moving along with the traffic in the
direction in tw minutes.
The accuracy of this method depends upon the number of tests conducted.
As the number of enumerators in our team is available and in the absence of modern
equipment, manual counting method is selected to continue traffic volume study.
Figure 3.1 Map and Length of our traffic study roadway.

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Figure 3.2 Tally Counter.
Figure 3.3 Road Measuring Wheel Traffic.

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CHAPTER 4
DATA COLLECTION
Location: Location of the traffic volume study was selected to be from Panathapath to
Russel Square. Vehicles from Panathapath to Russel Square and from Russel Square to
Panthapath were counted.
Date: Data for traffic volume study was collected on 23 March 2017.
Time: Time of data collection for traffic volume study was 8:30 AM to 8:40 AM.
Weather Condition: Sunny Day.
Observation: Classified Vehicle Counts.
Method: Direct Manual Method.
Duration: 10 minutes (Short Count).
Equipment: Tally Counter, Road measuring wheel stock, Vest.
Number of Enumerators: Seven.

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Table 4.1 Summary Data of First Four Group from Panthapath to Russsel Square.
Table 4.2 Summary Data of First Four Group from Russel Square to Panthapath.
TIME DIRECTION: PANTHAPATH -> RUSSEL SQUARE
MOTORIZED VEHICLES
GRO
UP
BU
S
(B)
TRU
CK
(T)
MOTORC
YCLE
(MC)
LIGHT VEHICLE (LV) AUTO
RICKSHAW
(AR)
SMALL
PUBLIC
TRANSPORT
(SP)
TOTAL
VEHICLES
CAR/T
AXI
JEEP/P
AJERO
PICK
UP
AMBULA
NCE
MICR
O
BUS
BABY
TAXI/MISHO
OK
MAXI /
TEMPOO
1st
Hour
1 4 0 33 94 5 4 0 16 41 0 197
2nd
Hour
2 2 0 16 70 8 6 1 10 27 0 140
3rd
Hour
3 6 5 26 104 7 10 5 22 38 0 223
4th
Hour
4 2 0 27 107 5 11 1 12 42 0 207
TOTAL:
1
4
5 102 375 25 31 7 60 148 0 767
TIME DIRECTION: RUSSEL SQUARE -> PANTHAPATH
MOTORIZED VEHICLES
GRO
UP
B
U
S
(
B
)
TR
UC
K
(T)
MOTOR
CYCLE
(MC)
LIGHT VEHICLE (LV) AUTO
RICKSHAW
(AR)
SMALL PUBLIC
TRANSPORT (SP)
TOTA
L
VEHI
CLESCAR/
TAXI
JEEP/PA
JERO
PICK
UP
AMBUL
ANCE
MIC
RO
BUS
BABY
TAXI/MISHOO
K
MAXI / TEMPOO
1st
Hour
8 3 0 48 188 6 2 3 11 43 0 304
2nd
Hour
7 4 0 62 131 4 8 2 20 33 0 264
3rd
Hour
6 5 0 50 91 6 1 4 17 55 0 229
4th
Hour
5 1 0 36 1
16
26 0 184
TOTAL:
AVERA
GE

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CHAPTER 5
DATA ANALYSIS
5.1 Detailed Calculation
Table 5.1 Total Vehicle in terms of PCU/10min.
Classified
Vehicle
Number of
Vehicles PCU Factor Number of
Vehicle
Equivalent to
Passenger Car
Total Vehicle
PCU/10min
Bus 4 3.0 12
Truck 0 3.0 0
Motor-Cycle 33 0.75 25 187
Light Vehicle 119 1.0 119
Auto-Rickshaw 41 0.75 31
Small Public
Transport
0 0.75 0

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Table 5.2 Hourly & Daily Expansion Factor.
Factor Value
Hourly Expansion Factor 22.05
Daily Expansion Factor 7.012
Monthly Expansion Factor 1.635
Service flow rate:
187 * 6 = 1122 vehicle/hour
Daily volume:
1122 * HEP = 1122 * 22.05 = 24741 vehicle/day
Weekly volume:
24741 * DEP = 27924 * 7.012 = 173484 vehicle/week
Average Daily Traffic:
ADT= 173484 / 7 = 24784 vehicle/day
Annual Average Daily Traffic:
AADT= ADT * MEF = 24784 * 1.635 = 40522 vehicle / day

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5.2 Vehicle Composition
Table 5.3 Vehicle Composition of Traffic Stream.
Classified Vehicle PCU/hour % of Total Flow
Bus 72 6
Light Vehicle 714 64
Motor-Cycle 150 13
Auto Rickshaw 186 17
Total=1122 Total=100
Figure 5.1 Vehicle Composition of Traffic Stream of Group-1.

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5.3 Service Flow Rate from Panthapath to Russel Square.
Table 5.4 Traffic Flow Rate (PCU/hour) from Panthapath to Russel Square.
5.4 Service Flow Rate from Russel Square to Panthapath.
Table 5.5 Traffic Flow Rate (PCU/hour) from Russel Square to Panthapath.
0
200
400
600
800
1000
1200
1400
Group 1 Group 2 Group 3 Group 4
1122
804
1374
1164
PCU/hour
Group
Group Time PCU/hour
1. 8:30-9:30 1122
2. 9:30-10:30 804
3. 10:30-11:30 1374
4. 11:30-12:30 1164
Group Time PCU/hour
8. 8:30-9:30 1149
7. 9:30-10:30 993
6. 10:30-11:30 851
5. 11:30-12:30 662

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Figure 5.3 Traffic Flow Rate from Russel Square to Panthapath at different section.
0
200
400
600
800
1000
1200
Group 8 Group 7 Group 6 Group 5
1149
993
851
662
PCU/hour
Group

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5.5 Directional Distribution
Table 5.6 Calculation of Directional Distribution of Traffic Stream.
Directional Distribution from
Panthapath to Russel Square = (4464 / 4464+3655) *100
= 54.98%
Russel Square to Panthapath = (3655 / 4464+3655) *100
= 45.02%
Panthapath to Russsel Square Russel Square to Panthapath
Group PCU/hour Group PCU/hour
1. 1122 5. 662
2. 804 6. 851
3. 1374 7. 993
4. 1164 8. 1149
Total 4464 Total 3655

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5.6 Flow Fluctuation:
Table 5.7 Flow Fluctuation table of all group.
Group ADT Group ADT
1. 24784 8. 25379
Panthapath to
Russel Square
2. 15142 Russel Square
to Pathapath
7. 18701
3. 23550 6. 14586
4. 21595 5. 12282
Total 85071 Total 70948
Table 5.8 Percent of ADT.
Group % ADT Group % ADT
1. 29.133 8. 35.771
Panthapath to
Russel Square
2. 17.799 Russel Square
to Pathapath
7. 26.358
3. 27.682 6. 20.558
4. 25.384 5. 17.311

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Figure 5.4 Flow Fluctuation Curve.
29.133
17.799
27.682
25.384
35.771
26.358
20.558
17.311
0
5
10
15
20
25
30
35
40
8:30-9:30 9:30-10:30 10:30-11:30 11:30-12:30
FLow Fluctuation Curve
% ADT From Pathaptha to Russel Square % ADT Russel Square to Panthapath

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CHAPTER 6
CONCLUSION AND RECOMMENDATRION
6.1 Traffic Volume Study from Panthapath to Russel Square draws out the
following conclusion –
On Vehicle Composition-
Vehicle composition of traffic stream shows that the most of the vehicle is light
vehicle and it is about 64% of total traffic. The reason behind this is the area
where we study traffic volume associated with industrial and residential purposes.
The percentage amount of Bus is low. To develop the existing traffic condition it
is suggested that if number of bus is increased by users, traffic congestion may be
reduced efficiently.
The condition of bus is old, rusty and sometimes having broken glass. To facilitate
public transport system, this condition must be developed.
As the light vehicle specially car composition is higher, it is said that most of the
rich people travel this roadway.
On Service Flow Rate-
From Panthapath to Russel Square the peak hour is happened to 10:30 AM to
11:30 AM. It is said that maximum vehicle is approached this road in that time.
From Russel Square to Panthpath the peak hour is happened to 8:30 AM to 9:30
AM. It is said that maximum vehicle is exit this road in that time.
On Directional Distribution-
The distribution of traffic from Panthapath to Russel square is 54.98% which is
higher that the distribution from Russel square to Panthapath 45.02%. From it is
concluded that the approached vehicle is higher than the exit vehicle.
On Flow Fluctuation Curve-
From flow fluctuation curve it is seen that peak is achieved during 8:30 AM to
9:30 AM on both lane.

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From Panthapath to Russel Sqaure flow is gradually decreased.
But from Russel square to Panthapath flow first decreased upto 9:30 AM to
10:30AM . Then it is increase and finally slightly decreased. So here fluctuation is
high.
6.2 Recommendation
Optimum vehicle composition of a traffic flow consists of 30-40% public transport
or BUS
while there was only 6% public transport in our study road.
The buses we observed on the road were too much old that they could not
maneuver easily
although the maneuverability of buses is originally low. So replacing these old
buses with
new ones is highly recommended.
Bicycle should have specific lanes of their own which typically is placed beside
the
footpath/shoulder. But there was not any specific lane in the road we studied. So it
is
recommended that a lane system should be introduced to increase efficiency of the
road at
the same time there should be a bicycle specific lane.
NMT or electrical low speed vehicles should not be permitted in this type of
arterial road.
Although they typically travel on the left lane but they create a drag force which
slows down
the high speed vehicles which creates congestion.
There were some large container trucks observed on the road. Congestion can be
slightly
avoided if these vehicles were allowed only at off peak hours.

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6.3 Limitation
We collected data for representative portion of traffic stream. However if it was possible
to collect data for each and every type of vehicle then a better scenario could have been
presented.
6.4 Future Work
In future the traffic volume study should be implemented through grater time to get more
proper and uniform result. There is more analysis can be added to this traffic volume
study. The reason behind the more people use light vehicle, Car can be find out in this
study.

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REFEREBCES
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3. Arkatkar, S.S. (2011), “Effect of Intercity Road Geometry on Capacity under
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al.pdf (Visiting Date: 01 April 2017)

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11. http://www.caliper.com/glossary/what-is-screenline-analysis.htm
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m
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APPENDIX
Appendix – A Data Collection Table
A.1 Volume Data Table for Individual Vehicle