DOI : 10.17577/IJERTV6IS080130
- Open Access
- Total Downloads : 191
- Authors : Priyanka K P, Vijay B G
- Paper ID : IJERTV6IS080130
- Volume & Issue : Volume 06, Issue 08 (August 2017)
- DOI : http://dx.doi.org/10.17577/IJERTV6IS080130
- Published (First Online): 19-08-2017
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License:
This work is licensed under a Creative Commons Attribution 4.0 International License
Study on Effect of Gradients on PCU and Capacity Factor for Undivided Two Lane National Highway (NH-209)
Priynaka. K. P
-
ech Student, Dept of Civil Engineering MVJ College of Engineering
Bangalore-560067, Karnataka state.
Vijay. B. G
Asst. Professor, Dept of Civil Engineering MVJ College of Engineering
Bangalore-560067, Karnataka state.
AbstractIn India, the quick development in mechanical and monetary advancement in the urban zones. In urban ranges the size and nature of activity stream will be not quite the same as provincial zones. In the respect, information of the roadway limit is a vital parameter for arranging, examination and operation of roadway framework. Passenger car units are used to represent the effect of varying mixed vehicles types on traffic stream. Traffic on congested highways is of the mixed nature to access the different types of vehicles on highways. This study is concerned to determine the PCU values of vehicles under mixed nature traffic flow at congested highways. An intension of this work is to analyze capacity of two lane undivided national highway in heterogeneous condition. For the capacity estimation it is relatively tough to estimate traffic volume on the road. The problem of measuring flow may addressed by using dynamic PCU values. In this present study the complete process of capacity estimation for NH 209 undivided two lanes has been expressed and the result obtained.
Keywords Volume, dynamic PCU, PHF, speed distribution and Capacity estimation
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INTRODUCTION
In India, the length of total road network presently is 4.2 million km still people groups in India, confronting enormous challenges in giving prevalent Vehicular movement stream. As growth in population altered modes of transportation are rises and resulted in congested traffic flow situation on road, for the transport of goods and passengers for short to medium distances roads plays a significant role and road transportation package is much flexible than further modes of transport available. The issue for the estimation of volume of activity measures of vehicles having a place with various sorts identified with its proportionate traveler autos values and communicating its volume basing on Passenger Car Unit (PCU) every hour. It is constantly extremely difficult to figure the association between the vehicles under heterogeneous movement conditions.
Fig 1. Heterogeneous traffic
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OBJECTIVES
-
-
Establishing the relationship between Speed and Volume it is necessary to analyze the spot speed of different vehicles (Car, LCV, HCV, Bus etc.)
-
Determination of Dynamic Passenger car units (PCU), Speed, Peak hour factor (PHF ) and Capacity of different gradients.
-
Comparison of capacity values at selected points (gradients) on two lane undivided national highway between actual capacity and capacity obtained according to Chandras method and linear regression analysis.
-
LITERATURE REVIEW
Dr.Satish Chandra has studied Capacity Estimation Procedure for Two-lane Roads under Mixed Traffic Condition. in his paper stated that the objective is to determine the PCU, grade percentage in both up and down movements, directional split, effects of grade, lane width, and road roughness. The results show that there is 2.61% decrease of capacity in upgrade and 3.09% increase in capacity in downgrade. Pothula sanyasi Naidu studied Capacity of road with vehicle characteristics and road geometrics . In this paper stated that the objective in studying variation in capacity with respective various width of road elements. Results obtained shown that the variation in capacities calculated in two methods are not more than 10%. Dr.B.V.Khode studied that Impact of lane width of road on passenger car unit capacity under mix traffic condition in cities on congested highways. The objective is to estimate the value of PCUs for mixed traffic condition of moving vehicles in the traffic flow. The capacity of a 7.2 m wide road in pcu values is estimate 3348.48 pcu/h which is larger than the value of 3,200 pcu/h suggested in HCM 2000. Deepika Mohan studied that Study on effect of gradient on stream equivalency factor for undivided two lane highways. To develop stream equivalency factor for undivided two lane highways with the main focus in its effect on varying gradient. The result from four sites a model for predicting SEF values were developed and the same was found valid for the fifth site.
Study area: The study was carried out on NH-209 of Kanakapura city in south part of Bangalore city. To meet the study requirements specific study sites are chosen from the various section of national highway stretches of Bangalore. To develop the capacity estimation of traffic volume primarily 3 sites were chosen.
-
DATA COLLECTION / EXTRACTION: Analysis for the estimation of capacity is carried out for the gradient section at Kanakapura road of national highway-209. The traffic studies were carried out to determine the traffic volume, average daily traffic (ADT), composition of traffic stream, and the speed of different types of vehicles at the selected road sections. The traffic volume survey is carried out on typical weekdays and weekends for a period of 12 hours from morning 7am to 7pm for 7 days on each site.
GEOMETRIC DETAILS
Site
Gradient 1
Gradient 2
Gradient 3
Study stretch
NH 209
NH 209
NH 209
Location
Hanumantha
nagara
Thoppaganahalli
Jattipalahalli
road
Direction
Bangalore towards
kanakapura
Bangalore towards
kanakapura
Kanakapura towards
malavalli
Carriageway condition
Undivided
undivided
undivided
Number of
lanes
2
2
2
Width of carriageway
7.13m
7.06m
7.6m
Sl
no
Gradients
Slope
Grade%
1
Gradient 1
1 in 17
5.88
2
Gradient 2
1 in 40
2.5
3
Gradient 3
1 in 17
1.11
Table 1. Geometric details of selected site GRADIENT CALCULATION
Table 2.Gradient calculation
ANALYSIS OF DATA: The rectangular projected area of different vechicles are shown below.
Sl
no
Category
Dimension
Projected
area
length
breadth
1
Car
3.72
1.44
5.39
2
Bus
10.10
2.43
24.74
3
Truck
7.50
2.35
7.62
4
LCV
6.10
2.10
12.81
5
HCV
2.35
12.0
<>28.60 6
Bikes
1.87
0.64
1.20
7
Cycle
1.90
0.45
0.85
8
Auto
3.20
1.40
4.48
Table 3.Rectangular projected area of vehicles
CHANDRAS method PCU = (Vc / Vi)
(Ac / Ai)
ADT AND PERCENTAGE COMPOSITION
Types of Vehicles
ADT
% composition
Total Vehicles
towards Bangalore (descending gradient)
towards Kanakapura (ascending gradient)
towards Bangalore (descending gradient)
towards Kanakapura (ascending gradient)
cars
5111
5265
21.37%
28.03%
LCV
7233
2271
30.25%
12.09%
HCV
310
297
1.30%
1.58%
buses
1412
1261
5.90%
6.71%
2w
9846
9691
41.18%
51.59%
Total
Vehicles
23912
18785
100.00%
100.00%
percentage
Table 4.Percentage composition
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
cars lcv hcv buses 2w
type of vehicles
Fig 2. Bar chart of percentage composition
Traffic volume variation graphs: The volume count has been done for 7 days on each gradient and then converted into average daily traffic (ADT) . Then the traffic volume variation graphs are drawn .
ascending
gradient
descending
gradient
1600
1400
1200
1000
800
600
400
200
0
Fig 3.Traffic volume variation of Gradient 1
1400
1200
1000
800
600
400
200
0
descending
gradient
1200
1000
800
600
400
ascending
gradient
07.00am to 08.00am 08.00am to 09.00am 09.00am to 10.00am 10.00am to 11.00am 11.00am to 12.00am 12.00pm to 01.00pm 01.00pm to 02.00pm 02.00pm to 03.00pm 03.00pm to 04.00pm 04.00pm to 05.00pm 05.00pm to 06.00pm 06.00pm to 07.00pm
Fig 4 .Traffic volume variation of Gradient 2
SL NO
GRA DE
%
SPEED (kmph)
CARS
BUSES
2W
LCV
HCV
1
+5.88
56
39
50
38
32
2
+2.5
58
41
53
40
35
3
+1.11
60
48
58
42
38
4
-1.11
68
57
79
53
41
5
-2.5
69
66
81
55
44
6
-5.88
70
68
83
56
45
Table (a)
SL NO
GRADIENT
%
PCU
CARS
BUSES
2W
LCV
HCV
1
+5.88
1
6.59
0.25
3.50
5.72
2
+2.5
1
6.49
0.24
3.45
5.42
3
+1.11
1
5.74
0.23
3.40
5.16
4
-1.11
1
5.48
0.192
3.05
5.42
5
-2.5
1
4.80
0.190
2.98
5.13
6
-5.88
1
4.72
0.188
2.97
5.09
Table (b)
Sl no
Grade %
Actual Vol.
Capacity (Chandras Method)
Capacity (Regressi on Analysis) based on
grade
Error b/w both method s (%)
1
(+)5.88%
606
866
806
6.92%
2
(+) 2.5%
687
816
817
0.12%
3
(+)1.11%
659
793
824
3.76%
4
(-)1.11%
573
621
750
17.2%
5
(-)2.5%
633
766
720
6.0%
6
(-)5.88%
787
912
713
21.8%
Table (c) Capacity Estimation by Chandras Method
ascending
gradient
200
0
descending
gradient
07.00am to
09.00am to 11.00am to 01.00pm to 03.00pm to
05.00pm to
Fig 5.Traffic volume variation of Gradient 3
Effect of Grade: The PCU values of different types of vehicles are given in table (a). Speed of the vehicles is given in table (b). The capacities with grade at different sections are also noted in table(c).
GRADIENT
Total lane width
Vehicle type
VOLUME
PCU
CAPACITY
(vol/hr)
descending
ascending
descending
ascending
Descending
ascending
Cars
245
195
1
1
Buses
58
39
4.72
6.59
5.88%
7.6
LCV
77
70
2.97
3.5
912
866
HCV
18
17
5.09
5.72
Bikes
389
285
0.18
0.25
Cars
194
189
1
1
Buses
33
45
4.8
6.49
2.50%
7.13
LCV
77
74
2.98
3.45
<>766 816
HCV
11
15
5.13
5.42
Bikes
365
298
0.19
0.24
Cars
173
196
1
1
1.11%
7.13
Buses LCV
30
58
36
72
5.48
3.05
5.74
3.4
621
793
HCV
9
13
5.42
5.16
Bikes
303
342
0.19
0.23
Table 5. Calculation of Capacity
PCU variation with respective speed
Fig 6. PCU variations on descending gradients
Fig 7. PCU variations on ascending gradients
capacity
Capacity variation with respective grade %
capacity variation at descending gradients
1000
y = 57.689x + 583.85
800
X= Grade
600
400
capacity
200
0
0
2
4
grade %
6
8
Fig 8. Capacity variation on descending gradients
capacity variation at ascending gradients
880
860 y = 15.209x + 776.89
840
820
800
780
X = Grade
capacity
0 1 2 3 4 5 6 7 8
grade %
capacity
Fig 9. Capacity variation on ascending gradients
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RESULTS
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After seven days of volume count the average percentage of vehicles in the total volume shows majority of two wheelers i.e.46.38%, cars 24.7%, LCV 21.17%, buses 6.3%, HCV 1.44%
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The average spot speed of all vehicles are tabulated and speed is found to be varying i.e. while vehicles travels on ascending gradient the speed is getting reduces as the % gradient increases and vice-versa.
-
PCU values for different types of vehicles at different sections on varying gradients are found as per Satish Chandras method and it is observed values are varying at ascending and descending gradients even though lane width is same i.e. only because of speed variation.
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Attempts have been made to develop linear regression equation to obtain capacity for two lane undivided optional highways based on lane width and % difference of gradient.
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The equation obtained are as follows, capacity based on lane width at ascending gradient is y=256.25x-107.75 and descending gradient is y=910.42x-2547.6 and capacity based on grade % at ascending gradient is y=15.209x+776.89 and descending gradient is y=57.689x+583.85.
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CONCLUSIONS
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The width of carriageway at three different gradients varies the PCU values and capacity of the road.
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After analyzing the collected data we determined PCU values which varies according to the speed of a vehicles on both ascending and descending gradients.
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The capacity is estimated by considering 2 methods i.e. Chandras method and linear regression method.
SCOPE OF FUTURE WORK
-
The studies can be made at intersections, curves and bus stops.
-
By the collected data we can develop capacity modal at different location on highways.
-
To calculate PCU we have consider only frontal area of vehicle we may extend our work considering carriageway, roughness and driver characteristics.
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In this work we have compared the actual capacity for 2 methods Chandras method and linear regression method. This work can be extended with other methods.
REFERENCES
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Dr.Satish Chandra Capacity Estimation Procedure for Two- lane Roads under Mixed Traffic Condition. Indian Road Congress paper no.498(December 2004).
-
A.R.Khanorkar , S.D.Ghodmare ,Dr B.V.Khode , Int.Journal of Engineering Research and Applications, ISSN:2248- 9622,May2014,pp 180-184. www.ijera.com
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Dr.B.V.Khode Impact of lane width of road on passenger car unit capacity under mix traffic condition in cities on congested highways.
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Pratik U.Mankar Capacity estimation of urban roads under mixed traffic condition(2016),(e- ISSN:2395-0056, p- ISSN:2395-0072), www.irjet.net.
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Deepika Mohana,Bino I Koshyb,Anusha S Pc Study on effect of gradient on stream equivalency factor for undivided two lane highways.
-
Prof. Nikhil Raval Development of speed-Density relationship for the urban area A case study of Ahmedabad city
-
Hemanth M Kamplimath Capacity estimation for a two lane undivided carriage way A case study for national highway- 63,4th International Conference on Science, Technology and Management, India International Center ,New delhi,(ICSTM- 16), ISBN:978-81-932074-8-2,pg 660-668
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V. Thamizh Arasan , " Micro simulation Study of Effect of Volume and Road Width on PCU of Vehicles under Heterogeneous Traffic".ASCE,(2010).
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K.K. Laxman, Pedestrian Flow Characteristics in Mixed Traffic Conditions, Journal of urban planning and development(2010)