Base Capacity Estimation of Four Lane Divided Urban
Carriageways under Mixed Traffic Conditions
Abstract:
In India, the rapid boom in industrial and economic development in the urban
areas has led to increased mobility in urban areas. Due to the above, there is an
exponential growth in the number of vehicles plying on the roads. In urban
areas the magnitude and nature of traffic flow will be different from rural areas.
In this regard, knowledge of the roadway capacity is an important parameter for
planning, analysis and operation of roadway systems. Passenger car unit is the
factor used for the conversion of mixed traffic into a common unit by keeping
the passenger car as reference vehicle. It may be noted that the lane capacity
provided in IRC (1990) is obsolete due to the fact rapid strides has been
witnessed during the last decade in the road engineering and vehicle technology
on the urban roads of India. The above radical changes can be attributed as the
primary reason for the increase in the roadway capacity as compared to the
values reported in IRC: 106 (1990). Highway capacity manuals (HCM) from
developed countries may lead to serious prediction errors of traffic performance
if applied directly in developing countries like India, due to homogeneity
condition and lane following behaviour in developed countries. In this paper,
four lane divided road sections located in different urban cities in India are
considered and the basic traffic parameters like speed, density and flow are
estimated and related.
Keywords: Capacity, Passenger car unit, Operating Speed and Urban Roads.
_______________________________________________________________
1.
Introduction
In India, the rapid boom in industrial and economic development in the urban areas has led to increased mobility
in urban areas. Due to the above, there is an exponential growth in the number of vehicles plying on the roads.
In urban areas the magnitude and nature of traffic flow will be different from rural areas. In this regard,
knowledge of the roadway capacity is an important parameter for planning, analysis and operation of roadway
systems. Passenger car unit is the factor used for the conversion of mixed traffic into a common unit by keeping
the passenger car as reference vehicle. The Highway Capacity Manual (HCM) 2000 defines capacity as the
maximum number of vehicles that can pass a given point during a specified period under prevailing roadway,
traffic, and control conditions. Highway capacity manuals (HCM) from developed countries may lead to serious
prediction errors of traffic performance if applied in developing countries like India, due to the absence of
homogeneity in traffic conditions as well as the absence of lane adherence concept due to driver heterogeneity.
This is because the traffic composition and traffic flow in India is vastly different from each other. This may be
due to the absence of lane discipline and the presence of diverse variety of vehicles ranging from smaller sized
motorized vehicles starting from two wheelers to larger sized vehicles like multi axial goods vehicles share the
same road space with the non-motorised vehicles like bicycles, cycle rickshaws and sometimes animal drawn
vehicles. Due to these unusual conditions the parameters like lane utility, speed, capacity reduces drastically.
Prediction and knowledge of capacity for the heterogeneous traffic conditions will provide the basis for
determining the lane width and number of lanes to be provided at any point in a road network with respect to the
volume and composition of mixed traffic. They are valuable tools for the evaluation of the investments needed
for future road construction and improvements, and for determining priorities between the competing projects.
Apart from other parameters, capacity is greatly influenced by roadway and driver conditions. Frictional factors
like lane width, lateral clearance, width of shoulders, horizontal and vertical alignment of the road, presence of
kerb side bus stops, pedestrian crossing, cross roads, etc., will have much influence in the capacity of the roads.
Lane and shoulder widths can have a substantial impact on traffic flow. On narrow lanes, vehicles travel closer
to each other laterally. This may reduce their speed or increase the longitudinal gaps. The capacity is reduced in
the situations where ever the ideal condition does not exist.
2. Literature Review
Conversion of heterogeneous traffic into a stream of homogeneous one by using appropriate Passenger Car
Equivalency (PCE) values is an elementary step for analysing mixed traffic on urban roads. There are several
methods available for the determination of Passenger Car Units (PCUs) namely, headway method,
homogenization, coefficient, semi-empirical method, Walker’s method, and so on. Static PCU values were
proposed in IRC: 106 (1990) based on the percentage of each category of vehicles for the conversion. However,
It may be noted that the lane capacity provided in IRC (1990) is obsolete due to the fact rapid strides
has been witnessed during the last decade in the road engineering and vehicle technology on the urban
roads of India. Moreover, the traffic stream parameters such as vehicular composition, speed and physical
size of vehicle would largely influence the PCU value of a particular vehicle type. Tiwari G et.al (2000) argued
that by adjusting the density method, it is possible to handle heterogeneous traffic and one can derive more
accurate passenger car units for Indian conditions and the data showed the 85th percentile distribution width of
each traffic type can serve as a more accurate measure than the marked lane width when traffic is
heterogeneous. Thereafter, it was proposed that the PCU under heterogeneous traffic conditions was proposed to
be dynamic in nature by establishing a relationship between speed ratio and area ratio of the subject vehicle
(Chandra, et al, 2004). Brooks R. (2010) determined the PCU values by taking the impedance caused by a
vehicle as the basis.
Chandra and Upendra, (2003) estimated capacity of a 7.2 m wide carriageway as 2818 PCU/h which is quite
close to the value of 2,800 PCU/h given in HCM (1994) but lower than the value of 3,200 PCU/h as taken in
HCM (2000). Highway Capacity Manual (HVM) study in China (1999), yielded the base capacity for four lane
divided carriageways as 3200 PCUs per hour. IRC106-1990 provided the design service volume of 3600 PCUs
per hour. By using enveloping curve technique for speed and flow, the capacity of four lane divided road was
found to vary between 3200 - 5300 PCUs per hour for Delhi and 3300 - 5850 PCUS per hour for Mumbai roads
respectively (CRRI, 1988). A comparison of the evolved roadway capacity of four lane divided urban roads in
Thailand and India yielded the capacity values in the range of 2810 - 3010 PCUs per hour and 2239 - 3018
PCUs per hour respectively, (Sinha,2012). Simulation model called HETEROSIM was used to derive PCU
values for different vehicle types and the capacity for one direction of movement of a level four-lane divided
road with 8.75 m wide road space is about 4600 PCU per hour (Arkatkar, 2011). Dhamaniya and Chandra, 2014
provided capacity values for four lane divide roads in the range of 2964 - 4086 PCUs per hour and derived the
relation between lane capacity and operating speed with second degree polynomial trend with the best fit of Rsquare value as 0.98. Himes and Donnell (2010) studied the effect of geometric design features and traffic flow
on operating speeds on four-lane highways.
3. Study Area
This paper covers only four lane divided urban roads. Divided roads are characterized by the presence of
medians, which are permanent barriers to separate conflicting traffic lanes. The candidate sections were
categorized as base / ideal test sections after a thorough reconnaissance study of several roads in the cities of
Delhi (DL), Mumbai (MU), Nagpur (NG), Kolkata (KL), and Roorkee (ROK). To categorize a road section as a
ideal / base section, it need to conform to the criteria of the absence of intersection, bus stops, parked vehicles,
pedestrian movement and any other side friction for about 200m on either direction of travel. The above selected
test sections across varying cities exhibited wide variations in proportions of different categories of vehicles.
Table 1 furnishes the details of study location.
Location
Idealism
Land Use
Carriageway
Width (m)
Friction Type
FLD1_DL
Yes
Commercial
7
Ideal
FLD2_ROK
Yes
Commercial
7
Ideal
FLD3_ROK
Yes
Commercial
7
Ideal
FLD4_NG
Yes
Commercial
7
Ideal
FLD5_NG
Yes
Commercial
7
Ideal
FLD6_ROK
Yes
Residential
7
Ideal
FLD7_ROK
Yes
Residential
7
Ideal
Table 1: Details of the Location
4. Data Collection
The data were collected on the above mentioned test section through videography method covering both peak
and non-peak hours of traffic flow during morning and evening hours. Videos collected in different locations
were decoded to deduce the data on traffic volume and speed based on the longitudinal trap length which is
marked in each location. Figure 1 show the composition of vehicles for a typical location. It can be observed
from the Figure 1 traffic composition is dominated by cars in major metropolitan cities.
Traffic composition (FLD_1)
LCV, 0.7
Mini Bus Buses, 2.4 Truck, 0.3
, 0.3
Cycles, 0.2
Two Wheelers, 23.1
Big Cars, 23.0
Three Wheelers, 8.2
Small Cars, 41.8
Figure 11I Traffic Composition at Typical Location (FLD1_DL)
5. Estimation of PCU
By deriving the relation between the speed and flow, capacity of any type of road section is calculated. In this
basic relationship flow is measured in PCU per hour. Generally by consider
considering
ing the passenger car as common
vehicle the equivalent unit is derived for all other types of vehicles that are called as Passenger
assenger Car Unit (PCU).
In this study speed ratio by area ratio, developed by Chandra and Kumar (2004)) is used for the determination of
PCU. This method is well known as Chandra’s method. Since speed is one of the basic parameter which
represent the true traffic characteristics. Following equation gives the mathematical representation of this
method
Vc * Vi
PCUi = ---------Ac * Ai
Where:
PCUi = PCU of ith vehicle
Vc
= speed of passenger car
Vi
= speed of ith vehicle whose PCU is going to be derived
Ac
= projected area of the passenger car
Ai
= projected area of ith vehicle whose PCU is going to be derived
The passenger car unit determined for the candidate test sections is tabulated in Table 2.
2 The higher values of
PCUs for HCV may be attributed to the low proportion of the goods vehicle due to entry restriction in vogue at
the time of data collection
ction in all the cities. Moreover, the higher PCU values for Bus can be attributed to the fact
speed of the buses is too low
Location
name
TW
3W
Small
Cars
Big
Cars
Mini
bus/jeep/temp
o traveller
Buses
LCV
Truck
FLD_1
0.22
0.93
1.00
1.78
4.16
8.70
2.31
4.50
FLD_2
0.29
1.21
1.00
1.79
4.05
7.28
2.53
5.02
FLD_3
0.28
1.10
1.00
1.71
2.77
6.82
2.45
FLD_4
0.22
0.92
1.00
1.71
2.55
6.05
FLD_5
0.23
0.92
1.00
1.69
2.49
FLD_6
0.25
1.03
1.00
1.77
FLD_7
0.24
1.00
1.00
1.67
Avg
0.25
1.02
1.00
1.73
HCV
Tractor
4.41
6.92
6.24
2.16
4.32
5.37
4.39
5.82
2.12
3.58
5.39
4.06
2.52
6.69
2.24
4.06
2.74
7.50
2.15
4.09
3.04
6.98
2.28
4.28
5.89
4.90
Table 2 Passenger Car Unit (PCU) for study locations
6. Estimation of capacity
Deriving the relationship between the basic traffic parameters like speed, density and flow would help to
determine capacity of any road section. In this study best fitting models were chosen for developing relationship
between speed and density and therea
thereafter the capacity is determined based on Speed - Flow
low relationship which is
derived based on the speed and density relation. In order to derive the relation between speed and flow for
heterogeneous condition, the observed volume is converted in single equi
equivalent
valent unit by multiplying with PCU
given in Table 2. Different models like Greenshield, Greenberg and Underwood models were attempted while
fitting the speed - density relationship as shown in Figure 2. Based on the R2 value, the best fitting model was
selected for the determination of capacity from speed - flow relationship. The speed-flow
flow relation for typical
section is shown in Figure 3. Table 3 provides the best fitting models and derived capacity for each test section.
Speed
Speed-Density Relation(FLD_1)
Speed-Density
Density models
70
Linear (Speed--Density
models)
Expon. (Speed-Density
(Speed
models)
Log. (Speed-Density
Density models)
60
Speed (kmph)
50
40
30
y = -0.183x
0.183x + 56.31
R² = 0.633
20
10
y = 68.19e-0.00x
R² = 0.725
0
-10 0
200
100
300
400
y = -26.9ln(x)
26.9ln(x) + 161.6
R² = 0.733
Density (PCU/km)
Figure 2: Speed-Density relationship for typical location
70
Speed
Speed-Flow Relation (FLD_1)
Speed (kmph)
60
50
40
30
Field Data
20
Modelled Data
Capacity = 4181 PCU/hr
10
0
0
2000
4000
6000
8000
Flow (PCU/hr)
Figure 3 Speed-Flow relationship for typical location
Location
name
R
square
Equation
Model
FLD_1
y = 68.196 e -0.006x
0.7257
Underwood
FLD_2
y = -0.4084x + 83.286
0.1443
Greenshield
FLD_3
y = -0.4175x + 80.616
0.1143
Greenshield
FLD_4
y = 63.53 e -0.0069x
0.2497
Underwood
FLD_5
y = 67.357 e -0.0074x
0.4598
Underwood
FLD_6
y = -0.2032x + 56.747
0.047
Greenshield
Capacity
(PCU/hr)
2972
3242
3147
3666
2912
2907
Operating
speed
(kmph)
Average
Capacity
(PCU/hr)
Average
Operating
speed
(kmph)
1570
64
69
79
76
52
52
61
Table 3: Speed-Density Model and Capacity
Lane Capacity (PCU/hr/lane)
Since the operating speed of the vehicles will have an impact on the capacity, it was felt prudent to develop a
relationship between operating speeds of the vehicles plying in each test sections and the derived lane capacity.
Basically, Operating Speeds were determined from the 85th percentile speed of free flow speed of Standard Cars
at each candidate test section. As such, a standard car (or any vehicle) is assumed as free flowing when it has
headway of 8 seconds or more to the vehicle ahead and 5 seconds or more to the vehicle behind in the same
traffic lane (HCM, 2010). Figure 4 shows the relation between the operating speed and capacity of different
candidate test sections.
2500
2000
1500
y = 14.22x + 1001.
R² = 0.731
1000
500
0
30
40
50
60
70
80
90
Operating Speed (kmph)
Figure 4: Operating Speed vs Capacity
7. Summary and Conclusion
The analysis of this study is based only on field data that has collected on different parts of India. During the
collection almost all vehicle types that are plying in Indian urban rods are considered. Following are the
result/findings from the present study:
• In the case of two wheelers and three wheelers, the PCU values obtained in this study are 0.25 and 1.02
respectively, which is lesser than the values given in IRC: 106 (1990)
• In the case of heavy vehicles like LCV and Heavy Commercial Vehicles, the PCU values obtained in this
study are 2.28 and 4.28 respectively, which is greater than the values given in IRC: 106 (1990). But in the
case of tractors, the value of is found to be consistent with the reported value in IRC: 106 (1990).
• From this study it has been found that the capacity of four lane urban roads is given as and the average lane
capacity is found to be 1570 PCU/hr/lane. This also shows that the increase in capacity as compared to 3600
PCU/hr in IRC: 106 (1990).
• The average operating speed of four lane urban arterial road is found to be 64 kmph.
• The linear relationship have to derived between operating speed and capacity with an R2 value of 0.731 and
the equation which showing the relationship is given below
Lane capacity = 14.222 (Operating speed) + 1001.4
• From the relation between operating speed and lane capacity it shows the marginal increase in operating
speed when there is increase in lane capacity.
• In the relation between speed and density, Greenberg seems to have higher R2 as compared to other model.
In this study, even though Greenberg model is having higher R2 only Greenshield or Underwood model is
used in order to eliminate unrealistic capacity value derived through Greenberg model.
Acknowledgement
The authors of this paper are grateful to Prof. Satish Chandra, Director, CSIR - Central Road Research
Institute for granting his permission to publish this paper.
8. References
1. Arkatkar S S (2011),” Effect of Intercity Road Geometry on Capacity under Heterogeneous Traffic
Conditions Using Microscopic Simulation Technique”, International Journal of Earth Sciences and
Engineering, ISSN 0974-5904, Volume 04, No 06 SPL, October 2011, pp. 375-380
2. Ashish Dhamaniya and Satish Chandra (2014), “Midblock Capacity of Urban Arterial Roads in India” IRC,
Indian Roads-A Review of Road and Road Transport Development, ISSN 0376-7256, Page-39
3. Capacity of roads in urban areas (Sponsored by Ministry of Surface Transport), Central Road Research
Institute of Technology, September 1988
4. Chandra S. (2004). “Capacity estimation procedure for two- lane roads under mixed traffic conditions.”
Journal of Indian Road Congress, Vol.65- 1, pp.139-170.
5. Chandra S and Upendra Kumar(2003), “Effect of Lane Width on Capacity under Mixed Traffic Conditions
in India”, Journal of Transportation Engineering, DOI:10.1061/(ASCE)0733-947X(2003)129:2(155)
6. CHCM (1999) China Highway Capacity Manual. National Highway Project of the People’s Republic of
China.
7. Guidelines for capacity of urban roads in plain area, IRC 106-1990.
8. HCM (2010) Highway Capacity Manual 2010. Transportation Research Board.
9. Himes, S. C., Donnell E. T., & R. J. Porter (2010). Speed Prediction Models for Multilane Highways:
Simultaneous Equations Approach. Journal of Transportation Engineering, ASCE, Vol. 136 (10), pp. 855862. DOI: 10.1061/(ASCE)TE.1943-5436.0000149
10. IHCM (1993) Indonesian Highway Capacity Manual. Directorate General of Highways Ministry of Public
Works.
11. Singhi B and Mokaddes Ali Ahmed (2013), “Evaluation of Roadway Capacity of Four-Lane Divided
Carriageway under Heterogeneous Urban Traffic Conditions”, Proc. of the Intl. Conf. on Advances in Civil,
Structural and Environmental Engineering-- ACSEE 2013, ISBN: 978-981-07-7965-8 doi:10.3850/ 978-98107-7965-8_30
12. Sinha S, Taneerananon P and Chandra S (2012), “A Comparative Study of Effect of Motorcycle Volume on
Capacity of Four Lane Urban Roads in India and Thailand”, Journal of Society for Transportation and
Traffic Studies (JSTS) Vol.3 No.4
13. Brooks, R. M. (2010), “Influence of Roadway Width and V/C Ratio on PCU values”. Transport Problems,
Volume 5, Issue 2, 102-109.
14. Geetam Tiwari, Joseph Fazio and Sri Pavitravas (2000), “Passenger Car Units for Heterogeneous Traffic
Using a Modified Density Method” Transportation Research Circular E-C018: 4th International Symposium
on Highway Capacity.