PCU Standards for Sri Lanka Highway Design

Amal S. Kumarage, BSc(Eng.), PhD, MCIT, AMIE(SL)

Paper Presented at the Annual Sessions

Institute of Engineers Sri Lanka

October 1996

i

Abstract

The Passenger Car Unit (PCU) value is a extremely sensitive parameter in highway capacity design.

Each country has its unique. PCU values depending on vehicle mix by type, make and age, road

design and driving habits.

This study attempts to establish statistically acceptable values for different traffic movements, and

design of highways in Sri Lanka. Suitable vehicle groupings have been identified to determine, the

appropriate PCU values. Mean values have been calculated for use in highway design and feasibility

studies in Sri Lanka. A comparison with homegenity modelling has also been carried out, together

with values from other countries.

1

1. INTRODUCTION

Passenger Car Units (PCUs) have been consistently used in traffic and highway design and planning

exercises around the world. They are popular among planners due to their simplification nature

whereby they convert operational characteristics of different vehicles into equivalent passenger car

units. Highway design manuals such as the Highway Capacity Manual are all based on PCU factors

for different vehicle types. Therefore, the accuracy of the PCU factors is generally a very important

aspect of highway planning as capacities and levels of service computations are extremely sensitive to

the PCU values ascribed to the different types of vehicles.

This importance is even greater in developing countries such as Sri Lanka, which have a very high

proportion of non-car vehicles. In developed countries, cars constitute between 70-80% of the traffic

flow. In Sri Lanka, it is only around 20-30%. Thus the correctness of the factors given for the non-car

vehicles is much more important in Sri Lanka.

Unfortunately, estimating the correct PCU values is not as easy a task as using them. This difficulty

arises, because there are no universal PCU values that can be used across different countries. Each

country will have its unique PCU values depending on vehicle mix by type, make and age, road

designs, driving habits etc. While a general idea prevails regarding the range of PCU values for Sri

Lanka, an exhaustive study which examines the PCU and its variations for the Sri Lankan context

have not been documented.

2. METHODOLOGY

There are several methods available for the estimation of PCU's. Under broad headings, they will

either determine the PCU value based on the effect on speed of other vehicles (such as under free

flow) or based on the effect of road capacity (such as under saturated flow).

2.1 Speed-Flow Method

This is considered as an indirect method of determining the relative PCU values by using the speed-

flow relationship. In this method, the mean observed speed of one vehicle type is given as the

dependant variable and regressed against observed flow being the independent variable. This

relationship derived from the speed-flow relationship can be shown as follows:

Q-C=V jjj β

2

where

V j is the observed mean space-mean speed of the vehicles of type j,

Q is the observed flow rate in PCUs per hour,

C j is the theoretical mean free speed of vehicle type j under free flow conditions,

βj is the rate at which speed of vehicle type j will diminish for a unit increase in flow rate.

2.2 Simulation

Computer based simulation techniques can also be used to model the PCU of a given vehicle type

under different flow conditions. These approaches however need prolonged study and development

and should be supported by large data bases on which they can be calibrated. Such databases are not

available in Sri Lanka.

2.3 Headway Method

This method is based on the simple relationship between volume and headway that

The relationship between headway and time leads to the relationship between volume and time given

as

Where

t i - time taken by platoon i,

qij

- number of vehicles of type j in platoon i,

C - constant time loss per platoon,

α j - flow rate (secs/veh) for vehicle type j.

y(h)TimeHeadwa

1=Volume(Q)

q+c=t ijji ∑α

3

3. DATA COLLECTION

The data collection process comprised of several components. These were:

(a) Measurement of Saturated Flow at Signalised Intersections (3 locations).

(b) Measurement of Saturated Flow at Roundabouts (4 locations).

(c) Measurement of Speed-Flow Relationship on Highways (14 locations).

3.1 Measurement of Saturated

Flow at Signalised

Intersection

Three intersections in Colombo, Sri Lanka were subjected to these surveys. These are:

SI-1 Dickman's Road/Galle Road (at Bambalapitiya)

SI-2 DS Senanayake Rd/Castle St (at Borella)

SI-3 Armour Street/Jetawana Rd (at Armour St)

The number of vehicles moving as a platoon under saturated flow condition on each turning

movement were recorded together with the time taken for that platoon movement. The vehicles and

pedestrian activity was classified into 16 different types.

The turning movements have been classified as:

(i) Through Only (TO)

(ii) Shared Through & Left (STL)

(iii) Shared Through & Right (STR)

(iv) Shared Through, Left & Right) (STLR)

(v) Left Turn Only (LO)

(vi) Right Turn Only (RO)

(vii) Shared Left & Right (SLR)

The vehicles have been classified as:

1.

Mot

4

or

Cyc

les:

All

mot

or

cycl

es

excl

udi

ng

chal

lys.

2. Three Wheelers: All three wheel

vehicles.

3. Cars & Station Wagons: All four wheel covered

vehicles up to station wagons, but not including Pick

ups, Jeeps & Vans.

4. Vans : Pick Ups, Jeeps and

Vans up to and including the size of the Toyota Hi

Ace (new model).

5. Light Trucks: All four wheel

lorries larger in size than a van typified by the four

wheel Isuzu 150.

6. Medium Trucks: All lorries in the 4-6

tonne category which have six wheels and typified

by the TATA 1210 or Isuzu 250.

7. Large Trucks, Containers

Land Vehicles: All trucks with more than six wheels.

5

8. Mini Buses: All vehicles

designed for the carriage of passengers larger in size

than the biggest Van (Toyota Hi Ace), upto and

including the single door TATA 909.

9. Buses: All buses larger in

size than the single door TATA 909.

10. Carts: Animal drawn or

hand cart with a vehicle floor area of more than 0.5

m sq.

11. Bicycles:

3.2 Measurement of Saturated Flows

at Roundabouts

The details of the four locations selected are as follows:

RA-1 Slave Island

RA-2A Galle Face (Near Hotel)

RA-2B Galle Face (Near Old Parliament)

RA-3 Panchikawatte

Unlike at signalised intersections, at roundabouts, flows are not at regular intervals and the observers

recorded separately for each occurrence of saturated flow condition, the number of vehicles using a

particular section of the roundabout and the time taken to complete the platoon flow of the section of

roundabout.

6

3.3 Measurement of Speed-Flow Relationships on Highways

The 14 locations selected are as follows:

SSCP Charles Place, Lunawa, Moratuwa. A typical straight section of this

one-lane highway, which is used by the No. 208 bus route.

SSAR1 Attidiya Road, at Ratmalana, which is an intermediate lane (1 & 1/2 lane)

highway. This location represents zero curvature and zero gradient.

SSAR2 Attidiya Road, at Attidiya, where this location represents high road side

development and moderate curvature and gradient (both rise (+) and fall (-)).

SSAR3 Attidiya Road, at Attidiya, where this location represents, low curvature and

+ gradient.

SSHR1 Horana Road, at Bokundara, representing a zero curvature, zero gradient

section of this two-lane highway, which was recently rehabilitated.

SSHR2 Horana Road, at Bokundara, representing rolling terrain of moderate gradient

and moderate curvature.

SSHR3 Horana Road, at Werehera, representing sections of straight road, curvatures,

gradients and bus stand.

SSKR1 Kandy Road, at Imbulgoda, representing a two-lane highway with

broad shoulders. This location represents very low curvature and zero

gradient.

SSKR2A Kandy Road at Ambanpitiya, representing high curvature and + gradient.

SSKR2B Kandy Road, at Ambanpitiya, representing high curvature and - gradient

(direction opposite to SSKR2A).

SSKR3 Kandy Road, at Nelundeniya, representing, zero curvature and +

gradient.

SSGR1 Galle Road, at Wellawatte, representing a four lane divided highway, recently

rehabilitated. This location represents a bus stop without a bus bay.

SSGR2 Galle Road, at Wellawatte, representing a bus stop with a bay.

SSGR3 Galle Road, at Ratmalana, representing the un-rehabilitated road with a bus

halt.

7

Two methods were employed for this purpose.

(a) Classified Movements

Since these surveys involved a particular section of road, the movements observed were always

through traffic. The flow, classified by vehicle types was recorded and totalled at intervals of 1-3

minutes, depending on the flow. For locations of heavy flow such as on Galle Road, totalling was

done every 1 minute and on low flow roads every 3 minutes. For undivided highways, the total flow

in the direction opposite to that of the surveys was recorded. The number of vehicles parked on the

road or on the shoulder was also recorded.

(b) Vehicle Speed Measurements

In the vehicle speed measurements, two sets of observers were stationed at distances varying from

180 metres to 750 metres. Both sets of observers used synchronised electronic stop-watches which

were checked both before and after each session of observations. The observers recorded the last two

digits of the registration plate no. (eg. 94 for vehicle bearing number 20 -3994) against the time on the

stop watch in the correct column for the particular vehicle type.

4. ANALYSIS

The analysis of the data was be carried out for each type of location separately.

4.1 Signalised Intersections

The assumption made in this analysis is that vehicles being discharged from a traffic signal will leave

at capacity or saturated flow conditions. However, the number of vehicles being discharged with each

green light will vary with the composition of the flow. For example, during a given green time, more

passenger cars will be able to pass the intersection than larger vehicles. This relative rate will

constitute the PCU value for an intersection under saturated flow conditions. The basic approach to

this method was introduced as the Headway Method in Section 2.3.

In the analysis, the time taken for each platoon of vehicles moving under saturated flow conditions to

leave the intersection has been analyzed against the number of vehicles in that platoon by type. The

analysis has been made using multiple linear regression where the dependant variable is the time

taken and the independent variables being , the number of vehicles in each category observed for each

platoon. The regression equation given as Equation 3 was used to obtain results of the multiple linear

8

regression for each turning movement at each of the three signalised intersections studied, amounting

to a total of 14 equations. The higher the R2ad and lower the F-statistic, the better is the fit of the data

to the equation. For the individual t-statistics, the closer it is to zero, the greater is the evidence that

the coefficient obtained is reliable. In general practice, coefficients of over 10% have not been

considered at all. Even then, only those with t-statistics of 5% and less can be considered for

prediction purposes. A total of 18,122 vehicle observations have been used in the PCU estimation of

signalised intersections.

The high level of variation of PCU estimates between different intersections indicates the non-

uniformity of conditions among intersections. For planning purposes, a more general PCU value

would be more desirable. Hence, the PCU values of similar turning movements but from different

intersections have been aggregated and the mean and coefficient of variation given in the Table 1.

The coefficient of variation is the percentage value of the ratio between the standard deviation and the

mean value of the different PCU values. Hence the smaller it is the more evidence there is to

consistency in values. As seen in Table 1, the coefficients of variations go upto 60%. This is not

unusual given the differing conditions at signalised intersections. In general, a high amount of

confidence can be placed for coefficients of variation of 20% and less. The last row on Table 1,

shows the mean of all types of turning movements, which is the best single PCU value we can arrive

at for signalised intersections in general. However, we can observe that such general values are not

very reliable and should be used only for very broad planning purposes and not for specific designs.

9

Table 1

10

4.2 Analysis of Roundabouts.

An approach similar to that of signalised intersections is made for roundabouts. The time-headway

Equation 3 was used to obtain results of the multiple linear regression for each turning movement at

each of the four roundabouts studied, amounting to a total of 13 equations.

Unlike in the case of signalised intersections, it can be seen that common PCU values can be

estimated with reliability for each roundabout. The Coefficient of Variations being very low between

different arms of the roundabout as well as between different roundabouts. This entertains evidence to

the ability of using a single PCU value for all roundabouts. The summary for all roundabouts is given

in Table 2. A total of 13,312 vehicle observations have been analyzed in arriving at these values.

Description of Flow

No of

Cases

Rate

for

Cars

Vehicle Type

Ranges

Cart

Byc

Mt.

Byc

3W

Car

Van

Mini

Bus

Bus

Lt.

Tk.

Md.

Tk.

LLg.

Tk.

Time

(Secs)

Veh

Roundabouts RA1 (Slave Island)

350

2250

-

0.65

0.72

0.86

1.00

1.16

1.25

2.68

1.51

1.83

-

7402

4665

RA2A (Galle Face -

Parliment)

183

3675

-

1.54

0.71

0.67

1.00

1.12

1.71

2.08

2.83*

2.05

3.51

3988

3419

RA2B (Galle Face -

Hotel)

192

3790

-

1.00

0.83

1.22

1.00

1.27

1.73

1.88

3.34*

2.24

6.08

3596

3159

RA3 (Panchikawatte)

253

4130

3.76

1.04

0.85

0.74

1.00

1.14

1.58

2.34

1.53

2.05

4.18

2145

2069

ALL

3.76

1.06

0.76

0.87

1.00

1.17

1.57

2.24

1.52

2.04

4.59

17,131

13,312

-

-

-

30%

8%

24%

-

4%

12%

13%

0%

7%

24%

-

-

Table 2 : Summary of PCU Values for Roundabouts

4.3 Analysis of Link Sections of Highways

The flow surveys is a speed based, indirect method of measuring the PCU's. This approach is

described under Section 2.1. This is the most suited for link sections of highways, where saturated

flow conditions do not occur. It is particularly well suited for highways wherein large speed variations

occur. In this approach, the space-mean-speeds of individual vehicles is recorded together with the

flow rate and its distribution at the time the particular speed observation was made. Grouping of these

speed measurements by vehicle type will yield a mean speed for a particular type of vehicle. This can

be analyzed with the mean flow conditions during the observation period.

To overcome problems of multi-collinearity, Equation 1 has been modified (transformed) as follows:

11

where

The above equations have been even further modified to account for the effects due to the opposing

flow and parked vehicles. This now reads

where

qpk

is the number of vehicles parked per km of road during the observation period

qopp

is the flow of vehicles in opposing direction (not PCU's).

The vehicle classification maintained in the previous sections (for roundabouts and signalised

intersections) was found to be too disaggregate for purposes of this analysis. Hence some amount of

aggregation of groups has been done to facilitate the regression. The aggregated groups are as

follows:

Carts

Bicycles

Motor cycles (including challys)

Three Wheelers

Cars & Vans

Buses (including minibuses)

Trucks (Light & Medium )

Heavy Trucks, Containers & Land Vehicles

A total of 16 regressions have been made for car based equations, where the base vehicle type j is the

aggregated car/van vehicle type. Of these 16 equations, two have been made for congested flow

conditions and the others for uncongested flow conditions. Furthermore, two truck based and two bus

based equations have also been calibrated making a total of 20 equations. A total of 44,141 vehicle

........+Q

q+

Q

q=

Q

C-V 2

2

1

1

jjββ

q=Qj

∑

.Q

q+

Q

q+

Q

q=

Q

C-V op

op

pk

pk

j

j

jjβββ∑

12

observations have been used in this analysis.

The large number of `un-estimatable' PCU's do not permit a comprehensive analysis of the PCU

change with road types, road geometry etc. However, mean PCU values can be estimated for general

planning purposes. These are given in Table 3, where the mean of the PCU estimates together with the

corresponding coefficient of variation are given. These also have been aggregated to a common car

base, truck base and bus based means, which in turn have been aggregated to arrive at a weighted

PCU mean for all roads.

4.4 Summary of Empirical PCU Computations

The summary of the PCU computations arrived by empirical means of the regression analysis of the

data described earlier are given in Table 4. This has been presented for roundabouts, signalised

intersections, and four different types of highways. It may be observed that there are several cells in

this table that are incomplete due to deficiencies in the data and/or analysis.

4.5 Comparison with PCU estimates by Homogenity Coefficient Modelling

A comparison is made of these empirically determined PCU values with those determined from the

modelling by homogenity coefficients (Kumarage, 1996).

From Table 4 we can see that except for the PCU values for three wheelers on one lane highways (0.6

vs. 1.2) and the PCU values for large vehicles on four lane highways (5.3 vs 3.4), the other values are

extremely well fitting. Since we can place confidence in both approaches, we can use an approach of

obtaining a mean value as the recommended PCU value. In the two cases where there were significant

discrepancies, the model value has been accepted, since it can be held that the empirical values can be

inaccurate especially given the fact that the number of observations in both three wheeler and large

vehicle category were quite small. The recommended PCU values for Sri Lanka are given in Table 5.

13

Description of Flow

Vehicle Type

Cart

Byc

Mt. Byc

3W

Car Van

Bus

Truck

CT & LV

SSCP (Car Based) (One Lane)

6.3

0.5

0.2

1.2

1

n/a

n/a

n/a

SSAR1 SSAR2 (Car Based) SSAR3

n/a

0.7

0.6

1.6

1

2.5

2.1

2.2

(Intermediate Lane)

-

9%

3%

-

-

70%

18%

-

SSHR1 SSHR2 (Car Based) SSHR3

n/a

n/a

0.4

n/a

1

1.8

1.3

-

(2 Lane)

-

-

19%

-

-

-

8%

-

SSKR1 SSKR2 (Car Based) SSKR3

n/a

0.7

n/a

n/a

1

1.8

1.6

3.0

(2 Lane)

-

-

-

-

-

4%

16%

29%

Overall (Car Based)

6.3

0.7

0.4

1.2

1

1.9

1.7

3.5

-

20%

35%

27%

-

19%

17%

38%

SSGR1 SSGR2 SSGR3 (4 Lane)

Car (Based)

1.8

0.9

0.5

0.8

1

1.5

1.6

5.4

-

-

29%

3%

-

40%

3%

24%

Buses (Based)

4.1

1.6

0.8

n/a

1

1.5

1.3

-

Trucks (Based)

-

0.6

0.4

0.9

1

1.9

1.4

5.1

All (Based)

5.2

1.0

0.5

1.1

1

1.8

1.5

4.3

Table 3 : Summary of PCU Values for Highway Section

Type of Road Section

Cart

Bicycle

Motor Bicycle

3 - Wheel

Car

Van

Mini Bus

Bus

Lt Tk

MdTk

LgTk

1. Roundabouts

Empirical

3.8

1.0

0.8

0.9

1.0

1.2

1.6

2.2

1.5

2.2

4.6

Model

3.8

1.0

0.6

0.9

1.0

1.0

1.6

2.2

1.5

2.0

4.1

2. Signals

Empirical

4.0

0.8

0.6

0.8

1.0

1.1

1.4

2.2

1.7

2.1

5.4

Model

3.6

1.0

0.5

0.9

1.0

1.0

1.7

2.5

1.6

2.2

4.9

3. Highways

Cart

Bicycle

Motor Bicycle

3 Wheel

Car

Van

Mini Bus

Bus

Lt. Tk.

MdTk.

Lg. Tk.

3.1 Single Lane

Empirical

6.3

0.5

0.2

1.2

1.0

n/a

n/a

n/a

Model

6.0

0.6

0.2

0.6

1.0

2.6

2.1

5.7

3.2 Intrm Lane

Empirical

n/a

n/a

0.4

n/a

1.0

1.8

1.3

n/a

Model

n/a

n/a

n/a

n/a

n/a

n/a

n/a

n/a

3.3 Two Lane Undivided

Empirical

n/a

0.7

0.4

n/a

1.0

1.8

1.5

3.0

Model

2.5

0.7

0.4

0.8

1.0

1.7

1.6

3.1

3.4 Four Lane Divided

Empirical

3.3

1.0

0.6

0.9

1.0

1.7

1.4

5.3

Model

4.0

1.0

0.5

0.8

1.0

1.7

1.6

3.4

Table 4 : PCU Estimates Obtained Empirically and By Modelling

14

Table 5 : Recommended PCU Values

Type of Road Section

Cart

Bicycle

Motor Bicycle

3 - Wheel

Car

Van

Mini Bus

Bus

Lt. Tk.

Md. Tk.

Lg. Tk

1. Roundabouts

3.8

1.0

0.7

0.9

1.0

1.2

1.6

2.2

1.5

2.0

4.4

2. Signals

3.9

0.9

0.6

0.8

1.0

1.1

1.5

2.3

1.7

2.1

5.2

3. Highways (Plain & rolling terrain)

Cart

Bicycle

Motor Bicycle

3 - Wheel

Car

Van

Mini Bus

Bus

Lt. Tk.

Md. Tk.

Lg. Tk.

3.1 Single Lane

6.1

0.5

0.2

0.6

1.0

2.6

2.1

5.7

3.2 Intrm Lane

n/a

n/a

0.4

n/a

1.0

1.8

1.3

n/a

3.3 Two Lane Undivided

2.5

0.7

0.4

0.8

1.0

1.8

1.5

3.0

3.4 Four Lane Divided

3.7

1.0

0.6

0.9

1.0

1.7

1.5

4.0

5. CONCLUSIONS

5.1 Discussion on PCU Values

The values in Table 5 are intuitively quite plausible, though there appear to be a few items of surprise.

The general pattern of increasing PCU with size of vehicle is seen quite consistently. The only

exception is that of the bicycle which in all cases demonstrates a higher PCU than the motor cycle.

5.1.1 Carts

The range of PCU values obtained for the carts is between 2.5 and 6.1. There is near equality of

around 4 for saturated flow conditions. On one lane highways we can expect this value to increase due

to the difficulties motor vehicles encounter in passing slow moving carts. A value of around 6 appears

reasonable. This passing difficulty decreases for two lane highways. Therefore, the value of 2.5

obtained for two lane highways appears acceptable. This pattern however changes for four lane

highways where it is seen to increase to 3.7. This actually arises due to the consideration of an overall

(Car/van, bus, truck) based PCU value (PCU values considered for one and two lane highways were

only car/van based). As discussed earlier, we observed that the PCU effect of carts on buses and

trucks was greater than that of the carts on passenger cars and vans.

5.1.2 Bicycles

Generally, international PCU norms consider a bicycle in the range of 0.2-0.3 (a large number of

studies ignore cycles altogether). However, the results for Sri Lanka show a consistently higher value.

As in the case of carts, there is a near equality of around 1 as a PCU value for bicycles under saturated

flows. This value decreases for one-lane highways. This is understandable, since the low traffic

15

volumes on these roads enables larger vehicles to travel at the centre of the road thus reducing the

impact that bicycles have on their movement. For two lane highways this value increases. This

appears to be counter intuitive. However, if one were to forward the argument that on two lane

highways faster vehicles cannot find gaps in oncoming flows as easily as they do on one lane

highways, there could be a possibility that the PCU of a bicycle on a two lane highway could be

greater than that on a one lane highway. Another factor is that faster vehicles travel at much greater

speeds on two lane highways than they do on one lane highways, whereas any increase in the speed of

bicycles will be only marginal. Thus the reductions necessary in the speeds of faster moving vehicles

will be greater on two lane highways than on one lane highways. For four lane highways, we again

observe a pattern similar to that of the carts, where the PCU of bicycles on buses was found to be

higher than on cars. The observation that on divided highways some cyclist tend to keep to the right

hand side curb may also add to the increased PCU value. Moreover, even those who do use the left

hand side often keep a good 2-4 metres away from the curb to avoid uneven pavement conditions,

parked vehicles and bus stops.

However, even after considering all these arguments it is rather difficult to accept a PCU value of

around 0.7-0.8 for bicycles. This could be on the one hand, partly due to the fact that traffic and

transport planners have consistently ignored the bicycle or have given it token PCU values have

created to road geometry which is not designed for bicycles. On the other hand, we cannot ignore the

findings of this analysis and choose to reduce the PCU value obtained for bicycles while accepting the

others as they are. Therefore it is recommended that these values be accepted. If this were to be done,

the impact of bicycles in highway design will have to taken much more seriously than it is at present.

5.1.3 Motor Cycles

The values obtained for Motor Cycles are not surprising in anyway, except the relatively high values

seen at roundabouts and signalised intersections. A value of around 0.6-0.7 seems more appropriate

for intersections as compared to the value of around 0.4 for highways. In the case of highways, we see

that the PCU value increases from 0.2 for a one lane highway to 0.6 for the four lane highway. This

increase could be attributable to the same reasons cited for the bicycle, albeit at a much lesser degree.

5.1.4 Three Wheelers

The analysis of three wheelers has returned quite close PCU values of between 0.6 to 0.9 for all road

operations. The general idea that a three wheeler will yield a PCU value between a motor cycle and a

passenger car has been confirmed in these results. As in the case of bicycles and motor cycles, we

observe that three wheelers also show near equal PCU values at intersections, and reduced values on

one lane highways while increasing for wider roads.

16

5.1.5 Cars & Vans

As suggested earlier, there appears to be no problem in considering the car plus van category of

vehicles as the common base for PCU considerations. At intersections, the difference in PCU

estimates has been only a maximum of 20% for vans over cars. Though values for the highways are

not available, it is anticipated that this would be less; probably in the 5-10% range.

5.1.6 Minibus & Buses

In the section of analysis on the highways these two groups have been considered together. Overall

the bus to minibus observed flow ratio is around 1: 3. At intersections, we observe that a bus has a

PCU value about 50% more than a minibus. On highway sections we can expect this difference to be

less; probably in the range 20-40%. The overall PCU value for all buses obtained for one lane

highways which is 2.6 is quite high. This is not surprising given that a large number of bus stops on

the one lane highways do not allow overtaking space for vehicles following a bus. Therefore delays

can be large. For wider roads this value is seen to reduce to around 1.7.

5.1.7 Light Trucks & Medium Trucks

As in the case of buses, these two vehicle types also have been aggregated in the analysis for the

highway sections. At intersections we observe that the medium trucks have a PCU value

approximately 30% more than the light trucks. For the highway section we once again see a higher

value for one lane highways. As expected it is lower than that of buses. This PCU value decreases for

larger roads but always it is lower than that of the bus, keeping to what one would expect.

5.1.8 Large Trucks, Container Trucks & Land Vehicles

This is a mixed bag of vehicle types. It has been so aggregated mainly due to the fact that it is difficult

to get a sufficiently large number of observations of any one particular type to facilitate an accurate

PCU computation of each individual vehicle type. Secondly, their operating nature does lead to an

expectations of PCU values higher than other trucks.

Though there are variations in values between roundabouts and intersections, the fact that the values

obtained are closely correlated with that of carts is an indication of their impact on the traffic flow. As

in the case of carts and bicycles, these large vehicles have a higher effect on buses and trucks than on

passenger cars.

5.2 Determination of Single PCU Value

17

As discussed earlier, it is quite inappropriate to use universal PCU values for different types of

highway planning exercises in Sri Lanka. It is strongly recommended that the results shown in Section

4 be considered in determining the appropriate PCU value to be used for each particular design or

planning application. Moreover, there are a number of road usages, such as the movements at

uncontrolled intersections, reversing and parking of vehicles, the PCU values for which cannot be

calculated accurately. However, the need arises ever often for broad planning exercises where a single

PCU value is sought for the entire highway network. The values given in Table 6 can be used in such

instances. These values have been computed at by taking an approximate mean of all values in Table

5. The assumption therein is that there is near equal usage of the different types considered therein.

One deficiency here is the lack of values for hilly terrain. Even without the values for hilly terrain,

these PCU values maybe considered as adequately accurate while being simple to use.

18

Vehicle Types

PCU

Carts

3.5

Bicycle

0.7

Motor Cycles

0.5

Three Wheelers

0.75

Passenger Cars & Station Wagons

1.0

Vans, Jeeps, Pick Ups

1.1

Mini/Medium Buses (one door)

1.6

Buses (two door)

2.4

Light Trucks (four wheels)

1.5

Medium Trucks (six wheels)

2.0

Land Vehicles

3.8

20 ft Container Trucks

& 3-axle (non-articulated) Trucks

3.8

40 ft Container Trucks

& Articulated Truck-Trailers

6.0

Table 6: Single PCU Values for Sri Lanka (except for hilly terrain)

5.3 Comparisons with Other PCU Studies

The comparison of PCU values from other countries was done only after the conclusion of the

estimation of the study results, so that no biases would be introduced. However, even if

comparisons are made, they should not in any way influence the study estimations. The

reason for this is the large variations in PCU values that could be expected due to the

differences in vehicle-user-road-environment of the different countries. Moreover, there in

usually no uniformity in vehicle type classification between studies. For example, in one

study "cars" may include only passenger cars whereas in others it could include cars and

station wagons and perhaps vans too. However, in Table 7, an attempt has been made to place

the results from this study alongside several other studies from which PCU estimates are

available for different countries. The countries considered are the U.S.A, U.K., Malaysia,

Indonesia and India. In all these studies, the distinction between minibuses and buses and also

the different types of trucks have not been made. The comparisons are therefore only

approximate in nature. Given this approximation, the values obtained for Sri Lanka can be

considered to be in general agreement with values from overseas, except in the case of

bicycles, where the Sri Lankan values appears to be consistently higher than all others and

19

also for motor cycles, where the Sri Lankan value is marginally lower than elsewhere.

Vehicle Type

Sri

Lanka Study

Results

HCM

UK

Malaysia

Indonesia

India

Carts

3.5

n/a

n/a

n/a

1.0

6.0

Bicycle

0.7

0.33 - 0.5

0.5

0.25

0.5

Motor Cycle

0.5

0.75 - 1.0

0.5

0.5 - 0.75

0.75

Three Wheeles

0.75

n/a

n/a

n/a

n/a

Cars, Station Wagon

1.0

1.0

1.0

1.0

1.0

1.0

Vans & Jeeps

1.1

n/a

n/a

n/a

n/a

n/a

Minibuses

1.6

1.6 - 5.0

3.0

2.0

2.0

3.0 Buses

2.4

Light Trucks

1.5

2.0 - 8.0

2.0 - 3.0

2.0 - 2.5

2.0 - 3.0

3.0

Medium Trucks

2.0

Heavy Trucks/ 30' Containers

3.8

40' Containers

6.0

Land Vehicles

3.8

3.0

n/a

n/a

5.0

4.0

Table 7 : Comparison with PCU Values for other Countries

6. ACKNOWLEDGEMENT

The author gratefully acknowledges the financial assistance received from the Transport

Studies & Planning Centre to undertake this work.

7. REFERENCES

[Transport Research Board, 1984] Transport Research Board, 1984, "Highway Capacity

Manual".

[Kadiyali, 1991] Kadiyali L.R., 1991, "Traffic

Engineering & Transport Planning", Khanna

Publishers, India.

[Kumarage, 1996] Kumarage A.S., (Under

preparation), "Determination of Multi-Faceted PCU

20

factors based on Vehicle Characteristics".