Saturation flow by using Passenger Car Unit (PCU) 58 

The first one was researched by Chu Cong Minh (2003) as his master thesis in the Asian Institute of Technology (AIT) with the title ‘’Analysis of motorcycle effects to saturation flow rate at signalised intersection in developing countries’’. This research was published by the journal of the Eastern Asia Society for Transportation Studies in October 2003.

In this study, he used the conventional concept of the saturation flow rate, that is, all other types of vehicle are converted into passenger car unit. He collected data at three signalised intersections in Bangkok in Thailand and four intersections in Hanoi in Vietnam to have a comparison between these two cities.

In Bangkok, the traffic data was collected in peak hours on the lane width from 3.2 m to 5 m depending on each approach. Traffic composition included only private cars, motorcycles, and buses, in which the proportion of motorcycles was in average of 20% in the traffic stream on lanes.

In Hanoi, the traffic data was also collected in peak hours on the lane width from 3.5 m to 5 m, trucks and heavy vehicles were prohibited at that time. The proportion of motorcycles was in average of 90%.

The varying saturated green times from 5 s to 45 s were recorded to estimate the equivalent factor of motorcycle into passenger car unit, the average saturation headway, and the saturation flow rate.

Chu Cong Minh assumed that: ‘’the relationship between dependent variables is linear’’, and he, therefore, used the following regression formula through his study as follows:

3 3 2 2 1 1

.n

a

.n

a

.n

a

t=

+

+

(6)

Where t = saturated green time (s),

a1, a2, a3: coefficients of motorcycle, private car, and bus, respectively,

Chapter 5: Calculation of Signal Program Elements for MDCs Saturation flow

Chu Cong Minh used the initial vehicular equivalent factors in Table 18 for determining saturation condition while collecting data. It means that, every consecutive five-second of green times is recorded, and vehicles passing the stop-line during these five seconds are converted into passenger car units by the equivalent factors in Table 18. If more than three passenger car units pass the stop-line during 5 seconds, the traffic flow is considered to be saturated.

Table 18: Passenger car equivalent (PCE) for other vehicles (1)

Vehicle PCE

Motorcycle, moped, scooter 0.25

Passenger car, van, taxi 1.00

Bus 2.00 (Chu Cong Minh, 2003 according to Mathetharan, 1997)

Then, the average saturation headway (after converting into passenger car unit) is determined as follows: 3 3 2 2 1 1

p

n

p

n

p

n

t

H

+

+

=

[s/veh] (7) Where 2 3 3 2 2 1 1

a

a

p

;

1

p

;

=

=

=

a

a

p

are equivalent factors of motorcycle, private car, and bus

into passenger car unit.

From the average saturation headway H, the saturation flow rate is then determined by the formula:

H

3600

[p.c.u/h].

After regression analyses from the collected data, Chu Cong Minh achieved the results as follows: In Hanoi: t = 0.207 n1 + 0.85 n2 + 1.918 n3 with R2 = 0.99

In Bangkok: t = 0.281 n1 + 1.603 n2 + 3.487 n3 with R2 = 0.99

Table 19: Passenger car equivalent (PCE) for other vehicles (2)

City Motorcycle Car, van, taxi Bus

Hanoi Bangkok 0.24 0.18 1.00 1.00 2.26 2.18 (Chu Cong Minh, 2003)

Chapter 5: Calculation of Signal Program Elements for MDCs Saturation flow

Looking at the results above, it is suspected that why the saturation flow rates in Hanoi and in Bangkok is quite different with the same lane width of 5m. The result of the saturation rate in Bangkok is too low while it is relatively high in Hanoi.

In order to make this suspicion clear, there are some considerations for the methodology of Chu Cong Minh as follows:

• The first consideration is in formula (6): t = a1.n1 + a2.n2 + a3.n3 [s]

Because t is the saturated green time in unit [second]; n1, n2, n3 are the number of

motorcycles, private cars, buses in unit [vehicle]; a1, a2, a3, therefore, could be

understood as saturation headways of motorcycles, private cars, buses, respectively, and in unit [s/veh]. Therefore, formula (6) is fit to the following traffic model:

Figure 45: Analysing Chu Cong Minh’s methodology

Nevertheless, Chu Cong Minh collected data under the mixed traffic condition and applied these data to the traffic model above without any adjustment. As a result, there is a big difference between the assumption and the reality (note that the mixed traffic condition is quite different from the traffic model in Figure 45). The result of his research, therefore, is far different from the reality.

• The second consideration is the determination of the saturated condition.

Chu Cong Minh used the equivalent factors in Table 18 as the initial values to determine the saturated condition for mixed traffic (more than three passenger car units passing the stop-line during 5 seconds). The questions are: why didn’t he choose three PCUs passing the stop-line during 6 seconds (2 seconds /PCU)? Did the study give the same results if he would have chosen the initial equivalent factors different from as shown in Table 18? And of course, if he chooses the values in Table 18 for saturated conditions, his results after regression analysis will be close to these values. Finally, it can be concluded that the basis for determining the saturated condition for the data collection is unreliable.

Therefore, the results of saturation flow rate according to Chu Cong Minh’s methodology cannot be applied for MDCs.

In document Traffic Signals in Motorcycle Dependent Cities (Page 72-74)