Exercise 1 - Traffic Data Collection Aditya Nugroho e

EXERCISE 1

TRAFFIC DATA COLLECTION AND PRESENTATION

CE 5203 TRAFFIC FLOW AND CONTROL

ADITYA NUGROHO

HT083276E

DEPARTMENT OF CIVIL ENGINEERING

NATIONAL UNIVERSITY OF SINGAPORE

2010

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Department of Civil Engineering

CE 5203 Traffic Flow and Control

1.0 INTRODUCTION

The measurement of traffic volumes is one of the most basic functions of highway planning

and management. Traffic counting can include volume, direction of travel, vehicle

classification, speed, and lane position. In this Exercise 1 the objectives are:

To understand how to observe, classify traffic by space, time and modes on Clementi

Avenue 6 in direction from AYE to PIE road;

To describe the traffic conditions (qualitatively) on this road section;

To measure the traffic and categorize by time interval, lane position, vehicle types.

2.0 DATA COLLECTION METHOD

2.1 Traffic measurement

Data collection is a critical step in the analysis process of traffic counts. Knowing what to

collect, when to collect, how long to collect, where to collect, and how to manage the data

must be addressed before starting the collection. In this Exercise 1, several matters should be

considered before do the traffic counts.

A marked line- a certain line should be set as a reference to count vehicles. We count

vehicle when they cross the lines drawn on the screen from the front bumper touching

the line within strict lane discipline.

Interval length-as traffic count is discrete, it is necessary to choose an appropriate time

interval to set vehicles into different groups. In our exercise the interval is

predetermined as 5-min by the lecturer.

Vehicle type-we divide vehicles into 4 groups including car, bus, lorry and

motorcycle.

Choosing lane- traffic lanes are often referred to by number. The right or “fast” lane is

called the “Number 1 Lane.” The lane to the left of the “Number 1 Lane” is called the

“Number 2 Lane”, then the “Number 3 Lane”,

Road type: Motorways, urban roads, and inter-urban roads. Road type is one of the

differentiating characteristics included in the calculation of the traffic counts.

2.2 Data collection and relevant information needed

Data collection sites of one direction from AYE to PIE is using camcorder and video

technologies. However, several problems on data collection are adresses below:

The observer records count data by videotaping traffic. Therefore traffic volumes can

be counted by viewing videotapes recorded with a camera at a collection site.

However, there is no a digital clock in the video image which can prove useful in

noting time intervals.

In regards to position of camcorder, it is necessary to set strategically positioned, to

capture along of highway section. This allowed for the viewing of the entire highway

width in one direction. Besides video recording technique, onsite surveys were

essential for collecting roadway geometry and characteristics.

In this Exercise, the count period is representative by the 5 minute to 30 minute count

interval from 6.50 AM-7.20 AM.

However, in order to represent real traffic condition, the count period itself should be

represent the time of day, day of month, and month of year for the study area.

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3.0 TRAFFIC CONDITIONS

As can be seen from the videotape recording, in general the characteristic of traffic on

Clementi Avenue 6 from direction of AYE to PIE segments can be characterised as

heterogenous traffic during period of count. During period of count the vehicles traffic in this

segment has strict lane discipline and has traffic various types whose dimensions vary much.

However, in order to describe the real problems of traffic condition, I will describe the

characteristic of road geometry, lane position and lane traffic markings which will be affected

the decision of lane changing behavior of drivers or vehicles. This issue will be explained by

road figure below were obtained from the Google Maps with Street View.

Figure 1. Road geometry design of study area

The study area of this exercise is road segment of Clementi Avenue 6 where all the traffic

come from two different exits of AYE (trumpet interchange). Based on observation from the

videotape recording, it can be seen that between locations A and B, the horizontal alignment

of road geometry is widen in order to accommodate an additional traffic volume from the

AYE exit of Jurong. However, a AYE exit of Jurong will adds considerable traffic to the road,

especially if the condition of B has interruption which occured by entrance and exit of buses

for alighting and boarding passenger to bus bay area especially in lane position of 3 and 4 (see

Figure 2). If lane 3 and 4 of location B reaches capacity due to this entrance and exit of buses,

there will be a backup of traffic on the mainstream, resulting in stop-and-go traffic at AYE

exit especially if the vehicles perform lane changing that may take place by vehicles.

In lane 1 and 2 position between location of A and B some vehicles can be considered to be in

a queue, waiting their turn to be served by the interruption section at location of B. Thus,

given by the record of traffic conditions, there is a good range of uncongested flow of road

segment in location B in lane position of 1 and 2. This cause between location A and B

drivers arrive at the front end of the queue moving very slowly, and accelerate away from that

point, increasing speed as they move through the bottleneck section. This segment of the

speedflow has been referred to as queue discharge flow.

1

2

3

4

AYE exit from

Jurong

Bus bay Marked

line

A

B

1

2

3

1

2

AYE exit from

City

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Figure 2. Interruption section at entrance bus bay and queue discharge flow area

4.0 DATA SUMMARY AND ANALYSIS

To more understand the traffic pattern on Clementi Avenue 6 of direction AYE to PIE road

segment, traffic counts were measured by time interval, lane position, and vehicle types. The

detail for traffic count data by site, entity type, and time interval is indicated on Appendix.

The percentage of traffic composition is shown on Figure 3.

69,3%

8,3%

11,4%11,0%

CAR

BUS

LORRY

MC

Figure 3 Traffic composition at Clementi Avenue 6.

From the figure above, we can conclude that the proportion of each vehicles is dominated by

passenger cars which give the significant portion of traffic composition during period of

count. In more detail following figure will represent the count of vehicles in lane position by

time interval (in minutes).

Uncongested

flow

Interruption

section

Merging and

lane changing

perform

Queue

discharge flow

5



0

10

20

30

40

50

60

70

6:50 -

6:55

6:55 -

7:00

7:00 -

7:05

7:05 -

7:10

7:10 -

7:15

7:15 -

7:20

No

of

co

un

ts

Time interval (minutes)

Lane 1

MC

LORRY

BUS

CAR 0

10

20

30

40

50

60

70

6:50 -

6:55

6:55 -

7:00

7:00 -

7:05

7:05 -

7:10

7:10 -

7:15

7:15 -

7:20

No

of

co

un

ts


Lane 3

MC

LORRY

BUS

CAR

0

10

20

30

40

50

60

70

6:50 -

6:55

6:55 -

7:00

7:00 -

7:05

7:05 -

7:10

7:10 -

7:15

7:15 -

7:20

No

of

co

un

ts


Lane 2

MC

LORRY

BUS

CAR 0

10

20

30

40

50

60

70

6:50 -

6:55

6:55 -

7:00

7:00 -

7:05

7:05 -

7:10

7:10 -

7:15

7:15 -

7:20

No

of

co

un

ts


Lane 4

MC

LORRY

BUS

CAR

Figure 4 No of vehicles count and time interval

In general, the distribution of passenger cars during the time interval at each lane is relatively

constant. From figure lane 2 it is seems that abrupt change in traffic composition a proportion

of bus which relatively higher than lane 4 which is a bus bay area. Therefore, since the

videotaped data allowed to spot check the counts and measurements. When miscounting or

mismeasurement occurred, reobservation of the entire 5-min segment is conducted again to

make a sure of traffic pattern. After reobservation, I found that most of private bus were

occupied of lane 2 position.

However, in more clearly to illustrate overall traffic stream condition therefore we should

converted all of each vehicles into PCE according to the following conversion coefficient

which obtained from study by Henry Fan on Passenger Car Equivalents for Vehicles on

Singapore Expressways.

Table 1 PCE factors for Singapore

Type Car Truck/Lorry Bus Motorcycle

Coefficient 1.0 2.6 2.7 0.4

After converting all types of vehicles into PCE, therefore it is easily to analyse the flow rates

in each time interval as illustrate by following figure and table.

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-

10

20

30

40

50

60

70

80

90

100

6:50 -

6:55

6:55 -

7:00

7:00 -

7:05

7:05 -

7:10

7:10 -

7:15

7:15 -

7:20

PCE conversion volume

Lane 1

Lane 2

Lane 3

Lane 4

-

100

200

300

400

500

600

700

800

900

1.000

6:50 -

6:55

6:55 -

7:00

7:00 -

7:05

7:05 -

7:10

7:10 -

7:15

7:15 -

7:20

Flow rates (vph)

Series1

Series2

Series3

Series4

Figure 2 Traffic volume and flow rates in each lane position

Table 2 Total traffic volume and flow rates on Clementi Avenue 6

5 minutes beginning Vehicle count Flow rate (vph)

6:50 - 6:55 226 2.717

6:55 - 7:00 170 2.045

7:00 - 7:05 256 3.074

7:05 - 7:10 237 2.845

7:10 - 7:15 195 2.339

7:15 - 7:20 238 2.851

5.0 DISCUSSION AND CONCLUSION

In this exercise, traffic count were measured at the road segment of Clementi Avenue 6 on

direction from AYE to PIE. However, since traffic and volume data does vary from day to

day. By collecting data on only one day, the data will likely not reflect the average traffic

patterns. Data should be collected during peak or off peak periods when typical traffic

conditions exist. Traffic data collection should be avoided during such conditions as during

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incidents, inclement weather, special events, construction, holidays and seasonal variations

(unless these special conditions are part of the analysis purpose).

Videotape being able to refer back to see how lanes join or where signs are located is very

helpful. This is especially true for situations where the analyst is not located near the site.

Videotaping and digital images should be captured during the peak hour so as to depict

accurate congestion levels and queues. Therefore, for the future analysis we should included

all traffic counts measurement in preparing data collection in order to better interpretation of

traffic condition.

6.0 REFERENCES

A Policy on Geometric Design of Highway and Streets 2001, 4th Ed. (AASHTO)

Highway Capacity Manual. 2000. Special Report 209, 4th Ed., TRB, National Research

Council, Washington, D.C.,

Traffic Monitoring Guide, 3rd Ed. Federal Highway Administration (FHWA)

Traffic Flow Theory A State-of-the-Art Report (2001). Committee on Traffic Flow Theory

and Characteristics (AHB45). TRB, National Research Council, Washington, D.C.,

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Appendix

Location: Clementi Ave 6

Recorder: Video

City/Town: Singapore

Interval: 5

Direction: AYE to PIE

(In Minutes)

______________

_

______________

_

______________

_

______________

_

______________

_

__________

_

Lane: TIME CAR BUS LORRY MC TOTAL

1 ENDING TYPE 1 TYPE 2 TYPE 3 TYPE 4

--------- --------- --------- --------- --------- ---------

6:50 - 6:55 49 5 0 6 60

6:55 - 7:00 40 2 0 5 47

7:00 - 7:05 50 3 3 5 61

7:05 - 7:10 42 9 0 5 56

7:10 - 7:15 50 2 0 7 59

7:15 - 7:20 40 2 2 7 51

Lane: --------- 271 23 5 35 334

2 6:50 - 6:55 19 9 12 15 55

6:55 - 7:00 10 6 8 5 29

7:00 - 7:05 13 9 17 7 46

7:05 - 7:10 12 11 8 14 45

7:10 - 7:15 14 0 14 15 43

7:15 - 7:20 13 1 24 16 54

Lane: --------- 81 36 83 72 272

3 6:50 - 6:55 22 2 1 1 26

6:55 - 7:00 16 0 0 1 17

7:00 - 7:05 20 2 0 0 22

7:05 - 7:10 17 1 2 0 20

7:10 - 7:15 15 0 2 3 20

7:15 - 7:20 22 2 3 2 29

Lane: --------- 112 7 8 7 134

4 6:50 - 6:55 29 4 4 1 38

6:55 - 7:00 47 2 2 0 51

7:00 - 7:05 47 4 8 0 59

7:05 - 7:10 52 4 5 0 61

7:10 - 7:15 45 5 0 1 51

7:15 - 7:20 46 3 5 0 54

--------- 266 22 24 2 314

TOTAL 730 88 120 116 1054

Exercise 1 - Traffic Data Collection Aditya Nugroho e

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