The Effect of Countdown Timer with Running Text at Signalized Intersection: An Empirical Study

Abstract

This study aims to analyze driving behaviour at signalized intersections due to the countdown timer. In the scenario, we also test the countdown timer with running text that lacks attention in the literature. We collect data on lost time, early start, number of vehicles passing per cycle, number of violations and vehicle's speed. In determining the signalized intersection for scenario implementation, we consider the volume of vehicles, the number of phases, and the geometric of the intersection in the city of Yogyakarta, Indonesia. The results show that the use of a countdown timer in traffic lights, whether with running text or not, is able to increase the efficiency of vehicle movement. The lost time decreases, and the number of vehicles that pass each cycle increases. However, the number of early starts at the signalized intersection increases. Meanwhile, the average speed of vehicles at the end of a green light signal does not show a statistical difference between traffic lights without and with a countdown timer, whether with running text or not. The use of running text in the last few seconds of the red-light signal tends to give a smaller early start than an unmodified countdown timer. In addition, the number of vehicles violating the rules when entering a red light tends to decrease for the traffic light with a countdown timer. The number of violations when using an unmodified countdown timer tends to be less than the countdown timer with running text.

Keywords
Traffic light; countdown timer; driving behaviour; running text; early start

Full text

Transactions on Transport Sciences | Vol. 1/20251
Transactions on Transport Sciences
Peer-Reviewed Open Access Journal
Vol. 1/2025 DOI: 10.5507/tots.2024.016
journal homepage: www.tots.upol.cz
The Effect of Countdown Timer with Running Text
atSignalized Intersection: An Empirical Study
RIZKA DIMAS FITRIAN, AGUS DARMAWAN
Department of Mechanical and Industrial Engineering, Universitas Gadjah Mada, Yogyakarta, 55281 Indonesia
ABSTRACT: is study aims to analyze driving behaviour at signal-
ized intersections due to the countdown timer. In the scenario, we also
test the countdown timer with running text that lacks attention in the
literature. We collect data on lost time, early start, number of vehicles
passing per cycle, number of violations and vehicle’s speed. In determin-
ing the signalized intersection for scenario implementation, we consider
the volume of vehicles, the number of phases, and the geometric of the
intersection in the city of Yogyakarta, Indonesia. e results show that
the use of acountdown timer in trac lights, whether with running text
or not, is able to increase the eciency of vehicle movement. e lost
time decreases, and the number of vehicles that pass each cycle increases.
However, the number of early starts at the signalized intersection in-
creases. Meanwhile, the average speed of vehicles at the end of agreen
light signal does not show astatistical dierence between trac lights
without and with acountdown timer, whether with running text or not.
e use of running text in the last few seconds of the red-light signal
tends to give asmaller early start than an unmodied countdown timer.
In addition, the number of vehicles violating the rules when entering
ared light tends to decrease for the trac light with acountdown timer.
e number of violations when using an unmodied countdown timer
tends to be less than the countdown timer with running text.
KEYWORDS: Trac light;countdown timer;driving behaviour;running
text;early start
1. INTRODUCTION
In urban areas with high mobility, trac is one of the ac-
tivities carried out almost every day that requires ethics in
driving. As users of motorized vehicles, we must adhere to
trac signs to ensure safety and maintain smooth trac
ow. One of the most common trac control signs is atrac
light. Almost at every intersection, we can nd trac lights,
especially at intersections that have the potential to cause
trac jams or accidents. Violations at signalized intersections
are still one of the most dominant violations in Indonesia.
ese violations often lead to trac accidents (Fitrian, 2014;
Agus, 2021; Arnani, 2021; Saputra, 2021).
According to Ma (2008), the interaction between adriver
and other road users or objects at asignalized intersection
generates information that enables the driver to make in-
formed decisions. is decision-making process is inuenced
not only by trac signals but also by road conditions, environ-
mental factors, and the driver’s own condition. Consequently,
several factors, including the characteristics of the driver, the
vehicle, the environment, and other vehicles, play arole in
shaping the driver’s behaviour at intersections.
Trac lights that exist today generally consist of red,
yellow, and green. However, since 2008, the Department of
Transportation of Yogyakarta has added acountdown timer
to trac lights at signalized intersections. e installation
of acountdown timer is expected to reduce driver ignorance,
enabling them to decide when to accelerate, slow down, or
stop at the appropriate time. For example, at the green light,
the driver can know the crucial time before changing to the
red signal, and at the red light, the driver can get ready before
the green light (Lu & Yuan, 2007). In addition, the countdown
timer can also reduce driver boredom while waiting (Zhang
et al., 2009).
is study aims to analyse driving behaviour at signal-
ized intersections due to the countdown timer. We conduct
scenarios related to the countdown timer, unmodied and
countdown timer with running text. In the latter, we modify
the countdown timer to display running text with awarn-
ing/exhortation during the last 10 seconds. In this study,
we discuss behavioural analysis using more trac eciency
metrics than previous studies. is approach enables amore
comprehensive evaluation of the impact of countdown tim-
ers, which we believe is an important contribution to the eld
of trac engineering.
is paper is organized as follows: e rst section pro-
vides the background and motivation for studying the eect
of countdown timers in trac engineering. e next section
outlines and discusses the key ndings from previous studies
on countdown timers. e third section presents the method-
ology of this study, detailing how we conducted scenarios at
two signalized intersections with high vehicle volumes. In the
fourth section, we present the results of the study, including
observations on lost time, the number of passing vehicles,
early starts, red light violations, and vehicle speed. Finally,
the last section oers conclusions and suggests directions
for further research.
2. LITERATURE REVIEW
Several previous studies have investigated the eectiveness
and impact of the countdown timer on the trac light. Wang
and Yang (2006) reveal that 50% of motorized vehicle users
felt that the countdown timer decreased start-up lost time.
Furthermore, they show that start-up lost time decreased
by 17.8%, and the number of vehicles passing every hour
increased by 10%. Kim and Kim (2020) analyse the impact
of acountdown timer at asignalized intersection. ey state
that apart from functioning to improve trac eciency and
safety, countdown timers can also encourage drivers to volun-
tarily control vehicle idling, reducing emissions at signalized
intersections by more than 50%. Yuan et al. (2009) present
that installing acountdown timer at atrac light can reduce
delays or reduce start-up lost time, the time lost between the

Transactions on Transport Sciences | Vol. 1/20252
start of the green light and the rst vehicle that passes. In
addition, the number of vehicles that pass in one trac light
cycle can increase. However, there are also adverse eects.
e number of violations at the beginning of the red light
increases and as well as the speed of vehicles carried out by
motorists in the last 5 seconds of the green light signal.
Islam et al. (2017) use adriving simulator to study the
driver’s response to the countdown timer. By involving 55
participants, they present that agreen signal countdown
timer could increase intersection safety. Drivers become more
orderly and start preparing to stop when the remaining time
is running out. Lum and Harun (2006), Paul and Ghosh (2020),
Jatoth et al. (2021) also show that the countdown timer can
reduce violations that occur at an intersection and lost time.
Malecki and Iwan (2019) develop atwo-lane road model with
atrac countdown timer. Using acomputer simulation, they
show that the countdown timer increases the number of ve-
hicles passing. ey argue that drivers become more focused
on the countdown timer than their surroundings and will be
ready to go when the time is right.
Pathivada and Perumal (2019) analyse the driver’s dilem-
ma at signalized intersections in India. ey state that the
essential factors in determining whether adriver will stop/go
are the distance from the stop line, the vehicle’s speed and
the type of intersection. For example, at the 4-arm signalized
intersection, drivers tend to be more impatient and aggres-
sive than at a3-arm signalized intersection. In addition, the
type of vehicle also inuences the decision to stop or not at
the onset of yellow, where two-wheeled drivers have less
probability of stopping than cars. In their study, Manan et
al. (2020) also state that two-wheeled drivers have alarge
portion in contributing to violations of the necessity to stop
when there is ared light.
Sun et al. (2013) present eects at asignalized intersection
with acountdown timer. Installing acountdown timer allows
us to know the drivers’ behaviour. e vehicle speed at the
end of the green light is higher than without acountdown
timer. At the rst 10 seconds of the green light, the vehicle’s
speed is very dierent and varies. ey suggest that the in-
stallation of acountdown timer should take into account the
trac ow at signalized intersections. For example, in atraf
-
c light with alarge enough volume of passing vehicles and
long red light in one cycle, it is advisable to install acount-
down timer. However, if the volume of passing vehicles is not
too large, the countdown timer does not need to be installed.
Elekwachi (2010) shows that countdown pedestrian signal
(CPS) reduces start-up lost time in each cycle of 1.1 - 1.8 and
increases the number of passing vehicles per hour.
Zhang et al.(2012) highlight that when the countdown
timer shows less than 3 seconds remaining at the end of
the green signal, drivers should exercise caution and reduce
their speed. However, some drivers accelerated the vehicle.
Even when the green light has turned o and the red signal
has just begun, some drivers may still proceed through the
intersection. is behaviour can be attributed to varying per-
ceptions of the countdown timer and the inuence of driving
habits. Additionally, drivers may experience frustration if
they have to wait too long for the red light to change. Vice
versa, if the green light is fast, the driver will hurry to cross.
Such an incident can result in anear miss that can endanger
the driver and others. erefore, it is necessary to improve the
existing countdown timer or trac light system and evaluate
driving behaviour.
Several previous studies have discussed the countdown
timer at signalized intersections and used two or three indi-
cators. is study uses ve indicators to measure the count-
down timer’s eectiveness: lost time, early start, number of
passing vehicles, number of violations, and vehicle’s speed.
We also conduct an experiment to adjust the countdown tim-
er to have running text containing awarning/exhortation in
the last 10 seconds. To the best of our knowledge, this is the
rst study that discusses the implementation of acountdown
timer with running text. In addition, we obtain data from
the scenarios that we implement directly to the signalized
intersections, which has previously received approval from
the Department of Transportation. Furthermore, this study
will add literature on driving behaviour due to countdown
timers in developing countries, particularly Indonesia, which
still lack attention.
3. METHODOLOGY
is study takes data directly from the eld on two signalized
intersections in Yogyakarta; Senopati and Wirobrajan inter-
section. We determine the above location based on ahigh
volume of vehicles, the number of phases, and the geom-
etry of the signalized intersection. During peak hours (i.e.
06.30-08.30 and 15.30-17.30), the volume of vehicles at the
Senopati and Wirobrajan intersections reaches 8879 - 11702
units/hour. Both intersections have 4 phases and are geo-
metrically symmetrical. Figure 1 illustrates the phase shift
at the two signalized intersections.
We get approval from the Yogyakarta transportation de-
partment for implementing scenarios (i.e. without and with
countdown timer) directly on the signalized intersections.
In the initial stage, the countdown timer is o, and then
in the second stage, the countdown timer is on. We use
digital cameras to record trac and driver’s behaviour at
signalized intersections. In addition, we place cameras at
intersection corners to get aclear view of drivers’ behaviour.
In both stages, we collect data on lost time, early start, the
number of vehicles, violations (red light violations) and
vehicle’s speed.
We run the scenarios at peak hours at 06.30-08.30 and
15.30-17.30 for eight days according to the permission ob-
tained from the Yogyakarta transportation department. e
trac light cycle lasts 152 and 156 seconds, respectively,
resulting in 184 and 188 data cycles over a2-hour period at
the signalized intersection. Because asignalized intersection
is only allowed to do amaximum of two scenarios, at the Se-
nopati intersection, we run the scenario without acountdown
timer and with amodied countdown timer (e.g. running
text in the last few secs of red/green light signal). Mean-
while, at the Wirobrajan intersection, we test signalized
intersection without and with an unmodied countdown
timer. We hypothesized that implementing countdown timers
North
Phase 1
West
East
South
North
Phase 2
West
East
South
North
Phase 3
West
East
South
North
Phase 4
West
East
South
Figure 1. An example of phase change at asignalized intersection

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with running text at signalized intersections would lead to
ameasurable improvement in trac eciency and safety. We
also hypothesized that the presence of these timers would
positively inuence driver behaviour, reducing instances of
abrupt stopping and accelerating.
4. RESULTS AND DISCUSSIONS
4.1 Lost time
We measure the time lost between the start of the green light
and the vehicle in the rst line passing through the stop line.
Figure 2 shows the average lost time per cycle for the south
arm at the Senopati intersection. For example, at 6:30 (rst
cycle), the lost time for trac lights without and with acount-
down timer is 2.56 and 1.45 sec, respectively.
Table 1 compares the average lost time between without
and with acountdown timer for the Senopati and Wirobrajan
intersections. For the north arm of Senopati, there was no
statistically signicant dierence in the lost time between
without and with countdown timer (p-value=0.878 > 0.05). In
general, Table 1 shows asignicant dierence (p-value = 0.000)
for the two scenarios, where the lost time value decreases for
signalized intersections with acountdown timer.
4.2 e number of passing vehicles
e dierent scenarios of countdown timers can aect the
number of passing vehicles. erefore, we count the vehicles
that pass each cycle during peak hours and then calculate the
average. Figure 3 and Figure 4 show the number of passing
vehicles before and after countdown timer installation.
Figure 2. Average lost time per cycle at south-arm of Senopati intersection
Intersection Arm Average lost time (and std.deviation) P-value
Without countdown timer With countdown timer
Senopati (*with
running text)
North 2.32 (0.57) 2.41 (0.86) 0.878
East 2.31 (0.74) 1.66 (0.45) 0.000
South 3.18 (0.67) 2.05 (0.3) 0.000
West 2.72 (0.8) 1.6 (0.38) 0.000
Total average 2.63 (0.76) 1.93 (0.62)
Wirobrajan North 3.62 (0.94) 1.31 (0.43) 0.000
East 2.87 (0.72) 1.4 (0.48) 0.000
South 3.02 (0.48) 0.96 (0.19) 0.000
West 3.39 (0.79) 1.73 (0.61) 0.000
Total average 3.22 (0.77) 1.35 (0.52)
Table 1. e average lost time at Senopati and Wirobrajan intersection
Figure 3. e average number of passing vehicles per cycle at
Senopati intersection
Figure 4. e average number of passing vehicles per cycle at
Wirobrajan intersection

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In general, the number of passing vehicles per cycle is
higher for the case with acountdown timer. e information
about the remaining time allows the driver to focus more on
preparing to move, which leads to an increase in the vehicle’s
movement. Based on observations, when there is no count-
down timer, some front-line drivers prepare when the green
light is on, which result in alonger delay.
4.3 Early start
In the early start, we count the number of vehicles that pass
the stop line before the green light turns on. Drivers start run-
ning when they are still in the last few seconds of red signal.
Figure 5 shows an illustration of when drivers make an early
start. Table 2 shows the average number of early starts at the
Senopati and Wirobrajan intersections in the case without
and with countdown timers.
Based on Table 2, the number of early starts before and
after the countdown timer installation was not signicantly
dierent (P-value > 0.05) for the north and south arms at the
Senopati intersection. However, in general, the countdown
timer increases the number of early starts signicantly (P-
value = 0.000). is result aligns with the ndings of Zhang
et al.(2012), who suggest that drivers should prepare to
stop as the signal approaches the last 3 seconds. However,
it is often observed that many drivers at the front of the
line start moving prematurely, even when the light is still
red. e result contradicts Yuan (2009), who shows that
the number of early start decreases after countdown timer
installation.
e overall ratio of early start between without and with
countdown timer are 1:2.7 and 1:11 for Senopati and Wirobrajan
intersections, respectively. e early start ratio at Senopati is
much smaller than Wirobrajan intersection. We replaced the
display of the remaining 10 seconds with running text con-
taining warnings and exhortations at the Senopati intersec-
tion. It seems that running text can cause drivers to wait afew
seconds before having condence that it will soon turn into
green light. In the case with an unmodied countdown timer
(Wirobrajan intersection), from interviews with several drivers,
the remaining time information allows the drivers to have more
control over when they run. Besides, they have presumptions
and experiences that in the last few seconds of red signal, the
other three arms usually have red lights, so they decide to run
rst before the green light is on. erefore, the countdown
timer with running text in red signal is better than the common
countdown timer in terms of the early start.
In addition, we also measure the average time of early
start at the end of the red signal until the green light turns
on. Figures 6 and 7 show the average early start time on the
4-arm signalized intersection.
Figure 5. An example of early start in the red-light signal
Intersection Arm Average early start (and std.deviation) P-value
Without countdown timer With countdown timer
Senopati (*with
running text)
North 0.05 (0.22) 0.05 (0.22) 0.650
East 1.00 (1.22) 3.25 (3.30) 0.000
South 0.30 (0.69) 0.38 (0.67) 0.510
West 1.28 (1.88) 3.50 (3.40) 0.000
Total average 0.66 (1.23) 1.79 (2.78)
Wirobrajan North 0.25 (0.87) 6.93 (3.13) 0.000
East 1.28 (2.12) 4.40 (2.06) 0.000
South 0.23 (0.83) 8.13 (3.05) 0.000
West 0.33 (0.73) 3.63 (2.13) 0.000
Total average 0.52 (1.27) 5.77 (3.16)
Table 2. Average early start for Senopati and Wirobrajan intersections
Figure 6. e average time of early start at Senopati intersection
Figure 7. e average time of early start at Wirobrajan intersection

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e average early start time at the south arm of the
Wirobrajan intersection is 2.5 seconds for the case without
acountdown timer. It means that the drivers have started
running 2.5 seconds before the green light on average. Mean-
while, in the case of the trac light with acountdown timer,
the average early start time is 3.58.
4.4 Red light violation
e red-light violation is the number of vehicles that pass at
the red light after the green signal. Figure 8 illustrates the
violation at the signalized intersection.
is section compares the number of violations for dier-
ent scenarios, without and with acountdown timer. Table 3
shows that in almost all arms at the Senopati intersection
except for the east arm, there was no statistical dierence
in the number of violations after the countdown timer in-
stallation (P-value >0.05). Based on interviews with several
drivers, the running text at the end of the green light signal
eliminates the remaining time information. It makes the
drivers assume that running without slowing down their
vehicle is still safe. e number of violations in the north
and east arms tends to be less than the south and west arms
because few vehicles pass at the green light’s end. us, the
probability of aviolation in the north and east arms is small.
Meanwhile, vehicles passing on the south and west arms
tend to be more congested, so the probability of aviolation
is greater.
An interesting result is at the Wirobrajan intersection,
where the countdown timer does not have running text. In
contrast to the Senopati intersection, there was asignicant
dierence (p-value < 0.05) between trac lights without and
with countdown timers for all arms at the Wirobrajan inter-
section. Acountdown timer can reduce the number of drivers
passing by when the red light starts. It indicates that the
remaining time information at the end of the green signal can
give the impression that drivers do not have to force them-
selves to pass and immediately get ready to stop. However,
this contradicts Yuan et al. (2009), who state that violations
increase if acountdown timer is installed.
4.5 Vehicle’s speed
We identify the vehicle’s speed for the vehicle passes at the
end of green light. Figure 9 shows the average vehicle’s speed
at the south arm of the Senopati intersection for the case
without and with acountdown timer.
Figure 8. An example of red-light violation
Intersection Arm Average violation (and std.deviation) P-value
Without countdown timer With countdown timer
Senopati (*CT with
running text)
North 2.25 (3.52) 2.93 (4.63) 0.680
East 2.53 (2.37) 1.55 (1.85) 0.020
South 4.95 (4.12) 5.65 (6.59) 0.830
West 3.60 (3.97) 3.88 (3.80) 0.560
Total average 3.33 (3.57) 3.50 (4.51)
Wirobrajan North 4.68 (4.30) 1.88 (1.98) 0.001
East 3.90 (4.55) 2.13 (2.07) 0.002
South 4.65 (4.75) 1.25 (1.86) 0.000
West 10.40 (5.07) 4.38 (3.48) 0.000
Total average 5.91 (5.11) 2.41 (3.36)
Table 3. e average number of violations at the Senopati and Wirobrajan Intersections
Figure 9. e vehicle’s speed at the south-arm Senopati intersection

Transactions on Transport Sciences | Vol. 1/20256
Table 4 shows the average speed on all arms at the Seno-
pati and Wirobrajan intersections. Again, we use statistical
tests to determine whether the use of the countdown timer
has asignicant dierence. From Table 4, the p-value > 0.05
for all sides, so we can conclude that there is no dierence
in the speed of passing vehicles without and with acount-
down timer statistically. is result is dierent from Zhang et
al.(2012), where they state that the vehicle’s speed decreases
after acountdown timer installation.
5. CONCLUSIONS
e use of acountdown timer in trac lights, whether with
running text or not, increases the eciency of vehicle move-
ment. For example, from the scenarios that we implement
directly to the signalized intersection, the average lost time
at the Senopati intersection decreases from 2.63 secs to
1.93secs, while the Wirobrajan intersection decreases from
3.22 secs to 1.35 secs. In addition, the number of passing ve-
hicles per cycle is higher for the trac light with acountdown
timer. Nevertheless, acountdown timer causes an increase in
the number of vehicles that run before the green light (ear-
ly start), especially at the Wirobrajan intersection. It is the
shortcoming of the countdown timer. Early start behaviour
will endanger the drivers because it can cause near misses,
especially with the drivers from other arms. erefore, the use
of running text in the last few seconds of the red-light signal
is better than the use of an unmodied countdown timer.
e red-light violations tend to decrease for the trac light
with acountdown timer, especially at the Wirobrajan inter-
section. is is because the drivers can estimate the time to
stop before the red light. However, the number of violations
at the Senopati intersection was not signicantly dierent
before and after installing the countdown timer with running
text. e use of an unmodied countdown timer is better
than acountdown timer with running text, especially for the
green light signal. Meanwhile, the vehicle’s speed at the end
of the green light signal does not signicantly dier between
the trac light without and with acountdown timer, either
with running text or not.
e results of our study provide insights into the eective-
ness of countdown timers with running text at signalized
intersections. Specically, our ndings suggest that these
timers can signicantly improve trac eciency and safety
by reducing driver anxiety and enhancing compliance with
trac signals. ese results can guide urban planners and
trac engineers to design more eective trac management
systems, potentially reducing accidents and improving traf-
c ow in urban areas. Additionally, the data can support
policymakers in making informed decisions about investing
in trac signal infrastructure.
We acknowledge the limitations of this study and sug-
gest several topics for further research. Firstly, this study
test dierent scenarios during peak hours. us, apossible
extension is to conduct an experiment during o-peak hours
to know whether there are dierences in results. Secondly,
this study could only perform two scenarios for each signal-
ized intersection due to the experimental permit obtained.
erefore, testing more than two scenarios at each signalized
intersection may make the comparison more fairly (i.e. with
-
out and with acountdown timer and acountdown timer with
running text). Finally, further empirical studies are necessary
to validate the results of this study.
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North 30.12 (7.47) 30.93 (8.84) 0.620
East 45.26 (11.44) 41.15 (16.15) 0.120
South 31.30 (7.65) 32.36 (7.60) 0.450
West 38.69 (8.98) 34.82 (12.85) 0.060
Total average 36.34 (10.62) 34.81 (11.92)
Wirobrajan North 28.09 (8.54) 25.34 (9.59) 0.060
East 29.44 (9.34) 30.50 (10.42) 0.130
South 28.21 (9.93) 30.21 (10.91) 0.590
West 29.59 (8.39) 30.88 (9.44) 0.162
Total average 28.83 (8.66) 29.23 (10.21)
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