K. Marintseva. Comparative analysis of check-in technologies at the airport 97
Copyright © 2014 National Aviation University
AIRPORTS AND THEIR INFRASTRUCTURE
UDC 656.7.072.52 (045)
COMPARATIVE ANALYSIS OF CHECK-IN TECHNOLOGIES AT THE AIRPORT
National Aviation University
Kosmonavta Komarova avenue 1, 03680, Kyiv, Ukraine
Abstract. The problem of check-in technologies at the airport is studied. The research is based on the experimental
data obtained by method of observation check-in process at Boryspil airport (Kyiv, Ukraine).Distribution laws of
waiting time and passenger service time at the check-in area are described. The method of dynamic opening and
closing of check-in counter, which based on a model of the queueing theory, is proposed.
Keywords: check-in technologies; CUTE system; queueing theory; self-service; simulation.
In 2012 the Government of Ukraine has approved
the long-term state strategy targeted at airport
development for the period until 2023 .
Among the basic principles that will be
incorporated into the program are the increase of the
airport capacities and aircraft traffic. Moreover, the
reconstruction and modernization of the airports will
be continued with the view to raising the
classification of the airports in accordance with the
recommendations of the International Civil Aviation
Organization and providing coordination for air
flights in difficult weather conditions. In addition,
the program will be aimed to reduce the time
required to service passengers and aircraft.
Public enterprise Boryspil International Airport
(KBP) was modernized in 2012. According to 
the area of the terminal D is 107 thousand square
meters, it can serve up to 15 million passengers per
year. There are 61 check-in counters, 18 control
points of aviation security, 28 passport control
points in the departure area of the new terminal.
Throughput of baggage handling systems is more
than 3 thousand units per hour. The terminal is
equipped with 11 fixed air bridges for 6 wide-body
and 5 medium-sized aircraft. It is planning to add 2
air bridges to long-term outlook. The maintenance
and parking of aircraft is carried out on a new ramp
with the area of 183 thousand square meters, which
can take up to 25 aircraft.
The ramp is equipped with Centralized Aircraft
Refuelling System, which allows fuelling up aircraft
directly in the parking with a speed of 2 tons per minute.
The cost of the terminal with attraction of foreign
investments amounted to 4.8 billion UAH.
Despite the significant investments in
modernization of Boryspil airport, the problems of
the airport operation were discussed at the Cabinet
of Ministers in early June, 2013 .
In passengers opinion problems of service
technology are the same: long waiting time for
check-in and dispensing baggage, lack of food
services area, and small capacity of car parking.
Many passengers spend much queuing time for
check-in or passport control.
2. Analysis of recent research and publications
Description of methods and technologies of
departing from airports passengers service can be
found in many scientific papers.
Already in 1976 the classification of methods of
technological operations for departing passengers
service (single flight and common flights services)
were submitted in paper .
The check-in and baggage handling comprehensive
automation was also reviewed in .
The study of departing passengers service
problem was also discussed in paper .
A.I. Kosov made a detailed study of the departing
passengers processes at six Soviet Union airports in the
period of the most intensive passengers traffic from June
to August 1982 aimed to determine the distribution laws
for the time of passengers arrival before check-in
opening and passengers service time .
Extensive statistical data  (about 7,500)
showed that this distribution is mainly log-normal.
Then these data were used in the statistical
optimization models for single flight and common
Over the last few years, e-commerce, online
check-in and self-service kiosks have changed the
98 ISSN 1813-1166 print / ISSN 2306-1472 online. Proceedings of the National Aviation University. 2014. N 2 (59): 97–104
travel. Today these technologies deliver flexibility to
passengers while reducing airport congestion. A new
disruptive trend in passenger interaction is the
mobile and social media revolution in travel.
Carried out at major international airports in key
regions of the world, the Passenger Self-Service
Survey  represents passenger opinions about
technology used throughout the journey. Self-service
continues to rise in popularity. Passengers are
welcoming new self-service options for baggage,
boarding and transfer. Airlines are actively
introducing technologies of self-service check-in.
For example, passengers who have checked-in on
the SWISS flight on the website swiss.com can order
the delivery boarding pass in the form of SMS or
email messages on a mobile with Internet access .
Bar code in the format 2D contains all the
necessary information about the flight.
The mobile boarding pass is valid for check-in
and baggage drop-off. However, the requirement of
a paper boarding pass for verification by the security
officers at Domodedovo airport (Moscow, Russia)
causes the necessity to use special machines, which
scan information and print the document.
The study of modern check-in technologies
submitted in papers [6, 12]. In those papers self-
service technology is defined as an object which
allows customers to interact with self-service
software. Such kiosks can be found in a variety of
locations, and they typically include a computer
loaded with the software and housed inside a
protective case, although a Self-Service Kiosk (SSK)
can also consist of a computer placed at a table or
desk in an accessible area for customers to use.
The research  focused on the feedback from
both Egypt Air agents and the passengers utilizing
The survey results reviewed that the passengers
are responding positively to self-service deployment
and generally understand the process.
However, the acceptance of this relatively new
technology within Egypt Air's own workforce
depends to a large extent on the type of station at
which the employee works.
The purpose of this paper is to discuss service
innovation to check-in technique at Boryspil airport.
The research is based on the experimental data,
obtained by method of observation, and analysis the
key parameters that affect the self-service and
traditional check-in process and the factors that
3. Check-in techniques in Boryspil International
Today CUTE and CUSS check-in techniques are
used in Ukrainian airports.
As mentioned in , (Common User Terminal
Equipment (CUTE) is the facilities at the airports are
shared between the airlines to reduce the space and
resources required. CUTE was first implemented in
1984 for the Los Angeles Summer Olympic Games.
IATA first created the recommended practice
(RP) 1797 defining CUTE.
From 1984 until the present, approximately 400
airports worldwide have installed some level of
CUTE. CUTE systems allow an airport to make
gates and ticket counters common use.
These systems are known as agent-facing systems,
because they are used by the airline agents to manage
the passenger check-in and boarding process.
Whenever an airline agent logs onto the CUTE
system, the terminal is reconfigured and connected
to the airline's host system. From an agent's point of
view, the agent is now working within his or her
airline's information technology network.
CUSS Common Use SSK were first introduced
by Continental Airlines in 1995 at US airports .
Since then the CUSS has become an integral part of
providing services for passengers.
Most schedule airlines now provide the option
for CUSS kiosk check-in at major airports.
The cost of check-in through kiosks is just $0.16
as against $3.68 with normal check-in with an agent.
At the Boryspil airport is used mainly single
flight method of check-in (Fig.1).
stands in a
and ticket (if
it is used) to
Bags are sent
Fig. 1. The Counter Check-in Process
K. Marintseva. Comparative analysis of check-in technologies at the airport 99
One of the foreign airlines applies the common
flights check-in method, however, only on a few
(about 4) allocated for it counters.
It was found that check-in areas of terminal D
has 61 check-in counters and 6 SSK, 18 aviation
security points, 28 passport control desks. As it is
declared in .
Terminal D can accommodate up to 10 million
passengers annually or 3000 passengers per hour
both for arrival and for departure.
For the purpose of identifying «queue» problems
at the counters at the new terminal D of Boryspil
airport, an analysis of the check-in process was
performed by observation method with the
subsequent processing of statistical data.
The check-in process was observed on the flights
from Kyiv (IEV/ KBP) to Moscow (MOW), Warsaw
(WAW), Almaty (ALA) and Tallinn (TLL). Check-
in for flights to MOW, ALA and TLL started before
2 h of the flight departure and closed before 30 min
Check-in for WAW started 1 h 50 min before the
scheduled departure time because of the flight from
WAW had been delayed. Check-in for TLL and
ALA has been opened on 3 check-in desks and for
MOW and WAW on 4 desks. The separate check-
in was provided for passengers of business and
economy class on all flights.
The used single flight check-in technology involves
the opening of a number of desks depending on the
aircraft load to a maximum of 50 passengers on one
check-in counter, but not less than two.
4. Passenger arrival distribution pattern
Fig. 2 clearly shows the peakedness of the arrival
pattern, because more than 60% of the passengers
arrive more than 2.5 h before scheduled time of
departure (STD) (excluding flight to TLL).
Fig. 2. Arrival pattern
The probability distribution of the passengers
arrival before STD (Fig. 3) depends on many
factors, the main of which are: methods of service
and the percentage of transfer passengers.
Fig. 3. Probability plot of passenger arrival time
Naturally at the check-in desks on flights to
MOW, WAW, ALA before the opening of check-in
were observed long queue, almost evenly distributed
between the desks.
The queue length depended on aircraft load.
So, queue in front of the economy class check-in
counter before 2 h of departure to MOW was about
35-40 passengers, to WAW and ALA about 30
For flight to TLL peak load started at approximately
before 1 h 40 min of departure, the queue in front of one
check-in counter was about 15 passengers.
CUSS technology for the MOW flight check-in
has been used by 3 passengers (1.7% of the total), 13
passengers (7.4%) took advantage of web-check-in.
9 (8.74 %) passengers used check-in via CUSS kiosk
to WAW, while 6 passengers (5.83%) embraced the
opportunity to web-check-in.
The results of the check-in to ALA showed that
self-checked-in up to 14 passengers, including 8
passengers (10.8%) that used CUSS kiosk.
5. Processing time
The processing time for each check-in process is
shown in Table1.
The average processing time per passenger at the
check-in counter was 3.51 min with a standard
deviation of 4.77 min for MOW flight against the
assumption that it takes less than 1.1 min (according
to calculations, which are set out below).
100 ISSN 1813-1166 print / ISSN 2306-1472 online. Proceedings of the National Aviation University. 2014. N 2 (59): 97–104
Table 1. Check-in time (in minutes per passenger)
in terminal D
IEV - MOW
CUTE 3.51 0.40 19.00 4.77 160
CUSS 1.15 0.92 1.55 0.34 3
IEV - ALA
CUTE 1.92 0.60 4.50 1.30 60
CUSS 0.95 0.70 1.30 0.19 8
IEV - WAW
CUTE 1.58 0.50 4.00 1.03 88
CUSS 0.93 0.70 1.10 0.13 9
CUTE 3.24 0.60 13.00 3.26 56
CUSS - - - - 0
The following characteristics to MOW flight
practically all passengers had a lot of baggage,
which required additional time for handling;
check-in of passengers for which the MOW
was the transfer point required additional time to
explain them the details of further travel;
processing time could increase up to 19 min per
passenger if check-in agents had to consider a
problem of any immigration documents and visa.
For other observable flights the time of one
passenger check-in also considerably increased
when passenger had a lot of baggage or excess
baggage or when agents demanded of additional
documents regarding immigration procedures.
It was also established that the procedure of an
Unaccompanied Minor (UM) check-in for the
IEV-TLL flight took about 40 min.
In addition, for this flight the passengers could
not use the registration by CUSS kiosk, because
airline did not provide this service.
For all observed flights it is true that the
processing time for the passenger who had some
experience of using CUSS kiosk was significantly
less than other.
Most of the passengers needed assistance in
completing the process. The location of the CUSS
kiosk must be very easily visible before the
passenger could see the check-in counters.
Minimum processing time (24 s) was achieved
when passengers without baggage were being
checked-in. And it could be seen that the minimum
processing time at check-in counters is smaller than
at kiosks. This is a result of the efficiency of the
6. Queuing Time
The other important aspect that was observed in the
process is the waiting times for each passenger.
Fig. 4 allows making of assumption that the
number of arrived passengers for check-in is
determined by Poisson distribution.
Fig. 4. Probability distribution of processing time on
Obtained by observation data also confirms the
hypothesis that the service time has exponential
distribution (Fig. 4).
This means that for estimation of the average
time of waiting in a queue and staying in the check-
in area of passenger arrived before 2 h of STD is
possible to use the M/M/s with finite source of jobs
model of the queuing theory .
Presented in Table 2 results of calculations
corroborate the obtained in monitoring of the flights
check-in process factual data.
Table 2. Check-in queue characteristics
(M/M/S with finite source of jobs)
Total number of passenger 90
Arrival intensity, passengers per minute 1,5
Service parameter, passengers per
The number of check-in counter 3
Check-in counter use factor, % 100
Probability that the counter is empty P(0) 0,0000
Expected queue length Lq, passengers 86,2000
Expected number of passenger in system
Expected time in queue Wq, min 71,8333
Expected total time in system
W, min 74,3333
Probability that passenger waits 1,0
K. Marintseva. Comparative analysis of check-in technologies at the airport 101
So, if it is necessary to check-in 90 passengers
using three counters, the waiting time in a queue
may take up to 1 h 11 min.
Because of more than 90 % of passengers arrive
before the check-in opening, it is clear that the
probability of waiting in the queue equal to 1.
Note that maximum number of passengers
waiting for the services was 0 for CUSS kiosks
against 45 in the case of check-in counters.
But check-in observation revealed cases when the
self-checked-in passengers had to stand in the
general queue to check-in their baggage.
Probably there is a problem with informing
passengers that Baggage Drop-Off desks are
Thus, the passenger with baggage needs to spend
a lot of waiting time in the queues using both check-
in counter and self-check-in kiosks techniques.
To maintain passenger comfort it will be
necessary to reduce waiting time, implying the more
resources during peak arrival.
7. Dynamic opening and closing of check-in counters
The availability of 61 check-in counters in terminal
D can actually provide service of 3,000 passengers
per hour (or 50 passengers per minute) if the time of
one passenger check-in does not exceed 1.1 min.
This statement can be proved by the
recommendations of the IATA  for the calculation
of the terminal are a optimal characteristics.
If the maximum passenger traffic is known the
optimal number of check-in counters N can be
found by the formula according to :
N t (1)
where pas the intensity of the arrival passenger,
passengers per minute;
t the average time of service, min.
However, the formula (1) seems to be more
applicable in situations of only common check-in.
It means that a passenger will be able to check-in
from any counter to any destination.
The queueing theory has a number of models for
calculation of optimal number of check-in counters
depending on the traffic flow. For example, in 
formula is used
pax wf w
N t tP t t (2)
where tw the maximum waiting time in the queue
estimated for passenger service, min;
W the probability that all counters are busy;
P ( f w
t t) the probability that the actual
passenger waiting time in a queue may exceed the
estimated waiting time.
It is also easy to determine the optimal
characteristics of check-in system, including the
required number of check-in counters and SSK, by
applying the M/M/s basic model of the queueing
Just note that the effectiveness of CUSS kiosk at
the airport Boryspil could be significantly increased
if passengers would be better informed about self-
check-in technology and baggage handling at the
Baggage Drop-Off desks with obligatory indication
of their location in check-in area (this information
must be on the airport website).
Formula (2) and the queueing theory models can
be used in simulation either a single flight or a
common check-in flights group.
If there is no possibility to implement the
common check-in flights method, for optimization
of the single flight check-in process at the Boryspil
airport it is proposed to use a dynamic approach to
identifying a number of check-in counters.
The point of such approach consists in
determining the optimal check-in counters number
for given time before SDT, depending on the
number of arrived passengers for check-in.
So, having a flight check-in arrival statistical
database it is possible to make an arrival pattern and
then use it for simulate the check-in process.
The main thing of this approach is to fix the size
of the queue at the counter according to the
technology requirements and take into account the
actual time of service.
If the number of passengers in the queue
becomes longer than it is fixed than an additional
counters must be opened.
The optimal number of counters can be
calculated by using the appropriate model of the
If arrival passenger flow will decrease than
number of counters which must be closed is
Dynamic approach has already been described in
foreign papers [5, 7].
Lets consider the example of calculation of the
check-in counters optimal number if the common
check-in flights method is applied.
102 ISSN 1813-1166 print / ISSN 2306-1472 online. Proceedings of the National Aviation University. 2014. N 2 (59): 97–104
Suppose that the expected arrival intensity is
1000 passengers per hour (ten flights are checked-in
practically at the same time) (Table 3).
Table 3. Modelling of common check-in queue
Arrival intensity, passengers per minute 16,66
Service parameter, passengers per
The number of check-in counter 42
Total number of passenger per hour 1000
Check-in counter use factor, % 99,21
Probability that the counter is empty
Expected queue length Lq, passengers 117,4060
Expected number of passenger in
system L 159,0727
Expected time in queue Wq, min 7,0444
Expected total time in system W, min 9,5444
Probability that passenger waits 0,9392
Applying the M/M/s model we can determine
that 42 check-in counters service in rush hour and
the average service time equal 2.5 min per passenger
could dramatically reduce the passenger waiting
time. Arriving at the airport 2 h before departure, the
passenger will spend no more 10 min in check-in
area. It means that passengers will have enough time
before the flight departure, and he or she becomes a
potential customer for additional services (cafes,
shopping, etc.). And that, in turn, is important for the
development of airport non-aviation activities
(according to the Boryspil airport financial report
, the revenues from non-aviation activities were
only 18 % of the total income in 2011).
Next, using the same M/M/s model, we can
calculate the suitable characteristics of the check-in
area by simulating the process on the basis of
statistical data or taking into account the factual data
of passengers arrival (it requires a sensor for
counting the number of arrived passengers to the
check-in counters) and factual time of service.
So, 13 check-in counters can provide quick
service (less than 10 min) for 300 passengers per
hour (if the average service time is 2.5 min per
As noted above, the M/M/s model can be used
for simulating single flight check-in process.
Fig. 5 presents the results of simulation to
determine the optimal number of check-in counters
on the flight IEV-MOW for a given time before
departure with step of 30 min.
Fig. 5. Simulation of dynamic opening and closing of
check-in counters for IEV-MOW flight
Assumptions were made in calculations about the
possibility of opening check-in counters 4 h before
Dynamic approach in this example gives 7 min of
expected waiting time of passenger at check-in area.
1. Development of self-check-in technology at
Boryspil airport requires more informative and
initial assistance to passengers for self-printing of
2. Clear instructions concerning the location and
baggage handling technology on the Baggage Drop-
Off desk allow improving the quality and usability
of the CUSS kiosk.
3. The factual time of service at the check-in
counters may differ significantly from the estimated
one, depending on the pieces of baggage, the
presence of transfer points and the need to verify the
4. Introduction a dynamic approach to the
opening and closing of check-in counters allows
reducing the maximum passengers waiting time at
the check-in area from 1 h 11 min to 10 min.
5. Reducing the waiting time for the airport
formalities hypothetically may affect growth of revenues
from non-aviation activities at Boryspil airport.
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K. Marintseva. Comparative analysis of check-in technologies at the airport 103
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Received 3 April 2014.
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104 ISSN 1813-1166 print / ISSN 2306-1472 online. Proceedings of the National Aviation University. 2014. N 2 (59): 97–104
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Marintseva Kristina (1979). Candidate of Economics. Associate Professor.
Department of Air Transportation Management, National Aviation University, Kyiv, Ukraine.
Education: National Aviation University with a Degree in International Transportation Management, Kyiv, Ukraine
Research area: transport systems.