=Paper=
{{Paper
|id=Vol-3101/Paper25
|storemode=property
|title=Enhancement of the methodology for the selection of the optimal location of the Remote Tower Centre
|pdfUrl=https://ceur-ws.org/Vol-3101/Paper25.pdf
|volume=Vol-3101
|authors=Tetiana Shmelova,Nina Rizun,Svetlana Kredentsar,Maksym Yastrub
|dblpUrl=https://dblp.org/rec/conf/citrisk/ShmelovaRKY21
}}
==Enhancement of the methodology for the selection of the optimal location of the Remote Tower Centre==
https://ceur-ws.org/Vol-3101/Paper25.pdf
Enhancement of the Methodology for the Selection of the
Optimal Location of the Remote Tower Centre
Tatiana Shmelova1, Nina Rizun2, Svetlana Kredentsar3 and Maksym Yastrub1
1National Aviation University, Lubomira Huzara ave., 1, Kyiv, 03680, Ukraine
Gdansk University of Technology (Politechnika Gdańska), 11/12 Gabriela Narutowicza Street, Gdańsk, 80-233, Poland
2
3Holding SaaSEmpire, IT company BSG
Abstract
Consistent and coherent development of regional airports of Ukraine to ensure enhancement of the air
transportation network of Ukraine is one of the priorities outlined in the Ukrainian National transport
strategy. The remote tower concept can be considered as one of the enablers for the development of
the small regional airports of Ukraine. One of the steps of the implementation of the remote tower
concept is a selection of the location for the remote tower centre/module and its facilities which is vital
for the efficient and safe provision of air traffic services. The focus of the research is an enhancement
of a methodology for the selection of an optimal location of a remote tower centre described in the
previous research. The article elaborates on the factors that can have an impact on the decision of the
selection of the location of the remote tower centre (e.g., the density of traffic, availability of resources,
etc.) and provides a means to quantify and process the factors using the decision-making model under
uncertainty to select the optimal location and minimise impact and risks related to the implementation
of the remote tower centre.
Keywords1
airport, air traffic control, air traffic management, decision-making process, decision-making under
uncertainty, risk minimisation, regional airport, remote tower concept.
1. Introduction
A common issue for small regional airports across the world is a low level of air traffic that limits
their ability for development and often does not allow them to be profitable. However, at the same
time, these small regional airports provide necessary access points and expand the air
transportation network with distant and remote locations and contribute to the development of the
local economies [1, 2].
One of the tasks outlined in the National transport of Ukraine up to 2030 is to expand the air
transportation network of Ukraine through consistent development of the regional airport of
Ukraine that would serve as nodes in the air transportation network [3]. One of the ways to
CITRisk’2021: 2nd International Workshop on Computational & Information Technologies for Risk-Informed Systems, September
16–17, 2021, Kherson, Ukraine
EMAIL: shmelova@ukr.net (T.Shmelova); nrz@polygda.pl (N.Rizun); ksm-na@ukr.net (S.Kredentsar); yastrubmi@ukr.net
(M.Yastrub)
ORCID: 0000-0002-9737-6906 (T.Shmelova); 0000-0002-4343-9713 (N.Rizun); 0000-0002-7731-138X (S.Kredentsar); 0000-0002-
7434-0310 (M.Yastrub)
© 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
accomplish this task is to reduce the air transportation costs for airspace users and attract more
flights to the regional airports of Ukraine.
Typically, airspace user costs for a flight consists of various components such as costs of
maintenance and fuel, airport charges, air navigation services costs and so on. A decrease in one
of these costs could lead to the overall reductions in the costs of air transportation and thus make
flights to regional airports more attractive for airspace users.
One of the significant costs in the overall costs of a flight is the provision of air navigation
services, specifically air traffic control in airports [4]. The decrease in air navigation service costs
can be achieved through optimisation of the operational costs and enhancement of the overall
efficiency of their provision. This has been addressed by several Single European Sky Air Traffic
Management (ATM) Research (SESAR) solutions that were developed to improve the current
operations at the airport and provision of the air traffic services (ATS). A few of those solutions
are dedicated to the use of the remote tower concept for different operating scenarios and
environments. This concept allows increasing the operational efficiency, flexibility, and safety at
airports where building or maintenance of a conventional tower is not economically beneficial.
The flexibility component becomes of utmost importance due to the issues experienced by the
aviation industry as the result of the COVID-19 pandemic [5].
One of the stages of the implementation of the remote tower concept is the selection of the
location for the remote tower centre/module and its facilities which is vital for the efficient and
safe provision of the air traffic services. The focus of this research is to enhance a methodology
for the selection of an optimal location of a remote tower centre described in [5]. The research is
focused on the factors that can have an impact on the decision of the selection of the location of
the remote tower centre (e.g. density of traffic, availability of resources, etc.) and provides a means
to quantify and process the factors using the decision-making model under uncertainty to select
the optimal location and minimise impact and risks related to the implementation of the remote
tower centre.
2. Analysis of the current state of the Ukrainian regional airports
To analyse the current state of the regional airports, it is necessary first to establish which airports
can be classified as regional ones in Ukraine. There is no single definition of the regional airports
thus it can vary from the context in which it is used. According to Airports Council International
(ACI) Europe, an airport can be considered as a regional if in general:
● serves short and medium-range flights;
● serves point-to-point connections [6].
European Commission defines regional airports as ones that have less than 3 million passengers
per year [7]. Also, airports can be split into two types: hub and feeder. Hub airports are used to
create a widespread air transportation network that connects a high number of flights with different
departure and destination airports with transit in the hub. The feeder airport is one of the branches
of such air transportation network and feeds the hub airports with connections to remote
regions [8].
The airport network of Ukraine is composed of 29 certified airports (16 of which can serve
international flights). Six airports (Kyiv Boryspil, Kyiv Zhuliany, Odesa, Lviv, Kharkiv and
Dnipro) are considered strategic airports [9]. Thus for the Ukrainian context, regional airports can
be defined as airports with a low number of flights, which serve point-to-point connections of short
or medium range and provide connections for hub airports and are not considered as strategic
airports.
Using the abovementioned definition of the regional airport, the following airports of Ukraine
can be classified as regional ones: Poltava, Kherson, Rivne, Sumy, Vinnytsia, Zaporizhzhia,
Uzhorod, Ivano-Frankivsk, Chernivtsi, Kropyvnytskyi, Kryvyi Rih, Mykolaiv, Kaniv Pekari,
Ternopil, and Cherkasy. Five of those airports (Mykolaiv, Kavin, Pekari, Ternopil, and Cherkasy)
provide aerodrome flight information service (AFIS) while others – air traffic service (ATS) in a
conventional manner (using a facility, e.g., air traffic control tower located at the corresponding
airport).
Most of the airports provide ATS or AFIS services for at least 8 hours a day (with some
exceptions for weekends and holidays) which means that their air traffic control or flight
information service units have to be manned by at least 4 air traffic control officers (ATCO) or
aerodrome flight information service officers (AFISO) to ensure the safe and orderly provision of
the services [10, 11].
For the period from June 2016 to January 2021 regional airports of Ukraine have served on
average from 0 (the lowest) to 12 (the highest) number of regular flights per day meaning that the
resources of the ATCOs/AFISOs were not used in the most efficient way. The distribution of the
number of regular flights in the regional airports of Ukraine is presented in Figure 1 [12].
Figure 1: Average amount of daily flights (only for airports with more than 1 flight/day) for
Ukrainian airports in the period from June 2016 to January 2021 [12]
Apart from that, some of the regional airports of Ukraine are affected by the seasonal variability
of air traffic. This can be clearly seen in Figure 2 – more traffic during the summer season due to
regular charter flights to touristic destinations and less or none during winter. The rapid drop in
the number of flights for airports in the period from February 2020 to August 2020 can be
explained by the restrictions introduced across the world due to the COVID-19 pandemic.
Due to the seasonal variability and low level of air traffic at the regional airports of Ukraine, it is
not efficient to maintain local aerodrome control towers or aerodrome flight information service
units to provide services to a small number of flights. One of the possibilities to optimize the use
of the resources and increase their flexibility at regional airports of Ukraine is to deploy a remote
tower concept that will be further detailed in the next section. [5]
Figure 2: Evolution of the number of flights in regional airports of Ukraine over time (only for
airports with more than 1 flight per day) [12]
12
9,634117647
9,481176471 9,327058824
10
Average number of flights
8,055294118 8,089411765
8 7,207352941 7,044117647 7,165882353
7,036470588
6,754117647 6,422058824
5,997058824
6
4
2
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Figure 3: Distribution of average number of flights in regional airports of Ukraine per month (only
for airports with more than 1 flight per day) [12]
3. Remote tower concept and its implementation
The core of the remote tower concept is the provision of air traffic services to one or multiple
airports from a remote location. That’s means that, in comparison with the conventional aerodrome
control tower or AFIS unit, ATCO or AFISO do not have to be physically located at the airport to
be able to provide services to it.
To provide ATCO/AFISO with the ability to visually observe and monitor the situation at the
aerodrome and its vicinity, a set of cameras located at the aerodrome is used to provide out of the
window (OTW) view. This OTW view can be also combined with data from other sensors (e.g.
surface movement radars, ADS-B, and so on) to increase the situational awareness of the
ATCO/AFISO. [13, 14, 15]
Different configurations have been envisaged for the implementation of the remote tower
concept: remote provision of ATS to a single airport, remote provision of ATS to multiple airports
and provision of remote ATS in contingency cases.
For the provision of the remote ATS, a remote tower module (RTM) that combines CWP and
OTW view is set up. The RTM might contain more than one position (for example, for another
ATCO or remote tower supervisor) depending on the complexity of the traffic and operating
environment.
For the provision of the remote ATS to multiple airports, there are two possible configurations:
sequential (RTM is connected to multiple airports but serve one airport at a time) or simultaneous
(RTM is connected to multiple airports and serve multiple airports at the same time). The high-
level diagram of the remote tower concept implementation is shown in Figure 3. [14, 15, 17]
Figure 3: High-level diagram of the remote tower concept implementation
Conducted large-scale demonstrations showed that the most optimal implementation option in
terms of the use of resources and reduction of the costs is a grouping of multiple RTMs in a
centralised facility which is called remote tower centre (RTC). [18]
Sweden is the first country that has successfully implemented the remote tower concept in its
airports. In 2015 a fully operational remote tower has been deployed at Örnsköldsvik airport with
cameras located at the Örnsköldsvik airport and remote tower centre at Sundsvall airport. Later,
the remote tower centre has been enhanced to also cover Sundsvall Timra airport.
At the end of 2020, Norway has opened the largest in the world remote tower centre located in
Bodø. The final goal is to provide remote ATS to 15 airports in Norway by 2022. [19]
Another country that decided to implement the remote tower concept is Germany. Deutsche
Flugsicherung (DFS), German air navigation service provider (ANSP) has launched a project to
provide remote ATS to three airports: Saarbrucken, Dresden, and Erfurt. In 2018, ATCOs of
Saarbrucken airport have been moved to Leipzig where a remote tower centre has been opened. It
is planned to move the provision of ATS for Dresden and Erfurt to Leipzig as well. [20, 21]
Several other countries have decided to follow the same approach and launched projects to
implement the remote tower concept. Those are – Belgium, the United Kingdom, Hungary,
Denmark, etc.
4. Factors influencing the decision of the selection of the location for a
remote tower centre
Selection of the location and facilities for the remote tower centre is one of the steps that have to
be considered during the planning of the implementation of the remote tower concept. [17] In [5]
an initial methodology for the selection of an optimal location for a remote tower centre has been
described. However, it has been identified that the methodology is based only on one factor while
a decision for the selection of the optimal location is influenced by multiple factors. The purpose
of this research is the identification of those factors and enhancement of the methodology with
them. The selection of the criteria is based on the subject-matter expertise due to the lack of
information and research of factors influencing the selection of the location of the remote tower
centre.
The first factor has been identified and partially described in the initial methodology – the
distance between a possible location of a remote tower centre and airports within a segment. The
initial methodology allows the grouping of airports into segments and obtaining a set of
coordinates of an optimal location of the remote tower centre from the point of view of
minimization of the distance between the RTC and airports within a segment.
The minimal distance is required to ensure stable and reliable network performance (through
minimization of network latency or data transmission delay) since the remote tower concept relies
heavily on real-time video and audio transmission for the cameras and communication
infrastructure (e.g., radio equipment) located at the airport to the remote location. With the higher
distance between remote locations and airports, it might not be possible to achieve the required
level of network performance and render the provision of remote ATS unsafe. Thus, the first factor
can be calculated as a difference between a possible location of the RTC and an optimal location
of the RTC calculated by the initial methodology [5, 15].
The second factor that has to be taken into account is the density of the traffic at the airports
within the segment. The higher the density of the traffic at the airport, the more often resources of
the RTC will be dedicated to that airport. That means also that there will be more data exchanged
between that airport and the RTC. Besides that, the airports with higher density will have more
human resources available to serve the higher number of aircraft. Placing the RTC closer to or at
the high-density airport might allow to make use of those human resources and reduce the number
of relocations.
Another factor (linked to the previous one) is the availability of the personnel at the possible
location of the RTC. A pool of qualified resources (ATCOs or AFISOs) is needed to satisfy the
needs of the RTC to be able to efficiently serves airports within the segment. In case of the lack
of resources or their absence, the personnel will have to be redeployed from another location that
could lead to additional expenses for the implementation of the RTC as well as issues with social
dialogue between personnel and organisation.
The fourth factor that has to be considered is the remoteness of the Communication, Navigation
and Surveillance (CNS) equipment from the possible RTC location. Even though it is relatively
common to have CNS (e.g. non-directional beacons, radio communication stations, etc.)
equipment collocated with the airport, however, that’s not the case for some airports, thus this has
to be considered as well. The RTC has to be located within a reasonable distance from the CNS
equipment to ensure that the reliable connection between the RTC and the equipment is ensured.
The last factor identified as part of this research is technical capabilities at the possible location
of the RTC. The deployment of the RTC requires the installation of data centre infrastructure (to
process and store information), controller working positions, supervision positions, etc. It also
poses certain requirements on the physical space needed for the remote tower modules, on the
power supply needed for the RTMs and data centre and so on [17]. Availability of the needed
infrastructure and technical capabilities would facilitate the deployment of the RTC.
To assess the factors and support the decision-making process for the selection of the optimal
location of the RTC, the decision-making under uncertainty methodology can be used. This
methodology is suitable for cases with a high level of data incompleteness and uncertainty for:
decision-making under stochastic risk (uncertainty) conditions when data can be
●
described using the probability distribution. In this case, the alternative solutions are
compared from the point of view of minimisation of expected losses. The optimal
solution would be the one that corresponds to a minimum loss:
𝑅𝑅 ∗ = 𝑚𝑚𝑚𝑚𝑚𝑚 {𝑅𝑅𝑖𝑖 }, (1)
where Ri – expected losses from the solution Ai
● decision-making under risk (uncertainty) when probability distributions are not
available.
The decision-making under uncertainty methodology allows defining payoff and risk matrixes
for the alternative solutions and factors influencing the decision-making process and analysing
them using various criteria (Minimax or Wald, Laplace, Savage, and Hurwicz) [22].
The payoff matrix for the selection of the optimal location of the remote tower centre is
represented in Table 1. The factors λ1 - λ6 are the ones described above:
● 1 – the remoteness of the possible location of the RTC from other airports within the
segment;
● 2 – density of the traffic at the possible location of the RTC;
● 3 – availability of the personnel at the possible location of the RTC;
● 4 – the remoteness of the CNS equipment;
● 5 – technical capabilities at the possible location of the RTC;
Table 1
Payoff matrix for the selection of the optimal location of RTC
Factors
Alternative decisions
1 2 3 4 5
Location 1 u11 u21 u31 u41 u51
Location 2 u12 u22 u32 u42 u52
…. … … … … …
Location n u1n u2n u3n u4n u5n
The cost of every alternative decision for each factor is described by uin. The values for each factor
are calculated as following:
● u1n is determined as a difference between the optimal location for the remote tower
centre from the point of view of minimization of the distance between RTC and airports
within the segment (calculated with the help of the initial methodology) and the
possible location of the RTC. The lowest value of the difference is ranked as 0 and the
highest as n, where n is a number of possible alternative locations.
● u2n is determined based on the density of traffic at the possible location of the RTC. If
the possible location of the RTC is not an airport, then the density of the closest airport
is assigned to that possible location. The location with the highest density is ranked as
0 and with the lowest – as n.
● u3n is calculated based on the amount of personnel available at the possible location of
the RTC. If the possible location of the RTC is not an airport and there is an airport
within a commutable distance (e.g. 50 km) then the amount of personnel available at
the airport is assigned to that location. Otherwise, the value of the available personnel
for that location is equal to 0. The possible location with the highest value of the
available personnel is ranked as 0 and with the lowest – as n.
● u4n is defined similarly as u1n – as a difference between the optimal location for the
RTC from the point of view of minimization of the distance between the possible
location of the RTC and CNS equipment within the segment. The lowest value of the
difference is ranked as 0 and the highest as n.
● u5n is determined as an expert estimate of the technical capabilities of the possible
location of the RTC since the setup of each airport or possible location can vary
significantly and that’s why requires expert assessment. The possible location of the
RTC with the best technical capabilities would be ranked as 0 and the lowest as n. For
this research, all possible locations of the RTC co-located with an airport will receive
the same value – 0 and those that are not co-located – 1.
The payoff matrix with values is analysed using four criteria: Wald (minimax), Laplace, Hurwitz,
and Savage. The Wald or minimax criterion implements a principle of “conservative attitude” and
provides a means to find the best option out of the worst ones (stable, guaranteed result):
𝐴𝐴∗𝑊𝑊 = �𝑢𝑢(𝑎𝑎𝑖𝑖 , 𝑗𝑗 ) � , (2)
∗
where 𝐴𝐴𝑊𝑊 - the evaluation function for the Wald criterion for the payoff matrix; 𝑢𝑢(𝑎𝑎𝑖𝑖 , 𝑗𝑗 ) –
costs for alternatives ai and factors λj.
The Laplace criterion is based on the principle of insufficient reason, according to which all
of the factors λj have equal weights for the decision-making process:
𝑚𝑚
𝐴𝐴∗𝐿𝐿 = �� 𝑢𝑢(𝑎𝑎𝑖𝑖 , 𝑗𝑗 ) � , (3)
𝑗𝑗=1
where 𝐴𝐴∗𝐿𝐿 - the evaluation function for the Laplace criterion for the payoff matrix; 𝑢𝑢(𝑎𝑎𝑖𝑖 , 𝑗𝑗 ) –
costs for alternatives ai and factors λj; m – number of factors.
The criterion of Savage aims at reducing conservatism of the Wald criterion by replacing the
payoff matrix with the risk matrix (Table 2):
𝐴𝐴𝑆𝑆∗ = �𝑟𝑟(𝑎𝑎𝑖𝑖 , 𝑗𝑗 ) �, (4)
𝑟𝑟�𝑎𝑎𝑖𝑖 , 𝑗𝑗 � = 𝑢𝑢�𝑎𝑎𝑖𝑖 , 𝑗𝑗 � − 𝑚𝑚𝑚𝑚𝑚𝑚�𝑢𝑢(𝑎𝑎𝑖𝑖 , 𝑗𝑗 �,𝑎𝑎𝑖𝑖 (5)
∗
where 𝐴𝐴𝑆𝑆 - the evaluation function for the Savage criterion; 𝑟𝑟(𝑎𝑎𝑖𝑖 , 𝑗𝑗 ) – elements of the risk
matrix for alternatives 𝑎𝑎𝑖𝑖 and factors 𝑗𝑗 .
Table 2
The risk matrix for Savage criterion
Factors
Alternative decisions
1 2 3 4 5
Location 1 r11 r21 r31 r41 r51
Location 2 r12 r22 r32 r42 r52
…. … … … … …
Location n r1n u2n r3n r4n r5n
The Hurwitz criterion provides a more complete approach to assess the alternative options
covering the most optimistic and pessimistic approaches:
𝐴𝐴∗𝐻𝐻 = �𝛼𝛼𝛼𝛼�𝑎𝑎𝑖𝑖 , 𝑗𝑗 � + (1 − 𝛼𝛼)𝑢𝑢�𝑎𝑎𝑖𝑖 , 𝑗𝑗 � � , (6)
where 𝐴𝐴∗𝐻𝐻 - the evaluation function for the Hurwitz criterion; 𝛼𝛼 – optimism index (0 ≤ 𝛼𝛼 ≤ 1)
[22]. The results of the calculations can be summarized in Table 3 for analysis.
Table 3
Processed payoff matrix for the selection of the optimal location of RTC
Alternative Factors Criteria
decisions Wald Laplac Savage Hurwit
1 2 3 4 5 e z
Location 1 u11 u21 u31 u41 u51 𝐴𝐴1𝑊𝑊 𝐴𝐴1𝐿𝐿 𝐴𝐴1𝑆𝑆 𝐴𝐴1𝐻𝐻
Location 2 u12 u22 u32 u42 u52 𝐴𝐴2𝑊𝑊 𝐴𝐴2𝐿𝐿 𝐴𝐴𝑆𝑆2 𝐴𝐴2𝐻𝐻
…. … … … … … … … … …
Location n u1n u2n u3n u4n u5n 𝐴𝐴𝑛𝑛𝑊𝑊 𝐴𝐴𝑛𝑛𝐿𝐿 𝐴𝐴𝑆𝑆𝑛𝑛 𝐴𝐴𝑆𝑆𝑛𝑛
5. Selection of the optimal location for the RTC using the described
methodology
To demonstrate how the methodology can be applied in practice, one of the segments (Segment
1) calculated in the initial methodology [5] will be considered and an optimal location for the RTC
will be selected. As the result of the execution of the initial methodology [5], an optimal location
for the RTC from point of view of minimization of distances between the RTC and airports within
the segment has been identified (Figure 4).
Figure 4: Calculation of optimal locations for the RTC (to minimize distance) for Segment 1 (green
dots – initial coordinates; blue dots – refined coordinates)
A list of possible locations for the RTC can be composed of the calculated location of the RTC by
the initial methodology and airports within the segment: Uzhgorod, Chernivtsi, Ivano-Frankivsk,
Lviv. For each of the it is necessary to calculate values uij for factors identified in the previous
section. For factors λ1, λ4 it is enough to have coordinates of the airports and CNS equipment while
for factors λ2, λ3, and λ5 additional information is required. The density of the traffic per airport can
be retrieved from EUROCONTROL STATFOR Dashboard [9] and information about available
personnel at each airport can be retrieved from the operational hours of the aerodrome control
towers at the airports and regulations on working hours for ATCO/AFISO, taking into account
that at least two ATCO/AFISO (a controller and a supervisor) must be present at the workplace
during a shift [10, 11].
Based on this information, it possible to create a payoff matrix for the airports in segment 1
and calculate criteria for each alternative option (Table 4).
Table 4
Processed payoff matrix for the alternative options in the segment 1
Factors Criteria
Alternative Wald Laplace Savage Hurwitz
decisions 1 2 3 4 5
RTC calculated 0 1 1 1 1 1 0,8 1 0,5
location
Uzhgorod 4 3 3 4 0 4 2,8 4 2
Chernivtsi 3 2 2 3 0 3 2 3 1,5
Lviv 2 0 0 3 0 3 1 3 1,5
Ivano-Frankivsk 1 1 1 0 0 1 0,6 1 0,5
According to the four criteria, the most suitable location for the RTC in segment 1 for the defined
factors is at the airport of Ivano-Frankivsk since it scores the lowest in each criterion.
The presented methodology can be applied to other segments of airports within Ukraine or any
other group of airports in other countries. The list of factors defined is not finite and can be
extended if a local context requires that. The use of the methodology and the criteria (Wald,
Laplace, Savage, and Hurwitz) will ensure that all factors are taken into account when making a
decision about an optimal location of the Remote Tower Centre.
6. Conclusions
An increase in the level of traffic at regional airports of Ukraine is an important enabler of their
development and therefore enhancement of the Ukrainian air transportation network. The
reduction of the costs (air navigation costs, airport charges, etc.) for airspace users is one of the
ways to attract more flights to the Ukrainian airports.
One of the ways to reduce one of the airspace user costs – air navigation service costs – is
through the increase in the operational efficiency and use of the resources for the provision of the
air traffic services at the airport. This can be achieved through the implementation of the remote
tower concept at the airport.
Selection of a location for a remote tower centre and facilities for it is one of the steps that has
to be considered during the implementation of the remote tower concept [12]. The decision for the
selection of the optimal location of the RTC is influenced by multiple factors. The initial
methodology to support the decision-making process for the selection of the optimal location has
been developed and described in [5], however, focusing only on one factor. The purpose of this
research was to identify additional factors and enhance the methodology with them.
The enhanced methodology takes into account different factors such as density of the traffic,
availability of the resources, technical capabilities, etc. and utilizes decision-making under an
uncertainty model to assess the factors and select the optimal location based on them to minimise
the impact and risks related to the implementation of the remote tower centre. The methodology
allows defining a payoff matrix for the alternative options and factors influencing the decision-
making process and analyzing them using various criteria (Minimax or Wald, Laplace, Savage,
and Hurwicz). It can be used for different segments of airports in Ukraine or any other group of
airports in other countries.
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