The authors present a new objective-subjective approach to conflict management to ensure proper collaboration of different aviation personnel using decision-making (DM) methods in Certainty, Risk, and Uncertainty. For improvement of outcomes of the collective solutions the collaborative decision-making (CDM) models are used, when is difficult to make the final right decision based on many factors influencing DM of different aviation specialists (pilot, air traffic controller, flight dispatcher) during the development of an emergency in flight. The Integration of Uncertainty Models to the Collective Model of CDM has been presented. An example is presented - the building of individual models and CDM models for the pilot-incommand, flight dispatcher, and air traffic control officer in bad weather conditions (lightning strikes and thunderstorm activity) during the approach of aircraft. The optimal landing aerodrome was chosen for landing in bad weather conditions.
In the process of aviation industry development, safe air transportation is the core objective of the
functioning of the aviation system. But despite the rapid and constant growth from the point of
developed technologies applied in the operational processes of air traffic control, flight planning,
modern airplanes manufacturing, and improvement of hours flown by pilots and flight performance, the
number of aviation accidents does not decrease. Detailed aviation accident statistics are presented in
the Annual safety reviews of the European Aviation Safety Agency (EASA) and the guide to European
statistics "Statistics Explained" [1; 2]. According to the published data from the EASA, the number of
aviation accidents during the last years has grown [
4. Availability of single guidance for multiple users for non-conflict decision-making (DM), especially in emergency situations 5. The influence of the socio-technical environment and non-professional factors (psychophysiological, individual psychological, socio-psychological) on the person
Most of these reasons belong to human factor. Human error is considered the first cause of accidents
[2; 3; 4]. Indeed, as many safety scholars affirm, human error is only an epiphenomenon, that is a
secondary phenomenon that occurs alongside or in parallel to a primary event. The real cause of
accidents which induces an error are human performance and limitations, poor teamwork,
organizational pressure on the professionals in the team to obtain unreasonable performance, faulty
human-machine interaction, and conflict interaction of professionals in important DM too [3; 4]. It’s
clear, human factor should be included for progressive and sustainable development and safety
enhancement of the complex aviation system. Safety is the functioning of certain operational processes
in the aviation systems with the objective of controlling the safety risks of the outcomes of hazards
during operation. International Civil Aviation Organization (ICAO) developing proactive approaches
for the safety provision based on risk and human performance assessment [
The main actions of aviation specialists in accordance with the stage aircraft operation are presented in the Table 1.
Responsible for flight planning and organization, for
choice of the optimal flight route, alternate aerodromes,
and proper fuel amount calculation for definite flights,
regulated by international and national documents,
orders, and instructions for the normal and abnormal
operational environment of aircraft [
flights of aircraft in the control sector
of airspace
Sometimes specialists from other fields, such as emergency and ground services, and medical staff may be involved in joint DM (Figure 1). For example, the digital health and telemedicine in emergencies are applied, allowing to invitie qualified medical personnel for a consultation in case of incapacitation of one of the pilots or one of the passengers [10; 11].
Figure 1: The team of human‐operators involved in Collaborative Decision‐Making during the flight
Mostly, the complexity, content, particularity of documents, regulations of the professional activity of each aviation personnel are different, which does not allow to develop the general algorithm of actions for all aviation staff in a specific situation, especially for difficult in-flight conditions, where the uncertainty, lack of information and time for DM take place. That’s why arises the conflict between actions and decisions of involved staff who making the decisions at the same time for one situation. Therefore, to ensure proper collaboration and conflict resolution between different aviation personnel for improvement of outcomes of group decisions, it is necessary to implement new approaches for conflict management and integrate DM stochastic and non-stochastic models for Air Navigation System (ANS) operators, especially in an emergency [12; 13].
In the concept of the Global Air Navigation Plan developed by ICAO [14], the proper collaboration is possible through the provision of air traffic management system (ATM) members with an environment that ensures enough storage of significant information and its proper usage among ATM system. In this environment, all members closely interact with each other in making common decisions and achieve so-called Collaborative Decision-Making (CDM). This concept foresees the improvement of the whole performance of the ATM system in general taking into consideration the individual performance of ATM system members. This approach allows choosing the direction of action with respect to selected objectives, based on decisions made by each participant, and information exchange influenced those decisions, applying main DM principles [15]. That is why ICAO promotes the global implementation of performance management principles, gradually transferring the existing ATM systems to performance-based global ANS. The performance-based approach (PBA) is a mean of establishing the performance management process and is based on three principles of obtaining effectiveness of solutions [16]: A strong and competent focus on desired results of DM Conscious and rightly of DM Reliance on real facts and data for rational DM.
Hence, according to the ICAO requirements, the meeting of the day-to-day performance in operations may be achieved through the mechanism of Flight and Flow Information for a Collaborative Environment (FF-ICE) Concept [17]. Concept FF-ICE defines air navigation information requirements for flight planning, flow management, air traffic management, and trajectory management, and to be a basis of the performance-based ANS [17].
In the monograph, “Intelligent Automated System for Supporting the Collaborative Decision Making by operators of the Air Navigation System during Flight Emergencies”, was researched the PIC and ATCO CDM during flight emergencies using deterministic models in order to achieve the maximum synchronization of operators’ technological procedures. Collaborative Decision Models are created for only two operators such as PIC and ATCO [18]. The ability to reach a general consent on the desired outcome to be achieved by all ANS operators (FDs, flight crews, ATCOs, maintenance staff, ground handling personnel) in terms of performance results is the basic condition for the successful application of the approach for conflict management, especially in emergency situations [13]. The application of classical DM criteria under uncertainty makes it possible to take into account the factors influencing the choice and find collective solutions for several participants in the process [19].
The purposes of the work are: 1. Integration of DM stochastic and non-stochastic models of ANS operators in emergency 2. To build the individual DM models for the PIC, FD, and ATCO in an emergency and to determine a collective solution for all operators-participants of the process. 3. To consider an example of building CDM models for the PIC, FD, and ATCO in conditions of uncertainty when it is required to choose an optimal alternate aerodrome in bad weather conditions before the approach. 2. The Integration of Uncertainty Models to Collective Model of Collaborative
For the effectiveness of DM of human-operators (H-O)’s of ANS in emergency situations the integration of Stochastic, and Non-stochastic models has been proposed [4; 12; 13]. There are the next main steps of the Method of the Integration of Stochastic models (DM under Risk and Uncertainty) and Non-stochastic models (DM in Certainty):
1. Analysis of the development of the emergency situation (ES) and synthesis of DM models in accordance with conditions, factors, potential participants, and stages of the development of the event (Figure 2).
2. Building deterministic DM models using Network Planning methods and determining output results (Figure 2): critical time Тcr; Тmid; Тmin; Тmax critical paths of performance of actions of ANS operators in ES ambiguous situations S1, S2, and synchronization of H-Os actions using stochastic models alternate situations S and optimal CDM using stochastic models.
Figure 2: The deterministic DM models in ES for 3 human‐operators
3. Analysis of procedures of the main technology, conditions of development of ESs, information about problem and conflict situations, and using the effective integration of DM models:
If there is statistical information about the conditions of the development of the ES (the presence of probabilities of the development of the ES), then DM models under Risk conditions are applied and a decision tree is built (Stochastic Uncertainty DM models)
In the case of absence of statistical information and probabilities, there are the factors which influence on the development of the situation, then DM models under Uncertainty are applied and a
Structural analysis of the ES and building of the Stochastic Uncertainty DM model (decision tree) according to conditions the development situation. Definition of the number of DM stages and time of stage ti; relevant output data: Ai; pi; ui; βi (alternatives at each stage Ai; probabilities pi and outcomes ui for each alternative Ai; added risks βk influence on DM according to stages of the development situation, increasing threats due DM of H-Os. (Figure 3). Optimal solutions according to conditions of development of ESs. Risk R defined as:
(1) Ai – alternative decisions, А = {А1, А2, … Аi, …Аm}; pj – probability of development situation, p = {p1, p2, … pi, … pm}; uij - expected outcomes of alternative actions, U = {u1, u2, … ui, … um}; βi – added risk (increasing threats), depend from stages of the development situation; B = {β1, β2, … ti - time of stage of the development situation, T = {t1, t2, … t, …tm}.
Ai where ... βi, ...βm}; factors - λj matrix where
; Figure 3: The Stochastic Uncertainty DM models in ES with outcomes {U}=f (A; p; β, t) 4. Factor analysis of the ES and building non-stochastic DM model (Table 2) in accordance with factors that influence DM as DM matrix:
Alternative actions А = {А1, А2 … Аi … Аm} Factors influence on DM according to situation Λ = {λ1, λ2 … λj… λn}, j Outcomes uij depending on actions / alternatives Аi , influence of variable (uv) or static (us) 1,
For variable factors (uv) is required to consider the development of the situation - time ti (from
NonStochastic DM model) and probability pj (from Stochastic Uncertainty DM model). For static factors
(us) is required to consider the normative documents [
Ai Ai {A} {A} {P} {P} {U}=f(A; p; β, t) {U}=f(A; p; β, t)
t - time of development of ES; p – probabilities of development ES;
Matrix of DM in uncertainty, with variable or static factors
Variable factors influence DM
in critical situation uv11, ,uv1n uv2,… uv2n uv3,… uv3n critical situation us1,… usm us2,… usm us3,… usm 5. The optimal solutions are found using classical DM criteria under uncertainty (criterion Wald (maximin), criterion Laplace, criterion Hurwitz, criterion Savage) [19]. The choice of criterion depends on the type of aircraft, type of flight, the conditions for the development of the situation, the nature of the emergency. The short characteristic of criterion and flights:
(4) (5) (6)
, , , 1
, where where optimism. where
, rij – loss matrix for recalculations after DM: , , , 6. Integration of the deterministic, stochastic uncertainty (DM in Risk) and non-stochastic uncertainty (DM in uncertainty) models and determining optimal solution.
The flight pattern of an aircraft, the occurrence of an emergency (for example, when approaching the destination airfield, weather conditions have changed, bad weather conditions (BWC) is shown in
Figure 4: The scheme of aircraft flight route with possible alternative aerodromes
The decision for the selection of the alternate aerodrome in an emergency was implemented with the following output data (Table 3): The decision-making matrix Alternative actions - {А} = {А1, А2, … Аi, … Аm} of DM H-O in ES and aerodromes of take-off (A1), landing (A2) and alternate aerodromes (A2; A3; A4) States of nature or factors {Λ}= {λ1, λ2, … λj, … λn} – variable or conditionally static factors {Λ} and outcomes Us(Λ) influence on DM in ES. For example, DM in BWC (lightning strike and thunderstorm activity); “variable factor” - are meteorological conditions on aerodromes; “static factor” - available approach systems and aerodrome, crew, aircraft capabilities Outcomes of DM matrix {U} = u11, u12, …, uij, …, unm. Conditions of DM under uncertainty if this flight is performed for the first time - Criterion Wald (maximin) Table 3 Matrix of DM in uncertainty for solution optimal aerodrome in BWC
Alternative Meteorological Distance Fuel Aerodrome Crew Aircraft aerodromes situation reserve capability capability capabilities λ1 λ2 λ3 λ4 λ5 λ6
A1 Landing aerodrome
A2
Alternate aerodrome A3
Alternate aerodrome A4
Alternate aerodrome A5 u11 u21 u31 u41 u51 u12 u22 u32 u42 u52 u13 u23 u33 u43 u53 u14 u24 u34 u44 u54 u15 u25 u35 u45 u55 u16 u26 u36 u46 u56
The expected outcomes of the decision matrix are formed based on the influence of factors on DM, and the requirements of regulatory documents [6 – 9; 14 - 17], according to the Aeronautical Information Publication (AIP) too. It is proposed to evaluate the outcomes of the decision matrix using the Expert Judgment Method (EJM) [4; 19]. Each participant in the event - an aviation specialist fills in the decision matrix based on personal opinion. All matrices have the same factors that influence DM.
Outcomes of choosing of alternative solutions caused by factors influencing on DM {U} Alternative solutions {А} - the list of alternate aerodromes (AA): , , … , … , , alternate aerodrome - an aerodrome of departure (ADep - A1) and it’s characteristics; alternate aerodrome - an aerodrome of destination (ADest – A2) and it’s characteristics; other alternate aerodromes and it’s characteristics according to the calculated route – A3; A4; A5, .
Factors {Λ} influencing on DM for each operator (O1 - PIC, O2 - ATCO, O3 - FD, and Oi - other aviation specialists). These factors may be original or identical and objective (Table 3). For example, next factors:
{Λ} =λ1, λ2 …, λj, …, λm,
The Algorithm of the Collaborative Decision‐Making in conflict / emergency situation
The Algorithm of the CDM in conflict/emergency was obtained using the methods of DM under uncertainty for effective collective solutions of different aviation specialists in an emergency: where where where λ1 – fuel reserve on board; λ2 – remoteness of alternate aerodrome; λ3 – runway technical characteristics; λ4 – meteorological conditions on alternate aerodromes; λ5 – the approach lighting system; λ6 – available approach system; λ7 – available navigation aids; λ8 – aircraft performance characteristics; λ9 – the presence of radiocommunication; λ10 –air traffic intensity, etc. the case of emergency:
Outcomes {U} - formation of possible consequences {U} influencing on the selection of AA in {U} = U11, U12, …, Uij, …, Unm, {U} - set of outcomes of DM matrix Uij (i =1, … m; j =1, …, n).
The possible consequences Uij are defined by means of using the EJM according to data from the regulatory documentation and opinions of Oi operators (PIC, FD, and ATCO and other aviation specialists) [4; 6 – 9; 14 - 17].
Formation of the matrixes of solutions for each operator. Formation of the matrix 1 of solutions for the first operator (O1 - PIC) (Table 4).
Table 4 The DM matrix of DM in Uncertainty for operator O1
Factors influencing on DM for operator O1 ‐ PIC … λj u1j U2j … uij … umj … … … … … … … λn u1n u2n …. uin … umn
Analogically, DM matrix for the second operator (O2 - ATCO); the third operator (O3 - FD) and other operators who are involved in this situation (Figure 1).
To choose the methods of DM under uncertainty (equations (2) – (6)) considering the conditions of DM under uncertainty (type of flight, emergency, conditions of development of situation).
Finding optimal solutions for each operator using the criteria of DM under uncertainty: Wald,
А1* = Aj(O1) - solutions of PIC A(O1), А2* = Aj(O2) - solutions ATCO, А3* = Aj(O3) - solutions FD.
specialists) from individual matrixes. conditions from individual matrixes Aj(O1); Aj(O2); Aj(O3)
Formation of the collective matrix of solutions (Table 5), where: {А} – alternate aerodromes; {λ} – optimal opinions of all operators (O1 - PIC, O2 - ATCO, O3 - FD, and Oi - other aviation {u} – outcomes - optimal decisions of operators in accordance with the selected criterion / flight collective matrix
The DM matrix of DM in Uncertainty for operators
{А} А1 А2 … Аi … Аm
Results of optimal solutions by all operators Aj(O1) u*11 u*21 u*i1 … … u*m1
Aj(O2) u*12 u*22 u*i2 … … u*m2
Aj(O3) u*13 u*23 u*i3 … … u*m3
Aj(Oj) …. u*ij …. … … … … … … …
An(On) u*1n u*2n …. u*in … u*mn
Finding of optimal solutions for all operators using the criteria of DM under uncertainty: Wald, Laplace, Savage, Hurwitz. For example, for criteria of Wald (2): , where
2.1.1. The illustrative example of the Collaborative Decision‐Making in emergency situation
Lightning strikes may affect airline operations because of costly delays and serious disruptions to flight schedules [20; 21]. The Aviation Safety Network safety database gives the following lightning strike accident statistics [22]: 29 occurrences with the contributory cause of the lightning strike, including 14 losses of control. A lot of jet airplane lightning strikes occur while in clouds, during the climb and descent phases of flight than in any other flight phase. The reason is that lightning activity is more prevalent between 5,000 to 15,000 feet altitude. The probability of a lightning strike decreases significantly above 20,000 feet. That’s why airplanes flying short routes in areas with a high incidence of lightning activity are likely to be struck more often than long-haul airplanes operating in more benign lightning environments [22; 23; 24; 25].
communication failure electrical problems emergency descends pilot incapacitation.
pilot may be blinded by a lightning strike navigation system problems.
The situation considered in this work: bad weather conditions - lightning strike and thunderstorm activity closely to the destination aerodrome.
Initial data: 1. Airplane: Boeing 737 2. Route (Figure 5): Kyiv (Boryspil) (A1) - Odessa (A2). 3. Actual and forecasted weather conditions at the time of arrival to Odessa - thunderstorm activity in the vicinity of aerodrome, heavy shower rain, hail. 4. Alternate aerodromes [19]: Chisinau (A4); Kharkiv (A5); Alternate aerodrome, which can be chosen along the route: Dnipro (A3).
{F} - factors considered by operator O1 (PIC); {L} - factors considered by operator O2 (ATCO); {Λ} - factors considered by operator O3 (FD).
Considering the interaction of the PIC, FD, and ATCO, it is necessary to understand their roles and responsibilities. The FD is responsible for the planning of the flight, the PIC is directly responsible for the safe execution of this flight, ATCO provides ATC service, information, and assistance to the crews. Therefore, when making a decision, they analyze a general group of factors, cause the main purpose is the completion of the task (flight from point A to point B), including risk analysis, but from different points of view. And the final decision in flight makes the PIC.
For rational CDM, each operator involved in DM has analyzed and considered the current situation. There are 3 operators in the CDM process: PIC (O1), ATCO (O2), FD (O3) (Figure 1, Table 1). Each operator composed a matrix of decisions, where alternative solutions are alternate aerodromes for the route Kyiv - Odesa, and each operator considers the same factors in the current situation, but with different priorities.
The common factors for each operator (fj, lj, λj) taken into consideration when making a decision when approaching the destination aerodrome: f1, l1, λ1 – fuel reserve on board of the aircraft (always controlled); f2, l2, λ2 – meteorological situation (of departure, destination, alternate aerodromes, en-route); f3, l3, λ3 – aircraft capabilities (available equipment on board, MEL peculiarities, existing operating limitations); f4, l4, λ4 – aerodrome capabilities (available approach systems, technical characteristics of the runways and taxiways, lightning system, service hours restrictions, aerodrome category, firefighting and search and rescue category, emergency service); f5, l5, λ5 – crew capability (crew operating minima, crew duty time); f6, l6, λ6 – location of obstacles in approach, missed approach and departure sectors; f7, l7, λ7 – air situation (intensity of air traffic control sector, radio frequency overload); f8, l8, λ8 – commercial point (airport charges, distance from destination aerodrome, passenger and cargo service facilities, the presence of contracts with handlers, the presence of customs, border and migration control service, etc.).
These factors are objective. Composed the operators' DM matrixes when approaching to the destination aerodrome in BWC (Tables 6-9). Expected outcomes considered by the PIC (operator O1) represented in Table 6. The optimal solutions were determined according to the criteria Wald, Laplace, Horvitz, Savage (2) - (5). The solution according to the criterion of Savage was obtained from the loss matrix (6).
The optimal landing aerodrome during the approach on the route "Kyiv - Odessa" in accordance with the PIC's decision is as follows: by Wald criterion - Chisinau (A4) by Laplace criterion - Kyiv (A1) by the Hurwitz criterion - Chisinau (A4) according to the Savage criterion - Chisinau (A4)
Table 7 The DM matrix in Uncertainty for operator O2 (ATCO)
Factors {L}, influencing on decision‐ The matrix 2 making of ATCO (O2) l 1 l2 l3 l4 l5 l6 l7 3 10 4 8 8 4
The optimal landing aerodrome during the approach on the route "Kyiv - Odessa" in accordance with the FD 's decision is as follows: by Wald criterion - Chisinau (A4) by Laplace criterion - Kyiv (A1) by the Hurwitz criterion - Chisinau (A4) and Kharkiv (A5)
The optimal landing aerodrome during the approach on the route "Kyiv - Odessa" in accordance with the ATCO's decision as follows: by Wald criterion - Chisinau (A4) by Laplace criterion - Kyiv (A1) by the Hurwitz criterion - Chisinau (A4) according to the Savage criterion - Chisinau (A4)
Evaluation of optimal alternate aerodrome for landing in difficult meteorological conditions by FD at the stage of flight planning. Matrix of possible outcomes of DM by FD during choosing of alternate aerodromes at the stage of flight planning represented in Table 8. Table 8 The DM matrix for operator O3 (FD)
Factors {Λ}, influencing on decision‐making Solutions The matrix 3
of FD (O3)
according to the Savage criterion - Dnipro (A3)
To determine the consistency of operators, collective matrices were constructed, in which the factors in the decision matrixes for the operators (PIC (O1), ATCO (O2), FD (O3)) are identical, the solutions of the operators and taken from matrices, presented in Tables 6; 7 and 8. In the CDM matrixes used subjective factors – opinions of operators. The optimal CDM if this flight is performed for the first time is presented in the Table 9 (Wald criterion). In this case, the optimal landing aerodrome, determined by objective (fuel reserve on board of the aircraft; meteorological situation; crew, aircraft and aerodrome capabilities; location of obstacles in approach; air situation and commercial point) and subjective factors (PIC, FD, and ATCO) is alternate aerodrome Chisinau (A4).
The optimal CDM if this flight is regular (Criterion of Laplace) presented in the Table 10 – is Kyiv (A1).
The optimal CDM in different approaches using optimism-pessimism coefficient α=0,5 (criterion of
Collective decisions were analyzed with varying degrees of optimism-pessimism coefficient α=0,5. The consistency of decisions increases with an increase in the coefficient of optimism, with a decrease in the coefficient in the direction of pessimism, the mismatch increases.
FD O3 5 1 5 5 4 FD O3 8,0 6,1 6,0 6,8 6,9 FD O3 5,5 5,5 7 7 5,5 PIC O1 4 1 5 6 4 PIC O1 8,8 5,5 7,0 7,9 6,5 PIC O1 5,5 7 7,5 7 5,5
O2 1 1 4 5 4
O2 7,8 6,1 6,0 7,1 6,9
O2 5,5 7 7,5 7 5,5
Kyiv (A1) Odessa (A2) Dnipro (A3) Chisinau (A4) Kharkiv (A5) The CDM matrix for all operators (criteria Savage) – recalculation) FD O3 7 9 5 4 6 O3 3 5 1 0 2
CDM Savage 3 6 1 0 3 3 6 1 0 3
The consistency of decisions determined using the Savage criterion (the recalculation after a flight), were determined for cost initial matrix (Table 12): , , 3; 6; 1; 0; 3 0
, 3; 6; 1; 0; 3
The loss matrix presents on the Table 13. The loss matrix shows risks if operators do not choose the optimal collective solution. The maximum risks are selected, which then are minimized. The loss CDM matrix for all operators (criteria Savage))
O2 7 9 6 5 6 O2 2 4 1 0 1 PIC / loss
PIC O1 6 9 4 3 6 O1 3 6 1 0 3
The optimal landing aerodrome, determined by objective and subjective factors is alternate aerodrome Chisinau (A4) as in Wald criterion. The calculations showed a balance between safety and cost of the flight using criteria Wald (maximum safety) and criteria Savage (minimal cost and loss).
dispatches from airline.
Thanks to participants of the scientific research - professional aviation specialists such as pilots and To demonstrate the new method of Integration of Decision-Making Stochastic Models and CDM used the individual science works of aviation students in education (courses “Informatic of DM in ANS” in National Aviation University, Kyiv). Students of different qualifications (PIC, FD, and ATCO, operators of Unmanned Air Vehicles, engineers, and technical personnel) study theoretical courses and then use their knowledge for scientific research. In the chapter "Collaborative Decision Making in Emergencies by the Integration of Deterministic, Stochastic, and Non-Stochastic Models" [13] was presented example of the emergency situation "Lightning strike" from a master's diploma of Zhanna Maksymchuk's “Dynamic models of air traffic controller decision-making in difficult meteorological conditions "Lightning strike" [25]. The diploma considers an example of choosing the optimal landing aerodrome for the ATCO. The authors proposed to find joint solutions for the PIC, FD, and ATCO in an emergency situation.
Collaborative Decision-Making is a process of presenting individual and collaborative information
and decisions made by various interacting participants, such as PIC, FD, and ATCO in professional
solutions, providing synchronization of decisions taken by participants, the exchange of information
between them, the effective balancing between safety and cost in collective solutions. It is important to
ensure the possibility of making a joint, integrated solution by aviation specialists at an acceptable level
of efficiency with minimal risk and maximum safety [
he objective-subjective approach is effective for determining the optimal solution in important and difficult situations and in conflict interactions between operators. After analysis of the situation firstly the performance of the synthesis (aggregation) of individual models (with objective factors), the next step is to determine collective solutions (with subjective factors). The example of choosing an aerodrome in case of an emergency (for example, in difficult meteorological conditions) using the methods of DM under uncertainty was presented. The calculations showed a balance between safety and cost using criteria Wald (maximum safety) and criteria Savage (minimal cost and loss).
The direction of further research is to develop the DM models for all CDM participants within the Airport CDM (A-CDM) concept may aggregate the solutions of partners (airport operators, manned aircraft operators, unmanned aircraft operators, ground handling agents, and air traffic services) in joint work within non-segregated airspace [26]. For more accurate and timely information provision all partners at the airport are required to create a single operational picture of air traffic [15; 17]. The research was carried out during the simulator training of air traffic controllers [27], it is planned to build the same models for other aviation specialists, operators of manned and unmanned aircraft, flights in integrated airspace [28]. Specialists from other fields, for example, emergency and ground services, and medical staff may be involved in joint DM. Priorities and effectiveness of connecting specialists in the group for CDM will be in the next research. For effective CDM is proposed to include the participant (Artificial Intelligence) in the group of participants in a joint solution and organize the research of a hybrid optimal solution.
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