scholarly journals Мethod of automated development of solutions for special cases in flight

Connectivity ◽  
2020 ◽  
Vol 146 (5) ◽  
Author(s):  
A. V. Kolesnyk ◽  
◽  
I. V. Zakharchenko ◽  
R. V. Tarasov ◽  
P. G. Berdnik ◽  
...  
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Bayesian Network ◽  
Bayesian Learning ◽  
Air Traffic ◽  
Inference Algorithm ◽  
Air Traffic Controller ◽  
Special Cases ◽  
The Creation ◽  
Automated Decision Making

The article develops a method of automated decision making in the framework of the creation of DSS air traffic controller. The method of automated decision-making for special cases in flight is being developed as one of the stages of information technology for the creation of decision support system for air traffic controllers. This is necessary to help decide on the option of terminating the flight in the event of a special case in flight on the example of engine failure on the aircraft. The developed method involves the use of probabilistic programming technology. It includes: construction of a probabilistic hierarchical model of emergency based on the Bayesian network taking into account the factors influencing the decision-making process, creating a sample of examples for learning the model to improve future situations models on examples using the Bayesian learning paradigm, the choice of inference algorithm to obtain a probabilistic conclusion. The proposed method is implemented in the probabilistic programming system Figaro, which is free and available under an open source license. The program code is written in Scala. The set of training data was formed based on the results of the investigation of aviation accidents and catastrophes and contained fifty-two cases of forced landing at the aerodrome and on the site with different consequences. The learning process was learning the parameters of the model on the data and was performed on thirty- six examples. Other cases (sixteen) were used to test the prediction quality of the created model. The Bayesian learning paradigm is used to teach the model, which does not require a special learning algorithm and is performed using the inference algorithm. The Metropolis-Hastings approximation algorithm is used as the derivation algorithm. The developed method showed high accuracy of forecasting. The error between the actual result and the estimate obtained using the Bayesian network was 10%. Further research will be aimed at developing information technology for the creation of DSS air traffic controller for special cases in flight.

A Decision Making Assist System Based on Plan Conflict Detection and Alerting for Air Traffic Controller at Aerodrome

2014 ◽  
Vol 543-547 ◽  
pp. 926-929
Author(s):  
Zheng Xiang ◽  
Yu Tang ◽  
Feng Kang
Keyword(s):  
Decision Making ◽  
Conflict Detection ◽  
Air Traffic ◽  
Air Traffic Controller ◽  
Control Traffic ◽  
Traffic Operation

To help air traffic controller at aerodrome better control traffic in maneuvering area, a decision making assist system based on plan conflict detection and alerting is proposed. The most important feature of the proposed system is the module of taxi conflict detection. After an aerodrome controller issues taxi instructions to different flights, the module will detect the potential taxi conflict between flights based on the planned taxi routes and therefore alter the controller. Once the proposed system is used in operation, the efficiency and the safety of the taxi instructions given by the air traffic controller at aerodrome will improve, and traffic operation at aerodrome will become smoother and more efficient.

Intelligent Automated System for Supporting the Collaborative Decision Making by Operators of the Air Navigation System During Flight Emergencies

2020 ◽  
pp. 66-90
Author(s):  
Yuliya Sikirda ◽  
Mykola Kasatkin ◽  
Dmytro Tkachenko
Keyword(s):  
Decision Making ◽  
Traffic Control ◽  
Air Traffic ◽  
Automated System ◽  
Sequential Optimization ◽  
Collaborative Decision Making ◽  
Air Traffic Controller ◽  
Planning Methods ◽  
Human Operators ◽  
Collaborative Decision

This chapter researches pilot and air traffic controller collaborative decision making (CDM) during flight emergencies for maximum synchronization of operators' technological procedures. Deterministic models of CDM by the Air Navigation System's human operators were obtained by network planning methods; their adequacy is confirmed by full-scale modeling on a complex flight simulator. For the sequential optimization of the collaborative two-channel network “Air traffic controller-Pilot” to achieve the end-to-end effectiveness of joint solutions, a multi-criteria approach was used: ensuring the minimum time to parry flight emergency with maximum safety/maximum consistency over the time of operators' actions. With the help of the multiplicative function, the influence of organizational risk factors on flight safety in the air traffic control was evaluated. A conceptual model of System for control and forecasting the flight emergency development on the base of Intelligent Automated System for supporting the CDM by operators was developed.

scholarly journals Analysis of effectiveness of the program of joined air traffic controlles and pilotes training

2019 ◽  
Vol 22 (5) ◽  
pp. 32-42
Author(s):  
A. I. Stepnova ◽  
S. M. Stepanov ◽  
V. V. Borsoeva ◽  
V. A. Borsoev
Keyword(s):  
Decision Making ◽  
Air Traffic ◽  
Educational Process ◽  
Educational Institutions ◽  
Atmospheric Conditions ◽  
Air Traffic Controller ◽  
Air Traffic Controllers ◽  
Conflict Situations ◽  
Urgent Task ◽  
Joint Training

Training of cadets-air traffic controllers and cadets-pilots is an integral part of the training, which allows you to form the skills of quick and correct decision-making in different types of situations. For the air traffic controller, these are exercises to solve conflict situations with aircraft in the area of their responsibility, solving problems in normal flight conditions, in unfavorable atmospheric conditions and in the non-routine situations in flight. For the pilots, solutions to the problems are reduced to the rapid decisionmaking on aircraft control in normal flight conditions, adverse atmospheric conditions and non-routine situations in flight. As you know, the work of air traffic controllers is associated with the work of pilots, but training in educational institutions takes place separately, resulting in gaps in knowledge of the specifics of the adjacent specialty, and, eventually, leads to errors. Optimization of the educational process is currently an urgent task. The program of joint training can act as an optimization tool. The program enables you to collaboratively practice the skills of fast decision-making, clearly to learn the specifics of the related specialties that will allow you to create a complete picture of the air situation. The program of joint training implies the joint operational logic simulator that combines two simulators. For the air traffic controller, this is a separate airspace area in the form of a sector, for the pilot it is the cockpit. Thus, the solution to the problems occurs sequentially from the air traffic controller to the pilot and vice versa, and the controller has the ability to observe the algorithm of the pilot's actions, and the pilot is able to monitor the algorithm of the controller's actions.

Air Traffic Controller Decision-Making Support using the Solution Space Diagram

2010 ◽  
Vol 43 (13) ◽  
pp. 227-232
Author(s):  
G.A. Mercado Velasco ◽  
M. Mulder ◽  
M.M. van Paassen
Keyword(s):  
Decision Making ◽  
Solution Space ◽  
Air Traffic ◽  
Air Traffic Controller ◽  
Decision Making Support

scholarly journals Propuesta de una arquitectura para un Smart Campus Universitario

2020 ◽  
pp. 21-27
Author(s):  
José María CRUZ-PARADA ◽  
Víctor Manuel ZAMUDIO-RODRIGUEZ ◽  
Carlos LINO-RAMÍREZ ◽  
David Asael GUTIERREZ-HERNANDEZ
Keyword(s):  
Decision Making ◽  
Control System ◽  
Data Collection ◽  
Intelligent Agents ◽  
Mobile Application ◽  
University Campus ◽  
Information Analysis ◽  
Smart Campus ◽  
The Creation ◽  
Automated Decision Making

A proposal of an architecture is described for the use of intelligent agents connected to a mobile application and the same time is also linked to a control system that is managed by the institution. In this document the idea is analyzed from its conception, through the elaborated development and the tests and the results that have been carried out. This architecture is planned to be used in the creation of an intelligent university campus with data collection, information analysis and automated decision making.

Predictive Validity of a Selection Procedure for Air Traffic Controller Trainees

2013 ◽  
Vol 3 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Yvonne Pecena ◽  
Doris Keye ◽  
Kristin Conzelmann ◽  
Dietrich Grasshoff ◽  
Peter Maschke ◽  
...  
Keyword(s):  
Predictive Validity ◽  
Selection Procedure ◽  
Air Traffic ◽  
Performance Criteria ◽  
Training Phase ◽  
Air Traffic Controller ◽  
Training Performance ◽  
Navigation Service ◽  
German Aerospace ◽  
Training Success

The job of an air traffic controller (ATCO) is very specific and demanding. The assessment of potential suitable candidates requires a customized and efficient selection procedure. The German Aerospace Center DLR conducts a highly selective, multiple-stage selection procedure for ab initio ATCO applicants for the German Air Navigation Service Provider DFS. Successful applicants start their training with a training phase at the DFS Academy and then continue with a unit training phase in live traffic. ATCO validity studies are scarcely reported in the international scientific literature and have mainly been conducted in a military context with only small and male samples. This validation study encompasses the data from 430 DFS ATCO trainees, starting with candidate selection and extending to the completion of their training. Validity analyses involved the prediction of training success and several training performance criteria derived from initial training. The final training success rate of about 79% was highly satisfactory and higher than that of other countries. The findings demonstrated that all stages of the selection procedure showed predictive validity toward training performance. Among the best predictors were scores measuring attention and multitasking ability, and ratings on general motivation from the interview.

Air Traffic Controller Situation Awareness Is Embodied

2014 ◽  
Author(s):  
Dan Chiappe ◽  
Thomas Strybel ◽  
Kim-Phuong Vu ◽  
Lindsay Sturre
Keyword(s):  
Situation Awareness ◽  
Air Traffic ◽  
Air Traffic Controller
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