APPLICATION OF SOFTWARE, REPRESENTING CUMULONIMBUS CLOUDS, IN AIR TRAFFIC CONTROL

An Agent-Based Approach to Aircraft Conflict Resolution with Constraints

The paper deals with the diagnosis and development of core skills of air traffic (AT) controllers based on a professiogram analysis of their work. The aim was to assess how professional skills are related to experience and to explore the opportunities of purposeful training of these skills. The study was conducted with the participation of air traffic (AT) controllers who were graduates of an ATC school aged 22–25 years and had no experience and eleven first-class operators aged 31–37 years with eight to ten years of experience. The professiogram analysis of work was carried out using a specially crafted skill tests battery followed by training (ten sessions during ten school days) for inexperienced air traffic controllers, which was tied up to regular refresher training. The study pinpointed the core skills that were improved significantly by the special training and proved the possibility of their development using a training cycle during planned teaching.

Current study is aiming to find a more suitable behavioral fatigue index for Air Traffic Controllers(ATC) using PVT test and fatigue self-assessment questionnaires as tools, and gives these tests before and after ATC duty. Through PVT test and self-assessment questionnaire, this finding indicates hit rate and hit response time (the first 20% trials) of PVT can be potential fatigue index since we found first 2min hit response time of air traffic controller(ATC) after duty is significantly longer than before duty, together with the hit rate after duty is lower than before duty. 8 items in Stanford Sleepiness Scale(SSS) and Visual Analogy Scale(VAS) also show significant difference in self assessment on fatigue. ATCs think themselves are much more fatigue after duty than before duty.Besides, ATCs in regional control area show significant fatigue effect than those in terminal control area, indicating different work load in two different working areas. Those ATC work at night especially in midnight show much more significant fatigue than those work in the daytime showed by longer first 20% hit response time. In sum, hit rate and first 20% (first 2min) hit response time can be effective fatigue indexes of ATC.

Decision support system in tactical air traffic flow management for air traffic flow controllers

This paper describes a simulation tool developed to aid the analysis of air traffic management domains and potential air traffic control strategies. The simulation represents aircraft and automated air traffic control support tool functionality based on a computational model of aircraft flight management system trajectories. It simulates the effects of environmental disturbances and air traffic controller intervention on air traffic in fast time. The paper outlines a methodology that leverages these capabilities to help with tool design and evaluation, and discusses the results of preliminary simulations aimed toward using the proposed methodology for characterizing the effectiveness of particular strategy-tool combinations for supporting more efficient terminal-area air traffic management. This research is supported by NASA's Vehicle Systems Program Quiet Aircraft Technology project and Airspace Systems Program Advanced Air Transportation Technology project.

Objective: The objectives of current study are to explore whether serious fatigue of Air Traffic Controller (ATC) exist in their duty, and to explore a sensitive fatigue index. Method: Number recognition task was used to explore ATC fatigue. Following results were found, firstly, significant fatigue effect was found in all 55 ATC. Besides, significant fatigue effects were only found in ATC in tower control area and terminal control area, but not in regional control area. Thirdly, only reaction time before and after ATC duty were found significant difference but not in accuracy. Conclusion: Fatigue effect really exist in ATC after their duty, and ATC in different work location suffer different work load. Finally, reaction time of number recognition task can be a very sensitive and reliable fatigue index.

Contents: B.H. Kantowitz, Series Foreword. Preface. Part I:Introduction. J.M. Koonce, A Historical Overview of Aviation Human Factors. J.E. Deaton, J.G. Morrison, Aviation Research and Development: A Framework for the Effective Practice of Human Factors, or What Your Mentor Never Told You About a Career in Human Factors... D. Meister, Measurement in Aviation Systems. D.W. Abbott, M.A. Wise, J.A. Wise, Underpinnings of System Evaluation. R. Westrum, A.J. Adamski, Organizational Factors Associated With Safety and Mission Success in Aviation Environments. Part II:Human Capabilities and Performance. L. Bainbridge, Processes Underlying Human Performance. R.R. Amalberti, Automation in Aviation: A Human Factors Perspective. C. Prince, E. Salas, Team Processes and Their Training in Aviation. D.E. Maurino, Crew Resource Management: A Time for Reflection. G. Costa, Fatigue and Biological Rhythms. M.R. Endsley, Situation Awareness in Aviation Systems. D.L. Pohlman, J.D. Fletcher, Aviation Personnel Selection and Training. Part III:Aircraft. L. Hitchcock, Pilot Performance. J.M. Reising, K.K. Liggett, R.C. Munns, Controls, Displays, and Workplace Design. W.F. Moroney, B.W. Moroney, Flight Simulation. L.E. Kovarik, R.C. Graeber, P.R. Mitchell, Human Factors Considerations in Aircraft Cabin Design. B.E. Hamilton, Helicopter Human Factors. Part IV:Air Traffic Control. M.S. Nolan, Air Traffic Control. D.J. Garland, E.S. Stein, J.K. Muller, Air Traffic Controller Memory: Capabilities, Limitations, and Volatility. V.D. Hopkin, Air Traffic Control Automation. K. Kerns, Human Factors in Air Traffic Control/Flight Deck Integration: Implications of Data-Link Simulation Research. Part V:Aviation Operations and Design. J.M. Hammer, Human Factors of Functionality and Intelligent Avionics. T.A. Lindholm, Weather Information Presentation. C.G. Drury, Human Factors in Aviation Maintenance. R.J. Lofaro, Human Factors in U.S. Civil Aviation Security. S. Baker, Aviation Incident and Accident Investigation. R.D. Gilson, Forensic Aviation Human Factors [Accident/Incident Analyses for Legal Proceedings].

Air Traffic Control Students Tendencies of Desirability Levels during Flight Norms Violations

Air Traffic Management (ATM) is a complex decision-making process. Air traffic controllers' decision on aircraft trajectory control actions directly leads to the efficiency of traffic flow management. In the Automated Point Merge Trajectory Planning (APMTP) problem, it aims to realize an automated routine trajectory management in Terminal Manoeuvring Area (TMA) with an intelligent decision-making agent. An Artificial Intelligence-based approach, mainly Reinforcement Learning (RL) algorithm, is applied to adaptively and smartly integrate four types of de-conflict actions for solving conflicts with fewer delays on the environment. In this paper, we will mainly discuss the policy optimization in APMTP, focus on improving the agent's learning quality and exploration efficiency. Firstly, application of RL in adaptive trajectory planning is presented. APMTP problem is adaptively divided into several sub-problems. For each sub-problem, an online policy π is applied to guide the simulation and optimization modules to find out the conflict-free and less-delay solution. The online policy π is a scale of weight distribution for choosing desirable actions. It follows the rule of Roulette-wheel selection with weighted probability. The highest desirable decision variable has the largest share of the roulette wheel, while the lowest desirable decision variable has the smallest share of the roulette wheel. The RL direct policy optimization algorithm is designed to update the online policy π, Finally, experiments are built up for validation of the proposed policy optimization algorithm for the intelligent decision-making in APMTP. The results in the test environment show that learning agent with different exploration and exploitation ability will result in different system performance in conflict resolution and delay.

The delegation to the flight crew of some tasks currently performed by air traffic controllers provides new perspectives to potentially increase air traffic control efficiency. More specifically, the task of establishing properly spaced landing sequences is very demanding in heavy traffic conditions for the air traffic controllers in charge of the terminal maneuvering area. Automatic merging and station keeping operations could relieve air traffic controller of providing time consuming radar vectoring instructions. The objective of this communication is to provide technical insight into the airborne devices and algorithms which may be used onboard aircraft to automatically achieve a specified distance or delay with respect to another aircraft at a specified meter fix. A nonlinear control law based on sliding mode control is proposed to control the lateral motion of the trailing aircraft. The design is followed by two illustrative examples which show the effectiveness of the proposed approach.

This paper proposes, for the first time, a unified optimal approach applicable for both fuel-powered and allelectric aircraft to solve a direct operating cost (DOC) minimization problem where the cost index (CI) is modeled as a timevarying parameter, which is either commanded by Air Traffic Control (ATC) or assigned by the airline. Furthermore, this paper demonstrates how a variable CI affects the solution of the optimization problem as it presents the equations that allow the computation of optimal constant cruise airspeed and flight time in response to step changes in the CI value. The proposed methodology is validated using a simulated flight scenario, where inputs from ATC are received during flight, requiring the aircraft to adjust its optimal airspeed, flight time, and total energy consumption accordingly. The optimal values of airspeed, flight time, and energy consumption are calculated for both a fuelpowered and an all-electric aircraft, thus allowing applications of the proposed approach to future air mobility all-electric vehicles.

Growing political pressure and widespread social concerns about climate change are triggering a paradigm shift in the aviation sector. Projects with the target of reducing aviation’s CO2 emissions and their impact on climate change are being launched to improve currently used procedures. In this paper, a new coordination process between aircraft flight management systems (FMSs) and an arrival manager (AMAN) was investigated to enable fuel-efficient and more sustainable approaches. This coordination posed two major challenges. Firstly, current capacity-centred AMANs’ planning processes are not optimised towards fuel-efficient trajectories. To investigate the benefit of negotiated trajectories with fixed target times for waypoints and thresholds, the terminal manoeuvring area was redesigned for an independent parallel runway system. Secondly, the FMS-AMAN negotiation process plan the trajectories based on time, whereas air traffic controllers guide traffic based on distance. Three tactical assisting tools were implemented in an air traffic controller’s working position to enable a smooth transition from distance-based to time-based coordination and guidance. The whole concept was implemented and tested in real-time human-in-the-loop studies at DLR’s Air Traffic Validation Center. Results showed that the new airspace design and concept was feasible, and a reduction in flown distance was measured.

This paper addresses the speed regulation problem in air traffic management. Because global air traffic volume is continuously increasing, improvement in air traffic control has become a priority. During this decade, European and United States initiatives have been launched to design the future of air traffic management. One of their objectives is to increase air traffic density and optimize flight route plans. This can be achieved through en route deconfliction. Air conflicts have the potential to occur when two or more aircraft are predicted to be below a separation norm in the near future. Such situations affect air traffic controllers' workload; thus, these situations limit controllers' capacity to deal with large numbers of aircraft and induce flight delay. Reducing air traffic controllers' potential workload through speed regulation has been investigated in the En Route Air Traffic Soft Management Ultimate System project. Efficiency of the method has been validated through simulations, including human-in-the-loop experiments, which opens the door to conflict resolution algorithms based on speed regulation. In this paper a formulation for the speed regulation problem is proposed. First, a potential conflict detection and resolution framework is presented. Uncertainty is then introduced in the model, with the aim of reproducing realistic air navigation conditions. A case study of real air traffic instances is described, and results are discussed to assess the potential of the proposed algorithm.

Data-driven prediction of Air Traffic Controllers reactions to resolving conflicts.

As air traffic volumes continue to grow, understanding and managing traffic flows within Terminal Maneuvering Areas (TMAs) has become essential to meet increasing capacity demands.TMAs, the airspaces surrounding airports managed by Air Traffic Controller (ATC) for landings and takeoffs, often face challenges due to limited capacity, leading to performance degradation and significant environmental footprint.While existing Key Performance Indicators (KPIs) effectively assess the en route phase of flight journeys, there remains a gap in the metrics specifically designed for evaluating TMAs.The purpose of this thesis is to develop a comprehensive evaluation framework tailored for TMAs to assess performance, identify inefficiencies, and highlight areas for improvement.First, the existing general metrics were modified for TMA-specific evaluation, proved effective in detecting inconsistencies in air traffic control and identifying optimization opportunities.New TMA-specific performance indicators were also developed and applied to various TMAs with different types of arrival procedures.In the second phase, dependencies between the metrics were examined to create a performance assessment tool tailored to specific operational scopes.Statistical Ordinary Least Squares (OLS) analysis was performed on two subsets of metrics, uncovering that the newly-introduced metric, 'threshold,' correlates significantly with other performance indicators.This metric serves for the predicting TMAs performance based on entry conditions, improving air traffic management.Recently, the focus was placed on Point Merge-specific metrics to assess their potential in improving environmental efficiency of the arrivals.Testing across seven airports revealed that Point Merge (PM) structures are often underutilized.Finally, the PM-specific metrics and the overall performance evaluation framework were refined for more efficient evaluation and further optimization of TMAs featuring different types of arrival operations.