Dynamic Network Flow Model for Short-Term Air Traffic Flow Management

In order to solve the short-term air traffic flow management problem (ST-TFMP) efficiently, we present an algorithm using Lagrangian relaxation technique. The primal problem is decoupled by relaxing the air route capacity constraints, and then the corresponding dual problem is solved by subgradient method. We also propose a heuristic procedure in combination with the knowledge of air traffic management. It forces the dual solution from infeasible to feasible by adding non-coupled constraints. At last, the algorithm is validated by practical data from the Beijing ATC Center of the Civil Aviation Administration of China (CAAC). The computational results show that the algorithm can improve the performance of ST-TFMP.

This paper builds on top of a collaborative ATFM framework previously published, which demonstrated a potential in significant pre-tactical system delay reduction over the current European ATFM practices. In this paper, we aim to raise the technology readiness level (TRL) of the original works, focusing on improving the tractability of its DCB optimizer. To this end, we apply a Dantzig-Wolfe (DW) decomposition approach and use high performance computing (HPC) techniques to attempt the solution in a short time. The main contribution of this paper is to mitigate the computational burden faced by previous approaches, which will make all the contributions demonstrated therein more operationally feasible.

Air Traffic Management (ATM) is defined as a broad domain that consists of complex activities such as Air Traffic Flow Management (ATFM). Within this context this paper presents two prototypes of a module (MAAD) assembled in a decision support device that is based on Artificial Intelligence, which generates suggestions for air traffic flow control according to each traffic saturation scenario. The device known as Distributed Decision Support System for Air Traffic Flow Management (SISCONFLUX) was built with a computational agent based on Reinforcement Learning (Module MAAD), which uses Q-learning algorithm. Two prototypes were built and one of them incorporated the specialist's (human agent) experience. The performance of the prototypes was evaluated through a case study modeled from real traffic demands verified on certain dates. The results obtained in the case study are promising; the behavior of the prototypes demonstrated that the Q-learning algorithm converged in a satisfying way. The prototypes generated actions that contributed effectively to the reduction of saturation in the air traffic scenarios under test.

Air Traffic Flow Network Rerouting Problem ATFNRP, which aims to alleviate the flight delays caused by the increasing traffic and extreme weather, has become more and more serious in air traffic flow management. This paper proposes a multi-objective general rerouting model considering both total delay cost and airlines fairness and adopts Multi-Objective Evolutionary Algorithm based on Decomposition MOEA/D for ATNFRP. Empirical studies using the real data of China airspace demonstrate that MOEA/D outperforms or performs similarly to three well-acknowledged Multi-Objective Evolutionary Algorithms MOEAs on ATFNRP.

In order to improve air traffic operational safety and efficiency in China, Civil Aviation Administration of China (CAAC) and Ministry of Science and Technology (MOST) of China launched the project of Initial Four-Dimensional (I4D) flight trial in 2015. The project aims to evaluate the I4D operational concept and the performance of the technical enablers. The flight trial was performed on 20th March 2019. An A320 aircraft equipped with I4D avionics flew between Tianjin Binhai International Airport (ZBTJ) and Guangzhou Baiyun International Airport (ZGGG). In this paper, the performance of flight trial was evaluated, including Aeronautical Telecommunication Network (ATN) performance, Automatic Dependent Surveillance-Contract Extended Projected Profile (ADS-C EPP) performance, Controller Pilot Data Link Communications (CPDLC) service performance, Controlled Time of Arrival (CTA) operations. The evaluation shows I4D offers safety gains with better air and ground trajectory information sharing. The efficiency of Air Traffic Management (ATM) system can be improved as the flight time of arrival is more predictable and precisely controllable. Meanwhile, these changes in operation can reduce both pilot and controller workload by using CPDLCC/ADS-C. Specifically, 62.7% of the regular communication time can be saved. Besides, Top of Descent (TOD) changes during the progress of CTA operations, thus, its information is necessary to help controllers. In addition, some suggestions are derived from this trial. The analyses and evaluation in this paper will help shed light on policies development of I4D implementation.

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

This paper explores how applying a basic management science principle to air traffic management operations can lead to revised roles and responsibilities that allow operations to be handled by the most appropriate participants. Previous research that applied the principle to local departure and arrival management is reviewed; the application is then expanded to regional and national air traffic management. The paper examines the operational and engineering implications of the resulting concept, contrasted with current operations and tools, and identifies where additional research or development is needed. Examples are provided that illustrate the resulting activities at the various air traffic management facilities across a broad range of look-ahead timeframes. I. Introduction HE High-Density Area Departure and Arrival Management (HDDAM) concept was developed in the context of arrival and departure air traffic management in high-density airspace such as Metroplex areas. The management science principles underlying HDDAM appear to be applicable to National Airspace System (NAS) operations at any level, including all phases of planning and flight. This paper explores some operational and engineering implications of such an application to local, regional, and NAS-wide air traffic operations. As described elsewhere, 1-3 HDDAM redefines the decision making processes within the Air Route Traffic Control Center (ARTCC), the Terminal Radar Approach Control (TRACON), and multiple Air Traffic Control Towers (ATCTs) for high-density area departure/arrival traffic management. The decision making authority proposed for each facility reflects the information available to each decision maker and the impact of the decision on their operating environment. Specifically, each facility is responsible for defining the capacity of its air traffic management resources (such as airports, airspace, airways) and requesting resources for flights to use. As shown in Fig. 1 for a single Metroplex, the TRACON has a central role in these interactions, serving as a “broker” between the facilities with the resources and the facilities with requests for use of those resources that are not within their scope of control, while also accounting for the TRACON’s ability to deliver the flights to the resources in question. ATCTs are responsible for requesting resources for departing flights and the ARTCC for requesting resources for arriving flights, as they each possess the best information regarding the status of these flights. Because of the uncertainties present in predicting individual flight departure readiness and inbound air traffic arrival times, the TRACON does not assign specific departure and arrival slots to individual flights. Instead, the TRACON allocates slots to the airports (for departures) and ARTCC (for arrivals) so they can make flight-specific assignments as deemed best for their individual operating environments. This effectively decouples the decisions of the individual ATCTs and the ARTCC, giving each facility increased flexibility to handle situations dynamically as they develop. Air traffic management operations are most effective when the decision makers work as a team. The underlying principle of HDDAM is that this can be accomplished best when all facilities’ roles and responsibilities are based on the management science principle that allows the appropriate level of autonomy at each facility. The principle states that decisions should be assigned to those who are already performing other tasks with the relevant data—those who know the most about the factors affecting the decision—and will be most directly affected by the consequences of 1 Lead Multi-Discipline System Engineer, TFM System Engineering and Evolution, 7515 Colshire Drive, Mailstop

To the characteristics of air traffic management system, the safety risk coupling elements are analyzed on human factors, equipment factors, environment factors and management factors, the contribution of air traffic safety risk coupling elements is analyzed. The contribution of coupling elements are assessed by extension analytic hierarchy process (EAHP), taking inner communication risks, for instance, and the feasibility of the method is demonstrated by examination. The research objective is to determine the primary coupling element of the air traffic safety risk, propose the targeted pre-control program, so as to improve effectiveness of air traffic safety risk management. 1. INTRODUCTION In recent years, China's civil aviation industry has developed rapidly. With the rapid growth of flights and air traffic flow, air traffic security risks have become increasingly prominent. The pressures of protecting the safe operation of flights have increased gradually, which leads the higher requirements of air traffic safety management. Aviation accidents, incidents and unsafe events often results from interaction between man, machine and the environment, management. Air traffic safety risks usually present very complex nonlinear coupling process. Determining the coupling mechanisms of air traffic safety risks, mining hazard incentives and presenting a pre-control strategies, is a key risk management of the air traffic control. Based on the statistical analysis of China Civil Aviation unsafe incident report, air traffic control incidents were 0, 2, and 1 in 2009, 2010, and 2011, respectively. The other unsafe events were 13, 28 and 34, in 2009, 2010, and 2011, respectively which presents the upward trend. The unsafe events of air traffic control in 2011 is mainly caused by runway incursion, dangerously close to the flight conflict as well as communication interrupt type event, accounting for 71% of the security risks of the ATC. The above events are just the tip of the iceberg, which reflects the poor management of part of the control units, the weak sense of duty, the non-serious style, the lack of qualification and capacity and the poor awareness of observing law and discipline. Therefore, it has important practical significance to investigate the

A study on basic research priorities and development suggestions for the digital transformation of air traffic management

A goal of any precision departure concept, such as NASA Precision Departure Release Capability, is to improve throughput, efficiency and capacity by integrating departure, arrival and surface operations. This kind of concept is believed to have the potential of increasing flight efficiency and throughput by not missing assigned overhead-stream or arrival-stream slots. In the current Call For Release scheduling, a slot can be missed because of airport-departure delay, which is the sum of gate-departure delay, ramp delay, and taxi-out delay. This delay can be reduced by improved precision departure scheduling. The main thrust of the paper is to determine the delay-cost impact of Call For Release scheduling before gate-push-back and at gate-pushback. Seven different variations of scheduling algorithms were used in the simulation. Results reported in the paper considers 37,346 flights in the National Airspace System for one day in January 2011. Approximately 1,500 airports were included in the simulation. Results show that there is no significant benefit of scheduling before gate-push-back as opposed to at gate-push-back under assumed gate-departure and taxi-out time uncertainties, assuming a Call For Release is strategically done for all departures from all airports. However, if there were no gate-departure and taxi-out time uncertainty, which is unlikely in reality, the maximum benefit of scheduling an hour before gate-push-back is limited to 6.8% reduction in weighted delay (2*airborne delay + ground delay) compared to delay resulting from scheduling at gate-push-back.

The rapid advancement of cutting-edge technology has reshaped the global dynamics of the airline sector, elevating the significance of service quality, effectiveness, and protection. As a vital contributor to national economic growth and a public utility, aviation's expansion has directly impacted businesses in the service sector, leading to increased operational opportunities for hotels, restaurants, and travel agencies. This article addresses the challenges within Air Traffic Management (ATM), focusing on the aviation industry's primary concerns. With the continuous growth of aviation traffic, there is a pressing need to enhance security, productivity, and environmental sustainability. The article aims to stimulate business innovation and collaboration in advanced study areas such as dynamic airspace management (DAM), air traffic flow management (ATFM), and collaborative/non-collaborative surveillance. The proposed frameworks, based on Clean Sky and NextGen, incorporate 4D Trajectory Optimization techniques, advanced surveillance technologies, and data link connections to establish a foundation for ATM industry development. Additionally, the research explores adaptive Human-Machine Interface and Interaction (HMI2) forms to automate the assessment and negotiation of aircraft intentions, thereby improving the efficiency and security of ATM operations. The study also addresses specific requirements for cooperative and non-cooperative Detect-and-Avoid (DAA) systems for Remotely Piloted Aircraft Systems (RPAS) within the evolving CNS+A process, ensuring their safe and unrestricted access to all airspace types.

This chapter reviews the International Civil Aviation Organization air traffic management (ATM) work programme along with ATM developments taking place around the world. It examines the various elements of the ATM system and suggests some of die research, trials and demonstrations. Airspace management is traditionally recognized mainly as involving a dynamic or tactical sharing of airspace by civil and military users. Air Traffic Services itself is comprised of several subelements, one of these being air traffic control. The increasing number of long-range interregional flights may require integration of regional Air Traffic Flow Management systems and procedures. Free Right is the guiding vision, mission and operational concept of the Federal Aviation Administration, based on Communications, Navigation, Surveillance/Air Traffic Management systems (CNS/ATM). Africa is composed of many delicate national economies separated by vast wilderness areas. The main scope of Airspace management will be toward a strategic planning function of airspace infrastructure, and flexibility of airspace use.

A dynamic rerouting model for air traffic flow management

Air Traffic Management Bureau of Civil Aviation Administration of China (ATMB) has steadily promoted capacity building of smart ATM under the guidance of the Action Plan of Four Enhancement of ATM. However, at present, the evaluation method for the effectiveness of capacity building of smart ATM is not systematic, there is also a lack of statistical analysis of capacity building of smart ATM. In 2012, the International Civil Aviation Organization (ICAO) proposed an authoritative and instructive Aviation System Block Upgrade plan, which provides guidance for the capacity building of smart ATM. Therefore, based on the analysis of the threads of capacity improvement proposed in ASBU and the current situation of ATMB, this paper constructs an evaluation index system of capacity building of smart ATM, at the same time, the current situation of ATMB in the implementation of various threads is obtained according to the survey. And the above-mentioned evaluation index system is used to implement a case study for the effectiveness analysis of the capacity building of smart ATM, which verifies the feasibility of the evaluation index system.

In order to make a sensible prediction on the air traffic flow management with conditions of wave-off and bolter, a system dynamic model for the night recovery operations of embarked aircrafts is built to ensure the adaption of air traffic flow with the capacity of air control at each phase of the recovery operations. The model aims at the characteristics of multiple feedbacks, delays and complex time varying, builds a stock flow diagram and operation model with impact factors of the night recovery system, and is simulated in Vensim® Personal Learning Edition 5.9. The simulation shows a reasonable prediction result for the night recovery of embarked aircrafts with conditions of bolter and wave-off and can provide a theoretical basis for scheduling the air traffic flow management of embarked aircrafts formation recovery.