Research on Contribution Evaluation of Coupling Elements in Air Traffic Safety Risks

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.

An Agent-Based Approach to Aircraft Conflict Resolution with Constraints

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

With the rapid development of China's civil aviation industry and the increasing amount of air traffic flow, as one of the main security and civil aviation system, civil aviation system is facing new challenges. This paper discusses the impact of the system: human, mechanical, environmental and other factors that affect the air traffic control system security, analyze the three main components of air traffic control areas: man, machine and environment (airspace control room environment and microenvironment) for air traffic control system affect security; Based on accident causation theory, this paper analyzes the mechanism of ATC unsafe events.

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.

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.

With the China’s civil aviation industry gradual market-oriented and the rapid development of China’s economy, China’s civil aviation transportation fuel consumption has grown significantly in nearly past three decades. Therefore, it’s a very important strategic significance of the prediction of China’s civil aviation transportation fuel consumption. In this paper, gray system and neural network approach, combined with China’s civil aviation industry 1980-2010 total traffic volume of the data, we establish gray system GM (1,1) model and BP neural network model for civil aviation transport volume. Training and simulation of the back propagation neutral network model and the gray system GM(1,1) used MATLAB. BP neural network modeling takes into account in three factors: the number of aircraft aviation industry, flight hours and total turnover. The fitting precision of the gray system GM(1,1) model is 64.2% while the fitting precision of the back propagation neutral network model is 90.16%. Thus, the back propagation neutral network model is better for estimating Civil aviation fuel consumption.

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

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.

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

Adapting a Human – Automation Trust Scale to an Air Traffic Management Environment

With the increasing development of science and technology, the increasing popularity of the Internet, and the increasingly widespread application of high-tech technology in various industries, profound changes have taken place in the operation mode of airports in China's civil aviation industry. Research on the development of smart civil aviation airports is also increasingly enriched. Airports are beginning to use information and intelligent technology to change their operating modes. From the current situation of China's civil aviation airport control, it is an unprecedented opportunity to apply VRT (Virtual Reality Technology) to the visual management of smart civil aviation airports. Utilize VRT to establish a real immersive visual management system that integrates operational dynamic display, virtual simulation, and simulation training that can be used for control and efficiency improvement based on the current situation of smart civil aviation airports. The system is mainly built through three-dimensional models that are highly close to the scene, thereby verifying and optimizing the operation mode of smart civil aviation airports, and obtaining the best scheme. Realized the application of VRT in the visual management of smart civil aviation airports.

Based on a long-term prediction by the International Civil Aviation Organization indicating steady increases in air traffic demand throughout the world, the workloads of air traffic controllers are expected to continuously increase. Air traffic control and management (ATC/M) includes the processing of various unstructured composite data along with the real-time visualization of aircraft data. To prepare for future air traffic, research and development intended to effectively present various complex navigation data to air traffic controllers is necessary. This paper presents a mixed reality-based air traffic control system for the improvement of and support for air traffic controllers’ workflow using mixed reality technology that is effective for the delivery of information such as complex navigation data. The existing control systems involve difficulties in information access and interpretation. Therefore, taking notice of the necessity for the integration of air traffic control systems, this study presents the mixed reality (MR) system, which is a new approach, that enables the control of air traffic in interactive environments. This system is provided in a form usable in actual operational environments with a head-mounted see-through display installed with a controller to enable more structured work support. In addition, since this system can be controlled first-hand by air traffic controllers, it provides a new experience through improved work efficiency and productivity.

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.

This paper/chapter deals with the key drivers for adopting and developing an Occupational Health and Safety System (OHS) with a special focus on air traffic management and traffic controller’s workplace. A such system includes regulation and legal compliance procedures, actions and monitoring for ensuring workplace safety, incentives and motivation for the air traffic controller and associate personnel health and wellbeing. By a systemic approach, the key characteristics of OHS towards air traffic management are presented, highlighting the key aspects for implementing a quality management system in air traffic control, which is the cornerstone of airport operation efficiency and productivity on one hand; and the nature of job and the intensive working environment is well recognised. Based on air traffic providers functional analysis the key occupational aspects for air traffic control are taken into consideration, providing the benefits for implementing quality management systems (QMS) and OHS is real business. Conventional wisdom is to highlight the importance for establishing and incorporating a modern custom-made OHS system in accordance with the requirements addressed by OHSAS 18001 to develop and implement a QMS for air traffic services. Contribution of this paper is to highlight the key priorities for managers and decision makers in field of air traffic services providers, depicting ways and recommendation for adopting an efficient path for implementing OHS in a QMS environment.