Genetic Programming With Multifidelity Surrogates for Large-Scale Dynamic Air Traffic Flow Management

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.

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 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

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

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.

The existing Air Traffic Management (ATM) system can evolve into a Space and Air Traffic Management System (SATMS), as space operations become a more common event. An assessment tool has been developed as a catalyst for this evolution; the Dynamic Flight Path Tool was developed to utilize real time situational information to minimize the impact of space flight to operations while at the same time ensuring a level of safety acceptable to the public. This tool capitalizes on methods that rapidly compute the debris clouds within a four-dimensional space (3D space plus time). The tool has two modes of operation: 1) Pre- mission Planning and 2) Real-time Mission Mode. The Dynamic Flight Path Tool has been applied to a range of sample scenarios that demonstrate how the impact of space launch operations on air traffic can be significantly reduced. 1 . An assessment tool has been developed as a catalyst for this evolution; the Dynamic Flight Path Tool, a Research and Development prototype, was developed to utilize real time situational information to minimize the impact of space flight to operations while at the same time ensuring a level of safety acceptable to the public. This tool capitalizes on methods that rapidly compute the debris clouds within a four-dimensional space (3D space plus time). The tool has two modes of operation: 1. Pre-mission Planning. The Tool enables the planner to identify scheduled air traffic affected by a planned operation and potentially schedule a launch operation during the time of lowest air traffic density and thus, lowest overall risk and disruption. 2. Real-time Mission Mode. The Tool performs trajectory prediction to identify what air traffic will enter the operational area of interest. The Tool provides the Flight Safety Officer (FSO) and Air Traffic Control (ATC) with situational awareness information on the space and air traffic. This allows the FSO and ATC to dynamically manage the airspace as the launch operation progresses, as opposed to issuing a blanket NOTAM (Notice to Airmen) restricting a large area of airspace. The Dynamic Flight Path Tool has been applied to a range of sample scenarios that demonstrate how the impact of space launch operations on air traffic can be significantly reduced. While destruct events are very rare and the vast majority of launch operations are nominal, the dynamic understanding of the space and air traffic picture between the FSO and ATC facilitated by the Dynamic Flight Path Tool gives all users of the airspace considerably more flexibility in managing the needs of their respective airspace users while guaranteeing an acceptable level of safety. Presently the Federal Aviation Administration (FAA) considers the risk to flying and not how to respond to the real time situation that exists during a space launch. The FAA follows its strategic planning and does not formulate contingency plans - rather it relies on tactically moving aircraft - to account for the actual location of

The continuous growth of population in large cities, the intensive development of the economy, and the rising number of vehicles on the roads lead to the overload of transportation networks, resulting in traffic congestion. These congestions cause significant delays in movement, increase time and fuel consumption, and also have a negative impact on the environment. To address this problem in large cities, it is worthwhile to implement intelligent traffic flow management systems. The variability of methodologies underlying these systems significantly differs depending on their initial purpose. However, the resources of such individual methodologies deplete over time, necessitating the search for and implementation of new ones. The rapid loss of efficiency in such systems is rooted in the absence of a centralized node facilitating communication between systems and managing them. In other words, combining intelligent methodologies into a unified system can be useful in the creation of efficient and dynamic traffic flow management systems with significantly greater re-sources. Such an approach to organizing an intelligent traffic flow management system for the city’s transpor-tation network has been considered in this work. During the research, a brief overview of approaches to improv-ing the efficiency of the city’s transportation network along key directions was conducted. The structure, princi-ples, and ways of forming a robust integrated system for managing the traffic flow were outlined. This system consists of subsystems based on effective optimization and organization methodologies for traffic processes. The effectiveness of tested methodologies that meet the needs of such an integrated system was also discussed and evaluated. Keywords: intelligent transportation systems, traffic congestion, comprehensive approach, adaptive traffic light control, traffic prediction, Internet of things.

An Agent-Based Approach to Aircraft Conflict Resolution with Constraints

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.

The Federal Aviation Administration (FAA) is funding and encouraging new concepts for improving air traffic flow management (TFM) decision-making. The resulting automation capabilities will need to be operationally integrated into the existing air traffic management (ATM) system. Understanding how a new capability will interact with existing system components is challenging because of the range of possible real-world situations, which must be handled by the ATM system. Although there are fast-time traffic simulation tools available for modeling the impact of TFM actions, they are often developed as stand-alone tools, which are not extensible or flexible to work in concert with other advanced TFM capabilities for conducting integration studies or quantifying benefits. To address this gap, we have built a fast-time, distributed simulation platform integrating state-of-the-art traffic simulator and allows the plug-in of advanced TFM prototypes - or other experimental capabilities that already exist - so their interactions can be studied. In this paper, we discuss the requirements and the necessary components for building this platform, which requires an architecture that is flexible enough to support many different configurations of modeling tools and applications. We then use a TFM integration case study to demonstrate the utility of the platform. We show, with only minor effort, a proposed TFM prototype can be plugged into the platform and its benefits can be evaluated.

Dynamic traffic management plays an essential role within the Dutch national traffic and transport policy. To continue the contribution to the implementation of this policy, it is necessary that the dynamic traffic management is further developed and implemented. A pro-active and network-wide approach to traffic management is envisaged to replace the more reactive and locally oriented approach currently being taken. The Ministry of Transport, Public Works and Water Management has defined a framework, the traffic control architecture, as part of the national Architecture for Traffic Management. We present the traffic control architecture for which we focus on the role of a so called frame of reference in this architecture. The developed frames of reference is presented and the experiences of the application discussed.

Air Traffic Management decisions affect the interests of a diverse group of organizations and individuals. Agents, including individual aircraft, airlines, and ground control centers, look for conflictfree options that meet their own interests without depreciating other agents' operations. A cooperative structure for interactions of agents has been defined on the basis of Principled Negotiation. This method allows distributed decision-making for all users while providing a fair coordination through Air Traffic Management systems. The major interest of Principled Negotiation relies in its mutual gain approach to selection of options. Agents negotiate options with a traffic coordinator that ensures coordination of all users preferred operations while satisfying safety criteria. Thus, the model is flexible in responding to the needs and goals of agents, and it maintains safety. It provides users with different interests the freedom to optimize their operations, it includes Air Traffic Flow Management processes, and it certifies safe aircraft separations. A computer simulation dedicated to evaluating the benefits of such a cooperative structure is under development. The simulation provides trajectorybased traffic modeling with freedom of routing, communication, and negotiation modeling. It incorporates intelligent behavior modeling and incorporates airborne collision avoidance systems. First results show that Principled Negotiation is appropriate for coordination in a multi-agent/multi-interest system such as the Aircraft/Airspace System.

Contributors

Currently, the models and theories for dynamic network traffic assignment have a great deal of limitations and couldn’ t describe and predict the state flow in the dynamic network in real-time online, and couldn’ t support setting the dynamic information platform of ITS. In this paper, we present a new real-time, network, space-time and ahead of time (predictive) model for dynamic network traffic assignment. We derive the splitting parallel algorithms of this model, and could simulate.It can follow, recognize and predict the future state of dynamic traffic flow. We provide theories and methods to the ITS that integrating the function such as dynamic traffic guidance, dynamic traffic system management and control, and dynamic traffic jam easing.

In this paper, we develop an analytical approach to planning air traffic flow management (TFM) strategies under uncertain weather. To do that, we model the dynamics of an air traffic flow under uncertain weather as a discrete jump-linear system, which enacts the tracking of transient traffic congestion statistics. We then conduct a sensitivity analysis of traffic congestion to disturbances introduced by mean inflow rate and flow restriction constraint. The integrated framework of jump-linear modeling and sensitivity analysis permits optimal planning for flow redistribution and flow restriction redesign. We demonstrate the design procedure through an example of a major flow splitting into multiple flows that enter a bank of weather zones.