Machine Learning-Enhanced Aircraft Landing Scheduling under Uncertainties

This paper addresses aircraft delays, emphasizing their impact on safety and financial losses. To mitigate these issues, an innovative machine learning (ML)-enhanced landing scheduling methodology is proposed, aiming to improve automation and safety. Analyzing flight arrival delay scenarios reveals strong multimodal distributions and clusters in arrival flight time durations. A multi-stage conditional ML predictor enhances separation time prediction based on flight events. ML predictions are then integrated as safety constraints in a time-constrained traveling salesman problem formulation, solved using mixed-integer linear programming (MILP). Historical flight recordings and model predictions address uncertainties between successive flights, ensuring reliability. The proposed method is validated using real-world data from the Atlanta Air Route Traffic Control Center (ARTCC ZTL). Case studies demonstrate an average 17.2% reduction in total landing time compared to the First-Come-First-Served (FCFS) rule. Unlike FCFS, the proposed methodology considers uncertainties, instilling confidence in scheduling. The study concludes with remarks and outlines future research directions

Wind effect analysis on air traffic congestion in terminal area via cellular automata

The behavior of any traffic flow is sensitive to the speed pattern of the vehicles involved. The heavier the traffic, the more sensitive the behavior is to speed changes. Focusing on air traffic flow, weather condition has a major role in the deviations of aircraft operational speed from the desired speed and causes surplus delays. In this paper, the effects of wind on delays in a terminal area are analyzed using a Cellular Automaton (CA) model. Cellular automata are discrete models that are widely used for simulating complex emerging properties of dynamic systems. A one-dimensional cellular array is used to model the flow of the terminal traffic into a wind field. The proposed model, due to the quickness and acceptable level of accuracy, can be utilized online in the tactical phase of air traffic control processes and system-level decision-makings, where quick response and system behavior are needed. The modeled route is an RNAV STAR route to Atlanta International Airport. The model is verified by real traffic data in a non-delayed scenario. Based on simulation results, the proposed model exhibits an acceptable level of accuracy (3–15% accuracy drop), with worthy time and computational efficiency (about 2.9 seconds run time for a 2-hour operation)

Integrated and joint optimisation of runway-taxiway-apron operations on airport surface

Airports are the main bottlenecks in the Air Traffic Management (ATM) system. The predicted 84% increase in global air traffic in the next two decades has rendered the improvement of airport operational efficiency a key issue in ATM. Although the operations on runways, taxiways, and aprons are highly interconnected and interdependent, the current practice is not integrated and piecemeal, and overly relies on the experience of air traffic controllers and stand allocators to manage operations, which has resulted in sub-optimal performance of the airport surface in terms of operational efficiency, capacity, and safety. This thesis proposes a mixed qualitative-quantitative methodology for integrated and joint optimisation of runways, taxiways, and aprons, aiming to improve the efficiency of airport surface operations by integrating the operations of all three resources and optimising their coordination. This is achieved through a two-stage optimisation procedure: (1) the Integrated Apron and Runway Assignment (IARA) model, which optimises the apron and runway allocations for individual aircraft on a pre-tactical level, and (2) the Integrated Dynamic Routing and Off-block (IDRO) model, which generates taxiing routes and off-block timing decisions for aircraft on an operational (real-time) level. This two-stage procedure considers the interdependencies of the operations of different airport resources, detailed network configurations, air traffic flow characteristics, and operational rules and constraints. The proposed framework is implemented and assessed in a case study at Beijing Capital International Airport. Compared to the current operations, the proposed apron-runway assignment reduces total taxiing distance, average taxiing time, taxiing conflicts, runway queuing time and fuel consumption respectively by 15.5%, 15.28%, 45.1%, [58.7%, 35.3%, 16%] (RWY01, RWY36R, RWY36L) and 6.6%; gated assignment is increased by 11.8%. The operational feasibility of this proposed framework is further validated qualitatively by subject matter experts (SMEs). The potential impact of the integrated apron-runway-taxiway operation is explored with a discussion of its real-world implementation issues and recommendations for industrial and academic practice.Open Acces

Agent-based Modelling and Simulation of Air Transport Technology

Declining travel time differences of mid-distance transport modes motivate use of multi-agent simulation models to analyze and forecast behaviour of actors in the transport system. This paper focuses on air-transport technology. A simulation model is proposed, that represents details of air traffic microscopically but is fast enough to enable an iterative simulation-based passenger-trip assignment. Aircraft are modelled in detail in respect to departure time and seat availability. Modelling of airports and routes of aircraft focuses on the available capacity of runways. Several simulation runs illustrate how the model can be calibrated using available parameters. The model can be used for an agent-based traffic assignment. Overall, the approach appears to be suited to analyze and forecast mid-distance transport

Evaluating Network Analysis and Agent Based Modeling for Investigating the Stability of Commercial Air Carrier Schedules

For a number of years, the United States Federal Government has been formulating the Next Generation Air Transportation System plans for National Airspace System improvement. These improvements attempt to address air transportation holistically, but often address individual improvements in one arena such as ground or in-flight equipment. In fact, air transportation system designers have had only limited success using traditional Operations Research and parametric modeling approaches in their analyses of innovative operations. They need a systemic methodology for modeling of safety-critical infrastructure that is comprehensive, objective, and sufficiently concrete, yet simple enough to be deployed with reasonable investment. The methodology must also be amenable to quantitative analysis so issues of system safety and stability can be rigorously addressed

Discrete Event Simulations

Considered by many authors as a technique for modelling stochastic, dynamic and discretely evolving systems, this technique has gained widespread acceptance among the practitioners who want to represent and improve complex systems. Since DES is a technique applied in incredibly different areas, this book reflects many different points of view about DES, thus, all authors describe how it is understood and applied within their context of work, providing an extensive understanding of what DES is. It can be said that the name of the book itself reflects the plurality that these points of view represent. The book embraces a number of topics covering theory, methods and applications to a wide range of sectors and problem areas that have been categorised into five groups. As well as the previously explained variety of points of view concerning DES, there is one additional thing to remark about this book: its richness when talking about actual data or actual data based analysis. When most academic areas are lacking application cases, roughly the half part of the chapters included in this book deal with actual problems or at least are based on actual data. Thus, the editor firmly believes that this book will be interesting for both beginners and practitioners in the area of DES

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 320)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during January, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Macroscopic Model and Simulation Analysis of Air Traffic Flow in Airport Terminal Area

We focus on the spatiotemporal characteristics and their evolvement law of the air traffic flow in airport terminal area to provide scientific basis for optimizing flight control processes and alleviating severe air traffic conditions. Methods in this work combine mathematical derivation and simulation analysis. Based on cell transmission model the macroscopic models of arrival and departure air traffic flow in terminal area are established. Meanwhile, the interrelationship and influential factors of the three characteristic parameters as traffic flux, density, and velocity are presented. Then according to such models, the macro emergence of traffic flow evolution is emulated with the NetLogo simulation platform, and the correlativity of basic traffic flow parameters is deduced and verified by means of sensitivity analysis. The results suggest that there are remarkable relations among the three characteristic parameters of the air traffic flow in terminal area. Moreover, such relationships evolve distinctly with the flight procedures, control separations, and ATC strategies

Optimización estática de la secuencia de aterrizajes en entornos con varias pistas

Este proyecto se ocupa de la resolución del problema de secuenciar los aterrizajes de un conjunto de aviones en un aeropuerto (ALP) considerando un entorno estático. En los aeropuertos es habitual que el gestor aeroportuario se enfrente a problemas de capacidad que se agravan en determinadas épocas del año, días concretos o rangos horarios. Esta circunstancia se manifiesta en forma de retrasos generalizados, ya que, cuando en un aeropuerto congestionado es necesario modificar el horario de un vuelo, reajustar la planificación hace que muchos otros se vean afectados. Aumentar la capacidad de los aeropuertos (pistas de aterrizajes y puertas de embarque) se ha convertido en un factor limitante a la hora de hacer frente a la creciente demanda de vuelos en la actualidad. Uno de los principales factores que determinan el rendimiento y eficiencia de las pistas de aterrizaje son los criterios de separación requeridos entre los aterrizajes y despegues de los aviones. Debido a su complejidad, es muy difícil encontrar la solución óptima al problema en la mayoría de los casos. El colapso no afecta solamente a la infraestructura del aeropuerto, sino también en los espacios para estacionar coches, en las zonas reservadas para taxis, en la necesidad de contar con conexiones ferroviarias y, sobre todo, en que las terminales cuenten con suficientes slots para que las aeronaves puedan operar. Sin embargo, otro problema y de mayor relevancia es la saturación de las rutas. En puntos del planeta como el Atlántico Norte o el Sudeste Asiático se viven auténticas autopistas de aviones, cuyo número crece año a año y puede ocasionar retrasos y cancelaciones. Para obtener soluciones al problema presentado, se utilizan los algoritmos de recocido simulado (SA) y búsqueda en entornos variables (VNS). Para comparar el desempeño de ambas técnicas se resuelven cinco problemas de dimensiones 10, 15, 20, 30 y 50 aviones, respectivamenteThis project deals with solving the problem of sequencing the landings of a set of airplanes at an airport (ALP) considering a static environment. It is usual for the airport manager to face capacity problems that worsen at certain times of the year, specific days or time ranges. This circumstance manifests itself in the form of generalized delays, since when a congested airport needs to modify the schedule of a flight, readjusting the planning causes many others to be affected. Increasing the capacity of airports (runways and boarding gates) has become a limiting factor when it comes to coping with the growing demand for flights today. One of the main factors that determine the performance and efficiency of runways are the separation criteria required between aircraft landings and takeoffs. Due to its complexity, it is very difficult to find the optimal solution to the problem in most cases. The collapse does not only affect the infrastructure of the airport, but also in spaces for parking cars, in areas reserved for taxis, in the need to have rail connections and, above all, in which the terminals have enough slots so that the aircraft can operate. However, another problem and of greater relevance is the saturation of the routes. In areas of the planet such as the North Atlantic or Southeast Asia real motorways of airplanes live, whose number grows every year and can cause delays and cancellations. To obtain solutions to the presented problem, the Simulated Annealing (SA) and Variable Neighbourhood Search (VNS) algorithms are used. To compare the performance of both techniques, five problems of dimensions 10, 15, 20, 30 and 50 aircraft, respectively, are solved.Universidad de Sevilla. Máster en Ingeniería Industria