Risk-Based Framework for the Integration of RPAS in Non-Segregated Airspace

Remotely Piloted Aircraft Systems (RPAS) are new airspace users that require to be safely integrated into the non-segregated airspace. Currently, their integration is planned for the horizon 2025, but there is a lot of pressure by RPAS operators to fly as soon as possible. This research focuses on the development of a risk-based framework for the integration of RPAS in non-segregated airspace. The risk-based framework relies on a hierarchical methodology that is split into two time horizons: design and operation. Different operational and geometrical factors characterise each stage. Then, a set of risk and operational indicators are defined for each stage. These indicators evaluate the operational airspace state and provide information about how the integration of RPAS should be. Primary results provide information about geographical and temporary restrictions. Geographical restrictions refer to the airways that favour or inhibit the integration of RPAS, and temporary restrictions denote the time span when the RPAS can pierce into the airspace

Estudio sobre la viabilidad de la implementación de criterios medioambientales en la operación de ascenso continuo

El objetivo de esta investigación es el de analizar las distintas metodologías utilizadas actualmente en la evaluación medioambiental de las operaciones aeronáuticas, particularizando su estudio en las operaciones de ascenso continuo y su integración en una optimización multiobjetiv

Bayesian Networks for Decision-Making and Causal Analysis under Uncertainty in Aviation

Most decisions in aviation regarding systems and operation are currently taken under uncertainty, relaying in limited measurable information, and with little assistance of formal methods and tools to help decision makers to cope with all those uncertainties. This chapter illustrates how Bayesian analysis can constitute a systematic approach for dealing with uncertainties in aviation and air transport. The chapter addresses the three main ways in which Bayesian networks are currently employed for scientific or regulatory decision-making purposes in the aviation industry, depending on the extent to which decision makers rely totally or partially on formal methods. These three alternatives are illustrated with three aviation case studies that reflect research work carried out by the authors

Continuous climb operations: the following steps

Typically air traffic controller manages departure traffic gradually in the airport airspace neighborhoods, providing clearances for the access to higher altitudes determined by conditions of traffic flow mix. This air traffic management implies the realization of several level-offs at each departure which suppose an increase of the fuel consumption firstly and as result the rise of overall cost of operation. Furthermore, not only operational costs are affected but both noise and pollutants emissions are increased, eco-friendly departure procedures requires a special heed because a new international range of equirements desire to abate the environmental impact due to aircraft operations. In order to avoid this inefficient departure procedure, continuous climb operations (CCOs) are defined as novel procedures which will ease the pilot departure perform. CCO is the ideal path an aircraft might fly in the absence of any ATC issues. The aim of this work is to analyze different CCOs techniques and evaluate the feasibility of implement them in a real scenario. A review of diverse CCOs based on different concepts of operation is presented, as minimizing fuel consumption, noise impact, constant climb speed,etc., as well as the definition of the requirements a CCO must fulfill which shape the feasible solution space. Lastly, Palma ATM environment is presented as case study of the viability of implementing CCO procedures among real requirements and expected drawbacks

Impact of continuous climb operations in a high traffic density TMA = Impacto en la capacidad operativa de un TMA de alta densidad por la integración de operaciones de ascenso continuo

El transporte aéreo actual está sufriendo una de las mayores transformaciones en su historia debido al desarrollo de los macro programas SESAR y NextGen. Para gestionar este impresionante crecimiento, SESAR y NextGen están desarrollando nuevos procedimientos que contribuyen a la reducción del impacto medioambiental en los alrededores aeroportuarios. Estos procedimientos amigables con el medioambiente se basan en la operación de trayectorias continuas a lo largo del vuelo. Sin embargo, cada vez es más difícil usar trayectorias de vuelo óptimas debido al aumento del tráfico aéreo. Esta tesis tiene como objetivo analizar el impacto de las Operaciones de Ascenso Continuo (CCOs) en un Area de Control Terminal (TMA) de alta densidad de tráfico. Las CCOs son nuevas trayectorias optimizadas de despegue que minimizan el consumo de combustible, las emisiones y los niveles de ruido en los alrededores de los aeropuertos. Complementaria a la investigación realizada hasta ahora, esta tesis no se centra en las técnicas de optimización de estos procedimientos si no en su impacto en términos de seguridad y capacidad. La razón es que la introducción de CCOs en aeropuertos con poco tráfico aéreo no supone ningún impedimento, sin embargo, en TMAs con un elevado número de operaciones estos procedimientos pueden estar prohibidos durante las horas de mayor afluencia de tráfico. La finalidad última de la integración de CCOs es permitir el vuelo de trayectorias optimizadas por las aerolíneas. No obstante, la variabilidad asociada a los perfiles óptimos que pueden ser operados es muy grande. El diseño del espacio aéreo y de los procedimientos, así como el Control del Tráfico Aéreo (ATC) deben proporcionar un sistema del tráfico aéreo que favorezca la integración de CCOs. Una CCO no desaparece por la intervención del ATC, pero la aeronave empeora sus actuaciones. Por lo tanto, el ATC debería tener como objetivo facilitar la operación de trayectorias optimizadas libres de su interacción. Este objetivo no puede alcanzarse si n la modificación de las actuales técnicas de trabajo del ATC y del diseño del espacio aéreo. Por lo tanto, se han calculado nuevas mínimas de separación en pista para consecutivas CCOs. Estas mínimas de separación para CCOs permiten una salida libre de conflictos desde la pista hasta el nivel de vuelo. Las compatibilidades entre los flujos aéreos de CCOs y de llegadas se han evaluado mediante el desarrollo de un nuevo modelo de riesgo de conflicto. Este modelo analiza estadísticamente la probabilidad de conflicto en los cruces del espacio aéreo. Esta valoración permite conocer si el actual diseño del espacio aéreo valida la integración de trayectorias CCOs o, por el contrario, se necesita un rediseño de los procedimientos de vuelo. De este modo, se puede inferir si la integración de estas nuevas trayectorias va a requerir un elevado número de intervenciones ATC. Finalmente, esta tesis concluye con un análisis de capacidad. Este análisis necesita el desarrollo de un algoritmo de programación de aeronaves y de un algoritmo de detección y resolución de conflictos para obtener programaciones de aeronaves libres de conflictos. Además, se aplican los métodos de Monte Carlo para variar el porcentaje de CCOs considerado en una programación. Las mayores contribuciones de esta tesis son la cuantificación de nuevas mínimas de separación para CCOs, el desarrollo de un nuevo modelo de riesgo de conflicto que puede sustentar un proceso de toma de decisiones para el diseño del espacio aéreo y la cuantificación del impacto en la capacidad por la integración de CCOs. La reducción de capacidad en el TMA de palma para la integración de un 100% de trayectorias CCO supera el 30% de la capacidad teórica máxima. Sin embargo, el peor resultado de capacidad para la integración de un 100% de trayectorias CCO es mayor que la capacidad declarada actual. Esto significa que se puede alcanzar un 100% de integración de trayectorias CCO sin una reducción en la capacidad operacional declarada durante periodos pico. ----------ABSTRACT---------- Air transport is currently undergoing one of the biggest transformations in its history due to the development of the macro-programs SESAR and NextGen. To manage this growth, SESAR and NextGen are developing novel procedures that contribute to pollutant reduction in the vicinity of airports. These eco-friendly procedures are based on continuous operations throughout the flight. However, it is increasingly difficult to use flight-optimal trajectories due to the on-going growth in air traffic. This dissertation aims to assess the impact of Continuous Climb Operations (CCOs) in a high traffic density Terminal Control Area (TMA). CCOs are new optimal departing trajectories that minimise fuel consumption, emissions and noise-levels within the vicinity of airports. In contrast to previous research, this dissertation does not focus on the optimisation techniques of these procedures but the impact in terms of safety and capacity. The reason is that the introduction of CCOs in low-density airports does not mean any impediment. However, these procedures can be prevented from their use during rush hours in high-density TMAs. The ultimate goal of the CCO integration is to permit the operation of optimised trajectories by airlines. Nonetheless, the variability associated with optimised trajectories that can be operated is very large. Airspace and procedure design, as well as Air Traffic Control (ATC), must provide an air transport system that favour the integration of CCOs. A CCO is not removed by the ATC interaction, but the aircraft worsen their performances. Then, ATC should focus on facilitating the operation of optimised trajectories free of their interactions. This cannot be achieved without the modification of current ATC techniques and airspace design. Therefore, new runway separation minima are calculated for consecutive CCOs. These CCO separation minima ensure a conflict-free departure from the runway to the cruise level with other CCOs. Compatibilities between CCO and arriving flows are assessed by the development of a new conflict-risk model. This conflict-risk model statistically assesses the probability of conflict in the crossing points of the airspace. This assessment permits to know if the current airspace design validates the integration of CCOs or, conversely, a redesign of the flight procedures is required. In doing so, it can be inferred whether or not the integration of these new optimal trajectories will require a high-level of ATC interventions. Finally, this dissertation concludes with a capacity assessment. The capacity assessment needs the development of a scheduling algorithm and a conflict-detection and resolution algorithm to obtain conflict-free scheduling. Moreover, Monte Carlo methods are applied to vary the percentage of CCOs and air traffic flows considered in scheduling. Therefore, the most significant contributions of this dissertation are the quantification of new CCO runway separation minima, the development of a new conflict-risk model that could underlie a making-decision process for airspace design, and the quantification of the capacity impact by the integration of CCOs. The capacity reduction in Palma TMA for the integration of 100% CCO trajectories is over 30% of the maximum theoretical capacity. However, the worst capacity result for 100% CCO integration is major than current operational capacity. This implies that 100% CCO integration can be achieved without reducing current operational capacity during rush periods

Ad Hoc Minimum Separation: A challenge for Air Traffic Control (ATC)

Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de BurgosThe SESAR programme aims at developing the future European air traffic management system. It focuses on four keys areas: capacity, safety, efficiency and environment. In view of the expected growth in air traffic demand in the coming years, the current goal is to increase the airspace capacity, which is already close to saturation in many cases. Currently, the separation standards applied in a given volume of airspace are fixed, both horizontally and vertically, which means that in many cases this is one of the determining factors of capacity. Separation management is an area where improvement is sought, in particular through the application of new operational concepts (separation modes) which include the redefinition of aircraft separation minima. One of the solutions to be investigated is the variable (Ad Hoc) separation proposal put forward by SESAR. This future concept implies a change in the application of separation minima from the current fixed standards to a new variable approach. With this new concept, ATCo (Air Traffic Controller) would separate aircraft by applying different separation minima in the same volume of airspace. These separation values are tactically determined for each particular aircraft pair (Ad Hoc) depending on a number of factors: aircraft categories, encounter geometry, atmospheric conditions, etc. Applying different separation minima in the same volume of airspace implies a substantial change in some of the ATC activities. Also, new functionalities in ATC support tools are needed. This study presents the Ad Hoc separation operational concept and provides the basis for the development of the algorithm for calculating variable separation minima

Performance Impact Assessment of Reducing Separation Minima for En-Route Operations

The required minimum separation distance between aircraft is believed to be one of the limiting factors on airspace capacity. In recent decades, aircraft separation rules have been modified by progressively shortening the required minimum separation distance. Following this trend in the coming years, a further reduction in the minimum separation distance would be expected. Still, a thorough assessment of the impact of this action on air traffic management performance should be carried out before investing in a reduction of separation minima. A Monte Carlo analysis of the en-route Spanish airspace shows that it is worth reducing the en-route minimum separation distance from 5 NM to 3 NM. This paper shows that a separation minima reduction will bring significant fuel savings, flight delay reduction, air traffic controller workload drop, and overall improvement of safety

Performance impact assessment of reducing separation minima for en-route operations

This article belongs to the Special Issue Advances in Air Traffic and Airspace Control and Management.The required minimum separation distance between aircraft is believed to be one of the limiting factors on airspace capacity. In recent decades, aircraft separation rules have been modified by progressively shortening the required minimum separation distance. Following this trend in the coming years, a further reduction in the minimum separation distance would be expected. Still, a thorough assessment of the impact of this action on air traffic management performance should be carried out before investing in a reduction of separation minima. A Monte Carlo analysis of the en-route Spanish airspace shows that it is worth reducing the en-route minimum separation distance from 5 NM to 3 NM. This paper shows that a separation minima reduction will bring significant fuel savings, flight delay reduction, air traffic controller workload drop, and overall improvement of safety

Tactical runway scheduling for demand and delay management

Airports are limited in terms of capacity. Particularly, runways can only accommodate a certain number of movements (arrivals and departures) while ensuring safety and determined operational requirements. In such a constrained operating environment, any reduction in system capacity results in major delays with significant costs for airlines and passengers. Therefore, the efficient operation of airports is a critical cornerstone for demand and delay management of the whole air transportation system. Runway scheduling deals with the sequencing of arriving and departing aircraft at airports such that a predefined objective is optimized subject to several operational constraints, like the dependency of separation on the leading and trailing aircraft type or the runway occupancy time. Scheduling arrivals and departures at runways is a complex problem that needs to address diverse and often competing considerations among involved flights. In the context of the Airport Collaborative Decision Making (A-CDM) programme, airport operators and air navigation service providers require arrival and departure management tools that improve aircraft flows at airports. Airport runway optimization, as the main element that combines airside and groundside operations, is an ongoing challenge for air traffic management. By considering real airport performance data with scheduled and actual movements, as well as arrival/departure delays, we present a robust model together with an optimization algorithm, which incorporates the knowledge of uncertainty into the tactical operational step. Our model has been validated with real data from a large international European airport in different traffic scenarios. Results are compared to the actual sequencing of flights and show that the algorithm can significantly contribute to the reduction of delay, while adhering as much as possible to the operative procedures and constraints, and to the objectives of the airport stakeholders. Computational experiments performed on the case study illustrate the benefits of this arrival/departure integrated approach

Design of an ATC Tool for Conflict Detection Based on Machine Learning Techniques

Given the ongoing interest in the application of Machine Learning (ML) techniques, the development of new Air Traffic Control (ATC) tools is paramount for the improvement of the management of the air transport system. This article develops an ATC tool based on ML techniques for conflict detection. The methodology develops a data-driven approach that predicts separation infringements between aircraft within airspace. The methodology exploits two different ML algorithms: classification and regression. Classification algorithms denote aircraft pairs as a Situation of Interest (SI), i.e., when two aircraft are predicted to cross with a separation lower than 10 Nautical Miles (NM) and 1000 feet. Regression algorithms predict the minimum separation expected between an aircraft pair. This data-driven approach extracts ADS-B trajectories from the OpenSky Network. In addition, the historical ADS-B trajectories work as 4D trajectory predictions to be used as inputs for the database. Conflict and SI are simulated by performing temporary modifications to ensure that the aircraft pierces into the airspace in the same time period. The methodology is applied to Switzerland’s airspace. The results show that the ML algorithms could perform conflict prediction with high-accuracy metrics: 99% for SI classification and 1.5 NM for RMSE