Lessons from building an automated pre-departure sequencer for airports

Commercial airports are under increasing pressure to comply with the Eurocontrol collaborative decision making (CDM) initiative, to ensure that information is passed between stakeholders, integrate automated decision support or make predictions. These systems can also aid effective operations beyond the airport by communicating scheduling decisions to other relevant parties, such as Eurocontrol, for passing on to downstream airports and enabling overall airspace improvements. One of the major CDM components is aimed at producing the target take-off times and target startup-approval times, i.e. scheduling when the aircraft should push back from the gates and start their engines and when they will take off. For medium-sized airports, a common choice for this is a “pre-departure sequencer” (PDS). In this paper, we describe the design and requirements challenges which arose during our development of a PDS system for medium sized international airports. Firstly, the scheduling problem is highly dynamic and event driven. Secondly, it is important to end-users that the system be predictable and, as far as possible, transparent in its operation, with decisions that can be explained. Thirdly, users can override decisions, and this information has to be taken into account. Finally, it is important that the system is as fair as possible for all users of the airport, and the interpretation of this is considered here. Together, these factors have influenced the design of the PDS system which has been built to work within an existing large system which is being used at many airport

Standard concepts for performance improvements in the airport operations areas: global interoprability

Because of the exponential growth of air traffic and its importance of integration of countries, the implementation of improvements in the Global ATM system is becoming increasingly necessary. Within this scope, ICAO brings, within its Global Air Navigation Plan (GANP), an easily understood methodology called: “Aviation System Blocks Upgrade” (ASBU). It defines a language with a programmatic and flexible approach, aiming at performance improvements in the systems. And one of the sectors where one of these performance improvements is sought, as recommended in the ASBU, is the Airport Operations Area. In this area is the Airport Collaborative Decision Making (A-CDM) process. This research aimed to review and improve the A-CDM method to enable its use in airports with lower disbursement capacity. It is based on regulations issued by the International Civil Aviation Organization (ICAO) and academic papers. Theoretically, it went deeper into the various global air navigation systems, such as the processes employed by the European Organization for the Safety of Air Navigation (EUROCONTROL) and the Federal Aviation Administration (FAA). Positions from entities such as the International Air Transport Association (IATA) and the Civil Air Navigation Services Organization (CANSO) were also researched. Subsequently, case studies of airports and interviews with international experts with knowledge on the subject were carried out. Finally, a survey was conducted with members of the Air Sector from around the world. Always focused on seeking compatibilities and opportunities for improvement in the process, mainly in economic gains. According to the sequential strategy exposed above, a scenario analysis is done based on the results obtained at the end of the work. Then, a conclusion is presented, which aims to to apply the referred system, not only in countries with high capacity disbursement but mainly to deliver a solution that allows its application in countries and airports with medium to low financial resources. This solution presented is the goal sought in the research.Tendo em vista o crescimento exponencial do tráfego aéreo e a sua importância na integração dos países, a implantação de melhorias no sistema ATM Global torna-se cada vez mais necessária. Neste sentido a ICAO preconiza, dentro do seu Global Air Navigation Plan (GANP), uma metodologia de fácil entendimento chamada: “Aviation System Blocks Upgrade” (ASBU). Tal metodologia define uma linguagem com abordagem programática, e flexível, visando melhorias de desempenho nos sistemas. E um dos setores onde é procurada uma dessas melhorias de desempenho, conforme preconizado no ASBU, é a área de Operações Aeroportuárias e, em particular, o processo de Airport Colaborative Decision Making (A-CDM). Esta investigação visou realizar uma revisão do método A-CDM, com base em regulamentos e trabalhos acadêmicos sobre o assunto. Aprofundando teoricamente com base nos diversos sistemas de navegação aérea globais, como os processos empregados pela European Organisation for the Safety of Air Navigation (EUROCONTROL) e pela Federal Aviation Administration (FAA). Também foram pesquisados os posicionamentos a respeito do tema de entidades associativas, como da Airports Council International (ACI), da International Air Transport Association (IATA) e da Civil Air Navigation Services Organisation (CANSO). De forma subsequente realizaram-se estudos de caso de aeroportos e foram realizadas entrevistas com especialistas internacionais conhecedores do assunto. Finalmente realizou-se um inquérito com integrantes do Setor Aéreo de todo o mundo. Sempre com o foco de buscar compatibilidades e oportunidades de melhoria no referido processo, principalmente em termos de ganhos econômicos. Ao final do trabalho, de acordo com a estratégia sequencial acima exposta, e com base no resultados colhidos, é feita uma análise de cenário e apresentada uma conclusão, a qual visa que o referido sistema possa ser aplicado, não somente em países de grande capacidade de investimento mas também, e principalmente, apresentar uma solução que permita sua aplicação em países, e aeroportos, com médios a baixos recursos financeiros. Sendo este o resultado buscado na pesquisa

Arrival manager (AMAN) and its implementation study at Vilnius International Airport

The aim of this thesis is to study in detail the working principle of AMAN, its components involved, develop a trajectory prediction simulator using BADA 3.6 and compare the initial flight plan predicted time with that of TP simulator. Due to the increasing traffic demands in major European airports, those airports are implementing it to assist the controllers and decrease their workload. AMAN is used to balance the flow of inbound aircraft and capacity of airport by proving sequence of aircrafts approaching the runway and it also helps controllers in the sequencing and merging process which reduces the workload of the controllers. In this thesis special attention is given to Baltic FAB and in particular study of AMAN and its implementation is done for Vilnius International Airport. The objective of thesis is to develop a trajectory prediction simulator because all AMAN's are based on prediction of aircrafts arrival time and is also the most important part of the AMAN. In order to develop this simulator software like MATLAB and NEST are used. However all the aircraft performance data for descent phase of aircrafts are obtained using the BADA 3.6. The arrival time calculated by the trajectory prediction simulator is quite similar to that of initial flight plan arrival time. Better result in the prediction of arrival time is obtained using the trajectory prediction simulator. Nevertheless, we need to take into account that some assumptions were made in the development of the simulator and the results obtained are not hundred percent realistic. On the other hand, it is seen that the traffic growth is getting higher and higher every year in Vilnius International Airport. But, it is operating far below the potential physical capacity of the airport and provided with higher number of flights to and from this airport, it can handle the traffic without any major problems. In long run if the air traffic goes on increasing in the same rate then there will be the need of AMAN implementation in Vilnius Airport to assist controllers and maintain the security level marked by the SESARJU

A multi-objective, decomposition-based algorithm design methodology and its application to runaway operations planning

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2004.Includes bibliographical references (p. 283-296).(cont.) to the design of a heuristic decomposed algorithm for solving the ROP problem. This decomposition methodology offers an original paradigm potentially applicable to the design of solution algorithms for a class of problems with functions and parameters that, similar to those of the ROP problem, can be parsed in subsets. The potential merit in decomposing the ROP problem in two stages and the resulting utility of the two-stage solution algorithm are evaluated by performing benefits analysis across specific dimensions related to airport efficiency, as well as stability and robustness analysis of the algorithm output.Significant delays and resulting environmental impacts are commonly observed during departure operations at major US and European airports. One approach for mitigating airport congestion and delays is to exercise tactical operations planning and control with an objective to improve the efficiency of surface and terminal area operations. As a subtask of planning airport surface operations, this thesis presents a thorough study of the structure and properties of the Runway Operations Planning (ROP) problem. Runway Operations Planning is a workload-intensive task for controllers because airport operations involve many parameters, such as departure demand level and timing that are typically characterized by a highly dynamic behavior. This research work provides insight to the nature of this task, by analyzing the different parameters involved in it and illuminating how they interact with each other and how they affect the main functions in the problem of planning operations at the runway, such as departure runway throughput and runway queuing delays. Analysis of the Runway Operations Planning problem revealed that there is a parameter of the problem, namely the demand "weight class mix", which: a) is more "dominant" on the problem performance functions that other parameters, b) changes value much slower than other parameters and c) its value is available earlier and with more certainty than the value of other parameters. These observations enabled the parsing of the set of functions and the set of parameters in subsets, so that the problem can be addressed sequentially in more than one stage where different parameter subsets are treated in different stages. Thus, a decomposition-based algorithm design technique was introduced and appliedby Ioannis D. Anagnostakis.Ph.D

A Multi-Objective, Decomposition-Based Algorithm Design Methodology and its Application to Runway Operations Planning

Significant delays and resulting environmental impacts are commonly observed during departure operations at major US and European airports. One approach for mitigating airport congestion and delays is to exercise tactical operations planning and control with an objective to improve the efficiency of surface and terminal area operations. As a subtask of planning airport surface operations, this thesis presents a thorough study of the structure and properties of the Runway Operations Planning (ROP) problem. Runway Operations Planning is a workload-intensive task for controllers because airport operations involve many parameters, such as departure demand level and timing that are typically characterized by a highly dynamic behavior. This research work provides insight to the nature of this task, by analyzing the different parameters involved in it and illuminating how they interact with each other and how they affect the main functions in the problem of planning operations at the runway, such as departure runway throughput and runway queuing delays. Analysis of the Runway Operations Planning problem revealed that there is a parameter of the problem, namely the demand “weight class mix”, which: a) is more “dominant” on the problem performance functions that other parameters, b) changes value much slower than other parameters and c) its value is available earlier and with more certainty than the value of other parameters. These observations enabled the parsing of the set of functions and the set of parameters in subsets, so that the problem can be addressed sequentially in more than one stage where different parameter subsets are treated in different stages. Thus, a decompositionbased algorithm design technique was introduced and applied to the design of a heuristic decomposed algorithm for solving the ROP problem. This decomposition methodology offers an original paradigm potentially applicable to the design of solution algorithms for a class of problems with functions and parameters that, similar to those of the ROP problem, can be parsed in subsets. The potential merit in decomposing the ROP problem in two stages and the resulting utility of the two-stage solution algorithm are evaluated by performing benefits analysis across specific dimensions related to airport efficiency, as well as stability and robustness analysis of the algorithm output

A Hybrid Tabu/Scatter Search Algorithm for Simulation-Based Optimization of Multi-Objective Runway Operations Scheduling

As air traffic continues to increase, air traffic flow management is becoming more challenging to effectively and efficiently utilize airport capacity without compromising safety, environmental and economic requirements. Since runways are often the primary limiting factor in airport capacity, runway operations scheduling emerge as an important problem to be solved to alleviate flight delays and air traffic congestion while reducing unnecessary fuel consumption and negative environmental impacts. However, even a moderately sized real-life runway operations scheduling problem tends to be too complex to be solved by analytical methods, where all mathematical models for this problem belong to the complexity class of NP-Hard in a strong sense due to combinatorial nature of the problem. Therefore, it is only possible to solve practical runway operations scheduling problem by making a large number of simplifications and assumptions in a deterministic context. As a result, most analytical models proposed in the literature suffer from too much abstraction, avoid uncertainties and, in turn, have little applicability in practice. On the other hand, simulation-based methods have the capability to characterize complex and stochastic real-life runway operations in detail, and to cope with several constraints and stakeholders’ preferences, which are commonly considered as important factors in practice. This dissertation proposes a simulation-based optimization (SbO) approach for multi-objective runway operations scheduling problem. The SbO approach utilizes a discrete-event simulation model for accounting for uncertain conditions, and an optimization component for finding the best known Pareto set of solutions. This approach explicitly considers uncertainty to decrease the real operational cost of the runway operations as well as fairness among aircraft as part of the optimization process. Due to the problem’s large, complex and unstructured search space, a hybrid Tabu/Scatter Search algorithm is developed to find solutions by using an elitist strategy to preserve non-dominated solutions, a dynamic update mechanism to produce high-quality solutions and a rebuilding strategy to promote solution diversity. The proposed algorithm is applied to bi-objective (i.e., maximizing runway utilization and fairness) runway operations schedule optimization as the optimization component of the SbO framework, where the developed simulation model acts as an external function evaluator. To the best of our knowledge, this is the first SbO approach that explicitly considers uncertainties in the development of schedules for runway operations as well as considers fairness as a secondary objective. In addition, computational experiments are conducted using real-life datasets for a major US airport to demonstrate that the proposed approach is effective and computationally tractable in a practical sense. In the experimental design, statistical design of experiments method is employed to analyze the impacts of parameters on the simulation as well as on the optimization component’s performance, and to identify the appropriate parameter levels. The results show that the implementation of the proposed SbO approach provides operational benefits when compared to First-Come-First-Served (FCFS) and deterministic approaches without compromising schedule fairness. It is also shown that proposed algorithm is capable of generating a set of solutions that represent the inherent trade-offs between the objectives that are considered. The proposed decision-making algorithm might be used as part of decision support tools to aid air traffic controllers in solving the real-life runway operations scheduling problem

Aeronautical engineering: A continuing bibliography with indexes (supplement 258)

This bibliography lists 536 reports, articles, and other documents introduced into the NASA scientific and technical information system in October 1990. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Aeronautical engineering, a continuing bibliography with indexes

This bibliography lists 567 reports, articles and other documents introduced into the NASA scientific and technical information system in January 1984

Forensic Analysis

It is my pleasure to place before you the book ''Forensic Analysis - From Death to Justice'' which presents one of the major portions of the broad specialty of Forensic Science comprising mainly of Thanatology and Criminalistics. This book has been designed to incorporate a wide range of new ideas and unique works from all authors from topics like Forensic Engineering, Forensic Entomology and Crime Scene Investigation. I hope that it will be useful to practitioners of forensic medicine, experts, pathologists, law makers, investigating authorities, undergraduate and postgraduate medical school graduates of medicine

Cybernetics in Music

This thesis examines the use of cybernetics (the science of systems) in music, through the tracing of an obscured history. The author postulates that cybernetic music may be thought of as genera of music in its own right, whose practitioners share a common ontology and set of working practices that distinctly differ from traditional approaches to composing electronic music. Ultimately, this critical examination of cybernetics in music provides the framework for a series of original compositions and the foundation of the further study of cybernetic music