Efficient Algorithms For Optimal Arrival Scheduling And Air Traffic Flow Management
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Efficient Algorithms For Optimal Arrival Scheduling And Air Traffic Flow Management
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Author : Aditya Saraf
language : en
Publisher:
Release Date : 2007
Efficient Algorithms For Optimal Arrival Scheduling And Air Traffic Flow Management written by Aditya Saraf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
The research presented in this dissertation is motivated by the need for new, efficient algorithms for the solution of two important problems currently faced by the air-traffic control community: (i) optimal scheduling of aircraft arrivals at congested airports, and (ii) optimal National Airspace System (NAS) wide traffic flow management. In the first part of this dissertation, we present an optimal airport arrival scheduling algorithm, which works within a hierarchical scheduling structure. This structure consists of schedulers at multiple points along the arrival-route. Schedulers are linked through acceptance-rate constraints, which are passed up from downstream metering-points. The innovation in this scheduling algorithm is that these constraints are computed by using an Eulerian model-based optimization scheme. This rate computation removes inefficiencies introduced in the schedule through ad hoc acceptance-rate computations. The scheduling process at every metering-point uses its optimal acceptance-rate as a constraint and computes optimal arrival sequences by using a combinatorial search-algorithm. We test this algorithm in a dynamic air-traffic environment, which can be customized to emulate different arrival scenarios. In the second part of this dissertation, we introduce a novel two-level control system for optimal traffic-flow management. The outer-level control module of this two-level control system generates an Eulerian-model of the NAS by aggregating aircraft into interconnected controlvolumes. Using this Eulerian model of the airspace, control strategies like Model Predictive Control are applied to find the optimal inflow and outflow commands for each control-volume so that efficient flows are achieved in the NAS. Each control-volume has its separate innerlevel control-module. The inner-level control-module takes in the optimal inflow and outflow commands generated by the outer control-module as reference inputs and uses hybrid aircraft models to search for optimal trajectories to be flown by each aircraft so that the flows commanded by the outer control-module are achieved. The two-level control system is tested in a dynamic simulation. Furthermore, as a component of the Eulerian part of this two-level system, we present a method for deriving an aggregate airspace-model in real-time, without depending on online integration of aircraft trajectories. This method uses a baseline Eulerian airspace-model, which is derived offline using historical track-data. In real-time, parameters of this model are adapted depending on the differences between the baseline-model and the real-world. This book-keeping based model-derivation indirectly retains some trajectory information. Hence, it serves as an excellent trade-off between Eulerian and trajectory-based modeling approaches. Most importantly, as a vital improvement over previous approaches, we take into consideration the control-dependent nature of the Eulerian-model while computing optimal flow-control decisions. As a proof of concept, we derive a baseline model for the Fort-Worth center and adapt it to predict sector-counts for another set of air traffic data. We also demonstrate the use of this model in a simulation-based optimization scheme for regulating the arrival flow at the Dallas Fort-Worth airport. An application to optimal re-routing strategy computation is also presented.
Optimal Sequencing And Scheduling Algorithm For Traffic Flows Based On Extracted Control Actions Near The Airport
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Author : Sharmistha Chakrabarti
language : en
Publisher:
Release Date : 2023
Optimal Sequencing And Scheduling Algorithm For Traffic Flows Based On Extracted Control Actions Near The Airport written by Sharmistha Chakrabarti and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
This dissertation seeks to design an optimization algorithm, based on naturalistic flight data, with emphasis on safety to perform a benefits' analysis when sequencing and scheduling aircraft at the runway. The viability of creating a decision-support tool to aid air traffic controllers in sequencing and optimizing airport operations is evaluated through the benefits' analysis. Air traffic control is a complex and critical system that ensures the safe and efficient movement of aircraft within the airspace. This is particularly true in the immediate vicinity of an airport. Unlike in en-route or terminal area airspace where aircraft usually traverse well established routes and procedures, near the airport after completing a standard arrival procedure, the routes to the final approach are only partially defined. With safety being the foremost priority, the local tower controllers monitor and maintain separation between aircraft to prevent collisions and ensure the overall safety of the airspace. This involves constant surveillance, coordination, and decision-making to manage the dynamic movement of aircraft, changing weather conditions, and potential hazards. All the while, the controllers make decisions regarding tromboning or vectoring based on various factors, including traffic volume, airspace restrictions, weather conditions, operational efficiency, and safety considerations to ensure a safe traffic sequencing of aircraft at the runway. A novel framework is presented for modeling, characterizing, and clustering aircraft trajectories by extracting traffic control decisions of air traffic controllers. A hidden Markov model was developed and applied to transform trajectories from a sequence of temporal spatial position reports to a series of control actions. The edit distance is utilized for quantifying the dissimilarity of two variable-length trajectory strings, followed by the application of k-medoids algorithm to cluster the arrival flows. Next, a repeatable process for detecting and labeling outlier trajectories within a cluster is introduced. Through application on a set of historical trajectories at Ronald Reagan Washington National Airport (DCA), it is demonstrated that the proposed clustering framework overcomes the deficiency of the classical approach and successfully captures the arrival flows of trajectories, that undergo similar control actions. Leveraging on the set of arrival flows, statistical and machine learning models of air traffic controllers are created and evaluated when ordering aircraft to land at the runway. The potential inefficiencies are identified at DCA when sequencing aircraft. As such, there is a potential performance gap, and it appears that there is room for additional sequence optimization. With the goal of overcoming the potential inefficiencies at DCA, a mixed-integer zero-one formulation is designed for a single runway that takes into consideration safety constraints by means of separation constraints between aircraft imposed at each metering point from the entry to the airspace until landing. With the objective of maximizing runway throughput and minimizing the traversed distance, the model sequences and schedules arrivals and departures and generates safe and conflict-free arrival trajectories to actualize that scheduling. The output of the optimization shows that the model successfully recovers approximately 52% of the performance gap between the actual distance traversed and idealized (cluster centroids) distance traversed by all arrival aircraft. Moreover, each arrival aircraft, on average, traverses 2.12 nautical miles shorter than its historical trajectory and thus saving approximately 10 US gallons of jet fuel. By showcasing the potential benefits of the optimization, this dissertation takes a step towards achieving the long-term vision of developing a decision-support tool to assist air traffic controllers in optimally sequencing and scheduling aircraft. To fully leverage the potential benefits of optimization, further development and refinement of the algorithm are necessary to align it with real-world operational demands. As future work, the research would be expanded to integrate uncertainties like weather conditions, wind directions, etc. into the optimization.
Airline Scheduling And Air Traffic Control
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Author : Chiwei Yan
language : en
Publisher:
Release Date : 2017
Airline Scheduling And Air Traffic Control written by Chiwei Yan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
The global airline industry is a multi-stakeholder stochastic system whose performance is the outcome of complex interactions between its multiple decisions-makers under a high degree of uncertainty. Inadequate understanding of uncertainty and stakeholder preferences leads to adverse effects including airline losses, delays and disruptions. This thesis studies a set of topics in airline scheduling and air traffic control to mitigate some of these issues. The first part of the thesis focuses on building aircraft schedules that are robust against delays. We develop a robust optimization approach for building aircraft routes. The goal is to mitigate propagated delays, which are defined as the delays caused by the late arrival of aircraft from earlier flights and are the top cause of flight delays in the United States air transportation system. The key feature of our model is that it allows us to handle correlation in flight delays explicitly that existing approaches cannot handle efficiently. We propose an efficient decomposition algorithm to solve the robust model and present the results of numerical experiments, based on data from a major U.S. airline, to demonstrate its effectiveness compared to existing approaches. The second part of the thesis focuses on improving the planning of air traffic flow management (ATFM) programs by incorporating airline preferences into the decision-making process. We develop a voting mechanism to gather airline preferences of candidate ATFM designs. A unique feature of this mechanism is that the candidates are drawn from a domain with infinite cardinality described by polyhedral sets. We conduct a detailed case study based on actual schedule data at San Francisco International Airport to assess its benefits in planning of ground delay programs. Finally, we study an integrated airline network planning model which incorporates passenger choice behavior. We model passenger demand using a multinomial logit choice model and integrate it into a fleet assignment and schedule design model. To tackle the formidable computational challenge associated with solving this model, we develop a reformulation, decomposition and approximation scheme. Using data from a major U.S. airline, we prove that the proposed approach brings significant profit improvements over existing methods.
Air Transportation Systems Engineering
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Author : George L. Donohue
language : en
Publisher: AIAA
Release Date : 2001
Air Transportation Systems Engineering written by George L. Donohue and has been published by AIAA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Aeronautics categories.
The Dynamic Planner
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Author : Gregory L. Wong
language : en
Publisher: BiblioGov
Release Date : 2013-08
The Dynamic Planner written by Gregory L. Wong and has been published by BiblioGov this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08 with categories.
The Dynamic Planner (DP) has been designed, implemented, and integrated into the Center-TRACON Automation System (CTAS) to assist Traffic Management Coordinators (TMCs), in real time, with the task of planning and scheduling arrival traffic approximately 35 to 200 nautical miles from the destination airport. The TMC may input to the DP a series of current and future scheduling constraints that reflect the operation and environmental conditions of the airspace. Under these constraints, the DP uses flight plans, track updates, and Estimated Time of Arrival (ETA) predictions to calculate optimal runway assignments and arrival schedules that help ensure an orderly, efficient, and conflict-free flow of traffic into the terminal area. These runway assignments and schedules can be shown directly to controllers or they can be used by other CTAS tools to generate advisories to the controllers. Additionally, the TMC and controllers may override the decisions made by the DP for tactical considerations. The DP will adapt to computations to accommodate these manual inputs.
Analysis Of Sequencing And Scheduling Methods For Arrival Traffic
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Author : National Aeronautics and Space Administration (NASA)
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-07-06
Analysis Of Sequencing And Scheduling Methods For Arrival Traffic written by National Aeronautics and Space Administration (NASA) and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-06 with categories.
The air traffic control subsystem that performs scheduling is discussed. The function of the scheduling algorithms is to plan automatically the most efficient landing order and to assign optimally spaced landing times to all arrivals. Several important scheduling algorithms are described and the statistical performance of the scheduling algorithms is examined. Scheduling brings order to an arrival sequence for aircraft. First-come-first-served scheduling (FCFS) establishes a fair order, based on estimated times of arrival, and determines proper separations. Because of the randomness of the traffic, gaps will remain in the scheduled sequence of aircraft. These gaps are filled, or partially filled, by time-advancing the leading aircraft after a gap while still preserving the FCFS order. Tightly scheduled groups of aircraft remain with a mix of heavy and large aircraft. Separation requirements differ for different types of aircraft trailing each other. Advantage is taken of this fact through mild reordering of the traffic, thus shortening the groups and reducing average delays. Actual delays for different samples with the same statistical parameters vary widely, especially for heavy traffic. Neuman, Frank and Erzberger, Heinz Ames Research Center...
The Dynamic Planner
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Author : National Aeronautics and Space Administration (NASA)
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-06-11
The Dynamic Planner written by National Aeronautics and Space Administration (NASA) and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-11 with categories.
The Dynamic Planner (DP) has been designed, implemented, and integrated into the Center-TRACON Automation System (CTAS) to assist Traffic Management Coordinators (TMCs), in real time, with the task of planning and scheduling arrival traffic approximately 35 to 200 nautical miles from the destination airport. The TMC may input to the DP a series of current and future scheduling constraints that reflect the operation and environmental conditions of the airspace. Under these constraints, the DP uses flight plans, track updates, and Estimated Time of Arrival (ETA) predictions to calculate optimal runway assignments and arrival schedules that help ensure an orderly, efficient, and conflict-free flow of traffic into the terminal area. These runway assignments and schedules can be shown directly to controllers or they can be used by other CTAS tools to generate advisories to the controllers. Additionally, the TMC and controllers may override the decisions made by the DP for tactical considerations. The DP will adapt to computations to accommodate these manual inputs.Wong, Gregory L. and Denery, Dallas (Technical Monitor)Ames Research CenterAIR TRAFFIC CONTROL; AUTOMATIC CONTROL; SCHEDULING; FLIGHT PLANS; CONTROLLERS; AIRSPACE; RUNWAYS; REAL TIME OPERATION; ESTIMATING
On Line Handling Of Air Traffic
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Author : André Benoît
language : en
Publisher:
Release Date : 1994
On Line Handling Of Air Traffic written by André Benoît and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Air traffic control categories.
Quantitative Problem Solving Methods In The Airline Industry
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Author : Cynthia Barnhart
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-12-22
Quantitative Problem Solving Methods In The Airline Industry written by Cynthia Barnhart and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-22 with Business & Economics categories.
This book reviews Operations Research theory, applications and practice in seven major areas of airline planning and operations. In each area, a team of academic and industry experts provides an overview of the business and technical landscape, a view of current best practices, a summary of open research questions and suggestions for relevant future research. There are several common themes in current airline Operations Research efforts. First is a growing focus on the customer in terms of: 1) what they want; 2) what they are willing to pay for services; and 3) how they are impacted by planning, marketing and operational decisions. Second, as algorithms improve and computing power increases, the scope of modeling applications expands, often re-integrating processes that had been broken into smaller parts in order to solve them in the past. Finally, there is a growing awareness of the uncertainty in many airline planning and operational processes and decisions. Airlines now recognize the need to develop ‘robust’ solutions that effectively cover many possible outcomes, not just the best case, “blue sky” scenario. Individual chapters cover: Customer Modeling methodologies, including current and emerging applications. Airline Planning and Schedule Development, with a look at many remaining open research questions. Revenue Management, including a view of current business and technical landscapes, as well as suggested areas for future research. Airline Distribution -- a comprehensive overview of this newly emerging area. Crew Management Information Systems, including a review of recent algorithmic advances, as well as the development of information systems that facilitate the integration of crew management modeling with airline planning and operations. Airline Operations, with consideration of recent advances and successes in solving the airline operations problem. Air Traffic Flow Management, including the modeling environment and opportunities for both Air Traffic Flow Management and the airlines.
Stochastic Programming Approaches To Air Traffic Flow Management Under The Uncertainty Of Weather
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Author : Yu-Heng Chang
language : en
Publisher:
Release Date : 2010
Stochastic Programming Approaches To Air Traffic Flow Management Under The Uncertainty Of Weather written by Yu-Heng Chang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Air traffic capacity categories.
As air traffic congestion grows, air traffic flow management (ATFM) is becoming a great concern. ATFM deals with air traffic and the efficient utilization of the airport and airspace. Air traffic efficiency is heavily influenced by unanticipated factors, or uncertainties, which can come from several sources such as mechanical breakdown; however, weather is the main unavoidable cause of uncertainty. Because weather is unpredictable, it poses a critical challenge for ATFM in current airport and airspace operations. Convective weather results in congestion at airports as well as in airspace sectors. During times of congestion, the decision as how and when to send aircraft toward an airspace sector in the presence of weather is difficult. To approach this problem, we first propose a two-stage stochastic integer program by emphasizing a given single sector. By considering ground delay, cancellation, and cruise speed for each flight on the ground in the first stage, as well as air holding and diversion recourse actions for each flight in the air in the second stage, our model determines how aircraft are sent toward a sector under the uncertainty of weather. However, due to the large number of weather scenarios, the model is intractable in practice. To overcome the intractability, we suggest a rolling horizon method to solve the problem to near optimal. Lagrangian relaxation and subgradient method are used to justify the rolling horizon method. Since the rolling horizon method can be solved in real time, we can apply it to actual aircraft schedules to reduce the costs incurred on the ground as well as in airspace. We then extend our two-stage model to a multistage stochastic program, which increases the number of possible weather realizations and results a more efficient schedule in terms of costs. The rolling horizon method as well as Lagrangian relaxation and subgradient method are applied to this multistage model. An overall comparison among the previously described methodologies are presented.