Analysis and modeling of airport surface operations

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 97-99).The focus of research in air traffic control has traditionally been on the airborne flight phase. Recently, increasing the efficiency of surface operations has been recognized to have significant potential benefits in terms of fuel and emissions savings. To identify opportunities for improvement and to quantify the consequent gains in efficiency, it is necessary to characterize current operational practices. This thesis describes a framework for analysis of airport surface operations and proposes metrics to quantify operational performance. These metrics are then evaluated for Boston Logan International Airport using actual surface surveillance data. A probabilistic model for real-time prediction of aircraft taxi-out times is described, which improves upon the accuracy of previous models based on queuing theory and regression. Finally, a regression model for estimation of aircraft taxi-out fuel burn is described. Together, the modules described here form the basis for a surface operations optimization tool that is currently under development.by Harshad Khadilkar.S.M

Networked control of aircraft operations at airports and in terminal areas

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 149-157).The goal of this thesis is to develop a control strategy for airport operations that integrates the management of arrivals and departures. The strategy is based on four central ideas: (1) the objective of reducing aircraft flight times, taxi times and fuel burn, (2) the emphasis on developing models using data from actual aircraft operations, (3) the need to be compatible with current air traffic control procedures, and (4) the requirement to not adversely affect airport performance. The scope of this work covers the airport surface and arrival airspace, which are two of the most congested regions of the air transportation network. A new approach is proposed for modeling airport surface operations. Drawing an analogy from the field of network congestion control, the airport surface is assumed to be a network consisting of major taxiways and their intersections. Posing the problem in this framework relaxes the requirement of precisely predicting the taxi time of each aircraft, instead emphasizing the accurate representation of the underlying stochastic processes. At the same time, it allows one to address the issues of network stability and performance through analytical approaches. Based on this model for surface operations, a control algorithm is developed for regulating the time of entry of aircraft into the network. Simulations show that this strategy can significantly reduce surface congestion and aircraft fuel burn without hampering airport performance. The arrival airspace control algorithm presented in this thesis proposes a hybrid centralized / distributed algorithm for conflict detection and resolution. It combines distributed control in low-density airspace with centralized control in high-density terminal areas. This approach has the advantage of reducing ground infrastructure cost due to decentralization, while still operating at an efficiency level close to that of a fully centralized control strategy. The arrival and departure control algorithms are then combined to formulate an integrated strategy for managing airport operations, significantly improving the separate gains that can be obtained from each component.by Harshad Khadilkar.Ph. D

Network Congestion Control of Airport Surface Operations

The reduction of taxi-out times at airports has the potential to substantially reduce delays and fuel consumption on the airport surface, and to improve the air quality in surrounding communities. The taxiway and runway systems at an airport determine its maximum possible departure throughput, or the number of aircraft departures that it can handle per unit time. Current air traffic control procedures allow aircraft to push from their gates and enter the taxiway system as soon as they are ready. As this pushback rate approaches the maximum departure throughput of the airport, runway queues grow longer and surface congestion increases, resulting in increased taxi-out times

Optimal Control of Airport Operations with Gate Capacity Constraints

The mitigation of airport surface congestion is an important step towards increasing the efficiency of the air transportation system, and decreasing flight delays. This paper proposes a strategy to control the release of departing flights from their gates with the specific objective of reducing their taxi times and fuel consumption, while limiting the impact on airport throughput. The proposed strategy also explicitly accounts for the practical constraints that arise due to limited gate resources at the airport. A stochastic network abstraction of the airport surface is used to model aircraft movement, and the optimal release time for each aircraft is calculated using dynamic programming. Simulations of operations at Boston's Logan International Airport in the US are used to illustrate the effects of the resultant policies.National Science Foundation (U.S.) (CAREER Award ECCS-0745237)National Science Foundation (U.S.) (Cyber-Physical Systems Award 0931843

Analysis of Airport Performance using Surface Surveillance Data: A Case Study of BOS

Detailed surface surveillance datasets from sources such as the Airport Surface Detection Equipment, Model-X (ASDE-X) have the potential to be used for analysis of airport operations, in addition to their primary purpose of enhancing safety. In this paper, we describe how airport performance characteristics such as departure queue dynamics and throughput can be analyzed using surface surveillance data. We also propose and evaluate several metrics to measure the daily operational performance of an airport, and present them for the speci c case of Boston Logan International Airport

Metrics to Characterize Airport Operational Performance Using Surface Surveillance Data

Detailed surface surveillance datasets from sources such as the Airport Surface Detection Equipment, Model-X (ASDE-X) have the potential to be used for the analysis of airport operations, in addition to their primary purpose of enhancing safety. This paper describes how surface surveillance data can be used to measure airport performance characteristics in three different ways: (1) Characterization of surface flows, including identification of congestion hotspots, queue dynamics and departure throughput ; (2) Development of metrics to evaluate the daily operational performance; and (3) Development of metrics to gauge long-term performance across different runway configurations and operating conditions. The proposed metrics have been developed with active feedback from operations personnel at Boston Logan International Airport, and are therefore evaluated and discussed using this airport as an example. These metrics can provide useful feedback on operational performance to airport operators, and therefore have the potential to improve the efficiency of surface operations at airports

Hybrid Communication Protocols and Control Algorithms for NextGen Aircraft Arrivals

Capacity constraints imposed by current air traffic management technologies and protocols could severely limit the performance of the Next Generation Air Transportation System (NextGen). A fundamental design decision in the development of this system is the level of decentralization that balances system safety and efficiency. A new surveillance technology called automatic dependent surveillance-broadcast (ADS-B) can be potentially used to shift air traffic control to a more distributed architecture; however, channel variations and interference with existing secondary radar replies can affect ADS-B systems. This paper presents a framework for managing arrivals at an airport by using a hybrid centralized/distributed algorithm for communication and control. The algorithm combines the centralized control that is used in congested regions with the distributed control that is used in lower traffic density regions. The hybrid algorithm is evaluated through realistic simulations of operations around a major airport. The proposed strategy is shown to significantly improve air traffic control performance under various operating conditions by adapting to the underlying communication, navigation, and surveillance systems. The performance of the proposed strategy is found to be comparable to fully centralized strategies, despite requiring significantly less ground infrastructure.National Science Foundation (U.S.) (Grant CNS-931843)United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N0014-08-0696)United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N00014-09-1-1051)United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N00014-12-1-0609)United States. Air Force Office of Scientific Research. Multidisciplinary University Research Initiative (Grant FA9550-10-1-0567

Assessing the impacts of the JFK Ground Management Program

The Ground Management Program at John F. Kennedy International Airport (JFK) aims to leverage the availability of comprehensive airport surface surveillance data and airline schedule information to better manage the taxi-out process, reduce taxi times, and improve efficiency. During periods when departure demand exceeds capacity, departing aircraft are held at the gate or another holding location, and released to the runway in time to join a short departure queue before taking off. As a result, aircraft absorb delay with engines off, and decrease their fuel burn, emissions, and engine maintenance costs. This paper evaluates data from before and after departure metering was initiated at JFK, to assess its impacts. The results show that airport performance has improved, and that the departure metering is responsible for a significant portion of the improvements. The paper also finds that the new, more automated, Ground Management Program that was implemented in April 2012 has continued to yield significant benefits. The average taxi-out time savings at JFK due to departure metering in the summer of 2012 is estimated to be about 1.5-2.7 minutes per flight

High Confidence Networked Control for Next Generation Air Transportation Systems

This paper addresses the design of a secure and fault-tolerant air transportation system in the presence of attempts to disrupt the system through the satellite-based navigation system. Adversarial aircraft are assumed to transmit incorrect position and intent information, potentially leading to violations of separation requirements among aircraft. We propose a framework for the identification of adversaries and malicious aircraft, and then for air traffic control in the presence of such deliberately erroneous data. The framework consists of three mechanisms that allow each aircraft to detect attacks and to resolve conflicts: fault detection and defense techniques to improve Global Positioning System (GPS)/inertial navigation, detection and defense techniques using the Doppler/received signal strength, and a fault-tolerant control algorithm. A Kalman filter is used to fuse high frequency inertial sensor information with low frequency GPS data. To verify aircraft position through GPS/inertial navigation, we propose a technique for aircraft localization utilizing the Doppler effect and received signal strength from neighboring aircraft. The control algorithm is designed to minimize flight times while meeting safety constraints. Additional separation is introduced to compensate for the uncertainty of surveillance information in the presence of adversaries. We evaluate the effect of air traffic surveillance attacks on system performance through simulations. The results show that the proposed mechanism robustly detects and corrects faults generated by the injection of malicious data. Moreover, the proposed control algorithm continuously adapts operations in order to mitigate the effects these faults. The ability of the proposed approaches to defend against attacks enables reliable air traffic operations even in highly adversarial surveillance conditions.National Science Foundation (U.S.) (CNS-931843)United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N0014-08-0696)United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N00014-09-1-1051)United States. Office of Naval Research (Grant N00014-12-1-0609)United States. Air Force Office of Scientific Research. Multidisciplinary University Research Initiative (Grant FA9550-10-1-0567

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This paper presents a novel approach to managing the aircraft taxi-out process at airports, by posing the problem in a network congestion control framework. We develop a network model for a generic airport and then validate it using surface surveillance data from Boston Logan International Airport. A set of stochastic processes that constitute the link travel times are proposed, followed by a discussion of the theoretical maximum network throughput. Finally, we propose a control algorithm that balances network congestion with performance, while maintaining stability. We show through simulation that the algorithm is capable of regulating total traffic in the network to a desired level