The Small Aircraft Transportation System, or SATS, is a NASA-led initiative that seeks to revolutionize commercial air travel by increasing accessibility and mobility for the general consumer. The hallmark of SATS is on-demand, point-to-point air transportation from one of the nation's 5,400 public use airports and landing facilities. A second-order benefit is that it may help relieve congestion on the nation's highways and at our mid- to large size airport hubs. In 1999, NASA initiated a five-year, $69 million research program to study the feasibility and viability of SATS including development of the emerging technologies necessary to make SATS a reality. The five-year plan culminated in June 2005 in Danville, VA with a highly publicized flight demonstration and exposition serving as the SATS proof of concept. The "Highways-in-the-Sky" (HITS) premise inherent to SATS is arguably its biggest enabler, and it depends heavily on the idea of free flight. HITS will potentially be the first step in moving from traditional cars and other vehicles that travel on the ground to ones that will operate largely, if not entirely, in the air. The notion of "cars" that fly was first introduced by the entertainment industry in movies and television programs decades ago. But if mankind is ever to achieve that vision, we must have a start point. This research focuses not on the economic viability of SATS but rather on the degree of flight safety inherent to a program such as this. One can easily see how the introduction of a large number of autonomous vehicles operating simultaneously in an already dense region such as the National Airspace System might carry some degree of risk. This research introduces a modeling and simulation framework that will have applications to SATS at such time as the program must be evaluated from a safety of flight perspective. That will invariably include a high degree of simulation. This work also represents the first large-scale simulation focused primarily on how SATS will perform in the out-years. / Master of Science

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No description available.

Thesis (M.A. in Security Studies (Homeland Security and Defense))--Naval Postgraduate School, December 2008. / Thesis Advisor(s): Wirtz, James J. "December 2008." Description based on title screen as viewed on January 30, 2009. Includes bibliographical references (p. 99-108). Also available in print.

Thesis (M.S.)--Ohio University, August, 1996. / Title from PDF t.p.

Thesis (Ph. D. in Engineering-Civil and Environmental)--University of California, Berkeley, 2004. / "Fall 2004." Includes bibliographical references (p. 145-147). Also available online via the ITS Berkeley web site (www.its.berkeley.edu).

Thesis (Ph. D.)--University of California, Berkeley, 2004. / Includes bibliographical references (p. 145-147). Also available online via the Institute of Transportation Studies, University of California, Berkeley web site (www.its.berkeley.edu).

The modernization of the National Air Traffic Control System is on the horizon, and with it, the possible introduction of autonomous air vehicles into the national airspace. Per the FAA Aerospace Forecast (FAA, 2013), U.S. carrier passenger traffic is expected to average 2.2 percent growth per year over the next 20 years with government statistics indicating that the average domestic load factor for airlines in 2014 was approximately 84.4 percent (US Department of Transportation, 2015). Adding to that demand, the potential introduction of unmanned and autonomous air vehicles motivates reconsideration of control schemes. One of the proposed solutions (Eby, 1994) would involve a decentralized control protocol. Equipping each aircraft with the information necessary to navigate safely through integrated airspace becomes an information sharing problem: how much information about other aircraft is required for a pilot to safely fly the gamut of a heavily populated airspace and what paradigm shifts may be necessary to safely and efficiently utilize available airspace? This thesis describes the development of a tool for testing alternative traffic management systems, centralized or decentralized, in the presence of uncertainty. Applying a computational fluid dynamics-inspired approach to the problem creates a simulation tool to model both the movement of traffic within the airspace and also allows study of the effects of interactions between vehicles. By incorporating a Smoothed Particle Hydrodynamics (SPH) based model, discrete particle aircraft each carry a set of unique deterministic and stochastic properties. With this model, aircraft interaction can be studied to better understand how variations in the nondeterministic properties of the system affect its overall efficiency and safety. The tool is structured to be sufficiently flexible as to allow incorporation of different collision detection and avoidance rules for aircraft traffic management. / Master of Science

Increased efficiency at airports is necessary to reduce delays and fuel consumption. Many of the busiest airports in the nation have at least one pair of closely spaced parallel runways (CSPRs), defined by a separation of less than 2500 ft, with one runway dedicated to arrivals and the other to departures. CSPRs experience a large decrease in capacity under instrument conditions because they can no longer operate independently. In order to mitigate this decrease in capacity and to increase efficiency, proposed herein is a departure regulator for runways so configured, along with a plan of study to investigate the effects of this regulator. The proposed departure regulator makes use of data from precision tracking systems such as ADS-B to issue automated or semi-automated departure clearances. Assuming sequential departure separations are sufficient for clearance, the regulator will automatically issue, or advise the controller to issue, the departure clearance as soon as the arrival on the adjacent runway has descended below its decision height. By issuing the departure clearance earlier, the departure regulator reduces the gap between a pair of arrivals that is required to clear a departure. By decreasing the gap, the regulator increases the number of opportunities where a departure clearance can be issued, given a particular arrival stream. A simulation models the effects of the regulator and quantifies the resulting increases in capacity. The simulation results indicate that all forms of the regulator would provide significant gains of between 14% and 23% in capacity over the current operating paradigm. The results also indicate that the capacity gains are greatest at high arrival rates. Therefore, implementation of the departure regulator could significantly decrease the congestion at many major airports during inclement weather.

We develop and evaluate two significant modeling concepts within the context of a large-scale Airspace Planning and Collaborative Decision-Making Model (APCDM) and, thereby, enhance its current functionality in support of both strategic and tactical level flight assessments. The first major concept is a new severe weather-modeling paradigm that can be used to assess existing tactical en route flight plan strategies such as the Flight Management System (FMS) as well as to provide rerouting strategies. The second major concept concerns modeling the mediated bartering of slot exchanges involving airline trade offers for arrival/departure slots at an arrival airport that is affected by the Ground Delay Program (GDP), while simultaneously considering issues related to sector workloads, airspace conflicts, as well as overall equity concerns among the airlines. This research effort is part of an $11.5B, 10-year, Federal Aviation Administration (FAA)-sponsored program to increase the U.S. National Airspace (NAS) capacity by 30 percent by the year 2010. Our innovative contributions of this research with respect to the severe weather rerouting include (a) the concept of "Probability-Nets" and the development of discretized representations of various weather phenomena that affect aviation operations; (b) the integration of readily accessible severe weather probabilities from existing weather forecast data provided by the National Weather Service (NWS); (c) the generation of flight plans that circumvent severe weather phenomena with specified probability levels, and (d) a probabilistic delay assessment methodology for evaluating planned flight routes that might encounter potentially disruptive weather along its trajectory. Given a fixed set of reporting stations from the CONUS Model Output Statistics (MOS), we begin by constructing weather-specific probability-nets that are dynamic with respect to time and space. Essential to the construction of the probability-nets are the point-by-point forecast probabilities associated with MOS reporting sites throughout the United States. Connections between the MOS reporting sites form the strands within the probability-nets, and are constructed based upon a user-defined adjacency threshold, which is defined as the maximum allowable great circle distance between any such pair of sites. When a flight plan traverses through a probability-net, we extract probability data corresponding to the points where the flight plan and the probability-net strand(s) intersect. The ability to quickly extract this trajectory-related probability data is critical to our weather-based rerouting concepts and the derived expected delay and related cost computations in support of the decision-making process. Next, we consider the superimposition of a flight-trajectory-grid network upon the probability-nets. Using the U.S. Navigational Aids (Navaids) as the network nodes, we develop an approach to generate flight plans that can circumvent severe weather phenomena with specified probability levels based on determining restricted, time-dependent shortest paths between the origin and destination airports. By generating alternative flight plans pertaining to specified threshold strand probabilities, we prescribe a methodology for computing appropriate expected weather delays and related disruption factors for inclusion within the APCDM model. We conclude our severe weather-modeling research by conducting an economic benefit analysis using a k-means clustering mechanism in concert with our delay assessment methodology in order to evaluate delay costs and system disruptions associated with variations in probability-net refinement-based information. As a flight passes through the probability-net(s), we can generate a probability-footprint that acts as a record of the strand intersections and the associated probabilities from origin to destination. A flight plan's probability-footprint will differ for each level of data refinement, from whence we construct route-dependent scenarios and, subsequently, compute expected weather delay costs for each scenario for comparative purposes. Our second major contribution is the development of a novel slot-exchange modeling concept within the APCDM model that incorporates various practical issues pertaining to the Ground Delay Program (GDP), a principal feature in the FAA's adoption of the Collaborative Decision-Making (CDM) paradigm. The key ideas introduced here include innovative model formulations and several new equity concepts that examine the impact of "at-least, at-most" trade offers on the entire mix of resulting flight plans from respective origins to destinations, while focusing on achieving defined measures of "fairness" with respect to the selected slot exchanges. The idea is to permit airlines to barter assigned slots at airports affected by the Ground Delay Program to their mutual advantage, with the FAA acting as a mediator, while being cognizant of the overall effect of the resulting mix of flight plans on air traffic control sector workloads, collision risk and safety, and equity considerations. We start by developing two separate slot-exchange approaches. The first consists of an external approach in which we formulate a model for generating a set of package-deals, where each package-deal represents a potential slot-exchange solution. These package-deals are then embedded within the APCDM model. We further tighten the model representation using maximal clique cover-based cuts that relate to the joint compatibility among the individual package-deals. The second approach significantly improves the overall model efficiency by automatically generating package-deals as required within the APCDM model itself. The model output prescribes a set of equitable flight plans based on admissible trades and exchanges of assigned slots, which are in addition conformant with sector workload capabilities and conflict risk restrictions. The net reduction in passenger-minutes of delay for each airline is the primary metric used to assess and compare model solutions. Appropriate constraints are included in the model to ensure that the generated slot exchanges induce nonnegative values of this realized net reduction for each airline. In keeping with the spirit of the FAA's CDM initiative, we next propose four alternative equity methods that are predicated on different specified performance ratios and related efficiency functions. These four methods respectively address equity with respect to slot-exchange-related measures such as total average delay, net delay savings, proportion of acceptable moves, and suitable value function realizations. For our computational experiments, we constructed several scenarios using real data obtained from the FAA based on the Enhanced Traffic Management System (ETMS) flight information pertaining to the Miami and Jacksonville Air Route Traffic Control Centers (ARTCC). Through our experimentation, we provide insights into the effect of the different proposed modeling concepts and study the sensitivity with respect to certain key parameters. In particular, we compare the alternative proposed equity formulations by evaluating their corresponding slot-exchange solutions with respect to the net reduction in passenger-minutes of delay for each airline. Additionally, we evaluate and compare the computational-effort performance, under both time limits and optimality thresholds, for each equity method in order to assess the efficiency of the model. The four slot-exchange-based equity formulations, in conjunction with the internal slot-exchange mechanisms, demonstrate significant net savings in computational effort ranging from 25% to 86% over the original APCDM model equity formulation. The model has been implemented using Microsoft Visual C++ and evaluated using a C++ interface with CPLEX 9.0. The overall results indicate that the proposed modeling concepts offer viable tools that can be used by the FAA in a timely fashion for both tactical purposes, as well as for exploring various strategic issues such as air traffic control policy evaluations; dynamic airspace resectorization strategies as a function of severe weather probabilities; and flight plan generation in response to various disruption scenarios. / Ph. D.