Estimating and Exploring Sources of Temporal Deviations from Flight Plans

This paper discusses the results of modeling and simulation performed by FAA’s Performance Analysis and Strategy office to forecast delays at thirty major US airports six months ahead of time. In order to have reliable delay forecasts, it is important that the simulation model validates well with historic actual data. As part of the validation efforts, we recognize that an aircraft’s movement in the US National Airspace System (NAS) involves its interaction with various resources along the flight path, such as airport runways, arrival and departure fixes, airspace sectors, and terminal gates. When multiple aircraft compete for access to these resources, their movements are impeded due to operational and safety considerations, resulting in flight delays. The objective of this study is to understand how various resources contribute to total flight delays, and how sensitive the delays are to changes in resource capacities. The results to date indicate that reduced airport runway capacities play a significant role in overall delays, but arrival and departure fixes and airspace sector constraints do not. Our use of historical airport AARs and ADRs for runway capacities, which may inherently account for fix constraints, yields delays that agree very well with actual values reported in ASPM. However, care has to be taken to use and interpret these rates when there are runway additions or closures. One area in which all NAS-wide models fail to replicate the behavior of the NAS is gate-out delay. Our simulation includes modeled distributions to capture gate-out delays, but they were found to capture only a fraction of actual gate-out delays. Terminal gate constraints were added to verify if they yielded large gate-in delays that would result in additional gate-out delays. No significant additional gate-out delays were obtained, although we gained better insight into how gate-in delays may occur. We are continuing to research potential NAS interactions that would account for the gap in predicting gate-out delays. Additional simulation model enhancements are planned to account for traffic flow initiatives such as GDP, as well as itinerary adjustments due to flight cancellation and substitutions.

A number of Federal Aviation Administration (FAA) automation systems and developmental programs interoperate to support the day-to-day operations of the National Airspace System (NAS). The integration of New Entrants (NEs), such as Remotely Piloted Aircraft (RPA) 1 and Space Vehicle (SV) operations, into the NAS will require modification to the current state of automation. Examining the relevant operational, technical, and procedural implications of integrated NE operations, in addition to exploring the potential impacts of accelerated RPA usage on NAS dynamics, are critically important efforts necessary to understanding operational impacts to NAS systems and users. Our paper presents the potential impacts of RPA integration on two of these systems: En Route Automation Modernization (ERAM) and Traffic Flow Management System (TFMS). A significant component of the impact on NAS systems comes from flight plan and related data processing since all SVs and many RPAs will fly non-standard flight patterns (e.g., RPA loitering and grid search). The processes and details of the non-traditional flight routes, as well different RPA performance specifications, need to be considered as missions are overlaid on the national jet route structure. Of particular concern and interest are the changes in air traffic control (ATC) and air traffic management (ATM) systems and sub-systems needed to address air traffic controller workload and workload complexity concerns associated with NE activities. One potential accommodation approach, presented in this paper, is the use of Dynamic Airspace Configuration both for RPA routine operations and contingency events. Additionally, we present an RPA 1 In this paper, UAS and RPA are used interchangeably without intending any difference per se. It is noted that the U.S. DoD and ICAO use RPA while NASA and the FAA use UAS. demand forecast tool developed under a National Aeronautics and Space Administration (NASA) project. This tool will assist the FAA in meeting its objectives for accommodation of RPA by providing accurate demand forecast information.

Separation assurance is an important facet of the safety guarantee in the the National Airspace System (NAS). Separation requirement for aircraft are defined by horizontal and vertical separation buffers depending on the type of aircraft and type of airspace. The violation of these standards or encroachment into the separation buffers are indicative of reduced safety margins in the airspace. We analyze the buffer encroachment trends in the terminal airspace of 24 major airports in the U.S. over a period of 21 months from April 2019 to December 2020. The analysis measures the duration of encroachments within the terminal airspace for 15-minute epochs and the trends across the airports and their temporal evolution. The period at the beginning of the Covid-19 pandemic in mid-March 2020 and the slow recovery over the remainder of the year is of special interest as it provides a natural experiment for evaluating the impact of unusually low traffic density on aviation operations. Our analysis indicates that the airports show significant variability in the encroachment levels. Some airports like Dallas/Fort Worth International Airport (DFW) and Charlotte Douglas International Airport (CLT) show encroachment levels higher than expected during the reduced traffic period. Furthermore, the trends reveal spikes in encroachment levels during the pre-pandemic period at other airports like Atlanta International Airport (ATL) and Denver International Airport (DEN). The observed trends suggest the utility for real-time measurement of buffer encroachments across airports as a proxy for monitoring safety margin levels and aid the decision-making of different stakeholders.

This paper presents simulation and experimental testing being performed on electrical protection systems for Approach Lighting System (ALS) used in major US airports. The main focus of the investigations is to validate selected protection topology needed to safeguard critical Individual Control Cabinet (ICC) used by Federal Aviation Administration (FAA) in their ALS. The approach used is based on (a) selection of appropriate protection topology, (b) simulation of protection systems with practical ground resistance sensitivity values, and (c) testing of a scaled model based on laboratory setup and testing. PSpice(r) simulation was used to provide insights to ALS protection. The experimental work via hands-on destructive tests is being used to provide practical results to confirm the effectiveness of suggested protection schemes. The results obtained are consistent with the minimum design requirements.

BackgroundMany health departments and private enterprises began offering SARS-CoV-2 testing to travelers at US airports in 2020. Persons with positive SARS-CoV-2 test results who have planned upcoming travel may be subject to US federal public health travel restrictions.We assessed availability of testing for SARS-CoV-2 at major US airports. We then describe the management of cases and close contacts at Denver International Airport’s testing site.MethodsWe selected 100 US airports. Online surveys were conducted during November–December 2020 and assessed availability of testing for air travelers, flight crew, and airport employees. Respondents included health department (HD) staff or airport directors.We analyzed testing data and management practices for persons who tested positive and their close contacts at one airport (Denver International) from 12/21/2020 to 3/31/2021.ResultsAmong the 100 selected airports, we received information on 77 airports; 38 (49%) had a testing site and several more planned to offer one (N = 7; 9%). Most sites began testing in the fall of 2020. The most frequently offered tests were RT-PCR or other NAAT tests (N = 28).Denver International Airport offered voluntary SARS-CoV-2 testing. Fifty-four people had positive results among 5724 tests conducted from 12/21/2020 to 3/31/2021 for a total positivity of < 1%. Of these, 15 were travelers with imminent flights. The Denver HD issued an order requiring the testing site to immediately report cases and notify airlines to cancel upcoming flight itineraries for infected travelers and their traveling close contacts, minimizing the use of federal travel restrictions.ConclusionsAs of December 2020, nearly half of surveyed US airports had SARS-CoV-2 testing sites. Such large-scale adoption of airport testing for a communicable disease is unprecedented and presents new challenges for travelers, airlines, airports, and public health authorities. This assessment was completed before the US and other countries began enforcing entry testing requirements; testing at airports will likely increase as travel demand returns and test requirements for travel evolve.Lessons from Denver demonstrate how HDs can play a key role in engaging airport testing sites to ensure people who test positive for SARS-CoV-2 immediately before travel do not travel on commercial aircraft.

This chapter focuses on an alternative robust estimation/testing procedure for possibly infinite variance time series models. In the context of inference for heavy-tailed observation, least absolute deviations (LAD) estimators are known to be less sensitive to outliers than the classical least squares regression. This section generalizes the LAD regression-based inference procedure to the self-weighted version, which is a concept originally introduced by Ling (2005) for AR processes. Using the self-weighting method, we extend the generalized empirical likelihood (GEL) method to possibly infinite variance process, and construct feasible and robust estimation/testing procedures. The former half of this chapter provides a brief introduction to the LAD regression method for possibly infinite variance ARMA models, and construct the self-weighted GEL statistic following Akashi (2017). The desirable asymptotic properties of the proposed statistics will be elucidated. The latter half of this chapter illustrates an important application of the self-weighted GEL method to the change point problem of time series models.

Air Traffic Management helps to ensure all National Airspace System (NAS) operators have the opportunity to safely accomplish their operational goals while maintaining NAS efficiency. Advancements in technology and a robust global demand for access to space are leading to new space flight participants and increasing numbers of space launch and reentry operations, adding complexity to NAS management coordination and decision-making processes. Diversity of launch and reentry profiles and locations, coupled with increased activity [1, 2], will impact airspace management planning by requiring increased coordination among the Federal Aviation Administration (FAA) and other federal agencies, civilian facilities, and commercial operators. Current processes will not scale as space activity in the NAS increases. The MITRE Corporation is working with the FAA to improve launch and reentry operations efficiency and repeatability. The approach includes analyzing current processes and identifying how more standardized communication mechanisms, integrated information flows, and consistent analysis capabilities can be applied. This paper describes a concept for sharing information and integrating it as part of a standardized, repeatable process that can help the FAA meet future space activity needs in the NAS. A key feature is to integrate information related to NAS effects assessment into the process to facilitate rapid analysis and feedback.

This paper addresses topics concerning the development of future Unmanned Aerial Vehicles (UAV) so that they can operate safely within the community of the Federal Aviation Administration (FAA) and the International Civil Aviation Organization (ICAO). Studies by the Defense Science Board; the Office of Science and Technology; Government Accountability Office; and the Congressional Research Service: Library of Congress; have all emphasized that soon there will be a significant number of UAVs operating sideby- side with manned civil aircraft in the FAA’s National Airspace System (NAS). It is anticipated that future UAVs will start to perform many of the dull, dirty, and dangerous civilian missions. In 2006, about 600 UAVs are expected to be manufactured in the US alone. Therefore, there is an urgent need for developers of UAVs to understand safety certification for operations in the NAS, and that safety certification starts with the safety requirements; safety design; safe development process; safety verification; and safe operating procedures in the planned operational environment. This paper presents and discusses the experiences and lessons gained by the authors on the development of end-toend aviation safety; from the safety requirements to their final safety certification in the planned operational environment. The authors’ previous and ongoing works include the Global Navigation Satellite Systems (GNSS) systems such as the GPS; WAAS; LAAS; MSAS; GPS III; and different operational environments at different airports such as Incheon International Airport. The FAA started with the two traditional safety certifications processes: airborne system certification and ground system certification; governed mostly by Federal Aviation Regulations (FAR) and FAA’s Acquisition Management System (AMS), respectively. However, when FAA started to implement GNSS, the lines between airborne and ground systems became blurred, and as a result many current Communications, Navigation, Surveillance, and Air Traffic Management (CNS/ATM) systems have to follow both processes. We will also discuss the current Safety Management Systems being developed by both FAA and ICAO as an integrated, systematic, and harmonized approach and process to sort out the differing safety requirements from FAA, SAE-ARP, MIL-STD, RTCA, ASTM, ICAO, etc. to provide the eventual safe operations within the NAS. The discussion will then focus on the real world of institutional, operational, and technical issues for safety certification worldwide. Despite the numerous standards and guidance documents, many past safety analyses and studies were guided by best practices that had been used successfully in the past to streamline the process of providing all the required documentations and verifications. One such area is in the use of the “Integrity Panel of Experts” that had been used successful in the implementation of safety for the FAA’s Wide Area Augmentation System (WAAS) and Local Area Augmentation System (LAAS) programs. In many areas of the world, safety certification from a technical point of view is only the first step to achieving safety certification to fly in their national and sovereign airspace. Finally, we will show the first steps that UAV manufactures need to consider if they want their UAVs to be approved to fly safely in different national civilian airspace.

A number of the worlds’ major airports have a high proportion of their capacity utilised by a single airline, or alliance of airlines. At major US airports, for example, it is common for the leading carrier to account for threequarters or more of the flights; at European airports the proportions are generally smaller but often exceed 50 per cent (see Annex 1). This has lead to concerns that such high levels of capacity utilisation (‘slot concentration’) will impact adversely on competition and prices and, in turn, has inclined policy makers and regulatory bodies towards pro-active competition measures. In the US, for example, the General Accounting Office (GAO, 1996) judged that the buy-sell market in slots established at certain US airports in 1985, had failed because it was argued to have done little to reduce slot concentration and introduce competition into the market. It went on to recommend that slots should be re-distributed. In Europe, the current slot allocation regulation (Regulation 95/93, Article 10) requires that at slot co-ordinated airports preference be given to new entrant carriers in the allocation of unused, returned or new slots (that together constitute the slot pool); there is also a reluctance on the part of the European Commission to accept unrestricted slot trading because of the fear that it will reinforce dominant positions; and approval of proposed alliances between carriers has often been accompanied by conditions requiring slot divestiture.

Bootstrap tests for unit roots based on LAD estimation

Least absolute deviations (LAD) estimation of linear time series models is considered under conditional heteroskedasticity and serial correlation. The limit theory of the LAD estimator is obtained without assuming the finite density condition for the errors that is required in standard LAD asymptotics. The results are particularly useful in application of LAD estimation to financial time series data.

For a system to be managed, it must be measured. The National Airspace System (NAS), the collection of airspace and airport resources in and under the control of the United States (U.S.), is a very complex system which presents great challenges of measurement and management. One key measure of en route airspace efficiency is flying time, i.e., the amount of time it takes for an aircraft to travel through en route airspace on its flight from origin to destination airport. A number of factors influence flying time, the most obvious being the winds. Other important factors are: traffic congestion, air traffic management (ATM) interventions, route structure, industry strategies, and weather. In this paper, we calculate en route flying time in the aggregate and compare a subset of data for the years 2001 and 2002. We account for aircraft equipment type and adjusted flying time for wind effects. In addition, we have selected for analysis a sample of only good weather days (15 in each of the 2 years). The results show that 2002 has slightly shorter flying times than 2001, on the order of 20–25 seconds shorter. Although we did not investigate the causes for the change, we conjecture that the lower levels of traffic after the Fall of 2001 are causing less congestion and less delay. New automation and procedural initiatives may also be contributing to the improvement. Introduction The Federal Aviation Administration (FAA) is charged with the safe, efficient movement of air traffic in U.S. airspace. In recent years, the FAA has begun initiatives to measure efficiency of airspace usage. The measurements are useful for determining the impact of automation and procedural enhancements. Such measurements are also useful for identifying problem areas in the NAS, which can be targeted for remediation. Changes in efficiency may be examined as a function of time. This study assessed system efficiency using en route flying times, comparing 2001 versus 2002. Although several studies have been performed in the past calculating changes in en route flying distance, the authors are familiar with one time-based analysis in the open literature. Bolczak, et al. used Estimated Time of Arrival (ETA) data to analyze a trend in flying time, and discover some year-to-year changes. Other studies of flight times are in the literature, though they have not compared actual or modeled values across years. An early simulation of Free Flight, Ball, et al. analyzed flying times for flights without the constraints of route structuring. Efficiency may be defined as the level of utilization of a resource, with consideration of the cost or effort undertaken to achieve that level. † Free Flight is an industry/government initiative which provides greater freedom for pilots and airlines to select planned and flown routes and take-off times. Free Flight supports collaboration between airspace managers and airspace users. 1 American Institute of Aeronautics and Astronautics Willemain examined sources of variability in flying times for certain city pairs. The Bureau of Transportation Statistics has collected flight time statistics and hosts a web site which allows the public to access this information. In this study, results are presented in aggregated form, with some detail with respect to city pairs. Differences were found in the flying time metrics: 2002 has slightly lower flying times than 2001. The causes for this difference are not discussed.

Least absolute deviation (LAD) is a well-known criterion to fit statistical models, but little is known about LAD estimation in structural equation modeling (SEM). To address this gap, the authors use the LAD criterion in SEM by minimizing the sum of the absolute deviations between the observed and the model-implied covariance matrices. Using Monte Carlo simulations, the authors compare the performance of this LAD estimator along several dimensions (bias, efficiency, convergence, frequencies of improper solutions, and absolute percentage deviation) to the full information maximum likelihood (ML) and unweighted least squares (ULS) estimators in structural equation modeling. The results for LAD are mixed: There are special conditions under which the LAD estimator outperforms ML and ULS, but the simulation evidence does not support a general claim that LAD is superior to ML and ULS in small samples.

* † ‡† * *† § The Aviation Integrated Model is a policy assessment tool designed to simulate the operation and economic/environmental effects of local and world airline networks over the next 30-50 years within a modular framework. Feedback between demand, capacity, air traffic delays and policy measures is a key part of this model. For example, unconstrained model projections of US air transportation system growth with no passenger, airline or policy response included show average arrival delays of over two hours at major US airports in 2030, a condition that is unlikely to materialize. A more likely situation is that a combination of responses act to bring the air transport system to a new equilibrium at which higher fares, extra capacity or increased operational efficiency reduces the delays to a more acceptable level. Similarly, the application of policies designed to mitigate some of the environmental impacts of air transportation will also alter the system equilibrium state. In this paper we use the Aviation Integrated Model to systematically examine these feedback effects, concentrating specifically on the passenger response to increases in travel time, airfare, and policy responses to environmental concerns. We contrast the reference case in which the main feedback effect is passenger and airline response to air traffic delay with sample policy scenarios.

The impact on the US economy of changes in wait times at ports of entry