Search

Urban Air Mobility (UAM) aims to reduce congestion on the roads and highways by offering air taxi as an alternative to driving on surface roads. Integration of UAM operations in the National Airspace System (NAS) has been the focus of the research conducted at NASA Ames Research Center. A simulation was performed in collaboration with Uber Technologies Inc to investigate if NASA's UTM architecture and its implementation as demonstrated in the 2019 UTM field tests were extensible for UAM operations, and if the data exchange between multiple operators as planned under UTM were adequate for UAM operations in the shared airspace. In order to explore these research questions, three Use Cases were defined to investigate different airspace management challenges. This paper will describe the lessons learned from exercising the uses cases and the airspace management services including scheduling and separation developed to facilitate initial UAM operations.

Flight delays in the U. S. National Airspace System (NAS) present a fundamental challenge to capacity growth under ever-increasing traffic volumes, and lead to significant financial burdens that reverberate across a multitude of aviation industry stakeholders. Roughly 20% of passengers’ total travel time is due to such delays, causing $35 billion annually in lost revenue and impacting not only the airline industry, but the retail, lodging, restaurant, and tourism industries, as well. The Federal Aviation Administration’s effort in aiding decision-making at airports is readily apparent in the Next Generation Air Traffic Control (NextGen) System’s System-Wide Information Management (SWIM) program, and in-flight delay information from the FAA Air Traffic Control System Command Center (ATCSCC). Academic researchers are concurrently developing various algorithms to predict flight delays that include advanced statistics, machine learning, and graph theory using various network topologies. Other stakeholders have initiated delay prediction methods to adjust their operational schedules. This suggests an opportunity to centralize, validate, and integrate the various delay prediction methods under development; furthermore, these methods are limited in scope with regard to geography, operators, and efficacy.The authors propose here a platform supporting the FAA’s Collaborative Decision-Making (CDM) process with the intent of reducing flight delays in the NAS. Building upon existing deep learning algorithms and utilizing the NextGen SWIM program, this research suggests a central delay prediction platform suited to the complex and dynamic needs of America’s airport infrastructure. assessments of risks and sustainability of the proposed platform are presented. The authors interviewed experts in industry and academic fields related to aviation and information technology, and used the information obtained to refine the model. It is anticipated that this model will accurately produce location-specific departure and arrival delay forecasts that can further be integrated into the CDM and Ground Delay Program (GDP) initiatives.

Commercial space research is different in many ways when compared to space research historically conducted by military and governmental space organizations. Differences in possible topics, subjects, and technology characteristics drive researchers to search for different types of solutions to what seem to be familiar problems. A research consortium sponsored by the United States (US) Federal Aviation Administration (FAA), the Center of Excellence for Commercial Space Transportation (COE CST), was established in 2010 to facilitate collaborative research activities with a specific emphasis on the commercial aspects of space-related research. Major research areas have been identified that encompass as many possible research topics as could be imagined (as they are pertinent to commercial space activities). The first research domain focuses on the operational challenges of integrating commercial space activities into the national air space (NAS), the management of space “traffic” on-orbit, and the safe operations of spaceports. The second research area most resembles the governmental space research activities, with an emphasis on engineering of systems, subsystems, operations, and analyses surrounding the vehicle and its safety. The third research area encircles the human as a part of the space activity. Research on physiology, human factors, human rating, and training are some of the primary concerns of this domain. Finally, research based in the social sciences are included to study the markets, policy, law, and regulatory environments that will be required to ensure long-term viability of the evolving commercial space industries.

An aggregate route model for strategic air traffic flow management is presented. It is an Eulerian model, describing the flow between segments of unidirectional point-to-point routes. Aggregate rou...

The Federal Aviation Administration (FAA) publishes an annual Aerospace Forecast covering aviation activity in the National Airspace System (NAS), including en route Air Route Traffic Control Center (ARTCC) operational counts. The FAA uses the ARTCC forecast to inform staffing, budgetary, and other operational decisions for the facilities responsible for en route activity within the NAS.The ARTCC portion of the Aerospace Forecast is time-series based, utilizing historic counts of Instrument Flight Rules (IFR) aircraft handled by 21 ARTCCs and three Center Radar Approach Control Facilities (CERAPs). The existing forecasting methodology does not explicitly consider airline routes or passenger flows.The MITRE Corporation (MITRE), in collaboration with the FAA Office of Aviation Policy and Plans (APO), developed an ARTCC forecasting methodology using a quarterly origin-and-destination (O-D) passenger demand framework consistent with the Terminal Area Forecast (TAF). The TAF is the FAA’s official annual forecast of airport activity, which incorporates O-D passenger demand and other market data at airports with 100,000 or more annual commercial enplanements. The ARTCC forecast combines predicted O-D segment counts from TAF with historic flight path distributions derived from the FAA Traffic Flow Management System (TFMS).Existing forecasts do not explicitly account for variance in flight path distribution. This paper provides a description of the methodology for this O-D segment-based ARTCC forecast.

Today’s National Airspace System (NAS) is facing a challenge of dealing with an increasingly larger number of flight operations. To address this, the Next Generation Air Transportation System (NextGen) is introduced by the Federal Aviation Administration (FAA) to improve the efficiency and safety of the NAS. Currently, the performance of the NAS is mainly measured using the delay-based metrics that cannot capture the positive aspects of the performance and level of utilization of the NAS. To address this issue, a diagnostic throughput factor analysis tool is proposed to analyze and quantify the factors that have greater responsibility for poor/better regions/times of performance of the en-route airspace using the concept of throughput. Through a function-level comparison with other applications such as ground transportation, manufacturing, and wireless communication, major factors affecting the NAS’s throughput performance are identified as Monitor Alert Parameter violation, aircraft conflict, metering, c...

Modernization of the National Air Traffic Control System is on the horizon and with it the likely introduction of autonomous air vehicles into the national airspace. With the increase in air traffic to an already congested management scheme, the implementation of a decentralized control protocol may be the answer to replace the current classical centralized management system. 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 fly the gamut of a heavily populated airspace safely? What paradigm shifts may be necessary for safe and efficient use of available airspace? This paper describes the development of a tool for testing alternative traffic management systems—centralized and decentralized—in the presence of uncertainty. Applying a computational fluid dynamics–inspired approach to the problem both creates a simulation tool to model the movement of traffic within the airspace and allows study of the effects of interactions between vehicles. With incorporation of a model based on smoothed particle hydrodynamics, discrete particle aircraft each carry a set of unique deterministic and stochastic properties. With this model, aircraft interaction can be studied for better understanding of how variations in the nondeterministic properties of the system affect its overall efficiency and safety. The tool is structured to be sufficiently flexible to allow incorporation of different governing equations (right-of-way rules) for aircraft traffic management.

A large fraction of safety incidents occurs on the ground during airport surface operations. Although these incidents are mostly non-fatal with a few exceptions, they are high profile incidents that remain a source of concern for the National Transportation Safety Board (NTSB), the Federal Aviation Administration (FAA), major airlines, and other stakeholders of the National Airspace System (NAS). These incidents have historically been mitigated by implementing changes to regulations, policies, and procedures over time. This approach has minimized but not eliminated the risk of occurrences. It is thus important to develop integrated techniques to assess, model, and prevent these incidents by analyzing the risk and likelihood of occurrence and communicating results of the analysis to decision-making personnel who can mitigate and prevent incidents in real time. The research presented in this report builds on prior work of researchers at the NASA Ames Research Center who developed an automated framework, Real-Time Safety Monitoring (RTSM), to enable monitoring and prediction of the safety of the NAS. In the RTSM framework, hazards to flight are translated to safety metrics such as wake vortex encounters or loss of separation, that can be modeled and analyzed offline and also predicted and monitored in real time (online). The intent of this report is to integrate predictable incidents that occur during surface and ground operations into the safety portfolio of the RTSM project by (i) identifying suitable information sources from which ground incidents can be studied, (ii) developing safety metrics correlated with surface operations, and (iii) recommending suitable data sources that can be quantified and used for the computation of pertinent safety metrics.

The desire for Unmanned Aerial Systems (UAS) to routinely access manned airspace has grown substantially due to the proliferation of UAS and their associated applications. A key challenge to safely integrating UAS into the National Airspace System (NAS) is providing a reliable means for UAS to sense and avoid (SAA) other aircraft. The US Air Force is addressing this challenge through the Common Airborne Sense and Avoid (C-ABSAA) program. C-ABSAA is developing a sophisticated SAA capability that will be integrated onboard larger UAS. This paper summarizes key human factors efforts to develop a SAA traffic display with the appropriate level of information needed to aid the pilot in successfully maintaining self-separation and collision avoidance from other aircraft. The present study examined performance differences between candidate SAA displays as well as the most efficient manner to communicate recommended maneuvers. Fifteen Class 3-5 UAS military pilots compared five stand-alone SAA displays across two weather constraint levels (no weather, weather). Results indicated that the Banding Display tended to be most effective in aiding pilot performance during a SAA situation, with faster response times, less change in response time between weather conditions, no collision avoidance alert violations, and favorable subjective feedback. Implications of these findings on determining the acceptable level of information needed on a SAA display to aid pilot performance are discussed.

This study examined environmental situation awareness issues associated with accidents and incidents involving civil and public use unmanned aircraft systems operating in the National Airspace System. The data were derived from an information synthesis of archival publically available reports from the FAA Preliminary Reports of Unmanned Aircraft System Accidents and Incidents database, as recorded in the Aviation Safety Information and Analysis Sharing system. Some type of environmental situation awareness was an issue in 13 of the 274 accident and incidents examined, with navigation situation awareness as the most prevalent issue followed by lesser frequencies of weather, terrain, and altitude situation awareness related events. The identification of the types of environmental situation awareness issues associated with accidents and incidents provided insights for consideration when developing technology and training for unmanned aircraft systems.

Recent advances in unmanned and autonomous vehicle technology are accelerating the push to integrate these vehicles into human-centered environments such as commercial aviation and public roads. Much of the current research into autonomous systems examines improving the performance of individual unmanned vehicles or improving the safety of their interactions with individual humans; very little examines the behavior of the broader system. For large-scale transportation systems, real-world field trials involving unmanned vehicles are difficult to execute due to concerns of cost, feasibility of construction, and the maturity of the technologies. This paper describes the use of an agent-based model of unmanned vehicle behavior in human-centered environments to explore the effects of their implementation in these domains. In particular, this work explores how safety protocols governing the integration of manned and unmanned vehicles affect performance in an aircraft carrier ground control environment. Three di...

This research investigates how lightning strike–induced outages of airport infrastructure and facilities affect airport performance from an economic perspective, using Baltimore (Maryland)–Washington (D.C.) Thurgood Marshall International (BWI) Airport as a case study. On September 12, 2013, lightning struck within 300 m of the air traffic control (ATC) tower at BWI, causing injury and ATC tower and airport closures. The study findings reveal that the economic losses of the outage-related delays from that single event were almost five times higher than the ATC tower refurbishment that was planned, but unimplemented, in support of lightning protection, grounding, bonding, and shielding (LPGBS). The aim of this research is to support FAA's mission to better understand and quantify consequences of lightning strike–induced outages on airport performance. The research methodology and results can assist FAA in making sound decisions in support of LPGBS, and thereby help protect the National Airspace System infrastructure from lightning strikes and extreme weather and related delays.

The charter of FAA is to promote the safe, orderly, and expeditious use of the National Airspace System (NAS). To ensure that traffic flow is safe and efficient, FAA needs to know the expected traffic demand on the sector and the sector's capacity to accommodate that demand. When sector capacity is inadequate to meet the demand, congestion occurs. To ensure that safety is not compromised, FAA often takes action to reduce demand or increase capacity to avoid congestion. The MITRE Corporation's Center for Advanced Aviation System Development developed a time-on-task workload model to assess capacity and congestion in en route NAS sectors. A metric was developed and used along with the workload generated by the model and a workload threshold to estimate sector capacity. The metric, as constructed, enabled equitable comparison of capacity of different sectors, regardless of size. A field and lab evaluation of the workload model was used to quantify the model's task coverage and to calibrate its parameter values. The workload model was used to generate workload, capacity, and congestion profiles for selected en route sectors during good weather and during convective weather. The data used to generate the profiles can be used for various air traffic management applications.

The combined transit of departure flights from the airport surface, through the terminal airspace and merging into overhead en route traffic streams is a major source of delay in the National Airspace System (NAS). This is especially true in metroplex regions where departures and arrivals from/to multiple, proximate airports compete for limited resources (e.g., mixed-use runways, shared departure-fixes, busy overhead traffic streams). Current-day metroplex traffic management practices lead to multiple shortfalls. Under the Airspace Technology Demonstration — 2 (ATD-2) subproject, NASA plans to address these shortfalls by demonstrating Integrated Arrival, Departure, Surface (IADS) technologies and transitioning them to field-implementation. These technologies aim to increase the predictability, efficiency, and throughput of metroplex operations while meeting future air traffic demand. In order to help with effective transition of ATD-2 tools to the field, NASA needs reliable information regarding the operational shortfalls that ATD-2 can address, its benefit mechanisms and relevant performance metrics as well as high-fidelity benefit-cost estimates of implementing the ATD-2 system at major airports in the NAS. This paper describes the results of modeling, simulation and data analysis work performed in order to develop reliable estimates of the benefits of NASA's ATD-2 concept on a nationwide scale based on high-fidelity, realistic models of ATD-2 performance.

This chapter provides an in-depth analysis of mission-critical applications in aviation that involve the decision triad of aircraft, Flight Operations Control (FOC), and the Air Navigation Service Provider (ANSP). A characterization of operations and system requirements is carried out to provide bases for identifying cyber-physical system (CPS) transformation opportunities. Transformation opportunities are examined from the perspectives of the aircraft, the FOC, and the ANSP respectively. Benefits provided by the transformation and the challenges faced by this transformation are discussed, with potential path for addressing them identified. It is concluded that CPS integration is already happening in some segments, and ultimately an industry-wide transformation can be achieved.

Improved Air Traffic Management (ATM) leading to reduced en route and gate delay, greater predictability in flight planning, and reduced terminal inefficiencies has a role to play in reducing aviation fuel consumption. Air navigation service providers are working to quantify this role to help prioritize and justify ATM modernization efforts. In the following study we analyze actual flight-level fuel consumption data reported by a major U.S. based airline to study the possible fuel savings from ATM improvements that allow flights to better adhere to their planned trajectories both en route and in the terminal area. To do so we isolate the contribution of airborne delay, departure delay, excess planned flight time, and terminal area inefficiencies on fuel consumption using econometric techniques. The model results indicate that, for two commonly operated aircraft types, the system-wide averages of flight fuel consumption attributed to ATM delay and terminal inefficiencies are 1.0–1.5% and 1.5–4.5%, respectively. We quantify the fuel impact of predicted delay to be 10–20% that of unanticipated delay, reinforcing the role of flight plan predictability in reducing fuel consumption. We rank terminal areas by quantifying a Terminal Inefficiency metric based on the variation in terminal area fuel consumed across flights. Our results help prioritize ATM modernization investments by quantifying the trade-offs in planned and unplanned delays and identifying terminal areas with high potential for improvement.

In 2011 the National Aeronautics and Space Administration (NASA) began a five-year Project to address the technical barriers related to routine access of Unmanned Aerial Systems (UAS) in the National Airspace System (NAS). Planned in two phases, the goal of the first phase was to lay the foundations for the Project by identifying those barriers and key issues to be addressed to achieve integration. Phase 1 activities were completed two years into the five-year Project. The purpose of this paper is to review activities within the Human Systems Integration (HSI) subproject in Phase 1 toward its two objectives: 1) develop GCS guidelines for routine UAS access to the NAS, and 2) develop a prototype display suite within an existing Ground Control Station (GCS). The first objective directly addresses a critical barrier for UAS integration into the NAS – a lack of GCS design standards or requirements. First, the paper describes the initial development of a prototype GCS display suite and supporting simulation software capabilities. Then, three simulation experiments utilizing this simulation architecture are summarized. The first experiment sought to determine a baseline performance of UAS pilots operating in civil airspace under current instrument flight rules for manned aircraft. The second experiment examined the effect of currently employed UAS contingency procedures on Air Traffic Control (ATC) participants. The third experiment compared three GCS command and control interfaces on UAS pilot response times in compliance with ATC clearances. The authors discuss how the results of these and future simulation and flight-testing activities contribute to the development of GCS guidelines to support the safe integration of UAS into the NAS. Finally, the planned activities for Phase 2, including an integrated human-in-the-loop simulation and two flight tests are briefly described.

Surface operations at airports in the US are based on tactical operations, where departure aircraft primarily queue up and wait at the departure runways. NASAs Spot And Runway Departure Advisor (SARDA) tool was developed to address these inefficiencies through Air Traffic Control Tower advisories. The SARDA system is being updated to include collaborative gate hold, either tactically or strategically. This paper presents the results of the human-in-the-loop evaluation of the tactical gate hold version of SARDA in a 360 degree simulated tower setting. The simulations were conducted for the east side of the Dallas-Fort Worth airport. The new system provides gate hold, ground controller and local controller advisories based on a single scheduler. Simulations were conducted with SARDA on and off, the off case reflecting current day operations with no gate hold. Scenarios based on medium (1.2x current levels) and heavy (1.5x current levels) traffic were explored. Data collected from the simulation was analyzed for runway usage, delay for departures and arrivals, and fuel consumption. Further, Traffic Management Initiatives were introduced for a subset of the aircraft. Results indicated that runway usage did not change with the use of SARDA, i.e., there was no loss in runway throughput as compared to baseline. Taxiing delay was significantly reduced with the use of advisory by 45 in medium scenarios and 60 in heavy. Arrival delay was unaffected by the use of advisory. Total fuel consumption was also reduced by 23 in medium traffic and 33 in heavy. TMI compliance appeared unaffected by the advisory.

The FAA intends to considerably increase the usage of area navigation (RNAV) approach and departure procedures in order to achieve the proposed NextGen goals for improved efficiency and capacity. RNAV procedures enable aircraft to have better access and flexibility for point-to-point operations. In an effort to better understand the potential impact of increased RNAV usage, a human factors safety assessment was conducted to identify the key human factors issues present in current RNAV operations. An analysis of 100 RNAV narrative-based safety reports from the Air Traffic Safety Action Program (ATSAP) and 68 narrative-based safety reports from the Aviation Safety Reporting System (ASRS) was conducted to identify key causal factors. The analysis found several key causal factors related to RNAV procedure design, controller-pilot communication, automation systems, and track deviations. Specific human performance concerns and mitigation strategies for each causal factor were developed. These results should drive future requirements associated with the implementation of future RNAV procedures.

The optimized profile descent is an example of one of the many NextGen technologies under development to modernize and increase the efficiency of the national airspace system. The first publicly charted optimized profile descent procedure was implemented at Los Angeles International Airport in December 2007. This new flight procedure was designed so that aircraft could conduct arrival and approach operations with the engines remaining at or near minimum idle power settings; thereby, saving an average of 25 gal of jet fuel per flight when compared to the various aircraft types conducting an arrival and approach along the same lateral path at Los Angeles International Airport. This optimized profile descent translates into annual reductions of approximately 2,000,000 gal of jet fuel and 41,000,000 lb of carbon dioxide emissions. Given the positive environmental benefits of an optimized profile descent, there are several projects underway to increase the use of environmentally friendly arrival procedures wit...

As air traffic grows, improving the resilience of an increasingly congested airspace is becoming a primary concern to ensure its sustainability and avoid the propagation of localized disruptions. The fire set at Chicago Air Traffic Control facility in September 2014 is a striking and worrisome case where one ill-intentioned individual halted traffic in a facility which caused ripple effects across the National Airspace. This paper analyzes the particular role that the Chicago center plays in the National airspace. Then it provides a detailed analysis of the local and global impact of the fire, through the day of the event and for the next two weeks while the facility remained closed for repairs. Finally, it draws the lessons learnt from this event as well as other recent infrastructure failures.

The Next Generation Air Transportation System (NextGen) refers to the federal programs (predominately airspace, air traffic, or avionics related) that are designed to modernize the National Airspace System (NAS). ACRP’s NextGen initiative aims to inform airport operators about some of these programs and how the enabling practices, data, and technologies resulting from them will affect airports and change how they operate. This volume, the first report in this series, provides comprehensive information to practitioners concerning all aspects of Performance-Based Navigation (PBN) and how implementation affects overall airport operations. This Resource Guide encompasses background information, description of effects on short- and long-term airport development, impacts on safety and performance measures, and other critical factors affecting future airport operations. In addition to providing guidance to users on available resources for additional assistance, this volume also includes lessons learned and best practices based on findings from case studies that examined the airport operator’s role in PBN implementation.

The air transportation system is a network of many interacting, capacity-constrained elements. When the demand for airport and airspace resources exceed the available capacities of these resources, delays occur. The state of the air transportation system at any time can be represented as a weighted directed graph in which the nodes correspond to airports, and the weight on each arc is the delay experienced by departures on that origin-destination pair. Over the course of any day, the state of the system progresses through a time-series, where the state at any time-step is the weighted directed graph described above. This paper presents algorithms for the clustering of air traffic delay network data from the US National Airspace System, in order to identify characteristic delay states (i.e., weighted directed graphs) as well as characteristic types-of-days (i.e., sequences of such weighted directed graphs) that are experienced by the air transportation system. The similarity of delay states during clustering are evaluated on the basis of not only the in- and out-degrees of the nodes (the total inbound and outbound delays), but also network-theoretic properties such as the eigenvector centralities, and the hub and authority scores of different nodes. Finally, the paper looks at community detection, that is, the grouping of nodes (airports) based on their similarities within a system delay state. The type of day is found to have an impact on the observed community structures., United States. National Aeronautics and Space Administration (FA8721-05-C-0002), National Science Foundation (U.S.) (1239054)

The purpose of Air Transportation is to move people and cargo safely, efficiently and swiftly to their destinations. The companies and individuals who use aircraft for this purpose, the airspace users, desire to operate their aircraft according to a dynamically optimized business trajectory for their specific mission and operational business model. In current operations, the dynamic optimization of business trajectories is limited by constraints built into operations in the National Airspace System (NAS) for reasons of safety and operational needs of the air navigation service providers. NASA has been developing and testing means to overcome many of these constraints and permit operations to be conducted closer to the airspace user's changing business trajectory as conditions unfold before and during the flight. A roadmap of logical steps progressing toward increased user autonomy is proposed, beginning with NASA's Traffic Aware Strategic Aircrew Requests (TASAR) concept that enables flight crews to make informed, deconflicted flight-optimization requests to air traffic control. These steps include the use of data communications for route change requests and approvals, integration with time-based arrival flow management processes under development by the Federal Aviation Administration (FAA), increased user authority for defining and modifying downstream, strategic portions of the trajectory, and ultimately application of self-separation. This progression takes advantage of existing FAA NextGen programs and RTCA standards development, and it is designed to minimize the number of hardware upgrades required of airspace users to take advantage of these advanced capabilities to achieve dynamically optimized business trajectories in NAS operations. The roadmap is designed to provide operational benefits to first adopters so that investment decisions do not depend upon a large segment of the user community becoming equipped before benefits can be realized. The issues of equipment certification and operational approval of new procedures are addressed in a way that minimizes their impact on the transition by deferring a change in the assignment of separation responsibility until a large body of operational data is available to support the safety case for this change in the last roadmap step.This paper will relate the roadmap steps to ongoing activities to clarify the economics-based transition to these technologies for operational use.

A key component to solving many of the engineering challenges for integrating UAS into the National Airspace System (NAS) is being able to state within discrete airspace, the numbers of forecasted UAS by airframe type and the type of mission or operational use being performed.

Ongoing measurement of system performance is an essential input to management of the National Airspace System (NAS) by the Federal Aviation Administration (FAA). MITRE has been working with the Air Traffic Management System Command Center (ATCSCC) since 2000 to provide new performance metrics and data visualizations to better measure and understand system performance, and inform changes to behavior to reduce delays in the future.

This paper advocates for a specific design approach, based on simple principals, yet addresses challenges faced by the system engineers when designing complex data and information infrastructure. The document provides guidance for breaking out various work elements in the overall network architecture design, so that communication systems are conceived and effectively realized regardless of their location, size and local specifics. Although targeted at the Global Airspace System (GAS) and National Airspace System (NAS), this framework can be applied to any network-centric architecture.

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.

Congressional attention to Unmanned Aircraft Systems (UAS)1 has caused the Federal Aviation Administration (FAA) to move the National Airspace System (NAS) Integration project forward, but using guidelines, practices and procedures that are yet to be fully integrated with the FAA Aviation Management System. The real drive for change in the NAS will to come from both UAS operators and the government jointly seeing an accurate forecast of UAS usage demand data. This solid forecast information would truly get the attention of planners. This requires not an aggregate demand, but rather a picture of how the demand is spread across small to large UAS, how it is spread across a wide range of missions, how it is expected over time and where, in terms of geospatial locations, will the demand appear. In 2012 the Volpe Center performed a study of the overall future demand for UAS. This was done by aggregate classes of aircraft types. However, the realistic expected demand will appear in clusters of aircraft activities grouped by similar missions on a smaller geographical footprint and then growing from those small cells. In general, there is not a demand forecast that is tightly coupled to the real purpose of the mission requirements (e.g. in terms of real locations and physical structures such as wind mills to inspect, farms to survey, pipelines to patrol, etc.). Being able to present a solid basis for the demand is crucial to getting the attention of investment, government and other fiscal planners. To this end, Mosaic ATM under NASA guidance is developing a crowd sourced, demand forecast engine that can draw forecast details from commercial and government users and vendors. These forecasts will be vetted by a governance panel and then provide for a sharable accurate set of projection data. Our paper describes the project and the technical approach we are using to design and create access for users to the forecast system.

The Federal Aviation Administration (FAA) is undertaking a National Airspace System (NAS) modernization effort known as NextGen. NextGen includes a significant number of new system acquisitions that must be integrated with legacy NAS infrastructure which is continuously undergoing modifications in parallel. Each change to the NAS requires a safety analysis to identify and control safety risks. The FAA commissioned a software tool to assist with evaluating these safety analyses so that oversight activities may be planned accordingly. To accomplish this mission, a model of system and safety data that identifies interdependencies between NAS systems and safety hazards was developed. This model, along with a taxonomy of the data captured, can be used to identify relationships and trends in system and safety data that might otherwise be overlooked in safety analyses prepared separately for each NAS change. This paper discusses the approach used to build the integrated system safety model, the data captured to-date, and preliminary findings and trends from analysis of the model. This model can be used by safety practitioners to evaluate system changes and their contributions to existing hazards in the NAS and to focus oversight activities on systems and changes with the greatest predicted impacts on NAS safety. (Note: The views, opinions, and findings contained in this paper are those of the author and should not be construed as an official FAA position, policy, or decision.)

Interval Management is a suite of ADS-B-enabled applications that allows the air traffic controller to instruct a flight crew to achieve and maintain a desired spacing relative to another aircraft. The flight crew, assisted by automation, manages the speed of their aircraft to deliver more precise inter-aircraft spacing than is otherwise possible, which increases traffic throughput at the same or higher levels of safety. Interval Management has evolved from a long history of research and is now seen as a core NextGen capability. With avionics standards recently published, completion of an Investment Analysis Readiness Decision by the FAA, and multiple flight tests planned, Interval Management will soon be part of everyday use in the National Airspace System. Second generation, Advanced Interval Management capabilities are being planned to provide a wider range of operations and improved performance and benefits. This paper briefly reviews the evolution of Interval Management and describes current development and deployment plans. It also reviews concepts under development as the next generation of applications.

DOI: 10.2514/1.53975 Policy decisions that target effective utilization of the national airspace often relate to the capacities of individual airports in the system, and decisions to increase or reduce capacity (e.g., via slot restrictions) must be supported quantitatively. It is of particular interest to assess global impacts of capacity adjustments, because addressing congestion issues at one airport may have a“ripple effect” on the utilization of capacity elsewhere in the network. In this paper, an analytical model was developed that addresses system-wide implications of capacity decisions at the levelofinteractionsbetweenOperationalEvolutionPartnership35airports.Twomainelementscomprisethemodel: 1) a network flow model that describes both the capacities of Operational Evolution Partnership 35 airports and the demand for aircraft serving origin–destination traffic across the network and 2) a novel mathematical program referred to as the minimax node utilization problem that, when solved, minimizes the worst-case capacity utilization across all of the airports in the network. Both elements combine to allow quick assessment of both local and global effects of airport capacity adjustments. The analytical model is evaluated via case studies, including two capacity reduction scenarios and one capacity expansion scenario, focusing on the model’s ability to describe how capacity influences airport utilization throughout a network representing actual origin–destination demands in the airspace. The results from these scenarios indicate that the model provides a simple and effective technique for describing impacts of airport capacity perturbations, providing valuable high-level insight into airport utilization patterns.

As a result of the FAA Modernization and Reform Act of 2012, Unmanned Aerial Systems (UAS) are expected to be integrated into the National Airspace System (NAS) by 2015. Several human factors challenges need to be addressed before UAS can safely and routinely fly in the NAS with manned aircraft. Perhaps the most significant challenge is for the UAS to be non-disruptive to the air traffic management system. Another human factors challenge is how to provide UAS pilots with intuitive traffic information in order to support situation awareness (SA) of their airspace environment as well as a see-and-avoid capability comparable to manned aircraft so that a UAS pilot could safely maneuver the aircraft to maintain separation and collision avoidance if necessary. A simulation experiment was conducted to examine baseline compliance of UAS operations in the current airspace system. Researchers also examined the effects of introducing a Cockpit Situation Display (CSD) into a UAS Ground Control Station (GCS) on UAS pilot performance, workload and situation awareness while flying in a positively controlled sector. Pilots were tasked with conducting a highway patrol police mission with a Medium Altitude Long Endurance (MALE) UAS in L.A. Center airspace with two mission objectives: 1) to reroute the UAS when issued new instructions from their commander, and 2) to communicate with Air Traffic Control (ATC) to negotiate flight plan changes and respond to vectoring and altitude change instructions. Objective aircraft separation data, workload ratings, SA data, and subjective ratings regarding UAS operations in the NAS were collected. Results indicate that UAS pilots were able to comply appropriately with ATC instructions. In addition, the introduction of the CSD improved pilot SA and reduced workload associated with UAS and ATC interactions.

In an effort to modernize the National Airspace System (NAS), the Federal Aviation Administration (FAA) has introduced the Next Generation Air Transportation System (NextGen). The introduction of new capabilities and operational improvements (OI) offers the potential for changes to the roles and responsibilities of the traffic management unit (TMU). Each change presents the opportunity to positively or adversely impact the overall safety of the NAS. This paper applies a proactive approach to identifying potential human performance hazards associated with NextGen TMU operations. The TMU performance hazards identified were primarily related to the potential for selecting inadequate airspace and airport configurations. The potential effects of these hazards will directly affect the NextGen controller and thus represent rich opportunities for researchers to mitigate potential issues in the early stages of system design.

In an effort to modernize the National Airspace System (NAS) the Federal Aviation Administration (FAA) has introduced the Next Generation Air Transportation System (NextGen). The introduction of new systems and procedures as described in NextGen offers the potential for significant changes to the daily activities of air traffic controllers. Along with the many proposed NextGen capabilities and improvements comes the need for new controller alerts and notifications. This research presents fourteen potential new alerts directly or indirectly proposed by literature describing NextGen midterm operations. Each new alert along with the potential positive and negative implications of providing the controller with the alert is discussed. This high-level survey of alerts should serve to inform researchers and system designers as they develop research and design requirements.

On the basis of weather and high traffic, the Next Generation Air Transportation System envisions an airspace that is adaptable, flexible, controller friendly, and dynamic. Sector geometries, developed with average traffic patterns, have remained structurally static with occasional changes in geometry due to limited forming of sectors. Dynamic airspace configuration aims at migrating from a rigid to a more flexible airspace structure. Efficient management of airspace capacity is important to ensure safe and systematic operation of the U.S. National Airspace System and maximum benefit to stakeholders. The primary initiative is to strike a balance between airspace capacity and air traffic demand. Imbalances in capacity and demand are resolved by initiatives such as the ground delay program and rerouting, often resulting in systemwide delays. This paper, a proof of concept for the dynamic programming approach to dynamic airspace configuration by static forming of sectors, addresses static forming of sectors by partitioning airspace according to controller workload. The paper applies the dynamic programming technique to generate sectors in the Fort Worth, Texas, Air Route Traffic Control Center; compares it with current sectors; and lays a foundation for future work. Initial results of the dynamic programming methodology are promising in terms of sector shapes and the number of sectors that are comparable to current operations.

A review of the research accomplished in 2009 in the System-Level Design, Analysis and Simulation Tools (SLDAST) of the NASA's Airspace Systems Program is presented. This research thrust focuses on the integrated system-level assessment of component level innovations, concepts and technologies of the Next Generation Air Traffic System (NextGen) under research in the ASP program to enable the development of revolutionary improvements and modernization of the National Airspace System. The review includes the accomplishments on baseline research and the advancements on design studies and system-level assessment, including the cluster analysis as an annualization standard of the air traffic in the U.S. National Airspace, and the ACES-Air MIDAS integration for human-in-the-loop analyzes within the NAS air traffic simulation.

Unmanned Aircraft Systems (UAS) emerge as a viable, operational technology for potential civil and commercial applications in the National Airspace System (NAS). Although this new type of aircraft presents great potential, it also introduces the need for a thorough inquiry into its safety impact on the NAS. This study presents a systems-level approach to analyze the safety impact of introducing a new technology, such as UAS, into the NAS. Utilizing Safety Management Systems (SMS) principles and existing regulatory structure, this paper outlines a methodology to determine a mandatory minimum safety baseline for conducting safe operations in the NAS. In this context, a proof-of-concept study, which applies the proposed framework to Federal Aviation Regulations, is presented to demonstrate the feasibility of the methodology at a systems-level.

U.S. air transport is under significant stress, experiencing frequent delays and high levels of congestion. At certain times, individual airports become bottlenecks within the National Airspace System (NAS). Major causes of flight delay at airports include overscheduling, en route convective weather, reduced ceiling and visibility around airports, and upstream delay propagation. Delay at one airport can be passed on to other airports in the NAS. Hence, to allocate resources for airport capacity expansion in an optimal way, the impact of single airport delay to the NAS and vice versa must be quantified. This research applies multivariate simultaneous regression models to quantify airport delay spillover effects across 34 of the 35 Operational Evolution Partnership airports and the rest of the NAS. This analysis considers such contributing factors as average daily arrival delay, deterministic queuing delay, weather patterns, aircraft equipment type, and others. The three-stage least-square method is used to regress the models and obtain coefficients for the multivariate equations. The outcomes are used to explain the interactions among airports in the NAS and to identify the major delay contributors at each.

The limitations of the current National Airspace System (NAS) have necessitated the planning and development of the Next Generation Air Transportation System (NextGen). The core objectives of NextGen include increasing the safety and efficiency of air traffic management as well as expanding throughput at the nation's most congested airports. However, NextGen advances will also precipitate changes in the fundamental structure of air traffic operations, which could have profound effects on how humans, technology, and policy interact. Robust means for design and evaluation are needed to ensure success. Panel members will discuss current works in progress devised to facilitate NextGen objectives.

The Federal Aviation Administration (FAA) has embarked on a large effort to create the Next Generation Air Transportation System (NextGen). NextGen will prepare the National Airspace System to accept increasing air traffic levels and complexity in a safe and efficient manner. Data Communications (Data Comm) is one of the core technologies of NextGen. The use of Data Comm will improve information exchange between pilots and air traffic controllers. In 2009, the FAA conducted three human-in-the-loop experiments to address the use of Data Comm in the Airport Traffic Control Tower, the Terminal Radar Approach Control, and the En Route airspace. The experiments focused on human factors aspects of air traffic control tasks under a variety of conditions including varying percentages of aircraft equipped for Data Comm, different interface designs, and changes in roles of responsibilities of air traffic controllers.

Increasingly detailed planning is addressing a range of human factors considerations associated with the Next Generation Air Transportation System (NextGen). The practice of human factors program management for NextGen poses complex opportunities and challenges. Relationships between human factors research programs and their elements and with other programs and portfolios are identified and aligned using a human system integration roadmap. Effective planning that addresses human factors issues associated with transitions of new NextGen technologies, automation and procedures will facilitate realization of intended benefits from NextGen involving increased throughput, efficiency, and safety in the National Airspace System.

Adverse weather conditions are hazardous to flight and contribute to re-routes and delays. This has a negative impact on the National Airspace System (NAS) due to reduced capacity and increased cost. In today's air traffic control (ATC) system there is no automated weather information for air traffic management decision-support systems. There are also no automatic weather decision-support tools at the air traffic controller workstation. As a result, air traffic operators must integrate weather information and traffic information manually while making decisions. The vision in the Next Generation Air Transportation System (NextGen) includes new automation concepts with an integration of weather information and decision-making tools. Weather-sensitive traffic flow algorithms could automatically handle re-routes around weather affected areas; this would optimize the capacity during adverse conditions. In this paper, we outline a weather probe concept called automatic identification of risky weather objects in line of flight (AIRWOLF). The AIRWOLF operates in two steps: (a) derivation of polygons and weather objects from grid-based weather data and (b) subsequent identification of risky weather objects that conflict with an aircraft's line of flight. We discuss how the AIRWOLF concept could increase capacity and safety while reducing pilot and air traffic operator workload. This could translate to reduced weather-related delays and reduced operating costs in the future NAS.

New air traffic control concepts and automation tools designed to improve the capacity of the National Airspace System are continually researched, including those that test early prototypes and their impact on the operators to adequately perform the task at hand. This study investigated the workload, situation awareness and other human factors issues related to using a prototype surface automation tool (“GoSAFE-Ground Operations Situation Awareness and Efficiency Tool”) for managing precision taxi operations, with increased traffic relative to current day operations. Our team of controller participants working four air traffic positions handled airport traffic using GoSAFE under two different levels of automation: (1) Mixed voice/datalink [partially equipped] and (2) Datalink only [fully equipped]. The study found statistically significant differences on workload due to automation level. The impact of automation was also investigated for the four air traffic control positions. Results on one situation awa...

Traffic flow management (TFM) allocates the various airport, airspace, and other resources to maintain an efficient traffic flow consistent with safety. TFM is a complex area of research involving the disciplines of operations research, guidance and control, human factors, and software engineering. Hundreds of human operators make TFM decisions that involve tens of thousands of aircraft, en route air traffic control centers, the Federal Aviation Administration's System Command Center, and many airline operation centers. This paper provides an overview of how TFM decisions are made today and challenges facing the system in the future, and reviews modeling and optimization approaches for facilitating system-wide modeling, performance assessments, and system-level optimization of the national airspace system in the presence of both en route and airport capacity constraints.

A human-in-the-loop simulation experiment was conducted at the NASA Langley Research Center's Air Traffic Operations Laboratory in an effort to comprehensively validate tools and procedures intended to enable the small aircraft transportation system higher-volume-operations concept of operations. These procedures were developed with the goal of increasing the rate of operations at nontowered, nonradar airports in near all-weather conditions. A key element of the new design is the establishment of a volume of airspace around designated airports at which pilots accept responsibility for self-separation. Flights operating at these airports are given approach-sequencing information computed by a ground-based automated system. The validation experiment was conducted to determine if a pilot could safely and proficiently fly an airplane while performing the newly developed procedures. Comparative measures of flight path error, perceived workload, and situation awareness were obtained for two types of simulated scenarios. Baseline scenarios were representative of today's system using procedure separation, in which air traffic control grants one approach or departure clearance at a time. Test scenarios represented the newly developed approach and departure procedures. Results from the experiment indicate that low-time pilots were able to fly the test procedures in a simulation environment and maintain self-separation as safely and proficiently as flying today's procedures.

The primary objective of the National Airspace System (NAS) is the transportation of passengers and cargo. Since passenger trip time performance is positively correlated with passenger satisfaction, airfare elasticity, and airline profits, it follows that the evaluation of performance and modernization of the NAS, as well as consumer protection, should be based on passenger trip performance (in addition to airline flight performance). Publicly available regulatory measures of NAS performance, however, are based on flight data and not passenger trip data. Researchers have demonstrated that the trip delays experienced by passengers disrupted by missed connections, canceled flights, and diverted flights are not negligible. Further, research demonstrated that flight delays are a poor proxy for measuring passenger trip delays. A comparative statistical analysis is described between flight delay data and estimated passenger trip delay data for 1 year's worth of flights on the 1,030 single-segment routes between the 35 [airports of FAA's Operational Evolution Partnership (OEP)]. The estimated passenger trip data are derived from publicly available databases and account for delays experienced by passengers on single-segment routes because of canceled flights as well as delayed flights. The statistical analysis indicates that (a) the estimated percentage of on-time passengers is equal to the percentage of on-time flights plus the percentage of canceled flights, (b) the estimated average passenger trip delay is 34 min in excess of the average flight delay, and (c) estimated average passenger trip delay for the worst 5% of delayed passengers is 150 min in excess of the flight delay. The implications of these results for consumers, industry performance measures, and FAA modernization efforts are discussed.

Very light jets constitute a class of three to eight passenger turbofan-powered aircraft that will enter service in 2006 and will need to be integrated into the National Airspace System. An aircraft performance analysis showed similarities between the predicted performance and capabilities of very light jets and the performance of existing light jets. Based on this, an analysis of operating patterns of existing light jets was used to predict how very light jets will be operated. Using 396 days of traffic data from the FAA enhanced traffic management system, the operating patterns of existing light jets were analyzed. It was found that 64% of all the flights flown by lightjets had their origin, destination, or both within the top 23 regional airport systems in the continental United States. This concentration of light jet traffic was found in areas of the air transportation system that are currently exhibiting dense traffic and capacity constraints. The structure of the network of routes flown by existing light jets was also studied and a model of network growth was developed. It is anticipated that this concentration will persist with emerging very light jet traffic. This concentration of traffic at key areas in the system will have implications for air traffic control management and airport activity. For regional airport systems, core airports are expected to saturate and, reliever airports will become critical for accommodating traffic demand. The entry of very light jets will increase the traffic load at the terminal airspace: terminal radar approach control. These impacts need to be taken into account to allow a successful integration of these aircraft in the National Airspace System.

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.

NASA's Aeronautics Research Mission Directorate (ARMD) collaborates with the FAA and industry to provide concepts and technologies that enhance the transition to the next-generation air-traffic management system (NextGen). To facilitate this collaboration, ARMD has a series of Airspace Technology Demonstration (ATD) sub-projects that develop, demonstrate, and transitions NASA technologies and concepts for implementation in the National Airspace System (NAS). The second of these sub-projects, ATD-2, is focused on the potential benefits to NAS stakeholders of integrated arrival, departure, surface (IADS) operations. To determine the project objectives and assess the benefits of a potential solution, NASA surveyed NAS stakeholders to understand the existing issues in arrival, departure, and surface operations, and the perceived benefits of better integrating these operations. NASA surveyed a broad cross-section of stakeholders representing the airlines, airports, air-navigation service providers, and industry providers of NAS tools. The survey indicated that improving the predictability of flight times (schedules) could improve efficiency in arrival, departure, and surface operations. Stakeholders also mentioned the need for better strategic and tactical information on traffic constraints as well as better information sharing and a coupled collaborative planning process that allows stakeholders to coordinate IADS operations. To assess the impact of a potential solution, NASA sketched an initial departure scheduling concept and assessed its viability by surveying a select group of stakeholders for a second time. The objective of the departure scheduler was to enable flights to move continuously from gate to cruise with minimal interruption in a busy metroplex airspace environment using strategic and tactical scheduling enhanced by collaborative planning between airlines and service providers. The stakeholders agreed that this departure concept could improve schedule predictability and suggested several key attributes that were necessary to make the concept successful. The goals and objectives of the planned ATD-2 sub-project will incorporate the results of this stakeholder feedback.