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The International Civil Aviation Organization identifies departure and arrival punctuality as on-time key performance indicators. However, these metrics assume a flight’s delay is a result of either the origin or destination airport, providing limited information on where delay should be mitigated in the U.S. National Airspace System (NAS). This study evaluates the relationship between delay propagation magnitude, delay causal factor, airport size, and charged facility (airport or Air Route Traffic Control Center), to examine if certain delays take longer to dissipate. First, using flights from July 2018, results show that most delay propagation chains originate at large-hub airports. However, these delays were the quickest to recover. Second, this study presents a regression model, predicting total propagated delay using fixed effects based on the weather region where the original delay occurred. Each additional flight affected by downstream delay adds 18.7 min on average to total arrival delay in a propagation chain. Additionally, if weather was the original causal factor, total propagated delay increased by 11.6 min compared with non-weather delays. Lastly, this study compares delay propagation in July 2018 and July 2020. Results show uneven impacts of the coronavirus disease 2019 (COVID-19) across the large-hub airports. Some of the investigated airports did not witness large improvements in average delay per delayed flight, warranting further research in the future. While delay and delay propagation have not been completely eradicated in the NAS during the COVID-19 pandemic, findings suggest that both have significantly declined on average.

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback of these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS XU alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.

The primary mission of the Federal Aviation Administration (FAA) is to maintain the safety of the National Airspace System (NAS). As part of this mission, the FAA is tasked with ensuring that future air traffic controllers are adequately trained to perform the high-risk job of directing air traffic. The FAA Academy curriculum for newly hired controllers involves 3-4 months of intensive lessons and performance assessments. It has been suggested that this training program is quite stressful, and successful trainees tend to be those who can better manage stress. To support ATC trainees, researchers at the Civil Aerospace Medical Institute (CAMI) have conducted operational research to develop and evaluate a stress management training to help trainees manage their stress during training at the FAA Academy.

An Activity Theory framework was applied in investigating the pressing issue of Unmanned Aircraft System (UAS) integration into the National Airspace System. As stated in the FAA’s UAS Operational Approval policy notice, the UAS pilot and/or crew are collectively responsible for successfully exercising see-and-avoid duties. To describe how this is achieved in practice, field recordings of visual observers and other UAS crewmembers were collected during three phases of a long-endurance UAS flight test: takeoff, mid-flight, and landing. Four separate radio communications channels were utilized, and pilots’ workload was offloaded in three ways: takeoff and landing flight dynamics were offloaded to the external pilot, see-and-avoid duties were offloaded to visual observers, and some communications were offloaded to the mission commander. Visual observers relied on a combination of visual perception, communication, and team coordination skills to assist pilots and the mission commander in effectively accomplishing see-and-avoid duties during UAS operations.

The National Airspace System suffers from a reduction in airport throughput or even closure when weather or traffic volume constrains arrival or departure gates to and from the Terminal Radar Approach Control (TRACON) facilities. To alleviate this, the Federal Aviation Administration introduced the Integrated Arrival and Departure Control Services (IADCS) concept that would extend terminal separations and procedures to the adjacent Air Route Traffic Control Center (ARTCC) sectors for more flexible traffic. It proposes the use of resectorization, bidirectional gates, bidirectional routes, and Air Traffic Control assigned routes. We evaluated them in the human-in-the-loop high-fidelity experiment and collected objective and subjective data. Our results clearly showed that all IADCS procedures except the vertically separated/bidirectional gate procedure were more effective than the Baseline condition that controllers currently use in the field. We conjecture the vertically separated/bidirectional gate procedure requires more complex perceptual and cognitive processes than the other procedures.

Because of recent technological advancements, a growing number of unmanned aircraft systems (UASs) are anticipated to occupy the U.S. National Airspace System (NAS) and operate side-by-side with human pilot controlled civil aircraft. UAS technology has transitioned to broader applications, including commercial, scientific, and expanded military use. There have been significant challenges concerning the safe and suitable integration of UASs with existing systems. The interaction between humans and increasingly automated systems is of concern to researchers. Additionally, the number of UAS sightings has increased significantly during the last few years. In this study, the research team compiled 7,400 reports of UAS sightings (2015–2018). The Latent Dirichlet Allocation (LDA) method was then applied to develop topics relevant to UAS sighting incidents. This study also developed an online interactive tool to show keywords associated with different topics. These interactive topic models can help policymakers establish new policies and regulations to address specific safety concerns.

NASA has been developing and testing the Traffic Aware Strategic Aircrew Requests (TASAR) concept for aircraft operations featuring a NASA-developed cockpit automation tool, the Traffic Aware Planner (TAP), which computes traffic/hazard-compatible route changes to improve flight efficiency. The TAP technology is anticipated to save fuel and flight time and thereby provide immediate and pervasive benefits to the aircraft operator, as well as improving flight schedule compliance, passenger comfort, and pilot and controller work-load. Previous work has indicated the potential for significant benefits for TASAR-equipped aircraft, and a flight trial of the TAP software application in the National Airspace System has demonstrated its technical viability. As part of ongoing software research, development, and testing of the TAP software, we developed the capability to run the current build of the TAP software using the NASA Airspace and Traffic Operations Simulator (ATOS) with preloaded flight scenarios. Our demonstration is fully interactive and will allow participants to operate the TAP software on an iPad Air themselves, or observe the demonstrators operating it. The purpose of developing this capability is not only to assist with testing during software development, but also to acquaint researchers and potential stakeholders with the TAP human machine interface and the functionality and capabilities of the software itself.

Minimum display requirements for Detect-and-Avoid (DAA) systems are being developed in order to support the expansion of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS). The present study examines UAS pilots’ subjective assessments of four DAA display configurations with varying forms of maneuver guidance. For each configuration, pilots rated the intuitiveness of the display and how well it supported their ability to perform the DAA task. Responses revealed a clear preference for the DAA displays that presented suggestive maneuver guidance in the form of “banding” compared to an Information Only display, which lacked any maneuver guidance. Implications on DAA display requirements, as well as the relation between the subjective evaluations and the objective performance data from previous studies are discussed.

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.

Literature New capabilities to modernize the U.S. National Airspace System (NAS) include support of real-time information streams derived from many data sources across the NAS. As an emergent property, safety of the NAS arises from interactions between many elements at different levels, ranging from those attributable to humans, technology, and the environment. Each component in the NAS needs to interact with other components, exchange resources and information, and operate under broad regulations to achieve overall system objectives (Harris & Stanton, 2010). Sometimes, incidents and accidents result from insufficient interaction (communication and coordination) between humans (e.g., pilot-controller). The content of communication provides value and supports understanding with a multitude of individual, group, team, and data sets within air traffic research. In addition, another dimension to communication with a potentially rich source of understanding is everything outside of its explicit meaning. Cooke and Gorman (2009) describe methods of communication flow between teams (considered to be a system) that have proven insightful. The first is a ratio of team members speech quantity, which can indicate the degree of influence one member has over others. Another is the communication required and passed score, or how much variation there is in actual team communication from expectations. Flow quantity represents how much speech each member of the team produces. Gorman et al.’s (2012) study applied discrete Recurrence Quantification Analysis (RQA) to team communication flow data in order to visualize and measure coordination dynamics of Unnamed Aircraft Vehicle (UAV) teams, both mixed teams (i.e., team members changed) and intact teams (i.e., team members stayed the same over successive experimental sessions). Interestingly, mixed teams were better able to adjust to unexpected perturbations; this ability was linked to team level coordination dynamics. That is, mixed teams adopted a globally stable pattern of communication while exhibiting strong temporal dependence (Gorman, Cooke, Amazeen, & Fouse, 2012). Similarly, Demir, Cooke, & Amazeen (2018) applied discrete RQA on human-robot interaction in an Urban Search and Rescue task and multivariate extension of RQA on human-synthetic team in a UAV task. They underline that metastable team coordination (not too stable nor too flexible) between team members is associated with the ability to successfully overcome novel events (i.e., team situation awareness) in a dynamic task environment. The current project addresses the question of how human factors related to air traffic control (ATC), specifically situation awareness and cognitive load, interact with other factors in the NAS to affect ATC performance and a result in a safe and effective NAS? One way to answer this question is focusing on ATC-pilot communication as a chief performance indicator. In the current study, we investigate the potential of dynamical systems perspectives to capture the differential dynamics of three cases between controller-pilot communication flow during incidents and accidents. Method One of the approaches for investigating interaction patterns between system components (in the controller-pilot case) and their change over time involves looking at communication flow using discrete Recurrence Plot (RP) and corresponding Recurrence Quantification Analysis (RQA), which quantifies how many recurrences with a certain length are present by multidimensional space (phase space) trajectory in a dynamical system (Marwan, Carmen Romano, Thiel, & Kurths, 2007). RP is the basis of discrete RQA (Eckmann, Kamphorst, & Ruelle, 1987), which is a visual tool for demonstrating a system’s recurrent structure in the phase space when a system revisits specific states or sequences of states within a region of phase space over a period of time. In the case of two or more systems, discrete RP displays the times when two or more separate dynamical systems show a recurrence simultaneously (Marwan et al., 2007). Three cases of controller-pilot audio transmissions with their communication time stamps were obtained from “Cockpit Voice Recorder Transcripts” (2019), visualized using RP, and analyzed via discrete RQA. The cases represent situations of particular interest, communication, and coordination. Discrete RQA quantifies not only the effect of interventions (such as unexpected events) on instability, but also the dyad interaction processes and the dynamics that contribute to that process. The RQA was used to produce several measures, including percent recurrence rate, percent determinism (DET), longest diagonal line, longest vertical line, entropy, and laminarity. Of these, the focal variable was determinism (Marwan et al., 2007), which indicates the amount of organization in the communication of a system. DET is derived from the recurrence plot by examining how the recurrent points are distributed. Dyads with high determinism tend to repeat sequences of states many times, while a controller-pilot with low determinism rarely repeats a sequence of states, producing few diagonal lines. Results and discussion One of the objectives of this study is to monitor human performance indicators in real-time in the NAS to make predictions about risk. The current exploratory paper presents an idea about how to model human interaction between two or more roles with the larger purpose of developing NAS risk prognostics. We have presented three controller-pilot communication flows via discrete RP and RQA methods that differentiate three real cases based on discrete interaction sequences. The measures extracted from the RQA and visualizations of the interaction patterns show that effective communication and coordination is needed for effective situation awareness, i.e., overcoming the failures. Based on previous studies (Demir et al., 2018), we expected that the rigidity of the coordination dynamics between controller and pilot in one of the cases would associated with a fatal accident as well as lack of communication (confusion during the landing), resulting in a lack of situation awareness. On the other hand, two other incidents demonstrated more flexible behavior across the roles (controller-pilot) to adapt to the dynamic environment. In this case, the key lies in the dynamic transition between interaction and the environment. The controller and pilot are compelled to adjust their interaction patterns (flexibility) to adapt to changes in the environment and maintain a stable trajectory toward meeting their goals, such as landing safely. Thus, there are three crucial states for effective interaction in both temporal and spatial states: what needs to be communicated, when it needs to be coordinated, and how it needs to be communicated and coordinated”.

Unmanned air vehicles (UAVs), which have been popular in military context, have recently attracted attention of many researchers because of their potential civilian applications. However, before the UAVs can be used for civilian applications, a systematic integration of UAVs in the National Airspace System (NAS) is needed that can allow safe operation of UAVs along with other manned aircrafts. One of the critical capabilities needed for safe operation of the UAVs in the NAS is the ability of UAV to carry out sense and avoid task which would allow the UAV to amend its path to avoid collision with other aircrafts. Despite recent technological advances, such as availability of automatic dependent surveillance broadcast that can transmit position of an aircraft to others in the vicinity, planning a collision-free path autonomously is still challenging in a dynamic environment. The objective of this paper is to develop a methodology for discovering a path for the UAV that meets mission goals, avoids collision, is optimal in terms of path length and, more importantly, is feasible. The paper formulates the problem of path planning using the mathematical paradigm of mixed integer linear programming and provides a solution strategy for solving this problem in the dynamic sense. The tasks of avoidance of obstacles and waypoint navigation are incorporated as constraints in the MILP problem. The paper presents the solution of the MILP problem and verifies the performance of the proposed methodology with regard to optimality of the solution and computational time requirement via several simulated scenarios of different complexities.

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 research explored how pilots perceived the concept of the Well Clear Boundary (WCB), observing if that boundary changed depending on aircraft type: manned versus unmanned aircraft systems (UAS). Pilots’ WCB perceptions were collected through simulator recordings and subjectively through questionnaires. Significant differences were found in WCB perception between two pilot types (General Aviation [GA], and Airline Transport Pilots [ATPs]), and significant WCB differences were evident when comparing two intruding aircraft types (manned versus unmanned aircraft). Significant differences were dependent on other manipulated variables (intruder approach angle, ownship speed, and background traffic levels). Subjectively, there were differences in WCB perception across pilot types; GA pilots trusted UAS aircraft higher than the more experienced ATPs. Overall, analyses indicated that pilots’ mental models for WCB varied depending on position from ownship. Aircraft in front on ownship were perceived as time - based boundaries while aircraft to the rear of ownship were perceived distance based.

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.

Minimum display requirements and performance standards for Detect and Avoid (DAA) systems are currently being developed to safely integrate Unmanned Aircraft Systems into the National Airspace System (NAS). The present study examines UAS pilots’ subjective assessments of four display configurations with either basic or advanced levels of information presented on a standalone or integrated display. Post-trial and post-simulation questionnaires queried pilots on their subjective ability to safely perform tasks and effectively utilize available information on each display. Responses indicated that the majority of pilots considered each display to be acceptable for a pilot-in-the-loop DAA task overall, but also revealed a strong preference for an integrated display with advanced information in the form of conflict resolution tools. Implications on the development of DAA display requirements, as well as the relation between the subjective evaluations and the objective performance data from previous studies are discussed.

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.

As the FAA forecasts air traffic growth for U.S. carriers to increase (by 90% in revenue passenger miles and by 50% in the number of handled aircraft) over the next 20 years, airports consequently will be subjected to problems associated with substantially increased levels of demand. One component of the solution is expected to come from further investments in improvements to airport infrastructure. Given current fiscal constraints, the inherent network structure of the National Airspace System, and the fact that delays and congestions propagate throughout the system, would it be more efficient for capital investments to be made in an integrated and intelligent fashion—one that serves to maximize the productivity of the entire system—rather than on an airport-by-airport basis? Therefore, the goals of this research were to understand current airport interactions and to provide a framework for quantifying how interactions spread throughout the network. These insights were uncovered by exploiting the network structure of the National Airspace System in the framework of spatial econometric modeling. The data necessary to determine these relationships came from multiple sources: the Bureau of Transportation Statistics Schedule T-100 data on origin–destination pairs provided dynamic measures of connectivity, while FAA data on airport investments provided the necessary information to determine infrastructure investment patterns.

The U.S. Congress passed the FAA Modernization and Reform Act in 2012, which calls for a plan to integrate Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS). For UAS to be allowed to operate in the NAS, they will be required to “act and respond as manned aircraft do.” FAA regulations require that pilots respond promptly to air traffic controller (ATCo) commands. However, they do not quantify what an acceptable latency is. We maintain that research needs to be carried out to identify an acceptable latency in UAS responding, known as the “measured response.” While the measured response can be broken down into several components, the present paper provides an overview of how latencies in verbal communication and command execution can impact Pilot-ATCo communications and acceptability ratings when single and multiple UAS are operating in a simulated NAS environment.

Unmanned aerial systems (UAS) are starting to access manned airspace today and this trend will grow substantially as the number of UAS and their associated missions expand. 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 “sense-and-avoid” capability that will be integrated onboard larger UAS. This paper summarizes human factors activities associated with enabling this revolutionary capability. Existing knowledge was reviewed and crosschecked to formulate a first draft set of minimum information requirements for SAA tasks. A gap analysis spawned an intruder depiction study and an operator requirements survey. Finally, operator interface prototypes were designed to support: 1) a minimum information set for SAA, as well as 2) the availability of several advanced situation assessment and maneuver guidance aids. Through collaboration with NASA’s UAS in the NAS project, these concepts were incorporated into a UAS ground control station for formal evaluation through a high fidelity human-in-the-loop simulation.

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.

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.

In the National Airspace System (NAS), Air Traffic Control (ATC) expects aircraft to complete ATC clearances in a timely manner in order to maintain minimum separation between aircraft. The end-to-end response time for an aircraft to complete a clearance, as measured from the end of ATC instructing the pilot of the clearance to the just noticeable difference (JND) on the ATC display of the aircraft satisfying the clearance (i.e., initiation/completion of an altitude climb), can be referred to as measured response (MR). This MR is not quantified in Federal Aviation Administration (FAA) standards, regulations, or policy; however, as manned aircraft have developed along with the Air Traffic Management System, a shared understanding of reasonable and timely response has evolved. By contrast, the introduction of unmanned aircraft systems (UAS) into the NAS has highlighted this issue. This paper seeks to define MR and its components, and describe a methodology, with an example, that can be used to investigate it.

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.

In an effort to modernize the National Airspace System, the Federal Aviation Administration 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. Each change presents the opportunity for both positive and negative effects on the overall safety of the NAS and the role of the air traffic manager. This paper presents a methodology for prospectively identifying hazards to the performance of air traffic controllers as well as a summary of the categorization of the hazards by task. Scenarios describing NextGen airport departure operations and operations with varying levels of equipage presented the most significant human performance hazards. These identified hazards represent rich opportunities for future human factors research.

The operation and safety of the National Airspace System (NAS) is reliant on a multitude of actors and systems, which includes the members of the Airline Operation Center (AOC), whose primary job is to ensure flight safety (Sheremeta & Weitzel, 2005). The FAA’s NextGen will constitute many changes within the NAS, and the effects of these changes need to be examined in respect to the AOC. However, before these changes can be examined in detail, it is necessary to have a baseline understanding of the current operations and actors of an AOC. In this study, AOC actors that are critical to the day-to-day operation of an AOC were identified and a functional allocation was performed. Using this research as a baseline, further research should be conducted to examine how those AOC actors and their functions will change with the implementation of NextGen.

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.

Airline delays lead to a tremendous loss of time and resources and cost billions of dollars every year in the United States. To explore solutions for reducing delay, it is essential to understand factors causing flight delays and also the network impact of delays at one airport in the National Airspace System (NAS). For air transportation planning and policy purposes, this study concentrates on providing answers from a macroscopic point of view without being distracted by volatile operational details. A set of multivariate equations is proposed to model daily average arrival delay at one airport, and another for the rest of the NAS. The model for the single airport considers independent variables such as deterministic arrival queuing delay, delay at other airports in the NAS, adverse weather (convective and local), and different demand management regimes. The model for the rest of the NAS considers arrival delay as a function of deterministic arrival queuing delay, arrival delay at the single airport, adverse weather (convective and local), and other factors. Observation of the interactions between these two models shows that they can be regressed with an econometric technique: two-stage least squares. This macroscopic framework of delay impact analysis can be used to investigate the network effect of capacity improvement or new demand management strategies at a single airport. Hypothetical scenarios are generated and the systemwide delay reduction is calculated. This is a powerful decision support tool for stakeholders to use in deciding how to allocate resources optimally and to reduce delays.

The Washington State Department of Transportation's (DOT) snow avalanche control program reduces winter roadway closure times and hazards to motorists. The University of Washington and the Washington State DOT evaluated small unmanned aircraft systems (UASs) as a tool to enhance this program. Because of military investment, UAS technology has dropped in cost as it has become increasingly capable and easier to operate. Commercially available UASs, which fly autonomously, can be operated off a roadway and can collect low-cost, real-time aerial imagery while also carrying payloads. This project conducted a series of test flights involving both fixed- and rotary-wing (helicopter) UASs over a roadway in mountainous terrain. The flights demonstrated that UASs can conduct snowpack and terrain surveillance and can accurately drop explosive charges such as those used to trigger controlled avalanches. The rotary-wing UAS was particularly usable because of its ability to hover, which provided a stable camera platform, and because it required minimal area to land. The reliability of UASs is a concern, and their capabilities may be challenged by mountainous terrain and weather. This problem may be reduced as UASs become either less expensive and more expendable or more reliable and all-weather capable. A major barrier to use of UASs is the need to obtain approval to fly from FAA, a process that can be time-consuming and restrictive. FAA is currently updating its plans to integrate UASs into the national airspace, and a number of technology-based solutions are being considered.

Flight cancellations are costly to airlines and air passengers, but the question is, how costly? Little quantitative analysis about cancellation cost has been done, and current studies are focused on flight delays. However, cancellations should be studied to supplement delay metrics to assess the performance of the National Airspace System, as well as to evaluate the effectiveness of air traffic management. Postoperation data of the ground delay program were explored, and relative value of cancellations in terms of delay savings were inferred. Two cancellation metrics were developed for this purpose. In addition, flight cancellation decisions were modeled with a discrete choice model by using the two cancellation metrics that were generated as well as some other flight characteristics. Three models are presented in this study. The results reveal the value of a flight cancellation and airline preference structure in making decisions in canceling a flight in response to schedule disturbance. The study contributes to the literature in a distinct way: post-operation data are used to understand airline flight cancellation behavior in the context of ground delay programs.

Future concepts for the National Airspace System rely on technologies, such as synthetic and enhanced vision systems, to support flight efficiency associated with improved terrain and traffic awareness. While these technologies provide the pilot access to information not available with traditional flight instrumentation, the presentation of this additional information may serve to produce display clutter, thus inhibiting the processes and tasks they are designed to support. An experiment was conducted to assess pilot perceptions and identification of both bottom-up (data-driven) and top-down (knowledge-driven) contributing factors to display clutter. Results revealed the importance of both visual and information density (bottom-up and top-down factors, respectively) to the perception of clutter. Although added display elements provided pilots with critical flight information, pilots considered displays to be cluttered when the imposed visual density exceeded the information density required for specific flight tasks. These findings suggest that moderate levels of display clutter may be tolerable, to the extent that the information is relevant to the tasks at hand.

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.

Flight delay is one of the pressing problems that have far-reaching effects on society and the nation's economy. A primary cause of flight delay in the National Airspace System is high taxi-out times (time between gate push-back and wheels-off) at major airports. Accurate prediction of taxi-out time is needed to make downstream schedule adjustments and for better departure planning, which could mitigate delays, emissions, and congestion on the ground. However, accurate prediction of taxi-out time is difficult because of uncertainties associated with the dynamically changing airport operation. A novel stochastic approximation scheme based on reinforcement learning (RL) is presented for predicting taxi-out times in the presence of weather and other departure-related uncertainties. The prediction problem is cast in a probabilistic framework of stochastic dynamic programming and solved by using approximate dynamic programming approaches (particularly RL). The strengths of the method are that it is nonparametric, unlike regression models with fixed parameters, it is highly adaptable to the dynamic airport environment since it is learning based, it is scalable, it is inexpensive since it does not need highly sophisticated surface management systems, and it can effectively handle uncertainties because of the probabilistic framework. Taxi-out prediction performance was tested on data obtained from the FAA Aviation System Performance Metrics database on Detroit International and Washington Reagan National Airports. Results show that the root-mean-square prediction error calculated 15 min before gate departure time is on average 2.9 min for about 80% of the predicted flights.

The Federal Aviation Administration (FAA) has been increasing the National Airspace System (NAS) capacity to accommodate the predicted rapid growth of air traffic. One method to increase the capacity is reducing air traffic controller workload so that they can handle more air traffic. It is crucial to measure the impact of the increasing future air traffic on controller workload. Our experimental data show a linear relationship between the number of aircraft in the en route center sector and controllers' perceived workload. Based on the extensive range of aircraft count from 14 to 38 in the experiment, we can predict en route center controllers working as a team of Radar and Data controllers with the automation tools available in the our experiment could handle up to about 28 aircraft. This is 33% more than the 21 aircraft that en route center controllers typically handle in a busy sector.

Traffic Management Specialists within the Air Traffic Control (ATC) system strategically manage the flow of air traffic to minimize delays and congestion due to system stressors such as heavy volume, weather, and equipment outages. ATC facilities are required to log all Traffic Management Initiatives (TMIs), coordinate the implementation of some initiatives with the Air Traffic Control System Command Center, and communicate TMIs to Traffic Management Specialists at all affected facilities and to the controllers within their facility. The Federal Aviation Administration developed the National Traffic Management Log (NTML) to provide a single system for automated coordination, logging, and communication of TMIs throughout the National Airspace System. This report describes the results of an empirical comparison of TMI processing with and without the NTML. Researchers observed benefits in completion times, potential for user error, and workload. Furthermore, the completion time and potential for error remained relatively unaffected by TMI complexity. These results suggest that the NTML will continue to provide benefits as ATC complexity increases in the future.

The general aviation airport choice model is used to estimate general aviation (GA) person trips and number of aircraft operations through a set of airports given initial trip demand (GA person trips) from a set of counties. A pseudogravity model embedded in the model is used to distribute the intercounty person trips to the set of airports. The interairport person trips are then split into person trips by aircraft type (single, multiple, or jet engine). To split the trips, an attractiveness factor is developed on the basis of average occupancy, level of use, a distance distribution factor, and number of operations of each aircraft type. The person trips by aircraft type are then converted to aircraft operations with the use of occupancy factors for each aircraft type. The final model output is the number of aircraft operations by each aircraft type, in the form of three interairport trip tables. The estimated GA operations provide a means of assessing the impact of GA activities on the National Airspace System. The model output may also be used to assess the viability of GA aircraft as a competitive mode of transportation for intercity travel.

Effective communication in the National Airspace System (NAS) is an essential safety component of successful air travel. As the NAS migrates from its current ground infrastructure and voice communications system to one that encompasses both ground and airborne systems, digital data transmission may become the principal communication medium. As technological advances lead to innovations in communications system development, these emerging systems will be evaluated against the existing legacy system's performance parameters such as setup delay, voice streaming, pause duration, and message propagation. The data presented here are but a first step in providing objective and quantifiable communications system performance metrics that may prove valuable to communication systems developers and personnel charged with evaluating, certifying, and deploying the next generation of communications systems. The authors analyzed nearly 8,000 transmissions that represented the busiest air-ground communications from the five terminal radar approach control facilities with the highest number of operations in the contiguous United States. Typically, setup delays lasted 81 ms, voice streaming 2568 ms, pause duration 127 ms, and message propagation 73 ms for a total of 2849 ms per transmission. On average, transmissions were separated by 1736 ms of silence. Disruptions to efficient information transfer can result from blocked, stepped-on, and clipped transmissions - but they are rare events and occurred in only 1.16% of the sampled transmissions. A comparison between aircraft with and without disruptions revealed that when a disruption was present, an average of 14.54 messages were transmitted, compared with an average of 9.90 messages when no disruption was present. Even so, there appears to be some type of a detection mechanism in place to alert the controller to the presence of blocked transmissions. The source of this detection system is unclear; however, systems developers may want to exploit and expand this capability to include stepped-on and clipped transmissions.

The Surface Management System (SMS) aims to increase airport capacity and decrease surface gridlock, which are goals consistent with the Federal Aviation Administration's (FAA) National Airspace System Operational Evolution Plan (FAA, 2002). An operational trial was conducted to evaluate the initial design of the SMS traffic management tools. Although the dataset was small, participant responses were positive on four dimensions (usefulness, frequency of use, perceived accuracy, and ease of use) for nearly all of the six traffic management tools. Participant debriefs highlighted additional issues including the effects of SMS on coordination between Air Traffic Management facilities. This paper outlines the conduct of the operational trials and explores two of the major issues raised by the observations made during the trials.

The En Route Controller-Pilot Data Link Communications (CPDLC) program is designed to enable digital data communications between controllers and pilots. CPDLC Build 1A has been proposed as the first step in the nationwide rollout of this program to en route airspace by implementation in eight air route traffic control centers. Because CPDLC will automate several routine air-ground communications tasks, one potential benefit is reduced controller workload, which could lead to increased sector capacity and thus reduced flight times for flights traversing busy sectors. To quantify the workload reduction, a comparison has been made of the time currently required to perform communications tasks, as determined from recordings of actual air-ground communications, and the time required to perform the same tasks with CPDLC, as determined by a controller-in-the-loop simulation. This comparison indicated the potential for a significant reduction in the time spent on controller-pilot communications. A model was constructed to relate the reduced controller communications workload to increased sector capacity. The National Airspace System Performance Analysis Capability (NASPAC) model was used to estimate the reduction in flight times associated with the modeled sector capacity increase. NASPAC was run for both an idealized good weather day and a sample actual bad weather day. By 2017, the last year of the projected economic lifetime of CPDLC, average flight time savings from CPDLC-related capacity increases were estimated to exceed 9, 400 min/day.

Jet:Wise is an agent-based model that explores the evolution of the airline industry and its interactions with the National Airspace System (NAS). It models competitive decisions airlines make, such as setting fleet mix, itineraries, schedules, and fares and responding to delays and missed connections. The model addresses questions of the form, “How would a specific, quantifiable change in one aspect of the NAS affect the entire NAS?” Examples include changes in operational costs, passenger demand, and flight times; removal of certain Federal Aviation Administration restrictions; improvements in technology; new facilities; congestion pricing; mergers; startup airlines; and the expansion of low-cost carriers. Understanding their complex interaction is beyond the ability of traditional modeling tools and has not been attempted until now. Validation evidence is presented: Jet:Wise is shown to produce a close correlation between simulated and observed leisure passenger counts both by origin-destination city pairs and for individual flights.

Making greater use of smaller airports is one way that has been proposed to increase the capacity of the National Airspace System. A major difficulty is that many small airports do not have control towers, and thus capacity is severely limited during poor visibility. The authors consider a proposed system in which airplanes self-separate, so they are able to land at higher capacities without a control tower. Before such a system is implemented, it must first be shown to be safe. Safety is a difficult metric to measure and predict because accidents are so rare. Even computer simulation can be slow because of the long time to observe accidents. One methodology that has been successful in assessing aviation safety through simulation is TOPAZ (Traffic Organizer and Perturbation AnalyZer). In this study, the authors apply the methodology to assess the safety of the proposed nontowered system.

Safety and efficiency are two of the most important goals of the national airspace system (NAS). However, these goals are typically viewed as competing or independent, rather than complementary. The complementary aspect of safety and efficiency is illustrated from the point of view of human factors and ergonomics. Statistical methods were used to analyze safety and efficiency performance measurements, operational errors, and daily flight time index (DFTI). Factors related to weather and complexity were found to be more likely on days with poor operational performance as measured by DFTI. The results indicate a positive relationship between NAS safety and efficiency and imply that NAS safety performance may be improved by increasing efficiency, and vice versa.

This research involved the evaluation of a multimodal asynchronous communications tool to support collaborative analysis of post-operations in the National Airspace System (NAS). Collaborating authors have been shown to provide different feedback with asynchronous speech based communications compared to text. Voice synchronized with pointing in asynchronous annotation systems has been found to be more efficient in scheduling tasks, than voice-only, or text only communication. This research investigated how synchronized voice and pointing annotation over asynchronously shared slide shows composed of post operations graphical and tabular data differs in its effect compared to text based annotation, as collections of flights ranked low by standard performance metrics are discussed by FAA (Federal Aviation Administration) and airline representatives. The results showed the combined problem solving and message creation time was shorter when working in the voice and pointing mode than the text based mode, without having an effect on the number and type of ideas generated for improving performance. In both modes the system was also considered useful and usable to both dispatchers and traffic managers.

Free Flight Phase 1 (FFP1) is an FAA program for improving the performance of the National Airspace System (NAS) through the deployment of advanced technologies for air traffic management. In addition to the deployment activities, FFP1 includes a significant evaluation component, which faces a significant hurdle. A plethora of factors—weather, demand, enhancements to the NAS infrastructure not related to FFP1, facility outages, and so on—may also cause changes in NAS performance. It is necessary to normalize for these factors in order to determine the effect of FFP1. Normalization procedures to isolate the impact of the implementation of an FFP1 technology—the Terminal Area Traffic Management Advisor (T-TMA)—are documented at the Southern California TRACON, where it is used for controlling traffic into Los Angeles International Airport. Two examples of normalization are presented. One examines the effect of T-TMA on airport arrival capacity, and the other looks at arrival delay. The results, although preliminary given the short time since implementation, are consistent: it appears that capacities have increased and delays decreased as a result of the deployment of the tool. Moreover, the magnitudes of the delay reductions and capacity increases are consistent.