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The identification of precursors to safety incidents in aviation data is a crucial task, yet extremely challenging. The main approach in practice leverages domain expertise to define expected toler...

This paper aims to provide a resiliency management strategy of the air transportation network through network stability theory. To ensure the network to recover quickly from an upset condition, an ...

The authors would like to thank the following people for participating in the 2018 UAS Safety Symposium at Georgia Tech since that effort provided much of the driver for this research: Roy Burke, Julianna Burke, Anthony Mormino, Eric Richey, Chris Proudlove, Naira Hovakimyan, Jeong Jur, Greg Ourada, and Michael Miller. The authors are also thankful to Olivia Jagiella-Lodise and Philippe Monmousseau for their contributions in editing and formatting this paper.

Autonomous operation of unmanned aerial vehicles (UAVs) requires development of technologies that allow for safer flight control and response to various flight anomalies. Software for autonomous co...

The arrival sequencing and scheduling problem have been formulated in the urban air mobility (UAM) context for homogeneous and mixed fleets of electric vertical takeoff and landing (EVTOL) aircraft...

Emergency landing is a critical safety feature for the expected increase of autonomous vehicles in the airspace. This paper presents Safe2Ditch, an autonomous crash management system for landing sm...

As air traffic management becomes increasingly automated, technologies for detecting and resolving conflicts are critical to maintain the safety of an airspace. There exists a need to understand ho...

By modeling compatibilities, benefits, and penalties of various technology packages at the subsystem level in a vehicle design tool, bottom-up assessments of projected technological benefits can be...

Adverse weather impacts the safety and efficiency of aviation. Convective storms, turbulence, and icing are aviation weather hazards that can lead to unpleasant rides and, in the worst case scenari...

To achieve a level of safety equivalent to manned aircraft in the national airspace system, the pilot-in-command of small unmanned aircraft systems should be able to maintain situational awareness ...

As small unmanned aircraft systems (sUAS) evolve, more sUAS are being used for various applications, such as parcel delivery. Consequently, sUAS traffic is increasing, which is bringing about conce...

To achieve a level of safety equivalent to manned aircraft in the national airspace system, the pilot in command of small unmanned aircraft systems should be able to maintain situational awareness ...

In this Paper, we present a complete, proof-of-concept sense-and-avoid solution for small unmanned aircraft systems, including a small low-cost ground-based radar system, multitarget tracking and e...

Unmanned aircraft systems must demonstrate a capability to sense and avoid air traffic as part of a layered conflict management system to enable safe operations in the National Airspace System. Dur...

Autonomous contingency management systems, such as a forced-landing system, which reacts appropriately to an engine failure, are important for the safe operation of unmanned aircraft systems. This ...

For unmanned aircraft systems to gain full access to the National Airspace System, they must have the capability to detect and avoid other aircraft. To safely avoid another aircraft, an unmanned ai...

This paper presents a Bezier-curve-based collision prediction and avoidance algorithm for multivehicle cooperative missions. The proposed algorithm runs on each vehicle independently from other veh...

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 focus of this paper is to present a game theoretical modeling framework for the integration of unmanned aircraft systems into the National Airspace System. The problem of predicting the outcome of complex scenarios, where manned and unmanned air vehicles coexist, is the research problem of this work. The fundamental gap in the literature is that the models of interaction between manned and unmanned vehicles are insufficient: 1) They assume that pilot behavior is known a priori, and 2) They disregard pilot reaction and the decision-making process. The contribution of this paper is to propose a realistic modeling framework that will fill this gap. The foundations of the proposed method are formedbygame theory, which investigates strategic decision makingbetween intelligent agents; bounded rationality concept, which is based on the fact that humans cannot always make perfect decisions; and reinforcement learning, which is shown to be effective in human learning in psychology literature. An analysis of integration is conducted using an example scenario in the presence of manned aircraft and fully autonomous unmanned aircraft systems equipped with sense-and-avoid algorithms. © Copyright 2016 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Space launch and reentry operations are expected to increase in the coming years with the expansion of commercial space operators and spaceport development. Every launch and reentry in the United S...

This is a technical note published in the Journal of Aerospace Information Systems [© by the American Institute of Aeronautics and Astronautics, Inc.].

Among the premises of the Next Generation Air Transportation System initiative is the necessity for precision procedures in air traffic operations. Conformance with such procedures can help safety and the ability to accommodate higher traffic demand. The contribution of this paper is an algorithm for automating the process of speed control, aimed at separation assurance and conducted in current air traffic operations by human air traffic controllers. If a separation-compliant collective speed profile for the given set of aircraft exists, the algorithm computes this profile. If no such speed profile exists, the computer reports the nonexistence. Uncertainties such as weather are not considered, but the algorithm can be modified to include them. The algorithm proceeds in two stages. First, it finds an arrival sequence for the aircraft. The computational complexity of this stage is factorial in the number of aircraft but allows substantial parallelization. The second stage finds a collective speed profile fo...

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...

Trajectory-based operations is a NextGen program concept that uses trajectory prediction, scheduling tools, and improved methods for trajectory management to improve the capacity and efficiency of the National Airspace System. Metering operations are one element of trajectory-based operations and involve the sequencing and scheduling of aircraft to flow-constrained points or meter points. Aircraft trajectories are managed to the schedule to ensure aircraft-to-aircraft spacing across the meter point. Automation tools are being developed to support air traffic controller tasks in managing aircraft trajectories to meet scheduled times of arrival at the meter points. Uncertainties in trajectory prediction, such as those related to wind-forecast and aircraft-modeling errors, pose a significant challenge in the design of automation for trajectory management. This paper proposes a framework for exploring and designing metering strategies in the presence of trajectory uncertainties, in which tradeoffs between the...

This paper describes new methods to reach safety targets for sense-and-avoid sensors for unmanned aircraft systems by evaluating integrity and continuity risks. These methods can be used to set sensor requirements. The closest-point-of-approach distance and time to closest point of approach, τ, are used to measure the hazards associated with the intruder aircraft. The contribution to knowledge in this paper is a new method that uses hazard state estimates and estimate error to establish 1) the integrity risk of the sense-and-avoid system not detecting imminent loss of self-separation, and 2) the probability of false alert, the flight-path continuity risk. A sensitivity analysis evaluates the impact on integrity and continuity of sensor noise, range, and sample interval. The methods described in this paper can be used to set potential sense-and-avoid sensor requirements for unmanned aircraft system integration into the National Airspace System.

Algorithms for the end-to-end optimized scheduling of aircraft to enhance the efficiency of the National Airspace System are developed. For a given set of flights and desired departing schedules, routes are constructed and unimpeded four-dimensional trajectories are simulated. These trajectories serve as an input to a linear-programming-based approach, and they result in optimized schedules that are deconflicted while assuring adherence to the system capacity constraints. For a large number of flights, the computational effort is formidable and optimization coupled with the Dantzig–Wolfe decomposition technique has been found to be a suitable approach. Techniques for accelerating the decomposition and solver on emerging high-performance computing hardware are discussed. A multithreaded central-processing-unit implementation and a novel implementation on general-purpose graphics processing units show acceleration over a state-of-the-art open-source decomposition-based solver. The acceleration observed can ...

Convective weather, recognized as the leading contributor to delays in the National Airspace System, causes demand–capacity imbalance in the airspace. Strategic air traffic management aims to resolve the imbalance for offnominal conditions (for example, convective weather events) through redistributing flows and resources at the strategic timeframe (2–15 h in advance). As a component of scenario-driven strategic air traffic management, this paper develops a multiresolution spatiotemporal distance measure that, combined with standard distance-based clustering algorithms, can be used to group a wide range of possible weather-impact scenarios into a few representative clusters to facilitate corresponding management strategy design. Motivations of this new distance measure, its generation algorithm, and parameter impact analysis are described in detail to facilitate practical implementation and subsequent use in decision support. This multiresolution spatiotemporal distance measure not only addresses the need...

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...

The problem of estimating the characteristics of the air traffic flow in the terminal area is considered. The estimated parameters can be used by the traffic flow coordinators and terminal area controllers to improve their response to varying air traffic flow. The approach is based on a queuing abstraction of the arrival and departure traffic routes in the terminal area. The routes are discretized as spatial servers for enforcing Federal Aviation Administration mandated separation requirements. Particle filtering methodology is employed for estimating the time-varying queuing parameters using radar track data. By considering the waypoint crossing times and airspeed as measurements, it is shown that it is feasible to estimate the time delay and its rate at various points along the arrival/departure routes. The proposed approach is illustrated using historical radar track data. A graphic display of estimated parameters to serve as a decision-support tool for use by the terminal area traffic controllers is a...

With the increasing demand to integrate unmanned aircraft systems (UAS) into the National Airspace System (NAS), new procedures and technologies are necessary to ensure safe airspace operations and...

New performance standards for a detect and avoid (DAA) system are being developed to support the broader integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS). One subset of these performance standards will address the minimum DAA display requirements to support pilot performance on maintaining well clear of other aircraft. These performance standards must take into account the current air traffic control (ATC) operational environment. In particular, the DAA system, and pilots’ interactions with that system, must account for the requirement for pilots to request a clearance for deviations from their approved instrument flight rules route. A series of human-in-the-loop (HITL) experiments were conducted to help identify the minimum information requirements for DAA displays. As part of these experiments, several pilot-ATC interaction metrics were collected, such as the amount of time it took pilots to request an ATC clearance prior to executing a maneuver to maintain well cle...

Coordinating nationwide air traffic flow is a large-scale problem. The modeling process generally involves analysis of massive flight data, and its optimization involves computationally expensive algorithms. This paper uses Hadoop MapReduce, a big data processing model, to facilitate air traffic flow modeling and optimization, where computationally intensive tasks are automatically spread to Hadoop clusters for concurrent executions. The overall wall-clock time of computation is reduced. A nationwide traffic flow management problem that has been previously studied was restructured under the MapReduce framework. The problem aims at minimizing flight delays while respecting system capacities. Due to its temporal and spatial scope, the size of this problem grows to an extent where it is too big to be solved on standalone computers. Lagrangian relaxation was applied to decompose the original problem into a collection of solvable subproblems. The optimization proceeds in two iterative stages: solving subproble...

On any given day, constraints in the National Airspace System (for instance, weather) necessitate the implementation of traffic flow management initiatives, such as ground delay programs. The goal ...

Given its static and rigid structure, the current National Airspace System lacks the ability to cope efficiently with the increasingly severe demand–capacity imbalances expected to develop over the coming years. To better accommodate the flexibility desired for future flight operations and to alleviate the demand–capacity imbalances, research initiatives have been conducted under the dynamic airspace configuration concept. Although most past dynamic airspace configuration researchers have focused on en route airspace, this paper investigates terminal airspace operations. A dynamic sectorization algorithm for terminal airspace is developed, which combines a k-means clustering-based vertical sectorization algorithm, an integer-programming-based horizontal sectorization algorithm, and an α-shapes-based airspace sectorization algorithm. This dynamic sectorization algorithm is validated with real traffic data from several major international airports in the United States and simulated traffic data with project...

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 integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) requires that UAS meet or exceed the safety requirements established for conventional aircraft, and for the UAS pilots to interact with air traffic controllers (ATCos) in an acceptable manner. UAS have several characteristics that differentiate them from conventional aircraft, including the possibility of greater latencies associated with remote pilot communication and command execution. The goal of the present study was to determine how adding delays to UAS pilot communications and command executions affect ATCos’ interactions with UAS and conventional aircraft. Six previously certified radar controllers and two currently certified radar controllers were recruited as participants to manage traffic in a simulated sector with conventional traffic and one UAS flying in it. The UAS pilot verbal communication and execution latencies were varied in separate scenarios to include an additional delay that was either short (1.5 s) or long (5 s), and constant or variable within each scenario. We measured both UAS and conventional pilots’ verbal communication and execution initiation latencies, and obtained ATCos’ acceptability ratings for the different delay conditions. Also examined were the number of communication step-ons created by the additional communication delays implemented in the UAS control station, as well as other measures of the ATCo-pilot interactions. We found ATCos rated UAS pilot verbal communication latencies to be acceptable when the latencies were short rather than long and that acceptability ratings often reflect broader features of the sectors being managed. Implications of these findings for UAS integration in the NAS and limitations of the present study are discussed.

Highly complex and coupled nature of the National Airspace System makes it challenging to understand the safety implications of changes to its operations. A comprehensive assessment of the hazards associated with the introduction of new technologies must involve modeling of interactions among aircraft behavior, supporting infrastructure, and the operational procedures. The traditional approach to risk assessment does not focus on the relative timing of relevant events. The likelihoods of those events are computed externally, usually by means of physics-based simulations, which, while increasingly realistic in capturing physical phenomena, are limited to describing only few relevant interactions to keep the overall complexity tractable. This paper discusses an intermediate layer of analysis with enough fidelity to capture time-dependent coupling among relevant entities of the system that is compact enough to track a large number of those relevant entities simultaneously. To this end, Stochastic Petri nets ...

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...

Unmanned Aircraft Systems (UAS) integration into the National Airspace System (NAS) will require overcoming numerous challenges, including evaluating the responsiveness of Unmanned Aircraft (UA) to...

Unrestricted access to civil airspace requires the ability to see-and-avoid other aircraft. While an on-board pilot normally provides this capability, unmanned aircraft systems must develop an alte...

Introduction of Unmanned Aircraft Systems (UAS) into positively controlled airspace may cause greater per-aircraft impact on the National Airspace System than existing traffic because UAS aerodynamic performance and mission types are often different from aircraft that typically fly in positively controller airspace (i.e. commercial passenger traffic). This paper examines the impact new UAS operations will have on existing aircraft and measures that impact by the number of predicted conflicts and associated conflict resolution delays that occurred in fast-time simulation. The two conflict metrics are quantified as a function of the UAS altitude and cruise speed. Two mitigation approaches are also investigated: increasing horizontal separation requirements for UAS and “burdening” UAS with the responsibility to execute all resolution maneuvers when possible. Results indicate that en route conflict maneuver delay for existing traffic because of new UAS operations can be nearly eliminated by burdening UAS with...

The planned introduction of unmanned aircraft (UA) systems (UAS) into non-segregated civil airspace will require highly reliable radio links to enable remote pilots to maintain operational control ...

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.

The concept of dynamic sector design suggests a strategic approach to ease air traffic congestion, which is predicted to become a serious problem in the national airspace system by 2025. Considerable research has been conducted to address the sectorization problem. In previous work, an approach that combines the Voronoi diagrams, Genetic Algorithms (GA), and the iterative deepening algorithm was proposed. However, as originally formulated, the number of sectors used was predefined and only two-dimensional partitions were allowed, which constrained the method's ability to achieve good designs. The current work extends the earlier Voronoi-based method by treating the number of sectors as an additional decision variable, allowing 3D partitions, and developing more comprehensive costs.