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NASA NTRS2015

Annualized TASAR Benefit Estimate for Alaska Airlines Operations

The Traffic Aware Strategic Aircrew Request (TASAR) concept offers onboard automation for the purpose of advising the pilot of traffic compatible trajectory changes that would be beneficial to the flight. A fast-time simulation study was conducted to assess the benefits of TASAR to Alaska Airlines. The simulation compares historical trajectories without TASAR to trajectories developed with TASAR and evaluated by controllers against their objectives. It was estimated that between 8,000 and 12,000 gallons of fuel and 900 to 1,300 minutes could be saved annually per aircraft. These savings were applied fleet-wide to produce an estimated annual cost savings to Alaska Airlines in excess of $5 million due to fuel, maintenance, and depreciation cost savings. Switching to a more wind-optimal trajectory was found to be the use case that generated the highest benefits out of the three TASAR use cases analyzed. Alaska TASAR requests peaked at four to eight requests per hour in high-altitude Seattle center sectors south of Seattle-Tacoma airport.

Henderson, Jeffrey↗
NASA NTRS2015

Annualized TASAR Benefit Estimate for Virgin America Operations

The Traffic Aware Strategic Aircrew Request (TASAR) concept offers onboard automation for the purpose of advising the pilot of traffic compatible trajectory changes that would be beneficial to the flight. A fast-time simulation study was conducted to assess the benefits of TASAR to Virgin America. The simulation compares historical trajectories without TASAR to trajectories developed with TASAR and evaluated by controllers against their objectives. It was estimated that about 25,000 gallons of fuel and about 2,500 minutes could be saved annually per aircraft. These savings were applied fleet-wide to produce an estimated annual cost savings to Virgin America in excess of $5 million due to fuel, maintenance, and depreciation cost savings. Switching to a more wind-optimal trajectory was found to be the use case that generated the highest benefits out of the three TASAR use cases analyzed. Virgin America TASAR requests peaked at two to four requests per hour per sector in high-altitude Oakland and Salt Lake City center sectors east of San Francisco.

Henderson, Jeffrey↗
NASA NTRS2016

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5% per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM(Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas/Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte/Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration - 2 (ATD-2) project for technology demonstration of Integrated Arrival/Departure/Surface (ADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement)/KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

scheduling↗
NASA NTRS2016

ACES M and S: Unmitigated Factorial Encounter Study on DAA/TCAS Interoperability

Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements for DAA alerting and guidance systems. This presentation contains the results of two combinatorial encounter analysis studies using NASA's SAA Control fast-time simulation capability for this purpose. In these studies, encounters between two aircraft were simulated one at a time for the full factorial combination of encounter geometries (e.g., encounter angle, CPA offset) and aircraft performance (e.g., ownership and intruder ground speeds and vertical rates). The first study analyzes the relationships (e.g., timeline) between the different alerting-safety regions in the SC-228 MOPS (in order of increasing severity): 1) DAA warning alert, 2) well clear recovery (WCR) guidance, 3) DAA-Collision Avoidance (CA), and 4) TCAS RA. This study will focus primarily on encounter situations in which TCAS RA occurs prior to any of the other alerting-safety boundaries. In particular, this study will investigate whether using vertical distance or vertical distance at closest point of approach (i.e., vertical miss distance or VMD) is more appropriate for the definition of the DAA-CA region. In addition, cases where transitions between different regions skip an intermediate region will be analyzed. The second study in this presentation explores a proposal to use an altitude rate error threshold to determine if vertical maneuvers are acceptable for DAA WCR guidance against non-cooperative intruders. This study incorporates the radar from the Honeywell sensor model and examines a series of pairwise encounters between a non-cooperative intruder and a UAS ownship, with different combinations of intruder states and ownship performance levels. The study uses SAA Control as a simulation platform and pilot model, and Omnibands to provide DWC recovery guidance. Two simulation sets, one that allows vertical DWC recovery guidance and one that does not, are compared to determine if encounters with altitude rate errors above 250 feet-per-minute are more likely to have more severe losses of well clear, as determined by the Loss of Well-Clear Severity metric.

SaaControl↗
NASA NTRS2016

A Coupled Probabilistic Wake Vortex and Aircraft Response Prediction Model

Wake vortex spacing standards along with weather and runway occupancy time, restrict terminal area throughput and impose major constraints on the overall capacity and efficiency of the National Airspace System (NAS). For more than two decades, the National Aeronautics and Space Administration (NASA) has been conducting research on characterizing wake vortex behavior in order to develop fast-time wake transport and decay prediction models. It is expected that the models can be used in the systems level design of advanced air traffic management (ATM) concepts that safely increase the capacity of the NAS. It is also envisioned that at a later stage of maturity, these models could potentially be used operationally, in groundbased spacing and scheduling systems as well as on the flight deck.

Gloudemans, Thijs↗
NASA NTRS2016

Performance Evaluation of the Approaches and Algorithms for Hamburg Airport Operations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.

air traffic management↗
NASA NTRS2016

Effect of Vertical Rate Error on Recovery from Loss of Well Clear Between UAS and Non-Cooperative Intruders

When an Unmanned Aircraft System (UAS) encounters an intruder and is unable to maintain required temporal and spatial separation between the two vehicles, it is referred to as a loss of well-clear. In this state, the UAS must make its best attempt to regain separation while maximizing the minimum separation between itself and the intruder. When encountering a non-cooperative intruder (an aircraft operating under visual flight rules without ADS-B or an active transponder) the UAS must rely on the radar system to provide the intruders location, velocity, and heading information. As many UAS have limited climb and descent performance, vertical position andor vertical rate errors make it difficult to determine whether an intruder will pass above or below them. To account for that, there is a proposal by RTCA Special Committee 228 to prohibit guidance systems from providing vertical guidance to regain well-clear to UAS in an encounter with a non-cooperative intruder unless their radar system has vertical position error below 175 feet (95) and vertical velocity errors below 200 fpm (95). Two sets of fast-time parametric studies was conducted, each with 54000 pairwise encounters between a UAS and non-cooperative intruder to determine the suitability of offering vertical guidance to regain well clear to a UAS in the presence of radar sensor noise. The UAS was not allowed to maneuver until it received well-clear recovery guidance. The maximum severity of the loss of well-clear was logged and used as the primary indicator of the separation achieved by the UAS. One set of 54000 encounters allowed the UAS to maneuver either vertically or horizontally, while the second permitted horizontal maneuvers, only. Comparing the two data sets allowed researchers to see the effect of allowing vertical guidance to a UAS for a particular encounter and vertical rate error. Study results show there is a small reduction in the average severity of a loss of well-clear when vertical maneuvers are suppressed, for all vertical error rate thresholds examined. However, results also show that in roughly 35 of the encounters where a vertical maneuver was selected, forcing the UAS to do a horizontal maneuver instead increased the severity of the loss of well-clear for that encounter. Finally, results showed a small reduction in the number of severe losses of well-clear when the high performance UAS (2000 fpm climb and descent rate) was allowed to maneuver vertically, and the vertical rate error was below 500 fpm. Overall, the results show that using a single vertical rate threshold is not advisable, and that limiting a UAS to horizontal maneuvers when vertical rate errors are above 175 fpm can make a UAS less safe about a third of the time. It is suggested that the hard limit be removed, and system manufacturers instructed to account for their own UAS performance, as well as vertical rate error and encounter geometry, when determining whether or not to provide vertical guidance to regain well-clear.

detect and avoid↗
NASA NTRS2016

Airport Traffic Conflict Detection and Resolution Algorithm Evaluation

Two conflict detection and resolution (CD&R) algorithms for the terminal maneuvering area (TMA) were evaluated in a fast-time batch simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. One CD&R algorithm, developed at NASA, was designed to enhance surface situation awareness and provide cockpit alerts of potential conflicts during runway, taxi, and low altitude air-to-air operations. The second algorithm, Enhanced Traffic Situation Awareness on the Airport Surface with Indications and Alerts (SURF IA), was designed to increase flight crew awareness of the runway environment and facilitate an appropriate and timely response to potential conflict situations. The purpose of the study was to evaluate the performance of the aircraft-based CD&R algorithms during various runway, taxiway, and low altitude scenarios, multiple levels of CD&R system equipage, and various levels of horizontal position accuracy. Algorithm performance was assessed through various metrics including the collision rate, nuisance and missed alert rate, and alert toggling rate. The data suggests that, in general, alert toggling, nuisance and missed alerts, and unnecessary maneuvering occurred more frequently as the position accuracy was reduced. Collision avoidance was more effective when all of the aircraft were equipped with CD&R and maneuvered to avoid a collision after an alert was issued. In order to reduce the number of unwanted (nuisance) alerts when taxiing across a runway, a buffer is needed between the hold line and the alerting zone so alerts are not generated when an aircraft is behind the hold line. All of the results support RTCA horizontal position accuracy requirements for performing a CD&R function to reduce the likelihood and severity of runway incursions and collisions.

Jones, Denise R.↗
NASA NTRS2015

The SMART-NAS Testbed

The SMART-NAS Testbed for Safe Trajectory Based Operations Project will deliver an evaluation capability, critical to the ATM community, allowing full NextGen and beyond-NextGen concepts to be assessed and developed. To meet this objective a strong focus will be placed on concept integration and validation to enable a gate-to-gate trajectory-based system capability that satisfies a full vision for NextGen. The SMART-NAS for Safe TBO Project consists of six sub-projects. Three of the sub-projects are focused on exploring and developing technologies, concepts and models for evolving and transforming air traffic management operations in the ATM+2 time horizon, while the remaining three sub-projects are focused on developing the tools and capabilities needed for testing these advanced concepts. Function Allocation, Networked Air Traffic Management and Trajectory Based Operations are developing concepts and models. SMART-NAS Test-bed, System Assurance Technologies and Real-time Safety Modeling are developing the tools and capabilities to test these concepts. Simulation and modeling capabilities will include the ability to assess multiple operational scenarios of the national airspace system, accept data feeds, allowing shadowing of actual operations in either real-time, fast-time and/or hybrid modes of operations in distributed environments, and enable integrated examinations of concepts, algorithms, technologies, and NAS architectures. An important focus within this project is to enable the development of a real-time, system-wide safety assurance system. The basis of such a system is a continuum of information acquisition, analysis, and assessment that enables awareness and corrective action to detect and mitigate potential threats to continuous system-wide safety at all levels. This process, which currently can only be done post operations, will be driven towards "real-time" assessments in the 2035 time frame.

Trajectory Based Operations↗
NASA NTRS2016

Overview of Sense and Avoid/Separation Assurance Interoperability (SSI)

The UAS in the NAS project is studying the minimum operational performance standards for unmanned aerial systems (UAS's) detect-and-avoid (DAA) system in order to operate in the National Airspace System. The project is executing a series of fast-time simulation, human-in-the-loop experiments, and flight test in support of this effort. Officials of the Swiss Government (Peter Winter, Director of Aeronautical Systems, and Michel Godinat, Head of the Certification Office) are visiting NASA to become more familiar with the advances being made to integrate UAS into civilian airspace. This briefing will review the activities and results over the past 3 years within the Separation AssuranceSense-and-Avoid Interoperability team.

Santiago, Confesor↗
NASA NTRS2016

Simulation and Flight Test Data Collection to Support Phase 1 Detect-and-Avoid MOPS

The UAS Integration into the NAS (UASNAS) project is studying the minimum operational performance standards for unmanned aerial system (UAS) detect-and-avoid (DAA) systems in order to operate in the National Airspace System (NAS). The project is executing a series of fast-time simulation, human-in-the-loop experiments, and flight tests in support of this effort. Armstrong Flight Research Center is hosting a VIP Day in conjunction with the UAS-NAS Project's Flight Test 4 activity, and the Ames Project Engineer (or designate) will be presenting a briefing. This briefing will review the data collection and analysis activities for Flight Test 4 within the Separation assurance-Sense-and-avoid Interoperability (SSI) team.

data analysis↗
NASA NTRS2014

Investigating the Impacts of a Separation Standard for UAS Operations in Enroute and Transition Airspace

Unmanned aircraft systems will be required to equip with a detect and avoid system in order to satisfy the federal aviation regulations to remain well clear of other aircraft. To comply with regulations in today’s operations manned aircraft must “see and avoid” other aircraft and use subjective judgment to determine whether those aircraft are well clear. For a detect-and- avoid (DAA) system to satisfy the requirement to stay well clear, a quantitative definition of well clear needs to be defined and evaluated. Definitions for the boundary of well clear have been proposed by the Unmanned Aircraft System (UAS) Executive Committee Science and Research Panel (SaRP) and the Radio Technical Commission for Aeronautics (RTCA) Special Committee 228 on Detect and Avoid Systems. This study investigates the interoperability implications of UAS using proposed well clear definitions as a separation standard for conducting operations in the national airspace system. The first analysis in the study focuses on the effect of variations in well clear definition parameters on the rate of losses of well clear per flight hour. The second analysis considers three well clear definitions and presents the relative state conditions of intruder aircraft as they encroach upon the well clear boundary. The third analysis focuses on the definition of the alerting criteria needed to inform the UAS operator of a potential loss of well clear. All three analyses are conducted in a NAS-wide fast-time simulation environment using UAS aircraft models, proposed UAS missions, and historical air defense radar data to populate the background traffic operating under visual flight rules. The results from the three analyses presented in this study inform the safety case, requirements development, and the operational environment for the DAA minimum operational performance standards.

UAS Seperation Standard↗
NASA NTRS2015

Proposal for a Sample Pilot Response Model

Regulations to establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions. Those requirements will apply to the new detect and avoid (DAA) systems and other equipment necessary to integrate UAS with the National Airspace System (NAS) and are determined according to their contribution to the overall safety case for such an integration. In order to perform end-to-end verification and validation of DAA requirements, a committee accepted pilot response model is needed to emulate UAS pilots in closed-loop Monte Carlo fast-time simulations. This briefing focuses on background of the pilot model used in previous Airspace Concept Evaluation System studies, identification of strengths and weaknesses in that model, and proposals on model improvements. The briefing also looks to build consensus around a common architecture and assumptions for modeling the pilot for UAS DAA systems.

Santiago, Confesor↗
NASA NTRS2016

Simulation and Flight Test Data Collection Review for Supporting Phase 1 Detect and Avoid MOPS

RTCA Special Committee 228 is a consortium of government, industry, and academic organizations tasked to develop minimum operational performance standards for UAS detect and avoid systems. The UAS in the NAS (National Airspace System) project is studying the minimum operational performance standards for unmanned aerial systems (UAS's) detect-and-avoid (DAA) system in order to operate in the National Airspace System. Over the past 3 years, the project has executed a series of fast-time simulation, human-in-the-loop experiments, and flight tests in support of this effort. The purpose of this briefing is to summarize the models developed and data collected to overcome UAS integration barriers, so UAS can remain well clear of all traffic.

Santiago, Confesor↗
NASA NTRS2014

Investigating Surveillance Performance for UAS Detect-and-Avoid Systems

Most unmanned aircraft systems will be required to be equipped with a detect-and-avoid system that is capable of maintaining appropriate separation from other aircraft. One of the critical components of detect-and-avoid systems is a surveillance system that identifies potential threat aircraft in real time and tracks these aircraft so that their future trajectories may be used to predict conflicts. The performance of the detect-and-avoid system generally depends on technical parameters of the surveillance system, such as the surveillance range. The quantitative requirements for detect-and-avoid systems will be determined to meet safety metrics for the operation of unmanned aircraft systems in the National Airspace System. This study employs a sensor model comprised of the surveillance range, and horizontal and vertical fields of regard that mainly characterize the overall performance of a surveillance system. In this study, potential metrics for evaluating the performance of a surveillance system were investigated through fast-time simulation with a traffic scenario that included both proposed unmanned aircraft flights and historical visual flight rule aircraft tracks. Using the simulation results, an overall analysis of encounter geometry highlights the encounter characteristics that relate surveillance parameters to safety metrics and detect-and-avoid system performance. Then, given several candidate surveillance volumes, performance and safety metrics are derived; these metrics include the ratio of undetected and late-detected violations and the time to violation at first detection. These example metrics demonstrate the utility of the database of encounters created in this work, a database which will be useful in the derivation of required detect-and-avoid surveillance system requirements.

Lee, Seung Man↗
NASA NTRS2015

Enhancing the Traffic Management Advisor's Schedule by Time Advance

A time advance algorithm associated with the scheduling functionalities of the Traffic Management Advisor (TMA) for arrival flights is presented and evaluated. The algorithm enhances TMA's meter fix schedule by advancing the flights' Scheduled Time of Arrival (STA) by an amount that minimizes their systemic operating cost. The systemic operating cost leverages the inherent trade-off of time and fuel efficiency resident in the cost index of modern flight management systems. The resulting STAs are achievable by speeding up the leading flights from their desired nominal speed profiles. A key advantage of this approach is that it reduces systemic delay to tight groupings of arriving aircraft as well as increases sustained throughput of the operation. A fast-time, Monte Carlo simulation that emulates TMA's scheduling functionalities is performed for arrival flights to the Phoenix Airport to quantify the benefit of the time advance algorithm. Results show consistent time saving benefits, ranging from 3 to 50 minutes for 112 flights with varying levels of traffic congestion.

arrival traffic management↗
NASA NTRS2015

Characteristics of a Well Clear Definition and Alerting Criteria for Encounters Between UAS and Manned Aircraft in Class E Airspace

Unmanned aircraft systems (UAS) will be required to equip with a detect-and-avoid (DAA) system in order to satisfy the federal aviation regulations to remain well clear of other aircraft. For a DAA system to satisfy the requirement to stay well clear of other airborne traffic, a quantitative definition of well clear needs to be defined and evaluated. This study investigates the implications of UAS using proposed well clear definitions as a separation standard for conducting operations in the National Airspace System (NAS). The first analysis considers three well clear definitions and presents the relative state conditions of intruder aircraft as they encroach upon the well clear boundary. The second analysis focuses on the definition of the alerting criteria needed to inform the UAS operator of a potential loss of well clear. All analyses are conducted in a NAS-wide fast-time simulation environment using UAS aircraft models, proposed UAS missions, and historical air defense radar data to populate the background traffic operating under visual flight rules. The results presented in this study inform the safety case, requirements development, and the operational environment for DAA minimum operational performance standards.

Safety↗
NASA NTRS2016

Optimized Route Capability (ORC) Intelligent Offloading of Congested Arrival Routes

The Optimized Route Capability (ORC) concept is designed to enable intelligent offloading of congested arrival routes. When ORC predicts arrival route congestion as projected excess arrival meter fix delay, automation offers decision support to traffic managers by identifying candidate flights to strategically reroute to alternate meter fixes and alleviate the congestion. This concept was applied to a model of arrival operations into Houston International Airport. An arrival rush from the Northeast was simulated in fast-time to analyze ORC algorithm behavior. The results demonstrate how strategically rerouting a few flights to alternate meter fixes not only has the potential to manage meter fix delay (and possibly the need for traffic management initiatives applied upstream), but may also increase airport capacity utilization and reduce total flight delay.

Zelinski, Shannon↗