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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 percent 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 (IADS) 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.

surface operations analysis↗

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

Performance Evaluation of the Approaches and Algorithms for Hamburg Airport Operations

In this work, fast-time simulations have been conducted using SARDA tools at Hamburg airport by NASA and real-time simulations using CADEO and TRACC with the NLR ATM Research Simulator (NARSIM) by DLR. The outputs are analyzed using a set of common metrics collaborated between DLR and NASA. The proposed metrics are derived from International Civil Aviation Organization (ICAO)s Key Performance Areas (KPAs) in capability, efficiency, predictability and environment, and adapted to simulation studies. The results are examined to explore and compare the merits and shortcomings of the two approaches using the common performance metrics. Particular attention is paid to the concept of the close-loop, trajectory-based taxi as well as the application of US concept to the European airport. Both teams consider the trajectory-based surface operation concept a critical technology advance in not only addressing the current surface traffic management problems, but also having potential application in unmanned vehicle maneuver on airport surface, such as autonomous towing or TaxiBot [6][7] and even Remote Piloted Aircraft (RPA). Based on this work, a future integration of TRACC and SOSS is described aiming at bringing conflict-free trajectory-based operation concept to US airport.

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 NTRS2015

SOSS User Guide

This User Guide describes SOSS (Surface Operations Simulator and Scheduler) software build and graphic user interface. SOSS is a desktop application that simulates airport surface operations in fast time using traffic management algorithms. It moves aircraft on the airport surface based on information provided by scheduling algorithm prototypes, monitors separation violation and scheduling conformance, and produces scheduling algorithm performance data.

air traffic control↗

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 NTRS2017

UAS Well Clear Recovery Against Non-Cooperative Intruders Using Vertical Maneuvers

This paper documents a study that drove the development of a mathematical expression in the detect-and-avoid (DAA) minimum operational performance standards (MOPS) for unmanned aircraft systems (UAS). This equation describes the conditions under which vertical maneuver guidance should be provided during recovery of DAA well clear separation with a non-cooperative VFR aircraft. Although the original hypothesis was that vertical maneuvers for DAA well clear recovery should only be offered when sensor vertical rate errors are small, this paper suggests that UAS climb and descent performance should be considered-in addition to sensor errors for vertical position and vertical rate-when determining whether to offer vertical guidance. A fast-time simulation study involving 108,000 encounters between a UAS and a non-cooperative visual-flight-rules aircraft was conducted. Results are presented showing that, when vertical maneuver guidance for DAA well clear recovery was suppressed, the minimum vertical separation increased by roughly 50 feet (or horizontal separation by 500 to 800 feet). However, the percentage of encounters that had a risk of collision when performing vertical well clear recovery maneuvers was reduced as UAS vertical rate performance increased and sensor vertical rate errors decreased. A class of encounter is identified for which vertical-rate error had a large effect on the efficacy of horizontal maneuvers due to the difficulty of making the correct left/right turn decision: crossing conflict with intruder changing altitude. Overall, these results support logic that would allow vertical maneuvers when UAS vertical performance is sufficient to avoid the intruder, based on the intruder's estimated vertical position and vertical rate, as well as the vertical rate error of the UAS' sensor.

UAS in the NAS↗

NASA NTRS2017

Safeguard: Progress and Test Results for a Reliable Independent On-Board Safety Net for UAS

As demands increase to use unmanned aircraft systems (UAS) for a broad spectrum of commercial applications, regulatory authorities are examining how to safely integrate them without compromising safety or disrupting traditional airspace operations. For small UAS, several operational rules have been established; e.g., do not operate beyond visual line-of-sight, do not fly within five miles of a commercial airport, do not fly above 400 feet above ground level. Enforcing these rules is challenging for UAS, as evidenced by the number of incident reports received by the Federal Aviation Administration (FAA). This paper reviews the development of an onboard system - Safeguard - designed to monitor and enforce conformance to a set of operational rules defined prior to flight (e.g., geospatial stay-out or stay-in regions, speed limits, and altitude constraints). Unlike typical geofencing or geo-limitation functions, Safeguard operates independently of the off-the-shelf UAS autopilot and is designed in a way that can be realized by a small set of verifiable functions to simplify compliance with existing standards for safety-critical systems (e.g. for spacecraft and manned commercial transportation aircraft systems). A framework is described that decouples the system from any other devices on the UAS as well as introduces complementary positioning source(s) for applications that require integrity and availability beyond what can be provided by the Global Positioning System (GPS). This paper summarizes the progress and test results for Safeguard research and development since presentation of the design concept at the 35th Digital Avionics Systems Conference (DASC '16). Significant accomplishments include completion of software verification and validation in accordance with NASA standards for spacecraft systems (to Class B), development of improved hardware prototypes, development of a simulation platform that allows for hardware-in-the-loop testing and fast-time Monte Carlo evaluations, and flight testing on multiple air vehicles. Integration testing with NASA's UAS Traffic Management (UTM) service-oriented architecture was also demonstrated.

Young, Steven D.↗

NASA NTRS2017

Modeling and Simulating Airport Surface Operations with Gate Conflicts

The Surface Operations Simulator and Scheduler (SOSS) is a fast-time simulation platform used to develop and test future surface scheduling concepts such as NASAs Air Traffic Demonstration 2 of time-based surface metering at Charlotte Douglas International Airport (CLT). Challenges associated with CLT surface operations have driven much of SOSS development. Recently, SOSS functionality for modeling hardstand operations was developed to address gate conflicts, which occur when an arrival and departure wish to occupy the same gate at the same time. Because surface metering concepts such as ATD2 have the potential to increase gates conflicts as departure are held at their gates, it is important to study the interaction between surface metering and gate conflict management. Several approaches to managing gate conflicts with and without the use of hardstands were simulated and their effects on surface operations and scheduler performance compared.

Zelinski, Shannon↗

NASA NTRS2017

TRACC_PB SOSS Integrated Traffic Simulation for CLT Ramp Operation

This presentation provides the current task under the NASA-DLR research collaboration for airport surface. It presents the effort done to adapt TRACC and SOSS software components to simulate airport (CLT) ramp area traffic management using TRACC's conflict free taxi trajectory optimization and SOSS's fast time simulation platform.

surface operations↗

NASA NTRS2017

Modeling and Simulating Airport Surface Operations with Gate Conflicts

The Surface Operations Simulator and Scheduler (SOSS) is a fast-time simulation platform used to develop and test future surface scheduling concepts such as NASA's Air Traffic Demonstration 2 of time-based surface metering at Charlotte Douglass International Airport (CLT). Challenges associated with CLT surface operations have driven much of SOSS development. Recently, SOSS functionality for modeling harsdstand operations was developed to address gate conflicts, which occur when an arrival and departure wish to occupy the same gate at the same time. Because surface metering concepts such as ATD2 have the potential to increase gates conflicts as departures are held at their gates, it is important to study the interaction between surface metering and gate conflict management. Several approaches to managing gate conflicts with and without the use of hardstands were simulated and their effects on surface operations and scheduler performance compared.

Zelinski, Shannon↗

NASA NTRS2018

Fe(3): An Evaluation Tool for Low-Altitude Air Traffic Operations

The concepts of unmanned aircraft system traffic management (UTM) and urban air mobility (UAM) are introducing high-density operations in low altitude airspace in closer proximity to populated areas than conventional high-altitude air traffic. The Flexible engine for Fast-time Evaluation of Flight Environments (Fe (sup 3)) provides the capability of statistically analyzing the high-density, high-fidelity, and low-altitude traffic system under numerous scenarios, such that stake holders can study impacts of factors in the low-altitude high-density traffic system and define requirements, policies, and protocols needed to support a safe yet efficient traffic system, and even assess operational risks and optimize flight schedules without conducting infeasible and cost-prohibitive flight tests that involve a large volume of aerial vehicles. This work provides an introduction to this simulation tool including its architecture and various models involved. Its performance and sample application in UAM and UTM are also presented.

Collision Avoidance↗

NASA NTRS2018

Fe3: An Evaluation Tool for Low-Altitude Air Traffic Operations

Trajectory Modeling↗

NASA NTRS2018

Urban Air Mobility Airspace Integration Concepts and Considerations

Urban Air Mobility (UAM) - defined as safe and efficient air traffic operations in a metropolitan area for manned aircraft and unmanned aircraft systems - is being researched and developed by industry, academia, and government. Significant resources have been invested toward cultivating an ecosystem for Urban Air Mobility that includes manufacturers of electric vertical takeoff and landing aircraft, builders of takeoff and landing areas, and researchers of the airspace integration concepts, technologies, and procedures needed to conduct Urban Air Mobility operations safely and efficiently alongside other airspace users. This paper provides high-level descriptions of both emergent and early expanded operational concepts for Urban Air Mobility that NASA is developing. The scope of this work is defined in terms of missions, aircraft, airspace, and hazards. Past and current Urban Air Mobility operations are also reviewed, and the considerations for the data exchange architecture and communication, navigation, and surveillance requirements are also discussed. This paper will serve as a starting point to develop a framework for NASA's Urban Air Mobility airspace integration research and development efforts with partners and stakeholders that could include fast-time simulations, human-in-the-loop (HITL) simulations, and flight demonstrations.

airspace integration↗

NASA NTRS2018

Simulation Evaluations of an Autonomous Urban Air Mobility Network Management and Separation Service

This paper presents an initial implementation of an autonomous Urban Air Mobility network management and aircraft separation service for urban airspace that does 1) departure and arrival scheduling across the network, 2) continuous trajectory management to ensure safe separation between aircraft, and 3) seamless integration with traditional operations. The highly-autonomous AutoResolver algorithm developed for traditional aviation was extended to provide these capabilities. An evaluation of this initial implementation was conducted in fast-time simulations using a dense, two-hour traffic scenario with Urban Air Mobility aircraft flying between a network of 20 vertiports in the Dallas-Fort Worth metroplex. When the spatial separation was reduced from 0:3nmi to 0:1nmi, the total de- lay decreased by 7:3%; when the temporal separation was reduced from 60s to 45s, the total delay decreased by 28:4%. The total number of conflict resolutions decreased by 26% and 17%, respectively. Furthermore, when a scheduling horizon greater than the duration of UAM flights was used (50min), most conflicts were resolved pre-departure producing ground delay. By comparison, when a shorter scheduling horizon was used (8min), most conflicts were resolved post-departure generating airborne delay. For all scheduling and separation constraints tested, AutoResolver prevented loss of separation from occurring. Urban Air Mobility operations have the ability to revolutionize how people and goods are transported and this paper presents initial research focusing on the high levels of autonomy required for an airspace system capable of scaling to handle significantly higher densities of aircraft.

Bosson, Christabelle S.↗

NASA NTRS2018

Simulation Evaluations of an Autonomous Urban Air Mobility Network Management and Separation Service

This presents an initial implementation of an autonomous Urban Air Mobility network management and aircraft separation service for urban airspace that does 1) departure and arrival scheduling across the network, 2) continuous trajectory management to ensure safe separation between aircraft, and 3) seamless integration with traditional operations. The highly-autonomous AutoResolver algorithm developed for traditional aviation was extended to provide these capabilities. An evaluation of this initial implementation was conducted in fast-time simulations using a dense, two-hour traffic scenario with Urban Air Mobility aircraft flying between a network of 20 vertiports in the Dallas-Fort Worth metroplex. When the spatial separation was reduced from 0:3 nmi (nautical miles) to 0:1nmi, the total delay decreased by 7:3 percent...

Bosson, Christabelle S.↗

NASA NTRS2018

En Route Detect and Avoid Well Clear in Terminal Area Landing Pattern

A fast time simulation was conducted to test the detect and avoid Well Clear definition designed for en route use when an unmanned aircraft (UA) is approaching the landing pattern of the terminal area. Measures focused on were loss of well clear and alerts intended to help the pilot avoid loss of well clear. Data indicated warning-level alerts will occur outside the typical Class D airspace which may prevent the UA from normal operations in the terminal airspace. Other aircraft on 45o entry could result in “nuisance” alerts which may also prevent the UA from normal operations in the terminal airspace. However, eliminating horizontal proximity (τmod) has the potential to increase “nuisance” alerts on the 45o entry and downwind legs. Overall, this suggests that a more stringent definition of Well Clear may be advisable in the landing pattern of the terminal area.

Trujillo, Anna C.↗

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↗